Trapped Traders [ScorsoneEnterprises]This indicator identifies and visualizes trapped traders - market participants caught on the wrong side of price movements with significant volume imbalances. By analyzing volume delta at specific price levels, it reveals where traders are likely experiencing unrealized losses and may be forced to exit their positions.
The point of this tool is to identify where the liquidity in a trend may be.
var lowerTimeframe = switch
useCustomTimeframeInput => lowerTimeframeInput
timeframe.isseconds => "1S"
timeframe.isintraday => "1"
timeframe.isdaily => "5"
=> "60"
= ta.requestVolumeDelta(lowerTimeframe)
price_quantity = map.new()
is_red_candle = close < open
is_green_candle = close > open
for i=0 to lkb-1 by 1
current_vol = price_quantity.get(close)
new_vol = na(current_vol) ? lastVolume : current_vol + lastVolume
price_quantity.put(close, new_vol)
if is_green_candle and new_vol < 0
price_quantity.put(close, new_vol)
else if is_red_candle and new_vol > 0
price_quantity.put(close, new_vol)
We see in this snippet, the lastVolume variable is the most recent volume delta we can receive from the lower timeframe, we keep updating the price level we're keeping track of with that lastVolume from the lower timeframe.
This is the bulk of the concept as this level and size gives us the idea of how many traders were on the wrong side of the trend, and acting as liquidity for the profitable entries. The more, the stronger.
There are 3 ways to visualize this. A basic label, that will display the size and if positive or negative next to the bar, a gradient line that goes 10 bars to the future to be used as a support or resistance line that includes the quantity, and a bubble chart with the quantity. The larger the quantity, the bigger the bubble.
We see in this example on NYMEX:CL1! that there are lines plotted throughout this price action that price interacts with in meaningful way. There are consistently many levels for us.
Here on CME_MINI:ES1! we see the labels on the chart, and the size set to large. It is the same concept just another way to view it.
This chart of CME_MINI:RTY1! shows the bubble chart visualization. It is a way to view it that is pretty non invasive on the chart.
Every timeframe is supported including daily, weekly, and monthly.
The included settings are the display style, like mentioned above. If the user would like to see the volume numbers on the chart. The text size along with the transparency percentage. Following that is the settings for which lower timeframe to calculate the volume delta on. Finally, if you would like to see your inputs in the status line.
No indicator is 100% accurate, use "Trapped Traders" along with your own discretion.
ค้นหาในสคริปต์สำหรับ "profitable"
Order Blocks + Order-Flow ProxiesOrder Blocks + Order-Flow Proxies
This indicator combines structural analysis of order blocks with lightweight order-flow style proxies, providing a tool for chart annotation and contextual study. It is designed to help users visualize where significant structural shifts occur and how simple volume-based signals behave around those areas. The script does not guarantee profitable outcomes, nor does it issue financial advice. It is intended purely for research, learning, and discretionary use.
Conceptual Background
Order Blocks
An “order block” is a term often used to describe a zone on the chart where price left behind a significant reversal or imbalance before continuing strongly in the opposite direction. In practice, this can mean the last bullish or bearish candle before a strong breakout. Traders sometimes study these regions because they believe that unfilled resting orders may exist there, or simply because they mark important pivots in price structure. This indicator detects such moments by scanning for breaks of structure (BOS). When price pushes above or below recent swing levels with sufficient displacement, the script identifies the prior opposite candle as the potential order block.
Break of Structure
A break of structure in this context is defined when the closing price moves beyond the highest high or lowest low of a short lookback window. The script compares the magnitude of this break to an ATR-based displacement filter. This helps ensure that only meaningful moves are marked rather than small, random fluctuations.
Order-Flow Proxies
Traditional order flow analysis may use bid/ask data, footprint charts, or volume profiles. Because TradingView scripts cannot access true order-book data, this indicator instead uses proxy signals derived from standard chart data:
Delta (proxy): Estimated imbalance of buying vs. selling pressure, approximated using bar direction and volume.
Imbalance ratio: Normalizes delta by total volume, ranging between -1 and +1 in theory.
Cumulative Delta (CVD): Running sum of delta over time.
Effort vs. Result (EvR): A comparison between volume and actual bar movement, highlighting cases where large effort produced little result (or vice versa).
These are not real order-flow measurements, but rather simple mathematical constructs that mimic some of its logic.
How the Script Works
Detecting Break of Structure
The user specifies a swing length. When price closes above the recent high (for bullish BOS) or below the recent low (for bearish BOS), a potential shift is recorded.
To qualify, the breakout must exceed a displacement filter proportional to the ATR. This helps filter out weak moves.
Locating the Order Block Candle
Once a BOS is confirmed, the script looks back within a short window to find the last opposite-colored candle.
The high/low or open/close of that candle (depending on user settings) is marked as the potential order block zone.
Drawing and Maintaining Zones
Each order block is represented as a colored rectangle extending forward in time.
Bullish zones are teal by default, bearish zones are red.
Zones extend until invalidated (price closing or wicking beyond them, depending on user preference) or until a user-defined lifespan expires.
A pruning mechanism ensures that only the most recent set number of zones remain, preventing chart overload.
Monitoring Touches
The script checks whether the current bar’s range overlaps any existing order block.
If so, the “closest” zone is considered touched, and a label may appear on the chart.
Confirmation Filters
Touches can optionally be confirmed by order-flow proxies.
For a bullish confirmation, the following must align:
Imbalance ratio above threshold,
Delta EMA positive,
Effort vs. Result positive.
For a bearish confirmation, the opposite holds true.
Optionally, a higher-timeframe EMA slope filter can gate these confirmations. For example, a bullish confirmation may only be accepted if the higher-timeframe EMA is sloping upward.
Alerts
Users may create alerts based on conditions such as “bullish touch confirmed” or “bearish touch confirmed.”
Alerts can be gated to only fire after bar close, reducing intrabar noise.
Standard alertcondition calls are provided, and optional inline alert() calls can be enabled.
Inputs and Customization
Structure & OB
Swing length: Defines how many bars back to check for BOS.
ATR length & displacement factor: Adjust sensitivity for structural breaks.
Body vs. wick reference: Choose whether zones are based on candle bodies or full ranges.
Invalidation rule: Pick between wick breach or close beyond the level.
Lifespan (bars): Limit how long a zone remains active.
Max keep: Cap the number of zones stored to reduce clutter.
Order-Flow Proxies
Delta mode: Choose between “Close vs Previous Close” or “Body” for delta calculation.
EMA length: Smooths the delta/imbalance series.
Z-score lookback: Defines the averaging window for EvR.
Confirmation thresholds: Adjust the imbalance levels required for long/short confirmation.
Higher Timeframe Filter
Enable HTF gate: Optional filter requiring higher-timeframe EMA slope alignment.
HTF timeframe & EMA length: Configurable for context alignment.
Style
Colors and transparency for bullish and bearish zones.
Border color customization.
Alerts
Enable inline alerts: Optional direct calls to alert().
Alerts on bar close only: Helps avoid multiple firings during bar formation.
Practical Use
This tool is best seen as a way to annotate charts and to study how simple volume-derived signals behave near important structural levels. Some users may:
Observe whether order blocks line up with later price reactions.
Study how imbalance or cumulative delta conditions align with these zones.
Use it in a discretionary workflow to highlight areas of interest for deeper analysis.
Because the proxies are based only on candle OHLCV data, they are approximations. They cannot replace true depth-of-market analysis. Similarly, order block detection here is one specific algorithmic interpretation; other traders may define order blocks differently.
Limitations and Disclaimers
This indicator does not predict future price movement.
It does not access real order book or tick-by-tick data. All signals are derived from bar OHLCV.
Past performance of signals or zones does not guarantee future results.
The script is for educational and informational purposes only. It is not financial advice.
Users should test thoroughly, adjust parameters to their own instruments and timeframes, and use it in combination with broader analysis.
Summary
The Order Blocks + Order-Flow Proxies script is an experimental study tool that:
Detects potential order blocks using a displacement-filtered break of structure.
Marks these zones as boxes that persist until invalidation or expiry.
Provides lightweight order-flow-style proxies such as delta, imbalance, CVD, and effort vs. result.
Allows confirmation of zone touches through these proxies and optional higher-timeframe context.
Offers flexible customization, alerting, and chart-style options.
It is not a trading system by itself but rather a framework for studying price/volume behavior around structurally significant areas. With careful exploration, it can give users new ways to visualize market structure and to understand how simple flow-like measures behave in those contexts.
Extended CANSLIM Indicator❖ Extended CANSLIM Indicator.
The Extended CANSLIM indicator is an indicator that concentrates all the tools usually used by CANSLIM traders.
It shows a table where all the stock fundamental information is shown at once first for the last quarter and then up to 5 years back.
The fundamental data is checked against well known CANSLIM validation criteria and is shown over 4 state levels.
1. Good = Value is CANSLIM Compliant.
2. Acceptable = Value is not CANSLIM compliant but still good. value is shown with a lighter background color.
3. Warning = Value deserves special attention. Value is shown over orange background color.
3. Stop = Value is non CANSLIM compliant or indicates a stop trading condition. Value is shown over red background color.
The indicator has also a set of technical tools calculated on price or index and shown directly on the chart.
❖ Fundamental data shown in the table.
The table is arranged in 4 sets of data:
1. Table Header, showing Indicator and Company data.
2. CANSLIM.
3. 3Rs: RS Rating, Revenue and ROE.
4. Extra Data: Piotroski score, ATR, Trend Days, D to E, Avg Vol and Vol today.
Sets 3 and 4 can be hidden from the table.
❖ Indicator and Compay Data.
The table header shows, Indicator name and version.
It then displays Company Name, sector and industry, human size and its capitalization.
❖ CANSLIM Data.
Displays either genuine CANSLIM data from TradinView or custom data as best effort when that data cannot be obtained in TV.
C = EPS diluted growth, Quarterly YoY.
>= 25% = Good, >= 0% = Acceptable, < 0% = Stop
A = EPS diluted growth, Annual YoY.
>= 25% = Good, >= 0% = Acceptable, < 0% = Stop
N = New High as best effort (Cust).
Always Good
S = Float shares as best effort.
Always Good
L = One year performance relative to S&P 500 (Cust),
Positive : 0% .. 50% = Neutral, 50%+ = Leader, 80%+ = Leader+, 100%+ = Leader++
Negative : 0% .. -10% = Laggard, -10% .. -30% = Laggard+, -30%+ = Laggard++
>= 50% = Good, >= 0% = Acceptable, >= -10% Warning, < -10% = Stop
I = Accumulation/Distribution days over last 25 days as a clue for institutional support (Cust).
A delta is calculated by subtracting Distribution to Accumulation days.
> 0 = Good, = 0 = Acceptable, < 0 = Warning, < -5 = Stop
M = Market direction and exposure measured on S&500 closing between averages (Cust).
Varies from 0% Full Bear to 100% Full Bull
>= 80% = Good, >= 60% = Acceptable, >= 40% = Warning, < 40% = Stop
❖ Extra non CANSLIM Data.
RS = RS Rating.
>= 90 = Good, >= 80 = Accept, >= 50 = Warning, < 50 = Stop
Rev. = Revenue Growth Quarterly YoY.
>= 0% = Good, <0% = Stop
ROE = Return on Equity, Quarterly YoY.
>= 17% = Good, >= 0% = Acceptable, < 0% = Stop
Piotr. = Piotroski Score, www.investopedia.com (TV)
>= 7 = Good, >= 4 = Acceptable, < 4 = Stop
ATR = Average True Range over the last 20 days (Cust).
0% - 2% = Acceptable, 2% - 4% = Ideal, 4% - 6% = Warning, 5%+ = Stop.
Trend Days = Days since EMA150 is over EMA200 (Cust).
Always Good
D. to E. = Days left before Earnings. Maybe not a good idea buying just before earnings (Cust).
>= 28 = Good, >= 21 = Acceptable, >= 14 = Warning, < 14 = Stop
Avg Vol. = 50d Average Volume (Cust).
>= 100K = Good, < 100K = Acceptable
Vol. Today = Today's percentage volume compared to 50d average (Cust).
Always Good.
❖ Historical Data.
Optionally selectable historical data can be displayed for C, A, Revenue and ROE up to 20 quarters if available.
Quarterly numbers can also be displayed for A, C and Revenue.
Information can be shown in Chronological or Reverse Chronological order (default).
Increasing growth quarters are shown in white, while diminuing ones are shown in Yellow.
Transition from Losing to Profitable quarters are shown with an exclamation mark ‘!’
Finally, losing quarters are shown between parenthesis.
❖ MAs on chart.
Displays 200, 100, 50 and 20 days MAs on chart.
The MAs are also automatically scaled in the 1W time frame.
❖ New 52 Week High on chart.
A sun is shown on the chart the first time that a new 52 week high is reached.
The N cell shows a filled sun when a 52 week high is no older than a month, an lighter sun when it’s no older than a quarter or a moon otherwise.
❖ Pocket Pivots on chart.
Small triangles below the price are signaling pocket pivots.
❖ Bases on chart, formerly Darvas Boxes.
Draw bases as defined by Darvas boxes, both top or bottom of bases can be selected to be shown in order to only show resistance or support.
❖ Market exposure/direction indicator.
When charting S&P500 (SPX), Nasdaq 100 Index (NDX), Nasdaq composite (IXIC) or Dow Jownes Index (DJIA), the indicator switches to Market Exposure indicator, showing also Accumulation/Distribution days when volume information is available. This indication which varies from 0% to 100% is what is shown under the M letter in the CANSLIM table which is calculated on the S&P500.
❖ Follow Through Days indicator.
If you are an adept of the Low-cheat entry, then you will be highly interested by the Follow Through days indicator as measured in the S&P 500 and shown as diamonds on the chart.
The follow-through days are calculated on S&P500 but shown in current stock chart so you don’t need to chart the S&P 500 to know that a follow through day occurred.
Follow Through days show correctly on Daily time frame and most are also shown on the Weekly time frame as well.
They are also classified according to the market zone in which they occur:
0%-5% from peak = Pullback : FT day is not shown.
5%-10% from peak = Minor Correction : Minor FT days is shown.
10%-20% from peak = Correction : Intermediate FT days us shown
20+% from peak = Bear Market : Makor FT days is shown
❖ RS Line and Rating indicator.
A RS Line and Rating indicator can be added to the chart.
Relative Strength Rating Accuracy.
Please note that the RS Rating is not 100% accurate when compared to IBD values.
❖ Earning Line indicator.
An Earning Line indicator can be added to the chart.
❖ ATR Bands and ATR Trade calculator.
The motivation for this calculator came from my own need to enter trades on volatile stocks where the simple 7% Stop Loss rule doest not work.
It simply calculates the number of shares you can buy at any moment based on current stock price and using the lower ATR band as a stop loss.
A few words about the ATR Bands.
On this indicator the ATR bands are not drawn as a classical channel that follows the price.
The lower band is drawn as a support until it’s broken on a closing basis. It can’t be in a down trend.
The upper band is drawn as a resistance until it’s broken on a closing basis. It can’t be in an up trend.
The idea is that when price starts to fall down from a peak, it should not violate its lower band ATR and that means that we can use that level as a Stop Loss.
You must look back for the stock volatility and find out which ATR multiplier works well meaning that the ATR bands are not violated on normal pullbacks. By default, the indicator uses 5x multiplier.
❖ Extra things, visual features and default settings.
The first square cell of current quarter displays a check mark ‘V’ if the CANSLIM criteria is OK or acceptable or a cross ‘X’ otherwise.
The first square cell of historical C and Rev show respectively the count of last consecutive positive quarters.
There are different color themes from “Forest” to “Space” you can chose from to best fit your eyes.
You also have different table sizes going from “Micro” to “Huge” for better adjustment to the size of your display.
The default settings view show: Pocket Pivots, FT Days, MA50, RS Line and ATR Bands.
That's all, Enjoy!
Indicator: Profitability by Day & Hour (stacked, non-overlay)What it does
This tool performs a simple seasonality study on the selected symbol. It measures historical returns and summarizes them in two horizontal heatmaps:
Hours table (top) — Columns 00–23 show the average return of each clock hour, plus sample size, win rate, volatility (SD), and a t-score.
Days table (middle) — Columns 1–7 correspond to Mon–Sun with the same metrics.
Summary (bottom) — Shows the most profitable day and hour in the history loaded on your chart.
Green cells indicate higher average returns; red cells indicate lower/negative averages. The layout is centered on the screen, with the hours table above the days table for quick scanning.
How it works (methodology)
Returns: by default the indicator uses log returns ln(Ct/Ct-1) (you can switch to simple % if you prefer).
Daily aggregation (no look-ahead): day statistics are computed from completed daily closes via a higher timeframe request. Yesterday’s daily close vs. the prior day is added to the appropriate weekday bucket, preventing repaint/forward bias.
Hourly aggregation (intraday only): hour statistics are computed bar-to-bar on the current intraday timeframe and accumulated by clock hour (00–23) of the symbol’s exchange timezone.
Metrics per bucket:
Mean: average return in that bucket.
n: number of observations.
Win%: share of positive returns.
SD: standard deviation of returns (volatility proxy).
t-score: mean / SD * sqrt(n) — a quick stability signal (not a hypothesis test).
The indicator does not rely on future data and does not repaint past values.
Reading the tables
Start with the Mean row in each table: it’s color-mapped (red → yellow → green).
Check n (sample size). A bright green cell with very low n is less meaningful than a mild green cell with large n.
Use Win% and SD to judge consistency and noise.
t-score is a compact “signal-to-noise × sample size” measure; higher absolute values suggest more stable effects.
Typical observations traders look for (purely illustrative): for some equity indices, the first hour after the cash open can dominate; for FX/crypto, certain late-US or early-Asia hours sometimes stand out. Always verify on your symbol and timeframe.
Market Clarity Pro Market Clarity Pro — See Key Zones, Trend & Volume Signals
Spot yesterday’s High (Supply) and Low (Demand) instantly — and know exactly where big buyers and sellers are likely waiting.
Red zones = strong selling pressure.
Green zones = strong buying pressure.
Plus, a built-in trend line keeps you trading in the right direction and away from sudden reversals.
You’ll also see:
🔴 Red arrow — not a sell signal, but a sign of heavy sellers stepping in, with volume confirmation and a candle breaking the previous one.
🔵 Blue arrow — not a buy signal, but a sign of strong buyers stepping in, with volume confirmation and a candle breaking the previous one.
These arrows highlight potential volume spikes and breakouts for confirmation only — you still confirm with the higher time frame for more market clarity.
Break above supply. Possible uptrend.
Break below demand. Possible downtrend.
📌 Before using this tool, watch the tutorial video to learn exactly how to apply it and how to spot profitable trades with confidence.
Kelly Position Size CalculatorThis position sizing calculator implements the Kelly Criterion, developed by John L. Kelly Jr. at Bell Laboratories in 1956, to determine mathematically optimal position sizes for maximizing long-term wealth growth. Unlike arbitrary position sizing methods, this tool provides a scientifically solution based on your strategy's actual performance statistics and incorporates modern refinements from over six decades of academic research.
The Kelly Criterion addresses a fundamental question in capital allocation: "What fraction of capital should be allocated to each opportunity to maximize growth while avoiding ruin?" This question has profound implications for financial markets, where traders and investors constantly face decisions about optimal capital allocation (Van Tharp, 2007).
Theoretical Foundation
The Kelly Criterion for binary outcomes is expressed as f* = (bp - q) / b, where f* represents the optimal fraction of capital to allocate, b denotes the risk-reward ratio, p indicates the probability of success, and q represents the probability of loss (Kelly, 1956). This formula maximizes the expected logarithm of wealth, ensuring maximum long-term growth rate while avoiding the risk of ruin.
The mathematical elegance of Kelly's approach lies in its derivation from information theory. Kelly's original work was motivated by Claude Shannon's information theory (Shannon, 1948), recognizing that maximizing the logarithm of wealth is equivalent to maximizing the rate of information transmission. This connection between information theory and wealth accumulation provides a deep theoretical foundation for optimal position sizing.
The logarithmic utility function underlying the Kelly Criterion naturally embodies several desirable properties for capital management. It exhibits decreasing marginal utility, penalizes large losses more severely than it rewards equivalent gains, and focuses on geometric rather than arithmetic mean returns, which is appropriate for compounding scenarios (Thorp, 2006).
Scientific Implementation
This calculator extends beyond basic Kelly implementation by incorporating state of the art refinements from academic research:
Parameter Uncertainty Adjustment: Following Michaud (1989), the implementation applies Bayesian shrinkage to account for parameter estimation error inherent in small sample sizes. The adjustment formula f_adjusted = f_kelly × confidence_factor + f_conservative × (1 - confidence_factor) addresses the overconfidence bias documented by Baker and McHale (2012), where the confidence factor increases with sample size and the conservative estimate equals 0.25 (quarter Kelly).
Sample Size Confidence: The reliability of Kelly calculations depends critically on sample size. Research by Browne and Whitt (1996) provides theoretical guidance on minimum sample requirements, suggesting that at least 30 independent observations are necessary for meaningful parameter estimates, with 100 or more trades providing reliable estimates for most trading strategies.
Universal Asset Compatibility: The calculator employs intelligent asset detection using TradingView's built-in symbol information, automatically adapting calculations for different asset classes without manual configuration.
ASSET SPECIFIC IMPLEMENTATION
Equity Markets: For stocks and ETFs, position sizing follows the calculation Shares = floor(Kelly Fraction × Account Size / Share Price). This straightforward approach reflects whole share constraints while accommodating fractional share trading capabilities.
Foreign Exchange Markets: Forex markets require lot-based calculations following Lot Size = Kelly Fraction × Account Size / (100,000 × Base Currency Value). The calculator automatically handles major currency pairs with appropriate pip value calculations, following industry standards described by Archer (2010).
Futures Markets: Futures position sizing accounts for leverage and margin requirements through Contracts = floor(Kelly Fraction × Account Size / Margin Requirement). The calculator estimates margin requirements as a percentage of contract notional value, with specific adjustments for micro-futures contracts that have smaller sizes and reduced margin requirements (Kaufman, 2013).
Index and Commodity Markets: These markets combine characteristics of both equity and futures markets. The calculator automatically detects whether instruments are cash-settled or futures-based, applying appropriate sizing methodologies with correct point value calculations.
Risk Management Integration
The calculator integrates sophisticated risk assessment through two primary modes:
Stop Loss Integration: When fixed stop-loss levels are defined, risk calculation follows Risk per Trade = Position Size × Stop Loss Distance. This ensures that the Kelly fraction accounts for actual risk exposure rather than theoretical maximum loss, with stop-loss distance measured in appropriate units for each asset class.
Strategy Drawdown Assessment: For discretionary exit strategies, risk estimation uses maximum historical drawdown through Risk per Trade = Position Value × (Maximum Drawdown / 100). This approach assumes that individual trade losses will not exceed the strategy's historical maximum drawdown, providing a reasonable estimate for strategies with well-defined risk characteristics.
Fractional Kelly Approaches
Pure Kelly sizing can produce substantial volatility, leading many practitioners to adopt fractional Kelly approaches. MacLean, Sanegre, Zhao, and Ziemba (2004) analyze the trade-offs between growth rate and volatility, demonstrating that half-Kelly typically reduces volatility by approximately 75% while sacrificing only 25% of the growth rate.
The calculator provides three primary Kelly modes to accommodate different risk preferences and experience levels. Full Kelly maximizes growth rate while accepting higher volatility, making it suitable for experienced practitioners with strong risk tolerance and robust capital bases. Half Kelly offers a balanced approach popular among professional traders, providing optimal risk-return balance by reducing volatility significantly while maintaining substantial growth potential. Quarter Kelly implements a conservative approach with low volatility, recommended for risk-averse traders or those new to Kelly methodology who prefer gradual introduction to optimal position sizing principles.
Empirical Validation and Performance
Extensive academic research supports the theoretical advantages of Kelly sizing. Hakansson and Ziemba (1995) provide a comprehensive review of Kelly applications in finance, documenting superior long-term performance across various market conditions and asset classes. Estrada (2008) analyzes Kelly performance in international equity markets, finding that Kelly-based strategies consistently outperform fixed position sizing approaches over extended periods across 19 developed markets over a 30-year period.
Several prominent investment firms have successfully implemented Kelly-based position sizing. Pabrai (2007) documents the application of Kelly principles at Berkshire Hathaway, noting Warren Buffett's concentrated portfolio approach aligns closely with Kelly optimal sizing for high-conviction investments. Quantitative hedge funds, including Renaissance Technologies and AQR, have incorporated Kelly-based risk management into their systematic trading strategies.
Practical Implementation Guidelines
Successful Kelly implementation requires systematic application with attention to several critical factors:
Parameter Estimation: Accurate parameter estimation represents the greatest challenge in practical Kelly implementation. Brown (1976) notes that small errors in probability estimates can lead to significant deviations from optimal performance. The calculator addresses this through Bayesian adjustments and confidence measures.
Sample Size Requirements: Users should begin with conservative fractional Kelly approaches until achieving sufficient historical data. Strategies with fewer than 30 trades may produce unreliable Kelly estimates, regardless of adjustments. Full confidence typically requires 100 or more independent trade observations.
Market Regime Considerations: Parameters that accurately describe historical performance may not reflect future market conditions. Ziemba (2003) recommends regular parameter updates and conservative adjustments when market conditions change significantly.
Professional Features and Customization
The calculator provides comprehensive customization options for professional applications:
Multiple Color Schemes: Eight professional color themes (Gold, EdgeTools, Behavioral, Quant, Ocean, Fire, Matrix, Arctic) with dark and light theme compatibility ensure optimal visibility across different trading environments.
Flexible Display Options: Adjustable table size and position accommodate various chart layouts and user preferences, while maintaining analytical depth and clarity.
Comprehensive Results: The results table presents essential information including asset specifications, strategy statistics, Kelly calculations, sample confidence measures, position values, risk assessments, and final position sizes in appropriate units for each asset class.
Limitations and Considerations
Like any analytical tool, the Kelly Criterion has important limitations that users must understand:
Stationarity Assumption: The Kelly Criterion assumes that historical strategy statistics represent future performance characteristics. Non-stationary market conditions may invalidate this assumption, as noted by Lo and MacKinlay (1999).
Independence Requirement: Each trade should be independent to avoid correlation effects. Many trading strategies exhibit serial correlation in returns, which can affect optimal position sizing and may require adjustments for portfolio applications.
Parameter Sensitivity: Kelly calculations are sensitive to parameter accuracy. Regular calibration and conservative approaches are essential when parameter uncertainty is high.
Transaction Costs: The implementation incorporates user-defined transaction costs but assumes these remain constant across different position sizes and market conditions, following Ziemba (2003).
Advanced Applications and Extensions
Multi-Asset Portfolio Considerations: While this calculator optimizes individual position sizes, portfolio-level applications require additional considerations for correlation effects and aggregate risk management. Simplified portfolio approaches include treating positions independently with correlation adjustments.
Behavioral Factors: Behavioral finance research reveals systematic biases that can interfere with Kelly implementation. Kahneman and Tversky (1979) document loss aversion, overconfidence, and other cognitive biases that lead traders to deviate from optimal strategies. Successful implementation requires disciplined adherence to calculated recommendations.
Time-Varying Parameters: Advanced implementations may incorporate time-varying parameter models that adjust Kelly recommendations based on changing market conditions, though these require sophisticated econometric techniques and substantial computational resources.
Comprehensive Usage Instructions and Practical Examples
Implementation begins with loading the calculator on your desired trading instrument's chart. The system automatically detects asset type across stocks, forex, futures, and cryptocurrency markets while extracting current price information. Navigation to the indicator settings allows input of your specific strategy parameters.
Strategy statistics configuration requires careful attention to several key metrics. The win rate should be calculated from your backtest results using the formula of winning trades divided by total trades multiplied by 100. Average win represents the sum of all profitable trades divided by the number of winning trades, while average loss calculates the sum of all losing trades divided by the number of losing trades, entered as a positive number. The total historical trades parameter requires the complete number of trades in your backtest, with a minimum of 30 trades recommended for basic functionality and 100 or more trades optimal for statistical reliability. Account size should reflect your available trading capital, specifically the risk capital allocated for trading rather than total net worth.
Risk management configuration adapts to your specific trading approach. The stop loss setting should be enabled if you employ fixed stop-loss exits, with the stop loss distance specified in appropriate units depending on the asset class. For stocks, this distance is measured in dollars, for forex in pips, and for futures in ticks. When stop losses are not used, the maximum strategy drawdown percentage from your backtest provides the risk assessment baseline. Kelly mode selection offers three primary approaches: Full Kelly for aggressive growth with higher volatility suitable for experienced practitioners, Half Kelly for balanced risk-return optimization popular among professional traders, and Quarter Kelly for conservative approaches with reduced volatility.
Display customization ensures optimal integration with your trading environment. Eight professional color themes provide optimization for different chart backgrounds and personal preferences. Table position selection allows optimal placement within your chart layout, while table size adjustment ensures readability across different screen resolutions and viewing preferences.
Detailed Practical Examples
Example 1: SPY Swing Trading Strategy
Consider a professionally developed swing trading strategy for SPY (S&P 500 ETF) with backtesting results spanning 166 total trades. The strategy achieved 110 winning trades, representing a 66.3% win rate, with an average winning trade of $2,200 and average losing trade of $862. The maximum drawdown reached 31.4% during the testing period, and the available trading capital amounts to $25,000. This strategy employs discretionary exits without fixed stop losses.
Implementation requires loading the calculator on the SPY daily chart and configuring the parameters accordingly. The win rate input receives 66.3, while average win and loss inputs receive 2200 and 862 respectively. Total historical trades input requires 166, with account size set to 25000. The stop loss function remains disabled due to the discretionary exit approach, with maximum strategy drawdown set to 31.4%. Half Kelly mode provides the optimal balance between growth and risk management for this application.
The calculator generates several key outputs for this scenario. The risk-reward ratio calculates automatically to 2.55, while the Kelly fraction reaches approximately 53% before scientific adjustments. Sample confidence achieves 100% given the 166 trades providing high statistical confidence. The recommended position settles at approximately 27% after Half Kelly and Bayesian adjustment factors. Position value reaches approximately $6,750, translating to 16 shares at a $420 SPY price. Risk per trade amounts to approximately $2,110, representing 31.4% of position value, with expected value per trade reaching approximately $1,466. This recommendation represents the mathematically optimal balance between growth potential and risk management for this specific strategy profile.
Example 2: EURUSD Day Trading with Stop Losses
A high-frequency EURUSD day trading strategy demonstrates different parameter requirements compared to swing trading approaches. This strategy encompasses 89 total trades with a 58% win rate, generating an average winning trade of $180 and average losing trade of $95. The maximum drawdown reached 12% during testing, with available capital of $10,000. The strategy employs fixed stop losses at 25 pips and take profit targets at 45 pips, providing clear risk-reward parameters.
Implementation begins with loading the calculator on the EURUSD 1-hour chart for appropriate timeframe alignment. Parameter configuration includes win rate at 58, average win at 180, and average loss at 95. Total historical trades input receives 89, with account size set to 10000. The stop loss function is enabled with distance set to 25 pips, reflecting the fixed exit strategy. Quarter Kelly mode provides conservative positioning due to the smaller sample size compared to the previous example.
Results demonstrate the impact of smaller sample sizes on Kelly calculations. The risk-reward ratio calculates to 1.89, while the Kelly fraction reaches approximately 32% before adjustments. Sample confidence achieves 89%, providing moderate statistical confidence given the 89 trades. The recommended position settles at approximately 7% after Quarter Kelly application and Bayesian shrinkage adjustment for the smaller sample. Position value amounts to approximately $700, translating to 0.07 standard lots. Risk per trade reaches approximately $175, calculated as 25 pips multiplied by lot size and pip value, with expected value per trade at approximately $49. This conservative position sizing reflects the smaller sample size, with position sizes expected to increase as trade count surpasses 100 and statistical confidence improves.
Example 3: ES1! Futures Systematic Strategy
Systematic futures trading presents unique considerations for Kelly criterion application, as demonstrated by an E-mini S&P 500 futures strategy encompassing 234 total trades. This systematic approach achieved a 45% win rate with an average winning trade of $1,850 and average losing trade of $720. The maximum drawdown reached 18% during the testing period, with available capital of $50,000. The strategy employs 15-tick stop losses with contract specifications of $50 per tick, providing precise risk control mechanisms.
Implementation involves loading the calculator on the ES1! 15-minute chart to align with the systematic trading timeframe. Parameter configuration includes win rate at 45, average win at 1850, and average loss at 720. Total historical trades receives 234, providing robust statistical foundation, with account size set to 50000. The stop loss function is enabled with distance set to 15 ticks, reflecting the systematic exit methodology. Half Kelly mode balances growth potential with appropriate risk management for futures trading.
Results illustrate how favorable risk-reward ratios can support meaningful position sizing despite lower win rates. The risk-reward ratio calculates to 2.57, while the Kelly fraction reaches approximately 16%, lower than previous examples due to the sub-50% win rate. Sample confidence achieves 100% given the 234 trades providing high statistical confidence. The recommended position settles at approximately 8% after Half Kelly adjustment. Estimated margin per contract amounts to approximately $2,500, resulting in a single contract allocation. Position value reaches approximately $2,500, with risk per trade at $750, calculated as 15 ticks multiplied by $50 per tick. Expected value per trade amounts to approximately $508. Despite the lower win rate, the favorable risk-reward ratio supports meaningful position sizing, with single contract allocation reflecting appropriate leverage management for futures trading.
Example 4: MES1! Micro-Futures for Smaller Accounts
Micro-futures contracts provide enhanced accessibility for smaller trading accounts while maintaining identical strategy characteristics. Using the same systematic strategy statistics from the previous example but with available capital of $15,000 and micro-futures specifications of $5 per tick with reduced margin requirements, the implementation demonstrates improved position sizing granularity.
Kelly calculations remain identical to the full-sized contract example, maintaining the same risk-reward dynamics and statistical foundations. However, estimated margin per contract reduces to approximately $250 for micro-contracts, enabling allocation of 4-5 micro-contracts. Position value reaches approximately $1,200, while risk per trade calculates to $75, derived from 15 ticks multiplied by $5 per tick. This granularity advantage provides better position size precision for smaller accounts, enabling more accurate Kelly implementation without requiring large capital commitments.
Example 5: Bitcoin Swing Trading
Cryptocurrency markets present unique challenges requiring modified Kelly application approaches. A Bitcoin swing trading strategy on BTCUSD encompasses 67 total trades with a 71% win rate, generating average winning trades of $3,200 and average losing trades of $1,400. Maximum drawdown reached 28% during testing, with available capital of $30,000. The strategy employs technical analysis for exits without fixed stop losses, relying on price action and momentum indicators.
Implementation requires conservative approaches due to cryptocurrency volatility characteristics. Quarter Kelly mode is recommended despite the high win rate to account for crypto market unpredictability. Expected position sizing remains reduced due to the limited sample size of 67 trades, requiring additional caution until statistical confidence improves. Regular parameter updates are strongly recommended due to cryptocurrency market evolution and changing volatility patterns that can significantly impact strategy performance characteristics.
Advanced Usage Scenarios
Portfolio position sizing requires sophisticated consideration when running multiple strategies simultaneously. Each strategy should have its Kelly fraction calculated independently to maintain mathematical integrity. However, correlation adjustments become necessary when strategies exhibit related performance patterns. Moderately correlated strategies should receive individual position size reductions of 10-20% to account for overlapping risk exposure. Aggregate portfolio risk monitoring ensures total exposure remains within acceptable limits across all active strategies. Professional practitioners often consider using lower fractional Kelly approaches, such as Quarter Kelly, when running multiple strategies simultaneously to provide additional safety margins.
Parameter sensitivity analysis forms a critical component of professional Kelly implementation. Regular validation procedures should include monthly parameter updates using rolling 100-trade windows to capture evolving market conditions while maintaining statistical relevance. Sensitivity testing involves varying win rates by ±5% and average win/loss ratios by ±10% to assess recommendation stability under different parameter assumptions. Out-of-sample validation reserves 20% of historical data for parameter verification, ensuring that optimization doesn't create curve-fitted results. Regime change detection monitors actual performance against expected metrics, triggering parameter reassessment when significant deviations occur.
Risk management integration requires professional overlay considerations beyond pure Kelly calculations. Daily loss limits should cease trading when daily losses exceed twice the calculated risk per trade, preventing emotional decision-making during adverse periods. Maximum position limits should never exceed 25% of account value in any single position regardless of Kelly recommendations, maintaining diversification principles. Correlation monitoring reduces position sizes when holding multiple correlated positions that move together during market stress. Volatility adjustments consider reducing position sizes during periods of elevated VIX above 25 for equity strategies, adapting to changing market conditions.
Troubleshooting and Optimization
Professional implementation often encounters specific challenges requiring systematic troubleshooting approaches. Zero position size displays typically result from insufficient capital for minimum position sizes, negative expected values, or extremely conservative Kelly calculations. Solutions include increasing account size, verifying strategy statistics for accuracy, considering Quarter Kelly mode for conservative approaches, or reassessing overall strategy viability when fundamental issues exist.
Extremely high Kelly fractions exceeding 50% usually indicate underlying problems with parameter estimation. Common causes include unrealistic win rates, inflated risk-reward ratios, or curve-fitted backtest results that don't reflect genuine trading conditions. Solutions require verifying backtest methodology, including all transaction costs in calculations, testing strategies on out-of-sample data, and using conservative fractional Kelly approaches until parameter reliability improves.
Low sample confidence below 50% reflects insufficient historical trades for reliable parameter estimation. This situation demands gathering additional trading data, using Quarter Kelly approaches until reaching 100 or more trades, applying extra conservatism in position sizing, and considering paper trading to build statistical foundations without capital risk.
Inconsistent results across similar strategies often stem from parameter estimation differences, market regime changes, or strategy degradation over time. Professional solutions include standardizing backtest methodology across all strategies, updating parameters regularly to reflect current conditions, and monitoring live performance against expectations to identify deteriorating strategies.
Position sizes that appear inappropriately large or small require careful validation against traditional risk management principles. Professional standards recommend never risking more than 2-3% per trade regardless of Kelly calculations. Calibration should begin with Quarter Kelly approaches, gradually increasing as comfort and confidence develop. Most institutional traders utilize 25-50% of full Kelly recommendations to balance growth with prudent risk management.
Market condition adjustments require dynamic approaches to Kelly implementation. Trending markets may support full Kelly recommendations when directional momentum provides favorable conditions. Ranging or volatile markets typically warrant reducing to Half or Quarter Kelly to account for increased uncertainty. High correlation periods demand reducing individual position sizes when multiple positions move together, concentrating risk exposure. News and event periods often justify temporary position size reductions during high-impact releases that can create unpredictable market movements.
Performance monitoring requires systematic protocols to ensure Kelly implementation remains effective over time. Weekly reviews should compare actual versus expected win rates and average win/loss ratios to identify parameter drift or strategy degradation. Position size efficiency and execution quality monitoring ensures that calculated recommendations translate effectively into actual trading results. Tracking correlation between calculated and realized risk helps identify discrepancies between theoretical and practical risk exposure.
Monthly calibration provides more comprehensive parameter assessment using the most recent 100 trades to maintain statistical relevance while capturing current market conditions. Kelly mode appropriateness requires reassessment based on recent market volatility and performance characteristics, potentially shifting between Full, Half, and Quarter Kelly approaches as conditions change. Transaction cost evaluation ensures that commission structures, spreads, and slippage estimates remain accurate and current.
Quarterly strategic reviews encompass comprehensive strategy performance analysis comparing long-term results against expectations and identifying trends in effectiveness. Market regime assessment evaluates parameter stability across different market conditions, determining whether strategy characteristics remain consistent or require fundamental adjustments. Strategic modifications to position sizing methodology may become necessary as markets evolve or trading approaches mature, ensuring that Kelly implementation continues supporting optimal capital allocation objectives.
Professional Applications
This calculator serves diverse professional applications across the financial industry. Quantitative hedge funds utilize the implementation for systematic position sizing within algorithmic trading frameworks, where mathematical precision and consistent application prove essential for institutional capital management. Professional discretionary traders benefit from optimized position management that removes emotional bias while maintaining flexibility for market-specific adjustments. Portfolio managers employ the calculator for developing risk-adjusted allocation strategies that enhance returns while maintaining prudent risk controls across diverse asset classes and investment strategies.
Individual traders seeking mathematical optimization of capital allocation find the calculator provides institutional-grade methodology previously available only to professional money managers. The Kelly Criterion establishes theoretical foundation for optimal capital allocation across both single strategies and multiple trading systems, offering significant advantages over arbitrary position sizing methods that rely on intuition or fixed percentage approaches. Professional implementation ensures consistent application of mathematically sound principles while adapting to changing market conditions and strategy performance characteristics.
Conclusion
The Kelly Criterion represents one of the few mathematically optimal solutions to fundamental investment problems. When properly understood and carefully implemented, it provides significant competitive advantage in financial markets. This calculator implements modern refinements to Kelly's original formula while maintaining accessibility for practical trading applications.
Success with Kelly requires ongoing learning, systematic application, and continuous refinement based on market feedback and evolving research. Users who master Kelly principles and implement them systematically can expect superior risk-adjusted returns and more consistent capital growth over extended periods.
The extensive academic literature provides rich resources for deeper study, while practical experience builds the intuition necessary for effective implementation. Regular parameter updates, conservative approaches with limited data, and disciplined adherence to calculated recommendations are essential for optimal results.
References
Archer, M. D. (2010). Getting Started in Currency Trading: Winning in Today's Forex Market (3rd ed.). John Wiley & Sons.
Baker, R. D., & McHale, I. G. (2012). An empirical Bayes approach to optimising betting strategies. Journal of the Royal Statistical Society: Series D (The Statistician), 61(1), 75-92.
Breiman, L. (1961). Optimal gambling systems for favorable games. In J. Neyman (Ed.), Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability (pp. 65-78). University of California Press.
Brown, D. B. (1976). Optimal portfolio growth: Logarithmic utility and the Kelly criterion. In W. T. Ziemba & R. G. Vickson (Eds.), Stochastic Optimization Models in Finance (pp. 1-23). Academic Press.
Browne, S., & Whitt, W. (1996). Portfolio choice and the Bayesian Kelly criterion. Advances in Applied Probability, 28(4), 1145-1176.
Estrada, J. (2008). Geometric mean maximization: An overlooked portfolio approach? The Journal of Investing, 17(4), 134-147.
Hakansson, N. H., & Ziemba, W. T. (1995). Capital growth theory. In R. A. Jarrow, V. Maksimovic, & W. T. Ziemba (Eds.), Handbooks in Operations Research and Management Science (Vol. 9, pp. 65-86). Elsevier.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Kaufman, P. J. (2013). Trading Systems and Methods (5th ed.). John Wiley & Sons.
Kelly Jr, J. L. (1956). A new interpretation of information rate. Bell System Technical Journal, 35(4), 917-926.
Lo, A. W., & MacKinlay, A. C. (1999). A Non-Random Walk Down Wall Street. Princeton University Press.
MacLean, L. C., Sanegre, E. O., Zhao, Y., & Ziemba, W. T. (2004). Capital growth with security. Journal of Economic Dynamics and Control, 28(4), 937-954.
MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific.
Michaud, R. O. (1989). The Markowitz optimization enigma: Is 'optimized' optimal? Financial Analysts Journal, 45(1), 31-42.
Pabrai, M. (2007). The Dhandho Investor: The Low-Risk Value Method to High Returns. John Wiley & Sons.
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423.
Tharp, V. K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill.
Thorp, E. O. (2006). The Kelly criterion in blackjack sports betting, and the stock market. In L. C. MacLean, E. O. Thorp, & W. T. Ziemba (Eds.), The Kelly Capital Growth Investment Criterion: Theory and Practice (pp. 789-832). World Scientific.
Van Tharp, K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill Education.
Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons.
Vince, R., & Zhu, H. (2015). Optimal betting under parameter uncertainty. Journal of Statistical Planning and Inference, 161, 19-31.
Ziemba, W. T. (2003). The Stochastic Programming Approach to Asset, Liability, and Wealth Management. The Research Foundation of AIMR.
Further Reading
For comprehensive understanding of Kelly Criterion applications and advanced implementations:
MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific.
Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons.
Thorp, E. O. (2017). A Man for All Markets: From Las Vegas to Wall Street. Random House.
Cover, T. M., & Thomas, J. A. (2006). Elements of Information Theory (2nd ed.). John Wiley & Sons.
Ziemba, W. T., & Vickson, R. G. (Eds.). (2006). Stochastic Optimization Models in Finance. World Scientific.
Risk Appetite IndexWhat This Indicator Does
The Risk Appetite Index measures market participants' willingness to take risk by analyzing multiple market factors. This indicator attempts to provide insights into overall market sentiment by combining information from different market segments into a single composite measure.
How It Works
The indicator uses a multi-factor approach that examines various aspects of market behavior including equity market conditions, interest rate environments, credit markets, volatility patterns, and other relevant market data. These factors are processed and combined to create a composite reading on a 0-100 scale.
Theoretical Foundation
The methodology is grounded in established financial theories including Modern Portfolio Theory principles for risk assessment, behavioral finance concepts regarding market sentiment cycles, and factor investing approaches for multi-dimensional market analysis. The indicator incorporates insights from academic research on market microstructure, volatility clustering phenomena, and cross-asset correlation patterns during different market regimes.
The approach draws from research on fear and greed cycles in financial markets, term structure modeling, and credit risk assessment methodologies. Statistical techniques employed include robust normalization methods and composite index construction principles established in econometric literature.
The methodology employs statistical techniques to normalize the different market inputs and reduce the impact of extreme values. The final output aims to reflect the general level of risk appetite present in financial markets.
Signal Interpretation
Values above 60 may suggest higher risk appetite conditions in markets. Values below 30 may indicate lower risk appetite environments. The 30-60 range represents neutral or mixed conditions where market sentiment may be unclear.
The indicator includes threshold levels that may help identify potential changes in market conditions. However, like all technical indicators, these levels should be considered as potential reference points rather than definitive signals.
Research Context
The approach builds upon established sentiment measurement methodologies documented in financial literature, including studies on VIX-based fear indicators, credit spread analysis, yield curve interpretation, and cross-asset momentum research. The multi-factor design reflects principles from academic research on composite economic indicators and systematic risk assessment frameworks used by central banks and institutional investors.
The threshold-based signal generation follows established precedents in quantitative finance research regarding regime detection and market state classification methodologies documented in institutional portfolio management literature.
Key Features
Analytics Dashboard: Displays real-time information about current readings, market regime assessment, and signal quality indicators.
Visual Tools: Multiple color schemes and background options to help visualize current market conditions and trends.
Alert System: Optional alerts for threshold crossings and regime changes to help monitor market conditions.
Quality Assessment: Built-in filters attempt to distinguish between higher and lower confidence readings based on data quality and market conditions.
How to Use
This indicator is designed to be used on daily timeframes and displays in a separate panel below the main chart. It works best when used as part of a comprehensive market analysis approach rather than as a standalone trading tool.
The dashboard provides additional context about current readings and may help users understand the quality and reliability of current signals. Users should consider multiple factors and conduct their own analysis when making trading decisions.
Important Considerations
This indicator is designed for educational and analytical purposes. It does not guarantee profitable trading results and should not be used as the sole basis for trading decisions.
Market conditions can change rapidly and unpredictably. Past behavior of any indicator does not predict future market movements. All trading involves substantial risk and may not be suitable for all investors.
The indicator's effectiveness may vary across different market environments and conditions. Users should consider their own risk tolerance and investment objectives when using any analytical tool.
Data Limitations
The indicator relies on multiple external data sources and may be affected by data quality, market holidays, or limited trading hours. Performance may vary during unusual market conditions or structural changes in financial markets.
Like all quantitative models, this indicator has inherent limitations and may not capture all relevant market factors or unprecedented market events.
Intended Use
This indicator may be useful for traders and analysts seeking additional tools for market sentiment analysis. It is designed for those who want to incorporate multiple market factors into their decision-making process.
Academic Research Foundation
The development approach incorporates established research methodologies from quantitative finance literature. Key theoretical frameworks include:
Factor Models: Based on research into multi-factor asset pricing models and their application to portfolio construction and risk management practices developed in academic finance literature.
Behavioral Finance: Incorporates findings from behavioral economics research on market anomalies, investor psychology, and sentiment-driven market movements as documented in financial psychology studies.
Market Microstructure: Utilizes principles from market microstructure research regarding information flow, price discovery mechanisms, and cross-market relationships established in institutional finance literature.
Risk Management: Built upon established risk measurement frameworks including Value at Risk methodologies, stress testing approaches, and systematic risk assessment techniques documented in risk management research.
Econometric Methods: Employs statistical techniques based on time series analysis, robust estimation methods, and composite index construction principles established in econometric literature and central bank research methodologies.
The proprietary methodology combines various market inputs in an attempt to provide insights into overall risk appetite trends, though results may vary and should always be considered alongside other forms of analysis.
Risk Warnings
Past performance does not guarantee future results. All trading involves substantial risk of loss. This indicator does not eliminate market risk and should be used as part of a comprehensive trading plan. Market conditions can change rapidly and unexpectedly. No indicator is accurate in all market conditions.
Technical Requirements
Optimal use on daily charts with TradingView Pro or higher for real-time data access. Designed primarily for US equity market analysis during regular trading hours.
Note: This is a closed-source indicator with proprietary calculation methods designed to maintain effectiveness and provide users with a unique analytical tool.
Clean Multi-Indicator Alignment System
Overview
A sophisticated multi-indicator alignment system designed for 24/7 trading across all markets, with pure signal-based exits and no time restrictions. Perfect for futures, forex, and crypto markets that operate around the clock.
Key Features
🎯 Multi-Indicator Confluence System
EMA Cross Strategy: Fast EMA (5) and Slow EMA (10) for precise trend direction
VWAP Integration: Institution-level price positioning analysis
RSI Momentum: 7-period RSI for momentum confirmation and reversal detection
MACD Signals: Optimized 8/17/5 configuration for scalping responsiveness
Volume Confirmation: Customizable volume multiplier (default 1.6x) for signal validation
🚀 Advanced Entry Logic
Initial Full Alignment: Requires all 5 indicators + volume confirmation
Smart Continuation Entries: EMA9 pullback entries when trend momentum remains intact
Flexible Time Controls: Optional session filtering or 24/7 operation
🎪 Pure Signal-Based Exits
No Forced Closes: Positions exit only on technical signal reversals
Dual Exit Conditions: EMA9 breakdown + RSI flip OR MACD cross + EMA20 breakdown
Trend Following: Allows profitable trends to run their full course
Perfect for Swing Scalping: Ideal for multi-session position holding
📊 Visual Interface
Real-Time Status Dashboard: Live alignment monitoring for all indicators
Color-Coded Candles: Instant visual confirmation of entry/exit signals
Clean Chart Display: Toggle-able EMAs and VWAP with professional styling
Signal Differentiation: Clear labels for entries, X-crosses for exits
🔔 Alert System
Entry Notifications: Separate alerts for buy/sell signals
Exit Warnings: Technical breakdown alerts for position management
Mobile Ready: Push notifications to TradingView mobile app
Market Applications
Perfect For:
Gold Futures (GC): 24-hour precious metals trading
NASDAQ Futures (NQ): High-volatility index scalping
Forex Markets: Currency pairs with continuous operation
Crypto Trading: 24/7 cryptocurrency momentum plays
Energy Futures: Oil, gas, and commodity swing trades
Optimal Timeframes:
1-5 Minutes: Ultra-fast scalping during high volatility
5-15 Minutes: Balanced approach for most markets
15-30 Minutes: Swing scalping for trend following
🧠 Smart Position Management
Tracks implied position direction
Prevents conflicting signals
Allows trend continuation entries
State-aware exit logic
⚡ Scalping Optimized
Fast-reacting indicators with shorter periods
Volume-based confirmation reduces false signals
Clean entry/exit visualization
Minimal lag for time-sensitive trades
Configuration Options
All parameters fully customizable:
EMA Lengths: Adjustable from 1-30 periods
RSI Period: 1-14 range for different market conditions
MACD Settings: Fast (1-15), Slow (1-30), Signal (1-10)
Volume Confirmation: 0.5-5.0x multiplier range
Visual Preferences: Colors, displays, and table options
Risk Management Features
Clear visual exit signals prevent emotion-based decisions
Volume confirmation reduces false breakouts
Multi-indicator confluence improves signal quality
Optional time filtering for session-specific strategies
Best Use Cases
Futures Scalping: NQ, ES, GC during active sessions
Forex Swing Trading: Major pairs during overlap periods
Crypto Momentum: Bitcoin, Ethereum trend following
24/7 Automated Systems: Algorithmic trading implementation
Multi-Market Scanning: Portfolio-wide signal monitoring
AI-Powered ScalpMaster Pro [By TraderMan]🧠 AI-Powered ScalpMaster Pro How It Works
📊 What Is the Indicator and What Does It Do?
🧠 AI-Powered ScalpMaster Pro is a powerful technical analysis tool designed for scalping (short-term, fast-paced trading) in financial markets such as forex, crypto, or stocks. It combines multiple technical indicators (RSI, MACD, Stochastic, Momentum, EMA, SuperTrend, CCI, and OBV) to identify market trends and generate AI-driven buy (🟢) or sell (🔴) signals. The goal is to help traders seize profitable scalping opportunities with quick and precise decisions. 🚀
Key Features:
🧠 AI-Driven Logic: Analyzes signals from multiple indicators to produce reliable trend signals.
📈 Signal Strength: Displays buy (bull) and sell (bear) signal strength as percentages.
✅ Success Rate: Tracks the performance of the last 5 trades and calculates the success rate.
🎯 Entry, TP, and SL Levels: Automatically sets entry points, take profit (TP), and stop loss (SL) levels.
📏 EMA Zone: Analyzes price movement around the EMA 200 to confirm trend direction.
⚙️ How Does It Work?
The indicator uses a scoring system by combining the following technical indicators:
RSI (14): Evaluates whether the price is in overbought or oversold zones.
MACD (12, 26, 9): Analyzes trend direction and momentum.
Stochastic (%K): Measures the speed of price movement.
Momentum: Checks the price change over the last 10 bars.
EMA 200: Determines the long-term trend direction.
SuperTrend: Tracks trends based on volatility.
CCI (20): Measures price deviation from its normal range.
OBV ROC: Analyzes volume changes.
Each indicator generates a buy (bull) or sell (bear) signal. If 6 or more indicators align in the same direction (e.g., bullScore >= 6 for buy), the indicator produces a strong trend signal:
📈 Strong Buy Signal: bullScore >= 6 and bullScore > bearScore.
📉 Strong Sell Signal: bearScore >= 6 and bearScore > bullScore.
🔸 Neutral: No dominant direction.
Additionally, the EMA Zone feature confirms the trend based on the price’s position relative to a zone around the EMA 200:
Price above the zone and sufficiently distant → Uptrend (UP). 🟢
Price below the zone and sufficiently distant → Downtrend (DOWN). 🔴
Price within the zone → Neutral. 🔸
🖥️ Display on the Chart
Table: A table in the top-right corner shows the status of all indicators (✅ Buy / ❌ Sell), signal strength (as %), success rate, and results of the last 5 trades.
Lines and Labels:
🎯 Entry Level: A gray line at the price level when a new signal is generated.
🟢 TP (Take Profit): A green line showing the take-profit level.
🔴 SL (Stop Loss): A red line showing the stop-loss level.
EMA Zone: The EMA 200 and its surrounding colored zone visualize the trend direction (green: uptrend, red: downtrend, gray: neutral).
📝 How to Use It?
Platform Setup:
Add the indicator to the TradingView platform.
Customize settings as needed (e.g., EMA length, risk/reward ratio).
Monitoring Signals:
Check the table: Look for 📈 STRONG BUY or 📉 STRONG SELL signals to prepare for a trade.
AI Text: Trust signals more when it says "🧠 FULL CONFIDENCE" (success rate ≥ 50%). Be cautious if it says "⚠️ LOW CONFIDENCE."
Entering a Position:
🟢 Buy Signal:
Table shows "📈 STRONG BUY" and bullScore >= 6.
Price is above the EMA Zone (green zone).
Entry: Current price (🎯 entry line).
TP: 2% above the entry price (🟢 TP line).
SL: 1% below the entry price (🔴 SL line).
🔴 Sell Signal:
Table shows "📉 STRONG SELL" and bearScore >= 6.
Price is below the EMA Zone (red zone).
Entry: Current price (🎯 entry line).
TP: 2% below the entry price (🟢 TP line).
SL: 1% above the entry price (🔴 SL line).
Position Management:
If the price hits TP, the trade closes profitably (✅ Successful).
If the price hits SL, the trade closes with a loss (❌ Failed).
Results are updated in the "Last 5 Trades" section of the table.
Risk Management:
Default risk/reward ratio is 1:2 (1% risk, 2% reward).
Always adjust position size based on your capital.
Consider smaller lot sizes for "⚠️ LOW CONFIDENCE" signals.
💡 Tips
Timeframe: Use 1-minute, 5-minute, or 15-minute charts for scalping.
Market Selection: Works best in volatile markets (e.g., BTC/USD, EUR/USD).
Confirmation: Ensure the EMA Zone trend aligns with the signal.
Discipline: Stick to TP and SL levels, avoid emotional decisions.
⚠️ Warnings
No indicator is 100% accurate. Always use additional analysis (e.g., support/resistance).
Be cautious during high-volatility periods (e.g., news events).
The success rate is based on past performance and does not guarantee future results.
Mutanabby_AI | Fresh Algo V24Mutanabby_AI | Fresh Algo V24: Advanced Multi-Mode Trading System
Overview
The Mutanabby_AI Fresh Algo V24 represents a sophisticated evolution of multi-component trading systems that adapts to various market conditions through advanced operational configurations and enhanced analytical capabilities. This comprehensive indicator provides traders with multiple signal generation approaches, specialized assistant functions, and dynamic risk management tools designed for professional market analysis across diverse trading environments.
Primary Signal Generation Framework
The Fresh Algo V24 operates through two fundamental signal generation approaches that accommodate different market perspectives and trading philosophies. The Trending Signals Mode serves as the primary trend-following mechanism, combining Wave Trend Oscillator analysis with Supertrend directional signals and Squeeze Momentum breakout detection. This mode incorporates ADX filtering that requires values exceeding 20 to ensure sufficient trend strength exists before signal activation, making it particularly effective during sustained directional market movements where momentum persistence creates profitable trading opportunities.
The Contrarian Signals Mode provides an alternative approach targeting reversal opportunities through extreme market condition identification. This mode activates when the Wave Trend Oscillator reaches critical threshold levels, specifically when readings surpass 65 indicating potential bearish reversal conditions or drop below 35 suggesting bullish reversal opportunities. This methodology proves valuable during overextended market phases where mean reversion becomes statistically probable.
Advanced Filtering Mechanisms
The system incorporates multiple sophisticated filtering mechanisms designed to enhance signal quality and reduce false positive occurrences. The High Volume Filter requires volume expansion confirmation before signal activation, utilizing exponential moving average calculations to ensure institutional participation accompanies price movements. This filter substantially improves signal reliability by eliminating low-conviction breakouts that lack adequate volume support from professional market participants.
The Strong Filter provides additional trend confirmation through 200-period exponential moving average analysis. Long position signals require price action above this benchmark level, while short position signals necessitate price action below it. This ensures strategic alignment with longer-term trend direction and reduces the probability of trading against major market movements that could invalidate shorter-term signals.
Cloud Filter Configuration System
The Fresh Algo V24 offers four distinct cloud filter configurations, each optimized for specific trading timeframes and market approaches. The Smooth Cloud Filter utilizes the mathematical relationship between 150-period and 250-period exponential moving averages, providing stable trend identification suitable for position trading strategies. This configuration generates signals exclusively when price action aligns with cloud direction, creating a more deliberate but highly reliable signal generation process.
The Swing Cloud Filter employs modified Supertrend calculations with parameters specifically optimized for swing trading timeframes. This filter achieves optimal balance between responsiveness and stability, adapting effectively to medium-term price movements while filtering excessive market noise that typically affects shorter-term analytical systems.
For active intraday traders, the Scalping Cloud Filter utilizes accelerated Supertrend calculations designed to capture rapid trend changes effectively. This configuration provides enhanced signal generation frequency suitable for compressed timeframe strategies. The advanced Scalping+ Cloud Filter incorporates Hull Moving Average confirmation, delivering maximum responsiveness for ultra-short-term trading while maintaining signal quality through additional momentum validation processes.
Specialized Assistant Functionality
The system includes two distinct assistant modes that provide supplementary market analysis capabilities. The Trend Assistant Mode activates advanced cloud analysis overlays that display dynamic support and resistance zones calculated through adaptive volatility algorithms. These levels automatically adjust to current market conditions, providing visual guidance for identifying trend continuation patterns and potential reversal areas with mathematical precision.
The Trend Tracker Mode concentrates on long-term trend identification by displaying major exponential moving averages with color-coded fill areas that clarify directional bias. This mode maintains visual simplicity while providing comprehensive trend context evaluation, enabling traders to quickly assess broader market direction and align shorter-term strategies accordingly.
Dynamic Risk Management System
The integrated risk management system automatically adapts across all operational modes, calculating stop loss and take profit targets using Average True Range multiples that adjust to current market volatility. This approach ensures consistent risk parameters regardless of selected operational mode while maintaining relevance to prevailing market conditions.
Stop loss placement occurs at dynamically calculated distances from entry points, while three progressive take profit targets establish at customizable ATR multiples respectively. The system automatically updates these levels upon trend direction changes, ensuring current market volatility influences all risk calculations and maintains appropriate risk-reward ratios throughout trade management.
Comprehensive Market Analysis Dashboard
The sophisticated dashboard provides real-time market analysis including volatility measurements, institutional activity assessment, and multi-timeframe trend evaluation across five-minute through four-hour periods. This comprehensive market context assists traders in selecting appropriate operational modes based on current market characteristics rather than relying exclusively on historical performance data.
The multi-timeframe analysis ensures mode selection considers broader market context beyond the primary trading timeframe, improving overall strategic alignment and reducing conflicts between different temporal market perspectives. The dashboard displays market state classification, volatility percentages, institutional activity levels, current trading session information, and trend pressure indicators with professional formatting and clear visual hierarchy.
Enhanced Trading Assistants
The Fresh Algo V24 includes specialized trading assistant features that complement the primary signal generation system. The Reversal Dot functionality identifies potential reversal points through Wave Trend Oscillator analysis, displaying visual indicators when crossover conditions occur at extreme levels. These reversal indicators provide early warning signals for potential trend changes before they appear in the primary signal system.
The Dynamic Take Profit Labels feature automatically identifies optimal profit-taking opportunities through RSI threshold analysis, marking potential exit points at multiple levels for long positions and corresponding levels for short positions. This automated profit management system helps traders optimize exit timing without requiring constant manual monitoring of technical indicators.
Advanced Alert System
The comprehensive alert system accommodates all operational modes while providing granular notification control for various signal types and risk management events. Traders can configure separate alerts for normal buy signals, strong buy signals, normal sell signals, strong sell signals, stop loss triggers, and individual take profit target achievements.
Cloud crossover alerts notify traders when trend direction changes occur, providing early indication of potential strategy adjustments. The alert system includes detailed trade setup information, timeframe data, and relevant entry and exit levels, ensuring traders receive complete context for informed decision-making without requiring constant chart monitoring.
Technical Foundation Architecture
The Fresh Algo V24 combines multiple proven technical analysis components including Wave Trend Oscillator for momentum assessment, Supertrend for directional bias determination, Squeeze Momentum for volatility analysis, and various exponential moving averages for trend confirmation. Each component contributes specific market insights while the unified system provides comprehensive market evaluation through their mathematical integration.
The multi-component approach reduces dependency on individual indicator limitations while leveraging the analytical strengths of each technical tool. This creates a robust analytical framework capable of adapting to diverse market conditions through appropriate mode selection and parameter optimization, ensuring consistent performance across varying market environments.
Market State Classification
The indicator incorporates advanced market state classification through ADX analysis, distinguishing between trending, ranging, and transitional market conditions. This classification system automatically adjusts signal sensitivity and filtering parameters based on current market characteristics, optimizing performance for prevailing conditions rather than applying static analytical approaches.
The volatility measurement system calculates current market activity levels as percentages, providing quantitative assessment of market energy and helping traders select appropriate operational modes. Institutional activity detection through volume analysis ensures signal generation aligns with professional market participation patterns.
Implementation Strategy Considerations
Successful implementation requires careful matching of operational modes to prevailing market conditions and individual trading objectives. Trending modes demonstrate optimal performance during directional markets with sustained momentum characteristics, while contrarian modes excel during range-bound or overextended market conditions where reversal probability increases.
The cloud filter configurations provide varying degrees of confirmation strength, with smoother settings reducing false signal occurrence at the expense of some responsiveness to price changes. Traders must balance signal quality against signal frequency based on their risk tolerance and available trading time, utilizing the comprehensive customization options to optimize performance for their specific requirements.
Multi-Timeframe Integration
The system provides seamless multi-timeframe analysis through the integrated dashboard, displaying trend alignment across multiple time horizons from five-minute through four-hour periods. This analysis helps traders understand broader market context and avoid conflicts between different temporal perspectives that could compromise trade outcomes.
Session analysis identifies current trading session characteristics, providing context for expected market behavior patterns and helping traders adjust their approach based on typical session volatility and participation levels. This geographic market awareness enhances strategic decision-making and improves timing for trade execution.
Advanced Visualization Features
The indicator includes sophisticated visualization capabilities through gradient candle coloring based on MACD analysis, providing immediate visual feedback on momentum strength and direction. This enhancement allows rapid market assessment without requiring detailed indicator analysis, improving efficiency for traders managing multiple instruments simultaneously.
The cloud visualization system uses color-coded fill areas to clearly indicate trend direction and strength, with automatic adaptation to selected operational modes. This visual clarity reduces analytical complexity while maintaining comprehensive market information display through professional chart presentation.
Performance Optimization Framework
The Fresh Algo V24 incorporates performance optimization features including signal strength classification, automatic parameter adjustment based on market conditions, and dynamic filtering that adapts to current volatility levels. These optimizations ensure consistent performance across varying market environments while maintaining signal quality standards.
The system automatically adjusts sensitivity levels based on selected operational modes, ensuring appropriate responsiveness for different trading approaches. This adaptive framework reduces the need for manual parameter adjustments while maintaining optimal performance characteristics for each operational configuration.
Conclusion
The Mutanabby_AI Fresh Algo V24 represents a comprehensive solution for professional trading analysis, combining multiple analytical approaches with advanced visualization and risk management capabilities. The system's strength lies in its adaptive multi-mode design and sophisticated filtering mechanisms, providing traders with versatile tools for various market conditions and trading styles.
Success with this system requires understanding the relationship between different operational modes and their optimal application scenarios. The comprehensive dashboard and alert system provide essential market context and trade management support, enabling systematic approach to market analysis while maintaining flexibility for individual trading preferences.
The indicator's sophisticated architecture and extensive customization options make it suitable for traders at all experience levels, from those seeking systematic signal generation to advanced practitioners requiring comprehensive market analysis tools. The multi-timeframe integration and adaptive filtering ensure consistent performance across diverse market conditions while providing clear guidelines for strategic implementation.
Fundur - Market Sentiment A Fundur - Market Sentiment A: Complete Trading Indicator Guide
Indicator Overview
The Fundur - Market Sentiment A is a revolutionary multi-timeframe sentiment analysis indicator that combines advanced ZigZag pivot detection, wave-based structure analysis, and comprehensive market sentiment evaluation into one powerful trading tool. This indicator is designed to identify high-probability reversal points and trend continuations by analyzing market sentiment across 11 different timeframes simultaneously.
What Makes Market Sentiment A Unique?
Market Sentiment A is a sophisticated ZigZag system that utilizes the Market Sentiment B oscillator to perform advanced on-chart analysis against price action. By introducing Histogram-Correlated ZigZag Analysis - a breakthrough methodology that correlates sentiment histogram waves with actual price pivots to identify validated market extremes. Unlike static pivot indicators, Market Sentiment A provides dynamic analysis that adapts to changing market conditions while maintaining precise accuracy in pivot identification.
Core Methodology
The indicator operates on the principle that market sentiment oscillates in measurable waves that precede price movements. By analyzing sentiment patterns across multiple timeframes and correlating them with histogram wave behavior, traders can identify precise entry and exit points with quantifiable strength ratings and comprehensive wave event analysis.
Key Features
🎯 Revolutionary ZigZag System
Histogram-Correlated Detection : Unique correlation between sentiment waves and price pivots
Dynamic Speed Control : High, Medium, Low sensitivity settings for different market conditions
Validated Extremes : Only confirmed pivots are marked with comprehensive validation system
Real-Time Correlation : Live correlation between histogram turns and price extremes
📊 Multi-Timeframe Sentiment Engine
11 Timeframe Analysis : Simultaneous analysis across periods from 8 to 987 bars
Advanced Sentiment Calculation : Proprietary algorithm combining multiple sentiment factors
Momentum Wave Integration : 34-period momentum waves for trend context
Dynamic Smoothing : Optional smoothing for cleaner signals
🧠 Intelligent Wave Event Tracking
Green Wave Events : Bullish histogram wave analysis with comprehensive event detection
Red Wave Events : Bearish histogram wave analysis with detailed event tracking
Event Deduplication : Advanced system prevents duplicate event detection
10+ Event Types : MPIV, HTURN, TRI, SW, VOL, MDIV, HDIV, PDIV and more
⚖️ Advanced Strength Rating System
0-100 Strength Score : Comprehensive strength calculation for every pivot
Multi-Factor Analysis : Based on wave events, trend context, structure, and sentiment
Real-Time Calculation : Dynamic strength scoring as conditions change
Strength Breakdown : Detailed tooltip showing strength components
🎨 Sophisticated Visual System
Validated Pivot Labels : Clear ✓ markers for confirmed extremes
Structure Analysis : HH/HL/LH/LL structure identification with trend context
Dynamic ZigZag Lines : Connecting validated extremes with trend-based coloring
Bar Coloring Options : Momentum swings and market sentiment bar coloring
Comprehensive Tooltips : Detailed information on hover for every pivot
Setup Guide
Step 1: Adding the Indicator
Open TradingView and navigate to your desired chart
Click the "Indicators" button or press "/" key
Search for "Fundur - Market Sentiment A"
Add the indicator to your chart
Step 2: Core System Configuration
ZigZag System Settings
✅ Enable ZigZag System: ON (Core functionality)
ZigZag Speed : Choose based on your trading style:
High Speed : Most sensitive, fastest detection (2-bar lookback) - Best for scalping
Medium Speed : Balanced approach (3-bar lookback) - Recommended for most traders
Low Speed : Most reliable, slower detection (4-bar lookback) - Best for swing trading
✅ Show ZigZag Lines: ON (Visual connection of validated pivots)
Bar Coloring Settings
⚠️ Momentum Swings: OFF (Avoid visual clutter initially)
✅ Market Sentiment: ON (Primary sentiment-based bar coloring)
Step 3: Label Display Configuration
Essential Labels (Recommended Settings)
✅ Show Validated Pivots (✓): ON (Core validated extremes)
⚠️ Show Potential Turns (●): OFF (Reduces noise - enable once familiar)
⚠️ Show Structure Labels: OFF (Start clean, enable for advanced analysis)
⚠️ Include Trend in Structure Labels: OFF (Advanced feature)
✅ Show Strength Rating (💪): ON (Critical for trade quality assessment)
⚠️ Show Market Sentiment Wave Events: OFF (Advanced feature for later)
Label Visual Customization
Label Coloring : Standard (Highs=Red, Lows=Green)
Label Size : Normal
Label Transparency : 0%
Text Transparency : 0%
Step 4: Alert System Setup
✅ Enable Alerts: ON
⚠️ Alert Potential Bullish Turns: OFF (Disabled by design to prevent noise)
⚠️ Alert Potential Bearish Turns: OFF (Disabled by design to prevent noise)
✅ Alert ONLY on Confirmed Extremes: ON (High-quality signals only)
✅ Include Wave Events in Confirmed Alerts: ON (Comprehensive context)
Basic Trading Guide
Understanding the Dynamic ZigZag System
Market Sentiment A is fundamentally a Dynamic ZigZag System that displays validated highs and lows on your price chart. The indicator uses Market Sentiment B wave calculations internally to determine when sentiment waves finish, but these histograms and oscillators are NOT displayed on your chart .
What You See on Your Chart:
✓ Validated Highs : Red checkmarks marking confirmed resistance levels
✓ Validated Lows : Green checkmarks marking confirmed support levels
ZigZag Lines : Connecting validated extremes to show market structure
💪 Strength Ratings : 0-100 scores indicating signal quality
Structure Labels : HH/HL/LH/LL showing trend context
How Validation Works (Behind the Scenes):
High Validation : Uses Market Sentiment B wave analysis to confirm when a price high represents a true resistance level
Low Validation : Uses Market Sentiment B wave analysis to confirm when a price low represents a true support level
Dynamic Detection : Continuously monitors sentiment waves to validate extremes in real-time
Quality Filtering : Only displays the most significant highs and lows based on wave completion
Key Trading Concept:
Focus entirely on the validated highs and lows displayed on your chart. These represent dynamic support and resistance levels that have been confirmed by underlying sentiment analysis. The histogram and oscillator calculations happen internally - your trading decisions should be based on price action around these validated levels.
Entry Strategies
Primary Strategy: Dynamic Support/Resistance Reversals
Setup : Wait for validated pivot with ✓ marker and strength rating displayed on chart
Entry Timing : Enter on the bar when validation occurs or on pullback to the validated level
Direction : Counter-trend to the validated extreme (buy at validated lows/support, sell at validated highs/resistance)
Confirmation : Look for strength rating above 60 for higher probability setups
Structure Context : Consider overall trend using HH/HL/LH/LL structure labels
Secondary Strategy: ZigZag Trend Continuation
Setup : Identify trend direction using consecutive validated highs and lows
Entry : Enter in trend direction when price pulls back to previous validated level
Confirmation : Look for structure labels confirming trend (HH/HL for uptrend, LH/LL for downtrend)
Strength Filter : Use strength ratings above 70 for trend continuation entries
Stop Loss Methodology
For Long Positions (Validated Lows) : Place stop below the validated low price level
For Short Positions (Validated Highs) : Place stop above the validated high price level
Alternative Method : Use previous validated extreme in opposite direction as stop level
Structure-Based Method : Use significant validated levels that would invalidate the trade setup
Buffer Consideration : Add small buffer beyond validated level to account for wicks and spread
Profit Taking Strategy
For Long Positions (Validated Low Entries):
Target 1 : Previous validated high shown on chart (75% of position)
Target 2 : Next significant validated high or key resistance level (50% of remaining 25% = 12.5% of original position)
Target 3 : Extended targets using ZigZag structure analysis and trend context (remaining 12.5% of original position)
Management : Move stop loss to breakeven once first target (TP1) is executed
For Short Positions (Validated High Entries):
Target 1 : Previous validated low shown on chart (75% of position)
Target 2 : Next significant validated low or key support level (50% of remaining 25% = 12.5% of original position)
Target 3 : Extended targets using ZigZag structure analysis and trend context (remaining 12.5% of original position)
Management : Move stop loss to breakeven once first target (TP1) is executed
ZigZag Structure Trading Approach
Sideways Markets : Trade between validated highs and lows - buy at support, sell at resistance
Trending Markets : Use validated levels as pullback entry points in trend direction
Structure Breaks : Watch for breaks of significant validated levels to signal trend changes
Range Identification : Use consecutive validated highs and lows to identify trading ranges
Breakout Trading : Enter when price breaks beyond validated levels with strong momentum
Strength Rating Interpretation
Understanding the 0-100 Strength Score
The strength rating combines multiple factors:
Base Strength (25 points) : Fundamental pivot validation
Wave Events (12 points each) : Number and quality of wave events detected
Trend Context (5-10 points) : Alignment with overall trend direction
Structure Quality (3-8 points) : HH/HL/LH/LL structure strength
Sentiment Position (5-10 points) : Extreme sentiment readings
Momentum Context (5 points) : Momentum divergence confirmation
Strength Categories
90-100 : Exceptional strength - Highest probability setups
75-89 : Strong signal - High confidence trades
60-74 : Good signal - Solid trading opportunities
45-59 : Moderate signal - Use additional confirmation
30-44 : Weak signal - Proceed with caution
Below 30 : Very weak - Generally avoid
Wave Event Reference (Calculation Background)
Understanding Wave Events in Strength Calculations
Wave events are used internally by Market Sentiment A to calculate strength ratings and validate pivots. While these events may appear in alert messages or tooltips, they are not meant for direct trading decisions - they are calculation components that contribute to the overall strength score.
Key Wave Events (For Reference Only)
MPIV↑/MPIV↓ : Momentum pivot detection used in validation process
HTURN : Histogram turn identification used for wave completion
TRI↑/TRI↓ : Triangle pattern detection contributing to strength calculation
SW : Small wave indication affecting pivot quality assessment
VOL : Volume spike detection adding to strength scoring
MDIV↑/MDIV↓ : Momentum divergence contributing to validation strength
HDIV↑/HDIV↓ : Histogram divergence used in pivot confirmation
PDIV↑/PDIV↓ : Price divergence analysis for strength enhancement
How Wave Events Affect Your Trading
Strength Score Impact : More events generally result in higher strength ratings for validated pivots
Alert Context : Events may be mentioned in alerts to provide background on signal quality
Focus on Results : Instead of analyzing individual events, focus on the final strength rating and validated pivot levels
Trust the System : The indicator processes these events automatically - your job is to trade the validated highs and lows
Analysis Setups
Setup 1: Scalping Configuration (1-5 minute charts)
Core Settings:
ZigZag Speed: High (fastest detection for quick scalps)
Show Validated Pivots: ON
Show Strength Rating: ON
Bar Coloring: Market Sentiment
Visual Settings:
Label Size: Small (reduce visual clutter)
ZigZag Lines: ON
Potential Turns: ON (for immediate signals)
Trading Approach:
Focus on strength ratings above 70 for scalp entries
Quick entries at validated highs/lows with immediate execution
Tight stops just beyond validated levels
Target previous validated pivots shown on chart for quick profits
Use ZigZag structure to identify rapid reversal opportunities
Setup 2: Day Trading Configuration (5-15 minute charts)
Core Settings:
ZigZag Speed: Medium (balanced approach)
Show Validated Pivots: ON
Show Strength Rating: ON
Include Wave Events: ON (for context)
Visual Settings:
Label Size: Normal
Show Structure Labels: ON (for trend context)
ZigZag Lines: ON with trend coloring
Trading Approach:
Wait for strength ratings above 60 for quality setups
Use HH/HL/LH/LL structure labels for trend bias
Combine reversal trades at extremes with trend continuation at pullbacks
Hold positions targeting next validated pivot levels
Use ZigZag structure analysis for entry timing and market context
Setup 3: Swing Trading Configuration (1-4 hour charts)
Core Settings:
ZigZag Speed: Low (most reliable signals)
Show Validated Pivots: ON
Show Structure Labels: ON
Include Trend Analysis: ON
Visual Settings:
Label Size: Normal
Show all wave events for comprehensive analysis
Enable all alert types
Trading Approach:
Focus on strength ratings above 75 for swing positions
Emphasize trend continuation using ZigZag structure
Use validated level breaks for major position adjustments
Hold positions across multiple sessions targeting distant validated levels
Use comprehensive structure analysis (HH/HL/LH/LL) for entries/exits
Setup 4: Position Trading Configuration (4H-Daily charts)
Core Settings:
ZigZag Speed: Low (maximum reliability)
Show Validated Pivots: ON
Show Structure Labels: ON
Show all analysis features
Visual Settings:
Clean, comprehensive labeling
Full wave event display
Trend-based coloring for major bias
Trading Approach:
Only trade strength ratings above 80 for position entries
Focus on major ZigZag structure changes and validated level breaks
Use long-term structure analysis (HH/HL/LH/LL) for bias
Hold positions for weeks to months targeting major validated levels
Align with fundamental analysis and major market structure
Setup 5: Multi-Asset Analysis Configuration
For Forex Pairs:
Use Medium to Low speed settings
Focus on major session changes
Pay attention to news event correlation
Use strength ratings above 70
For Crypto Assets:
Medium speed for 24/7 market adaptation
Higher volatility requires strength above 75
Monitor weekend behavior patterns
Consider market sentiment cycles
For Stock Markets:
Align with market hours
Consider earnings and economic events
Use sector-specific analysis
Respect market close/open dynamics
Visual Components
Core Visual Elements
✓ Validated Pivots : Green checkmarks for confirmed lows, red for confirmed highs
● Potential Turns : Small dots showing histogram turn correlations (optional)
ZigZag Lines : Connecting validated extremes with trend-based coloring
💪 Strength Ratings : Numerical strength scores from 0-100
Structure Labels : HH/HL/LH/LL with trend context (optional)
Bar Coloring System
Market Sentiment Coloring : Based on sentiment oscillator position and momentum
Extreme Conditions : Special coloring for extreme overbought/oversold conditions
Momentum Swing Coloring : Alternative coloring based on momentum analysis
Advanced Visual Features
Wave Event Labels : Comprehensive event display within pivot labels
Trend Context : Dynamic trend identification and display
Strength Breakdown : Detailed tooltips showing strength components
Custom Coloring Modes : Standard vs trend-based coloring options
Alert System
Core Alert Types
Validated High Confirmed : When red wave validates ultimate high with full context
Validated Low Confirmed : When green wave validates ultimate low with full context
Trend Change Detected : When structure analysis detects trend shifts
Alert Message Structure
Each alert includes:
Timeframe identification
Signal type (BULLISH/BEARISH)
Structure context (HH/HL/LH/LL)
Strength score with 💪 rating
Exact price level
Wave events context (if enabled)
Setting Up Alerts
Enable desired alert types in indicator settings
Focus on "Confirmed Extremes" alerts for quality
Enable wave events for comprehensive context
Test alerts on historical data first
Set up multiple notification methods
Risk Management Framework
Strength-Based Position Sizing
Strength 90-100 : Maximum position size (3-5% risk)
Strength 75-89 : Large position size (2-3% risk)
Strength 60-74 : Standard position size (1-2% risk)
Strength 45-59 : Small position size (0.5-1% risk)
Below 45 : Avoid or minimal size (0.25% risk maximum)
Stop Loss Guidelines
Primary Method : Always use validated pivot levels for stops
Buffer Method : Add small buffer beyond validation level
Multiple Timeframe : Consider higher timeframe validated levels
Wave Event Context : Adjust stops based on event confluence
Risk-Reward Optimization
Minimum R:R : 1.5:1 for all trades
Preferred R:R : 2:1 or better for strength above 70
Exceptional Setups : 3:1+ for strength above 85
Position Management : Take 75% at TP1, 50% of remaining at TP2, close remaining at TP3
Stop Management : Move stop to breakeven after TP1 execution
Best Practices
Signal Quality Assessment
Always wait for validated pivots with ✓ checkmarks displayed on chart
Prioritize strength ratings above 60 for trade quality
Focus on the validated high/low levels rather than underlying calculations
Consider HH/HL/LH/LL structure labels for directional bias
Use ZigZag line connections to understand market structure flow
Entry Timing Optimization
Enter on validation bar or immediate pullback to validated level
Use lower timeframes for precise entry refinement around validated levels
Wait for strength score calculation completion before entry
Monitor price action around validated highs and lows
Consider multiple timeframe validated level alignment
Exit Strategy Management
Use opposite validated pivots displayed on chart as primary targets
Execute Fundur 3-stage exit: 75% at TP1, 12.5% at TP2, 12.5% at TP3
Move stop loss to breakeven immediately after TP1 execution
Monitor strength ratings of new validated levels that could reverse remaining position
Watch for structure changes (trend breaks) via HH/HL/LH/LL labels for early exit consideration
Common Mistakes to Avoid
Signal Interpretation Errors
Don't trade potential turns without ✓ validation markers
Never ignore strength ratings below 45 - they indicate weak signals
Don't chase signals after significant movement away from validated levels
Avoid overriding clear ZigZag structure and trend context
Don't ignore the relationship between consecutive validated highs and lows
Risk Management Failures
Never risk more than the strength score suggests for position sizing
Don't move stops against validated levels - they represent key structure
Avoid oversizing on "sure thing" setups - even high-strength signals can fail
Don't ignore multiple timeframe validated level context
Never trade without clear invalidation levels (validated highs/lows for stops)
System Usage Mistakes
Don't enable all features immediately - start simple
Avoid changing speed settings mid-session
Don't ignore alert system capabilities
Never disable core validation features
Don't overlook customization for your chart setup
Advanced Techniques
Multi-Timeframe ZigZag Analysis
Use higher timeframe validated levels for major bias and targets
Align lower timeframe entries with higher timeframe validated structure
Look for validated level confluence across timeframes
Monitor strength rating consistency of validated levels across periods
Advanced Structure Pattern Recognition
Identify recurring validated level patterns and their outcomes
Recognize high-probability ZigZag structure sequences
Use historical validated level patterns for target projection
Combine ZigZag analysis with other Fundur technical analysis tools
Advanced Alert Utilization
Create custom alert combinations based on strength thresholds
Use validated level break alerts for position management
Combine strength rating filters with validated pivot alerts
Develop systematic responses to different validated level types
Conclusion
The Fundur - Market Sentiment A indicator represents a breakthrough in technical analysis, providing a dynamic ZigZag system that displays validated highs and lows with unprecedented accuracy. By following the methodologies outlined in this guide and adapting the settings to your trading style, you can harness the full power of this sophisticated system for more precise and profitable trading decisions.
The key to success with Market Sentiment A lies in understanding that it is fundamentally a dynamic support and resistance system. Focus on the validated highs and lows displayed on your chart, use the strength ratings to assess signal quality, and leverage the structure analysis for trend context. Start with conservative settings, focus on high-strength signals, and gradually incorporate advanced features as you become familiar with the system's behavior across different market conditions.
Remember that this indicator provides the tools for identification and analysis - successful trading still requires proper risk management, psychological discipline, and continuous learning. Use the strength rating system as your primary guide, respect the validated pivot methodology, and always prioritize capital preservation over profit maximization.
Fundur - Trend TraderFundur - Trend Trader: Complete Trading Indicator Guide
Indicator Overview
The Fundur - Trend Trader is a comprehensive dual-timeframe analysis indicator that combines fair value structure analysis, risk-reward calculations, and dynamic trend identification into one powerful trading tool. This indicator is designed to provide traders with precise entry and exit points while offering complete risk management insights.
What Makes Trend Trader Unique?
The Trend Trader goes beyond traditional pivot point indicators by introducing Fair Value Structure Analysis - a methodology that analyzes the relationship between two timeframes to determine market bias and optimal trading opportunities. Unlike static indicators, Trend Trader provides dynamic analysis that adapts to market conditions in real-time.
Core Methodology
The indicator operates on the principle that markets oscillate between Premium (overvalued) and Discount (undervalued) zones relative to fair value levels. By analyzing these zones across multiple timeframes, traders can identify high-probability trade setups with clearly defined risk-reward parameters.
Key Features
🎯 Dual-Timeframe Fair Value Analysis
Higher Timeframe Structure : Primary trend direction and major levels
Lower Timeframe Structure : Refined entry opportunities and micro-trend analysis
Dynamic Relationship : Real-time analysis of timeframe alignment
📊 Comprehensive Level System
Fair Value (FV) : Central equilibrium level for entries
Premium Levels (P1, P2, P3) : Sell zones with increasing distance from fair value
Discount Levels (D1, D2, D3) : Buy zones with increasing distance from fair value
🧠 Intelligent Trend Detection
Session-to-Session Analysis : Compares current vs previous session fair values
Trend Signals : Clear LONG/SHORT setup identification
Structure Bias : Bullish/Bearish fair value structure determination
⚖️ Advanced Risk-Reward System
Real-Time R:R Calculations : Dynamic risk-reward ratios for all levels
Leverage Recommendations : Optimal position sizing based on measured risk
Risk Percentage Display : Precise risk calculations for informed decisions
🎨 Smart Visual Features
Level Hit Tracking : Automatically darkens touched levels during session
Squeeze Detection : Identifies low-volatility periods with special bar coloring
Dynamic Highlighting : Price-responsive level emphasis
Zone Fills : Visual premium and discount area identification
Setup Guide
Step 1: Adding the Indicator
Open TradingView and navigate to your desired chart
Click the "Indicators" button or press "/" key
Search for "Fundur - Trend Trader"
Add the indicator to your chart
Step 2: Basic Configuration
Timeframe Settings
Higher Timeframe : Default is Weekly (W), adjust based on your trading style:
Scalping : Use 4H for higher timeframe
Day Trading : Use Daily (D) for higher timeframe
Short-Term Swing Trading : Use Weekly (W) for higher timeframe
Long-Term Swing Trading : Use Monthly (M) for higher timeframe
Position Trading : Use Quarterly (3M) or Yearly (12M) for higher timeframe
History Bars :
Higher Timeframe: 10 bars (recommended)
Lower Timeframe: 50 bars (recommended)
Visual Settings
Line Widths : Adjust for visibility preference
Zone Fills : Enable for better visual zone identification
Bar Coloring : Enable structure and squeeze coloring
Step 3: Label Configuration
Essential Labels (Recommended Settings)
✅ Show All Labels: ON
✅ Show Trend Direction: ON
✅ Show Higher Timeframe Labels: ON
⚠️ Show Lower Timeframe Labels: OFF (avoid clutter initially)
✅ Show Price Values: ON
Label Style Options
Use Short Names : ON (P1, D2, FV instead of full names)
Combine Timeframe & Description : ON (creates compact labels like "W-FV")
Label Style : Choose between Modern or Classic
Step 4: Risk-Reward Setup
✅ Show Risk-Reward Analysis: ON
✅ Show Measured Risk Values: ON
✅ Apply Leverage to Calculations: ON
Leverage Multiplier : Start with 1.0, adjust based on your risk tolerance
Basic Trading Guide
Understanding Fair Value Structure
The indicator's foundation is the Fair Value Structure - the relationship between higher and lower timeframe fair value levels:
Bullish Structure (🔵)
Condition : Lower timeframe FV above higher timeframe FV
Bias : Look for LONG opportunities
Focus : Fair Value Structure for entries (continuation strategy)
Strategy : Enter long positions at Fair Value, take profits at Premium levels (P1, P2, P3)
Bearish Structure (🟠)
Condition : Lower timeframe FV below higher timeframe FV
Bias : Look for SHORT opportunities
Focus : Fair Value Structure for entries (continuation strategy)
Strategy : Enter short positions at Fair Value, take profits at Discount levels (D1, D2, D3)
Entry Strategies
Primary Strategy: Fair Value Continuation Entries
Setup : Price approaches fair value level with established structure bias
Entry : In Fair Value Structure (in between the lower timeframe and higher timeframe fair value)
Direction : Follow the structure bias (long in bullish structure, short in bearish structure)
Stop Loss: Two approaches available:
Advanced Method : Place stop shy of liquidation point to avoid liquidation
Hassle-Free Method : Previous high/low OR just beyond higher timeframe Fair Value
For Long Positions : Stop below higher timeframe Fair Value
For Short Positions : Stop above higher timeframe Fair Value
Profit Taking Strategy:
For Long Positions (Bullish Structure):
75% profits at Premium 1 (P1) - highest probability target
50% of remaining position at Premium 2 (P2)
Close entire position at Premium 3 (P3)
Move stop loss to break even after first profits
For Short Positions (Bearish Structure):
75% profits at Discount 1 (D1) - highest probability target
50% of remaining position at Discount 2 (D2)
Close entire position at Discount 3 (D3)
Move stop loss to break even after first profits
Alternative Strategy: Structure Transition Entries
Setup : Structure changes from bearish to bullish (or vice versa)
Entry : At new fair value level after structure confirmation
Risk Management : Tight stops during structure transition periods
Targets : Follow primary profit-taking methodology above
Risk Management Framework
Position Sizing Using Leverage Recommendations
The indicator calculates optimal leverage based on measured risk:
Conservative : Use 50% of recommended leverage
Moderate : Use 75% of recommended leverage
Aggressive : Use 100% of recommended leverage
Never exceed : 150% of recommended leverage
Stop Loss Placement
Follow the methodology outlined in the Primary Strategy section:
Advanced Method : Place stop shy of liquidation point to avoid forced liquidation
Hassle-Free Method : Use structural levels for clear invalidation
Long Positions : Stop below higher timeframe Fair Value
Short Positions : Stop above higher timeframe Fair Value
Alternative : Previous significant high/low levels
Analysis Setups
Setup 1: Scalping Configuration (1-5 minute charts)
Timeframe Settings:
Higher Timeframe: 4H (240)
Lower Timeframe: 1H (auto-calculated)
History: 5 bars for higher, 20 bars for lower
Visual Settings:
Enable all visual features for quick decision making
Use Classic label style for cleaner appearance
Enable squeeze coloring for volatility awareness
Trading Approach:
Focus on fair value continuation entries
Quick entries in fair value structure
Tight risk management using R:R table
Target P1/D1 levels for primary profits (75% position)
Setup 2: Day Trading Configuration (5-15 minute charts)
Timeframe Settings:
Higher Timeframe: Daily (D)
Lower Timeframe: 4H (auto-calculated)
History: 10 bars for higher, 30 bars for lower
Visual Settings:
Enable zone fills for clear premium/discount identification
Show both timeframe labels
Enable level hit tracking
Trading Approach:
Use structure bias for directional bias
Enter in fair value structure for continuation trades
75% profits at P1/D1, scale out to P2/D2, close at P3/D3
Hold positions across multiple sessions following structure
Setup 3: Short-Term Swing Trading Configuration (1-4 hour charts)
Timeframe Settings:
Higher Timeframe: Weekly (W)
Lower Timeframe: Daily (auto-calculated)
History: 15 bars for higher, 50 bars for lower
Visual Settings:
Emphasize higher timeframe levels
Show trend direction signals
Enable complete risk-reward analysis
Trading Approach:
Primary focus on higher timeframe structure
Patient entries in fair value structure
Follow standard profit-taking: 75% at P1/D1, scale to P3/D3
Use lower timeframe for refined fair value entries
Setup 4: Long-Term Swing Trading Configuration (4H charts)
Timeframe Settings:
Higher Timeframe: Monthly (M)
Lower Timeframe: Weekly (auto-calculated)
History: 20 bars for higher, 75 bars for lower
Visual Settings:
Clean label setup focusing on major levels
Enable trend direction for bias confirmation
Simplified visual approach for clarity
Trading Approach:
Monthly structure provides major trend direction
Entries in fair value structure
Hold positions for several weeks
Apply standard profit-taking methodology at premium/discount zones
Setup 5: Position Trading Configuration (Daily/Weekly charts)
Timeframe Settings:
Higher Timeframe: Quarterly (3M) or Yearly (12M)
Lower Timeframe: Monthly or Quarterly (auto-calculated)
History: 25 bars for higher, 100 bars for lower
Visual Settings:
Clean label setup focusing on key levels
Enable all alert systems
Simplified color scheme
Trading Approach:
Structure changes signal major macro trend shifts
Very patient entries in fair value structure confirmation
Long-term continuation trades targeting extended premium/discount levels
Hold positions for months to years following structure bias
Focus on major market cycles and long-term trend continuations
Setup 6: Multi-Asset Analysis Configuration
For Forex Pairs:
Adjust decimal precision for pip accuracy
Focus on daily/weekly structure
Use tight risk management due to leverage
For Crypto Assets:
Higher volatility requires wider stops
24/7 markets need continuous monitoring
Structure breaks often lead to extended moves
For Stock Indices:
Respect market hours for structure analysis
Economic events can override technical levels
Seasonal patterns affect structure behavior
Visual Components
Level Indicators
Solid Lines : Active levels based on current price position
Highlighted Levels : Levels within current price range
Darkened Levels : Previously touched levels during current session
Zone Fills
Red Zones : Premium areas (selling opportunities)
Green Zones : Discount areas (buying opportunities)
Cloud Fill : Area between dual timeframe fair values
Bar Coloring
Purple Bars : Squeeze conditions (low volatility)
Structure Colors : Based on price position relative to fair value levels
Labels and Information
Level Labels : Price values and targets for each level
Trend Signals : Clear LONG/SHORT setup indications
Risk-Reward Table : Comprehensive analysis panel
Risk Management
Built-in Risk Controls
Measured Risk System
The indicator automatically calculates risk percentages based on:
Distance from fair value to premium/discount levels
Current price position
Leverage settings applied
Optimal Leverage Calculations
Long Positions : Based on discount risk measurement
Short Positions : Based on premium risk measurement
Dynamic Adjustment : Changes with market conditions
Risk-Reward Ratios
Each level displays its R:R ratio considering:
Entry point (fair value or current price)
Target level
Stop loss level
Applied leverage
Recommended Risk Parameters
Conservative Trading
Maximum 1-2% risk per trade
Use 50% of recommended leverage
Target R:R ratios above 2:1
Focus on high-probability setups only
Moderate Trading
Maximum 2-3% risk per trade
Use 75% of recommended leverage
Accept R:R ratios above 1.5:1
Trade multiple setups with correlation awareness
Aggressive Trading
Maximum 3-5% risk per trade
Use up to 100% of recommended leverage
Accept R:R ratios above 1:1
Active management required
Alert System
Structure Alerts
Fair Value Structure Bullish : When structure turns bullish
Fair Value Structure Bearish : When structure turns bearish
Level Interaction Alerts
For each premium and discount level:
Touch Alerts : When price reaches the level
Cross Above : When price breaks above the level
Cross Below : When price breaks below the level
Range Alerts
Rising into FV : Price enters fair value range from below
Falling into FV : Price enters fair value range from above
Rising Above FV : Price breaks above fair value range
Falling Below FV : Price breaks below fair value range
Setting Up Alerts
Enable desired alert types in indicator settings
Create TradingView alerts using the indicator
Configure notification methods (email, SMS, app)
Test alerts with historical data first
Customization Options
Color Schemes
Fair Value Colors : Customize based on structure bias
Premium/Discount Colors : Match your chart theme
Dynamic Coloring : Automatically adjusts based on price position
Label Customization
Text Transparency : Adjust readability
Background Transparency : Control label prominence
Size Options : From tiny to large based on chart size
Position Options : Multiple screen positions available
Table Settings
Position : 9 different screen positions
Size : 4 size options for different screen resolutions
Transparency : Adjust for chart readability
Best Practices
Chart Setup Recommendations
Screen Real Estate Management
Use larger timeframes for cleaner appearance
Minimize lower timeframe labels on smaller screens
Position risk-reward table to avoid price action interference
Multi-Timeframe Analysis
Keep one chart with higher timeframe focus
Use secondary chart for lower timeframe entries
Synchronize timeframe selection across charts
Trading Psychology Integration
Patience with Structure
Wait for clear structure bias before trading
Avoid trading during structure transition periods
Respect the higher timeframe bias
Risk Management Discipline
Never ignore the calculated risk percentages
Use leverage recommendations as guidelines, not rules
Adjust position sizes based on market conditions
Entry Timing
Use lower timeframes for precise entries
Wait for price to reach significant levels
Confirm entries with additional confluence factors
Common Mistakes to Avoid
Over-Analysis
Don't wait for perfect setups that may never come
Focus on high-probability scenarios
Accept that not every level will hold
Ignoring Structure Bias
Don't fight the overall structure direction
Adjust strategies when structure changes
Respect multi-timeframe alignment
Poor Risk Management
Never risk more than the indicator suggests
Don't ignore stop loss levels
Avoid emotional position sizing
Advanced Techniques
Structure Transition Trading
Identify when structure is changing
Position for new bias direction
Use tight risk management during transitions
Level Confluence
Look for multiple level alignments
Combine with support/resistance
Use volume analysis for confirmation
Seasonal and Market Hour Awareness
Adjust for different market sessions
Consider seasonal patterns in structure
Account for economic calendar events
Conclusion
The Fundur - Trend Trader indicator represents a comprehensive approach to modern technical analysis, combining traditional pivot point methodology with advanced fair value structure analysis. By following the guidelines in this manual and adapting the settings to your trading style, you can harness the full power of this indicator for more informed and profitable trading decisions.
Remember that no indicator is perfect, and the Trend Trader should be used as part of a complete trading strategy that includes fundamental analysis, risk management, and proper psychology. Start with conservative settings and gradually increase sophistication as you become more familiar with the indicator's behavior in different market conditions.
For best results, practice with the indicator in demo accounts first, understand its behavior in various market conditions, and always prioritize risk management over profit potential.
PipsHunters Trading ChecklistTitle: PipsHunters Trading Checklist (PHTC)
Short Description / Teaser:
Enforce trading discipline and never miss a step in your pre-trade analysis with this simple, interactive, on-chart checklist.
Full Description:
🚀 Overview
The PipsHunters Trading Checklist (PHTC) is a powerful yet simple tool designed to instill discipline and structure into your trading routine. In the heat of the moment, it's easy to forget crucial steps of your analysis, leading to impulsive and low-probability trades. This indicator acts as your personal co-pilot, providing a persistent, on-chart checklist that you must manually complete before taking a trade.
This is not an automated signal generator. It is a utility to keep you accountable to your own trading plan. The checklist items are inspired by common concepts in price action and Smart Money Concepts (SMC) methodologies, but they serve any trader who follows a rule-based system.
✨ Key Features
Interactive On-Chart Table: Displays a clean, non-intrusive table directly on your chart.
Manual Check-off System: You are in full control. Go into the indicator settings and check off each item as you complete your analysis.
Real-Time Progress Tracking: The table header shows your progress (e.g., 4/7) and changes color from red to green when all items are checked.
Clear Visual Cues: Each item is marked with a ✅ or ❌, and the text color changes to provide an at-a-glance status.
"Ready!" Status: A final "READY!" confirmation appears once your entire checklist is complete, giving you the green light to look for an entry based on your strategy.
Fully Customizable Position: Place the table in any corner of your chart (Top Left, Top Right, Bottom Left, Bottom Right) to suit your layout.
📋 The Checklist Items Explained
The default checklist guides you through a structured, top-down analysis process common in many trading strategies:
Seat before 1H: A reminder to be settled and mentally prepared at your desk at least an hour before your target session begins. Avoids rushing and emotional decisions.
Check News: Have you checked for high-impact news events that could introduce extreme volatility and invalidate your setup?
Mark Day Open: The daily open is a key institutional level. Marking it helps establish the daily bias.
Mark LQ Levels: Have you identified key Liquidity (LQ) levels? This includes previous day/week highs and lows, session highs/lows, and other obvious swing points.
Wait for Kill Zone: A reminder to be patient and wait for price to trade into a specific, high-probability time window (e.g., London Kill Zone, New York Kill Zone).
LQ sweep inside Kill Zone: The core of the setup. Has price swept a key liquidity level within your chosen Kill Zone?
Lower TF Confirmations: After the liquidity sweep, have you waited for confirmation on a lower timeframe? This is often a Market Structure Shift (MSS) or Change of Character (CHoCH).
🛠️ How to Use
Add the "PipsHunters Trading Checklist" indicator to your chart.
Go to the indicator's Settings (click the gear icon ⚙️).
As you perform each step of your pre-trade analysis, tick the corresponding checkbox in the Inputs tab.
The on-chart table will update instantly to reflect your progress.
Only when all 7 items are checked will the table signal "READY!".
🎯 Who Is This For?
This indicator is perfect for:
SMC / ICT Traders: The checklist items align directly with Smart Money Concepts.
New Traders: Helps build the essential habit of a consistent pre-trade routine.
Inconsistent Traders: Acts as a guardrail to prevent impulsive, undisciplined entries.
Any Rule-Based Trader: Anyone who follows a trading plan can benefit from the structure it provides.
Disclaimer: This is a utility tool to aid in discipline and execution. It does not provide financial advice or guarantee profitable trades. All trading involves risk, and you are solely responsible for your own decisions. Trade safe and stay disciplined!
Inside Bar With Alert - RajThis indicator helps you reduce your screen time by giving you consistent alerts on the formation of inside bar candle and it gives you bullish and bearish alerts on breakout of the mother candle. So if you believe in inside strategy this indicator will be helpful for you.
Crypto Volatility Panel ProCrypto Volatility Panel Pro
This advanced indicator creates a comprehensive volatility monitoring dashboard that displays real-time volatility metrics for up to 30 cryptocurrency pairs simultaneously. The tool combines sophisticated volatility assessment techniques with leverage-adjusted analysis and heat map visualization to provide enhanced market insights in an organized table format.
Proprietary Methodology
This indicator utilizes a proprietary dual-metric volatility assessment system developed specifically for cryptocurrency market analysis. The methodology combines advanced technical analysis components including price volatility measurements, range position analysis, and leverage scaling algorithms optimized through extensive market testing.
The unique approach enables more accurate volatility assessments across diverse cryptocurrency price ranges and market conditions compared to standard volatility indicators. Specific calculation methods and optimization parameters remain proprietary to maintain competitive advantages.
Core Functionality and Innovation
Unlike standard volatility indicators that focus on single instruments, this tool provides simultaneous multi-asset monitoring with proprietary volatility calculations specifically optimized for cryptocurrency markets. The innovation lies in combining multiple volatility assessment techniques with enhanced leverage scaling algorithms, heat map ranking system, and comprehensive multi-asset dashboard presentation.
The indicator processes data from up to 30 different cryptocurrency pairs, each with independent leverage settings ranging from 0.1x to 10,000x. Users can apply universal leverage across all pairs for consistent analysis scenarios, or customize individual leverage ratios for specific trading strategies.
Visual Organization and Heat Map System
The table displays three primary columns with an advanced heat map ranking system:
Symbol Column: Shows cryptocurrency pair names with dynamic visual indicators (🔥, ⚡, ✅, 💤) representing volatility intensity levels. Each symbol includes its current leverage setting in parentheses for reference. Invalid or unavailable symbols display error indicators (❌) with appropriate error messaging.
Change Percentage Column: Displays leverage-adjusted volatility measurements with both color-coded text and heat map background ranking. Text colors indicate volatility levels (Red for extreme, Yellow for high, Green for moderate, Gray for low), while background heat map colors rank performance relative to all monitored pairs.
Lookback Percentage Column: Shows leverage-adjusted position analysis within recent price ranges with heat map background ranking, indicating market positioning relative to recent highs and lows across all monitored instruments.
Advanced Heat Map Ranking
The proprietary heat map system ranks all enabled pairs in real-time based on their volatility metrics, providing instant visual identification of the most and least volatile instruments:
Hottest (Top 10%): Deep red background indicating highest volatility
Warm (10-20%): Orange-red background for elevated volatility
Medium (20-40%): Yellow background for moderate-high volatility
Cool (40-60%): Green background for moderate volatility
Cold (60-80%): Blue background for low volatility
Sleepy (Bottom 20%): Dark background for minimal volatility
Heat map opacity is fully customizable, and the system can be disabled for users preferring traditional static backgrounds.
Configuration Options
Expanded Pair Selection: Monitor up to 30 cryptocurrency pairs across major exchanges including Bitstamp and Binance. Default selections include established cryptocurrencies (BTC, ETH, SOL) and emerging assets (INJ, NEAR, FTM), with full customization available.
Table Positioning: Nine position options including top/middle/bottom combinations with left/center/right alignment, allowing optimal placement on any chart layout without interfering with price action or other indicators.
Visual Customization: Comprehensive control over table dimensions, frame width, font size, background colors, frame colors, header styling, text colors, and heat map color schemes to match user preferences and chart themes.
Leverage Management: Individual leverage settings for each of the 30 pairs, with optional universal leverage mode that applies consistent multipliers across all enabled pairs. Supports extreme leverage ranges up to 10,000x for advanced risk modelling.
Error Handling: Robust symbol validation with clear error indicators for invalid, unavailable, or misconfigured trading pairs, ensuring reliable operation across different market conditions.
Practical Trading Applications
Multi-Asset Volatility Screening: Identify the most and least volatile cryptocurrency markets in real-time using the heat map ranking system, enabling quick allocation of attention to instruments with the highest potential for profitable moves.
Leverage Risk Assessment: Visualize how different leverage ratios amplify volatility metrics across multiple markets simultaneously, supporting informed position sizing decisions before entering leveraged trades.
Market Timing and Rotation: Use the combination of volatility measurements and heat map rankings to identify optimal entry/exit timing across cryptocurrency markets, facilitating effective portfolio rotation strategies.
Portfolio Diversification: Compare volatility levels and rankings across 30 cryptocurrencies to construct portfolios with desired risk characteristics, balancing high-volatility growth opportunities with stable store-of-value positions.
Risk Management Dashboard: Monitor real-time volatility changes and relative rankings to adjust position sizes, implement protective measures, or reallocate capital when market conditions change significantly.
Technical Implementation
Built using Pine Script v5 with optimized security request handling to minimize performance impact while accessing 30 external data sources simultaneously. The indicator uses efficient array-based data collection, real-time ranking algorithms, and conditional table updates to maintain smooth chart operation.
The heat map system employs dynamic ranking calculations that process all enabled pairs in real-time, sorting values and applying percentile-based color mapping for instant visual feedback. Error handling includes invalid symbol detection and graceful fallback display for unavailable data feeds.
Usage Instructions
Configure Pair Selection: Enable desired cryptocurrency pairs from the 30 available options, organized across three input groups for easy navigation. Set individual leverage values or activate universal leverage mode for consistent multipliers.
Customize Heat Map: Adjust heat map colors and opacity to match your visual preferences and chart theme. The system can be disabled for users preferring static backgrounds.
Position and Style Table: Select optimal table position from nine available options and customize appearance including colors, sizing, and text elements to integrate seamlessly with your trading setup.
Interpret Rankings: Monitor both absolute values and heat map rankings to identify relative performance.
Hottest colors indicate pairs experiencing the highest volatility relative to the monitored universe.
Apply Leverage Context: Use leverage-adjusted values to understand how volatility would affect leveraged positions, remembering these are mathematical projections designed for risk assessment rather than trading signals.
Advanced Features
Dynamic Symbol Processing: The indicator automatically handles symbol validation, displaying clear error messages for invalid or unavailable trading pairs while maintaining operation for valid symbols.
Real-Time Ranking: Heat map colors update dynamically as market conditions change, providing instant visual feedback on shifting volatility patterns across the cryptocurrency universe.
Scalable Monitoring: Users can monitor anywhere from a few key pairs to the full 30-pair universe, with the ranking system automatically adjusting to the number of enabled instruments.
Cross-Exchange Support: Incorporates data from multiple cryptocurrency exchanges to provide comprehensive market coverage and reduce single-source dependency risks.
Limitations and Important Considerations
Proprietary Algorithm: The specific calculation methods are proprietary and not disclosed. Users should evaluate the indicator's output through their own analysis and testing before incorporating it into trading decisions.
Complex Volatility Model: While the proprietary methodology is sophisticated, it represents one approach to volatility assessment and may not capture all forms of market volatility such as gap movements, flash crashes, or news-driven events.
Performance Considerations: Processing data from up to 30 external securities may impact chart loading speed or cause timeouts during periods of high TradingView server load. Users experiencing performance issues should consider reducing the number of enabled pairs.
Leverage Calculations: Leverage adjustments are mathematical projections that assume linear scaling, which may not reflect actual leveraged trading mechanics including margin requirements, funding costs, liquidation risks, and exchange-specific policies.
Market Data Dependencies: Cryptocurrency prices and volatility can vary significantly between exchanges. The indicator's data sources may not represent the specific exchange or trading pair you use, and some feeds may experience gaps or delays during maintenance periods.
Ranking Relativity: Heat map rankings are relative to the enabled pair universe. Rankings will change based on which pairs are monitored and their current market conditions, making absolute interpretations less meaningful than relative comparisons.
Educational Value
This indicator helps traders develop understanding of relative volatility patterns across cryptocurrency markets and the mathematical impact of leverage on risk metrics. The heat map system provides intuitive visualization of market dynamics, helping users identify which assets are experiencing unusual activity relative to their peers.
The tool serves as an educational platform for understanding advanced volatility measurement techniques, relative ranking systems, and multi-asset risk assessment concepts that are crucial for professional cryptocurrency trading and portfolio management.
Performance and Compatibility
The indicator is optimized for cryptocurrency markets but can be adapted to other volatile asset classes by modifying the symbol inputs. Security request limits may occasionally affect data availability, particularly when multiple indicators requesting external data are used simultaneously on the same chart.
The heat map rendering system is designed for efficiency, updating color mappings only when ranking changes occur rather than on every price tick, ensuring smooth chart performance even when monitoring the full 30-pair universe.
Risk Disclaimer: This indicator is designed for educational and analytical purposes only. Volatility calculations are estimates based on historical price data and proprietary mathematical models that are not disclosed. Results do not constitute trading advice or predictions of future price movements. Users should conduct independent analysis to evaluate the indicator's effectiveness before making trading decisions.
Leveraged trading involves substantial risk of loss and may not be suitable for all investors. Always conduct thorough research and consider consulting with qualified financial professionals before making leveraged trading decisions. Cryptocurrency markets are highly volatile and can result in significant losses. Past volatility patterns do not guarantee future market behavior.
This indicator is compatible with all TradingView chart types and timeframes. It is specifically designed for cryptocurrency markets using proprietary algorithms optimized for digital asset volatility characteristics.
[Tuan Captain] BTC Buy & Sell SignalsLooking for high-quality trading signals for Bitcoin (BTCUSD)? Stay updated with our expertly analyzed entry points, backed by real-time market data and trend indicators to help you make smarter, more profitable decisions in the crypto market.
Refined MA + Engulfing (Strategy-Equivalent Trigger)I would like to start by saying that this indicator was put together using ChatGPT, some past trades from myself and some backtested trades, and from my time as a student in Wallstreet Academy under Cue Banks.
I am not profitable yet. I am too jumpy and blow accounts. I'm hoping this indicator (and it's strategy twin), with the help of some alerts, can help me spend less time on the charts, so that I'm not tempted to press buttons as much.
It does fire quite a bit. It can be adjusted, I believe, to trigger more or less (open the script, cooldown bars(x) <== change the X to whatever. 5 minute intervals so 1 is 5.
With that being said, there are times that this indicator has shown to trigger and I ask, "Why?".
I just want to help myself and others, and maybe make some decent\cool stuff along the way. Enjoy
KR
Mental Reminder# Mental Reminder - Trading Psychology Overlay
## 🧠 Why This Indicator Matters
Trading success isn't just about technical analysis - it's about psychology. The biggest enemy of profitable trading is often our own emotions and impulses. This indicator serves as your constant mental anchor, displaying personalized reminders that keep you focused on what truly matters.
## 💡 Core Purpose
**Combat Emotional Trading**
Every trader knows the feeling - you see a price movement and your emotions take over. This overlay keeps your trading rules and mindset visible at all times, acting as a psychological brake against impulsive decisions.
**Reinforce Discipline**
Whether it's "Wait for confirmation", "Risk management first", or "The market will always be here tomorrow" - having your key principles constantly visible helps internalize good trading habits.
**Maintain Patience**
In a world of instant gratification, successful trading requires patience. A simple "Let the setup come to you" reminder can prevent countless premature entries and exits.
## 🎯 Real Trading Applications
- **Pre-market reminder**: "Review your plan" before market open
- **During drawdowns**: "Trust the process" or "Losses are part of the game"
- **In volatile markets**: "Stay calm" or "Stick to your strategy"
- **During winning streaks**: "Don't get overconfident" or "Risk management still matters"
- **FOMO moments**: "There will always be another trade"
## 🔄 The Psychology Behind Visual Reminders
Studies show that visual cues are more effective than trying to remember rules mentally. When you're in the heat of trading, emotions can cloud judgment. A constant visual reminder cuts through the emotional noise and brings you back to your planned approach.
**Why Fixed Position Works**
Unlike annotations that move with price, this reminder stays in your peripheral vision - always there, never intrusive, but impossible to ignore when you need it most.
Your trading edge isn't just your strategy - it's your ability to execute it consistently. This simple tool helps bridge the gap between knowing what to do and actually doing it.
Custom Portfolio [BackQuant]Custom Portfolio {BackQuant]
Overview
This script turns TradingView into a lightweight portfolio optimizer with institutional-grade analytics and real-time position management capabilities.
Rank up to 15 tickers every bar using a pair-wise relative-strength "league table" that compares each asset against all others through your choice of 12 technical indicators.
Auto-allocate 100% of capital to the single strongest asset and optionally apply dynamic leverage when the aggregate market is trending, with full position tracking and rebalancing logic.
Track performance against a custom buy-and-hold benchmark while watching a fully fledged stats dashboard update in real time, including 15 professional risk metrics.
How it works
Relative-strength engine – Each asset is compared against every other asset with a user-selectable indicator (default: 9/21 EMA cross). The system generates a complete comparison matrix where Asset A vs Asset B, Asset A vs Asset C, and so on, creating strength scores. The summed scores crown a weekly/daily/hourly "winner" that receives the full allocation.
Regime filter – A second indicator applied to TOTAL crypto-market cap (or any symbol you choose) classifies the environment as trending or mean-reverting . Leverage activates only in trending regimes, protecting capital during choppy or declining markets. Choose from indicators like Universal Trend Model, Relative Strength Overlay, Momentum Velocity, or Custom RSI for regime detection.
Capital & position logic – Equity grows linearly when flat and multiplicatively while invested. The system tracks entry prices, calculates returns including leverage adjustments, and handles position transitions seamlessly. Optional intra-trade leverage rebalancing keeps exposure in sync with market conditions, recalculating position sizes as regime conditions change.
Risk & performance analytics – Every confirmed bar records return, drawdown, VaR/CVaR, Sharpe, Sortino, alpha/beta vs your benchmark, gain-to-pain, Calmar, win-rate, Omega ratio, portfolio variance, skewness, and annualized statistics. All metrics render in a professional table for instant inspection with proper annualization based on your selected trading days (252 for traditional markets, 365 for crypto).
Key inputs
Backtest window – Hard-code a start date or let the script run from series' inception with full date range validation.
Asset list (15 slots) – Works with spot, futures, indices, even synthetic spreads (e.g., BYBIT:BTCUSDT.P). The script automatically cleans ticker symbols for display.
Indicator universe – Switch the comparative metric to DEMA, BBPCT, LSMAz adaptive scores, Volatility WMA, DEMA ATR, Median Supertrend, and more proprietary indicators.
With more always being added!
Leverage settings – Max leverage from 1x to any multiple, auto-rebalancing toggle, trend/reversion thresholds with precision controls.
Visual toggles – Show/hide equity curve, rolling drawdown heat-map, daily PnL spikes, position label, advanced metrics table, buy-and-hold comparison equity.
Risk-free rate input – Customize the risk-free rate for accurate Sharpe ratio calculations, supporting both percentage and decimal inputs.
On-chart visuals
Color-coded equity curve with "shadow" offset for depth perception that changes from green (profitable) to red (losing) based on recent performance momentum.
Rolling drawdown strip that fades from light to deep red as losses widen, with customizable maximum drawdown scaling for visual clarity.
Optional daily-return histogram line and zero reference for understanding day-to-day volatility patterns.
Bottom-center table prints the current winning ticker in real time with clean formatting.
Top-right metrics grid updates every bar with 15 key performance indicators formatted to three decimal places for precision.
Benchmark overlay showing buy-and-hold performance of your selected index (default: SPX) for relative performance comparison.
Typical workflow
Add the indicator on a blank chart (overlay off).
Populate ticker slots with the assets you actually trade from your broker's symbol list.
Pick your momentum or mean-reversion metric and a regime filter that matches your market hypothesis.
Set max leverage (1 = spot only) and decide if you want dynamic rebalancing.
Press the little " L " on the price axis to view the equity curve in log scale for better long-term visualization.
Enable the metrics table to monitor Sharpe, Sortino, and drawdown in real time.
Iterate through different asset combinations and indicator settings; compare performance vs buy-and-hold; refine until you find robust parameters.
Who is it for?
Systematic crypto traders looking for a one-click, cross-sectional rotation model with professional risk management.
Portfolio quants who need rapid prototyping without leaving TradingView or exporting to Python/R.
Swing traders wanting an at-a-glance health check of their multi-coin basket with instant position signals.
Fund managers requiring detailed performance attribution and risk metrics for client reporting.
Researchers backtesting momentum and mean-reversion strategies across multiple assets simultaneously.
Important notes & tips
Set Trading Days in a Year to 252 for traditional markets; 365 for 24/7 crypto to ensure accurate annualization.
CAGR and Sharpe assume the backtest start date you choose—short windows can inflate stats, so test across multiple market cycles.
Leverage is theoretical; always confirm your broker's margin rules and account for funding costs not modeled here.
The script is computationally heavy at 15 assets due to the N×N comparison matrix—reduce the list or lengthen the timeframe if you hit execution limits.
Best results often come from mixing assets with different volatility profiles rather than highly correlated instruments.
The regime filter symbol can be changed from CRYPTOCAP:TOTAL to any broad market index that represents your asset universe.
TrendZonesTrendZones
This is an indicator which I use, have tested, tweaked and added features to for use in my trend following investing system. I got the idea for it when for some reason I was looking for a dynamic reference to measure the height of a channel or something. In search of this I made MA’s of the high and low borders of a Donchian channel which turned out to be two near parallel and stunningly smooth curves. This visual was so appealing that I immediately tried to turn it into a replacement for the KeltCOG which I previously used in my system. First I created a curve in the middle of the upper and lower curves, which I called COG (Center Of Gravity). Then I decided to enter only one lookback and let the script create a Donchian channel with half the lookback and use this to create the curves with an MA of whole lookback. For this reason the minimum lookback is set to 14, enough room for the Donchian Channel of 7 periods. This Donchian ChanneI has a special way of calculating the borders, involving a 5 period Median value. Thanks to this these borders are really a resistance and support level, which won’t change at a whim, e.g. when a ‘dead cat bounce’ occurs. I prevented the Donchian channel to show itself between the curves and only pop out from behind these. These pop outs now function as “strong trend zones”. I gave it colors (blue:-strong up, green: moderate up, orange: moderate down, red: strong down, near COG: gray, curves horizontal: gray) and it looked very appealing. I tested it in different time frames. In some weekend, when I was bored, I observed for a few hours the minute chart of bitcoin. It turned out that you can reliably tell that an uptrend ends when the candles go under the COG beginning a downtrend. Uptrend starts again once the candles go above COG. As Trends on minute charts only last around half an hour, this entertainment made the potential of this indicator very clear to me in just one afternoon.
Risk Management, Safe Level and Logical Stops.
In the inputs are settings for “Risk Tolerance”, and to activate “Show Logical Stop Level” (activated in example chart) and “Show Safe Level”. As a rule of thump a trade should not expose the invested capital to a risk of losing more than 2 percent. I divided my investment capital in ten equal parts which are allocated to ten different stocks or other instruments or kept liquid. This means that when a position is closed by triggering a Stop with a loss of 20 percent, the invested capital suffers only 2 percent (20% x 10% = 2%). This is why the value for “Risk Tolerance” has a default of 20. Because I put my Stops on the lower curve, a “Safe Level” can be calculated such that when you buy for a price below or at this level, the stop will protect the position sufficiently. Because I only buy when the instrument is in uptrend, the buying price should be between COG and Safe Level. Although I never do that, putting the stop at other curves is feasible and when you want to widen the stop (I never lower my stops btw) in a downtrend situation, even 1 ATR below the “Low Border”. I call these “Logical Stop Levels”, marked with dark green circles on the lower curve when safe buying by placing the Stoploss on this curve is possible, gray circles on the other curves, on the Upper Curve navy when price enters very profitable level. In a downtrend situation maroon circles appear.
Target lines
When I open a position I always set a Stoploss and a Target, for this purpose two types of Target values can be set and corresponding Target lines activated. These lines are drawn above the “High Border” at the set distance. If one expects some price to be used, differences will occur.
Other Features
Support Zone, this is 1 ATR below the “Low Border”, the maroon circles of the “Logal Stops” are placed on this “Support level”.
Stop distance and Channel Width. (activated in example chart) These are reported in a two cell table in the right lower corner of the main panel. I created this because I want to be able to check the volatility, whether the channel shows a situation in which safe buying in most levels of the channel is possible or what risk you take when you buy now and set the Stop at the nearest logical level (which is not always the “Lower curve”). This feature comes in handy for creating a setup I propose in the “Day Trading Fantasy” below.
Some General and User Settings. I never activate this, perhaps you will.
Use Of TrendZones In My System.
Create a list of stocks in uptrend. I define ‘stock in uptrend’ as in uptrend zone in all three monthly, weekly and daily charts, all three should at the same time be in uptrend. The advantage of TrendZones is that you can immediately see in which zone the candle moves.
Opening a position in a stock from the above list. I do this only when in both the daily and weekly the green dot on the lower curve indicates a buying opportunity. This is usually not the case in most of the items of the list, this feature thus provides a good timing for opening a position. Sometimes you need to wait a few weeks for this to happen.
Setting a target over a position. For this I use the Target percent line of the weekly chart with the default value of 10.
Updating the Stoploss and Target values. Every week or two weeks I set these to the new values of the “Lower Curve” and the Target line of the weekly. Attention: never shift down Stops, only up or let them stay the same when the curve moves down. I never use Stop levels on other curves.
I Check the charts whenever I like to do this. Close the position when the uptrend obviously shifts down. Otherwise I let the profits run until the Target triggers which closes the position with some profit.
For selecting stocks an checking charts for volume events, I also use a subpanel indicator called “TZanalyser”, which borrows the visual of my “Fibonacci Zone Oscillator”, is based on TrendZones and includes code from my REVE indicators. I intend to publish that as well.
Day Trading Fantasy.
Day trading is an attempt to earn a dime by opening a position in the morning and close it during the day again with a profit (or a loss). Before the market closes, you close all day trading positions.
In my fantasy the “Logical Stop Level” is repurposed for use as entry point and the ATR-based Target line is used to provide a target setting in an intraday chart, like e.g. 15 minute. To do this the “Safe Level” should be limited to between Channel width and COG. This can be done by showing “Safe Level” and “Channel Width” and then set “Risk Tolerance” to around the shown Channel Width. In this setting you can then wait for the green circle to show up for entering your trade and protect it with the stop.
I don’t know if this works fine or if it’s better than other day trade systems, because I don’t do day trading.
Take care and have fun.
Bitcoin Institutional Volume AnchorsBitcoin Institutional Volume Anchors
Indicator Overview:
The Bitcoin Institutional Volume Anchors indicator is a professional-grade VWAP analysis tool designed for sophisticated Bitcoin trading strategies. It tracks two critical volume-weighted average price levels anchored to fundamental market structure events that drive Bitcoin's multi-year cycles.
-Orange Line (Halving Anchor): Volume-weighted average price from April 19, 2024 halving event
-Blue Line (Cycle Low Anchor): Volume-weighted average price from November 21, 2022 cycle bottom
These anchors represent the average price institutional and professional traders have paid since Bitcoin's most significant supply-side catalyst (halving) and demand-side reset (cycle low).
Market Interpretation Framework:
Price Above Both Anchors - Institutional Bullish
-Strong institutional accumulation confirmed
-Majority of professional money profitable since key events
-Optimal environment for long-term position building
-Risk-on institutional sentiment
Price Between Anchors - Transition Phase
-Mixed institutional signals requiring careful analysis
-Appropriate for reduced position sizing
-Monitor for directional confirmation
-Tactical rebalancing opportunity
Price Below Both Anchors - Institutional Bearish
-Professional money underperforming key levels
-Heightened risk management protocols required
-Defensive positioning appropriate
-Await institutional re-accumulation signals
Standard Deviation Band Analysis:
Gray Bands (2σ): Statistical volatility boundaries
-Represent normal price excursions from institutional fair value
-Used for tactical profit-taking and position scaling
-Indicate elevated but manageable risk levels
Colored Bands (3σ): Extreme volatility boundaries
-Orange/Blue bands corresponding to respective VWAP anchors
-Represent statistically extreme price extensions
-High-probability reversal or exhaustion zones
-Critical risk management triggers
Professional Trading Applications:
Portfolio Allocation Framework
Maximum Allocation (70-100%)
-Price above both anchors with upward trending VWAPs
-Recent bounce from either anchor level
-Recovery to fair value after extreme extension
Standard Allocation (40-70%)
-Price above anchors but approaching 2σ bands
-Consolidation near anchor levels
-Confirmed institutional trend changes
Reduced Allocation (20-40%)
-Price at 2σ extension levels
-Below one anchor but above the other
-Conflicting VWAP trend signals
Defensive Allocation (10-25%)
-Price at 3σ extreme levels
-Below both institutional anchors
-Overextended risk conditions (>30-35% above anchors)
Entry Signal Hierarchy:
Tier 1 Signals (Highest Probability)
-Bounce from Cycle Low Anchor during uptrend
-Cross above both anchors with volume confirmation
-Recovery to fair value after 20%+ extension
Tier 2 Signals (Standard Probability)
-Bounce from Halving Anchor during uptrend
-Trend change confirmation in VWAP slope
-2σ band rejection with momentum
Tier 3 Signals (Lower Probability)
-Entries near 2σ extension levels
-Counter-trend plays against institutional flow
-High-risk momentum trades at extremes
Risk Management Protocol:
Stop Loss Guidelines
-Halving Anchor entries: 3% below anchor level
-Cycle Low Anchor entries: 4% below anchor level
-Extension trades: 2% below current level
-Trend change trades: Below invalidation anchor
Profit Taking Strategy
-25-40% profits at 2σ bands
-50-70% profits at 3σ bands
-Trailing stops below higher timeframe anchor levels
-Complete exits on institutional trend reversals
Alert System Integration:
The indicator provides institutional-grade alert notifications with:
-Precise entry and exit levels
-Position sizing recommendations
-Historical win rate data
-Risk/reward calculations
-Stop loss and target guidelines
-Timeframe expectations
-Volume confirmation requirements
Implementation Notes
-Timeframe Suitability: Daily charts recommended for primary analysis
-Asset Specificity: Optimized exclusively for Bitcoin spot markets
-Volume Consideration: Higher volume enhances signal reliability
-Market Context: Most effective during trending market conditions
-Institutional Alignment: Designed for professional risk management standards
-Key Performance Metrics
Based on historical backtesting:
-Overall Win Rate: 74% for primary signals
-Risk Reduction: 31% drawdown improvement vs buy-and-hold
-Signal Accuracy: 85% at extreme (3σ) levels
-Optimal Timeframe: 1-12 week holding periods
-Best Performance: April 2024 - January 2025 period
This indicator is designed for professional traders and institutional investors who require sophisticated market analysis tools with quantified risk parameters and historically validated performance metrics.
GCM Bull Bear RiderGCM Bull Bear Rider (GCM BBR)
Your Ultimate Trend-Riding Companion
GCM Bull Bear Rider is a comprehensive, all-in-one trend analysis tool designed to eliminate guesswork and provide a crystal-clear view of market direction. By leveraging a highly responsive Jurik Moving Average (JMA), this indicator not only identifies bullish and bearish trends with precision but also tracks their performance in real-time, helping you ride the waves of momentum from start to finish.
Whether you are a scalper, day trader, or swing trader, the GCM BBR adapts to your style, offering a clean, intuitive, and powerful visual guide to the market's pulse.
Key Features
JMA-Powered Trend Lines (UTPL & DTPL): The core of the indicator. A green "Up Trend Period Line" (UTPL) appears when the JMA's slope turns positive (buyers are in control), and a red "Down Trend Period Line" (DTPL) appears when the slope turns negative (sellers are in control). The JMA is used for its low lag and superior smoothing, giving you timely and reliable trend signals.
Live Profit Tracking Labels: This is the standout feature. As soon as a trend period begins, a label appears showing the real-time profit (P:) from the trend's starting price. This label moves with the trend, giving you instant feedback on its performance and helping you make informed trade management decisions.
Historical Performance Analysis: The profit labels remain on the chart for completed trends, allowing you to instantly review past performance. See at a glance which trends were profitable and which were not, aiding in strategy refinement and backtesting.
Automatic Chart Decluttering: To keep your chart clean and focused on significant moves, the indicator automatically removes the historical profit label for any trend that fails to achieve a minimum profit threshold (default is 0.5 points).
Dual-Ribbon Momentum System:
JMA / Short EMA Ribbon: Visualizes short-term momentum. A green fill indicates immediate bullish strength, while a red fill shows bearish pressure.
Short EMA / Long EMA Ribbon: Acts as a long-term trend filter, providing broader market context for your decisions.
"GCM Hunt" Entry Signals: The indicator includes optional pullback entry signals (green and red triangles). These appear when the price pulls back to a key moving average and then recovers in the direction of the primary trend, offering high-probability entry opportunities.
How to Use
Identify the Trend: Look for the appearance of a solid green line (UTPL) for a bullish bias or a solid red line (DTPL) for a bearish bias. Use the wider EMA ribbon for macro trend confirmation.
Time Your Entry: For aggressive entries, you can enter as soon as a new trend line appears. For more conservative entries, wait for a "GCM Hunt" triangle signal, which confirms a successful pullback.
Ride the Trend & Manage Your Trade: The moving profit label (P:) is your guide. As long as the trend line continues and the profit is increasing, you can confidently stay in the trade. A flattening JMA or a decreasing profit value can signal that the trend is losing steam.
Focus Your Strategy: Use the Display Mode setting to switch between "Buyers Only," "Sellers Only," or both. This allows you to completely hide opposing signals and focus solely on long or short opportunities.
Core Settings
Display Mode: The master switch. Choose to see visuals for "Buyers & Sellers," "Buyers Only," or "Sellers Only."
JMA Settings (Length, Phase): Fine-tune the responsiveness of the core JMA engine.
EMA Settings (Long, Short): Adjust the lengths of the moving averages that define the ribbons and "Hunt" signals.
Label Offset (ATR Multiplier): Customize the gap between the trend lines and the profit labels to avoid overlap with candles.
Filters (EMA, RSI, ATR, Strong Candle): Enable or disable various confirmation filters to strengthen the "Hunt" entry signals according to your risk tolerance.
Add the GCM Bull Bear Rider to your chart today and transform the way you see and trade the trend!
ENJOY
Economic Event Timer & Alerts [AlgoXcalibur]Stay ahead of market-moving news with this real-time event tracker and countdown alert system.
This essential algorithm displays critical scheduled events that may influence sudden spikes in market volatility, helping you stay aware and reduce exposure to unpredictable moves before they even happen. Featuring a captivating on-chart display with event titles, adjustable time zone, real-time countdowns, and live alert notifications — you’ll always know what’s ahead — so you can prepare, not react.
🧠 Algorithm Logic
The Economic Event Timer & Alerts system delivers critical market awareness through an array of integrated functions. At its core, a live countdown table provides real-time updates on the day’s scheduled economic events, with dynamic, color-coded countdowns that ensure fast and easy interpretation at a glance. Complementing the table, Countdown Alerts notify you 30 minutes, 10 minutes, and 1 minute prior to each event—giving you clear, timely reminders without the need to constantly monitor your chart. The adjustable time zone input supports ET, CT, MT, PT, or UTC, so the displayed time-of-event aligns with your trading session. Rigorously refined, the algorithm updates the table daily—and clearly displays No Scheduled Events Today to provide certainty and reassurance on days without scheduled events. Packaged in a minimalist, unobtrusive design, the tool remains visually clean and focused for serious traders.
Updated automatically for hassle-free peace of mind.
⚙️ Features
• Time Zone Selector: Easily toggle between time zones to match your trading session.
• Countdown Alerts: Enable real-time notifications to keep you informed and aware of events without having to monitor the chart.
• Update & Expiration Awareness Feature:
This innovative feature includes a simple visual and alert system that prompts you when it’s time to reload the indicator & recreate alerts — ensuring your alerts are always tied to the latest data update.
🔄 Update Available
On the final day of current event data, the indicator will:
• Display Update Available on the indicator’s table
• Send an alert at 4:00 PM ET reminding you to reload & recreate alerts
You can load the updated version anytime that day.
⛔ Expired
If not reloaded, the next day the indicator will:
• Display an EXPIRED banner on the indicator’s table
• Send a Data Expired alert every day at 8:30 AM ET that prompts you to recreate alerts, until you do or disable the alert.
This prevents missing event alerts unknowingly.
Why is this feature necessary?
Even though the indicator is updated when necessary (typically every 2–4 weeks) to provide upcoming event data automatically, TradingView alerts do not auto-update —they stay tied to the version of the script that was active when the alert was created.
This thoughtful refinement is designed to ensure your alerts remain synced to current events and ready for when it matters most.
🚨 Protect Your Capital
At AlgoXcalibur, we understand that the best way to be profitable is to avoid unnecessary risk.
Dedicated to empowering traders with insight that matters, we designed this tool to transform inconvenient economic calendars into effortless, essential information—displayed directly on your chart. Whether you’re managing open positions or timing new trades, knowing when impactful events are about to hit is crucial to being proactive, protecting capital, and trading with confidence. This is not a technical analysis indicator—this is a risk management tool that provides traders with a fundamental edge.
Built for traders who value risk management, market awareness, and algorithm automation.
🔐 To get access or learn more, visit the Author’s Instructions section.
