Day & Swing Trading EMA Clouds with Adaptive LevelsDay & Swing Trading EMA Clouds with Adaptive Levels is a tool designed for traders who need a flexible indicator that adapts to both short-term (day trading) and long-term (swing trading) strategies. The indicator blends EMA clouds and adaptive support/resistance levels, making it suitable for analyzing trend strength and key price zones.
How It Works:
EMA Clouds for Trend Detection:
This indicator uses three EMAs (Fast, Intermediate, Slow) to create two clouds:
Fast Cloud: The area between the fast and Intermediate EMAs.
Slow Cloud: The area between the Intermediate and slow EMAs.
The cloud colors change based on trend direction:
Positive (uptrend): When the fast EMA is above the Intermediate EMA (turquoise) or the Intermediate EMA is above the slow EMA (teal).
Negative (downtrend): When the fast EMA is below the Intermediate EMA (pink) or the Intermediate EMA is below the slow EMA (magenta).
Traders can use these clouds to visually gauge market momentum and trend reversals.
Adaptive EMA Settings Based on Trading Mode:
The EMA lengths adjust automatically depending on whether you're in Day Trading or Swing Trading mode:
Day Trading Mode uses shorter periods to capture quick price movements:
Fast EMA: 5-period
Mid EMA: 13-period
Slow EMA: 21-period
Swing Trading Mode uses longer periods to capture broader trends:
Fast EMA: 12-period
Mid EMA: 26-period
Slow EMA: 50-period
This dynamic adjustment allows you to switch between trading styles seamlessly, with the EMAs reflecting the most relevant timeframes for each strategy.
Adaptive Support and Resistance Levels:
Depending on the selected trading mode, the indicator dynamically plots key levels:
Day Trading Mode: Previous day’s high, low, and midpoint, as well as 2-day levels.
Swing Trading Mode: Previous month’s high, low, and midpoint, as well as 2-month levels.
These levels act as dynamic support and resistance zones, giving traders critical areas to monitor for potential reversals or breakouts.
Buy & Sell Signals:
Visual buy/sell signals are generated when the fast EMA crosses above or below the slow EMA. These signals can help traders identify potential trend reversals.
Customization:
You can fully adjust the transparency and colors of the clouds to fit your personal preferences and trading style.
Why This Combination?
Combining EMA clouds with adaptive levels provides traders with a complete picture. The clouds highlight the underlying market momentum and trend strength, while the adaptive levels offer potential entry/exit points based on historical price action. This unique mashup allows traders to follow trends and plan trades around key support and resistance zones.
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E9 Shark-32 PatternUnderstanding the Shark-32 Pattern and its Trading Applications
The Shark-32 Pattern is a bearish technical trading formation used to predict market reversals or trend continuations. It highlights a downward move followed by a corrective rally, signaling a potential resumption of the downtrend. Here’s a breakdown of how it works:
What is the Shark-32 Pattern?
The Shark-32 pattern is a five-wave structure typically observed in bearish markets:
Wave 0 to X: A significant price decline starts the pattern.
Wave X to A: A correction pushes the price slightly upward.
Wave A to B: The price drops again but doesn’t reach the initial low.
Wave B to C: A final sharp decline concludes the pattern.
Once Wave C is formed, it suggests that the market will continue to move downward, presenting a potential selling or shorting opportunity.
Using the Pattern in Trading
This pattern is valuable for traders seeking high-probability bearish setups. The goal is to capitalize on the continuation of a downtrend following the corrective rally (X to A). Identifying the Shark-32 pattern helps anticipate the next wave of selling pressure.
Trading Setup
Identify a Shark-32 pattern.
If the price closes above the pattern's high, buy at the open the next day.
If the price closes below the pattern's low, short at the open the next day.
Sell/cover when the price moves 7% in the direction of the breakout.
Close the trade for a loss if the price moves 7% in the opposite direction.
For example, in a bull market after an upward breakout from a Shark-32, the net gain was $69.55. The method won 56% of the time with 5,218 winning trades and an average gain of $714.07. Conversely, 44% of trades were losers, with an average loss of $747.33. The average holding period was 26 calendar days.
The gains and losses were closely aligned with the 7% threshold set for this test.
Key Target Levels
To enhance the strategy, use dotted projection lines as target levels:
Upper Target: Drawn above the high of the corrective rally (Wave A). If the price breaks above this line, it may signal further upward movement, indicating a potentially weaker downtrend.
Lower Target: Positioned below the low of Wave C, providing a target for bearish trades.
These lines help determine future price targets and assist in setting take-profit or stop-loss levels.
Trading the Breakout
Look for breakouts once the Shark-32 pattern is identified:
Upward Breakout: If the price closes above the green line (high from two bars ago), it indicates a potential reversal to the upside.
Downward Breakout: If the price breaks below the red line (low from two bars ago), it confirms the bearish continuation.
Breakouts allow traders to adjust their positions based on market shifts.
Trading Tips
Continuation: The Shark-32 pattern acts as a continuation 60% of the time, confirming the ongoing trend.
Breakout Confirmation: Wait for the price to close above or below the pattern’s key levels before entering a trade.
Trade with the Trend: Since the Shark-32 is a continuation pattern, expect the breakout to align with the inbound price trend.
Symmetry: Patterns with symmetry often perform better. For more insights, refer to detailed trading literature.
Half-Staff: The Shark-32 can form midway in a trend, similar to flags and pennants.
Shark-32: Trading Performance
Based on an analysis of 23,369 trades, the following performance metrics were observed:
Bull Market with Upward Breakout: The average net profit was $69.55. This method won 56% of the time, with winning trades averaging $714.07. Losing trades, which constituted 44% of the total, had an average loss of $747.33. The average holding period was 26 calendar days.
Bull Market with Downward Breakout: The average net loss was $(76.36). This method won 43% of the time, with winning trades averaging $753.56. Losing trades, which constituted 57% of the total, had an average loss of $706.32. The average holding period was 23 calendar days.
Bear Market with Upward Breakout: The average net loss was $(89.13). This method won 46% of the time, with winning trades averaging $710.77. Losing trades, which constituted 54% of the total, had an average loss of $756.97. The average holding period was 16 calendar days.
Bear Market with Downward Breakout: The average net profit was $65.17. This method won 52% of the time, with winning trades averaging $781.62. Losing trades, which constituted 48% of the total, had an average loss of $722.41. The average holding period was 13 calendar days.
Session HighlighterSession Highlighter Script
This Pine Script highlights the major trading sessions on your chart with distinct background colors and markers:
- Asian Session: From 22:00 to 06:00 UTC (Tokyo Open to Close), highlighted in blue.
-European Session: From 07:00 to 15:00 UTC (London Open to Close), highlighted in green.
-U.S. Session: From 13:00 to 21:00 UTC (New York Open to Close), highlighted in red.
Features:
- Background Colors: Different colors indicate the active trading session.
- Markers: Displays labels or shapes at the start of each session to show session changes.
Usage:
- Helps visualize trading session overlaps and market activity throughout the day.
- Ideal for identifying session-specific trends and planning trading strategies.
This script ensures that you can easily see when each major trading session starts and ends, allowing for better market timing and analysis.
Larry Conners Vix Reversal II Strategy (approx.)This Pine Script™ strategy is a modified version of the original Larry Connors VIX Reversal II Strategy, designed for short-term trading in market indices like the S&P 500. The strategy utilizes the Relative Strength Index (RSI) of the VIX (Volatility Index) to identify potential overbought or oversold market conditions. The logic is based on the assumption that extreme levels of market volatility often precede reversals in price.
How the Strategy Works
The strategy calculates the RSI of the VIX using a 25-period lookback window. The RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is often used to identify overbought and oversold conditions in assets.
Overbought Signal: When the RSI of the VIX rises above 61, it signals a potential overbought condition in the market. The strategy looks for a RSI downtick (i.e., when RSI starts to fall after reaching this level) as a trigger to enter a long position.
Oversold Signal: Conversely, when the RSI of the VIX drops below 42, the market is considered oversold. A RSI uptick (i.e., when RSI starts to rise after hitting this level) serves as a signal to enter a short position.
The strategy holds the position for a minimum of 7 days and a maximum of 12 days, after which it exits automatically.
Larry Connors: Background
Larry Connors is a prominent figure in quantitative trading, specializing in short-term market strategies. He is the co-author of several influential books on trading, such as Street Smarts (1995), co-written with Linda Raschke, and How Markets Really Work. Connors' work focuses on developing rules-based systems using volatility indicators like the VIX and oscillators such as RSI to exploit mean-reversion patterns in financial markets.
Risks of the Strategy
While the Larry Connors VIX Reversal II Strategy can capture reversals in volatile market environments, it also carries significant risks:
Over-Optimization: This modified version adjusts RSI levels and holding periods to fit recent market data. If market conditions change, the strategy might no longer be effective, leading to false signals.
Drawdowns in Trending Markets: This is a mean-reversion strategy, designed to profit when markets return to a previous mean. However, in strongly trending markets, especially during extended bull or bear phases, the strategy might generate losses due to early entries or exits.
Volatility Risk: Since this strategy is linked to the VIX, an instrument that reflects market volatility, large spikes in volatility can lead to unexpected, fast-moving market conditions, potentially leading to larger-than-expected losses.
Scientific Literature and Supporting Research
The use of RSI and VIX in trading strategies has been widely discussed in academic research. RSI is one of the most studied momentum oscillators, and numerous studies show that it can capture mean-reversion effects in various markets, including equities and derivatives.
Wong et al. (2003) investigated the effectiveness of technical trading rules such as RSI, finding that it has predictive power in certain market conditions, particularly in mean-reverting markets .
The VIX, often referred to as the “fear index,” reflects market expectations of volatility and has been a focal point in research exploring volatility-based strategies. Whaley (2000) extensively reviewed the predictive power of VIX, noting that extreme VIX readings often correlate with turning points in the stock market .
Modified Version of Original Strategy
This script is a modified version of Larry Connors' original VIX Reversal II strategy. The key differences include:
Adjusted RSI period to 25 (instead of 2 or 4 commonly used in Connors’ other work).
Overbought and oversold levels modified to 61 and 42, respectively.
Specific holding period (7 to 12 days) is predefined to reduce holding risk.
These modifications aim to adapt the strategy to different market environments, potentially enhancing performance under specific volatility conditions. However, as with any system, constant evaluation and testing in live markets are crucial.
References
Wong, W. K., Manzur, M., & Chew, B. K. (2003). How rewarding is technical analysis? Evidence from Singapore stock market. Applied Financial Economics, 13(7), 543-551.
Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
Bull Bear Power With EMA FilterDescription of Indicator:
This Pine Script indicator colors price bars based on the open price in relation to custom moving averages (EMA/SMA), Bull/Bear Power (BBPower), and an optional VWAP filter. The bar colors help identify bullish and bearish conditions with added visual cues for price positioning relative to VWAP.
Key Features:
Customizable Moving Averages (EMA/SMA):
The user can select between EMA or SMA for both short-term and long-term moving averages.
Default moving averages are set to 5 (short-term) and 9 (long-term) but can be adjusted by the user.
Bullish Condition (Blue or Purple Bars):
A bar is colored blue if the following conditions are met:
The open price is above both the short-term and long-term moving averages.
The short-term moving average (MA 1) is above the long-term moving average (MA 2).
BBPower (open price minus the 13-period EMA) is positive, indicating bullish strength.
If the VWAP filter is enabled and the price opens below VWAP, the bullish bars will turn purple.
Bearish Condition (Yellow or Orange Bars):
A bar is colored yellow if the following conditions are met:
The open price is below both the short-term and long-term moving averages.
The short-term moving average (MA 1) is below the long-term moving average (MA 2).
BBPower is negative or zero, indicating bearish market conditions.
If the VWAP filter is enabled and the price opens above VWAP, the bearish bars will turn orange.
VWAP Filter (Optional):
An optional filter allows the user to add VWAP (Volume-Weighted Average Price) to the bar coloring logic.
When the VWAP filter is enabled, it provides additional information about price positioning relative to VWAP, turning bullish bars purple and bearish bars orange depending on whether the price opens above or below VWAP.
Usage:
Bullish Trend: Look for blue or purple bars to identify potential bullish momentum.
Bearish Trend: Look for yellow or orange bars to spot bearish conditions in the market.
The indicator allows users to customize the length and type of moving averages (EMA or SMA), as well as decide whether to apply the VWAP filter.
This indicator provides traders with clear visual signals to quickly assess the strength of bullish or bearish conditions based on the price's position relative to custom moving averages, BBPower, and VWAP, helping with trend identification and potential trade setups.
Break of High/Low with Volume, MACD, and MAsHow It Works:
Sessions:
The London session is defined between 8:00 and 16:00 UTC.
The New York session is defined between 13:00 and 21:00 UTC.
Previous High/Low:
The script identifies the highest high and lowest low from the previous bar using ta.highest(high, 1) and ta.lowest(low, 1) .
Candle Body Size:
The script calculates the size of the current candle's body and checks if it is at least double the size of the previous candle's body.
Volume Check:
A high volume threshold is set as 1.5 times the 50-period SMA of the volume.
MACD Crossover:
The script calculates the MACD and its signal line and checks for bullish (buy) or bearish (sell) crossovers.
Signals:
A long signal (buy) is generated if the price breaks the previous high with a large body candle, high volume, and a bullish MACD crossover during the specified sessions.
A short signal (sell) is generated if the price breaks the previous low with a large body candle, high volume, and a bearish MACD crossover during the specified sessions.
Plotting:
The 50-period and 200-period moving averages, previous high, and previous low are plotted on the chart.
If a long condition is met, a "BUY" label is displayed below the bar. If a short condition is met, a "SELL" label is displayed above the bar.
Alerts:
Alerts are triggered whenever the conditions for a long or short trade are met.
Customization:
Feel free to adjust the session times, volume threshold, MACD settings, or moving averages based on your trading strategy or the specific asset you are trading.
Ehlers Band-Pass FilterHeyo,
This indicator is an original translation from Ehlers' book "Cycle Analytics for Traders Advanced".
First, I describe the indicator as usual and later you can find a very insightful quote of the book.
Key Features
Signal Line: Represents the output of the band-pass filter, highlighting the dominant cycle in the data.
Trigger Line: A leading indicator derived from the signal line, providing early signals for potential market reversals.
Dominant Cycle: Measures the dominant cycle period by counting the number of bars between zero crossings of the band-pass filter output.
Calculation:
The band-pass filter is implemented using a combination of high-pass and low-pass filters.
The filter's parameters, such as period and bandwidth, can be adjusted to tune the filter to specific market cycles.
The signal line is normalized using an Automatic Gain Control (AGC) to provide consistent amplitude regardless of price swings.
The trigger line is derived by applying a high-pass filter to the signal line, creating a leading
waveform.
Usage
The indicator is effective in identifying peaks and valleys in the market data.
It works best in cyclic market conditions and may produce false signals during trending periods.
The dominant cycle measurement helps traders understand the prevailing market cycle length, aiding in better decision-making.
Quoted from the Book
Band-Pass Filters
“A little of the data narrowly passed,” said Tom broadly.
Perhaps the least appreciated and most underutilized filter in technical analysis is the band-pass filter. The band-pass filter simultaneously diminishes the amplitude at low frequencies, qualifying it as a detrender, and diminishes the amplitude at high frequencies, qualifying it as a data smoother.
It passes only those frequency components from input to output in which the trader is interested. The filtering produced by a band-pass filter is superior because the rejection in the stop bands is related to its bandwidth. The degree of rejection of undesired frequency components is called selectivity. The band-stop filter is the dual of the band-pass filter. It rejects a band of frequency components as a notch at the output and passes all other frequency components virtually unattenuated. Since the bandwidth of the deep rejection in the notch is relatively narrow and since the spectrum of market cycles is relatively broad due to systemic noise, the band-stop filter has little application in trading.
Measuring the Cycle Period
The band-pass filter can be used as a relatively simple measurement of the dominant cycle.
A cycle is complete when the waveform crosses zero two times from the last zero crossing. Therefore, each successive zero crossing of the indicator marks a half cycle period. We can establish the dominant cycle period as twice the spacing between successive zero crossings.
When we measure the dominant cycle period this way, it is best to widen the pass band of the band-pass filter to avoid distorting the measurement simply due to the selectivity of the filter. Using an input bandwidth of 0.7 produces an octave-wide pass band. For example, if the center period of the filter is 20 and the relative bandwidth is 0.7, the bandwidth is 14. That means the pass band of the filter extends from 13-bar periods to 27-bar periods.
That is, roughly an octave exists because the longest period is twice the shortest period of the pass band. It is imperative that a high-pass filter is tuned one octave below the half-bandwidth edge of the band-pass filter to ensure a nominal zero mean of the filtered output. Without a zero mean, the zero crossings can have a substantial error.
Since the measurement of the dominant cycle can vary dramatically from zero crossing to zero
crossing, the code limits the change between measurements to be no more than 25 percent.
While measuring the changing dominant cycle period via zero crossings of the band-pass waveform is easy, it is not necessarily the most accurate method.
Best regards,
simwai
Good Luck with your trading! 🙌
Enhanced BOS Strategy with SL/TP and EMA TableDescription:
The Enhanced BOS (Break of Structure) Strategy is an advanced open-source trading indicator designed to identify key market structure changes, integrated with dynamic Stop Loss (SL) and Take Profit (TP) levels, along with an informative EMA (Exponential Moving Average) table for added trend analysis.
Key Features:
Break of Structure (BOS) Detection:
The script detects bullish and bearish BOS by identifying pivot points using a custom pivot period. When the price crosses above or below these points, it signals a potential market trend reversal or continuation.
Dynamic SL/TP Levels:
Users can toggle static SL/TP settings, which automatically calculate levels based on user-defined points. These levels are visualized on the chart with dotted lines and labeled for clarity.
Volume Filters:
The strategy includes a volume condition filter to ensure that only trades within a specified volume range are considered. This helps in avoiding low-volume trades that might lead to false signals.
EMA Table Display:
An on-chart table displaying the current values of the 13-period, 50-period, and 200-period EMAs. This provides a quick reference for trend identification and confirmation, helping traders to stay aligned with the broader market trend.
How It Works:
The script utilizes a combination of moving averages and pivot points to identify potential breakouts or breakdowns in market structure. When a bullish BOS is detected, and the volume conditions are met, the strategy suggests a long position, marking potential SL/TP levels. Similarly, it suggests short positions for bearish BOS.
The EMA table serves as a visual aid, providing real-time updates of the EMA values, allowing traders to gauge the market’s directional bias quickly.
How to Use:
Setting Parameters:
Adjust the pivot period to fine-tune BOS detection according to your trading style and the asset’s volatility.
Configure the SL/TP settings based on your risk tolerance and target profit levels.
Interpreting Signals:
A “Buy” label on the chart indicates a bullish BOS with volume confirmation, signaling a potential long entry.
A “Sell” label indicates a bearish BOS with volume confirmation, signaling a potential short entry.
The EMA table aids in confirming these signals, where the position of the fast, mid, and slow EMAs can provide additional context to the trend’s strength and direction.
Volume Filtering:
Ensure your trades are filtered through the script’s volume condition, which allows for the exclusion of low-volume periods that might generate unreliable signals.
Unique Value:
Unlike many other BOS strategies, this script integrates volume conditions and a visual EMA table, providing a comprehensive toolkit for traders looking to capture market structure shifts while maintaining an eye on trend direction and trade execution precision.
Additional Information:
This script is designed for use on standard bar or candlestick charts for best results.
It is open-source and free to use, encouraging collaboration and improvement by the TradingView community.
By combining powerful trend-following EMAs with the precision of BOS detection and the safety of volume filtering, the Enhanced BOS Strategy offers a balanced approach to trading market structure changes.
Monthly Purchase Strategy with Dynamic Contract Size This trading strategy is designed to automate monthly purchases of a security, adjusting the size of each purchase based on the percentage of the portfolio's equity. The key features of this strategy include:
Monthly Purchases: The strategy buys the security on a specified day of each month, based on the user's input.
Dynamic Position Sizing: The size of each purchase is calculated as a percentage of the current equity. This allows the position size to adjust dynamically with the portfolio's performance.
Slippage and Commission Considerations: Slippage is simulated by adjusting the entry price by a set number of ticks, while commissions are factored in as fixed costs per trade.
Drawdown Calculation: The strategy tracks the highest equity value and calculates the drawdown, which is the percentage decrease from this peak equity. This helps in assessing the performance and risk of the strategy.
Benefits of the Strategy
Automated Investment: The strategy automates the investment process, reducing the need for manual trading decisions and ensuring consistent execution.
Dynamic Position Sizing: By adjusting the purchase size based on the portfolio’s equity, the strategy helps in managing risk and capitalizing on market movements proportionally to the portfolio’s performance.
Regular Investments: Investing on a regular schedule helps in averaging the purchase price of the security, which can reduce the impact of short-term volatility.
Risk Management: Monitoring drawdown helps in assessing the risk and performance of the strategy, providing insights into potential losses relative to the highest equity value.
Scientific Documentation on ETF Savings Plans
1. Dollar-Cost Averaging and Investment Behavior:
Title: "The Benefits of Dollar-Cost Averaging: A Study of Investment Behavior"
Authors: William F. Sharpe
Journal: Financial Analysts Journal, 1994
Summary: This study discusses the concept of dollar-cost averaging (DCA), which involves investing a fixed amount of money at regular intervals regardless of market conditions. The study highlights that DCA can reduce the impact of market volatility and lower the average cost of investments over time.
Reference: Sharpe, W. F. (1994). The Benefits of Dollar-Cost Averaging: A Study of Investment Behavior. Financial Analysts Journal, 50(4), 27-36.
2. ETFs and Long-Term Investment Strategies:
Title: "Exchange-Traded Funds and Their Role in Long-Term Investment Strategies"
Authors: John C. Bogle
Journal: The Journal of Portfolio Management, 2007
Summary: This paper explores the advantages of using ETFs for long-term investment strategies, emphasizing their low costs, tax efficiency, and diversification benefits. It also discusses how ETFs can be used effectively in automated investment plans like ETF savings plans.
Reference: Bogle, J. C. (2007). Exchange-Traded Funds and Their Role in Long-Term Investment Strategies. The Journal of Portfolio Management, 33(4), 14-25.
3. Risk and Return in ETF Investments:
Title: "Risk and Return Characteristics of Exchange-Traded Funds"
Authors: Eugene F. Fama and Kenneth R. French
Journal: Journal of Financial Economics, 2010
Summary: Fama and French analyze the risk and return characteristics of ETFs compared to traditional mutual funds. The study provides insights into how ETFs can be a viable option for investors seeking diversified exposure while managing risk and optimizing returns.
Reference: Fama, E. F., & French, K. R. (2010). Risk and Return Characteristics of Exchange-Traded Funds. Journal of Financial Economics, 96(2), 257-278.
4. The Impact of Automated Investment Plans:
Title: "The Impact of Automated Investment Plans on Portfolio Performance"
Authors: David G. Blanchflower and Andrew J. Oswald
Journal: Journal of Behavioral Finance, 2012
Summary: This research examines how automated investment plans, including ETF savings plans, affect portfolio performance. It highlights the benefits of automation in reducing behavioral biases and ensuring consistent investment practices.
Reference: Blanchflower, D. G., & Oswald, A. J. (2012). The Impact of Automated Investment Plans on Portfolio Performance. Journal of Behavioral Finance, 13(2), 77-89.
Summary
The "Monthly Purchase Strategy with Dynamic Contract Size and Drawdown" provides a disciplined approach to investing by automating purchases and adjusting position sizes based on portfolio equity. It leverages the benefits of dollar-cost averaging and regular investment, with risk management through drawdown monitoring. Scientific literature supports the effectiveness of ETF savings plans and automated investment strategies in optimizing returns and managing investment risk.
Enhanced Alligator Trend Indicator By Er. Parvez HaleemPurpose: The Enhanced Alligator Trend Indicator aims to identify strong and reliable buy and sell signals on the price chart by combining the Alligator Indicator with trend strength and volume filters. It is specifically designed for use on a 1-minute chart to enhance precision in short-term trading decisions.
Components:
Alligator Indicator:
Jaw Line (Blue): Calculated as a simple moving average (SMA) of the closing price over a specified period (default: 13 bars). Represents the long-term trend.
Teeth Line (Red): Calculated as a simple moving average (SMA) of the closing price over a shorter period (default: 8 bars). Represents the medium-term trend.
Lips Line (Green): Calculated as a simple moving average (SMA) of the closing price over an even shorter period (default: 5 bars). Represents the short-term trend.
Trend Strength Indicator:
Relative Strength Index (RSI): Measures the strength of the current trend, using a default period of 14 bars. RSI values above 50 suggest a bullish trend, while values below 50 suggest a bearish trend.
Volume Filter:
Volume Threshold: Filters signals based on trading volume to ensure they only appear when volume exceeds a specified threshold (default: 100,000). This helps to avoid low-volume noise and enhance signal reliability.
Additional Trend Filters:
Short-Term SMA: A simple moving average with a default period of 20 bars, used to assess short-term trend direction.
Long-Term SMA: A simple moving average with a default period of 50 bars, used to assess long-term trend direction.
SMA Crossover: A bullish crossover occurs when the short-term SMA is above the long-term SMA, and a bearish crossover occurs when the short-term SMA is below the long-term SMA.
Signal Generation:
Buy Signal: Generated when:
The Lips line is above the Teeth line, and the Teeth line is above the Jaw line (indicating a bullish alignment in the Alligator Indicator).
The RSI is above 50 (indicating strong bullish trend strength).
The trading volume exceeds the specified volume threshold (indicating sufficient trading activity).
The short-term SMA is above the long-term SMA (confirming a bullish trend).
Sell Signal: Generated when:
The Lips line is below the Teeth line, and the Teeth line is below the Jaw line (indicating a bearish alignment in the Alligator Indicator).
The RSI is below 50 (indicating strong bearish trend strength).
The trading volume exceeds the specified volume threshold (indicating sufficient trading activity).
The short-term SMA is below the long-term SMA (confirming a bearish trend).
Plotting on Chart:
Alligator Lines: The Jaw, Teeth, and Lips lines are plotted directly on the price chart in blue, red, and green, respectively, to indicate the long-term, medium-term, and short-term trends.
Buy/Sell Signals: Buy signals are plotted below the price bars in green, and sell signals are plotted above the price bars in red. These signals are marked with labels ("BUY" and "SELL") to clearly indicate trading opportunities.
Debugging: RSI and SMA lines are plotted but hidden by default. They can be revealed for verification purposes to ensure the correctness of the indicator’s calculations.
Alerts:
Buy Alert: Triggers when a buy signal condition is met, sending a notification that a buy opportunity has been identified.
Sell Alert: Triggers when a sell signal condition is met, sending a notification that a sell opportunity has been identified.
CoT Trend Change MomentumI discovered that whenever there's huge change in long IO or short IO there will be a momentum shift. So, I created this indicator to spot massive explosive volume changes for commercials and non commercials activity. Using standard deviation 2 and -2 as extreme point. Whatever crossing above standard deviation 2 indicating positions are added regardless whether it is long or shorts, whatever crossing below standard deviation -2 means positions are closed.
This is how I use this indicator:
1) In this example , i use only the commercials long and shorts. Whenever the longs exceed stdeviation +2, means that long volume flow in massively, for me this can be indicating potential to the upside. Whenever longs fall below stdeviation-2, for me this can be indicating that commercials are either taking profits for the short positions or accumulating for another bull price.
2) For shorts same logic applied here, when it exceeds stdeviation +2, mean commercials shorts position increase massively, when it exceeds stdeviation-2, means that commercials closed their short positions.
For this script, I use 13 weeks period as lookback, u guys may directly modify the period in the script to set the period that u want.
I've added for non-commercials as well, to ease people who emphasizes on non-commercials positioning analysis process.
I'm still trying to incorporate this with Open Interest Analysis. Hopefully u guys find this indicator useful. Feel free to modify it, to understand it more, my suggestions are u compare date by date the positions, to see the extreme points. The indicator only works in weekly chart, it is non repainted only in weekly chart, meaning that the indicator shows the histogram just as the week open.
Six PillarsGeneral Overview
The "Six Pillars" indicator is a comprehensive trading tool that combines six different technical analysis methods to provide a holistic view of market conditions.
These six pillars are:
Trend
Momentum
Directional Movement (DM)
Stochastic
Fractal
On-Balance Volume (OBV)
The indicator calculates the state of each pillar and presents them in an easy-to-read table format. It also compares the current timeframe with a user-defined comparison timeframe to offer a multi-timeframe analysis.
A key feature of this indicator is the Confluence Strength meter. This unique metric quantifies the overall agreement between the six pillars across both timeframes, providing a score out of 100. A higher score indicates stronger agreement among the pillars, suggesting a more reliable trading signal.
I also included a visual cue in the form of candle coloring. When all six pillars agree on a bullish or bearish direction, the candle is colored green or red, respectively. This feature allows traders to quickly identify potential high-probability trade setups.
The Six Pillars indicator is designed to work across multiple timeframes, offering a comparison between the current timeframe and a user-defined comparison timeframe. This multi-timeframe analysis provides traders with a more comprehensive understanding of market dynamics.
Origin and Inspiration
The Six Pillars indicator was inspired by the work of Dr. Barry Burns, author of "Trend Trading for Dummies" and his concept of "5 energies." (Trend, Momentum, Cycle, Support/Resistance, Scale) I was intrigued by Dr. Burns' approach to analyzing market dynamics and decided to put my own twist upon his ideas.
Comparing the Six Pillars to Dr. Burns' 5 energies, you'll notice I kept Trend and Momentum, but I swapped out Cycle, Support/Resistance, and Scale for Directional Movement, Stochastic, Fractal, and On-Balance Volume. These changes give you a more dynamic view of market strength, potential reversals, and volume confirmation all in one package.
What Makes This Indicator Unique
The standout feature of the Six Pillars indicator is its Confluence Strength meter. This feature calculates the overall agreement between the six pillars, providing traders with a clear, numerical representation of signal strength.
The strength is calculated by considering the state of each pillar in both the current and comparison timeframes, resulting in a score out of 100.
Here's how it calculates the strength:
It considers the state of each pillar in both the current timeframe and the comparison timeframe.
For each pillar, the absolute value of its state is taken. This means that both strongly bullish (2) and strongly bearish (-2) states contribute equally to the strength.
The absolute values for all six pillars are summed up for both timeframes, resulting in two sums: current_sum and alternate_sum.
These sums are then added together to get a total_sum.
The total_sum is divided by 24 (the maximum possible sum if all pillars were at their strongest states in both timeframes) and multiplied by 100 to get a percentage.
The result is rounded to the nearest integer and capped at a minimum of 1.
This calculation method ensures that the Confluence Strength meter takes into account not only the current timeframe but also the comparison timeframe, providing a more robust measure of overall market sentiment. The resulting score, ranging from 1 to 100, gives traders a clear and intuitive measure of how strongly the pillars agree, with higher scores indicating stronger potential signals.
This approach to measuring signal strength is unique in that it doesn't just rely on a single aspect of price action or volume. Instead, it takes into account multiple factors, providing a more robust and reliable indication of potential market moves. The higher the Confluence Strength score, the more confident traders can be in the signal.
The Confluence Strength meter helps traders in several ways:
It provides a quick and easy way to gauge the overall market sentiment.
It helps prioritize potential trades by identifying the strongest signals.
It can be used as a filter to avoid weaker setups and focus on high-probability trades.
It offers an additional layer of confirmation for other trading strategies or indicators.
By combining the Six Pillars analysis with the Confluence Strength meter, I've created a powerful tool that not only identifies potential trading opportunities but also quantifies their strength, giving traders a significant edge in their decision-making process.
How the Pillars Work (What Determines Bullish or Bearish)
While developing this indicator, I selected and configured six key components that work together to provide a comprehensive view of market conditions. Each pillar is set up to complement the others, creating a synergistic effect that offers traders a more nuanced understanding of price action and volume.
Trend Pillar: Based on two Exponential Moving Averages (EMAs) - a fast EMA (8 period) and a slow EMA (21 period). It determines the trend by comparing these EMAs, with stronger trends indicated when the fast EMA is significantly above or below the slow EMA.
Directional Movement (DM) Pillar: Utilizes the Average Directional Index (ADX) with a default period of 14. It measures trend strength, with values above 25 indicating a strong trend. It also considers the Positive and Negative Directional Indicators (DI+ and DI-) to determine trend direction.
Momentum Pillar: Uses the Moving Average Convergence Divergence (MACD) with customizable fast (12), slow (26), and signal (9) lengths. It compares the MACD line to the signal line to determine momentum strength and direction.
Stochastic Pillar: Employs the Stochastic oscillator with a default period of 13. It identifies overbought conditions (above 80) and oversold conditions (below 20), with intermediate zones between 60-80 and 20-40.
Fractal Pillar: Uses Williams' Fractal indicator with a default period of 3. It identifies potential reversal points by looking for specific high and low patterns over the given period.
On-Balance Volume (OBV) Pillar: Incorporates On-Balance Volume with three EMAs - short (3), medium (13), and long (21) periods. It assesses volume trends by comparing these EMAs.
Each pillar outputs a state ranging from -2 (strongly bearish) to 2 (strongly bullish), with 0 indicating a neutral state. This standardized output allows for easy comparison and aggregation of signals across all pillars.
Users can customize various parameters for each pillar, allowing them to fine-tune the indicator to their specific trading style and market conditions. The multi-timeframe comparison feature also allows users to compare pillar states between the current timeframe and a user-defined comparison timeframe, providing additional context for decision-making.
Design
From a design standpoint, I've put considerable effort into making the Six Pillars indicator visually appealing and user-friendly. The clean and minimalistic design is a key feature that sets this indicator apart.
I've implemented a sleek table layout that displays all the essential information in a compact and organized manner. The use of a dark background (#030712) for the table creates a sleek look that's easy on the eyes, especially during extended trading sessions.
The overall design philosophy focuses on presenting complex information in a simple, intuitive format, allowing traders to make informed decisions quickly and efficiently.
The color scheme is carefully chosen to provide clear visual cues:
White text for headers ensures readability
Green (#22C55E) for bullish signals
Blue (#3B82F6) for neutral states
Red (#EF4444) for bearish signals
This color coding extends to the candle coloring, making it easy to spot when all pillars agree on a bullish or bearish outlook.
I've also incorporated intuitive symbols (↑↑, ↑, →, ↓, ↓↓) to represent the different states of each pillar, allowing for quick interpretation at a glance.
The table layout is thoughtfully organized, with clear sections for the current and comparison timeframes. The Confluence Strength meter is prominently displayed, providing traders with an immediate sense of signal strength.
To enhance usability, I've added tooltips to various elements, offering additional information and explanations when users hover over different parts of the indicator.
How to Use This Indicator
The Six Pillars indicator is a versatile tool that can be used for various trading strategies. Here are some general usage guidelines and specific scenarios:
General Usage Guidelines:
Pay attention to the Confluence Strength meter. Higher values indicate stronger agreement among the pillars and potentially more reliable signals.
Use the multi-timeframe comparison to confirm signals across different time horizons.
Look for alignment between the current timeframe and comparison timeframe pillars for stronger signals.
One of the strengths of this indicator is it can let you know when markets are sideways – so in general you can know to avoid entering when the Confluence Strength is low, indicating disagreement among the pillars.
Customization Options
The Six Pillars indicator offers a wide range of customization options, allowing traders to tailor the tool to their specific needs and trading style. Here are the key customizable elements:
Comparison Timeframe:
Users can select any timeframe for comparison with the current timeframe, providing flexibility in multi-timeframe analysis.
Trend Pillar:
Fast EMA Period: Adjustable for quicker or slower trend identification
Slow EMA Period: Can be modified to capture longer-term trends
Momentum Pillar:
MACD Fast Length
MACD Slow Length
MACD Signal Length These can be adjusted to fine-tune momentum sensitivity
DM Pillar:
ADX Period: Customizable to change the lookback period for trend strength measurement
ADX Threshold: Adjustable to define what constitutes a strong trend
Stochastic Pillar:
Stochastic Period: Can be modified to change the sensitivity of overbought/oversold readings
Fractal Pillar:
Fractal Period: Adjustable to identify potential reversal points over different timeframes
OBV Pillar:
Short OBV EMA
Medium OBV EMA
Long OBV EMA These periods can be customized to analyze volume trends over different timeframes
These customization options allow traders to experiment with different settings to find the optimal configuration for their trading strategy and market conditions. The flexibility of the Six Pillars indicator makes it adaptable to various trading styles and market environments.
ICT opening price lineShows you the opening price of a certain time of day. I will show as line starting from the time selected and ending a few bars into the future. Available times are the ones ICT said are relevant for framing a premium and discount using opening prices: 00:00, 8:30 and 13:30. To show all 3 you have to add the indicator 3 times.
The script offers some customization on how the line should look line and if you want a label telling the time of it after the line.
Ripster MTF CloudsDescription:
MTF EMA Cloud By Ripster
EMA Cloud System is a Trading System Invented by Ripster where areas are shaded between two desired EMAs. The concept implies the EMA cloud area serves as support or resistance for Intraday & Swing Trading. This can be utilized effectively on 10 Min for day trading and 1Hr/Daily for Swings. Ripster himself utilizes various combinations of the 5-12, 34-50, 8-9, 20-21 EMA clouds but the possibilities are endless to find what works best for you.
“Ideally, 5-12 or 5-13 EMA cloud acts as a fluid trendline for day trades. 8-9 EMA Clouds can be used as pullback Levels –(optional). Additionally, a high level price over or under 34-50 EMA clouds confirms either bullish or bearish bias on the price action for any timeframe” – Ripster
This indicator is an extension of the Ripster EMA Clouds. It allows you to visualize Exponential Moving Average (EMA) clouds from any time frame on your current chart, regardless of the chart's own time frame. This functionality is especially useful for traders who want to monitor higher time frame trends and support/resistance levels while trading on lower time frames.
What does this code do?
The Ripster MTF Clouds indicator displays two sets of EMA clouds. Each set consists of a short EMA and a long EMA. By default, the indicator uses Daily 20/21 and 50/55 EMAs, but you can customize these settings to fit your trading strategy. The EMAs are plotted on your chart along with their corresponding clouds, colored for easy differentiation:
EMA 1 (default 50/55): Plotted in blue.
EMA 2 (default 20/21): Plotted in teal.
The indicator uses the security function to fetch EMA values from higher time frames and plots them on your current chart, allowing you to see how these higher time frame EMAs interact with your current time frame's price action.
How to use this indicator:
Adjust Resolution:
Set the "Resolution" input to the time frame from which you want to fetch EMA values. For example, set it to "1H" if you want to see 1-hour EMAs on your current chart.
Customize EMAs:
Modify the "EMA 1 Short Length" and "EMA 1 Long Length" inputs to change the default 50/55 EMAs.
Adjust the "EMA 2 Short Length" and "EMA 2 Long Length" inputs to change the default 20/21 EMAs.
Monitor Clouds:
The indicator fills the area between the short and long EMAs, creating a cloud that helps visualize the trend. A blue cloud indicates the area between the EMA 1 pair, while a teal cloud indicates the area between the EMA 2 pair.
Use Multiple Instances:
You can add multiple instances of this indicator to your chart to monitor multiple higher time frames simultaneously. For instance, one instance can show daily clouds while another shows hourly clouds.
Integration with Trading Strategy:
Use this indicator to identify higher time frame trends and support/resistance levels, which can help improve your trading decisions on lower time frames.
For example, you can go long when the stock is above the 50-55 EMA clouds and 20-21 EMA clouds with daily resolution on a 10-minute chart and short when it is below it.
Similarly, you can short a stock under the 1-hour 34/50 EMA clouds while still trading on a 10-minute chart.
Average Session Range [QuantVue]The Average Session Range or ASR is a tool designed to find the average range of a user defined session over a user defined lookback period.
Not only is this indicator is useful for understanding volatility and price movement tendencies within sessions, but it also plots dynamic support and resistance levels based on the ASR.
The average session range is calculated over a specific period (default 14 sessions) by averaging the range (high - low) for each session.
Knowing what the ASR is allows the user to determine if current price action is normal or abnormal.
When a new session begins, potential support and resistance levels are calculated by breaking the ASR into quartiles which are then added and subtracted from the sessions opening price.
The indicator also shows an ASR label so traders can know what the ASR is in terms of dollars.
Session Time Configuration:
The indicator allows users to define the session time, with default timing set from 13:00 to 22:00.
ASR Calculation:
The ASR is calculated over a specified period (default 14 sessions) by averaging the range (high - low) of each session.
Various levels based on the ASR are computed: 0.25 ASR, 0.5 ASR, 0.75 ASR, 1 ASR, 1.25 ASR, 1.5 ASR, 1.75 ASR, and 2 ASR.
Visual Representation:
The indicator plots lines on the chart representing different ASR levels.
Customize the visibility, color, width, and style (Solid, Dashed, Dotted) of these lines for better visualization.
Labels for these lines can also be displayed, with customizable positions and text properties.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
Gator TailGator Tail
Building on Bill William’s Alligator, the Gator Tail provides the trader with a scaled value of deviation between the market price and the rolling average. Meant to be used as a trend reversal indicator, best results when combined with the Awesome Oscillator (AO).
Script Theory Basics
This script is based off of the Bill Williams Alligator indicator. In this indicator, the variance between the ‘jaw’ and the current price represents the deviation of price from its average. Using the alligator, the trader must identify this using their eye only. This script provides a numerical value, charted in histogram format like the Awesome Oscillator. Using the two in tandem allows the trader to identify reversal points and act on positions accordingly.
Script Technicalities
The Gator Tail value is derived as follows. To preface, the ‘jaw’ is a 13 period simple moving average, plotted 8 periods into the future on the chart. A calculation is performed on the ‘jaw’ value to extract its current value less the offset. This value is compared to the current price at the time of printing the equation. Price takes the hl2 value (high + low / 2). The variance between the two values is calculated by subtracting the jaw offset from the price value, and dividing this value by the offset value ( / jaw offset). This value prints as an absolute (irrespective of positive or negative) and gets plotted on the chart for the period. The range of values is 0.00 to 1.00.
Using Gator Tail
Any value above 0.20 is considered to be in the warning range. Values exceeding the 0.35-0.40 range are considered to be highly deviated. Highly deviated Gator Tail values combined with a color reversal from the AO indicate an entry/exit point in the chart.
Using the two indicators on top of one another provides an easy visual cue to identify market reversal points. In the example chart above, we can see the red arrows on the Gator Tail coinciding with the AO reversals to result in the chart movements in the candlestick pane.
Limitations
This indicator does not work well with cryptocurrencies (altcoins or otherwise). The prices in these markets have few ties to macroeconomic trends or performance of an underlying asset. When testing this script, it was not found to be a reliable predictor of market reversals. This script is meant to be used with standard equities (stocks, stock options, currencies) where markets follow a reasonable level of predictability and have some underlying tie to real world events and relativity to historical prices.
ICT KillZones Hunt [TradingFinder] 4 Sessions + OB + FVG + Alert🔵 Introduction
🟣 ICT
The "ICT" style is a subset of "Price Action" technical analysis. The primary goal of the ICT trading strategy is to merge "Price Action" with the "Smart Money" concept to pinpoint optimal trade entry points.
However, this approach's strength extends beyond merely finding entry points. It also helps traders gain a deeper understanding of price behavior and adapt their trading strategies to the market structure.
The most important concepts of "ICT" :
Order Block
Fair Value Gap(FVG)
Liquidity
🟣 Session
Financial markets are divided into several time periods, each featuring distinct characteristics and levels of activity. These periods, known as sessions, are active at different times during the day.
The primary active sessions in financial markets include :
Asian Session
European Session
New York Session
Based on the UTC time zone, the schedule for these key sessions is :
Asian Session: 23:00 to 06:00
European Session: 07:00 to 16:30
New York Session: 13:00 to 22:00
Note
To avoid session overlap and minimize interference during kill zones, the session times have been modified as follows :
Asian Session: 23:00 to 06:00
European Session: 07:00 to 14:25
New York Session: 14:30 to 22:55
🟣 KillZone
Kill zones are periods within a session where trader activity spikes. During these times, trading volume surges, and price movements become more pronounced.
The major kill zones, according to the UTC time zone, are as follows :
Asian Kill Zone: 23:00 to 03:55
European Kill Zone: 07:00 to 09:55
New York Morning Kill Zone: 14:30 to 16:55
New York Evening Kill Zone: 19:30 to 20:55
🔵 How to Use
🟣 Order Block
Order blocks are a distinct category of "Supply and Demand" zones, formed when a series of orders are grouped together. These blocks are often created by banks or other significant market participants.
Banks typically execute large orders in blocks during their trading sessions. If they were to enter the market with small quantities, substantial price movements would occur before the orders were fully executed, reducing potential profit.
To mitigate this, they divide their orders into smaller, more manageable positions. Traders should seek "buy" opportunities in "demand order blocks" and "sell" opportunities in "supply order blocks."
🟣 Fair Value Gap (FVG)
To pinpoint the "Fair Value Gap" on the chart, meticulous candle-by-candle analysis is essential. Pay close attention to candles with significant bodies, examining each candle alongside the one preceding it.
The candles flanking this central candle should exhibit elongated shadows, with bodies that do not intersect the body of the central candle. The span between the shadows of the first and third candles is referred to as the FVG range.
Note :
The origin of all Order Blocks and FVGs starts from inside a kill zone and extends up to the end of the same session.
🟣 Kill Zone Hunt
Following this strategy, after the conclusion of the kill zone and the stabilization of its high and low lines, if the price touches either of these lines within the same session and encounters a robust rejection, it presents an opportunity to enter a trade.
🔵 Setting
🟣 Global Setting
Show All Order Block :
If it is turned off, only the last Order Block will be displayed.
Show All FVG :
If it is turned off, only the last FVG will be displayed.
Show More Info Session :
If it is turned on, more information about kill zones (Trade Volume, Time, Number of Candles) will be displayed.
🟣 Logic Parameter
Pivot Period of Order Blocks Detector :
Enter the desired pivot period to identify the Order Block.
Order Block Validity Period (Bar) :
You can specify the maximum time the Order Block remains valid based on the number of candles from the origin.
Mitigation Level Order Block :
Determining the basic level of a block order. When the price hits the basic level, the order block due to mitigation.
🟣 Order Blocks Display
Demand Order Block :
Show or not show and specify color.
Supply order Block :
Show or not show and specify color.
🟣 Order Block Refinement
Refine Demand OB :
Enable or disable the refinement feature. Mode selection.
Refine Supply OB :
Enable or disable the refinement feature. Mode selection.
🟣 FVG
FVG Validity Period (Bar) :
You can specify the maximum time the FVG remains valid based on the number of candles from the origin.
Mitigation Level FVG :
Determining the basic level of a FVG. When the price hits the basic level, the FVG due to mitigation.
Show Demand FVG :
Show or not show and specify color.
Show Supply FVG :
Show or not show and specify color.
FVG Filter :
Enable or disable filtering of FVGs. Select filter mode.
🟣 Session
Show More Info Session Color
Asia Session, London Sesseion, New York am Session & New York pm Session :
Show or not show session and kill zones. Change the display color.
🟣 Alert
Send Alert When Touched Session high & Low :
On / Off
Alert Demand OB Mitigation :
On / Off
Alert Supply OB Mitigation :
On / Off
Alert Demand FVG Mitigation :
On / Off
Alert Supply FVG Mitigation :
On / Off
Message Frequency :
This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone :
The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
Display More Info :
Displays information about the price range of the order blocks (Zone Price) and the date, hour, and minute under "Display More Info". If you do not want this information to appear in the received message along with the alert, you should set it to "Off".
Chuck Dukas Market Phases of Trends (based on 2 Moving Averages)This script is based on the article “Defining The Bull And The Bear” by Chuck Duckas, published in Stocks & Commodities V. 25:13 (14-22); (S&C Bonus Issue, 2007).
The article “Defining The Bull And The Bear” discusses the concepts of “bullish” and “bearish” in relation to the price behavior of financial instruments. Chuck Dukas explains the importance of analyzing price trends and provides a framework for categorizing price activity into six phases. These phases, including recovery, accumulation, bullish, warning, distribution, and bearish, help to assess the quality of the price structure and guide decision-making in trading. Moving averages are used as tools for determining the context preceding the current price action, and the slope of a moving average is seen as an indicator of trend and price phase analysis.
The six phases of trends
// Definitions of Market Phases
recovery_phase = src > ma050 and src < ma200 and ma050 < ma200 // color: blue
accumulation_phase = src > ma050 and src > ma200 and ma050 < ma200 // color: purple
bullish_phase = src > ma050 and src > ma200 and ma050 > ma200 // color: green
warning_phase = src < ma050 and src > ma200 and ma050 > ma200 // color: yellow
distribution_phase = src < ma050 and src < ma200 and ma050 > ma200 // color: orange
bearish_phase = src < ma050 and src < ma200 and ma050 < ma200 // color red
Recovery Phase : This phase marks the beginning of a new trend after a period of consolidation or downtrend. It is characterized by the gradual increase in prices as the market starts to recover from previous losses.
Accumulation Phase : In this phase, the market continues to build a base as prices stabilize before making a significant move. It is a period of consolidation where buying and selling are balanced.
Bullish Phase : The bullish phase indicates a strong upward trend in prices with higher highs and higher lows. It is a period of optimism and positive sentiment in the market.
Warning Phase : This phase occurs when the bullish trend starts to show signs of weakness or exhaustion. It serves as a cautionary signal to traders and investors that a potential reversal or correction may be imminent.
Distribution Phase : The distribution phase is characterized by the market topping out as selling pressure increases. It is a period where supply exceeds demand, leading to a potential shift in trend direction.
Bearish Phase : The bearish phase signifies a strong downward trend in prices with lower lows and lower highs. It is a period of pessimism and negative sentiment in the market.
These rules of the six phases outline the cyclical nature of market trends and provide traders with a framework for understanding and analyzing price behavior to make informed trading decisions based on the current market phase.
60-period channel
The 60-period channel should be applied differently in each phase of the market cycle.
Recovery Phase : In this phase, the 60-period channel can help identify the beginning of a potential uptrend as price stabilizes or improves. Traders can look for new highs frequently in the 60-period channel to confirm the trend initiation or continuation.
Accumulation Phase : During the accumulation phase, the 60-period channel can highlight that the current price is sufficiently strong to be above recent price and longer-term price. Traders may observe new highs frequently in the 60-period channel as the slope of the 50-period moving average (SMA) trends upwards while the 200-period moving average (SMA) slope is losing its downward slope.
Bullish Phase : In the bullish phase, the 60-period channel showing a series of higher highs is crucial for confirming the uptrend. Additionally, traders should observe an upward-sloping 50-period SMA above an upward-sloping 200-period SMA for further validation of the bullish phase.
Warning Phase : When in the warning phase, the 60-period channel can provide insights into whether the current price is weaker than recent prices. Traders should pay attention to the relationship between the price close, the 50-period SMA, and the 200-period SMA to gauge the strength of the phase.
Distribution Phase : In the distribution phase, traders should look for new lows frequently in the 60-period channel, hinting at a weakening trend. It is crucial to observe that the 50-period SMA is still above the 200-period SMA in this phase.
Bearish Phase : Lastly, in the bearish phase, the 60-period channel reflecting a series of lower lows confirms the downtrend. Traders should also note that the price close is below both the 50-period SMA and the 200-period SMA, with the relationship of the 50-period SMA being less than the 200-period SMA.
By carefully analyzing the 60-period channel in each phase, traders can better understand market trends and make informed decisions regarding their investments.
Color Stochastic IndicatorThis Pine Script™ indicator, "Color Stochastic Indicator," is designed to visualize the stochastic oscillator with color-coded trends and shaded background levels, providing a clearer understanding of market trends and potential trading signals.
Key Features:
Customizable Parameters:
K Period: The period for the %K line in the stochastic calculation (default: 50).
D Period: The period for the %D line, which is the moving average of %K (default: 13).
Slowing: The slowing factor applied to the stochastic calculation (default: 2).
Smoothing: A factor for additional smoothing of the stochastic values (default: 1.0).
Use Crossover: Option to determine trend based on the crossover of %K and %D lines.
Display Levels: Option to show significant stochastic levels on the chart (0.2, 0.5, 0.8).
Price Field: Selection of the price field used in calculations.
Stoch Width: Line width for the %K line.
Signal Width: Line width for the %D line.
Background Colors:
Upper Level Background: Shaded area between 0.5 and 0.8 with a customizable color.
Lower Level Background: Shaded area between 0.2 and 0.5 with a customizable color.
Color-Coded Trends:
Wait (Gray): Neutral state when no clear trend is detected.
Uptrend (Green): Indicates a potential buying signal.
Downtrend (Red): Indicates a potential selling signal.
Signal Line (Blue): Represents the %D line for clearer signal identification.
Alerts:
Customizable alerts trigger when the trend changes, providing timely notifications for potential trade opportunities.
How It Works:
Stochastic Calculation:
The %K line is calculated based on the selected K Period.
The %D line is a simple moving average (SMA) of the %K line over the D Period.
Additional smoothing is applied to both %K and %D lines using the specified Smoothing factor.
Fisher Transform:
The script applies a Fisher transform to the smoothed %K values, enhancing the clarity of trend signals.
Trend Determination:
If Use Crossover is enabled, the trend is determined based on the crossover of smoothed %K and %D lines.
If Use Crossover is disabled, the trend is determined based on whether the smoothed %K value is above or below 0.5.
Background Shading:
Fixed background colors are applied using hline and fill functions, highlighting the specified levels on the chart (0.2, 0.5, 0.8).
Plotting:
The smoothed %K line is plotted with color coding based on its value relative to the %D line and threshold levels.
The %D line is plotted for reference.
How to Use:
Adding the Indicator:
Copy and paste the provided Pine Script™ code into a new indicator script in TradingView.
Save and add the indicator to your desired chart.
Configuring Parameters:
Adjust the input parameters (K Period, D Period, Slowing, etc.) according to your trading strategy and preferences.
Enable or disable the Use Crossover option based on whether you prefer trend determination by crossover or threshold.
Interpreting Signals:
Observe the color-coded %K line to identify potential buy (green) and sell (red) signals.
Use the shaded background areas to quickly assess overbought (0.5 to 0.8) and oversold (0.2 to 0.5) conditions.
Monitor alerts for trend changes to take timely trading actions.
Alerts Setup:
Set up custom alerts based on the provided alert conditions to receive notifications when the trend changes.
Originality:
This script combines the stochastic oscillator with color-coding and background shading for enhanced visualization.
It introduces a unique Fisher transform application to the smoothed %K values.
The crossover and threshold-based trend determination options provide flexibility for different trading strategies.
Customizable alert messages help traders stay informed about trend changes in real time.
By incorporating these features, the "Color Stochastic Indicator" offers a comprehensive tool for traders seeking to leverage stochastic analysis with improved clarity and actionable insights.
KillZones Hunt + Sessions [TradingFinder] Alert & Volume Ranges🟣 Introduction
🔵 Session
Financial markets are divided into various time segments, each with its own characteristics and activity levels. These segments are called sessions, and they are active at different times of the day.
The most important active sessions in financial markets are :
1. Asian Session
2. European Session
3. New York Session
The timing of these major sessions based on the UTC time zone is as follows :
1. Asian Session: 23:00 to 06:00
2. European Session: 07:00 to 16:30
3. New York Session: 13:00 to 22:00
Note
To avoid overlap between sessions and interference in kill zones, we have adjusted the session timings as follows :
• Asian Session: 23:00 to 06:00
• European Session: 07:00 to 14:25
• New York Session: 14:30 to 22:55
🔵 Kill Zones
Kill zones are parts of a session where trader activity is higher than usual. During these periods, trading volume increases and price fluctuations are more intense.
The timing of the major kill zones based on the UTC time zone is as follows :
• Asian Kill Zone: 23:00 to 03:55
• European Kill Zone: 07:00 to 09:55
• New York Morning Kill Zone: 14:30 to 16:55
• New York Evening Kill Zone: 19:30 to 20:55
This indicator focuses on tracking the kill zone and its range. For example, once a kill zone ends, the high and low formed during it remain unchanged.
If the price reaches the high or low of the kill zone while the session is still active, the corresponding line is not drawn any further. Based on this information, various strategies can be developed, and the most important ones are discussed below.
🟣 How to Use
There are three main ways to trade based on the kill zone :
• Kill Zone Hunt
• Breakout and Pullback to Kill Zone
• Trading in the Trend of the Kill Zone
🔵 Kill Zone Hunt
According to this strategy, once the kill zone ends and its high and low lines no longer change, if the price reaches one of these lines within the same session and is strongly rejected, a trade can be entered.
🔵 Breakout and Pullback to Kill Zone
According to this strategy, once the kill zone ends and its high and low lines no longer change, if the price breaks one of these lines strongly within the same session, a trade can be entered on the pullback to that level.
Trading in the Trend of the Kill Zone
We know that kill zones are areas where high-volume trading occurs and powerful trends form. Therefore, trades can be made in the direction of the trend. For example, when an upward trend dominates this area, you can enter a buy trade when the price reaches a demand order block.
🟣 Features
🔵 Alerts
You can set alerts to be notified when the price hits the high or low lines of the kill zone.
🔵 More Information
By enabling this feature, you can view information such as the time and trading volume within the kill zone. This allows you to compare the trading volume with the same period on the previous day or other kill zones.
🟣 Settings
Through the settings, you have access to the following options :
• Show or hide additional information
• Enable or disable alerts
• Show or hide sessions
• Show or hide kill zones
• Set preferred colors for displaying sessions
• Customize the time range of sessions
• Customize the time range of kill zones
Stocastic Reference Dinoa technical analysis indicator named "Stocastic Reference Dino," which is a stochastic oscillator used to analyze market trends and potential price reversals.
Key Features:
Inputs:
K Period (lengthK): Defines the period for the %K line calculation (default 13).
D Period (lengthD): Defines the period for the %D line calculation (default 9).
Smoothing Period (smoothK): Smoothing period for the %K line (default 8).
Low Threshold (lowThreshold): Lower bound threshold for the oscillator (default 10).
High Threshold (highThreshold): Upper bound threshold for the oscillator (default 80).
%K Line Calculation:
Calculates the lowest low and highest high over the lengthK period.
Computes the %K value and smooths it using a simple moving average over smoothK periods.
%D Line Calculation:
Calculates the %D line as a simple moving average of the %K line over the lengthD period.
Plotting:
Plots the %K line in blue and the %D line in red on a new pane.
Adds horizontal lines to represent the low and high thresholds, colored green and red, respectively.
This indicator helps traders identify potential overbought and oversold conditions by analyzing the stochastic oscillator lines (%K and %D) relative to the defined thresholds.
[blackcat] L1 Dynamic Momentum Indicator
**1. Overview**
" L1 Dynamic Momentum Indicator" is a custom TradingView indicator designed to analyze price momentum and market trends. It combines the calculation methods of Stoch (RSV) and Moving Average (SMA) to provide market overbought and oversold signals.
**2. Calculation Method**
- **RSV Value Calculation**: The RSV value is calculated using the relative relationship between the current price and the lowest and highest prices over the past 89 periods.
- **K Value Calculation**: The calculated RSV value is subjected to a 3-period Simple Moving Average (SMA) to obtain the K value.
- **D Value Calculation**: The K value is subjected to a 3-period Simple Moving Average (SMA) to obtain the D value.
- **Momentum Difference Calculation**: The difference between the 13-period Exponential Moving Average (EMA) and the 34-period EMA of closing prices is calculated, and then the moving average of this difference is calculated.
**3. Indicator Display**
- **K and D Lines**: The moving averages of the K value and D value are displayed on the chart, indicating a strong market condition when the K line is above the D line, and a weak market condition when the K line is below the D line.
- **Threshold Line**: A fixed threshold line of 50 is displayed to distinguish the overbought and oversold areas.
- **Green and Red Bars**: Green and red bars are drawn on the chart based on the relationship between the momentum difference and the average value, indicating the market trend.
**4. Usage Suggestions**
- When the market is in a strong condition, a potential reversal may occur in the overbought area after selling. When the market is in a weak condition, a potential bounce may occur in the oversold area after buying.
- Pay attention to the changes in market trends, with the appearance of green bars may indicate that the market is about to rise, and the appearance of red bars may indicate that the market is about to fall.
**5. Caution**
- The indicator is based on the provided code and may require adjustments based on market conditions.
- The accuracy of the indicator depends on the selection of calculation parameters and the reliability of market data.
Movement based on Buying/Selling VolumeDescription:
The "Buying Selling Volume" indicator calculates buying and selling volumes based on price movements within a specified lookback period. It then computes exponential moving averages (EMAs) of these volumes to determine trend direction. The indicator visually represents trend direction on the chart.
Volume Calculation and Normalization (Lines #1 - #12):
The indicator first computes the buying volume (BV) and selling volume (SV) based on price movements within the specified lookback period. These volumes are calculated proportionally to the distance between the closing price and the high and low of each candle.
To ensure consistent behavior and prevent division by zero, the volumes are normalized using a conditional statement to handle cases where the high and low are equal, which implies a lack of price movement.
Additionally, the volume (vol) is normalized to ensure non-zero division in subsequent calculations.
Total Volume and Proportional Volume Calculation (Lines #13 - #20):
The total volume (TP) is computed by summing the buying and selling volumes.
The proportional buying volume (BPV) and selling volume (SPV) are then calculated based on their respective contributions to the total volume.
These proportional volumes are scaled by the total volume to ensure accurate representation relative to market activity.
Evaluating Buying and Selling Pressure (Lines #21 - #24):
The code segment assigns positive or negative values to represent buying and selling pressure, respectively, based on the comparison between BPV and SPV. This step involves determining whether the buying pressure exceeds the selling pressure or vice versa.
The calculated values, denoted as BPc1 and SPc1, encapsulate the relative strength of buying and selling forces within the market.
EMA Calculation and Trend Identification (Lines #25 - #32):
The BPc1 and SPc1 values are subjected to exponential moving average (EMA) calculations using the specified lookback period (LookbackL). This process involves smoothing out the buying and selling pressure data to reveal underlying trends.
The resulting EMAs, represented by ema1B and ema1S, serve as crucial indicators of trend direction. A bullish trend is indicated when ema1B exceeds ema1S, while a bearish trend is signaled when ema1B falls below ema1S.
Secondary Volume Analysis and Trend Confirmation (Lines #33 - #42):
A similar volume analysis and EMA calculation process is repeated in this segment, using a different lookback period (LookbackL2). This allows for a secondary assessment of market dynamics and trend direction.
The resulting EMAs, denoted as ema1B2 and ema1S2, are compared to validate the trend direction identified in the primary analysis.
Visual Representation and Trend Display (Lines #43 - #46):
Finally, the indicator visualizes the identified trends on the chart by plotting colored shapes based on the comparison between the primary and secondary trend directions.
A green color indicates alignment in bullish trends, a red color signifies alignment in bearish trends, while a neutral color (gray) represents no clear consensus between the primary and secondary analyses.
Ideal Usage:
1. **Trend Confirmation:** Traders can use this indicator to confirm trend direction before entering trades.
2. **Reversal Signals:** Changes in trend direction, indicated by shifts in plotted shape colors, can signal potential market reversals.
Warnings:
1. **False Signals:** Like any technical indicator, false signals may occur, especially during low-volume or choppy market conditions. Additional analysis and risk management techniques are essential to mitigate potential losses.
2. **Parameter Sensitivity:** Adjusting lookback periods can impact the indicator's sensitivity to price movements. Traders should test different parameter settings and consider market conditions when using the indicator.
