Mogwai Method with RSI and EMA - BTCUSD 15mThis is a custom TradingView indicator designed for trading Bitcoin (BTCUSD) on a 15-minute timeframe. It’s based on the Mogwai Method—a mean-reversion strategy—enhanced with the Relative Strength Index (RSI) for momentum confirmation. The indicator generates buy and sell signals, visualized as green and red triangle arrows on the chart, to help identify potential entry and exit points in the volatile cryptocurrency market.
Components
Bollinger Bands (BB):
Purpose: Identifies overextended price movements, signaling potential reversions to the mean.
Parameters:
Length: 20 periods (standard for mean-reversion).
Multiplier: 2.2 (slightly wider than the default 2.0 to suit BTCUSD’s volatility).
Role:
Buy signal when price drops below the lower band (oversold).
Sell signal when price rises above the upper band (overbought).
Relative Strength Index (RSI):
Purpose: Confirms momentum to filter out false signals from Bollinger Bands.
Parameters:
Length: 14 periods (classic setting, effective for crypto).
Overbought Level: 70 (price may be overextended upward).
Oversold Level: 30 (price may be overextended downward).
Role:
Buy signal requires RSI < 30 (oversold).
Sell signal requires RSI > 70 (overbought).
Exponential Moving Averages (EMAs) (Plotted but not currently in signal logic):
Purpose: Provides trend context (included in the script for visualization, optional for signal filtering).
Parameters:
Fast EMA: 9 periods (short-term trend).
Slow EMA: 50 periods (longer-term trend).
Role: Can be re-added to filter signals (e.g., buy only when Fast EMA > Slow EMA).
Signals (Triangles):
Buy Signal: Green upward triangle below the bar when price is below the lower Bollinger Band and RSI is below 30.
Sell Signal: Red downward triangle above the bar when price is above the upper Bollinger Band and RSI is above 70.
How It Works
The indicator combines Bollinger Bands and RSI to spot mean-reversion opportunities:
Buy Condition: Price breaks below the lower Bollinger Band (indicating oversold conditions), and RSI confirms this with a reading below 30.
Sell Condition: Price breaks above the upper Bollinger Band (indicating overbought conditions), and RSI confirms this with a reading above 70.
The strategy assumes that extreme price movements in BTCUSD will often revert to the mean, especially in choppy or ranging markets.
Visual Elements
Green Upward Triangles: Appear below the candlestick to indicate a buy signal.
Red Downward Triangles: Appear above the candlestick to indicate a sell signal.
Bollinger Bands: Gray lines (upper, middle, lower) plotted for reference.
EMAs: Blue (Fast) and Orange (Slow) lines for trend visualization.
How to Use the Indicator
Setup
Open TradingView:
Log into TradingView and select a BTCUSD chart from a supported exchange (e.g., Binance, Coinbase, Bitfinex).
Set Timeframe:
Switch the chart to a 15-minute timeframe (15m).
Add the Indicator:
Open the Pine Editor (bottom panel in TradingView).
Copy and paste the script provided.
Click “Add to Chart” to apply it.
Verify Display:
You should see Bollinger Bands (gray), Fast EMA (blue), Slow EMA (orange), and buy/sell triangles when conditions are met.
Trading Guidelines
Buy Signal (Green Triangle Below Bar):
What It Means: Price is oversold, potentially ready to bounce back toward the Bollinger Band middle line.
Action:
Enter a long position (buy BTCUSD).
Set a take-profit near the middle Bollinger Band (bb_middle) or a resistance level.
Place a stop-loss 1-2% below the entry (or based on ATR, e.g., ta.atr(14) * 2).
Best Context: Works well in ranging markets; avoid during strong downtrends.
Sell Signal (Red Triangle Above Bar):
What It Means: Price is overbought, potentially ready to drop back toward the middle line.
Action:
Enter a short position (sell BTCUSD) or exit a long position.
Set a take-profit near the middle Bollinger Band or a support level.
Place a stop-loss 1-2% above the entry.
Best Context: Effective in ranging markets; avoid during strong uptrends.
Trend Filter (Optional):
To reduce false signals in trending markets, you can modify the script:
Add and ema_fast > ema_slow to the buy condition (only buy in uptrends).
Add and ema_fast < ema_slow to the sell condition (only sell in downtrends).
Check the Fast EMA (blue) vs. Slow EMA (orange) alignment visually.
Tips for BTCUSD on 15-Minute Charts
Volatility: BTCUSD can be erratic. If signals are too frequent, increase bb_mult (e.g., to 2.5) or adjust RSI levels (e.g., 75/25).
Confirmation: Use volume spikes or candlestick patterns (e.g., doji, engulfing) to confirm signals.
Time of Day: Mean-reversion works best during low-volume periods (e.g., Asian session in crypto).
Backtesting: Use TradingView’s Strategy Tester (convert to a strategy by adding entry/exit logic) to evaluate performance with historical BTCUSD data up to March 13, 2025.
Risk Management
Position Size: Risk no more than 1-2% of your account per trade.
Stop Losses: Always use stops to protect against BTCUSD’s sudden moves.
Avoid Overtrading: Wait for clear signals; don’t force trades in choppy or unclear conditions.
Example Scenario
Chart: BTCUSD, 15-minute timeframe.
Buy Signal: Price drops to $58,000, below the lower Bollinger Band, RSI at 28. A green triangle appears.
Action: Buy at $58,000, target $59,000 (middle BB), stop at $57,500.
Sell Signal: Price rises to $60,500, above the upper Bollinger Band, RSI at 72. A red triangle appears.
Action: Sell at $60,500, target $59,500 (middle BB), stop at $61,000.
This indicator is tailored for mean-reversion trading on BTCUSD. Let me know if you’d like to tweak it further (e.g., add filters, alerts, or alternative indicators)!
ค้นหาในสคริปต์สำหรับ "the strat"
Accumulation & Breakout Detectorاستراتيجية كشف التجميع والاستعداد للانطلاق
الوصف العام:
تهدف هذه الاستراتيجية إلى اكتشاف الأصول المالية (الأسهم أو العملات الرقمية) التي تمر بمرحلة التجميع، حيث يتحرك السعر في نطاق ضيق مع انخفاض في حجم التداول، مما يشير إلى احتمال قرب حدوث انطلاق صعودي. بمجرد تحقق شروط معينة، تعطي الاستراتيجية إشارة تفيد بأن الأصل المالي جاهز للخروج من التجميع والانطلاق في اتجاه صاعد.
شروط التجميع (Accumulation Phase):
تشير مرحلة التجميع إلى فترة يتم فيها تكديس الأصول من قبل المستثمرين الكبار قبل التحرك الكبير. تحدث إشارات التجميع عندما تتحقق الشروط التالية:
السعر يتحرك داخل نطاق ضيق بين الحد العلوي والسفلي لمؤشر بولينجر باند.
السعر أقل من المتوسط المتحرك 50 والمتوسط المتحرك 200، مما يدل على وجود اتجاه هابط أو فترة تكديس.
مؤشر القوة النسبية (RSI) أقل من 40، مما يشير إلى التشبع البيعي واحتمالية حدوث انعكاس قريب.
حجم التداول أقل من متوسط حجم التداول (50 شمعة) بنسبة 1.2، مما يدل على انخفاض الاهتمام بالأصل قبل الحركة القوية.
عند تحقق هذه الشروط، يظهر نقطة زرقاء على المخطط، مما يشير إلى أن الأصل المالي قد يكون في مرحلة تجميع.
شروط قرب الانطلاق (Breakout Readiness Phase):
عند انتهاء مرحلة التجميع، يدخل الأصل المالي في مرحلة الاستعداد للانطلاق، والتي تحدث عند تحقق الشروط التالية:
السعر يخترق المتوسط المتحرك 50، مما يدل على بداية اتجاه صعودي.
حجم التداول يرتفع فوق متوسط حجم التداول (50 شمعة) بنسبة 1.5، مما يشير إلى دخول سيولة قوية.
مؤشر القوة النسبية (RSI) يتجاوز 50، مما يعكس تحسن الزخم الصعودي.
عند تحقق هذه الشروط، تظهر نقطة خضراء على المخطط، مما يشير إلى أن الأصل المالي جاهز للانطلاق.
كيفية استخدام الإشارات؟
النقاط الزرقاء تعني أن الأصل المالي في مرحلة تجميع محتملة، وقد يكون من المناسب مراقبته استعدادًا لحركة قادمة.
النقاط الخضراء تعني أن الأصل المالي جاهز للخروج من التجميع وقد يكون في طريقه للانطلاق الصعودي.
يمكن استخدام هذه الإشارات مع أدوات تحليل إضافية مثل مستويات الدعم والمقاومة، النماذج السعرية، أو المؤشرات الأخرى لتأكيد القرار قبل التداول.
🚀 هذه الاستراتيجية مفيدة للمتداولين الذين يبحثون عن فرص دخول مبكرة في الاتجاهات الصاعدة بعد انتهاء فترات التجميع.
Accumulation & Breakout Detection Strategy
General Description:
This strategy aims to identify financial assets (stocks or cryptocurrencies) that are in an accumulation phase, where price moves within a narrow range with low trading volume, signaling a potential breakout. Once certain conditions are met, the strategy provides an alert indicating that the asset is ready to break out and move upward.
Accumulation Phase Conditions:
The accumulation phase occurs when large investors accumulate assets before a significant price move. The strategy detects accumulation when the following conditions are met:
Price moves within a narrow range between the upper and lower Bollinger Bands.
Price is below both the 50-period and 200-period moving averages, indicating a downtrend or consolidation.
Relative Strength Index (RSI) is below 40, suggesting an oversold condition with a possible reversal.
Trading volume is less than 1.2 times the 50-period average volume, indicating weak activity before a strong move.
When these conditions are met, a blue dot appears on the chart, signaling a potential accumulation phase.
Breakout Readiness Phase Conditions:
Once the accumulation phase ends, the asset enters the breakout readiness phase, which occurs when the following conditions are met:
Price breaks above the 50-period moving average, signaling the start of an uptrend.
Trading volume increases above 1.5 times the 50-period average volume, indicating strong liquidity inflow.
RSI rises above 50, reflecting positive momentum and increasing bullish strength.
When these conditions are met, a green dot appears on the chart, indicating that the asset is ready for a breakout.
How to Use the Signals?
Blue dots indicate that the asset is in a potential accumulation phase, suggesting it may soon break out.
Green dots indicate that the asset is ready to break out and move upward.
These signals can be combined with additional technical analysis tools such as support/resistance levels, chart patterns, or other indicators for confirmation before making a trade.
🚀 This strategy is useful for traders looking for early entry points in uptrending markets following accumulation phases.
Supertrend and Fast and Slow EMA StrategyThis strategy combines Exponential Moving Averages (EMAs) and Average True Range (ATR) to create a simple, yet effective, trend-following approach. The strategy filters out fake or sideways signals by incorporating the ATR as a volatility filter, ensuring that trades are only taken during trending conditions. The key idea is to buy when the short-term trend (Fast EMA) aligns with the long-term trend (Slow EMA), and to avoid trades during low volatility periods.
How It Works:
EMA Crossover:
1). Buy Signal: When the Fast EMA (shorter-term, e.g., 20-period) crosses above the Slow EMA (longer-term, e.g., 50-period), this indicates a potential uptrend.
2). Sell Signal: When the Fast EMA crosses below the Slow EMA, this indicates a potential downtrend.
ATR Filter:
1). The ATR (Average True Range) is used to measure market volatility.
2). Trending Market: If the ATR is above a certain threshold, it indicates high volatility and a trending market. Only when ATR is above the threshold will the strategy generate buy/sell signals.
3). Sideways Market: If ATR is low (sideways or choppy market), the strategy will suppress signals to avoid entering during non-trending conditions.
When to Buy:
1). Condition 1: The Fast EMA crosses above the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, indicating that the market is trending (not sideways or choppy).
When to Sell:
1). Condition 1: The Fast EMA crosses below the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, confirming that the market is in a downtrend.
When Not to Enter the Trade:
1). Sideways Market: If the ATR is below the threshold, signaling low volatility and sideways or choppy market conditions, the strategy will not trigger any buy or sell signals.
2). False Crossovers: In low volatility conditions, price action tends to be noisy, which could lead to false signals. Therefore, avoiding trades during these periods reduces the risk of false breakouts.
Additional Factors to Consider Adding:
=> RSI (Relative Strength Index): Adding an RSI filter can help confirm overbought or oversold conditions to avoid buying into overextended moves or selling too low.
1). RSI Buy Filter: Only take buy signals when RSI is below 70 (avoiding overbought conditions).
2). RSI Sell Filter: Only take sell signals when RSI is above 30 (avoiding oversold conditions).
=> MACD (Moving Average Convergence Divergence): Using MACD can help validate the strength of the trend.
1). Buy when the MACD histogram is above the zero line and the Fast EMA crosses above the Slow EMA.
2). Sell when the MACD histogram is below the zero line and the Fast EMA crosses below the Slow EMA.
=> Support/Resistance Levels: Adding support and resistance levels can help you understand market structure and decide whether to enter or exit a trade.
1). Buy when price breaks above a significant resistance level (after a valid buy signal).
2). Sell when price breaks below a major support level (after a valid sell signal).
=> Volume: Consider adding a volume filter to ensure that buy/sell signals are supported by strong market participation. You could only take signals if the volume is above the moving average of volume over a certain period.
=> Trailing Stop Loss: Instead of a fixed stop loss, use a trailing stop based on a percentage or ATR to lock in profits as the trade moves in your favor.
=> Exit Signals: Besides the EMA crossover, consider adding Take Profit or Stop Loss levels, or even using a secondary indicator like RSI to signal an overbought/oversold condition and exit the trade.
Example Usage:
=> Buy Example:
1). Fast EMA (20-period) crosses above the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is below 70, the buy signal is further confirmed as not being overbought.
=> Sell Example:
1). Fast EMA (20-period) crosses below the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is above 30, the sell signal is further confirmed as not being oversold.
Conclusion:
This strategy helps to identify trending markets and filters out sideways or choppy market conditions. By using Fast and Slow EMAs combined with the ATR volatility filter, it provides a reliable approach to catching trending moves while avoiding false signals during low-volatility, sideways markets.
ORB with 100 EMAORB Trading Strategy for FX Pairs on the 30-Minute Time Frame
Overview
This Opening Range Breakout (ORB) strategy is designed for trading FX pairs on the 30-minute time frame. The strategy is structured to take advantage of price momentum while aligning trades with the overall trend using the 100-period Exponential Moving Average (100EMA). The primary objective is to enter trades when price breaks and closes above or below the Opening Range (OR), with additional confirmation from a retest of the OR level if the initial entry is missed.
Strategy Rules
1. Defining the Opening Range (OR)
- The OR is determined by the high and low of the first 30-minute candle after market open.
- This range acts as the key level for breakout trading.
2. Trend Confirmation Using the 100EMA
- The 100EMA serves as a filter to determine trade direction:
- Buy Setup: Only take buy trades when the OR is above the 100EMA.
- Sell Setup: Only take sell trades when the OR is below the 100EMA.
3. Entry Criteria
- Buy Trade: Enter a long position when a candle breaks and closes above the OR high, confirming the breakout.
- Sell Trade: Enter a short position when a candle breaks and closes below the OR low, confirming the breakout.
- Retest Entry: If the initial entry is missed, wait for a price retest of the OR level for a secondary entry opportunity.
4. Risk-to-Reward Ratio (R2R)
- The goal is to target a 1:1 Risk-to-Reward (R2R) ratio.
- Stop-loss placement:
- Buy Trade: Place stop-loss just below the OR low.
- Sell Trade: Place stop-loss just above the OR high.
- Take profit at a distance equal to the stop-loss for a 1:1 R2R.
5. Risk Management
- Risk per trade should be based on personal risk tolerance.
- Adjust lot sizes accordingly to maintain a controlled risk percentage of account balance.
- Avoid over-leveraging, and consider moving stop-loss to breakeven if the price moves favourably.
Additional Considerations
- Avoid trading during major news events that may cause high volatility and unpredictable price movements.
- Monitor market conditions to ensure breakout confirmation with strong momentum rather than false breakouts.
- Use additional confluences such as candlestick patterns, support/resistance zones, or volume analysis for stronger trade validation.
This ORB strategy is designed to provide structured trade opportunities by combining breakout momentum with trend confirmation via the 100EMA. The strategy is straightforward, allowing traders to capitalise on clear breakout movements while implementing effective risk management practices. While the 1:1 R2R target provides a balanced approach, traders should always adapt their risk tolerance and market conditions to optimise trade performance.
By following these rules and maintaining discipline, traders can use this strategy effectively across various FX pairs on the 30-minute time frame.
SatoshiSteps Swing StrategyCore Components:
The indicator combines three popular technical analysis tools:
Ichimoku Cloud: This helps identify the trend, support, and resistance levels.
RSI (Relative Strength Index): This momentum oscillator identifies overbought and oversold conditions.
MACD (Moving Average Convergence Divergence): This trend-following momentum indicator shows the relationship between two moving averages1 of prices.
Logic:
The strategy aims to identify potential swing trading opportunities by combining signals from these three components. It essentially looks for:
Trend Confirmation (Ichimoku):
Price should be above the Ichimoku cloud for buy signals.
Price should be below the Ichimoku cloud for sell signals.
The Tenkan-sen (conversion line) should cross above the Kijun-sen (base line) for buy signals.
The Tenkan-sen should cross below the Kijun-sen for sell signals.
Overbought/Oversold Conditions (RSI):
RSI should be below the overbought level for buy signals (avoiding buying when the market is potentially overextended).
RSI should be above the oversold level for sell signals (avoiding selling when the market is potentially oversold).
Momentum Confirmation (MACD):
The MACD line should be above the signal line for buy signals (indicating upward momentum).
The MACD line should be below the signal line for sell signals (indicating downward momentum).
Buy Signal:
A buy signal is generated when all the following conditions are met:
The Tenkan-sen crosses above the Kijun-sen.
The price is above both the Senkou Span A and Senkou Span B (the cloud).
The RSI is below the overbought level.
The MACD line is above the signal line.
Sell Signal:
A sell signal is generated when all the following conditions are met:
The Tenkan-sen crosses below the Kijun-sen.
The price is below both the Senkou Span A and Senkou Span B (the cloud).
The RSI is above the oversold level.
The MACD line is below the signal line.
Key Considerations:
Time Frame: The indicator has built-in adjustments for 1-hour and 4-hour timeframes, optimizing the parameters for each.
Customization: You can customize the overbought/oversold RSI levels and the styles of the buy/sell signals (triangle, label, arrow, circle) through the indicator's settings.
Accuracy: While the strategy combines multiple indicators to improve accuracy, remember that no trading indicator is perfect. Market conditions can change rapidly, and false signals can occur.
Risk Management: Always use proper risk management techniques, such as stop-loss orders, and never risk more than you can afford to lose.
Live Portfolio P<his script calculates live P&L (Profit & Loss) for up to 40 instruments — stocks, ETFs, options, futures, and Forex pairs supported by TradingView. Instead of juggling numerous inputs, you paste your portfolio in CSV format into a single text field, and the script handles the rest. It parses each position and displays a comprehensive table showing the symbol, current price, position value, total P&L, and today’s P&L—all updated in real time.
Key Features
CSV Portfolio Input – Effortlessly import all your positions at once without filling in multiple fields. You can export the position from your broker, save it in the required format, and paste it into this script.
Supports Various Asset Classes – Works with any instrument that TradingView provides data for, including futures, options, and Forex.
Up to 40 Instruments – Track a broad and diverse set of holdings in one place.
Real-Time Updates – Get immediate feedback on live price changes, total value, and current P&L.
Today’s P&L – Monitor your daily performance to gauge short-term trends.
CSV is consumed in the following format:
Symbol (supported TradingView instruments)
Entry Price
Quantity (negative for short position)
Lot Size (for futures/options, it might not be one)
For example:
AAPL,237,100,1
TSLA,400,-150,1
ESM2025,6000,5,50
Planned Enhancements
Multi-Currency Support – Automatically convert and display your positions’ values in different currencies.
Advanced Metrics – Get deeper insights with calculations for drawdown, Sharpe ratio, and more.
Risk Management Tools – Set stop-loss and take-profit levels and receive alerts when thresholds are hit.
Option Greeks & Margin Calculations – Manage complex option strategies and track margin requirements.
Questions for You
What additional features would you like to see?
Are there any specific metrics or analytics you’d find especially valuable?
How might this script fit into your current trading workflow?
Feel free to share your thoughts and suggestions. Your feedback will help shape future updates and make this tool even more helpful for traders like you!
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Multi Stochastic AlertHello Everyone,
I have created a Multi Stochastic Alert based on Scalping Strategy
The Strategy uses below 4 Stochastic indicator:
1. Stochastic (9,3)
2. Stochastic (14,3)
3. Stochastic (40,4)
4. Stochastic (60,10)
Trade entry become active when all of these goes below 20 or above 80, In this indicator you don't need to use all 4, this will show red and green background whenever all of them goes below 20 or above 80.
As shown in picture below, it works better when script is making a channel, Our indicator shows green or red signal, we wait for RSI Divergence and we enter. We book when blue line (9,3) goes above 80, as shown by arrow, and trail rest at breakeven or your own trailing method
Same Situation shown for Short side. We book 50% when Blue line (9,3) Goes below 20 and trail rest at breakeven or your own trailing method
Happy trading, Let me know if any improvements required.
Breakout Josip strategy is focused on analyzing price movements during specific time intervals (from 9:00 AM to 12:00 PM) each day. It tracks the highest and lowest prices in that period and uses them to set targets for potential trades, placing horizontal lines based on these levels. Additionally, you're interested in tracking the success and failure of trades based on whether price breaks certain levels during this time range. The strategy also calculates various metrics like the percentage of successful trades, failed trades, and total trades during a selected time range.
[blackcat] L1 Small Wave Operation L1 Small Wave Operation
Overview
Are you looking to catch those elusive small waves in the market? Look no further than " L1 Small Wave Operation." This script offers a unique way to identify potential buying opportunities by analyzing price movements, volume changes, and trend directions. With customizable inputs and clear visual indicators, it’s designed to help traders spot favorable entry points with precision.
Features
Dynamic Signal Identification: Automatically detects two types of buy signals labeled "S" and "B."
Adaptable Parameters: Allows users to adjust low period, high period, EMA periods, SMA period, and various threshold values to fine-tune the strategy.
Visual Clarity: Plots K and D lines along with four distinct threshold levels for easy visualization.
Condition-Based Signals: Uses multiple conditions including volume increases, price actions, and crossover events to confirm signals.
How It Works
Calculate Percent Range: Determines where the current closing price lies within the recent low and high range.
Compute Moving Averages: Calculates Exponential Moving Average (EMA) and Simple Moving Average (SMA) of the percent range.
Define Conditions: Checks for bullish or strong bullish patterns, uptrends, and specific crossover events between K and D lines.
Generate Signals: Marks potential buying opportunities when predetermined conditions are met.
How To Use
Add this script to your TradingView chart.
Adjust the input parameters according to your preferred settings.
Monitor the plotted lines and look for "S" and "B" labels indicating buy signals.
Consider incorporating these signals into a broader trading strategy that includes risk management techniques.
What Makes It Special
Flexibility: Users can easily modify parameters to adapt the script to different markets or personal preferences.
Automation: Saves time by automatically scanning for trade setups based on predefined rules.
Comprehensive Analysis: Combines multiple factors like volume, price action, and moving averages to provide reliable signals.
Limitations
Past performance does not guarantee future results.
Market conditions can vary, affecting signal reliability.
Not suitable for very short-term trades without additional refinements.
Notes
Always perform backtesting on historical data before implementing live trades.
Understand the underlying logic of the script to avoid misinterpretation of signals.
Regularly review and adjust parameters based on changing market dynamics.
SCE Price Action SuiteThis is an indicator designed to use past market data to mark key price action levels as well as provide a different kind of insight. There are 8 different features in the script that users can turn on and off. This description will go in depth on all 8 with chart examples.
#1 Absorption Zones
I defined Absorption Zones as follows.
//----------------------------------------------
//---------------Absorption---------------------
//----------------------------------------------
box absorptionBox = na
absorptionBar = ta.highest(bodySize, absorptionLkb)
bsab = ta.barssince(bool(ta.change(absorptionBar)))
if bsab == 0 and upBar and showAbsorption
absorptionBox := box.new(left = bar_index - 1, top = close, right = bar_index + az_strcuture, bottom = open, border_color = color.rgb(0, 80, 75), border_width = boxLineSize, bgcolor = color.rgb(0, 80, 75))
absorptionBox
else if bsab == 0 and downBar and showAbsorption
absorptionBox := box.new(left = bar_index - 1, top = close, right = bar_index + az_strcuture, bottom = open, border_color = color.rgb(105, 15, 15), border_width = boxLineSize, bgcolor = color.rgb(105, 15, 15))
absorptionBox
What this means is that absorption bars are defined as the bars with the largest bodies over a selected lookback period. Those large bodies represent areas where price may react. I was inspired by the concept of a Fair Value Gap for this concept. In that body price may enter to be a point of support or resistance, market participants get “absorbed” in the area so price can continue in whichever direction.
#2 Candle Wick Theory/Strategy
I defined Candle Wick Theory/Strategy as follows.
//----------------------------------------------
//---------------Candle Wick--------------------
//----------------------------------------------
highWick = upBar ? high - close : downBar ? high - open : na
lowWick = upBar ? open - low : downBar ? close - low : na
upWick = upBar ? close + highWick : downBar ? open + highWick : na
downWick = upBar ? open - lowWick : downBar ? close - lowWick : na
downDelivery = upBar and downBar and high > upWick and highWick > lowWick and totalSize > totalSize and barstate.isconfirmed and session.ismarket
upDelivery = downBar and upBar and low < downWick and highWick < lowWick and totalSize > totalSize and barstate.isconfirmed and session.ismarket
line lG = na
line lE = na
line lR = na
bodyMidpoint = math.abs(body) / 2
upWickMidpoint = math.abs(upWickSize) / 2
downWickkMidpoint = math.abs(downWickSize) / 2
if upDelivery and showCdTheory
cpE = chart.point.new(time, bar_index - 1, downWickkMidpoint)
cpE2 = chart.point.new(time, bar_index + bl, downWickkMidpoint)
cpG = chart.point.new(time, bar_index + bl, downWickkMidpoint * (1 + tp))
cpR = chart.point.new(time, bar_index + bl, downWickkMidpoint * (1 - sl))
cpG1 = chart.point.new(time, bar_index - 1, downWickkMidpoint * (1 + tp))
cpR1 = chart.point.new(time, bar_index - 1, downWickkMidpoint * (1 - sl))
lG := line.new(cpG1, cpG, xloc.bar_index, extend.none, color.green, line.style_solid, 1)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.white, line.style_solid, 1)
lR := line.new(cpR1, cpR, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
lR
else if downDelivery and showCdTheory
cpE = chart.point.new(time, bar_index - 1, upWickMidpoint)
cpE2 = chart.point.new(time, bar_index + bl, upWickMidpoint)
cpG = chart.point.new(time, bar_index + bl, upWickMidpoint * (1 - tp))
cpR = chart.point.new(time, bar_index + bl, upWickMidpoint * (1 + sl))
cpG1 = chart.point.new(time, bar_index - 1, upWickMidpoint * (1 - tp))
cpR1 = chart.point.new(time, bar_index - 1, upWickMidpoint * (1 + sl))
lG := line.new(cpG1, cpG, xloc.bar_index, extend.none, color.green, line.style_solid, 1)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.white, line.style_solid, 1)
lR := line.new(cpR1, cpR, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
lR
First I get the size of the wicks for the top and bottoms of the candles. This depends on if the bar is red or green. If the bar is green the wick is the high minus the close, if red the high minus the open, and so on. Next, the script defines the upper and lower bounds of the wicks for further comparison. If the candle is green, it's the open price minus the bottom wick. If the candle is red, it's the close price minus the bottom wick, and so on. Next we have the condition for when this strategy is present.
Down delivery:
Occurs when the previous candle is green, the current candle is red, and:
The high of the current candle is above the upper wick of the previous candle.
The size of the current candle's top wick is greater than its bottom wick.
The total size of the previous candle is greater than the total size of the current candle.
The current bar is confirmed (barstate.isconfirmed).
The session is during market hours (session.ismarket).
Up delivery:
Occurs when the previous candle is red, the current candle is green, and:
The low of the current candle is below the lower wick of the previous candle.
The size of the current candle's bottom wick is greater than its top wick.
The total size of the previous candle is greater than the total size of the current candle.
The current bar is confirmed.
The session is during market hours
Then risk is plotted from the percentage that users can input from an ideal entry spot.
#3 Candle Size Theory
I defined Candle Size Theory as follows.
//----------------------------------------------
//---------------Candle displacement------------
//----------------------------------------------
line lECD = na
notableDown = bodySize > bodySize * candle_size_sensitivity and downBar and session.ismarket and barstate.isconfirmed
notableUp = bodySize > bodySize * candle_size_sensitivity and upBar and session.ismarket and barstate.isconfirmed
if notableUp and showCdSizeTheory
cpE = chart.point.new(time, bar_index - 1, close)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, close)
lECD := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.rgb(0, 80, 75), line.style_solid, 3)
lECD
else if notableDown and showCdSizeTheory
cpE = chart.point.new(time, bar_index - 1, close)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, close)
lECD := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.rgb(105, 15, 15), line.style_solid, 3)
lECD
This plots candles that are “notable” or out of the ordinary. Candles that are larger than the last by a value users get to specify. These candles' highs or lows, if they are green or red, act as levels for support or resistance.
#4 Candle Structure Theory
I defined Candle Structure Theory as follows.
//----------------------------------------------
//---------------Structure----------------------
//----------------------------------------------
breakDownStructure = low < low and low < low and high > high and upBar and downBar and upBar and downBar and session.ismarket and barstate.isconfirmed
breakUpStructure = low > low and low > low and high < high and downBar and upBar and downBar and upBar and session.ismarket and barstate.isconfirmed
if breakUpStructure and showStructureTheory
cpE = chart.point.new(time, bar_index - 1, close)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, close)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.teal, line.style_solid, 3)
lE
else if breakDownStructure and showStructureTheory
cpE = chart.point.new(time, bar_index - 1, open)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, open)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.red, line.style_solid, 3)
lE
It is a series of candles to create a notable event. 2 lower lows in a row, a lower high, then green bar, red bar, green bar is a structure for a breakdown. 2 higher lows in a row, a higher high, red bar, green bar, red bar for a break up.
#5 Candle Swing Structure Theory
I defined Candle Swing Structure Theory as follows.
//----------------------------------------------
//---------------Swing Structure----------------
//----------------------------------------------
line htb = na
line ltb = na
if totalSize * swing_struct_sense < totalSize and upBar and downBar and high > high and showSwingSturcture and session.ismarket and barstate.isconfirmed
cpS = chart.point.new(time, bar_index - 1, high)
cpE = chart.point.new(time, bar_index + bl_strcuture, high)
htb := line.new(cpS, cpE, xloc.bar_index, color = color.red, style = line.style_dashed)
htb
else if totalSize * swing_struct_sense < totalSize and downBar and upBar and low > low and showSwingSturcture and session.ismarket and barstate.isconfirmed
cpS = chart.point.new(time, bar_index - 1, low)
cpE = chart.point.new(time, bar_index + bl_strcuture, low)
ltb := line.new(cpS, cpE, xloc.bar_index, color = color.teal, style = line.style_dashed)
ltb
A bearish swing structure is defined as the last candle’s total size, times a scalar that the user can input, is less than the current candles. Like a size imbalance. The last bar must be green and this one red. The last high should also be less than this high. For a bullish swing structure the same size imbalance must be present, but we need a red bar then a green bar, and the last low higher than the current low.
#6 Fractal Boxes
I define the Fractal Boxes as follows
//----------------------------------------------
//---------------Fractal Boxes------------------
//----------------------------------------------
box b = na
int indexx = na
if bar_index % (n * 2) == 0 and session.ismarket and showBoxes
b := box.new(left = bar_index, top = topBox, right = bar_index + n, bottom = bottomBox, border_color = color.rgb(105, 15, 15), border_width = boxLineSize, bgcolor = na)
indexx := bar_index + 1
indexx
The idea of this strategy is that the market is fractal. It is considered impossible to be able to tell apart two different time frames from just the chart. So inside the chart there are many many breakouts and breakdowns happening as price bounces around. The boxes are there to give you the view from your timeframe if the market is in a range from a time frame that would be higher than it. Like if we are inside what a larger time frame candle’s range. If we break out or down from this, we might be able to trade it. Users can specify a lookback period and the box is that period’s, as an interval, high and low. I say as an interval because it is plotted every n * 2 bars. So we get a box, price moves, then a new box.
#7 Potential Move Width
I define the Potential Move Width as follows
//----------------------------------------------
//---------------Move width---------------------
//----------------------------------------------
velocity = V(n)
line lC = na
line l = na
line l2 = na
line l3 = na
line l4 = na
line l5 = na
line l6 = na
line l7 = na
line l8 = na
line lGFractal = na
line lRFractal = na
cp2 = chart.point.new(time, bar_index + n, close + velocity)
cp3 = chart.point.new(time, bar_index + n, close - velocity)
cp4 = chart.point.new(time, bar_index + n, close + velocity * 5)
cp5 = chart.point.new(time, bar_index + n, close - velocity * 5)
cp6 = chart.point.new(time, bar_index + n, close + velocity * 10)
cp7 = chart.point.new(time, bar_index + n, close - velocity * 10)
cp8 = chart.point.new(time, bar_index + n, close + velocity * 15)
cp9 = chart.point.new(time, bar_index + n, close - velocity * 15)
cpG = chart.point.new(time, bar_index + n, close + R)
cpR = chart.point.new(time, bar_index + n, close - R)
if ((bar_index + n) * 2 - bar_index) % n == 0 and session.ismarket and barstate.isconfirmed and showPredictionWidtn
cp = chart.point.new(time, bar_index, close)
cpG1 = chart.point.new(time, bar_index, close + R)
cpR1 = chart.point.new(time, bar_index, close - R)
l := line.new(cp, cp2, xloc.bar_index, extend.none, color.aqua, line.style_solid, 1)
l2 := line.new(cp, cp3, xloc.bar_index, extend.none, color.aqua, line.style_solid, 1)
l3 := line.new(cp, cp4, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
l4 := line.new(cp, cp5, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
l5 := line.new(cp, cp6, xloc.bar_index, extend.none, color.teal, line.style_solid, 1)
l6 := line.new(cp, cp7, xloc.bar_index, extend.none, color.teal, line.style_solid, 1)
l7 := line.new(cp, cp8, xloc.bar_index, extend.none, color.blue, line.style_solid, 1)
l8 := line.new(cp, cp9, xloc.bar_index, extend.none, color.blue, line.style_solid, 1)
l8
By using the past n bar’s velocity, or directional speed, every n * 2 bars. I can use it to scale the close value and get an estimate for how wide the next moves might be.
#8 Linear regression
//----------------------------------------------
//---------------Linear Regression--------------
//----------------------------------------------
lr = showLR ? ta.linreg(close, n, 0) : na
plot(lr, 'Linear Regression', color.blue)
I used TradingView’s built in linear regression to not reinvent the wheel. This is present to see past market strength of weakness from a different perspective.
User input
Users can control a lot about this script. For the strategy based plots you can enter what you want the risk to be in percentages. So the default 0.01 is 1%. You can also control how far forward the line goes.
Look back at where it is needed as well as line width for the Fractal Boxes are controllable. Also users can check on and off what they would like to see on the charts.
No indicator is 100% reliable, do not follow this one blindly. I encourage traders to make their own decisions and not trade solely based on technical indicators. I encourage constructive criticism in the comments below. Thank you.
Candle 1 2 3 on XAUUSD (by Veronica)Description
Discover the Candle 1 2 3 Strategy, a simple yet effective trading method tailored exclusively for XAUUSD on the 15-minute timeframe. Designed by Veronica, this strategy focuses on identifying key reversal and continuation patterns during the London and New York sessions, making it ideal for traders who prioritise high-probability entries during these active market hours.
Key Features:
1. Session-Specific Trading:
The strategy operates strictly during London (03:00–06:00 UTC) and New York (08:30–12:30 UTC) sessions, where XAUUSD tends to show higher volatility and clearer price movements.
Pattern Criteria:
- Works best if the first candle is NOT a pin bar or a doji.
- Third candle should either:
a. Be a marubozu (large body with minimal wicks).
a. Have a significant body with wicks, ensuring the close of the third candle is above Candle 2 (for Buy) or below Candle 2 (for Sell).
Callout Labels and Alerts:
Automatic Buy and Sell labels are displayed on the chart during qualifying sessions, ensuring clarity for decision-making.
Integrated alerts notify you of trading opportunities in real-time.
Risk Management:
Built-in Risk Calculator to estimate lot sizes based on your account size, risk percentage, and stop-loss levels.
Customizable Table:
Displays your calculated lot size for various stop-loss pip values, making risk management seamless and efficient.
How to Use:
1. Apply the indicator to XAUUSD (M15).
2. Focus on setups appearing within the London and New York sessions only.
3. Ensure the first candle is neither a pin bar nor a doji.
4. Validate the third candle's body placement:
For a Buy, the third candle’s close must be above the second candle.
For a Sell, the third candle’s close must be below the second candle.
5. Use the generated alerts to streamline your entry process.
Notes:
This strategy is meant to complement your existing knowledge of market structure and price action.
Always backtest thoroughly and adjust parameters to fit your personal trading style and risk tolerance.
Credit:
This strategy is the intellectual property of Veronica, developed specifically for XAUUSD (M15) traders seeking precision entries during high-volume sessions.
Thrax - Pullback based short side scalping⯁ This indicator is built for short trades only.
⤞ Pullback based scalping is a strategy where a trader anticipates a pullback and makes a quick scalp in this pullback. This strategy usually works in a ranging market as probability of pullbacks occurrence in ranging market is quite high.
⤞ The strategy is built by first determining a possible candidate price levels having high chance of pullbacks. This is determined by finding out multiple rejection point and creating a zone around this price. A rejection is considered to be valid only if it comes to this zone after going down by a minimum pullback percentage. Once the price has gone down by this minimum pullback percentage multiple times and reaches the zone again chances of pullback goes high and an indication on chart for the same is given.
⯁ Inputs
⤞ Zone-Top : This input parameter determines the upper range for the price zone.
⤞ Zone bottom : This input parameter determines the lower range for price zone.
⤞ Minimum Pullback : This input parameter determines the minimum pullback percentage required for valid rejection. Below is the recommended settings
⤞ Lookback : lookback period before resetting all the variables
⬦Below is the recommended settings across timeframes
⤞ 15-min : lookback – 24, Pullback – 2, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
⤞ 5-min : lookback – 50, pullback – 1% - 1.5%, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
⤞ 1-min : lookback – 100, pullback – 1%, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
⤞ Anything > 30-min : lookback – 11, pullback – 3%, Zone Top Size %– 0.4, Zone Bottom Size % – 0.2
✵ This indicator gives early pullback detection which can be used in below ways
1. To take short trades in the pullback.
2. To use this to exit an existing position in the next few candles as pullback may be incoming.
📌 Kindly note, it’s not necessary that pullback will happen at the exact point given on the chart. Instead, the indictor gives you early signals for the pullback
⯁ Trade Steup
1. Wait for pullback signal to occur on the chart.
2. Once the pullback warning has been displayed on the chart, you can either straight away enter the short position or wait for next 2-4 candles for initial sign of actual pullback to occurrence.
3. Once you have initiated short trade, since this is pullback-based strategy, a quick scalp should be made and closed as price may resume it’s original direction. If you have risk appetite you can stay in the trade longer and trial the stops if price keeps pulling back.
4. You can zone top as your stop, usually zone top + some% should be used as stop where ‘some %’ is based on your risk appetite.
5. It’s important to note that this indicator gives early sings of pullback so you may actually wait for 2-3 candles post ‘Pullback warning’ occurs on the chart before entering short trade.
[blackcat] L2 BullBear OscillatorOVERVIEW
The " L2 BullBear Oscillator" is a custom trading indicator for TradingView that helps traders identify market trends, potential tops and bottoms, and the strength of trends using various moving averages and price relationships.
FEATURES
Calculates a base oscillator based on the close price relative to the highest and lowest prices over the past 60 periods.
Smoothes the oscillator using exponential moving averages (EMAs).
Determines market strength through relative strength indicators and moving averages.
Identifies potential tops and strong support levels based on specific conditions involving oscillators and price actions.
Plots several signals to help traders make informed decisions.
HOW TO USE
Install the script on your TradingView chart.
Customize the settings in the "Inputs" section:
Set the periods for the short-term and long-term EMAs.
Set the periods for the three SMAs used in calculations.
Interpret the plots:
BullBear Signal (Fuchsia Line): Indicates the overall market trend. Uptrends suggest buying opportunities, while downtrends suggest selling.
Decreasing BullBear Signal (Aqua Line): Highlights periods when the trend is weakening or turning bearish, signaling possible selling opportunities.
Potential Top Condition (Yellow Plot): Signals possible trend reversals from bullish to bearish, indicating times to consider taking profits or preparing for a downtrend.
High Price Condition (Yellow Plot): Indicates strong bullish momentum but also potentially overbought conditions, which might precede a correction.
Earning Condition (Red Line): Possibly signifies strong bullish signals, indicating good times to enter long positions.
Strong Support Condition (White Arrows): Signals potential bottoms or support levels, indicating buying opportunities.
Start Hiding Condition (Fuchsia Plot): Might indicate times to exit positions or reduce exposure due to unfavorable market conditions.
ALGORITHMS
Moving Averages:
Simple Moving Averages (SMAs): Used to calculate averages of price data over specified periods.
Exponential Moving Averages (EMAs): Used to give more weight to recent prices, making the moving averages more responsive to new data.
Oscillator Calculation:
The base oscillator is calculated based on the close price's position within the highest and lowest prices over 60 periods, normalized to a 0-100 scale.
This oscillator is then smoothed using EMAs to reduce noise and make trends more visible.
Relative Strength Indicator:
Calculated based on the close price's position within the highest and lowest prices over 20 periods, also normalized to a 0-100 scale.
This is smoothed using SMAs to get a more stable signal.
Condition Checks:
Various conditions are checked to identify potential tops, strong support, and other market states based on the relationships between these indicators and price actions.
LIMITATIONS
The script is based on historical data and does not guarantee future performance.
It is recommended to use the script in conjunction with other analysis tools.
The effectiveness of the strategy may vary depending on the market conditions and asset being traded.
NOTES
The script is designed for educational purposes and should not be considered financial advice.
Users are encouraged to backtest the strategy on a demo account before applying it to live trades.
THANKS
Special thanks to the TradingView community for their support and feedback.
Angkol StrategyKey Components:
Time Zones:
Kill Zone: A specific time window during which the strategy tracks price action for potential signals.
You can modify the start and end time of this kill zone with a time zone offset for your preferred market hours (e.g., New York).
Entry Restriction Zone: A time window during which entry signals are restricted (i.e., no entries are allowed). You can modify the start and end time for this restriction.
Trade Biases:
Sell Bias: Occurs when the price breaks the previous day's kill zone high.
Buy Bias: Occurs when the price breaks the previous day's kill zone low.
Trade Signals:
Bearish Signal (Sell): Triggered when:
A Bearish Engulfing pattern occurs (where the current bar closes lower than it opens and it engulfs the previous bar).
A Bearish Order Block forms (where the previous candle is bullish and the current one closes below the previous low).
The price breaks the previous day’s kill zone high.
The signal is outside the entry restriction window.
Bullish Signal (Buy): Triggered when:
A Bullish Engulfing pattern occurs (where the current bar closes higher than it opens and it engulfs the previous bar).
A Bullish Order Block forms (where the previous candle is bearish and the current one closes above the previous high).
The price breaks the previous day’s kill zone low.
The signal is outside the entry restriction window.
Plotting:
Kill Zone Background: The chart’s background turns blue during the kill zone to visually highlight the target time window.
Buy/Sell Signals: Buy and sell signals are marked on the chart using small upward and downward labels.
Previous Day's High/Low: The high and low from the previous day’s kill zone are plotted on the chart for reference.
Alerts:
Alerts for Buy and Sell Signals: Alerts are triggered when either buy or sell signals are generated, based on your conditions.
Customization:
Time Zone Offset: Adjusts the entire strategy to the desired time zone (e.g., New York time).
Kill Zone: You can adjust the start and end times of the kill zone, reflecting the active market session.
Entry Restriction Window: You have control over the start and end times of the entry window, ensuring no trades are executed during this period.
Goal:
Your strategy aims to capture buy or sell opportunities after the price breaks key levels (previous day’s high/low) within specific time windows (the kill zone and entry restriction zone). You focus on order block and engulfing candle patterns to validate entries.
4H CRT (1AM and 5AM)This TradingView script is designed to assist traders in implementing the "4-Hour Candle Ranges Theory Strategy (CRT)" by identifying key levels and setups based on the 1am and 4am (5am) 4-hour candles. This strategy is particularly effective for trading high-volatility assets such as Gold, EUR/USD, NAS100, US30, and S&P500, with US30 showing a notably high win rate. Here's how the strategy works:
Key Features:
1. Marking 1am and 4am 4-Hour Candle Ranges
- The script highlights the high and low of the 1am 4-hour candle.
- It visually tracks whether the high or low of the 1am candle is taken out by the subsequent 4-hour candle (5am).
2. Entry Setup Rules
- Primary Setup: Wait for the high or low of the 1am candle to be taken out by the 5am candle. Once this sweep occurs, wait for a Market Structure Shift (MSS) on the lower time frame (15min) to confirm your entry.
- Secondary Setup: If the 5am candle fails to take out the high or low of the 1am candle, the setup focuses on the levels formed by the 5am candle.
3. Trade Execution on 15-Minute Timeframe
- The script supports a lower time frame (15min) view to identify MSS and fine-tune entries.
4. Rinse and Repeat
- This process can be applied daily for consistent opportunities across the specified assets.
Advantages:
- Provides clear visual markers for key levels based on the 4-hour candles.
- Automates level plotting, saving traders time and reducing manual errors.
- Integrates well with the 15-minute timeframe for precise entry triggers.
- Optimized for popular trading instruments, especially US30 for a higher probability of success.
This script simplifies the application of CRT by automating the process of identifying and marking critical levels, enabling traders to focus on executing high-probability setups effectively.
Created by Hamid (poraymanfx)
Fibonacci Trading Strategy (Auto Levels)How It Works
Swing Highs and Lows Detection:
The script identifies the highest high and lowest low over a specified lookback period (default: 50 candles). These points are used as the basis for Fibonacci calculations.
Fibonacci Levels:
Fibonacci retracement levels: 0%, 38.2%, 50%, 61.8%, 78.6%, and 100%.
Fibonacci extension levels: 127.2%, 161.8%, 200%, 261.8%, and 361.8%.
Each level is plotted on the chart with a specific color and labeled with the corresponding price.
Entry Zones:
Pullback Area: Between the 50% and 61.8% retracement levels. This area is highlighted in green, indicating a potential entry for conservative traders.
Full Margin Area: Between the 61.8% and 78.6% retracement levels. This area is highlighted in red, suggesting a higher-risk entry for aggressive traders.
Stop Loss (SL):
The Stop Loss is placed at the 78.6% Fibonacci retracement level. A dotted red line is drawn at this level to provide a visual reference for risk management.
Entry labels include the Stop Loss price for clarity.
Take Profit (TP) Levels:
Multiple take-profit targets are identified using Fibonacci extension levels (127.2%, 161.8%, 200%, 261.8%, and 361.8%).
Each level is labeled with the price and target percentage.
Visual Aids:
The script dynamically labels each Fibonacci level with its corresponding price.
Entry points (Pullback and Full Margin) are marked with clear labels, including the recommended Stop Loss.
Background highlights help distinguish the Pullback and Full Margin areas.
Strategy Highlights
Risk Management:
Incorporates a well-defined Stop Loss at the 78.6% level to limit downside risk.
Multiple take-profit levels help traders scale out of positions gradually.
Automation:
Automatically recalculates levels when new swing highs or lows are detected, ensuring accuracy in dynamic markets.
Customizability:
Users can adjust the lookback period to suit different timeframes or trading styles.
Clarity:
Clean visuals and detailed labels ensure the strategy is easy to interpret and apply.
When to Use
The strategy is suitable for trend-following traders looking to enter during pullbacks in an established trend.
It works best in trending markets where Fibonacci levels often act as strong support or resistance.
Example Scenario
Bullish Setup:
Price retraces to the 50%-61.8% area (Pullback Area) after a swing high.
A buy order is placed in this zone, with the Stop Loss at the 78.6% level.
Profit targets are set at the 127.2%, 161.8%, and higher Fibonacci extensions.
Bearish Setup:
In a downtrend, price retraces upward to the 50%-61.8% zone.
A sell order is placed, with the Stop Loss at the 78.6% level and take-profit levels below.
Composer Strategy 1 (Haggis Levered)This strategy dynamically selects an asset to trade each day based on a set of predefined market conditions and technical indicators. It uses relative strength index (RSI) and moving averages to evaluate momentum and trends across multiple tickers, aiming to identify the most advantageous asset for the current market environment. By switching between leveraged ETFs, inverse funds, and defensive assets, the strategy seeks to capitalize on both bullish and bearish scenarios while mitigating risk during uncertain periods.
The approach emphasizes adaptability by monitoring key metrics like overbought or oversold signals and comparing cumulative returns and relative performance across asset classes. This flexibility allows the strategy to respond to changing market dynamics daily, aligning with short-term trends while maintaining a systematic and disciplined methodology for asset allocation.
3_SMA_Strategy_V-Singhal by ParthibIndicator Name: 3_SMA_Strategy_V-Singhal by Parthib
Description:
The 3_SMA_Strategy_V-Singhal by Parthib is a dynamic trend-following strategy that combines three key simple moving averages (SMA) — SMA 20, SMA 50, and SMA 200 — to generate buy and sell signals. This strategy uses these SMAs to capture and follow market trends, helping traders identify optimal entry (buy) and exit (sell) points. Additionally, the strategy highlights the closing price (CP), which plays a critical role in confirming buy and sell signals.
The strategy also features a Second Buy Signal triggered if the price falls more than 10% after an initial buy signal, providing a re-entry opportunity with a different visual highlight for the second buy signal.
Features:
Three Simple Moving Averages (SMA):
SMA 20: Short-term moving average reflecting immediate market trends.
SMA 50: Medium-term moving average showing the prevailing trend.
SMA 200: Long-term moving average that indicates the overall market trend.
Buy Signal (B1):
Triggered when:
SMA 200 > SMA 50 > SMA 20, indicating a bullish market structure.
The closing price is positioned below all three SMAs, confirming a potential upward reversal.
A green label appears at the low of the bar with the text B1-Price, indicating the price at which the buy signal is generated.
Second Buy Signal (B2):
Triggered if the price falls more than 10% after the first buy signal, providing an opportunity to re-enter the market at a potentially better price.
A blue label appears at the low of the bar with the text B2-Price, showing the price at which the second buy opportunity arises.
Sell Signal (S):
Triggered when:
SMA 20 > SMA 50 > SMA 200, indicating a bearish trend.
The closing price (CP) is positioned above all three SMAs, confirming a potential downward movement.
A red label appears at the high of the bar with the text S-Price, showing the price at which the sell signal is triggered.
How It Works:
Buy Conditions:
SMA 200 > SMA 50 > SMA 20: Indicates a bullish market where the long-term trend (SMA 200) is above the medium-term (SMA 50), and the medium-term trend is above the short-term (SMA 20).
Closing price below all three SMAs: Confirms that the price is in a favorable position for a potential upward reversal.
Sell Conditions:
SMA 20 > SMA 50 > SMA 200: This setup indicates a bearish trend.
Closing price above all three SMAs: Confirms that the price is in a favorable position for a potential downward movement.
Second Buy Signal (B2): If the price falls more than 10% after the first buy signal, the strategy triggers a second buy opportunity (B2) at a potentially better price. This helps traders take advantage of pullbacks or corrections after an initial favorable entry.
Labeling System:
B1-Price: The first buy signal label, appearing when the market is bullish and the closing price is below all three SMAs.
B2-Price: The second buy signal label, triggered if the price falls more than 10% after the initial buy signal.
S-Price: The sell signal label, appearing when the market turns bearish and the closing price is above all three SMAs.
How to Use:
Add the Indicator: Add "3_SMA_Strategy_V-Singhal by Parthib" to your chart on TradingView.
Interpret Buy Signals (B1): Look for green labels with the text "B1-Price" when the closing price (CP) is below all three SMAs and the trend is bullish.
Interpret Second Buy Signals (B2): If the price falls more than 10% after the first buy, look for blue labels with "B2-Price" and a re-entry opportunity.
Interpret Sell Signals (S): Look for red labels with the text "S-Price" when the market turns bearish, and the closing price (CP) is above all three SMAs.
Conclusion:
The 3_SMA_Strategy_V-Singhal by Parthib is an efficient and simple trend-following tool for traders looking to make informed buy and sell decisions. By combining the power of three SMAs and the closing price (CP) confirmation, this strategy helps traders to buy when the market shows a strong bullish setup and sell when the trend turns bearish. Additionally, the second buy signal feature ensures that traders don’t miss out on re-entry opportunities after price corrections, giving them a chance to re-enter the market at a favorable price.
CauchyTrend [InvestorUnknown]The CauchyTrend is an experimental tool that leverages a Cauchy-weighted moving average combined with a modified Supertrend calculation. This unique approach provides traders with insight into trend direction, while also offering an optional ATR-based range analysis to understand how often the market closes within, above, or below a defined volatility band.
Core Concepts
Cauchy Distribution and Gamma Parameter
The Cauchy distribution is a probability distribution known for its heavy tails and lack of a defined mean or variance. It is characterized by two parameters: a location parameter (x0, often 0 in our usage) and a scale parameter (γ, "gamma").
Gamma (γ): Determines the "width" or scale of the distribution. Smaller gamma values produce a distribution more concentrated near the center, giving more weight to recent data points, while larger gamma values spread the weight more evenly across the sample.
In this indicator, gamma influences how much emphasis is placed on values closer to the current price versus those further away in time. This makes the resulting weighted average either more reactive or smoother, depending on gamma’s value.
// Cauchy PDF formula used for weighting:
// f(x; γ) = (1/(π*γ)) *
f_cauchyPDF(offset, gamma) =>
numerator = gamma * gamma
denominator = (offset * offset) + (gamma * gamma)
pdf = (1 / (math.pi * gamma)) * (numerator / denominator)
pdf
A chart showing different Cauchy PDFs with various gamma values, illustrating how gamma affects the weight distribution.
Cauchy-Weighted Moving Average (CWMA)
Using the Cauchy PDF, we calculate normalized weights to create a custom Weighted Moving Average. Each bar in the lookback period receives a weight according to the Cauchy PDF. The result is a Cauchy Weighted Average (cwm_avg) that differs from typical moving averages, potentially offering unique sensitivity to price movements.
// Summation of weighted prices using Cauchy distribution weights
cwm_avg = 0.0
for i = 0 to length - 1
w_norm = array.get(weights, i) / sum_w
cwm_avg += array.get(values, i) * w_norm
Supertrend with a Cauchy Twist
The indicator integrates a modified Supertrend calculation using the cwm_avg as its reference point. The Supertrend logic typically sets upper and lower bands based on volatility (ATR), and flips direction when price crosses these bands.
In this case, the Cauchy-based average replaces the usual baseline, aiming to capture trend direction via a different weighting mechanism.
When price closes above the upper band, the trend is considered bullish; closing below the lower band signals a bearish trend.
ATR Stats Range (Optional)
Beyond the fundamental trend detection, the indicator optionally computes ATR-based stats to understand price distribution relative to a volatility corridor centered on the cwm_avg line:
Volatility Range:
Defined as cwm_avg ± (ATR * atr_mult), this range creates upper and lower bands. Turning on atr_stats computes how often the daily close falls: Within the range, Above the upper ATR boundary, Below the lower ATR boundary, Within the range but above cwm_avg, Within the range but below cwm_avg
These statistics can help traders gauge how the market behaves relative to this volatility envelope and possibly identify if the market tends to revert to the mean or break out more often.
Backtesting and Performance Metrics
The code is integrated with a backtesting library that allows users to assess strategy performance historically:
Equity Curve Calculation: Compares CauchyTrend-based signals against the underlying asset.
Performance Metrics Table: Once enabled, displays key metrics such as mean returns, Sharpe Ratio, Sortino Ratio, and more, comparing the strategy to a simple Buy & Hold approach.
Alerts and Notifications
The indicator provides Alerts for key events:
Long Alert: Triggered when the trend flips bullish.
Short Alert: Triggered when the trend flips bearish.
Customization and Calibration
Important: The default parameters are not optimized for any specific instrument or time frame. Traders should:
Adjust the length and gamma parameters to influence how sharply or broadly the cwm_avg reacts to price changes.
Tune the atr_len and atr_mult for the Supertrend logic to better match the asset’s volatility characteristics.
Experiment with atr_stats on/off to see if that additional volatility distribution information provides helpful insights.
Traders may find certain sets of parameters that align better with their preferred trading style, risk tolerance, or asset volatility profile.
Disclaimer: This indicator is for educational and informational purposes only. Past performance in backtesting does not guarantee future results. Always perform due diligence, and consider consulting a qualified financial advisor before trading.
James Gordon StrategyThis strategy is designed to identify potential bullish “bounce” points off a long-term moving average, specifically the 200-period Exponential Moving Average (EMA), on a 4-hour chart. The logic behind the strategy assumes that when price action interacts with this key support level and then closes above it, buyers are showing renewed interest and strength at that price level.
How It Works:
1. Focus on the 200 EMA:
The 200 EMA is often considered a long-term trend indicator. Price trading above the 200 EMA generally suggests an uptrend, while price trading below it suggests a downtrend. By targeting bounces on this EMA, the strategy looks for moments when price is demonstrating a willingness to hold or reclaim a pivotal support level.
2. Bounce Condition:
A “bounce” is defined by two key criteria:
- Test of Support: During the chosen candle (4-hour timeframe), the low price of the candle reaches the 200 EMA or dips just below it, indicating the market is testing that support zone.
- Close Above the EMA: By the end of that same candle, the price closes above the 200 EMA, signaling that buyers stepped in and defended that level.
3. Why This Matters:
When a candle’s low touches or moves below an important moving average, it might appear that the price could break down further. However, if the candle still manages to close above this moving average, it indicates resilience and potential bullish momentum. This can be an early sign of a price rebound, potentially offering a trading opportunity for those looking to go long.
4. Practical Use:
- Entry Signals: Traders may use these bounce signals to time entries, betting on the idea that price could move higher now that key support has held.
- Stop Placement and Risk Management: Traders can define their risk by placing stops just below the recent low or slightly under the 200 EMA.
- Market Context: To maximize its usefulness, traders should combine the bounce condition with other indicators, market structure analysis, and fundamental insights.
Traders should consider the overall trend, momentum indicators, volume profiles, or macro events to increase confidence in the signal.
In essence, the strategy aims to highlight moments when price action “bounces” off a crucial support level, potentially signaling a favorable entry point for bullish trades.
Did it move?That is the eternal question in trading.: Is the price moving? This indicators aims to answer that question. It is based on concepts from 2 Bars from "The Strat". This indicator measures the distance the current price is above the previous high or below the previous low and on two timeframes. The assumption is that the price is moving as long as the price is above or below the previous bar.
The distance the price moved is normalized by the standard deviation. This serves the trader in two ways: 1) you can quickly determine if a price movement is significant (score > 1), and 2) you can plan exits when the score falls below 1 (e.g., movement become insignificant). Movement upwards are colored green and down movements are red. When the price is also above the higher timeframe high (below the HTF low), the color are more intense. When the price is not moving, the background is highlighted.
Finally, there are two alert setting. One is for then the price stops moving (movement score falls below a threshold. The other is a exit/reversal warning. For example if there is a strong move in the opposite it will trigger that alert.
EMA with Supply and Demand Zones
The EMA with Supply and Demand Strategy is a trend-following trading approach that integrates Exponential Moving Averages (EMA) with supply and demand zones to identify potential entry and exit points. Below is a detailed description of its components and logic:
Key Components of the Strategy
1. EMA (Exponential Moving Average)
The EMA is used as a trend filter:
Bullish Trend: Price is above the EMA.
Bearish Trend: Price is below the EMA.
The EMA ensures that trades align with the overall market trend, reducing counter-trend risks.
2. Supply and Demand Zones
Demand Zone:
Represents areas where the price historically found support (buyers dominated).
Calculated using the lowest low over a specified lookback period.
Used for identifying potential long entry points.
Supply Zone:
Represents areas where the price historically faced resistance (sellers dominated).
Calculated using the highest high over a specified lookback period.
Used for identifying potential short entry points.
3. Trade Conditions
Long Trade:
Triggered when:
The price is above the EMA (bullish trend).
The low of the current candle touches or penetrates the most recent demand zone.
Short Trade:
Triggered when:
The price is below the EMA (bearish trend).
The high of the current candle touches or penetrates the most recent supply zone.
4. Exit Conditions
Long Exit:
Exit the trade when the price closes below the EMA, indicating a potential trend reversal.
Short Exit:
Exit the trade when the price closes above the EMA, signaling a potential upward reversal.
Visual Representation
EMA: A blue line plotted on the chart to show the trend.
Supply Zones: Red horizontal lines representing potential resistance levels.
Demand Zones: Green horizontal lines representing potential support levels.
These zones dynamically adjust to reflect the most recent 3 levels.
How the Strategy Works
Trend Identification:
The EMA determines the direction of the trade:
Look for long trades only in a bullish trend (price above EMA).
Look for short trades only in a bearish trend (price below EMA).
Entry Points:
Wait for price interaction with a supply or demand zone:
If the price touches a demand zone during a bullish trend, initiate a long trade.
If the price touches a supply zone during a bearish trend, initiate a short trade.
Risk Management:
The strategy exits trades if the price moves against the trend (crosses the EMA).
This ensures minimal exposure during adverse market movements.
Benefits of the Strategy
Trend Alignment:
Reduces counter-trend trades, improving the win rate.
Clear Entry and Exit Rules:
Combines price action (zones) with a reliable trend filter (EMA).
Dynamic Levels:
The supply and demand zones adapt to changing market conditions.
Customization Options
EMA Length:
Adjust to suit different timeframes or market conditions (e.g., 20 for faster trends, 50 for slower trends).
Lookback Period:
Fine-tune to capture broader or narrower supply and demand zones.
Risk/Reward Preferences:
Pair the strategy with stop-loss and take-profit levels for enhanced control.
This strategy is ideal for traders looking for a structured approach to identify high-probability trades while aligning with the prevailing trend. Backtest and optimize parameters based on your trading style and the specific asset you're tradin
RSI-EMA Signal by stock shooter## Strategy Description: 200 EMA Crossover with RSI, Green/Red Candles, Volume, and Exit Conditions
This strategy combines several technical indicators to identify potential long and short entry opportunities in a trading instrument. Here's a breakdown of its components:
1. 200-period Exponential Moving Average (EMA):
* The 200-period EMA acts as a long-term trend indicator.
* The strategy looks for entries when the price is above (long) or below (short) the 200 EMA.
2. Relative Strength Index (RSI):
* The RSI measures the momentum of price movements and helps identify overbought and oversold conditions.
* The strategy looks for entries when the RSI is below 40 (oversold) for long positions and above 60 (overbought) for short positions.
3. Green/Red Candles:
* This indicator filters out potential entries based on the current candle's closing price relative to its opening price.
* The strategy only considers long entries on green candles (closing price higher than opening) and short entries on red candles (closing price lower than opening).
4. Volume:
* This indicator adds a volume filter to the entry conditions.
* The strategy only considers entries when the current candle's volume is higher than the average volume of the previous 20 candles, aiming for stronger signals.
Overall:
This strategy aims to capture long opportunities during potential uptrends and short opportunities during downtrends, based on a combination of price action, momentum, and volume confirmation.
Important Notes:
Backtesting is crucial to evaluate the historical performance of this strategy before deploying it with real capital.
Consider incorporating additional risk management techniques like stop-loss orders.
This strategy is just a starting point and can be further customized based on your trading goals and risk tolerance.
