PVSRA v5Overview of the PVSRA Strategy
This strategy is designed to detect and capitalize on volume-driven threshold breaches in price candles. It operates on the premise that when a high-volume candle breaks a critical price threshold, not all orders are filled within that candle’s range. This creates an imbalance—similar to a physical system being perturbed—causing the price to revert toward the level where the breach occurred to “absorb” the residual orders.
Key Features and Their Theoretical Underpinnings
Dynamic Volume Analysis and Threshold Detection
Volume Surges as Market Perturbations:
The script computes a moving average of volume over a short window and flags moments when the current volume significantly exceeds this average. These surges act as a perturbation—injecting “energy” into the market.
Adaptive Abnormal Volume Threshold:
By calculating a dynamic abnormal threshold using a daily volume average (via an 89-period VWMA) and standard deviation, the strategy identifies when the current volume is abnormally high. This mechanism mirrors the idea that when a system is disturbed (here, by a volume surge), it naturally seeks to return to equilibrium.
Candle Coloring and Visual Signal Identification
Differentiation of Candle Types:
The script distinguishes between bullish (green) and bearish (red) candles. It applies different colors based on the strength of the volume signal, providing a clear, visual representation of whether a candle is likely to trigger a price reversion.
Implication of Unfilled Orders:
A red (bearish) candle with high volume implies that sell pressure has pushed the price past a critical threshold—yet not all buy orders have been fulfilled. Conversely, a green (bullish) candle indicates that aggressive buying has left pending sell orders. In both cases, the market is expected to reverse toward the breach point to restore balance.
Trade Execution Logic: Normal and Reversal Trades
Normal Trades:
When a high-volume candle breaches a threshold and meets the directional conditions (e.g., a red candle paired with price above a daily upper band), the strategy enters a trade anticipating a reversion. The underlying idea is that the market will move back to the level where the threshold was crossed—clearing the residual orders in a manner analogous to a system following the path of least resistance.
Reversal Trades:
The strategy also monitors for clusters of consecutive signals within a short lookback period. When multiple signals accumulate, it interprets this as the market having overextended and, in a corrective move, reverses the typical trade direction. This inversion captures the market’s natural tendency to “correct” itself by moving in discrete, quantized steps—each step representing the absorption of a minimum quantum of order imbalance.
Risk and Trade Management
Stop Loss and Take Profit Buffers:
Both normal and reversal trades include predetermined buffers for stop loss and take profit levels. This systematic risk management approach is designed to capture the anticipated reversion while minimizing potential losses, aligning with the idea that market corrections follow the most energy-efficient path back to equilibrium.
Symbol Flexibility:
An option to override the chart’s symbol allows the strategy to be applied consistently across different markets, ensuring that the volume and price dynamics are analyzed uniformly.
Conceptual Bridge: From Market Dynamics to Trade Execution
At its core, the strategy treats market price movements much like a physical system that seeks to minimize “transactional energy” or inefficiency. When a price candle breaches a key threshold on high volume, it mimics an injection of energy into the system. The subsequent price reversion is the market’s natural response—moving in the most efficient path back to balance. This perspective is akin to the principle of least action, where the system evolves along the trajectory that minimizes cumulative imbalance, and it acknowledges that these corrections occur in discrete steps reflective of quantized order execution.
This unified framework allows the PVSRA strategy to not only identify when significant volume-based threshold breaches occur but also to systematically execute trades that benefit from the expected corrective moves.
Volume
Volume Block Order AnalyzerCore Concept
The Volume Block Order Analyzer is a sophisticated Pine Script strategy designed to detect and analyze institutional money flow through large block trades. It identifies unusually high volume candles and evaluates their directional bias to provide clear visual signals of potential market movements.
How It Works: The Mathematical Model
1. Volume Anomaly Detection
The strategy first identifies "block trades" using a statistical approach:
```
avgVolume = ta.sma(volume, lookbackPeriod)
isHighVolume = volume > avgVolume * volumeThreshold
```
This means a candle must have volume exceeding the recent average by a user-defined multiplier (default 2.0x) to be considered a significant block trade.
2. Directional Impact Calculation
For each block trade identified, its price action determines direction:
- Bullish candle (close > open): Positive impact
- Bearish candle (close < open): Negative impact
The magnitude of impact is proportional to the volume size:
```
volumeWeight = volume / avgVolume // How many times larger than average
blockImpact = (isBullish ? 1.0 : -1.0) * (volumeWeight / 10)
```
This creates a normalized impact score typically ranging from -1.0 to 1.0, scaled by dividing by 10 to prevent excessive values.
3. Cumulative Impact with Time Decay
The key innovation is the cumulative impact calculation with decay:
```
cumulativeImpact := cumulativeImpact * impactDecay + blockImpact
```
This mathematical model has important properties:
- Recent block trades have stronger influence than older ones
- Impact gradually "fades" at rate determined by decay factor (default 0.95)
- Sustained directional pressure accumulates over time
- Opposing pressure gradually counteracts previous momentum
Trading Logic
Signal Generation
The strategy generates trading signals based on momentum shifts in institutional order flow:
1. Long Entry Signal: When cumulative impact crosses from negative to positive
```
if ta.crossover(cumulativeImpact, 0)
strategy.entry("Long", strategy.long)
```
*Logic: Institutional buying pressure has overcome selling pressure, indicating potential upward movement*
2. Short Entry Signal: When cumulative impact crosses from positive to negative
```
if ta.crossunder(cumulativeImpact, 0)
strategy.entry("Short", strategy.short)
```
*Logic: Institutional selling pressure has overcome buying pressure, indicating potential downward movement*
3. Exit Logic: Positions are closed when the cumulative impact moves against the position
```
if cumulativeImpact < 0
strategy.close("Long")
```
*Logic: The original signal is no longer valid as institutional flow has reversed*
Visual Interpretation System
The strategy employs multiple visualization techniques:
1. Color Gradient Bar System:
- Deep green: Strong buying pressure (impact > 0.5)
- Light green: Moderate buying pressure (0.1 < impact ≤ 0.5)
- Yellow-green: Mild buying pressure (0 < impact ≤ 0.1)
- Yellow: Neutral (impact = 0)
- Yellow-orange: Mild selling pressure (-0.1 < impact ≤ 0)
- Orange: Moderate selling pressure (-0.5 < impact ≤ -0.1)
- Red: Strong selling pressure (impact ≤ -0.5)
2. Dynamic Impact Line:
- Plots the cumulative impact as a line
- Line color shifts with impact value
- Line movement shows momentum and trend strength
3. Block Trade Labels:
- Marks significant block trades directly on the chart
- Shows direction and volume amount
- Helps identify key moments of institutional activity
4. Information Dashboard:
- Current impact value and signal direction
- Average volume benchmark
- Count of significant block trades
- Min/Max impact range
Benefits and Use Cases
This strategy provides several advantages:
1. Institutional Flow Detection: Identifies where large players are positioning themselves
2. Early Trend Identification: Often detects institutional accumulation/distribution before major price movements
3. Market Context Enhancement: Provides deeper insight than simple price action alone
4. Objective Decision Framework: Quantifies what might otherwise be subjective observations
5. Adaptive to Market Conditions: Works across different timeframes and instruments by using relative volume rather than absolute thresholds
Customization Options
The strategy allows users to fine-tune its behavior:
- Volume Threshold: How unusual a volume spike must be to qualify
- Lookback Period: How far back to measure average volume
- Impact Decay Factor: How quickly older trades lose influence
- Visual Settings: Labels and line width customization
This sophisticated yet intuitive strategy provides traders with a window into institutional activity, helping identify potential trend changes before they become obvious in price action alone.
Advanced Adaptive Grid Trading StrategyThis strategy employs an advanced grid trading approach that dynamically adapts to market conditions, including trend, volatility, and risk management considerations. The strategy aims to capitalize on price fluctuations in both rising (long) and falling (short) markets, as well as during sideways movements. It combines multiple indicators to determine the trend and automatically adjusts grid parameters for more efficient trading.
How it Works:
Trend Analysis:
Short, long, and super long Moving Averages (MA) to determine the trend direction.
RSI (Relative Strength Index) to identify overbought and oversold levels, and to confirm the trend.
MACD (Moving Average Convergence Divergence) to confirm momentum and trend direction.
Momentum indicator.
The strategy uses a weighted scoring system to assess trend strength (strong bullish, moderate bullish, strong bearish, moderate bearish, sideways).
Grid System:
The grid size (the distance between buy and sell levels) changes dynamically based on market volatility, using the ATR (Average True Range) indicator.
Grid density also adapts to the trend: in a strong trend, the grid is denser in the direction of the trend.
Grid levels are shifted depending on the trend direction (upwards in a bear market, downwards in a bull market).
Trading Logic:
The strategy opens long positions if the trend is bullish and the price reaches one of the lower grid levels.
It opens short positions if the trend is bearish and the price reaches one of the upper grid levels.
In a sideways market, it can open positions in both directions.
Risk Management:
Stop Loss for every position.
Take Profit for every position.
Trailing Stop Loss to protect profits.
Maximum daily loss limit.
Maximum number of positions limit.
Time-based exit (if the position is open for too long).
Risk-based position sizing (optional).
Input Options:
The strategy offers numerous settings that allow users to customize its operation:
Timeframe: The chart's timeframe (e.g., 1 minute, 5 minutes, 1 hour, 4 hours, 1 day, 1 week).
Base Grid Size (%): The base size of the grid, expressed as a percentage.
Max Positions: The maximum number of open positions allowed.
Use Volatility Grid: If enabled, the grid size changes dynamically based on the ATR indicator.
ATR Length: The period of the ATR indicator.
ATR Multiplier: The multiplier for the ATR to fine-tune the grid size.
RSI Length: The period of the RSI indicator.
RSI Overbought: The overbought level for the RSI.
RSI Oversold: The oversold level for the RSI.
Short MA Length: The period of the short moving average.
Long MA Length: The period of the long moving average.
Super Long MA Length: The period of the super long moving average.
MACD Fast Length: The fast period of the MACD.
MACD Slow Length: The slow period of the MACD.
MACD Signal Length: The period of the MACD signal line.
Stop Loss (%): The stop loss level, expressed as a percentage.
Take Profit (%): The take profit level, expressed as a percentage.
Use Trailing Stop: If enabled, the strategy uses a trailing stop loss.
Trailing Stop (%): The trailing stop loss level, expressed as a percentage.
Max Loss Per Day (%): The maximum daily loss, expressed as a percentage.
Time Based Exit: If enabled, the strategy exits the position after a certain amount of time.
Max Holding Period (hours): The maximum holding time in hours.
Use Risk Based Position: If enabled, the strategy calculates position size based on risk.
Risk Per Trade (%): The risk per trade, expressed as a percentage.
Max Leverage: The maximum leverage.
Important Notes:
This strategy does not guarantee profits. Cryptocurrency markets are volatile, and trading involves risk.
The strategy's effectiveness depends on market conditions and settings.
It is recommended to thoroughly backtest the strategy under various market conditions before using it live.
Past performance is not indicative of future results.
Liquidity Sweep Filter Strategy [AlgoAlpha X PineIndicators]This strategy is based on the Liquidity Sweep Filter developed by AlgoAlpha. Full credit for the concept and original indicator goes to AlgoAlpha.
The Liquidity Sweep Filter Strategy is a non-repainting trading system designed to identify liquidity sweeps, trend shifts, and high-impact price levels. It incorporates volume-based liquidation analysis, trend confirmation, and dynamic support/resistance detection to optimize trade entries and exits.
This strategy helps traders:
Detect liquidity sweeps where major market participants trigger stop losses and liquidations.
Identify trend shifts using a volatility-based moving average system.
Analyze volume distribution with a built-in volume profile visualization.
Filter noise by differentiating between major and minor liquidity sweeps.
How the Liquidity Sweep Filter Strategy Works
1. Trend Detection Using Volatility-Based Filtering
The strategy applies a volatility-adjusted moving average system to determine trend direction:
A central trend line is calculated using an EMA smoothed over a user-defined length.
Upper and lower deviation bands are created based on the average price deviation over multiple periods.
If price closes above the upper band, the strategy signals an uptrend.
If price closes below the lower band, the strategy signals a downtrend.
This approach ensures that trend shifts are confirmed only when price significantly moves beyond normal market fluctuations.
2. Liquidity Sweep Detection
Liquidity sweeps occur when price temporarily breaks key levels, triggering stop-loss liquidations or margin call events. The strategy tracks swing highs and lows, marking potential liquidity grabs:
Bearish Liquidity Sweeps – Price breaks a recent high, then reverses downward.
Bullish Liquidity Sweeps – Price breaks a recent low, then reverses upward.
Volume Integration – The strategy analyzes trading volume at each sweep to differentiate between major and minor sweeps.
Key levels where liquidity sweeps occur are plotted as color-coded horizontal lines:
Red lines indicate bearish liquidity sweeps.
Green lines indicate bullish liquidity sweeps.
Labels are displayed at each sweep, showing the volume of liquidated positions at that level.
3. Volume Profile Analysis
The strategy includes an optional volume profile visualization, displaying how trading volume is distributed across different price levels.
Features of the volume profile:
Point of Control (POC) – The price level with the highest traded volume is marked as a key area of interest.
Bounding Box – The profile is enclosed within a transparent box, helping traders visualize the price range of high trading activity.
Customizable Resolution & Scale – Traders can adjust the granularity of the profile to match their preferred time frame.
The volume profile helps identify zones of strong support and resistance, making it easier to anticipate price reactions at key levels.
Trade Entry & Exit Conditions
The strategy allows traders to configure trade direction:
Long Only – Only takes long trades.
Short Only – Only takes short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish trend shift is confirmed.
A bullish liquidity sweep occurs (price sweeps below a key level and reverses).
The trade direction setting allows long trades.
Short Entry:
A bearish trend shift is confirmed.
A bearish liquidity sweep occurs (price sweeps above a key level and reverses).
The trade direction setting allows short trades.
Exit Conditions
Closing a Long Position:
A bearish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Closing a Short Position:
A bullish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Customization Options
The strategy offers multiple adjustable settings:
Trade Mode: Choose between Long Only, Short Only, or Long & Short.
Trend Calculation Length & Multiplier: Adjust how trend signals are calculated.
Liquidity Sweep Sensitivity: Customize how aggressively the strategy identifies sweeps.
Volume Profile Display: Enable or disable the volume profile visualization.
Bounding Box & Scaling: Control the size and position of the volume profile.
Color Customization: Adjust colors for bullish and bearish signals.
Considerations & Limitations
Liquidity sweeps do not always result in reversals. Some price sweeps may continue in the same direction.
Works best in volatile markets. In low-volatility environments, liquidity sweeps may be less reliable.
Trend confirmation adds a slight delay. The strategy ensures valid signals, but this may result in slightly later entries.
Large volume imbalances may distort the volume profile. Adjusting the scale settings can help improve visualization.
Conclusion
The Liquidity Sweep Filter Strategy is a volume-integrated trading system that combines liquidity sweeps, trend analysis, and volume profile data to optimize trade execution.
By identifying key price levels where liquidations occur, this strategy provides valuable insight into market behavior, helping traders make better-informed trading decisions.
Key use cases for this strategy:
Liquidity-Based Trading – Capturing moves triggered by stop hunts and liquidations.
Volume Analysis – Using volume profile data to confirm high-activity price zones.
Trend Following – Entering trades based on confirmed trend shifts.
Support & Resistance Trading – Using liquidity sweep levels as dynamic price zones.
This strategy is fully customizable, allowing traders to adapt it to different market conditions, timeframes, and risk preferences.
Full credit for the original concept and indicator goes to AlgoAlpha.
IronBot v4IronBot v4 – Trading Strategy Overview
1. Quick Context
IronBot v4 is a trading strategy designed for users who want a simple yet effective approach to reading the markets. It uses a combination of Fibonacci retracement levels, custom logic triggers, and innovative modules (EMA validation, Iron Impulse Shield and Iron Auto Volume Detector) to identify potential entry and exit points, strengthening the strategy’s detection of sudden market volatility or shifts in trading volume.
2. Theoretical Details
Fibonacci Analysis
The script identifies recent market highs and lows, then calculates key Fibonacci levels (high- and low-based). These levels can help confirm potential reversals or trends.
EMA Option
When enabled, the exponential moving average (EMA) offers additional validation for trade entries. If the current price remains above a certain EMA threshold, long positions may be favored; conversely, if it stays below the EMA, short positions may be initiated.
IIS (Iron Impulse Shield)
IIS helps to filter out risky trades by measuring recent price shocks or surges. If an extreme movement is detected, the strategy may temporarily disable longs or shorts to avoid false signals.
IAVD (Iron Auto Volume Detector)
This functionality automatically detects the average market volume over a defined period (regardless of the market, since it relies on real data). When entering a position, it ensures that overall volume is high enough to confirm a genuinely active, robust market. By providing an additional filter, it can strengthen the decision-making process whenever the market’s participation level is in question.
Panel
IronBot v4 displays a real-time backtest panel that summarizes the selected configuration (including the current pair, analysis window, enabled filters), as well as showing net profit, applicable exchange fees, country taxes, and the final net balance. This gives traders an immediate overview of strategy performance and risk metrics.
What Pinescript Adds Visually
The script plots:
Fibonacci levels (highlighting potential reversal zones)
Trend lines indicating bullish (green) or bearish (red) lean
Optional EMA line
Optional Fibonacci forecast lines for anticipating future moves
Automatic labeling of entry, take-profit, and stop-loss levels, indicating the profit percentage of each trade.
3. Explanation of Inputs
The strategy exposes multiple inputs that can be toggled or configured by the user:
Analysis Window : Dictates how many bars to consider for high/low calculations and the fib retracement thresholds.
TRADES
Display TP/SL: For displaying Take profits and Stop loss.
Display Forecast: When enabled, this feature calculates and projects possible future Fibonacci retracements using historical data, helping traders anticipate potential upcoming trade setups.
Leverage: Only used for the Panel and not for trades. Lets you amplify your position size; higher leverage increases potential gains but also heightens risk. TradingView strategy is using properties for doing this.
Exchange Maker Fees & Exchange Taker Fees: Only used for the Panel and not for trades. Define the percentage cost applied by your exchange for maker and taker trades, respectively. These fees are accounted for in final profit calculations of the Panel.
Country Tax: Only used for the Panel and not for trades. Specifies a tax percentage to be deducted from net profits.
STOP LOSS and TAKE PROFITS
Stop-Loss & Take-Profit Parameters: Controls the percentage distances at which the strategy will exit positions. Additionally, you can configure up to four distinct take-profit levels (TP1 through TP4). Each level should be higher target than the previous one, and you can assign a specific percentage of the total position to close at each TP, ensuring the sum equals 100%. A break-even feature is also available when multiple TPs are used.
EMA
EMA (Exponential Moving Average) Option: When enabled, the strategy opens long trades only if the current price is above the specified EMA length, and opens short trades only if it is below that threshold.
PANELS
Show Panel: For displaying the backtest integrated panel.
IRON IMPULSE SHIELD (IIS)
IIS (Iron Impulse Shield) Option: When enabled, IIS continuously monitors recent price volatility depending on the analysis window set. If the market experiences an extreme surge or drop beyond a specified threshold, IIS temporarily blocks new long or short positions.
IRON AUTO VOLUME DETECTOR (IAVD)
IAVD (Iron Auto Volume Detector) Option: When enabled, it continuously measures the average market volume over a special period, irrespective of the specific trading pair. This ensures that IronBot v4 focuses on markets with robust participation, reducing the likelihood of entering trades during low-liquidity conditions.
By changing these values, IronBot v4 reacts differently to market structure and risk management requirements. Stop-loss and take-profit levels will adjust accordingly, while advanced filters (like EMA or IIS) influence when trades can open.
4. TradingView Strategy Properties
IronBot v4 uses the built-in TradingView “strategy” functionality. In particular:
Order Placement: The code calls strategy.entry() and strategy.close() for direct orders, ensuring signals are sent immediately (no limit orders are used). This helps connect with exchange signal bots for automated execution.
Initial Capital: The code uses initial capital defined in properties for calculating Net balance in the integrated panel.
On bar close: This strategy fill orders on bar close.
Pyramiding: This strategy can take only 1 successive trade in the same direction
Be careful to configure your leverage input depending on your strategy properties.
5. Visualization
5. Purpose & Disclaimer
This script is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always confirm your own risk tolerance and consult a financial professional before placing live trades. Trading leveraged products can involve substantial risk of loss.
GOLD Volume-Based Entry StrategyShort Description:
This script identifies potential long entries by detecting two consecutive bars with above-average volume and bullish price action. When these conditions are met, a trade is entered, and an optional profit target is set based on user input. This strategy can help highlight momentum-driven breakouts or trend continuations triggered by a surge in buying volume.
How It Works
Volume Moving Average
A simple moving average of volume (vol_ma) is calculated over a user-defined period (default: 20 bars). This helps us distinguish when volume is above or below recent averages.
Consecutive Green Volume Bars
First bar: Must be bullish (close > open) and have volume above the volume MA.
Second bar: Must also be bullish, with volume above the volume MA and higher than the first bar’s volume.
When these two bars appear in sequence, we interpret it as strong buying pressure that could drive price higher.
Entry & Profit Target
Upon detecting these two consecutive bullish bars, the script places a long entry.
A profit target is set at current price plus a user-defined fixed amount (default: 5 USD).
You can adjust this target, or you can add a stop-loss in the script to manage risk further.
Visual Cues
Buy Signal Marker appears on the chart when the second bar confirms the signal.
Green Volume Columns highlight the bars that fulfill the criteria, providing a quick visual confirmation of high-volume bullish bars.
Works fine on 1M-2M-5M-15M-30M. Do not use it on higher TF. Due the lack of historical data on lower TF, the backtest result is limited.
Candle Emotion Index (CEI) StrategyThe Candle Emotion Index (CEI) Strategy is an innovative sentiment-based trading approach designed to help traders identify and capitalize on market psychology. By analyzing candlestick patterns and combining them into a unified metric, the CEI Strategy provides clear entry and exit signals while dynamically managing risk. This strategy is ideal for traders looking to leverage market sentiment to identify high-probability trading opportunities.
How It Works
The CEI Strategy is built around three core oscillators that reflect key emotional states in the market:
Indecision Oscillator . Measures market uncertainty using patterns like Doji and Spinning Tops. High values indicate hesitation, signaling potential turning points.
Fear Oscillator . Tracks bearish sentiment through patterns like Shooting Star, Hanging Man, and Bearish Engulfing. Helps identify moments of intense selling pressure.
Greed Oscillator . Detects bullish sentiment using patterns like Marubozu, Hammer, Bullish Engulfing, and Three White Soldiers. Highlights periods of strong buying interest.
These oscillators are averaged into the Candle Emotion Index (CEI):
CEI = (Indecision + Fear + Greed) / 3
This single value quantifies overall market sentiment and drives the strategy’s trading decisions.
Key Features
Sentiment-Based Trading Signals . Long Entry: Triggered when the CEI crosses above a lower threshold (e.g., 0.1), indicating increasing bullish sentiment. Short Entry: Triggered when the CEI crosses above a higher threshold (e.g., 0.2), signaling rising bearish sentiment.
Volume Confirmation . Trades are validated only if volume exceeds a user-defined multiplier of the average volume over the lookback period. This ensures entries are backed by significant market activity.
Break-Even Recovery Mechanism . If a trade moves into a loss, the strategy attempts to recover to break-even instead of immediately exiting at a loss. This feature provides flexibility, allowing the market to recover while maintaining disciplined risk management.
Dynamic Risk Management . Maximum Holding Period: Trades are closed after a user-defined number of candles to avoid overexposure to prolonged uncertainty. Profit-Taking Conditions: Positions are exited when favorable price moves are confirmed by increased volume, locking in gains. Loss Threshold: Trades are exited early if the price moves unfavorably beyond a set percentage of the entry price, limiting potential losses.
Cooldown Period . After a trade is closed, a cooldown period prevents immediate re-entry, reducing overtrading and improving signal quality.
Why Use This Strategy?
The CEI Strategy combines advanced sentiment analysis with robust trade management, making it a powerful tool for traders seeking to understand market psychology and identify high-probability setups. Its unique features, such as the break-even recovery mechanism and volume confirmation, add an extra layer of discipline and reliability to trading decisions.
Best Practices
Combine with Other Indicators . Use trend-following tools (e.g., moving averages, ADX) and momentum oscillators (e.g., RSI, MACD) to confirm signals.
Align with Key Levels . Incorporate support and resistance levels for refined entries and exits.
Multi-Market Compatibility . Apply this strategy to forex, crypto, stocks, or any asset class with strong volume and price action.
BullBear with Volume-Percentile TP - Strategy [presentTrading] Happy New Year, everyone! I hope we have a fantastic year ahead.
It's been a while since I published an open script, but it's time to return.
This strategy introduces an indicator called Bull Bear Power, combined with an advanced take-profit system, which is the main innovative and educational aspect of this script. I hope all of you find some useful insights here. Welcome to engage in meaningful exchanges. This is a versatile tool suitable for both novice and experienced traders.
█ Introduction and How it is Different
Unlike traditional strategies that rely solely on price or volume indicators, this approach combines Bull Bear Power (BBP) with volume percentile analysis to identify optimal entry and exit points. It features a dynamic take-profit mechanism based on ATR (Average True Range) multipliers adjusted by volume and percentile factors, ensuring adaptability to diverse market conditions. This multifaceted strategy not only improves signal accuracy but also optimizes risk management, distinguishing it from conventional trading methods.
BTCUSD 6hr performance
Disable the visualization of Bull Bear Power (BBP) to clearly view the Z-Score.
█ Strategy, How it Works: Detailed Explanation
The BBP Strategy with Volume-Percentile TP utilizes several interconnected components to analyze market data and generate trading signals. Here's an overview with essential equations:
🔶 Core Indicators and Calculations
1. Exponential Moving Average (EMA):
- **Purpose:** Smoothens price data to identify trends.
- **Formula:**
EMA_t = (Close_t * (2 / (lengthInput + 1))) + (EMA_(t-1) * (1 - (2 / (lengthInput + 1))))
- Usage: Baseline for Bull and Bear Power.
2. Bull and Bear Power:
- Bull Power: `BullPower = High_t - EMA_t`
- Bear Power: `BearPower = Low_t - EMA_t`
- BBP:** `BBP = BullPower + BearPower`
- Interpretation: Positive BBP indicates bullish strength, negative indicates bearish.
3. Z-Score Calculation:
- Purpose: Normalizes BBP to assess deviation from the mean.
- Formula:
Z-Score = (BBP_t - bbp_mean) / bbp_std
- Components:
- `bbp_mean` = SMA of BBP over `zLength` periods.
- `bbp_std` = Standard deviation of BBP over `zLength` periods.
- Usage: Identifies overbought or oversold conditions based on thresholds.
🔶 Volume Analysis
1. Volume Moving Average (`vol_sma`):
vol_sma = (Volume_1 + Volume_2 + ... + Volume_vol_period) / vol_period
2. Volume Multiplier (`vol_mult`):
vol_mult = Current Volume / vol_sma
- Thresholds:
- High Volume: `vol_mult > 2.0`
- Medium Volume: `1.5 < vol_mult ≤ 2.0`
- Low Volume: `1.0 < vol_mult ≤ 1.5`
🔶 Percentile Analysis
1. Percentile Calculation (`calcPercentile`):
Percentile = (Number of values ≤ Current Value / perc_period) * 100
2. Thresholds:
- High Percentile: >90%
- Medium Percentile: >80%
- Low Percentile: >70%
🔶 Dynamic Take-Profit Mechanism
1. ATR-Based Targets:
TP1 Price = Entry Price ± (ATR * atrMult1 * TP_Factor)
TP2 Price = Entry Price ± (ATR * atrMult2 * TP_Factor)
TP3 Price = Entry Price ± (ATR * atrMult3 * TP_Factor)
- ATR Calculation:
ATR_t = (True Range_1 + True Range_2 + ... + True Range_baseAtrLength) / baseAtrLength
2. Adjustment Factors:
TP_Factor = (vol_score + price_score) / 2
- **vol_score** and **price_score** are based on current volume and price percentiles.
Local performance
🔶 Entry and Exit Logic
1. Long Entry: If Z-Score crosses above 1.618, then Enter Long.
2. Short Entry: If Z-Score crosses below -1.618, then Enter Short.
3. Exiting Positions:
If Long and Z-Score crosses below 0:
Exit Long
If Short and Z-Score crosses above 0:
Exit Short
4. Take-Profit Execution:
- Set multiple exit orders at dynamically calculated TP levels based on ATR and adjusted by `TP_Factor`.
█ Trade Direction
The strategy determines trade direction using the Z-Score from the BBP indicator:
- Long Positions:
- Condition: Z-Score crosses above 1.618.
- Short Positions:
- Condition: Z-Score crosses below -1.618.
- Exiting Trades:
- Long Exit: Z-Score drops below 0.
- Short Exit: Z-Score rises above 0.
This approach aligns trades with prevailing market trends, increasing the likelihood of successful outcomes.
█ Usage
Implementing the BBP Strategy with Volume-Percentile TP in TradingView involves:
1. Adding the Strategy:
- Copy the Pine Script code.
- Paste it into TradingView's Pine Editor.
- Save and apply the strategy to your chart.
2. Configuring Settings:
- Adjust parameters like EMA length, Z-Score thresholds, ATR multipliers, volume periods, and percentile settings to match your trading preferences and asset behavior.
3. Backtesting:
- Use TradingView’s backtesting tools to evaluate historical performance.
- Analyze metrics such as profit factor, drawdown, and win rate.
4. Optimization:
- Fine-tune parameters based on backtesting results.
- Test across different assets and timeframes to enhance adaptability.
5. Deployment:
- Apply the strategy in a live trading environment.
- Continuously monitor and adjust settings as market conditions change.
█ Default Settings
The BBP Strategy with Volume-Percentile TP includes default parameters designed for balanced performance across various markets. Understanding these settings and their impact is essential for optimizing strategy performance:
Bull Bear Power Settings:
- EMA Length (`lengthInput`): 21
- **Effect:** Balances sensitivity and trend identification; shorter lengths respond quicker but may generate false signals.
- Z-Score Length (`zLength`): 252
- **Effect:** Long period for stable mean and standard deviation, reducing false signals but less responsive to recent changes.
- Z-Score Threshold (`zThreshold`): 1.618
- **Effect:** Higher threshold filters out weaker signals, focusing on significant market moves.
Take Profit Settings:
- Use Take Profit (`useTP`): Enabled (`true`)
- **Effect:** Activates dynamic profit-taking, enhancing profitability and risk management.
- ATR Period (`baseAtrLength`): 20
- **Effect:** Shorter period for sensitive volatility measurement, allowing tighter profit targets.
- ATR Multipliers:
- **Effect:** Define conservative to aggressive profit targets based on volatility.
- Position Sizes:
- **Effect:** Diversifies profit-taking across multiple levels, balancing risk and reward.
Volume Analysis Settings:
- Volume MA Period (`vol_period`): 100
- **Effect:** Longer period for stable volume average, reducing the impact of short-term spikes.
- Volume Multipliers:
- **Effect:** Determines volume conditions affecting take-profit adjustments.
- Volume Factors:
- **Effect:** Adjusts ATR multipliers based on volume strength.
Percentile Analysis Settings:
- Percentile Period (`perc_period`): 100
- **Effect:** Balances historical context with responsiveness to recent data.
- Percentile Thresholds:
- **Effect:** Defines price and volume percentile levels influencing take-profit adjustments.
- Percentile Factors:
- **Effect:** Modulates ATR multipliers based on price percentile strength.
Impact on Performance:
- EMA Length: Shorter EMAs increase sensitivity but may cause more false signals; longer EMAs provide stability but react slower to market changes.
- Z-Score Parameters:*Longer Z-Score periods create more stable signals, while higher thresholds reduce trade frequency but increase signal reliability.
- ATR Multipliers and Position Sizes: Higher multipliers allow for larger profit targets with increased risk, while diversified position sizes help in securing profits at multiple levels.
- Volume and Percentile Settings: These adjustments ensure that take-profit targets adapt to current market conditions, enhancing flexibility and performance across different volatility environments.
- Commission and Slippage: Accurate settings prevent overestimation of profitability and ensure the strategy remains viable after accounting for trading costs.
Conclusion
The BBP Strategy with Volume-Percentile TP offers a robust framework by combining BBP indicators with volume and percentile analyses. Its dynamic take-profit mechanism, tailored through ATR adjustments, ensures that traders can effectively capture profits while managing risks in varying market conditions.
Ichimoku by FarmerBTCLegal Disclaimer
This strategy, "Ichimoku by FarmerBTC," is provided for educational and informational purposes only. It does not constitute financial advice and should not be relied upon as such. Trading and investing involve substantial risk, including the potential for losing more than your initial investment. Past performance is not indicative of future results. Always consult with a qualified financial advisor before making trading or investment decisions. The author of this strategy is not responsible for any financial losses incurred through its use.
Overview
The "Ichimoku by FarmerBTC" strategy is a trend-following system built on the Ichimoku Cloud indicator, enhanced with volume analysis and a high-timeframe Simple Moving Average (HTF SMA) condition. It is designed to identify long-only trade opportunities and performs optimally on higher timeframes, such as the daily chart or above.
Core Components
1. Ichimoku Cloud
The Ichimoku Cloud is a comprehensive trend-following indicator that helps identify the overall market direction and momentum. It consists of:
Conversion Line (Tenkan-Sen): Measures short-term momentum.
Base Line (Kijun-Sen): Filters medium-term trends.
Leading Span A: The average of the Conversion and Base Lines, forming one cloud boundary.
Leading Span B: The midpoint of the highest high and lowest low over a longer period, forming the other cloud boundary.
Key Ichimoku Rules Applied:
The strategy identifies bullish trends when:
The price is above the cloud.
The cloud is bullish (Leading Span A > Leading Span B).
2. High-Timeframe Simple Moving Average (HTF SMA)
This condition ensures alignment with the broader trend:
Default SMA Length: 13 periods.
Default Timeframe: 1 day.
HTF SMA Rule:
Trades are allowed only when the price is above the HTF SMA, ensuring alignment with the larger trend.
3. Volume Analysis
The strategy uses volume to validate trade setups:
Volume MA: A 20-period moving average of volume is calculated.
Trades are allowed only when the current volume is at least 1.5x the Volume MA, indicating strong market participation.
Entry and Exit Rules
Entry Condition (Long Only):
Price above the Ichimoku Cloud: Confirms a bullish trend.
Bullish Cloud: Leading Span A > Leading Span B indicates upward momentum.
Price above the HTF SMA: Ensures alignment with the broader trend.
Volume exceeds threshold: Confirms strong market participation.
Exit Condition:
The strategy exits the position when the price moves below the Ichimoku Cloud, signaling a potential trend reversal.
Best Timeframes
This strategy is optimized for daily (1D) or higher timeframes (e.g., weekly 1W). Using it on lower timeframes may produce false signals due to increased noise in price and volume data.
Default Settings
Ichimoku Settings:
Conversion Line Period: 10
Base Line Period: 30
Lagging Span Period: 53
Displacement: 26
HTF SMA Settings:
SMA Length: 13
Timeframe: 1 Day
Volume Settings:
Volume MA Length: 20
Volume Multiplier: 1.5x
Visualization
Ichimoku Cloud:
Dynamic cloud coloring (green for bullish, red for bearish) helps identify the current trend.
HTF SMA:
A purple line overlays the chart, providing a clear representation of the high-timeframe trend.
Volume Panel:
An optional panel displays volume (blue histogram) and the Volume Moving Average (orange line) to analyze market participation.
Advantages of This Strategy
High Accuracy on Higher Timeframes:
Filtering trades using the Ichimoku Cloud, HTF SMA, and volume ensures robust trend alignment, reducing false signals.
Volume Confirmation:
Incorporates volume as a validation metric to enter trades only during strong market participation.
Easy Customization:
Parameters like Ichimoku periods, SMA length, timeframe, and volume thresholds can be adjusted to suit different assets or trading styles.
Limitations
Not Suitable for Low Timeframes:
Lower timeframes can produce excessive noise, leading to false signals.
Long-Only:
The strategy is designed only for bullish markets and does not support short trades.
Lagging Nature of Indicators:
Both the Ichimoku Cloud and SMA are lagging indicators, meaning they react to past price movements.
Conclusion
The "Ichimoku by FarmerBTC" strategy is an excellent tool for trend-following on daily or higher timeframes. Its combination of Ichimoku Cloud, high-timeframe SMA, and volume ensures a robust framework for identifying high-probability long trades in trending markets. However, users are advised to test the strategy thoroughly and manage their risk appropriately. Always consult with a financial professional before making trading decisions.
Triple CCI Strategy MFI Confirmed [Skyrexio]Overview
Triple CCI Strategy MFI Confirmed leverages 3 different periods Commodity Channel Index (CCI) indicator in conjunction Money Flow Index (MFI) and Exponential Moving Average (EMA) to obtain the high probability setups. Fast period CCI is used for having the high probability to enter in the direction of short term trend, middle and slow period CCI are used for confirmation, if market now likely in the mid and long-term uptrend. MFI is used to confirm trade with the money inflow/outflow with the high probability. EMA is used as an additional trend filter. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Four layers trade filtering system: Strategy utilizes two different period CCI indicators, MFI and EMA indicators to confirm the signals produced by fast period CCI.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Fast period CCI shall crossover the zero-line.
Slow and Middle period CCI shall be above zero-lines.
Price shall close above the EMA. Crossover is not obligatory
MFI shall be above 50
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 14, used for calculation short term period CCI)
CCI Middle Length (by default = 25, used for calculation short term period CCI)
CCI Slow Length (by default = 50, used for calculation long term period CCI)
MFI Length (by default = 14, used for calculation MFI
EMA Length (by default = 50, period of EMA, used for trend filtering EMA calculation)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI, MFI and EMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator that measures the deviation of a security's price from its average price over a specific period. It helps traders identify overbought or oversold conditions and potential trend reversals.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Money Flow Index (MFI) is a technical indicator that measures the strength of money flowing into and out of a security. It combines price and volume data to assess buying and selling pressure and is often used to identify overbought or oversold conditions. The formula for MFI involves several steps:
1. Calculate the Typical Price (TP):
TP = (high + low + close) / 3
2. Calculate the Raw Money Flow (RMF):
Raw Money Flow = TP × Volume
3. Determine Positive and Negative Money Flow:
If the current TP is greater than the previous TP, it's Positive Money Flow.
If the current TP is less than the previous TP, it's Negative Money Flow.
4. Calculate the Money Flow Ratio (MFR):
Money Flow Ratio = Sum of Positive Money Flow (over n periods) / Sum of Negative Money Flow (over n periods)
5. Calculate the Money Flow Index (MFI):
MFI = 100 − (100 / (1 + Money Flow Ratio))
MFI above 80 can be considered as overbought, below 20 - oversold.
The Exponential Moving Average (EMA) is a type of moving average that places greater weight and significance on the most recent data points. It is widely used in technical analysis to smooth price data and identify trends more quickly than the Simple Moving Average (SMA).
Formula:
1. Calculate the multiplier
Multiplier = 2 / (n + 1) , Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
This strategy leverages Fast period CCI, which shall break the zero line to the upside to say that probability of short term trend change to the upside increased. This zero line crossover shall be confirmed by the Middle and Slow periods CCI Indicators. At the moment of breakout these two CCIs shall be above 0, indicating that there is a high probability that price is in middle and long term uptrend. This approach increases chances to have a long trade setup in the direction of mid-term and long-term trends when the short-term trend starts to reverse to the upside.
Additionally strategy uses MFI to have a greater probability that fast CCI breakout is confirmed by this indicator. We consider the values of MFI above 50 as a higher probability that trend change from downtrend to the uptrend is real. Script opens long trades only if MFI is above 50. As you already know from the MFI description, it incorporates volume in its calculation, therefore we have another one confirmation factor.
Finally, strategy uses EMA an additional trend filter. It allows to open long trades only if price close above EMA (by default 50 period). It increases the probability of taking long trades only in the direction of the trend.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses another one EMA (by default = 20 period) as a trailing profit level.
Backtest Results
Operating window: Date range of backtests is 2022.04.01 - 2024.11.25. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -4.13%
Maximum Single Profit: +19.66%
Net Profit: +5421.21 USDT (+54.21%)
Total Trades: 108 (44.44% win rate)
Profit Factor: 2.006
Maximum Accumulated Loss: 777.40 USDT (-7.77%)
Average Profit per Trade: 50.20 USDT (+0.85%)
Average Trade Duration: 44 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Max Pain StrategyThe Max Pain Strategy uses a combination of volume and price movement thresholds to identify potential "pain zones" in the market. A "pain zone" is considered when the volume exceeds a certain multiple of its average over a defined lookback period, and the price movement exceeds a predefined percentage relative to the price at the beginning of the lookback period.
Here’s how the strategy functions step-by-step:
Inputs:
length: Defines the lookback period used to calculate the moving average of volume and the price change over that period.
volMultiplier: Sets a threshold multiplier for the volume; if the volume exceeds the average volume multiplied by this factor, it triggers the condition for a potential "pain zone."
priceMultiplier: Sets a threshold for the minimum percentage price change that is required for a "pain zone" condition.
Calculations:
averageVolume: The simple moving average (SMA) of volume over the specified lookback period.
priceChange: The absolute difference in price between the current bar's close and the close from the lookback period (length).
Pain Zone Condition:
The condition for entering a position is triggered if both the volume is higher than the average volume by the volMultiplier and the price change exceeds the price at the length-period ago by the priceMultiplier. This is an indication of significant market activity that could result in a price move.
Position Entry:
A long position is entered when the "pain zone" condition is met.
Exit Strategy:
The position is closed after the specified holdPeriods, which defines how many periods the position will be held after being entered.
Visualization:
A small triangle is plotted on the chart where the "pain zone" condition is met.
The background color changes to a semi-transparent red when the "pain zone" is active.
Scientific Explanation of the Components
Volume Analysis and Price Movement: These are two critical factors in trading strategies. Volume often serves as an indicator of market strength (or weakness), and price movement is a direct reflection of market sentiment. Higher volume with significant price movement may suggest that the market is entering a phase of increased volatility or trend formation, which the strategy aims to exploit.
Volume analysis: The study of volume as an indicator of market participation, with increased volume often signaling stronger trends (Murphy, J. J., Technical Analysis of the Financial Markets).
Price movement thresholds: A large price change over a short period may be interpreted as a breakout or a potential reversal point, aligning with volatility and liquidity analysis (Schwager, J. D., Market Wizards).
Repainting Check: This strategy does not involve any repainting because it is based on current and past data, and there is no reference to future values in the decision-making process. However, any strategy that uses lagging indicators or conditions based on historical bars, like close , is inherently a lagging strategy and might not predict real-time price action accurately until after the fact.
Risk Management: The position hold duration is predefined, which adds an element of time-based risk control. This duration ensures that the strategy does not hold a position indefinitely, which could expose it to unnecessary risk.
Potential Issues and Considerations
Repainting:
The strategy does not utilize future data or conditions that depend on future bars, so it does not inherently suffer from repainting issues.
However, since the strategy relies on volume and price change over a set lookback period, the decision to enter or exit a trade is only made after the data for the current bar is complete, meaning the trade decisions are somewhat delayed, which could be seen as a lagging feature rather than a repainting one.
Lagging Nature:
As with many technical analysis-based strategies, this one is based on past data (moving averages, price changes), meaning it reacts to market movements after they have already occurred, rather than predicting future price actions.
Overfitting Risk:
With parameters like the lookback period and multipliers being user-adjustable, there is a risk of overfitting to historical data. Adjusting parameters too much based on past performance can lead to poor out-of-sample results (Gauthier, P., Practical Quantitative Finance).
Conclusion
The Max Pain Strategy is a simple approach to identifying potential market entries based on volume spikes and significant price changes. It avoids repainting by relying solely on historical and current bar data, but it is inherently a lagging strategy that reacts to price and volume patterns after they have occurred. Therefore, the strategy can be effective in trending markets but may struggle in highly volatile, sideways markets.
SMB MagicSMB Magic
Overview: SMB Magic is a powerful technical strategy designed to capture breakout opportunities based on price movements, volume spikes, and trend-following logic. This strategy works exclusively on the XAU/USD symbol and is optimized for the 15-minute time frame. By incorporating multiple factors, this strategy identifies high-probability trades with a focus on risk management.
Key Features:
Breakout Confirmation:
This strategy looks for price breakouts above the previous high or below the previous low, with a significant volume increase. A breakout is considered valid when it is supported by strong volume, confirming the strength of the price move.
Price Movement Filter:
The strategy ensures that only significant price movements are considered for trades, helping to avoid low-volatility noise. This filter targets larger price swings to maximize potential profits.
Exponential Moving Average (EMA):
A long-term trend filter is applied to ensure that buy trades occur only when the price is above the moving average, and sell trades only when the price is below it.
Fibonacci Levels:
Custom Fibonacci retracement levels are drawn based on recent price action. These levels act as dynamic support and resistance zones and help determine the exit points for trades.
Take Profit/Stop Loss:
The strategy incorporates predefined take profit and stop loss levels, designed to manage risk effectively. These levels are automatically applied to trades and are adjusted based on the market's volatility.
Volume Confirmation:
A volume multiplier confirms the strength of the breakout. A trade is only considered when the volume exceeds a certain threshold, ensuring that the breakout is supported by sufficient market participation.
How It Works:
Entry Signals:
Buy Signal: A breakout above the previous high, accompanied by significant volume and price movement, occurs when the price is above the trend-following filter (e.g., EMA).
Sell Signal: A breakout below the previous low, accompanied by significant volume and price movement, occurs when the price is below the trend-following filter.
Exit Strategy:
Each position (long or short) has predefined take-profit and stop-loss levels, which are designed to protect capital and lock in profits at key points in the market.
Fibonacci Levels:
Fibonacci levels are drawn to identify potential areas of support or resistance, which can be used to guide exits and stop-loss placements.
Important Notes:
Timeframe Restriction: This strategy is designed specifically for the 15-minute time frame.
Symbol Restriction: The strategy works exclusively on the XAU/USD (Gold) symbol and is not recommended for use with other instruments.
Best Performance in Trending Markets: It works best in trending conditions where breakouts occur frequently.
Disclaimer:
Risk Warning: Trading involves risk, and past performance is not indicative of future results. Always conduct your own research and make informed decisions before trading.
Ichimoku + RSI + MACD Strategy1. Relative Strength Index (RSI)
Overview:
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is typically used to identify overbought or oversold conditions in a market.
How to Use with Ichimoku:
Long Entry: Look for RSI to be above 30 (indicating it is not oversold) when the price is above the Ichimoku Cloud.
Short Entry: Look for RSI to be below 70 (indicating it is not overbought) when the price is below the Ichimoku Cloud.
2. Moving Average Convergence Divergence (MACD)
Overview:
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. It consists of the MACD line, signal line, and histogram.
How to Use with Ichimoku:
Long Entry: Enter a long position when the MACD line crosses above the signal line while the price is above the Ichimoku Cloud.
Short Entry: Enter a short position when the MACD line crosses below the signal line while the price is below the Ichimoku Cloud.
Combined Strategy Example
Here’s a brief outline of how to structure a trading strategy using Ichimoku, RSI, and MACD:
Long Entry Conditions:
Price is above the Ichimoku Cloud.
RSI is above 30.
MACD line crosses above the signal line.
Short Entry Conditions:
Price is below the Ichimoku Cloud.
RSI is below 70.
MACD line crosses below the signal line.
Exit Conditions:
Exit long when MACD line crosses below the signal line.
Exit short when MACD line crosses above the signal line.
MFI Strategy with Oversold Zone Exit and AveragingThis strategy is based on the Money Flow Index (MFI) and aims to enter a long position when the MFI exits an oversold zone, with specific rules for limit orders, stop-loss, and take-profit settings. Here's a detailed breakdown:
Key Components
1. **Money Flow Index (MFI)**: The strategy uses the MFI, a volume-weighted indicator, to gauge whether the market is in an oversold condition (default threshold of MFI < 20). Once the MFI rises above the oversold threshold, it signals a potential buying opportunity.
2. **Limit Order for Long Entry**: Instead of entering immediately after the oversold condition is cleared, the strategy places a limit order at a price slightly below the current price (by a user-defined percentage). This helps achieve a better entry price.
3. **Stop-Loss and Take-Profit**:
- **Stop-Loss**: A stop-loss is set to protect against significant losses, calculated as a percentage below the entry price.
- **Take-Profit**: A take-profit target is set as a percentage above the entry price to lock in gains.
4. **Order Cancellation**: If the limit order isn’t filled within a specific number of bars (default is 5 bars), it’s automatically canceled to avoid being filled at a potentially suboptimal price as market conditions change.
Strategy Workflow
1. **Identify Oversold Zone**: The strategy checks if the MFI falls below a defined oversold level (default is 20). Once this condition is met, the flag `inOversoldZone` is set to `true`.
2. **Wait for Exit from Oversold Zone**: When the MFI rises back above the oversold level, it’s considered a signal that the market is potentially recovering, and the strategy prepares to enter a position.
3. **Place Limit Order**: Upon exiting the oversold zone, the strategy places a limit order for a long position at a price below the current price, defined by the `Long Entry Percentage` parameter.
4. **Monitor Limit Order**: A counter (`barsSinceEntryOrder`) starts counting the bars since the limit order was placed. If the order isn’t filled within the specified number of bars, it’s canceled automatically.
5. **Set Stop-Loss and Take-Profit**: Once the order is filled, a stop-loss and take-profit are set based on user-defined percentages relative to the entry price.
6. **Exit Strategy**: The trade will close automatically when either the stop-loss or take-profit level is hit.
Advantages
- **Risk Management**: With configurable stop-loss and take-profit, the strategy ensures losses are limited while capturing profits at pre-defined levels.
- **Controlled Entry**: The use of a limit order below the current price helps secure a better entry point, enhancing risk-reward.
- **Oversold Exit Trigger**: Using the exit from an oversold zone as an entry condition can help catch reversals.
Disadvantages
- **Missed Entries**: If the limit order isn’t filled due to insufficient downward movement after the oversold signal, potential opportunities may be missed.
- **Dependency on MFI Sensitivity**: As the MFI is sensitive to both price and volume, its fluctuations might not always accurately represent oversold conditions.
Overall Purpose
The strategy is suited for traders who want to capture potential reversals after oversold conditions in the market, with a focus on precise entries, risk management, and an automated exit plan.
Velocity/Volatility/Volume StrategyThe "Vel/Vty/Vol Strategy" is a momentum-based trading approach designed to take advantage of strong price movements that are confirmed by both volatility and volume (if enabled). It provides a high level of customization, allowing traders to adjust various settings based on market conditions and individual preferences. By combining three critical indicators—velocity, volatility (measured through Bollinger Band Width), and an optional volume filter—the strategy generates trade signals for both long and short positions. Here’s a comprehensive explanation of how the strategy works, how the parameters can be customized, and how those adjustments benefit users.
At its core, the strategy focuses on velocity, which measures the speed at which price is changing over time. This is a key indicator of momentum, with a "StrongUp" signal indicating bullish momentum and a "StrongDown" signal suggesting bearish momentum. In addition to velocity, the strategy factors in acceleration, which helps gauge whether momentum is building or weakening. The second essential component is Bollinger Band Width (BBW), which measures volatility in the market. When the BBW expands, it signals increasing volatility, a condition that must be met in combination with a velocity signal to generate a trade. Lastly, the strategy includes an optional Volume Oscillator to filter trades. When this volume filter is enabled, trades will only be executed if there’s an increase in volume, further validating market activity.
The strategy generates long and short trade signals based on specific conditions. A long trade is triggered when there is a strong upward velocity, accompanied by an increase in Bollinger Band Width, indicating both momentum and heightened volatility. If the volume filter is toggled on, a rise in volume must also confirm the signal. Similarly, a short trade is initiated when a strong downward velocity is detected, again paired with an increase in volatility and, optionally, a volume rise. This ensures that trades occur during periods of heightened market activity, reducing the likelihood of false signals.
To help manage risk, the strategy includes several customizable tools. Users can set take profit levels to automatically close positions and lock in gains once a predefined profit percentage is reached. For example, if a 2% take profit is set, a long position will be closed once the price has risen by 2%. Additionally, a trailing take profit option can be enabled, allowing the strategy to dynamically adjust the take-profit target as the market moves in the user’s favor. This ensures that profits are locked in as long as the market continues to trend positively, while providing protection in case of a reversal. The strategy also includes a trailing stop-loss feature, which adjusts the stop price as the market moves in favor of the trade, helping to minimize losses and protect gains.
The strategy offers a variety of parameters that can be customized to suit different trading styles and market conditions. The velocity lookback period controls how far back the strategy looks to calculate velocity. A shorter lookback makes the strategy more sensitive to recent price changes, generating more signals, which can benefit day traders or those seeking to capture short-term price swings. Conversely, a longer lookback smooths out the velocity calculation, reducing false signals and making the strategy more suitable for traders seeking to capture larger trends. Similarly, the Bollinger Band Width (BBW) length can be adjusted to control how far back the strategy looks to calculate volatility. A shorter BBW length makes the strategy more sensitive to volatility spikes, useful in rapidly changing markets. In contrast, a longer BBW length filters out short-term noise and focuses on more sustainable volatility shifts, better suited for slower, more stable markets.
The volume filter is another powerful feature that can be toggled on or off. When turned on, the strategy will only execute trades if there is an increase in volume alongside velocity and volatility signals. This helps filter out false signals in low-volume markets, ensuring that price movements are supported by actual market activity. If the volume filter is turned off, the strategy focuses purely on price and volatility changes, which can be useful in markets where volume data is unreliable or less relevant.
The take profit percentage can be adjusted to define how aggressively or conservatively profits are locked in. A lower take profit percentage allows traders to capture smaller, quicker profits, which can be advantageous in volatile markets. A higher take profit percentage suits traders who prefer to capture larger moves, allowing them to stay in trades longer to benefit from extended trends. Similarly, the trailing take profit percentage determines how tightly the strategy follows market prices as they move in favor of the trade. A tighter trailing percentage ensures that profits are locked in quickly, while a wider trailing percentage gives trades more room to run, ideal for capturing large trends.
The stop loss percentage is another key setting that controls how much risk a trader is willing to take before the position is closed. A tighter stop loss minimizes losses but may result in more frequent stop-outs, particularly in volatile markets. A wider stop loss provides more room for trades to develop, which is useful for traders aiming to capture longer trends despite short-term fluctuations. Additionally, the velocity thresholds can be adjusted to set how sensitive the strategy is to price movements. Lower thresholds increase sensitivity, generating more signals in fast-moving markets, while higher thresholds filter out weaker signals, focusing on larger momentum shifts.
The strategy also allows users to define a time range during which it is active, offering flexibility in backtesting and optimizing for specific market conditions. By limiting the strategy to certain periods, users can tailor it to seasonal trends or historical data that matches their current trading environment.
The flexibility of this strategy makes it suitable for a wide range of traders. Day traders can benefit from adjusting the velocity and BBW lookback periods, tightening take profit and stop loss settings to capture short, fast price movements in highly volatile markets. Trend traders can lengthen the lookback periods and widen the velocity thresholds to capture larger, sustained moves while riding out short-term volatility. Traders with a lower risk tolerance can enable the volume filter and tighten stop losses to reduce false signals and minimize losses. On the other hand, aggressive traders can widen the take profit and trailing stop percentages to allow trades to develop fully, maximizing potential gains in trending markets.
Central Pivot Point Cross & Retrace Strategy // AlgoFyreThe Central Pivot Point Cross & Retrace Strategy uses pivot points for trend identification and trade entry. It combines accumulation/distribution indicators with pivot point levels to generate signals. The strategy incorporates dynamic position sizing based on a fixed risk amount and allows for both long and short positions with customizable stop-loss levels.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Pivot Point-Based Trading
🔸Accumulation/Distribution
🔸Dynamic Position Sizing
🔸Customizable Risk Management
🔶 FUNCTIONALITY
🔸Indicators
🞘 Pivot Points
🞘 Accumulation/Distribution
🔸Conditions
🞘 Long Entry
🞘 Short Entry
🞘 Take Profit
🞘 Stop Loss
🔶 INSTRUCTIONS
🔸Adding the Strategy to the Chart
🔸Configuring the Strategy
🔸Backtesting and Practice
🔸Market Awareness
🔸Visual Customization
🔶 CONCLUSION
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🔶 ORIGINALITY The Central Pivot Point Cross & Retrace Strategy uniquely combines pivot point analysis with accumulation/distribution indicators to identify optimal entry and exit points. It employs dynamic position sizing based on a fixed risk amount, ensuring consistent risk management across trades. This approach allows traders to adapt to varying market conditions by adjusting position sizes according to predefined risk parameters, enhancing both flexibility and control in trading decisions. The strategy's integration of customizable stop-loss levels further refines its risk management capabilities.
🔸Pivot Point-Based Trading This strategy utilizes daily pivot points to identify key support and resistance levels, providing a framework for trend identification and trade entry. The central pivot point serves as the intraday point of balance between buyers and sellers, with the largest amount of trading volume assumed to take place in this area.
🔸Accumulation/Distribution The strategy incorporates the Accumulation/Distribution (A/D) line, an underrated volume-based indicator, to establish the main trend. The A/D line is used in conjunction with a trend based indicator like the 200-period Exponential Moving Average (EMA) to confirm trend direction and strength.
🔸Dynamic Position Sizing Position sizes are calculated dynamically based on a fixed risk amount, allowing traders to maintain consistent risk exposure across trades.
🔸Customizable Risk Management Traders can set flexible risk-reward ratios and adjust stop-loss and take-profit levels, tailoring the strategy to their risk tolerance and market conditions. The strategy recommends taking partial profits at S1 or R1 levels and moving the stop-loss to break-even for remaining positions.
🔶 FUNCTIONALITY The Central Pivot Point Cross & Retrace Strategy leverages pivot points and accumulation/distribution indicators to identify optimal trading opportunities. This strategy is designed to capitalize on price movements around key pivot levels by dynamically adjusting position sizes based on predefined risk parameters. It allows traders to manage risk effectively while taking advantage of both long and short positions.
🔸Indicators 🞘 Pivot Points: Calculates daily pivot points (PP, R1, R2, S1, S2) to identify key support and resistance levels. The central pivot point is crucial for determining market bias and entry points.
🞘 Accumulation/Distribution: Uses the A/D line and with a trend based indicator like the 200 EMA to determine market direction and trend strength. This combination helps eliminate noise and provides more reliable trend signals. We recommend using the Adaptive MAs (Hurst, CVaR, Fractal) // AlgoFyre , but any moving average could be used.
🔸Conditions 🞘 Long Entry: Initiates a long position when the price crosses above the central pivot point (PP), retraces back to it and the A/D line is above its 200 EMA, indicating an uptrend. A limit entry order is set at the PP for entering the long trade.
🞘 Short Entry: Initiates a short position when the price crosses below the central pivot point (PP), retraces back to it and the A/D line is below its 200 EMA, indicating a downtrend. A limit entry order is set at the PP for entering the short trade.
🞘 Take Profit: 50% of the position is closed as profit when R1 for Longs and S1 for Shorts is reached. The position is fully closed when R2 for Longs and S2 for Shorts is reached.
🞘 Stop Loss: Stop loss is set via strategy settings. When the first 50% take profit for both long and shorts is taken, stop loss for both will be moved to break-even/entry.
🔶 INSTRUCTIONS
The Central Pivot Point Cross & Retrace Strategy can be set up by adding it to your TradingView chart and configuring parameters such as the accumulation/distribution source, stop-loss percentage, and risk management settings. This strategy is designed to capitalize on price movements around key pivot levels by dynamically adjusting position sizes based on predefined risk parameters. Enhance the accuracy of signals by combining this strategy with additional indicators like trend-following or momentum-based tools. Adjust settings to better manage risk and optimize entry and exit points.
🔸Adding the Strategy to the Chart Go to your TradingView chart.
Click on the "Pine Editor" button at the bottom of the chart.
Copy and paste the strategy code into the Pine Editor.
Click "Add to Chart" to apply the strategy.
Add the technical indicator "Accumulation/Distribution" to the chart.
Add the trend indicator " Adaptive MAs (Hurst, CVaR, Fractal) // AlgoFyre " or any other MA to the chart and move it to the "Accumulation/Distribution" pane.
Set the source of your trend indicator to "Accumulation/Distribution".
🔸Configuring the Strategy Open the strategy settings by clicking on the gear icon next to its name on the chart.
Accumulation/Distribution Source: Select the source for the accumulation/distribution indicator.
Accumulation/Distribution EMA Source: Select the source for the trend indicator.
Stop Loss Percentage: Set the stop loss distance from the pivot point as a percentage.
Risk Amount: Define the fixed risk amount for position sizing.
Base Order Size: Set the base order size for position calculations.
Number of Positions: Specify the maximum number of positions allowed.
Time Frame: Adjust the time frame based on the currency pair or asset being traded (e.g., 15-minute for EUR/USD, 30-minute for GBP/USD).
🔸Backtesting and Practice Backtest the strategy on historical data to understand how it performs in various market environments.
Practice using the strategy on a demo account before implementing it in live trading.
Test different time frames and asset pairs to find the most suitable combinations.
🔸Market Awareness Keep an eye on market news and events that might cause extreme price movements. The strategy reacts to price data and might not account for news-driven events that can cause large deviations.
Remember that this strategy is not recommended for stocks due to the A/D line's inability to account for gaps in its calculation.
🔸Visual Customization Visualization Settings: Customize the display of entry price, take profit, and stop loss levels.
Color Settings: Switch to the AlgoFyre theme or set custom colors for bullish, bearish, and neutral states.
Table Settings: Enable or disable the information table and adjust its position.
🔶 CONCLUSION
The Central Pivot Point Cross & Retrace Strategy provides a robust framework for capitalizing on price movements around key pivot levels by combining pivot point analysis with accumulation/distribution indicators. This strategy leverages pivot point crossovers to identify entry points and utilizes the A/D line crossover with its 200 EMA for trend confirmation, ensuring trades align with prevailing market conditions. By incorporating dynamic position sizing based on a fixed risk amount, traders can effectively manage risk and adapt to varying market conditions. The strategy's focus on trading around the central pivot point and its customizable stop-loss and take-profit levels further enhance its risk management capabilities, making it a versatile tool for both trending and ranging markets. With its strategic blend of technical indicators and risk management, the Central Pivot Point Cross & Retrace Strategy offers traders a comprehensive approach to optimizing trade execution and maximizing potential returns across various currency pairs and commodities.
XAU/USD Strategy with Correct ADX and Bollinger Bands Fill1. *Indicators Used*:
- *Exponential Moving Averages (EMAs)*: Two EMAs (20-period and 50-period) are used to identify the trend direction and potential entry points based on crossovers.
- *Relative Strength Index (RSI)*: A momentum oscillator that measures the speed and change of price movements. It identifies overbought and oversold conditions.
- *Bollinger Bands*: These consist of a middle line (simple moving average) and two outer bands (standard deviations away from the middle). They help to identify price volatility and potential reversal points.
- *Average Directional Index (ADX)*: This indicator quantifies trend strength. It's derived from the Directional Movement Index (DMI) and helps confirm the presence of a strong trend.
- *Average True Range (ATR)*: Used to calculate position size based on volatility, ensuring that trades align with the trader's risk tolerance.
2. *Entry Conditions*:
- *Long Entry*:
- The 20 EMA crosses above the 50 EMA (indicating a potential bullish trend).
- The RSI is below the oversold level (30), suggesting the asset may be undervalued.
- The price is below the lower Bollinger Band, indicating potential price reversal.
- The ADX is above a specified threshold (25), confirming that there is sufficient trend strength.
- *Short Entry*:
- The 20 EMA crosses below the 50 EMA (indicating a potential bearish trend).
- The RSI is above the overbought level (70), suggesting the asset may be overvalued.
- The price is above the upper Bollinger Band, indicating potential price reversal.
- The ADX is above the specified threshold (25), confirming trend strength.
3. *Position Sizing*:
- The script calculates the position size dynamically based on the trader's risk per trade (expressed as a percentage of the total capital) and the ATR. This ensures that the trader does not risk more than the specified percentage on any single trade, adjusting the position size according to market volatility.
4. *Exit Conditions*:
- The strategy uses a trailing stop-loss mechanism to secure profits as the price moves in the trader's favor. The trailing stop is set at a percentage (1.5% by default) below the highest price reached since entry for long positions and above the lowest price for short positions.
- Additionally, if the RSI crosses back above the overbought level while in a long position or below the oversold level while in a short position, the position is closed to prevent losses.
5. *Alerts*:
- Alerts are set to notify the trader when a buy or sell condition is met based on the strategy's rules. This allows for timely execution of trades.
### Summary
This strategy aims to capture significant price movements in the XAU/USD market by combining trend-following (EMAs, ADX) and momentum indicators (RSI, Bollinger Bands). The dynamic position sizing based on ATR helps manage risk effectively. By implementing trailing stops and alert mechanisms, the strategy enhances the trader's ability to act quickly on opportunities while mitigating potential losses.
Custom Buy BID StrategyThis Pine Script strategy is designed to identify and capitalize on upward trends in the market using the Average True Range (ATR) as a core component of the analysis. The script provides the following features:
Customizable ATR Calculation: Users can switch between different methods of ATR calculation (traditional or simple moving average).
Adjustable Parameters: The strategy allows for adjustable ATR periods, ATR multipliers, and custom time windows for executing trades.
Buy Signal Alerts: The strategy generates buy signals when the market shifts from a downtrend to an uptrend, based on ATR and price action.
Profit and Stop-Loss Management: Built-in take profit and stop-loss conditions are calculated as a percentage of the entry price, allowing for automatic position management.
Visual Enhancements: The script highlights the uptrend with green lines and optionally colors bars to help visualize market direction.
Flexible Timeframe: Users can configure a specific date range to activate the strategy, offering more control over when trades are executed.
This strategy is ideal for traders looking to automate their buy entries and manage risk with a straightforward trend-following approach. By utilizing customizable settings, it adapts to various market conditions and timeframes.
Nifty scalping 3 minutes options on Dhan
Strategy Description for Publishing: Nifty Scalping 3 Minutes Options on Dhan
Overview:
The Nifty Scalping 3 Minutes Options on Dhan strategy is an enhanced version tailored for trading Nifty Options, building on the core logic used in the previously published Nifty Scalping 3 Minutes Strategy. This strategy provides automated order execution via JSON alerts for seamless integration with the Dhan platform, enabling hands-free options trading.
This system is designed to capture short-term market moves using a combination of technical indicators like the Jurik Moving Average (JMA), Exponential Moving Average (EMA), and Bollinger Bands, while also allowing traders to manage risk effectively with custom inputs for maximum loss per lot and partial profit booking.
For more details on the core logic and performance of the strategy, please refer to our earlier published strategy:
Nifty Scalping 3 Minutes Strategy
Key Features:
JMA and EMA Crossovers: Trades are executed when the Jurik Moving Average (JMA) crosses over (for long trades) or under (for short trades) the Exponential Moving Average (EMA), signaling trend direction.
Price-Volume Spike Detection: Ensures that trades are executed only when significant market activity is detected, avoiding low-momentum conditions. Price-volume relationships are monitored to confirm the strength of market movements.
Bollinger Band Noise Filter: Filters out low-volatility periods by executing trades only when prices break through the upper or lower Bollinger Bands, confirming high volatility.
Customizable Risk Management: Traders can set their own maximum risk per lot (e.g., ₹650), and the strategy adjusts the stop-loss accordingly to ensure that no trade exceeds this threshold.
Partial Profit Booking: A predefined percentage (e.g., 60%) of the position can be booked as profit once the first profit target is reached, with the remaining position trailed using an ATR-based stop.
STBT/BTST Support: The strategy offers the flexibility to carry trades overnight, supporting Sell Today, Buy Tomorrow (STBT) and Buy Today, Sell Tomorrow (BTST).
Time-Based Exit: The strategy automatically closes any open positions by 3:20 PM to avoid the volatile end-of-day market conditions.
Inputs for Traders:
Option Quantity: Select the number of contracts to trade (e.g., 10).
Maximum Risk Per Lot: Set your maximum allowable loss per lot (e.g., ₹650), ensuring that your risk is managed effectively.
Partial Profit Booking Percentage: Define what percentage of your position to book as profit (e.g., 60%) when the first target is hit.
STBT/BTST Option: Choose whether to allow positions to be carried overnight.
Alert Secret Key: Input your secret key for the Dhan platform to trigger automated orders via JSON alerts.
Option Expiry Date: Specify the expiry date for the options being traded.
Trade Logic:
Long Trades: Triggered when JMA crosses above EMA, supported by filters like price-volume spikes and Bollinger Band breakouts. The strategy waits for momentum confirmation before entering long trades, with stop-loss and profit-taking mechanisms in place.
Short Trades: Triggered when JMA crosses below EMA, with confirmation through additional filters to ensure strong market trends before entering short positions.
Risk Management:
Stop-Loss: A dynamic stop-loss is placed for each trade based on the trader's maximum risk per lot. The stop-loss adapts to market conditions using ATR trailing stops to capture further gains as the trade progresses.
Partial Profit Booking: Once the first profit target is hit (2.1x risk for long trades and 2.5x risk for short trades), a percentage of the position is booked as profit, and the remainder is trailed using an ATR stop.
Automation via JSON Alerts:This strategy sends automated JSON alerts to the Dhan platform for seamless execution of orders. The alerts support multi-leg orders for both entry and exit, ensuring that trades are executed efficiently without manual intervention.
Why Use This Strategy?
The Nifty Scalping 3 Minutes Options on Dhan strategy is perfect for traders who want to capitalize on quick market moves in options, backed by strong risk management and automation. With automated alerts, customizable inputs, and advanced technical filters, this strategy is ideal for traders looking to engage in high-probability options trades with minimal effort.
For more detailed information about the underlying logic, you can refer to the previously published Nifty Scalping 3 Minutes Strategy here.
Disclaimer:
This strategy is provided as an educational tool, and we are not affiliated with or sponsored by Dhan. The strategy integrates with the Dhan platform for automated trading, but there is no formal relationship between this strategy and Dhan.
TRIN (Arms Index) Trading StrategyThe TRIN (Arms Index), also known as the Short-Term Trading Index, is a technical indicator designed to gauge the internal strength or weakness of the market. It compares the number of advancing and declining stocks to the advancing and declining volume (AD Volume). A TRIN value above 1.0 generally indicates bearish market conditions, while a value below 1.0 suggests bullish market sentiment.
Strategy Rules:
Entry Condition (Long Position): When the TRIN value is above 1.0, the strategy enters a long position, indicating that the market may be oversold, and a potential reversal could occur.
Exit Condition: The strategy exits the long position when the closing price is higher than the previous day’s high, signaling a potential rebound in the market.
This strategy aims to capitalize on short-term market inefficiencies by entering trades during periods of potential market weakness and exiting when signs of recovery appear.
How the TRIN Index Works:
The TRIN is calculated as follows:
TRIN=Advancing Issues / Declining IssuesAdvancing Volume / Declining Volume
TRIN=Advancing Volume / Declining VolumeAdvancing Issues / Declining Issues
A TRIN value above 1.0 indicates that the market is potentially oversold (more declining stocks with higher volume), while a value below 1.0 suggests the market may be overbought (more advancing stocks with higher volume) .
Empirical Evidence:
Market Sentiment Indicator: The TRIN has been widely used as a sentiment indicator. Research by Zweig (1997) suggests that extreme TRIN values can serve as a contrarian signal, indicating potential turning points in the market. For instance, a TRIN above 2.0 is often considered a sign of panic selling, which can precede a market bottom .
Overbought/Oversold Conditions: Studies have shown that indicators like TRIN, which measure market breadth and volume, can be effective in identifying overbought and oversold conditions. According to Fama and French (1988), market sentiment indicators that consider both price and volume data can offer insights into future price movements .
Risks and Limitations:
False Signals:
One of the primary risks of using the TRIN-based strategy is the possibility of false signals. A TRIN value above 1.0 does not always guarantee a market rebound, especially in sustained bearish trends. In such cases, the strategy might enter long positions prematurely, leading to losses.
Research by Brock, Lakonishok, and LeBaron (1992) found that while market indicators like TRIN can be useful, they are not foolproof and can generate multiple false positives, particularly in volatile markets .
Market Regimes:
The effectiveness of the TRIN index can vary depending on the market regime. In strongly trending markets, either bullish or bearish, the TRIN may not provide reliable reversal signals, and relying on it could result in trades that go against the prevailing trend. For instance, during strong bear markets, the TRIN may frequently remain above 1.0, leading to multiple losing trades as the market continues to decline.
Short-Term Focus:
The TRIN strategy is inherently short-term focused, aiming to capture quick market reversals. This makes it sensitive to market noise and less effective for longer-term investors. Moreover, short-term trading strategies often require more frequent adjustments and can incur higher transaction costs, which may erode profitability over time.
Liquidity and Execution Risk:
Since the TRIN strategy requires entering and exiting trades based on short-term market movements, it is vulnerable to liquidity and execution risks. In fast-moving markets, the execution of trades may be delayed, leading to slippage and potentially unfavorable entry or exit points.
Conclusion:
The TRIN (Arms Index) Trading Strategy can be an effective tool for traders looking to capitalize on short-term market inefficiencies and potential reversals. However, it is important to recognize the risks associated with this strategy, including false signals, sensitivity to market regimes, and execution risks. Traders should employ proper risk management techniques and consider combining the TRIN with other indicators to improve the robustness of the strategy.
While the TRIN provides valuable insights into market sentiment, it is not a standalone solution and should be used in conjunction with a broader trading plan that takes into account both technical and fundamental analysis.
References:
Arms, Richard W. "Volume Adjusted Moving Averages." Technical Analysis of Stocks & Commodities, 1993.
Zweig, Martin. Winning on Wall Street. Warner Books, 1997.
Fama, Eugene F., and Kenneth R. French. "Permanent and Temporary Components of Stock Prices." Journal of Political Economy, 1988.
Brock, William, Josef Lakonishok, and Blake LeBaron. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns." Journal of Finance, 1992.
Nifty scalping 3 minutesOverview:
The "Nifty Scalping 3 Minutes" strategy is a uniquely tailored trading system for Nifty Futures traders, with a clear focus on capital preservation, dynamic risk management, and high-probability trade entries. This strategy uses unique combination of standard technical indicators like Jurik Moving Average (JMA), Exponential Moving Average (EMA), and Bollinger Bands, but it truly stands out through its Price-Volume Spike Detection system—a unique mechanism designed to trigger trades only during periods of high momentum and market participation. The strategy also incorporates robust risk management, ensuring that traders minimize losses while maximizing profits. in complete back test range max drawdown is less than 1%
Scalping Approach and Requirements:
The strategy focuses on quick in and out trades, aiming to capture small, quick profits during periods of heightened market activity. For optimal performance, traders should have ₹2,00,000 or more in capital available per trade. The dynamic lot calculation and risk controls require this level of capital to function effectively.
Small, frequent trades are the focus, and the strategy is ideal for traders comfortable with high-frequency executions. Traders with insufficient capital or those not comfortable with frequent trades may find this strategy unsuitable.
Default Properties for Publication:
Initial Capital: ₹2,000,000
Lot Size: 25 contracts (adjusted dynamically based on available margin)
Stop-Loss: Risk per trade capped at 1% of equity.
Slippage and Commission: Realistic values are factored into the backtesting.
Key Feature: Price-Volume Spike Detection
1. Condition: Trades are executed only when there is a significant price spike confirmed by a volume spike. The candle width is calculated by multiplying the price change (difference between the candle's open and close) by the volume, and this result is compared to a 126-period average of both price and volume.
A trade is triggered when the current price-volume spike exceeds this average by a preset volume multiplier (default set at 3). This ensures that both the price change and volume are unusually strong compared to normal market behavior.
2. Reasoning: Many traders fail to incorporate the relationship between price movement and volume effectively. By using this Price-Volume Spike Detection mechanism, the strategy ensures that it only enters trades during periods of strong market momentum when both price and volume confirm a real market move, not just noise or small fluctuations.
The 126-period moving average of volume is chosen specifically because it represents a complete trading session on the 3-minute chart. This ensures that the volume spike is compared against a realistic baseline of daily activity, making the detection more robust and reliable.
The volume multiplier allows flexibility in determining the threshold for a significant spike, enabling users to fine-tune the strategy according to their risk tolerance and market conditions.
Trade Placement Logic:
1. Trend Confirmation with JMA and EMA:
Condition: The strategy will only consider entering a trade when JMA crosses above EMA for a long trade or JMA crosses below EMA for a short trade.
Reasoning: The JMA is used for its low lag and responsiveness, allowing it to capture early trends, while the EMA adds a level of confirmation by weighing recent price action more heavily. This dual confirmation ensures that trades are entered only when a solid trend is in place.
2. Bollinger Bands for Volatility Breakouts:
Condition: In addition to the JMA-EMA crossover, the price must break outside the Bollinger Bands—above the upper band for long trades, or below the lower band for short trades.
Reasoning: Bollinger Bands are a volatility indicator. By requiring a price breakout beyond the bands, the strategy ensures that trades are placed during periods of high volatility, avoiding low-momentum, sideways markets.
3. Volume and Price Confirmation (Price-Volume Spike Detection):
Condition: A trade is only triggered if the price-volume spike condition is met. This ensures that the market move is backed by strong volume and that the price change is significant relative to the recent average activity.
Reasoning: This condition filters out low-volume environments where price movements are more likely to reverse or stall. By waiting for a spike in both price and volume, the strategy ensures that it enters trades during high-momentum periods, where follow-through is more likely.
Exit Logic and Risk Management:
1. Stop-Loss (SL) Placement:
Condition: Upon entering a trade, an initial stop-loss is placed below the candle low for long trades or above the candle high for short trades. This is adjusted if the risk exceeds 1% of total capital.
Reasoning: The stop-loss is placed at a logical level that accounts for recent price action, ensuring that the trade is given room to develop while protecting capital from unexpected market reversals.
2. Profit Target and Partial Profit Booking:
Condition: The first profit target is set at 2.1x the initial risk for long trades, and 2.5x the initial risk for short trades.
Reasoning: The 2.1x risk-reward ratio for long trades provides a solid return while maintaining a conservative risk profile. For short trades, the strategy uses a higher 2.5x risk-reward ratio because market falls tend to be sharper and quicker than rises, allowing for larger profit targets to be reached more reliably.
Partial Profit Booking: Once the first target is hit, 60% of the position is closed to lock in profits. The remaining 40% is left to run with a trailing stop.
3. ATR-Based Trailing Stop:
Condition: Once the first target is hit, the ATR (Average True Range) trailing stop is applied to the remaining position. This dynamically adjusts the stop-loss as the trade moves in a favorable direction.
Reasoning: The trailing stop allows the trade to capture further gains if the trend continues, while protecting profits if the momentum weakens. The ATR ensures that the stop adjusts according to the market's current volatility, providing flexibility and protection.
4. Time-Based Exit:
Condition: If a trade is still open by 3:20 PM, it is automatically closed to avoid end-of-day volatility.
Reasoning: The time-based exit ensures that trades are not held into the often-volatile closing minutes of the market, reducing the risk of unexpected price swings.
Capital and Risk Management:
1. Lot Size Calculation:
Condition: The strategy calculates the number of lots dynamically based on the available margin. It uses only 10% of total equity for each trade, and ensures that the maximum risk per trade does not exceed 1% of total capital.
Reasoning: This ensures that traders are not over-leveraged and that the risk is controlled for each trade. Capital protection is at the core of the strategy, ensuring that even during adverse market conditions, the trader’s capital is preserved.
2. Stop-Loss Protection:
Condition: The stop-loss is designed to ensure that no more than 1% of capital is at risk in any trade.
Reasoning: By limiting risk exposure, the strategy focuses on long-term capital preservation while still allowing for profitable trades in favorable market conditions.
STBT/BTST Facilitation:
1. Feature: The strategy allows traders the option to hold positions overnight, facilitating STBT (Sell Today Buy Tomorrow) and BTST (Buy Today Sell Tomorrow) trades.
Reasoning: Backtests show that holding positions overnight when all trade conditions are still valid can lead to beneficial outcomes. This feature allows traders to take advantage of overnight market movements, providing flexibility beyond intraday trades.
Why This Strategy Stands Out:
Price-Volume Spike Detection: Unlike traditional strategies, this one uniquely focuses on Price-Volume Spike Detection to filter out low-probability trades. By ensuring that both price and volume spikes are present, the strategy guarantees that trades are placed only when there is significant market momentum.
Risk Management with Capital Protection: The strategy strictly limits the risk per trade to 1% of capital, ensuring long-term capital preservation. This is especially important for traders who wish to avoid large drawdowns and prefer a sustainable approach to trading.
2.5x Risk-Reward for Short Trades: Recognizing the sharpness of market declines, the strategy employs a 2.5x risk-reward ratio for short trades, maximizing profits during bearish trends.
Dynamic Exit Strategy: With partial profit booking and ATR-based trailing stops, the strategy is designed to capture gains efficiently while protecting capital through dynamic exit conditions.
Summary of Execution:
Entry: Triggered when JMA crosses EMA, combined with Bollinger Band breakouts and Price-Volume Spike Detection.
Capital Management: Trades are executed with 10% of available capital, and the risk per trade is capped at 1%.
Exit: Trades exit when stop-loss, ATR trailing stop, or time-based exit conditions are met.
Profit Booking: 60% of the position is closed at the first target, with the remainder trailed using an ATR-based stop.
Price-Volume w Trendline - Strategy [presentTrading]█ Introduction and How it is Different
The Price-Volume with Trendline Strategy is an innovative strategy that combines volume profile analysis, price-based Z-scores, and dynamic trendline filtering to identify optimal entry and exit points in the market. What sets this strategy apart is the integration of volume concentration (Point of Control or PoC) with dynamic volatility thresholds. Additionally, this strategy introduces a multi-step take profit (TP) mechanism that adjusts based on predefined levels, allowing traders to exit trades progressively while capitalizing on market momentum.
BTCUSD 6hr LS Performance
█ Strategy, How it Works: Detailed Explanation
The combination of multiple indicators and methodologies serves to create a more robust and reliable trading system. Each element is carefully chosen for its complementary role in providing accurate signals while minimizing false entries and exits. Here’s why the different components were chosen and how they work together:
- PoC and Z-Scores: The volume profile identifies key price areas, while the Z-score measures deviations from the mean. Together, they highlight points where the market is likely to react. For example, when the Z-score indicates an oversold condition near a PoC support level, it increases the probability of a reversal, providing a clear entry signal.
- Trendlines and Z-Scores: Trendlines serve as a secondary filter to ensure that price deviations identified by Z-scores align with broader market trends. This ensures that trades are only entered when the price has both deviated from its average and broken through a significant trendline level, reducing the likelihood of false signals.
- Multi-Step TP and Risk Management: Finally, the multi-step take profit logic works in tandem with the entry signals generated by the PoC, Z-scores, and trendlines. As the price moves in favor of the trade, profits are gradually locked in, ensuring the trader captures gains while still leaving room for further upside.
🔶 Point of Control (PoC) and Volume Profile Analysis
The PoC identifies the price level with the highest volume concentration within a specified lookback period. This price level represents where the most trading activity has occurred, often acting as a strong support or resistance. By breaking down the range into several rows (bins), the strategy identifies how much volume was traded at each price level.
🔶 Z-Score Calculation
The Z-score is a statistical metric that measures how far the current price is from its mean, expressed in terms of standard deviations. This is calculated both for price deviation and PoC-based deviation.
🔶 Trendline Breakout Filtering
The trendline filtering is a crucial aspect that refines entry signals by confirming trend continuation or reversals. It calculates trendlines based on pivot highs and lows using the selected method (e.g., ATR or standard deviation).
🔶 Multi-Step Take Profit
The multi-step take profit mechanism allows the strategy to take partial profits at several predefined levels. For example, when the price reaches 3%, 8%, 14%, or 21% above (or below) the entry price, it exits portions of the position. This is a useful technique for locking in profits as the market moves favorably.
Local
█ Usage
The Price-Volume with Trendline Strategy can be applied to various asset classes, including stocks, cryptocurrencies, and commodities. It is particularly effective in volatile markets where price deviations and volume concentrations signal potential reversals or trend continuations. By adjusting the settings for volatility and the lookback period, this strategy can be tailored to both short-term intraday trades and longer-term swing trades.
█ Default Settings
The default settings in the strategy play a vital role in shaping its performance.
- POC_lookbackLength (144): This defines the number of bars used to calculate the PoC. A longer lookback captures more data, leading to a more stable PoC, but may result in delayed signals. A shorter lookback increases responsiveness but may introduce noise.
- priceDeviationLength (200): This determines the period for calculating the standard deviation of price. A higher length smooths out the volatility, reducing the likelihood of false signals. Shorter lengths make the strategy more sensitive to sudden price movements.
- TL_length (14): Controls the swing detection period for trendline calculation. A shorter length will generate more frequent trendline breakouts, while a longer length captures only significant moves.
- Stop Loss and Take Profit: The strategy offers both fixed and SuperTrend-based stop losses. SuperTrend is adaptive to volatility, while fixed stop losses provide simpler risk control. The multi-step take profit ensures that profits are secured progressively, which can improve performance in trending markets by reducing the risk of full reversals.
Each of these settings can significantly affect the strategy’s risk-reward balance. For instance, increasing the stop loss level or the take profit percentages allows the strategy to stay in trades longer, potentially increasing profit per trade but at the cost of larger drawdowns. Conversely, tighter stops and smaller profit targets result in more frequent trades with lower average profit per trade.
PVT Crossover Strategy**Release Notes**
**Strategy Name**: PVT Crossover Strategy
**Purpose**: This strategy aims to capture entry and exit points in the market using the Price-Volume Trend (PVT) and its Exponential Moving Average (EMA). It specifically uses the crossover of PVT with its EMA as signals to identify changes in market trends.
**Uniqueness and Usefulness**
**Uniqueness**: This strategy is unique in its use of the PVT indicator, which combines price changes with trading volume to track trends. The filtering with EMA reduces noise and provides more accurate signals compared to other indicators.
**Usefulness**: This strategy is effective for traders looking to detect trend changes early. The signals based on PVT and its EMA crossover work particularly well in markets where volume fluctuations are significant.
**Entry Conditions**
**Long Entry**:
- **Condition**: A crossover occurs where PVT crosses above its EMA.
- **Signal**: A buy signal is generated, indicating a potential uptrend.
**Short Entry**:
- **Condition**: A crossunder occurs where PVT crosses below its EMA.
- **Signal**: A sell signal is generated, indicating a potential downtrend.
**Exit Conditions**
**Exit Strategy**:
- The strategy does not explicitly program exit conditions beyond the entry signals, but traders are encouraged to close positions manually based on signals or apply their own risk management strategy.
**Risk Management**
This strategy does not include default risk management rules, so traders should implement their own. Consider using trailing stops or fixed stop losses to manage risk.
**Account Size**: ¥100,000
**Commissions and Slippage**: 94 pips per trade for commissions and 1 pip for slippage
**Risk per Trade**: 10% of account equity
**Configurable Options**
**Configurable Options**:
- **EMA Length**: The length of the EMA used to calculate the EMA of PVT (default is 20).
- **Signal Display Control**: The option to turn the display of signals on or off.
**Adequate Sample Size**
To ensure the robustness and reliability of this strategy, it is recommended to backtest it with a sufficiently long period of historical data, especially across different market conditions.
**Credits**
**Acknowledgments**:
This strategy is based on the concept of the PVT indicator and its application in strategy design, drawing on contributions from technical analysis and the trading community.
**Clean Chart Description**
**Chart Appearance**:
This strategy is designed to maintain a clean and simple chart by turning off the plot of PVT, its EMA, and entry signals. This reduces clutter and allows for more effective trend analysis.
**Addressing the House Rule Violations**
**Omissions and Unrealistic Claims**
**Clarification**:
This strategy does not make unrealistic or unsupported claims about its performance, and all signals are for educational purposes only, not guaranteeing future results. It is important to understand that past performance does not guarantee future outcomes.
