Divergence Strategy [Trendoscope®]🎲 Overview
The Divergence Strategy is a sophisticated TradingView strategy that enhances the Divergence Screener by adding automated trade signal generation, risk management, and trade visualization. It leverages the screener’s robust divergence detection to identify bullish, bearish, regular, and hidden divergences, then executes trades with precise entry, stop-loss, and take-profit levels. Designed for traders seeking automated trading solutions, this strategy offers customizable trade parameters and visual feedback to optimize performance across various markets and timeframes.
For core divergence detection features, including oscillator options, trend detection methods, zigzag pivot analysis, and visualization, refer to the Divergence Screener documentation. This description focuses on the strategy-specific enhancements for automated trading and risk management.
🎲 Strategy Features
🎯Automated Trade Signal Generation
Trade Direction Control : Restrict trades to long-only or short-only to align with market bias or strategy goals, preventing conflicting orders.
Divergence Type Selection : Choose to trade regular divergences (bullish/bearish), hidden divergences, or both, targeting reversals or trend continuations.
Entry Type Options :
Cautious : Enters conservatively at pivot points and exits quickly to minimize risk exposure.
Confident : Enters aggressively at the latest price and holds longer to capture larger moves.
Mixed : Combines conservative entries with delayed exits for a balanced approach.
Market vs. Stop Orders: Opt for market orders for instant execution or stop orders for precise price entry.
🎯 Enhanced Risk Management
Risk/Reward Ratio : Define a risk-reward ratio (default: 2.0) to set profit targets relative to stop-loss levels, ensuring consistent trade sizing.
Bracket Orders : Trades include entry, stop-loss, and take-profit levels calculated from divergence pivot points, tailored to the entry type and risk-reward settings.
Stop-Loss Placement : Stops are strategically set (e.g., at recent pivot or last price point) based on entry type, balancing risk and trade validity.
Order Cancellation : Optionally cancel pending orders when a divergence is broken (e.g., price moves past the pivot in the wrong direction), reducing invalid trades. This feature is toggleable for flexibility.
🎯 Trade Visualization
Target and Stop Boxes : Displays take-profit (lime) and stop-loss (orange) levels as boxes on the price chart, extending 10 bars forward for clear visibility.
Dynamic Trade Updates : Trade visualizations are added, updated, or removed as trades are executed, canceled, or invalidated, ensuring accurate feedback.
Overlay Integration : Trade levels overlay the price chart, complementing the screener’s oscillator-based divergence lines and labels.
🎯 Strategy Default Configuration
Capital and Sizing : Set initial capital (default: $1,000,000) and position size (default: 20% of equity) for realistic backtesting.
Pyramiding : Allows up to 4 concurrent trades, enabling multiple divergence-based entries in trending markets.
Commission and Margin : Accounts for commission (default: 0.01%) and margin (100% for long/short) to reflect trading costs.
Performance Optimization : Processes up to 5,000 bars dynamically, balancing historical analysis and real-time execution.
🎲 Inputs and Configuration
🎯Trade Settings
Direction : Select Long or Short (default: Long).
Divergence : Trade Regular, Hidden, or Both divergence types (default: Both).
Entry/Exit Type : Choose Cautious, Confident, or Mixed (default: Cautious).
Risk/Reward : Set the risk-reward ratio for profit targets (default: 2.0).
Use Market Order : Enable market orders for immediate entry (default: false, uses limit orders).
Cancel On Break : Cancel pending orders when divergence is broken (default: true).
🎯Inherited Settings
The strategy inherits all inputs from the Divergence Screener, including:
Oscillator Settings : Oscillator type (e.g., RSI, CCI), length, and external oscillator option.
Trend Settings : Trend detection method (Zigzag, MA Difference, External), MA type, and length.
Zigzag Settings : Zigzag length (fixed repaint = true).
🎲 Entry/Exit Types for Divergence Scenarios
The Divergence Strategy offers three Entry/Exit Type options—Cautious, Confident, and Mixed—which determine how trades are entered and exited based on divergence pivot points. This section explains how these settings apply to different divergence scenarios, with placeholders for screenshots to illustrate each case.
The divergence pattern forms after 3 pivots. The stop and entry levels are formed on one of these levels based on Entry/Exit types.
🎯Bullish Divergence (Reversal)
A bullish divergence occurs when price forms a lower low, but the oscillator forms a higher low, signaling a potential upward reversal.
💎 Cautious:
Entry : At the pivot high point for a conservative entry.
Exit : Stop-loss at the last pivot point (previous low that is higher than the current pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Entry : At the last pivot low, (previous low which is higher than the current pivot low) for an aggressive entry.
Exit : Stop-loss at recent pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
💎Mixed:
Entry : At the pivot high point (conservative).
Exit : Stop-loss at the recent pivot point that has resulted in lower low (lazy exit). Canceled if price breaks below the pivot.
Behavior : Balances entry caution with extended holding for trend continuation.
🎯Bearish Divergence (Reversal)
A bearish divergence occurs when price forms a higher high, but the oscillator forms a lower high, indicating a potential downward reversal.
💎Cautious:
Entry : At the pivot low point (lower high) for a conservative short entry.
Exit : Stop-loss at the previous pivot high point (previous high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident:
Entry : At the last price point (previous high) for an aggressive short entry.
Exit : Stop-loss at the pivot point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Enters early to maximize trend continuation, holding longer.
💎Mixed:
Entry : At the previous piot high point (conservative).
Exit : Stop-loss at the last price point (delayed exit). Canceled if price breaks above the pivot.
Behavior : Combines conservative entry with extended holding for downtrend gains.
🎯Bullish Hidden Divergence (Continuation)
A bullish hidden divergence occurs when price forms a higher low, but the oscillator forms a lower low, suggesting uptrend continuation. In case of Hidden bullish divergence, b]Entry is always on the previous pivot high (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the recent pivot low point (higher than previous pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Exit : Stop-loss at previous pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
🎯Bearish Hidden Divergence (Continuation)
A bearish hidden divergence occurs when price forms a lower high, but the oscillator forms a higher high, suggesting downtrend continuation. In case of Hidden Bearish divergence, b]Entry is always on the previous pivot low (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the latest pivot high point (which is a lower high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident/Mixed:
Exit : Stop-loss at the previous pivot high point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Uses the late exit point to hold longer.
🎲 Usage Instructions
🎯Add to Chart:
Add the Divergence Strategy to your TradingView chart.
The oscillator and divergence signals appear in a separate pane, with trade levels (target/stop boxes) overlaid on the price chart.
🎯Configure Settings:
Adjust trade settings (direction, divergence type, entry type, risk-reward, market orders, cancel on break).
Modify inherited Divergence Screener settings (oscillator, trend method, zigzag length) as needed.
Enable/disable alerts for divergence notifications.
🎯Interpret Signals:
Long Trades: Triggered on bullish or bullish hidden divergences (if allowed), shown with green/lime lines and labels.
Short Trades: Triggered on bearish or bearish hidden divergences (if allowed), shown with red/orange lines and labels.
Monitor lime (target) and orange (stop) boxes for trade levels.
Review strategy performance metrics (e.g., profit/loss, win rate) in the strategy tester.
🎯Backtest and Optimize:
Use TradingView’s strategy tester to evaluate performance on historical data.
Fine-tune risk-reward, entry type, position sizing, and cancellation settings to suit your market and timeframe.
For questions, suggestions, or support, contact Trendoscope via TradingView or official support channels. Stay tuned for updates and enhancements to the Divergence Strategy!
Cari dalam skrip untuk "stop loss"
Long Explosive V1The “Long Explosive V1” strategy calculates the percentage change in price from the last closing price of the candlestick, so that if it increases by a certain percentage it goes long, but if it decreases by another percentage it sends an exit order, so that the percentage limits above and below the current price function as inherent stop loss and take profit, with the benefit of taking advantage of the volatility of the bull market.
Entries and exits are always at the market and based on percentage changes in the price. Of course, the default configuration of the strategy considers a position with a 5% risk control, modest initial capital and standard commissions, which helps to obtain realistic results and protect the user from unexpectedly controlled potential losses.
It is again emphasized that it is always advisable to adjust the parameters of the strategy well, so that the risk-reward is well controlled.
Livermore-Seykota Breakout StrategyStrategy Name: Livermore-Seykota Breakout Strategy
Objective: Execute breakout trades inspired by Jesse Livermore, filtered by trend confirmation (Ed Seykota) and risk-managed with ATR (Paul Tudor Jones style).
Entry Conditions:
Long Entry:
Close price breaks above recent pivot high.
Price is above main EMA (EMA50).
EMA20 > EMA200 (uptrend confirmation).
Current volume > 20-period SMA (volume confirmation).
Short Entry:
Close price breaks below recent pivot low.
Price is below main EMA (EMA50).
EMA20 < EMA200 (downtrend confirmation).
Current volume > 20-period SMA.
Exit Conditions:
Stop-loss: ATR × 3 from entry price.
Trailing stop: activated with offset of ATR × 2.
Strengths:
Trend-aligned entries with volume breakout confirmation.
Dynamic ATR-based risk management.
Inspired by principles of three legendary traders.
REVELATIONS (VoVix - PoC) REVELATIONS (VoVix - POC): True Regime Detection Before the Move
Let’s not sugarcoat it: Most strategies on TradingView are recycled—RSI, MACD, OBV, CCI, Stochastics. They all lag. No matter how many overlays you stack, every one of these “standard” indicators fires after the move is underway. The retail crowd almost always gets in late. That’s never been enough for my team, for DAFE, or for anyone who’s traded enough to know the real edge vanishes by the time the masses react.
How is this different?
REVELATIONS (VoVix - POC) was engineered from raw principle, structured to detect pre-move regime change—before standard technicals even light up. We built, tested, and refined VoVix to answer one hard question:
What if you could see the spike before the trend?
Here’s what sets this system apart, line-by-line:
o True volatility-of-volatility mathematics: It’s not just "ATR of ATR" or noise smoothing. VoVix uses normalized, multi-timeframe v-vol spikes, instantly detecting orderbook stress and "outlier" market events—before the chart shows them as trends.
o Purist regime clustering: Every trade is enabled only during coordinated, multi-filter regime stress. No more signals in meaningless chop.
o Nonlinear entry logic: No trade is ever sent just for a “good enough” condition. Every entry fires only if every requirement is aligned—local extremes, super-spike threshold, regime index, higher timeframe, all must trigger in sync.
o Adaptive position size: Your contracts scale up with event strength. Tiny size during nominal moves, max leverage during true regime breaks—never guesswork, never static exposure.
o All exits governed by regime decay logic: Trades are closed not just on price targets but at the precise moment the market regime exhausts—the hardest part of systemic trading, now solved.
How this destroys the lag:
Standard indicators (RSI, MACD, OBV, CCI, and even most “momentum” overlays) simply tell you what already happened. VoVix triggers as price structure transitions—anyone running these generic scripts will trade behind the move while VoVix gets in as stress emerges. Real alpha comes from anticipation, not confirmation.
The visuals only show what matters:
Top right, you get a live, live quant dashboard—regime index, current position size, real-time performance (Sharpe, Sortino, win rate, and wins). Bottom right: a VoVix "engine bar" that adapts live with regime stress. Everything you see is a direct function of logic driving this edge—no cosmetics, no fake momentum.
Inputs/Signals—explained carefully for clarity:
o ATR Fast Length & ATR Slow Length:
These are the heart of VoVix’s regime sensing. Fast ATR reacts to sharp volatility; Slow ATR is stability baseline. Lower Fast = reacts to every twitch; higher Slow = requires more persistent, “real” regime shifts.
Tip: If you want more signals or faster markets, lower ATR Fast. To eliminate noise, raise ATR Slow.
o ATR StdDev Window: Smoothing for volatility-of-volatility normalization. Lower = more jumpy, higher = only the cleanest spikes trigger.
Tip: Shorten for “jumpy” assets, raise for indices/futures.
o Base Spike Threshold: Think of this as your “minimum event strength.” If the current move isn’t volatile enough (normalized), no signal.
Tip: Higher = only biggest moves matter. Lower for more signals but more potential noise.
o Super Spike Multiplier: The “are you sure?” test—entry only when the current spike is this multiple above local average.
Tip: Raise for ultra-selective/swing-trading; lower for more active style.
Regime & MultiTF:
o Regime Window (Bars):
How many bars to scan for regime cluster “events.” Short for turbo markets, long for big swings/trends only.
o Regime Event Count: Only trade when this many spikes occur within the Regime Window—filters for real stress, not isolated ticks.
Tip: Raise to only ever trade during true breakouts/crashes.
o Local Window for Extremes:
How many bars to check that a spike is a local max.
Tip: Raise to demand only true, “clearest” local regime events; lower for early triggers.
o HTF Confirm:
Higher timeframe regime confirmation (like 45m on an intraday chart). Ensures any event you act on is visible in the broader context.
Tip: Use higher timeframes for only major moves; lower for scalping or fast regimes.
Adaptive Sizing:
o Max Contracts (Adaptive): The largest size your system will ever scale to, even on extreme event.
Tip: Lower for small accounts/conservative risk; raise on big accounts or when you're willing to go big only on outlier events.
o Min Contracts (Adaptive): The “toe-in-the-water.” Smallest possible trade.
Tip: Set as low as your broker/exchange allows for safety, or higher if you want to always have meaningful skin in the game.
Trade Management:
o Stop %: Tightness of your stop-loss relative to entry. Lower for tighter/safer, higher for more breathing room at cost of greater drawdown.
o Take Profit %: How much you'll hold out for on a win. Lower = more scalps. Higher = only run with the best.
o Decay Exit Sensitivity Buffer: Regime index must dip this far below the trading threshold before you exit for “regime decay.”
Tip: 0 = exit as soon as stress fails, higher = exits only on stronger confirmation regime is over.
o Bars Decay Must Persist to Exit: How long must decay be present before system closes—set higher to avoid quick fades and whipsaws.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Tip: Set to 1 for instant regime exit; raise for extra confirmation (less whipsaw risk, exits held longer).
________________________________________
Bottom line: Tune the sensitivity, selectivity, and risk of REVELATIONS by these inputs. Raise thresholds and windows for only the best, most powerful signals (institutional style); lower for activity (scalpers, fast cryptos, signals in constant motion). Sizing is always adaptive—never static or martingale. Exits are always based on both price and regime health. Every input is there for your control, not to sell “complexity.” Use with discipline, and make it your own.
This strategy is not just a technical achievement: It’s a statement about trading smarter, not just more.
* I went back through the code to make sure no the strategy would not suffer from repainting, forward looking, or any frowned upon loopholes.
Disclaimer:
Trading is risky and carries the risk of substantial loss. Do not use funds you aren’t prepared to lose. This is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
Expect more: We’ll keep pushing the standard, keep evolving the bar until “quant” actually means something in the public code space.
Use with clarity, use with discipline, and always trade your edge.
— Dskyz , for DAFE Trading Systems
Strategy Stats [presentTrading]Hello! it's another weekend. This tool is a strategy performance analysis tool. Looking at the TradingView community, it seems few creators focus on this aspect. I've intentionally created a shared version. Welcome to share your idea or question on this.
█ Introduction and How it is Different
Strategy Stats is a comprehensive performance analytics framework designed specifically for trading strategies. Unlike standard strategy backtesting tools that simply show cumulative profits, this analytics suite provides real-time, multi-timeframe statistical analysis of your trading performance.
Multi-timeframe analysis: Automatically tracks performance metrics across the most recent time periods (last 7 days, 30 days, 90 days, 1 year, and 4 years)
Advanced statistical measures: Goes beyond basic metrics to include Information Coefficient (IC) and Sortino Ratio
Real-time feedback: Updates performance statistics with each new trade
Visual analytics: Color-coded performance table provides instant visual feedback on strategy health
Integrated risk management: Implements sophisticated take profit mechanisms with 3-step ATR and percentage-based exits
BTCUSD Performance
The table in the upper right corner is a comprehensive performance dashboard showing trading strategy statistics.
Note: While this presentation uses Vegas SuperTrend as the underlying strategy, this is merely an example. The Stats framework can be applied to any trading strategy. The Vegas SuperTrend implementation is included solely to demonstrate how the analytics module integrates with a trading strategy.
⚠️ Timeframe Limitations
Important: TradingView's backtesting engine has a maximum storage limit of 10,000 bars. When using this strategy stats framework on smaller timeframes such as 1-hour or 2-hour charts, you may encounter errors if your backtesting period is too long.
Recommended Timeframe Usage:
Ideal for: 4H, 6H, 8H, Daily charts and above
May cause errors on: 1H, 2H charts spanning multiple years
Not recommended for: Timeframes below 1H with long history
█ Strategy, How it Works: Detailed Explanation
The Strategy Stats framework consists of three primary components: statistical data collection, performance analysis, and visualization.
🔶 Statistical Data Collection
The system maintains several critical data arrays:
equityHistory: Tracks equity curve over time
tradeHistory: Records profit/loss of each trade
predictionSignals: Stores trade direction signals (1 for long, -1 for short)
actualReturns: Records corresponding actual returns from each trade
For each closed trade, the system captures:
float tradePnL = strategy.closedtrades.profit(tradeIndex)
float tradeReturn = strategy.closedtrades.profit_percent(tradeIndex)
int tradeType = entryPrice < exitPrice ? 1 : -1 // Direction
🔶 Performance Metrics Calculation
The framework calculates several key performance metrics:
Information Coefficient (IC):
The correlation between prediction signals and actual returns, measuring forecast skill.
IC = Correlation(predictionSignals, actualReturns)
Where Correlation is the Pearson correlation coefficient:
Correlation(X,Y) = (nΣXY - ΣXY) / √
Sortino Ratio:
Measures risk-adjusted return focusing only on downside risk:
Sortino = (Avg_Return - Risk_Free_Rate) / Downside_Deviation
Where Downside Deviation is:
Downside_Deviation = √
R_i represents individual returns, T is the target return (typically the risk-free rate), and n is the number of observations.
Maximum Drawdown:
Tracks the largest percentage drop from peak to trough:
DD = (Peak_Equity - Trough_Equity) / Peak_Equity * 100
🔶 Time Period Calculation
The system automatically determines the appropriate number of bars to analyze for each timeframe based on the current chart timeframe:
bars_7d = math.max(1, math.round(7 * barsPerDay))
bars_30d = math.max(1, math.round(30 * barsPerDay))
bars_90d = math.max(1, math.round(90 * barsPerDay))
bars_365d = math.max(1, math.round(365 * barsPerDay))
bars_4y = math.max(1, math.round(365 * 4 * barsPerDay))
Where barsPerDay is calculated based on the chart timeframe:
barsPerDay = timeframe.isintraday ?
24 * 60 / math.max(1, (timeframe.in_seconds() / 60)) :
timeframe.isdaily ? 1 :
timeframe.isweekly ? 1/7 :
timeframe.ismonthly ? 1/30 : 0.01
🔶 Visual Representation
The system presents performance data in a color-coded table with intuitive visual indicators:
Green: Excellent performance
Lime: Good performance
Gray: Neutral performance
Orange: Mediocre performance
Red: Poor performance
█ Trade Direction
The Strategy Stats framework supports three trading directions:
Long Only: Only takes long positions when entry conditions are met
Short Only: Only takes short positions when entry conditions are met
Both: Takes both long and short positions depending on market conditions
█ Usage
To effectively use the Strategy Stats framework:
Apply to existing strategies: Add the performance tracking code to any strategy to gain advanced analytics
Monitor multiple timeframes: Use the multi-timeframe analysis to identify performance trends
Evaluate strategy health: Review IC and Sortino ratios to assess predictive power and risk-adjusted returns
Optimize parameters: Use performance data to refine strategy parameters
Compare strategies: Apply the framework to multiple strategies to identify the most effective approach
For best results, allow the strategy to generate sufficient trade history for meaningful statistical analysis (at least 20-30 trades).
█ Default Settings
The default settings have been carefully calibrated for cryptocurrency markets:
Performance Tracking:
Time periods: 7D, 30D, 90D, 1Y, 4Y
Statistical measures: Return, Win%, MaxDD, IC, Sortino Ratio
IC color thresholds: >0.3 (green), >0.1 (lime), <-0.1 (orange), <-0.3 (red)
Sortino color thresholds: >1.0 (green), >0.5 (lime), <0 (red)
Multi-Step Take Profit:
ATR multipliers: 2.618, 5.0, 10.0
Percentage levels: 3%, 8%, 17%
Short multiplier: 1.5x (makes short take profits more aggressive)
Stop loss: 20%
Hierarchical + K-Means Clustering Strategy===== USER GUIDE =====
Hierarchical + K-Means Clustering Strategy
OVERVIEW:
This strategy combines hierarchical clustering and K-means algorithms to analyze market volatility patterns
and generate trading signals. It uses a modified SuperTrend indicator with ATR-based volatility clustering
to identify potential trend changes and market conditions.
KEY FEATURES:
- Advanced volatility analysis using hierarchical clustering and K-means algorithms
- Modified SuperTrend indicator for trend identification
- Multiple filter options including moving average and ADX trend strength
- Volume-based exit mechanism to protect profits
- Customizable appearance settings
SETTINGS EXPLANATION:
1. SuperTrend Settings:
- ATR Length: Period for ATR calculation (default: 11)
- SuperTrend Factor: Multiplier for ATR to determine trend bands (default: 3)
2. Hierarchical Clustering Settings:
- Training Data Length: Number of bars used for clustering analysis (default: 200)
3. Appearance Settings:
- Transparency 1 & 2: Control the opacity of trend lines and fills
- Bullish/Bearish Color: Colors for uptrend and downtrend visualization
4. Time Settings:
- Start Year/Month: Define when the strategy should start executing trades
5. Filter Settings:
- Moving Average Filter: Uses SMA to filter trades (only enter when price is on correct side of MA)
- Trend Strength Filter: Uses ADX to ensure trades are taken in strong trend conditions
6. Volume Stop Loss Settings:
- Volume Ratio Threshold: Controls sensitivity of volume-based exits
- Monitoring Delay Bars: Number of bars to wait before monitoring volume for exit signals
HOW TO USE:
1. Apply the indicator to your chart
2. Adjust settings according to your trading preferences and timeframe
3. Long signals appear when price crosses above the SuperTrend line (▲k marker)
4. Short signals appear when price crosses below the SuperTrend line (▼k marker)
5. The strategy automatically manages exits based on volume balance conditions
INTERPRETATION:
- Green line/area: Bullish trend - consider long positions
- Red line/area: Bearish trend - consider short positions
- Yellow line: Moving average for additional trend confirmation
- Volume balance exits occur when buying/selling pressure equalizes
RECOMMENDED TIMEFRAMES:
This strategy works best on 1H, 4H, and daily charts for most markets.
For highly volatile assets, shorter timeframes may also be effective.
RISK MANAGEMENT:
Always use proper position sizing and consider setting additional stop losses
beyond the strategy's built-in exit mechanisms.
===== END OF USER GUIDE =====
Arpeet MACDOverview
This strategy is based on the zero-lag version of the MACD (Moving Average Convergence Divergence) indicator, which captures short-term trends by quickly responding to price changes, enabling high-frequency trading. The strategy uses two moving averages with different periods (fast and slow lines) to construct the MACD indicator and introduces a zero-lag algorithm to eliminate the delay between the indicator and the price, improving the timeliness of signals. Additionally, the crossover of the signal line and the MACD line is used as buy and sell signals, and alerts are set up to help traders seize trading opportunities in a timely manner.
Strategy Principle
Calculate the EMA (Exponential Moving Average) or SMA (Simple Moving Average) of the fast line (default 12 periods) and slow line (default 26 periods).
Use the zero-lag algorithm to double-smooth the fast and slow lines, eliminating the delay between the indicator and the price.
The MACD line is formed by the difference between the zero-lag fast line and the zero-lag slow line.
The signal line is formed by the EMA (default 9 periods) or SMA of the MACD line.
The MACD histogram is formed by the difference between the MACD line and the signal line, with blue representing positive values and red representing negative values.
When the MACD line crosses the signal line from below and the crossover point is below the zero axis, a buy signal (blue dot) is generated.
When the MACD line crosses the signal line from above and the crossover point is above the zero axis, a sell signal (red dot) is generated.
The strategy automatically places orders based on the buy and sell signals and triggers corresponding alerts.
Advantage Analysis
The zero-lag algorithm effectively eliminates the delay between the indicator and the price, improving the timeliness and accuracy of signals.
The design of dual moving averages can better capture market trends and adapt to different market environments.
The MACD histogram intuitively reflects the comparison of bullish and bearish forces, assisting in trading decisions.
The automatic order placement and alert functions make it convenient for traders to seize trading opportunities in a timely manner, improving trading efficiency.
Risk Analysis
In volatile markets, frequent crossover signals may lead to overtrading and losses.
Improper parameter settings may cause signal distortion and affect strategy performance.
The strategy relies on historical data for calculations and has poor adaptability to sudden events and black swan events.
Optimization Direction
Introduce trend confirmation indicators, such as ADX, to filter out false signals in volatile markets.
Optimize parameters to find the best combination of fast and slow line periods and signal line periods, improving strategy stability.
Combine other technical indicators or fundamental factors to construct a multi-factor model, improving risk-adjusted returns of the strategy.
Introduce stop-loss and take-profit mechanisms to control single-trade risk.
Summary
The MACD Dual Crossover Zero Lag Trading Strategy achieves high-frequency trading by quickly responding to price changes and capturing short-term trends. The zero-lag algorithm and dual moving average design improve the timeliness and accuracy of signals. The strategy has certain advantages, such as intuitive signals and convenient operation, but also faces risks such as overtrading and parameter sensitivity. In the future, the strategy can be optimized by introducing trend confirmation indicators, parameter optimization, multi-factor models, etc., to improve the robustness and profitability of the strategy.
Liquidity Trading Algorithm (LTA)
The Liquidity Trading Algorithm is an algorithm designed to provide trade signals based on
liquidity conditions in the market. The underlying algorithm is based on the Liquidity
Dependent Price Movement (LDPM) metric and the Liquidity Dependent Price Stability (LDPS)
algorithm.
Together, LDPM and LDPS demonstrate statistically significant forecasting capabilities for price-
action on equities, cryptocurrencies, and futures. LTA takes these liquidity measurements and
translates them into actionable insights by way of entering or exiting a position based
on the future outlooks, as measured by the current liquidity status.
The benefit of LTA is that it can incorporate these powerful liquidity measurements into
actionable insights with several features designed to help you tailor LTA's behavior and
measurements to your desired vantage point. These customizable features come by the way of determining LTA's assessment style, and additional monitoring systems for avoiding bear and bull traps, along with various other quality of life features, discussed in more detail below.
First, a few quick facts:
- LTA is compatible on a wide array of instruments, including Equities, Futures, Cryptocurrencies, and Forex.
- LTA is compatible on most intervals in so long as the data can be calculated appropriately,
(be sure to do a backtest on timescales less than 1-minue to ensure the data can be computed).
- LTA only measures liquidity at the end of the interval of the chart chosen, and does not respond to conditions during the candle interval, unless specified (such as with `Stops`).
- LTA is interval-dependent, this means it will measure and behave differently on different
intervals as the underlying algorithms are dependent on the interval chosen.
- LTA can utilize fractional share sizing for cryptocurrencies.
- LTA can be restricted to either bullish or bearish indications.
- Additional Monitoring Systems are available for additional risk mitigation.
In short, LTA is a widely applicable, unique algorithm designed to translate liquidity measurements into liquidity insights.
Before getting more into the details, here is a quick list of the main features and settings
available for customization:
- Backtesting Start Date: Manual selection of the start date for the algorithm during backtesting.
- Assessment Style: adjust how LDPM and LDPS measure and respond to changes in liquidity.
- Impose Wait: force LTA to wait before entering or exiting a position to ensure conditions have remained conducive.
- Trade Direction Allowance: Restrict LTA to only long or only short, if desired.
- Position Sizing Method: determine how LTA calculates position sizing.
- Fractional Share Sizing: allow LTA to calculate fractional share sizes for cryptocurrencies
- Max Size Limit: Impose a maximum size on LTA's positions.
- Initial Capital: Indicate how much capital LTA should stat with.
- Portfolio Allotment: Indicate to LTA how much (in percentages) of the available balance should be considered when calculating position size.
- Enact Additional Monitoring Systems: Indicate if LTA should impose additional safety criteria when monitoring liquidity.
- Configure Take Profit, Stop-Loss, Trailing Stop Loss
- Display Information tables on the current position, overall strategy performance, along
with a text output showing LTA's processes.
- Real-time text output and updates on LTA's inner workings.
Let's get into some more of the details.
LTA's Assessment Style
LTA's assessment style determines how LTA collects and responds to changing data. In traditional terms, this is akin to (but not quite exactly the same as) the sensitivity versus specificity spectrum, whereby on one end (the sensitive end), an algorithm responds to changes in data in a reactive manner (which tends to lower its specificity, or how often it is correct in its indications), and on the other end, the opposite one, the algorithm foresakes quick changes for longevity of outlook.
While this is in part true, it is not a full view of the underlying mechanisms that changing the assessment style augments. A better analogy would be that the sensitive end of the spectrum (`Aggressive`) is in a state such that the algorithm wants to changing its outlooks, and as such, with changes in data, the algorithm has to be convinced as to why that is not a good idea to change outlooks, whereas the the more specific states (`Conservative`, `Diamond`) must be convinced that their view is no longer valid and that it needs to be changed.
This means the `Aggressive` and the `Diamond` settings fundamentally differ not just in their
data collection, but also in the data processing such that the `Aggressive` decision tree has to
be convinced that the data is the same (as its defualt is that it has changed),
and the `Diamond` decision tree has to be convinced that the data is not the same, and as such, the outlook need changed.
From there, the algorithm cooks through the data and determines to what the outlook should be changed to, given the current state of liquidity.
`Balanced` lies in the middle of this balance, attempting to balance being open to new ideas while not removing the wisdom of the past, as it were.
On a scale of most `sensitive` to most `specific`, it is as follows: `Aggressive`, `Balanced`,
`Conservative`, `Diamond`.
Functionally, these different modes can help in different liquidity environments, as certain
environments are more conducive to an eager approach (such as found near `Aggressive`) or are more conducive to a more conservative approach, where sudden changes in liquidity are known to be short-lived and unremarkable (such as many previously identified bull or bear traps).
For instance, on low interval views, it can often-times be beneficial to keep the algorithm towards the `Sensitive` end, since on the lower-timeframes, the crosswinds can change quite dramatically; whereas on the longer intervals, it may be useful to maintain a more `Specific` algorithm (such as found near `Diamond` mode) setting since longer intervals typically lend themselves to longer time-horizons, which themselves typically lend themselves to "weathering the storm", as it were.
LTA's Assessment Style is also supported by the Additional Monitoring Systems which works
to add sensitivity without sacrificing specificity by enacting a separate monitoring system, as described below.
Additional Monitoring Systems
The Additional Monitoring System (AMS) attempts to add more context to any changes in liquidity conditions as measured, such that LTA as a whole will have an expanded view into any rapidly changing liquidity conditions before these changes manifest in the traditional data streams. The ideal is that this allows for early exits or early entrances to positions "a head of time".
The traditional use of this system is to indicate when liquidity is suggestive of the end of a particular run (be it a bear run or a bull run), so an early exit can be initiated (and thus,
downside averted) even before the data officially showcase such changes. In such cases (when AMS becomes activated), the algorithm will signal to exit any open positions, and will restrict the opening of any new positions.
When a position is exited because of AMS, it is denoted as an `Early Exit` and if a position is prevented from being entered, the text output will display `AM prevented entry...` to indicate that conditions are not meeting AMS' additional standards.
The algorithm will wait to make any actions while `AMS` is `active` and will only enter into a new position once `AMS` has been `deactivated` and overall liquidity conditions are appropriate.
Functionally, the benefits of AMS translate to:
- Toggeling AMS on will typically see a net reduction in overall profitability, but
- AMS will typically (almost always) reduce max drawdown,
an increases in max runup, and increase return-over-maxdrawdown, and
- AMS can provide benefit for equities that experience a lot of "traps" by navigating early
entrance and early exits.
So in short, AMS is way of adding an additional level of liquidity monitoring that attempts to
exit positions if conditions look to be deteriorating, and to enter conditions if they look to be
improving. The cost of this additional monitoring, however, is a greater number of trades indicated, and a lower overall profitability.
Impose Wait
Note: `Impose Wait` will not force Take Profit, Stop Loss, or Trailing Stop Loss to
wait.
LTA can be indicated to `wait` before entering or exiting a position if desired. This means that if conditions change, whereas without a `wait` imposed, the algorithm would immediately indicate this change via a signal to alter the strategy's position, with a `wait` imposed, the algorithm will `wait` the indicated number of bars, and then re-check conditions before proceeding.
If, while waiting, conditions change to a state that is no longer compatible with the "order-in-
waiting", then the order-in-waiting is removed, and the counts reset (i.e.: conditions must remain favorable to the intended positional change throughout the wait period).
Since LTA works at the end-of-intervals, there is an inherently "built-in" wait of 1 bar when
switching directly from long to short (i.e.: if a full switch is indicated, then it is indicated as
conditions change -> exit new position -> wait until -> check conditions ->
enter new position as indicated). Thus, to impose a wait of `1 bar` would be to effectively have a total of two candles' ends prior to the entrance of the new position).
There are two main styles of `Impose Wait` that you can utilize:
- `Wait` : this mode will cause LTA to `wait` when both entering and exiting a position (in so long as it is not an exit signaled via a Take Profit, Stop Loss or Trailing Stop Loss).
- `Exit-Wait` : This mode will >not< cause LTA to `wait` if conditions require the closing of a position, but will force LTA to wait before entering into a position.
Position:
In addition to the availability to restrict LTA to either a long-only or short-only strategy, LTA
also comprises additional flexibility when deciding on how it should navigate the markets with
regards to sizing. Notably, this flexibility benefits several aspects of LTA's existence, namely the ability to determine the `Sizing Method`, or if `Fractional Share Sizing` should be employed, and more, as discussed below.
Position Sizing Method
There are two main ways LTA can determine the size of a position. Either via the `Fixed-Share` choice, or the `Fixed-Percentage` choice.
- `Fixed-Share` will use the amount indicated in the `Max Sizing Limit` field as the position size, always.
Note: With `Fixed-Share` sizing, LTA will >not< check if the balance is sufficient
prior to signaling an entrance.
- `Fixed-Percentage` will use the percentage amount indicated in the `Portfolio Allotment` field as the percentage of available funds to use when calculating the position size. Additionally, with the `Fixed-Percentage` choice, you can set the `Max Sizing Limit` if desired, which will ensure that no position will be entered greater than the amount indicated in the field.
Fractional Share Sizing
If the underlying instrument supports it (typically only cryptocurrencies), share sizing can be
fractionalized. If this is done, the resulting positin size is rounded to `4 digits`. This means any
position with a size less than `0.00005` will be rounded to `0.0000`
Note: Ensure that the underlying instrument supports fractional share sizing prior
to initiating.
Max Sizing Limit
As discussed above, the `Max Sizing Limit` will determine:
- The position size for every position, if `Sizing Method : Fixed-Share` is utilized, or
- The maximum allowed size, regardless of available capital, if `Sizing Method : Fixed-Percentage` is utilized.
Note: There is an internal maximum of 100,000 units.
Initial Capital
Note: There are 2 `Initial Capital` settings; one in LTA's settings and one in the
`Properties` tab. Ensure these two are the same when doing backtesting.
The initial capital field will be used to determine the starting balanace of the strategy, and
is used to calculate the internal data reporting (the data tables).
Portfolio Allotment
You can specify how much of the total available balance should be used when calculating the share size. The default is 100%.
Stops
Note: Stops over-ride `AMS` and `Impose Wait`, and are not restricted to only the
end-of-candle and will occur instantaneously upon their activation. Neither `AMS` nor `Impose Wait` can over-ride a signal from a `Take-Profit`, `Stop-Loss`, or a `Trailing-Stop Loss`.
LTA enhouses three stops that can be configured, a `Take-Profit`, a `Stop-Loss` and a `Trailing-Stop Loss`. The configurations can be set in the settings in percent terms. These exit signals will always over-ride AMS or any other restrictions on position exit.
Their configuration is rather standard; set the percentages you want the signal to be sent at and so it will be done.
Some quick notes on the `Trailing-Stop Loss`:
- The activation percentage must be reached (in profits) prior to the `Traililng-Stop Loss`
from activating the downside protection. For example, if the `Activation Percentage` is 10%, then unless the position reaches (at any point) a 10% profit, then it will not signal any exits on the downside, should it occur.
- The downside price-point is continuously updated and is calculated from the maximum profit reached in the given position and the loss percentage placed in the appropriate field.
Data Tables and Data Output
LTA provides real-time data output through a variety of mechanisms:
- `Position Table`
The `Position Table` displays information about the current position, including:
> Position Duration : how long the position has been open for.
> Indicates if the side is Long or Short, depending on if it is long or short.
> Entry Price: the price the position was entered at.
> Current Price (% Dif): the current price of the underlying and the %-difference between the entry price and the current price.
> Max Profit ($/%): the maximum profit reached in $ and % terms.
> Current PnL ($/%) : the current PnL for the open position.
- `Performance Table`
The `Performance Table` displays information regarding the overall performance of the algorithm since its `Start Date`. These data include:
> Initial Equity ($): The initial equity the algorithm started with.
> Current Equity ($): The current total equity of the account (including open positions)
> Net Profits ($|%) : The overall net profit in $ and % terms.
> Long / Short Trade Counts: The respective trade counts for the positions entered.
> Total Closed Trades: The running sum of the number of trades closed.
> Profitability: The calculation of the number of profitable trades over the total number of
trades.
> Avg. Profit / Trade: The calculation of the average profit per trade in both $ and % terms.
> Avg. Loss / Trade: The calculation of the average loss per trade in both $ and % terms.
> Max Run-Up: The maximum run-up the algorithm has seen in both $ and % terms.
> Max Drawdown: The maximum draw-down the algorithm has seen in both $ and % terms.
> Return-Over-Max-Drawdown: the ratio of the maximum drawdown against the current net profits.
- `Text Output`
LTA will output, if desired, signals to the text output field every time it analysis or performs and action. These messages can include information such as:
"
08:00:00 >> AM Protocol activated ... exiting position ...
08:00:00 >> Exit Order Created for qty: 2, profit: 380 (4.34%)
...
09:30:00 >> Checking conditions ...
09:30:00 >> AM protocol prevented entry ... waiting ...
"
This way, you can keep an eye out on what is happening "under the hood", as it were.
LTA will produce a message at the end of its assessment at the end of each candle interval, as well as when a position is exited due to a `Stop` or due to `AMS` being activated.
Additionally, the `Text Output` includes a initial message, but for space-constraints, this
can be toggled off with the `Blank Text Output` option within LTA's configurations.
For additional information, please refer to the Author's Instructions below.
HMA Crossover 1H with RSI, Stochastic RSI, and Trailing StopThe strategy script provided is a trading algorithm designed to help traders make informed buy and sell decisions based on certain technical indicators. Here’s a breakdown of what each part of the script does and how the strategy works:
Key Components:
Hull Moving Averages (HMA):
HMA 5: This is a Hull Moving Average calculated over 5 periods. HMAs are used to smooth out price data and identify trends more quickly than traditional moving averages.
HMA 20: This is another HMA but calculated over 20 periods, providing a broader view of the trend.
Relative Strength Index (RSI):
RSI 14: This is a momentum oscillator that measures the speed and change of price movements over a 14-period timeframe. It helps identify overbought or oversold conditions in the market.
Stochastic RSI:
%K: This is the main line of the Stochastic RSI, which combines the RSI and the Stochastic Oscillator to provide a more sensitive measure of overbought and oversold conditions. It is smoothed with a 3-period simple moving average.
Trading Signals:
Buy Signal:
Generated when the 5-period HMA crosses above the 20-period HMA, indicating a potential upward trend.
Additionally, the RSI must be below 45, suggesting that the market is not overbought.
The Stochastic RSI %K must also be below 39, confirming the oversold condition.
Sell Signal:
Generated when the 5-period HMA crosses below the 20-period HMA, indicating a potential downward trend.
The RSI must be above 60, suggesting that the market is not oversold.
The Stochastic RSI %K must also be above 63, confirming the overbought condition.
Trailing Stop Loss:
This feature helps protect profits by automatically selling the position if the price moves against the trade by 5%.
For sell positions, an additional trailing stop of 100 points is included.
Trend Following Parabolic Buy Sell Strategy [TradeDots]The Trend Following Parabolic Buy-Sell Strategy leverages the Parabolic SAR in combination with moving average crossovers to deliver buy and sell signals within a trend-following framework.
This strategy synthesizes proven methodologies sourced from various trading tutorials available on platforms such as YouTube and blogs, enabling traders to conduct robust backtesting on their selected trading pairs to assess the strategy's effectiveness.
HOW IT WORKS
This strategy employs four key indicators to orchestrate its trading signals:
1. Trend Alignment: It first assesses the relationship between the price and the predominant trendline to determine the directional stance—taking long positions only when the price trends above the moving average, signaling an upward market trajectory.
2. Momentum Confirmation: Subsequent to trend alignment, the strategy looks for moving average crossovers as a confirmation that the price is gaining momentum in the direction of the intended trades.
3. Signal Finalization: Finally, buy or sell signals are validated using the Parabolic SAR indicator. A long order is validated when the closing price is above the Parabolic SAR dots, and similarly, conditions are reversed for short orders.
4. Risk Management: The strategy institutes a fixed stop-loss at the moving average trendline and a take-profit level determinable by a prefixed risk-reward ratio calculated from the moving average trendline. These parameters are customizable by the users within the strategy settings.
APPLICATION
Designed for assets exhibiting pronounced directional momentum, this strategy aims to capitalize on clear trend movements conducive to achieving set take-profit targets.
As a lagging strategy that waits for multiple confirmatory signals, entry into trades might occasionally lag beyond optimal timing.
Furthermore, in periods of consolidation or sideways movement, the strategy may generate several false signals, suggesting the potential need for additional market condition filters to enhance signal accuracy during volatile phases.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 70%
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Channels With NVI Strategy [TradeDots]The "Channels With NVI Strategy" is a trading strategy that identifies oversold market instances during a bullish trading market. Specifically, the strategy integrates two principal indicators to deliver profitable opportunities, anticipating potential uptrends.
2 MAIN COMPONENTS
1. Channel Indicators: This strategy gives users the flexibility to choose between Bollinger Band Channels or Keltner Channels. This selection can be made straight from the settings, allowing the traders to adjust the tool according to their preferences and strategies.
2. Negative Volume Indicator (NVI): An indicator that calculates today's price rate of change, but only when today's trading volume is less than the previous day's. This functionality enables users to detect potential shifts in the trading volume with time and price.
ENTRY CONDITION
First, the assets price must drop below the lower band of the channel indicator.
Second, NVI must ascend above the exponential moving average line, signifying a possible flood of 'smart money' (large institutional investors or savvy traders), indicating an imminent price rally.
EXIT CONDITION
Exit conditions can be customized based on individual trading styles and risk tolerance levels. Traders can define their ideal take profit or stop loss percentages.
Moreover, the strategy also employs an NVI-based exit policy. Specifically, if the NVI dips under the exponential moving average – suggestive of a fading trading momentum, the strategy grants an exit call.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Strategy Container_Variable Pyramiding & Leverage [Tradingwhale]This is a strategy container . It doesn’t provide a trading strategy. What it does is provide functionality that is not readily available with standard strategy ’shells.’
More specifically, this Strategy Container enables Tradingview users to create trading strategies without knowing any Pine Script code .
Furthermore, you can use most indicators on tradingview to build a strategy without any coding at all, whether or not you have access to the code.
To illustrate a possible output in the image (buy and sell orders) of this strategy container, we are using here an indicator that provides buy and sell signals, only for illustration purposes. Again, this is a strategy container, not a strategy. So we need to include an indicator with this published strategy to be able to show the strategy execution.
What can you do with this strategy container? Please read below.
Trade Direction
You can select to trade Long trades only, Short trades only, or both, assuming that whatever strategy you create with this container will produce buy and sell signals.
Exit on Opposite
You can select if Long signals cause the exit of Short positions and vice versa. If you turn this on, then a sell/short signal will cause the closing of your entire long position, and a buy/long signal will cause the closing of your entire short position.
Use external data sources (indicators) to (a) import signals, or (b) create trading signals using almost any of the indicators available on Tradingview.
Option 1:
When you check the box ‘Use external indicator Buy & Sell signals?’ and continue to select an external indicator that plots LONG/BUY signals as value '1' and SHORT/SELL signals as value '-1, then this strategy container will use those signals for the strategy, in combination with all other available settings.
Here an example of code in an indicator that you could use to import signals with this strategy container:
buy = long_cond and barstate.isconfirmed
sell = short_cond and barstate.isconfirmed
//—------- Signal for Strategy
signal = buy ? 1 : sell ? -1 : 0
plot(plot_connector? signal : na, title="OMEGA Signals", display = display.none)
Option 2:
You can create buy/long and sell/short signals from within this strategy container under the sections called “ Define 'LONG' Signal ” and “ Define 'SHORT' Signal .”
You can do this with a single external indicator, by comparing two external indicators, or by comparing one external indicator with a fixed value. The indicator/s you use need to be on the same chart as this strategy container. You can add up to two (2) external indicators that can be compared to each other at a time. A checkbox allows you to select whether the logical operation is executed between Source #1 and #2, between Source # 1 and an absolute value, or just by analyzing the behavior of Source #1.
Without an image of the strategy container settings it’s a bit hard to explain. However, below you see a list of all possible operations.
Operations available , whenever possible based on source data, include:
- "crossing"
- "crossing up"
- "crossing down"
- "rejected from resistance (Source #1) in the last bar", which means ‘High’ was above Source #1 (resistance level) in the last completed bar and 'Close' (current price of the symbol) is now below Source #1" (resistance level).
- "rejected from resistance (Source #1) in the last 2 bars", which means ‘High’ was above Source #1 (resistance level) in one of the last two (2) completed bars and 'Close' (current price of the symbol) is now below Source #1" (resistance level).
- "rejected from support (Source #1) in the last bar" --- similar to above except with Lows and rejection from support level
- "rejected from support (Source #1) in the last 2 bars" --- similar to above except with Lows and rejection from support level
- "greater than"
- "less than"
- "is up"
- "is down"
- "is up %"
- "is down %"
Variable Pyramiding, Leverage, and Pyramiding Direction
Variable Pyramiding
With this strategy container, you can define how much capital you want to invest for three consecutive trades in the same direction (pyramiding). You can define what percentage of your equity you want to invest for each pyramid-trade separately, which means they don’t have to be identical.
As an example: You can invest 5% in the first trade let’s call this pyramid trade #0), 10% in the second trade (pyramid trade #1), and 7% in the third trade (pyramid trade #2), or any other combination. If your trading strategy doesn’t produce pyramid trading opportunities (consecutive trades in the same direction), then the pyramid trade settings won’t come to bear for the second and third trades, because only the first trade will be executed with each signal.
Leverage
You can enter numbers for the three pyramid trades that are combined greater than 100%. Once that is the case, you are using leverage in your trades and have to manage the risk that is associated with that.
Pyramiding Direction
You can decide to scale only into Winners, Losers, or Both. Pyramid into a:
- Losers : A losing streak occurs when the price of the underlying security at the current signal is lower than the average cost of the position.
- Winners : A winning streak occurs when the price of the underlying security at the current signal is higher than the average cost of the position.
- Both means that you are selecting to scale/pyramid into both Winning and Losing streaks.
Other Inputs that influence signal execution:
You can choose to turn these on or off.
1. Limit Long exits with a WMA to stay longer in Long positions: If you check this box and enter a Length number (integer) for the WMA (Weighted Moving Average), then Long positions can only be exited with short signals when the current WMA is lower than on the previous bar/candle. Short signals sometimes increase with uptrends. We’re using this WMA here to limit short signals by adding another condition (WMA going down) for the short signal to be valid.
2. Maximum length of trades in the number of candles. Positions that have been in place for the specified number of trades are excited automatically.
3. Set the backtest period (from-to). Only trades within this range will be executed.
4. Market Volatility Adjustment Settings
- Use ATR to limit when Long trades can be entered (enter ATR length and Offset). We’re using the 3-day ATR here, with your entries for ATR length and offset. When the 3-day ATR is below its signal line, then Long trades are enabled; otherwise, they are not.
- Use VIX to limit when Short trades can be entered (enter VIX). If you select this checkbox, then Short trades will only be executed if the daily VIX is above your set value.
- Use Momentum Algo functions to limit Short trades. This uses the average distance of Momentum Highs and Lows over the lookback period to gauge whether markets are calm or swinging more profoundly. Based on that you can limit short entries to more volatile market regimes.
Set:
- Fast EMA and Slow EMA period lengths
- Number of left and right candles for High and Low pivots
- Lookback period to calculate the High/Low average and then the distance between the two.
The assumption here is that greater distances between momentum highs and lows correlate positively with greater volatility and greater swings in the underlying security.
Stop-Loss
Set separate stop-losses based on % for Long and Short positions. If the position loses X% since entry, then the position will be closed.
Take-Profit
Set separate take-profit levels based on % for Long and Short positions. If the position wins X% since entry, then the position will be closed.
Time Session Filter - MACD exampleTime Session Filter in TradingView Strategy: A Comprehensive Guide
Welcome to this educational TradingView blog where we dive deep into the functionality and utility of the time session filter in trading strategies. It's interesting to note that the time session filter is a commonly overlooked feature in Pine Script, often not integrated into overall trading strategies. Yet, when used wisely, this tool can significantly enhance your trading approach. In essence, the session filter ensures that trades are only made within a specific, user-defined time frame. By incorporating this often-neglected building block, you can make your strategy more adaptable to various market conditions and trading preferences.
What is a Time Session Filter?
A time session filter is designed to:
Select Times of the Day to Trade: The filter allows you to choose specific hours during the day in which trades are allowed to be excecuted.
Toggle Days to Trade: You can decide which days of the week you want to trade, giving you the flexibility to avoid days that are historically not profitable for your strategy.
Close Trade When Session Ends: The filter can automatically close any open trade once the specified time session concludes, reducing the risk associated with holding positions outside your chosen time frame.
The user interface is streamlined, taking minimal space for the input sections, making it convenient to integrate with other indicators in your overall strategy script. In addition the script colors the background of the chart green when the timesession filter is on and makes the background red when the filter doesn't allow any trades. This helps you to visualise the selected timeframes in relation to chart patterns.
Best Practices for Time Selection
From my personal trading experience I share some input settings you can try to play around with:
Stocks: Trading stocks sometimes yield better results if you only trade in the mornings until lunchtime. This is the period when markets are generally more active, and traders are keenly participating.
Cryptocurrencies: For cryptocurrencies, it sometimes makes sense to avoid trading on Fridays, a day when futures contracts often expire. Various other market-moving events also typically occur on Fridays.
Random Selection: Interestingly, sometimes choosing a random selection of times and days can improve the script's performance, adding an element of unpredictability that might outperform more systematic approaches.
Strategy Overview
This strategy script incorporates various elements, including risk position size and MACD indicator, to provide a comprehensive trading strategy. For a detailed explanation of risk position sizing, please refer to this article:
For a complete understanding of the MACD indicator utilized, visit the following explanation:
Additionally, for high time frame trend filters, consult this resource for more info:
Educational Purposes and Risks
Please note that this script is for educational purposes and serves merely as an example of how to incorporate a time session filter into a trading strategy for pinescript. It is a simplified strategy without a fixed stop-loss, which can result in higher exposure to significant losses. The time session filter can be a powerful addition to your trading strategy, providing you with the tools to tailor your approach according to time-specific market conditions. By understanding its functionalities and best practices, you can make more informed trading decisions, but always remember that trading carries inherent risks.
Happy trading!
Buy&Sell Bullish Engulfing - The Quant Science🇺🇸
GENERAL OVERVIEW
Buy&Sell Bullish Engulfing - The Quant Science It is a Buy&Sell strategy based on the 'Bullish Engulfing' candlestick pattern. The main goal of the strategy is to achieve a consistent and sustainable return over time, with a manageable level of risk.
Bullish Engulfing
The template was developed at the top of the Indicator provided by TradingView called 'Engulfing - Bullish'.
ENTRY AND EXIT CRITERIA
Entry: A single long order is opened when the candlestick pattern is formed, and the percentage size of the order (%) is fixed by the trader through the user interface.
Exit: The long trade is closed on a percentage equity take profit-stop loss.
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
🇮🇹
PANORAMICA GENERALE
Buy&Sell Bullish Engulfing - The Quant Science è una strategia Buy&Sell basata sul candlestick pattern 'Bullish Engulfing'. L'obiettivo principale della strategia è ottenere un ritorno costante e sostenibile nel tempo, con un livello gestibile di rischio.
Bullish Engulfing
Il template è stato sviluppato al top dell' Indicatore fornito da Trading View chiamato 'Engulfing - Bullish'.
CRITERI DI ENTRATA E USCITA
Entrata: viene aperto un singolo ordine long quando si forma il candlestick pattern, la size percentuale dell'ordine (%) viene selezionato tramite l'interfaccia utente dal trader.
Uscita: la chiusura della posizione avviene unicamente tramite un take profit-stop loss percentuale calcolato sul capitale.
FRAMA & CPMA Strategy [CSM]The script is an advanced technical analysis tool specifically designed for trading in financial markets, with a particular focus on the BankNifty market. It utilizes two powerful indicators: the Fractal Adaptive Moving Average (FRAMA) and the CPMA (Conceptive Price Moving Average), which is similar to the well-known Chande Momentum Oscillator (CMO) with Center of Gravity (COG) bands.
The FRAMA is a dynamic moving average that adapts to changing market conditions, providing traders with a more precise representation of price movements. The CMO is an oscillator that measures momentum in the market, helping traders identify potential entry and exit points. The COG bands are a technical indicator used to identify potential support and resistance levels in the market.
Custom functions are included in the script to calculate the FRAMA and CSM_CPMA indicators, with the FRAMA function calculating the value of the FRAMA indicator based on user-specified parameters of length and multiplier, while the CSM_CPMA function calculates the value of the CMO with COG bands indicator based on the user-specified parameters of length and various price types.
The script also includes trailing profit and stop loss functions, which while not meeting expectations, have been backtested with a success rate of over 90%, making the script a valuable tool for traders.
Overall, the script provides traders with a comprehensive technical analysis tool for analyzing cryptocurrency markets and making informed trading decisions. Traders can improve their success rate and overall profitability by using smaller targets with trailing profit and minimizing losses. Feedback is always welcome, and the script can be improved for future use. Special thanks go to Tradingview for providing inbuilt functions that are utilized in the script.
PowerX by jwitt98This strategy attempts to replicate the PowerX strategy as described in the book by by Markus Heitkoetter
Three indicators are used:
RSI (7) - An RSI above 50 indicates and uptrend. An RSI below 50 indicates a downtrend.
Slow Stochastics (14, 3, 3) - A %K above 50 indicates an uptrend. A %K below 50 indicates a downtrend.
MACD (12, 26, 9) - A MACD above the signal line indicates an uptrend. A MACD below the signal line indicates a downtrend
In addition, multiples of ADR (7) is used for setting the stops and profit targets
Setup:
When all 3 indicators are indicating an uptrend, the OHLC bar is green.
When all 3 indicators are indicating a downtrend, the OHLC bar is red.
When one or more indicators are conflicting, the OHLC bar is black
The basic rules are:
When the OHLC bar is green and the preceding bar is black or Red, enter a long stop-limit order .01 above the high of the first green bar
When the OHLC bar is red and the preceding bar is black or green, enter a short stop-limit order .01 below the low of the first red bar
If a red or black bar is encountered while in a long trade, or a green or black bar for a short trade, exit the trade at the close of that bar with a market order.
Stop losses are set by default at a multiple of 1.5 times the ADR.
Profit targets are set by default at a multiple of 3 times the ADR.
Options:
You can adjust the start and end dates for the trading range
You can configure this strategy for long only, short only, or both long and short.
You can adjust the multiples used to set the stop losses and profit targets.
There is an option to use a money management system very similar to the one described in the PowerX book. Some assumptions had to be made for cases where the equity is underwater as those cases are not clearly defined in the book. There is an option to override this behavior and keep the risk at or above the set point (2% by default), rather than further reduce the risk when equity is underwater. Position sizing is limited when using money management so as not to exceed the current strategy equity. The starting risk can be adjusted from the default of 2%.
Final notes: If you find any errors, have any questions, or have suggestions for improvements, please leave your message in the comments.
Happy trading!
Statistical Correlation Algorithm - The Quant ScienceStatistical Correlation Algorithm - The Quant Science™ is a quantitative trading algorithm.
ALGORITHM DESCRIPTION
This algorithm analyses the correlation ratios between two assets. The main asset (on the chart), and the secondary asset (set by the user). Then apply the long or short trading strategy.
The algorithm divides trading work into three parts:
1. Correlation analysis
2. Long or short entry
3. Closing trades
Inside the strategy: the algorithm analyses the percentage change yields from a previous session, of the secondary asset. If the variation meets the set condition then it will open a long or short position, on the primary asset. The open position is closed after 'x' number of sessions. Stop loss and take profit can be added to the trade exit parameters.
Logic: analyses the correlation between two assets and looks for a statistical advantage within the correlation.
INDICATOR DESCRIPTION
The algorithm includes a quantitative indicator. This indicator is used for correlation analysis and offers a quick reading of the quantitative data. The blue area shows the correlation ratio values. The yellow histograms show the percentage change in the yields of the main asset. Purple histograms show the percentage change in secondary asset yields.
GENERAL FEATURES
Multi time-frame: the user can set any time-frame for the secondary asset.
Multi asset: the user analyses the conditions on a second asset.
Multi-strategy: the algorithm can apply either the long strategy or the short strategy.
Built-in alerts: the algorithm contains alerts that can be customized from the user interface.
Integrated indicator: the quantity indicator is included.
Backtesting included: automatic backtesting of the strategy is generated based on the values set.
Auto-trading compliant: functions for auto trading are included.
USER INTERFACE SETTINGS
Through the intuitive user interface, you can manage all the parameters of this algorithm without any programming experience. The user interface is extremely descriptive and contains all the information needed to understand the logic of the algorithm and to configure it correctly.
1. Date range: through this function you can adjust the analysis and working period of the algorithm.
2. Asset: through this function you can adjust the secondary asset and its time-frame. You can enter any type of asset, even indices and economic indicators.
3. Asset details: this function is used to adjust the percentage change to be analyzed on the secondary asset. The analysis and input conditions are also chosen.
4. Active long or short strategy: this function is used to set the type of strategy to be used, long or short.
5. Setting algo trading alert: with this function, users can manage alerts for their web-hook.
6. Exit&Money management: with this function the user can adjust the exit periods of each trade and activate or deactivate any stop losses and take profits.
7. Data Value Analysis: this function is used to adjust the parameters for the quantity indicator.
Booz StrategyBooz Backtesting : Booz Backtesting is a method for analyzing the performance of your current trading strategy . Booz Backtesting aims to help you generate results and evaluate risk and return without risking real capital.
The Booz Backtesting is the Booz Super Swing Indicator equivalent but gives you the ability to backtest data on different charts.
This is an Indicator created for the purpose of identifying trends in Multiple Markets, it is based on Moving Average Crossover and extra features.
Swing Trading: This function allows you to navigate the entire trend until it is not strong enough, so you can compare it with fixed parameters such as Take Profit and Stop Loss.
Take Profit and Stop Loss function: With this function you will be able to choose the most optimal parameters and see in real time the results in order to choose the best combination of parameters.
Leverage : We have this function for the futures markets where you can check which is the most appropriate leverage for your operation.
Trend Filter: allows you to take multiple entries in the same direction of the market.
If the market crosses below the 200 moving average, it will take only short entries.
If the market crosses above the 200 moving average, it will take only long entries.
Timeframes
Charting from 1 Hour, 4 Hour, Daily, Weekly, Weekly
Markets :Booz Backtesting can be tested in Cryptocurrency, Stocks and Futures markets.
Background Color : at a glance, you can see what cycle the market is in.
Green background : Shows that the market is in a bullish cycle.
Red background: Shows that the market is in a bearish cycle.
Bozz Strategy
Booz Backtesting : Booz Backtesting is a method for analyzing the performance of your current trading strategy . Booz Backtesting aims to help you generate results and evaluate risk and return without risking real capital.
The Booz Backtesting is the Booz Super Swing Indicator equivalent but gives you the ability to backtest data on different charts.
This is an Indicator created for the purpose of identifying trends in Multiple Markets, it is based on Moving Average Crossover and extra features.
Swing Trading: This function allows you to navigate the entire trend until it is not strong enough, so you can compare it with fixed parameters such as Take Profit and Stop Loss.
Take Profit and Stop Loss function: With this function you will be able to choose the most optimal parameters and see in real time the results in order to choose the best combination of parameters.
Leverage : We have this function for the futures markets where you can check which is the most appropriate leverage for your operation.
Trend Filter: allows you to take multiple entries in the same direction of the market.
If the market crosses below the 200 moving average, it will take only short entries.
If the market crosses above the 200 moving average, it will take only long entries.
Timeframes
Charting from 1 Hour, 4 Hour, Daily, Weekly, Weekly
Markets :Booz Backtesting can be tested in Cryptocurrency, Stocks and Futures markets.
Background Color : at a glance, you can see what cycle the market is in.
Green background : Shows that the market is in a bullish cycle.
Red background: Shows that the market is in a bearish cycle.
Twitter
Website
[VJ]First Candle StrategyHello Traders, this is a simple intraday strategy involving the first candle of the day with an additional twist to the traditional style . You can modify the time of candle on the stock and see what are your best picks. Comment below if you found something with good returns
Strategy: Observe the first candle of the day within any time frame. 15m works best. If the first candle is RED ,then go for buy side for the rest of the day. You could square off at close of session or have a fixed take profit and stop loss. This is a contrarian indicator where people just use this as their first entry for the day. The same holds good when a Green candle is seen you go short side.
There is stop loss and take profit that can be used to optimise your trade
The template also includes daily square off based on your time.
Multi Entry Signal Strategy by TradeSmartThis strategy is intended to test different entry signals. You can use 13 different entry signals in the strategy.
Available signals with all their settings:
Heikin Ashi
RSI + EMA
Wavetrend
MACD
Stochastic RSI
Squeeze Momentum
Kairi Relative Index
SSL
Supertrend
Parabolic SAR
Chandelier Exit
Directional Movement Index
Quantitative Qualitative Estimation
For exact rules of entries please relate to the tooltips of each entry signal. All the signals can be used together or separately in the strategy.
Additional settings that can be used:
Trend Filter (limit long or short entries based on a moving average of your choice)
Exit Strategy settings (ATR is used to determine stop loss and take profit levels)
Trailing Loss Setups (you can use 3 different types of trailing losses)
Setups (you can set Long and Short entries as well as the order size based on either Capital % or Risk %)
Date Range (you can limit trades to specific date ranges)
Trading Time (you can limit on which days to trade)
RSI StrategyThis RSI strategy will allow you to go long when RSI is overbought and go short when RSI is oversold. You can also change the checked boxes to reverse this. Uncheck "Overbought Go Long & Oversold Go Short" and check "Overbought Go Short & Oversold Go Long" to use this reversed option.
You can also choose to use an ema filter as an additional qualifier for entry. Uncheck "No EMA Filter" and check "Use EMA Filter" if you want to use it.
Be sure to enter slippage and commission into the properties to give you realistic results.
I've also built in backtesting date ranges and the ability to trade only within certain times of day and have it close all trades at the end of that time frame. This is especially useful for day trading stocks. To specify a time from use the format 0930-1100 or whatever your trading hours will be. Check off "Enable Close Trade At End Of Time Frame" to close the trade at the end of your trading hours.
You can also specify a % based take profit and stop loss. Also keep in mind that the way this code is designed if you use the stop loss and/or take profit and it reaches either target and closes, then it will immediately re-enter if the condition for long or short entry is true.
Finally there's custom alert fields so you can send custom alert messages for strategy entry and exit for use with automated trading services. Simply enter your messages in the fields within the strategy properties and then put {{strategy.order.alert_message}} in your alert message body and it will dynamically pull in the appropriate message.
CCI StrategyThis CCI strategy will allow you to enter a long or short off a CCI zero line cross or control entries and exits from custom upper and lower band lengths. You can set a custom upper band which it will buy when it crosses up and then a custom upper band exit which it will sell when it crosses down. For a short you can set a custom lower band which it will short when it crosses down and the custom lower band exit which it will exit the short when it crosses up. Be sure to enter slippage and commission into the properties to give you realistic results.
I've also built in backtesting date ranges and the ability to trade only within certain times of day and have it close all trades at the end of that time frame. This is especially useful for day trading stocks. If you check off "Enter First Trade ASAP" then when using the time frame option it will enter the current trade. If however you uncheck that box and instead check off "Wait To Enter First Trade" it will wait for the trend to change and then enter.
You can also specify a % based take profit and stop loss. Also keep in mind that if you have "Enter First Trade ASAP" checked off and use the stop loss and/or take profit then it will re-enter the current trend again.
Finally there's custom alert fields so you can send custom alert messages for strategy entry and exit for use with automated trading services. Simply enter your messages in the fields within the strategy properties and then put {{strategy.order.alert_message}} in your alert message body and it will dynamically pull in the appropriate message.
