Hosoda’s CloudsMany investors aim to develop trading systems with a high win rate, mistakenly associating it with substantial profits. In reality, high returns are typically achieved through greater exposure to market trends, which inevitably lowers the win rate due to increased risk and more volatile conditions.
The system I present, called “Hosoda’s Clouds” in honor of Goichi Hosoda , the creator of the Ichimoku Kinko Hyo indicator, is likely one of the first profitable systems many traders will encounter. Designed to capture trends, it performs best in markets with clear directional movements and is less suitable for range-bound markets like Forex, which often exhibit lateral price action.
This system is not recommended for low timeframes, such as minute charts, due to the random and emotionally driven nature of price movements in those periods. For a deeper exploration of this topic, I recommend reading my article “Timeframe is Everything”, which discusses the critical importance of selecting the appropriate timeframe.
I suggest testing and applying the “Hosoda’s Clouds” strategy on assets with a strong trending nature and a proven track record of performance. Ideal markets include Tesla (1-hour, 4-hour, and daily), BTC/USDT (daily), SPY (daily), and XAU/USD (daily), as these have consistently shown clear directional trends over time.
Commissions and Configuration
Commissions can be adjusted in the system’s settings to suit individual needs. For evaluating the effectiveness of “Hosoda’s Clouds,” I’ve used a standard commission of $1 per order as a baseline, though this can be modified in the code to accommodate different brokers or preferences.
The margin per trade is set to $1,000 by default, but users are encouraged to experiment with different margin settings in the configuration to match their trading style.
Rules of the “Hosoda’s Clouds” System (Bullish Strategy)
This strategy is designed to capture trending movements in bullish markets using the Ichimoku Kinko Hyo indicator. The rules are as follows:
Long Entry: A long position is triggered when the Tenkan-sen crosses above the Kijun-sen below the Ichimoku cloud, identifying potential reversals or bounces in a bearish context.
Stop Loss (SL): Placed at the low of the candle 12 bars prior to the entry candle. This setting has proven optimal in my tests, but it can be adjusted in the code based on risk tolerance.
Take Profit (TP): The position is closed when the Tenkan-sen crosses below the bottom of the Ichimoku cloud (the minimum of Senkou Span A and Senkou Span B).
Notes on the Code
margin_long=0: Ideal for strategies requiring a fixed position size, particularly useful for manual entries or testing with a constant capital allocation.
margin_long=100: Recommended for high-frequency systems where positions are closed quickly, simulating gradual growth based on realized profits and reflecting real-world broker constraints.
System Performance
The following performance metrics account for $1 per order commissions and were tested on the specified assets and timeframes:
Tesla (H1)
Trades: 148
Win Rate: 29.05%
Period: Jan 2, 2014 – Jan 6, 2020 (+172%)
Simple Annual Growth Rate: +34.3%
Trades: 130
Win Rate: 30.77%
Period: Jan 2, 2020 – Sep 24, 2025 (+858.90%)
Simple Annual Growth Rate: +150.7%
Tesla (H4)
Trades: 102
Win Rate: 32.35%
Period: Jun 29, 2010 – Sep 24, 2025 (+11,356.36%)
Simple Annual Growth Rate: +758.5%
Tesla (Daily)
Trades: 56
Win Rate: 35.71%
Period: Jun 29, 2010 – Sep 24, 2025 (+3,166.64%)
Simple Annual Growth Rate: +211.5%
BTC/USDT (Daily)
Trades: 44
Win Rate: 31.82%
Period: Sep 30, 2017 – Sep 24, 2025 (+2,592.23%)
Simple Annual Growth Rate: +324.8%
SPY (Daily)
Trades: 81
Win Rate: 37.04%
Period: Jan 23, 1993 – Sep 24, 2025 (+476.90%)
Simple Annual Growth Rate: +14.3%
XAU/USD (Daily)
Trades: 216
Win Rate: 32.87%
Period: Jan 6, 1833 – Sep 24, 2025 (+5,241.73%)
Simple Annual Growth Rate: +27.1%
SPX (Daily)
Trades: 217
Win Rate: 38.25%
Period: Feb 1, 1871 – Sep 24, 2025 (+16,791.02%)
Simple Annual Growth Rate: +108.1%
Conclusion
With the “ Hosoda’s Clouds ” strategy, I aim to showcase the potential of technical analysis to generate consistent profits in trending markets, challenging recent doubts about its effectiveness. My goal is for this system to serve as both a practical tool for traders and a source of inspiration for the trading community I deeply respect. I hope it encourages the creation of new strategies, fosters creativity in technical analysis, and empowers traders to approach the markets with confidence and discipline.
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Katz Calypso Indicator (Refactored)Overview
The Katz Calypso Indicator is a comprehensive momentum oscillator designed to identify potential entry and exit points in the market. At its core, it uses the True Strength Index (TSI) to gauge the strength and direction of a trend. To enhance signal accuracy and reduce false positives, the indicator integrates several optional filters, including the Waddah Attar Explosion, an EMA filter, and an ATR filter. It also provides an optional RVGI-based exit signal system.
This tool is designed to provide a clear, visual representation of market momentum, with customizable filters to adapt to various trading styles and market conditions.
How to Use the Indicator
The indicator is displayed in a separate pane below the main price chart.
TSI Line (Blue): This is the main oscillator line. Its position relative to the zero line indicates the overall trend bias (above 0 is bullish, below is bearish).
Signal Line (Red): A moving average of the TSI line. Crossovers between the TSI and Signal Line are the primary triggers for trade signals.
Zero Line: The centerline of the oscillator. A cross of the Zero Line can indicate a significant shift in momentum.
Overbought/Oversold Levels: These user-defined levels (defaulting to 65 and -65) help identify potential exhaustion points in a trend, which can be used for taking profits.
On-Chart Signals: The indicator plots shapes directly on the chart to make signals easy to spot:
Green Triangles (Up): Indicate long entry or continuation signals.
Red Triangles (Down): Indicate short entry or continuation signals.
Yellow Triangles: Suggest taking profits.
Maroon/Lime Triangles: Indicate an exit based on a signal cross (like RVGI or the Zero Line).
Trading Rules
Long Trade Rules
Entry: A long trade is signaled when ALL of the following conditions are met:
The blue TSI Line crosses above the red Signal Line.
The blue TSI Line is above the 0 Zero Line.
All enabled filters (Waddah Attar, EMA, ATR) confirm bullish conditions.
A green triangle labeled "Long" will appear below the price.
Exit (Take Profit): A take-profit signal for a long trade is generated when either of these occurs:
The TSI Line crosses below the Overbought level.
The TSI Line crosses back below the Signal Line while still above zero.
A yellow triangle labeled "TPL" (Take Profit Long) will appear above the price.
Exit (Stop/Reverse): A signal to exit a long trade is generated when either of these occurs:
The TSI Line crosses below the 0 Zero Line.
The RVGI Exit filter is enabled and generates a bearish crossover signal.
A maroon triangle labeled "Exit Long" will appear above the price.
Short Trade Rules
Entry: A short trade is signaled when ALL of the following conditions are met:
The blue TSI Line crosses below the red Signal Line.
The blue TSI Line is below the 0 Zero Line.
All enabled filters (Waddah Attar, EMA, ATR) confirm bearish conditions.
A red triangle labeled "Short" will appear above the price.
Exit (Take Profit): A take-profit signal for a short trade is generated when either of these occurs:
The TSI Line crosses above the Oversold level.
The TSI Line crosses back above the Signal Line while still below zero.
A yellow triangle labeled "TPS" (Take Profit Short) will appear below the price.
Exit (Stop/Reverse): A signal to exit a short trade is generated when either of these occurs:
The TSI Line crosses above the 0 Zero Line.
The RVGI Exit filter is enabled and generates a bullish crossover signal.
A lime green triangle labeled "Exit Short" will appear below the price.
Optional Filters
You can enable or disable these filters in the indicator's settings to fine-tune its sensitivity.
Waddah Attar Explosion Filter: This filter measures trend strength and volatility. When enabled, it ensures that entries are only taken during periods of strong, confirmed momentum, helping to avoid sideways or choppy markets.
EMA Price Filter: A classic trend filter. When enabled, it will only allow long entries if the price is above the specified Exponential Moving Average and short entries only if the price is below it.
ATR Filter: This acts as a volatility-based filter to prevent chasing a move. It helps ensure that you are not entering a long trade when the price has already moved too far above its EMA, or vice-versa for a short trade.
RVGI Exit Filter: The Relative Vigor Index (RVGI) is used here exclusively as an exit signal. When enabled, a crossover of the RVGI and its signal line can provide an earlier exit signal before the TSI crosses the zero line, potentially locking in profits sooner.
Disclaimer: This indicator is provided for educational and informational purposes only. It is not financial advice. Trading carries a high level of risk, and you can lose more than your initial investment. You should use this indicator at your own risk and discretion. Always conduct your own research and consider your risk tolerance before making any trading decisions.
Hilly's Advanced Crypto Scalping Strategy - 5 Min ChartTo determine the "best" input parameters for the Advanced Crypto Scalping Strategy on a 5-minute chart, we need to consider the goals of optimizing for profitability, minimizing false signals, and adapting to the volatile nature of cryptocurrencies. The default parameters in the script are a starting point, but the optimal values depend on the specific cryptocurrency pair, market conditions, and your risk tolerance. Below, I'll provide recommended input values based on common practices in crypto scalping, along with reasoning for each parameter. I’ll also suggest how to fine-tune them using TradingView’s backtesting and optimization tools.
Recommended Input Parameters
These values are tailored for a 5-minute chart for liquid cryptocurrencies like BTC/USD or ETH/USD on exchanges like Binance or Coinbase. They aim to balance signal frequency and accuracy for day trading.
Fast EMA Length (emaFastLen): 9
Reasoning: A 9-period EMA is commonly used in scalping to capture short-term price movements while remaining sensitive to recent price action. It reacts faster than the default 10, aligning with the 5-minute timeframe.
Slow EMA Length (emaSlowLen): 21
Reasoning: A 21-period EMA provides a good balance for identifying the broader trend on a 5-minute chart. It’s slightly longer than the default 20 to reduce noise while confirming the trend direction.
RSI Length (rsiLen): 14
Reasoning: The default 14-period RSI is a standard choice for momentum analysis. It works well for detecting overbought/oversold conditions without being too sensitive on short timeframes.
RSI Overbought (rsiOverbought): 75
Reasoning: Raising the overbought threshold to 75 (from 70) reduces false sell signals in strong bullish trends, which are common in crypto markets.
RSI Oversold (rsiOversold): 25
Reasoning: Lowering the oversold threshold to 25 (from 30) filters out weaker buy signals, ensuring entries occur during stronger reversals.
MACD Fast Length (macdFast): 12
Reasoning: The default 12-period fast EMA for MACD is effective for capturing short-term momentum shifts in crypto, aligning with scalping goals.
MACD Slow Length (macdSlow): 26
Reasoning: The default 26-period slow EMA is a standard setting that works well for confirming momentum trends without lagging too much.
MACD Signal Smoothing (macdSignal): 9
Reasoning: The default 9-period signal line is widely used and provides a good balance for smoothing MACD crossovers on a 5-minute chart.
Bollinger Bands Length (bbLen): 20
Reasoning: The default 20-period Bollinger Bands are effective for identifying volatility breakouts, which are key for scalping in crypto markets.
Bollinger Bands Multiplier (bbMult): 2.0
Reasoning: A 2.0 multiplier is standard and captures most price action within the bands. Increasing it to 2.5 could reduce signals but improve accuracy in highly volatile markets.
Stop Loss % (slPerc): 0.8%
Reasoning: A tighter stop loss of 0.8% (from 1.0%) suits the high volatility of crypto, helping to limit losses on false breakouts while keeping risk manageable.
Take Profit % (tpPerc): 1.5%
Reasoning: A 1.5% take-profit target (from 2.0%) aligns with scalping’s goal of capturing small, frequent gains. Crypto markets often see quick reversals, so a smaller target increases the likelihood of hitting profits.
Use Candlestick Patterns (useCandlePatterns): True
Reasoning: Enabling candlestick patterns (e.g., engulfing, hammer) adds confirmation to signals, reducing false entries in choppy markets.
Use Volume Filter (useVolumeFilter): True
Reasoning: The volume filter ensures signals occur during high-volume breakouts, which are more likely to sustain in crypto markets.
Signal Arrow Size (signalSize): 2.0
Reasoning: Increasing the arrow size to 2.0 (from 1.5) makes buy/sell signals more visible on the chart, especially on smaller screens or volatile price action.
Background Highlight Transparency (bgTransparency): 85
Reasoning: A slightly higher transparency (85 from 80) keeps the background highlights subtle but visible, avoiding chart clutter.
How to Apply These Parameters
Copy the Script: Use the Pine Script provided in the previous response.
Paste in TradingView: Open TradingView, go to the Pine Editor, paste the code, and click "Add to Chart."
Set Parameters: In the strategy settings, manually input the recommended values above or adjust them via the input fields.
Test on a 5-Minute Chart: Apply the strategy to a liquid crypto pair (e.g., BTC/USDT, ETH/USDT) on a 5-minute chart.
Fine-Tuning for Optimal Performance
To find the absolute best parameters for your specific trading pair and market conditions, use TradingView’s Strategy Tester and optimization features:
Backtesting:
Run the strategy on historical data for your chosen pair (e.g., BTC/USDT on Binance).
Check metrics like Net Profit, Profit Factor, Win Rate, and Max Drawdown in the Strategy Tester.
Focus on a sample period of at least 1–3 months to capture various market conditions (bull, bear, sideways).
Parameter Optimization:
In the Strategy Tester, click the settings gear next to the strategy name.
Enable optimization for key inputs like emaFastLen (test range: 7–12), emaSlowLen (15–25), slPerc (0.5–1.5), and tpPerc (1.0–3.0).
Run the optimization to find the combination with the highest net profit or best Sharpe ratio, but avoid over-optimization (curve-fitting) by testing on out-of-sample data.
Market-Specific Adjustments:
Volatile Pairs (e.g., DOGE/USDT): Use tighter stop losses (e.g., 0.5–0.7%) and smaller take-profit targets (e.g., 1.0–1.2%) to account for rapid price swings.
Stable Pairs (e.g., BTC/USDT): Slightly wider stop losses (e.g., 1.0–1.2%) and take-profit targets (e.g., 1.8–2.5%) may work better.
Trending Markets: Increase emaSlowLen (e.g., to 25–30) to follow stronger trends.
Choppy Markets: Tighten bbMult (e.g., to 1.8) and lower rsiOverbought/rsiOversold (e.g., to 70/30) to filter noise.
Forward Testing:
After backtesting, run the strategy in real-time on a demo account for 1–2 weeks to validate performance under current market conditions.
Important Notes
No Universal "Best" Numbers: Optimal parameters vary by crypto pair, exchange, and market conditions (e.g., bull vs. bear market). The suggested values are a starting point based on common scalping practices.
Risk Management: Never risk more than 1–2% of your account per trade. Adjust position sizing in TradingView’s strategy settings to align with your risk tolerance.
Market Volatility: Crypto markets are highly volatile. Test the strategy on your specific pair and adjust parameters if signals are too frequent or too rare.
Not Financial Advice: This is an educational tool. Backtest thoroughly and use a demo account before trading with real funds.
If you want me to generate a chart showing backtest performance for specific parameters or to tweak the script further (e.g., adding more indicators or adjusting signal logic), let me know!can you add clear buy ans sell signs above the candles in this codeTo add clear buy and sell signals above the candles in the provided Pine Script, I'll modify the existing code to include prominent text labels directly above (for sell signals) and below (for buy signals) the candles. These labels will be larger, color-coded, and positioned to avoid clutter, ensuring they are easily visible on the chart. The core strategy logic (EMA, RSI, MACD, Bollinger Bands, candlestick patterns, and volume filter) will remain unchanged, and I'll reuse the same artifact_id since this is an update to the previous script.AdvancedCryptoScalpingStrategy.pinex-pine
Calculator - AOC📊 Calculator - AOC Indicator 🚀
The Calculator - AOC indicator is a powerful and user-friendly tool designed for TradingView to help traders plan and visualize trades with precision. It calculates key trade metrics, displays entry, take-profit (TP), stop-loss (SL), and liquidation levels, and provides a clear overview of risk management and potential profits. Perfect for both novice and experienced traders! 💡
✨ Features
📈 Trade Planning: Input your Entry Price, Take Profit (TP), Stop Loss (SL), and Trade Direction (Long/Short) to visualize your trade setup on the chart.
💰 Risk Management: Set your Initial Capital and Risk per Trade (%) to calculate the optimal Position Size and Risk Amount for each trade.
⚖️ Leverage Support: Define your Leverage to compute the Required Margin and Liquidation Price, ensuring you stay aware of potential risks.
📊 Risk/Reward Ratio: Automatically calculates the Risk-to-Reward Ratio to evaluate trade profitability.
🎨 Visuals: Displays Entry, TP, SL, and Liquidation levels as lines and boxes on the chart, with customizable Line Width, Line Style, and Label Size.
✅ Trade Validation: Checks if your trade setup is valid (e.g., correct TP/SL placement) and highlights issues like potential liquidation risks with color-coded statuses (Correct ✅, Incorrect ❌, or Liquidation ⚠️).
📋 Summary Table: A clean, top-right table summarizes key metrics: Capital, Risk %, Risk Amount, Position Size, Potential Profit, Risk/Reward, Margin, Liquidation Price, Trade Status, and % to TP/SL.
🖌️ Customization: Adjust Line Extension (Bars) for how far lines extend, and choose from Solid, Dashed, or Dotted line styles for a personalized chart experience.
🛠️ How to Use
Add to Chart: Apply the indicator to your TradingView chart.
Configure Inputs:
Accountability: Set your Initial Capital and Risk per Trade (%).
Target: Enter Entry Price, TP, and SL prices.
Leverage: Specify your leverage (e.g., 10x).
Direction: Choose Long or Short.
Display Settings: Customize Line Width, Line Style, Label Size, and Line Extension.
Analyze: The indicator plots Entry, TP, SL, and Liquidation levels on the chart and displays a table with all trade metrics.
Validate: Check the Trade Status in the table to ensure your setup is valid or if adjustments are needed.
🎯 Why Use It?
Plan Smarter: Visualize your trade setup and understand your risk/reward profile instantly.
Stay Disciplined: Precise position sizing and risk calculations help you stick to your trading plan.
Avoid Mistakes: Clear validation warnings prevent costly errors like incorrect TP/SL placement or liquidation risks.
User-Friendly: Intuitive visuals and a summary table make trade analysis quick and easy.
📝 Notes
Ensure Entry, TP, and SL prices align with your trade direction to avoid "Incorrect" or "Liquidation" statuses.
The indicator updates dynamically on the latest bar, ensuring real-time visuals.
Best used with proper risk management to maximize trading success! 💪
Happy trading! 🚀📈
Game Theory Trading StrategyGame Theory Trading Strategy: Explanation and Working Logic
This Pine Script (version 5) code implements a trading strategy named "Game Theory Trading Strategy" in TradingView. Unlike the previous indicator, this is a full-fledged strategy with automated entry/exit rules, risk management, and backtesting capabilities. It uses Game Theory principles to analyze market behavior, focusing on herd behavior, institutional flows, liquidity traps, and Nash equilibrium to generate buy (long) and sell (short) signals. Below, I'll explain the strategy's purpose, working logic, key components, and usage tips in detail.
1. General Description
Purpose: The strategy identifies high-probability trading opportunities by combining Game Theory concepts (herd behavior, contrarian signals, Nash equilibrium) with technical analysis (RSI, volume, momentum). It aims to exploit market inefficiencies caused by retail herd behavior, institutional flows, and liquidity traps. The strategy is designed for automated trading with defined risk management (stop-loss/take-profit) and position sizing based on market conditions.
Key Features:
Herd Behavior Detection: Identifies retail panic buying/selling using RSI and volume spikes.
Liquidity Traps: Detects stop-loss hunting zones where price breaks recent highs/lows but reverses.
Institutional Flow Analysis: Tracks high-volume institutional activity via Accumulation/Distribution and volume spikes.
Nash Equilibrium: Uses statistical price bands to assess whether the market is in equilibrium or deviated (overbought/oversold).
Risk Management: Configurable stop-loss (SL) and take-profit (TP) percentages, dynamic position sizing based on Game Theory (minimax principle).
Visualization: Displays Nash bands, signals, background colors, and two tables (Game Theory status and backtest results).
Backtesting: Tracks performance metrics like win rate, profit factor, max drawdown, and Sharpe ratio.
Strategy Settings:
Initial capital: $10,000.
Pyramiding: Up to 3 positions.
Position size: 10% of equity (default_qty_value=10).
Configurable inputs for RSI, volume, liquidity, institutional flow, Nash equilibrium, and risk management.
Warning: This is a strategy, not just an indicator. It executes trades automatically in TradingView's Strategy Tester. Always backtest thoroughly and use proper risk management before live trading.
2. Working Logic (Step by Step)
The strategy processes each bar (candle) to generate signals, manage positions, and update performance metrics. Here's how it works:
a. Input Parameters
The inputs are grouped for clarity:
Herd Behavior (🐑):
RSI Period (14): For overbought/oversold detection.
Volume MA Period (20): To calculate average volume for spike detection.
Herd Threshold (2.0): Volume multiplier for detecting herd activity.
Liquidity Analysis (💧):
Liquidity Lookback (50): Bars to check for recent highs/lows.
Liquidity Sensitivity (1.5): Volume multiplier for trap detection.
Institutional Flow (🏦):
Institutional Volume Multiplier (2.5): For detecting large volume spikes.
Institutional MA Period (21): For Accumulation/Distribution smoothing.
Nash Equilibrium (⚖️):
Nash Period (100): For calculating price mean and standard deviation.
Nash Deviation (0.02): Multiplier for equilibrium bands.
Risk Management (🛡️):
Use Stop-Loss (true): Enables SL at 2% below/above entry price.
Use Take-Profit (true): Enables TP at 5% above/below entry price.
b. Herd Behavior Detection
RSI (14): Checks for extreme conditions:
Overbought: RSI > 70 (potential herd buying).
Oversold: RSI < 30 (potential herd selling).
Volume Spike: Volume > SMA(20) x 2.0 (herd_threshold).
Momentum: Price change over 10 bars (close - close ) compared to its SMA(20).
Herd Signals:
Herd Buying: RSI > 70 + volume spike + positive momentum = Retail buying frenzy (red background).
Herd Selling: RSI < 30 + volume spike + negative momentum = Retail selling panic (green background).
c. Liquidity Trap Detection
Recent Highs/Lows: Calculated over 50 bars (liquidity_lookback).
Psychological Levels: Nearest round numbers (e.g., $100, $110) as potential stop-loss zones.
Trap Conditions:
Up Trap: Price breaks recent high, closes below it, with a volume spike (volume > SMA x 1.5).
Down Trap: Price breaks recent low, closes above it, with a volume spike.
Visualization: Traps are marked with small red/green crosses above/below bars.
d. Institutional Flow Analysis
Volume Check: Volume > SMA(20) x 2.5 (inst_volume_mult) = Institutional activity.
Accumulation/Distribution (AD):
Formula: ((close - low) - (high - close)) / (high - low) * volume, cumulated over time.
Smoothed with SMA(21) (inst_ma_length).
Accumulation: AD > MA + high volume = Institutions buying.
Distribution: AD < MA + high volume = Institutions selling.
Smart Money Index: (close - open) / (high - low) * volume, smoothed with SMA(20). Positive = Smart money buying.
e. Nash Equilibrium
Calculation:
Price mean: SMA(100) (nash_period).
Standard deviation: stdev(100).
Upper Nash: Mean + StdDev x 0.02 (nash_deviation).
Lower Nash: Mean - StdDev x 0.02.
Conditions:
Near Equilibrium: Price between upper and lower Nash bands (stable market).
Above Nash: Price > upper band (overbought, sell potential).
Below Nash: Price < lower band (oversold, buy potential).
Visualization: Orange line (mean), red/green lines (upper/lower bands).
f. Game Theory Signals
The strategy generates three types of signals, combined into long/short triggers:
Contrarian Signals:
Buy: Herd selling + (accumulation or down trap) = Go against retail panic.
Sell: Herd buying + (distribution or up trap).
Momentum Signals:
Buy: Below Nash + positive smart money + no herd buying.
Sell: Above Nash + negative smart money + no herd selling.
Nash Reversion Signals:
Buy: Below Nash + rising close (close > close ) + volume > MA.
Sell: Above Nash + falling close + volume > MA.
Final Signals:
Long Signal: Contrarian buy OR momentum buy OR Nash reversion buy.
Short Signal: Contrarian sell OR momentum sell OR Nash reversion sell.
g. Position Management
Position Sizing (Minimax Principle):
Default: 1.0 (10% of equity).
In Nash equilibrium: Reduced to 0.5 (conservative).
During institutional volume: Increased to 1.5 (aggressive).
Entries:
Long: If long_signal is true and no existing long position (strategy.position_size <= 0).
Short: If short_signal is true and no existing short position (strategy.position_size >= 0).
Exits:
Stop-Loss: If use_sl=true, set at 2% below/above entry price.
Take-Profit: If use_tp=true, set at 5% above/below entry price.
Pyramiding: Up to 3 concurrent positions allowed.
h. Visualization
Nash Bands: Orange (mean), red (upper), green (lower).
Background Colors:
Herd buying: Red (90% transparency).
Herd selling: Green.
Institutional volume: Blue.
Signals:
Contrarian buy/sell: Green/red triangles below/above bars.
Liquidity traps: Red/green crosses above/below bars.
Tables:
Game Theory Table (Top-Right):
Herd Behavior: Buying frenzy, selling panic, or normal.
Institutional Flow: Accumulation, distribution, or neutral.
Nash Equilibrium: In equilibrium, above, or below.
Liquidity Status: Trap detected or safe.
Position Suggestion: Long (green), Short (red), or Wait (gray).
Backtest Table (Bottom-Right):
Total Trades: Number of closed trades.
Win Rate: Percentage of winning trades.
Net Profit/Loss: In USD, colored green/red.
Profit Factor: Gross profit / gross loss.
Max Drawdown: Peak-to-trough equity drop (%).
Win/Loss Trades: Number of winning/losing trades.
Risk/Reward Ratio: Simplified Sharpe ratio (returns / drawdown).
Avg Win/Loss Ratio: Average win per trade / average loss per trade.
Last Update: Current time.
i. Backtesting Metrics
Tracks:
Total trades, winning/losing trades.
Win rate (%).
Net profit ($).
Profit factor (gross profit / gross loss).
Max drawdown (%).
Simplified Sharpe ratio (returns / drawdown).
Average win/loss ratio.
Updates metrics on each closed trade.
Displays a label on the last bar with backtest period, total trades, win rate, and net profit.
j. Alerts
No explicit alertconditions defined, but you can add them for long_signal and short_signal (e.g., alertcondition(long_signal, "GT Long Entry", "Long Signal Detected!")).
Use TradingView's alert system with Strategy Tester outputs.
3. Usage Tips
Timeframe: Best for H1-D1 timeframes. Shorter frames (M1-M15) may produce noisy signals.
Settings:
Risk Management: Adjust sl_percent (e.g., 1% for volatile markets) and tp_percent (e.g., 3% for scalping).
Herd Threshold: Increase to 2.5 for stricter herd detection in choppy markets.
Liquidity Lookback: Reduce to 20 for faster markets (e.g., crypto).
Nash Period: Increase to 200 for longer-term analysis.
Backtesting:
Use TradingView's Strategy Tester to evaluate performance.
Check win rate (>50%), profit factor (>1.5), and max drawdown (<20%) for viability.
Test on different assets/timeframes to ensure robustness.
Live Trading:
Start with a demo account.
Combine with other indicators (e.g., EMAs, support/resistance) for confirmation.
Monitor liquidity traps and institutional flow for context.
Risk Management:
Always use SL/TP to limit losses.
Adjust position_size for risk tolerance (e.g., 5% of equity for conservative trading).
Avoid over-leveraging (pyramiding=3 can amplify risk).
Troubleshooting:
If no trades are executed, check signal conditions (e.g., lower herd_threshold or liquidity_sensitivity).
Ensure sufficient historical data for Nash and liquidity calculations.
If tables overlap, adjust position.top_right/bottom_right coordinates.
4. Key Differences from the Previous Indicator
Indicator vs. Strategy: The previous code was an indicator (VP + Game Theory Integrated Strategy) focused on visualization and alerts. This is a strategy with automated entries/exits and backtesting.
Volume Profile: Absent in this strategy, making it lighter but less focused on high-volume zones.
Wick Analysis: Not included here, unlike the previous indicator's heavy reliance on wick patterns.
Backtesting: This strategy includes detailed performance metrics and a backtest table, absent in the indicator.
Simpler Signals: Focuses on Game Theory signals (contrarian, momentum, Nash reversion) without the "Power/Ultra Power" hierarchy.
Risk Management: Explicit SL/TP and dynamic position sizing, not present in the indicator.
5. Conclusion
The "Game Theory Trading Strategy" is a sophisticated system leveraging herd behavior, institutional flows, liquidity traps, and Nash equilibrium to trade market inefficiencies. It’s designed for traders who understand Game Theory principles and want automated execution with robust risk management. However, it requires thorough backtesting and parameter optimization for specific markets (e.g., forex, crypto, stocks). The backtest table and visual aids make it easy to monitor performance, but always combine with other analysis tools and proper capital management.
If you need help with backtesting, adding alerts, or optimizing parameters, let me know!
TrendZonesTrendZones
This is an indicator which I use, have tested, tweaked and added features to for use in my trend following investing system. I got the idea for it when for some reason I was looking for a dynamic reference to measure the height of a channel or something. In search of this I made MA’s of the high and low borders of a Donchian channel which turned out to be two near parallel and stunningly smooth curves. This visual was so appealing that I immediately tried to turn it into a replacement for the KeltCOG which I previously used in my system. First I created a curve in the middle of the upper and lower curves, which I called COG (Center Of Gravity). Then I decided to enter only one lookback and let the script create a Donchian channel with half the lookback and use this to create the curves with an MA of whole lookback. For this reason the minimum lookback is set to 14, enough room for the Donchian Channel of 7 periods. This Donchian ChanneI has a special way of calculating the borders, involving a 5 period Median value. Thanks to this these borders are really a resistance and support level, which won’t change at a whim, e.g. when a ‘dead cat bounce’ occurs. I prevented the Donchian channel to show itself between the curves and only pop out from behind these. These pop outs now function as “strong trend zones”. I gave it colors (blue:-strong up, green: moderate up, orange: moderate down, red: strong down, near COG: gray, curves horizontal: gray) and it looked very appealing. I tested it in different time frames. In some weekend, when I was bored, I observed for a few hours the minute chart of bitcoin. It turned out that you can reliably tell that an uptrend ends when the candles go under the COG beginning a downtrend. Uptrend starts again once the candles go above COG. As Trends on minute charts only last around half an hour, this entertainment made the potential of this indicator very clear to me in just one afternoon.
Risk Management, Safe Level and Logical Stops.
In the inputs are settings for “Risk Tolerance”, and to activate “Show Logical Stop Level” (activated in example chart) and “Show Safe Level”. As a rule of thump a trade should not expose the invested capital to a risk of losing more than 2 percent. I divided my investment capital in ten equal parts which are allocated to ten different stocks or other instruments or kept liquid. This means that when a position is closed by triggering a Stop with a loss of 20 percent, the invested capital suffers only 2 percent (20% x 10% = 2%). This is why the value for “Risk Tolerance” has a default of 20. Because I put my Stops on the lower curve, a “Safe Level” can be calculated such that when you buy for a price below or at this level, the stop will protect the position sufficiently. Because I only buy when the instrument is in uptrend, the buying price should be between COG and Safe Level. Although I never do that, putting the stop at other curves is feasible and when you want to widen the stop (I never lower my stops btw) in a downtrend situation, even 1 ATR below the “Low Border”. I call these “Logical Stop Levels”, marked with dark green circles on the lower curve when safe buying by placing the Stoploss on this curve is possible, gray circles on the other curves, on the Upper Curve navy when price enters very profitable level. In a downtrend situation maroon circles appear.
Target lines
When I open a position I always set a Stoploss and a Target, for this purpose two types of Target values can be set and corresponding Target lines activated. These lines are drawn above the “High Border” at the set distance. If one expects some price to be used, differences will occur.
Other Features
Support Zone, this is 1 ATR below the “Low Border”, the maroon circles of the “Logal Stops” are placed on this “Support level”.
Stop distance and Channel Width. (activated in example chart) These are reported in a two cell table in the right lower corner of the main panel. I created this because I want to be able to check the volatility, whether the channel shows a situation in which safe buying in most levels of the channel is possible or what risk you take when you buy now and set the Stop at the nearest logical level (which is not always the “Lower curve”). This feature comes in handy for creating a setup I propose in the “Day Trading Fantasy” below.
Some General and User Settings. I never activate this, perhaps you will.
Use Of TrendZones In My System.
Create a list of stocks in uptrend. I define ‘stock in uptrend’ as in uptrend zone in all three monthly, weekly and daily charts, all three should at the same time be in uptrend. The advantage of TrendZones is that you can immediately see in which zone the candle moves.
Opening a position in a stock from the above list. I do this only when in both the daily and weekly the green dot on the lower curve indicates a buying opportunity. This is usually not the case in most of the items of the list, this feature thus provides a good timing for opening a position. Sometimes you need to wait a few weeks for this to happen.
Setting a target over a position. For this I use the Target percent line of the weekly chart with the default value of 10.
Updating the Stoploss and Target values. Every week or two weeks I set these to the new values of the “Lower Curve” and the Target line of the weekly. Attention: never shift down Stops, only up or let them stay the same when the curve moves down. I never use Stop levels on other curves.
I Check the charts whenever I like to do this. Close the position when the uptrend obviously shifts down. Otherwise I let the profits run until the Target triggers which closes the position with some profit.
For selecting stocks an checking charts for volume events, I also use a subpanel indicator called “TZanalyser”, which borrows the visual of my “Fibonacci Zone Oscillator”, is based on TrendZones and includes code from my REVE indicators. I intend to publish that as well.
Day Trading Fantasy.
Day trading is an attempt to earn a dime by opening a position in the morning and close it during the day again with a profit (or a loss). Before the market closes, you close all day trading positions.
In my fantasy the “Logical Stop Level” is repurposed for use as entry point and the ATR-based Target line is used to provide a target setting in an intraday chart, like e.g. 15 minute. To do this the “Safe Level” should be limited to between Channel width and COG. This can be done by showing “Safe Level” and “Channel Width” and then set “Risk Tolerance” to around the shown Channel Width. In this setting you can then wait for the green circle to show up for entering your trade and protect it with the stop.
I don’t know if this works fine or if it’s better than other day trade systems, because I don’t do day trading.
Take care and have fun.
Canuck Trading Trader StrategyCanuck Trading Trader Strategy
Overview
The Canuck Trading Trader Strategy is a high-performance, trend-following trading system designed for NASDAQ:TSLA on a 15-minute timeframe. Optimized for precision and profitability, this strategy leverages short-term price trends to capture consistent gains while maintaining robust risk management. Ideal for traders seeking an automated, data-driven approach to trading Tesla’s volatile market, it delivers strong returns with controlled drawdowns.
Key Features
Trend-Based Entries: Identifies short-term trends using a 2-candle lookback period and a minimum trend strength of 0.2%, ensuring responsive trade signals.
Risk Management: Includes a configurable 3.0% stop-loss to cap losses and a 2.0% take-profit to lock in gains, balancing risk and reward.
High Precision: Utilizes bar magnification for accurate backtesting, reflecting realistic trade execution with 1-tick slippage and 0.1 commission.
Clean Interface: No on-chart indicators, providing a distraction-free trading experience focused on performance.
Flexible Sizing: Allocates 10% of equity per trade with support for up to 2 simultaneous positions (pyramiding).
Performance Highlights
Backtested from March 1, 2024, to June 20, 2025, on NASDAQ:TSLA (15-minute timeframe) with $1,000,000 initial capital:
Net Profit: $2,279,888.08 (227.99%)
Win Rate: 52.94% (3,039 winning trades out of 5,741)
Profit Factor: 3.495
Max Drawdown: 2.20%
Average Winning Trade: $1,050.91 (0.55%)
Average Losing Trade: $338.20 (0.18%)
Sharpe Ratio: 2.468
Note: Past performance is not indicative of future results. Always validate with your own backtesting and forward testing.
Usage Instructions
Setup:
Apply the strategy to a NASDAQ:TSLA 15-minute chart.
Ensure your TradingView account supports bar magnification for accurate results.
Configuration:
Lookback Candles: Default is 2 (recommended).
Min Trend Strength: Set to 0.2% for optimal trade frequency.
Stop Loss: Default 3.0% to cap losses.
Take Profit: Default 2.0% to secure gains.
Order Size: 10% of equity per trade.
Pyramiding: Allows up to 2 orders.
Commission: Set to 0.1.
Slippage: Set to 1 tick.
Enable "Recalculate After Order is Filled" and "Recalculate on Every Tick" in backtest settings.
Backtesting:
Run backtests over March 1, 2024, to June 20, 2025, to verify performance.
Adjust stop-loss (e.g., 2.5%) or take-profit (e.g., 1–3%) to suit your risk tolerance.
Live Trading:
Use with a compatible broker or TradingView alerts for automated execution.
Monitor execution for slippage or latency, especially given the high trade frequency (5,741 trades).
Validate in a demo account before deploying with real capital.
Risk Disclosure
Trading involves significant risk and may result in losses exceeding your initial capital. The Canuck Trading Trader Strategy is provided for educational and informational purposes only. Users are responsible for their own trading decisions and should conduct thorough testing before using in live markets. The strategy’s high trade frequency requires reliable execution infrastructure to minimize slippage and latency.
Money Risk Management with Trade Tracking
Overview
The Money Risk Management with Trade Tracking indicator is a powerful tool designed for traders on TradingView to simplify trade simulation and risk management. Unlike the TradingView Strategy Tester, which can be complex for beginners, this indicator provides an intuitive, beginner-friendly interface to evaluate trading strategies in a realistic manner, mirroring real-world trading conditions.
Built on the foundation of open-source contributions from LuxAlgo and TCP, this indicator integrates external indicator signals, overlays take-profit (TP) and stop-loss (SL) levels, and provides detailed money management analytics. It empowers traders to visualize potential profits, losses, and risk-reward ratios, making it easier to understand the financial outcomes of their strategies.
Key Features
Signal Integration: Seamlessly integrates with external long and short signals from other indicators, allowing traders to overlay TP/SL levels based on their preferred strategies.
Realistic Trade Simulation: Simulates trades as they would occur in real-world scenarios, accounting for initial capital, risk percentage, leverage, and compounding effects.
Money Management Dashboard: Displays critical metrics such as current capital, unrealized P&L, risk amount, potential profit, risk-reward ratio, and trade status in a customizable, beginner-friendly table.
TP/SL Visualization: Plots TP and SL levels on the chart with customizable styles (solid, dashed, dotted) and colors, along with optional labels for clarity.
Performance Tracking: Tracks total trades, win/loss counts, win rate, and profit factor, providing a clear overview of strategy performance.
Liquidation Risk Alerts: Warns traders if stop-loss levels risk liquidation based on leverage settings, enhancing risk awareness.
Benefits for Traders
Beginner-Friendly: Simplifies the complexities of the TradingView Strategy Tester, offering an intuitive interface for new traders to simulate and evaluate trades without confusion.
Real-World Insights: Helps traders understand the actual profit or loss potential of their strategies by factoring in capital, risk, and leverage, bridging the gap between theoretical backtesting and real-world execution.
Enhanced Decision-Making: Provides clear, real-time analytics on risk-reward ratios, unrealized P&L, and trade performance, enabling informed trading decisions.
Customizable and Flexible: Allows customization of TP/SL settings, table positions, colors, and sizes, catering to individual trader preferences.
Risk Management Focus: Encourages disciplined trading by highlighting risk amounts, potential profits, and liquidation risks, fostering better financial planning.
Why This Indicator Stands Out
Many traders struggle to translate backtested strategy results into real-world outcomes due to the abstract nature of percentage-based profitability metrics. This indicator addresses that challenge by providing a practical, user-friendly tool that simulates trades with real-world parameters like capital, leverage, and compounding. Its open-source nature ensures accessibility, while its integration with other indicators makes it versatile for various trading styles.
How to Use
Add to TradingView: Copy the Pine Script code into TradingView’s Pine Editor and add it to your chart.
Configure Inputs: Set your initial capital, risk percentage, leverage, and TP/SL values in the indicator settings. Select external long/short signal sources if integrating with other indicators.
Monitor Dashboards: Use the Money Management and Target Dashboard tables to track trade performance and risk metrics in real time.
Analyze Results: Review win rates, profit factors, and P&L to refine your trading strategy.
Credits
This indicator builds upon the open-source contributions of LuxAlgo and TCP , whose efforts in sharing their code have made this tool possible. Their dedication to the trading community is deeply appreciated.
magic wand STSM"Magic Wand STSM" Strategy: Trend-Following with Dynamic Risk Management
Overview:
The "Magic Wand STSM" (Supertrend & SMA Momentum) is an automated trading strategy designed to identify and capitalize on sustained trends in the market. It combines a multi-timeframe Supertrend for trend direction and potential reversal signals, along with a 200-period Simple Moving Average (SMA) for overall market bias. A key feature of this strategy is its dynamic position sizing based on a user-defined risk percentage per trade, and a built-in daily and monthly profit/loss tracking system to manage overall exposure and prevent overtrading.
How it Works (Underlying Concepts):
Multi-Timeframe Trend Confirmation (Supertrend):
The strategy uses two Supertrend indicators: one on the current chart timeframe and another on a higher timeframe (e.g., if your chart is 5-minute, the higher timeframe Supertrend might be 15-minute).
Trend Identification: The Supertrend's direction output is crucial. A negative direction indicates a bearish trend (price below Supertrend), while a positive direction indicates a bullish trend (price above Supertrend).
Confirmation: A core principle is that trades are only considered when the Supertrend on both the current and the higher timeframe align in the same direction. This helps to filter out noise and focus on stronger, more confirmed trends. For example, for a long trade, both Supertrends must be indicating a bearish trend (price below Supertrend line, implying an uptrend context where price is expected to stay above/rebound from Supertrend). Similarly, for short trades, both must be indicating a bullish trend (price above Supertrend line, implying a downtrend context where price is expected to stay below/retest Supertrend).
Trend "Readiness": The strategy specifically looks for situations where the Supertrend has been stable for a few bars (checking barssince the last direction change).
Long-Term Market Bias (200 SMA):
A 200-period Simple Moving Average is plotted on the chart.
Filter: For long trades, the price must be above the 200 SMA, confirming an overall bullish bias. For short trades, the price must be below the 200 SMA, confirming an overall bearish bias. This acts as a macro filter, ensuring trades are taken in alignment with the broader market direction.
"Lowest/Highest Value" Pullback Entries:
The strategy employs custom functions (LowestValueAndBar, HighestValueAndBar) to identify specific price action within the recent trend:
For Long Entries: It looks for a "buy ready" condition where the price has found a recent lowest point within a specific number of bars since the Supertrend turned bearish (indicating an uptrend). This suggests a potential pullback or consolidation before continuation. The entry trigger is a close above the open of this identified lowest bar, and also above the current bar's open.
For Short Entries: It looks for a "sell ready" condition where the price has found a recent highest point within a specific number of bars since the Supertrend turned bullish (indicating a downtrend). This suggests a potential rally or consolidation before continuation downwards. The entry trigger is a close below the open of this identified highest bar, and also below the current bar's open.
Candle Confirmation: The strategy also incorporates a check on the candle type at the "lowest/highest value" bar (e.g., closevalue_b < openvalue_b for buy signals, meaning a bearish candle at the low, suggesting a potential reversal before a buy).
Risk Management and Position Sizing:
Dynamic Lot Sizing: The lotsvalue function calculates the appropriate position size based on your Your Equity input, the Risk to Reward ratio, and your risk percentage for your balance % input. This ensures that the capital risked per trade remains consistent as a percentage of your equity, regardless of the instrument's volatility or price. The stop loss distance is directly used in this calculation.
Fixed Risk Reward: All trades are entered with a predefined Risk to Reward ratio (default 2.0). This means for every unit of risk (stop loss distance), the target profit is rr times that distance.
Daily and Monthly Performance Monitoring:
The strategy tracks todaysWins, todaysLosses, and res (daily net result) in real-time.
A "daily profit target" is implemented (day_profit): If the daily net result is very favorable (e.g., res >= 4 with todaysLosses >= 2 or todaysWins + todaysLosses >= 8), the strategy may temporarily halt trading for the remainder of the session to "lock in" profits and prevent overtrading during volatile periods.
A "monthly stop-out" (monthly_trade) is implemented: If the lres (overall net result from all closed trades) falls below a certain threshold (e.g., -12), the strategy will stop trading for a set period (one week in this case) to protect capital during prolonged drawdowns.
Trade Execution:
Entry Triggers: Trades are entered when all buy/sell conditions (Supertrend alignment, SMA filter, "buy/sell situation" candle confirmation, and risk management checks) are met, and there are no open positions.
Stop Loss and Take Profit:
Stop Loss: The stop loss is dynamically placed at the upTrendValue for long trades and downTrendValue for short trades. These values are derived from the Supertrend indicator, which naturally adjusts to market volatility.
Take Profit: The take profit is calculated based on the entry price, the stop loss, and the Risk to Reward ratio (rr).
Position Locks: lock_long and lock_short variables prevent immediate re-entry into the same direction once a trade is initiated, or after a trend reversal based on Supertrend changes.
Visual Elements:
The 200 SMA is plotted in yellow.
Entry, Stop Loss, and Take Profit lines are plotted in white, red, and green respectively when a trade is active, with shaded areas between them to visually represent risk and reward.
Diamond shapes are plotted at the bottom of the chart (green for potential buy signals, red for potential sell signals) to visually indicate when the buy_sit or sell_sit conditions are met, along with other key filters.
A comprehensive trade statistics table is displayed on the chart, showing daily wins/losses, daily profit, total deals, and overall profit/loss.
A background color indicates the active trading session.
Ideal Usage:
This strategy is best applied to instruments with clear trends and sufficient liquidity. Users should carefully adjust the Your Equity, Risk to Reward, and risk percentage inputs to align with their individual risk tolerance and capital. Experimentation with different ATR Length and Factor values for the Supertrend might be beneficial depending on the asset and timeframe.
Stochastic RSI with MTF TableShort Description of the Script
The provided Pine Script indicator, titled "Stochastic RSI with MTF Table," calculates and displays the Stochastic RSI for the current timeframe and multiple other timeframes (5m, 15m, 30m, 60m, 240m, and daily). The Stochastic RSI is a momentum indicator that blends the Relative Strength Index (RSI) and Stochastic Oscillator to identify overbought and oversold conditions, as well as potential trend reversals via K and D line crossovers.
Key features of the script include:
Inputs: Customizable parameters such as K smoothing (default 3), D smoothing (default 3), RSI length (default 14), Stochastic length (default 14), source price (default close), and overbought/oversold levels (default 80/20).
MTF Table: A table displays the Stochastic RSI status for each timeframe:
"OB" (overbought) if K > 80, "OS" (oversold) if K < 20, or "N" (neutral) otherwise.
Crossovers: "K↑D" for bullish (K crosses above D) and "K↓D" for bearish (K crosses below D).
Visualization: Plots the K and D lines for the current timeframe, with horizontal lines at 80 (overbought), 50 (middle), and 20 (oversold), plus a background fill for clarity.
Table Position: Configurable to appear in one of four chart corners (default: top-right).
This indicator helps traders assess momentum across multiple timeframes simultaneously, aiding in the identification of trend strength and potential entry/exit points.
Trading Strategy with 50EMA and 200EMA for Highest Winning Rate
To create a strategy with the best probability of a high winning rate using the Stochastic RSI MTF indicator alongside the 50-period Exponential Moving Average (50EMA) and 200-period Exponential Moving Average (200EMA), we can combine trend identification with momentum-based entry timing. The 50EMA and 200EMA are widely used to determine medium- and long-term trends, while the Stochastic RSI MTF table provides multi-timeframe momentum signals. Here’s the strategy:
1. Determine the Overall Trend
Bullish Trend: The 50EMA is above the 200EMA on the current timeframe (e.g., daily or 60m chart). This suggests an uptrend, often associated with a "Golden Cross."
Bearish Trend: The 50EMA is below the 200EMA on the current timeframe. This indicates a downtrend, often linked to a "Death Cross."
Implementation: Plot the 50EMA and 200EMA on your chart and visually confirm their relative positions.
2. Identify Entry Signals Using the Stochastic RSI MTF Table
In a Bullish Trend (50EMA > 200EMA):
Look for timeframes in the MTF table showing:
Oversold (OS): K < 20, indicating a potential pullback in the uptrend where price may rebound.
Bullish Crossover (K↑D): K crosses above D, signaling rising momentum and a potential entry point.
Example: If the 60m and 240m timeframes show "OS" or "K↑D," this could be a buy signal.
In a Bearish Trend (50EMA < 200EMA):
Look for timeframes in the MTF table showing:
Overbought (OB): K > 80, suggesting a rally in the downtrend where price may reverse downward.
Bearish Crossover (K↓D): K crosses below D, indicating declining momentum and a potential short entry.
Example: If the 30m and daily timeframes show "OB" or "K↓D," this could be a sell/short signal.
Current Timeframe Check: Use the plotted K and D lines on your trading timeframe for precise entry timing (e.g., confirm a K↑D crossover on a 60m chart for a long trade).
3. Confirm Signals Across Multiple Timeframes
Strengthen the Signal: A higher winning rate is more likely when multiple timeframes align with the trend and signal. For instance:
Bullish trend + "OS" or "K↑D" on 60m, 240m, and daily = strong buy signal.
Bearish trend + "OB" or "K↓D" on 15m, 60m, and 240m = strong sell signal.
Prioritize Higher Timeframes: Signals from the 240m or daily timeframe carry more weight due to their indication of broader trends, increasing reliability.
4. Set Stop-Loss and Take-Profit Levels
Long Trades (Bullish):
Stop-Loss: Place below the most recent swing low or below the 50EMA, whichever is closer, to protect against trend reversals.
Take-Profit: Target a key resistance level or use a risk-reward ratio (e.g., 2:1 or 3:1) based on the stop-loss distance.
Short Trades (Bearish):
Stop-Loss: Place above the most recent swing high or above the 50EMA, whichever is closer.
Take-Profit: Target a key support level or apply a similar risk-reward ratio.
Trailing Stop Option: As the trend progresses, trail the stop below the 50EMA (for longs) or above it (for shorts) to lock in profits.
5. Risk Management
Position Sizing: Risk no more than 1-2% of your trading capital per trade to minimize losses from false signals.
Volatility Consideration: Adjust stop-loss distances and position sizes based on the asset’s volatility (e.g., wider stops for volatile stocks or crypto).
Avoid Overtrading: Wait for clear alignment between the EMA trend and MTF signals to avoid low-probability setups.
Example Scenario
Chart: 60-minute timeframe.
Trend: 50EMA > 200EMA (bullish).
MTF Table: 60m shows "OS," 240m shows "K↑D," and daily is "N."
Action: Enter a long position when the 60m K line crosses above D, confirming the table signal.
Stop-Loss: Below the recent 60m swing low (e.g., 2% below entry).
Take-Profit: At the next resistance level or a 3:1 reward-to-risk ratio.
Outcome: High probability of success due to trend alignment and multi-timeframe confirmation.
Why This Strategy Works
Trend Following: Trading in the direction of the 50EMA/200EMA trend reduces the risk of fighting the market’s momentum.
Momentum Timing: The Stochastic RSI MTF table pinpoints pullbacks or reversals within the trend, improving entry timing.
Multi-Timeframe Confirmation: Alignment across timeframes filters out noise, increasing the win rate.
Risk Control: Defined stop-loss and position sizing protect against inevitable losses.
Caveats
No strategy guarantees a 100% win rate; false signals can occur, especially in choppy markets.
Test this strategy on historical data or a demo account to verify its effectiveness for your asset and timeframe.
This approach leverages the strengths of both trend-following (EMA) and momentum (Stochastic RSI) tools, aiming for a high-probability, disciplined trading system.
SuperTrade ST1 StrategyOverview
The SuperTrade ST1 Strategy is a long-only trend-following strategy that combines a Supertrend indicator with a 200-period EMA filter to isolate high-probability bullish trade setups. It is designed to operate in trending markets, using volatility-based exits with a strict 1:4 Risk-to-Reward (R:R) ratio, meaning that each trade targets a profit 4× the size of its predefined risk.
This strategy is ideal for traders looking to align with medium- to long-term trends, while maintaining disciplined risk control and minimal trade frequency.
How It Works
This strategy leverages three key components:
Supertrend Indicator
A trend-following indicator based on Average True Range (ATR).
Identifies bullish/bearish trend direction by plotting a trailing stop line that moves with price volatility.
200-period Exponential Moving Average (EMA) Filter
Trades are only taken when the price is above the EMA, ensuring participation only during confirmed uptrends.
Helps filter out counter-trend entries during market pullbacks or ranges.
ATR-Based Stop Loss and Take Profit
Each trade uses the ATR to calculate volatility-adjusted exit levels.
Stop Loss: 1× ATR below entry.
Take Profit: 4× ATR above entry (1:4 R:R).
This asymmetry ensures that even with a lower win rate, the strategy can remain profitable.
Entry Conditions
A long trade is triggered when:
Supertrend flips from bearish to bullish (trend reversal).
Price closes above the Supertrend line.
Price is above the 200 EMA (bullish market bias).
Exit Logic
Once a long position is entered:
Stop loss is set 1 ATR below entry.
Take profit is set 4 ATR above entry.
The strategy automatically exits the position on either target.
Backtest Settings
This strategy is configured for realistic backtesting, including:
$10,000 account size
2% equity risk per trade
0.1% commission
1 tick slippage
These settings aim to simulate real-world conditions and avoid overly optimistic results.
How to Use
Apply the script to any timeframe, though higher timeframes (1H, 4H, Daily) often yield more reliable signals.
Works best in clearly trending markets (especially in crypto, stocks, indices).
Can be paired with alerts for live trading or analysis.
Important Notes
This version is long-only by design. No short positions are executed.
Ideal for swing traders or position traders seeking asymmetric returns.
Users can modify the ATR period, Supertrend factor, or EMA filter length based on asset behavior.
Key Financial index**Basic Indicators** (updates may be delayed by a few weeks after dividend distribution):
1. **P/E Ratio**: *Price-to-Earnings*. This ratio shows the price investors are willing to pay for each unit of profit the company generates.
- A P/E below 8 is considered good, meaning the company yields a 12.5% annual profit, which implies a payback period of 8 years.
2. **P/B Ratio**: *Price-to-Book Ratio*. This is used to compare a company's market value with its book value.
- A low P/B (usually below 1): May indicate that the stock is undervalued compared to the company’s net asset value. This can be a good investment opportunity but may also signal financial trouble.
- A high P/B (usually above 3): May suggest the stock is overvalued relative to the company’s net assets. This could reflect high growth expectations or potential overvaluation.
3. **D/E Ratio**: *Debt-to-Equity Ratio* is a financial metric that measures a company’s financial leverage.
D/E Ratio = Total Liabilities / Shareholders' Equity.
It compares the total liabilities of a company to its equity to indicate how much debt is used to finance its assets compared to shareholder investments.
- D/E Ratio below 1: Generally considered safe.
- D/E Ratio between 1 and 2: May be acceptable depending on the industry.
- D/E Ratio above 2: May indicate high financial risk.
4. **CR Ratio**: *Current Ratio*, an important liquidity metric used to assess a company’s ability to pay off short-term liabilities using its short-term assets.
- CR Ratio > 1: Indicates the company has enough current assets to pay off its short-term debts. The higher the ratio, the better the liquidity position.
- CR Ratio < 1: Suggests the company may face difficulties in meeting short-term obligations. This can be a red flag for financial stability.
5. **Profit Margin**: A key financial indicator that measures a company’s profitability relative to its revenue. It shows what percentage of revenue remains after all related costs are deducted.
**General significance of Profit Margin**:
- **Operational Efficiency**: A high profit margin indicates efficient cost management and the ability to generate strong profits from revenue.
- **Industry Comparison**: Comparing a company’s profit margin with its industry peers helps assess its competitive position and relative performance.
**Note**:
- There is no single “good” margin across all industries. Each industry has different cost structures and competition levels, leading to varying average margins.
- When analyzing profit margins, one must consider the industry context, the company’s business model, and market trends.
6. **Growth Expectation ↑**: This refers to the expected profit growth. The percentage figure reflects how much growth the market expects the company to achieve in the next financial report based on the current stock price.
- The lower the expected growth rate (typically below 15%), the safer the current price is considered.
- A high expected growth rate may indicate that the market anticipates a profit breakthrough or that the stock is trading above its intrinsic value relative to actual earnings.
BONK 1H Long Volatility StrategyGrok 1hr bonk strategy:
Key Changes and Why They’re Made
1. Indicator Adjustments
Moving Averages:
Fast MA: Changed to 5 periods (from, e.g., 9 on a higher timeframe).
Slow MA: Changed to 13 periods (from, e.g., 21).
Why: Shorter periods make the moving averages more sensitive to quick price changes on the 1-hour chart, helping identify trends faster.
ATR (Average True Range):
Length: Set to 10 periods (down from, e.g., 14).
Multiplier: Reduced to 1.5 (from, e.g., 2.0).
Why: A shorter ATR length tracks recent volatility better, and a lower multiplier lets the strategy catch smaller price swings, which are more common hourly.
RSI:
Kept at 14 periods with an overbought level of 70.
Why: RSI stays the same to filter out overbought conditions, maintaining consistency with the original strategy.
2. Entry Conditions
Trend: Requires the fast MA to be above the slow MA, ensuring a bullish direction.
Volatility: The candle’s range (high - low) must exceed 1.5 times the ATR, confirming a significant move.
Momentum: RSI must be below 70, avoiding entries at potential peaks.
Price: The close must be above the fast MA, signaling a pullback or trend continuation.
Why: These conditions are tightened to capture frequent volatility spikes while filtering out noise, which is more prevalent on a 1-hour chart.
3. Exit Strategy
Profit Target: Default is 5% (adjustable from 3-7%).
Stop-Loss: Default is 3% (adjustable from 1-5%).
Why: These levels remain conservative to lock in gains quickly and limit losses, suitable for the faster pace of a 1-hour timeframe.
4. Risk Management
The strategy may trigger more trades on a 1-hour chart. To avoid overtrading:
The ATR filter ensures only volatile moves are traded.
Trading fees (e.g., 0.5% on Coinbase) reduce the net profit to ~4% on winners and -3.5% on losers, requiring a win rate above 47% for profitability.
Suggestion: Risk only 1-2% of your capital per trade to manage exposure.
5. Visuals and Alerts
Plots: Blue fast MA, red slow MA, and green triangles for buy signals.
Alerts: Trigger when an entry condition is met, so you don’t need to watch the chart constantly.
How to Use the Strategy
Setup:
Load TradingView, select BONK/USD on the 1-hour chart (Coinbase pair).
Paste the script into the Pine Editor and add it to your chart.
Customize:
Adjust the profit target (e.g., 5%) and stop-loss (e.g., 3%) to your preference.
Tweak ATR or MA lengths if BONK’s volatility shifts.
Trade:
Look for green triangle signals and confirm with market context (e.g., volume or news).
Enter trades manually or via TradingView’s broker tools if supported.
Exit when the profit target or stop-loss is hit.
Test:
Use TradingView’s Strategy Tester to backtest on historical data and refine settings.
Benefits of the 1-Hour Timeframe
Faster Opportunities: Captures shorter-term uptrends in BONK’s volatile price action.
Responsive: Adjusted indicators react quickly to hourly changes.
Conservative: Maintains the 3-7% profit goal with tight risk control.
Potential Challenges
Noise: The 1-hour chart has more false signals. The ATR and MA filters help, but caution is needed.
Fees: Frequent trading increases costs, so ensure each trade’s potential justifies the expense.
Volatility: BONK can move unpredictably—monitor broader market trends or Solana ecosystem news.
Final Thoughts
Switching to a 1-hour timeframe makes the strategy more active, targeting shorter volatility spikes while keeping profits conservative at 3-7%. The adjusted indicators and conditions balance responsiveness with reliability. Backtest it on TradingView to confirm it suits BONK’s behavior, and always use proper risk management, as meme coins are highly speculative.
Disclaimer: This is for educational purposes, not financial advice. Cryptocurrency trading, especially with assets like BONK, is risky. Test thoroughly and trade responsibly.
BTC Trading RobotOverview
This Pine Script strategy is designed for trading Bitcoin (BTC) by placing pending orders (BuyStop and SellStop) based on local price extremes. The script also implements a trailing stop mechanism to protect profits once a position becomes sufficiently profitable.
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Inputs and Parameter Setup
1. Trading Profile:
o The strategy is set up specifically for BTC trading.
o The systemType input is set to 1, which means the strategy will calculate trade parameters using the BTC-specific inputs.
2. Common Trading Inputs:
o Risk Parameters: Although RiskPercent is defined, its actual use (e.g., for position sizing) isn’t implemented in this version.
o Trading Hours Filter:
SHInput and EHInput let you restrict trading to a specific hour range. If these are set (non-zero), orders will only be placed during the allowed hours.
3. BTC-Specific Inputs:
o Take Profit (TP) and Stop Loss (SL) Percentages:
TPasPctBTC and SLasPctBTC are used to determine the TP and SL levels as a percentage of the current price.
o Trailing Stop Parameters:
TSLasPctofTPBTC and TSLTgrasPctofTPBTC determine when and by how much a trailing stop is applied, again as percentages of the TP.
4. Other Parameters:
o BarsN is used to define the window (number of bars) over which the local high and low are calculated.
o OrderDistPoints acts as a buffer to prevent the entry orders from being triggered too early.
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Trade Parameter Calculation
• Price Reference:
o The strategy uses the current closing price as the reference for calculations.
• Calculation of TP and SL Levels:
o If the systemType is set to BTC (value 1), then:
Take Profit Points (Tppoints) are calculated by multiplying the current price by TPasPctBTC.
Stop Loss Points (Slpoints) are calculated similarly using SLasPctBTC.
A buffer (OrderDistPoints) is set to half of the take profit points.
Trailing Stop Levels:
TslPoints is calculated as a fraction of the TP (using TSLTgrasPctofTPBTC).
TslTriggerPoints is similarly determined, which sets the profit level at which the trailing stop will start to activate.
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Time Filtering
• Session Control:
o The current hour is compared against SHInput (start hour) and EHInput (end hour).
o If the current time falls outside the allowed window, the script will not place any new orders.
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Entry Orders
• Local Price Extremes:
o The strategy calculates a local high and local low using a window of BarsN * 2 + 1 bars.
• Placing Stop Orders:
o BuyStop Order:
A long entry is triggered if the current price is less than the local high minus the order distance buffer.
The BuyStop order is set to trigger at the level of the local high.
o SellStop Order:
A short entry is triggered if the current price is greater than the local low plus the order distance buffer.
The SellStop order is set to trigger at the level of the local low.
Note: Orders are only placed if there is no current open position and if the session conditions are met.
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Trailing Stop Logic
Once a position is open, the strategy monitors profit levels to protect gains:
• For Long Positions:
o The script calculates the profit as the difference between the current price and the average entry price.
o If this profit exceeds the TslTriggerPoints threshold, a trailing stop is applied by placing an exit order.
o The stop price is set at a distance below the current price, while a limit (profit target) is also defined.
• For Short Positions:
o The profit is calculated as the difference between the average entry price and the current price.
o A similar trailing stop exit is applied if the profit exceeds the trigger threshold.
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Summary
In essence, this strategy works by:
• Defining entry levels based on recent local highs and lows.
• Placing pending stop orders to enter the market when those levels are breached.
• Filtering orders by time, ensuring trades are only taken during specified hours.
• Implementing a trailing stop mechanism to secure profits once the trade moves favorably.
This approach is designed to automate BTC trading based on price action and dynamic risk management, although further enhancements (like dynamic position sizing based on RiskPercent) could be added for a more complete risk management system.
Supertrend + MACD CrossoverKey Elements of the Template:
Supertrend Settings:
supertrendFactor: Adjustable to control the sensitivity of the Supertrend.
supertrendATRLength: ATR length used for Supertrend calculation.
MACD Settings:
macdFastLength, macdSlowLength, macdSignalSmoothing: These settings allow you to fine-tune the MACD for better results.
Risk Management:
Stop-Loss: The stop-loss is based on the ATR (Average True Range), a volatility-based indicator.
Take-Profit: The take-profit is based on the risk-reward ratio (set to 3x by default).
Both stop-loss and take-profit are dynamic, based on ATR, which adjusts according to market volatility.
Buy and Sell Signals:
Buy Signal: Supertrend is bullish, and MACD line crosses above the Signal line.
Sell Signal: Supertrend is bearish, and MACD line crosses below the Signal line.
Visual Elements:
The Supertrend line is plotted in green (bullish) and red (bearish).
Buy and Sell signals are shown with green and red triangles on the chart.
Next Steps for Optimization:
Backtesting:
Run backtests on BTC in the 5-minute timeframe and adjust parameters (Supertrend factor, MACD settings, risk-reward ratio) to find the optimal configuration for the 60% win ratio.
Fine-Tuning Parameters:
Adjust supertrendFactor and macdFastLength to find more optimal values based on BTC's market behavior.
Tweak the risk-reward ratio to maximize profitability while maintaining a good win ratio.
Evaluate Market Conditions:
The performance of the strategy can vary based on market volatility. It may be helpful to evaluate performance in different market conditions or pair it with a filter like RSI or volume.
Let me know if you'd like further tweaks or explanations!
Sniper Trade Pro (ES 15-Min) - Topstep Optimized🔹 Overview
Sniper Trade Pro is an advanced algorithmic trading strategy designed specifically for E-mini S&P 500 (ES) Futures on the 15-minute timeframe. This strategy is optimized for Topstep 50K evaluations, incorporating strict risk management to comply with their max $1,000 daily loss limit while maintaining a high probability of success.
It uses a multi-confirmation approach, integrating:
✅ Money Flow Divergence (MFD) → To track liquidity imbalances and institutional accumulation/distribution.
✅ Trend Confirmation (EMA + VWAP) → To identify strong trend direction and avoid choppy markets.
✅ ADX Strength Filter → To ensure entries only occur in trending conditions, avoiding weak setups.
✅ Break-Even & Dynamic Stop-Losses → To reduce drawdowns and protect profits dynamically.
This script automatically generates Buy and Sell signals and provides built-in risk management for automated trading execution through TradingView Webhooks.
🔹 How Does This Strategy Work?
📌 1. Trend Confirmation (EMA + VWAP)
The strategy uses:
✔ 9-EMA & 21-EMA: Fast-moving averages to detect short-term momentum.
✔ VWAP (Volume-Weighted Average Price): Ensures trades align with institutional volume flow.
How it works:
Bullish Condition: 9-EMA above 21-EMA AND price above VWAP → Confirms buy trend.
Bearish Condition: 9-EMA below 21-EMA AND price below VWAP → Confirms sell trend.
📌 2. Liquidity & Money Flow Divergence (MFD)
This indicator measures liquidity shifts by tracking momentum changes in price and volume.
✔ MFD Calculation:
Uses Exponential Moving Average (EMA) of Momentum (MOM) to detect changes in buying/selling pressure.
If MFD is above its moving average, it signals liquidity inflows → bullish strength.
If MFD is below its moving average, it signals liquidity outflows → bearish weakness.
Why is this important?
Detects when Smart Money is accumulating or distributing before major moves.
Filters out false breakouts by confirming momentum strength before entry.
📌 3. Trade Entry Triggers (Candlestick Patterns & ADX Filter)
To avoid random entries, the strategy waits for specific candlestick confirmations with ADX trend strength:
✔ Bullish Entry (Buy Signal) → Requires:
Bullish Engulfing Candle (Reversal confirmation)
ADX > 20 (Ensures strong trending conditions)
MFD above its moving average (Liquidity inflows)
9-EMA > 21-EMA & price above VWAP (Trend confirmation)
✔ Bearish Entry (Sell Signal) → Requires:
Bearish Engulfing Candle (Reversal confirmation)
ADX > 20 (Ensures strong trending conditions)
MFD below its moving average (Liquidity outflows)
9-EMA < 21-EMA & price below VWAP (Trend confirmation)
📌 4. Risk Management & Profit Protection
This strategy is built with strict risk management to maintain low drawdowns and maximize profits:
✔ Dynamic Position Sizing → Automatically adjusts trade size to risk a fixed $400 per trade.
✔ Adaptive Stop-Losses → Uses ATR-based stop-loss (0.8x ATR) to adapt to market volatility.
✔ Take-Profit Targets → Fixed at 2x ATR for a Risk:Reward ratio of 2:1.
✔ Break-Even Protection → Moves stop-loss to entry once price moves 1x ATR in profit, locking in gains.
✔ Max Daily Loss Limit (-$1,000) → Stops trading if total losses exceed $1,000, complying with Topstep rules.
Mile Runner - Swing Trade LONGMile Runner - Swing Trade LONG Indicator - By @jerolourenco
Overview
The Mile Runner - Swing Trade LONG indicator is designed for swing traders who focus on LONG positions in stocks, BDRs (Brazilian Depositary Receipts), and ETFs. It provides clear entry signals, stop loss, and take profit levels, helping traders identify optimal buying opportunities with a robust set of technical filters. The indicator is optimized for daily candlestick charts and combines multiple technical analysis tools to ensure high-probability trades.
Key Features
Entry Signals: Visualized as green triangles below the price bars, indicating a potential LONG entry.
Stop Loss and Take Profit Levels: Automatically plotted on the chart for easy reference.
Stop Loss: Based on the most recent pivot low (support level).
Take Profit: Calculated using a Fibonacci-based projection from the entry price to the stop loss.
Trend and Momentum Filters: Ensures trades align with the prevailing trend and have sufficient momentum.
Volume and Volatility Confirmation: Verifies market interest and price movement potential.
How It Works
The indicator uses a combination of technical tools to filter and confirm trade setups:
Exponential Moving Averages (EMAs):
A short EMA (default: 9 periods) and a long EMA (default: 21 periods) identify the trend.
A bullish crossover (EMA9 crosses above EMA21) signals a potential upward trend.
Money Flow Index (MFI):
Confirms buying pressure when MFI > 50.
Average True Range (ATR):
Ensures sufficient volatility by checking if ATR exceeds its 20-period moving average.
Volume:
Confirms market interest when volume exceeds its 20-period moving average.
Pivot Lows:
Identifies recent support levels (pivot lows) to set the stop loss.
Ensures the pivot low is recent (within the last 10 bars by default).
Additional Trend Filter:
Confirms the long EMA is rising, reinforcing the bullish trend.
Inputs and Customization
The indicator is highly customizable, allowing traders to tailor it to their strategies:
EMA Periods: Adjust the short and long EMA lengths.
ATR and MFI Periods: Modify lookback periods for volatility and momentum.
Pivot Lookback: Control the sensitivity of pivot low detection.
Fibonacci Level: Adjust the Fibonacci retracement level for take profit.
Take Profit Multiplier: Fine-tune the aggressiveness of the take profit target.
Max Pivot Age: Set the maximum bars since the last pivot low for relevance.
Usage Instructions
Apply the Indicator:
Add the "Mile Runner - Swing Trade LONG" indicator to your TradingView chart.
Best used on daily charts for swing trading.
Look for Entry Signals:
A green triangle below the price bar signals a potential LONG entry.
Set Stop Loss and Take Profit:
Stop Loss: Red dashed line indicating the stop loss level.
Take Profit: Purple dashed line showing the take profit level.
Monitor the Trade:
The entry price is marked with a green dashed line for reference.
Adjust trade management based on the plotted levels.
Set Alerts:
Use the built-in alert condition to get notified of new LONG entry signals.
Important Notes
For LONG Positions Only : Designed exclusively for swing trading LONG positions.
Timeframe: Optimized for daily charts but can be tested on other timeframes.
Asset Types: Works best with stocks, BDRs, and ETFs.
Risk Management: Always align stop loss and take profit levels with your risk tolerance.
Why Use Mile Runner?
The Mile Runner indicator simplifies swing trading by integrating trend, momentum, volume, and volatility filters into one user-friendly tool. It helps traders:
Identify high-probability entry points.
Establish clear stop loss and take profit levels.
Avoid low-volatility or low-volume markets.
Focus on assets with strong buying pressure and recent support.
By following its signals and levels, traders can make informed decisions and enhance their swing trading performance. Customize the inputs and test it on your favorite assets—happy trading!
RV- Intrinsic Value AnalyzerWhy These Metrics Matter in IVA Pro (Intrinsic Value Analyzer)?
The IVA Pro consolidates key valuation, profitability, and efficiency metrics into a single, easy-to-read table. These indicators provide a comprehensive view of a company’s financial health, helping traders and investors make informed decisions based on growth potential, profitability, and valuation. The color-coded signals (green for strong, orange for moderate, and red for weak values) simplify fundamental analysis and enable quick comparisons across different stocks.
Key Fundamental Parameters in IVA Pro
Market Capitalization (Market Cap): Measures a company's total market value, helping assess size, stability, and growth potential.
Earnings Yield (TTM): Indicates how much profit a company generates relative to its stock price—useful for comparing against bonds and other assets.
Return on Capital Employed (ROCE): Shows how efficiently a company generates profits using its capital—a key profitability metric.
Return on Equity (ROE): Evaluates how well a company uses shareholder funds to generate earnings.
Price-to-Earnings Ratio (PE): Helps determine whether a stock is overvalued or undervalued based on earnings.
Price-to-Book Ratio (PB): Assesses if a stock is trading above or below its net asset value—useful for asset-heavy industries.
Price-to-Sales Ratio (PS): Helps evaluate revenue potential, particularly for growth-stage companies.
PEG Ratio: Enhances PE ratio by factoring in earnings growth—ideal for identifying undervalued growth stocks.
Forward PE Ratio: Provides a future-looking valuation based on projected earnings.
Forward PS Ratio: Helps evaluate future revenue potential and overall stock valuation.
JMA Quantum Edge: Adaptive Precision Trading System JMA Quantum Edge: Adaptive Precision Trading System - Enhanced Visuals & Risk Management
Get ready to experience a groundbreaking trading strategy that adapts in real-time to market conditions! This powerful, open-source script combines advanced technical analysis with state-of-the-art risk management tools, designed to give you the edge you need in today's dynamic markets.
What It Does:
Adaptive JMA Indicator:
Utilizes a custom Jurik Moving Average (JMA) that adjusts its sensitivity based on market volatility, ensuring you get precise signals even in the most fluctuating environments.
Dynamic Risk Management:
Features built-in support for partial exits (scaling out) to secure profits, along with an optional Kelly Criterion-based position sizing that tailors your exposure based on historical performance metrics.
Robust Error Handling:
Incorporates market condition filters—like minimum volume and maximum allowed gap percentage—to ensure trades are only executed under favorable conditions.
Vivid Visual Enhancements:
Enjoy an animated background that reflects market momentum, dynamic pivot markers, and clearly drawn trend channels. Plus, interactive tables provide real-time performance analytics and detailed error metrics.
Fully Customizable:
With a comprehensive set of inputs, you can easily tailor the strategy to your personal trading style and market preferences. Adjust everything from JMA parameters to refresh intervals for tables and labels!
How to Use It:
Add the Script:
Copy and paste the script into the Pine Script Editor on TradingView and click “Add to Chart.”
Configure Your Settings:
Customize your risk management (capital, commission, position sizing, partial exits, etc.) and tweak the JMA settings to match your preferred trading style. Use the extensive input panel to adjust visuals, alerts, and more.
Backtest & Optimize:
Run the strategy in the Strategy Tester to analyze its historical performance. Monitor real-time analytics and error metrics via the interactive tables, and fine-tune your parameters for optimal performance.
Go Live with Confidence:
Once you're satisfied with the backtest results, use the generated signals for live trading, and let the system help you stay ahead in fast-paced markets!
How to use the imputs:
This cutting-edge strategy is designed to adapt to changing market conditions and offers you complete control over your trading parameters. Here’s a breakdown of what each group of inputs does and how you should use them:
Risk Management & Trade Settings
Recalculate on Every Tick:
What it does: When enabled, the strategy recalculates on every price update.
Recommendation: Leave it true for fast charts.
Initial Capital:
What it does: Sets your starting capital for backtesting, which influences position sizing and performance metrics.
Recommendation: Start with $10,000 (or adjust according to your trading capital).
Commission (%):
What it does: Simulates the cost per trade.
Recommendation: Use a realistic rate (e.g., 0.04%).
Position Size & Quantity Type:
What they do: Define how large each trade will be. Choose between a fixed unit amount or a percentage of equity.
Recommendation: For beginners, the default fixed value is a good start. Experiment later with percentage-based sizing if needed.
Order Comment:
What it does: Adds a label to your orders for easier tracking.
Allow Reverse Orders:
What it does: If disabled, the strategy will close opposing positions before entering a new trade, reducing conflicts.
Enable Dynamic Position Sizing:
What it does: Adjusts trade size based on current volatility.
Recommendation: Beginners may start with this disabled until they understand basic sizing.
Partial Exit Inputs:
What they do:
Enable Partial Exits: When turned on, you can scale out of your position to lock in profits.
Partial Exit Profit (%): The profit percentage that triggers a partial exit.
Partial Exit Percentage: The percentage of your current position to exit. Recommendation: Use defaults (e.g., 5% profit, 50% exit) to secure profits gradually.
Kelly Criterion Option:
What it does: When enabled, adjusts your position sizing using historical performance (win rate and profit factor).
Recommendation: Beginners might leave this disabled until comfortable with backtest performance metrics.
Market Condition Filters:
What they do:
Minimum Volume: Ensures trades occur only when there’s sufficient market activity.
Maximum Gap (%): Prevents trading if there’s an unusually large gap between the previous close and current open. Recommendation: Defaults work well for most markets. If trades seem erratic, consider tightening these limits.
JMA Settings
Price Source:
What it does: The input series for the JMA calculation, typically set to the closing price.
JMA Length:
What it does: Controls the smoothing period of the JMA. Lower values are more sensitive; higher values smooth out the noise. Recommendation: Start with 21.
JMA Phase & Power:
What they do: Adjust how responsive the JMA is. Phase controls timing; power adjusts the intensity. Recommendation: Default settings (63 phase and 3 power) are a balanced starting point.
Visual Settings & Style
Show JMA Line, Pivot Lines, and Pivot Labels:
What they do: Toggle visual elements on your chart for easier signal identification.
Pivot History Count:
What it does: Limits how many historical pivot markers are displayed.
Color Settings (Up/Down Neon Colors):
What they do: Set the visual cues for buy and sell signals.
Pivot Marker & Line Style:
What they do: Choose the style and thickness of your pivot markers and lines.
Show Stats Panel:
What it does: Displays real-time performance and error metrics.
Dynamic Background & Visual Enhancements
Animate Background:
What it does: Changes the background color based on market momentum.
Show Trend Channels & Volume Zones:
What they do: Draw trend channels and highlight areas of high volatility/volume.
Show Data-Rich Labels:
What it does: Displays key metrics like volume, error percentage, and momentum on the chart.
High Volatility Threshold:
What it does: Determines the multiplier for when the chart background should change due to high volatility.
Multi-Timeframe Settings
Higher Timeframe:
What it does: Uses a higher timeframe’s JMA for trend confirmation. Recommendation: Use Daily ('D') or Weekly ('W') for broader trend analysis.
Show HTF Trend Zone & Opacity:
What they do: Display a visual zone from the higher timeframe to help confirm trends.
6. Trailing Stop Settings
Trailing Stop ATR Factor & Offset Multiplier:
What they do: Calculate trailing stops based on the Average True Range (ATR), adjusting stop distances dynamically. Recommendation: Default settings are a good balance but can be fine-tuned based on asset volatility.
Alerts & Notifications
Alerts on Pivot Formation & JMA Crossover:
What they do: Notify you when key events occur.
Dynamic Power Threshold:
What it does: Sets the sensitivity for dynamic alerts.
8. Static Stop Loss / Take Profit
Static Stop Loss (%) & Take Profit (%):
What they do: Allow you to set fixed stop loss or take profit levels. Recommendation: Leave them at 0 to disable if you prefer dynamic risk management, or set them if you have strict risk/reward preferences.
Advanced Settings
ATR Length:
What it does: Determines the period for ATR calculation, impacting trailing stop sensitivity. Recommendation: Start with 14.
Optimization Feedback & Enhanced Error Analysis
Error Metric Length & Error Threshold (%):
What they do: Calculate error metrics (like average error, skewness, and kurtosis) to help you fine-tune the JMA. Recommendation: Use the defaults and adjust if the error metrics seem off during backtesting.
UI - User-Driven Tweaking & Table Customization
Parameter Tweaker Panel, Debug/Performance Table Settings:
What they do: Provide interactive tables that display real-time performance, error metrics, and allow you to monitor strategy parameters.
Refresh Frequency Options (Table & Label Refresh Intervals):
What they do: Set how often the tables and labels update.
Recommendation: Start with an interval of 1 bar; increase it if your chart is too busy.
Important for Beginners:
Default Settings:
All default values have been chosen for balanced performance across different markets. If you ever experience unexpected behavior, start by resetting the inputs to their defaults.
Step-by-Step Adjustments:
Experiment by changing one setting at a time while observing how the strategy’s signals and performance metrics change. This will help you understand the impact of each parameter.
Resetting to Defaults:
If things seem off or you’re not getting the expected results, you can always reset the indicator. Either reload the script or use the “Reset Inputs” option (if available) to revert to the default settings.
Jump in, experiment, and enjoy the power of adaptive precision trading. This strategy is built to grow with your skills—have fun exploring and refining your trading edge!
Happy trading!
SL Hunting Detector📌 Step 1: Identify Liquidity Zones
The script plots high-liquidity zones (red) and low-liquidity zones (green).
These are areas where big players target stop-losses before reversing the price.
Example:
If price is near a red liquidity zone, expect a potential stop-loss hunt & reversal downward.
If price is near a green liquidity zone, expect a potential stop-loss hunt & reversal upward.
📌 Step 2: Watch for Stop-Loss Hunts (Fakeouts)
The indicator marks stop-loss hunts with red (bearish) or green (bullish) arrows.
When do stop-loss hunts occur?
✅ A long wick below support (with high volume) = Stop hunt before reversal upward.
✅ A long wick above resistance (with high volume) = Stop hunt before reversal downward.
Confirmation:
Volume must spike (volume > 1.5x the average volume).
ATR-based wicks must be longer than usual (showing a stop-hunt trap).
📌 Step 3: Enter a Trade After a Stop-Hunt
🔹 Bullish Trade (Buying a Dip)
If a green arrow appears (stop-hunt below support):
✅ Enter a long (buy) trade at or just above the wick’s recovery level.
✅ Stop-loss: Below the wick’s low (avoid getting hunted again).
✅ Take-profit: Next resistance level or mid-range of the liquidity zone.
🔹 Bearish Trade (Shorting a Fakeout)
If a red arrow appears (stop-hunt above resistance):
✅ Enter a short (sell) trade at or just below the wick’s rejection level.
✅ Stop-loss: Above the wick’s high (avoid getting stopped out).
✅ Take-profit: Next support level or mid-range of the liquidity zone.
📌 Step 4: Set Alerts & Automate
✅ The indicator triggers alerts when a stop-hunt is detected.
✅ You can set TradingView to notify you instantly when:
A bullish stop-hunt occurs → Look for long entry.
A bearish stop-hunt occurs → Look for short entry.
📌 Example Trade Setup
Example (BTC Long Trade on Stop-Hunt)
BTC is near $40,000 support (green liquidity zone).
A long wick drops to $39,800 with a green arrow (bullish stop-hunt signal).
Volume spikes, and price recovers quickly back above $40,000.
Trade entry: Buy at $40,050.
Stop-loss: Below wick ($39,700).
Take-profit: $41,500 (next resistance).
Result: BTC pumps, stop-loss remains safe, and trade profits.
🔥 Final Tips
Always wait for confirmation (don’t enter blindly on signals).
Use higher timeframes (15m, 1H, 4H) for better accuracy.
Combine with Order Flow tools (like Bookmap) to see real liquidity zones.
🚀 Now try it on TradingView! Let me know if you need adjustments. 📈🔥
Pure Price Action Breakout with 1:5 RR
Description of the Price Action Trading Script (Pine Script v6)
Overview
This script is a pure price action-based breakout strategy designed for TradingView. It identifies key breakout levels and executes long and short trades based on market structure. The strategy ensures a minimum risk-to-reward ratio (RR) of 1:5, aiming for high profitability with well-defined stop-loss and take-profit levels.
How the Script Works
1️⃣ Breakout Identification
The script uses a lookback period to find the highest high and lowest low over the last n bars.
A bullish breakout occurs when the price closes above the previous highest high.
A bearish breakout happens when the price closes below the previous lowest low.
2️⃣ Entry & Exit Strategy
Long Entry: If a bullish breakout is detected, the script enters a long position.
Short Entry: If a bearish breakout is detected, the script enters a short position.
The stop-loss is placed at the recent swing low (for long trades) or recent swing high (for short trades).
The target price is calculated based on a risk-to-reward ratio of 1:5, ensuring profitable trades.
3️⃣ Risk Management
The stop-loss prevents excessive losses by exiting trades when the market moves unfavorably.
The strategy ensures that each trade has a reward potential at least 5 times the risk.
Positions are executed based on price action only, without indicators like moving averages or RSI.
4️⃣ Visual Representation
The script plots breakout levels to help traders visualize potential trade setups.
Entry points, stop-loss, and take-profit levels are labeled on the chart for easy tracking.
Key Features & Benefits
✔ Pure Price Action – No lagging indicators, only real-time price movements.
✔ High Risk-to-Reward Ratio (1:5) – Ensures high-profit potential trades.
✔ Real-time Entry & Exit Signals – Provides accurate trade setups.
✔ Dynamic Stop-loss Calculation – Adjusts based on recent market structure.
✔ Customizable Parameters – Lookback periods and risk ratios can be modified.
Enhanced Bollinger Bands Strategy with SL/TP// Title: Enhanced Bollinger Bands Strategy with SL/TP
// Description:
// This strategy is based on the classic Bollinger Bands indicator and incorporates Stop Loss (SL) and Take Profit (TP) levels for automated trading. It identifies potential long and short entry points based on price crossing the lower and upper Bollinger Bands, respectively. The strategy allows users to customize several parameters to suit different market conditions and risk tolerances.
// Key Features:
// * **Bollinger Bands:** Uses Simple Moving Average (SMA) as the basis and calculates upper and lower bands based on a user-defined standard deviation multiplier.
// * **Customizable Parameters:** Offers extensive customization, including SMA length, standard deviation multiplier, Stop Loss (SL) in pips, and Take Profit (TP) in pips.
// * **Long/Short Position Control:** Allows users to independently enable or disable long and short positions.
// * **Stop Loss and Take Profit:** Implements Stop Loss and Take Profit levels based on pip values to manage risk and secure profits. Entry prices are set to the band levels on signals.
// * **Visualizations:** Provides options to display Bollinger Bands and entry signals on the chart for easy analysis.
// Strategy Logic:
// 1. **Bollinger Bands Calculation:** The strategy calculates the Bollinger Bands using the specified SMA length and standard deviation multiplier.
// 2. **Entry Conditions:**
// * **Long Entry:** Enters a long position when the closing price crosses above the lower Bollinger Band and the `Enable Long Positions` setting is enabled.
// * **Short Entry:** Enters a short position when the closing price crosses below the upper Bollinger Band and the `Enable Short Positions` setting is enabled.
// 3. **Exit Conditions:**
// * **Stop Loss:** Exits the position if the price reaches the Stop Loss level, calculated based on the input `Stop Loss (Pips)`.
// * **Take Profit:** Exits the position if the price reaches the Take Profit level, calculated based on the input `Take Profit (Pips)`.
// Input Parameters:
// * **SMA Length (length):** The length of the Simple Moving Average used to calculate the Bollinger Bands (default: 20).
// * **Standard Deviation Multiplier (mult):** The multiplier applied to the standard deviation to determine the width of the Bollinger Bands (default: 2.0).
// * **Enable Long Positions (enableLong):** A boolean value to enable or disable long positions (default: true).
// * **Enable Short Positions (enableShort):** A boolean value to enable or disable short positions (default: true).
// * **Pip Value (pipValue):** The value of a pip for the traded instrument. This is crucial for accurate Stop Loss and Take Profit calculations (default: 0.0001 for most currency pairs). **Important: Adjust this value to match the specific instrument you are trading.**
// * **Stop Loss (Pips) (slPips):** The Stop Loss level in pips (default: 10).
// * **Take Profit (Pips) (tpPips):** The Take Profit level in pips (default: 20).
// * **Show Bollinger Bands (showBands):** A boolean value to show or hide the Bollinger Bands on the chart (default: true).
// * **Show Entry Signals (showSignals):** A boolean value to show or hide entry signals on the chart (default: true).
// How to Use:
// 1. Add the strategy to your TradingView chart.
// 2. Adjust the input parameters to optimize the strategy for your chosen instrument and timeframe. Pay close attention to the `Pip Value`.
// 3. Backtest the strategy over different periods to evaluate its performance.
// 4. Use the `Enable Long Positions` and `Enable Short Positions` settings to customize the strategy for specific market conditions (e.g., only long positions in an uptrend).
// Important Notes and Disclaimers:
// * **Backtesting Results:** Past performance is not indicative of future results. Backtesting results can be affected by various factors, including market volatility, slippage, and transaction costs.
// * **Risk Management:** This strategy is provided for informational and educational purposes only and should not be considered financial advice. Always use proper risk management techniques when trading. Adjust Stop Loss and Take Profit levels according to your risk tolerance.
// * **Slippage:** The strategy takes into account slippage by specifying a slippage parameter on the `strategy` declaration. However, real-world slippage may vary.
// * **Market Conditions:** The performance of this strategy can vary significantly depending on market conditions. It may perform well in trending markets but poorly in ranging or choppy markets.
// * **Pip Value Accuracy:** **Ensure the `Pip Value` is correctly set for the specific instrument you are trading. Incorrect pip value will result in incorrect stop loss and take profit placement.** This is critical.
// * **Broker Compatibility:** The strategy's performance may vary depending on your broker's execution policies and fees.
// * **Disclaimer:** I am not a financial advisor, and this script is not financial advice. Use this strategy at your own risk. I am not responsible for any losses incurred while using this strategy.
High-Probability IndicatorExplanation of the Code
Trend Filter (EMA):
A 50-period Exponential Moving Average (EMA) is used to determine the overall trend.
trendUp is true when the price is above the EMA.
trendDown is true when the price is below the EMA.
Momentum Filter (RSI):
A 14-period RSI is used to identify overbought and oversold conditions.
oversold is true when RSI ≤ 30.
overbought is true when RSI ≥ 70.
Volatility Filter (ATR):
A 14-period Average True Range (ATR) is used to measure volatility.
ATR is multiplied by a user-defined multiplier (default: 2.0) to set a volatility threshold.
Ensures trades are only taken during periods of sufficient volatility.
Entry Conditions:
Long Entry: Price is above the EMA (uptrend), RSI is oversold, and the candle range exceeds the ATR threshold.
Short Entry: Price is below the EMA (downtrend), RSI is overbought, and the candle range exceeds the ATR threshold.
Exit Conditions:
Take Profit: A fixed percentage above/below the entry price.
Stop Loss: A fixed percentage below/above the entry price.
Visualization:
The EMA is plotted on the chart.
Background colors highlight uptrends and downtrends.
Buy and sell signals are displayed as labels on the chart.
Alerts:
Alerts are triggered for buy and sell signals.
How to Use the Indicator
Trend Filter:
Only take trades in the direction of the trend (e.g., long in an uptrend, short in a downtrend).
Momentum Filter:
Look for oversold conditions in an uptrend for long entries.
Look for overbought conditions in a downtrend for short entries.
Volatility Filter:
Ensure the candle range exceeds the ATR threshold to avoid low-volatility trades.
Risk Management:
Use the built-in take profit and stop loss levels to manage risk.
Optimization Tips
Backtesting:
Test the indicator on multiple timeframes and assets to evaluate its performance.
Adjust the input parameters (e.g., EMA length, RSI length, ATR multiplier) to optimize for specific markets.
Combination with Other Strategies:
Add additional filters, such as volume analysis or support/resistance levels, to improve accuracy.
Risk Management:
Use proper position sizing and risk-reward ratios to maximize profitability.
Disclaimer
No indicator can guarantee an 85% win ratio due to the inherent unpredictability of financial markets. This script is provided for educational purposes only. Always conduct thorough backtesting and paper trading before using any strategy in live trading.
Let me know if you need further assistance or enhancements!
