Strategy Overview
The Smart Money Reversal Trading Strategy is a quantitative trading approach that combines the Relative Strength Index (RSI) with Smart Money behavior detection. This strategy aims to identify high-probability reversal points in trending markets through strict entry and exit rules, coupled with a 10% hard stop-loss for effective risk management. The core logic focuses on capturing potential reversal opportunities in overbought or oversold market conditions accompanied by unusual trading volume and price extremes, which often represent institutional money (Smart Money) involvement.

Strategy Principles
Through in-depth code analysis, the strategy's principles can be broken down into the following key components:

Entry Conditions:

• Long Entry (Buy): RSI below 38 (oversold condition), accompanied by "Smart Money" confirmation signals, including a bullish candle (closing price higher than opening price), volume greater than the 10-period volume SMA, and price touching the lowest point of 10 candles.
• Short Entry (Sell): RSI above 80 (overbought condition), accompanied by "Smart Money" confirmation signals, including a bearish candle (closing price lower than opening price), volume greater than the 10-period volume SMA, and price touching the highest point of 10 candles.

Exit Conditions:

• Long Exit: RSI reaches or exceeds 70 (entering overbought territory)
• Short Exit: RSI reaches or falls below 40 (early profit-taking)
• Stop-Loss: All trades have a 20% hard stop-loss

Position Management:

• No overlapping trades (only one position can be held at a time)
• Stop-loss line visualized on the chart (red line)

The strategy uses a 19-period RSI as the primary indicator, combined with volume and price extremes to confirm "Smart Money" behavior. This combination effectively filters out false breakouts and reversal signals.

Strategy Advantages
Deep analysis of the strategy code reveals the following significant advantages:

1. Counter-Trend Capture Capability: The strategy focuses on capturing reversal points in overbought and oversold areas, often allowing entry at more favorable prices compared to trend-following strategies.

2. Smart Money Confirmation Mechanism: By combining price action (candle patterns), unusual volume, and price extremes in a triple confirmation approach, the strategy greatly enhances signal reliability, avoiding false signals that might occur when relying solely on the RSI indicator.

3. Asymmetric Risk Management: The strategy applies different exit standards for long and short positions. Long positions are held until the RSI reaches 70 (fully overbought), while short positions take profit earlier when the RSI reaches 40. This asymmetric design aligns with the general market principle that "prices rise slowly but fall quickly."

4. Strict Risk Control: The 20% hard stop-loss effectively prevents large drawdowns, protecting capital safety.

5. Minimal Parameter Optimization: The strategy uses relatively simple parameters with sound market logic foundations, avoiding over-optimization, which enhances its robustness and adaptability.

Strategy Risks
Despite the rational design, the strategy still has the following potential risks:

1. False Reversal Signal Risk: Although the strategy uses multiple confirmations to filter false signals, in strong trending markets, prices may continue their original trend after briefly touching overbought or oversold zones, causing the strategy to generate incorrect signals. Solution: Consider adding a trend filter to only open positions in specific trend directions.

2. Large Stop-Loss Percentage: The current 20% stop-loss percentage is relatively large and may lead to significant single-trade losses in highly volatile markets. Solution: Dynamically adjust the stop-loss percentage based on market volatility or adopt a trailing stop-loss strategy.

3. Parameter Sensitivity: The choice of RSI parameters (19), overbought/oversold thresholds (38/80), and volume SMA period (10) significantly affects strategy performance. Solution: Conduct robustness testing to understand how parameter changes impact strategy performance.

4. Liquidity Risk: In low-liquidity markets, large buy or sell orders may cause slippage, affecting actual execution prices. Solution: Add liquidity filtering conditions to avoid trading during low-liquidity periods.

5. Fixed Exit Condition Limitations: Fixed RSI exit levels may lead to premature position closing in strong trends. Solution: Consider dynamically adjusting exit conditions based on trend strength indicators.

Strategy Optimization Directions
Based on code analysis, the strategy can be optimized in the following directions:

1. Dynamic RSI Thresholds: The current strategy uses fixed RSI thresholds (38/80). Consider dynamically adjusting these thresholds based on market volatility or trend strength. For example, in strong trending markets, RSI may remain in overbought/oversold territory for extended periods, warranting higher thresholds. This optimization can reduce false reversal signals in strong trends.

2. Intelligent Stop-Loss Mechanism: Replace the fixed percentage stop-loss with a volatility-based ATR stop-loss or trailing stop-loss to better adapt to different market environments. ATR stop-loss can adjust the stop-loss distance based on actual market volatility, better aligning with market characteristics.

3. Trading Session Filtering: Add trading session filters to avoid low-liquidity or high-volatility periods, reducing risks from slippage and abnormal price fluctuations.

4. Multi-Timeframe Confirmation: Introduce multi-timeframe analysis, requiring that the trend direction in higher timeframes aligns with the trading direction, which can improve the strategy's win rate. For example, when going long on a 4-hour chart, require that the daily trend is also upward.

5. Staged Profit-Taking: The current strategy closes positions entirely at once. Consider a staged profit-taking strategy, such as closing 50% of the position at the first target and setting a trailing stop-loss for the remainder to track the trend. This approach balances short-term profits with capturing larger market movements.

6. Incorporate Moving Average Systems: Combine medium and long-term moving averages as trend filters, only looking for long opportunities when prices are above the moving average and short opportunities when prices are below, avoiding the risk of trading against major trends.

Conclusion
The Smart Money Reversal Trading Strategy skillfully combines the RSI indicator with Smart Money behavior detection, providing a systematic solution for trend reversal trading. The strategy's greatest strength lies in its multiple confirmation mechanisms, effectively filtering out false signals and improving the win rate of trades. At the same time, its asymmetric exit design and strict risk control enable the strategy to maintain relatively stable performance across different market environments.

Nevertheless, there is still room for optimization, particularly in dynamic parameter adjustment, intelligent stop-loss mechanisms, and multi-timeframe confirmation. Through these optimizations, the strategy's robustness and adaptability can be further enhanced, allowing it to perform well under various market conditions.

For quantitative traders, this strategy provides a framework worth referencing, especially its method for detecting "Smart Money" behavior, which can be applied to various trading strategies. With reasonable parameter settings and risk management, this strategy has the potential to become a powerful weapon in a trader's toolkit.

Strategy source code

/*backtest
start: 2024-06-05 00:00:00
end: 2025-06-04 00:00:00
period: 2d
basePeriod: 2d
exchanges: [{"eid":"Futures_Binance","currency":"ETH_USDT"}]
*/

//@version=6
strategy("GStrategy XRP 4h", overlay=true, margin_long=100, margin_short=100, pyramiding=0)

// RSI settings
rsiLength = input(19, "RSI Length")
oversold = input(38, "Oversold level")
overbought = input(80, "Overbought level")
exitLongLevel = input(70, "Long Exit Level")
exitShortLevel = input(40, "Short Exit Level") // Added exit level for short
stopLossPerc = input.float(20.0, "Stop loss %", minval=0.1, step=0.1) / 100

// RSI calculation
rsi = ta.rsi(close, rsiLength)

// Smart Money Indicators
smartMoneyLong = (close > open) and (volume > ta.sma(volume, 10)) and (low == ta.lowest(low, 10))

smartMoneyShort = (close < open) and (volume > ta.sma(volume, 10)) and (high == ta.highest(high, 10))

// Checking for an open position
noActivePosition = strategy.position_size == 0

// Entry conditions
enterLong = (rsi < oversold) and smartMoneyLong and noActivePosition
enterShort = (rsi > overbought) and smartMoneyShort and noActivePosition

// Exit conditions
exitLong = rsi >= exitLongLevel
exitShort = rsi <= exitShortLevel // Using the new parameter to exit the short

// Execution of strategy with stop loss
if (enterLong)
    strategy.entry("Long", strategy.long)
    strategy.exit("Stop Loss Long", "Long", stop=strategy.position_avg_price * (1 - stopLossPerc))

if (enterShort)
    strategy.entry("Short", strategy.short)
    strategy.exit("Stop Loss Short", "Short", stop=strategy.position_avg_price * (1 + stopLossPerc))

if (exitLong)
    strategy.close("Long")

if (exitShort)
    strategy.close("Short")

// Visualization
plotshape(enterLong, style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small, title="Long Signal")
plotshape(enterShort, style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small, title="Short Signal")
plot(rsi, "RSI", color=color.blue)
hline(oversold, "Oversold", color=color.green)
hline(overbought, "Overbought", color=color.red)
hline(exitShortLevel, "Exit Short Level", color=color.orange) // Added short exit level line

// Stop Loss Visualization
stopLossLongLevel = strategy.position_avg_price * (1 - stopLossPerc)
stopLossShortLevel = strategy.position_avg_price * (1 + stopLossPerc)
plot(strategy.position_size > 0 ? stopLossLongLevel : na, "Stop Loss Long", color=color.red, style=plot.style_linebr)
plot(strategy.position_size < 0 ? stopLossShortLevel : na, "Stop Loss Short", color=color.red, style=plot.style_linebr)

Strategy parameters

The original address: Smart Money Reversal Trading Strategy with RSI and Volume Confirmation