Overview
This strategy is a trend-following trading system that combines Exponential Moving Averages (EMA) and Simple Moving Averages (SMA). It generates trading signals based on the crossover of EMA50 and EMA150, uses SMA150 as a stop-loss line, and includes a re-entry mechanism after stop-loss. This design enables both medium to long-term trend capture and effective risk control.

Strategy Principles
The core logic includes several key elements:

1. Entry signals: Long positions are triggered when EMA50 crosses above EMA150; short positions when EMA50 crosses below EMA150.
2. Stop-loss mechanism: Positions are closed when price falls below SMA150.
3. Re-entry mechanism: After a stop-loss, re-entry long positions are triggered when price breaks above EMA150; short positions when EMA50 crosses below EMA150 again.
4. Trade execution: The strategy executes trades within a specified time range, considering 0.1% commission and 3 pips slippage.

Strategy Advantages

1. Strong trend-following capability: Effectively captures market trends using different period moving average combinations.
2. Comprehensive risk control: Clear stop-loss conditions prevent excessive losses.
3. Flexible re-entry mechanism: Allows re-entry when market conditions improve, increasing profit opportunities.
4. Reasonable parameter settings: EMA50 and EMA150 periods balance sensitivity and stability.
5. Considers actual trading costs: Includes commission and slippage factors, closer to real trading environment.

Strategy Risks

1. Volatile market risk: May generate frequent false breakout signals in sideways markets.
2. Lag risk: Moving averages have inherent lag, potentially missing optimal entry points.
3. Re-entry risk: Consecutive stop-losses may occur in highly volatile markets.
4. Money management risk: Strategy lacks specific position sizing rules.
5. Market environment dependence: Strategy performance may vary significantly across different market cycles.

Optimization Directions

1. Incorporate volatility indicators: Add ATR or Bollinger Bands to adjust stop-loss positions adaptively.
2. Improve position management: Implement volatility-based dynamic position sizing system.
3. Optimize re-entry conditions: Combine with oscillators like RSI to improve re-entry signal accuracy.
4. Add market environment filters: Include trend strength indicators to reduce trading frequency in low-trend markets.
5. Develop adaptive parameters: Dynamically adjust moving average periods based on market volatility.

Summary
This is a well-designed trend-following strategy that captures trends through moving average crossovers and includes comprehensive risk control mechanisms. Its main strengths lie in systematic trend-following capability and risk management design, but market environment impact needs consideration in practical application. The strategy has potential for further improvement through the suggested optimization directions.

Strategy source code

/*backtest
start: 2024-02-22 00:00:00
end: 2025-02-19 08:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Binance","currency":"SOL_USDT"}]
*/

//@version=6
strategy("EMA 50 and EMA 150 with SMA150 Stop-loss and Re-Entry #ganges", overlay=true, commission_type=strategy.commission.percent, commission_value=0.1, slippage=3)



// EMA and SMA Calculations
ema50 = ta.ema(close, 50)
ema150 = ta.ema(close, 150)
sma150 = ta.sma(close, 150)

// Conditions for Buy, Sell, and Stop-Loss
ema50CrossAboveEMA150 = ta.crossover(ema50, ema150)  // Buy signal
ema50CrossBelowEMA150 = ta.crossunder(ema50, ema150) // Sell signal
priceCrossAboveEMA150 = ta.crossover(close, ema150) // Price crosses EMA 150 from below
priceCloseBelowSMA150 = close < sma150              // Stop-loss for long positions



// Track stop-loss hit state
var bool stopLossHit = false

// Strategy Logic
// Buy Logic: EMA 50 crosses EMA 150 from below
if ema50CrossAboveEMA150 
    strategy.entry("Buy Signal", strategy.long, qty=1)
    stopLossHit := false // Reset stop-loss state when a new buy position is opened

// Sell Logic: EMA 50 crosses EMA 150 from above
if ema50CrossBelowEMA150 
    strategy.entry("Sell Signal", strategy.short, qty=1)
    stopLossHit := false // Reset stop-loss state when a new sell position is opened

// Stop-Loss for Long Positions: Close if price falls below SMA 150
if strategy.position_size > 0 and priceCloseBelowSMA150
    strategy.close("Buy Signal")
    stopLossHit := true // Mark stop-loss hit

// Re-Entry Logic After Stop-Loss
if stopLossHit 
    if priceCrossAboveEMA150 // Re-buy logic: PRICE crosses EMA 150 from below
        strategy.entry("Re-Buy Signal", strategy.long, qty=1)
        stopLossHit := false // Reset stop-loss state after re-entry
    if ema50CrossBelowEMA150 // Re-sell logic: EMA 50 crosses EMA 150 from above
        strategy.entry("Re-Sell Signal", strategy.short, qty=1)
        stopLossHit := false // Reset stop-loss state after re-entry

// Plot EMA and SMA Lines
plot(ema50, color=color.blue, title="EMA 50")
plot(ema150, color=color.red, title="EMA 150")
plot(sma150, color=color.orange, title="SMA 150")


// // Calculate Recent All-Time High
// highestHigh = ta.highest(high, 500) // Lookback period of 500 bars
// percentageFall = ((highestHigh - close) / highestHigh) * 100

// // Display Percentage Fall on the Most Recent Candle Only
// isLastBar = bar_index == ta.max(bar_index)
// if isLastBar
//     labelText = str.tostring(percentageFall, "#.##") + "% Fall from ATH"
//     labelPosition = high + ta.atr(14) * 2 // Positioning label above the candle
//     label.new(bar_index, labelPosition, labelText, color=color.red, textcolor=color.white, size=size.small, style=label.style_label_down)

The original address: EMA Cross Trend Following Strategy with SMA Stop-Loss and Re-Entry Mechanism