Strategy Analyzer

Deep analysis of trading strategies using AI

Strategy Selection

Choose a strategy to analyze

Golden Cross

EMA 50/200 Crossover

RSI Divergence

4H Timeframe

Volume Spike

Daily Breakouts

AI Analysis Results

Comprehensive breakdown of the strategy

Strategy Effectiveness
78% Success Probability
Market Conditions
65% Current Fit
Risk Level
Medium Risk

Key Insights

  • This strategy performs best in trending markets with clear direction
  • Effectiveness decreases during periods of high volatility or ranging markets
  • Optimal when combined with volume confirmation (increases win rate by ~15%)
  • Consider adding a stop-loss at 1.5x the average true range for better risk management
  • Backtest shows 12% improvement on 4H timeframe vs daily in current market conditions

Recommended Parameters

Parameter Default Optimized Improvement
Short EMA 50 42 +5.2%
Long EMA 200 185 +3.8%
Stop Loss 2% 1.5% +7.1%
Take Profit 4% 3.2% +2.9%

Pine Script Code

//@version=5
strategy("Optimized Golden Cross", overlay=true)

// Inputs
shortEma = input(42, title="Short EMA Length")
longEma = input(185, title="Long EMA Length")
slPerc = input(1.5, title="Stop Loss %") / 100
tpPerc = input(3.2, title="Take Profit %") / 100

// Calculations
emaShort = ta.ema(close, shortEma)
emaLong = ta.ema(close, longEma)

// Entry Conditions
longCondition = ta.crossover(emaShort, emaLong)
shortCondition = ta.crossunder(emaShort, emaLong)

// Strategy
if (longCondition)
    strategy.entry("Long", strategy.long)
    strategy.exit("Exit Long", "Long", stop=close * (1 - slPerc), limit=close * (1 + tpPerc))
    
if (shortCondition)
    strategy.entry("Short", strategy.short)
    strategy.exit("Exit Short", "Short", stop=close * (1 + slPerc), limit=close * (1 - tpPerc))

// Plotting
plot(emaShort, color=color.blue, title="Short EMA")
plot(emaLong, color=color.red, title="Long EMA")

Performance Simulation