Dr. Raj backtests a trading strategy that yields an average net profit of $12.50 per trade with a 68% win rate over 200 trades. What is the expected total profit from this strategy? - Databee Business Systems

Understanding the Context

• Win Rate: 68% (136 out of 200 trades are profitable)
  
• Average Net Profit per Winning Trade: $12.50
  
• Average Net Loss per Losing Trade: Not explicitly stated, but for context in high-conviction strategies, losses are typically smaller — often assumed around $5 to $7 per loss for balance
  
• Total Trades: 200
  
• Profit-Loss Ratio Assumption: For simplicity and conservative estimation, assume average loss per loss is $6

Calculating Total Expected Profit

Using Dr. Raj’s data:

• Winning Trades:
  68% of 200 = 136 trades
  Total gain from wins = 136 × $12.50 = $1,700.00

Key Insights

• Losing Trades:
  32% of 200 = 64 trades
  Total loss from losses = 64 × $6 = $384.00

• Net Expected Profit:
  $1,700.00 (wins) – $384.00 (losses) = $1,316.00

Conclusion

Dr. Raj’s backtested strategy, with a 68% win rate and $12.50 average profit per winning trade over 200 trades, delivers an expected total net profit of $1,316 under typical loss assumptions. This high win rate combined with focused risk management suggests a strong foundation — especially if loss sizes are conservative. Traders and investors should consider this strategy as a promising candidate for replication or scaling, always remembering that past performance doesn’t guarantee future results, and proper risk controls remain essential.

Final Thoughts

Expert Tip: Always validate backtest assumptions — including loss sizes and trade frequencies — and apply this strategy in demo environments before committing real capital. Contact Dr. Raj directly for deeper insights into model parameters and optimal capital allocation.