1. The Mathematical Expectancy Formula
Trading expectancy calculates the average amount you can expect to win (or lose) per rupee risked over a series of 100 trades.
Expectancy = (Win Rate × Average Win) - (Loss Rate × Average Loss). If this number is positive, your system possesses an authentic mathematical edge. If negative, even a high 80% win rate will ultimately result in bankruptcy if occasional losses are outsized.
Breakeven Win Rate % = 1 / (1 + Reward-to-Risk Ratio) × 100. For 1:1 RRR = 50% Win Rate Required. For 1:2 RRR = 33.3% Win Rate Required. For 1:3 RRR = 25.0% Win Rate Required.
2. Why Most Retail Traders Invert Risk-Reward
Untrained traders regularly operate with an inverted risk-reward ratio of 2:1 or 3:1. They cut winning trades quickly after a tiny ₹500 gain out of fear, but hold onto losing positions as they bleed down ₹2,500, hoping for a turnaround.
By strictly requiring every setup to have at least twice as much upside as defined downside risk, TradeNov helps traders break free from this self-destructive pattern.
3. Position Sizing: How to Apply Risk-Reward in Real Life
To execute a 1:2 trade properly, you must calculate your position size based on your stop-loss distance, not your account balance.
Number of Shares = (Total Capital × Risk % per Trade) / (Entry Price - Stop-Loss Price). If you have ₹1,00,000 and risk 1% (₹1,000) with a ₹10 stop-loss distance, your position size is exactly 100 shares. If your target is ₹20 higher, your potential reward is ₹2,000 (1:2).
