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Many traders become obsessed with risk-to-reward ratios because they believe large winners automatically create profitability. In reality, risk-to-reward only matters relative to win rate and execution quality.

A strategy targeting 1:4 risk-to-reward sounds attractive on paper, but if market conditions only allow that target to be reached occasionally, the system becomes unstable.



For example, imagine two traders:

Trader A risks $100 to make $400 but wins only 20% of trades.
Trader B risks $100 to make $150 and wins 55% of trades.

After 10 trades:

Trader A:
8 losses = -$800
2 wins = +$800
Net result = breakeven

Trader B:
5 losses = -$500
5 wins = +$750
Net result = +$250

The higher reward ratio did not create the better system.

This is why experienced traders focus less on maximizing reward multiples and more on matching targets to realistic market conditions. In slower environments, smaller but more consistent targets often outperform aggressive expectations.

A strong strategy is not built around impressive single trades. It is built around repeatable probabilities over large sample sizes.