A planned reward-to-risk ratio compares a target profit to a stop loss, but it does not describe the likelihood of either occurring. Expectancy combines outcome size with win and loss probabilities based on evidence.
How to work through the calculation or research
Use actual filled trades to estimate win and loss frequency after costs, while remembering that a small sample is unreliable. A 2:1 target-to-stop ratio is not proof of a profitable strategy if wins are sufficiently rare.
A concrete worked example
Suppose a trade system wins 40% of the time for $200 and loses 60% for $100. Expected gross value per trade is 0.4×$200 − 0.6×$100 = $20, before fees. A change in win rate or slippage can reverse that result.
Common errors and important limitations
Backtests can overfit historical data and execution costs can rise during stress. Keep expectancy assumptions transparent, avoid guaranteed win-rate language and test worst-case losses.
Put the idea into practice with a working tool
For a practical calculation, the Crypto Risk Reward Calculator lets you examine: Entry price (USD), Stop price (USD), Target price (USD). The tool documents its method as: Reward:Risk = (target − entry) / (entry − stop). A favorable ratio does not imply a trade is likely to succeed.
Practical checks before relying on the result
- Confirm the asset, chain, amount and date apply to your own situation.
- Separate supplied assumptions from verifiable source data and do not treat a scenario as a live market quote.
- Document fees, rounding rules and constraints before making an irreversible financial or blockchain decision.
Sources and further verification
These references support technical definitions and research context; they do not validate any hypothetical market price or individual investment.
Financial and blockchain information is educational. No investment advice, custody, private keys or guaranteed outcomes. Examples use illustrative inputs rather than live quotes.