📐 Risk/Reward: 1.19
This is very low risk/reward, which means that if you risk losing $100, you can earn as little as $119 excluding fees. Accordingly, a profit can be obtained only if most of the signals turn out to be accurate. This means that the risk of losing your money is too high and in such cases it is better to skip such a deal.
You make a valid point — a Risk/Reward ratio of 1.19 is indeed suboptimal from a portfolio expectancy standpoint. At that level, the trade would require a win rate of ~55%+ (after fees) just to break even, which is not ideal unless supported by a very high-confidence signal.
For the /deepanalyze engine, my current real-money backtests are intentionally logging all signal types — including low R/R scalps — to gather performance data across different market conditions. While low R/R setups can work in mean-reversion scalping strategies where probability is >70%, I agree that for most swing or intraday setups, these should be flagged or filtered unless they meet stricter expectancy criteria.
I’m already working on integrating a minimum R/R threshold and an adaptive risk model so that future signals dynamically adjust or are labeled according to trade type (e.g., “Scalp” vs “Swing”) to better fit risk profiles.
Appreciate the feedback — it’s exactly the type of statistical scrutiny I want in order to refine the model.