Thank you for taking the time to share your observations.
I’d like to highlight one important point. Suggestions around re-entries or multiple stop-losses are naturally influenced by the outcome of recent trades. If the same re-entry had resulted in a profitable trade, it’s quite possible that the discussion would have been different. This is why strategy decisions cannot be evaluated based on a few recent outcomes alone.
It’s important to recognise that this is a common form of hindsight bias and outcome bias, where strategy rules are judged based on the outcome of recent trades rather than on their long-term statistical edge across different market conditions.
The Algo is currently functioning exactly as designed, based on its predefined entry, exit, and re-entry criteria. Every trade, including a re-entry, is taken only when the strategy conditions are satisfied. A losing sequence does not by itself indicate that the strategy logic is incorrect or that the Algo requires optimisation.
Our philosophy is to build robust strategies that can perform across different market environments rather than continuously modifying them in response to recent drawdowns. Frequent changes based on short-term performance can lead to curve-fitting, where a strategy appears better for recent data but becomes less reliable over the long run.
If you personally prefer not to take re-entry trades during a particular phase, you may pause the Algo after the first trade is completed. This can be done from the PnL section by turning off the toggle available at the top-right corner under the Automated Algos tab. This gives you control over your deployment without changing the underlying strategy for all users.
Finally, it’s important to remember that every Algo on the platform is designed with a specific risk profile. Drawdown phases, including periods where multiple losses occur consecutively, are a normal part of systematic trading. For this reason, we always encourage users to evaluate historical drawdowns, worst phases, and risk metrics before deploying an Algo and to ensure that the selected strategies align with their own risk appetite and investment horizon.
I sincerely appreciate your observations and the time you’ve taken to document them. Your suggestions have been noted, and we’ll continue evaluating the Algo based on its long-term performance and behaviour across different market conditions.