Key insights
- A software engineer backtested an equity swing trading strategy, showing high win rates and average returns. However, backtesting results can be misleading due to overfitting and survivorship bias. The strategy's real-world performance may differ significantly, especially during unforeseen market conditions. The lack of discussion of risk-adjusted returns and drawdown metrics further limits the usefulness of the backtest.
Hi All,
I have read several books and became deeply interested in them. As a software engineer, I coded my own trading strategy and performed backtesting. Please find the summary of my test results.
I have been learning and refining this strategy for around six years without actively trading. My goal was to make it as solid and robust as possible. I am now planning to start trading after the bear market.
I would really appreciate your opinion on these results, as I do not have anyone experienced in the stock market to discuss this with. I have also used tools like Claude and ChatGPT to further strengthen the strategy.
At this stage, I am looking for expert feedback on whether these results are reasonable. I do not have any bias toward this strategy, and the current results are based only on equity trading.
Do you think these results are decent? I believe the strategy has potential, but I would value your honest opinion.
Overall:
- Selected entries: 365 * Trades with returns: 364 * Win rate: 96.15% * Average return: 46.20% * Median return: 23.77% * Best trade: 1570.85% * Worst trade: -13.35%
Year-wise average return:
- 2010: 51.38% * 2011: 6.79% * 2012: 58.27% * 2013: 45.20% * 2014: 65.41% * 2015: 37.14% * 2016: 29.86% * 2017: 31.74% * 2018: 11.40% * 2019: 18.26% * 2020: 28.38% * 2021: 134.11% * 2022: 33.06% * 2023: 69.41% * 2024: 31.90% * 2025: 18.43%