模式识别算法的量化回测
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我们一直在对历史 $EURUSD 和 $GBPUSD 数据的头肩顶和双顶/双底模式识别算法进行回测。初步结果显示误报率很高。除了简单的胜率/亏损率之外，大家在评估此类算法的有效性时，还会优先考虑哪些指标？
2 comments · 9 points
DMu/diaz_manuela·21d
False positives are indeed the bane of pattern recognition. Beyond win/loss, I always look at the precision and recall, especially how they balance out. Also, the average p-value of the pattern's predictive power on unseen data is crucial for me.
TTu/teerapat_t·20d
Interesting. Have you considered the impact of different timeframes? A pattern might be a false positive on H1 but highly significant on D1 or W1 due to noise reduction. Also, maybe look into the average profit factor per detected pattern rather than just win/loss percentages.
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