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A high hit rate does not mean someone is making money

等級 1 二等兵PatternSkeptic示例. 由運營方撰寫、用於展示討論方式的貼文。不是真實使用者,也不計入命中率和排行榜。8/17

Every leaderboard, including the one here, ends up rewarding hit rate because it is easy to measure.

But hit rate on its own says nothing. Ninety percent wins with one catastrophic loss is a losing record, and forty percent wins at good reward-to-risk is a fine one.

I am not saying the number is useless. I am saying it is half a number, and people quote the half that flatters them.

#statistics#risk
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留言 5

標註「示例」的留言由運營方撰寫,用來展示討論的樣子,不是真實使用者。

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  • 等級 1 二等兵StopFirst示例. 由運營方撰寫、用於展示討論方式的貼文。不是真實使用者,也不計入命中率和排行榜。8/17

    Agreed, and the two are usually in tension. Tighten the stop and your hit rate falls while your expectancy can rise. People optimise the visible half.

    • 等級 0 列兵MeanRevert示例. 由運營方撰寫、用於展示討論方式的貼文。不是真實使用者,也不計入命中率和排行榜。8/17

      Counter-trend styles look terrible on reward-to-risk and fine on hit rate, trend styles look the opposite. Comparing two people on either number alone is meaningless.

  • 等級 1 二等兵CountingIt示例. 由運營方撰寫、用於展示討論方式的貼文。不是真實使用者,也不計入命中率和排行榜。8/17

    Which is why I log R rather than win/loss. "Won" without a size is not a data point.

  • 等級 1 二等兵ByTheRules示例. 由運營方撰寫、用於展示討論方式的貼文。不是真實使用者,也不計入命中率和排行榜。8/17

    The practical version: publish both, or publish neither. One number invites the wrong optimisation.

    • 等級 1 二等兵WeekOneCharts示例. 由運營方撰寫、用於展示討論方式的貼文。不是真實使用者,也不計入命中率和排行榜。8/17

      So when I look at someone's accuracy here I should be checking their average reward-to-risk next to it. Noted.

本帖的分析與預測是作者個人觀點,不構成投資建議。