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我正在尝试比较使用 MAPE 的多种方法在不同商品市场(如玉米、小麦、大豆、咖啡、棉花)中的预测准确性。显然,相对 MAPE 的面积受到每种商品的相对波动性的影响:小麦的 MAPE 高可能只是反映市场波动,不一定是预测不佳。

我想知道如何纠正这一点:我想是某种音量调整的 MAPE,但我找不到任何关于此的文献。或者,我正在考虑将某种预测方法的 MAPE 与幼稚预测的 MAPE 进行比较……我想这也应该在一定程度上纠正 vol 差异。

非常感谢任何进一步的建议/意见。

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I'm not aware of any measures that directly incorporates volatility, in order to enable comparison across. I would also question the relevance of directly comparing accuracy measures across like that, as the accuracy would depend - as you also points out - on the volatility/signal-to-noise ratio of the time series.

I approach a problem like this by what you also suggest - create a naïve forecast, and have that as the lowest acceptable accuracy for that series, and also an initial measure of the forecastability of the series.

Note: i follow the definition of a naïve forecast as: one which is a very simple forecast model, could be naive1, naive2, moving average or combination of those - where no further work needs to be done on parameters.

Try to have a look at the work of Michael Gilliland on FVA for inspiration

于 2021-08-06T07:26:19.623 回答