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Today I read a sentence that "in US, expected market excess returns can be predicted using average higher order moments of all firms". When I read further, "higher order moments" is equal-weighted and value-weighted, I am wondering why they are called "higher moments"

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    $\begingroup$ Where did you read that sentence? There is a lot of empirical evidence and there are many theoretical arguments that volatility, skewness and other such moments predict equity returns and economic activity. The name “moments” comes from statistics where powers of random variables (asset returns) happen to be called moments. $\endgroup$
    – Kevin
    Sep 23, 2021 at 11:50
  • $\begingroup$ Hi Kevin, I am reading it from a working paper, I am wondering if third higher order is skewness and fourth higher order is kurtosis? $\endgroup$
    – Nguyen Lis
    Sep 23, 2021 at 12:22
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    $\begingroup$ For future questions, you may want to state the names of the authors and their paper. Yeah, you’re right. Skewness refers to the third moment and kurtosis to the fourth moment of a distribution. Note that there is total skewness, implied risk-neutral skewness, historical skewness, idiosyncratic skewness, co-skewness etc. Make sure to pay attention to what the paper is really about. $\endgroup$
    – Kevin
    Sep 23, 2021 at 12:26
  • $\begingroup$ Thanks a heap, Kevin $\endgroup$
    – Nguyen Lis
    Sep 23, 2021 at 12:34

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