The Informational Content in Lepto-Variance and Its Relation to Higher Moments
Lepto-regression is defined as the machine learning process of constructing a Regression Tree of a target feature on itself. It is a novel, model-free method potentially revealing information on important sample structure properties. But it is yet not clear what the informational content of lepto-variance is and how it is related to other well-known statistics of a sample. One significant finding is that 58% of the historical US stock return variability is 1-bit lepto-variance that can not be explained by any financial factor. The central question investigated in this paper is to use small normal N(0, 1) drawn samples to explore how the 1-bit sample lepto-variance and lepto-ratio relate t...
| Authors | Vassilis Polimenis |
|---|---|
| Primary category | stat.ME |
| Published | 21 September 2026 |
| Last updated at source | 21 September 2026 |
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