The Conditional Expected Return and Autocorrelation from the Derivatives
59 Pages Posted: 7 Apr 2021 Last revised: 4 Feb 2022
Date Written: March 23, 2021
We express conditional expected future returns and stock market autocorrelations with publicly available derivatives data. Our approach is model-free, robust to pricing kernel process choice, and provides a real-time conditional point of view. We demonstrate a moderate short-term reversal of market returns with this approach. Furthermore, our approach implies comparable autocorrelation by statistical inference model with a gradually fading memory feature. We construct a reversal signal based on this approach and show that the corresponding market timing strategy outperforms the buy-and-hold strategy overall. Finally, we demonstrate that the term structure of one-month future returns is pro-cyclical.
Keywords: Autocorrelation, conditional expected return, derivatives, market spanning, recovery
JEL Classification: G1, G12, G13
Suggested Citation: Suggested Citation