We measure the nature and severity of a variety of belief distortions in market reactions to hundreds of economic news events using a new methodology that synthesizes estimation of a structural asset pricing model with algorithmic machine learning to quantify bias. We estimate that investors systematically overreact to perceptions about multiple fundamental shocks in a macro-dynamic system, generating asymmetric compositional effects when several counteracting shocks occur simultaneously in real-world events. We show that belief overreaction to all shocks can lead the market to over- or underreact to events, amplifying or dampening volatility.
Authors
- Acknowledgements & Disclosure
- Bianchi and Ludvigson received financial support from the National Science Foundation under Grant 2116641. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
- DOI
- https://doi.org/10.3386/w32301
- Published in
- United States of America
