What Hundreds of Economic News Events Say About Belief Overreaction in the Stock Market
Working Paper 32301
DOI 10.3386/w32301
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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.