What Hundreds of Economic News Events Say About Belief Overreaction in the Stock Market

Francesco Bianchi, Sydney Ludvigson and Sai Ma

No 32301, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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 real-world events produce conflicting signals with counteracting market implications. We show that such events can lead the market to underreact to news, even when investors overreact to all shocks.

JEL-codes: G1 G12 G4 G41 (search for similar items in EconPapers)
Date: 2024-04
New Economics Papers: this item is included in nep-big, nep-fdg, nep-fmk and nep-mst
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