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Resource allocation in the brain and the Capital Asset Pricing Model

Siddiqi, Hammad (2020): Resource allocation in the brain and the Capital Asset Pricing Model.

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Abstract

What happens when information reaches the human brain? In economics, a black-box approach to information processing in the brain is generally taken with an implicit assumption that information, once it reaches the brain, is accurately processed. In sharp contrast, research in brain sciences has established that when information reaches the brain, a mental template or schema (neural substrate of knowledge) is first activated, which influences information absorption. Schemas are created through a resource intensive process in which finite brain resources are allocated to different tasks, with resource allocation in the brain having an impact on the structure of schemas. In this article, we explore the implications of this richer view from brain sciences for the capital asset pricing model (CAPM). We show that two versions of CAPM arise depending on how the brain resources are allocated in schema creation. In one version, the relationship between beta and expected returns is flat along with features akin to value, size, and momentum effects. In the second version, the relationship between beta and expected return is strongly positive with an implied risk-free rate which could be negative. Novel predictions emerging from this approach are: momentum is negatively correlated with value, size, and betting-against-beta, and stocks that command a lion’s share of investor attention have lower risk-adjusted returns.

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