Stock Boundary Behavior

Le résumé fourni par la source

People have limited memory and cannot recall a constant stream of experiences. A continuous memory only happens when we create boundaries to divide experiences into separate events. Observable or not, we see the world full of necessary boundaries. Since people tend to behave differently near boundaries, we can only infer that investors may trade differently near their perceived price boundaries. To model investor boundary behavior, we assume that risk-averse investors price stocks no more than their certainty equivalent levels which are below their expected values. As prices approach these levels, new data Bayesian updates their expectations and increases confidence at an accelerating rate. This leads to a surge in stock price adjustment near a boundary, as if drawn by a magnetic force. Much like Coulomb’s Law, where magnetic force increases as distance decreases, stock price movement intensifies as it gets near a perceived boundary. Empirically, we used a synthetic option replication to extract investors’ perceived boundaries. It is clear that not all boundaries exert the magnetic pull. Stock prices are only pulled toward “relevant” boundaries – those exploitable for excess returns. To be relevant, a boundary must balance anonymity against market efficiency, creditability against uncertainty, and urgency to prompt Bayesian updates.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.