Bounded Rationality and Price Adjustment: A Cognitive Load Perspective on Investor Overreaction and Underreaction

Abstract

This paper, inspired by the psychological mechanisms of human cognition and microstructure economics, proposed and tested the theory of Cognitive Load-Based Price Adjustment (CLBPA), where equity-market overreactions and underreactions are united to explain better market behaviour. Utilising abnormally intense intraday tick-by-tick TAQ data for 2,847 stocks traded in NYSE, NASDAQ, LSE, NSE (India), and B3 (Brazil) during the months of January 2018–December 2023 (approximately 15.4 million distinct intraday observations), the researchers assessed cognitive load toward a composite index formed as the behavioural proxy for reaction time, VPIN, and order-to-trade ratios. Thus, instead of some esoteric constellations of regime-switching models, panel threshold estimators, and modified GMM steamrolled by fishing for "just-in-time data," this study formally and experimentally applied these and several other methodologies—most notably, real-time dimensions of cognitive-load-influenced market regulation: (1) on the very essence of the matter, both proofs of the impact of System-1 vs. System-2 on prices; and (3) sub-allenance. Not surprisingly, under the circumstances, the empirical-regression techniques converting instantaneous reactions into relevant reaction times allowed for evaluating trading dynamics with respect to cognitive processing and for rigorously analysing the effects of CG on more than one iteration over the downturn. Conclusions include designing dynamic, empirical-regression-driven circuit breakers, enabling them to install further temporal information architecture on their exchange circuits, and encouraging them to use cognitive-aware execution algorithms for fair and efficient price discovery. Future work would test the same metrics.