Financial Disclosure Timeliness and Market Reaction to Accounting Information

Abstract

This research introduces a novel methodological framework for examining the
relationship between the timeliness of financial disclosures and the subsequent market reaction to accounting information, moving beyond traditional event-study
paradigms. We propose a temporal granularity model that decomposes disclosure timeliness into three distinct, non-linear dimensions: procedural latency (the
internal delay from fiscal period-end to disclosure authorization), transmission immediacy (the speed of information dissemination across market channels), and cognitive absorption lag (the time required for market participants to process and integrate the information). By applying this tripartite model to a unique longitudinal
dataset of corporate disclosures from 1998 to 2004, we challenge the conventional
assumption that earlier disclosure is uniformly beneficial. Our findings reveal a
complex, context-dependent relationship. While reduced procedural latency is associated with lower immediate volatility, we identify an optimal zone for transmission immediacy; disclosures that are excessively rapid, before supporting analytical
frameworks are widely available, can lead to misinterpretation and subsequent corrective volatility. Most originally, we find that a moderate cognitive absorption lag,
contrary to prevailing efficiency theory, can enhance long-term price accuracy by
allowing for more deliberate analyst scrutiny and peer benchmarking. The study
further employs a bio-inspired optimization algorithm, modeled on fungal network
communication patterns, to simulate information flow and identify disclosure schedules that maximize market stability. Our results suggest that regulatory emphasis
on sheer speed may be suboptimal, and we propose a new metric, the Integrated
Timeliness Efficiency Score, which balances speed with market preparedness. This
research contributes a fundamentally new perspective to disclosure theory, integrating concepts from information theory, behavioral finance, and complex systems
to reframe timeliness not as a simple scalar but as a multi-dimensional property
interacting dynamically with market ecology