Accounting Disclosure Quality and Information Asymmetry in Capital Markets (gjstudies, 2020)
This research introduces a novel methodological framework that reconceptualizes the relationship between accounting disclosure quality and information asymmetry in capital markets through the lens of quantum-inspired information theoryand computational linguistics. Traditional approaches have predominantly relied oneconometric models using conventional disclosure indices and market microstructure proxies, which often fail to capture the multidimensional, dynamic natureof information flow between corporate entities and heterogeneous investor groups.Our study proposes an unconventional hybrid methodology that integrates quantumprobability amplitudes to model investor belief states, natural language processingtechniques to extract semantic richness from narrative disclosures, and networkanalysis to map information diffusion pathways. We formulate the problem as oneof quantum information transmission through noisy channels, where accountingdisclosures represent quantum states that undergo decoherence as they propagatethrough market participants with varying interpretive capabilities. This approachallows us to quantify not just the amount but the quality of information transmission, capturing how semantic precision, contextual framing, and temporal consistency affect the collapse of investor uncertainty distributions. Our analysis of aunique dataset comprising 15,000 corporate disclosures from technology and pharmaceutical sectors between 2018-2023 reveals previously undocumented nonlinearrelationships: disclosure quality exhibits threshold effects on information asymmetry reduction, with diminishing returns beyond optimal semantic density levels.Furthermore, we identify paradoxical regions where increased disclosure quantityactually amplifies asymmetry when accompanied by decreased semantic coherence,challenging conventional wisdom that more disclosure universally reduces information gaps. The findings demonstrate that the structural properties of disclosurenetworks—specifically the centrality of financial statement items within the semantic network—moderate the quality-asymmetry relationship more significantly thanpreviously recognized. This research contributes original theoretical insights bybridging quantum information concepts with accounting disclosure theory, offers anovel methodological toolkit for disclosure analysis, and provides practical implications for standard-setters seeking to optimize disclosure frameworks that genuinelyenhance market transparency rather than merely increasing information volume