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Strategic information asymmetry in tail-risk markets

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  • Ardakani, Omid M.

Abstract

This paper develops a novel information-theoretic measure of strategic asymmetry, asymmetric information entropy, that quantifies disparities in agents’ knowledge states through differential Shannon entropy. I integrate k-level cognitive hierarchies with Bayesian games to analyze how strategic depth attenuates information gaps, proving almost sure convergence and Pareto-optimal limit equilibria. Using generalized extreme value distributions, I show strategic restructuring alters financial market outcomes through parameter shifts in tail risk and location that converge geometrically under Lipschitz belief updating. Empirical analysis of U.S. tender offers reveals legal defenses (Level-2 strategies) increase bid premiums versus the baseline, while combined strategies exhibit subadditive effects. The proposed entropy measure formalizes Akerlof-style market failures, providing a quantitative basis for securities regulation and mechanism design.

Suggested Citation

  • Ardakani, Omid M., 2025. "Strategic information asymmetry in tail-risk markets," The North American Journal of Economics and Finance, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:ecofin:v:79:y:2025:i:c:s1062940825001007
    DOI: 10.1016/j.najef.2025.102460
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    Keywords

    Strategic information asymmetry; Cognitive hierarchy; Bayesian games; Extreme value theory; Tender offers; Market design;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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