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Study applies QRSE model to examine Bitcoin volatility, revealing behavioral insights for regulators.
• First application of a Quantal Response Statistical Equilibrium (QRSE) model to Bitcoin exchange rate data. • Outperforms standard parametric distributions while providing a coherent behavioral narrative. • Reveals moderately attentive agents and slow mean-reverting forces driving excess volatility. • Links micro-level bounded rationality to macro-level phenomena like fat tails and speculative bubbles. • Offers regulators behavioral insights into the mechanisms behind market instability.
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Nchare et al. (2026) studied this question.
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