Cryptocurrency’s price volatility and adaptive learning

Joy D. Xiuyao Yang

Global Finance Journal, 2025, vol. 67, issue C

Abstract: This paper studies a theoretical question: Why is cryptocurrency so volatile? To investigate this, I apply a New Monetary model that incorporates an adaptive learning assumption. Specifically, building on the baseline framework of Choi and Rocheteau (2021), I relax their perfect foresight assumption by replacing it with adaptive learning. I show how high volatility can emerge under this revised assumption. With a simple learning rate algorithm, I find that adaptive learning can alter the stability of steady states. For instance, with a high learning rate, the system can experience a period of doubling bifurcation, potentially leading to chaotic regimes or explosive paths. These price dynamics help explain the extreme volatility observed in cryptocurrency markets.

Keywords: Cryptocurrency; Money Search; Adaptive learning; Learning rate (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:glofin:v:67:y:2025:i:c:s1044028325000596

DOI: 10.1016/j.gfj.2025.101132

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