Modeling Bitcoin Price Dynamics: Overcoming Kurtosis and Skewness Challenges for Enhanced Predictive Accuracy

Mostafa Tamandi ()
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Mostafa Tamandi: Vali-e-Asr University of Rafsanjan

Computational Economics, 2025, vol. 65, issue 5, No 5, 2579-2594

Abstract: Abstract In recent years, the surge of unofficial digital currencies, often referred to as cryptocurrencies, has disrupted traditional financial landscapes. Bitcoin, being the most prominent among them in terms of market adoption and capitalization, presents unique modeling challenges. This study delves into the application of an autoregressive model of order one, incorporating a skew-normal mean-variance mixture of Birnbaum–Saunders innovations, to better capture the dynamic behavior of Bitcoin prices. The model’s robustness to atypical observations and its effectiveness in handling the inherent price volatility associated with Bitcoin make it a promising tool for financial analysis and prediction in this novel asset class.

Keywords: Autoregressive model; Cryptocurrency price dynamics; Bitcoin modeling; Volatility modeling; Outlier detection; Birnbaum–Saunders (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10614-024-10652-y

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