International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Advancing volatility forecasting in cryptocurrencies through GARCH and stochastic volatility frameworks.

Author(s) Dr. K. Jagannayaki, Dr. P. Lavanya, Mr. N. Suresh, Ms. MBVSV Lakshmi
Country India
Abstract The extreme price fluctuations of cryptocurrencies create both opportunities and risks for investors, regulators, and policymakers. Forecasting volatility is essential for managing risk, pricing derivatives, and understanding market behavior. This study improves volatility forecasting in cryptocurrencies by applying and comparing Generalised Autoregressive Conditional Heteroskedasticity (GARCH) family models and Stochastic Volatility (SV) frameworks. High-frequency data from major cryptocurrencies, such as Bitcoin and Ethereum, was used to assess model performance across various market conditions, including periods of extreme stress and relative stability. The analysis examines volatility clustering, persistence, and spillover effects, while considering leverage asymmetry and fat-tailed return distributions. Assessment of forecast accuracy is done through various loss functions and out-of-sample tests. The results provide insights into the relative strengths of GARCH and SV models in capturing the unique features of cryptocurrency markets. This has significant implications for managing portfolio risk, regulatory oversight, and the development of volatility-linked crypto derivatives.
Keywords cryptocurrencies, GARCH model, Stochastic Volatility, Bitcoin, Ethereum, clustering, risk management, market dynamics
Field Business Administration
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-07
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.62701
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E-ISSN 2582-2160
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