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The value of crypto currency is determined by its supply and demand, while interwoven with macroeconomic environment and the price various crucial investment instrument. Bitcoin could be an alternative investment opportunity to the traditional financial markets. The intrinsic value of virtual currency reflect macroeconomic environment and influenced by foreign exchange market, gold market, oil market and commodity market. However, the drastic change in Bitcoin seems to far exceed the changes in fundamental determinants of macroeconomic situation. Time series analysis is adopted to explore the pattern of volatility. Five different sets of model are established to estimate the volatility of daily Bitcoin price from the year 2022 to 2023. With all the models from ARCH family, GARCH model has better goodness of fit than ARCH model. While ARCH-M model does not has satisfactory goodness of fit, estimation result from EGARCH model and PARCH model is significantly better. The better goodness of fit from EGARCH and PARCH is consistent with the theory that data in financial market is not symmetrical. In the future research, event based analysis could be used to understand the reaction time and extant. Outlier analysis, comparison analysis, and spot-derivative market hedging could also be explored.

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Empirical Analysis on Crypto Currency Volatility Based on ARCH Model

  • 会议论文

  • 发表日期：

    2025年

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  • Yao Yao,
  • Yizhen Zhou,
  • Jiangping Zhu

摘要

The value of crypto currency is determined by its supply and demand, while interwoven with macroeconomic environment and the price various crucial investment instrument. Bitcoin could be an alternative investment opportunity to the traditional financial markets. The intrinsic value of virtual currency reflect macroeconomic environment and influenced by foreign exchange market, gold market, oil market and commodity market. However, the drastic change in Bitcoin seems to far exceed the changes in fundamental determinants of macroeconomic situation. Time series analysis is adopted to explore the pattern of volatility. Five different sets of model are established to estimate the volatility of daily Bitcoin price from the year 2022 to 2023. With all the models from ARCH family, GARCH model has better goodness of fit than ARCH model. While ARCH-M model does not has satisfactory goodness of fit, estimation result from EGARCH model and PARCH model is significantly better. The better goodness of fit from EGARCH and PARCH is consistent with the theory that data in financial market is not symmetrical. In the future research, event based analysis could be used to understand the reaction time and extant. Outlier analysis, comparison analysis, and spot-derivative market hedging could also be explored.