Modeling the Dynamics of Cryptocurrency Market Volatility Using a System Dynamics Approach

Abstract

The present study aimed to analyze the factors affecting cryptocurrency market volatility and to explain the mechanisms underlying the formation of such fluctuations using a system dynamics approach. In terms of objective, this research is applied, and in terms of methodology, it is a descriptive–analytical study based on modeling and simulation. The data used in this study included historical cryptocurrency market information such as price, trading volume, market capitalization, hash rate, and circulating supply, which were collected from sources including CoinMarketCap and Blockchain.com. In addition, macroeconomic variables such as interest rates, the S&P 500 index, and gold prices were employed to examine the effects of the broader economic environment. The statistical population consisted of all active cryptocurrencies in the global market, from which Bitcoin and Ethereum were selected as the primary samples using purposive sampling. In this study, causal relationships among the key variables were first identified through causal loop diagrams, and subsequently, the quantitative structure of the model was implemented in the Vensim DSS software environment through stock-and-flow diagrams. After formulating the mathematical equations and calibrating the parameters based on historical data, the model was simulated for the period from 2018 to 2024 and evaluated using various validation tests, including behavior reproduction, sensitivity analysis, and extreme condition tests. The results of the data analysis indicated that factors such as capital inflow, investor confidence, trading volume, mining rate, and macroeconomic conditions have significant effects on cryptocurrency price volatility. Furthermore, the simulation results of future scenarios demonstrated that if the trend of institutional adoption and relative economic stability continues, the cryptocurrency market may experience an upward trajectory accompanied by considerable volatility in the coming years. Overall, the findings of this study indicate that cryptocurrency market volatility results from the complex interaction of economic, technical, and behavioral factors, and that the system dynamics approach can provide an appropriate tool for understanding these interactions and predicting future market behavior. The findings of this research may be useful for investors, market analysts, and financial policymakers in improving their understanding of cryptocurrency market dynamics and managing the associated risks.