Analysis of Cryptocurrency Volatility for Estimated Value at Risk Using the GARCH Model

Oct 13, 2025 by magicalceylontours.com 96 views

Analysis of Cryptocurrency Volatility for Estimated Value at Risk Using the GARCH Model

Introduction

The rise of cryptocurrency as an alternative investment has attracted significant attention in recent years. However, the high volatility inherent in this digital asset poses a challenge for investors. To manage investment risk, it is essential to analyze volatility and estimate the value at risk (VAR). The GARCH model, which is capable of capturing the dynamics of volatility, has been proven effective in analyzing cryptocurrency data. This study examines the volatility of Bitcoin, Ethereum, and Ripple through the application of the GARCH model, with a focus on estimating VAR using the Corn-Fisher Expansion approach.

Background

Cryptocurrency, such as Bitcoin, Ethereum, and Ripple, has gained popularity as an alternative investment option. However, the high volatility associated with this digital asset poses a significant risk for investors. To mitigate this risk, it is crucial to analyze volatility and estimate VAR. The GARCH model, which is a statistical tool used to analyze volatility, has been widely used in finance to estimate VAR. The model is capable of capturing the dynamics of volatility, making it an effective tool for analyzing cryptocurrency data.

Methodology

This study employed a series of methods to analyze the volatility of Bitcoin, Ethereum, and Ripple. The first step involved transforming the data into returns, which is a common practice in finance. The Augmented Dickey-Fuller (ADF) test was then used to determine the stationarity of the data. The Berra-Jarque test was also conducted to check for normality. The optimal ARIMA model was then determined using the LJUNG-BOX test and the ARCH-LM test. The next step involved determining the best GARCH model, which was then used to estimate VAR. VAR estimation validation was carried out using backtesting and the proportion of failures test.

Results

The results of this study showed that the best models for each cryptocurrency are:

Bitcoin: ARIMA (2,0,0) GARCH (1,1)
Ethereum: ARIMA (4,0,3) GARCH (2,2)
Ripple: ARIMA (3,0,4) GARCH (1,2)

VAR estimation in period t = 973 with a holding period of one day and a 95% confidence level, which was corrected with the Corn-Fisher Expansion approach, produced a value of 0.02070 for Bitcoin, 0.03136 for Ethereum, and 0.04098 for Ripple.

Validity Test

The validity test showed various results. VAR estimation for Ripple was proven valid based on backtesting and the proportion of failures test. However, the VAR estimation for Bitcoin and Ethereum was declared invalid, with each of them experiencing exceedance 109 times and 131 times, respectively. Ripple itself experienced exceedance 53 times.

Discussion

The results of this study reveal that the GARCH model with the Corn-Fisher Expansion approach is able to provide valid VAR estimates for Ripple, but not for Bitcoin and Ethereum. This shows that the use of the GARCH model for VAR estimation in cryptocurrency has limitations and needs to be adjusted to the characteristics of each digital asset. Investors need to consider these results in making investment decisions, as well as paying attention to the risks attached to cryptocurrency.

Conclusion

This study demonstrates the effectiveness of the GARCH model in analyzing cryptocurrency volatility and estimating VAR. However, the results also highlight the limitations of the GARCH model in providing valid VAR estimates for all cryptocurrencies. Investors need to be aware of these limitations and take necessary precautions when making investment decisions.

Recommendations for Investors

Perform comprehensive research and analysis before investing in cryptocurrency.
Portfolio diversification to minimize risk.
Take advantage of analytical aids such as GARCH models to understand the dynamics of volatility and manage risk.
Consult with professional financial experts before making investment decisions.

Limitations of the Study

This study has several limitations. Firstly, the study only analyzed three cryptocurrencies, which may not be representative of all cryptocurrencies. Secondly, the study used a specific GARCH model, which may not be the best model for all cryptocurrencies. Finally, the study only estimated VAR using the Corn-Fisher Expansion approach, which may not be the most accurate approach.

Future Research Directions

Future research should focus on analyzing a larger number of cryptocurrencies and using different GARCH models to estimate VAR. Additionally, researchers should explore other approaches to estimating VAR, such as using machine learning algorithms. Finally, researchers should investigate the impact of cryptocurrency regulations on volatility and VAR estimation.

References

Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of U.K. inflation. Econometrica, 50(4), 987-1007.
Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of nominal excess return on stocks. Journal of Finance, 48(5), 1779-1801.

Appendices

Appendix A: Data Description
Appendix B: Methodology Details
Appendix C: Results Tables
Appendix D: Validity Test Results
Q&A: Cryptocurrency Volatility and Value at Risk

Introduction

The rise of cryptocurrency as an alternative investment has attracted significant attention in recent years. However, the high volatility inherent in this digital asset poses a challenge for investors. To manage investment risk, it is essential to analyze volatility and estimate the value at risk (VAR). In our previous article, we discussed the analysis of cryptocurrency volatility for estimated value at risk using the GARCH model. In this Q&A article, we will address some of the most frequently asked questions related to cryptocurrency volatility and VAR estimation.

Q: What is cryptocurrency volatility?

A: Cryptocurrency volatility refers to the degree of fluctuation in the price of a cryptocurrency over a given period of time. It is a measure of the risk associated with investing in cryptocurrency.

Q: Why is cryptocurrency volatility a concern for investors?

A: High volatility in cryptocurrency can result in significant losses for investors. It can also make it difficult to predict the future price of a cryptocurrency, making it challenging to make informed investment decisions.

Q: What is value at risk (VAR)?

A: VAR is a measure of the potential loss of an investment over a given period of time, with a certain level of confidence. It is a widely used risk management tool in finance.

Q: How is VAR estimated?

A: VAR is estimated using statistical models, such as the GARCH model, which takes into account the historical volatility of a cryptocurrency.

Q: What is the GARCH model?

A: The GARCH model is a statistical model that is used to analyze volatility and estimate VAR. It is a widely used model in finance and has been proven effective in estimating VAR for various assets, including cryptocurrency.

Q: What are the limitations of the GARCH model?

A: The GARCH model has several limitations, including the assumption of normality and the use of historical data. Additionally, the model may not be able to capture extreme events or sudden changes in market conditions.

Q: What are some alternative approaches to estimating VAR?

A: Some alternative approaches to estimating VAR include using machine learning algorithms, such as neural networks, and incorporating macroeconomic variables into the model.

Q: How can investors manage risk associated with cryptocurrency volatility?

A: Investors can manage risk associated with cryptocurrency volatility by diversifying their portfolio, using stop-loss orders, and monitoring market conditions closely.

Q: What are some best practices for investors when it comes to cryptocurrency investment?

A: Some best practices for investors when it comes to cryptocurrency investment include conducting thorough research, setting clear investment goals, and monitoring market conditions closely.

Q: Can cryptocurrency investment be suitable for all investors?

A: No, cryptocurrency investment is not suitable for all investors. It is a high-risk investment that requires a high level of risk tolerance and financial sophistication.

Q: What are some common mistakes that investors make when it comes to cryptocurrency investment?

A: Some common mistakes that investors make when it comes to cryptocurrency investment include investing without conducting thorough research, failing to set clear investment goals, and not monitoring market conditions closely.

Q: How can investors stay up-to-date with the latest developments in cryptocurrency?

A: Investors can stay up-to-date with the latest developments in cryptocurrency by following reputable news sources, attending industry events, and participating in online forums and communities.

Conclusion

Cryptocurrency volatility and VAR estimation are complex topics that require a deep understanding of finance and statistics. By understanding the risks associated with cryptocurrency investment and using effective risk management tools, such as the GARCH model, investors can make informed investment decisions and manage risk associated with cryptocurrency volatility.