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Time series analysis of Cryptocurrency returns and volatilities

Author

Listed:
  • Rama K. Malladi

    (California State University, Dominguez Hills)

  • Prakash L. Dheeriya

    (California State University, Dominguez Hills)

Abstract

There is a significant interest in the growth and development of cryptocurrencies, the most notable ones being Bitcoin and Ripple. Global trading in these cryptocurrencies has led to highly speculative and “bubble-like” price movements. Since these cryptocurrencies trade like stocks, provide a feasible alternative to gold and appreciate during uncertain times, it can be hypothesized that their prices are partly determined by the global stock indices, gold prices, and fear gauges such as the VIX and the US Economic Policy Uncertainty Index. In this paper, we test this hypothesis by conducting a time series analysis of returns and volatilities of Bitcoin and of Ripple. We use the Autoregressive-moving-average model with exogenous inputs model (ARMAX), Generalized Autoregressive Conditionally Heteroscedastic (GARCH) model, Vector Autoregression (VAR) model, and Granger causality tests to determine linkages between returns and volatilities of Bitcoin and of Ripple. We find that the Bitcoin crash of 2018 could have been explained using these time series methods. We also find that returns of global stock markets and of gold do not have a causal effect on Bitcoin returns, but we do find returns on Ripple have a causal effect on Bitcoin prices.

Suggested Citation

  • Rama K. Malladi & Prakash L. Dheeriya, 2021. "Time series analysis of Cryptocurrency returns and volatilities," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(1), pages 75-94, January.
    • Handle: RePEc:spr:jecfin:v:45:y:2021:i:1:d:10.1007_s12197-020-09526-4
    DOI: 10.1007/s12197-020-09526-4
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    Cited by:

    1. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    2. Marcel C. Minutolo & Werner Kristjanpoller & Prakash Dheeriya, 2022. "Impact of COVID-19 effective reproductive rate on cryptocurrency," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-27, December.
    3. Tanya Ara'ujo & Paulo Barbosa, 2023. "Reconstructing cryptocurrency processes via Markov chains," Papers 2308.07626, arXiv.org.
    4. Yen, Kuang-Chieh & Nie, Wei-Ying & Chang, Hsuan-Ling & Chang, Li-Han, 2023. "Cryptocurrency return dependency and economic policy uncertainty," Finance Research Letters, Elsevier, vol. 56(C).
    5. Ahmed, Walid M.A., 2021. "How do Islamic equity markets respond to good and bad volatility of cryptocurrencies? The case of Bitcoin," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    6. Mustafa Tevfik Kartal & Mustafa Kevser & Fatih Ayhan, 2023. "Asymmetric effects of global factors on return of cryptocurrencies by novel nonlinear quantile approaches," Economic Change and Restructuring, Springer, vol. 56(3), pages 1515-1535, June.
    7. Peng‐Fei Dai & John W. Goodell & Luu Duc Toan Huynh & Zhifeng Liu & Shaen Corbet, 2023. "Understanding the transmission of crash risk between cryptocurrency and equity markets," The Financial Review, Eastern Finance Association, vol. 58(3), pages 539-573, August.
    8. Kamil Kashif & Robert 'Slepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Papers 2406.18206, arXiv.org.
    9. Virginie Terraza & Aslı Boru İpek & Mohammad Mahdi Rounaghi, 2024. "The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-34, December.
    10. Bazán-Palomino, Walter & Svogun, Daniel, 2023. "On the drivers of technical analysis profits in cryptocurrency markets: A Distributed Lag approach," International Review of Financial Analysis, Elsevier, vol. 86(C).
    11. Chang, Hsuan-Ling & Nie, Wei-Ying & Chang, Li-Han & Cheng, Hung-Wen & Yen, Kuang-Chieh, 2023. "Cryptocurrency Momentum and VIX premium," Finance Research Letters, Elsevier, vol. 57(C).
    12. Rasoul Amirzadeh & Asef Nazari & Dhananjay Thiruvady & Mong Shan Ee, 2023. "Modelling Determinants of Cryptocurrency Prices: A Bayesian Network Approach," Papers 2303.16148, arXiv.org.

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    More about this item

    Keywords

    Asset management; Alternative investments; Digital currency; Cryptocurrency; Bitcoin; ripple; BTC; XRP; economic uncertainty index;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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