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Forecasting bitcoin volatility: Evidence from the options market

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  • Lai T. Hoang
  • Dirk G. Baur

Abstract

This paper studies a large number of bitcoin (BTC) options traded on the options exchange Deribit. We use the trades to calculate implied volatility (IV) and analyze if volatility forecasts can be improved using such information. IV is less accurate than AutoRegressive–Moving‐Average or Heterogeneous Auto‐Regressive model forecasts in predicting short‐term BTC volatility (1 day ahead), but superior in predicting long‐term volatility (7, 10, 15 days ahead). Furthermore, a combination of IV and model‐based forecasts provides the highest accuracy for all forecasting horizons revealing that the BTC options market contains unique information.

Suggested Citation

  • Lai T. Hoang & Dirk G. Baur, 2020. "Forecasting bitcoin volatility: Evidence from the options market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(10), pages 1584-1602, October.
    • Handle: RePEc:wly:jfutmk:v:40:y:2020:i:10:p:1584-1602
    DOI: 10.1002/fut.22144
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    as
    1. Paolo Pagnottoni & Thomas Dimpfl, 2019. "Price discovery on Bitcoin markets," Digital Finance, Springer, vol. 1(1), pages 139-161, November.
    2. Haugom, Erik & Langeland, Henrik & Molnár, Peter & Westgaard, Sjur, 2014. "Forecasting volatility of the U.S. oil market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 1-14.
    3. Tiwari, Aviral Kumar & Jana, R.K. & Das, Debojyoti & Roubaud, David, 2018. "Informational efficiency of Bitcoin—An extension," Economics Letters, Elsevier, vol. 163(C), pages 106-109.
    4. Jorion, Philippe, 1995. "Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-528, June.
    5. Konstantinos Metaxoglou & Aaron Smith, 2017. "Forecasting Stock Returns Using Option-Implied State Prices," Journal of Financial Econometrics, Oxford University Press, vol. 15(3), pages 427-473.
    6. Busch, Thomas & Christensen, Bent Jesper & Nielsen, Morten Ørregaard, 2011. "The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets," Journal of Econometrics, Elsevier, vol. 160(1), pages 48-57, January.
    7. Jun Pan & Allen M. Poteshman, 2006. "The Information in Option Volume for Future Stock Prices," Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 871-908.
    8. Stavroula P. Fameliti & Vasiliki D. Skintzi, 2020. "Predictive ability and economic gains from volatility forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 200-219, March.
    9. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2016. "Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(12), pages 1127-1163, December.
    10. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
    11. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    12. Dunis, Christian & Kellard, Neil M. & Snaith, Stuart, 2013. "Forecasting EUR–USD implied volatility: The case of intraday data," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4943-4957.
    13. Easley, David & O'Hara, Maureen, 1987. "Price, trade size, and information in securities markets," Journal of Financial Economics, Elsevier, vol. 19(1), pages 69-90, September.
    14. Klein, Tony & Pham Thu, Hien & Walther, Thomas, 2018. "Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 105-116.
    15. Bart Frijns & Christian Tallau & Alireza Tourani‐Rad, 2010. "The information content of implied volatility: Evidence from Australia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(2), pages 134-155, February.
    16. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    17. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    18. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    19. Dirk G. Baur & Thomas Dimpfl, 2019. "Price discovery in bitcoin spot or futures?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 803-817, July.
    20. Bryan Kelly & Ľuboš Pástor & Pietro Veronesi, 2016. "The Price of Political Uncertainty: Theory and Evidence from the Option Market," Journal of Finance, American Finance Association, vol. 71(5), pages 2417-2480, October.
    21. Carol Alexander & Jaehyuk Choi & Heungju Park & Sungbin Sohn, 2020. "BitMEX bitcoin derivatives: Price discovery, informational efficiency, and hedging effectiveness," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(1), pages 23-43, January.
    22. Koski, Jennifer Lynch & Michaely, Roni, 2000. "Prices, Liquidity, and the Information Content of Trades," Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 659-696.
    23. Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
    24. David Yermack, 2013. "Is Bitcoin a Real Currency? An economic appraisal," NBER Working Papers 19747, National Bureau of Economic Research, Inc.
    25. Baur, Dirk G. & Dimpfl, Thomas, 2018. "Asymmetric volatility in cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 148-151.
    26. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    27. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    28. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    29. Louis H. Ederington & Wei Guan, 2002. "Measuring implied volatility: Is an average better? Which average?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(9), pages 811-837, September.
    30. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    31. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    32. Chang, Chuang-Chang & Hsieh, Pei-Fang & Lai, Hung-Neng, 2009. "Do informed option investors predict stock returns? Evidence from the Taiwan stock exchange," Journal of Banking & Finance, Elsevier, vol. 33(4), pages 757-764, April.
    33. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    34. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, June.
    35. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
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    2. Hoang, Lai T. & Baur, Dirk G., 2022. "Loaded for bear: Bitcoin private wallets, exchange reserves and prices," Journal of Banking & Finance, Elsevier, vol. 144(C).
    3. Skander Slim & Ibrahim Tabche & Yosra Koubaa & Mohamed Osman & Andreas Karathanasopoulos, 2023. "Forecasting realized volatility of Bitcoin: The informative role of price duration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1909-1929, November.
    4. Shimeng Shi, 2022. "Bitcoin futures risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2190-2217, December.
    5. Weige Huang & Xiang Gao, 2023. "Forecasting Bitcoin Futures: A Lasso-BMA Two-Step Predictor Selection for Investment and Hedging Strategies," SAGE Open, , vol. 13(1), pages 21582440231, January.
    6. Sasan Barak & Navid Parvini, 2023. "Transfer‐entropy‐based dynamic feature selection for evaluating Bitcoin price drivers," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(12), pages 1695-1726, December.
    7. Wu, Xinyu & Yin, Xuebao & Umar, Zaghum & Iqbal, Najaf, 2023. "Volatility forecasting in the Bitcoin market: A new proposed measure based on the VS-ACARR approach," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).

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