IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v42y2022i7p1264-1283.html
   My bibliography  Save this article

Overnight volatility, realized volatility, and option pricing

Author

Listed:
  • Tianyi Wang
  • Sicong Cheng
  • Fangsheng Yin
  • Mei Yu

Abstract

The equity market is not trading around the clock, and the overnight information has been proved be important for understanding pricing anomalies, improving volatility forecasting accuracy, and so forth. However, there is little research investigating its impact on option pricing. In this paper, we provide a framework that integrates intraday, overnight returns, and realized volatility simultaneously within an augmented Autoregressive Volatility model. The analytical option‐pricing formula for the new model is derived through the closed‐form moment generation function. The empirical results based on S&P 500 index options show that distinguishing the overnight component from daily returns has the potential capability to reduce the pricing errors, both in‐sample and out‐of‐sample.

Suggested Citation

  • Tianyi Wang & Sicong Cheng & Fangsheng Yin & Mei Yu, 2022. "Overnight volatility, realized volatility, and option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1264-1283, July.
    • Handle: RePEc:wly:jfutmk:v:42:y:2022:i:7:p:1264-1283
    DOI: 10.1002/fut.22330
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.22330
    Download Restriction: no
    File URL: https://libkey.io/10.1002/fut.22330?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Oldfield, George S, Jr & Rogalski, Richard J, 1980. "A Theory of Common Stock Returns over Trading and Non-Trading Periods," Journal of Finance, American Finance Association, vol. 35(3), pages 729-751, June.
    2. Anders B. Trolle & Eduardo S. Schwartz, 2009. "Unspanned Stochastic Volatility and the Pricing of Commodity Derivatives," Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4423-4461, November.
    3. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    4. Boes, Mark-Jan & Drost, Feike C. & Werker, Bas J. M., 2007. "The Impact of Overnight Periods on Option Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(2), pages 517-533, June.
    5. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    6. Christoffersen, Peter & Feunou, Bruno & Jeon, Yoontae, 2015. "Option valuation with observable volatility and jump dynamics," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 101-120.
    7. Peter Reinhard Hansen & Zhuo Huang, 2016. "Exponential GARCH Modeling With Realized Measures of Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 269-287, April.
    8. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    9. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    10. Pierre Blanc & R'emy Chicheportiche & Jean-Philippe Bouchaud, 2013. "The fine structure of volatility feedback II: overnight and intra-day effects," Papers 1309.5806, arXiv.org, revised May 2014.
    11. Christoffersen, Peter & Feunou, Bruno & Jacobs, Kris & Meddahi, Nour, 2014. "The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 663-697, June.
    12. Muravyev, Dmitriy & Ni, Xuechuan (Charles), 2020. "Why do option returns change sign from day to night?," Journal of Financial Economics, Elsevier, vol. 136(1), pages 219-238.
    13. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    14. Peter Christoffersen & Redouane Elkamhi & Bruno Feunou & Kris Jacobs, 2010. "Option Valuation with Conditional Heteroskedasticity and Nonnormality," The Review of Financial Studies, Society for Financial Studies, vol. 23(5), pages 2139-2183.
    15. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    16. Peter F. Christoffersen & Francis X. Diebold, 2006. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, INFORMS, vol. 52(8), pages 1273-1287, August.
    17. Corsi, Fulvio & Fusari, Nicola & La Vecchia, Davide, 2013. "Realizing smiles: Options pricing with realized volatility," Journal of Financial Economics, Elsevier, vol. 107(2), pages 284-304.
    18. Majewski, Adam A. & Bormetti, Giacomo & Corsi, Fulvio, 2015. "Smile from the past: A general option pricing framework with multiple volatility and leverage components," Journal of Econometrics, Elsevier, vol. 187(2), pages 521-531.
    19. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
    20. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    21. Blanc, Pierre & Chicheportiche, Rémy & Bouchaud, Jean-Philippe, 2014. "The fine structure of volatility feedback II: Overnight and intra-day effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 58-75.
    22. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    23. Lou, Dong & Polk, Christopher & Skouras, Spyros, 2019. "A tug of war: overnight versus intraday expected returns," LSE Research Online Documents on Economics 87481, London School of Economics and Political Science, LSE Library.
    24. Lou, Dong & Polk, Christopher & Skouras, Spyros, 2019. "A tug of war: Overnight versus intraday expected returns," Journal of Financial Economics, Elsevier, vol. 134(1), pages 192-213.
    25. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    26. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.
    27. Heston, Steven L & Nandi, Saikat, 2000. "A Closed-Form GARCH Option Valuation Model," Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 585-625.
    28. Masulis, Ronald W & Ng, Victor K, 1995. "Overnight and Daytime Stock-Return Dynamics on the London Stock Exchange: The Impact of the "Big Bang" and the 1987 Stock-Market Crash," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 365-378, October.
    29. Tsiakas, Ilias, 2008. "Overnight information and stochastic volatility: A study of European and US stock exchanges," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 251-268, February.
    30. Peter Reinhard Hansen & Zhuo Huang & Howard Howan Shek, 2012. "Realized GARCH: a joint model for returns and realized measures of volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 877-906, September.
    31. 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.
    32. Jin‐Chuan Duan, 1995. "The Garch Option Pricing Model," Mathematical Finance, Wiley Blackwell, vol. 5(1), pages 13-32, January.
    33. Michael A Kelly & Steven P Clark, 2011. "Returns in trading versus non-trading hours: The difference is day and night," Journal of Asset Management, Palgrave Macmillan, vol. 12(2), pages 132-145, June.
    34. Zhuo Huang & Tianyi Wang & Peter Reinhard Hansen, 2017. "Option Pricing with the Realized GARCH Model: An Analytical Approximation Approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(4), pages 328-358, April.
    35. Hull, John C & White, Alan D, 1987. "The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fang Liang & Lingshan Du & Zhuo Huang, 2023. "Option pricing with overnight and intraday volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1576-1614, November.
    2. Jing Hao & Feng He & Feng Ma & Tong Fu, 2023. "Trading around the clock: Revisit volatility spillover between crude oil and equity markets in different trading sessions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 771-791, June.
    3. Wan Jia Lin, 2023. "VIX to S&P 500 Correlation Over the Weekend: Are Market Makers Using S&P 500 Weekend Returns to Price VIX on Monday Morning?," Applied Economics and Finance, Redfame publishing, vol. 10(1), pages 3843-3843, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fang Liang & Lingshan Du & Zhuo Huang, 2023. "Option pricing with overnight and intraday volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1576-1614, November.
    2. Zhiyuan Pan & Yudong Wang & Li Liu, 2021. "Realized bipower variation, jump components, and option valuation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1933-1958, December.
    3. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Oct 2022.
    4. Fangsheng Yin & Yang Bian & Tianyi Wang, 2021. "A short cut: Directly pricing VIX futures with discrete‐time long memory model and asymmetric jumps," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(4), pages 458-477, April.
    5. Yu-Hua Zeng & Shou-Lei Wang & Yu-Fei Yang, 2014. "Calibration of the Volatility in Option Pricing Using the Total Variation Regularization," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-9, March.
    6. Feunou, Bruno & Okou, Cédric, 2019. "Good Volatility, Bad Volatility, and Option Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(2), pages 695-727, April.
    7. Pan, Zhiyuan & Shuai, Jiangyu & Liang, Zhilei & Sun, Xianchao, 2022. "Jump dynamics, spillover effect and option valuation," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    8. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
    9. Masato Ubukata & Toshiaki Watanabe, 2014. "Pricing Nikkei 225 Options Using Realized Volatility," The Japanese Economic Review, Japanese Economic Association, vol. 65(4), pages 431-467, December.
    10. Peter Reinhard Hansen & Zhuo Huang & Chen Tong & Tianyi Wang, 2021. "Realized GARCH, CBOE VIX, and the Volatility Risk Premium," Papers 2112.05302, arXiv.org.
    11. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    12. Dario Alitab & Giacomo Bormetti & Fulvio Corsi & Adam A. Majewski, 2019. "A realized volatility approach to option pricing with continuous and jump variance components," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 639-664, December.
    13. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    14. Qiao, Gaoxiu & Yang, Jiyu & Li, Weiping, 2020. "VIX forecasting based on GARCH-type model with observable dynamic jumps: A new perspective," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    15. Christoffersen, Peter & Feunou, Bruno & Jeon, Yoontae, 2015. "Option valuation with observable volatility and jump dynamics," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 101-120.
    16. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    17. Yan Liu & Xiong Zhang, 2023. "Option Pricing Using LSTM: A Perspective of Realized Skewness," Mathematics, MDPI, vol. 11(2), pages 1-21, January.
    18. Gaoxiu Qiao & Gongyue Jiang, 2023. "VIX futures pricing based on high‐frequency VIX: A hybrid approach combining SVR with parametric models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1238-1260, September.
    19. Qiao, Gaoxiu & Jiang, Gongyue & Yang, Jiyu, 2022. "VIX term structure forecasting: New evidence based on the realized semi-variances," International Review of Financial Analysis, Elsevier, vol. 82(C).
    20. Zhuo Huang & Chen Tong & Tianyi Wang, 2019. "VIX term structure and VIX futures pricing with realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 72-93, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jfutmk:v:42:y:2022:i:7:p:1264-1283. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.