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Long memory and the relation between options and stock prices

Author

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  • Huang, Teng-Ching
  • Tu, Yu-Chen
  • Chou, Heng-Chih

Abstract

This study investigates the long-memory property and the fractionally cointegration between absolute changes in observed stock prices and implied stock prices from option pricing model. We find a stylized fact that absolute price movements in stock and option markets are characterized by long memory and they present a fractionally cointegrated relation. The option prices appear to be valuable for the stock prices based on an appropriate econometric methodology, which captures the persistence of both price series. Our empirical results also support the presence of information effect in call option, but the volume effect is absent for all cases.

Suggested Citation

  • Huang, Teng-Ching & Tu, Yu-Chen & Chou, Heng-Chih, 2015. "Long memory and the relation between options and stock prices," Finance Research Letters, Elsevier, vol. 12(C), pages 77-91.
  • Handle: RePEc:eee:finlet:v:12:y:2015:i:c:p:77-91
    DOI: 10.1016/j.frl.2014.11.005
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    References listed on IDEAS

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    1. Jun Pan & Allen M. Poteshman, 2006. "The Information in Option Volume for Future Stock Prices," The Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 871-908.
    2. Donald W. K. Andrews & Patrik Guggenberger, 2003. "A Bias--Reduced Log--Periodogram Regression Estimator for the Long--Memory Parameter," Econometrica, Econometric Society, vol. 71(2), pages 675-712, March.
    3. Schlag, Christian & Stoll, Hans, 2005. "Price impacts of options volume," Journal of Financial Markets, Elsevier, vol. 8(1), pages 69-87, February.
    4. Fleming, Jeff & Kirby, Chris, 2011. "Long memory in volatility and trading volume," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1714-1726, July.
    5. Federico M. Bandi & Benoit Perron, 2006. "Long Memory and the Relation Between Implied and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 636-670.
    6. Marinucci, D & Robinson, Peter, 2001. "Narrow-band analysis of nonstationary processes," LSE Research Online Documents on Economics 2015, London School of Economics and Political Science, LSE Library.
    7. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    8. Tarun Chordia & Richard Roll & Avanidhar Subrahmanyam, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, April.
    9. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    10. Marinucci, D. & Robinson, Peter M., 2001. "Narrow-band analysis of nonstationary processes," LSE Research Online Documents on Economics 303, London School of Economics and Political Science, LSE Library.
    11. George J. Jiang & Yisong S. Tian, 2005. "The Model-Free Implied Volatility and Its Information Content," The Review of Financial Studies, Society for Financial Studies, vol. 18(4), pages 1305-1342.
    12. Bollerslev, Tim & Jubinski, Dan, 1999. "Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 9-21, January.
    13. Stephan, Jens A & Whaley, Robert E, 1990. "Intraday Price Change and Trading Volume Relations in the Stock and Stock Option Markets," Journal of Finance, American Finance Association, vol. 45(1), pages 191-220, March.
    14. Lobato, Ignacio N., 1999. "A semiparametric two-step estimator in a multivariate long memory model," Journal of Econometrics, Elsevier, vol. 90(1), pages 129-153, May.
    15. Donald W. K. Andrews & Yixiao Sun, 2004. "Adaptive Local Polynomial Whittle Estimation of Long-range Dependence," Econometrica, Econometric Society, vol. 72(2), pages 569-614, March.
    16. Kalok Chan & Y. Peter Chung & Wai-Ming Fong, 2002. "The Informational Role of Stock and Option Volume," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1049-1075.
    17. repec:bla:jfinan:v:53:y:1998:i:2:p:431-465 is not listed on IDEAS
    18. Bhattacharya, Mihir, 1987. "Price Changes of Related Securities: The Case of Call Options and Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 1-15, March.
    19. repec:bla:jfinan:v:59:y:2004:i:3:p:1235-1258 is not listed on IDEAS
    20. Clifford M. Hurvich & Bonnie K. Ray, 2003. "The Local Whittle Estimator of Long-Memory Stochastic Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 1(3), pages 445-470.
    21. Christensen, Bent Jesper & Nielsen, Morten Orregaard, 2006. "Asymptotic normality of narrow-band least squares in the stationary fractional cointegration model and volatility forecasting," Journal of Econometrics, Elsevier, vol. 133(1), pages 343-371, July.
    22. repec:bla:jfinan:v:59:y:2004:i:2:p:711-753 is not listed on IDEAS
    23. D Marinucci & Peter M Robinson, 2001. "Narrow-Band Analysis of Nonstationary Processes," STICERD - Econometrics Paper Series 421, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    24. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    25. repec:bla:jfinan:v:43:y:1988:i:4:p:949-64 is not listed on IDEAS
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    Cited by:

    1. Zhang, Wei-Guo & Li, Zhe & Liu, Yong-Jun, 2018. "Analytical pricing of geometric Asian power options on an underlying driven by a mixed fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 402-418.
    2. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia, 2023. "Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence," International Review of Financial Analysis, Elsevier, vol. 87(C).
    3. Muhammad Aftab & Abid Ali & Scott W. Hegerty, 2021. "Foreign exchange market pressure and stock market dynamics in emerging Asia," International Economics and Economic Policy, Springer, vol. 18(4), pages 699-719, October.
    4. Sant'Anna, Leonardo Riegel & de Oliveira, Alan Delgado & Filomena, Tiago Pascoal & Caldeira, João Frois, 2020. "Solving the index tracking problem based on a convex reformulation for cointegration," Finance Research Letters, Elsevier, vol. 37(C).
    5. Sheng, Hainan, 2022. "Option measures and stock characteristics," Finance Research Letters, Elsevier, vol. 44(C).

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    More about this item

    Keywords

    Long memory; Fractional cointegration; Information effect; Volume effect; NBLS formula;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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