IDEAS home Printed from https://ideas.repec.org/a/sae/ausman/v8y1983i2p71-93.html
   My bibliography  Save this article

Stock Market Efficiency and Price Predictions Implicit in Option Trading

Author

Listed:
  • R. L. Brown

    (Department of Accounting and Finance, Monash University. For helpful comments on earlier drafts we are grateful to Philip Brown, Graham Peirson, Richard Rendleman and participants in seminars at Monash University, the University of New South Wales and the University of Queensland. We are also grateful to Peter Small of the Options Clearing House (Sydney) for advice on certain details regarding data collection and to the Australian Merchant Bankers Association for providing us with interest rate data.)

  • T. J. Shevlin

    (Department of Accounting and Finance, Monash University. For helpful comments on earlier drafts we are grateful to Philip Brown, Graham Peirson, Richard Rendleman and participants in seminars at Monash University, the University of New South Wales and the University of Queensland. We are also grateful to Peter Small of the Options Clearing House (Sydney) for advice on certain details regarding data collection and to the Australian Merchant Bankers Association for providing us with interest rate data.)

Abstract

The Black-Scholes option pricing model (with approximate adjustments for dividends and exercise price changes) was used to generate stock prices which are “implied†by the model. If the stock market is efficient, these implied prices should not be capable of being used profitably by traders. This hypothesis is tested using prices established in the Australian Options Market and the Sydney Stock Exchange over the period February 1976 to December 1980. A close correspondence is found between implied stock prices and actual stock prices. Tests of the predictive power of the implied prices were unable to discover evidence of market inefficiency. However, a simulated trading strategy executed over one trading day and based on the largest discrepancies between actual and implied prices did meet with some success.

Suggested Citation

  • R. L. Brown & T. J. Shevlin, 1983. "Stock Market Efficiency and Price Predictions Implicit in Option Trading," Australian Journal of Management, Australian School of Business, vol. 8(2), pages 71-93, December.
  • Handle: RePEc:sae:ausman:v:8:y:1983:i:2:p:71-93
    DOI: 10.1177/031289628300800205
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/031289628300800205
    Download Restriction: no

    File URL: https://libkey.io/10.1177/031289628300800205?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. Manaster, Steven & Rendleman, Richard J, Jr, 1982. "Option Prices as Predictors of Equilibrium Stock Prices," Journal of Finance, American Finance Association, vol. 37(4), pages 1043-1057, September.
    2. Chiras, Donald P. & Manaster, Steven, 1978. "The information content of option prices and a test of market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 213-234.
    3. Latane, Henry A & Rendleman, Richard J, Jr, 1976. "Standard Deviations of Stock Price Ratios Implied in Option Prices," Journal of Finance, American Finance Association, vol. 31(2), pages 369-381, May.
    4. Whaley, Robert E., 1981. "On the valuation of American call options on stocks with known dividends," Journal of Financial Economics, Elsevier, vol. 9(2), pages 207-211, June.
    5. MacBeth, James D & Merville, Larry J, 1979. "An Empirical Examination of the Black-Scholes Call Option Pricing Model," Journal of Finance, American Finance Association, vol. 34(5), pages 1173-1186, December.
    Full references (including those not matched with items on IDEAS)

    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. Veld, C.H., 1991. "Warrant pricing : A review of theoretical and empirical research," Other publications TiSEM ac252bad-d1c0-45d6-832a-f, Tilburg University, School of Economics and Management.
    2. Ncube, Mthuli, 1996. "Modelling implied volatility with OLS and panel data models," Journal of Banking & Finance, Elsevier, vol. 20(1), pages 71-84, January.
    3. William Pedersen, 1998. "Capturing all the information in foreign currency option prices: solving for one versus two implied variables," Applied Economics, Taylor & Francis Journals, vol. 30(12), pages 1679-1683.
    4. David R. Peterson, 1986. "An Empirical Test Of An Ex-Ante Model Of The Determination Of Stock Return Volatility," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 9(3), pages 203-214, September.
    5. Hun Y. Park & R. Stephen Sears, 1985. "Changing Volatility And The Pricing Of Options On Stock Index Futures," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 8(4), pages 265-274, December.
    6. Alex Frino & Caihong Xu & Z. Ivy Zhou, 2022. "Are option traders more informed than Twitter users? A PVAR analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(9), pages 1755-1771, September.
    7. Debaditya Mohanti & P. K. Priyan, 2014. "An Empirical Test of Market Efficiency of Indian Index Options Market Using the Black–Scholes Model and Dynamic Hedging Strategy," Paradigm, , vol. 18(2), pages 221-237, December.
    8. Heejoon Han & Myung D. Park, 2013. "Comparison of Realized Measure and Implied Volatility in Forecasting Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 522-533, September.
    9. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
    10. Ben Hunt, 1991. "A Forecasting Model of Option Pricing Volatility," Working Paper Series 10, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    11. Linda S. Klein & David R. Peterson, 1988. "Investor Expectations Of Volatility Increases Around Large Stock Splits As Implied In Call Option Premia," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 11(1), pages 71-80, March.
    12. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
    13. Szakmary, Andrew & Ors, Evren & Kyoung Kim, Jin & Davidson, Wallace III, 2003. "The predictive power of implied volatility: Evidence from 35 futures markets," Journal of Banking & Finance, Elsevier, vol. 27(11), pages 2151-2175, November.
    14. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    15. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    16. Steven Li & Qianqian Yang, 2009. "The relationship between implied and realized volatility: evidence from the Australian stock index option market," Review of Quantitative Finance and Accounting, Springer, vol. 32(4), pages 405-419, May.
    17. Davidson, Wallace N. & Kim, Jin Kyoung & Ors, Evren & Szakmary, Andrew, 2001. "Using implied volatility on options to measure the relation between asset returns and variability," Journal of Banking & Finance, Elsevier, vol. 25(7), pages 1245-1269, July.
    18. Sherrick, Bruce J. & Irwin, Scott H. & Forster, D. Lynn, 1990. "Nonstationarity Of Soybean Futures Price Distributions: Option-Based Evidence," 1990 Annual meeting, August 5-8, Vancouver, Canada 270920, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Guan Wang & Pierre Yourougou & Yue Wang, 2012. "Which implied volatility provides the best measure of future volatility?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 93-105, January.
    20. Fackler, Paul L. & King, Robert P., 1987. "The Evaluation of Probability Distributions with Special Emphasis on Price Distributions Derived from Option Premiums," Regional Research Projects > 1987: S-180 Annual Meeting, March 22-25, 1987, San Antonio, Texas 272343, Regional Research Projects > S-180: An Economic Analysis of Risk Management Strategies for Agricultural Production Firms.

    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:sae:ausman:v:8:y:1983:i:2:p:71-93. 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: SAGE Publications (email available below). General contact details of provider: http://www.agsm.edu.au .

    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.