IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v36y2004i5p399-412.html
   My bibliography  Save this article

Prequential analysis of stock market returns

Author

Listed:
  • David Bessler
  • Robert Ruffley

Abstract

The Brier score and a covariance partition due to Yates are considered to study the probabilistic forecasts of a vector autoregression on stock market returns. Probabilistic forecasts from a model and data developed by Campbell (1991) are studied with ordinary least squares. Calibration measures and the Brier score and its partition are used for model assessment. The partitions indicate that the ordinary least squares version of Campbell's model does not forecast stock market returns particularly well. While the model offers honest probabilistic forecasts (they are well-calibrated), the model shows little ability to sort events that occur into different groups from events that do not occur. The Yates-partition demonstrates this shortcoming. Calibration metrics do not.

Suggested Citation

  • David Bessler & Robert Ruffley, 2004. "Prequential analysis of stock market returns," Applied Economics, Taylor & Francis Journals, vol. 36(5), pages 399-412.
    • Handle: RePEc:taf:applec:v:36:y:2004:i:5:p:399-412
    DOI: 10.1080/00036840410001682115
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/00036840410001682115
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036840410001682115?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-179, March.
    2. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," The Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 195-228.
    3. Covey, Ted & Bessler, David A, 1992. "Testing for Granger's Full Causality," The Review of Economics and Statistics, MIT Press, vol. 74(1), pages 146-153, February.
    4. Allan H. Murphy & Robert L. Winkler, 1977. "Reliability of Subjective Probability Forecasts of Precipitation and Temperature," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 26(1), pages 41-47, March.
    5. Kling, John L & Bessler, David A, 1989. "Calibration-Based Predictive Distributions: An Application of Prequential Analysis to Interest Rates, Money, Prices, and Output," The Journal of Business, University of Chicago Press, vol. 62(4), pages 477-499, October.
    6. Zellner, Arnold & Hong, Chansik & Min, Chung-ki, 1991. "Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter, and pooling techniques," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 275-304.
    7. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1999. "Multivariate Density Forecast Evaluation And Calibration In Financial Risk Management: High-Frequency Returns On Foreign Exchange," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 661-673, November.
    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. Dharmasena, Senarath & Bessler, David & Capps, Oral. Jr, 2016. "On the Evaluation of Probability Forecasts: An Application to Qualitative Choice Models," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235424, Agricultural and Applied Economics Association.
    2. Kannika Duangnate & James W. Mjelde, 2020. "Prequential forecasting in the presence of structure breaks in natural gas spot markets," Empirical Economics, Springer, vol. 59(5), pages 2363-2384, November.
    3. Casillas-Olvera, Gabriel & Bessler, David A., 2006. "Probability forecasting and central bank accountability," Journal of Policy Modeling, Elsevier, vol. 28(2), pages 223-234, February.
    4. Kyle E. Binder & Mohsen Pourahmadi & James W. Mjelde, 2020. "The role of temporal dependence in factor selection and forecasting oil prices," Empirical Economics, Springer, vol. 58(3), pages 1185-1223, March.
    5. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
    6. Chen, Junyi & McCarl, Bruce A. & Price, Edwin & Wu, Ximing & Bessler, David A., 2016. "Climate as a Cause of Conflict: An Econometric Analysis," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 229783, Southern Agricultural Economics Association.
    7. Yi-Mien Lin & Yun-Sheng Hsu & Shieh-Liang Chen, 2009. "Cash-flow news, market liquidity and liquidity risk," Applied Economics, Taylor & Francis Journals, vol. 41(9), pages 1137-1156.
    8. Huong Dang, 2014. "A Competing Risks Dynamic Hazard Approach to Investigate the Insolvency Outcomes of Property-Casualty Insurers," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 39(1), pages 42-76, January.
    9. Juan Yao & Graham Partington & Max Stevenson, 2005. "Run length and the predictability of stock price reversals," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 45(4), pages 653-671, December.

    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. Dharmasena, Senarath & Bessler, David & Capps, Oral. Jr, 2016. "On the Evaluation of Probability Forecasts: An Application to Qualitative Choice Models," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235424, Agricultural and Applied Economics Association.
    2. Brian H. Boyer & Taylor D. Nadauld & Keith P. Vorkink & Michael S. Weisbach, 2023. "Discount‐Rate Risk in Private Equity: Evidence from Secondary Market Transactions," Journal of Finance, American Finance Association, vol. 78(2), pages 835-885, April.
    3. Sellin, Peter, 1998. "Monetary Policy and the Stock Market: Theory and Empirical Evidence," Working Paper Series 72, Sveriges Riksbank (Central Bank of Sweden).
    4. Roni Michaely & Stefano Rossi & Michael Weber & Michael Weber, 2017. "The Information Content of Dividends: Safer Profits, Not Higher Profits," CESifo Working Paper Series 6751, CESifo.
    5. Stefano DellaVigna & Joshua M. Pollet, 2005. "Attention, Demographics, and the Stock Market," NBER Working Papers 11211, National Bureau of Economic Research, Inc.
    6. Tzavalis, Elias & Wickens, Michael, 1998. "A Re-examination of the Rational Expectations Hypothesis of the Term Structure: Reconciling the Evidence from Long-Run and Short-Run Tests," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 3(3), pages 229-239, July.
    7. Tuomo Vuolteenaho, 2002. "What Drives Firm‐Level Stock Returns?," Journal of Finance, American Finance Association, vol. 57(1), pages 233-264, February.
    8. Wagner, Moritz & Lee, John Byong-Tek & Margaritis, Dimitris, 2022. "Mutual fund flows and seasonalities in stock returns," Journal of Banking & Finance, Elsevier, vol. 144(C).
    9. Beeler, Jason & Campbell, John Y., 2012. "The Long-Run Risks Model and Aggregate Asset Prices: An Empirical Assessment," Critical Finance Review, now publishers, vol. 1(1), pages 141-182, January.
    10. John Y. Campbell & Yeung Lewis Chanb & M. Viceira, 2013. "A multivariate model of strategic asset allocation," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part II, chapter 39, pages 809-848, World Scientific Publishing Co. Pte. Ltd..
    11. Kenneth A. Froot & Melvyn Teo, 2004. "Equity Style Returns and Institutional Investor Flows," NBER Working Papers 10355, National Bureau of Economic Research, Inc.
    12. K. J. Martijn Cremers & Vinay B. Nair & Kose John, 2009. "Takeovers and the Cross-Section of Returns," Review of Financial Studies, Society for Financial Studies, vol. 22(4), pages 1409-1445, April.
    13. John Ammer & Jianping Mei, 1995. "Strategic returns to international diversification: An application to the equity markets of Europe, Japan and North America," European Financial Management, European Financial Management Association, vol. 1(1), pages 49-59, March.
    14. Qureshi, Fiza & Khan, Habib Hussain & Rehman, Ijaz Ur & Ghafoor, Abdul & Qureshi, Saba, 2019. "Mutual fund flows and investors’ expectations in BRICS economies: Implications for international diversification," Economic Systems, Elsevier, vol. 43(1), pages 130-150.
    15. Chen, Yong & Da, Zhi & Huang, Dayong, 2022. "Short selling efficiency," Journal of Financial Economics, Elsevier, vol. 145(2), pages 387-408.
    16. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang, 2022. "Predicting returns and dividend growth — The role of non-Gaussian innovations," Finance Research Letters, Elsevier, vol. 46(PA).
    17. Wu, Shue-Jen, 2023. "The role of the past long-run oil price changes in stock market," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 274-291.
    18. Chen Lian & Yueran Ma & Carmen Wang, 2019. "Low Interest Rates and Risk-Taking: Evidence from Individual Investment Decisions," The Review of Financial Studies, Society for Financial Studies, vol. 32(6), pages 2107-2148.
    19. Francisco Peñaranda, 2004. "Are Vector Autoregressions an Accurate Model for Dynamic Asset Allocation?," Working Papers wp2004_0419, CEMFI.
    20. Jorgensen, Bjorn & Li, Jing & Sadka, Gil, 2012. "Earnings dispersion and aggregate stock returns," Journal of Accounting and Economics, Elsevier, vol. 53(1), pages 1-20.

    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:taf:applec:v:36:y:2004:i:5:p:399-412. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.