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A theoretical analysis of trading rules: an application to the moving average case with Markovian returns

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  • Emmanuel Acar
  • Stephen Satchell

Abstract

A general framework for analysing trading rules is presented. We discuss different return concepts and different statistical processes for returns. We then concentrate on moving average trading rules and show, in the case of moving average models of length two, closed form expressions for the characteristic function of realized returns when the underlying return process follows a switching Markovian Gaussian process. An example is included which illustrates the technique.

Suggested Citation

  • Emmanuel Acar & Stephen Satchell, 1997. "A theoretical analysis of trading rules: an application to the moving average case with Markovian returns," Applied Mathematical Finance, Taylor & Francis Journals, vol. 4(3), pages 165-180.
    • Handle: RePEc:taf:apmtfi:v:4:y:1997:i:3:p:165-180
    DOI: 10.1080/135048697334791
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    References listed on IDEAS

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    1. Blake LeBaron, "undated". "Technical Trading Rules and Regime Shifts in Foreign Exchange," Working papers _007, University of Wisconsin - Madison.
    2. Charles J. Corrado & Suk-Hun Lee, 1992. "Filter Rule Tests Of The Economic Significance Of Serial Dependencies In Daily Stock Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 15(4), pages 369-387, December.
    3. Leuthold, Raymond M & Garcia, Philip & Lu, Richard, 1994. "The Returns and Forecasting Ability of Large Traders in the Frozen Pork Bellies Futures Market," The Journal of Business, University of Chicago Press, vol. 67(3), pages 459-473, July.
    4. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    5. LeBaron, B., 1992. "Do Moving Average Trading Rule Results Imply Nonlinearites in Foreign Exchange Markets?," Working papers 9222, Wisconsin Madison - Social Systems.
    6. Neftci, Salih N, 1991. "Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis."," The Journal of Business, University of Chicago Press, vol. 64(4), pages 549-571, October.
    7. J. L. Knight & S. E. Satchell & K. C. Tran, 1995. "Statistical modelling of asymmetric risk in asset returns," Applied Mathematical Finance, Taylor & Francis Journals, vol. 2(3), pages 155-172.
    8. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. "Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
    9. Blake LeBaron, "undated". "Do Moving Average Trading Rule Results Imply Nonlinearities in Foreign Exchange?," Working papers _005, University of Wisconsin - Madison.
    10. Charles J. Corrado & Suk-Hun Lee, 1992. "Filter Rule Tests Of The Economic Significance Of Serial Dependencies In Daily Stock Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 15(4), pages 369-387, December.
    11. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
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    Cited by:

    1. K. J. Hong & S. Satchell, 2013. "Time Series Momentum Trading Strategy and Autocorrelation Amplification," Cambridge Working Papers in Economics 1322, Faculty of Economics, University of Cambridge.
    2. Hong, KiHoon & Wu, Eliza, 2016. "The roles of past returns and firm fundamentals in driving US stock price movements," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 62-75.
    3. K. J. Hong & S. Satchell, 2015. "Time series momentum trading strategy and autocorrelation amplification," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1471-1487, September.
    4. KiHoon Jimmy Hong & Eliza Wu, 2014. "Can Momentum Factors Be Used to Enhance Accounting Information based Fundamental Analysis in Explaining Stock Price Movements?," Research Paper Series 346, Quantitative Finance Research Centre, University of Technology, Sydney.

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