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Entropy Risk Factor Model of Exchange Rate Prediction

Author

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  • Darrol J. Stanley
  • Levan Efremidze
  • Jannie Rossouw

Abstract

We investigate the predictability of an exchange rate with entropy risk factor model, as there is growing evidence that financial markets behave as complex systems. The model is tested on the data of South African Rand (ZAR) exchange rate for the period of 2004-2015. We calculate sample entropy based on the daily data of the exchange rate and conduct empirical implementation of several market timing rules based on these entropy signals. The dynamic investment portfolio based on entropy signals produces better risk adjusted performance than a buy and hold strategy. The returns are estimated on the portfolio values in U.S. dollars. The results raise the potential attractiveness of complex systems analyses, especially the methods of entropy, for foreign exchange market research and applications.

Suggested Citation

  • Darrol J. Stanley & Levan Efremidze & Jannie Rossouw, 2017. "Entropy Risk Factor Model of Exchange Rate Prediction," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 8(3), pages 51-56, July.
    • Handle: RePEc:jfr:ijfr11:v:8:y:2017:i:3:p:51-56
    DOI: 10.5430/ijfr.v8n3p51
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    References listed on IDEAS

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    1. Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
    2. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    3. Steve Pincus, 2008. "Approximate Entropy as an Irregularity Measure for Financial Data," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 329-362.
    4. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
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    1. Efremidze, Levan & Stanley, Darrol J. & Kownatzki, Clemens, 2021. "Entropy trading strategies reveal inefficiencies in Japanese stock market," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 464-477.

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