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A momentum trading strategy based on the low frequency component of the exchange rate

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Author Info

  • Harris, Richard D.F.
  • Yilmaz, Fatih

Abstract

In this paper, we develop a momentum trading strategy based on the low frequency trend component of the spot exchange rate. Using kernel regression and the high-pass filter of Hodrick and Prescott [Hodrick, R., Prescott, E., 1997. Post-war US business cycles: An empirical investigation. Journal of Money, Credit and Banking 29, 1-16], we recover the non-linear trend in the monthly exchange rate and use short-term momentum in this to generate buy and sell signals. The low frequency momentum trading strategy offers greater directional accuracy, higher returns and Sharpe ratios, lower maximum drawdown and less frequent trading than traditional moving average rules. Moreover, unlike traditional moving average rules, the performance of the low frequency momentum trading strategy is relatively robust across different time periods. The low frequency momentum trading strategy is also robust to the choice of smoothing parameter (in the case of the HP filter) and the distribution and bandwidth parameter (in the case of kernel regression) over a wide range of values.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Banking & Finance.

Volume (Year): 33 (2009)
Issue (Month): 9 (September)
Pages: 1575-1585

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Handle: RePEc:eee:jbfina:v:33:y:2009:i:9:p:1575-1585

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Web page: http://www.elsevier.com/locate/jbf

Related research

Keywords: Momentum Moving average rules Hodrick-Prescott filter Kernel regression Trading strategy;

References

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  1. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(04), pages 405-426, December.
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Citations

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Cited by:
  1. Lukas Menkhoff & Lucio Sarno & Maik Schmeling & Andreas Schrimpf, 2012. "Currency Momentum Strategies," Working Paper Series 09_12, The Rimini Centre for Economic Analysis.
  2. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2573-2586, November.
  3. Tajaddini, Reza & Crack, Timothy Falcon, 2012. "Do momentum-based trading strategies work in emerging currency markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(3), pages 521-537.
  4. Serban, Alina F., 2010. "Combining mean reversion and momentum trading strategies in foreign exchange markets," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2720-2727, November.
  5. Nikola Gradojevic & Camillo Lento, 2012. "Multiscale Analysis of Foreign Exchange Order Flows and Technical Trading Profitability," Working Paper Series 31_12, The Rimini Centre for Economic Analysis.
  6. Szakmary, Andrew C. & Shen, Qian & Sharma, Subhash C., 2010. "Trend-following trading strategies in commodity futures: A re-examination," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 409-426, February.
  7. Park, Young S. & Lee, Jaehyun, 2010. "Detecting insider trading: The theory and validation in Korea Exchange," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2110-2120, September.
  8. Schuhmacher, Frank & Eling, Martin, 2011. "Sufficient conditions for expected utility to imply drawdown-based performance rankings," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2311-2318, September.

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