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Using Macroeconomic Forecasts to Improve Mean Reverting Trading Strategies

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  • Yash Sharma

Abstract

A large class of trading strategies focus on opportunities offered by the yield curve. In particular, a set of yield curve trading strategies are based on the view that the yield curve mean-reverts. Based on these strategies' positive performance, a multiple pairs trading strategy on major currency pairs was implemented. To improve the algorithm's performance, machine learning forecasts of a series of pertinent macroeconomic variables were factored in, by optimizing the weights of the trading signals. This resulted in a clear improvement in the APR over the evaluation period, demonstrating that macroeconomic indicators, not only technical indicators, should be considered in trading strategies.

Suggested Citation

  • Yash Sharma, 2017. "Using Macroeconomic Forecasts to Improve Mean Reverting Trading Strategies," Papers 1705.08022, arXiv.org.
    • Handle: RePEc:arx:papers:1705.08022
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    References listed on IDEAS

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    1. Krishna Ramaswamy & Choong-Tze Chua & Winston T.H. Koh, 2004. "Profiting from Mean-Reverting Yield Curve Trading Strategies," Econometric Society 2004 Australasian Meetings 142, Econometric Society.
    2. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
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