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The Journal of Financial Data Science

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Time-Series Momentum: A Monte Carlo Approach

Clemens Struck and Enoch Cheng
The Journal of Financial Data Science Fall 2019, 1 (4) 103-123; DOI: https://doi.org/10.3905/jfds.2019.1.012
Clemens Struck
is an assistant professor in the School of Economics at University College in Dublin, Ireland and head of machine learning at PicardAngst AG in Switzerland;
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Enoch Cheng
is an assistant professor in the department of economics at the University of Colorado, Denver in Denver, CO
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Abstract

In this article the authors develop a Monte Carlo backtesting procedure for risk premium strategies and employ it to study time-series momentum (TSM). Relying on time-series models, empirical residual distributions, and copulas, the authors address two key drawbacks of conventional backtesting procedures. They create 10,000 paths of different TSM strategies based on the S&P 500 and a cross-asset-class futures portfolio. The simulations reveal a probability distribution that shows that strategies that outperform buy-and-hold in-sample using historical backtests may (1) exhibit tail risks and (2) underperform or outperform when out-of-sample. The results are robust to using different time-series models, time periods, asset classes, and risk measures.

TOPICS: Statistical methods, simulations, big data/machine learning

Key Findings

  • • Historical backtests suffer from the problem that they contain few tail events which may be an important driver for the performance of risk premium strategies.

  • • We develop a Monte-Carlo procedure that uses a combination of copulas, time-series models, and empirical residual distributions to overcome this problem.

  • • Applied to time-series momentum, we find that this strategy may (1) exhibit tail risks (2) underperform or outperform in the long run.

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The Journal of Financial Data Science: 1 (4)
The Journal of Financial Data Science
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Time-Series Momentum: A Monte Carlo Approach
Clemens Struck, Enoch Cheng
The Journal of Financial Data Science Oct 2019, 1 (4) 103-123; DOI: 10.3905/jfds.2019.1.012

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Time-Series Momentum: A Monte Carlo Approach
Clemens Struck, Enoch Cheng
The Journal of Financial Data Science Oct 2019, 1 (4) 103-123; DOI: 10.3905/jfds.2019.1.012
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