Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/198582
Authors: 
Cheng, Enoch
Struck, Clemens
Year of Publication: 
2019
Series/Report no.: 
UCD Centre for Economic Research Working Paper Series No. WP19/06
Abstract: 
This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time-Series Momentum (TSM). Relying on time-series models, empirical residual distributions and copulas we overcome two key drawbacks of conventional backtesting procedures. We 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 which shows that strategies that outperform Buy-and-Hold in-sample using historical backtests may out-ofsample i) exhibit sizable tail risks ii) underperform or outperform. Our results are robust to using different time-series models, time periods, asset classes, and risk measures.
Subjects: 
Monte-Carlo
Extreme Value Theory
Backtesting
Risk Premia
Time-Series Momentum
JEL: 
C12
C52
G12
F37
Document Type: 
Working Paper

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