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Time-Series Momentum: A Monte-Carlo Approach
Author(s)
Date Issued
2019-03
Date Available
2019-05-23T09:30:04Z
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-of-sample i) exhibit sizeable tail risks ii) underperform or outperform. Our results are robust to using different time-series models, time periods, asset classes, and risk measures.
Type of Material
Working Paper
Publisher
University College Dublin. School of Economics
Series
UCD Centre for Economic Research Working Paper Series
WP19/06
Copyright (Published Version)
2019 the Authors
Classification
C12
C52
G12
F37
Language
English
Status of Item
Not peer reviewed
This item is made available under a Creative Commons License
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