Time-series momentum: A Monte-Carlo approach

Arbeitspapier

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: UCD Centre for Economic Research Working Paper Series ; No. WP19/06

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Hypothesis Testing: General ; Model Evaluation, Validation, and Selection ; Asset Pricing; Trading Volume; Bond Interest Rates ; International Finance Forecasting and Simulation: Models and Applications
• Thema: Monte-Carlo ; Extreme Value Theory ; Backtesting ; Risk Premia ; Time-Series Momentum

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Cheng, Enoch ; Struck, Clemens
• Ereignis: Veröffentlichung
• (wer): University College Dublin, UCD School of Economics
• (wo): Dublin
• (wann): 2019

Weitere Informationen

• Handle: http://hdl.handle.net/10419/198582
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ