Optimal time series momentum

He, X; Li, K; Shi, L

Optimal time series momentum

He, X

Li, K Shi, L

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Publication Type:: Conference Proceeding
Citation:: 3rd NUS Workshop on Risk and Regulation, 2015
Issue Date:: 2015-01-08

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Field	Value	Language
dc.contributor.author	He, X https://orcid.org/0000-0003-1446-9996	en_US
dc.contributor.author	Li, K	en_US
dc.contributor.author	Shi, L https://orcid.org/0000-0002-6226-1762	en_US
dc.date	2015-01-08	en_US
dc.date.issued	2015-01-08	en_US
dc.identifier.citation	3rd NUS Workshop on Risk and Regulation, 2015	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120404
dc.description.abstract	We develop a continuous-time asset price model to capture the time series momentum documented recently. The underlying stochastic delay differential system facilitates the analysis of effects of different time horizons used by momentum trading. By studying an optimal asset allocation problem, we find that the performance of time series momentum strategy can be significantly improved by combining with market fundamentals and timing opportunity with respect to market trend and volatility. Furthermore, the results also hold for different time horizons, the out-of-sample tests and with short-sale constraints. The outperformance of the optimal strategy is immune to market states, investor sentiment and market volatility.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP130103210
dc.relation.ispartof	3rd NUS Workshop on Risk and Regulation	en_US
dc.relation.ispartof	NUS Workshop on Risk and Regulation	en_US
dc.title	Optimal time series momentum	en_US
dc.type	Conference Proceeding
utslib.location.activity	Singapore	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	open_access
pubs.consider-herdc	false	en_US
pubs.finish-date	2015-01-09	en_US
pubs.start-date	2015-01-08	en_US

Abstract:

We develop a continuous-time asset price model to capture the time series momentum documented recently. The underlying stochastic delay differential system facilitates the analysis of effects of different time horizons used by momentum trading. By studying an optimal asset allocation problem, we find that the performance of time series momentum strategy can be significantly improved by combining with market fundamentals and timing opportunity with respect to market trend and volatility. Furthermore, the results also hold for different time horizons, the out-of-sample tests and with short-sale constraints. The outperformance of the optimal strategy is immune to market states, investor sentiment and market volatility.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/120404