Time-series momentum: Is it there?

Time-series momentum (TSM) refers to the predictability of the past 12-month return on the next one-month return, and is the focus of several recent influential studies. This paper shows, however, that asset-by-asset time-series regressions reveal little evidence of TSM, both in- and out-of-sample....

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Main Authors: HUANG, Dashan, LI, Jiangyuan, WANG, Liyao, ZHOU, Guofu
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2020
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/6521
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7520/viewcontent/Time_series_momentum_JFE_sv.pdf
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spelling sg-smu-ink.lkcsb_research-75202020-04-16T01:19:37Z Time-series momentum: Is it there? HUANG, Dashan LI, Jiangyuan WANG, Liyao ZHOU, Guofu Time-series momentum (TSM) refers to the predictability of the past 12-month return on the next one-month return, and is the focus of several recent influential studies. This paper shows, however, that asset-by-asset time-series regressions reveal little evidence of TSM, both in- and out-of-sample. While the t-statistic in a pooled regression appears large, it is not statistically reliable as it is less than the critical values of parametric and non-parametric bootstraps. From an investment perspective, the TSM strategy is profitable, but its performance is virtually the same as that of a similar strategy that is based on historical sample mean and does not require predictability. Overall, the evidence on TSM is weak, particularly for the large cross section of assets. 2020-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/6521 info:doi/10.1016/j.jfineco.2019.08.004 https://ink.library.smu.edu.sg/context/lkcsb_research/article/7520/viewcontent/Time_series_momentum_JFE_sv.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Time-series momentum Risk premium Return predictability Pooled regression Finance Finance and Financial Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Time-series momentum
Risk premium
Return predictability
Pooled regression
Finance
Finance and Financial Management
spellingShingle Time-series momentum
Risk premium
Return predictability
Pooled regression
Finance
Finance and Financial Management
HUANG, Dashan
LI, Jiangyuan
WANG, Liyao
ZHOU, Guofu
Time-series momentum: Is it there?
description Time-series momentum (TSM) refers to the predictability of the past 12-month return on the next one-month return, and is the focus of several recent influential studies. This paper shows, however, that asset-by-asset time-series regressions reveal little evidence of TSM, both in- and out-of-sample. While the t-statistic in a pooled regression appears large, it is not statistically reliable as it is less than the critical values of parametric and non-parametric bootstraps. From an investment perspective, the TSM strategy is profitable, but its performance is virtually the same as that of a similar strategy that is based on historical sample mean and does not require predictability. Overall, the evidence on TSM is weak, particularly for the large cross section of assets.
format text
author HUANG, Dashan
LI, Jiangyuan
WANG, Liyao
ZHOU, Guofu
author_facet HUANG, Dashan
LI, Jiangyuan
WANG, Liyao
ZHOU, Guofu
author_sort HUANG, Dashan
title Time-series momentum: Is it there?
title_short Time-series momentum: Is it there?
title_full Time-series momentum: Is it there?
title_fullStr Time-series momentum: Is it there?
title_full_unstemmed Time-series momentum: Is it there?
title_sort time-series momentum: is it there?
publisher Institutional Knowledge at Singapore Management University
publishDate 2020
url https://ink.library.smu.edu.sg/lkcsb_research/6521
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7520/viewcontent/Time_series_momentum_JFE_sv.pdf
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