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Published on 10 November 2023
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Duan,S. (2023). Performance of Time-series Momentum Strategy: US Evidence. Advances in Economics, Management and Political Sciences,35,45-54.
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Performance of Time-series Momentum Strategy: US Evidence

Siyao Duan *,1,
  • 1 University of Glasgow

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2754-1169/35/20231722

Abstract

This paper examines the effectiveness of the time series momentum strategy in generating positive returns in the US stock market, with a focus on exploring its dynamics and performance using different moving average methods. The author conducted an empirical analysis of the time series momentum strategy using S&P500 data from 2000 to 2022. A regression model was applied to estimate the expected returns and volatility of each as-set, and then an evaluation of momentum trading strategy based on different moving average methods was developed. The author evaluates the performance of the strategy with and without transaction costs. The study contributes to the literature by providing empirical evidence on the effectiveness of the time series momentum strategy in the US stock market and by exploring the performance of different moving average methods on the strategy. The findings of this study can provide insights for investors and portfolio managers interested in implementing momentum strategies in their investment portfolios.

Keywords

momentum strategy, time-series momentum, quantitative portfolio

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Cite this article

Duan,S. (2023). Performance of Time-series Momentum Strategy: US Evidence. Advances in Economics, Management and Political Sciences,35,45-54.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 7th International Conference on Economic Management and Green Development

Conference website: https://www.icemgd.org/
ISBN:978-1-83558-091-2(Print) / 978-1-83558-092-9(Online)
Conference date: 6 August 2023
Editor:Canh Thien Dang
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.35
ISSN:2754-1169(Print) / 2754-1177(Online)

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