Time‐series momentum in China's commodity futures market

• Author: Hoon Cho,Hyuna Ham,Hyeongjun Kim,Doojin Ryu
• DOI: http://doi.org/10.1002/fut.22053
• Published date: 01 December 2019
• Date: 01 December 2019

J Futures Markets. 2019;39:1515–1528. wileyonlinelibrary.com/journal/fut © 2019 Wiley Periodicals, Inc.

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1515

Received: 7 January 2019

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Accepted: 17 August 2019

DOI: 10.1002/fut.22053

RESEARCH ARTICLE

Time‐series momentum in China’s commodity futures

market

Hyuna Ham

1

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Hoon Cho

2

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Hyeongjun Kim

3

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Doojin Ryu

4

1

December & Company Inc, Seoul, Korea

2

Graduate School of Finance, Korea

Advanced Institute of Science and

Technology, Seoul, Korea

3

Department of Business Administration,

Yeungnam University, Gyeongsan, Korea

4

Department of Economics,

Sungkyunkwan University, Seoul, Korea

Correspondence

Doojin Ryu, Department of Economics,

Sungkyunkwan University, 25‐2

Sungkyunkwan-ro, Jongno‐gu,

Seoul 03063, Korea

Email: sharpjin@skku.edu

Abstract

This study examines the time‐series momentum in China’s commodity futures

market. We find that a time‐series momentum strategy outperforms classical

passive long and cross‐sectional momentum strategies in terms of the Sharpe

ratio, risk‐adjusted excess returns, and cumulative returns. The time‐series

momentum strategy with a 1‐month look‐back period and a 1‐month holding

period exhibits the best performance. We observe clear time‐series momentum

patterns and find that the time‐series momentum strategy is effective in the

Chinese commodity futures market. However, the momentum lasts for less time

in China than in the United States because China’s futures market seems to

have a greater number of speculative investors.

KEYWORDS

China, commodity futures, market anomaly, time‐series momentum, trading strategy

JEL CLASSIFICATION

G12; G13; G15

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INTRODUCTION

Asset price momentum, a financial market anomaly, is actively researched in the fields of behavioral finance and asset

pricing (Andrei & Cujean, 2017). Momentum strategies, which are based on the momentum anomaly, can be classified

as either cross‐sectional or time‐series momentum strategies. In the last decade, numerous studies have examined the

momentum anomaly in global financial markets to demonstrate the effectiveness of these momentum‐based strategies.

These previous studies predominantly focus on the cross‐sectional momentum in stock markets (Barroso &

Santa‐Clara, 2015; Docherty & Hurst, 2018). Cross‐sectional momentum strategies assume that the equity portfolios

with the highest earnings on recent trading days, that is, the so‐called “winner portfolios,”will outperform the

portfolios with the worst returns, that is, the so‐called “loser portfolios.”For example, Jegadeesh and Titman (1993)

show that cross‐sectional momentum strategies yield significant excess returns in equity markets.

The following studies examine momentum in derivatives markets worldwide to demonstrate the effectiveness and

implications of momentum strategies, but they also mainly focus on cross‐sectional momentum strategies. Asness,

Moskowitz, and Pedersen (2013), Bakshi, Gao, and Rossi (2019), Blitz and de Groot (2014), Fuertes, Miffre, and Rallis

(2010), Miffre and Rallis (2007), and Shen, Szakmary, and Sharma (2007) all study the cross‐sectional momentum in

commodity futures markets, although they use different definitions of winner and loser portfolios. Miffre (2016) reports

that the average Sharpe ratio of a cross‐sectional momentum strategy is 0.5, which is greater than the corresponding

value of –0.24 for a long‐only equally weighted portfolio. Kang and Kwon (2017) argue that cross‐sectional momentum

prevails in the global commodity futures markets. They find that the observed cross‐sectional momentum patterns are

not explained by traditional risk factors, macroeconomic indicators, or sector‐specific momentum.