Do trend following strategies work in Chinese futures markets?

• DOI: http://doi.org/10.1002/fut.21856
• Published date: 01 December 2017
• Author: Yang Zhou,Di Zhang,Bin Li
• Date: 01 December 2017

Received: 22 June 2016

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Accepted: 31 March 2017

DOI: 10.1002/fut.21856

RESEARCH ARTICLE

Do trend following strategies work in Chinese futures markets?

Bin Li

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Di Zhang

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Yang Zhou

Department of Finance, Economics and

Management School, Wuhan University,

Wuhan, P.R. China

Correspondence

Bin Li, Department of Finance, Economics

and Management School, Wuhan

University, Wuhan 430072, P.R. China.

Email: binli.whu@whu.edu.cn

Funding information

National Natural Science Foundation of

China, Grant numbers: 71401128,

91646206; The Academic Team Building

Plan for Young Scholars from Wuhan

University, Grant number: WHU2016012;

Natural Scientific Research Program of

Wuhan University, Grant number:

2042017kf0225

We examine the performance of trend following strategies in Chinese commodity

futures markets. We provide evidence that trend following-based technical trading

rules yield better performance than the buy and hold strategy on both individual

contracts and sorted portfolios. The outperformance is robust to transaction costs,

data frequency, sub-prime crisis, shorting constraint, delayed execution, liquidity and

parameters. Finally, the profitability of the trend following strategy may be subject to

data snooping bias.

1

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INTRODUCTION

1.1

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Background and motivations

Trend following technical analysis has been widely applied in the financial markets. Researchers and practitioners have

investigated its performance, but no consensus has been reached yet. Early studies (Fama & Blume, 1966; Jensen & Benington,

1970) support the efficient market hypothesis, which asserts that no exploitable trend exists in the market. Recent empirical

results (Han, Yang, & Zhou, 2013; Neely, Rapach, Tu, & Zhou, 2014) find evidence of the profitability of technical analysis, and

some empirical studies (Alexander, 1961; Cootner, 1962; Han, Hu, & Yang, 2016; Marshall, Cahan, & Cahan, 2008; Praetz,

1975) find that technical analysis is not always profitable. Miffre and Rallis (2007) demonstrate that momentum and contrarian

strategies are profitable on the agricultural futures. Park and Irwin (2010) show that the profitability of technical trading rules

could be reduced due to the data snooping issue. Szakmary, Shen, and Sharma (2007, 2010) examine 28 commodity futures

contracts and show that moving average trading rules are profitable on 22 of them. Clare, Seaton, Smith, and Thomas (2014) find

evidence that moving averages can outperform momentum-based trading rules on individual contracts. Narayan, Ahmed, and

Narayan (2015) show that the momentum-based strategy works well on 19 commodity futures contracts. In contrast, Marshall,

Cahan, and Cahan (2008) find that the timing strategy is not consistently profitable on 15 major commodity futures contracts.

Han et al. (2016) show that the simple moving average strategy robustly outperforms the buy and hold strategy on sorted

portfolios but does not consistently profit on 35 individual commodity futures.

As the largest emerging economy, China has been the second-largest economy since 2010 and the largest trading nation since

2013. Chinese commodity futures markets have played an increasingly important role in global financial systems. According to

the Futures Industry Association (FIA) 2015 annual trading volume survey, the exchanges in Dalian, Shanghai, and Zhengzhou

all rank among the top 10 commodity exchanges in the world. Both the encouragement from Chinese authorities and the

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© 2017 Wiley Periodicals, Inc. wileyonlinelibrary.com/journal/fut J Futures Markets. 2017;37:1226–1254.

expansion of China’s industrial sectors create surging demand for new types of futures contracts, which tends to stimulate further

growth of trading in future years (Fung & Tse, 2010).

Situated in the largest eme rging economy, Chinese fut ures markets are differen t from those of the develo ped countries,

such as the US, in several aspe cts. First and foremost, Chi nese futures markets are fil led with dominated by indiv idual

investors, while the market s in developed countries are u sually dominated by institu tional investors. Accord ing to the

Chinese Futures Associatio n, by the end of 2015, individual in vestors constituted 95.6 % of investors in Chinese futur es

markets, contributing 74.1 3% of the trading volume and 60.52% of open interes ts. In contrast, institutional investors norma lly

constitute more than 80% of the investo rs in US, Japan, and Hong Kong futures mark ets. Individual investors are ty pically

more emotional than institut ional investors (Liu & An, 2014 ; Ng & Wu, 2007), leading to highe r volatility, less informati on

efficiency, and more-ext reme events in Chinese fut ures markets. For example , on November 11, 2016, most commodity

futures experienced flas h crashes. In particular, the cotton contract slumped from a limit-u p price to a limit-down pric e in a

flash. Second, Chinese fut ures markets exhibit some un ique characteristics (se e, e.g., Zhen, 2013), such as in terventions by

authorities, inaccessib ility to foreign investor s and particular trade pra ctices, leading to differ ent return patterns from th e

futures markets in develo ped countries. Third, the di stinctive market structu res in Chinese futures mar kets lead to different

expectations from the results in U.S . markets. Since the launching of Chine se futures markets was very recen t in the 1990s,

advanced trading technol ogies have greatly reduce d transaction costs and impr oved market efficiency, leading to different

levels of profitability amon g trading strategies (Park & Irwin, 2007). In addition, in the pa st decades, Chinese author ities

have gradually implemented p rofound regulatory reform s (Chang, Luo, & Ren, 2014), which have greatly improved the

efficiency of futures marke ts. These reforms include th e introduction of QFIIs, the setup of CFFEX, the introduction of new

futures contracts, and the revision of old futures contracts. In summary, given the different patterns from the developed U .S.

futures markets, it is int eresting to see whether a pr ofitable trading strateg y in US futures market will still work in the

Chinese futures markets.

Although Han et al. (2016) show that a simple moving average is profitable on the sorted portfolios in the US futures markets,

it might not be straightforward to extend their results to Chinese futures markets, because of the distinct characteristics relative to

the US futures markets. In the following, we analyze how these characteristics may affect a trading strategy’s profitability,

especially the trend following strategies.

The first difference is the dominance of individual investors. On the one hand, individual investors typically have less

information than institutional investors. Because the information available to investors can largely affect their trading behavior,

individual investors tend to behave more like trend-followers than institutional investors (Watanabe, 2008). Wang, Zhang, and

Hua (2011) find empirical evidence supporting this pattern in Chinese futures markets. The herding behavior of individual

investors will cause asset prices to exhibit trends and may improve a trend following strategy’s profitability. On the other hand,

many individual investors in China adopt technical trading rules, which may deteriorate the performance due to their self-

destructive nature. The logic behind such a phenomenon is that when more investors adopt a strategy, the information will be

incorporated into the asset price, thereby weakening the strategy’s profitability. This logic is found to hold for technical analysis,

including the trend following indicators (Timmermann & Granger, 2004). Therefore, the popularity of technical indicators

among Chinese individual investors is likely to deteriorate the trend following strategy’s profitability. In summary, the

dominance of individual investors in the Chinese futures markets may have two opposing effects on a trend following strategy’s

profitability.

The second difference is the unique characteristics in Chinese futures markets, including constraints on capital flow,

authorities’interventions and low liquidity. First, Chinese government has set strict constraints on capital flows, which

hinders foreign investors from participating in Chinese futures markets. Therefore, Chinese futures markets are more

restricted to domestic participants, while global investors have easy access to well-established US futures markets. Under

this constraint, futures prices would exhibit a pattern of slow adjustment to a new equilibrium for limited arbitrage when

new information or shock comes. This feature naturally provides profitable opportunities to domestic investors in China.

Second, Chinese authorities are more active in enhancing macro-economic regulations to stabilize the economy. According

to the World Bank WDI Database, China’s capital formation ratio in 2012 was 48.7%, much larger than that of the U.S.

(19.1%) and the global average (21.8%), confirming the Chinese authorities’interventions. In the U.S., authorities’

interventions were common in foreign currency in the mid-1990s and declined afterward, accompanied by the declined

profit of technical traders (Sapp, 2004). More interventions in Chinese futures markets may induce predictable trends for

futures prices and therefore provide more-profitable trading opportunities. Third, Chinese futures markets exhibit lower

liquidity on average. Even though trading volume experienced an explosive increase in 2016, some Chinese futures

contracts are still illiquid. For example, during the period 2003–2014, there were 11 contracts with daily trading volume

lower than 500 contracts. Previous literature finds evidence of a liquidity premium in various markets, including stock,

LI ET AL.

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