Fractal momentum investment strategies based on liquidity non-linear fluctuations in Chinese stock market
| Date | 29 October 2024 |
| Pages | 193-219 |
| DOI | https://doi.org/10.1108/JCEFTS-12-2023-0063 |
| Published date | 29 October 2024 |
| Author | Ruzhen Yan,Xin Zhu,Kun Wang,Fanming Ma,Xu Wu |
Fractal momentum investment
strategies based on liquidity non-linear
fluctuations in Chinese stock market
Ruzhen Yan,Xin Zhu and Kun Wang
School of Business, Chengdu University of Technology, Chengdu, China
Fanming Ma
University of Wollongong, Wollongong, Australia, and
Xu Wu
School of Business, Chengdu University of Technology, Chengdu, China and
Post-Doctoral Research Station of Management Science and Engineering,
Chengdu University of Technology, Chengdu, China
Abstract
Purpose –This paper aims to the relationship between liquidity fluctuation trends and stocks’expected
returns.
Design/methodology/approach –The authors use the multi-fractal detrendedfluctuation analysis to study
the liquidity non-linear multi-fractal characteristics of stock market and predict the future volatility trend of
market liquidity with the help of potential entropy dimensional model and also consider the non-linear
volatility trend of liquidity, construct a fractal momentum strategy under different sortingperiods and holding
periods, to test the liquidity momentum effects of Chinese stock market and, finally, compare with the
traditionalprice momentum strategy.
Findings –The result suggests that: Chinese stock market liquidity has obvious non-linear multi-fractal
characteristics;the trend entropy dimensional model can accuratelypredict the future volatility trend of market
liquidity; significant liquidity trend momentum effects persist in the Chinese stock market, while price
momentum effects exist only in the short term; a significant liquidity premium exists in the Chinese equity
market; the fractal momentumstrategy constructed in this paper achieves higherreturns and less risk than the
price momentumstrategy.
Originality/value –Based on the above analysis, this paper will further construct a momentum strategy
incorporating liquidity trends, i.e. fractal momentum strategy (LMP strategy), with the realistic background
that Chinese stock market liquidityhas non-linear multi-fractal characteristics –the main contributionof this
paper is to overcome the shortcomings of existing momentumstrategies, which seldom combine the trend of
future liquidity fluctuations with momentum strategies, and to incorporate the real characteristics of the
market.
Keywords Liquidity trend forecasting, Momentum strategy, Multi-fractal, Portfolio,
Chinese stock market
Paper type Research paper
This research is financially supported by the National Natural Science Foundation of China
(71903017). The authors are solely responsible for any errors or omissions herein.
The data that support the findings of this study are available in iFinD database at http://ft.10jqka.
com.cn/index.php?c=index&a=iFinDPC.
Journal of
Chinese
Economic and
Foreign Trade
Studies
193
Journalof Chinese Economicand
ForeignTrade Studies
Vol.17 No. 2/3, 2024
pp. 193-219
© Emerald Publishing Limited
1754-4408
DOI 10.1108/JCEFTS-12-2023-0063
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1754-4408.htm
1. Introduction
With the size of individual investors in China’s A-share market having surpassed the 190
million mark in 2021, a figure that has led to a steady increase in the institutionalization of
the market, and stock and fundinvestments have become an important part of many families’
asset allocation. Furthermore, as the primary determinant of investment performance,
investment strategy has naturally received wide attention from both institutional and
individual investors.
Among the various investment strategies, the momentum strategy, which is based on the
theory of momentum effect, is the most commonly used trend investment strategy in
practice, and its core idea is that “the stronger the stronger”,i.e. it is believed that assets that
have performed better recently will continue to perform well over time. At the same time,
research has found that the existence and validity of the momentum effect have been
confirmed over time, across capital markets and asset classes in different countries and
regions (Liew and Vassalou, 2000;Rouwenhorst, 1998;Chen et al., 2014; Sehgal andJain,
2015; Ruenzi and Weigert, 2018). However, although the momentum effect is prevalent in
the stock market and provides the basis for investors’investment practices, it does not mean
that investors can achieve stable long-term excess returns. When market conditions change
abruptly,it can even trigger a momentum collapse and significant losses (Barrosoand Santa-
Clara, 2015;Daniel and Moskowitz, 2016;Wu et al., 2023). In 2015, the Chinese stock
market’s Shanghai Composite Index fell by nearly 30%, culminating in the “financial
tsunami”that saw a “thousand shares fall”. In 2020, the US stock market experienced four
significant declines in just 10 days underthe dual pressure of the “new crown epidemic”and
the “oil price crash”, with the NASDAQindex falling by more than 32% in total. In February
2022, the Russia-Ukraineconflict also led to severe turmoil in global stock markets.
In the context of international stock market crises, liquidity has been a key factor. Indeed,
significant alterations in yields are frequently accompanied by corresponding changes in
liquidity, which is also consistent with the liquidity premium theory. In a past study, Amihud
et al. (2015), using a sample of 45 national stock markets, found that stocks with high liquidity
have low expected returns and conversely stocks with low liquidity have high expected returns.
Furthermore, it was found that there is a very close link between the fluctuation trend of returns
and liquidity, i.e. the fluctuation trend of liquidity is an important factor affecting the pricing of
assets. Acharya and Pedersen (2005) constructed a liquidity-adjusted CAPM model and found
that the expected return on securities is closely related to liquidity. Stereńczak (2021) conducted
a study on the Polish stock market return–liquidity relationship using a panel model regression,
demonstrating that liquidity in emerging markets similarly affects expected returns. Zhang and
Lence (2023) introduce a two-factor model combining both market and liquidity factors to
confirm the existence of a significant liquidity premium in China’s stock market, using the
Shanghai and Shenzhen stock markets as the study sample for the period 2000–2019. Therefore,
this paper proposes the incorporation of liquidity into momentum strategies with the objective
of optimizing traditional momentum strategies for higher returns and lower risks.
Although momentum strategies incorporating liquidity are practicable, if research is not
conducted under the actualcharacteristics of stock market liquidity,the conclusions obtained
are difficult to ensure their reliabilityand even more difficult to direct investment practice (Li
et al.,2021). Many scholars have found that the stock market actually hasnon-linear multi-
fractal characteristics (Chen and Wang, 2017;Han et al., 2019;Zhang et al., 2022), In the
context of the fractal characteristicsof the stock market, liquidity, as a key factor of the stock
market, may also have non-linear multi-fractal characteristics. As multi-fractal detrended
fluctuation analysis (MF-DFA) does not impose requirements for time series smoothness
compared to other methods, it is more conduciveto simplifying the actual validation process
JCEFTS
17,2/3
194
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