The Left-tail Momentum of The Chinese Stock Market

Authors

  • Rong Fan

DOI:

https://doi.org/10.54097/j9qqh875

Keywords:

Asset pricing; Left tail risk; Analyst focus.

Abstract

In the research on the correlation between "risk and return", the capital pricing model and arbitrage pricing model have always occupied an important position, but in recent years, when the research market continues to expand and the research indicators are constantly enriched, the negative correlation between tail risk and cross-sectional returns of stocks has received more and more attention. Studies have used data from the U.S. stock market to find that the relationship between the left-tail risk of individual stocks and their cross-sectional returns is significantly negatively correlated, that is, stocks with higher left-tail risk have lower future returns. This finding contradicts the positive correlation between return and risk under traditional financial research, and then promotes the formation of left-tail risk anomalies. However, compared with the US stock market, the overall development time of China's stock market is relatively short, there are many retail investors, and market participants often do not have professional investment knowledge, so information asymmetry prompts blindly following market participants to invest irrationally like a herd, and most of the anomalies in asset pricing can be explained from the perspective of behavioral finance. Therefore, this paper draws on his research ideas to examine whether there is left-tailed momentum in the Chinese stock market, and whether the company characteristic indicator can strengthen this relationship and explain it through behavioral finance. This paper studies the period from January 1, 2000 to December 31, 2022, and aims to explore the cross-sectional correlation between left-tail risk and stock return in the coming month, using the return of all stocks in the Shanghai and Shenzhen markets to measure left-tail risk at risk. Firstly, the fundamental relationship between risk and return is explored through univariate combination analysis, and then the role and marginal contribution of company characteristic indicators on the relationship between risk and return are considered from the perspective of behavioral finance, considering common company characteristic indicators, such as book-to-market capitalization ratio, and indicators linked to poor investor information, such as analyst coverage, etc., to consider the role of corporate characteristic indicators on the relationship between risk and return from the perspective of behavioral finance. The results show that there is a significant left-tail momentum in China's stock market, that is, there is a negative correlation between left-tail risk and expected return, and the phenomenon of left-tail risk is more obvious in stocks with retail holdings and low analyst attention. When the yield is adjusted by the four-factor model, the performance of the left-tail momentum effect will be significantly strengthened, which is significantly better than the traditional capital asset pricing model and the three-factor model. In the research sense, frequent "black swan" events have made investors pay more and more attention to the huge risk contagion chain behind small probability events or extreme events, and at the same time suggest that the tail risks of relevant government departments may pose a major threat to the systematic smooth and orderly operation of the entire financial market.

Downloads

Download data is not yet available.

References

[1] Bali T G. An extreme value approach to estimating volatility and value at risk [J]. The Journal of Business, 2003, 76(1): 83-108.

[2] Atilgan Y, Bali T G, Demirtas K Ozgur, et al. Left-tail momentum: Underreaction to bad news, costly arbitrage and equity returns [J]. Journal of Financial Economics, 2020, 135(3): 725-53.

[3] Dowd K. A value at risk approach to risk-return analysis [J]. The Journal of Portfolio Management, 1999, 25(4): 60-7.

[4] Christoffersen P, Errunza V. Towards a global financial architecture: capital mobility and risk management issues [J]. Emerging Markets Review, 2000, 1(1): 3-20.

[5] Campbell R, Huisman R, Koedijk K, et al. Optimal portfolio selection in a Value-at-Risk framework [J]. Journal of Banking Finance, 2001, 25(9): 1789-804.

[6] Pritsker M. The channels for financial contagion [J]. International financial contagion, 2001: 67-95.

[7] Selmi R, Mensi W, Hammoudeh S, et al. Is Bitcoin a hedge, a safe haven or a diversifier for oil price movements? A comparison with gold [J]. Energy Economics, 2018, 74: 787-801.

[8] Bachelier L. Théorie de la spéculation; proceedings of the Annales scientifiques de l'École normale supérieure, F, 1900 [C].

[9] Qin J, FINANCE. Regret-based capital asset pricing model [J]. Journal of Banking Finance, 2020, 114: 105784.

[10] Horenstein A R. The unintended impact of academic research on asset returns: The capital asset pricing model alpha [J]. Management Science, 2021, 67(6): 3655-73.

[11] Yuan C, Haibo Y. Applicability test of CAPM model in cryptocurrency market[J]. Journal of Jiamusi University (Natural Science Edition), 2021, 39(04): 122-5.

[12] Fama E F, MacBeth J D. Risk, return, and equilibrium: Empirical tests [J]. Journal of political economy, 1973, 81(3 ): 607-36.

[13] Roll R, Ross S A. On the cross‐sectional relation between expected returns and betas [J]. The journal of finance, 1994, 49(1): 101-21.

[14] Fama E F, French K R. Common risk factors in the returns on stocks and bonds [J]. Journal of financial economics, 1993, 33(1): 3-56.

[15] Novy-Marx R. The other side of value: The gross profitability premium [J]. Journal of financial economics, 2013, 108(1): 1-28.

[16] Fama E F, French K R. Incremental variables and the investment opportunity set [J]. Journal of Financial Economics, 2015, 117(3): 470-88.

[17] Hejin L, Zhan L. Empirical test of capital asset pricing model in Shanghai stock market[J]. Forecasting, 2000, (05): 75-7+68.

[18] Kebin D, Haihua Z. Financing constraints of Chinese firms: characterizing the phenomenon and examining its causes[J]. Economic Research, 2014, 49(02): 47-60+140.

[19] Zhiyong H, Jingxin Z, Ni L, Beibei Y. Optimization analysis of five-factor model based on accounting information relevance[J]. Mathematical Statistics and Management, 2021, 40(04): 737-47.

[20] De Bondt W FM, Thaler R H. Further evidence on investor overreaction and stock market seasonality [J]. The Journal of finance, 1987, 42(3): 557-81.

Downloads

Published

28-05-2025

Issue

Section

Articles

How to Cite

Fan, R. (2025). The Left-tail Momentum of The Chinese Stock Market. Journal of Innovation and Development, 11(2), 84-93. https://doi.org/10.54097/j9qqh875