The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example

Yiqin Sun

doi:doi:10.11648/j.si.20180604.20

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The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example

Yiqin Sun

Published in Science Innovation (Volume 6, Issue 4)

Received: 2 August 2018 Published: 3 August 2018

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Abstract

The volatility of stock returns is affected by macro variables, economic policies, company fundamentals and investor sentiment. This paper studies the effect of behavioral finance on the asymmetry of stock market volatility, and selects the CSI 300 daily return rate from January 4, 2008 to December 31, 2016 as the research observations, using the EGARCH model that introduces the loss aversion function to model.The CSI 300 index daily returns volatility model is empirically tested. Empirical findings: (1) Loss of aversion and overreaction can explain the asymmetry (leverage) of volatility in China's stock market, that is, the fluctuation caused by the same amount of “bad” is greater than the fluctuation caused by the same “good” news. (2) The revised model more closely describes the asymmetry of China's stock market volatility and reflects the impact of asymmetric volatility on stock market risk control, pricing, and asset allocation. Finally, the article proposes to adopt a reversal strategy to reduce the bias caused by some human factors by quantifying transactions.

Published in	Science Innovation (Volume 6, Issue 4)
DOI	10.11648/j.si.20180604.20
Page(s)	232-239
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Stock Market Volatility, Asymmetry, Loss Aversion, Overreaction

References

[1]	巴曙松,朱虹.融资融券、投资者情绪与市场波动[J].国际金融研究,2016(08):82-96。
[2]	卞进，郭建鸾.股票市场过度反应与反向收益影响因素研究[J].财经问题研究，2016，(05)：76-82。
[3]	陈其安,雷小燕.货币政策、投资者情绪与中国股票市场波动性:理论与实证[J].中国管理科学.2017，(11)：1-11。
[4]	邵振文,侯丹.我国股指期货市场非对称性波动与下行风险研究[J].经济纵横,2018(03):108-113。
[5]	单馨,李旭瑞.投资者情绪与不同规模股票市场指数的关系研究[J].经济界,2017(05):54-61。
[6]	高奥，谭娅，吴卫星.中国股市收益波动性与投资者损失厌恶——基于上证综合指数的实证研究[J].南方金融，2015，(01):62-73。
[7]	贺刚,朱淑珍,顾海峰.中美股市的“创造空间效应”与“弗里德曼效应”比较分析:基于投资者情绪波动影响视角[J].世界经济研究,2017(10):34-44+135。
[8]	贺志芳,文凤华,黄创霞,杨晓光,郑石明.投资者情绪与时变风险补偿系数[J].管理科学学报,2017,20(12):29-38。
[9]	胡昌生,池阳春.投资者情绪、资产估值与股票市场波动[J].金融研究.2013，(10)：181-193。
[10]	刘璐，张倩.亚洲地区股票指数收益率的波动性研究——基于GARCH族模型[J].区域金融研究，2011，(01):34-39。
[11]	刘维奇,武翰章.投资者情绪会影响股票市场的误定价吗?——基于上证A股市场的实证研究[J].金融与经济,2018(03):19-25。
[12]	卢斌，王霞.中国股票市场波动非对称性的行为金融学解释[J].南京财经大学学报，2008，(06):36-41。
[13]	陆静,周媛.投资者情绪对股价的影响——基于AH股交叉上市股票的实证分析[J].中国管理科学,2015,23(11):21-28。
[14]	文凤华,肖金利,黄创霞,陈晓红,杨晓光.投资者情绪特征对股票价格行为的影响研究[J].管理科学学报,2014,17(03):60-69。
[15]	杨胜刚,成博.基于贝叶斯决策的证券市场过度反应[J].系统工程,2014,32(10):24-29。
[16]	翟佳茹.基于GRACH类模型的法兰克福DAX指数收益率波动性研究[J].企业改革与管理,2017(15):104-105。
[17]	张普,陈亮,曹启龙.信息视角下基于异质信念的股票波动性价值研究[J].管理科学,2018,31(02):147-160。
[18]	张宗新，王海亮.投资者情绪、主观信念调整与市场波动[J].金融研究，2013，(04)：142-155。
[19]	郑伟伦.上证综合指数股票价格短期预测——基于ARIMA模型的研究分析[J].经济研究导刊，2014，(16):136-13。
[20]	朱钧钧，谢识予.中国股市波动率的双重不对称性及其解释——基于MS-TGARCH模型的MCMC估计和分析[J].金融研究，2011，(03)：134-148。
[21]	朱超,曹洳宜.投资者非理性情绪、分析师评级变动与股票市场波动[J].金融科学,2017(02):58-76。
[22]	Baek C. Stock prices, dividends, earnings, and investor sentiment[J]. Review of Quantitative Finance & Accounting, 2016, 47(4):1043-1061.
[23]	Benartzi S.，R. H. Thaler. Myopic Loss Aversion and the Equity Premium Puzzle[J].The Quarterly Journal of Economics，1995，110(1).
[24]	Bondt,W.F.M.D.,Thaler,R. Does The Stock Market Overreact? [J]. The Journal of Finance, 1985,40(3):793-805.
[25]	Bollerslev T. Generalised Autoregressive Conditional Heteroskedasticity[J]. Econometrica, 1986, 31(302):2-27.
[26]	Box G E P, Jenkins G M, Reinsel G C. Time Series Analysis, Fourth Edition [M].Time Series Analysis. 2013:137-191.
[27]	Chandra A, Thenmozhi M. Investor Sentiment, Volatility and Stock Return Comovements[J]. Ssrn Electronic Journal, 2013.
[28]	Engle R F. Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation[J]. Econometrica, 1982, 50(4):987-1007.
[29]	Frugier A. Returns, volatility and investor sentiment: Evidence from European stock markets[J]. Research in International Business & Finance, 2016, 38:45-55.
[30]	Jacobs H. Market maturity and mispricing [J]. Journal of Financial Economics, 2016, 122(2):270-287.
[31]	Khatua S, Pradhan H K. Examining Overreaction in Indian Stock Market for Quarterly News[J]. Emaj Emerging Markets Journal, 2014, 4(1).
[32]	Kumari J, Mahakud J. Does investor sentiment predict the asset volatility? Evidence from emerging stock market India[J]. Journal of Behavioral & Experimental Finance, 2015, 8:25-39.
[33]	Labidi C, Yaakoubi S. Investor sentiment and aggregate volatility pricing[J]. Quarterly Review of Economics & Finance, 2016, 61:53-63.
[34]	Sayim M, Morris P D, Rahman H. The effect of US individual investor sentiment on industry‐specific stock returns and volatility[J]. Review of Behavioral Finance, 2013, 5(1):58-76.
[35]	Spyros Spyrou. Sentiment changes, stock returns and volatility: evidence from NYSE, AMEX and NASDAQ stocks[J]. Applied Financial Economics, 2012, 22(19):1631-1646.
[36]	Schneller D, Heiden S, Heiden M, et al. Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility[J]. German Economic Review, 2017.
[37]	Tversky A， Kahneman D. Advance in Prospect Theory: Cumulative Representation of Uncertainty [J]. Journal of Risk and Uncertainty，1992，5：297-323.
[38]	TC Chiang，CWS Chen，MKP So Asymmetric Return and Volatility Responses to Composite News from Stock Markets，[J].Multinational Finance Journal，2007，11 (3-4):179-210.
[39]	Uygur U, Taş O. The impacts of investor sentiment on returns and conditional volatility of international stock markets[J]. Quality & Quantity, 2014, 48(3):1165-1179.
[40]	Walid Saleh. Overreaction: the sensitivity of defining the duration of the formation period[J]. Applied Financial Economics. 2007， (1):45-61.
[41]	Yang K. Investor Sentiment and the Short-term Volatility of Stock Market:on What Happened in China in 2015[J]. Future & Development, 2016.
[42]	Zhang W Y, Meng N D, Zhang T P. Research on the Stock Market Volatility Influenced by Institutional Investor in China: Based on Investor Sentiment[J]. Journal of Beijing University of Technology, 2017.

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Yiqin Sun. (2018). The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example. Science Innovation, 6(4), 232-239. https://doi.org/10.11648/j.si.20180604.20

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ACS Style

Yiqin Sun. The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example. Sci. Innov. 2018, 6(4), 232-239. doi: 10.11648/j.si.20180604.20

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AMA Style

Yiqin Sun. The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example. Sci Innov. 2018;6(4):232-239. doi: 10.11648/j.si.20180604.20

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@article{10.11648/j.si.20180604.20,
  author = {Yiqin Sun},
  title = {The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example},
  journal = {Science Innovation},
  volume = {6},
  number = {4},
  pages = {232-239},
  doi = {10.11648/j.si.20180604.20},
  url = {https://doi.org/10.11648/j.si.20180604.20},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20180604.20},
  abstract = {The volatility of stock returns is affected by macro variables, economic policies, company fundamentals and investor sentiment. This paper studies the effect of behavioral finance on the asymmetry of stock market volatility, and selects the CSI 300 daily return rate from January 4, 2008 to December 31, 2016 as the research observations, using the EGARCH model that introduces the loss aversion function to model.The CSI 300 index daily returns volatility model is empirically tested. Empirical findings: (1) Loss of aversion and overreaction can explain the asymmetry (leverage) of volatility in China's stock market, that is, the fluctuation caused by the same amount of “bad” is greater than the fluctuation caused by the same “good” news. (2) The revised model more closely describes the asymmetry of China's stock market volatility and reflects the impact of asymmetric volatility on stock market risk control, pricing, and asset allocation. Finally, the article proposes to adopt a reversal strategy to reduce the bias caused by some human factors by quantifying transactions.},
 year = {2018}
}

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TY  - JOUR
T1  - The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example
AU  - Yiqin Sun
Y1  - 2018/08/03
PY  - 2018
N1  - https://doi.org/10.11648/j.si.20180604.20
DO  - 10.11648/j.si.20180604.20
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 232
EP  - 239
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20180604.20
AB  - The volatility of stock returns is affected by macro variables, economic policies, company fundamentals and investor sentiment. This paper studies the effect of behavioral finance on the asymmetry of stock market volatility, and selects the CSI 300 daily return rate from January 4, 2008 to December 31, 2016 as the research observations, using the EGARCH model that introduces the loss aversion function to model.The CSI 300 index daily returns volatility model is empirically tested. Empirical findings: (1) Loss of aversion and overreaction can explain the asymmetry (leverage) of volatility in China's stock market, that is, the fluctuation caused by the same amount of “bad” is greater than the fluctuation caused by the same “good” news. (2) The revised model more closely describes the asymmetry of China's stock market volatility and reflects the impact of asymmetric volatility on stock market risk control, pricing, and asset allocation. Finally, the article proposes to adopt a reversal strategy to reduce the bias caused by some human factors by quantifying transactions.
VL  - 6
IS  - 4
ER  -

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Yiqin Sun

School of Economics, Shanghai University, Shanghai, China

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APA Style

Yiqin Sun. (2018). The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example. Science Innovation, 6(4), 232-239. https://doi.org/10.11648/j.si.20180604.20

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ACS Style

Yiqin Sun. The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example. Sci. Innov. 2018, 6(4), 232-239. doi: 10.11648/j.si.20180604.20

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AMA Style

Yiqin Sun. The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example. Sci Innov. 2018;6(4):232-239. doi: 10.11648/j.si.20180604.20

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@article{10.11648/j.si.20180604.20,
  author = {Yiqin Sun},
  title = {The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example},
  journal = {Science Innovation},
  volume = {6},
  number = {4},
  pages = {232-239},
  doi = {10.11648/j.si.20180604.20},
  url = {https://doi.org/10.11648/j.si.20180604.20},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20180604.20},
  abstract = {The volatility of stock returns is affected by macro variables, economic policies, company fundamentals and investor sentiment. This paper studies the effect of behavioral finance on the asymmetry of stock market volatility, and selects the CSI 300 daily return rate from January 4, 2008 to December 31, 2016 as the research observations, using the EGARCH model that introduces the loss aversion function to model.The CSI 300 index daily returns volatility model is empirically tested. Empirical findings: (1) Loss of aversion and overreaction can explain the asymmetry (leverage) of volatility in China's stock market, that is, the fluctuation caused by the same amount of “bad” is greater than the fluctuation caused by the same “good” news. (2) The revised model more closely describes the asymmetry of China's stock market volatility and reflects the impact of asymmetric volatility on stock market risk control, pricing, and asset allocation. Finally, the article proposes to adopt a reversal strategy to reduce the bias caused by some human factors by quantifying transactions.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - The Influence of Behavioral Finance on Capital Market in China - Take the Asymmetrical Stock Market Fluctuation as an Example
AU  - Yiqin Sun
Y1  - 2018/08/03
PY  - 2018
N1  - https://doi.org/10.11648/j.si.20180604.20
DO  - 10.11648/j.si.20180604.20
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 232
EP  - 239
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20180604.20
AB  - The volatility of stock returns is affected by macro variables, economic policies, company fundamentals and investor sentiment. This paper studies the effect of behavioral finance on the asymmetry of stock market volatility, and selects the CSI 300 daily return rate from January 4, 2008 to December 31, 2016 as the research observations, using the EGARCH model that introduces the loss aversion function to model.The CSI 300 index daily returns volatility model is empirically tested. Empirical findings: (1) Loss of aversion and overreaction can explain the asymmetry (leverage) of volatility in China's stock market, that is, the fluctuation caused by the same amount of “bad” is greater than the fluctuation caused by the same “good” news. (2) The revised model more closely describes the asymmetry of China's stock market volatility and reflects the impact of asymmetric volatility on stock market risk control, pricing, and asset allocation. Finally, the article proposes to adopt a reversal strategy to reduce the bias caused by some human factors by quantifying transactions.
VL  - 6
IS  - 4
ER  -

Copy | Download