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DEPENDENCE BETWEEN STOCK RETURNS AND investor sentiment IN CHINESE MARKETS:A COPULA APPROACH

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Journal of Systems Science & Complexity 2012年第3期25卷 529-548页

作者： Xunfa LU Kin Keung LAI Liang LIANG Department of Management Sciences City University of Hong KongHong KongChina School of Business University of Science and Technology of China

Using data of newly opened stock trading accounts in China as a proxy of investor sentiment index, the authors employ the time-varying copula-GARCH model with Hansen＇s skewed Student-t innovations to investigate the dynamic dependence between investor sentiment and stock returns. The empirical findings show that shifts in investor sentiment are asymptotically positively correlated to stock returns in extreme value situations in both A shares market and B shares market in China, that is to say, stock prices will increase （decrease） more when investors become more bullish （bearish）. Also, results show that the dependence between investor sentiment and stock returns is time-varying, which means that the traditional Pearson＇s correlation based on normal distribution is not enough to describe the relationship between stock market behavior and investor behavior.

关键词： Behavioral finance copula GARCH investor sentiment newly opened stock trading accounts.

A Study of Multi-Scale Relationship Between investor sentiment and Stock Index Fluctuation Based on the Analysis of BEMD Spillover Index

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Journal of Systems Science and Information 2021年第4期9卷 399-420页

作者： Weiguo CHEN Shufen ZHOU Yin ZHANG Yi SUN College of Economics and Management Beijing University of TechnologyBeijing 100124China China Post Group Corporation Limited Training Center Shijiazhuang 050021China School of Finance Anhui University of Finance and EconomicsBengbu 233000China

According to behavioral finance theory, investor sentiment generally exists in investors’ trading activities and influences financial market. In order to investigate the interaction between investor sentiment and stock market as well as financial industry, this study decomposed investor sentiment, stock price index and SWS index of financial industry into IMF components at different scales by using BEMD algorithm. Moreover, the fluctuation characteristics of time series at different time scales were extracted, and the IMF components were reconstructed into short-term high-frequency components, medium-term important event low-frequency components and long-term trend components. The short-term interaction between investor sentiment and Shanghai Composite Index, Shenzhen Component Index and financial industries represented by SWS index was investigated based on the spillover index. The time difference correlation coefficient was employed to determine the medium-term and long-term correlation among variables. Results demonstrate that investor sentiment has a strong correlation with Shanghai Composite Index, Shenzhen Component Index and different financial industries represented by SWS index at the original scale, and the change of investor sentiment is mainly influenced by external market information. The interaction between most markets at the short-term scale is weaker than that at the original scale. investor sentiment is more significantly correlated with SWS Bond, SWS Diversified Finance and Shanghai Composite Index at the long-term scale than that at the medium-term scale.

关键词： investor sentiment spillover index BEMD algorithm

Prediction of Shanghai Stock Index Based on investor sentiment and CNN-LSTM Model

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Journal of Systems Science and Information 2022年第6期10卷 620-632页

作者： Yi SUN Qingsong SUN Shan ZHU School of Finance Anhui University of Finance&EconomicsBengbu 233030China Management College Ocean University of ChinaQingdao 266100China School of Business Hong Kong Baptist UniversityHong Kong 999077China

In view of the breakthrough progress of the depth learning method in image and other fields,this paper attempts to introduce the depth learning method into stock price forecasting to provide investors with reasonable investment *** paper proposes a stock prediction hybrid model named ISI-CNN-LSTM considering investor sentiment based on the combination of long short-term memory(LSTM) and convolutional neural network(CNN).The model adopts an end-to-end network structure,using LSTM to extract the temporal features in the data and CNN to mine the deep features in the data can effectively improve the prediction ability of the model by increasing investor sentiment in the network *** empirical part makes a comparative experimental analysis based on Shanghai stock index in *** comparing the experimental prediction results and evaluation indicators,it verifies the prediction effectiveness and feasibility of ISI-CNN-LSTM network model.

关键词： convolution neural network long short-term memory investor sentiment stock price forecasting

An empirical examination of investor sentiment and stock market volatility: evidence from India

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Financial Innovation 2020年第1期6卷 667-681页

作者： Haritha P H Abdul Rishad Central University of Kerala KasaragodIndia Central University of Himachal Pradesh DharamsalaHimachal PradeshIndia

Understanding the irrational sentiments of the market participants is necessary for making good investment *** the recent academic effort to examine the role of investors’sentiments in market dynamics,there is a lack of consensus in delineating the structural aspect of market *** research is an attempt to address this *** study explores the role of irrational investors’sentiments in determining stock market *** employing monthly data on market-related implicit indices,we constructed an irrational sentiment index using principal component *** sentiment index was modelled in the GARCH and Granger causality framework to analyse its contribution to *** results showed that irrational sentiment significantly causes excess market ***,the study indicates that the asymmetrical aspects of an inefficient market contribute to excess volatility and *** findings are crucial for retail investors as well as portfolio managers seeking to make an optimum portfolio to maximise profits.

关键词： investor sentiment Stock market volatility Principal component analysis GARCH Granger causality test

investor sentiment and Cross-Sectional Return after Share Issuance:Evidence from Seasonal Equity Offering in China Market

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维普期刊数据库

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Journal of Finance Research 2020年第1期4卷 42-54页

作者： Di Liu Central University of Finance and Economics Chinese Academy of Finance and DevelopmentBeijing100081China

Our research on private placement of equity on China capital market reveals that firms prefer to equity financing when their stock price is overvalued and investor sentiment is high,following the market timing ***,after private issuance,we document a significant positive abnormal return within three *** believe firms choose to polish their financial statement before the exit of institutional investors and controlling *** manipulation of discretional accruals,firms improve the profitability and market valuation,and help institutional investors and controlling shareholders obtain the abnormal return after private placement of ***,such manipulation cannot be sustained and will do harm to other investors in the long-term.

关键词： investor sentiment Cross-sectional return Seasonal equity offering China market

IPO Underpricing and investor sentiment——Base on the SME Board Under the Circumstance of the Full Circulation

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维普期刊数据库

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International Journal of Systems and Control

International Journal of Systems and Control 2008年第3期 158-168页

作者： CHEN Shan-ang,GUO Shi-yu Deparment of Finance,School of Economics,Xiamen University,Xiamen 361005,China

It was found in this paper that,based on the empirical analysis of IPO underpricing of 222 companies listed on the Small & Medium Enterprise Board of the Shenzhen Stock Exchange(hereinafter referred to as the SME Board) during June 2004 to March 2008,the reform of listed companies’ non-tradable shares has not changed the structure of IPO underpricing on the SME Board,and that the success rate,the turnover rate of the first day,and the transformation between bull and bear markets,which reflect investor’s sentiment,are possibly the key factors influencing IPO underpricing of the SME *** the particularity of Chinese issuing system and the scarcity of stock supply are possibly another important factor of high IPO underpricing.

关键词： IPO underpricing behavioral finance investor sentiment

Study on the Relationship between investor sentiment and Stock Bubble

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同方期刊数据库

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Study on the Relationship between Investor Sentiment and Sto...

investor sentiments and stock marketsduring the COVID-19 pandemic

第30届中国控制与决策会议

作者： Weidong Yao Gang Liu School of Economics and Finance Xi’an Jiaotong University

The change of investors’ sentiment is one of the important factors which can affect the volatility of stock ***,few studies are related to stock bubble from the perspective of investor *** on behavioral finance theory,this paper builds the investor sentiment index by principal component ***,it uses the quarter panel data of listed companies of our country in 2006-2015,explores the relationship of investor sentiment and stock *** indicates:1) it finds that stock bubble is positively correlated with investor sentiment,new stock accounts,market price earning ratio,the amount of ***,the stock bubble is negative correlation with volume of market transactions,market turnover rate.2) it calculates the fundamental value of the stock by using residual income model,and finds that there are lots of bubbles among the listed companies of our *** results improve the system of behavioral finance theory,and provides some suggestions for government.

关键词： investor sentiment Stock Bubble Principal Component Analysis Residual Income Model

来源： cnki会议评论

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cnki会议

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Financial Innovation 2022年第1期8卷 1896-1929页

作者： Emre Cevik Buket Kirci Altinkeski Emrah Ismail Cevik Sel Dibooglu Tekirdag Namik Kemal Universitesi TekirdaǧTurkey Kırklareli University KırklareliTurkey University of Sharjah SharjahUnited Arab Emirates

This study examines the relationship between positive and negative investor sentiments and stock market returns and volatility in Group of 20 countries using variousmethods, including panel regression with fixed effects, panel quantile regressions, apanel vector autoregression (PVAR) model, and country-specific regressions. We proxyfor negative and positive investor sentiments using the Google Search Volume Indexfor terms related to the coronavirus disease (COVID-19) and COVID-19 vaccine, respectively. Using weekly data from March 2020 to May 2021, we document significantrelationships between positive and negative investor sentiments and stock marketreturns and volatility. Specifically, an increase in positive investor sentiment leads toan increase in stock returns while negative investor sentiment decreases stock returnsat lower quantiles. The effect of investor sentiment on volatility is consistent acrossthe distribution: negative sentiment increases volatility, whereas positive sentimentreduces volatility. These results are robust as they are corroborated by Granger causalitytests and a PVAR model. The findings may have portfolio implications as they indicatethat proxies for positive and negative investor sentiments seem to be good predictorsof stock returns and volatility during the pandemic.

关键词： COVID-19 investor sentiment Stock market returns Volatility

Intraday Market-Wide Ups/Downs and Returns

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维普期刊数据库

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Journal of Management Science and Engineering 2016年第1期1卷 28-57页

作者： Wei Zhang Shen Lin Yongjie Zhang The College of Management and Economics Tianjin UniversityTianjin 300072China China Center for Social Computing and Analytics Tianjin UniversityTianjin 300072China

Using stock market data over 16 years for Chinese stock markets and over 3 years for *** markets,this study explores the explanatory power of early intraday market-wide up and down movements to the subsequent intraday returns within the same trading *** compared to the closing of the previous trading day,we introduce two intraday market-wide up/down indicators in terms of the index return and the proportional difference in the numbers of stocks moving upwards to downwards at each minute.A time series analysis shows an economically and statistically significant positive relation between the intraday indicators and the subsequent intraday returns of the market *** trading strategies that exploit this intraday relationship lead to monthly returns of 4.1%in the Chinese market and 2.8%in the *** addition,the strategies are more profitable in markets with high activity of individual investors(i.e.,high trading value,low trading volume per transaction,small-cap,high B/M ratio,low institutional ownership,low price,and high number of shareholders).The results indicate that simple intraday market-wide up/down movements in the earlier trading affect the sentiment of retail investors,resulting in market movements in the same direction within the trading day.

关键词： Intraday market-wide movements Intraday returns investor sentiment Individual(retail)investors