Investor Sentiment Volatility And Stock Return Comovements

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Investor Sentiment Volatility And Stock Return Comovements

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Author : Abhijeet Chandra
language : en
Publisher:
Release Date : 2013

Investor Sentiment Volatility And Stock Return Comovements written by Abhijeet Chandra and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.

We study the stock return comovements from two different perspectives, one being trading behaviour-induced return comovements and the other volatility-induced return comovements. Following Baker and Wurglur (2006), we construct an investor sentiment index and examine whether it has relationship with return comovements induced by investor's trading behaviour and market volatility. We find that a correlated trading behaviour along with investor sentiment significantly determines excess stock returns. Also stocks with high volatility exhibit higher return comovement properties compared to low volatilie stocks. In a cross-sectional framework, we find higher level of market uncertainty characterized by more biased investor sentiment induces highly correlated trading behaviour and thereby generates stronger correlated returns, causing stronger return comovements. The findings from our study imply that irrational and idiosyncratic sentiment of market participants, particularly which of investors, causes significant return comovement.

Essays On Investors Sentiment And Attention

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Author : Daniele Ballinari
language : en
Publisher:
Release Date : 2021

Essays On Investors Sentiment And Attention written by Daniele Ballinari and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.

The first paper investigates the predictive power of investors' sentiment and attention for the stock returns' volatility. We introduce a novel and extensive dataset that combines information from social media platforms, news articles, search engine data, and information consumption. Applying a state-of-the-art sentiment classification technique, we construct measures of investors' sentiment and attention for 18 U.S. stocks and the financial market in general. We identify investors' attention, as measured by the number of Google searches on financial keywords (e.g. «financial market» and «stock market»), and the daily volume of company-specific short messages posted on the social media platform StockTwits to be the most relevant variables. The second paper investigates a potential driver of the predictive power documented in the first paper. We focus on news releases of 360 U.S. companies from the S&P 500 universe and analyze how investors' attention affects the speed at which new information is incorporated in stock prices. Our results show that higher investors' attention around news releases is related to higher contemporaneous volatility. Further, retail investor attention increases the post-announcement volatility, whereas institutional investor attention has a small but negative impact on volatility on days following news releases. The third paper extends the analysis of the first paper to the multivariate stock return volatility. Building on the theoretical and empirical evidence that links the price comovements with retail investors' behavior, we analyze the predictive power of retail investors' sentiment and attention for the realized correlation matrix of 35 Dow Jones stocks. We propose a new model of realized covariances that allows exogenous predictors to influence the correlation dynamics while ensuring the predicted matrices' positive definiteness. Using this model, we find retail investors' attention to have predictive power for return correlations, especially for longer forecasting horizons and during the COVID-19 pandemic. The last paper analyzes in more detail the time-series properties of the daily online investor sentiment measures used in the first two papers. We detect structural breaks in the sentiment series for most of the 360 U.S. companies considered in this paper. We illustrate the economic significance of this finding with a return prediction exercise.

Excess Stock Return Comovements And The Role Of Investor Sentiment

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Author : Bart Frijns
language : en
Publisher:
Release Date : 2017

Excess Stock Return Comovements And The Role Of Investor Sentiment written by Bart Frijns and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

This paper investigates whether investor sentiment can explain stock return comovements. Our findings demonstrate that since the 1960s, there has been a clear and rapid increase in correlations between international equity markets. Decomposing the equity returns into fundamental and non-fundamental components reveals that the increased correlation is driven by the non-fundamental part. We find that stock return comovements are mainly driven by investor sentiment, which explains the level, variance, and covariance of the non-fundamental component of returns.

Another Look At Stock Return Comovement

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Author : Kaihua Deng
language : en
Publisher:
Release Date : 2015

Another Look At Stock Return Comovement written by Kaihua Deng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

The study of the comovement between asset returns reflects an ongoing effort by economists to understand investment risk in financial markets. Building on previous findings, in the current thesis I provide some new evidence on this topic with a focus on large-cap stocks and highlight an innovative way to evaluate the statistical significance of comovement asymmetry. In the first part of the thesis, I revisit the question of how large-cap stock return comovement varies with volatility and market returns. I propose the use of an eigenvalue-based measure of comovement in a multivariate semi-Markov-switching framework. I conduct various model evaluation checks and compare the new results with that based on a benchmark. I estimate models with two to four regimes and consider the impact of sample selection and outlier reduction. Contrary to the sweeping sentiment that comovement is highest when market is down and volatile, I illustrate the significance of comovement differential across states and find in most case studies evidence that suggests otherwise. In the second part, I propose a test of asymmetric stock return comovement across states. The test can be viewed as a variation of Kendall's [unknown mathematical symbol] conditional on the state and has an asymptotic X^2-distribution. A refined version of the test is derived based on the Markov chain theory of regenerative cycles which substantially improves finite sample size and power. I show that the test has power against local alternatives, which is nonetheless compromised due to a finite sample convergence bound put on the implied local alternative data generating process. I evaluate the new test against traditional correlation-based measures and demonstrate power attrition due to nuisance parameters when states are ignored. I find that asymmetric tail dependence becomes much less significant when considered state by state. A list of related tests is given as an extension at the end.

Behavioral Corporate Finance

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Author : Hersh Shefrin
language : en
Publisher: College Ie Overruns
Release Date : 2017-04-16

Behavioral Corporate Finance written by Hersh Shefrin and has been published by College Ie Overruns this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-16 with Corporations categories.

Investor Sentiment In The Stock Market

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Author : Malcolm P. Baker
language : en
Publisher:
Release Date : 2007

Investor Sentiment In The Stock Market written by Malcolm P. Baker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Finance categories.

"Real investors and markets are too complicated to be neatly summarized by a few selected biases and trading frictions. The "top down" approach to behavioral finance focuses on the measurement of reduced form, aggregate sentiment and traces its effects to stock returns. It builds on the two broader and more irrefutable assumptions of behavioral finance -- sentiment and the limits to arbitrage -- to explain which stocks are likely to be most affected by sentiment. In particular, stocks of low capitalization, younger, unprofitable, high volatility, non-dividend paying, growth companies, or stocks of firms in financial distress, are likely to be disproportionately sensitive to broad waves of investor sentiment. We review the theoretical and empirical evidence for these predictions."--abstract.

Investor Sentiment And The Cross Section Of Stock Returns

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Author : Malcolm Baker
language : en
Publisher:
Release Date : 2004

Investor Sentiment And The Cross Section Of Stock Returns written by Malcolm Baker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Investments categories.

We examine how investor sentiment affects the cross-section of stock returns. Theory predicts that a broad wave of sentiment will disproportionately affect stocks whose valuations are highly subjective and are difficult to arbitrage. We test this prediction by studying how the cross-section of subsequent stock returns varies with proxies for beginning-of-period investor sentiment. When sentiment is low, subsequent returns are relatively high on smaller stocks, high volatility stocks, unprofitable stocks, non-dividend-paying stocks, extreme-growth stocks, and distressed stocks, consistent with an initial underpricing of these stocks. When sentiment is high, on the other hand, these patterns attenuate or fully reverse. The results are consistent with predictions and appear unlikely to reflect an alternative explanation based on compensation for systematic risk.

How Does Investor Sentiment Have Impacts On Stock Returns And Volatility In The Growth Enterprise Market In China

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Author : Jinshi Zheng
language : en
Publisher:
Release Date : 2020

How Does Investor Sentiment Have Impacts On Stock Returns And Volatility In The Growth Enterprise Market In China written by Jinshi Zheng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

This dissertation mainly explores the effect of investor sentiment on stock returns and volatility on Growth Enterprise in China using monthly data from Shenzhen Stock Exchange of China from June 2010 to November 2019. Using five explicit and market-related implicit indicators an investor sentiment has been measured and constructed with the help of principal component analysis. The analysis has been done by employing a vector autoregression(VAR) model and impulse response functions (IRFs) generated from a VAR model to examine the relationship between the unanticipated changes in investor sentiment and stock returns and volatility. We also establish EGARCH model to test the validity of previous results and if the asymmetric impact of positive and negative news on market returns volatility. The results show a significant impact of investor sentiment on stock return and volatility. We also document that there is a positive leverage effect between investor sentiment and the volatility of returns. The findings of this paper can help both individual and institutional investors have a better understanding of GEM market and improve their investment returns by incorporating investor sentiment into their asset forecasting model. This paper also provides policymakers guidance on reducing volatility on stock markets from the perspective of investor sentiment. Additionally, this paper has important contributions to behavioral finance and adds to the limited number of studies on investor sentiment and stock return in not only the Chinese market but emerging markets.

Relationship Between Individual Investor Sentiment With Its Volatility And Returns Of Small Cap Stocks

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Author : Qin Yong
language : en
Publisher:
Release Date : 2015

Relationship Between Individual Investor Sentiment With Its Volatility And Returns Of Small Cap Stocks written by Qin Yong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

Due to the irrational behavior of individual investors have a significant impact on the stock market, and Chinese stock market with inexperienced individual investors as the main body, our individual investor sentiment may play a more important role than in Western countries in the stock trading process. Therefore, this paper use ARMA-GARCH model to examine the relationship between the investor sentiment along its volatility and the small-cap stocks, which are individually described by newly opened stock trading accounts and the CSI 500. The results show that: The individual investor behavior exhibits a short-term ARCH effects and small-cap stocks exhibit short-term gain inertia; the high number of newly opened stock trading accounts responses to high small-cap stocks yields and display a "spillover effect" to market return; using newly opened stock trading accounts as individual investor sentiment index has great explanatory power to small-cap stocks in China.

Investor Sentiment In The Stock Market

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Author : Malcolm P. Baker
language : en
Publisher:
Release Date : 2009

Investor Sentiment In The Stock Market written by Malcolm P. Baker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.

Real investors and markets are too complicated to be neatly summarized by a few selected biases and trading frictions. The quot;top downquot; approach to behavioral finance focuses on the measurement of reduced form, aggregate sentiment and traces its effects to stock returns. It builds on the two broader and more irrefutable assumptions of behavioral finance - sentiment and the limits to arbitrage - to explain which stocks are likely to be most affected by sentiment. In particular, stocks of low capitalization, younger, unprofitable, high volatility, non-dividend paying, growth companies, or stocks of firms in financial distress, are likely to be disproportionately sensitive to broad waves of investor sentiment. We review the theoretical and empirical evidence for these predictions.