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Investor Sentiment, Volatility and Stock Return Comovements

Investor Sentiment, Volatility and Stock Return Comovements
Author: Abhijeet Chandra
Publisher:
Total Pages: 32
Release: 2013
Genre:
ISBN:

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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.


Excess Stock Return Comovements and the Role of Investor Sentiment

Excess Stock Return Comovements and the Role of Investor Sentiment
Author: Bart Frijns
Publisher:
Total Pages: 25
Release: 2017
Genre:
ISBN:

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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.


Essays on Investors' Sentiment and Attention

Essays on Investors' Sentiment and Attention
Author: Daniele Ballinari
Publisher:
Total Pages:
Release: 2021
Genre:
ISBN:

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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.


Another Look at Stock Return Comovement

Another Look at Stock Return Comovement
Author: Kaihua Deng
Publisher:
Total Pages: 92
Release: 2015
Genre:
ISBN:

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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

Behavioral Corporate Finance
Author: Hersh Shefrin
Publisher: College Ie Overruns
Total Pages: 300
Release: 2017-04-16
Genre: Corporations
ISBN: 9781259254864

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Market Volatility and Investor Confidence

Market Volatility and Investor Confidence
Author: New York Stock Exchange. Market Volatility and Investor Confidence Panel
Publisher:
Total Pages: 396
Release: 1990
Genre: Program trading (Securities)
ISBN:

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Investor Sentiment and the Cross-section of Stock Returns

Investor Sentiment and the Cross-section of Stock Returns
Author: Malcolm Baker
Publisher:
Total Pages: 36
Release: 2004
Genre: Investments
ISBN:

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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.


The Internationalization of Equity Markets

The Internationalization of Equity Markets
Author: Jeffrey A. Frankel
Publisher: University of Chicago Press
Total Pages: 428
Release: 2008-04-15
Genre: Business & Economics
ISBN: 0226260216

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This timely volume addresses three important recent trends in the internationalization of United States equity markets: extensive market integration through foreign investment and links among stock prices around the world; increasing securitization as countries such as Japan come to rely more than ever before on markets in equities and bonds at the expense of banks; and the opening of national financial systems of newly industrializing countries to international financial flows and institutions, as governments remove capital controls and other barriers. Eight essays examine such issues as the current extent of international market integration, gains to U.S. investors through international diversification, home-country bias in investing, the role of time and location around the world in stock trading, and the behavior of country funds. Other, long-standing questions about equity markets are also addressed, including market efficiency and the accuracy of models of expected returns, with a particular focus on variances, covariances, and the price of risk according to the Capital Asset Pricing Model.


How Does Investor Sentiment Have Impacts on Stock Returns and Volatility in the Growth Enterprise Market in China?

How Does Investor Sentiment Have Impacts on Stock Returns and Volatility in the Growth Enterprise Market in China?
Author: Jinshi Zheng
Publisher:
Total Pages:
Release: 2020
Genre:
ISBN:

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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

Relationship Between Individual Investor Sentiment with Its Volatility and Returns of Small-Cap Stocks
Author: Qin Yong
Publisher:
Total Pages: 12
Release: 2015
Genre:
ISBN:

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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.