Download or read book On the Relationship Between the Conditional Mean and Volatility of Stock Return written by Michael W. Brandt and published by . This book was released on 2002 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book On the Relationship Between the Conditional Mean and Volatility of Stock Returns written by Michael W. Brandt and published by . This book was released on 2002 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads to pronounced counter-cyclical variation in the Sharpe ratio. We document significant lead-lag correlations between the conditional moments that also appear related to business cycles. Finally, we show that although the conditional correlation between the mean and volatility is negative, the unconditional correlation is positive due to the lead-lag correlations
Download or read book On the Relationship Between the Conditional and Volatility of Stock Returns written by Michael W. Brandt (Ph.D.) and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Causal Relationship Between Stock Returns and Volume written by Rochelle L. Antoniewicz and published by . This book was released on 1992 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Relationship between Stock Returns and Volatility in International Stock Markets written by Qi Li and published by . This book was released on 2005 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study examines the relationship between expected stock returns and volatility in the twelve largest international stock markets during January 1980 - December 2001. Consistent with most previous studies, we find a positive but insignificant relationship during the sample period for the majority of the markets based on parametric EGARCH-M models. However, using a flexible semiparametric specification of conditional variance, we find evidence of a significant negative relationship between expected returns and volatility in six out of the twelve markets under study. The results lend support to the recent claim (Bekaert and Wu, 2000; Whitelaw, 2000) that stock market returns are negatively correlated with stock market volatility.
Download or read book Information Volatility and the Cost of Capital written by Tanguy de Launois and published by Presses univ. de Louvain. This book was released on 2009 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: We all have in mind a couple of dramatic examples of how information released by some economical or political entity resulted in tremendous consequences for a private company or, worst, for the whole financial market. This is the purpose of this dissertation to investigate the relations between information,stock volatility and the cost of capital. After the extension of the standard CAPM model to a more realistic world where some investors are “constrained” and deviate from their optimal CAPM quantities, we confront our theoretical model to the empirical reality by investigating the so-called “index effect”. Thanks to econometric specifications robust to endogeneity, we test different hypotheses proposed by the literature to explain this well known value premium of firms belonging to large indices. In a next step, we investigate how the quality and quantity of micro and macro public signals impact the main determinants of our pricing equation initially developed. We show that in a world of constrained investors, firms benefiting from a high deviation have less incentive to communicate than others. Finally, we study the link between public information and conditional volatility thanks to an original sample of several tens of thousands of Reuters and Dow Jones news releases on both the French and US markets. Thanks to various econometric specifications like GARCH models and Markov Switching Regressions, we conclude that a larger daily number of news releases increases the probability to be in the high probability regime and that the impact ofinformation is strongly dependent on the topic and the timing of the release of this information.
Download or read book Stock Returns and Volatility written by Ramon P. DeGennaro and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Most asset pricing models postulate a positive relationship between a stock portfolio's expected returns and risk, which is often modeled by the variance of the asset price. This paper uses GARCH-in-mean models to examine the relationship between mean returns on a stock portfolio and its conditional variance or standard deviation.After estimating a variety of models from daily and monthly portfolio return data we conclude that any relationship between mean returns and own variance or standard deviation is weak. The results suggest that investors consider some other risk measure to be more important than the variance of portfolio returns.
Download or read book The Asymmetry of Market Returns and Its Impact on the Mean Variance Frontier written by Jatikumar Sengupta and published by . This book was released on 1990 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Persistence and Implied Persistence of Volatility of Stock Returns written by Chowdhury B. A. Mustafa and published by . This book was released on 1988 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stock Returns and Volatility written by Ramon P. DeGennaro and published by . This book was released on 2003 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most empirical work examining the intertemporal mean-variance relationship in stock returns has tended to use relatively simple specifications of the mean and especially of the conditional variance. We augment the information set to include economic variables that other researchers have found to be important and use GARCH-M models to explore the relation between volatility and expected stock returns. We find that the additional variables have little impact on the conditional variance and that any intertemporal relationship between volatility and stock returns is weak or unstable. Our results signal the need for theoretical models of the intertemporal volatility-return relationship, and call for further studies of the determinants of the conditional variance of stock returns.
Download or read book Risk Return and Volatility Feedback written by Mark J. Jensen and published by . This book was released on 2015 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: The relationship between risk and return is one of the most studied topics in finance. The majority of the literature is based on a linear, parametric relationship between expected returns and conditional volatility. This paper models the contemporaneous relationship between market excess returns and contemporaneous log-realized variances nonparametrically with an infinite mixture representation of their joint distribution. The conditional distribution of excess returns given log-realized variance will also have an infinite mixture representation but with probabilities and arguments depending on the value of realized variance. Our nonparametric approach allows for deviation from Gaussianity by allowing for higher-order nonzero moments and a smooth nonlinear relationship between the conditional mean of excess returns and contemporaneous log-realized variance. We find strong robust evidence of volatility feedback in monthly data. Once volatility feedback is accounted for, there is an unambiguous positive relationship between expected excess returns and expected log-realized variance. This relationship is nonlinear. Volatility feedback impacts the whole distribution and not just the conditional mean.
Download or read book On Business Cycle Variation in the Mean Volatility and Conditional Distribution of Stock Returns written by Gabriel Perez-Quiros and published by . This book was released on 1996 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Econometric Analysis of Models with Risk Terms written by A. R. Pagan and published by London : Centre for Decision Sciences and Econometrics, University of Western Ontario. This book was released on 1986 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book On the Predictability of Stock Returns written by Shmuel Kandel and published by . This book was released on 1995 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: The predictability of monthly stock returns is investigated from the perspective of a risk-averse investor who uses the data to update initially vague beliefs about the conditional distribution of returns. The optimal stocks-versus-cash allocation of the investor can depend importantly on the current value of a predictive variable, such as dividend yield, even though a null hypothesis of no predictability might not be rejected at conventional significance levels. When viewed in this economic context, the empirical evidence indicates a strong degree of predictability in monthly stock returns.
Download or read book Testing Mean Reversion in Stock Market Volatility written by Turan G. Bali and published by . This book was released on 2012 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper presents a comprehensive study of continuous time GARCH modeling with the thin-tailed normal and the fat-tailed Student-t and generalized error distributions. The paper measures the degree of mean reversion in stock return volatility based on the relationship between discrete time GARCH and continuous time diffusion models. The convergence results based on the aforementioned distribution functions are shown to have similar implications for testing mean reversion in stochastic volatility. Alternative models are compared in terms of their ability to capture mean-reverting behavior of stock return volatility. The empirical evidence obtained from several stock market indices indicates that the conditional variance, log-variance, and standard deviation of stock market returns are pulled back to some long-run average level over time.
Download or read book A Risk Return Relation in Stock Markets written by Napon Hongsakulvasu and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, I propose a new semi-parametric GARCH-in-Mean model. Since many empirical papers have the mix results on the risk-return relation, the cause of problem may come from the misspecification of conditional mean equation or conditional variance equation or both of them. My model uses non-parametric estimation in conditional mean equation and semi-parametric estimation in conditional variance equation which allows the non-linear risk return relation in conditional mean equation and allows the non-linear relation between the volatility and the cumulative sum of exponentially weighted past returns. Three parameters on my model are GARCH parameter, the leverage effect parameter and leptokurtic parameter. I also extend my model to include four exogenous variables, dividend yield, term spread, default spread and momentum into conditional mean equation by using additive model which allows each variable to have non-linear relation with the return. An empirical study on S&P 500 suggests that risk has a small affect on market return. However, when four exogenous variables are added to the model, my model shows that the risk-return relation has a positive hump shape. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155545
