The Time-Series Behavior and Pricing of Idiosyncratic Volatility PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download The Time-Series Behavior and Pricing of Idiosyncratic Volatility PDF full book. Access full book title The Time-Series Behavior and Pricing of Idiosyncratic Volatility by Paul Brockman. Download full books in PDF and EPUB format.
Author: Paul Brockman
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
Get Book Here
Book Description
Recent research on idiosyncratic volatility has documented three main empirical findings. First, Campbell, Lettau, Malkiel, and Xu (2001) show that idiosyncratic volatility exhibits an upward trend between 1962 and 1997. Second, Goyal and Santa-Clara (2003) find that aggregate measures of idiosyncratic volatility predict one-month-ahead excess market returns from 1962 to 1999. Third, Ang, Hodrick, Xing, and Zhang (2006) report a negative and significant relation between idiosyncratic volatility and cross-sectional stock returns from 1963 to 2000. We re-examine these three findings using a 37-year holdout sample of daily returns from 1926 to 1962. We find robust empirical evidence of (1) a statistically significant downward trend in idiosyncratic volatility, (2) an insignificant relation between average idiosyncratic volatility and one-month-ahead excess market returns, and (3) a highly significant inverse relation between idiosyncratic volatility and cross-sectional stock returns. These results shed new light on the time-series behavior and pricing of idiosyncratic volatility.
Author: Paul Brockman
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
Get Book Here
Book Description
Recent research on idiosyncratic volatility has documented three main empirical findings. First, Campbell, Lettau, Malkiel, and Xu (2001) show that idiosyncratic volatility exhibits an upward trend between 1962 and 1997. Second, Goyal and Santa-Clara (2003) find that aggregate measures of idiosyncratic volatility predict one-month-ahead excess market returns from 1962 to 1999. Third, Ang, Hodrick, Xing, and Zhang (2006) report a negative and significant relation between idiosyncratic volatility and cross-sectional stock returns from 1963 to 2000. We re-examine these three findings using a 37-year holdout sample of daily returns from 1926 to 1962. We find robust empirical evidence of (1) a statistically significant downward trend in idiosyncratic volatility, (2) an insignificant relation between average idiosyncratic volatility and one-month-ahead excess market returns, and (3) a highly significant inverse relation between idiosyncratic volatility and cross-sectional stock returns. These results shed new light on the time-series behavior and pricing of idiosyncratic volatility.
Author: Zhentao Liu
Publisher:
ISBN:
Category :
Languages : en
Pages : 28
Get Book Here
Book Description
Purpose: The current research is to investigate the time series behavior of idiosyncratic volatility (IVOL) and its role in asset pricing in France in a twenty-year testing period. Design/methodology/approach: We test for the presence of trends in aggregate idiosyncratic and market volatility using Bunzel and Vogelsang's (2005) t-dan test. We follow Bekaert et al. (2012) to test for regime shifts of both aggregate idiosyncratic and market volatilities. And then, we employ portfolio level analysis and cross-sectional univariate Fama-MacBeth regressions to examine the relationship between IVOL and cross-sectional stock returns in French stock market.Findings: First, we find that both idiosyncratic and market volatility do not exhibit long-term trends. Instead, their patterns are consistent with regime switching behavior. Second, though we initially find a strong significant negative IVOL effect in the French stock market which is robust in bi-variate Fama-MacBeth regressions, the negative IVOL effect is becoming marginal significant when we control for SIZE, BM, momentum, and short-term reversal simultaneously. Our new evidence suggests that there is a marginal IVOL effect in the French stock market adding to the increasing number of studies questioning the ubiquity of the negative IVOL puzzle.Originality/value: First, we present the first empirical evidence on examining the trends of both aggregate idiosyncratic and market volatilities, and the pricing role of IVOL in French stock market. We draw an attention for both academia and practitioners on an individual developed stock market. Second, we add new evidence to the mounting results questioning the ubiquity of the IVOL effect. This highlights the importance of country verification of so called anomalies in the US, even in developed markets. Finally, we confirm earlier evidence both aggregate idiosyncratic and market volatilities in the French stock market exhibits regime switching behavior rather than showing a long-term time trends.
Author: Gilbert Nartea
Publisher:
ISBN:
Category :
Languages : en
Pages : 44
Get Book Here
Book Description
We investigate the time series behavior of idiosyncratic volatility and its role in asset pricing in China. We find no evidence of a long-term trend in the time series behavior of idiosyncratic volatility. Idiosyncratic volatility in China is best characterized by an autoregressive process with regime shifts that coincide with structural market reforms. We also document evidence of a negative idiosyncratic volatility effect in China with anecdotal evidence suggesting that it could be driven by investor preference for high idiosyncratic volatility stocks.
Author: Eric C. Chang
Publisher:
ISBN:
Category :
Languages : en
Pages : 29
Get Book Here
Book Description
We offer evidence at both portfolio level and firm level that variations in idiosyncratic volatility are related to both behavioral and fundamental factors. Using Japanese data from 1975 to 2003, we show that both institutional herding and firm earnings are positively related to idiosyncratic volatility. We reject the hypothesis that institutional investors herd toward stocks with high idiosyncratic volatility and systematic risk. Our results suggest that a behavior story may explain the negative premium earned by high volatility stocks found by Ang et al. (2004). In addition to cross sectional results, we present preliminary results on the co-movement of dispersions of change in institutional ownership and return-on-asset with the market aggregate idiosyncratic volatility in the Japanese market. Our results, when related to evidence from the US market, suggest that investor behavior and stock fundamentals may both help explain the time-series pattern of market aggregate idiosyncratic volatility.
Author: Turan G. Bali
Publisher: John Wiley & Sons
ISBN: 1118589475
Category : Business & Economics
Languages : en
Pages : 512
Get Book Here
Book Description
“Bali, Engle, and Murray have produced a highly accessible introduction to the techniques and evidence of modern empirical asset pricing. This book should be read and absorbed by every serious student of the field, academic and professional.” Eugene Fama, Robert R. McCormick Distinguished Service Professor of Finance, University of Chicago and 2013 Nobel Laureate in Economic Sciences “The empirical analysis of the cross-section of stock returns is a monumental achievement of half a century of finance research. Both the established facts and the methods used to discover them have subtle complexities that can mislead casual observers and novice researchers. Bali, Engle, and Murray’s clear and careful guide to these issues provides a firm foundation for future discoveries.” John Campbell, Morton L. and Carole S. Olshan Professor of Economics, Harvard University “Bali, Engle, and Murray provide clear and accessible descriptions of many of the most important empirical techniques and results in asset pricing.” Kenneth R. French, Roth Family Distinguished Professor of Finance, Tuck School of Business, Dartmouth College “This exciting new book presents a thorough review of what we know about the cross-section of stock returns. Given its comprehensive nature, systematic approach, and easy-to-understand language, the book is a valuable resource for any introductory PhD class in empirical asset pricing.” Lubos Pastor, Charles P. McQuaid Professor of Finance, University of Chicago Empirical Asset Pricing: The Cross Section of Stock Returns is a comprehensive overview of the most important findings of empirical asset pricing research. The book begins with thorough expositions of the most prevalent econometric techniques with in-depth discussions of the implementation and interpretation of results illustrated through detailed examples. The second half of the book applies these techniques to demonstrate the most salient patterns observed in stock returns. The phenomena documented form the basis for a range of investment strategies as well as the foundations of contemporary empirical asset pricing research. Empirical Asset Pricing: The Cross Section of Stock Returns also includes: Discussions on the driving forces behind the patterns observed in the stock market An extensive set of results that serve as a reference for practitioners and academics alike Numerous references to both contemporary and foundational research articles Empirical Asset Pricing: The Cross Section of Stock Returns is an ideal textbook for graduate-level courses in asset pricing and portfolio management. The book is also an indispensable reference for researchers and practitioners in finance and economics. Turan G. Bali, PhD, is the Robert Parker Chair Professor of Finance in the McDonough School of Business at Georgetown University. The recipient of the 2014 Jack Treynor prize, he is the coauthor of Mathematical Methods for Finance: Tools for Asset and Risk Management, also published by Wiley. Robert F. Engle, PhD, is the Michael Armellino Professor of Finance in the Stern School of Business at New York University. He is the 2003 Nobel Laureate in Economic Sciences, Director of the New York University Stern Volatility Institute, and co-founding President of the Society for Financial Econometrics. Scott Murray, PhD, is an Assistant Professor in the Department of Finance in the J. Mack Robinson College of Business at Georgia State University. He is the recipient of the 2014 Jack Treynor prize.
Author: Kenneth S. Rogoff
Publisher: MIT Press
ISBN: 0262072726
Category : Business & Economics
Languages : en
Pages : 479
Get Book Here
Book Description
The 20th NBER Macroeconomics Annual, covering questions at the cutting edge of macroeconomics that are central to current policy debates.
Author: Fatma Sonmez Saryal
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
In this thesis, I study three aspects of idiosyncratic volatility. First, I examine the relation between idiosyncratic volatility and future stock returns. Next, I examine the share price effect and its interaction with the idiosyncratic volatility on stock returns. Finally, I examine the time series pattern of monthly aggregate monthly idiosyncratic volatility. In the first chapter, I examine the relation between idiosyncratic volatility and future stock returns. In their paper, Ang, Hodrick, Xing, and Zhang [AHXZ (2006)] show that idiosyncratic volatility is inversely related to future stock returns: low idiosyncratic volatility stocks earn higher returns than do high idiosyncratic volatility stocks. The main contribution of this paper is to provide evidence that it is the month to month changes in idiosyncratic volatility that produce AHXZ's results. More specifically, a portfolio of stocks that move from Quintile 1 (low idiosyncratic volatility) to Quintile 5 (high idiosyncratic volatility) earns an average risk-adjusted return of 5.64% per month in the month of the change. Whereas, a portfolio of stocks that move from the highest to the lowest idiosyncratic volatility quintiles earns -0.94% per month in the month of the change. Eliminating all firm-month observations with idiosyncratic volatility quintile changes, I find the opposite results to AHXZ: it is persistently low idiosyncratic volatility stocks that earn lower returns than do persistently high idiosyncratic volatility stocks. I find that many of the extreme changes in idiosyncratic volatility are related to business events. In general, the pattern usually observed is that an announcement or an event increases uncertainty about a stock and hence, its idiosyncratic volatility increases. After the event, uncertainty is resolved and the stock returns to a lower idiosyncratic volatility quintile. In the second chapter, I examine how the level of the share price interacts with idiosyncratic volatility to affect future stock returns. Ignoring transaction costs, a trading strategy that is long high-priced and short low-priced stocks earns positive abnormal returns with respect to the Fama-French (1992) three factor model. However, the observed positive abnormal returns are less significant if momentum is taken into account via the Carhart (1997) four factor model. Also the relation between idiosyncratic volatility and future stock returns differs for price sorted portfolios: it is negative for low and mid-priced stocks but positive for high-priced ones. These results are robust for low and-mid-priced stocks even after momentum is included. However, the positive relation for high-priced stocks disappears due to relatively large loadings on momentum for high idiosyncratic volatility stocks. I also show that skewness and momentum are significant determinants of idiosyncratic volatility for low-priced stocks and high-priced stocks respectively. One implication is that the importance of idiosyncratic volatility for future stock returns may in part be due its role as a disguised risk factor: either for momentum for high-priced stocks and skewness for low and mid-priced stocks. In the third chapter, I investigate the time series pattern of aggregate monthly idiosyncratic volatility. It has been shown that new riskier listings in the US stock markets are a reason for the increase in idiosyncratic volatility during the period 1963-2004. First, I show that this is more pronounced for Nasdaq new listings. Second, I show that for Nasdaq, prior to 1994 low-priced new listings became riskier, whereas during the internet bubble period it is the higher-priced listings that became riskier. Third, I show that institutional holdings have increased over time and have had a different impact on each new listing group: a negative for pre-1994 listings and a positive impact for post-1994 listings. Hence, I conclude that the observed time-series pattern of idiosyncratic volatility is a result of the changing nature of Nasdaq's investor clientele.
Author: Daniel B. Nelson
Publisher:
ISBN:
Category :
Languages : en
Pages : 174
Get Book Here
Book Description
Author: Daniel Barlow Nelson
Publisher:
ISBN:
Category :
Languages : en
Pages : 174
Get Book Here
Book Description
Author: François M. Longin
Publisher:
ISBN:
Category : International finance
Languages : en
Pages : 44
Get Book Here
Book Description
