Stock Returns, Implied Volatility Innovations, and the Asymmetric Volatility Phenomenon

2006 ◽  
Vol 41 (2) ◽  
pp. 381-406 ◽  
Author(s):  
Patrick Dennis ◽  
Stewart Mayhew ◽  
Chris Stivers
Keyword(s):  
Stock Returns ◽  
Implied Volatility ◽  
Idiosyncratic Volatility ◽  
Firm Level ◽  
Stock Volatility ◽  
Present Evidence ◽  
Asymmetric Volatility ◽  
Dynamic Relation ◽  
Daily Stock Returns

AbstractWe study the dynamic relation between daily stock returns and daily innovations in optionderived implied volatilities. By simultaneously analyzing innovations in index- and firmlevel implied volatilities, we distinguish between innovations in systematic and idiosyncratic volatility in an effort to better understand the asymmetric volatility phenomenon. Our results indicate that the relation between stock returns and innovations in systematic volatility (idiosyncratic volatility) is substantially negative (near zero). These results suggest that asymmetric volatility is primarily attributed to systematic market-wide factors rather than aggregated firm-level effects. We also present evidence that supports our assumption that innovations in implied volatility are good proxies for innovations in expected stock volatility.

Bayesian Analysis of Stochastic Betas

2005 ◽  
Vol 40 (4) ◽  
pp. 747-778 ◽  
Author(s):  
Gergana Jostova ◽  
Alexander Philipov
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Idiosyncratic Volatility ◽  
Firm Level ◽  
Conditional Capm ◽  
Asset Pricing Anomalies ◽  
Proposed Model ◽  
Out Of Sample ◽  
Market Beta ◽  
Rolling Regression

AbstractWe propose a mean-reverting stochastic process for the market beta. In a simulation study, the proposed model generates significantly more precise beta estimates than GARCH betas, betas conditioned on aggregate or firm-level variables, and rolling regression betas, even when the true betas are generated based on these competing specifications. Our model significantly improves out-of-sample hedging effectiveness. In asset pricing tests, our model provides substantially stronger support for the conditional CAPM relative to competing beta models and helps resolve asset pricing anomalies such as the size, book-to-market, and idiosyncratic volatility effects in the cross section of stock returns.

scholarly journals The cross-section of expected stock returns and components of idiosyncratic volatility

2021 ◽  
Author(s):  
◽  
Seyed Reza Tabatabaei Poudeh
Keyword(s):  
Risk Factors ◽  
Stock Returns ◽  
Cross Section ◽  
Idiosyncratic Volatility ◽  
Firm Level ◽  
Cross Sectional ◽  
Expected Stock Returns ◽  
Book To Market Ratio ◽  
Alpha Risk ◽  
The Relationship

We examine the relationship between stock returns and components of idiosyncratic volatility—two volatility and two covariance terms— derived from the decomposition of stock returns variance. The portfolio analysis result shows that volatility terms are negatively related to expected stock returns. On the contrary, covariance terms have positive relationships with expected stock returns at the portfolio level. These relationships are robust to controlling for risk factors such as size, book-to-market ratio, momentum, volume, and turnover. Furthermore, the results of Fama-MacBeth cross-sectional regression show that only alpha risk can explain variations in stock returns at the firm level. Another finding is that when volatility and covariance terms are excluded from idiosyncratic volatility, the relation between idiosyncratic volatility and stock returns becomes weak at the portfolio level and disappears at the firm level.

Positive Tone in Management Reports and Volatility of Stock Returns

2021 ◽  
pp. 097215092110542
Author(s):  
Rodrigo Fernandes Malaquias ◽  
Dermeval Martins Borges Júnior
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Return Volatility ◽  
Stock Volatility ◽  
Financial Reports ◽  
Stock Return Volatility ◽  
Daily Stock Returns ◽  
Disclosure Tone ◽  
Textual Content ◽  
And Control

This article aims to analyse the effects of positive tone in management reports on stock return volatility. It is expected that this article contributes to the literature about disclosure by proposing an objective textual content analysis of management reports, focussing on optimistic words or expressions employed by firms and their effect on stock return volatility. The sample consisted of management reports and financial data from 576 different Brazilian firms’ stocks. Regarding volatility, our measure is based on daily stock returns from 1 April 2011 to 23 October 2020. The data related to positive tone and control variables were based on the fiscal years 2010–2019. Therefore, the database contains 3,945 stock-year observations. The study hypothesis was tested through a regression model with panel data. The main results suggest that companies with higher positive disclosure tone scores do not necessarily present lower stock return volatility in the subsequent period. The objective content of financial reports (for example, in relation to profitability) seems to be related to stock volatility; however, the tone of subjective expressions does not represent the main determinant of stock volatility.

Can Twitter Help Predict Firm-Level Earnings and Stock Returns?

2017 ◽  
Vol 93 (3) ◽  
pp. 25-57 ◽  
Author(s):  
Eli Bartov ◽  
Lucile Faurel ◽  
Partha S. Mohanram
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Future Prospects ◽  
Traditional Media ◽  
Stock Trading ◽  
Firm Level ◽  
Quarterly Earnings ◽  
Announcement Returns ◽  
Twitter Activity ◽  
Original Information

ABSTRACT Prior research has examined how companies exploit Twitter in communicating with investors, and whether Twitter activity predicts the stock market as a whole. We test whether opinions of individuals tweeted just prior to a firm's earnings announcement predict its earnings and announcement returns. Using a broad sample from 2009 to 2012, we find that the aggregate opinion from individual tweets successfully predicts a firm's forthcoming quarterly earnings and announcement returns. These results hold for tweets that convey original information, as well as tweets that disseminate existing information, and are stronger for tweets providing information directly related to firm fundamentals and stock trading. Importantly, our results hold even after controlling for concurrent information or opinion from traditional media sources, and are stronger for firms in weaker information environments. Our findings highlight the importance of considering the aggregate opinion from individual tweets when assessing a stock's future prospects and value.

scholarly journals Idiosyncratic volatility, option-based measures of informed trading, and investor attention

2021 ◽  
Author(s):  
Hannes Mohrschladt ◽  
Judith C. Schneider
Keyword(s):  
Stock Returns ◽  
Idiosyncratic Volatility ◽  
Investor Attention ◽  
Intuitive Idea ◽  
Joint Examination ◽  
Stock Market Investors ◽  
Private Investors ◽  
High Level ◽  
Do So ◽  
Option Market

AbstractWe establish a direct link between sophisticated investors in the option market, private stock market investors, and the idiosyncratic volatility (IVol) puzzle. To do so, we employ three option-based volatility spreads and attention data from Google Trends. In line with the IVol puzzle, the volatility spreads indicate that sophisticated investors indeed consider high-IVol stocks as being overvalued. Moreover, the option measures help to distinguish overpriced from fairly priced high-IVol stocks. Thus, these measures are able to predict the IVol puzzle’s magnitude in the cross-section of stock returns. Further, we link the origin of the IVol puzzle to the trading activity of irrational private investors as the return predictability only exists among stocks that receive a high level of private investor attention. Overall, our joint examination of option and stock markets sheds light on the behavior of different investor groups and their contribution to the IVol puzzle. Thereby, our analyses support the intuitive idea that noise trading leads to mispricing, which is identified by sophisticated investors and exploited in the option market.

Information risk, stock returns, and asset pricing: Evidence from China

2017 ◽  
Vol 30 (4) ◽  
pp. 379-394 ◽  
Author(s):  
Raheel Safdar ◽  
Chen Yan
Keyword(s):  
Stock Returns ◽  
Factor Model ◽  
Empirical Literature ◽  
Firm Level ◽  
Cross Sectional ◽  
Market Pricing ◽  
Content Type ◽  
Information Risk ◽  
Accruals Quality ◽  
Three Factor

Purpose This study aims to investigate information risk in relation to stock returns of a firm and whether information risk is priced in China. Design/methodology/approach The authors used accruals quality (AQ) as their measure of information risk and performed Fama-Macbeth regressions to investigate association of AQ with future realized stock returns. Moreover, two-stage cross-sectional regression analysis was performed, both at firm level and at portfolio level, to test if the AQ factor is priced in China in addition to existing factors in the Fama French three-factor model. Findings The authors found poor AQ being associated with higher future realized stock returns. Moreover, they found evidence of market pricing of AQ in addition to existing factors in the Fama French three-factor model. Further, subsample analysis revealed that investors value AQ more in non-state owned enterprises than in state owned enterprises. Research limitations/implications The study sample comprises A-shares only and the generalization of the findings is limited by the peculiar institutional and economic setup in China. Originality/value This study contributes to market-based accounting literature by providing further insight into how and if investors value information risk, and it seeks to fill gap in empirical literature by providing evidence from the Chinese capital market.

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