Earnings Announcement Idiosyncratic Volatility and the Cross-Section of Stock Returns

2015 ◽  
Author(s):  
Cameron Truong
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Idiosyncratic Volatility ◽  
Earnings Announcement ◽  
The Cross

Idiosyncratic Volatility and the Cross Section of Expected Returns

2008 ◽  
Vol 43 (1) ◽  
pp. 29-58 ◽  
Author(s):  
Turan G. Bali ◽  
Nusret Cakici
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Idiosyncratic Volatility ◽  
Expected Returns ◽  
Cross Sectional ◽  
Monthly Data ◽  
Portfolio Returns ◽  
Expected Stock Returns ◽  
The Cross ◽  
Data Frequency

AbstractThis paper examines the cross-sectional relation between idiosyncratic volatility and expected stock returns. The results indicate that i) the data frequency used to estimate idiosyncratic volatility, ii) the weighting scheme used to compute average portfolio returns, iii) the breakpoints utilized to sort stocks into quintile portfolios, and iv) using a screen for size, price, and liquidity play critical roles in determining the existence and significance of a relation between idiosyncratic risk and the cross section of expected returns. Portfoliolevel analyses based on two different measures of idiosyncratic volatility (estimated using daily and monthly data), three weighting schemes (value-weighted, equal-weighted, inverse volatility-weighted), three breakpoints (CRSP, NYSE, equal market share), and two different samples (NYSE/AMEX/NASDAQ and NYSE) indicate that no robustly significant relation exists between idiosyncratic volatility and expected returns.

scholarly journals A Model-Free Measure of Aggregate Idiosyncratic Volatility and the Prediction of Market Returns

2014 ◽  
Vol 49 (5-6) ◽  
pp. 1133-1165 ◽  
Author(s):  
René Garcia ◽  
Daniel Mantilla-García ◽  
Lionel Martellini
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Strong Predictor ◽  
Idiosyncratic Volatility ◽  
Cross Sectional ◽  
Volatility Risk ◽  
Model Free ◽  
Asymptotically Efficient Estimator ◽  
The Cross ◽  
Asymptotically Efficient

AbstractIn this paper, we formally show that the cross-sectional variance of stock returns is a consistent and asymptotically efficient estimator for aggregate idiosyncratic volatility. This measure has two key advantages: It is model free and observable at any frequency. Previous approaches have used monthly model-based measures constructed from time series of daily returns. The newly proposed cross-sectional volatility measure is a strong predictor for future returns on the aggregate stock market at the daily frequency. Using the cross section of size and book-to-market portfolios, we show that the portfolios’ exposures to the aggregate idiosyncratic volatility risk predict the cross section of expected returns.

scholarly journals Idiosyncratic Volatility and Cross-section of Stock Returns: Evidences from India

2016 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Prashant Sharma ◽  
Brajesh Kumar
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Empirical Relationship ◽  
Idiosyncratic Volatility ◽  
Expected Returns ◽  
Cross Sectional ◽  
The Cross ◽  
Highly Correlated ◽  
Indian Stock Market ◽  
The Relationship

<p>The present study examines the cross-sectional pricing ability of idiosyncratic volatility (IV) in Indian stock market and investigates the relationship amongst expected idiosyncratic volatility (EI), unexpected idiosyncratic volatility (UI), and cross-section of stocks returns. The study uses ARIMA (2, 0, 1) model to IV into EI and UI. The stocks returns are regressed on IV, EI and UI using Newey-West (1987) corrections, in order to investigate their empirical relationship.  The study finds that IV is positively related with stock returns. Further the IV significantly explains the cross-section of stock returns in Indian context. After imposing control over UI, as it is highly correlated with unexpected returns, the inter-temporal relationship between EI and expected returns turns out to be positive.</p>

Expectations Management and Stock Returns

2019 ◽  
Vol 33 (10) ◽  
pp. 4580-4626 ◽  
Author(s):  
Travis L Johnson ◽  
Jinhwan Kim ◽  
Eric C So
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Earnings Announcements ◽  
Performance Expectations ◽  
Earnings Announcement ◽  
Expectations Management ◽  
The Cross ◽  
Earnings Targets

Abstract We establish a link between firms managing investors’ performance expectations, earnings announcement premiums, and cyclical patterns (i.e., seasonalities) in returns. Firms that are more likely to manage expectations toward beatable levels predictably earn lower returns before, and higher returns during, their earnings announcements. This pattern repeats across firms’ fiscal quarters, suggesting firms manufacture positive “surprises” by negatively biasing investors’ expectations ahead of announcing earnings. We corroborate these findings using non-price-based outcomes indicative of expectations management. Together, our findings are consistent with the pressure for firms to meet earnings targets shaping the cross-section of firms’ stock returns.

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