Idiosyncratic Volatility and Skewness: Time-Series Relations and the Cross-Section of Expected Returns

2007 ◽  
Author(s):  
Brian Boyer ◽  
Todd Mitton ◽  
Keith Vorkink
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Idiosyncratic Volatility ◽  
Expected Returns ◽  
The Cross

The Determinants of Idiosyncratic Volatility

2017 ◽  
Vol 25 (4) ◽  
pp. 509-545
Author(s):  
Jaeuk Khil ◽  
Song Hee Kim ◽  
Eun Jung Lee
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Cross Section ◽  
Growth Rates ◽  
Idiosyncratic Volatility ◽  
Return Volatility ◽  
Firm Level ◽  
Cross Sectional ◽  
Asset Growth ◽  
The Cross

We investigate the cross-sectional and time-series determinants of idiosyncratic volatility in the Korean market. In particular, we focus on the empirical relation between firms’ asset growth rate and idiosyncratic stock return volatility. We find that, in the cross-section, companies with high idiosyncratic volatility tend to be small and highly leveraged, have high variance of ROE and Market to Book ratio, high turnover rate, and pay no dividends. Furthermore, firms with extreme (either high positive or negative) asset growth rates have high idiosyncratic return volatility than firms with moderate growth rates, suggesting the V-shaped relation between asset growth rate and idiosyncratic return volatility. We find that the V-shaped relation is robust even after controlling for other factors. In time-series, we find that firm-level idiosyncratic volatility is positively related to the dispersion of the cross-sectional asset growth rates. As a result, this study is contributed to show that the asset growth is the most important predictor of firm-level idiosyncratic return volatility in both the cross-section and the time-series in the Korean stock market. In addition, we show how the effect of risk factors varies with industries.

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 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>

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