The Common Component of Idiosyncratic Volatility

Duarte, Jefferson; Kamara, Avraham; Siegel, Stephan; Sun, Celine

doi:10.2139/ssrn.1787006

Cited by 5 publications

(11 citation statements)

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“…This implies that there is a common factor to idiosyncratic volatility across firms that is driven by realizations of the aggregate risk factor. This result is consistent with empirical evidence of a factor structure in the cross-section of idiosyncratic volatility that is correlated with the business cycle (e.g., Campbell, Lettau, Malkiel, and Xu 2001;Duarte, Kamara, Siegel, and Sun 2011).…”

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confidence: 89%

Factor-Loading Uncertainty and Expected Returns

Banerjee

Corona

2012

SSRN Journal

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Firm-specific information can affect expected returns if it affects investor uncertainty about risk-factor loadings. We show that a stock's expected return is decreasing in factor-loading uncertainty, controlling for the average level of its factor loading. When loadings are persistent, learning by investors can induce time-series variation in price-dividend ratios, expected returns, and idiosyncratic volatility, even when the aggregate riskpremium is constant and fundamental shocks are homoscedastic. Consistent with our predictions, we estimate that average annual returns of a firm with the median level of factor-loading uncertainty are 400 to 525 basis points lower than a comparable firm without factor-loading uncertainty. Firm-specific information can affect expected returns if it affects investor uncertainty about risk-factor loadings. We show that a stock's expected return is decreasing in factorloading uncertainty, controlling for the average level of its factor loading. When loadings are persistent, learning by investors can induce time-series variation in price-dividend ratios, expected returns, and idiosyncratic volatility, even when the aggregate risk-premium is constant and fundamental shocks are homoscedastic. Consistent with our predictions, we estimate that average annual returns of a firm with the median level of factor-loading uncertainty are 400 to 525 basis points lower than a comparable firm without factorloading uncertainty. (JEL: G12, G14)

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confidence: 89%

Factor-Loading Uncertainty and Expected Returns

Banerjee

Corona

2012

SSRN Journal

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“…where r i,t is the excess stock return for stock i at time t, βs reflect exposures to a set of systematic factors f that are orthogonal to each other and to the idiosyncratic return ε, and α denotes an intercept. Several studies identify a common volatility feature in the idiosyncratic component of stock returns ε (e.g., Campbell et al (2001), Connor, Korajczyk, andLinton (2006), Duarte, Kamara, Siegel, andSun (2014), andHerskovic et al (2016)). Related work (e.g., Engle and Marcucci (2006)) identifies common components in the total volatility of firm returns, a large fraction of which is idiosyncratic.…”

Section: Introductionmentioning

confidence: 99%

One Vol to Rule Them All: Common Volatility Dynamics in Factor Returns

Kapadia¹,

Linn²,

Paye³

2023

J. Financ. Quant. Anal.

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We show that a common component governs volatility dynamics across a wide range of traded equity factors. This “common factor volatility” (CFV) exists even among orthogonal factors. CFV occurs in both cash-flow and discount-rate components of factor returns and derives from market responses to fundamental news rather than underlying commonality in news volatility. Incorporating CFV improves factor volatility forecasts relative to models that include only own-factor volatility. CFV allows us to characterize stochastic discount factor (SDF) volatility dynamics in a very general sense and we show that many popular models imply SDFs with time-varying volatility that correlates strongly with CFV.

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“…On the risk‐based side, Chen and Petkova (2012) propose average stock variance as the missing risk factor that leads to the IVOL puzzle. Duarte et al (2014) use principal component analysis to identify the common component of IVOL and find that it has significant explanatory power for the cross‐section of returns. Herskovic et al (2016) argue IVOL proxies for household income risk.…”

Section: Introductionmentioning

confidence: 99%

Does idiosyncratic volatility proxy for a missing risk factor? Evidence using portfolios as test assets

Gempesaw

2021

Euro Fin Management

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We use various samples of portfolios (Fama-French portfolios formed on size and book-to-market, Fama-French industry portfolios, and exchange traded funds) as test assets to investigate whether the negative relation between lagged idiosyncratic volatility (IVOL) and future average returns initially documented by Ang, Hodrick, Xing, and Zhang ( 2006) is due to a missing risk factor. Analytically, we show that if IVOL proxies for a missing risk factor, then the negative relation between IVOL and returns persists at a portfolio level since systematic risk is not eliminated through diversification. However, when we take it to the data, we do not find economically and statistically significant evidence of a relation between lagged IVOL and subsequent average returns. Taken together, our results suggest that the IVOL puzzle is not due to a missing risk factor.

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The Common Component of Idiosyncratic Volatility

Cited by 5 publications

References 0 publications

Factor-Loading Uncertainty and Expected Returns

Factor-Loading Uncertainty and Expected Returns

One Vol to Rule Them All: Common Volatility Dynamics in Factor Returns

Does idiosyncratic volatility proxy for a missing risk factor? Evidence using portfolios as test assets

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