Expected stock returns, common idiosyncratic volatility, and average idiosyncratic correlation

AbstractA spurious positive relation between exponential generalized autoregressive conditional heteroskedasticity (EGARCH) estimates of expected monthtidiosyncratic volatility and monthtstock returns arises when the monthtreturn is included in estimation of model parameters. We illustrate via simulations that this look-ahead bias is problematic for empirically observed degrees of stock return skewness and typical monthly return time series lengths. Moreover, the empirical idiosyncratic risk-return relation becomes negligible when expected monthtidiosyncratic volatility is estimated using returns only up to montht− 1.

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Idiosyncratic Volatility and the Cross Section of Expected Returns

Journal of Financial and Quantitative Analysis ◽

10.1017/s002210900000274x ◽

2008 ◽

Vol 43 (1) ◽

pp. 29-58 ◽

Cited By ~ 339

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.

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Idiosyncratic Volatility, Stock Market Volatility, and Expected Stock Returns

Journal of Business and Economic Statistics ◽

10.1198/073500105000000180 ◽

2006 ◽

Vol 24 (1) ◽

pp. 43-56 ◽

Cited By ~ 78

Author(s):

Hui Guo ◽

Robert Savickas

Keyword(s):

Stock Market ◽

Stock Returns ◽

Market Volatility ◽

Idiosyncratic Volatility ◽

Stock Market Volatility ◽

Expected Stock Returns

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The Short-Run and Long-Run Components of Idiosyncratic Volatility and Stock Returns

Management Science ◽

10.1287/mnsc.2020.3884 ◽

2021 ◽

Author(s):

Yunting Liu

Keyword(s):

Risk Factors ◽

Stock Returns ◽

Systematic Risk ◽

Risk Exposure ◽

Idiosyncratic Volatility ◽

Growth Options ◽

Long Run ◽

Expected Stock Returns ◽

Short Run ◽

Systematic Risk Factors

To capture the dynamics of idiosyncratic volatility of stock returns over different horizons and investigate the relationship between idiosyncratic volatility and expected stock returns, this paper develops and estimates a parsimonious model of idiosyncratic volatility consisting of a short-run and a long-run component. The conditional short-run and long-run components are found to be positively and negatively related to expected stock returns, respectively. The positive relation between the short-run component and stock returns may be caused by investors requiring compensation for bearing idiosyncratic volatility risk when facing trading frictions and hold underdiversified portfolios. The negative relationship between the long-run component and stock returns may reflect the fact that stocks with high long-run idiosyncratic volatility are less exposed to systematic risk factors and, hence, earn lower returns. Moreover, the low-risk exposure of stocks characterized by high idiosyncratic volatility lends support to real-option-based mechanisms to explain this negative relation. In particular, the systematic risk of a firm with abundant growth options crucially depends upon the risk exposure of these options. The value of growth options could rise significantly because of convexity when the increase in idiosyncratic volatility occurs over long horizons. And growth options’ systematic risk could fall because the relative magnitude of their value in relation to systematic risk factors decreases. This paper was accepted by David Simchi-Levi, finance.

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On ethnicity of idiosyncratic risk and stock returns puzzle

Humanomics ◽

10.1108/h-06-2015-0043 ◽

2016 ◽

Vol 32 (1) ◽

pp. 48-68 ◽

Cited By ~ 3

Author(s):

Naseem Al Rahahleh ◽

Iman Adeinat ◽

Ishaq Bhatti

Keyword(s):

Stock Returns ◽

Financial Crises ◽

Factor Model ◽

Idiosyncratic Risk ◽

Idiosyncratic Volatility ◽

Content Type ◽

Country Level ◽

Expected Stock Returns ◽

The Relationship ◽

Three Factor

Purpose – The purpose of this paper is to understand the controversial issue of whether stock returns and idiosyncratic risks are related positively or negatively in case of Singaporean ethically poor screened stocks. Design/methodology/approach – To achieve the major objectives of this paper, it uses a multiple regression to explore the relationship between expected stock returns and idiosyncratic risk. The paper replicates the Lee and Faff’s (2009) three-factor capital asset-pricing model (CAPM) model in creating the six size/book-to-market portfolios from which it constructs the small minus big (SMB) and high minus low (HML) portfolios that capture the size and book-to-market equity factors, respectively. Findings – The basic finding of the paper is that there is a strong relation between idiosyncratic risk and the expected stock returns. In more details, we observe that the portfolio of stocks with the highest idiosyncratic volatility generates higher average returns (4.36 per cent) than the portfolio of stocks with the lowest idiosyncratic volatility (0.79 per cent) over the sample period. The paper observes that the stock’s idiosyncratic volatility is inversely correlated with the size of the underlying firm. Moreover, there is a pattern of relationships nearer the periods of financial crises: Asian and global financial crises. Research limitations/implications – This paper uses only a three-factor model on a single country. So it cannot be generalized to a multi-country level in the Association of Southeast Asian Nations (ASEAN) region, as the structure of each member country is different. Practical implications – This paper provides guidelines for policymakers and foreign investors in Singapore about the relationship. This research can also be extended to other ASEAN countries to understand this puzzle. Social implications – Ethically sensitive and faithful investors with small investment can benefit from the findings of this paper. Originality/value – The work reported in this paper is original, unpublished and is also not under consideration for publication elsewhere.

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