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This paper aims to examine whether idiosyncratic volatility and other asset pricing factors predict growth rates of the ten Australian economic indicators.

The authors use the Liew and Vassalou (2000) model augmented with an idiosyncratic volatility factor to investigate the issue.

Using regression analysis, the authors find that the asset pricing factors can be used to predict the growth rates for eight out of the ten economic indicators. Moreover, using portfolio performance analysis, the authors find that high returns of size factor and a book-to-market factor portfolios precede periods of good macroeconomic states, whereas high returns of HIMLI portfolios precede periods of bad macroeconomic states.

To the authors’ knowledge, the relationship between idiosyncratic volatility and Australian economic growth has not been investigated explicitly in the literature.

This paper aims to investigate whether idiosyncratic volatility is priced in returns of equity funds while controlling for fund size and return momentum.

Following Fama and French (1993), an idiosyncratic volatility mimicking factor and a fund-size factor are constructed. The pricing ability of this idiosyncratic volatility mimicking factor is investigated in the context of Carhart (1997).

Idiosyncratic volatility is an important pricing factor even when controlling for fund size and momentum. In addition, idiosyncratic volatility is strongly and positively associated with the momentum effect. Further, when controlling for the association between the momentum effect and idiosyncratic volatility, the explanatory power of the momentum factor almost disappears, which suggests the pricing of idiosyncratic volatility mediates momentum and returns.

These findings imply that both the idiosyncratic volatility factor and the fund-size factor should not be ignored by fund managers when evaluating the performance of the equity funds.

The authors aim to understand the driving forces behind the idiosyncratic volatility puzzle in the Korean stock market. The authors study the Korean stock market because previous works report a strong idiosyncratic volatility puzzle in Korea, and the market for the exchange-traded funds (ETFs) including low volatility ETFs has experienced drastic growth in Korea.

Using common stocks listed either on KOSPI or KOSDAQ over the period 1997–2016, the authors estimate idiosyncratic volatility using the Fama–French three-factor model. In addition, based on prior literature, the authors use turnover as a proxy for overvaluation. The authors then study the role of turnover in understanding the idiosyncratic volatility puzzle in Korea.

The authors find that turnover is highly associated with idiosyncratic volatility. Turnover is extremely large among firms with high idiosyncratic volatility and the puzzle disappears after we control for turnover, meaning that turnover subsumes the explanatory power of idiosyncratic volatility for equity returns. The authors also find underperformance of stocks with high turnover and high idiosyncratic volatility exclusively during earnings announcement periods. Overall, our finding implies that the puzzle arises since high idiosyncratic volatility stocks due to high turnover are overvalued and experience correction afterwards.

Literature has suggested explanations based on lottery preferences of investors and market frictions behind the idiosyncratic volatility puzzle. What makes our study distinct from previous work is that we find the role of turnover in understanding the idiosyncratic volatility puzzle using turnover measure as a proxy for overvaluation in the Korean stock market.

The purpose of this paper is to investigate the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and recent financial crisis.

Using a broad sample of stock options traded on the American Stock Exchange and the Chicago Board Options Exchange from January 2001 to December 2010, the effect of different idiosyncratic volatility forecasting measures are examined on future stock returns in four different periods (Bear and Bull markets).

First, the authors find clear and robust empirical evidence that the implied idiosyncratic volatility is the best stock return predictor for every sub-period both in Bear and Bull markets. Second, the cross-section firm-specific characteristics are important when it comes to stock returns forecasts, as the latter have mixed positive and negative effects on Bear and Bull markets. Third, the authors provide evidence that short selling constraints impact negatively on stock returns for only a Bull market and that liquidity is meaningless for both Bear and Bull markets after the recent financial crisis.

These results would be helpful to disclose more information on the best idiosyncratic volatility measure to be implemented in global financial crises.

This study empirically analyses the effect of different idiosyncratic volatility measures for a period that involves both the dotcom bubble and the recent financial crisis in four different periods (Bear and Bull markets) and contributes the existing literature on volatility measures, volatility risk and stock return predictability in global financial crises.

In this article we compare the performance of the traditional CAPM with the multi factor model of Fama and French (1996) for equities listed in the Shanghai Stock Exchange. We also investigate the explanatory power of idiosyncratic volatility and respond to the claim that multi factor model findings can be explained by the turn of the year effect. Our results show that firm size, book to market equity and idiosyncratic volatility are priced risk factors in addition to the theoretically well specified market factor. As far as the turn of the year effect is concerned we reject the claim that the findings are driven by seasonal factors.

This study is the first to examine the role of idiosyncratic risk in the pricing of European real estate equities. The capital asset pricing model predicts that in equilibrium, investors should hold the market portfolio. As a result, investors should only be rewarded for carrying undiversifiable systematic risk and not for diversifiable idiosyncratic risk. The study is adding to the growing body of countering studies by first examining time trends of idiosyncratic risk and subsequently the pricing of idiosyncratic risk in European real estate equities. The paper aims to discuss these issues.

The study analyses 293 real estate equities from 16 European capital markets over the 1991-2011 period. The framework of Fama and MacBeth is employed. Regressions of the cross-section of expected equity excess returns on idiosyncratic risk and other firm characteristics such as beta, size, book-to-market equity (BE/ME), momentum, liquidity and co-skewness are performed. Due to recent evidence on the conditional pricing of European real estate equities, the pricing is also investigated using the conditional framework of Pettengill et al. Either realised or expected idiosyncratic volatility forecasted using a set of exponential generalized autoregressive conditional heteroskedasticity models are employed.

The initial analysis of time trends in idiosyncratic risk reveals that while the early 1990s are characterised by both high total and idiosyncratic volatility, a strong downward trend emerged in 1992 which was only interrupted by the burst of the dotcom bubble and the 9/11 attacks along with the global financial and economic crisis. The largest part of total volatility is idiosyncratic and therefore firm-specific in nature. Simple cross-correlations indicate that high beta, small size, high BE/ME, low momentum, low liquidity and high co-skewness equities have higher idiosyncratic risk. While size and BE/ME are priced unconditionally from 1991 to 2011, both measures of idiosyncratic risk fail to achieve significance at reasonable levels. However, once conditioned on the general equity market or real estate equity market, a strong positive relationship between idiosyncratic risk and expected returns emerges in up-markets, while the opposite relationship exists in down-markets. The relationship is robust to firm-specific factors and a series of robustness checks.

The results show that ignoring the conditional relationship between idiosyncratic risk and returns might result in the false realisation that idiosyncratic risk does not matter in the pricing of risky (real estate) assets.

This study is the first to examine the role of idiosyncratic risk in the pricing of European real estate equities. The study reveals differences in the pricing of European real estate equities and US REITs. The study highlights that ignoring the conditional relationship between idiosyncratic risk and returns might result in the false realisation that idiosyncratic risk does not matter in the pricing of risky assets.

This paper analyzes the roles of idiosyncratic risk and firm-level conditional skewness in determining cross-sectional returns. It is shown that the traditional EGARCH estimates of conditional idiosyncratic volatility may bring significant finite sample estimation bias in the presence of non-Gaussianity. We propose a new estimator that has more robust sampling performance than the EGARCH MLE in the presence of heavy-tail or skewed innovations. Our cross-sectional portfolio analysis demonstrates that the idiosyncratic volatility puzzle documented by Ang, Hodrick, Xiang, and Zhang (2006) exists intertemporally. We conduct further analysis to solve the puzzle. We show that two factors idiosyncratic variance and individual conditional skewness play important roles in determining cross-sectional returns. A new concept, the “expected windfall,” is introduced as an alternate measure of conditional return skewness. After controlling for these two additional factors, we solve the major piece of this puzzle: Our cross-sectional regression tests identify a positive relationship between conditional idiosyncratic volatility and expected returns for over 99% of the total market capitalization of the NYSE, NASDAQ, and AMEX stock exchanges.

The purpose of our study is to explore the “idiosyncratic volatility puzzle” in Chinese stock market from the perspective of investors' heterogeneous beliefs. To delve into the relationship between idiosyncratic volatility and investors' heterogeneous beliefs, and uncover the ability of heterogeneous beliefs, as well as to explain the “idiosyncratic volatility puzzle”, we construct our study as follows.

Our study adopts the unexpected trading volume as proxies of heterogeneity, the residual of Fama–French three-factor model as proxies of idiosyncratic volatility. Portfolio strategies and Fama–MacBeth regression are used to investigate the relationship between the two proxies and stock returns in Chinese A-share market.

Investors' heterogeneous beliefs, as an intermediary variable, are positively correlated with idiosyncratic volatility. Meanwhile, it could better demonstrate the negative correlation between the idiosyncratic volatility and future stock returns. It is one of the economic mechanisms linking idiosyncratic volatility to subsequent stock returns, which can account for 11.28% of the puzzle.

The findings indicate that idiosyncratic volatility is significantly and positively correlated with heterogeneous beliefs and that heterogeneous beliefs are effective intervening variables to explain the “idiosyncratic volatility puzzle”.

The purpose of this paper is to add an important new dimension to the earnings management literature by establishing a link between idiosyncratic risk and the degree of accrual management.

Based on a comprehensive sample of 44,599 firm-year observations during the period spanning 1987-2009, the study offers robust empirical evidence of the importance of firm-specific idiosyncratic volatility as a determinant of earnings manipulation. The authors use standard measures of earnings management and idiosyncratic volatility. The authors test the hypotheses with robust econometrics techniques.

The authors document a strong positive relationship between idiosyncratic risk and accruals management. Further, the authors find a positive association between residual volatility and discretionary accruals whether accruals are income inflationary or income deflationary. The findings are robust to alternate idiosyncratic risk proxies and variables associated with earnings management.

Overall, the knowledge derived from this study provides additional tools to assess the degree of earnings management by firms, and hence the quality of the financial reporting. Thus the findings will enable standard setters, financial market regulators, analysts, and investors to make more informed legislative, regulatory, resource allocation, and investment decisions.

The purpose of this paper is to contribute to the existing stock return predictability and idiosyncratic risk literature by examining the relationship between stock returns and components derived from the decomposition of stock returns variance at the portfolio and firm levels.

A theoretical model is used to decompose the variance of stock returns into two volatility and two covariance terms by using a conditional Fama-French three-factor model. This study adopts portfolio analysis and Fama-MacBeth cross-sectional regression to examine the relationship between components of idiosyncratic risk and expected stock returns.

The portfolio analysis results show that volatility terms are negatively related to expected stock returns, and alpha risk has the most significant relationship with stock returns. On the contrary, covariance terms have positive relationships with expected stock returns at the portfolio level. Furthermore, the results of the 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.

This is the first study that examines the relations between all the components of idiosyncratic risk and expected stock returns in equal-weighted and value-weighted portfolios. This research also suggests covariance terms of idiosyncratic volatility as new predictors of stock returns at the portfolio level. Moreover, this paper contributes to the idiosyncratic risk literature by examining whether all the four additional components explain all the systematic patterns included in the unconditional idiosyncratic risk.