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Considering the role of analysts in disseminating information, the paper explains the idiosyncratic volatility puzzle of China's stock market. As the largest developing country, China's research can provide meaningful reference for the research of financial markets in other new countries.

From the perspective of behavior, establishing a direct link between individual investor attention and stock price overvaluation.

The authors find that there is a significant idiosyncratic volatility puzzle in China's stock market. Due to the role of mispricing, individual investor attention significantly enhances the idiosyncratic volatility effect, that is, as individual investor attention increases, the greater the idiosyncratic volatility, the lower the expected return. Attention can explain the idiosyncratic volatility puzzle in China's stock market. In addition, due to the role of information production and dissemination, securities analysts can reduce the degree of market information asymmetry and enhance the transparency of market information.

China is the second largest economy in the world, and few scholars analyze it from the perspective of investors' attention. The authors believe this paper has the potential in contributing to the academia.

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.

This paper aims to propose an alternative method to measure idiosyncratic volatility and test whether the idiosyncratic volatility puzzle holds in commodity futures markets.

This paper proposes a partially new measure of idiosyncratic volatility in commodity futures markets based on the Schwartz and Smith (2000) short-term/long-term model. This model enables us to capture systematic risks of commodity futures markets in a parsimonious way.

Using a sample of futures contracts for 20 commodities from 1973 to 2022, this paper demonstrates that idiosyncratic volatility is more significant than systematic volatility in commodity futures markets, and that the idiosyncratic volatility puzzle does not hold in these markets. This paper also performs robustness tests to investigate whether the puzzle holds during subsample periods when commodity markets are more volatile and find consistent results. This study highlights the differences between commodity futures markets and equity markets and emphasizes the importance of investigating idiosyncratic volatility in commodity futures markets.

The contributions of this paper are threefold. First, this paper contributes to the literature by focusing on the idiosyncratic volatility of commodity futures returns. Second, this paper constructs a partially new measure of idiosyncratic volatility in commodity futures markets. Finally, this paper also contributes to the literature on the idiosyncratic volatility puzzle and demonstrates that the puzzle may not exist in commodity futures markets.

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”.

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.

Prior studies use two measures of firm-specific return variation (FSRV): idiosyncratic volatility in absolute and relative terms, the latter of which is also termed stock price nonsynchronicity. Whereas most research focuses on investigating the idiosyncratic volatility puzzle, the authors carry out comparison of these two measures and further investigate which of the two constituents of nonsynchronicity explain the association between FSRV and stock returns, emphasising the importance of assessing which component drives stock returns.

The authors use the US individual stock returns from 1925 to 2016 and define the two measures of FRSV based on the Fama and French (1993) model. Specifically, the authors decompose the relative measure into two components: (i) absolute idiosyncratic volatility and (ii) systematic volatility. The authors conduct various tests based on high-minus-low, zero-investment quintile portfolio sorts and perform the Fama–MacBeth analysis by singling out each component.

The authors find a positive return on the portfolio sorted on relative idiosyncratic volatility or on systematic volatility, but find a negative return sorted on absolute idiosyncratic volatility. The results are robust after controlling for size, BM and other risk characteristics using a double-sorting approach. The Fama–MacBeth regression results show that a positive association between the relative measure and stock returns is driven primarily by the low-systematic-volatility anomaly across firms. The findings are robust to controlling for return residual momentum, skewness, jumps and information discreteness.

Extant research posits the idiosyncratic volatility puzzle and the low-volatility anomaly. The authors emphasize the importance of integrating these two streams of research. This study enhances the understanding of the driving force underlying the relationship between FSRV and cross-sectional stock returns.

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.

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.

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.

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.

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.

Ethically sensitive and faithful investors with small investment can benefit from the findings of this paper.

The work reported in this paper is original, unpublished and is also not under consideration for publication elsewhere.

This study aims to examine what underlies the estimated relation between idiosyncratic volatility and realized return.

Idiosyncratic volatility has a dual effect on stock pricing: it not only affects investors' expected return but also affects the efficiency of stock price in reflecting its value. Therefore, the estimated relation between idiosyncratic volatility and realized return captures its relations with both expected return and the mispricing-related component due to its dual effect on stock pricing. The sign of its relation with the mispricing-related component is indeterminate.

The estimated relation between idiosyncratic volatility and realized return decreases and switches from positive to negative as the estimation sample consists of proportionately more ex ante overvalued observations; it increases and switches from negative to positive as the estimation sample consists of proportionately more ex post overvalued observations. In sum, the relation of idiosyncratic volatility with the mispricing-related component dominates its relation with expected return in its estimated relation with realized return. Moreover, its estimated relation with realized return varies with research design choices and even switches sign due to their effects on its relation with the mispricing-related component.

The novelty of the study is evident in the implication of its findings that one cannot infer the sign of the relation of idiosyncratic volatility with expected return from its estimated relation with realized return.

The purpose of this paper is to use some of the contributions of the option pricing theory to solve three outstanding puzzles in finance: the underdiversification puzzle, the volatility puzzle and the equity premium puzzle.

To approach the issue, this paper considers the applications of the option pricing theory to both sides of the corporate balance sheet. Applications to the left-hand side of the balance sheet has led to the real options theory that has expressed the value of a capital budgeting project as the sum of the values of its “discounted cash flow (DCF) method” and “real options.” This paper argues that, because the balance sheet must balance, the value of equity, which appears on the right-hand side of the balance sheet, should also be expressed as the sum of the values of its “DCF method” and “equity options.”

This proposed model of equity valuation solves the three outstanding puzzles in finance: the underdiversification puzzle, the volatility puzzle and the equity premium puzzle.

This study may not be able to explain the full extent of the three puzzles.

The dividend discount model of equity valuation needs to be augmented by an option component.

The community of finance scholars will become more confident of their scholarly work because three puzzles will be solved to a great extent.

To the best of author’s knowledge, the extant literature does not either solve any single one of the three puzzles through the contributions of option pricing theory or solve all three puzzles at the same time with a single solution. The originality of this paper is that it makes both of these contributions to the extant literature.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.