Idiosyncratic Volatility Research Articles

Expected idiosyncratic moment risk and the cross-section of REIT returns

ABSTRACT In this paper, we investigate whether expected idiosyncratic volatility (IV) and expected idiosyncratic skewness (IS) risk are both present and significant in the cross-section of expected REIT returns. Our firm-level empirical tests indicate a significant and negative relationship between REIT returns and both IV and IS risk. The observed risk-return trade-off remains significant even after controlling for firm-level characteristics and common risk factors. The empirical results document that firm-level IS risk is consonant with firm-level IV and that IS risk is not subsumed by IV and vice versa. Using Hou and Loh’s (2016) cross-sectional decomposition analysis, we find that firm-level IV and IS capture a very small percentage of each other’s average return premium, while a residual component accounts for the rest.

Why do insiders sell stocks after receiving options?

ABSTRACT We investigate corporate insiders’ trading behaviour around option grants and find that they substantially increase their net sales after receiving options. The increase in insider net sales is positively associated with risk metrics such as idiosyncratic volatility and stock price crash risk, but not with proxies for insider opportunism. This suggests that the increase in net sales is likely driven by risk-reduction considerations rather than opportunistic trading based on inside information. Consistent with this view, we find that insider sales following option grants do not precede more negative returns.

Risks of heterogeneously persistent higher moments

Using intraday data for the cross-section of individual stocks, we show that both transitory and persistent fluctuations in realized market and average idiosyncratic volatility, skewness and kurtosis are differentially priced in the cross-section of asset returns, implying a heterogeneous persistence structure of different sources of higher moment risks. In particular, we find that both idiosyncratic transitory shocks to volatility and idiosyncratic persistent shocks to skewness share strong commonalities that are relevant to investors.

Multilayer network analysis of idiosyncratic volatility connectedness: Evidence from China

This paper proposes multilayer networks, including lagged, contemporaneous, and long-run networks, to examine the idiosyncratic connectedness among Chinese financial institutions. We explore the topology of multilayer networks through static and dynamic analysis to capture the information transmission mechanism of idiosyncratic risks. Moreover, we investigate the drivers influencing idiosyncratic connectedness across financial institutions. We find that idiosyncratic risk contagion among financial institutions is stronger in the long-run network. At the same time, we note that the three networks contain different connection structures, which means that the information transmission mechanism of idiosyncratic risks is heterogeneous in multilayer networks. In addition, when the financial system is under stress, we observe that the contemporaneous effect of idiosyncratic connectedness rises rapidly. Institutional level analysis shows that diversified financial institutions play active roles in the lagged network, securities institutions are transmitters of contemporaneous information spillovers, and banking institutions are the main drivers of the long-run network. Finally, our study shows that size is the main factor driving idiosyncratic risk spillovers among financial institutions.

베타의 변동성과 주식의 기대수익률

This paper presents the stocks with high volatility of beta (VolBeta) underperform those with low VolBeta in the Korean stock market. The main findings are summarized as follows: First, the portfolio with high VolBeta has lower return relative to the one with low VolBeta. The raw and Fama-French four factor risk-adjusted return on zero-cost portfolio buying the highest and selling lowest VolBeta deciles are -1.11% and -1.45%, respectively. Second, firm-level Fama-MacBeth cross-sectional regressions show negative and statistically significant relation between VolBeta in this month and the cross-section of future returns. The results are robust to controls for firm chracteristics reportedly affecting stock returns. Third, overpricing of the stocks with high VolBeta is mostly pronounced in the ones with high idiosyncratic volatility. On the contrary, overpricing disappears in the high VolBeta stocks with low idiosyncratic volatility. The results suggest stocks with higher arbitrage risk measured by idiosyncratic volatility are more likely to be mispriced, consistent with Stambaugh, Yu, Yuan(2015).

Does data asset disclosure contribute to the market efficiency? Evidence from China

Information regarding firms' data assets and stock pricing has been more closely related when data is integrated into firms' value creation processes. However, since data asset disclosure can also be engaged in impression management by firms, its contribution to market efficiency may be impeded. Using a sample of Chinese A-share listed firms from 2014 to 2020, this study examines the impact of increased data asset information disclosure on the subsequent stock price volatility. The findings suggest that more data asset disclosure reduces stock return idiosyncratic volatility. The mechanism analysis shows that data asset disclosure reduces idiosyncratic volatility of stock prices by mitigating analyst forecast dispersion and noise trading induced by buy-sell imbalances. Moreover, this mitigating effect is more pronounced in firms with more analyst following, observable digital investments, and higher liquidity. But the effect is diminished if firms use a more positive abnormal tone in their annual reports.

Energy-Related Uncertainty and Idiosyncratic Return Volatility: Implications for Sustainable Investment Strategies in Chinese Firms

This study examines the impact of energy-related uncertainty on idiosyncratic volatility (IVOL) in Chinese firms, leveraging data from the Shanghai and Shenzhen stock exchanges between 2007 and 2022. Utilizing the Energy-Related Uncertainty Index (EUI) and the Fama–French five-factor model, we analyze a comprehensive dataset of 20,998 firm-year observations to understand how macroeconomic uncertainties specific to the energy sector influence firm-specific risk. Our findings reveal that a one-unit increase in the EUI is associated with a 5.1% rise in idiosyncratic volatility across all firms, underscoring the significant impact of energy-related uncertainty on firm-specific risks. The effect is more pronounced in energy-related firms, where a one-unit increase in the EUI leads to a 6.4% increase in IVOL, compared to a 3.7% increase in non-energy-related firms. By incorporating industry-wise, heterogeneity, and phase-based analyses, our findings reveal significant variations in the EUI’s impact across energy and non-energy sectors. State-owned enterprises, firms with high ownership concentration, and smaller firms are more vulnerable to energy uncertainties. Additionally, the effect of the EUI on IVOL is more pronounced during periods of high uncertainty. These insights have important implications for sustainable investment strategies, risk management, and policymaking, providing a deeper understanding of the intricate dynamics of energy markets in fostering sustainable economic growth and development.

Hedge funds and the positive idiosyncratic volatility effect

Abstract While it is established that idiosyncratic volatility is negatively priced in the cross-section of stock returns, the relation between idiosyncratic volatility and hedge fund returns is largely unexplored. We document that hedge funds with high idiosyncratic volatility earn higher future risk-adjusted returns of 6 percent p.a. than hedge funds with low idiosyncratic volatility. The outperformance arises because hedge funds trade high idiosyncratic volatility stocks wisely. They pick high volatility stocks when they are underpriced and short-sell high volatility stocks when they are overpriced. Our results support the notion that hedge funds’ idiosyncratic volatility is a measure of managerial skill.

Firm-level political risk and stock price crashes

In this study, we examine the relationship between firm-level political risk and stock price crash risk. Using a broad dataset of 4230 U.S. firms, 38,097 firm-year observations from 2002 to 2019, we reveal a positive association between political risk and stock price crash risk. These findings are robust to several model specifications and endogeneity checks. By using the Brexit referendum as a quasi-natural experiment, we provide evidence of a causal relationship between political risk and crash risk. Through channel analysis, we identify that this relationship is mediated via higher idiosyncratic volatility, lower price informativeness, and higher distress risk. We also find that our results are more pronounced in intangible-intensive firms. Interestingly, we show that managers of these firms respond to political risk by engaging in bad news hoarding. Finally, strong (external or internal) corporate governance mechanisms can moderate the positive relationship between political risk and stock price crash risk.

Option trading volume and the cross-section of option returns

This paper examines a novel pattern of option return predictability. Specifically, we find option trading volume negatively and significantly predicts the cross-section of delta-hedged option returns. Our portfolio strategies of option trading volume yield significant returns in options across different moneyness and time to maturity. Furthermore, the evidence shows that market capitalization and idiosyncratic volatility are able to explain the predictability of option trading volume on option returns. Our results are robust to alternative measures of option returns and option subsamples.

Diversification and idiosyncratic volatility puzzle: Evidence from ETFs

Exchange Traded Funds (ETFs) are considered diversified portfolios with low transaction costs and high liquidity. We test the impact of idiosyncratic risk on the cross-sectional returns of ETFs. We find the magnitude of idiosyncratic risk for U.S. equity ETFs is less than half of that of the sector equity ETFs. We show evidence that the idiosyncratic volatility (IVOL) puzzle only exists for sector equity ETFs, albeit they have a significant number of constituents. These findings are robust to ETF price, size, liquidity, different idiosyncratic risk estimates, and the subset of ETFs with a large number of constituents.

Risky or hedging centre? A novel approach for bidirectional ripple effects of urban house prices

ABSTRACT This study introduces a novel bidirectional ripple effect model to examine the static and dynamic ripple effects in the housing markets of urban cities in China. By investigating the influence of idiosyncratic volatility on market co-movements, this study effectively identifies risky and hedging centres, along with the durations of the ripple effects. The results show that Beijing, Shanghai, Guangzhou, Hangzhou, Nanjing, Bengbu, Luoyang, and Wuhan are more likely to be identified as risky centres, whereas Ningbo and Wenzhou stand out as hedging centres. The results also show that most cities exhibit greater density and longer durations of risky ripple effects than hedging ripple effects, implying a switch between risky and hedging centres. Overall, the proposed method provides a comprehensive understanding of the ripple effects in housing markets and benefits policymakers and investors.

On the Robustness of Idiosyncratic Volatility Effect

The idiosyncratic volatility (IVol) effect is robust to restricting the sample to New York Stock Exchange (NYSE) firms (once the proper listing indicator is used) and to excluding from the sample small, illiquid, and low-price stocks. The idiosyncratic volatility effect is also unlikely to stem from the short-run reversal, as the IVol effect stays significant for about six months and seems stronger for high turnover firms, which do not exhibit short-term reversal. The IVol effect also does not seem to weaken postpublication. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.04140 .

Common and idiosyncratic conditional volatility: Theory and empirical evidence from electricity prices

. We propose and develop a robust score-driven multiplicative dynamic factor model for the conditional volatility of electricity prices. This model allows us to identify both common and idiosyncratic conditional volatility factors in the spot price of electricity across key Nord Pool European markets. Both factors are extracted using a single observation-driven filter that is simple and parsimonious. The common factor is robust by construction as it averages information over the cross-section of the high-dimensional vector of electricity price changes. The idiosyncratic factors are designed to capture the erratic shocks in prices and therefore rely on a robust updating equation which allows for outliers and fat-tailed innovations. Our model is suitable for high-dimensional applications and does not necessarily suffer from the curse of dimensionality. The parsimonious nature of the observation-driven filter leads to simple computations for the estimation of parameters and the signal extraction of factors. We derive the stochastic properties of the filter and its underlying factor model, including bounded moments, stationarity, ergodicity, and filter invertibility. We further establish the consistency and asymptotic normality of the maximum likelihood estimator. The finite sample properties of the estimator and the filter are explored in a Monte Carlo study. Finally, we apply our model and filter to the Nord Pool spot price data and find evidence that net-import and net-export electricity markets exhibit substantially different common and idiosyncratic volatilities. In particular, we confirm that net-import markets are considerably more exposed to cross-market volatility spillovers, and we quantify the relevant degree of exposition.

Rethinking family business resilience: an empirical examination of family firms’ performance amid the COVID-19 pandemic in the US

ABSTRACT Contrary to recent research suggesting heightened resilience in family firms amid crises such as COVID-19, our study based on data from publicly traded firms in the US, challenges this narrative. We find that family-owned firms did not exhibit superior market performance or profitability during the pandemic compared to their non-family counterparts, or lower idiosyncratic volatility. Moreover, there were no discernible differences in how family and non-family firms perceived the effects of COVID-19 related exposure, risk, and sentiment. A plausible explanation for this finding could be the isomorphic pressures during a pandemic where neither family nor non-family firms may better leverage their resources. Our contrary evidence is important as it challenges existing assumptions and calls for a more critical evaluation of family firm resilience during the crisis.

Institutional investor network and idiosyncratic volatility of stocks

AbstractThis paper constructs an institutional investor network based on the heavy holdings of the same stock in China and conducts a social network analysis to investigate the influence of this network on stock price volatility from the perspectives of network structure (density) and location (centrality). The study demonstrates that institutional investor network density is negatively related to stock price volatility, while network centrality is positively related to it. Mechanism analyses further reveal that network density reduces stock price volatility by mitigating private information arbitrage behavior among institutional investors, whereas network centrality increases stock price volatility by creating private information arbitrage opportunities within the network. Additionally, the paper finds that information asymmetry enhances the positive effect of network centrality on stock price volatility. These findings are generally consistent across subsample analyses for different market states, reactions to good and bad news, and types of equity ownership, as well as in other robustness tests. The practical implications of these findings are significant for market stability regulation.

Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models

We investigate the performances of the ARFIMA, HAR, and EGARCH models in capturing the time-varying property of idiosyncratic volatility (IVOL). We find that the expected IVOL predictions by HAR are superior. In diverse portfolio scenarios, a greater degree of judgment is required to assess the pricing ability of expected IVOLs. For the lowest value-weighted quintiles and the expected IVOL estimated by the HAR model, the IVOL-return relationship is negative. Conversely, the IVOL-return relationship is positive for the expected IVOL estimated by the EGARCH model. Further evidence suggests a complicated and mixed relationship between the expected IVOL estimated by the ARFIMA model and stock returns.

Understanding co-movements based on heterogeneous information associations

Both systematic and idiosyncratic information dissemination contribute to assets co-movement. To proxy for co-movement based on heterogeneous information diffusion, we construct two-layer network structures in terms of the correlations of systematic and idiosyncratic returns for Fama–French 49 industry portfolios. We further delve into the co-movement structures by studying their dynamics and interactions in terms of topological properties at both the system and individual levels. Our findings reveal the following: (1) Co-movement structures exhibit temporal changes and are closely associated with major risk events. (2) At the system level, there is time-varying mutual Granger causality between co-movement structures, particularly during or after recession periods. (3) At the individual level, we identify statistically significant but economically insignificant interplay between the two co-movement structures. Moreover, the co-movement structure based on systematic information diffusion is mainly influenced by industry-level characteristics, including idiosyncratic momentum, idiosyncratic volatility, and market beta. These results deepen our understanding of asset co-movement structures and bear significance for asset allocation and risk management practices.

An Index of Skilled Analysts and Stock Market Returns

ABSTRACT This study constructs a monthly index of skilled analysts (ISA) regarding the coverage by such analysts and explores their predictive ability on the future excess returns of Chinese A-share market. The empirical results reveal that ISA significantly and positively predicts excess stock market returns, with R 2 s of 4.39% and 4.13% in- and out-of-sample respectively, which surpasses the predictive ability of most commonly used economic variables. High ISA precedes a higher investor sentiment index (ISI) and lower idiosyncratic volatility (IVOL) at firm level. The conclusion remains valid after controlling for a series of other predictor variables and performing robustness tests.

Climate risk and the idiosyncratic volatility puzzle

ABSTRACT Our study offers intriguing evidence on the much-debated idiosyncratic volatility (IdVol) puzzle from a climate risk perspective. Using a set of US-listed stocks from July 2010 to December 2019, our robust portfolio- and stock-level results reveal that the IdVol puzzle exists in both carbon-footprint-disclosing and non-disclosing stocks. Furthermore, investors do not perceive a significant difference in the IdVol puzzle between carbon-footprint-disclosing and non-disclosing stocks. However, the IdVol puzzle is concentrated in high-carbon-intensive stocks as far as those carbon-footprint-disclosing stocks are concerned, implying the combined effect of investor attention and ethical screening of stocks. Overall, our results substantiate the specific impact of climate-related risks on asset pricing decisions.