High Idiosyncratic Volatility Stocks Research Articles

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.

Idiosyncratic volatility, turnover and the cross-section of stock returns: evidence from the Korean stock market

PurposeThe 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.Design/methodology/approachUsing 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.FindingsThe 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.Originality/valueLiterature 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.

Volatility and the Cross-Section of Equity Returns: The Role of Short-Selling Constraints

IHS Markit data reveals that stocks with high idiosyncratic volatility are far more likely to be hard-to-borrow than low idiosyncratic volatility stocks. When hard-to-borrow stocks are excluded, the relation between idiosyncratic volatility (IVOL) and stock returns disappears. The relation between idiosyncratic volatility and returns is more accurately described as a relation between being hard-to-borrow and stock returns. Arbitrage risk, on the other hand, is far too small to explain mispricing of high IVOL stocks. When the idiosyncratic volatility of portfolios rather than individual stocks is considered, Sharpe ratios of mispriced IVOL portfolios are much greater than the value-weighted market’s Sharpe ratio.

Idiosyncratic volatility, conditional liquidity and stock returns

There is strong evidence showing that stocks with higher levels of idiosyncratic risk provide relatively lower returns than stocks with lower levels of it. This paper points out that this negative idiosyncratic risk - expected returns relation is not pervasive over time, and provides a plausible explanation for its time-varying nature. Our results suggest that following recessions, the conditional pricing of liquidity creates a correction in prices of the high idiosyncratic volatility stocks that persists up to 9 months. As a result, the negative relation between idiosyncratic risk and expected returns is not observed following recessions.

The timing of low-volatility strategy

This study explores the role of investor attention impact on low-volatility strategy. Our evidence suggests that a low-volatility strategy for high investor attention stocks is more profitable than low investor attention stocks. Conditioned on high investor attention, the profitability of a low-volatility strategy significantly increases due to lower returns on higher idiosyncratic volatility stocks. Consistent with recent optimal beliefs theory, investors’ propensity for gambling-type strategies leads to negative returns with high idiosyncratic volatility stocks. Our results provide a behavioral support to explain the low-volatility strategy based on investors’ propensity to gamble.

Can Exposure to Aggregate Tail Risk Explain Size, Book-to-Market, and Idiosyncratic Volatility Anomalies?

We examine the impact of aggregate tail risk on return dynamics of size, book-to-market ratio, and idiosyncratic volatility sorted portfolios. Using changes in VIX Tail Hedge Index (ΔVXTH) as a proxy for aggregate tail risk, and controlling for market, size, book-to-market, and aggregate volatility risk, we document significant portfolio return exposures to tail risk. In particular, portfolios that contain small, value and volatile stocks exhibit consistently positive and statistically significant tail risk betas, whereas portfolios of big, growth and non-volatile stocks exhibit negative tail risk betas. We posit that due to their positive tail risk exposures, tail risk-averse investors demand extra compensation to hold small, value, and high idiosyncratic volatility stocks. Our results offer a tail risk-based explanation to size, value, and idiosyncratic volatility anomalies.

Idiosyncratic Volatility, Conditional Liquidity and Stock Returns

There is strong evidence showing that stocks with higher levels of idiosyncratic risk provide relatively lower returns than stocks with lower levels of it. This paper points out that this negative idiosyncratic risk - expected returns relation is not pervasive over time, and provides a plausible explanation for its time-varying nature. Our results suggest that following recessions, the conditional pricing of liquidity creates a correction in prices of the high idiosyncratic volatility stocks that persists up to 10 months. As a result, the negative relation between idiosyncratic risk and expected returns is not observed following recessions.

The Bid-Ask Bounce Effect and the Pricing of Cross-Sectional Idiosyncratic Volatility: An Australian Study

Han and Lesmond (2011) find that stock liquidity, namely bid-ask bounce, affects the pricing of idiosyncratic volatility. Following Ang et al. (2009) and Han and Lesmond (2011), we investigate the pricing of idiosyncratic volatility and liquidity-adjusted idiosyncratic volatility over the period January 2004 to December 2013 using a comprehensive Australian dataset. Our results indicate that (1) both lagged idiosyncratic volatility and lagged liquidity-adjusted idiosyncratic volatility are strongly and positively related to stock returns over the sample period; (2) consistent with Han and Lesmond (2011), the pricing of idiosyncratic volatility is largely captured by stock liquidity; (3) our liquidity adjusted idiosyncratic volatility estimates work well in explaining the variations of the stocks of small firms but do not explain much variations in stocks of large firms when size and BE/ME are controlled; (4) high idiosyncratic volatility stocks tend to be of small, volatile and illiquid.

Short-sale constraints and the idiosyncratic volatility puzzle: An event study approach

Abstract Using three natural experiments, we test the hypothesis that investor overconfidence produces overpricing of high idiosyncratic volatility stocks in the presence of binding short-sale constraints. We study three events: IPO lockup expirations, option introductions, and the 2008 short-sale ban on financial firms. Consistent with our prediction, we show that when short-sale constraints are relaxed, event stocks with high idiosyncratic volatility tend to experience greater price reductions, as well as larger increases in trading volume and short interest, than those with low idiosyncratic volatility. These results hold when we benchmark event stocks with non-event stocks with comparable idiosyncratic volatility. Overall, our findings suggest that biased investor beliefs and binding short-sale constraints contribute to idiosyncratic volatility overpricing.

Does Idiosyncratic Volatility Matter in Emerging Markets? Evidence From China

We investigate the time series behavior of idiosyncratic volatility and its role in asset pricing in China. We find no evidence of a long-term trend in the time series behavior of idiosyncratic volatility. Idiosyncratic volatility in China is best characterized by an autoregressive process with regime shifts that coincide with structural market reforms. We also document evidence of a negative idiosyncratic volatility effect in China with anecdotal evidence suggesting that it could be driven by investor preference for high idiosyncratic volatility stocks.

Does idiosyncratic volatility matter in emerging markets? Evidence from China

We investigate the time series behavior of idiosyncratic volatility and its role in asset pricing in China. We find no evidence of a long-term trend in the time series behavior of idiosyncratic volatility. Idiosyncratic volatility in China is best characterized by an autoregressive process with regime shifts that coincide with structural market reforms. We also document evidence of a negative idiosyncratic volatility effect in China with anecdotal evidence suggesting that it could be driven by investor preference for high idiosyncratic volatility stocks.

Cross section of option returns and idiosyncratic stock volatility

This paper presents a robust new finding that delta-hedged equity option return decreases monotonically with an increase in the idiosyncratic volatility of the underlying stock. This result cannot be explained by standard risk factors. It is distinct from existing anomalies in the stock market or volatility-related option mispricing. It is consistent with market imperfections and constrained financial intermediaries. Dealers charge a higher premium for options on high idiosyncratic volatility stocks due to their higher arbitrage costs. Controlling for limits to arbitrage proxies reduces the strength of the negative relation between delta-hedged option return and idiosyncratic volatility by about 40%.

Idiosyncratic Volatility, Realized Return, and Implied Cost of Capital

I use implied cost of capital as a proxy for expected return in testing the cross-sectional relation between expected return and idiosyncratic risk. I find a positive relation between idiosyncratic risk and expected return and a negative relation between idiosyncratic risk and future realized return. Ex-ante, investors expect high-idiosyncratic volatility stocks to earn 2.4% per year more than low-idiosyncratic volatility stocks, while ex-post, investors lose 8.4% per year by holding the high-minus-low idiosyncratic volatility portfolio. The ex-ante positive relation is robust to different estimation methods of idiosyncratic volatility, as well as return and volatility reversal. The positive relation is also robust to size, book-to-market, momentum, forecasted long-term growth, and analyst-forecast dispersion. The evidence suggests that the ex-ante and ex-post return differential is partly due to the more optimistic expectation of investors towards high-idiosyncratic volatility stocks. The ex-post underperformance of high-idiosyncratic volatility stocks can be attributed to short-term momentum and long-run return reversal. In addition, the return differential is also due to costly arbitrage for stocks with high-idiosyncratic volatility.

Low Risk and High Returns: Evidence from the German Stock Market

Although most of the empirical and theoretical asset pricing literature predicts a positive or no signi ficant relationship between idiosyncratic volatility and returns, Ang et al. (2006, 2009) find that high idiosyncratic volatility stocks have low returns and vice versa. We deliver further evidence and show that the cross-section of the German stock market re effects a negative premium for idiosyncratic risk. Even after controlling for the three Fama-French factors we estimate a signi ficant risk premium of -0.8% per month. In addition, we undertake further robustness checks like the differentiation between upside and downside idiosyncratic volatility, the application of the (E)GARCH approach to estimate idiosyncratic risk and the use of monthly instead of daily data. However, the puzzle still prevails.

Why Do Firms with High Idiosyncratic Volatility and High Trading Volume Volatility Have Low Returns?

Ang, Hodrick, Xing and Zhang (2006) document a negative relation between returns and idiosyncratic volatility (hereafter the AHXZ result). We show their result is significant and robust to various measures of idiosyncratic volatility and various return horizons after deleting penny stocks and controlling for January. Moreover, their result is not attributable to small firms. We examine whether the market misprices high idiosyncratic volatility stocks in a manner consistent with the effects of limits of arbitrage and information uncertainty. The results are supportive of this hypothesis. The AHXZ result exists only among stocks with low analyst coverage, and is strongest among low-coverage stocks with high returns over the prior three years. Earnings announcement returns are negative and significant for high idiosyncratic volatility stocks with low analyst coverage, but not those outside the low-coverage group. Outside of low-coverage stocks, the relation between returns and idiosyncratic volatility is insignificant or positive. Distinct patterns in earnings indicate that the AHXZ result arises because the market overestimates the persistence of earnings growth for low-coverage stocks with high idiosyncratic return volatility. We document a similar collection of results for stocks sorted on the volatility of share turnover, suggesting that the negative relation between returns and turnover volatility documented by Chordia, Subrahmanyam and Anshuman (2001) also reflects mispricing consistent with information uncertainty and limits of arbitrage.

Financial distress and idiosyncratic volatility: An empirical investigation

We investigate the link between distress and idiosyncratic volatility. Specifically, we examine the twin puzzles of anomalously low returns for high idiosyncratic volatility stocks and high distress risk stocks, documented by Ang et al. (2006) and Campbell et al. (2008), respectively. We document that these puzzles are empirically connected, and can be explained by a simple, theoretical, single-beta CAPM model.

Does Stock Volatility Reveal Mutual Fund Manager Skill?

If some mutual fund managers have the ability to outperform benchmarks on a risk-adjusted basis, then a natural question to ask is where they should concentrate their efforts. Stocks that display high volatility relative to the benchmark may occasionally offer greater opportunities to investors who are better informed about fundamental values than the market. As a result, skilled investors may end up having greater weights on stocks with high idiosyncratic risk and, in consequence, the volatility of the stocks in an investor's portfolio may indicate the investor's degree of skill. I propose a model that captures this intuition in which managers differ in their ability first to pick stocks, and second to predict future stock price increases with precision. I examine the stock portfolios of mutual funds and find that the mutual fund industry in general favors stocks with high idiosyncratic volatility: the average idiosyncratic volatility of the stocks in a mutual fund portfolio is 3-4 percent higher than the benchmark. Funds which hold stocks with higher idiosyncratic volatility have higher future returns and higher future inflows on average, regardless of the time interval and approaches to adjust return for risk. In a successful manager's portfolio, high idiosyncratic volatility stocks outperform the remainder, indicating skill is most deployed in stocks with high volatility, and this is not the case for unsuccessful managers.

High Idiosyncratic Volatility and Low Returns: International and Further U.S. Evidence

Stocks with recent past high idiosyncratic volatility have low future average returns around the world. Across 23 developed markets, the difference in average returns between the extreme quintile portfolios sorted on idiosyncratic volatility is -1.31% per month, after controlling for world market, size, and value factors. The effect is individually significant in each G7 country. In the U.S., we rule out explanations based on trading frictions, information dissemination, and higher moments. There is strong comovement in the low returns to high idiosyncratic volatility stocks across countries, suggesting that broad, not easily diversifiable, factors may lie behind this phenomenon.

Retail Clienteles and the Idiosyncratic Volatility Puzzle

This study examines whether the puzzling negative relation between idiosyncratic volatility and expected returns (Ang, Hodrick, Xing, and Zhang (2006, 2008)) is influenced by the preferences and the trading behavior of volatility-seeking retail investors. First, we show that volatility-seeking retail clienteles exist. Retail investors prefer to hold and actively trade high idiosyncratic volatility stocks due to their greater propensity to speculate or gamble (Dorn and Huberman (2007)) and also because those stocks offer a greater opportunity for experiencing higher levels of realization utility (Barberis and Xiong (2008)). In contrast, institutional investors prefer low idiosyncratic volatility stocks. Next, we show that the negative return-volatility relation is concentrated among stocks that are actively traded by retail investors and exhibit strong speculative characteristics (e.g., high idiosyncratic skewness). Among stocks with low levels of retail trading, future returns increase with idiosyncratic volatility. Collectively, our results indicate that the level of retail trading is a critical determinant of the volatility-return relation.

Short-Sale Constraints and the Idiosyncratic Volatility Puzzle: An Event Study Approach

Using three natural experiments, we test the hypothesis that investor overconfidence produces overpricing of high idiosyncratic volatility stocks in the presence of binding short-sale constraints. We study three events: IPO lockup expirations, option introductions, and the 2008 short-sale ban on financial firms. Consistent with our prediction, we show that when short-sale constraints are relaxed, event stocks with high idiosyncratic volatility tend to experience greater price reductions, as well as larger increases in trading volume and short interest, than those with low idiosyncratic volatility. These results hold when we benchmark event stocks with non-event stocks with comparable idiosyncratic volatility. Overall, our findings suggest that biased investor beliefs and binding short-sale constraints contribute to idiosyncratic volatility overpricing.