Low Idiosyncratic Volatility Research Articles

Effects of Idiosyncratic Volatility in Asset Pricing

This paper aims to evaluate the effects of the aggregate market volatility components - average volatility and average correlation - on the pricing of portfolios sorted by idiosyncratic volatility, using Brazilian data. The study investigates whether portfolios with high and low idiosyncratic volatility - in relation to the Fama and French model (1996) - have different exposures to innovations in average market volatility, and consequently, different expectations for return. The results are in line with those found for US data, although they portray the Brazilian reality. Decomposition of volatility allows the average volatility component, without the disturbance generated by the average correlation component, to better price the effects of a worsening or an improvement in the investment environment. This result is also identical to that found for US data. Average variance should thus command a risk premium. For US data, this premium is negative. According to Chen and Petkova (2012), the main reason for this negative sign is the high level of investment in research and development recorded by companies with high idiosyncratic volatility. As in Brazil this type of investment is significantly lower than in the US, it was expected that a result with the opposite sign would be found, which is in fact what occurred.

Credible Reforms and Stock Return Volatility: Evidence from Privatization

In this paper we investigate how privatization affects stock return volatility. We show that privatization is related to volatility via political risk. In particular, a privatization program that is maintained over time signals credibility, which reduces political risk and in turn volatility. We further show that privatization is associated with lower idiosyncratic volatility mainly among developed markets, while it is associated with lower systematic volatility in developing markets. Additional tests suggest that the reduction in volatility is greater when privatization sales are carried out through the stock market than when they are carried out through asset sales.

Idiosyncratic volatility and global equity markets

This article investigates the relation of idiosyncratic volatility (IVOL) and future returns on a portfolio level in global equity markets. In contrast to previous studies (Ang et al. 2006, 2009), it reveals that the spread between stock indices exhibiting a high IVOL and stock indices with low IVOL is positive and unrelated to movements in the business cycle. Traditional asset pricing models cannot explain the spread.

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.

Commodity Strategies Based on Momentum, Term Structure, and Idiosyncratic Volatility

This article demonstrates that momentum, term structure, and idiosyncratic volatility signals in commodity futures markets are not overlapping, which inspires a novel triple‐screen strategy. We show that simultaneously buying contracts with high past performance, high roll‐yields, and low idiosyncratic volatility, and shorting contracts with poor past performance, low roll‐yields, and high idiosyncratic volatility yields a Sharpe ratio over the 1985 to 2011 period that is five times that of the S&P‐GSCI. The triple‐screen strategy dominates the double‐screen and individual strategies and this outcome cannot be attributed to overreaction, liquidity risk, transaction costs, or the financialization of commodity futures markets. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 35:274–297, 2015

What Drives the Enhanced Momentum Profits of Growth Firms? Mispricing or Risk

We examine rational and behavioral explanations for the relatively larger momentum profits of growth firms. Our results provide support for the rational explanation for firms with low idiosyncratic volatility, and are consistent with the notion that growth options cause a wider spread in the risk and returns between winners and losers. However, the evidence is more aligned with the behavioral explanation for firms with high idiosyncratic volatility, which is consistent with the notion that investors are more prone to behavioral biases in the presence of idiosyncratic volatility, and the resulting mispricings are less likely to be immediately arbitraged away.

Time Horizon Effect on Real Investment Decisions

We consider the entrepreneur’s problem of having a real investment opportunity with undiversifiable risk in a finite horizon. By explicitly characterizing the consumption and investment problem, we show that the remaining time to undertake the project has a significant impact on the characteristics of a firm’s cash flow or return dynamics. Our theory predicts that a firm with an ample time horizon to invest tends to have a cash flow or the stock return with a higher idiosyncratic volatility. Furthermore, we also extend the baseline model to the cases in which the entrepreneur has several projects that can only be sequentially exercised. In this case, a project with a lower idiosyncratic volatility will be exercised first when the investment horizon is long.

Distribution Effect and Idiosyncratic Volatility Discount

Based on information signaling theory, this paper empirically shows that distribution effect matters for idiosyncratic volatility discount. Idiosyncratic volatility discount arises primarily among stocks with non-cash distributions. Such stocks show a significant idiosyncratic volatility discount, measured by the return difference between high and low idiosyncratic volatility portfolios. For stocks with cash distributions, this discount is statistically insignificant. We attribute these effects to the fact that the information content of cash distributions reduces the uncertainty of future capital gains, which in turn drives out the idiosyncratic volatility discount. We test several explanations of idiosyncratic volatility discount under the framework of distribution effect and find evidence contrary to those explanations. In addition, our empirical results suggest that extreme values may obscure some of the extant explanations on idiosyncratic volatility discount.

Stochastic Idiosyncratic Operating Risk and Real Options: Implications for Stock Returns

Stocks with high idiosyncratic volatility perform poorly relative to low idiosyncratic volatility stocks. We offer a novel explanation of this anomaly based on real options, which is consistent with earlier findings on idiosyncratic volatility (the positive contemporaneous relation between firm-level stock returns and idiosyncratic volatility). Our approach is based on introducing stochastic idiosyncratic cash flow risk into an equity valuation model of firms with growth options. Within our model, a firm's systematic risk depends on the delta of its growth option. The growth option's delta is lower when idiosyncratic volatility rises, driving down the firm's systematic risk and hence its expected return -- firms with higher idiosyncratic volatility therefore have lower expected returns. Our model offers the following novel empirical predictions (i) returns correlate positively with idiosyncratic volatility during intervals between large changes in idiosyncratic volatility (the switch effect), (ii) and that the anomalies and the switch effect are stronger for firms with more real options and which undergo larger changes in idiosyncratic volatility. Empirical results support the predictions of our model.

Idiosyncratic Volatility Strategies in Commodity Futures Markets

This article demonstrates that momentum, term structure and idiosyncratic volatility signals in commodity futures markets are not overlapping which inspires a novel triple-screen strategy. We show that simultaneously buying contracts with high past performance, high roll-yields and low idiosyncratic volatility, and shorting contracts with poor past performance, low roll-yields and high idiosyncratic volatility yields a Sharpe ratio over the 1985 to 2011 period which is five times that of the S&P-GSCI. The triple-screen strategy dominates the double-screen and individual strategies and this outcome cannot be attributed to overreaction, liquidity risk, transaction costs or the financialization of commodity futures markets.

On the Scope and Drivers of the Asset Growth Effect

AbstractRecent papers have debated whether the negative correlation between measures of firm asset growth and subsequent returns is of little importance since it applies only to small firms, is justified as compensation for risk, or is evidence of mispricing. We show that the asset growth effect is pervasive, and evidence to the contrary arises due to specification choices; that one measure of asset growth, the change in total assets, largely subsumes the explanatory power of other measures; that the ability of asset growth to explain either the cross section of returns or the time series of factor loadings is linked to firm idiosyncratic volatility (IVOL); that the return effect is concentrated around earnings announcements; and that analyst forecasts are systematically higher than realized earnings for faster growing firms. In general, there appears to be no asset growth effect in firms with low IVOL. Our findings are consistent with a mispricing-based explanation for the asset growth effect in which arbitrage costs allow the effect to persist.

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.

What’s IVol Got to Do With It?

Campbell et al.’s [2001] influential paper on idiosyncratic volatility has received a lot of research attention in recent years. The critical question for portfolio managers is: “How does idiosyncratic volatility affect stock selection and asset allocation signals?” This article examines that important question. Using well-accepted metrics of idiosyncratic volatility, the authors find that the effectiveness of both the momentum and the valuation signals critically depends on cross-sectional differences in idiosyncratic volatility. In particular, they find that the mean reversion signal works better for firms with low idiosyncratic volatility, whereas the momentum signal works better for those with high idiosyncratic volatility. This result is robust across different regimes of idiosyncratic volatility. Finally, the authors test whether a measure of idiosyncratic volatility has an impact on the Fed Model for asset allocation. They find that conditioning the signal in the Fed Model for cross-sectional differences in idiosyncratic volatility significantly improves the mean reversion effect that underlies the Fed Model. In summary, they note that it is important to condition stock selection and asset allocation models for cross-sectional differences in idiosyncratic volatility. TOPICS:Volatility measures, portfolio theory, security analysis and valuation

Idiosyncratic Volatility, Return Reversals and Momentum: Australian Evidence

This paper examines the interaction between short-run return reversals, momentum and idiosyncratic volatility in the Australian market. We confirm that stocks with high idiosyncratic volatility earn low average returns over the next month. Unlike US studies which attribute this negative relation to short-run return reversals, we find that it is partly caused by a group of loser stocks (formed over one month) which continue to exhibit negative return drift (over the next month). We also investigate whether these stocks continue to display negative returns over longer horizons. In turn, we broaden our study to examine whether the momentum effect is persistent in stocks with high idiosyncratic volatility. We find that stocks with high idiosyncratic volatility realize significant abnormal momentum returns over a six-month holding period relative to stocks with low idiosyncratic volatility. As we document the persistence of momentum profits amongst stocks with high idiosyncratic volatility, our work contributes to the existing literature which suggests that idiosyncratic volatility is an important limit to the arbitrage of the momentum effect.

Conference Calls and Stock Price Volatility in the Post‐Reg FD Era

Abstract Past research has documented that the utilisation of conference calls is greater in the high tech sector than in other industries. Do high tech firms benefit from that? This study attempts to answer this question by examining the impact of ‘post‐Reg FD’ conference calls on the price volatility of high tech firms listed in the US market. We find evidence that more open conference calls results in lower idiosyncratic volatility.

When Is Stock Picking Likely to Be Successful? Evidence from Mutual Funds

Consistent with a costly arbitrage equilibrium in which arbitrage costs insulate mispricing, this study finds that mutual fund managers have stock-picking ability for stocks with high idiosyncratic volatility but not for stocks with low idiosyncratic volatility. These findings suggest that fund managers and other investors may want to pay special attention to high-idiosyncratic-volatility stocks because they provide fertile ground for stock picking. The study also finds that the stock-picking ability of the average mutual fund manager declined after the extreme growth in the number of both mutual funds and hedge funds in the late 1990s.

When Is Stock Picking Likely to Be Successful? Evidence from Mutual Funds

Consistent with a costly arbitrage equilibrium in which arbitrage costs insulate mispricing, this study finds that mutual fund managers have stock-picking ability for stocks with high idiosyncratic volatility but not for stocks with low idiosyncratic volatility. These findings suggest that fund managers and other investors may want to pay special attention to high-idiosyncratic-volatility stocks because they provide fertile ground for stock picking. The study also finds that the stock-picking ability of the average mutual fund manager declined after the extreme growth in the number of both mutual funds and hedge funds in the late 1990s.

On the Scope and Drivers of the Asset Growth Effect

Recent papers have debated whether the negative correlation between measures of firm asset growth and subsequent returns is of little importance since it applies only to small firms, justified as compensation for risk, or evidence of mispricing. We show that the asset growth effect is pervasive and evidence to the contrary arises due to specification choices; that one measure of asset growth, the change in total assets, largely subsumes the explanatory power of other measures; that the ability of asset growth to explain either the cross section of returns or the time series of factor loadings is linked to firm idiosyncratic volatility; that the return effect is concentrated around earnings announcements; and that analyst forecasts are systematically higher than realized earnings for faster growing firms. In general, there appears to be no asset growth effect in firms with low idiosyncratic volatility. Our findings are consistent with a mispricing-based explanation for the asset growth effect in which arbitrage costs allow the effect to persist.

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.