Idiosyncratic Volatility Puzzle Research Articles

The idiosyncratic volatility puzzle and mergers and acquisitions activity

This paper examines whether the puzzling negative relationship between idiosyncratic volatility and next month performance is affected by the intensity of merger and acquisition (M&A) activity in the market. Our results show that the idiosyncratic volatility puzzle is stronger in periods of high M& A activity than in periods of low M&A activity. Further analysis shows that the negative relationship between idiosyncratic volatility and next month performance is the strongest in the high M&A activity sub-period spanning from 1982–1989. In contrast, M&A activity does not explain the negative relationship between the common factor in idiosyncratic volatility (CIV) and next month performance. M&A activity can in part explain the idiosyncratic volatility puzzle, but it does not subsume the negative relationship between CIV exposure and firm returns.

Idiosyncratic Volatility, Its Expected Variation, and the Cross-Section of Stock Returns

We show that the widely documented negative relation between idiosyncratic volatility (IVOL) and expected returns can be explained by the mean reversion of stocks' idiosyncratic volatilities. We use option-implied information to extract the mean reversion speed of IVOL in an almost model-free fashion. This allows us to identify stocks for which past IVOL is a bad proxy for expected IVOL. These stocks solely drive the negative relation, and a long--short portfolio earns a monthly risk-adjusted return of 2.74%, on average. In a horse race, the mean reversion speed is superior to prominent competing explanations of the IVOL puzzle.

Idiosyncratic volatility in the Australian equity market

This paper studies the idiosyncratic volatility (IV) puzzle in the Australian equity market. I document a negative relation between IV and future stock returns. More importantly, this is the first Australian study to investigate the role of the asset-pricing model used to estimate IV. While recent work advocates a five-factor model incorporating investment and profitability factors, the findings suggest that the IV puzzle is not an outcome of investment and profitability factors being omitted from the three-factor model used to estimate IV. The exploration of potential causes of the IV puzzle suggests that it is attributable to mispricing, since it concentrates amongst the most-overpriced stocks as given by an Australian mispricing index. Decomposing the source of mispricing, the IV puzzle is largely explained by investors' preference for lottery-like stocks.

Patterns and Pricing of Idiosyncratic Volatility in French Stock Market

Purpose: The current research is to investigate the time series behavior of idiosyncratic volatility (IVOL) and its role in asset pricing in France in a twenty-year testing period. Design/methodology/approach: We test for the presence of trends in aggregate idiosyncratic and market volatility using Bunzel and Vogelsang’s (2005) t-dan test. We follow Bekaert et al. (2012) to test for regime shifts of both aggregate idiosyncratic and market volatilities. And then, we employ portfolio level analysis and cross-sectional univariate Fama-MacBeth regressions to examine the relationship between IVOL and cross-sectional stock returns in French stock market. Findings: First, we find that both idiosyncratic and market volatility do not exhibit long-term trends. Instead, their patterns are consistent with regime switching behavior. Second, though we initially find a strong significant negative IVOL effect in the French stock market which is robust in bi-variate Fama-MacBeth regressions, the negative IVOL effect is becoming marginal significant when we control for SIZE, BM, momentum, and short-term reversal simultaneously. Our new evidence suggests that there is a marginal IVOL effect in the French stock market adding to the increasing number of studies questioning the ubiquity of the negative IVOL puzzle. Originality/value: First, we present the first empirical evidence on examining the trends of both aggregate idiosyncratic and market volatilities, and the pricing role of IVOL in French stock market. We draw an attention for both academia and practitioners on an individual developed stock market. Second, we add new evidence to the mounting results questioning the ubiquity of the IVOL effect. This highlights the importance of country verification of so called anomalies in the US, even in developed markets. Finally, we confirm earlier evidence both aggregate idiosyncratic and market volatilities in the French stock market exhibits regime switching behavior rather than showing a long-term time trends.

Daily Winners and Losers

One of the most salient events for a stock is being a daily winner or loser: these stocks are highlighted prominently in the media, leading to investor attention spikes. We demonstrate that ranked stocks underperform unranked stocks by over 1.50% during the month after the ranking, in line with attention-induced overpricing. To establish causality, we introduce an identification strategy that exploits unconventional return-measurement periods. We show that the underperformance of daily winners and losers provides a new attention-based solution for the idiosyncratic volatility puzzle and related return patterns, and thus a simple unifying explanation for important asset pricing anomalies.

Idiosyncratic volatility and stock returns: Indian evidence

This paper examines the idiosyncratic volatility (IV) puzzle in the Indian stock market for the period 1999–2014. Univariate and bivariate sorting, as well as cross-section regressions, suggest a p...

Research on Investment Preference and the MAX Effect in Chinese Stock Market

AbstractInvestors prefer to invest the stocks with high history returns, which results in that the return of the stock with high history maximum return is often lower than that with low history maximum return, i.e., the MAX effect. We show that the MAX effect is also significant in China stock market, that is, there is a significant negative relationship between maximum return and expected return. We then conduct portfolio analysis and Fama-Macbeth cross-sectional regression and find that range of price and turnover rate can explain the MAX effect in a certain extent, idiosyncratic volatility and idiosyncratic skewness cannot explain the negative relationship between maximum return and expected return. Moreover, maximum return explains the idiosyncratic volatility puzzle partially.

Public news arrival and the idiosyncratic volatility puzzle

Abstract This paper analyzes the effects of news and its sentiment on the idiosyncratic volatility ( IVOL ) — expected return relation. We postulate that the perceived negative IVOL -expected return relation could be the artifact of the confounding effect of public news arrivals. Using the stock return data from the Center for Research in Security Prices (CRSP) database and the news database from the RavenPack News Analytics over the period from 2000 to 2011, we show that the strength of the positive relation is reduced systematically by 50% after accounting for the arrivals of good and bad news releases, which are defined by their sentiment scores. This finding is robust to numerous model specifications, and the inclusion of firm-level characteristics, liquidity risk and information risk. When we restrict the firm-specific news to value-relevant news, the positive relation disappears. We conclude that that the public arrivals of firm-specific news play a significant role in explaining the IVOL puzzle.

The Effect of Arbitrage Asymmetry on the Idiosyncratic Volatility Puzzle: Korea Stock Market

The Effect of Arbitrage Asymmetry on the Idiosyncratic Volatility Puzzle: Korea Stock Market

Have we solved the idiosyncratic volatility puzzle?

We propose a simple methodology to evaluate a large number of potential explanations for the negative relation between idiosyncratic volatility and subsequent stock returns (the idiosyncratic volatility puzzle). Surprisingly, we find that many existing explanations explain less than 10% of the puzzle. On the other hand, explanations based on investors’ lottery preferences and market frictions show some promise in explaining the puzzle. Together, all existing explanations account for 29–54% of the puzzle in individual stocks and 78–84% of the puzzle in idiosyncratic volatility-sorted portfolios. Our methodology can be applied to evaluate competing explanations for other asset pricing anomalies.

Understanding the Idiosyncratic Volatility Puzzle: Evidence from Mutual Fund Flows

We use capital flows into and out of mutual funds to infer investors’ preferences towards idiosyncratic volatility (IV). We find investors are more likely to both purchase and redeem funds with high IV. This pattern is concentrated among funds in the top quintile of IV, and it is stronger among retail investors, non-incumbent investors, and funds with lower visibility. Our results suggest that search costs contribute to investors’ preference for IV when making trading decisions. Our findings that IV can result in increased visibility and liquidity may also help explain the puzzling negative relationship between IV and equity returns.

한국주식시장의 고유변동성 퍼즐과 투자자별 거래량

This paper examines the relationship between idiosyncratic volatility(IVOL) puzzle and trading volumes by trader types in the Korean stock market. The data set includes all stock in both KRX and KOSDAQ for the period from January 1999 through December 2013. Idiosyncratic volatility is measured by using the Fama-French's three-factor model. Traders are classified into individual, institution, and foreign trader. We construct (5X5) portfolios based on each trader's net buying and idiosyncratic volatility. We find that there are some special portfolios that show the idiosyncratic volatility puzzle. For individual investors, top net buying portfolios show clear the idiosyncratic volatility puzzle. However, for institution and foreign investors, lowest net buying portfolio show the idiosyncratic volatility puzzle. This results imply that the idiosyncratic volatility puzzle in the Korean stock market is mainly caused by individual investors.

Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle

ABSTRACTBuying is easier than shorting for many equity investors. Combining this arbitrage asymmetry with the arbitrage risk represented by idiosyncratic volatility (IVOL) explains the negative relation between IVOL and average return. The IVOL‐return relation is negative among overpriced stocks but positive among underpriced stocks, with mispricing determined by combining 11 return anomalies. Consistent with arbitrage asymmetry, the negative relation among overpriced stocks is stronger, especially for stocks less easily shorted, so the overall IVOL‐return relation is negative. Further supporting our explanation, high investor sentiment weakens the positive relation among underpriced stocks and, especially, strengthens the negative relation among overpriced stocks.

Investor Sentiment and Idiosyncratic Volatility Puzzle: Evidence from the Chinese Stock Market.

This paper examines the idiosyncratic volatility puzzle and whether investor sentiment influences the relation between idiosyncratic volatility and stock returns in the Chinese stock market. The findings indicate the existence of a negative idiosyncratic volatility effect. In addition, the results show that the relation between idiosyncratic volatility and returns significantly depends on investor sentiment. Thus, investor sentiment plays a very important role in reconciling the relation between idiosyncratic volatility and stock returns in the Chinese stock market. This implies that investor sentiment may be one of the major risk factors that should be considered in the Chinese stock market. In terms of predictive ability of investor sentiment, idiosyncratic volatility and market volatility, the findings indicate that idiosyncratic volatility positively predicts future excess market returns in the Chinese stock market.

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.

Retail Investors and the Idiosyncratic Volatility Puzzle: Evidence from the Korean Stock Market

AbstractIf the trading of noise traders is highly correlated and arbitrage risk exists, stock prices can deviate from their fundamental value. In particular, due to the short‐selling impediments, stock prices tend to be overpriced. We hypothesize that the idiosyncratic volatility (IVOL) puzzle is due to this overpricing caused by noise traders that can be proxied by retail traders, and provide evidence supporting it. Our empirical findings are as follows. First, the IVOL puzzle is more prominent among stocks with a high retail trading proportion (RTP). Second, the negative relation between IVOL and stock returns is stronger following high retail sentiment. Finally, return reversals for stocks with high RTP and high IVOL are observed.

Strategic Risk Shifting and the Idiosyncratic Volatility Puzzle

We find strong empirical support for the risk-shifting mechanism to account for the puzzling negative relation between idiosyncratic volatility and future stock returns documented by Ang, Hodrick, Xing, and Zhang (2006). First, underperformed firms have more incentives to take on high idiosyncratic risk investments. Using three different measures of idiosyncratic volatility, we show that firms increase their idiosyncratic risk in response to negative return on assets (RoAs) at least twice as much as they do in response to positive RoAs. Second, the increased idiosyncratic volatility reduces the sensitivity of stocks to assets and results in low future stock returns. Only the strategic risk-shifting component of idiosyncratic volatility predicted from the past RoAs has a significantly negative impact on future stock returns. Specifically, the strategic component alone explains 77.21% of the negative impact of monthly idiosyncratic volatility on monthly stock returns, which dominates other alternative explanations.

Lottery Preferences and the Time Series Variation of the Idiosyncratic Volatility Puzzle

We investigate the empirical implications of investors’ heterogeneous preferences for skewness with respect to the idiosyncratic volatility (IV) puzzle (the negative correlation between idiosyncratic volatility and mean returns). We show that the IV puzzle is stronger (1) within those stocks held primarily by agents with preference for lottery-like payoffs and (2) during economic downturns, when the demand for lottery-like payoffs is high. These results support recent theories that suggest lottery preferences may be a significant source of the IV puzzle.

Idiosyncratic Volatility Puzzle: Influence of Macro-Finance Factors

We analyze the cross-sectional relation between expected idiosyncratic volatility and stock returns. As a novelty, the expected idiosyncratic volatility is obtained by conditioning on macro-finance factors as well as traditional asset pricing factors. The macro-finance factors are constructed from a large pool of macroeconomic and financial variables. Accounting for macro-finance effects in the idiosyncratic volatility eliminates the well-known idiosyncratic volatility puzzle. Portfolio analysis shows that the effects from macro-finance factors are economically strong. The relation between expected idiosyncratic volatility and returns does not vary with the NBER business cycles. The empirical results are highly robust.

Sentiment and Asset Volatility Dynamics: A Content Analysis Approach

This paper analyses the effects of news on the so-called ‘idiosyncratic volatility puzzle’. By empirically modelling the stock return data from the Center for Research in Security Prices (CRSP) database from 2000 to 2011, we firstly find that idiosyncratic volatility has a positive effect on excess return. Existing studies suggest that both the quantity and quality of public information arrival (news flow) can significantly induce the stock return volatility. Following this idea, we employ various models to control for the potential news effects on the idiosyncratic volatility and re-visit this puzzle. Our empirical results suggest that when quantity, relevance and quality of news are all properly controlled for, the average magnitude of the idiosyncratic volatility effect on excess return can be reduced by roughly 50 per cent.