Volatility Puzzle Research Articles

The Unemployment Volatility and Wage Inertia Puzzles: The Centrality of Vacancy Posting Costs (to Output)

The Unemployment Volatility and Wage Inertia Puzzles: The Centrality of Vacancy Posting Costs (to Output)

The Low Volatility Puzzle:, Evidence From Amman Stock Exchange

The Low Volatility Puzzle:, Evidence From Amman Stock Exchange

Stock Volatility and the Great Depression

Abstract Stock return volatility during the Great Depression has been labeled a “volatility puzzle” because the standard deviation of stock returns was 2 to 3 times higher than any other period in American history. We investigate this puzzle using a new series of building permits and leverage. Our results suggest that volatility in building permit growth and financial leverage largely explain the high level of stock volatility during the Great Depression. Markets factored in the possibility of a forthcoming economic disaster. Received September 30, 2017; editorial decision August 27, 2018 by Editor Philip E. Strahan. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online

Have Hedge Funds Solved the Idiosyncratic Volatility Puzzle?

While it is established that idiosyncratic volatility has a negative impact on the cross-section of future stock returns, the relationship between idiosyncratic volatility and future hedge fund returns is largely unexplored. We document that hedge funds with high idiosyncratic volatility outperform and this pattern is explained by the positive return effect of idiosyncratic volatility in their equity portfolio holdings. Hedge funds select stocks wisely by picking high-volatility stocks when they are undervalued and shying away from high-volatility stocks when they are overvalued or display lottery-like payoffs. They also trade derivatives in a way to profit from the positive volatility effect.

Decomposition and Evaluation on the Determinants of the Idiosyncratic Volatility Puzzle in Korea Stock Market

Decomposition and Evaluation on the Determinants of the Idiosyncratic Volatility Puzzle in Korea Stock Market

The policy uncertainty and market volatility puzzle: Evidence from wavelet analysis

This article communicates a new dimension on the relationship of market volatility (VIX) and Economic Policy Uncertainty (EPU) using the propositions of Pastor and Veronesi (2017) and Das and Kumar (2018) by resorting to the wavelet analysis. We empirically examine the VIX-EPU puzzle and investigate the role of international and domestic policy shocks. We find (a) The VIX-EPU relationship is not always positive and is time-variant; (b) The combined DEPU-USEPU influence on VIX is more coherent to the developed markets; and (c) The VIX of the developed markets are more receptive to USEPU.

Firm-level political risk and asymmetric volatility

This paper examines whether proxies of political risk exposure at the firm-level can predict the aggregate stock market volatility. Utilizing a nonparametric causality-in-quantiles test which not only guards against misspecification due to nonlinearity, but also tests for causality over the entire conditional distribution of the realized volatilities, we show that political risk exposure can serve as a strong predictor of bad realized volatility, while the causal effects are non-existent in the case of overall and good realized volatilities. Our findings provide novel insight to the well-documented asymmetric volatility puzzle and the effect of political uncertainty on stock market fluctuations via the investor attention channel. The results also suggest that political risk exposure could be a contributing factor to jump risk in the cross-section of returns.

Endogenous Labor Market Cycles

This paper shows that in a perfectly stationary physical environment of the labor market, moral hazard and competition in long-term contracts can generate cycles in the tightness of the market, which in turn may induce job creation and destruction, and two periods or much longer cycles in employment and output. We claim that the model may shed light on the unemployment volatility puzzle, which has inspired many discussions in the literature.

고유변동성 이상 현상의 강건성에 관한 검토

고유변동성 이상 현상의 강건성에 관한 검토

Abnormal Returns and Idiosyncratic Volatility Puzzle: Evidence from the Chinese Stock Market

ABSTRACTThe well-documented idiosyncratic volatility anomaly indicates the stocks with higher idiosyncratic volatility tend to have lower returns. Using different models to estimate abnormal return (i.e. alpha), we show that in the Chinese stock market, the IVOL-return relation is negative among stocks with negative abnormal returns but positive among stocks with positive abnormal returns. A possible explanation is that when we take the expected return as the reference point, different signs of abnormal returns can be viewed as gains and losses. Under prospect theory, distinct risk attitudes in the domain of gains and losses lead to different IVOL-return relations.

Idiosyncratic Volatility Puzzle: The Role of Assets' Interconnections

The paper investigates the determinants of the idiosyncratic volatility puzzle by allowing linkages across asset returns. The first contribution of the paper is to show that portfolios sorted by increasing indegree computed on the network based on Granger causality test have lower expected returns, not related to idiosyncratic volatility. Secondly, empirical evidence indicates that stocks with higher idiosyncratic volatility have the lower exposition on the indegree risk factor.

Parameter regimes in partial functional panel regression

A new partial functional linear regression model for panel data with time varying parameters is introduced. The parameter vector of the multivariate model component is allowed to be completely time varying while the function-valued parameter of the functional model component is assumed to change over K unknown parameter regimes. Consistency is derived for the suggested estimators and for the classification procedure used to detect the K unknown parameter regimes. Additionally, the convergence rates of the estimators are derived under a double asymptotic differentiating between asymptotic scenarios depending on the relative order of the panel dimensions n and T. The statistical model is motivated by a real data application considering the so-called “idiosyncratic volatility puzzle” using high frequency data from the S&P500.

Uniform Nonparametric Series Inference for Dependent Data with an Application to the Search and Matching Model

This paper concerns the uniform inference for nonparametric series estimators in time-series applications. We develop a strong approximation theory of sample averages of serially dependent random vectors with dimensions growing with the sample size. The strong approximation is first proved for heterogeneous martingale difference arrays and then extended to general mixingales via martingale approximation, readily accommodating a majority of applications in applied econometrics. We use these results to justify the asymptotic validity of a uniform confidence band for series estimators and show that it can also be used to conduct nonparametric specification test for conditional moment restrictions. The validity of high-dimensional heteroskedasticity and autocorrelation consistent (HAC) estimators is established for making feasible inference. The proposed method is broadly useful for forecast evaluation, empirical microstructure, dynamic stochastic equilibrium models and inference problems based on inter-section bounds. We demonstrate the empirical relevance of the proposed method by studying the Mortensen–Pissarides search and matching model for equilibrium unemployment, and shed new light on the unemployment volatility puzzle from an econometric perspective.

Lottery preferences and the idiosyncratic volatility puzzle

AbstractWe investigate the empirical implications of investors’ heterogeneous preferences for skewness with respect to the idiosyncratic volatility (IVOL) puzzle, that is, the negative correlation between IVOL and mean returns. We show that the IVOL puzzle is stronger: (1) within stocks held primarily by agents with a 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 could be a significant source of the IVOL puzzle.

Time variation of MAX-premium with market volatility: Evidence from Korean stock market

Korean stock market provides an ideal setting to examine the time-variation of the premium for stocks with a large price jump (MAX) because the market is mostly dominated by individual investors who are more prone to behavioral bias than institutional investors are. We find that investors' overpayment for stocks with high MAX is driven by increased salience of such stocks especially in the period with high uncertainty, measured by high local market volatility. We further find evidence that the negative relation between stock returns and idiosyncratic volatility, which is much stronger for stocks with high MAX than for stocks with low MAX, is more pronounced in the period with high market volatility. Overall, our findings emphasize that when investors have limited attention, attention-grabbing features of high MAX drives the time-variation in the degree of overpayment for stocks with high MAX and helps explain the idiosyncratic volatility puzzle.

The robust “maximum daily return effect as demand for lottery” and “idiosyncratic volatility puzzle”

Abstract We form indexes of overpriced and underpriced stocks by ranking stocks based on the disposition effect and anchoring bias. We document the negative relation between maximum daily return and future returns (MAX effect) is confined to overpriced stocks which make up about half the entire sample. We find that the average cross-sectional correlation between maximum daily return and idiosyncratic volatility is nearly 90%. Consistent with prior studies the idiosyncratic volatility puzzle disappears after controlling for the MAX effect. However, when using a sample with a $5 price breakpoint and controlling for overpriced stocks the idiosyncratic volatility puzzle and the MAX effect are economically and statistically significant.

The Idiosyncratic Volatility Puzzle and its Interplay with Sophisticated and Private Investors

We establish a direct link between the idiosyncratic volatility (IVol) puzzle and the behavior of sophisticated and private investors. To do so, we employ three option-based measures of informed trading and attention data from Google Trends. Our analyses show that the IVol puzzle is particularly driven by a group of overpriced stocks that can be identified by the use of sophisticated trader opinion. Since IVol is no perfect mispricing indicator, the option measures can help to distinguish high-IVol stocks that are overvalued from high-IVol stocks that are not exposed to mispricing. We link the origin of the anomaly to the trading activity of irrational private investors. This supports the intuitive idea that noise trading leads to mispricing which can be exploited by sophisticated investors at the option market.

Idiosyncratic volatility puzzle: influence of macro-finance factors

We analyze the cross-sectional relation between expected idiosyncratic volatility and stock returns. The expected idiosyncratic volatility is conditioned on macro-finance factors as well as traditional asset pricing factors. The macro-finance factors are constructed from a large set of macroeconomic and financial variables. Our results show that the negative relation between expected idiosyncratic volatility and stock returns reverses to a positive one when accounting for the macro-finance effects. Portfolio analysis shows that the positive relation is economically important. The relation between expected idiosyncratic volatility and returns is not affected by business cycle variations. The empirical results are highly robust.

Mispricing, Research Design Choices, and the Idiosyncratic Volatility Puzzle

Mispricing, Research Design Choices, and the Idiosyncratic Volatility Puzzle

Nonlinearity, Return Reversals, Information Flow, and the Idiosyncratic Volatility Puzzle

Nonlinearity, Return Reversals, Information Flow, and the Idiosyncratic Volatility Puzzle