Volatility Puzzle Research Articles

“Superstitious” Investors

Abstract We reconsider the excess volatility puzzle through the lens of a model in which agents believe they can predict dividend growth when in fact they cannot. Besides excess volatility in the time series, the model explains the value premium, and the explanatory power of the value factor. In support of the model, we show that analysts’ earnings forecasts align with market valuation and that analysts are far more optimistic about growth stocks than they are about value stocks. Using both survey and price data, we show that the same mechanism can explain the excess returns earned by investing in high-interest rate currencies. JEL G12, G15, G41

A note on the labour market volatility puzzle: the role of endogenous participation

ABSTRACT This article studies the effects of endogenous participation of marginally attached workers on wage dynamics and hence on the unemployment fluctuations in a stylized search theoretic model. It shows that endogenous participation of these workers induces a countercyclical component in the wage equation under Nash bargaining. As a result, the elasticity of wage with respect to productivity becomes smaller and hence the model can generate larger unemployment fluctuations, compared to the textbook model. With careful calibration, I show that the model well captures the wage dynamics and can explain the unemployment and job openings volatility reasonably well.

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.

MIDAS and dividend growth predictability: Revisiting the excess volatility puzzle

AbstractWe examine dividend growth predictability and the excess volatility puzzle across a large sample of international equity markets using a mixed‐frequency data sampling (MIDAS) regression approach. We find that accounting for dividend seasonality under the MIDAS framework significantly improves dividend growth predictability compared to simple regressions with annually aggregated data. Moreover, variance bounds tests that allow for nonstationary dividends consistently fail to reject the market efficiency hypothesis across all countries. Our findings suggest that the common rejection of market efficiency in the literature is most likely driven by the annual aggregation of dividend data as well as by the assumption of stationary dividends.

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.

Is The Idiosyncratic Volatility Puzzle Driven By A Missing Factor?

Purpose - We investigate whether a potential missing pricing factor plays a significant role in the idiosyncratic volatility puzzle. Design/methodology/approach - We theoretically show how a missing pricing factor can affect the idiosyncratic volatility puzzle, and also show how to get around the problem empirically. We adopt the Fama-French five factor model for the estimation of the idiosyncratic risk and use randomly constructed portfolios as test assets. Findings - We find that a missing factor does not drive the idiosyncratic volatility puzzle. Thus, we conclude that the idiosyncratic volatility does affect the risk premium of its stock. Research implications or Originality - The Fama-French five factor model does a pretty good job in explaining the risk premiums of stocks, and it can be used to reliably estimate idiosyncratic risk of stocks.

Expected idiosyncratic entropy

PurposeWe propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.Design/methodology/approachWe estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.FindingsWe find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.Originality/valueWe propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

There is No Excess Volatility Puzzle

There is No Excess Volatility Puzzle

Dissecting the idiosyncratic volatility puzzle: A fundamental analysis approach

This paper argues fundamental information help resolve information uncertainty that leads to high idiosyncratic volatility premium. The IVOL-return relation is negative for stocks with poor fundamental strength but positive for stocks with strong fundamental strength. The arrival of fundamental news weakens the negative IVOL effect. Our findings are robust for alternative model specifications. Moreover, the negative IVOL effect dominates the positive IVOL effect due to arbitrage asymmetry that buying is easier than short selling stocks. Consistent with arbitrage asymmetry, the negative IVOL effect is stronger for stocks with low institutional ownership and following high investor sentiment. Overall, we provide a simple fundamental-based explanation for idiosyncratic volatility puzzle.

On the conditional performance of the IVOL anomaly

This paper proposes that the well-known idiosyncratic volatility (IVOL) puzzle is partly due to an overconditioning bias in IVOL estimates when there exists nonlinearity between stock and factor returns. We analytically derive the overconditioning bias when beta and IVOL are contemporaneously estimated using daily returns. To mitigate the estimation bias, we employ a conditional factor model, as in Avramov and Chordia (2006), to estimate systematic risk exposure and IVOL. Our empirical results show that the conditional IVOL estimates do not imply a negative return premium when firm fundamentals are used as conditioning variables, and the associated conditional factor-adjusted alpha is much smaller than the original IVOL puzzle. Our findings are robust in the U.S. and Chinese stock markets.

A closer look at the relationship between firm-specific return variation and stock returns

PurposePrior studies use two measures of firm-specific return variation (FSRV): idiosyncratic volatility in absolute and relative terms, the latter of which is also termed stock price nonsynchronicity. Whereas most research focuses on investigating the idiosyncratic volatility puzzle, the authors carry out comparison of these two measures and further investigate which of the two constituents of nonsynchronicity explain the association between FSRV and stock returns, emphasising the importance of assessing which component drives stock returns.Design/methodology/approachThe authors use the US individual stock returns from 1925 to 2016 and define the two measures of FRSV based on the Fama and French (1993) model. Specifically, the authors decompose the relative measure into two components: (i) absolute idiosyncratic volatility and (ii) systematic volatility. The authors conduct various tests based on high-minus-low, zero-investment quintile portfolio sorts and perform the Fama–MacBeth analysis by singling out each component.FindingsThe authors find a positive return on the portfolio sorted on relative idiosyncratic volatility or on systematic volatility, but find a negative return sorted on absolute idiosyncratic volatility. The results are robust after controlling for size, BM and other risk characteristics using a double-sorting approach. The Fama–MacBeth regression results show that a positive association between the relative measure and stock returns is driven primarily by the low-systematic-volatility anomaly across firms. The findings are robust to controlling for return residual momentum, skewness, jumps and information discreteness.Originality/valueExtant research posits the idiosyncratic volatility puzzle and the low-volatility anomaly. The authors emphasize the importance of integrating these two streams of research. This study enhances the understanding of the driving force underlying the relationship between FSRV and cross-sectional stock returns.

Research On the Impact of Margin Trading on The Stock Idiosyncratic Volatility

In classical asset pricing model, expected stock return is only determined by systematic risk, and idiosyncratic risk can be completely dispersed without asset pricing effect. However, the real world and the assumptions of classical asset pricing model are different, as idiosyncratic risk cannot be completely dispersed and has pricing effect. Recent studies found that the stock idiosyncratic volatility can actually predict stock return negatively, indicating the existence of the " Idiosyncratic volatility puzzle" in the Chinese stock market. There are constraints on margin trading in the Chinese stock market, which can affect investors' investment behavior and expectation of stock return. This article adopts difference-in-differences model and multivariable linear regression mode to test the impact of margin trading on idiosyncratic volatility, and further investigate the impact of margin trading on the " Idiosyncratic volatility puzzle ". The research results found that: In the process from the establishment of the margin trading system to the gradual expansion of underlying stocks, the impact of margin trading on idiosyncratic volatility has shifted from a positive impact to a negative impact. That is to say, margin trading has transitioned from initially increasing idiosyncratic volatility to later reducing idiosyncratic volatility, gradually playing a role in price discovery and reducing idiosyncratic risk in the stock market. The gradual improvement of the margin trading system is driving the development and maturity of the Chinese stock market.

Idiosyncratic volatility in commodity futures markets: measurement and puzzle

PurposeThis paper aims to propose an alternative method to measure idiosyncratic volatility and test whether the idiosyncratic volatility puzzle holds in commodity futures markets.Design/methodology/approachThis paper proposes a partially new measure of idiosyncratic volatility in commodity futures markets based on the Schwartz and Smith (2000) short-term/long-term model. This model enables us to capture systematic risks of commodity futures markets in a parsimonious way.FindingsUsing a sample of futures contracts for 20 commodities from 1973 to 2022, this paper demonstrates that idiosyncratic volatility is more significant than systematic volatility in commodity futures markets, and that the idiosyncratic volatility puzzle does not hold in these markets. This paper also performs robustness tests to investigate whether the puzzle holds during subsample periods when commodity markets are more volatile and find consistent results. This study highlights the differences between commodity futures markets and equity markets and emphasizes the importance of investigating idiosyncratic volatility in commodity futures markets.Originality/valueThe contributions of this paper are threefold. First, this paper contributes to the literature by focusing on the idiosyncratic volatility of commodity futures returns. Second, this paper constructs a partially new measure of idiosyncratic volatility in commodity futures markets. Finally, this paper also contributes to the literature on the idiosyncratic volatility puzzle and demonstrates that the puzzle may not exist in commodity futures markets.

The Causal Impact of Short-sale Constraints on the Idiosyncratic Volatility Puzzle

The Causal Impact of Short-sale Constraints on the Idiosyncratic Volatility Puzzle

Leasing and the Idiosyncratic Volatility Puzzle

Leasing and the Idiosyncratic Volatility Puzzle

Expected profitability, the 52-week high and the idiosyncratic volatility puzzle

We investigate the joint ability of fundamental-based and market-based news to explain the anomalous underperformance of stocks with high idiosyncratic volatility (high IVOL). An out-of-sample prediction of future profitability is adopted as a proxy for fundamental–based news while market-based news is represented by the 52-week high price ratio. A sample of UK stocks over the period January 1996 to December 2017 is analysed. The empirical results indicate that both the fundamental-based projected profitability and the 52-week high price ratio are important in explaining the IVOL anomaly. In contrast, individually, neither variable fully accounts for the anomaly. This relation is more pronounced following a period of high sentiment and during an upmarket. Further results suggest that underreaction lies at the heart of this explanation.

The excess volatility puzzle explained by financial noise amplification from endogenous feedbacks

The arguably most important paradox of financial economics—the excess volatility puzzle—first identified by Robert Shiller in 1981 states that asset prices fluctuate much more than information about their fundamental value. We show that this phenomenon is associated with an intrinsic propensity for financial markets to evolve towards instabilities. These properties, exemplified for two major financial markets, the foreign exchange and equity futures markets, can be expected to be generic in other complex systems where excess fluctuations result from the interplay between exogenous driving and endogenous feedback. Using an exact mapping of the key property (volatility/variance) of the price diffusion process onto that of a point process (arrival intensity of price changes), together with a self-excited epidemic model, we introduce a novel decomposition of the volatility of price fluctuations into an exogenous (i.e. efficient) component and an endogenous (i.e. inefficient) excess component. The endogenous excess volatility is found to be substantial, largely stable at longer time scales and thus provides a plausible explanation for the excess volatility puzzle. Our theory rationalises the remarkable fact that small stochastic exogenous fluctuations at the micro-scale of milliseconds to seconds are renormalised into long-term excess volatility with an amplification factor of around 5 for equity futures and 2 for exchange rates, in line with models including economic fundamentals explicitly.

Pricing Implications of Noise

Abstract We study the interaction between noisy demand and skewed asset payoffs. In our model, price as a function of quantities is convex in a neighborhood around zero if and only if skewness is positive. The combination of convexity and noise produces the idiosyncratic skewness effect, a documented negative relationship between an asset’s idiosyncratic skewness and its expected return. We further offer an explanation for the idiosyncratic volatility puzzle. Finally, our theory predicts that higher idiosyncratic skewness strengthens the idiosyncratic volatility effect (and vice versa). We find support for this prediction in the cross-section of stock returns.

Economic events and the volatility of government bill rates.

Many studies show that in many countries (especially the G7), volatility in government bill rates far exceeds that in consumption growth rates. This volatility puzzle cannot be predicted by traditional disaster models, in which rare economic disasters are defined as a peak-to-trough percent fall in consumption (or real per capita GDP) by a high threshold (≥10%). For this purpose, we extend the traditional definition of rare economic disasters and propose a novel asset pricing model that models both good and bad events. We define a bad (or good) event as a peak-to-trough absolute decline (or a trough-to-peak absolute rise) in consumption growth rates by a low threshold (<10%). Compared to traditional disaster models, our model contains three improvements. First, model good and bad events, not just bad ones (e.g., rare economic disasters). Second, the event's impact lasts for multiple periods rather than one period. Third, model non-rare economic events. We calibrate the parameters in our model to match the moments from U.S. asset return data. Simulation results indicate that the model can successfully predict the volatility of U.S. government bill rates higher than that of U.S. consumption growth rates.

Investor attention, analysts coverage and idiosyncratic volatility puzzle: based on behavioral perspective

PurposeConsidering the role of analysts in disseminating information, the paper explains the idiosyncratic volatility puzzle of China's stock market. As the largest developing country, China's research can provide meaningful reference for the research of financial markets in other new countries.Design/methodology/approachFrom the perspective of behavior, establishing a direct link between individual investor attention and stock price overvaluation.FindingsThe authors find that there is a significant idiosyncratic volatility puzzle in China's stock market. Due to the role of mispricing, individual investor attention significantly enhances the idiosyncratic volatility effect, that is, as individual investor attention increases, the greater the idiosyncratic volatility, the lower the expected return. Attention can explain the idiosyncratic volatility puzzle in China's stock market. In addition, due to the role of information production and dissemination, securities analysts can reduce the degree of market information asymmetry and enhance the transparency of market information.Originality/valueChina is the second largest economy in the world, and few scholars analyze it from the perspective of investors' attention. The authors believe this paper has the potential in contributing to the academia.