What drives idiosyncratic volatility over time?

We document the patterns of market-wide and firm-specific volatility in the Portuguese stock market over the 1991–2005 period and test several explanations for the behavior of firm-level idiosyncratic volatility. Unlike previous studies we find no evidence of a statistically significant rise in firm-specific volatility. On the contrary, the ratio of firm-specific risk to total risk slightly decreases. We show that this result stems from new listings of large privatized companies that display lower firm-specific risk. Our findings are consistent with the idea that changes in idiosyncratic volatility are related to changes in the composition of the market.

S&P 500 volatility,volatility regimes,and economic uncertainty

We assess the relationship between regime-dependent volatility in S&P 500, economic policy uncertainty, the S&P 500 bull and bear sentiment spread (bb_sp), as well as the Chicago Board Options Exchange's VIX over the period 2000–2018. Our findings from two-covariate GARCH–MIDAS (GM) methodology, regime switching Markov Chain, and quantile regressions suggest that the association of realized volatility and sentiment varies across high- and low-volatility regimes and depends on investors’ sensitivity toward incidents of market uncertainties under these regimes. The findings suggest that these indicators may not be useful in volatility forecasting, especially under high-volatility regimes.     

The 2007–2009 financial crisis: changing market dynamics and the impact of credit supply and aggregate demand sensitivity

This article singles out the determinants of changes in US firms’ systematic risk and idiosyncratic return induced by the 2007–2009 financial crisis. After establishing that systematic risk changes during the crisis, the results show that higher operational and financial leverage coincide with an increase in systematic risk, while high cash availability is associated with a decrease in systematic risk. The crisis-induced idiosyncratic return worsens with increasing financial leverage, higher sensitivity to aggregate demand shocks and banking sector problems, and lower operational leverage. Additional results show that the aforementioned variables have economically large effects on firm performance during the crisis.     

公司特质波动在上升吗?——基于文献的述评

文章针对目前金融经济学的新兴研究领域——公司特质波动,从两个方面进行文献述评:特质波动测度和时间趋势。公司特质波动的测度方法主要依赖于资产定价模型的选择,因此,其误差根据方法的不同而各异;在时间趋势方面,众多学者对在美国及其他发达国家股市存在明显的特质波动上升趋势从各种角度予以解释;由于针对公司特质波动的研究刚刚展开,国内学者的研究成果较少,大部分仅对中国A股市场平均特质波动水平进行相关测度。在文献综述的基础上,文章提出进一步的研究展望,为今后研究提供借鉴和参考之用。     

R&D, patents and stock return volatility

Recent finance literature highlights the role of technological change in increasing firm specific (idiosyncratic) and aggregate stock return volatility, yet innovation data is not used in these analyses, leaving the direct relationship between innovation and stock return volatility untested. The paper investigates the relationship between volatility and innovation using firm level patent data. The analysis builds on the empirical work by Mazzucato (Rev Econ Dyn 5:318–345, 2002; J Evol Econ 13(5):491–512, 2003) where it is found that stock return volatility is highest during periods in the industry life-cycle when innovation is the most ‘radical’. In this paper we ask whether firms which invest more in innovation (more R&D and more patents) and/or which have more important innovations (patents with more citations) experience more volatility in their returns. Given that returns should in theory be higher, on average, for higher risk stocks, we also look at the effect of innovation on the level of returns. To take into account the competition between firms within industries, firm returns and volatility are measured relative to the industry average. We focus the analysis on firms in the pharmaceutical industry between 1974 and 1999. Results suggest that there is a positive and significant relationship between volatility, R&D intensity and the various patent related measures—especially when the innovation measures are filtered to distinguish the very innovative firms from the less innovate ones.     

Hedge fund return higher moments over the business cycle

We investigate how macroeconomic and financial uncertainty impacts the behavior of hedge fund strategy higher moments—i.e., co-skewness and co-kurtosis—and their respective cross-sectional dispersions. Consistent with theoretical models, we find that strategy managers trade off these two higher moments when building optimal portfolios. Moreover, these trade-offs depend on the kind of strategy. Our experiments show that the VIX and its conditional variance are the most important factors affecting higher moment risk in the hedge fund industry. They also reveal that the behavior of hedge fund strategies is very asymmetric depending on the phase of the business cycle. In contrast to studies which rely on the mean-variance setting, we find that systemic risk—as measured by the cross-sectional dispersions of higher moments—tends to decrease in the low regime. The indicators of market volatility play a decisive role to explain this decline in systemic risk.     

Volatility in productivity and the impact on unemployment

Volatility, and the uncertainty it creates, has long been recognized as a factor in economic decision making. Since hiring occurs before shocks to productivity are realized, firms’ investment in new labour is inherently risky. How large a role uncertainty in productivity has on aggregate unemployment is an empirical question that we attempt to answer. In this paper we measure the impact of higher volatility in labour productivity on the unemployment rate in the U.S. economy using a SVAR-GARCH-M model. Using the conditional standard deviation of productivity innovations from a multivariate GARCH model to measure uncertainty, we provide compelling evidence that unemployment increases with volatility. This estimated relative effect is actually larger for positive productivity shocks leading to unemployment declines only 60% as large as would have occurred using models that exclude uncertainty.     

Industry-level determinants of the linkage between credit and stock markets

This paper examines the relationship between US credit default swaps (CDS) and stock returns on an industry-wide basis across a number of investment horizons, with particular focus on the major determinants of such a relationship. Wavelet analysis is first applied to extract the CDS–stock wavelet correlation for each US industry. Then, Bayesian Model Averaging is employed to identify the key driving factors of the industry CDS–stock wavelet correlations at short- and long-term horizons. The empirical results indicate that the wavelet correlations between the industry CDS and stock returns are primarily negative over time and across time scales. Moreover, the CDS–stock correlation at longer horizons exhibits a much more stable pattern than its counterpart at shorter time frames. The results also demonstrate that the volatility of US Treasury and stock markets, as measured by the MOVE and VIX indices, respectively, the volatility of volatility, as captured by the VVIX index, and US economic policy uncertainty, as measured by the EPU index, are the most robust determinants of the correlation between CDS and stock returns at shorter and longer horizons for most US industries. In contrast, the Fama–French systematic equity factors exhibit a practically negligible explanatory power on the CDS–stock link.     

The determinants of firms’ global diversification decisions

Why do some firms choose to be ‘born global’ and become early internationalizing firms (EIFs) while others choose to be ‘born-again global’ and develop into late internationalizing firms (LIFs)? What are the main factors impacting a firm’s decision on the timing of global diversification? Based on the theories of diversification, this study examines the role of peer influence and desire for growth on the timing of a firm’s globalization decision. We further study the idiosyncratic risk and the adoption of technological innovation hypotheses on global diversification. Our results document that innovation efficiency strongly enhances EIFs’ propensity to global diversification. On the other hand, peer pressure and idiosyncratic risk level significantly influence EIFs not to globalize. In contrast, LIFs are positively influenced by their industry peers, showing how young and mature companies respond to the market competition in a different manner.     

IPO初始回报与创业投资参与的研究——基于我国创业板的实证研究

本文在论述国际学术界关于创业投资在企业IPO中作用理论研究的基础上,通过采用实证分析方法,对我国创业板上市的153家公司2007—2009年的数据进行研究,得出如下结论：企业IPO初始回报与是否有创业投资参与具有显著的正相关关系。同时,IPO初始回报与公司规模显著负相关,与股份发行比例显著负相关,与公司上市时年龄显著负相关,与企业上市日的上证指数收益率显著正相关,与净资产收益率显著负相关。     

IPOs’ signalling effects for speculative stock detection: evidence from the Stock Exchange of Thailand

Using a unique data set from the Thai stock market about the so-called, ‘Turnover List (TOL)’ of speculative stocks spanning the period 2004–2012, we investigate and provide new evidence on the relationship between IPOs’ pricing effects and subsequent classification as speculative investments. To be more specific, we examine the signalling effects for the detection of speculative stocks in relation to the degree of their prior IPOs underpricing. We also employ the market-feedback hypothesis to investigate this signalling process. Our results reveal a significant positive relationship between the magnitudes of the IPO underpricing and the probability of an IPO firm being classified officially as speculative on the TOL. Furthermore, we find that a 6-month abnormal return after going public increases the probability of speculative dealing in the IPOs. Next, we consider all listed firms in the Thai stock market and highlight the role of both abnormal return and trading volume in the transmission of probability for appearing on the TOL. In addition, we find that IPOs and non-dividend paying companies further increase the risk of being on the TOL.     

Time-varying relationship of news sentiment,implied volatility and stock returns

I examine the relationship between aggregate news sentiment, S&P 500 index (SPX) returns, and changes in the implied volatility index (VIX). I find a significant negative contemporaneous relationship between changes in VIX and both news sentiment and stock returns. This relationship is asymmetric whereby changes in VIX are larger following negative news and/or stock market declines. Vector autoregression (VAR) analysis of the dynamics and cross-dependencies between variables reveals a strong positive relationship between previous and current period changes in implied volatility and stock returns, while current period and lagged news sentiment has a significant positive (negative) relationship with stock returns (changes in VIX). I develop a simple trading strategy whereby high (low) levels of implied volatility signal attractive opportunities to take short (long) positions in the underlying index, while extremely negative (positive) news sentiment signals opportunities to enter short (long) index positions. The investor fear gauge (VIX) appears to perform better than news sentiment measures in forecasting future returns.     

The Idiosyncratic Risk-Return Relation: A Quantile Regression Approach Based on the Prospect Theory

Given some debate on the empirical idiosyncratic risk-return relation in the literature, we reexamine the relation using a quantile regression approach based on the prospect theory developed by Kahneman and Tversky [1979]. The quantile regression approach allows the coefficient on the independent variable (idiosyncratic risk) to vary across the distribution of the dependent variable (return). Our sample consists of stocks traded on the NYSE, AMEX, and NASDAQ during 1980–2010: 80,324 firm-year observations and 8,123 firms in total. The quantile regression results show that idiosyncratic risk is positively (negatively) related to returns at the high (low) quantiles of returns. The findings are consistent with the prospect theory that investors have a tendency to be less (more) willing to gamble with profits (losses). The results also demonstrate that the least-squares and least-sum optimization methods commonly used in prior research do not capture the relations between idiosyncratic risk and returns at the tail parts of the distribution of returns. Therefore, our empirical results provide new insights into the idiosyncratic risk-return relation in the literature.     

Risk aversion,innovation and performance in family firms

An analysis of the effect of family governance on the relationships among risk aversion, innovation and performance is the purpose of this study. Beyond the level of risk and innovation, we are interested in analysing the relationship between them and their influence on performance in family firms. Traditionally, risk-seeking has been associated with innovation and performance. Our results confirm both components to be independent and, furthermore, show relationships with opposite signs as expected in the literature. In a sample of 500 firms, the results confirm an idiosyncratic behaviour in family firms; innovation contributes to performance to a higher extent in family firms, and at the same time, risk aversion is positively associated with performance only in non-family firms.     

Idiosyncratic volatility and the cross-section of anomaly returns: is risk your Ally?

Due to arbitrage risk asymmetries, the relationship between idiosyncratic risk and expected returns is positive (negative) among overpriced (underpriced) stocks. We offer a new active anomaly-selection strategy that capitalizes on this effect. To this end, we consider 11 equity anomalies in the U.S. market for years 1963–2016. Buying (selling) long (short) legs of the anomaly portfolios with the highest idiosyncratic volatility produces monthly abnormal returns ranging from 0.97% to 1.14% per month, outperforming a naive benchmark that equally weights all the anomalies by 45–70%. The effect cannot be subsumed by any other established anomaly-return predictor, such as momentum or seasonality. The results are robust to many considerations, including different numbers of anomalies in the portfolios, subperiod analysis, as well as estimation of idiosyncratic risk from the alternative models and throughout different periods.     

Law environment,government regulation and implicit contract: Empirical evidence from the scandals of China’s listed companies

In China’s transitional economy, government regulation could be a substitute for the lack of law mechanism and regulator’s power could spill over into other areas not regulated. Then, theoretically it could construct implicit contracts. For example, China Securities Regulatory Commission (CSRC) has the rights to choose initial public offering(IPO) firms among applicants. It might construct implicit contracts between CSRC and local governments if the former consider the frequency and the severity of the scandals among different areas. Local governments could make decisions on whether and how much to implement the implicit contracts.     

Idiosyncratic Uncertainty and Firm Investment

We test the impact of idiosyncratic demand uncertainty on investment using a panel of 82 Dutch listed manufacturing firms in the period 1984–1995. The measure of uncertainty is constructed by estimating a state space model at the firm level to isolate idiosyncratic uncertainty from other unobserved components. Generalised Method of Moments estimators show that demand uncertainty, which is specific to the firm, depresses firm investment. More interestingly, we find that idiosyncratic uncertainty is more important in explaining firm investment than total uncertainty that mixes idiosyncratic uncertainty with other sources of uncertainty.     

Noise traders and smart money: Evidence from online searches

Traditional finance theory considers that the impact of noise traders' attention on asset prices is offset by attention from smart investors. This paper uses online search data to study the influence of noise traders and smart investors on stock returns and volatility. Adopting an original approach, we construct a proxy for smart investor attention based on investors' online search behavior provided by Wikipedia Page Traffic. We combine this new measure with a standard measure of noise traders' attention as proxied by Google Search Volume Index. We show for a sample of 87 French firms over the period 2008–2018 that only noise traders' attention influences stock returns. Noise traders' attention increases volatility by creating an extra risk that is priced into the market. Conversely, smart investors' attention decreases volatility because their presence stabilizes stock prices by reducing uncertainty. Our empirical results support a behavioral explanation of stock prices.     

The risk-return relation and VIX: evidence from the S&P 500

A significantly positive risk-return relation for the S&P 500 market index is detected if the squared implied volatility index (VIX) is allowed for as an exogenous variable in the conditional variance equation of the parsimonious GARCH(1,1) model. This result holds for both daily and weekly observations, for extended conditional mean and variance specifications, and is robust to sub-samples. We show that the conditional variance obtained from the GARCH model with VIX has better predictive ability for realized volatility than the conditional variance from GARCH without VIX and VIX itself, thereby documenting an important information content of VIX for conditional variance. The results are interpreted as evidence that adding VIX squared in the conditional variance equation yields a better measure of conditional variance which, subsequently, uncovers a strong risk-return relation.