The Effect of US Stock Market Uncertainty on Emerging Market Returns

We investigate the effects of US stock market uncertainty (VIX) on the stock returns in Latin America and aggregate emerging markets before, during, and after the financial crisis. We find that increases in VIX lead to significant immediate and delayed declines in emerging market returns in all periods. However, changes in VIX explained a greater percentage of changes in emerging market returns during the financial crisis than in other periods. The higher US stock market uncertainty exerts a much stronger depressing effect on emerging market returns than their own-lagged and regional returns. Our risk transmission model suggests that a heightened US stock market uncertainty lowers emerging market returns by both reducing the mean returns and raising the variance of returns. The VIX fears raise the volatility of emerging market returns through generalized autoregressive conditional heteroskedasticity (GARCH)-type volatility transmission processes.     

“好”的不确定性、“坏”的不确定性与股票市场定价——基于中国股市高频数据分析

不确定性并不是都是“坏”的,“好”的不确定性也同样存在。本文采用Barndorff-Nielsen et al.(2010)提出的已实现半方差作为股票市场“好”的不确定性和“坏”的不确定性的代理指标,并在此基础上构建了相对符号变差(RSV),分析RSV对中国股市定价的影响。基于2007-2017年中国A股5分钟高频数据的实证研究发现:(1)与理论解释相一致,RSV与股票收益之间呈现负相关关系。无论是基于单变量分组、双变量分组还是公司层面的截面回归,这种影响在经济上和统计上都显著。(2)RSV是独立于已实现偏度的一个重要定价因子,且RSV对股票的定价能力强于已实现偏度的定价能力。(3)RSV对中国股市的影响是状态依存的,相对于经济景气程度高的状态,在经济景气程度低的状态下RSV定价影响更大。(4)基于RSV构建的投资组合的表现明显优于市场超额收益率组合、SMB组合和HML组合的表现。     

Market conditions and the optimal IPO allocation mechanism in China

This paper investigates the impact of market conditions of market return and volatility on choosing an IPO mechanism, using data of 942 IPOs on either Shanghai or Shenzhen stock exchanges of China from 1994 to 2003. We find, on average, the issuers are more likely to have their IPOs offering and listing during times of high market return and low market volatility. The fixed price procedure of the secondary market proportional offering is optimal in minimising the underpricing and cross-sectional variation of the first day returns. The bookbuilding procedure is optimal in counteracting adverse conditions created by low market profitability, high market volatility and uncertainty induced by the time ‘gap’ from offering to listing. By comparing the advantages between the secondary market proportional offering and bookbuilding procedures, the latter is preferred.     

Earnings quality and the heterogeneous relation between earnings and stock returns

We adopt a heterogeneous regime switching method to examine the informativeness of accounting earnings for stock returns. We identify two distinct time-series regimes in terms of the relation between earnings and returns. In the low volatility regime (typical of bull markets), earnings are moderately informative for stock returns. But in high volatility market conditions (typical of financial crisis), earnings are strongly related to returns. Our evidence suggests that earnings are more informative to investors when uncertainty and risk is high which is consistent with the idea that during market downturns investors rely more on fundamental information about the firm. Next, we identify groups of firms that follow similar regime dynamics. We find that the importance of accounting earnings for returns in each of the market regimes varies across firms: certain firms spend more time in a regime where their earnings are highly relevant to returns, and other firms spend more time in a regime where earnings are moderately relevant to returns. We also show that firms with poorer accrual quality have a greater probability of belonging to the high volatility regime.     

PRESIDENTIAL ELECTION UNCERTAINTY AND COMMON STOCK RETURNS IN THE UNITED STATES

There is substantial evidence on the influence of political outcomes on the business cycle and stock market. We further hypothesize that uncertainty about the outcome of a U.S. presidential election should be reflected in pre‐election common stock returns. Prior research pools returns based on the party of the winning candidate, assuming that the outcome of the election is known a priori. We use candidate preference (i.e., polling) data to construct a measure of election uncertainty. We find that if the election does not have a candidate with a dominant lead, stock market volatility (risk) and average returns rise.     

Stock Volatility during the Recent Financial Crisis

This paper uses monthly returns from 1802 to 2010, daily returns from 1885 to 2010, and intraday returns from 1982 to 2010 in the USA to show how stock volatility has changed over time. It also uses various measures of volatility implied by option prices to infer what the market was expecting to happen in the months following the financial crisis in late 2008. This episode was associated with historically high levels of stock market volatility, particularly among financial sector stocks, but the market did not expect volatility to remain high for long and it did not. This is in sharp contrast to the prolonged periods of high volatility during the Great Depression. Similar analysis of stock volatility in the United Kingdom and Japan reinforces the notion that the volatility seen in the 2008 crisis was relatively short‐lived. While there is a link between stock volatility and real economic activity, such as unemployment rates, it can be misleading.     

How does news sentiment affect the states of Japanese stock return volatility?

This paper examines the impact of public news sentiment on the volatility states of firm-level returns on the Japanese Stock market. We firstly adopt a novel Markov Regime Switching Long Memory GARCH (MRS-LMGARCH), which is employed to estimate the latent volatility states of intraday stock return. By using the RavenPack Dow Jones News Analytics database, we fit discrete choice models to investigate the impact of news sentiment on changes of volatility states of the constituent stocks in the TOPIX Core 30 Index. Our findings suggest that news occurrence and sentiment, especially those of macro-economic news, are a key factor that significantly drives the volatility state of Japanese stock returns. This provides essential information for traders of the Japanese stock market to optimize their trading strategies and risk management plans to combat volatility.     

Estimating the time Varying Components of international stock markets' risk

In this study an alternative approach for assessing securities' risk is applied. Various authors have argued that security returns are not homoskedastic but exhibit variation over time. They have observed that large changes tend be followed by more large changes in either direction, and so volatility must be predictably high after large changes. This phenomenon of securities' volatility, referred to as clustering, has important implications for security pricing and risk management. Among the most popular techniques currently used to capture the clustering effect and to forecast future volatilityare those belonging to the family of Autoregressive Conditional Heteroskedastic (ARCH) models. The main aim of this paper is to investigate whether such volatility modelling can be used to capture the time variation not only in the total risk of a security return but also its systematic and unsystematic components. Using weekly local stock market data, the time varying beta with the World Index has been estimated via a bivariate GARCH-M model. The GARCH-M parameterization used here is a dynamic specification of the SIM. The hypothesis that this dynamic specification holds cannot be rejected for 11 out of 13 local portfolios. The results provide evidence that both the systematic and the non-systematic counterparts are also changing over time. However, in some markets those risk changes may take place with some delay. This suggests that some of the low correlation coefficients computed for certain stock market returns may not be due to differences in business cycles among those countries, but may be caused by the non-synchronous response to world market developments. This finding should have important implications in many investment decisions such as portfolio selection, market timing and risk hedging.     

A behavioural explanation to the asymmetric volatility phenomenon: Evidence from market volatility index

This study examines how the behavioural explanations, in particular loss aversion, can be used to explain the asymmetric volatility phenomenon by investigating the relationship between stock market returns and changes in investor perceptions of risk measured by the volatility index. We study the behaviour of India volatility index vis‐à‐vis Hong Kong, Australia and UK volatility index, and provide a comprehensive comparative analysis. Using Bai‐Perron test, we identify structural breaks and volatility regimes in the time series of volatility index, and investigate the volatility index‐return relation during high, medium and low volatility periods. Regardless of volatility regimes, we find that volatility index moves in opposite direction in response to stock index returns, and contemporaneous return is the most dominating across the four markets. The negative relation is strongest for UK followed by Australia, Hong Kong and India. Second, volatility index reacts significantly different to positive and negative returns; negative return has higher impact on changes in volatility index than positive return across the markets over full‐sample and sub‐sample periods. The asymmetric effect is stronger in low volatility regime than in high and medium volatility periods for all the markets except UK. The strength of asymmetric effect is strongest for Hong Kong and weakest for India. Finally, negative returns have exponentially increasing effect and positive returns have exponentially decreasing effect on the changes in volatility index.     

Stock Market Volatility and Economic Factors

This paper examines the ability of rational economic factors to explain stock market volatility. A simple model of the economy under uncertainty identifies four determinants of stock market volatility: uncertainty about the price level, the riskless rate of interest, the risk premium on equity and the ratio of expected profits to expected revenues. In initial tests these variables have significant explanatory power and account for over 50 per cent of the variation in market volatility from 1929 to 1989. When the regression coefficients are allowed to vary over time using cluster regression, the four factors explain over 90 per cent of the variation in market volatility. The results are useful in explaining the past behavior of stock market volatility and in forecasting future volatility.     

Seasonality in stock returns and volatility: The Ramadan effect

Calendar anomalies in stock returns are well documented. Less obvious is the existence of seasonality in return volatility associated with moving calendar events such as the Muslim holy month of Ramadan. Using a GARCH specification and data for the Saudi Arabian stock market – now the largest stock market in the Muslim world – this paper documents a systematic pattern of decline in volatility during Ramadan, implying a predictable variation in the market price of risk. An examination of trading data shows that this anomaly appears to be consistent with a decline in trading activity during Ramadan. Evidence of systematic decline in volatility during Ramadan has significant implications for pricing of securities especially option-like products and asset allocation decisions by investors in the Islamic countries.     

Economic policy uncertainty and stock price crash risk

We examine the impact of economic policy uncertainty (EPU) on firm-specific crash risk. Based on a large sample of Chinese listed firms over the period from 2000 to 2017, we provide empirical evidence that firms are more likely to experience stock price crashes when EPU increases. Cross-sectionally analysis further reveals that the impact of EPU on stock price crash risk is stronger for firms whose returns are more sensitive to EPU. More specifically, young stocks, small stocks, high volatility stocks, and growth stocks, which have higher valuation uncertainty per se, are more sensitive to EPU and are more affected by EPU in terms of crash risk. We further show that EPU is significantly and positively associated with aggregated stock price crash risk at the market level.     

Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility

This paper investigates the impacts of News-based Implied Volatility (NVIX) on the long-term volatility of five cryptocurrencies using the GARCH-MIDAS model. We also evaluate the hedging effectiveness of cryptocurrencies against the S&P 500 index after incorporating NVIX. The empirical results show that NVIX has a negative and significant impact on the long-term volatility of five cryptocurrencies. The impact of NVIX remains robust even after controlling for Global Economic Policy Uncertainty (GEPU) and Realized Volatility (RV). The uncertainty derived from investor perception is more important than the uncertainty of economic fundamentals in predicting cryptocurrency volatility. The hedging effectiveness of Bitcoin against the S&P 500 index is improved due to consideration of NVIX. This paper provides new evidence concerning the impacts of uncertainty on the volatility of cryptocurrencies.     

Time-varying rare disaster risk and stock returns

This study provides empirical support for theoretical models that allow for time-varying rare disaster risk. Using a database of 447 international political crises during the period 1918-2006, we create a crisis index that shows substantial variation over time. Changes in this crisis index, our proxy for changes in perceived disaster probability, have a large impact on both the mean and volatility of world stock market returns. Crisis risk is positively correlated with the earnings-price ratio and the dividend yield. Cross-sectional tests also show that crisis risk is priced: Industries that are more crisis risk sensitive yield higher returns.     

Expected stock returns and volatility

This paper examines the relation between stock returns and stock market volatility. We find evidence that the expected market risk premium (the expected return on a stock portfolio minus the Treasury bill yield) is positively related to the predictable volatility of stock returns. There is also evidence that unexpected stock market returns are negatively related to the unexpected change in the volatility of stock returns. This negative relation provides indirect evidence of a positive relation between expected risk premiums and volatility.     

Modeling Time-Varying Volatility and Expected Returns: Evidence from the GCC and MENA Regions

The aim of this study is to investigate empirically the underlying nexus of stock market returns and volatility in the Gulf Cooperation Council (GCC) countries and Middle East and North Africa (MENA) region by using the GARCH-M model. We find that volatility is time-varying in all countries, which indicates substantial variation in the degree of risk across time. However, we do not find empirical support that this time-varying volatility significantly explains expected returns, except in the case of Kuwait, United Arab Emirates, and the MENA region portfolio. Our findings show that stock return volatility is negatively correlated with stock returns in these three markets under the assumption of investor risk aversion. This lends some support to the hypothesis of a volatility-driven negative relationship in the literature. The policy implications of our results are discussed.     

Measuring time-varying financial market integration: An unobserved components approach

We measure the time-varying degree of world stock market integration of five developed countries (Germany, France, UK, US, and Japan) over the period 1970:1–2011:10. Time-varying financial market integration of each country is measured through the conditional variances of the country-specific and common international risk premiums in equity excess returns. The country-specific and common risk premiums and their conditional variances are estimated from a latent factor decomposition through the use of state space methods that allow for GARCH errors. Our empirical results suggest that stock market integration has increased over the period 1970:1–2011:10 in all countries but Japan. And while there is a structural increase in stock market integration in four out of five countries, all countries also exhibit several shorter periods of disintegration (reversals), i.e. periods in which country-specific shocks play a more dominant role. Hence, stock market integration is measured as a dynamic process that is fluctuating in the short run while gradually increasing in the long run.     

Historic Changes in the High Yield Bond Market

In a history that now stretches about four decades, the high yield (HY) market has experienced growth in issuance and out‐standings that is remarkable both for its level (about 13% per annum, with HY bonds now accounting for about 25% of the total corporate bond market) and its cyclicality and sensitivity to the broad economy. The HY market has also experienced a notable shift away from B‐rated bonds and toward both lower‐risk Ba‐rated bonds and, to a lesser extent, more risky Caa‐rated bonds. Consistent with this development, studies of the performance of HY bonds show Ba‐rated bonds experiencing not only lower risk, but also higher returns than Caa‐rated bonds, which have produced surprisingly low average returns along with exceptionally high volatility. At the same time, studies of the correlation of HY bond returns with returns on other major asset classes report that all classes of HY bonds (but particularly the riskier B‐ and Caa‐rated bonds) have consistently stronger relationships with common stocks (especially small‐cap stocks) than with Treasuries and investment‐grade bonds. Analysis of the volatility of HY bond returns over time shows that during periods of stability in the economy and financial markets, the volatility of HY bond returns has been very similar to that of investment‐grade bonds. But during periods of political or economic uncertainty, the volatility of HY bonds has become two or three times that of investment‐grade bonds, approaching the volatility of common stocks. The main driver of the significant increase in the risk of the aggregate HY bond market during periods of uncertainty has been Caa‐rated bonds, whose risk pattern has been remarkably similar to that of small‐cap common stocks. Analysis of the credit risk spread (or CRS) series for both the composite HY bond market and each of its rating categories shows markedly non‐normal distributions with significant positive “skewness”—that is, periods of exceptionally high spreads (that are not counterbalanced by periods of exceptionally low spreads). The authors also report a consistently strong relationship of the CRS series with default rates and the general state of the economy, with major peaks occurring during or shortly after economic recessions. Near the end of 2008, however, there was a clear break in this relationship when the CRS reached an historic peak of 2,000 basis points, or more than five standard deviations above its long‐term mean, while the default rate (at 4%) was below its long‐term average. The authors offer two explanations for this break in CRS‐default rate relationship: the jump in the CRS caused by the extreme flight to quality and drop in liquidity for all risky securities during the second half of 2008; and the use of covenant‐lite securities and other sources of financial flexibility that appear to have enabled many HY issuers to defer defaults (if not avoid them entirely).     

Spreading the fear: The central role of CBOE VIX in global stock market uncertainty

Construction of efficient portfolios is reliant on understanding the correlation between assets. If correlations change markedly during times of economic turmoil then investors are exposed to greater risk at the most inopportune time. We examine the linkages between global stock markets using measures of market uncertainty (implied volatility). Using a sample of daily changes in G7 and BRIC implied volatility measures, over a 20-year sample period, we demonstrate that uncertainty in U.S. markets plays a pivotal role in global stock market uncertainty. “Fear is spread” across markets, as heightened uncertainty in U.S. markets is transmitted across global markets. Conversely, changes in global market uncertainty do not explain changes in U.S. market uncertainty. While there is a clear increase in connectedness during crisis periods, we observe a disparity in the way that inter-dependencies change during the two major economic crises in our sample period; the GFC (2007–2009) and COVID-pandemic (2020). The additional importance of US news largely drives our results during the GFC, while the effect is spread among several countries (particularly within European markets) during COVID.     

Mean reversion in Southeast Asian stock markets

This paper assesses the predictable component of South East Asian stock markets using a bootstrap resampling method to estimate the small sample distributions of variance ratio statistics. We find evidence of mean reversion in long horizon dollar adjusted excess returns. The robustness of the results is assessed by adjusting stock returns for potential time-varying expected returns and partial integration of these emerging markets into world capital markets. In all but one case, mean reversion is shown to be due to either time-variation of risk exposure and prices of risk or partial integration of the local market into world stock markets. These results clearly illustrate the dangers of testing market efficiency without carefully adjusting stock returns for time variation in expected returns and the partial integration of local markets into world markets.