Interest rates and risk premia in the stock market and in the foreign exchange market

This paper documents common empirical regularities in the foreign exchange market and in the US stock market. We find that increases in interest rates are associated with predictable increases in the volatility of returns in both markets, and that expected returns both in the stock market and in the foreign exchange market are negatively correlated with nominal interest rates.We show that not taking into account the time variation of second moments may seriously affect tests of asset pricing models. Using a numerical example based on the static capital asset pricing model, we are able to produce fluctuations in risk premia similar to those observed empirically. Finally we show that the overidentifying restrictions of the latent variable capital asset pricing model are not rejected when beats are assumed to be correlated with nominal interest rates.     

Linkages between Indian and US financial markets: impact of global financial crisis and Eurozone debt crisis

This paper examines inter-linkages between Indian and US equity, foreign exchange and money markets using the vector autoregressive-multivariate GARCH-BEKK framework. We investigate the impact of global financial crisis (GFC) and Eurozone debt crisis (EZDC) on the conditional volatility and conditional correlation estimates derived from the multivariate GARCH model for Indian and US financial markets. Our results indicate that there is significant bidirectional causality-in-mean between the Indian stock market returns and the Rs./USD market returns, and significant unidirectional causality-in-mean from the US stock market returns to the Indian stock market returns. As regards volatility spillovers, we find that volatility in the Indian stock market rises in response to domestic as well as US financial market shocks but Indian financial market shocks do not impact the US markets. Further, impact of the recent crisis episodes on the covariance matrix is found to be significant. We find that volatility in the Indian and US financial markets significantly amplified during GFC. The conditional correlations across asset markets were significantly accentuated in the wake of the two crisis episodes. The impact of GFC on cross-market conditional correlations is higher for majority of the asset market pairs in comparison to the EZDC.     

On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation

Recent studies in the empirical finance literature have reportedevidence of two types of asymmetries in the joint distributionof stock returns. The first is skewness in the distributionof individual stock returns. The second is an asymmetry in thedependence between stocks: stock returns appear to be more highlycorrelated during market downturns than during market upturns.In this article we examine the economic and statistical significanceof these asymmetries for asset allocation decisions in an out-of-samplesetting. We consider the problem of a constant relative riskaversion (CRRA) investor allocating wealth between the risk-freeasset, a small-cap portfolio, and a large-cap portfolio. Weuse models that can capture time-varying moments up to the fourthorder, and we use copula theory to construct models of the time-varyingdependence structure that allow for different dependence duringbear markets than bull markets. The importance of these twoasymmetries for asset allocation is assessed by comparing theperformance of a portfolio based on a normal distribution modelwith a portfolio based on a more flexible distribution model.For investors with no short-sales constraints, we find thatknowledge of higher moments and asymmetric dependence leadsto gains that are economically significant and statisticallysignificant in some cases. For short sales-constrained investorsthe gains are limited.     

Short-selling bans and institutional investors' herding behaviour: Evidence from the global financial crisis

The literature on short-selling restrictions focusses mainly on a ban's impact on market efficiency, liquidity and overpricing. Surprisingly, little is known about the effects of short-sale constraints on herd behaviour. Since institutional investors have come to dominate mature stock markets and rely extensively on short sales, constraining these traders may influence the asset pricing process. We investigate six stock markets that faced bans during the recent global financial crisis. Our empirical evidence shows that short-selling restrictions exhibit either no influence on herding formation or induce adverse herding. This implies a higher dispersion of returns around the market compared to rational asset pricing, which can be interpreted as an increase in uncertainty among stock market investors.     

Optimal investment under multi-factor stochastic volatility

We consider a model for multivariate intertemporal portfolio choice in complete and incomplete markets with a multi-factor stochastic covariance matrix of asset returns. The optimal investment strategies are derived in closed form. We estimate the model parameters and illustrate the optimal investment based on two stock indices: S&P500 and DAX. It is also shown that the model satisfies several stylized facts well known in the literature. We analyse the welfare losses due to suboptimal investment strategies and we find that investors who invest myopically, ignore derivative assets, model volatility by one factor and ignore stochastic covariance between asset returns can incur significant welfare losses.     

Firm characteristics and the impact of emerging market liberalizations

We provide a firm level analysis of the impact of capital market liberalization in 18 emerging markets. Consistent with models of international asset pricing, we find that firms’ stock returns increase during liberalization and that a majority of firms have lower mean returns and lower dividend yields after liberalization. We also find that emerging market firms have increased exposure to the world market and decreased exposure to the home market following liberalization. These changes in returns and exposures support the predictions of theoretical international asset pricing models. We also test and find support for the importance of size, local risk, foreign exchange risk, and cross-listing status in explaining the cross-section of changes in returns.     

Asset Price Dynamics and Infrequent Feedback Trades

This article combines the continuous arrival of information with the infrequency of trades, and investigates the effects on asset price dynamics of positive and negative-feedback trading. Specifically, we model an economy where stocks and bonds are traded by two types of agents: speculators who maximize expected utility, and feedback traders who mechanically respond to price changes and infrequently submit market orders. We show that positive-feedback strategies increase the volatility of stock returns, and the response of stock prices to dividend news. Conversely, the presence of negative-feedback traders makes stock returns less volatile, and prices less responsive to dividends.     

The relationship between stock returns and volatility in international stock markets

This study examines the relationship between expected stock returns and volatility in the 12 largest international stock markets during January 1980 to December 2001. Consistent with most previous studies, we find a positive but insignificant relationship during the sample period for the majority of the markets based on parametric EGARCH-M models. However, using a flexible semiparametric specification of conditional variance, we find evidence of a significant negative relationship between expected returns and volatility in 6 out of the 12 markets. The results lend some support to the recent claim [Bekaert, G., Wu, G., 2000. Asymmetric volatility and risk in equity markets. Review of Financial Studies 13, 1–42; Whitelaw, R., 2000. Stock market risk and return: an empirical equilibrium approach. Review of Financial Studies 13, 521–547] that stock market returns are negatively correlated with stock market volatility.     

How does trading volume affect financial return distributions?

We assess investors' reaction to new information arrivals in financial markets by examining the relationships between trading volume and the higher moments of returns in 18 international equity and currency markets. Our volume-volatility results support extant information theories and further contribute new evidence of cross market relations between volume and volatility. We also find that the direct impact of volume on the level of negative skewness is less significant for more diversified regional portfolios. Furthermore, the negative interaction between volume and kurtosis can be explained by the differences of opinion in financial markets. We observe stronger interdependence among higher moments in reaction to significant events, but the strength is dampened by trading volume. This result is consistent with trading volume being a source of heteroskedasticity in asset returns.     

Tests of the Relations Among Marketwide Factors,Firm-Specific Variables,and Stock Returns Using a Conditional Asset Pricing Model

In this article we generalize Harvey's (1989) empirical specification of conditional asset pricing models to allow for both time-varying covariances between stock returns and marketwide factors and time-varying reward-to-covariabilities. The model is then applied to examine the effects of firm size and book-to-market equity ratios. We find that the traditional asset pricing model with commonly used factors can only explain a small portion of the stock returns predicted by firm size and book-to-market equity ratios. The results indicate that allowing time-varying covariances and time-varying reward-to-covariabilities does little to salvage the traditional asset pricing models.     

The information content of implied skewness and kurtosis changes prior to earnings announcements for stock and option returns

We use option prices to examine whether changes in stock return skewness and kurtosis preceding earnings announcements provide information about subsequent stock and option returns. We demonstrate that changes in jump risk premiums can lead to changes in implied skewness and kurtosis and are also associated with the mean and variability of the stock price response to the earnings announcement. We find that changes in both moments have strong predictive power for future stock returns, even after controlling for implied volatility. Additionally, changes in both moments predict call returns, while put return predictability is primarily linked to changes in skewness.     

An International Asset Pricing Model with Time-Varying Hedging Risk

This paper employs a two-factor international equilibrium asset pricing model to examine the pricing relationships among the world's five largest equity markets. In addition to the traditional market factor premium, a hedging factor premium is included as the second factor to explain the relationship between risks and returns in the international stock markets. Moreover, a GARCH parameterization is adopted to characterize the general dynamics of the conditional second moments. The results suggest that the additional hedging risk premium is needed to explain rates of return on international equities. Furthermore, the restriction that the coefficient on the hedge-portfolio covariance is one smaller than the coefficient on the market-portfolio covariance can not be rejected. This suggests that the intertemporal asset pricing model proposed by Campbell (1993) can be used to explain the returns on the five largest stock market indices.     

Modeling the Conditional Covariance Between Stock and Bond Returns: A Multivariate GARCH Approach

To analyze the intertemporal interaction between the stock andbond market returns, we assume that the conditional covariancematrix follows a multivariate GARCH process. We allow for asymmetriceffects in conditional variances and covariances. Using dailydata, we find strong evidence of conditional heteroskedasticityin the covariance between stock and bond market returns. Theresults indicate that not only variances, but also covariancesrespond asymmetrically to return shocks. Bad news in the stockand bond market is typically followed by a higher conditionalcovariance than good news. Cross asymmetries, that is, asymmetriesfollowed from shocks of opposite signs, appear to be importantas well. Covariances between stock and bond returns tend tobe relatively low after bad news in the stock market and goodnews in the bond market. A financial application of our modelshows that optimal portfolio shares can be substantially affectedby asymmetries in covariances. Moreover, our results show sizablegains due to asymmetric volatility timing.     

Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility

This paper develops a two-step estimation methodology that allows us to apply catastrophe theory to stock market returns with time-varying volatility and to model stock market crashes. In the first step, we utilize high-frequency data to estimate daily realized volatility from returns. Then, we use stochastic cusp catastrophe theory on data normalized by the estimated volatility in the second step to study possible discontinuities in the markets. We support our methodology through simulations in which we discuss the importance of stochastic noise and volatility in a deterministic cusp catastrophe model. The methodology is empirically tested on nearly 27 years of US stock market returns covering several important recessions and crisis periods. While we find that the stock markets showed signs of bifurcation in the first half of the period, catastrophe theory was not able to confirm this behaviour in the second half. Translating the results, we find that the US stock market’s downturns were more likely to be driven by the endogenous market forces during the first half of the studied period, while during the second half of the period, exogenous forces seem to be driving the market’s instability. The results suggest that the proposed methodology provides an important shift in the application of catastrophe theory to stock markets.     

Stock Market Declines and Liquidity

Consistent with recent theoretical models where binding capital constraints lead to sudden liquidity dry-ups, we find that negative market returns decrease stock liquidity, especially during times of tightness in the funding market. The asymmetric effect of changes in aggregate asset values on liquidity and commonality in liquidity cannot be fully explained by changes in demand for liquidity or volatility effects. We document interindustry spillover effects in liquidity, which are likely to arise from capital constraints in the market making sector. We also find economically significant returns to supplying liquidity following periods of large drops in market valuations.     

Are short sellers positive feedback traders? Evidence from the global financial crisis

Short sellers are routinely blamed for destabilizing stock markets by exacerbating deviations from fundamental values. In response, regulators periodically impose short sale constraints aimed at preventing excessive stock market declines. One explanation is that policy makers regard short sellers as behaving like positive feedback traders. Relying on the theoretical model put forward by Sentana and Wadhwani (1992), which stresses the conditional nature of returns’ persistence, bans on selected financial stocks in six countries during the 2008/2009 global financial crisis are examined. These provide us with a setting to analyze the impact of short sale restrictions on feedback trading. Our findings suggest that, in the majority of markets examined, restrictions of this kind amplify positive feedback trading during periods of high volatility and, hence, contribute to stock market downturns. On balance then, short selling bans do not contribute to enhancing financial stability.     

Does Trading Volume Contain Information to Predict Stock Returns? Evidence from China's Stock Markets

This paper examines empirical contemporaneous and causal relationships between trading volume, stock returns and return volatility in China's four stock exchanges and across these markets. We find that trading volume does not Granger-cause stock market returns on each of the markets. As for the cross-market causal relationship in China's stock markets, there is evidence of a feedback relationship in returns between Shanghai A and Shenzhen B stocks, and between Shanghai B and Shenzhen B stocks. Shanghai B return helps predict the return of Shenzhen A stocks. Shanghai A volume Granger-causes return of Shenzhen B. Shenzhen B volume helps predict the return of Shanghai B stocks. This paper also investigates the causal relationship among these three variables between China's stock markets and the US stock market and between China and Hong Kong. We find that US return helps predict returns of Shanghai A and Shanghai B stocks. US and Hong Kong volumes do not Granger-cause either return or volatility in China's stock markets. In short, information contained in returns, volatility, and volume from financial markets in the US and Hong Kong has very weak predictive power for Chinese financial market variables.     

Liquidity in the cryptocurrency market and commonalities across anomalies

We examine how liquidity affects cryptocurrency market efficiency and study commonalities in anomaly performance in cryptocurrency markets. Based on the unique features of cryptocurrencies, we build a model with anonymous traders valuing cryptocurrencies as payments for goods and investment assets, and find that decreases in funding liquidity translate into lower asset liquidity in the cryptocurrency market. Empirically, we observe that many widely recognized stock market anomalies also exist in the cryptocurrency market, although some have opposite long and short legs. We also find evidence that a decrease in cryptocurrency liquidity enhances anomalous returns while preventing the cryptocurrency market from achieving efficiency.     

Testing stock market linkages for Poland and Hungary: A multivariate GARCH approach

This paper examines the linkages between the emerging stock markets in Warsaw and Budapest and the established markets in Frankfurt and the U.S. By using a four-variable asymmetric GARCH-BEKK model, we find evidence of returns and volatility spillovers from the developed to the emerging markets. However, as the estimated time-varying conditional covariances and the variance decompositions indicate limited interactions among the markets, the emerging markets are weakly linked to the developed markets. The implication is that foreign investors may benefit from the reduction of risk by adding the stocks in the emerging markets to their investment portfolio.     

信息不对称、过度自信与股价变动

信息传导的非同步和投资者情绪变化是股票市场的两个典型特征,前者会引发投资者之间出现信息不对称问题,后者主要体现为投资者过度自信,两者共同作用影响股票价格变动。本文将信息不对称和投资者过度自信情绪置于同一个分析框架,建立两阶段动态序贯定价理论模型研究现实市场上信息传导过程中股价变动的内在机制。结果表明:(1)面临新信息的进入,投资者对股票收益预期的调整与均衡价格之间具有正相关关系;(2)面临有利消息时,过度自信投资者比例越大,股票的均衡价格越高,投资收益将越低;面临不利消息时则相反;(3)随着过度自信投资者比例以及过度自信程度升高,市场风险溢价将下降;(4)投资者群体在信息传导过程中出现分化,对股价变动形成异质信念,未获取信息和获取信息但未出现过度自信的投资者认为股价被高估,获取信息且出现过度自信的投资者认为价格被低估,促使更多的交易,引发市场成交量和股价变动;(5)过度自信投资者比例与过度自信程度提高均会对市场效率产生正向影响,而对市场深度具有负向效应。最后,基于理论结果对非对称性和持续性等典型的市场波动性特征进行解释。