Trading volume,time-varying conditional volatility,and asymmetric volatility spillover in the Saudi stock market

Despite the well known importance of volatility–volume relationship, there is a paucity of research on this topic in emerging markets. We attempt to partially fill this gap by investigating volatility–volume relationship in the most important exchange market in the Middle East. We test the effect of trading volume on the persistence of the time-varying conditional volatility of returns in the Saudi stock market. Overall our results support the mixture of distribution hypothesis at the firm level. We also use two different proxies for information arrival, intra-day volatility, and overnight indicators. We find that these are good proxies for information and are important as contemporaneous volume in explaining conditional volatility. We also test for the volatility spillover direction between large- and small-cap portfolios. Our results show that the spillover effect is larger and statistically significant from large to small companies.     

Forecasting time-varying covariance with a range-based dynamic conditional correlation model

This paper proposes a range-based dynamic conditional correlation (DCC) model combined by the return-based DCC model and the conditional autoregressive range (CARR) model. The substantial gain in efficiency of volatility estimation can boost the accuracy for estimating time-varying covariances. As to the empirical study, we use the S&P 500 stock index and the 10-year treasury bond futures to examine both in-sample and out-of-sample results for six models, including MA100, EWMA_, CCC_, BEKK, return-based DCC, and range-based DCC. Of all the models considered, the range-based DCC model is largely supported in estimating and forecasting the covariance matrices.     

Testing conditional factor models

Using nonparametric techniques, we develop a methodology for estimating and testing conditional alphas and betas and long-run alphas and betas, which are the averages of conditional alphas and betas, respectively, across time. The estimators and tests can be implemented for a single asset or jointly across portfolios. The traditional Gibbons, Ross, and Shanken (1989) test arises as a special case of no time variation in the alphas and factor loadings and homoskedasticity. As applications of the methodology, we estimate conditional CAPM and multifactor models on book-to-market and momentum decile portfolios. We reject the null that long-run alphas are equal to zero even though there is substantial variation in the conditional factor loadings of these portfolios.     

Testing financial contagion on heteroskedastic asset returns in time-varying conditional correlation

We suggest that there is a significant relationship between cross-market comovement and time varying volatility. The time-varying component of cross-market dependence is attributed to the intertemporal risk-return adjustment by rational, risk-averse investors who systematically revise their expectation in response to changing volatility. To reflect the time-varying component of cross-market dependence, we propose a time-varying correlation test for contagion. Our results show that out of the countries reporting contagion evidence under the constant correlation test, none of the countries exhibits contagion evidence from the 1997 Asian crisis. We conclude that a high level of cross-market correlation during a crisis reported as contagion evidence under the standard constant correlation test is mostly due to the high level of cross-market co-movement resulting from the intertemporal risk-return adjustment.     

Testing conditional factor models: A nonparametric approach

Some recent studies of conditional factor models do not specify conditioning information but use data from small windows to estimate the time series of conditional alphas and betas. In this paper, we propose a nonparametric method using an optimal window to estimate time-varying coefficients. In addition, we offer two empirical tests of a conditional factor model. Using our new method, we examine the performance of the conditional CAPM and the conditional Fama-French three-factor model in explaining the return variations of portfolios sorted by size, book-to-market ratios, and past returns, for which recent literature has generated controversial results. We find that, although in general the conditional FF model outperforms the conditional CAPM, both models fail to explain well-known asset-pricing anomalies. Moreover, for both models, the failure is more pronounced for the equally-weighted portfolios than for the value-weighted ones.     

The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR

This paper investigates the role of high-order moments in the estimation of conditional value at risk (VaR). We use the skewed generalized t distribution (SGT) with time-varying parameters to provide an accurate characterization of the tails of the standardized return distribution. We allow the high-order moments of the SGT density to depend on the past information set, and hence relax the conventional assumption in conditional VaR calculation that the distribution of standardized returns is iid. The maximum likelihood estimates show that the time-varying conditional volatility, skewness, tail-thickness, and peakedness parameters of the SGT density are statistically significant. The in-sample and out-of-sample performance results indicate that the conditional SGT-GARCH approach with autoregressive conditional skewness and kurtosis provides very accurate and robust estimates of the actual VaR thresholds.     

The time-varying cost channel of monetary transmission

This paper studies the time-varying role of the cost channel of monetary transmission, i.e. the supply-side effect of monetary policy based on firms' costs of holding working capital. For that purpose, we provide rolling-window estimates of an augmented New Keynesian Phillips curve and show that the cost channel exhibits important time-varying dynamics. We find, as a general pattern, that the cost channel was most important in the pre-Volcker period and less important in the Volcker–Greenspan era. Recently, however, the cost channel regained importance. Since the cost channel is based on the transmission of policy impulses through bank lending, it is likely that the time-varying cost channel reflects the cyclical nature of financial frictions.     

Monetary policy shocks: : Testing identification conditions under time-varying conditional volatility

We propose an empirical procedure, which exploits the conditional heteroscedasticity of fundamental disturbances, to test the targeting and orthogonality restrictions imposed in the recent VAR literature to identify monetary policy shocks. Based on U.S. monthly data for the post-1982 period, we reject the non-borrowed-reserve and interest-rate targeting procedures. In contrast, we present evidence supporting targeting procedures implying more than one policy variable. We also always reject the orthogonality conditions between policy shocks and macroeconomic variables. We show that using invalid restrictions often produces misleading policy measures and dynamic responses. These results have important implications for the measurement of policy shocks and their temporal effects as well as for the estimation of the monetary authority's reaction function.     

The day-of-the-week effect in conditional correlation

The day-of-the-week effect in the first and second moments of the return distribution is a well researched area. However, not many studies have attempted to identify this effect in the comovement or correlation of the markets. This paper models the day-of-the-week effect in the returns and the conditional correlation for some Asia-Pacific equity markets. The paper finds a Monday, Wednesday and Friday effects in the returns for some of the markets. The effect is totally absent in the returns for Australia, Japan and Korea. For the fifteen conditional correlation series estimated, a predominant Tuesday effect is detected for five series. Three series exhibit a Monday effect. A Thursday effect is detected between the Singapore market and the markets of Australia, Hong Kong and Thailand. The paper finds no consistent day-of-the-week effect in the returns and the correlations for this region. JEL Classification G15 · G14     

Asymmetric predictability of conditional variances

We show that there is an asymmetry in the predictability ofthe volatilities of large versus small firms. Using both univariateand multivariate ARMA - GARCH-M parameterziations, we find thatvolatility surprises to large market value firms are importantto the future dynamics of their own returns as well as the returnsof small firms. Conversely, however, shocks to smaller firmshave no impact on the behavior of either the mean or the varianceof the returns of larger capitalization companies.     

The intertemporal capital asset pricing model with dynamic conditional correlations

The intertemporal capital asset pricing model of Merton (1973) is examined using the dynamic conditional correlation (DCC) model of Engle (2002). The mean-reverting DCC model is used to estimate a stock’s (portfolio’s) conditional covariance with the market and test whether the conditional covariance predicts time-variation in the stock’s (portfolio’s) expected return. The risk-aversion coefficient, restricted to be the same across assets in panel regression, is estimated to be between two and four and highly significant. The risk premium induced by the conditional covariation of assets with the market portfolio remains positive and significant after controlling for risk premia induced by conditional covariation with macroeconomic, financial, and volatility factors.     

A geometric treatment of time-varying volatilities

In this article, we propose a new framework for addressing multivariate time-varying volatilities. By employing methods of differential geometry, our model respects the geometric structure of the covariance space, i.e., symmetry and positive definiteness, in a way that is independent of any local coordinate parametrization. Its parsimonious specification makes it particularly suitable for large dimensional systems. Simulation studies suggest that our model embraces much of the nonlinear behaviour of the covariance dynamics. Applied to the US and the UK stock markets, the model performs well, especially when applied to risk measurement. In a broad context, our framework presents a new approach treating nonlinear properties observed in the financial market, and numerous areas of application can be further considered.     

The role of time-varying jump risk premia in pricing stock index options

This paper examines out-of-sample option pricing performances for the affine jump diffusion (AJD) models by using the S&P 500 stock index and its associated option contracts. In particular, we investigate the role of time-varying jump risk premia in the AJD specifications. Our empirical analysis shows strong evidence in favor of time-varying jump risk premia in pricing cross-sectional options. We also find that, during a period of low volatility, the role of jump risk premia becomes less pronounced, making the differences across pricing performances of the AJD models not as substantial as during a period of high volatility. This finding can possibly explain poor pricing perfomances of the sophisticated AJD models in some previous studies whose sample periods can be characterized by low volatility.     

The cross section of conditional mutual fund performance in European stock markets

This paper implements strategies that use macroeconomic variables to select European equity mutual funds, including Pan-European, country, and sector funds. We find that several macro-variables are useful in locating funds with future outperformance and that country-specific mutual funds provide the best opportunities for fund rotation strategies using macroeconomic information. Specifically, our baseline long-only strategies that exploit time-varying predictability provide four-factor alphas of 12–13% per year over the 1993–2008 period. Our study provides new evidence on the skills of local versus Pan-European asset managers, as well as how macroeconomic information can be used to locate and time these local fund manager skills.     

The impact of option introduction on the conditional return distribution of underlying securities

This paper combines several interesting econometric techniques to examine changes in the conditional return distribution of security returns following option introduction. An EGARCH model is used to characterize the return generating process. An intervention analysis is performed to determine whether the parameters of the EGARCH model shift following initial options listing. This paper finds that the conditional distribution of security returns is unaffected by option introduction. Estimation of a transfer function-noise model also shows that option introduction has no effect on conditional volatility.     

A general characterization of one factor affine term structure models

We give a complete characterization of affine term structure models based on a general nonnegative Markov short rate process. This applies to the classical CIR model but includes as well short rate processes with jumps. We provide a link to the theory of branching processes and show how CBI-processes naturally enter the field of term structure modelling. Using Markov semigroup theory we exploit the full structure behind an affine term structure model and provide a deeper understanding of some well-known properties of the CIR model. Based on these fundamental results we construct a new short rate model with jumps, which extends the CIR model and still gives closed form expressions for bond options. Manusript received: June 2000, final version received: October 2000     

The euro and pound volatility dynamics: An investigation from conditional jump process

This paper investigates the variations of the volatility of euro and pound after the introduction of euro. A GARJI model is employed to analyze the impact of the news arrivals on the exchange rate volatility. The results are robust to the data-splitting schemes and indicate: (1) the conditional variance of euro is larger than that of pound. (2) The stability of euro exchange rates has made progress in recent years, which is accomplished by the decreases in the jump innovations. This paper supports the arguments on the determinants of exchange rate stability claimed by Mundell (1998) and Mussa (2000).     

Market proxies and the conditional prediction of returns

Ex post efficient proxies for the market portfolio are tested against the equal weight proxy. The equal weight proxy outperforms the others when the criterion is squared error of conditional prediction of returns. The ex post efficient proxies use maximum likelihood estimates of return. Stein estimates of return will generally be different from the maximum likelihood estimates and they necessarily correspond to market proxies which are not efficient ex post. In other words, there generally exists a better, inefficient, proxy than an ex post efficient proxy when the criterion is squared error of conditional prediction of return.     

An empirical analysis of marginal conditional stochastic dominance

Stochastic dominance is a more general approach to expected utility maximization than the widely accepted mean–variance analysis. However, when applied to portfolios of assets, stochastic dominance rules become too complicated for meaningful empirical analysis, and, thus, its practical relevance has been difficult to establish. This paper develops a framework based on the concept of Marginal Conditional Stochastic Dominance (MCSD), introduced by Shalit and Yitzhaki (1994), to test for the first time the relationship between second order stochastic dominance (SSD) and stock returns. We find evidence that MCSD is a significant determinant of stock returns. Our results are robust with respect to the most popular pricing models.