Soo Sung Hwang

The purpose of this paper is to assess the incremental value of higher moments in modelling capital asset pricing models (CAPMs) of emerging markets. Whilst it is recognized that emerging markets are unlikely to yield sensible results in a mean-variance world, the high skewness and kurtosis present in emerging markets returns make our assessment potentially interesting. Generalized method of moments (GMM) is used for the estimation. We also present new versions of higher-moment market models of

Abstract It is shown that the ML estimates of the popular GARCH(1,1) model are significantly negatively biased in small samples and that in many cases converged estimates are not possible with Bollerslev’s non-negativity conditions. Results also indicate that a high level of persistence in GARCH(1,1) models obtained using a large number of observations has autocorrelations lower than these ML estimates suggest in small samples. Considering the size of biases and convergence errors, it is propose

This study introduces GARCH models with cross-sectional market volatility, which we call GARCHX model. The cross-sectional market volatility is equlvalent to common heteroskedasticity in asset specific returns, which was suggested by Connor and Linton (2001) as an important component in individual asset volatility. Using UK and US data, we find that daily return volatility can be better specified with GARCHX models, but GARCHX models do not necessarily perform better than conventional GARCH mode

This study investigates the effects of varying sampling intervals on the long memory characteristics of certain stochastic processes. We find that although different sampling intervals do not affect the decay rate of discrete time long memory autocorrelation functions in large lags, the autocorrelation functions in short lags are affected significantly. The level of the autocorrelation functions moves upward for temporally aggregated processes and downward for systematically sampled processes, a

We investigate the dynamics of the momentum premium in the USA. The momentum premium is significantly positive only during certain periods, notably from the 1940s to the mid-1960s and from the mid-1970s to the late 1990s, and it has disappeared since the late 1990s. Our results further suggest that momentum profits have slowly disappeared since the early 1990s, in a process which was delayed by the occurrence of the high-tech and telecom stock bubble of the late 1990s. In particular, we estimate

We propose a new non-parametric measure of herding, beta herding, by incorporating the interaction between sentiment and herding in standard linear factor models. Contrary to common belief that herding is significant when the market is under stress, we demonstrate that beta herding arises when investors are confident regarding the outlook for the market, whether it is rising or falling, rather than when the market is in crisis. In fact our study suggests that crises appear to lead investors to s

This paper suggests a refinement of the standard T2 test statistic used in testing asset pricing theories in linear factor models. The test is designed to have improved power characteristics and to deal with the empirically important case where there are many more assets than time periods. This is necessary because the case of too few time periods invalidates the conventional T2. Furthermore, the test is shown to have reasonable power in cases where common factors are present in the residual cov

This paper applies the LINEX loss functions to volatility forecasting. We derive the optimal one-step-ahead LINEX forecast for various volatility models. Our results suggest that the LINEX loss function may give us better forecasts than conventional ones.