Soosung Hwang

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Market Stress and Herding* We propose a new approach to detecting and measuring herding which is based on the cross-sectional dispersion of the factor sensitivity of assets within a given market. This method enables us to evaluate if there is herding towards particular sectors or styles in the market including the market index itself and critically we can(More)
This study proposes a new measure and test of herding which is based on the crosssectional dispersion of factor sensitivity of assets within a given market. This new measure enables us to evaluate the directions towards which the market may be herding and separate these from movements in fundamentals. We apply the test to an analysis of the US, UK, and(More)
The purpose of this paper is to consider how to forecast implied volatility for a selection of UK companies with traded options on their stocks. We consider a range of GARCH and logARFIMA based models as well as some simple forecasting rules. Overall, we find that a logARFIMA model forecasts best over short and long horizons. Key-words : Implied Volatility,(More)
We investigates what is an appropriate level of investment management fees. We extend existing results and provide a several formula for the case of power utility and normal returns. Using the CRRA utility function with the range of the coefficient of the CRRA suggested by Mehra and Prescott (1985), we find that the value of information added by linear(More)
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 speci...c returns, which was suggested by Connor and Linton (2001) as an important component in individual asset volatility. Using UK and US data, we ...nd that daily(More)
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(More)
This paper proposes an unobserved fundamental component of volatility as a measure of risk. This concept of fundamental volatility may be more meaningful than the usual measures of volatility for market regulators. Fundamental volatility can be obtained using a stochastic volatility model, which allows us to `®lterÕ out the signal in the volatility(More)
We introduce SV models with Markov regime changing state equation (SVMRS) to investigate the important properties of volatility, high persistence and smoothness. With the quasi-ML approach proposed in our study, we showed that volatility is far less persistent and smooth than the GARCH or SV models suggest.