Learn More
Finance, University of New South Wales and The Bank of England for their comments on earlier versions. We are grateful to two referees for their very constructive comments on the previous version of this paper. Abstract Herding is widely believed to be an important feature of financial markets and may be driven by a range of behavioural motivations that(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 log-ARFIMA based models as well as some simple forecasting rules. Overall, we find that a log-ARFIMA model forecasts best over short and long horizons. The authors are grateful to(More)
This paper applies Bayesian variable selection methods from the statistics literature to give guidance in the decision to include/omit factors in a global (linear factor) stock return model. Once one has accounted for country and sector, it is possible to see which style or styles best explains current asset returns. This study does not find compelling(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 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 tò®lterÕ out the signal in the volatility(More)