The value premium and time-varying volatility

Numerous studies have documented the failure of the static and conditional capital asset pricing models to explain the difference in returns between value and growth stocks. This paper examines the post-1963 value premium by employing a model that captures the time-varying total risk of the value-minus-growth portfolios. Our results show that the time-series of value premia is strongly and positively correlated with its volatility. This conclusion is robust to the criterion used to sort stocks into value and growth portfolios and to the country under review (the US and the UK). Our paper is consistent with evidence on the possible role of idiosyncratic risk in explaining equity returns, and also with a separate strand of literature concerning the relative lack of reversibility of value firms' investment decisions.

A comparison of extreme value theory approaches for determining value at risk

This paper compares a number of different extreme value models for determining the value at risk (VaR) of three LIFFE futures contracts. A semi-nonparametric approach is also proposed, where the tail events are modeled using the generalised Pareto distribution, and normal market conditions are captured by the empirical distribution function. The value at risk estimates from this approach are compared with those of standard nonparametric extreme value tail estimation approaches, with a small sample bias-corrected extreme value approach, and with those calculated from bootstrapping the unconditional density and bootstrapping from a GARCH(1,1) model. The results indicate that, for a holdout sample, the proposed semi-nonparametric extreme value approach yields superior results to other methods, but the small sample tail index technique is also accurate.