Improved testing for the efficiency of asset pricing theories in linear factor models

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 covariance matrix

Using Bayesian variable selection methods to choose style factors in global stock return models

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 evidence for global styles as useful explanatory factors, once country and sector have been accounted for

GARCH model with cross-sectional volatility; GARCHX models

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 models in forecasting

The disappearance of style in the US equity market

This paper investigates the modelling of style returns in the US and the returns to style "tilts" based on forecasts of enhanced future style returns. We use hidden Markov model to build our forecasts. Our finding that style returns are less forecastible in more recent years is consistent with the hypothesis that style returns are the result of anomalies rather than risk premia. The erosion of anomalous returns as public awareness of their presence is translated into strategies that arbitrage away the excess returns seems to be a hypothesis consistent with our modelling results

Modelling emerging market risk premia using higher moments

The purpose of this paper is to assess the incremental value of higher moments in modelling CAPMs of emerging markets. Whilst it is recognised 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 the data generating process of the individual emerging markets and use these to identify model parameters. We find some evidence that emerging markets are better explained with additional systematic risks such as co-skewness and co-kurtosis than the conventional mean-variance CAPM

Tracking error: ex-ante versus ex-post measures

In this paper we show that ex-ante and ex-post tracking errors must necessarily differ, since portfolio weights are ex-post stochastic in nature. In particular, ex-post tracking error is always larger than ex-ante tracking error. Our results imply that fund managers always have a higher ex-post tracking error than their planned tracking error, and thus unless our results are considered, any performance fee based on ex-post tracking error is unfavourable to fund managers

Market risk and the concept of fundamental volatility : measuring volatility across asset and derivative markets and testing for the impact of derivatives markets on financial markets

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 ‘filter’ out the signal in the volatility information. We decompose four FTSE100 stock index related volatilities into transitory noise and unobserved fundamental volatility. Our analysis is applied to the question as to whether derivative markets destabilise asset markets. We find that introducing European options reduces fundamental volatility, while transitory noise in the underlying and futures markets does not show significant changes. We conclude that, for the FTSE100 index, introducing a new options market has stabilised both the underlying market and existing derivative markets

The asset allocation decision in a loss aversion world

The purpose of this paper is to derive explicit formulae for the asset allocation decision for the loss aversion utility function proposed by Kahneman and Tuversky. We show that these utility functions exhibit constant absolute risk aversion. We also give analytic results which interpret the assumptions of risk-aversion with respect to gains but risk-a!ection with respect to losses in terms of changes of the optimal investment of equity when the probability that equity outperforms cash goes up. For the Knight, Satchell and Tran (1995) family of distributions, it is straightforward to derive closed form expressions for the optimal portfolio weights in all cases. Using UK and US data, we confirmed that the values of the parameters in the loss aversion function suggested by many previous studies are compatible with the observed proportions held in equity in both the UK and the US. The distributional assumptions are not innocuous. However, whilst modelling upside and downside returns by gamma distributions leads to plausible results, modelling upside and downside by truncated normals does not