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Abstract:
This paper proposes a simplified multivariate GARCH model that involves the estimation of only univariate GARCH models, both for the individual return series and for the sum and difference of each pair of series. The covariance between each pair of return series is then imputed from these variance estimates. The model that we propose is considerably easier to estimate than existing multivariate GARCH models and does not suffer from the convergence problems that characterize many of these models. Moreover, the model can be easily extended to include more complex dynamics or alternative forms of the GARCH specification. We use the simplified multivariate GARCH model to estimate the minimum-variance hedge ratio for the FTSE 100 index portfolio, hedged using index futures, and compare it to four of the most widely used multivariate GARCH models. The simplified multivariate GARCH model performs at least as well as the other models that we consider, and in some cases better than them.

Multivariate GARCH, hedging, minimum-variance hedge ratio, FTSE 100 index

Abstract:
Despite significant theoretical and empirical developments in the capital structure literature, the trade-off theory and the related question of the optimality of the gearing ratio remain the subject of intense debate. The pecking order theory emerged to directly contrast with the implications of the trade-off theory. This paper investigates whether industry-optimal gearing ratio targeting behavior arises in the long run while a hierarchy of financing (or pecking order) arises in the short run. The relationship between components of common corporate gearing ratios is investigated using a Johansen co-integration methodology. Evidence of target adjustment is found, though only with respect to certain gearing ratios. Further, adjustment speed coefficients of the error correction representation imply that UK firms close the majority of any deviation from the target with retained earnings rather than external financing. However, while firms in mature industries appear to close the second largest part of any deviation with debt, firms in younger industries appear to close the second largest part of any deviation with equity. A general version of the pecking order theory can reconcile these results.

Capital Structure, Trade-off, Pecking Order, Optimal Dynamic Debt Equity Choice, UK Quoted Firms, Cointegration of Capital Structure Ratio Components

Abstract:
In this paper, we document a very strong day-of-the-month effect in the performance of momentum strategies in the foreign exchange market. We show that this seasonality in trading strategy performance is attributable to seasonality in the conditional volatility of foreign exchange returns, and in the volatility of conditional volatility. Indeed a two-factor model employing conditional volatility and the volatility of conditional volatility explains as much as 70 percent of the intra-month variation in the Sharpe ratio. We further show that the seasonality in volatility is in turn closely linked to the pattern of US macroeconomic news announcements, which tend to be clustered around certain days of the month.

Momentum, Moving average rules, Seasonality, Conditional volatility

Abstract:
Despite much theoretical progress, Rajan and Zingales (1995) claim that "very little is known about the empirical relevance of the different capital structure theories". Indeed, the more recent developments such as Pecking Order Theory and Market Timing contradict the predictions of Trade-Off Theory. One of the aims of this paper is to test the relevance in the UK of a more general model where firms have long-run target gearing ratios but in the short run they might follow a pecking order to financing or time their equity issues when markets are buoyant. The relationship between measures of corporate capital structure is investigated using the unit root and cointegration tests. Evidence of long-run target adjustment is indeed found though, only with respect to certain ratios. Furthermore, adjustment speed coefficients imply that UK quoted firms prefer internal financing and when external funds are required debt is preferred to equity.

Capital Structure, Target Adjustment, Trade off Theory, Pecking Order Theory

Abstract:
Models of the time-varying conditional minimum-variance hedge ratio (MVHR) typically do not provide a significant improvement in terms of hedging performance over the unconditional MVHR model. In view of the widely documented success of conditional volatility models (on which models of the conditional MVHR are usually based), this is somewhat surprising. In this paper, using the recently developed realized beta framework of Andersen, Bollerslev, Diebold and Wu (2005), we explore the reasons for this finding. We firstly show that the reduction in hedged portfolio variance that conditional MVHR models offer falls far short of the ex post maximal reduction in variance obtained using an estimate of the unobserved 'integrated' MVHR. We investigate the statistical properties of the forecasts of conditional MVHR models and show that while they do contain significant information about the integrated MVHR, they are systematically biased and inefficient. However, correcting for this bias and inefficiency does little to improve their hedging performance, suggesting that their poor performance is more likely to be attributable to the unpredictability of the integrated MVHR.

Minimum-variance hedge ratio, Realized beta, Multivariate conditional volatility models, Bias correction

Abstract:
Value-at-Risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a new simple approach to estimation of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with time-varying higher moments. We allow the first four moments of the GCE to depend on past information, which leads to a more accurate approximation of the tails of the distribution. The results unambiguously show that our GCE-based VaR forecasts provide accurate and robust estimates of the realised VaR, outperforming those generated by the constant-higher-moments models.

Value-at-Risk (VaR) estimation, Time-varying variance, skewness, kurtosis, Gram-Charlier series expansion

Abstract:
This paper proposes a simplified multivariate GARCH model (the S-GARCH model) that involves the estimation of only univariate GARCH models, both for the individual return series and for the sum and difference of each pair of series. The covariance between each pair of return series is then imputed from these variance estimates. The model that we propose is considerably easier to estimate than existing multivariate GARCH models and does not suffer from the convergence problems that characterize many of these models. Moreover, the model can be easily extended to include more complex dynamics or alternative forms of the GARCH specification. We use the S-GARCH model to estimate the minimum-variance hedge ratio for the FTSE 100 index portfolio, hedged using index futures, and compare it to four of the most widely used multivariate GARCH models. Using both statistical and economic evaluation criteria, we find that the S-GARCH model performs at least as well as the other models that we consider, and in some cases better than them.

Multivariate GARCH, Hedging, Minimum-variance hedge ratio, FTSE 100 index