The signalling channel of Central Bank interventions:modelling the Yen/US dollar exchange rate

This paper presents a theoretical framework analysing the signalling channel of exchange rate interventions as an informational trigger. We develop an implicit target zone framework with learning in order to model the signalling channel. The theoretical premise of the model is that interventions convey signals that communicate information about the exchange rate objectives of the central bank. The model is used to analyse the impact of Japanese FX interventions during the period 1999--2011 on the yen/US dollar dynamics

Value at Risk models with long memory features and their economic performance

We study alternative dynamics for Value at Risk (VaR) that incorporate a slow moving component and information on recent aggregate returns in established quantile (auto) regression models. These models are compared on their economic performance, and also on metrics of first-order importance such as violation ratios. By better economic performance, we mean that changes in the VaR forecasts should have a lower variance to reduce transaction costs and should lead to lower exceedance sizes without raising the average level of the VaR. We find that, in combination with a targeted estimation strategy, our proposed models lead to improved performance in both statistical and economic terms

The impact of news on measures of undiversifiable risk: evidence from the UK stock market

Using UK equity index data, this paper considers the impact of news on time varying measures of beta, the usual measure of undiversifiable risk. The empirical model implies that beta depends on news about the market and news about the sector. The asymmetric response of beta to news about the market is consistent across all sectors considered. Recent research is divided as to whether abnormalities in equity returns arise from changes in expected returns in an efficient market or over-reactions to new information. The evidence suggests that such abnormalities may be due to changes in expected returns caused by time-variation and asymmetry in beta

Peculiar Velocity Limits from Measurements of the Spectrum of the Sunyaev-Zel'dovich Effect in Six Clusters of Galaxies

We have made measurements of the Sunyaev-Zel'dovich (SZ) effect in six galaxy clusters at z > 0.2 using the Sunyaev-Zel'dovich Infrared Experiment (SuZIE II) in three frequency bands between 150 and 350 GHz. Simultaneous multi-frequency measurements have been used to distinguish between thermal and kinematic components of the SZ effect, and to significantly reduce the effects of variations in atmospheric emission which can otherwise dominate the noise. We have set limits to the peculiar velocities of each cluster with respect to the Hubble flow, and have used the cluster sample to set a 95% confidence limit of < 1410 km/s to the bulk flow of the intermediate-redshift universe in the direction of the CMB dipole. This is the first time that SZ measurements have been used to constrain bulk flows. We show that systematic uncertainties in peculiar velocity determinations from the SZ effect are likely to be dominated by submillimeter point sources and we discuss the level of this contamination.Comment: Submitted to Astrophysical Journal. 32 pages, 13 tables, 9 figure

Information and ambiguity: herd and contrarian behaviour in financial markets

“The final publication is available at Springer via http://dx.doi.org/10.1007/s11238-012-9334-3”The paper studies the impact of informational ambiguity on behalf of informed traders on history-dependent price behaviour in a model of sequential trading in nancial markets. Following Chateauneuf, Eichberger and Grant (2006), we use neo-additive capacities to model ambiguity. Such ambiguity and attitudes to it can engender herd and contrarian behaviour, and also cause the market to break down. The latter, herd and contrarian behaviour, can be reduced by the existence of a bid-ask spread.Research in part funded by ESRC grant RES-000-22-0650

Forecasting exchange rate volatility: GARCH models versus implied volatility forecasts

This study investigates whether different specifications of univariate GARCH models can usefully forecast volatility in the foreign exchange market. The study compares in-sample forecasts from symmetric and asymmetric GARCH models with the implied volatility derived from currency options for four dollar parities. The data set covers the period 2002 to 2012. We divide the data into two periods one for the period 2002 to 2007 which is characterised by low volatility and the other for the period 2008 to 2012 characterised by high volatility. The results of this paper reveal that the implied volatility forecasts significantly outperforms the three GARCH models in both low and high volatility periods. The results strongly suggest that the foreign exchange market efficiently prices in future volatility