A time-domain veto for binary inspirals search

We describe a test to distinguish between actual gravitational waves from binary inspiral and false noise triggers. The test operates in the time domain, and considers the time evolution of the correlator and its statistical distribution. It should distinguish true versus noisy events with the same signal-to-noise ratio and chi-square frequency distribution. A similar test has been applied to S1 LIGO data

Modelling and forecasting volatility of East Asian Newly Industrialized Countries and Japan stock markets with non-linear models

This paper explores the forecasting performances of several non-linear models, namely GARCH, EGARCH, APARCH used with three distributions, namely the Gaussian normal, the Student-t and Generalized Error Distribution (GED). In order to evaluate the performance of the competing models we used the standard loss functions that is the Root Mean Squared Error, Mean Absolute Error, Mean Absolute Percentage Error and the Theil Inequality Coefficient. Our result show that the asymmetric GARCH family models are generally the best for forecasting NICs indices. We also find that both Root Mean Squared Error and Mean Absolute Error forecast statistic measures tend to choose models that were estimated assuming the normal distribution, while the other two remaining forecast measures privilege models with t-student and GED distribution.GARCH; Volatility forecasting; forecast evaluation.

The economic effects of oil prices shocks on the UK manufacturing and services sector

This paper investigates the relationship between changes in oil prices and the UK’s manufacturing and services sector performances. Only a few studies have been conducted at the sector level: the goal of this paper is to contribute in that direction. After presenting review of existing literature about oil effects on the UK’s sectors of manufacturing and services, an econometric analysis is carried out. In a more detailed analysis, three sets of vector autoregressive (VAR) models are employed using linear and non-linear oil price specifications among several key macroeconomic variables. From the linear oil price specification VAR model, the impulse response function reveals that oil price movement causes positive effects in both the output of manufacturing and services sectors. The variance decomposition shows that oil prices are quite important as a cause of the variance of the UK services sector output, while they do not have such a large role in the variance of the UK’s manufacturing output. From the asymmetric specification, it has been found that positive oil price changes determine a consistent contraction in manufacturing output, while the services sector does not seem to be affected by increases. Alternatively, negative oil price changes, show that manufacturing output does not increase so much despite a decrease in oil prices. The services sector is much more affected by oil prices decreases than increases. Finally considering the net oil price increase (NOPI) specification, it has been found that the manufacturing sector is much more affected by oil price changes than the services sector.Oil shock; VAR; impulse response function; variance decomposition;

European Central Bank and Federal Reserve USA: monetary policy effects on the returns volatility of the Italian Stock Market Index Mibtel

What is the effect of either European Central Bank and Federal Reserve monetary policies on the Italian Index Mibtel? This paper aims to evaluate the impact of monetary policy announcements of the most important Central Banks on the volatility of returns which have been considered at both sectorial and sub-sectorial levels during the period 1999-2008. Using EGARCH models, this work shows that expansive monetary policies may influence stock market indexes much more than restrictive monetary policies. The difference among the two central bank monetary policies is that the ECB influences indexes much more than Fed monetary policy.Monetary Policies, Stock Returns, Volatility, EGARCH, European Central Bank, Federal Reserve USA

Volatility and Long Term Relations in Equity Markets: Empirical Evidence from Germany, Switzerland, and the UK

The aim of this paper is twofold. First it aims to compare several GARCH family models in order to model and forecast the conditional variance of German, Swiss, and UK stock market indexes. The main result is that all GARCH family models show evidence of asymmetric effects. Based on the “out of sample” forecasts I can say that for each market considered there is a model that will lead to better volatility forecasts. Secondly a long run relation between these markets was investigated using the cointegration methodology. Cointegration tests show that DAX30, FTSE100, and SMI indexes move together in the long term. The VECM model indicates a positive long run relation among these indexes, while the error correction terms indicate that the Swiss market is the initial receptor of external shocks. One of the main findings of this analysis is that although the UK, Switzerland and Germany do not share a common currency, the diversification benefits of investing in these countries could be very low given that their stock markets seem to move together in the lung term.Stock Returns; Volatility; GARCH models; Cointegration

A genetic algorithm to design Laue lenses with optimal performance for focusing hard X- and gamma-rays

In order to focus hard X- and gamma-rays it is possible to make use of a Laue lens as a concentrator. With this optical tool it would be possible to improve the detection of radiation for several applications, spanning from the observation of the most violent phenomena in the sky to nuclear medicine applications, for diagnostic and therapeutic purposes. A code named LaueGen, based on a genetic algorithm and aimed to designing optimized Laue lenses, has been implemented. The genetic algorithm was selected because the optimization of a Laue lens is a complex and discretized problem. The output of the code consists in the design of a Laue lens composed of diffracting crystals selected and arranged in such a way to maximize the performance of the lens. The code allows one to manage crystals of any material and crystallographic orientation. The program is structured in such a way that the user can control all the initial parameters of the lens. As a result, LaueGen is highly versatile and can be used for the design of very small lens, e.g. for nuclear medicine, to very large lens, e.g. for satellite-borne astrophysical missions.Comment: 18 pages, 4 figure