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

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;

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

Microfinance institutions: financial sustainability and efficiency

The main objective of this research is to analyse the relationship between financial sustainability and efficiency of Microfinance Institutions (MFIs) in terms of outreach to the poor as well as the relation between gender and repayment in microfinance. The sample used is composed of all MFIs in the globe as reported to MixMarket. Our study covers the period 2000-2010. The study also investigates whether the current global financial crisis has had any effects on the issues we study. Our dataset is organised as a panel dataset given that we have multiple observations on the same economic units and a number of periods over time. The estimation techniques are based on the fixed-effects (FE) and random-effects (RE) models. However we use the Hausman test in order to make a choice between FE and RE approaches. Our results show that FE models perform better that RE models through all the period of analysis. For the whole period of analysis results show that MFIs focusing on female clients, are characterized by a greater size of loans provided. On the other hand, we also find that the credit risk in microfinance institutions increases as the number of female clients raise

Cointegration and conditional correlations among German and Eastern Europe equity markets

This paper aims to examine the long term relationship between German and three Central and Eastern Europe (CEE) equity markets. Application of Johansen as well as Engle-Granger cointegration tests show that there is no long-term relationship among these markets while the Gregory-Hansen cointegration test rejects the null hypothesis of no cointegration with structural break. An additional objective is to capture the time-varying correlation among these markets through the dynamic conditional correlation models. Empirical results suggest that correlations increased after the accession of the CEE countries into the European Union.Equity markets; Cointegration; Dynamic conditional correlation models.

AOA estimation with EM lens-embedded massive arrays

Recently, EM lens-embedded massive array antennas have been proposed for next 5G mobile wireless communications, as the adoption of a lens allows to discriminate the AOA of signals in the analog domain, with the possibility to preserve the processing complexity lower with respect to traditional massive arrays. In fact, in such a way, complex ADC chains can be avoided and the number of required antennas can be decreased. By exploiting these advantages, in this paper we study the possibility to use a single EM lens massive array at mm-wave for the AOA estimation of the received signal. In this perspective, ML estimator and practical approaches, tailored for the considered scenario, are derived. Results, obtained for different number of antennas, confirm the possibility to achieve interesting AOA estimation performance with an extremely compact architecture

Weak-form market efficiency and calendar anomalies for Eastern Europe equity markets

In this paper we test the weak form of the efficient market hypothesis for Central and Eastern Europe (CEE) equity markets for the period 1999-2009. To test weak form efficiency in the markets this study uses, autocorrelation analysis, runs test, and variance ratio test. We find that stock markets of the Central and Eastern Europe do not follow a random walk process. This is an important finding for the CEE markets as an informed investor can identify mispriced assets in the markets by studying the past prices in these markets. We also test the presence of daily anomalies for the same group of stock markets using a basic model and a more advanced Generalized Autoregressive Conditional Heteroskedasticity in Mean (GARCH-M) model. Results indicate that day-of-the-week effect is not evident in most markets except for some. Overall results indicate that some of these markets are not weak form efficient and an informed investor can make abnormal profits by studying the past prices of the assets in these markets.Emerging stock markets, day-of-the-week effect , market efficiency, variance ratio test, GARCH-M.

Financial Development and Income Inequality: Evidence from African Countries

This paper present empirical evidence on how financial development is related to income distribution in a panel data set covering 22 African countries for the period between 1990 to 2004. A dynamic panel estimation technique (GMM) is employ and the findings indicate that income inequality decrease as economies develop their financial sector, which is consistent with the bulk of theoretical and empirical research. The result also confirm that educational attainment play a significant role in making income distribution more equal. We also find no evidence supporting the Greenwood-Jovanovic hypothesis of an inverted-U- shaped relationship between financial sector development and inequality.Financial development, income inequality, Africa G20, D63, 055