An empirical approach to analysing the forward curve dynamics of energy futures is presented. For non-seasonal commodities—such as crude oil—the forward curve is well described by the first three principal components: the level, slope and curvature. A principal component indicator is...

The purpose of this study is to examine the determinants of the sovereign credit ratings provided by the three major rating agencies: Fitch Ratings, Moody's and Standard and Poor. A principal component analysis is employed in order to identify the common factors affecting these ratings. The...

Biplots display interunit distances, as well as variances and correlations of variables of large datasets. They can be used as a tool to reveal clustering, multicollinearity, and multivariate outliers, and to guide the interpretation of principal component analyses (PCA). This article describes...

This paper carries out an empirical assessment of the relationship between social capital and the quality of economic development in Italy. The analysis draws on a dataset collected by the author including about two hundred variables representing different aspects of economic development and...

This paper studies China’s stock market with respect to financial liberalization and international market interdependence after its accession to the WTO in 2001. Using the multi-factor R-squared measure, we derive a normalized index to measure the impact of financial liberalization policies on...

Using panel data of 19 OECD countries observed over 40 years and data on specific labor market reform episodes we conclude that labor market institutions matter for business cycle fluctuations. Spearman partial rank correlations reveal that more flexible institutions are associated with lower...

A method based on the classical principal component analysis leads to demonstrate that the role of co-authors should give a h-index measure to a group leader higher than usually accepted. The method rather easily gives what is usually searched for, i.e. an estimate of the role (or “weight”)...

Composite indicators as a tool for a ranking become more and more popular, because they illustrate a comprehensive view on a phenomenon that cannot be captured by only one single indicator. Indicators for Europe 2020 are set of indicators used for monitoring targets defined by the European...

Рассматривается задача анализа численности персонала и оценка эффективности его работы. Решение задачи базируется на построение «эталонной» модели...

In the symbolic data framework, probabilistic symbolic data are considered as those whose components are random variables with general probability distributions. Intervals (or uniform distributions), histograms (or empirical distributions), Gaussian distribution and Chi-squared distribution are...