In this paper, we investigate the temporal dynamics of correlations between sentiment indices worldwide. Employing the tools of Random Matrix Theory (RMT) and Principal Component Analysis (PCA), our paper aims to extract latent information embedded in the interactions between economic and...

We propose a novel approach to investigate the synchronization of business cycles and we apply it to a Eurostat database of manufacturing industrial production time-series in the European Union (EU) over the 2000-2017 period. Our approach exploits Random Matrix Theory and extracts the latent...

We examined the determinants of the U.S. consumer sentiment by applying linear and nonlinear models. The data are monthly from 2009 to 2019, covering a large set of financial and nonfinancial variables related to the stock market, personal income, confidence, education, environment,...

We investigate the synchronization of Eurozone's government bond yields at different maturities. For this purpose, we combine principal component analysis with random matrix theory. We find that synchronization depends upon yields maturity. Short-term yields are not synchronized. Medium- and...

A parameterization that is a modified version of a previous work is proposed for the returns and correlation matrix of financial time series and its properties are studied. This parameterization allows easy introduction of non-stationarity and it shows several of the characteristics of the true,...

A financial market is an example of an adaptive complex network consisting of many interacting units. This network reflects market’s behavior. In this paper, we use Random Matrix Theory (RMT) notion for specifying the largest eigenvector of correlation matrix as the market mode of stock...

Coordination among many interdependent actors in complex product development projects is recognized as a key activity in organizational theory. It is well known that this coordination becomes progressively more difficult with project size, but we do not yet sufficiently understand whether this...

It is well known that non-normality plays an important role in asset and risk management. However, handling a large number of assets has long been a challenge. In this paper, we present a statistical technique that extends Principal Component Analysis to higher moments such as skewness and...

In this paper we apply Random Matrix Theory (RMT) to study daily return correlations of 83 companies that are part of the Chilean stock market during the period 2000 to 2011. We find that using RMT to identify statistically significant correlations within our sample of stocks significantly...