We study the year-after-year properties of three different portfolios traded in the Athens Stock Exchange (ASE) for the time period 1987–2004. We use the minimum spanning tree (MST) technique and the random matrix theory (RMT), which make it possible to examine at the same time the temporal...

I find a topological arrangement of assets traded in phonographic markets which has associated a meaningful economic taxonomy. I continue using the Minimal Spanning Tree and the correlations between assets, but now outside the stock markets. This is the first attempt to use these methods on...

We examine the impact, on commodity derivative markets, of two financial crises: the Subprime crisis and the bankruptcy of Lehman Brothers. These crises are "external" for commodity markets: they appeared in the financial sphere. Still, because now commodity markets are highly integrated,...

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 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,...

Using the eigenvalues and eigenvectors of correlations matrices of some of the main financial market indices in the world, we show that high volatility of markets is directly linked with strong correlations between them. This means that markets tend to behave as one during great crashes. In...

This paper proposes cost sensitive criteria for constructing classification rules by supervised learning methods. Reinterpreting established loss functions and considering those introduced by Buja, Stuetzle, et al. (2005) and Hand (2009), we identify criteria reflecting different degrees of...