We explore the foreign exchange and stock market networks for 48 countries from 1999 to 2012 and propose a model, based on complex Hilbert principal component analysis, for extracting significant lead-lag relationships between these markets. The global set of countries, including large and small countries in Europe, the Americas, Asia, and the Middle East, is contrasted with the limited scopes ...

We study the application of Tuplix Calculus in modular financial budget design. We formalize organizational structure using financial transfer networks. We consider the notion of flux of money over a network, and a way to enforce the matching of influx and outflux for parts of a network. We exploit so-called signed attribute notation to make internal streams visible through encapsulations. Fina...

One of the biggest challenges facing financial research and trading organizations is how to well exploit unstructured financial information such as textual announcements. The automatic classification of this type of data poses many challenges for learning systems because the feature vector used to represent a document must capture some of the complex semantics of natural language. In this paper...

We present an Artificial Neural Network (ANN) approach to predict stock market indices, particularly with respect to the forecast of their trend movements up or down. Exploiting different Neural Networks architectures, we provide numerical analysis of concrete financial time series. In particular, after a brief résumé of the existing literature on the subject, we consider the Multi-layer Percep...

We propose a methodology for forecasting the systemic impact of financial institutions in interconnected systems. Utilizing a five-year sample including the 2008/9 financial crisis, we demonstrate how the approach can be used for timely systemic risk monitoring of large European banks and insurance companies. We predict firms’ systemic relevance as the marginal impact of individual downside ris...

We provide a framework for studying the relationship between the financial network architecture and the likelihood of systemic failures due to contagion of counterparty risk. We show that financial contagion exhibits a form of phase transition as interbank connections increase: as long as the magnitude and the number of negative shocks affecting financial institutions are sufficiently small, mo...

In this paper neural netw orks are applied to nancial data in order to predict the daily price of the nancial index LIFFE. Our atten tion is focused on the choice of the exogeneous variables and on the training of the netw ork itself. The rst problem is solved by using the pre-whitening method that provides information on which variables are the most relevan t for our prediction. The latter pro...

We discuss methods to quantitatively investigate the properties of correlation matrices of a financial system. Correlation matrices play an important role in portfolio optimization and in several other quantitative descriptions of asset price dynamics in financial markets. Specifically, we discuss how to define and obtain hierarchical trees, correlation-based trees and networks from a correlati...

If it is correct to generalize that, historically, Germany and Japan have had bank-oriented or bank-dominated financial systems, while Great Britain and the United States have had more marketoriented financial systems, then different network structures may have characterized these pairs’ financial systems. We explore that possibility, along with a few possible reasons that might account for suc...

Seasonal influenza is a major public health concern, and the first line of defense is the flu shot. Antigenic drifts and the high rate of influenza transmission require annual updates to the flu shot composition. The World Health Organization recommends which flu strains to include in the annual vaccine, based on surveillance and epidemiological analysis. There are two critical decisions regard...