Recently the topic of financial network dynamics has gained renewed interest from researchers in the field of empirical systemic risk measurements. We refer to this type of network analysis as information flow networks analysis (IFNA). This paper proposes a new method that applies Fisher information metric to the evolutionary dynamics of financial networks using IFNA. Our paper is the first to ...

In this paper, we propose a network performance/efficiency measure for the evaluation of financial networks with intermediation. The measure captures risk, transaction cost, price, transaction flow, revenue, and demand information in the context of the decision-makers’ behavior in multitiered financial networks that also allow for electronic transactions. The measure is then utilized to define ...

Neural networks demonstrate great potential for discovering non-linear relationships in time-series and extrapolating from them. Results of forecasting using financial data are particularly good [LapFar87, Schöne9O, ChaMeh92]. In contrast, traditional statistical methods are restrictive as they try to express these non-linear relationships as linear models. This thesis investigates the use of t...

Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models propos...

We consider how the introduction of centralized netting in financial networks affects total netted exposures between counterparties. In some cases there is a trade-off: centralized netting increases the expectation of net exposures, but reduces the variance. We show that the set of networks for which expected net exposures decreases is a strict subset of those for which the variance decreases, ...

Empirical evidence shows word-of-mouth communication has real effects on trading patterns in financial markets. On top of that, the social network through which the information conveys also plays a crucial role. We propose a framework that allows informed traders to directly and truthfully communicate information in four major social interaction structures represented by circle, tree, star and ...

When banks extend loans to each other, they generate a negative externality in the form of systemic risk. They create a network of interbank exposures by which they expose other banks to potential insolvency cascades. In this paper, we show how a regulator can use information about the financial network to devise a transactionspecific tax based on a network centrality measure that captures syst...