There is growing concern that decision-making informed by machine learning (ML) algorithms may unfairly discriminate based on personal demographic attributes, such as race and gender. Scholars have responded by introducing numerous mathematical definitions of fairness to test the algorithm, many...

To address the rising concern that algorithmic decision-making may reinforce discriminatory biases, researchers have proposed many notions of fairness and corresponding mathematical formalizations. Each of these notions is often presented as a one-size-fits-all, absolute condition; however, in...

As peer-to-peer (P2P) lenders evaluate the potential risk of each loan application, they may rely on subjective judgement given qualitative information. Academics have found loan approval rates to be associated with the borrower's personality traits, social capital, and appearances. However, the...

We show how to execute a macro-hedge on a portfolio that depends on several risk factors in a one period static context. We show, by applying a orthogonalization procedure, that adding a hedging instrument with just one underlying reduces the risk of the portfolio along several dimensions but up...

Financial networks' study and understanding has become extremely important since the global financial meltdown in 2007-2009 when the inter-connectedness of institutions has surfaced as one of the major culprits for the magnitude of the distress. This paper aims at providing a new approach, based...

Missing data is a problem appearing ubiquitously across many fields and needs to be dealt with systematically. For multivariate time series data imputation can be a challenging problem. We consider the particular case of credit default swap time series, where missing data can pose a considerable...

The purpose of this paper is to show a novel approach to automatically generating Probabilistic Causal Models (Bayesian Networks (BN)) by applying Natural Language Processing (NLP) techniques to a corpus of millions of digitally published news articles in which views by different authors are...