OpenEDGAR is an open source Python framework designed to rapidly construct research databases based on the Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system operated by the US Securities and Exchange Commission (SEC). OpenEDGAR is built on the Django application framework,...

LexNLP is an open source Python package focused on natural language processing and machine learning for legal and regulatory text. The package includes functionality to (i) segment documents, (ii) identify key text such as titles and section headings, (iii) extract over eighteen types of...

While permutation tests and bootstraps have very wide-ranging application, both share a common potential drawback: as data-intensive resampling methods, both can be runtime prohibitive when applied to large or even medium-sized data samples drawn from large datasets. The data explosion over the...

In this paper we present an option pricing model based on the assumption that the underlying asset price is an exponential Mixed Tempered Stable Lévy process. We also introduce a new R package called PricingMixedTS that allows the user to calibrate this model using procedures based on loss or...

We develop a Bayesian methodology for systemic risk assessment in financial networks such as the interbank market. Nodes represent participants in the network and weighted directed edges represent liabilities. Often, for every participant, only the total liabilities and total assets within this...

This paper will give a brief overview of the work of introducing machine learning intelligence in the Kineta e-markets system, to facilitate auto-hedging, smart price engine algorithms and proprietary automatic positioning within the foreign exchange market. In this paper we will give a brief...

Italian Abstract: Il presente saggio intende mettere a fuoco il fenomeno del cloud computing, tentando di setacciare i frammenti normativi dispersi in un fiume di norme difficilmente componibili a sistema, al fine di ricostruire il quadro giuridico vigente in materia. La certezza e la...

​In this paper discrete wavelet filtering techniques are applied to decompose macroeconomic data so that they can be simultaneously analyzed in both the time and frequency domains. The MODWT (Maximal Overlap Discrete Wavelet Transform) is applied to U.S. quarterly GDP data from 1947-2012 to...

This paper develops a wavelet-based control system model that can be used to simulate fiscal and monetary strategies in an open economy context in the time-frequency domain. As the emphasis on real exchange rate stability is increased, the model simulates the effects on both the aggregate and...

A large variety of information flows through a financial services firm. This information can come from a variety of sources, both external and internal. It is a significant task to reconcile the data from multiple sources and ensure that it is correct before being used within the firm.In this...