18 citations · 44 across the 6 of their papers we have counts for
7 papers
A Sparsity Algorithm with Applications to Corporate Credit Rating
Dan Wang, Zhi Chen, Ionut Florescu
In Artificial Intelligence, interpreting the results of a Machine Learning technique often termed as a black box is a difficult task. A counterfactual explanation of a particular "…
Is Image Encoding Beneficial for Deep Learning in Finance? An Analysis of Image Encoding Methods for the Application of Convolutional Neural Networks in Finance
Dan Wang, Tianrui Wang, Ionuţ Florescu
In 2012, SEC mandated all corporate filings for any company doing business in US be entered into the Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system. In this work…
A comparative study of forecasting Corporate Credit Ratings using Neural Networks, Support Vector Machines, and Decision Trees
Parisa Golbayani, Ionuţ Florescu, Rupak Chatterjee
Credit ratings are one of the primary keys that reflect the level of riskiness and reliability of corporations to meet their financial obligations. Rating agencies tend to take ext…
Application of Deep Neural Networks to assess corporate Credit Rating
Parisa Golbayani, Dan Wang, Ionut Florescu
Recent literature implements machine learning techniques to assess corporate credit rating based on financial statement reports. In this work, we analyze the performance of four ne…
SHIFT: A Highly Realistic Financial Market Simulation Platform
Thiago W. Alves, Ionut Florescu, George Calhoun +1
This paper presents a new financial market simulator that may be used as a tool in both industry and academia for research in market microstructure. It allows multiple automated tr…
Volatility Models Applied to Geophysics and High Frequency Financial Market Data
Maria C Mariani, Md Al Masum Bhuiyan, Osei K Tweneboah +2
This work is devoted to the study of modeling geophysical and financial time series. A class of volatility models with time-varying parameters is presented to forecast the volatili…