Using a small sample of sentences, I test the performances of three models in predicting sentence sentiment (positive, neutral, or negative): a simple model based on a financial word list, a simple neural network model based on vector representations of words, and a sentence-based neural network...

A single hidden layer neural network can be trained to predict whether a stock will be in the top, middle, or bottom third of sample stocks based on its return over the next month based on return, trading volume, and volatility measures available at the end of this month. In my preliminary work...

We implement an efficient methodology for extracting themes from Securities Exchange Commission 13D filings using aspects of human‐assisted active learning and long short‐term memory (LSTM) neural networks. Sentences from the ‘Purpose of Transaction' section of each filing are extracted...

Purpose: The purpose of this paper is to trace the evolution of the Archway Investment Fund (AIF) at Bryant University from its founding in 2005 as a portfolio focused exclusively on US equities to a multi-asset program that incorporates US equities, non-US equities, equity ETFs, REITs,...