Although investing in environmental, social, and governance (ESG)-driven portfolios is
already a large and growing portion of global assets under management, applications of …

The authors propose an approach that combines modern machine learning techniques in
natural language processing with portfolio optimization to incorporate views of companies’ …

Although investing in Environment-Social-Governance (ESG) driven portfolios is already a
large and growing portion of global assets under management, applications of quantitative …

Motivated by studies of the interplay between environmental, social and governance (ESG)
factors and fund flows, the authors demonstrate an alternative approach for analyzing the …

The COVID-19 pandemic has unequivocally impacted nearly every individual, household,
business, and organization on a global scale, with wide-ranging consequences for which …

This article introduces a new financial time-series representation model called representations
of interrelated financial time series (RIFT). RIFT combines a novel pretraining task and …

Summarization of long-form text data is a problem especially pertinent in knowledge economy
jobs such as medicine and finance, that require continuously remaining informed on a …

The dominant approaches for financial portfolio construction are reliant on estimating sample
covariance and correlations matrices, which serve as an input into a number of classical …

This paper introduces a novel machine learning (ML) framework for causal discovery based
on recent advances in Large Language Models (LLMs) and discusses the applications of …

In Weak Supervision and Black–Litterman for Automated ESG Portfolio Construction , published
in the Summer 2021 issue of The Journal of Financial Data Science, Alik Sokolov of SR.…