Executive Summary

Sentiment, Signals and Surveillance stat bar

Capital markets have become flooded with a deep pool of audio and written content that can provide unique insights for investors. This "unstructured" data can be absorbed by traders, but to truly unlock the full value of this ocean of data, trading and investment firms need to investigate the potential arising from natural language processing (NLP).

Firms seeking to utilize NLP will need to have an understanding of its value, the challenges associated with an NLP implementation, and the current and potential future state of the technology. Regardless of whether NLP is being used to analyze news sentiment, derive trading signals or enhance surveillance capabilities, understanding the basis for the technology is an important step toward unlocking its potential. Our research aims to address these important aspects for firms seeking to initiate or expand their use of NLP.

Methodology

From January–April 2020, senior analysts at Greenwich Associates conducted in-depth interviews with 16 quantitativefocused investors in the United States, Europe and Asia-Pacific. Respondents were asked a series of questions investigating their usage of NLP, including vendors used, the evaluation process of new datasets, as well as factors weighed in the decision to buy vs. build NLP solutions regarding sentiment data.

Respondents