At Probability & Partners, we see more and more asset managers willing to incorporate sentiment-based signals into their investment strategies. However, developing sentiment-based investment strategies, or incorporating sentiment in your existing investment process, is a non-trivial and multi-step task.

Steps towards incorporating sentiment in the current investment process

First, one must define the framework in which sentiment signals will be used and their purpose (for instance, alpha generation or risk reduction). Then, news and/or social media content must be collected and put through Natural Language Processing machinery in order to quantify the sentiment and other characteristics. Next, it is necessary to process the sentiment numbers by, for instance, de-noising and aggregating them through time and over the investment universe. Finally, the resulting sentiment indicators should be included in an appropriate way into quantitative or blended investment strategies, which ideally should be back-tested on historical data.

In this column, I would like to address the second step in the above process: how does one obtain the necessary sentiment data?