Unstructured data is largely underexplored in equity investing due to its higher costs. As a result, the information content remains largely untapped and offers an investment edge for investors. Discover an application of Natural Language Processing (NLP) in the context of systematic equity investing by introducing new stock selection ideas in the areas of I) Topic Identification II) Call Transparency III) Call Sentiment using more intricate yet intuitive NLP techniques and features.
Overview and Author Bio
Natural Language Processing: Feature Engineering in the Context of Stock Investing
Senior Director, Quantamental Research | S&P Global Market Intelligence