Next-generation quant

Alternative datasets offer untapped potential by providing valuable insights for investors looking to gain a competitive edge in the market. These unconventional sources of information include elements ranging from credit card transactions, audio from earnings calls, geolocation information, to textual data from news filings. For quant investors, this treasure trove of information can elevate the efficacy of investment strategies when skillfully integrated.

Machine learning (ML) gives quant investors an extra toolkit with which to explore and delve into economic problems and identify patterns within data. The flexible and powerful framework of ML can uncover nonlinear relationships between variables as well as shed light on their interactions. This can be incredibly valuable for quant investors when constructing return signals, risk models and portfolio construction algorithms, for example.

Natural language processing (NLP) revolutionizes data analysis, decoding spoken words and texts at an unprecedented pace and scale. While fundamental analysts examine broker research notes, analyze company reports, and meet with management teams to glean insights, quant investors can now perform similar tasks using NLP, such as sentiment analysis. In this transformative landscape, tools like ChatGPT provide nuanced and in-depth interpretation of language, bridging the gap between data and insight.