Posted on

The case for Alternative Data

AI-based strategies in the investment process are outperforming other investment strategies. Language technology enables significant alpha creation, as proven by the most successful hedge funds. Strategic initiatives are moving toward advanced analytics of both structured data (e.g. price data) and unstructured data (e.g. language data), in combination – to be used in mainstream asset management. On the back of Advanced Analytics, Machine Learning, Computational Linguistics, and advanced qual-to-quant tools, Alternative Data is growing rapidly and is predicted to be a major game-changer in the investment industry as a source for alpha creation. Compared with high-frequency trading, the edge in some Alternative Data is continuous in a complex system, and the Alternative Data has – therefore – much higher potential and more durable value (i.e. it is not an arbitrage). A major challenge for the industry is the lack of robust, consistent and long historical time-series needed to train machine learning models on how to create alpha from language data: There are rafts of new language technologies, investment and strategic initiatives to build trading models and leverage alternative data, but there is little or no training data. Firms are beginning to set up targets and they begin to accumulate data in multi-year projects, with the understanding that it takes several years to accumulate enough data to build predictive models that are robust enough for practical investment applications.