AI and the emerging technology cycle in financial markets

An article this week brings to the forefront the challenges facing artificial intelligence (AI) and machine learning(ML) for the financial markets. Using Paul Tudor Jones' experience creating a trading black box as one example of the ground yet to cover when applying the use of AI, ML and computers to create greater returns in the stock markets. Even after years of development there remains a human as the final decision maker when it comes to trading at Tudor Investment Corp.

While machine-learning algorithms and other technologies are indeed encroaching on work performed by money managers, traders and analysts, many firms are still working out the kinks. -  Saijel Kishan "Wall Street’s Robots Still Have a Lot to Learn About Being a Human Trader"

Bloomberg News continues their discussion with the possibility that AI is reaching the trough of disillusionment in the Hype Cycle for Emerging Technologies. As we discussed in "2017 TRENDS IN FINTECH-FOCUS ON ALTERNATIVE MARKET DATA AND ALPHA", RelateTheNews holds the view that AI and ML will be components of growth in the capital markets. However, these technologies and their effective implementation are still in an early stage when viewed through the lens of applications which drive continued measurable success. Additionally the true success of these technologies are going to arrive first in the form of data mining, data curation and data inlining (bringing the data into full investment lifecycle decision making processes).  At RelateTheNews we continue to perform in-house research on the use of AI, ML, NLP and other emerging technologies to insure the our clients can continue to be competitive in the global markets driving alpha with effective alternative data.