A recent technical development touted by JPMorgan could provide institutional investors an advantage in today’s algorithmically-driven markets. The world’s largest bank based on revenue is rolling out an automated stock execution platform that uses machine learning techniques to route orders along the most cost effective path, the Financial Times first reported. The technical mechanism for trading large blocks of stock orders without disrupting market pricing is “significantly better” than an unspecified pricing benchmark and high-frequency trading systems, beating the traditional human method to execute large institutional stock transactions, according to a JPMorgan executive. [dalio] Is JPMorgan technology turning the tables…
JPMorgan Develops Learning Algorithm Could Turn Tables On HFT
Mark Melin
Mark Melin is an alternative investment practitioner whose specialty is recognizing the impact of beta market environment on a technical trading strategy. A portfolio and industry consultant, wrote or edited three books including High Performance Managed Futures (Wiley 2010) and The Chicago Board of Trade’s Handbook of Futures and Options (McGraw-Hill 2008) and taught a course at Northwestern University's executive education program.