Since 2015, when the machines exceeded human accuracy in identifying objects for the first time, analyzing data, not only financial and economic but text, images, social media, news, and events data using complex statistical models is a reality. Major forays into the area of Natural Language Processing (NLP) and artificial intelligence is allowing money managers to efficiently analyze mountains of complex financial information and make prudent investment decisions based on the outcomes.

As one can imagine, it took a lot more than educated guesses to convince skeptical money managers about the importance of mathematical models and the analytical insights they can provide by analyzing complex market data. Decisions prescribed by these, sometimes challenging to understand, statistical models are designed to predict the most probable future events.

It is no secret that the intuitions gained from these models about the forthcoming developments in highly volatile financial markets are of immense value to asset managers. These savvy market participants are constantly evaluating the worth of incorporating technologies like AI, machine learning, and deep learning into their investment management workflow. The machines are becoming so good at this task that according to some estimates, the so-called Robo-advisors, may soon replace the traditional wealth advisors.

Nevertheless, there is always the dangers of not only overuse but as the famous saying goes garbage-in is garbage-out, what comes out of these models. Hence it is the responsibility of the money managers to interpret the results in the right context instead of blindly accepting whatever comes out the black box. Also, as these models penetrate the investment industry deeper, it becomes ever more important to understand their limitations and guard against the relentless urge of applying them indiscriminately to every single problem at hand. These models are not meant to replace the decision-making intuition of investment professionals but to assist them in making better decisions for the benefit of their clients.

 Dr. Advait Apte

After finishing a Bachelor’s degree in Biomedical Engineering from India, Dr. Apte joined Virginia Commonwealth University (VCU) to pursue a doctorate degree in Chemical Engineering. While at VCU, his primary research focused on building cellular automata models of biochemical systems with the aim of deciphering the regulatory mechanisms underlying human metabolism. Soon after receiving Ph.D., he joined Virginia Tech (VT) to pursue advance research to improve the efficiency of biofuel and commodity chemical production. His work at VT helped his lab secure considerable funding from reputed institutions such as the Departments of Energy (DOE) and Agriculture (USDA). Moving forward, Dr. Apte accepted a position at Arizona State University’s (ASU) Biodesign Institute to conduct cutting edge research in cancer metabolism and drug design. After a short tenure there, a strong desire to work in the investments industry motivated him to return to the east coast and join the MA in Economics program at the City College of New York (CCNY). While in the program, he not only completed the Chartered Financial Analyst (CFA) program but also achieved prestigious distinctions such as the Colin Powell Fellowship and the CCNY’s Business Alumni Award. He currently works in Richmond, VA as an Investment Officer, conducting quantitative research for the Virginia Retirement System (VRS). In line with the agency’s motto of ‘Serving Those Who Serve Others’, Dr. Apte helps manage the $80 Billion state pension plan that secures the financial future of over half-a-million Virginia state employees, retirees and their families. Apart from his professional contributions in the government sector, Dr. Apte is meaningfully engaged with the academic community through his numerous volunteering activities that include serving as a board member and student recruitment liaison on the VCU College of Engineering Alumni Board, member of the Grant-in-Aid Research committee of Sigma Xi, CFA Institute’s Investment Research Challenge mentor to Hampden-Sydney college and University of Richmond, judge to scientific completions, speaker on panels, and reviewer to various academic journals.