The Next Warren Buffett: AI?

The A.I team led by Nehaarika and Faizan presented a topic that had previously only been mentioned as supporting information: A.I’s effect on finance. The beginning overview discussed topics including the different forms of tradable units (stocks, bonds, and derivatives such as options and futures) and the different techniques that are utilized to support trade strategies such as fundamental, technical, and quantitative analysis. Fundamental analysis looks at the company itself and the internal financials and trends of the company. Technical analysis looks at the stock trends of the company and utilizes historical patterns and common trends to predict the future movement of the company’s stock. Finally, quantitative analysis utilizes historical data to create algorithms based on mathematics and statistics to devise a trading strategy. These distinctions were emphasized in the beginning of the presentation as the different techniques that investors use to make trades are impacted in vastly different ways by AI. In terms of the direct impact that AI has on trading, the use of statistical data allows the trader to predict a higher rate of return. The S&P500 return is closer to average 0 than the theoretical normal distribution, meaning that there is optimization possible which is done by AI systems. Ultimately the final deal is often placed by the trader, but AI systems are increasingly putting deals through themselves. In terms of forward looking trends, Faizan emphasizes a number of changes. First, the waning ability to arbitrage (buy low sell high) within different markets as AI systems accomplish that in milliseconds. Second, the potential for decreased volatility and increased volume and liquidity. Finally, the theory that 4 out of 5 experts expect AI to be fully integrated into trading within the next 3-5 years. Though there are denoted benefits such as the ability to do menial tasks, efficiency improvements, and money savings, the drawbacks of AI in finance must also be acknowledged: relatively small dataset, inability to do casual thinking, legal issues, and macro-environment changes. Ultimately, the decision of AI’s integration into finance will come down to the large institutional investors as well as the retail investors like you and me.

Our A.I in Finance discussion started off with our second ever debate, what we like to call the ring of fire, where our members volunteer to go one vs. one taking a stance for a given question of “yes” or “no.” The first question presented was “Will continued integration of A.I into finance mark an end to jobs in sales and trading?” The first speaker, Nehaarika, gave her two-minute defense for the opinion of “no” by first stating the essence of what finances and sells any good or service, and that is human connection. To sell a pitch, to buy a product, to make any transaction has to be a connecting human interaction to “seal the deal.” Neharrika points out on a final note that A.I will continue to take on more and more of the tasks we do i.e automate more of our work, but we as people will ultimately dictate our financial decisions. Sahana’s stance on the opposing side states clearly and immediately that human interaction is NOT necessary, and that finances and economics is the one place where presentability or empathy is optional. One key consideration by Sahana was a basic understanding of a major principle in economics, where the “person” who does the best job should get the job and A.I is starting to and will continue to get and be better than people at our jobs. Nehaarika’s rebuttal stated that machines and software do not have the capabilities to do this quite yet. She also went on to say that finance is sensitive and quite an important topic, where a human needs to make a final decision. She admits that A.I will cause a decrease in jobs in sales/trading, but never an end. Sahana and this debate’s final rebuttal was that the dawn where A.I takes our jobs as only a matter of time, making human error obsolete because, eventually, A.I will be better in aspects of finance.

During our discussion, we went over two questions. The first being, “Will personal financial analysts and advisors are needed, or will software analysts take over the advising job market?” Evan first noted that asking questions on the extremes of scenarios is unnecessary and that there is bound to be some plausible outcomes that possess some degree of each answer, but overall, Evan prioritized softs skills in addition to financial skills for an advisor, meaning advising cannot be solely run off A.I. Mauricio added on this by stating that human orientation is important and that finances will be better handled by humans because finances are dictated by humans, through prices and “whatnot.” The second question stated “Now that we have machines to do all the hard thinking and analyzing for us, what will be the impact on current financial analysts? Will they still be needed to interpret the data?” Mauricio started off the discussion commenting on the shortcomings of A.I, and how human work, even error, can be excused and therefore is better, at least for now. Sam, on a final note, adds that change is inevitable, but there will certainly be some way for job security to stay intact.