Women in FinTech Summit - AI: Can Machines Truly Make Smarter Investment Decisions Without Any Human Input?
Quantitative and semi-quant funds have consistently outperformed discretionary funds over the last few years. Does this mean the age of human intuition based investing is over? Can machines truly replace humans? We will explore the case for data driven decision making in investment management, the benefits and pitfalls of fully automated investing and why the human touch is still important. AI in finance, when done right, is not a replacement for human trader but a powerful tool that traders can combine with their own skill to massively augment their decision making and boost profitability.
AI in Finance Summit - AI for the buyside: Deep Learning for Factor Research
Problems in the financial markets are different from typical deep learning applications since the emphasis is not on replicating tasks that humans already do well. Humans have no innate ability to solve these problems that involve large data sets and complex data interactions that currently are difficult to specify in a purely economic model. Applying deep learning methods to these problems can detect and exploit interactions in the data that are, at least currently, invisible to any existing financial economic theory.
We will demonstrate an example of how we can combine the latest statistical techniques with deep learning methods to compute any relationship between thousands of raw indicators and asset prices, no matter how complex and non-linear. These insights can be used to create new empirical representations of fundamental factors which lead to long-term over-performance. This also enables a better understanding of portfolio exposure to different risk factors, allowing asset managers to create high performing, well diversified portfolios. We will compare the performance of these methods to the linear factor models of traditional financial economics and the ad hoc methods of statistical arbitrage and other quantitative asset management techniques.
Chandini Jain is the CEO and founder of Auquan. She has 7+ years of global experience in finance with Deutsche Bank in Mumbai/New York and as a derivatives trader with Optiver in Chicago and Amsterdam. At Optiver, she traded volatility arbitrage strategies and was involved first hand in making the shift from discretionary to automated trading. Since 2017, she has been working on Auquan, an early stage fintech startup employing new and cutting edge ML and Deep Learning techniques to solve financial prediction problems for hedge funds and asset managers.