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September 8 Math Colloquium

Nick Costanzino, Barclays Capital

Machine Learning Tools for Quantitative Finance

The types of problems that financial institutions are facing is changing, and so are the tools that quantitative analysts are using to solve them. Traditionally, quants were tasked to price and hedge derivatives and other complicated products which were amenable to stochastic calculus and PDE. However, under a tighter regulatory regime and the rise of quantitative funds, quants are increasingly asked to solve challenging problems whose solutions are most efficiently solved via machine learning techniques. In this talk I will briefly review some of the typically problems faced by financial institutions such as quant funds, and discuss some techniques to solve them. These include both supervised and unsupervised learning methods.

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