Piotr Karasinski is the global head of quantitative development at HSBC. He was a successful academic before he shifted to Wall Street. Therefore if anyone is able to give some insight into investment banking it would be him. Piotr Karasinski explained that the role of quantitative analysts is to “implement derivates pricing models, develop tools for calibrating model parameters, analyse model performance and provide trading desk support.”
He felt that applicants for banking jobs need to demonstrate interest in finance either by personal reading or specialized workshops. Among quantitative tools he particularly emphasized partial differential equations, probability & statistics, stochastic and programming skills. He also emphasized basic knowledge about stocks, bonds, call/put options, interest rates and inflation. He commented that some knowledge of Capital Asset Pricing Model, Black-Scholes model and Gaussian Mean-Reverting Short-Rate model is helpful.
Compared to other speakers, Dr. Karasinski gave tips (here, here, here, and here) about certain books to read. Among magazines, he recommended Risk, Financial Analyst Journal and Wilmott. He commented that additional dimensions of knowledge of psychology, economic history and business are crucial for any mathematical PhDs applying to be a quantitative analyst.
There were a couple of more focussed presentations on algorithmic trading which is of particular interest to me. There is great development in this area and it is something that has also attracted considerable interest in the computer science academic community. On the banking side, algorithmic trading involves complex modeling of historic movement to predict the future, and analysis for hedge strategy. There is also a scope of exotics which includes pricing of complex financial instruments and risk management techniques. One speaker emphasized proprietary trading as one of the key areas of focus. Overall, the presentations were insightful enough to provide a flavour of what life in an investment bank is like.
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