Hi Andy,
Thanks for the reply. From what I remember (need to brush up of course), financial math theory relies on and develops the assumption that change in a stock's price over time can be realized as a stochastic process where individual stock price movements are independent of one another (that is, the independent random variables in the process in question), so that it is possible to hedge against a potential loss with an option that does not depend on the price of the stock at a fixed or any point in time, given certain assumptions about the stock market. My background in probability theory and real analysis enables me to read and understand the proofs on which the theory relies, so that I can build a natural narrative from the theory to actual modeling using empirical data. I guess my biggest advantage over younger candidates is my considerable experience with actual applied mathematical modeling and the handling of numerical data, so that I am aware of the limitations of mathematical modeling and can spot potential problem areas as they arise. My background is in both pure and applied math, so I have the knowledge to make the necessary connections between different areas of math when differences arise between theoretical models and the algorithm-based numerical simulations on which the actual day-to--day practice of quant analysis relies. Also, as I mentioned before, I have seen financial math at the graduate level before, and often in math, the second time around is when you really learn and develop the confidence to deliver consistent results.
Thanks,
Patty
Thanks for the reply. From what I remember (need to brush up of course), financial math theory relies on and develops the assumption that change in a stock's price over time can be realized as a stochastic process where individual stock price movements are independent of one another (that is, the independent random variables in the process in question), so that it is possible to hedge against a potential loss with an option that does not depend on the price of the stock at a fixed or any point in time, given certain assumptions about the stock market. My background in probability theory and real analysis enables me to read and understand the proofs on which the theory relies, so that I can build a natural narrative from the theory to actual modeling using empirical data. I guess my biggest advantage over younger candidates is my considerable experience with actual applied mathematical modeling and the handling of numerical data, so that I am aware of the limitations of mathematical modeling and can spot potential problem areas as they arise. My background is in both pure and applied math, so I have the knowledge to make the necessary connections between different areas of math when differences arise between theoretical models and the algorithm-based numerical simulations on which the actual day-to--day practice of quant analysis relies. Also, as I mentioned before, I have seen financial math at the graduate level before, and often in math, the second time around is when you really learn and develop the confidence to deliver consistent results.
Thanks,
Patty