The industrialized countries are poor in a special, curious sense: The people are so eager to get financial security that motherhood is neglected. Or, when wives have to go to work for financial security, the country is still poor. In a sense, living in some of the tropical countries is better if only because can get by without heating oil in the winter or an expensive car.
Yes, Black-Scholes etc. have been important, were for a while via "covered call options", or as in the E. Thorpe, Beat the Street -- essentially the same as what Black-Scholes did the math for with a Brownian motion assumption, etc.
I got an interview at Morgan-Stanley, gave a little lecture on my recent work in anomaly detection, indicated that I wanted to work in developing applied math, algorithms, and software for automated trading, but was ignored. They just wanted people to hack code for back office record keeping. The money making was elsewhere in the company and was based on more traditional ideas, e.g., investment banking.
For automated trading, listen to a James Simons remark: Someone walks in and is just convinced that they should short GM and go long the German Mark or some such. Well, that's more traditional stock picking or hedge fund portfolio management, and Simons made clear that his group, no way, would ever do such a thing. Instead, each buy/sell decision was from some data, ideas, analysis, and software already thoroughly tested; when that software said buy/sell, there wasn't much doubt. Well, that's what Simons did. Don't expect many other people on Wall Street ever to have done such a thing -- it's a lot easier to have a gut feel to short GM and go long the Mark.
Lawyers have learned: A working lawyer reports only to another lawyer. Well, math guys need such a rule, but outside of academics and some national security shops, there are nearly no math guys to report to. So, my desire to do applied math, software, etc. for automated trading was just ignored. Once I was invited to lunch in lower Manhattan for a guy claiming to be recruiting for Goldman-Sachs .... There just is no respect for a mathematician on Wall Street, no matter what Obama said.
Other than James Simons, not clear that math made much money for anyone on Wall Street.
Yes, Black-Scholes etc. have been important, were for a while via "covered call options", or as in the E. Thorpe, Beat the Street -- essentially the same as what Black-Scholes did the math for with a Brownian motion assumption, etc.
I got an interview at Morgan-Stanley, gave a little lecture on my recent work in anomaly detection, indicated that I wanted to work in developing applied math, algorithms, and software for automated trading, but was ignored. They just wanted people to hack code for back office record keeping. The money making was elsewhere in the company and was based on more traditional ideas, e.g., investment banking.
For automated trading, listen to a James Simons remark: Someone walks in and is just convinced that they should short GM and go long the German Mark or some such. Well, that's more traditional stock picking or hedge fund portfolio management, and Simons made clear that his group, no way, would ever do such a thing. Instead, each buy/sell decision was from some data, ideas, analysis, and software already thoroughly tested; when that software said buy/sell, there wasn't much doubt. Well, that's what Simons did. Don't expect many other people on Wall Street ever to have done such a thing -- it's a lot easier to have a gut feel to short GM and go long the Mark.
Lawyers have learned: A working lawyer reports only to another lawyer. Well, math guys need such a rule, but outside of academics and some national security shops, there are nearly no math guys to report to. So, my desire to do applied math, software, etc. for automated trading was just ignored. Once I was invited to lunch in lower Manhattan for a guy claiming to be recruiting for Goldman-Sachs .... There just is no respect for a mathematician on Wall Street, no matter what Obama said.
Other than James Simons, not clear that math made much money for anyone on Wall Street.