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Don't bother. D.E. Shaw, Renaissance Tech, Goldman Sachs, etc. have already hired hundreds (if not thousands) of people smarter than you to do exactly this. Th
by smanek 17y ago
Don't bother.
D.E. Shaw, Renaissance Tech, Goldman Sachs, etc. have already hired hundreds (if not thousands) of people smarter than you to do exactly this. They have more Math, Physics, Econ, CS PhDs than you can count/
- steveplace 17y agoThey have more Math, Physics, Econ, CS PhDs than you can count/ So did BSC, AIG, LEH, and MER
- crpatino 17y agoMore to the point! The big disadvantage ML methods is that they are just fancy statistics. The main faulty assumption here is that they believe the future looks a lot like the past, so they try to find even more complex patterns in historical data to extrapolate future trends slightly faster than everybody else. In order for this approach to work, you need very precise market conditions. When markets are stable, your edge is zero and you would be better off investing in some sort hedged index (minimum effort, decent result). When markets are not that stable, it is when you can anticipate trends and get a decent profit for your effort. However, when markets suffer big unexpected turns is when fortunes change hands... and it is when your algorithms give you negative advantage! While you are warrantied to keep following the numbers wherever they take you,a savvy finance human agent has a chance to smell the blood and discretely head for the exit before everyone else. So, it is your call guys. In my opinion, this will not be a viable approach until we get some type of semantic-web-ly mine-able news feeder.