On Monday, 22 December 2014 at 13:37:55 UTC, aldanor wrote:
For some reason, people often relate quant finance / high frequency trading with one of the two: either ultra-low-latency execution or option pricing, which is just wrong. In most likelihood, the execution is performed on FPGA co-located grids, so that part is out of question; and options trading is just one of so many things hedge funds do. What takes the most time and effort is the usual "data science" (which in many cases boil down to data munging), as in, managing huge amounts of raw structured/unstructured high-frequency data; extracting the valuable information and learning strategies;
This description feels too broad. Assume that it is the "data munging" that takes the most time and effort. Included in that usually involves some transformations like (Data -> Numeric Data -> Mathematical Data Procssing -> Mathematical Solutions/Calibrations -> Math consumers (trading systems low frequency/high frequency/in general)). The quantitative "data science" is about turning data into value using numbers. The better you are at first getting to an all numbers world to start analyzing the better off you will be. But once in the all numbers world isn't it all about math, statistics, mathematical optimization, insight, iteration/mining, etc? Isn't that right now the world of R, NumPy, Matlab, etc and more recently now Julia? I don't see D attempting to tackle that at this point. If the bulk of the work for the "data sciences" piece is the maths, which I believe it is, then the attraction of D as a "data sciences" platform is muted. If the bulk of the work is preprocessing data to get to an all numbers world, then in that space D might shine.
implementing fast/efficient backtesting frameworks, simulators etc. The need for "efficiency" here naturally comes from the fact that a typical task in the pipeline requires dozens/hundreds GB of RAM and dozens of hours of runtime on a high-grade box (so noone would really care if that GC is going to stop the world for 0.05 seconds).
What is a backtesting system in the context of Winton Capital? Is it primarily a mathematical backtesting system? If so it still may be better suited to platforms focusing on maths.
