Walter's DConf 2014 Talks - Topics in Finance

[Daniel Davidson via Digitalmars-d]

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.