Walter's DConf 2014 Talks - Topics in Finance

[jmh530 via Digitalmars-d]

On Tuesday, 23 December 2014 at 03:07:10 UTC, Laeeth Isharc wrote:
>
> It would certainly be nice to have matrices, but I also don't 
> think it would be right to say D is dead in water here because 
> it is so far behind.  It also seems like the cost of writing 
> such a library is v small vs possible benefit.

I have a longer horizon than the HFT guys, but I still have quite 
a demand for high performance computing when backtesting a 
quantitative strategy. A backtest will typically involve
1) Put some data in a database
2) Apply statistical models to appropriate data
3) Create forecast distribution
4) Optimize portfolio given forecast
5) Repeat 2:4 in each period and calculate performance of strategy

The biggest limiting factor to implementing it in D is a mature 
math/stats library (I understand SciD is a thing, but I have not 
tried it). Most optimization packages are written in C and could 
probably be called in D (haven't tried, but I imagine). There's a 
mysql module for D, though I think python has much better options 
here (I have been pretty impressed with blaze). Python's Pandas 
is also pretty helpful, but as it is built upon numpy, something 
equivalent would need to built upon a matrix library in D.

I think it would also be helpful for bindings to Julia and C++ 
(so I can use MC Stan or Quantlib). I think the pyd project is 
pretty important. Might be good to write up an example using it 
for a finance application.