Walter's DConf 2014 Talks - Topics in Finance

[Laeeth Isharc via Digitalmars-d]

On Saturday, 22 March 2014 at 00:14:11 UTC, Daniel Davidson wrote:
> On Friday, 21 March 2014 at 21:14:15 UTC, TJB wrote:
>> Walter,
>>
>> I see that you will be discussing "High Performance Code Using 
>> D" at the 2014 DConf. This will be a very welcomed topic for 
>> many of us.  I am a Finance Professor.  I currently teach and 
>> do research in computational finance.  Might I suggest that 
>> you include some finance (say Monte Carlo options pricing) 
>> examples?  If you can get the finance industry interested in D 
>> you might see a massive adoption of the language.  Many are 
>> desperate for an alternative to C++ in that space.
>>
>> Just a thought.
>>
>> Best,
>>
>> TJB
>
> Maybe a good starting point would be to port some of QuantLib 
> and see how the performance compares. In High Frequency Trading 
> I think D would be a tough sell, unfortunately.
>
> Thanks
> Dan

In case it wasn't obvious from the discussion that followed: 
finance is a broad field with many different kinds of creature 
within, and there are different kinds of problems faced by 
different participants.

High Frequency Trading has peculiar requirements (relating to 
latency, amongst other things) that will not necessarily be 
representative of other areas.  Even within this area there is a 
difference between the needs of a Citadel in its option 
marketmaking activity versus the activity of a pure delta HFT 
player (although they also overlap).

A JP Morgan that needs to be able to price and calculate risk for 
large portfolios of convex instruments in its vanilla and exotic 
options books has different requirements, again.

You would typically use Monte Carlo (or quasi MC) to price more 
complex products for which there is not a good analytical 
approximation.  (Or to deal with the fact that volatility is not 
constant).  So that fits very much with the needs of large banks 
- and perhaps some hedge funds - but I don't think a typical HFT 
guy would be all that interested to know about this.  They are 
different domains.

Quant/CTA funds also have decent computational requirements, but 
these are not necessarily high frequency.  Winton Capital, for 
example, is one of the larger hedge funds in Europe by assets, 
but they have talked publicly about emphasizing longer-term 
horizons because even in liquid markets there simply is not the 
liquidity to turn over the volume they would need to to make an 
impact on their returns.  In this case, whilst execution is 
always important, the research side of things is where the value 
gets created.  And its not unusual to have quant funds where 
every portfolio manager also programs.  (I will not mention 
names).  One might think that rapid iteration here could have 
value.

http://www.efinancialcareers.co.uk/jobs-UK-London-Senior_Data_Scientist_-_Quant_Hedge_Fund.id00654869

Fwiw having spoken to a few people the past few weeks, I am 
struck by how hollowed-out front office has become, both within 
banks and hedge funds.  It's a nice business when things go well, 
but there is tremendous operating leverage, and if one builds up 
fixed costs then losing assets under management and having a poor 
period of performance (which is part of the game, not necessarily 
a sign of failure) can quickly mean that you cannot pay people 
(more than salaries) - which hurts morale and means you risk 
losing your best people.

So people have responded by paring down quant/research support to 
producing roles, even when that makes no sense.  (Programmers are 
not expensive).  In that environment, D may offer attractive 
productivity without sacrificing performance.