On Monday, 22 December 2014 at 19:25:51 UTC, aldanor wrote:
On Monday, 22 December 2014 at 17:28:39 UTC, Daniel Davidson
wrote:
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.
That is one of my points exactly -- the "bulk of the work", as
you put it, is quite often the data processing/preprocessing
pipeline (all the way from raw data parsing, aggregation,
validation and storage to data retrieval, feature extraction,
and then serialization, various persistency models, etc).
I don't know about low frequency which is why I asked about
Winton. Some of this is true in HFT but it is tough to break that
pipeline that exists in C++. Take live trading vs backtesting:
you require all that data processing before getting to the math
of it to be as low latency as possible for live trading which is
why you use C++ in the first place. To break into that pipeline
with another language like D to add value, say for backtesting,
is risky not just because the duplication of development cost but
also the risk of live not matching backtesting.
Maybe you have some ideas in mind where D would help that data
processing pipeline, so some specifics might help?
