hardikp

4 ms·

1.
Backtesting for Intraday Execution(hardikp.com)
2 points by hardikp 8y ago|0 comments
2.
RPC Frameworks: GRPC vs. Thrift vs. RPyC for Python(hardikp.com)
1 points by hardikp 8y ago|0 comments
3.
Microbes(hardikp.com)
1 points by hardikp 9y ago|0 comments
4.
Why is machine learning in finance so hard?(hardikp.com)
2 points by hardikp 9y ago|0 comments
5.
Python – C++ bindings(hardikp.com)
8 points by hardikp 9y ago|1 comments
6.
Machine Learning for Intraday Stock Price Prediction 1: Linear Models(hardikp.com)
3 points by hardikp 9y ago|0 comments
7.
Practical Text Classification for Production Systems(hardikp.com)
1 points by hardikp 9y ago|0 comments
8.
How Gandhi brought changes in himself and his followers(medium.com)
2 points by hardikp 9y ago|0 comments
9.
by hardikp 10y ago
Couldn't agree more. This also applies to other financial technologies as well. In general, I feel there is just too much opaqueness in the finance. On a slightly related note, I am working on the trading part mentioned in the article
10.
US Stocks: The Cost of Trading at Market Open(medium.com)
2 points by hardikp 11y ago|0 comments
11.
by hardikp 11y ago
You could be right (or wrong). But, if the point is to understand the market microstructure and dynamics (rather than endorse their philosophy), in my humble opinion, these articles do a good job there.
12.
by hardikp 11y ago
For US equities, nanex research articles ( http://www.nanex.net/NxResearch/ResearchPage/0/?sort_val=dat... ) provide good insight into various aspects. I haven't read any of the books you've mentioned