Who remembers Manoj Nerang? You know that guy that started started Tradewerx? That little high-frequency trading company that wanted all the media attention years ago. As we know, he got booted out of his own company he founded a while back. Anyways, this is not the whole point but he has resurfaced this week with a statement on how he feels statistical arbitrage for slow-moving data is the next wave for algo trading blended with HFT. This time, I think he’s absolutely right.
Speaking of slow moving statistical arbitrage trading strategies, guess what I have? You know, that Phase 1 of my course series in introducing just this, slow-moving statistical arbitrage or pair trading strategy for equities. Over 80% of the content has already been uploaded for all my Quant Elite members. Within a few days, they should be able to preview all of this content with lessons via video, source code, and all kinds of awesome little shenanigans I am world renown for. I will also be presenting 10 weeks of this LIVE starting the second week of May.
In the meantime, we are in our last weekend before I start my first LIVE lesson of this entire “Algo Trading Business with Python Course Series.” What am I speaking about?
This language does have some ingenious features but I do think you need to embed all your algo code into C++ libraries. From there you just use Python as the fron end to call them. It will make life easier.
R is an interesting language and ecosystem. As you know I find it very hard bring everything together as I hope to do with my Matlab scripts starting next week. You always need to transform one data type to another on top of abandoned packages you rely. Personally, I can no longer work like that unlike in the Matlab space. Also, we have not attacked the performance issues as well.
It sounds like Gigi the Python developer made some big head way with Cython to speed up his operation. But seriously, that is a lot of work
Is CQG considered useless to dropping feed and slow connectivity?
This came in from a newsletter subscriber:
CQG were hopeless. Their datafeed API is COM and kept dropping. We found problems in their datacentre with servers dropping our connection due to slow connectivity. They told us they’d fixed only for them to recur. Unusable
Comments like this are imporant but feel free to provide feedback
Is SQL really too slow for real time market data with equity, forex, and options? Even complex event processing?
From a Youtube visitor
SQL is too slow to handle options tick data if that’s the road you’re headed down. Something you might want to test out before you get too deeply involved. Options data is much heavier than equities data.
Yes this is quite possible but I have been extensively testing this. I am reporting these results to my QuantLabs.net Premium Members. I am finding this is not the case but I still need to put it through a real world all day test with real market data. So far, it is enouraging with SQL Server and Stream Insights for the complex event processing.