Quantscript is an old project of mine, which was hosted on google.code. Since google.code is shutting down, I had to either scrap it or migrate it to GitHub. I am not using this code on a daily basis anymore, and since the project is relatively small – the natural thing would have been to scrap it. However, I found myself a few times over the years pulling out the source code of the project to follow as an example how to do different things in Python. Hence, I thought better to spend the time to migrate the project.
Over the years I have tried to simplify and streamline my access to financial historic data. All different solutions I tried (see here, for example) so far have been unsatisfactory, at least to some degree. That however changed after I started using R6. Here is an example of using the R6 class for the same task as before:
Since February didn’t show anything interesting in the calendar analysis, I passed on writing a post about it. March, on the other hand, looks quite interesting. Let’s start with the top five performers (ordered by winning percentage):
The recent move by the Swiss National Bank (SNB) to remove the peg between the Swiss Franc and the Euro has caused lots of turmoil (see here and here) in an already volatile environment. The magnitude of the event was a pure surprise to me. Yes, this is Switzerland, and this is the Swiss Franc, but, from a mere technical point of view, after the peg in September 2011, the Franc should not have been treated any more as a major currency. Consider, which currencies are pegged? If China removes the peg between the Yuan and the US dollar, would it send the same shock waves through the world markets? I doubt it.
It’s embarrassing, but hoping it might be useful to others, I’ll share it anyways.
At the beginning of January, as usual, I posted the allocations for that month for the strategy I call Max-Sharpe and which I try to follow. So what’s the deal? Well, I wasn’t able to enter these positions, since I became too “greedy”.
Today over a coffee, me and a friend did a quick analysis on the Russell 2000. The reason was that I was holding a short, and was debating whether to close it or not. Not only the outcome of this analysis made my action clear, but it also surprised me quite a bit. Here are the monthly statistics for the month of December.
In an earlier post, I used mclapply to kick off parallel R processes and to demonstrate inter-process synchronization via the flock package. Although I have been using this approach to parallelism for a few years now, I admit, it has certain important disadvantages. It works only on a single machine, and also, it doesn’t work on Windows.