I recently had the opportunity to listen to some great minds in the area of high-frequency data and trading. While I won’t go into the details about what has been said, I wanted to illustrate the importance of proper out-of-sample testing and proper variable lags in potential trade algorithms or arbitrage models that has been brought up. This topic can also be generalized to a certain degree to all forecasts.
The following entry explains a basic principle of finance, the so-called efficient frontier and thus serves as a gentle introduction into one area of finance: “portfolio theory” using R. A second part will then concentrate on the Capital-Asset-Pricing-Method (CAPM) and its assumptions, implications and drawbacks.
This is a direct (though minor) answer to Daniel’s blogpost Power Analysis for default Bayesian t-tests, which I found very interesting, as I have been trying to get my head around Bayesian statistics for quite a while now. However, one thing that bugs me, is the time needed for the simulation. On my machine it took around 22 minutes. Depending on the task, 22 minutes for a signle test can be way too long (especially if the tests are done in a business environment where many tests are needed – yesterday) and a simple t-test might be more appealing only because it takes a shorter computing time. Here is my solution to speed-up the code using snowfall‘s load-balancing parallel structures to reduce the time to 8.5 minutes.
When dealing with large datasets that potentially exceed the memory of your machine it is nice to have another possibility such as your own server with an SQL/PostgreSQL database on it, where you can query the data in smaller digestible chunks. For example, recently I was facing a financial dataset of 5 GB. Although 5 GB fit into my RAM the data uses a lot of resources. One solution is to use an SQL-based database, where I can query data in smaller chunks, leaving resources for the computation.
For a project I recently faced the issue of getting a database of all aviation incidents. As I really wanted to try Hadley’s new rvest-package, I thought I will give it a try and share the code with you.