Statistical Algorithms | financial analysis through computational statistics and natural experiments

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May/10

8

Blog Syllabus

This blog will focus on the statistical tools needed to understand finance and empirical economic research, and the conclusions that can be drawn from this research. We will be progressing through these subjects in a logical, progressive fashion starting from basic concepts, although I will also provide occasional deviations as I consider specific questions that might be of either contemporary relevance or of personal interest.

I will cover univariate and multivariate models of stationary and nonstationary time series. The goals of the blog are to (1) develop a set of techniques to analyze univariate and multivariate time series, (2) gain understanding of the current literature in econometrics, and (3) learn the tools needed for this kind of analysis in the real world. I will be mostly concentrating on using R for the technical details, although I will also introduce other software as desired (including Clojure, Haskell, J, and C++).

Core blog textbooks:

Some selected university courses:

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Jan/10

20

Mosaic time series in R

I really like this chart as featured on flowingdata.com (from www.weathersealed.com).  Here's my brief attempt to recreate it.

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Aug/09

11

IDE: Eclipse (StatET)

There are many IDE's (Integrated Development Environments) for R.  So it is up to each developer to choose what's most important.  My personal favorite is Eclipse (see the wikipedia article).  Eclipse was originally created for Java development, but has become one of the most widely adopted IDE's for all languages at this stage thanks to it's architecture, which allows to easy extension through plugins.  For instance, Insightful created a new S-Plus GUI using Eclipse (which they call the S+ Workbench).

I show how to set up and use Eclipse for R development.

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