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:
- Options, Futures, and Other Derivatives with Derivagem CD (7th Edition)
- Statistics and Finance: An Introduction
(related R code)
- Analysis of Financial Time Series (Wiley Series in Probability and Statistics)
- Modeling Financial Time Series with S-PLUS®
Some selected university courses:
- U Chicago, Ruey Tsay
- U Penn Financial Time Series
- U Washington Time Series Econometrics
- MIT Econometrics
No tags
