If you haven't signed up for the Introduction to Computational Finance and Financial Econometrics course taught by Eric Zivot on Coursera, it's not too late. The second week just started and the first assignments aren't due until September 18th.J...
548 search results for "finance"
Review of “Numerical Methods and Optimization in Finance” by Gilli, Maringer and Schumann
Previously This book and the associated R package were introduced before. Executive Summary A very nice — and enlightening — discussion of a wide range of topics. Principles The Introduction to the book sets out 5 principles. This is probably the most important part of the book. The principles are: We don’t know much in … Continue reading...
Extending Gold time series
While back-testing trading strategies I want all assets to have long history. Unfortunately, sometimes there is no tradeable stock or ETF with sufficient history. For example, I might use GLD as a proxy for Gold allocation, but GLD is only began trading in November of 2004. We can extend the GLD’s historical returns with its 
Not fooled by randomness
The paper is “Not Fooled by Randomness: Using Random Portfolios to Analyze Investment Funds” by Roberto Stein. Here is an explanation of the idea of random portfolios. Favorite sentence The real question here is whether we’re actually measuring skill, or these are still measures of performance, so influenced by extraneous factors that the existence of … Continue reading...
Book Review: R Cookbook
The R Cookbook is written by Paul Teetor, a developer with degrees in statistics and computer science, specializing in finance. The programming language R is a specialized language designed for deep statistical research, although it has some support for other mathematical fields, such as matrix algebra and signal processing. True to the O’Reilly cookbook format,
Thalesians, and other events
Featured Thalesians, London 2012 September 12. Chia Tan on “Practical Financial Modeling”. Abstract: Financial modelling is not a competition in the mastery of complexity. Rather, the aim is to come up with the simplest models adequate to capture salient market features of traded products. There exists a wide gulf between material covered by traditional books … Continue reading...
A look at Bayesian statistics
An introduction to Bayesian analysis and why you might care. Fight club The subject of statistics is about how to learn. Given that it is about the unknown, it shouldn’t be surprising that there are deep differences of opinion on how to go about doing it (in spite of the stereotype that statisticians are accountants … Continue reading...
New Attribution Functions for PortfolioAnalytics
Another Google Summer of Code (GSoC) project this summer focused on creating functions for doing returns-based performance attribution. I’ve always been a little puzzled about why this functionality wasn’t covered already, but I think that most analysts do this kind of work in Excel. That, of course, has its own perils. But beyond the workflow 
Getting data on your government
I created an R package a while back to interact with some APIs that serve up data on what our elected represenatives are up to, including the New York Times Congress API, and the Sunlight Labs API. What kinds of things can you do with govdat? Here ...
DataGotham
As some of you may know already, I’m co-organizing an upcoming conference called DataGotham that’s taking place in September. To help spread the word about DataGotham, I’m cross-posting the most recent announcement below: We’d like to let you know about DataGotham: a celebration of New York City’s data community! http://datagotham.com This is an event run
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
