As the term has progressed, my LSM2241 lectures are getting more consistent. I’m aiming to use 45 slides for what is officially a two hour lecture, although in reality it lasts about 90 minutes. We take a break at about 50 … Continue reading →

What is variance targeting in garch estimation? And what is its effect? Previously Related posts are: A practical introduction to garch modeling Variability of garch estimates garch estimation on impossibly long series The last two of these show the variability of garch estimates on simulated series where we know the right answer. In response to … Continue reading...

I thought I would break up the posts about GSOC (no, I’m not done yet – there are a few more to do) with a quick note about FinancialInstrument. The FinancialInstrument package provides a construct for defining and storing meta-data for tradable contracts (referred to as instruments, e.g., stocks, futures, options, etc.). The package can

Not exactly pin-point accuracy. Previously Two related posts are: A practical introduction to garch modeling garch and long tails Experiment 1000 simulated return series were generated. The garch(1,1) parameters were alpha=.07, beta=.925, omega=.01. The asymptotic variance for this model is 2. The half-life is about 138 days. The simulated series used a Student’s t distribution … Continue reading...

I’m happy to present episode 10 of the R-Podcast! Season 1 of the R-Podcast concludes with part 2 of my series on data munging, in which I discuss issues surrounding importing data sets contained in HTML tables. I share how I used the XML and RCurl packages to validate and import data from hockey-reference.com for