In the last post, Classical Technical Patterns, I discussed the algorithm and pattern definitions presented in the Foundations of Technical Analysis by A. Lo, H. Mamaysky, J. Wang (2000) paper. Today, I want to check how different patterns performed historically using SPY. I will follow the rolling window procedure discussed on pages 14-15 of the 
The end is near! At least the semester is coming to an end, so students have crazy expectations like getting marks back for assignments, and administrators want to see exam scripts. Sigh! What has been happening meanwhile in Quantum Forest? … Continue reading →
Hello everybody, I am finally back with a new episode! In this episode: Hardware issues, major update to RStudio, new forums, and discussion on managing your workflow for projects. I discuss useful functions for executing R scripts and saving/loading R objects for future sessions, and summarize different solutions for organizing R code based on task
Call me uncouth, but I like my TV loud, my beer cold and my optimization functions as simple as possible. Therefore, what I write in this blog post is very much from a layman’s perspective, and I am happy to be corrected on any fundamental errors. I have recently become interested in writing my own 
Andrea Spanò, founder and partner at Quantide, held two seminars about Industrial Statistics at the University of Bergamo. Process Capability Analysis and Gage R&R were topics of seminars. Registered Milano R net users can download presentations from this page.
On the ICES Spatial Facility webpage one can obtain a view of the ICES statistical areas. Now since the projection used is more than a bit misleading I was wandering how these statistical areas would look like in Google Earth. Thankfully the ...
Haven't had much time to devote to new visualisations, mostly because work and baby have taken the precedence.But I just wanted to take a few minutes to share the latest version of the script I showed last time.It now saves to a pdf file, but that's no...
A look at return variability for portfolio changes. The problem Suppose we make some change to our portfolio. At a later date we can see if that change was good or bad for the portfolio return. Say, for instance, that it helped by 16 basis points. How do we properly account for variability in that … Continue reading...
It took us a loooong while but we finally ended up completing a paper on ABC using empirical likelihood (EL) that was started by me listening to Brunero Liseo’s tutorial in O’Bayes-2011 in Shanghai… Brunero mentioned empirical likelihood as a semi-parametric technique w/o much Bayesian connections and this got me thinking 
This blog and my other main blog (the companion blog for my book) are now syndicated via R-bloggers (posts tagged R only) and statsblogs.com. The latter is a relatively new blog aggregator but looks to have some interesting content. R-bloggers it quite...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
