http://asa-caltech.sourceforge.net/
I highly recommend this tool for your Optimisation purposes - very efficient code and a good example for learning how to implement Simulated Annealing Algorithm in C. What what inspires me is the approach the coder of the tool (Lester Ingber) has taken to implement the algorithm - well organised structure highlighting the prime benefits of C over Matlab.
The reason I tool the about page offline was that it did not accurately reflect the focus of this blog. I have drawn up a new chart that is supposed to replace the old one, and apart from it reflecting some of the topics I write about here I would like it to serve as a general chart that shows how Signal Processing and Machine Learning come together in developing Financial models. Please comment on any addition/alteration that can be made.
While reading on the subject of hard to forecast events I decided to investigate what the Signal Processing domain had to offer in terms of models that account for “fat-tail” distributions. Thankfully I came across a set of papers that specifically address the nature of such distributions in their modeling approach - which I think is insightful and worth having a look at despite being off-topic to quant work.
The set of papers was collectively published in a special edition journal under the theme “Signal processing with heavy-tailed distributions” and can be found here. I have uploaded the preface to the journal which gives a good overview of applications. You can download it from here.
Seriously, Graphviz is such an excellent graph plotting tool. I have used it on many occasions here and find myself using it more often than Visio. Might be useful to some who have not come across it before:
Nassim Nicholas Taleb is co-editing a special issue of the International Journal of Forecasting with focus on “decision making and planning under low levels of predictability”. The official invite can be found here and while I will not be submitting a paper, I will surely obtain a copy of the issue when it is published.
