I will be joining a risk management firm in a few months, and I was wondering if some of you could help we with resources on certain methods.
Some of the things that I would be called upon to work on are calibrating models using simulated methods of moments or Kalman filters. I am also supposed to work on Bayesian modeling though the details havent been discussed yet.
While the theoretical foundations for all these methods and techniques can be found in books and on the web, I wanted to get an understanding of how these methods are applied in finance. So resources like data-sets or projects that implement these things or at least guide (some of the way, not completely) would be helpful.
A little bit about me: I am a recent PhD in physics and economics. So technical things are fine with me. I have sufficient programming experience in python and c++. Thus, I am really looking for practical applications, given that I have little to no experience in Finance.