Via gapingvoid:

I tend to read books from the Fabozzi factory , not to get mathematical rigor in a subject but to get an intuitive understanding of the stuff. Overtime, this approach has helped me managed my expectations from Fabozzi books. Having never worked on Black-Litterman model till date, I wanted to get some intuition behind the model. With that mindset, I went through the book. The book is divided into four parts**.

Stumbled on to Dewarists! Brilliantly conceptualized and executed! The Dewarists is a new original series. Part music documentary and part travelogue, the show features inspiring musicians collaborating to create original music while traveling to locations across India.Set against the frenetic pace of the city of Mumbai, Episode 2 features a cross-border collaboration between Pakistani singer-songwriter duo Zeb & Haniya, and two veterans of Bollywood – composer Shantanu Moitra, and lyricist Swanand Kirkire.

Gibbs Sampling is an important method in the context of Bayesian estimation. There are other books on R that focus on Bayesian Simulation (Jim Albert), Monte Carlo simulation (Robert and Casella) that are very good and little advanced. So, where does this book fit in? If one has never done any kind of simulation in R, this book is the ideal reference. For someone who is already aware of the basic simulation stuff, there are 3 chapters in the book that talk about Markov Chain, Bayesian Estimation and Gibbs Sampler that are worth going over.

Emanuel Derman’s book, “Models.Behaving.Badly”, gives a physicist and quant’s perspective of models Vs theories, their nature, what to expect of them, how to differentiate between them and how to cope with their inadequacies. Derman starts off by citing a few incidents from his childhood in Africa, where political models, social movement models failed badly. He then talks about the need to understand the crucial difference between theories and models, thus providing the necessary motivation for a reader to go over the book.