Lloyd N. Trefethen

This book gives a non-rigorous treatment to Brownian motion and its applications to finance. Let me summarize a few points from various chapters. Chapter 1 : Brownian motion This chapter starts off by specifying Brownian motion by the properties of its increments such as independence, first and second moments, transition density etc. A discrete approximation of BM is shown via a binomial tree. Covariance of BM process is derived. A way to manufacture correlated BM is shown.

Speed reading online content - RSVP - Rapid serial visual presentation( Via Wiki) The unique method used by RSVP allows for the reading of unlimited text in a limited position. Researchers from Carnegie Mellon have found that as many as 12 words per second are readable in controlled situations (720wpm).Further research has shown that for shorter pieces of text, RSVP formats increased reading speed by 33% with no significant differences in comprehension or task load.

Steven Shreve’s books on Stochastic calculus (Volume I + Volume II) are amazing in terms of breadth. Basic intuition is built in Volume I using a discrete-time binomial asset pricing model. In Volume II, the author introduces all the concepts needed to build a financial model in continuous-time. In this post, I will try to summarize a few points from Volume II. Chapter 1: Introduction The most important mind shift that one needs to make when moving from the discrete-time case to continuous-time case is that of “uncountable outcome space”.

“Big Data” has entered every one’s vocabulary, thanks to the wild success of few companies that have used data to provide valuable information and services. This book gives a bird’s eye view of the emerging field. The book starts off with an interesting example of the way Google predicted the spread of flu in real time after analyzing two datasets, first one containing 50 million most common terms that Americans type and second one containing the data on the spread of seasonal flu from public health agency.