F#: contributing a chapter to an upcoming book, "F# Deep Dives"

Thanks to Tomas Petricek's invitation, I am honored by being able to write a chapter for an upcoming book - F# Deep Dives. The chapter I am responsible for is Chapter 4: Numerical computing in financial domain. The first draft of the chapter is now available online via Manning's early access program.

Currently the chapter covers the following:

1 Introducing financial derivatives

2 Using probability functions of Math.NET

2.1 Configuring F# Interactive (profiling and floating point formatting)

2.2 Setting up Math.NET Numerics

2.3 Introducing Random Variables, Expectation and Variance

2.4 Generating Normally Distributed Samples

3 Geometric Brownian Motion and Monte Carlo Estimate

3.1 Modeling stock prices using geometric Brownian motion

3.2 Payoff Function, Discounted Payoff, and Monte Carlo estimate

3.3 Analyzing variance of Monte Carlo estimates

3.4 Pricing Path-dependent options (Asian options and barrier options)

3.5 Reducing Variance by antithetic variates