Book Image

F# for Quantitative Finance

By : Johan Astborg
Book Image

F# for Quantitative Finance

By: Johan Astborg

Overview of this book

F# is a functional programming language that allows you to write simple code for complex problems. Currently, it is most commonly used in the financial sector. Quantitative finance makes heavy use of mathematics to model various parts of finance in the real world. If you are interested in using F# for your day-to-day work or research in quantitative finance, this book is a must-have.This book will cover everything you need to know about using functional programming for quantitative finance. Using a functional programming language will enable you to concentrate more on the problem itself rather than implementation details. Tutorials and snippets are summarized into an automated trading system throughout the book.This book will introduce you to F#, using Visual Studio, and provide examples with functional programming and finance combined. The book also covers topics such as downloading, visualizing and calculating statistics from data. F# is a first class programming language for the financial domain.
Table of Contents (17 chapters)
F# for Quantitative Finance
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Extending the application to use Bollinger bands


We'll now extend the application we used in the previous section to use Bollinger bands. Bollinger bands is an extension of moving average, where two bands are added—one upper band and one lower band. The bands are typically K (where K=2.0) times a moving standard deviation above and below the moving average. We need to add a function to calculate the moving standard deviation. We can use the standard deviation from the previous chapter and use it with the Seq.windowed function, as shown in the following code. In this example, we also add legends to specify which data series corresponds to which color. The screenshot is as follows:

Example application extended to use Bollinger Bands

The code looks pretty much like the code used in the preceding example; except for the calculation of the upper and lower band, and the moving standard deviation:

/// Another example with Bollinger Bands
#r "System.Windows.Forms.DataVisualization.dll" 

open System...