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F# for Quantitative Finance

By : Johan Astborg

3.8 (5)

F# for Quantitative Finance

3.8 (5)

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.

F# for Quantitative Finance

F# for Quantitative Finance

Credits

Credits

About the Author

About the Author

About the Reviewers

About the Reviewers

www.PacktPub.com

www.PacktPub.com

Preface

Preface

Free Chapter

Introducing F# Using Visual Studio

Introducing F# Using Visual Studio

Introduction

Getting started with Visual Studio

Understanding F# Interactive

Language overview

Explaining mutability and immutability

Primitive types

Explaining type inference

Explaining functions

Documenting your code

Your first application

The whole program

The power of prototyping

Functional languages in quantitative finance

Understanding the imperative code and interoperability

Summary

Learning More About F#

Learning More About F#

Structuring your F# program

Looking deeper inside data structures

Choosing data structures

More on functional programming

Asynchronous and parallel programming

A brief look at imperative programming

Using XML documentation

Summary

Financial Mathematics and Numerical Analysis

Financial Mathematics and Numerical Analysis

Understanding the number representation

Learning about numerical types in F#

Arithmetic operators

Learning about arithmetic comparisons

Math operators

Conversion functions

Introducing statistics

Using the Math.NET library

Learning about root-finding algorithms

Summary

Getting Started with Data Visualization

Getting Started with Data Visualization

Making your first GUI in F#

Composing interfaces

Displaying data

Extending the application to use Bollinger bands

Using FSharp.Charting

Creating a bar chart

Summary

Learning Option Pricing

Learning Option Pricing

Introduction to options

Learning the Black-Scholes formula

The Monte Carlo method

Summary

Exploring Volatility

Exploring Volatility

Introduction to volatility

Learning about implied volatility

Solving for implied volatility

Delta hedging using Black-Scholes

Exploring the volatility smile

Summary

Getting Started with Order Types and Market Data

Getting Started with Order Types and Market Data

Introducing orders

Understanding order execution

Introducing market data

Implementing simple pretrade risk analysis

Introducing FIX and QuickFIX/N

Summary

Setting Up the Trading System Project

Setting Up the Trading System Project

Explaining automated trading

Understanding software testing and test-driven development

Understanding NUnit and FsUnit

Connecting to Microsoft SQL Server

Introducing type providers

Writing test cases

Summary

Trading Volatility for Profit

Trading Volatility for Profit

Trading the volatility

Plotting payoff diagrams with FSharpCharts

Learning directional trading strategies

Deriving the mathematics

Learning relative value trading strategies

Defining the trading strategy

Summary

Putting the Pieces Together

Putting the Pieces Together

Understanding the requirements

Revisiting the structure of the system

Understanding the Model-View-Controller pattern

Executing the trading strategy using a framework

Building the GUI

Presenting information in the GUI

Adding support for downloading the data

Looking at possible additions to the system

Summary

Index

Index

Introducing statistics

In this section, we'll look at statistics using both built-in functions and simple custom ones. Statistics are used a lot throughout quantitative finance. Larger time series are often analyzed, and F# has great support for sequences of numbers; some of its power will be illustrated in the examples mentioned in this section.

Aggregate statistics

Aggregated statistics is all about statistics on aggregated data such as sequences of numbers collected from measurements. It's useful to know the average value in such a collection; this tells us where the values are centered. The min and max values are also useful to determine the extremes in the collection.

In F#, the Seq module has this functionality built-in. Let's take a look at how to use it in each case using an example.

Calculating the sum of a sequence

Consider a sequence of 100 random numbers:

let random = new System.Random()
let rnd() = random.NextDouble()
let data = [for i in 1 .. 100 -> rnd()]

We can calculate the...

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