Functional-first programming in F# is an effective tool for solving complex problems that often arise in financial computing. The strong typing of F# provides important correctness guarantees and means that numeric code written in F# runs efficiently. Furthermore, a number of case-studies show that F# significantly reduces time-to-market, especially in the financial domain.
The course is practically focused. Throughout the course, we look at examples of time-series analysis, modelling and pricing of stock options and more. Each lecture provides a number of fun exercises that guide you through the problem. Furthermore, F# and functional programming makes you a better programmer even if you do not end up using the language immediately after the course.
The course requires no prior functional programming knowledge and is designed for both software developers and quants or actuaries. You will learn:
A brief theoretical introduction to every concept will be followed by numerous practical demos and exercises. At the end of the first day, you’ll leave with a complete real-world F# application. In the second day, we’ll solve a number of complex problems in concurrent and data-oriented programming.
The course doesn’t require prior experience with F# or functional programming.
Domain specific languages for finance Domain specific languages (DSLs) are an effective way of solving recurring problems. In this lecture, we build a DSL for pricing financial options and for detecting patterns in changing prices. You’ll learn how to model problem domain using functional data structures and how to build an easy to use library on top of the model.
Explorative data and time-series analysis We look at F# type providers and Deedle. Type providers make it easy to access data from sources including CSV and XML files, Excel, SQL databases and Web and REST services. Using Deedle we can then align multiple time-series and perform interactive analysis – such as comparing different industry sectors or calculating daily returns.
F# in the larger context We wrap up by looking at the ways for integrating F# in the broader context. This lecture explores how to call advanced statistical libraries using the R provider, how to use object-oriented programming to integrate with .NET and how to use F# tools and libraries for unit testing, building and documenting code.
Really enjoying the @Quantshub course on F# in Finance by @tomaspetricek. It's week 2 and I am already learning things I didn't know #Fsharp
— Kevin Ashton (@ashtonkj) October 31, 2014
I highly recommend taking @tomaspetricek course if you're looking to jump start your #fsharp skills. I was great. https://t.co/CrIkdRBHPP
— Gene Chiaramonte (@waahhoo) May 11, 2016