Learn FSHARP-FINANCE with Real Code Examples

Updated Nov 27, 2025

Introduction & Fundamentals Setup & Configuration Architecture & Deep Internals Performance & Security Development Workflow Learning & Career Growth Business & Strategy Examples

Installation Setup

Install .NET SDK (latest LTS recommended)

Install F# compiler and tooling (via Visual Studio, VS Code, or JetBrains Rider)

Add NuGet packages for finance: Deedle, Math.NET, FSharp.Data, Plotly.NET

Configure project for console, web, or library use

Test with simple script accessing financial CSV or JSON data

Environment Setup

Install .NET SDK

Install Visual Studio Code or Visual Studio with F# tooling

Configure NuGet package sources

Test simple script execution

Install financial libraries: Deedle, Math.NET, FSharp.Data

Config Files

.fsproj - project definition

NuGet package references (Deedle, Math.NET, Plotly.NET)

Data configuration (CSV/JSON/API endpoints)

Script files (.fsx) for ad-hoc analysis

Documentation and versioned pipelines

Cli Commands

dotnet fsi script.fsx -> execute F# script

dotnet build -> build F# project

dotnet run -> run console application

dotnet add package PackageName -> add NuGet library

dotnet restore -> restore project dependencies

Internationalization

Unicode support in data handling

Financial reports can adapt to locale formatting

Decimal and currency formatting via .NET globalization

Strings and labels can be localized in visualizations

Supports multi-currency and multi-market data pipelines

Accessibility

Cross-platform via .NET Core

Scripts accessible in any text editor

Integration with screen readers through IDEs

Programmatic pipelines for reproducibility

Accessible to developers familiar with functional programming

Ui Styling

Minimal; relies on .NET visualization libraries

Plotly.NET or XPlot for charts

Optional integration with WPF/WinForms for dashboards

Focus on programmatic visualization

Web-based UI via F# and SAFE stack

State Management

Immutable values maintain predictable state

Use modules for encapsulating financial computations

Async workflows manage real-time or streaming data

Pipelines allow controlled transformations

Pattern matching ensures safe branching and state handling

Data Management

Financial time series and market data

CSV, JSON, SQL, or API-sourced data

In-memory Deedle frames for computation

Exported results to Excel, databases, or visualization dashboards