JuliaFin is a suite of products that simplify the workflow for quantitative finance including storage, retrieval, analysis and action.

JuliaFin is a collection of four components - Miletus, JuliaDB, JuliaInXL, and Bloomberg connectivity.

NOTE: - JuliaPro is a prerequisite for installing all JuliaFin components

Name Description Pricing
Miletus A Domain Specific Language for defining financial contracts and executing them at high performance and at scale Contact us for pricing
JuliaDB A high performance in-memory and distributed database Contact us for pricing
JuliaInXL A product that Integrates Julia with Excel Contact us for pricing
Bloomberg Integration Integration with the Bloomberg data feed Contact us for pricing

Each of these components can be evaluated separately and purchased separately.

Contact us for pricing options and other terms. (JuliaFin is free for EDU users)


Miletus is a powerful financial contract definition and modeling language, along with a valuation framework written in Julia. The idea originated in research papers by Peyton Jones and Eber [PJ&E2000], [PJ&E2003].

Miletus allows for complex financial contracts to be constructed with a combination of simple primitive components and operations. When viewed through the lens of functional programming, this basic set of primitive objects and operations form a set of "combinators" that can be used in the construction of more complex financial constructs.

Miletus provides both basic the primitives for the construction of financial contract payoffs as well as a decoupled set of valuation model routines that can be applied to various combinations of contract primitives. In Miletus, these "combinators" are implemented through the use of Julia's user-defined types, generic programming, and multiple dispatch capabilities.

Learn more about Miletus
Read the docs Try Miletus
Dr. Simon Byrne
Julia Computing, Inc.
An introduction to Miletus

JuliaDB is a high performance database for in-memory and distributed computing. It is a coherent environment for analytics, all in Julia, for storing and computing on large distributed datasets.

JuliaDB lets you leverage Julia's built-in parallelism to fully utilize any machine or cluster, performing indexing, filtering, aggregation, machine learning, and more without loading full datasets into main memory. Results can be saved to distributed storage. Julia’s rich ecosystem of packages for plotting, statistics, deep learning and optimization (to name a few) interoperate with the system effortlessly. Julia is natively distributed and compiles user code to machine instructions that are as fast as C/C++ or Fortran. This combination allows sending arbitrary user code to data, wherever it lives, achieving seamless scalable computing.

Integration with Excel

JuliaInXL is a package that’s designed to enhance Microsoft Excel® spreadsheets with Julia. It empowers users to access the Julia language and its rich package ecosystem from within the world’s most popular spreadsheet.

The package lets users call Julia functions from Excel and enables loading files and functions into new or existing Julia processes from the Excel ribbon. It also allows switching a single Excel session between multiple separate Julia environments and lets users effortlessly develop and deploy Julia functionality to Excel by using Juno and JuliaInXL together.

Dr. Andy Greenwell
Julia Computing, Inc.
JuliaInXL: Enhancing spreadheets with Julia
Read the docs
Bloomberg Connectivity

The Bloomberg APIs provide easy access to real-time market data as well as historic data. The data can be directly loaded and analysed effortlessly.

JuliaFin provides a variety of modelling and pricing engines, a high performance time series data store, as well as interoperability with various databases and data feeds. This will allow traders to quickly price options under a variety of models and automatically identify potential arbitrage opportunities, quants to develop and backtest new strategies, and risk analysts to efficiently manage portfolio risk and counterparty exposure.

Read the docs

Contact us at [email protected] for pricing options.

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