JuliaFin is a suite of Julia libraries that simplify the workflow for quantitative finance including storage, retrieval, analysis and action. These include Miletus, a DSL (domain specific language) for defining financial contracts; a high performance scalable time series database that can work with native Julia data types, and connectivity to common data APIs.

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
Time Series Database

JuliaFin also includes a high performance time series database, with the ability to store terabytes of historical tick data and quickly retrieve the necessary working set. Data can be loaded from a variety of data sources -- historical data can be loaded from CSV or HDF5 files, or sourced from providers such as Bloomberg, Quandl and Yahoo Finance. This can be further enhanced with live data from Bloomberg or Reuters. It combines this data store with a powerful computational finance Domain Specific Language that makes it easy to price various financial instruments. Julia programs can run “inside” the database, thus avoiding the need to extract data with SQL. Both large-scale batch workflows as well as real-time analytics are supported.

Our columnar data store is set apart from existing products in this area by its tight-knit integration of data and algorithms with the full power of the Julia ecosystem. High-performance analytics, easy parallelism, graphics and leveraging integrations with spreadsheets and data sources are the keys to simplifying algorithmic trading, backtesting, and risk analytics.

Integration with Excel

Presenting to you, JuliaInXL - a package specifically designed to enhance spreadsheets with Julia, to empower users with capabilities for accessing the Julia language and it's rich package ecosystem from within the world's most popular spreadsheet.

This package makes it a cake walk to call Julia functions from Excel, enables loading files and functions into a new or existing Julia process from the Excel ribbon. It also allows switching a single Excel session between multiple separate Julia environments, and lets you effortlessly develop and deploy Julia functionality to Excel by using Juno and JuliaInXL together.

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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