JuliaFin is a suite of Julia libraries that simplify the workflow for quantitative finance including retrieval, storage, analysis and action. JuliaFin provides the fastest path from market data to market transactions by leveraging the full power of Julia to design and implement new strategies and conduct transactions when microseconds count.
Miletus.jl

JuliaFin includes Miletus, a powerful financial contract definition, modeling language, and valuation framework written in Julia. Such contract definition languages 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
Simon Byrne
Julia Computing, Inc.
Demo of JuliaFin/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.

Bloomberg API

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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