Banking & Finance

Leverage Julia’s superior speed and performance for quantitative finance, trading, optimization, arbitrage, asset management and risk analysis

Why Julia in Finance?
It’s simple: Speed + Performance + Scalability + Ease of Use.

In the private sector, BlackRock, the world’s largest asset manager, is using Julia to upgrade its analytics capabilities.

Nobel prize winner Thomas J. Sargent says Julia is critical for his work because the next generation of macroeconomic models is very computationally intensive with large datasets and large numbers of variables. These macroeconomic models and their forecasts help solve large constrained optimization problems using massive datasets to inform policy analysis.

Economists at the Federal Reserve Bank of New York are porting their Dynamic Stochastic General Equilibrium (DSGE) models to Julia (DSGE.jl by Erica Moszkowski, Micah Smith, Pearl Li et. al.). They said they chose Julia because, “as the models that we use for forecasting and policy analysis grow more complicated, we need a language that can perform computations at high speed. Julia boasts performance as fast as that of languages like C or Fortran, and is still simple to learn. We want to address hard questions with our models—from understanding financial markets developments to modeling households’ heterogeneity—and we can do so only if we are close to the frontier of programming.”

They reported a 10x increase in the speed of model estimation, a 6x increase in speed for another algorithm and an 11x speed increase for the FRBNY’s ‘solve’ test - which is crucial because this test is run hundreds of thousands of times.

Aviva, one of the world’s largest insurers, is using Julia to comply with the European Union’s Solvency II regime and reported speed increases from 20x upto 1000x compared to their existing implementations. Furthermore, they reduced the code from 14,000 lines of a proprietary analytics language to 1,000 lines in Julia. This doesn’t just increase speed, efficiency and productivity - it also reduces errors and time spent checking and debugging code.

Julia is the fastest and most productive high-level dynamic computing language for:

Algorithmic trading

Risk analysis

Macroeconomic modeling


Economic forecasting

Options pricing

Market simulation

Monte Carlo simulations

Foreign exchange

Asset management

How does Julia improve on legacy systems?

Tight loops and easy parallelism for Monte Carlo simulations
Increase speed up to 1,000x
Eliminate the need for different languages for prototyping (e.g. Python, R) and deployment (e.g. C, C++)
Use a single language for model estimation and deployment
Shorter, tighter simpler code - more efficient, easier to check and debug
Ease of use - simple to learn, simple to program
Faster time to market for new models, and faster updates and upgrades which provide an important advantage in a highly competitive marketplace
Big data - as the number of variables, complexity and computational intensity increases, Julia provides critical improvements in capacity and productivity

See how Julia is being used in banking & finance

Erica Moszkowski
Federal reserve bank of new york

Julia at NY Fed

Aman thind
Best x

Powering Financial Analytics

related case studies


One of the UK’s largest insurers deploys Julia to meet strict Solvency II requirements

read more

Nobel Prize Laureate (Economics) Thomas J. Sargent

Nobel prize laureate Thomas J. Sargent created QuantEcon in Julia for quantitative economic modeling

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Global asset manager uses Julia for large-scale Monte Carlo simulations

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Berkery Noyes

Investment bank uses Julia for mergers and acquisitions

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Federal Reserve Bank of New York

The most powerful branch of the world’s most powerful central bank uses Julia to power its Dynamic Stochastic General Equilibrium model

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World’s largest asset manager uses Julia to power its trademark Aladdin platform

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Now-Casting Economics

Uses Julia to provide real-time estimates of current market conditions

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State Street / BestX

State Street / BestX uses Julia for foreign exchange trade analysis

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Brazilian National Bank for Economic and Social Development (BNDES)

BNDES uses Julia for asset and liability modeling BNDES increased speed 10x using Julia.

read more
related packages & products

For advanced time series analytics

Full integration with Bloomberg

A bespoke Julia library for advanced time series analytics, trade strategy design and execution

Deployment and scalability

Enterprise support

Enterprise governance, private package management

related articles
Waters Technology | 01 Feb 2017
Liberty Street Economics | 03 Dec 2015
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