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:
Monte Carlo simulations
How does Julia improve on legacy systems?
See how Julia is being used in banking & finance
Federal reserve bank of new york
One of the UK’s largest insurers deploys Julia to meet strict Solvency II requirements
Nobel Prize Laureate (Economics) Thomas J. Sargent
Nobel prize laureate Thomas J. Sargent created QuantEcon in Julia for quantitative economic modeling
Global asset manager uses Julia for large-scale Monte Carlo simulations
Investment bank uses Julia for mergers and acquisitions
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
World’s largest asset manager uses Julia to power its trademark Aladdin platform
Uses Julia to provide real-time estimates of current market conditions
State Street / BestX
State Street / BestX uses Julia for foreign exchange trade analysis
Brazilian National Bank for Economic and Social Development (BNDES)
BNDES uses Julia for asset and liability modeling BNDES increased speed 10x using Julia.
For advanced time series analytics
Full integration with Microsoft Excel
Full integration with Bloomberg
A bespoke Julia library for advanced time series analytics, trade strategy design and execution
Deployment and scalability
Enterprise governance, private package management
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