Julia Seminar for Quants in London

Last week’s Julia in Finance seminar in partnership with the CQF Institute, held in London, was a great success. More than 370 finance professionals registered online or attended in person. Register for Free Video.

2017 is turning out to be the year that Julia moves from early adopters within the finance community into the mainstream

Last week’s Julia in Finance seminar in partnership with the CQF Institute, held in London, was a great success.  More than 370 finance professionals registered online or attended in person.

Along with customer and partner presentations, there were product demonstrations by Julia Computing for financial quants to gain efficiencies in their daily work and for financial firms to save millions of dollars through higher productivity. This included Miletus, a component of the JuliaFin product that provides a flexible contract definition language for creating standard and custom payoffs, along with a suite of valuation routines that can be applied to relevant contracts. Simon Byrne demonstrates Miletus in this video, and it is also available for download.

Julia Computing also demonstrated JuliaRun, which enables quants to leverage large scale distributed compute facilities in Julia with a single click. It allows easy scaling of Julia processes on public or private clouds, leveraging Kubernetes and Docker.

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Customer and partner presentations included:

  • Aviva, one of Europe’s largest insurance companies: Using Julia for Solvency II compliance and increased the speed of their risk modeling by 1,000x
  • BestX, foreign exchange analytics: Using Julia to comply with MIFID II regulations in foreign exchange trades
  • Microsoft: Using Julia on Microsoft Azure

This seminar followed a similar Julia Day for Finance event held in New York in November.

According to Julia Computing CEO Viral Shah, “Finance professionals in New York and London can’t get enough of Julia.  2017 is turning out to be the year that Julia moves from early adopters within the finance community into the mainstream.”

For more information, please visit JuliaComputing.com or read Waters Technology’s “Inside Look at How Traders and Economists Are Using the Julia Programming Language.”

About Julia Computing and Julia

Julia Computing (JuliaComputing.com) was founded in 2015 by all the co-creators of the Julia language to provide support to businesses and researchers to get the most out of Julia.

Julia is the fastest modern high performance open source computing language for data and analytics. It combines the functionality and ease of use of Python, R, Matlab, SAS and Stata with the speed of Java and C++. Julia delivers dramatic improvements in simplicity, speed, capacity and productivity.

  1. Julia is lightning fast. Julia provides speed improvements up to 1,000x for insurance model estimation, 225x for parallel supercomputing image analysis and 11x for macroeconomic modeling. Learn how Julia solves the two language problem in the Julia paper published in the prestigious SIAM Review journal.
  2. Julia is easy to learn. Julia’s flexible syntax is familiar and comfortable for users of Python, R and Matlab. It is taught at dozens of universities and in MOOCs on Coursera and EdX.
  3. Julia provides unlimited scalability, parallel and distributed computing out of the box
  4. Julia integrates well with existing code and platforms. Users of Python, R, C++, Java and other languages can easily integrate their existing code into Julia.
  5. Elegant code. Julia was built from the ground up for mathematical, scientific and statistical computing, and has advanced libraries that make coding simple and fast, and dramatically reduce the number of lines of code required – in some cases, by 90% or more.
  6. Julia solves the two language problem. Because Julia combines the ease of use and familiar syntax of Python, R and Matlab with the speed of C, C++ or Java, programmers no longer need to estimate models in one language and reproduce them in a faster production language. This saves time and reduces error and cost.

 Employers looking to hire Julia programmers in 2017 include: Google, Apple, Amazon, Facebook, IBM, BlackRock, Capital One, PricewaterhouseCoopers, Ford, Oracle, Comcast, Massachusetts General Hospital, NaviHealth, Harvard University, Columbia University, Farmers Insurance, Pilot Flying J, Los Alamos National Laboratory, Oak Ridge National Laboratory and the National Renewable Energy Laboratory.

 Julia users and partners include: Amazon, IBM, Intel, Microsoft, DARPA, Lawrence Berkeley National Laboratory, National Energy Research Scientific Computing Center (NERSC), Federal Aviation Administration (FAA), MIT Lincoln Labs, Moore Foundation, Nobel Laureate Thomas J. Sargent, Federal Reserve Bank of New York (FRBNY), Capital One, Brazilian National Development Bank (BNDES), BlackRock, Aviva, Conning, Berkery Noyes, BestX, Path BioAnalytics, Invenia, AOT Energy, AlgoCircle, Gambit, Augmedics, Tangent Works, Voxel8, UC Berkeley Autonomous Race Car (BARC) and many of the world’s largest investment banks, asset managers, fund managers, foreign exchange analysts, insurers, hedge funds and regulators.

Universities and institutes using Julia include: MIT, Caltech, Stanford, UC Berkeley, Harvard, Columbia, NYU, Oxford, NUS, UCL, Nantes, Alan Turing Institute, University of Chicago, Cornell, Max Planck Institute, Australian National University, University of Warwick, University of Colorado, Queen Mary University of London, London Institute of Cancer Research, UC Irvine, University of Kaiserslautern.

Julia is being used to: analyze images of the universe and research dark matter, drive parallel computing on supercomputers, diagnose medical conditions, provide surgeons with real-time imagery using augmented reality, analyze cancer genomes, manage 3D printers, pilot self-driving racecars, build drones, improve air safety, manage the electric grid, provide analytics for foreign exchange trading, energy trading, insurance, regulatory compliance, macroeconomic modeling, sports analytics, manufacturing and much, much more.

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