Re-posted from: http://juliacomputing.com/press/2016/11/22/julia-day.html
New York, NY – Julia Computing is pleased to announce Julia Day for Finance in New York on Wednesday, November 30 from 3:30-6:30 pm at Fitch Learning Center, 55 Broad Street, 3rd Floor, New York, NY 10004.
Julia Day for Finance is free and open to quants, algorithmic traders, macroeconomists and other finance professionals who want to learn about Julia. Julia is the high-performance, easy-to-learn mathematical and scientific computing language that is quickly becoming the tool of choice for FinTech and RegTech (Regulatory Technology) with banks, insurers, financial firms and regulators using Julia to assess and manage risk.
Julia users include the world’s largest asset manager (BlackRock), several of the world’s largest fund managers, hedge funds, insurers, foreign exchange analysts, sports analysts, Nobel Economics Laureate Thomas J. Sargent, the Federal Reserve Bank of New York (FRBNY), the Brazilian National Development Bank (BNDES), and many others.
To sign up, please visit JuliaComputing.com.
Come learn how and why so many New York and London finance professionals are switching to Julia.
- 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.
- Julia is easy to learn. Julia’s flexible syntax is familiar and comfortable for users of Python and R.
- Julia integrates well with existing code and platforms. Users of Python, R and other languages can easily integrate their existing code into Julia.
- 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.
- Julia solves the two language problem. Because Julia combines the ease of use and familiar syntax of Python and R 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.
About Julia Computing and Julia
Julia Computing was founded in 2015 by the co-creators of the Julia language to provide support to businesses and researchers who use Julia, the fastest modern open source programming language for data and analytics. Julia combines the functionality of quantitative environments such as Python and R with the speed of production programming languages like Java and C++ to solve big data and analytics problems. Julia delivers dramatic improvements in simplicity, speed, capacity and productivity.
Julia users and partners include: IBM, Intel, 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), Brazilian National Development Bank (BNDES), BlackRock, Conning, Berkery Noyes, BestX and many of the world’s largest investment banks, asset managers, fund managers, foreign exchange analysts, insurers, hedge funds and regulators. Julia is being used to analyze images of the universe and research dark matter, drive parallel computing on supercomputers, diagnose medical conditions, manage 3D printers, build drones, improve air safety, provide analytics for foreign exchange trading, insurance, regulatory compliance, macroeconomic modeling, sports analytics, manufacturing and much, much more.
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