Wilmott – Why Julia Matters for Computational Finance

By: Julia Computing, Inc.

Re-posted from: http://juliacomputing.com/blog/2017/02/08/wilmott.html

In the November 2016 issue of Wilmott
Magazine
, Julia Computing’s Viral
Shah and Simon Byrne explain why Julia is taking the field of
quantitative finance by storm.

Why are so many quants from investment banking,
insurance,
asset
management
,
fund
management
,
foreign exchange
analytics
,
commodity trading, energy trading, central
banking
and risk
analysis switching to Julia?

Finance quants find Julia the optimal finance solution for a number of
reasons:

  • Julia is the fastest modern language for financial, mathematical,
    statistical and scientific computing

  • Julia delivers lightning fast speed – speed improvements up to 11x
    for macroeconomic
    modeling
    , 225x
    for parallel
    supercomputing

    and 1,000x for insurance risk model
    estimation

  • Julia is the only modern financial, mathematical, statistical or
    scientific language that can handle massive datasets updated in real
    time, such as financial tick data

  • Julia runs on your desktop, laptop, enterprise server, private or
    public cloud

  • Julia is optimized for supercomputers with
    accelerators
    and
    parallel
    computing

  • JuliaFin is fully integrated with Excel and Bloomberg

  • JuliaFin includes Miletus, a custom finance package to design and
    execute real-time trading strategies

  • Julia is easy to learn with flexible syntax that is familiar to
    users of Python, R and Matlab

  • Julia integrates well with existing code and platforms

  • Julia code is elegant – advanced libraries make coding simple and
    reduce the number of lines of code – in some cases, by 90% or more –
    resulting in a solution that is faster, easier to code, analyze and
    debug

  • Julia solves the two language problem – because Julia combines the
    ease of use and familiar syntax of Python, R, Matlab, or Stata 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. With Julia, these steps can be performed in a
    single high-level, high-capacity, high-speed environment.

No wonder users such as
BlackRock, the
Federal Reserve Bank of New
York
, Nobel
Laureate Thomas J.
Sargent
,
and the world’s largest investment banks,
insurers,
risk managers, fund
managers
, asset
managers, foreign exchange
analysts
, energy
traders, commodity traders and others are switching to Julia.