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,
commodity trading, energy trading, central
banking and risk
analysis switching to Julia?
Finance quants find Julia the optimal finance solution for a number of
Julia is the fastest modern language for financial, mathematical,
statistical and scientific computing
Julia delivers lightning fast speed – speed improvements up to 11x
and 1,000x for insurance risk model
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
Julia is optimized for supercomputers with
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
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
Federal Reserve Bank of New
Laureate Thomas J.
and the world’s largest investment banks,
risk managers, fund
managers, foreign exchange
traders, commodity traders and others are switching to Julia.
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