Rhisco Group and Julia Computing are delighted to announce a new partnership to collaborate in providing solutions in the regulatory risk and capital space.

As a highly-specialised boutique firm with significant expertise in risk analysis and various technologies, Rhisco provides services and solutions on risk capital technology implementations for banks, insurance and other financial companies. Julia Computing builds products focused on productivity, performance and scalability for multiple areas of data science and numerical computing leveraging the Julia programming language. Julia Computing’s products – JuliaPro, JuliaRun, and JuliaFin – are used for modelling financial contracts, asset management, risk management, algorithmic trading, backtesting, and many other areas of computational finance.

By integrating JuliaFin and other products of Julia Computing, Rhisco will significantly enhance its integration platform, Tegra, improving the technology offered to clients that need high performance solutions for risk management and regulatory requirements.

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.

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, scalability, capacity and productivity. Julia provides parallel computing capabilities out of the box and literally infinite scalability with minimal effort. With more than 1 million downloads and +161% annual growth, Julia adoption is growing rapidly in finance, energy, robotics, genomics and many other fields.

About Rhisco Group and TEGRA

Rhisco was founded in 2010 by expert professionals, supporting clients internationally through its head office in London, a subsidiary in Mexico, and a network of associates and consulting partners in Europe, Latin America, Middle East and Africa. The people behind Rhisco have professional, quantitative and technical acumen acquired through several years of industry and consulting practice internationally.

Rhisco has developed TEGRA, a modular integration platform to enhance existing client’s risk infrastructure and accelerate implementation of new age risk technology, including cloud-computing. TEGRA software components provide a significant edge to pricing/risk engines developed by third parties or by the client. This is done through innovative technology for data intelligence, distributed computing, and advance aggregation.

Online quantitative finance magazine Wilmott featured Julia yet again.

Julia Computing’s Dr. Simon Byrne and Dr. Andrew Greenwell engage the magazine readers in a solution they built in Julia, that uses Automatic Differentiation (AD) to calculate price sensitivities, also known as the Greeks.

Fast and accurate calculation of these price sensitivities is extremely crucial in understanding the risk of an option position, and using AD in Julia achieves precisely that.

Traditionally, the world is familiar with using finite-difference approximation for the same calculations. Simon and Andrew go on to argue how that solution is numerically unstable, and how their solution will not only shoot up numerical accuracy, but will also eliminate computational overheads.

To put that in context, there are C++ libraries that assist in these calculations too, QuantLib being one of them. However, a simple implementation of a Cox–Ross–Rubinstein tree (for pricing an American put) with AD in Julia fared 3x times faster than with the C++ library. The code for this example is available here.You can also read the article to know more.

At Julia Computing, we curate all this and much more as part of JuliaFin, a suite of Julia packages that simplify the workflow for quantitative finance, including storage, retrieval, analysis and action.

Julia is already solving a variety of use cases. 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 all using Julia to solve some of their very complex and challenging quantitive computational problems.

Bengaluru, India – Julia Computing featured at one of India’s most prominent AI conferences, demonstrating two very powerful Deep Learning use cases the company is trying to solve using Julia on Intel’s hardware.

The two day event was organized and crafted to showcase robust AI-supporting hardware and software solutions from Intel and it’s partners.

Julia Computing Inc, one of Intel’s partners from India, took centre-stage on day two for their demonstrations. The first of the two demos, namely Neural Styles caught the audience’s fancy – building a neural network imposing the style of one image onto another. Our very own Ranjan Anantharaman took a live picture of the audience and applied transforms to it in real-time.

The second demo targeted solving the serious problem of identifying if a person has symptoms of Diabetic Retinopathy by taking only but an image of his retina as an input, without any human intervention or prediction.

The following video holds a glimpse of what the two firms envision as the future of AI.

Julia Computing and Intel – Acelerating the AI revolution

Also see this whitepaper on Intel and Julia Computing working together on an AI stack.

About Julia

Julia is the simplest, fastest and most powerful numerical computing language available today. 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 for data scientists, algorithmic traders, quants, scientists, and engineers who need to solve massive computational problems quickly and accurately.

Julia offers an unbeatable combination of simplicity and productivity with speed that is thousands of times faster than other mathematical, scientific and statistical computing languages.

Partners and users include: Intel, The Federal Reserve Bank of New York, Lincoln Laboratory (MIT), The Moore Foundation and a number of private sector finance and industry leaders, including several of the world’s leading hedge funds, investment banks, asset managers and insurers.

About Julia Computing, Inc.

Julia Computing, Inc. was founded in 2015 to develop products around Julia such as JuliaFin. These products help financial firms leverage the 1,000x improvement in speed and productivity that Julia provides for trading, risk analytics, asset management, macroeconomic modeling and other areas. Products of Julia Computing make Julia easy to develop, easy to deploy and easy to scale.