Welcome to BRODA
BRODA supports all areas of information systems specializing in the development and marketing of innovative scientific software. BRODA also offers consultancy services to financial institutions and produces specialist financial software for quantitative analysts.
BRODA's success formula has been coined by talented people using robust technologies to meet complex business requirements. Through alliances with professionals from all over the world BRODA provides effective solutions for both large and small companies, tailoring software to meet the needs of our customers.
Company Brief
Banks today are looking to advance approaches that will ensure available capital is put to its most effective use. One way to improve profitability is to invest in IT infrastructure and new software that will better manage risk, decrease operating costs, and help drive growth. Monte Carlo (MC) simulation is unique universal method and it is at the heart of pricing and risk management engines.
Historically MC Methods have been used in the valuation of options with multiple sources of uncertainty or with complicated features such as path dependent structures. The MC method solves a problem by simulating the underlying process and then calculating the (average) result of the process. Basel III introduces two major changes in risk assessments: the Credit Valuation Adjustment (CVA) capital charge, and the new calculation of EEPE (Effective Expected Positive Exposure) to address wrong-way risk. Both of these measures require accurate estimation of credit exposure, which enables banks to actively manage counterparty credit risk and help reduce regulatory capital. The expected exposure is computed by simulating many future scenarios of risk factors for the given contract or portfolio. The number of risk factors (interest rates, stock indices, foreign exchange rates, etc.) multiplied by the number of time steps in the future can result in tens of thousands of dimensions. Hence, risk management engines require the use of multidimensional MC methods.
Although MC is a universal method widely used in finance, the rate of convergence of MC is rather slow. A much higher rate of convergence can be obtained by using quasi-Monte Carlo (QMC) methods based on Sobol' low discrepancy sequences which provide the best solution for applications in finance requiring MC methods.
Paul Glasserman in his highly acclaimed book "Monte Carlo Methods in Financial Engineering" (2004) says: “Preponderance of the experimental evidence amassed to date points to Sobol sequences as the most effective quasi-Monte Carlo method for application in financial engineering.” Comparison between MC and QMC shows that applications based on QMC converge up to two orders of magnitude faster without loss of accuracy than those based on MC. For the same number of scenarios, QMC methods show much more accurate and stable results properties than MC, which result in a dramatic reduction of computational time. Switching from MC to QMC is a straightforward replacement of MC generator by the Sobol sequence generator and it offers a cost-effective solution for improving bank’s existing computer capabilities.
BRODA has been developing, testing and distributing high-dimensional Sobol sequence generators for more than 20 years. All our generators were developed jointly with Prof. Sobol. Comparison tests show that our SobolSeq generators outperform all other known generators both in speed and accuracy. BRODA’s high dimensional Sobol sequences generators have become the industry standard in finance.
Take a look at our products and feel free to contact us for any additional information.
September 12, 2023
BRODA is pleased to announce publication of the paper "The importance of being scrambled: supercharged Quasi Monte Carlo" in the
Journal of Risk,26(1),1-20,2023
November 11, 2022
BRODA presented a talk on "The importance of being scrambled: supercharged Quasi Monte Carlo" at QuantMinds 2022 conference.
The full version of this talk is also published as a paper
May
5, 2021
SS&C Technologies Holdings, Inc. (Nasdaq: SSNC) today announced an exclusive partnership with BRODA Ltd. to provide BRODA's high dimensional Sobol sequence generators to financial services firms.
"SS&C has embedded BRODA's Sobol sequence generators within the SS&C Algorithmics suite of solutions to optimize risk performance."
August
1, 2020
BRODA with a team from Intel developed the "block" version of the SobolSeq65536 sequence generator with integrated
Intel oneAPI Math Kernel Library:
"Toward Accurate and Highly Performant Simulations with BRODA's SOBOL Quasi-random Number Generator"
December
10, 2019
BRODA and a team from KX systems - the leading provider of in-memory, time-series database technology joined forces and linked kdb+/q with advanced BRODA's SobolSeq generators: "Kx Whitepaper: Option Pricing Methods in kdb+/q"
March
14, 2018
BRODA and a team of bank practitioners present a series of talks on "Application of Quasi Monte Carlo Methods in Finance"
which covers Quasi Monte Carlo Methods from the basic theory to the benefits of using QMC in computations, including XVA's and counterparty risk measures with real world examples and simulations in the CQF Institute which is a part of
Fitch Learning.
February
12, 2018
BRODA released a new scrambled 131072 dimensional Sobol' sequence generator SobolSeq131072. Randomised QMC methods based on BRODA's SobolSeq131072
generator converge much faster in comparison the standard QMC.
August
15, 2017
BRODA congratulates Prof. Sobol'
on his 90th birthday. Prof. Sobol' is an outstanding mathematician internationally renowned for his fundamental works in mathematics. BRODA is proud to have a long term working relationship with Prof. Sobol. We wish him good health, new scientific achievements and many happy years ahead.
December
1, 2015
BRODA released a new 65536 dimensional Sobol' Sequence generator Not only this generator has very high dimensionality and employs the
super fast generation algorithm but the generated Sobol' sequences
satisfy Property A in all dimensions and property A' for the
adjacent dimensions. It was developed by Prof. Sobol' in collaboration with BRODA.
April 16, 2004
Wilmott magazine awarded Prof. Sobol' the first Wilmott fellowship.