Counterpoint Dynamics

Where quantitative insight meets engineered systems.

Specialist consulting for corporate, investment and retail banking.

We connect financial expertise, software architecture and advanced computation to solve complex risk and capital-markets problems.

cpStudio + cpδ

Transparent derivative pricing and risk analytics.

An independent platform connecting pricing, sensitivities, market risk, margin, xVA and counterparty analytics in one reproducible framework.

See cpStudio in action

From trade idea to a defensible result.

Start with the one-minute overview, then explore how cpStudio brings pre-trade economics, guided workflows and full traceability into one platform.

Pre-trade · 1 min

Know the trade before you book.

Price the rate—and see xVA, initial margin, capital and risk before committing.

Assistant · 1 min

Ask in plain words.

Navigate, complete workflows and interrogate results with an assistant that does the clicking.

Traceability · 1 min

Trace every number to its source.

Open a result into its formula, follow every input and review each versioned change.

The quantitative foundation

One pricing engine. Every result traceable.

cpδ provides the pricing foundation beneath cpStudio: explicit traced formulas, exact closed-form sensitivities and Monte Carlo analytics, optimized across CPU, GPU or cluster infrastructure.

F# pricing engineC# servicesPython + JupyterPostgreSQL
01

Trade capture

Capture one-line descriptions, detailed instruments or bulk trade imports, with conventions completing required detail.

02

Market data & curves

Manage versioned timeseries, reference rates and scheduled imports, with convention-driven curve bootstrapping and calibration.

03

Pricing & analytics

Run valuation, exact sensitivities and scenario analytics at trade, portfolio, counterparty or entity scope.

04

Open workflow

Work through the API, Python or Jupyter, then export formulas and their input data to Excel for independent verification.

Market risk—the core differentiator

Know the exposure. See exactly how it was derived.

Exact risk

Derive sensitivities from the traced pricing formula or by bumping curves and revaluing.

Transparency

Inspect the formula behind a price together with linked market data and versioned records.

Independent challenge

Export the live formula and data so disputed results can be reproduced outside cpStudio.

Regulatory measures

SIMM & FRTB

Sensitivity-based initial margin with forecasting, and market-risk regulatory capital built on the same exact sensitivity capability.

Counterparty credit risk

CVA / DVA / FVA & PFE

Monte Carlo exposure simulation by netting set, with exposure profiles over time at netting-set or counterparty scope.

Hedge effectiveness

Micro & macro hedge effectiveness

Assess hedge effectiveness at individual relationship or portfolio level, with the ability to include xVA in the calculation.

A typical market-risk workflow

  1. 01CaptureDescribe the trade
  2. 02PriceGenerate a traced formula
  3. 03SensitivitiesPV01, FX Delta, Vega, Gamma
  4. 04ReviewInspect formula and data
  5. 05ReproduceVerify independently in Excel
  6. 06Margin / xVAExtend the same foundation

One team, connected disciplines

Built for problems that cross finance and technology.

Since 2013, Counterpoint Dynamics has brought software architecture, trading and risk management into one consulting practice. We understand that a pricing model is only as effective as the data and systems around it.

Our quants, developers and integration engineers work across traditional boundaries—particularly where regulation, complex data and simulation-intensive workloads meet.

01

Financial context

Trading, risk and regulation understood from the inside.

02

Quantitative depth

Models and methods grounded in robust analysis.

03

Engineering discipline

Systems designed to perform, integrate and scale.

Our expertise

What we do

From models to production systems, we work across the full problem.

Quantitative Analysis and Development
  • Hedge effectiveness calculation
  • Derivative pricing libraries
  • XVA Optimisation
  • Model validation for market risk and front-office derivative pricing models, VaR and Expected Shortfall.
Financial Engineering/ Risk Analysis
  • Modelling of derivatives on risk and front-office software.
  • Implementation of FRTB, SIMM, VaR methodologies etc.
  • CVA, DVA, FVA and PFE calculation and validation.
  • Front Arena, Adaptiv Analytics, Murex, Matlab, IBM Algorithmics Riskwatch/ARA/ASE, SAS, Maitland.
Business Analysis and Software implementation
  • Feeds between source systems and risk systems for derivatives, market data, counterparty information and financial information.
  • Implementation of credit risk, market risk, prime broking, securitization and payments systems.
  • Trader specific interfaces for specific use cases
Software development and architecture
  • Full stack development using .Net - C#, F#, Javascript, Angular, SQL and Python.
  • Application Architecture.
  • Cross siloed business product development, enabling cross selling of retail banking clients with CIB type products
Computational scaling
  • CUDA, GPU and Cloud based scaling.
  • Monte Carlo simulation.

Careers at Counterpoint

Bring your curiosity to difficult, consequential problems.

We’re interested in people with backgrounds in actuarial science, engineering, mathematics, risk and software development.

Start a conversation

Trusted relationships

Experience across South African finance.

We are proud to have worked with leading banks and financial institutions.

Standard Bank

Investec

Nedbank

LibFin

RMB

ABSA

Ideas in practice

Latest insights

Notes from the intersection of quantitative finance and technology.

The fall and slight rise of the GPU

David Naylor
Quant FinanceGPUPerformance

Finance runs in double precision and makes decisions; GPUs prefer neither. Measured on an A100: where compiling our pric…

Read article

CP∂ versus Strata and QuantLib + ORE

Counterpoint Dynamics Engineering
Quant FinancePricing LibrariesInteractive

An interactive comparison of CP∂, OpenGamma Strata and QuantLib with ORE across instrument coverage, analytics, margin a…

Read article

Porting a SIMM calculator from Python to F# and C#

Armando Oberholzer
Quant FinanceSoftware EngineeringcpStudio

Three autonomous ports of our Python SIMM calculator reveal how design, independent verification and careful benchmarkin…

Read article

Five implementations, one set of trades, and the bug our tests could not see

David Naylor
Quant FinanceModel ValidationcpStudio

One calendar-free trade specification, five implementations and a closed form exposed two serious defects our own tests…

Read article

Mapping cpStudio: An Interactive Architecture City

Counterpoint Dynamics Engineering
cpStudioSoftware ArchitectureInteractive

Explore cpStudio as an interactive city: its major systems become districts, modules become buildings, and the connectio…

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We rebuilt the ISDA CDS Standard Model from its published test grids. The grids fought back.

David Naylor
Quant FinanceCredit DerivativescpStudio

Reproducing the ISDA CDS Standard Model to the cent exposed undocumented conventions, defects in the published test data…

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The Hidden Cost of Doing Things "Properly"

Counterpoint Dynamics Engineering
Software DevelopmentBest Practices

There's a quiet tragedy in software development that we don't talk about enough: the projects that fail not because they…

Read article
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010 900 4620

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