Electronic & Algorithmic Trading
Electronic execution depends on the stack behind the order: OMS, EMS, routing, market access, venue connectivity and algo controls.
Markets & Trading
Quant Development & Trading Models
We help trading businesses design, prototype, test and govern quant models, analytics and trading tools.
Overview
Trading businesses depend on models: execution logic, pricing, risk, signals, portfolio analytics, liquidity analysis, hedging tools and decision support.
The challenge is not only building the model. It is making sure the model is explainable enough to use, tested against the right data, integrated into the workflow and governed for the environment it operates in.
Capmark helps clients move quant and trading-model work from research, spreadsheet or prototype into a controlled delivery path. We work across business, quant, technology, risk, compliance and operations so the model fits the desk and the control environment.
We do not position this as a promise of trading performance. We help clients build, test, govern and operationalise the tools and models they need to run trading activity with better evidence and control.
What we do
We help define the model purpose, inputs, assumptions, outputs and intended use. The work connects the quant logic to the trading workflow, control requirements and decisions the model is meant to support.
We build prototypes and backtests that help teams test execution logic, signals, routing choices, pricing assumptions or portfolio rules. The emphasis is on disciplined testing, clean data, clear assumptions and evidence that can be reviewed.
We develop analytics for execution quality, slippage, spread capture, fill rates, venue performance, market impact and routing outcomes. These tools support algorithm selection, broker review, best execution and post-trade improvement.
We help move quant logic from spreadsheet, notebook or research code into controlled implementation. That can include Python services, APIs, data pipelines, model libraries, testing, release control, monitoring and integration with trading or risk platforms.
We document the model purpose, assumptions, limitations, testing, approval path and monitoring approach. Controls are designed around the way the model is used, whether it supports execution, pricing, risk, reporting or decision support.
We define the monitoring needed once models are live: performance drift, data-quality issues, exceptions, threshold breaches, user overrides and control evidence. Monitoring gives the desk and control functions a shared view of whether the model is behaving as expected.
What to expect
A senior practitioner leads the work with input from trading, quant, technology, risk, compliance and operations. The first stage defines the model purpose, users, data sources, decisions supported, control requirements and delivery constraints.
The work can then move through prototype, backtest, validation, implementation, testing, release control and monitoring.
Where the model affects client orders, execution decisions, pricing, risk or regulatory obligations, governance and evidence are built into the delivery path from the start.
01
Assess
Establish the current state, the constraints, the risks and the value at stake.
02
Define
Shape the target model and the business case with the executives who own the outcome.
03
Mobilise
Stand up the team, the plan and the governance around the outcome.
04
Implement
Design, build and test the change, with the business alongside.
05
Sustain
Cutover, hypercare and handover, so the business runs it under its own control.
The same five stages on every engagement, led by senior practitioners end to end. How we work
Client result
Proven in the work, not the pitch.
Capital Markets · Trading Technology
eFX and equities algorithmic-trading platform engineering for a US investment bank
A US Investment Bank · eFX & Equities Algorithmic Trading
The bank partnered with us to enhance its eFX platform, built on the third-party Integral solution, and its internal equities algorithmic trading platform: engineering back-to-back trades into the US book to manage risk, enhancing the Calypso-integrated middle office and updating order management systems including OPICS and Fenics.
- Integral
- Vendor eFX platform enhanced
- B2B
- Automated risk transfer to the US book
- Calypso
- Middle-office integration enhanced
- OPICS + Fenics
- Order management systems updated
Read the case study
Insights
Related thinking.
Get in touch
Talk to a Partner about Quant Development & Trading Models.
Tell us what needs to change and where the pressure or risk is showing.