Portfolio | Pricing | Risk | Forecasting | Execution
Plan a Call With UsFinancial products are full of decisions that can be optimised: how a portfolio is built, how a loan or premium is priced, how risk is hedged, when an order is executed. Too often those decisions still run on spreadsheets, rules of thumb and backtests that look better than reality. We build the algorithms and quant models that improve them, measured honestly against a baseline, explainable to risk and regulators, and yours to keep.
Quantitative models and optimisation algorithms that make financial products perform better, from research to production.
Better risk-adjusted returns from the same universe: portfolio construction, rebalancing and constraints modelled as a real optimisation problem.
Price loans, deposits, premiums and fees on data, not gut feel: models that balance margin, volume and risk across your book.
Credit, market and liquidity risk models with stress tests and scenarios, documented so risk, audit and regulators can follow every step.
Time-series forecasts and signal research for flows, volumes, defaults and markets, always measured out of sample against a baseline.
Point-in-time data, walk-forward testing and no look-ahead bias. We validate existing models as rigorously as we build new ones.
Algorithms that cut transaction costs and slippage: order scheduling, hedging and rebalancing logic, tested before they touch real money.
Pick your field. Not listed? If it's a financial product with a decision to optimise, ask us.
Optimise weights under real constraints: turnover, sector limits, ESG rules and liquidity.
Rebalance when it pays, not on the calendar: cost-aware triggers and trade sizing.
Test factors and signals on point-in-time data with honest out-of-sample results.
Portfolio construction as a real optimisation problem: the same constraints and the same universe, moved to the efficient frontier.
Point-in-time data, realistic costs, walk-forward validation. No look-ahead bias.
Loss distributions, VaR and stress scenarios, documented for risk and regulators.
From first scan to a validated model in production.
Loans, deposits, premiums and fees priced where margin and volume meet.
Every model is measured against a baseline before it ships: portfolios, prices, risk models and execution alike.
Four principles behind every model we build.
Impressive results on paper, no comparison with what you do today.
Every model measured out of sample against an agreed baseline or benchmark.
Backtests on cleaned-up data that quietly use information from the future.
Point-in-time data, realistic costs and walk-forward validation as standard.
A black-box model nobody can explain to the risk committee.
Documented assumptions, validation reports and a full audit trail.
A vendor model you rent, and a permanent dependency.
Your team works alongside ours. You own the code, the models and the know-how.
Short, methodical engagements, typically around eight weeks. Your team works alongside ours, so the knowledge stays in-house.
Map the product, the data and the decision; agree the baseline we must beat.
Build the algorithm or quant model on point-in-time data.
Walk-forward, out of sample, stress-tested and documented.
Running in production, explainable, and yours to keep evolving.
Tell us the decision: a portfolio, a price, a risk model or an execution problem. We'll tell you honestly what's possible.
Plan a Call With Us