The problems we are brought in to solve.
Weights were set once and adjusted by instinct. Nobody has tested whether the mix is actually efficient for the risk being carried.
Holdings sit across custodians, managers and asset classes. Concentration and correlation are invisible until something moves.
Quarterly packs are assembled manually, so they arrive late and cannot answer follow-up questions without more manual work.
Named deliverables, not capabilities.
Allocation and rebalancing modelled against your own holdings, constraints and liquidity needs, not a generic efficient frontier.
Drawdown, correlation, concentration and stress scenarios, so the downside is quantified rather than assumed.
Overlay structures and hedge logic designed around the exposures you actually hold, and automated where it makes sense.
Sharpe, Sortino, information ratio, standard deviation, beta to benchmark, max drawdown, sector and geography weights, gross and net returns, turnover.
Kush Mathow
Capital managed on behalf of others, running across several US brokers. We built the dashboard to design, backtest, deploy and monitor every strategy from one place, with intelligent order slicing and distributed execution at roughly 50ms, reduced slippage, and full internal control over what is live.
"Anyone looking for a properly built trading system can confidently trust the team end to end."
Projects like yours.
Drawn from live engagements. Client names are withheld throughout this segment.
Reporting across two brokers to a full institutional spec: Sharpe, Sortino, information ratio, standard deviation, beta to an MSCI World benchmark, max drawdown, sector and geography weights, gross and net returns, turnover ratio.
Allocation, exposure and concentration analysis across holdings, built in Python against the actual book rather than a model portfolio.
An algorithm already running was reviewed at code level and updated, establishing what still held before more capital went behind it.
Where a product is public we show it: CF Trading, Ticker Tape and iDividendStocks all have real screens on their case studies. Client trading systems are a different matter, and for those we will walk you through the architecture, the approach and the outcome on a call.
Read the full case studies.
Design, backtest, deploy and monitor across several US brokers from one interface, with order slicing and distributed execution at roughly 50ms.
Consolidated position, exposure and performance reporting across brokers and venues, with automation integrated into existing systems.
Four steps, fixed price before any build.
Free, with an engineer. If there is no defensible edge, or no viable product in it, we say so then.
Architecture, milestones and a fixed price, agreed before any build.
Milestone demos against your own data. Nothing touches capital untested.
A documented codebase your own developers can maintain. Retainer optional.
Common questions.
No. We integrate with whoever you already use, wherever they expose an API.
A build. Everything is specified around your holdings and constraints, and you own the code and IP on completion.
NDA on request before the first call. We do not keep a screenshot portfolio of client systems and we do not name clients without permission.
Tell us what you're working on.
A specialist reads every enquiry, not a sales team. Bring your rules, your current setup and your constraints, and we will tell you what we would build and roughly what it takes.
Get in touchQuants and engineers building trading and investment systems, infrastructure and products.