Quantitative investment technology
PromtFinance helps hedge funds, asset managers, family offices and trading firms design, validate and deploy quantitative strategies and institutional trading platforms — from alpha research to live execution.
Research → Data → Models → Backtesting → Portfolio → Risk → Execution → Monitoring → Production
Start from your problem — we’ll route you to the right engagement.
Strategy development, statistical arbitrage, factor research, machine learning, alternative data and independent validation.
Intrinsic-value and quantamental systems, research platforms, investment dashboards and portfolio construction.
Algorithmic trading platforms, execution engines, broker connectivity, order management and HFT infrastructure.
Multi-strategy fund platforms, portfolio optimization, real-time risk, reconciliation, monitoring and reporting.
We design, research, test and implement systematic strategies across equities, futures, FX, crypto and options — starting from your idea, academic research or proprietary signals.
An independent quantitative review before capital is allocated: we find where a backtest overstates the edge and where hidden risks sit.
Proprietary fundamental and quantamental equity research engines that turn valuation work into a repeatable, scalable process.
The internal operating system of a quantitative fund: many strategies, accounts and asset classes on one architecture.
Market-data and execution infrastructure for latency-sensitive strategies, designed around venue, asset class and latency budget.
Institutional portfolio engines for systematic and discretionary managers, with real-world constraints built in.
Risk built into the trading platform in real time — not a report produced after the fact.
Execution infrastructure that connects portfolio decisions to brokers and exchanges, and measures how well it executes.
Models are only as reliable as their data. We build research- and production-grade financial data pipelines.
Machine learning where it adds measurable value — validated with methods designed for noisy, non-stationary financial data.
Centralized research environments that make every experiment reproducible, from data to portfolio-level simulation.
Internal software for firms whose research is strong but whose tooling holds them back — including migrations and modernization.
Featured solution
Build a proprietary institutional equity research engine.
Ideal for: Asset managers, family offices, long-only and long/short equity funds, research firms.
Build an Intrinsic Value PlatformFeatured solution
One platform for strategies, portfolio construction, risk and execution.
Ideal for: Hedge funds, quant funds, proprietary trading companies.
Design My Hedge Fund PlatformFeatured solution
Low-latency architecture for execution-sensitive strategies.
Ideal for: Proprietary trading firms, crypto trading companies, HFT teams.
Discuss an HFT ArchitectureFeatured solution
From investment hypothesis to live trading.
Ideal for: Hedge funds, asset managers, family offices, fintech firms.
Discuss a StrategyAn impressive historical equity curve is not automatically a good strategy. Our objective is to determine whether an observed edge is likely to be a real, implementable investment advantage — before capital depends on it.
Request a quantitative reviewObjective, asset class, holding period, trading frequency, capital, risk limits, data and execution requirements.
Research methodology, data architecture, strategy and portfolio model, risk framework, execution and infrastructure.
A working research or software prototype to validate logic, workflow, performance and data before full build-out.
Strategy robustness, system reliability, data correctness, risk controls, execution and failure scenarios.
Into your infrastructure or cloud: AWS, GCP, Azure, private cloud, dedicated servers or colocation.
Strategy monitoring, model updates, data and infrastructure maintenance, new strategies and markets.
Strategy research, validation, backtesting and portfolio research with a defined scope.
Start a conversation →A defined system: trading platform, risk system, research platform, intrinsic-value or portfolio system.
Start a conversation →Quant researcher, data scientist, ML engineer, backend, frontend and DevOps for longer institutional projects.
Start a conversation →Focused strategy review, model validation, architecture, code and risk review — or a full platform audit.
Start a conversation →Whether you start from a trading hypothesis, an existing research model or a complete fund architecture, we design the quantitative and technical infrastructure to move it into production.