LQM

Build with quantitative models designed for financial computation.

FinanceGPT Large Quantitative Model capabilities are intended for structured quantitative financial work where numerical computation, model inputs, versioning and output interpretation must remain explicit.

Answer-first: A Large Quantitative Model (LQM) is a quantitative modelling capability designed for structured financial or market computation with explicit inputs, outputs, model lineage and governance.

Continue FinanceGPT Developer home

FinanceGPT Developers

intent = "forecast liquidity"evidence = workspace.data()model = LQM.run(evidence)reasoning = QLM.compose(model)action = policy.review(reasoning)

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Data & evidence→Quantitative model→Language orchestration→Governed tools

CAPABILITIES

What this workflow brings together.

The public page explains the outcome first, then keeps the underlying financial methods, evidence and review path visible.

Structured quantitative inputs

Financial computation

Model version lineage

Evaluation context

Scenario and distribution support where governed

Application integration

Human review

HOW IT WORKS

From intent to reviewable output.

FinanceGPT should make complex financial work easier to express without hiding the evidence, calculations or control points.

Define the quantitative financial problem.

Bind the relevant observed data and assumptions.

Select the governed quantitative model capability.

Evaluate outputs against the intended financial use.

Keep model output distinct from investment or financial action authority.

FinanceGPT DeveloperConnect quantitative context to natural-language financial experiences.

Explore FinanceGPT Quantitative Language Model concepts for combining structured quantitative context with natural-language financial interfaces.

FinanceGPT DeveloperConnect applications to FinanceGPT through governed APIs.

Build financial applications with FinanceGPT API surfaces for financial intelligence, data, models, agents and governed workflows.

FinanceGPT DeveloperPrototype financial applications inside bounded developer context.

Prototype FinanceGPT integrations in a bounded developer environment before promoting applications into production workflows.

FinanceGPT DeveloperTreat developer access and financial authority as separate controls.

Understand FinanceGPT developer controls for credentials, permissions, workspaces, model and tool lineage, integrations and Financial Actions authority.