Modular quantitative strategy system

ASTRIVERA is a privately deployed, local system for modular quantitative strategy assembly and immunity. Clients can select the components they need, retain existing strategies, data and broker connections, or deploy with our proprietary strategies or commissioned research.

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Modular assembly

Strategy components, data views, market rules, risk policies, execution modes, broker connections and account binding are managed separately. Each assembly retains its versions and configuration; interfaces, data and account conditions are checked before a run.

Local control plane

Strategy componentsData viewsMarket rules

Risk policiesExecution modes

Broker connectionsAccount binding

Evidence and reportsQuantitative immunity

Strategy sources and delivery

Client strategies

Integrate existing strategies and research models, compare behaviour before and after migration, and configure the required data, risk controls and execution conditions.

ASTRIVERA proprietary strategies

We research strategies for U.S. equities and China A-shares. Each strategy is assessed separately for its market, frequency, risk characteristics, data requirements and deployment conditions.

Commissioned strategy research

Data preparation, strategy development and evaluation follow agreed markets, asset coverage, holding periods and risk constraints. A project may deliver research findings alone, or proceed to system integration and deployment once the agreed validation conditions are met.

Research objectives, deliverables, schedule and fees are agreed separately. Research evaluation and production deployment have separate acceptance processes.

Research and runtime

Each run is linked to its strategy version, data, parameters and configuration, making results easier to review and differences easier to compare.

Run mode	Purpose
Backtest	Evaluate historical performance using agreed data, market rules and cost assumptions.
Replay	Reconstruct decisions from frozen inputs to compare behaviour and results.
Dry run	Check assembly and runtime workflows without submitting trading orders to a broker.

Execution and accounts

Generate order plans from portfolio targets, positions, cash and market rules; record broker responses and fills; and reconcile account state after the run.

Brokers and accounts. Connection configurations and individual accounts are managed separately, with explicit permissions, currencies and applicable markets.

Orders and fills. Track submission, acceptance, rejection, partial fills, cancellation and completion. Unconfirmed outcomes remain unresolved.

Positions and cash. Check internal accounting against broker records, retaining discrepancies and the evidence used for reconciliation.

Twin and evidence

The strategy twin checks runtime differences against relevant baselines. Evidence views show the corresponding records and coverage.

Comparison layer	Focus
Decision deviations	Data inputs, signals, target weights and risk decisions.
Execution deviations	Order plans, actual fills, latency, slippage and costs.
Accounting deviations	Positions, cash, cost attribution and account records.
Economic outcomes	Returns, volatility, drawdown, turnover and related measures.

Evidence and reports are linked to specific runs. Uncovered areas are listed separately and excluded from verified conclusions.

Deployment and support

A project may include environment assessment, software installation, data and broker adaptation, strategy integration, validation and operating guidance. Subsequent upgrades, maintenance and support are defined at delivery.

Strategy code, data, credentials and runtime records remain in the client environment by default. New markets, components or account configurations are added subject to the relevant compatibility and authorisation requirements.

Features, support and deployment depend on the current release and the project scope agreed in writing by both parties.

Operating environments. The current implementation is macOS (Apple Silicon · macOS 13+). Windows and Linux are architecture targets for future adaptation.

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