Alpha Stochastic Research

ASRQuant 1.2.0¶

A Python research platform for moving from data and hypotheses to models, portfolios, risk diagnostics and reproducible backtests without hiding chronology, assumptions or implementation choices.

Get started API reference

One import. Clear research domains.¶

import asrquant as asr

Research discovery

Data-driven and literature-derived hypotheses, search, ranking and novelty audit.

Quantitative analytics

Alpha, factors, statistics, portfolio risk and market microstructure.

Pricing & rates

Options, yield curves, swaps, rate options, stochastic models and calibration.

Backtesting & reproducibility

Chronology-aware backtests, costs, audit trails, manifests and guarded execution boundaries.

Canonical 1.2 API¶

Domain	Canonical entry point	Purpose
Data	`asr.data.load`, `asr.data.validate`	Load and validate time-series inputs
Hypotheses	`asr.hypotheses.discover`	Generate reviewable research candidates
Portfolio	`asr.portfolio.optimize`	Construct portfolios through a common result contract
Backtesting	`asr.backtesting.run`	Run auditable portfolio backtests
Options	`asr.options.price`	Price supported derivatives through one verb
Rates	`asr.rates.analyze`, `asr.rates.calibrate`	Inspect curves and calibrate supported rate models
Statistics	`asr.stats.regress`	Fit common regression specifications
Machine learning	`asr.ml.fit`	Chronology-safe walk-forward model evaluation

Research architecture¶

Question / Literature
        ↓
Data + provenance
        ↓
Hypothesis candidates
        ↓
Statistical / economic diagnostics
        ↓
Signals + factors
        ↓
Portfolio construction
        ↓
Risk decomposition
        ↓
Backtest + costs + robustness
        ↓
Research decision + reproducible output

ASRQuant is research software. Installation does not authorize live capital deployment, and successful backtests are not evidence of future profitability.