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This document covers the comprehensive trading model ecosystem in systematica, including statistical arbitrage models, range-based strategies, meta-learning approaches, and factor models. These models form the core quantitative strategies that generate trading signals from market data. For signal processing and conversion to trading decisions, see Signal Processing. For portfolio simulation and backtesting, research workflows and hyperparameter optimization, see Portfolio Management.

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Model Architecture Overview

Systematica implements a hierarchical model architecture built around the BaseStatArb base class, which provides standardized interfaces for model execution, signal generation, and portfolio simulation. Hero Light

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Sub-modules

  • systematica.api.models.arbitrage_index
  • systematica.api.models.meta_model
  • systematica.api.models.momentum
  • systematica.api.models.ou_process
  • systematica.api.models.range_breakout
  • systematica.api.models.spread
  • systematica.api.models.volatility
  • systematica.api.models.volume_profile