Algorithmic Trading Engine

From research to live trading

The Modulus Algorithmic Trading Engine is an event-driven, professional-caliber algorithmic trading platform engineered for deep quant modeling. It ships with out-of-the-box alternative-data and live-trading support, and a highly modular foundation that extends cleanly to your fund's needs.

Core feature set

The engine is built around the realities of professional quant research. It is survivorship-bias free, automatically accounting for splits, dividends, and corporate actions as well as listings, delistings, and mergers, so historical tests reflect what actually happened.

Universe selection lets you avoid selection bias with algorithmically chosen assets built from proprietary data and indicators. Portfolio management tracks performance, profit and loss, buying power, and holdings across multiple asset classes and margin models within a single strategy, while scheduled events trigger functions at the times you choose and custom data import brings your proprietary signals into any backtest.

• Survivorship-bias-free historical testing
• Automatic handling of splits, dividends, and corporate actions
• Algorithmic universe selection to avoid selection bias
• Portfolio management across asset classes and margin models
• Scheduled events for time- and day-based triggers
• Import proprietary signal data on almost any time series

Rich, extensible modular architecture

The engine is modular by design, every component is pluggable and customizable, and it ships with models for all the major plug-in points. That makes it straightforward to simulate real markets and brokerages accurately, then extend the engine as your strategies evolve.

Slippage, fill, and margin models reproduce the behavior of assets and brokerages, brokerage models capture fees and API nuances, and fee models handle rebates and dynamic order pricing. Cash-account, settlement, and margin models simulate configurable settlement cycles, margin trading, option assignment, and early exercise, while 100-plus technical indicators apply to any data source.

• Margin, fill, and slippage models for realistic simulation
• 100+ technical indicators usable on any data source
• Brokerage models for fees, order support, and API behavior
• Fee models for rebates and dynamic order pricing
• Settlement and margin models with configurable cycles and option assignment
• Load proprietary datasets from sockets, databases, or files

The algorithm framework

The Algorithm Framework bakes in key quantitative-finance concepts and gives you a well-defined scaffold for your strategy. Plug in and reuse existing modules to radically accelerate development, spending your effort where it matters.

Select a universe with predefined filters or from hundreds of universe-selection models, generate alpha signals for your chosen assets, and construct a weighted portfolio using pre-made models including Equal Weighting, Mean-Variance, and Black-Litterman. Pluggable execution algorithms place your target portfolio efficiently, and plug-in risk models, passive or active, adjust position sizes and hedge exposed positions as conditions demand.

• Universe selection with hundreds of pre-built models
• Alpha creation focused on expected-return signals
• Portfolio construction: Equal Weighting, Mean-Variance, Black-Litterman
• Pluggable execution models you can backtest and compare
• Passive or active risk models, combinable for varied conditions
• Reusable modules to fast-track algorithm development

Powerful data integrations and toolbox

The engine integrates with 40 price, fundamental, and alternative data sources, all preformatted, point-in-time, and ready for your fund. Code locally in VS Code and backtest in the cloud, monitoring runs straight from your IDE.

Iterate rapidly in an integrated Jupyter Lab environment with the extract-transform-load dataset work already done. Use bundled implementations of popular data vendors and broker live feeds for locally hosted strategies, and pull historical data from online repositories and brokerages into a native format automatically.

Built on a modern stack

Focus on what matters

The engine handles the heavy lifting of data, modeling, and infrastructure so your team can concentrate on developing alpha.

Pluggable models and data

The engine ships with models for every major plug-in point and a deep set of data integrations, all preformatted and point-in-time.