Software
Collection of Reusable Code to Develop and Test Your Investment Ideas.
Data Curator
Provides a highly customizable interface to retrieve, structure, and transform financial data from multiple data providers. Users can define the desired provider, date range, frequency, and type of data.
The output is a clean time-series dataset that preserves a point-in-time structure suitable for backtesting and empirical research. It also supports custom calculations and column selection, enabling users to tailor the dataset to specific modeling needs.
Cut your new data onboarding time and ensure clean and transparent data handling from your favorite vendors.
Feature Foundry
Transforms curated financial datasets into signal-ready, enriched feature libraries. It combines Exploratory Data Analysis, Feature Engineering, and Universe Filtering into a unified process that prepares the foundation for quantitative research and portfolio construction.
Its overarching goal is to help researchers detect outliers, discover meaningful data patterns, and weave multiple data sources into coherent, interpretable features that can later drive alpha generation and investment universe definitions.
Portfolio Construction
Provides a unified framework for transforming investment signals into structured, risk-aware portfolios. It bridges the gap between research and implementation by offering a consistent interface to design, test, and compare allocation methodologies, from classical optimization frameworks to practical, rule-based heuristics.
This library enables researchers and portfolio managers to move seamlessly from alpha generation to capital allocation, ensuring transparency, flexibility, and reproducibility throughout the investment process.
Backtest Engine
Designed to provide a transparent and reproducible environment for testing portfolio strategies over historical data. It supports custom rebalancing logic, dynamic weight allocation, execution price configuration (e.g., VWAP, adjusted close), and commission modeling.
The engine separates concerns between data input, order execution, portfolio valuation, and performance tracking, allowing users to plug in their own decision-making models while maintaining control over capital management and trading assumptions.
Attribution Analysis
Allows analysts and researchers to decompose portfolio returns into meaningful sources of value added. It supports return attribution across sectors, industries, factors (e.g., valuation, quality), or custom-defined groupings.
Compatible with both absolute and relative performance contexts, the tool provides granular insights into allocation effects, selection effects, and timing contributions. With flexible input formats and support for cross-sectional and time-series views, it integrates smoothly into the broader research and portfolio evaluation process.
