Linedata
Empowering investment and credit management with AI-driven operational alpha and cloud-native agility.
Open-source quantitative portfolio optimization and algorithmic trading framework for sophisticated investors.
Eiten is a high-performance, open-source framework designed for the development, backtesting, and deployment of quantitative investment strategies. Architected as a modular Python-based ecosystem, Eiten leverages advanced mathematical models such as Hierarchical Risk Parity (HRP), Mean-Variance Optimization (MVO), and Equal Risk Contribution (ERC) to provide users with institutional-grade portfolio construction capabilities. By 2026, Eiten has solidified its position in the market as the go-to alternative for quantitative researchers who require full transparency and control over their execution pipelines, moving away from 'black box' proprietary SaaS trading platforms. Its architecture facilitates a seamless transition from research to live trading via its decoupled engine, allowing for robust integration with various brokerage APIs like Interactive Brokers and Alpaca. The framework is specifically optimized for high-dimensional data handling and multi-asset classes, including equities, crypto, and forex. Its market positioning focuses on 'Alpha-as-Code,' empowering developers to automate complex rebalancing logic and risk management protocols without recurring licensing fees, making it a critical tool for independent hedge funds and sophisticated retail traders looking for high-fidelity backtesting and low-latency execution bridges.
Uses graph theory and hierarchical clustering to build portfolios that do not require matrix inversion, making it stable for highly correlated assets.
Empowering investment and credit management with AI-driven operational alpha and cloud-native agility.
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Professional-grade financial data and analytics at a fraction of the cost of a Bloomberg Terminal.
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Classic quadratic programming approach to find the optimal risk-return frontier based on historical covariance.
Allocates weights such that every asset in the portfolio contributes an equal amount to the total portfolio risk.
Decoupled logic for generating entry/exit signals from the portfolio weight optimization logic.
A robust backtesting methodology that optimizes parameters on a rolling window to prevent overfitting.
Direct connectivity to major brokerages through standardized order execution interfaces.
Built-in calculation of Sortino ratio, Calmar ratio, and Value-at-Risk (VaR).
Manual rebalancing of high-volatility crypto assets leads to slippage and suboptimal risk exposure.
Registry Updated:2/7/2026
Testing if specific factors (Value, Momentum) provide alpha over a 10-year period.
Retail investors wanting to mirror Ray Dalio's All-Weather style strategies without management fees.