longbridge-quant

Longbridge Quant provides frameworks for building and backtesting quantitative strategies, including pairs trading with cointegration, volatility regime detection, multi-factor stock selection, and factor research with IC/IR analysis. Run indicator scripts against K-line data via CLI, optimize strategy parameters with walk-forward validation, and model execution costs and hedging approaches.

Longbridge Quant builds and backtests quantitative trading strategies using multi-factor models, pairs trading, volatility analysis, and machine learning.

AI-generated summary based on this skill's SKILL.md

★ 44 ⁮ 8 MIT updated 2026-07-20 by longbridge

Install

longbridge/skills/longbridge-quant · repository language: Python

Manual (git clone) CLI (skillfed)coming soon

git clone https://github.com/longbridge/skills
cp -r skills/skills/longbridge-quant ~/.claude/skills/longbridge-quant

Frequently asked questions

AI-generated answers based on this skill's SKILL.md and metadata

How to run quant indicator scripts with longbridge-quant?

Longbridge Quant enables you to run indicator scripts and analyze K-line data directly via CLI for strategy development. The framework supports executing custom indicators against historical price data, making it straightforward to test signal generation and refine your trading logic before backtesting at scale.

What pairs trading strategy features does longbridge-quant offer?

Longbridge Quant implements pairs trading strategies using cointegration analysis to identify mean-reverting security pairs. The framework detects statistical relationships between assets, helping you build arbitrage strategies that exploit temporary pricing divergences while managing the correlation and spread dynamics.

Can longbridge-quant help with factor research and IC/IR analysis?

Yes, Longbridge Quant supports comprehensive factor research through IC (Information Coefficient) and IR (Information Ratio) analysis. Screen and rank factors using correlation testing and statistical methods to identify predictive signals, then validate their decay and stability across different market regimes.

How does longbridge-quant handle volatility and seasonality strategies?

Longbridge Quant provides tools to detect volatility regimes using statistical methods like GARCH and build seasonality-based strategies around calendar effects such as the January effect. Model volatility-driven signals and exploit recurring seasonal patterns to enhance strategy returns.

What backtesting and optimization capabilities does longbridge-quant include?

Longbridge Quant supports multi-factor model backtesting with walk-forward optimization to validate strategy robustness. Build composite ranking systems using Z-score methods, model execution costs and slippage, and design hedging approaches to manage portfolio risk and tail exposure.

Is longbridge-quant open source and what license does it use?

Longbridge Quant is released under the MIT license, making it freely available for commercial and personal use. You can modify, distribute, and integrate the framework into your own quantitative trading systems with minimal restrictions.

SKILL.md

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