⚠️Install with caution. This skill has very few installs. Always review the source and verify it on clawhub.ai before installing. Community-built skills run with agent permissions — only install ones you trust.

📉 Stock Trading

Quantitative Researchv1.0.0

Name: Quantitative Research
Author: zhengxinjipai

quantitative-research

zhengxinjipai

World-class systematic trading research - backtesting, alpha generation, factor models, statistical arbitrage. Transform hypotheses into edges. Use when "bac...

latest

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Installs (all time)

Installs (current)

Downloads

5.1K

Stars

CreatedMar 6, 2026

UpdatedMay 1, 2026

Install & Quick Start

Install via ClawdBot CLI:

clawdbot install zhengxinjipai/quantitative-research

Skill Package5 files

📋SKILL.mdmarkdown

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Quality Score

B64/100

Grade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.

Market Validation13/35

· 8 installs (low)
· 549 downloads (moderate demand)
· 1 stars

Documentation18/25

· SKILL.md present
· Moderate documentation (≥1500 chars)
· Contains usage examples or trigger description
· Detailed summary

Package Completeness8/15

💡

Usage Guide

Generated Mar 20, 2026

Quantitative ResearchersHedge Fund AnalystsAsset ManagersProprietary Tradersadvanced

💡 Application Scenarios

Backtesting a Momentum StrategyFinance - Hedge Funds

A hedge fund analyst wants to validate a new momentum-based trading strategy using historical data. The skill will guide them through rigorous backtesting methodology, emphasizing walk-forward analysis and transaction cost modeling to avoid overfitting and ensure robustness before deployment.

Developing a Factor Model for Portfolio ConstructionFinance - Asset Management

An asset manager seeks to build a factor model to enhance portfolio returns. The skill assists in identifying alpha signals, validating them against statistical benchmarks like t-statistics, and integrating contrarian insights to avoid disguised beta exposure in the model.

Statistical Arbitrage Signal ResearchFinance - Proprietary Trading

A quantitative researcher at a proprietary trading firm is exploring pairs trading opportunities. The skill provides expertise in statistical arbitrage, regime detection, and risk assessment using reference files to diagnose potential failures like look-ahead bias or market shifts.

Alpha Generation with Alternative DataFinance - Fintech

A fintech startup aims to generate alpha using alternative data sources such as satellite imagery or social media sentiment. The skill advises on signal validation, emphasizing statistical rigor and caution against over-reliance on complex machine learning, focusing on practical edges.

Regime Detection for Adaptive StrategiesFinance - Systematic Trading

A systematic trading desk needs to adapt strategies to changing market conditions. The skill helps implement regime detection techniques, using walk-forward analysis and reference validations to ensure strategies remain effective during volatility, like in March 2020 events.

💼 Business Models

Quantitative Hedge FundManagement and performance fees

This model involves developing and deploying systematic trading strategies based on rigorous backtesting and alpha research. Revenue is generated through management fees (e.g., 2% of assets) and performance fees (e.g., 20% of profits), leveraging the skill's expertise to minimize risks like overfitting and transaction costs.

Asset Management with Factor InvestingAdvisory or asset-based fees

Firms use factor models to construct portfolios that aim to outperform benchmarks. Revenue comes from advisory fees or asset-based charges, supported by the skill's focus on statistical validation and avoiding disguised beta to deliver consistent returns to clients.

Proprietary Trading FirmTrading profits

This model involves trading the firm's own capital using statistical arbitrage and alpha signals. Revenue is derived from trading profits, with the skill aiding in signal research and risk management to navigate pitfalls like regime shifts and ensure profitability.

💬 Integration Tip

Integrate this skill by first consulting the reference files for patterns, sharp edges, and validations to ensure all analyses are grounded in domain-specific best practices and avoid common pitfalls.