sickn33/agentic-awesome-skills/longbridge-quant

Claude Code and agent skill by sickn33/agentic-awesome-skills

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Curated upstream guidance for Longbridge Quant; use when the workflow matches the user goal.

Install

npx vskill@latest install sickn33/agentic-awesome-skills/longbridge-quant

SKILL.md

When to Use

  • Use when this upstream workflow matches the user's stated goal.
  • Use when the task requires the procedures documented in this skill.

Longbridge Quant

Quantitative analysis frameworks and CLI indicator scripting via Longbridge.

Response language: match the user's input language — English / Simplified Chinese / Traditional Chinese.
RULE: Response language priority: English is the default when language is ambiguous. If the user input is only a slash command, command name, ticker / symbol, or contains no natural-language language signal, you MUST respond in English. Do not infer Chinese from trigger keywords, skill metadata, or examples.
Data-source scope: this skill documents Longbridge. If its data is unavailable or insufficient, report the gap rather than inventing data or asserting that other sources are disallowed.
Connector availability: discover the tools actually available in the host; do not assume a Longbridge plugin or parity with CLI capabilities.

When to Use

Trigger when user asks about: quantitative indicator scripts (running against K-line data), pairs trading / cointegration, volatility regime strategies, seasonality / calendar effects, multi-factor stock selection, factor research (IC/IR analysis), factor screening, correlation and cointegration analysis, statistical methods (ADF/GARCH/bootstrap), strategy optimization, execution cost modeling, hedging strategies, or ML-based prediction.

Sub-topic Routing

User intentLoad references file
Run indicator scripts on klinereferences/quant-cli.md
Pairs trading / cointegrationreferences/pairs-trading.md
Volatility regime strategyreferences/volatility-strategy.md
Seasonality / calendar effectsreferences/seasonality.md
Multi-factor modelreferences/multifactor.md
Factor research (IC/IR analysis)references/factor-research.md
Factor screeningreferences/factor-screen.md
Correlation / cointegrationreferences/correlation.md
Statistical methods (ADF/GARCH)references/quant-stats.md
Strategy optimizationreferences/strategy-optimizer.md
Execution cost modelingreferences/execution-model.md
Hedging strategy designreferences/hedging.md
ML-based predictionreferences/ml-strategy.md

CLI: quant

The quant command runs user-defined indicator scripts against K-line data.

bash
longbridge quant --help

Use longbridge kline <SYMBOL> --format json (from longbridge-market-data) to obtain OHLCV input data.

Quantitative Frameworks

Pairs Trading / Statistical Arbitrage

Engle-Granger cointegration, hedge ratio via OLS, Z-score, half-life of mean reversion, entry/exit signals. See [references/pairs-trading.md].

Volatility Strategy

20-day / 60-day HV, percentile rank, long-vol (buy straddle) vs short-vol (iron condor) regime signals. See [references/volatility-strategy.md].

Seasonality / Calendar Effects

Month-of-year returns (January Effect), day-of-week effects, pre/post-holiday drift, earnings season effect. See [references/seasonality.md].

Multi-Factor Model

Value (1/PE, 1/PB), momentum (60-day), quality (ROE), low-vol (60-day HV) — Z-score composite, TopN portfolio. See [references/multifactor.md].

Factor Research

IC, IR, factor decay, layer backtest, IC-weighted combination. See [references/factor-research.md].

Factor Screening

Batch screening with PE, PB, ROE, revenue growth, dividend yield filters. See [references/factor-screen.md].

Correlation & Cointegration

Pairwise return correlation, rolling correlation, Johansen test. See [references/correlation.md].

Quantitative Statistics

ADF unit-root test, GARCH volatility modeling, regression diagnostics, bootstrap. See [references/quant-stats.md].

Strategy Optimizer

Parameter sweep, walk-forward optimization, out-of-sample validation. See [references/strategy-optimizer.md].

Execution Model (Backtest)

Slippage formulas (linear / square-root), VWAP/TWAP logic, market impact estimation. See [references/execution-model.md].

Hedging Strategy

Beta hedging, options protection, tail-risk hedging, cross-asset hedging. See [references/hedging.md].

ML Strategy (sklearn)

Rolling walk-forward Random Forest / Gradient Boosting, feature engineering, signal generation. See [references/ml-strategy.md].

Auth requirements

quant execution is analytical but sends the supplied script to a remote service. Market-data access can require login/entitlements; positions require explicit account-access scope. Verify installed CLI capabilities and current permissions. Do not submit proprietary strategy code without authorization.

Error handling

SituationResponse
command not found: longbridgeInstall longbridge-terminal
ModuleNotFoundError: sklearnRun pip install scikit-learn
Insufficient data for ADF testNeed at least 50 observations; increase kline history

MCP fallback

Use MCP server for kline data if CLI unavailable. Discover tools at runtime.

Related skills

User wantsUse
Raw K-line datalongbridge-market-data
Technical analysislongbridge-technical
Options volatilitylongbridge-derivatives

File layout

longbridge-quant/
├── SKILL.md
└── references/
├── quant-cli.md
├── pairs-trading.md · volatility-strategy.md · seasonality.md
├── multifactor.md · factor-research.md · factor-screen.md · correlation.md
├── quant-stats.md · strategy-optimizer.md · execution-model.md
└── hedging.md · ml-strategy.md

Examples

text
User: Apply this skill to my current task.
Assistant: Follow the workflow in this skill, cite limitations, and ask before risky steps.

Limitations

  • This skill performs analysis, not order execution. Strategy descriptions are hypotheses requiring realistic costs, liquidity, borrow/margin and out-of-sample validation. Do not invent recommendations from missing data.
  • For historical research, require point-in-time constituents and fundamentals with publication timestamps; current values cannot support a historical factor backtest. Adjust prices for corporate actions and align currency, timestamps and trading calendars.
  • Cite Longbridge only when data was actually retrieved there; report its timestamp, coverage and adjustments. Redact credentials/private account data from errors and reports.
  • Imported upstream skill; verify credentials, permissions, and safety boundaries before execution.
  • Does not replace environment-specific validation, testing, or maintainer review.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
47,054
Repository forks
6,853
7-day trend score
54

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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