How does the 'Execution Philosophy' benefit the user?

Instead of just providing code snippets, the skill actively runs the code, performs the backtests, and displays actual results and charts immediately on screen.

What kind of data can I access for strategies?

You can access over 900 data fields, including revenue, ROE, P/E ratios, technical indicators like RSI and MACD, and institutional investor buy/sell volumes.

What markets does this skill support?

It primarily supports the Taiwan stock market (TSE and OTC), including comprehensive historical data for prices, fundamentals, and institutional trading summary.

Do I need a FinLab API token to use this?

Yes, an API token is required. The skill can guide you through the authentication process via OAuth or load an existing token from a .env file.

Can this skill actually place trades?

Yes, it can interface with supported brokers like Sinopac to convert backtest results into live orders using the OrderExecutor functionality.

FinLab Quant Trading

Name: FinLab Quant Trading
Author: koreal6803

bykoreal6803

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138

Data Science & ML

Automates the development, backtesting, and execution of Taiwan stock market quantitative trading strategies using the FinLab package.

About

FinLab is a specialized skill for Claude Code designed to streamline quantitative trading workflows specifically for the Taiwan stock market (台股). It enables developers and traders to fetch comprehensive datasets—including fundamental, technical, and institutional data—construct complex factors, and run detailed backtests with built-in risk management. By following an execution-first philosophy, the skill handles environment setup, data retrieval, and visual report generation, effectively turning natural language trading ideas into actionable quantitative results and live order execution.

Key Features

Automated backtesting engine with customizable rebalancing, stop-loss, and take-profit parameters
Secure API token management and automated OAuth authentication workflow
Seamless transition from strategy research to live trading order execution with supported brokers
138 GitHub stars
Instant Taiwan stock market data retrieval including fundamental, technical, and institutional metrics
Factor analysis and stock selection using specialized FinLabDataFrame methods

Use Cases

Developing and backtesting multi-factor stock selection models for the Taiwan stock market
Automating daily stock picking and order generation for live trading via broker APIs
Analyzing historical performance and risk metrics like Sharpe Ratio and Max Drawdown for trading ideas

About

Key Features

Automated backtesting engine with customizable rebalancing, stop-loss, and take-profit parameters
Secure API token management and automated OAuth authentication workflow
Seamless transition from strategy research to live trading order execution with supported brokers
138 GitHub stars
Instant Taiwan stock market data retrieval including fundamental, technical, and institutional metrics
Factor analysis and stock selection using specialized FinLabDataFrame methods

Use Cases

Developing and backtesting multi-factor stock selection models for the Taiwan stock market
Automating daily stock picking and order generation for live trading via broker APIs
Analyzing historical performance and risk metrics like Sharpe Ratio and Max Drawdown for trading ideas