trading-indicators-from-price-data

Calculate 20 trading indicators from OHLCV price data using pandas-ta.

128|31|Updated Feb 13, 2026

Search Tags:#python #analysis #finance #trading #indicators #ohlcv

Ready to run

npx skills add https://github.com/besoeasy/open-skills --skill trading-indicators-from-price-data

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: trading-indicators-from-price-data
Source: https://github.com/besoeasy/open-skills/tree/main/skills/trading-indicators-from-price-data
Command: npx skills add https://github.com/besoeasy/open-skills --skill trading-indicators-from-price-data

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, pandas-ta, and includes scripts (resource) components.

What problem does it solve?

This Skill automates the calculation of 20 common technical trading indicators from OHLCV price data, streamlining financial analysis and strategy development.

Core Features & Use Cases

Indicator Calculation: Computes a comprehensive suite of 20 popular indicators including RSI, MACD, SMAs, EMAs, Bollinger Bands, and more.
Data Preparation: Essential for signal generation, backtesting trading strategies, and feature engineering for machine learning models in finance.
Use Case: Analyze historical stock prices to identify potential buy or sell signals by calculating and visualizing indicators like RSI and MACD.

Quick Start

Use the trading-indicators-from-price-data skill to calculate the 20 specified trading indicators from the provided OHLCV price data.

Frequently Asked Questions about trading-indicators-from-price-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I calculate RSI and MACD from OHLCV price data in Python?▼

You can calculate RSI and MACD from OHLCV price data using this skill, which computes 20 common trading indicators. It leverages the pandas and pandas-ta libraries to process candle data and generate indicator values for financial analysis.

What technical indicators can I compute for stock trading strategy backtesting?▼

For stock trading strategy backtesting, you can compute a comprehensive suite of 20 indicators including SMAs, EMAs, Bollinger Bands, Stochastic, ATR, ADX, CCI, OBV, MFI, and ROC. This covers essential momentum, volatility, and volume-based metrics.

Does pandas-ta work with pandas for generating technical analysis features?▼

Yes, pandas-ta works seamlessly with pandas for generating technical analysis features. This skill requires both libraries to process OHLCV candle data and calculate indicator values, making it suitable for machine learning feature engineering in finance.

Can I generate machine learning features from historical stock prices?▼

Yes, you can generate machine learning features from historical stock prices by calculating technical indicators like RSI, MACD, and Bollinger Bands. This skill automates the feature engineering process by transforming OHLCV data into 20 quantitative indicator values.

What's the best way to automate financial analysis of candle data?▼

The best way to automate financial analysis of candle data is by using a Python script to calculate multiple trading indicators simultaneously. This skill automates the calculation of 20 indicators from OHLCV data, streamlining signal generation and strategy development.

Do I need specific Python libraries to process OHLCV data for trading indicators?▼

Yes, you need the pandas and pandas-ta Python libraries to process OHLCV data for trading indicators. These dependencies are required to handle the candle data and execute the calculations for the 20 supported technical indicators.