technical-indicators

Technical indicators like MACD, RSI, and Bollinger Bands are computed from OHLCV (open, high, low, close, volume) data using mathematical formulas. This Skill calculates all four major indicators—MA, MACD, RSI, BOLL—directly from a pandas DataFrame with a closing price column, returning a new DataFrame with indicator columns appended for charting or backtesting.

Yes. This Skill supports batch calculation of all mainstream indicators—moving average, MACD, RSI, and Bollinger Bands—in a single operation. Pass your OHLCV DataFrame once and receive all indicator columns augmented to the same DataFrame, eliminating the need for separate calculations.

Input must be a pandas DataFrame containing at minimum a closing price column. OHLCV fields (open, high, low, close, volume) are optional but required for certain indicators. The Skill uses vectorized computation with pandas and TA-Lib to process the data efficiently and return augmented results.

Yes. The Skill is designed for technical analysis, quantitative backtesting, and trend assessment. It computes indicators quickly and accurately from OHLCV data, enabling you to build indicator columns directly into backtesting datasets for strategy evaluation.

This Skill requires pandas for DataFrame operations and TA-Lib for vectorized technical indicator computation. Both dependencies enable fast, accurate calculation of MA, MACD, RSI, and Bollinger Bands across large datasets.

Yes. The Skill supports single-indicator calculations as well as batch computation. You can calculate individual indicators like MA, MACD, RSI, or BOLL independently while retaining the option to compute all four together for convenience.