How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
Common financial technical indicators implemented in Pandas.
The main features of peerchemist/finta are: Financial Analytics, Financial Analytics Tools, Technical Indicators, Technical Analysis Libraries.
Open-source alternatives to peerchemist/finta include: mrjbq7/ta-lib — This project is a Python wrapper for the TA-Lib C library, serving as a financial technical analysis library and… enthought/pyql — Cython QuantLib wrappers. bukosabino/ta — This is a pandas-based technical analysis library and financial feature engineering tool. It serves as a vectorized… dcajasn/riskfolio-lib — Riskfolio-Lib is a Python portfolio optimization library and convex risk management tool. It provides a framework for… domokane/financepy — A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including… google/tf-quant-finance — This is a quantitative finance library built on TensorFlow for financial engineering, asset pricing, and risk…
This project is a Python wrapper for the TA-Lib C library, serving as a financial technical analysis library and quantitative trading tool. It provides a collection of mathematical functions designed to analyze market price movements, identify trading signals, and recognize candlestick patterns within financial data. The library focuses on the computation of trend, momentum, and volume metrics. It includes specialized tools for candlestick pattern recognition to detect recurring price action shapes in both historical and real-time data. The system integrates with NumPy arrays to process cont
Riskfolio-Lib is a Python portfolio optimization library and convex risk management tool. It provides a framework for calculating optimal asset allocations using convex risk measures and mathematical programming solvers, supporting linear, quadratic, and semidefinite programming. The library features a hierarchical risk parity framework and financial asset clustering tools to group similar instruments and improve diversification. It includes a portfolio backtesting engine for simulating investment strategies using historical data and cross-validation. The system covers a broad range of quant
This is a pandas-based technical analysis library and financial feature engineering tool. It serves as a vectorized indicator calculator that transforms raw price and volume data into derived metrics for time series analysis. The library uses a NumPy-based engine to perform mathematical operations across entire arrays, avoiding iterative loops to maintain high performance. It organizes technical indicators into a modular class hierarchy with a consistent interface, allowing for bulk feature generation and the direct appending of results as new columns to a pandas DataFrame. The system covers
A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.