Micro-sheep/efinance
Efinance
efinance is a Python financial data library and programmatic interface designed to automate the acquisition of market data for quantitative trading and analysis. It serves as a toolkit for retrieving real-time and historical information across various asset classes to support the development of backtesting systems and trading strategies.
The library provides a multi-asset toolkit for monitoring diverse financial instruments, including stocks, funds, bonds, and futures. It allows for the extraction of specific data points such as shareholder counts, corporate index memberships, and net asset values for investment funds.
The project covers a broad range of data acquisition capabilities, including the retrieval of minute-level price action, candlestick data, and transaction-level details. It also enables the tracking of sector performance and the collection of historical order inflow data for derivatives.
Features
- Market Data Acquisition - Fetches historical and real-time price data for stocks, funds, bonds, and futures to support quantitative analysis.
- Historical Price Data Fetchers - Retrieves minute-level price action and candlestick data for a specified number of recent days.
- Multi-Asset Holdings Trackers - Monitors current quotes, net asset values, and sector performance across a diverse set of financial instruments.
- Fund Composition Data - Collects historical net asset values and public holding data for investment funds.
- Market Data Access APIs - Provides a programmatic interface for extracting price action, net asset values, and corporate index information.
- Market Data Providers - Retrieves real-time quotes, snapshots, sector membership, and shareholder counts for stocks across multiple exchanges.
- Multi-Asset Quote Retrievers - Offers a comprehensive toolkit for retrieving quotes across diverse asset classes, including sectors and shareholders.
- Exchange-Traded Fund Data Connectors - Fetches real-time quotes and market information for exchange-traded and open-ended funds.
- Financial Data Libraries - Provides a Python library for retrieving real-time and historical market data for stocks, funds, bonds, and futures.
- Trading Strategy Backtesting - Retrieves historical candlestick and minute-level data to simulate and evaluate trading strategy performance.
- Equity Market Monitoring - Provides real-time tracking of stock quotes, shareholder counts, and corporate index memberships.
- Sector and Industry Analysis - Fetches real-time quotes for constituent stocks within multiple sectors and retrieves historical trends.
- Investment Trend Analysis - Gathers historical holdings and market trend data for funds and convertible bonds.
- Recent Trade Retrievals - Fetches transaction-level details and top-trader lists for the most recent trading day.
- Quantitative Trading Platforms - Provides the data acquisition foundation necessary for building backtesting systems and quantitative trading strategies.
- Financial Index Constituent Listings - Extracts index constituent members and current IPO audit status for companies.
- Futures Market Data Acquisition - Retrieves exchange information and historical price action for futures contracts to analyze volatility.
- Convertible Bond Data - Retrieves market trends and detailed price action charts specifically for convertible bonds.
- Derivative Quotes - Collects real-time quotes and historical order inflow data for futures and bonds.
Star history
How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
