This project is a financial market data API and quantitative analysis tool designed to aggregate metrics, scrape web data, and monitor market sentiment. It functions as a financial indicator aggregator and stock market web scraper that provides a programmatic interface for retrieving stock prices, indices, and ETF metadata from multiple data providers.
Principalele funcționalități ale 1nchaos/adata sunt: Financial Data Collection Pipelines, Sector and Industry Analysis, Market Sentiment Analyzers, Financial Data APIs, Capital Flow Analyzers, Investor Behavior Tracking, Market Data Acquisition, Quantitative Data Extraction.
Alternativele open-source pentru 1nchaos/adata includ: simonlin1212/a-stock-data — This project is a comprehensive market data toolkit and financial analysis system specifically designed for China… micro-sheep/efinance — efinance is a Python financial data library and programmatic interface designed to automate the acquisition of market… akfamily/akshare — This project is a Python library designed for the programmatic retrieval and analysis of diverse financial datasets.… yutiansut/quantaxis — Quantaxis is a quantitative trading framework designed for building, backtesting, and executing automated strategies… 0xemmkty/quantmuse — QuantMuse is an algorithmic trading platform and quantitative trading framework that integrates large language models… shinnytech/tqsdk-python — tqsdk-python is a quantitative trading SDK and framework designed for developing automated strategies for futures,…
This project is a comprehensive market data toolkit and financial analysis system specifically designed for China A-shares. It serves as a data pipeline for retrieving real-time quotes, aggregating corporate financial statements, and automating equity research. The system distinguishes itself through specialized monitors for institutional capital movements, including Northbound fund flows, margin trading balances, and large block transactions. It also features a dedicated options Greeks calculator for ETF derivatives and tools to gauge market sentiment via retail popularity rankings and trend
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 v
This project is a Python library designed for the programmatic retrieval and analysis of diverse financial datasets. It functions as a comprehensive toolkit for quantitative research, providing a unified interface to fetch historical and real-time market data across asset classes including equities, futures, bonds, cryptocurrencies, and foreign exchange. By abstracting complex network requests into simple, parameter-driven functions, it enables users to integrate financial data into research workflows and automated trading systems. The library distinguishes itself through its scraper-based ag
Quantaxis is a quantitative trading framework designed for building, backtesting, and executing automated strategies across global equities, futures, and cryptocurrencies. It integrates an event-driven backtesting engine, a multi-market execution gateway for order routing, and a quantitative data pipeline for ingesting and storing multi-asset market data. The system features a Rust-accelerated financial library that utilizes Apache Arrow for high-performance technical indicator calculation and zero-copy data processing. It provides a containerized infrastructure model designed for orchestrati