Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
翻译 - 技术分析指标-Pandas TA是具有120多个指标的易于使用的Python 3 Pandas扩展
Technical Analysis Library using Pandas and Numpy
This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.
翻译 - 这是一个包含股票，ETF，基金，指数，期货，期权，货币，加密货币和货币市场的超过180.000个符号的数据库。
#区块链#modular quant framework.
翻译 - 编写一次交易算法，在所有市场上运行
Transparent and Efficient Financial Analysis
#区块链#quant framework for stock
Finviz analysis python library.
#时序数据库#Teaches step-by-step to analysis stock data in python.
A tool that allows you to visually compare the fundamentals of over 6,000 companies.
#计算机科学#Find your trading, investing edge using the most advanced web app for technical and fundamental research combined with real time sentiment analysis.
Python program that rates stocks out of 100 based on valuation, profitability, growth, and price performance metrics, relative to the company's sector.
#计算机科学#Financial pipeline for the data-driven investor to research, develop and deploy robust strategies. Big Data ingestion, risk factor modeling, stock screening, portfolio optimization, and broker API.
#计算机科学#FinML: A Practical Machine Learning Framework for Dynamic Stock Selection
A financial chat application powered by LangChain, OpenBB, and Claude 3 Opus.
#自然语言处理#This is my github repository where I post trading strategies, tutorials and research on quantitative finance with R, C++ and Python. Some of the topics explored include: machine learning, high frequen...
#计算机科学#Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the article...
Database for crypto data, supporting several exchanges. Can be used for TA, bots, backtest, realtime trading, etc.
This repository enables traders/investors to spot undervalued stocks automatically in the market efficiently to help them maximise their profits.
Screen stocks on fundamentals and estimate their intrinsic value
Time Series forecasting using Seasonal ARIMA & Prophet. Applied statistical tests like Augmented Dickey–Fuller test to check stationary of series. Checked ACF ,PACF plots to identify Moving average an...