tushare行情数据本地化存储、行情数据分析、形态选股
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Updated
Apr 6, 2021 - Python
tushare行情数据本地化存储、行情数据分析、形态选股
Stock-Robo-Advisor project including backtesting, simulating and practicality for future.
This is a project of portfolio optimization using Quantum-inspired Tabu Search and Trend Ratio
A stock investment assistant tool which utilized supervised machine learning models such as Logistic Regression, Random Forest, and Support Vector Machine to predict the stock’s 60 days’ return rate. If a specific stock outperformed the average return rate, the model would recommend to hold.
Uses SQL DB and API (live prices) to display info, prices and logo. Built using Flask
A Julia package for selecting assets based on volume, volatility, and market cap. Supports multiple selection methods for financial analysis.
Using PCA(Principle Component Analysis) and DEA(Data Envelope Analysis) techniques to identify relative efficient firms (stocks).
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