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black-litterman-model icon black-litterman-model

使用Python复现Black-Litterman模型。Black-Litterman模型创造性地采用贝叶斯方法将投资者对预期收益的主观看法与资产的市场均衡收益相结合，有效地解决了Markowitz均值-方差模型中投资者难以准确估计各个投资品种预期收益率、以及其权重对预期收益率的极度敏感性这两大问题。本项目使用美国市场2009年-2019年十年间的10只股票数据进行回测，证明了合理观点对资产组合收益率具有显著的正面影响效果。

fudan-datamining icon fudan-datamining

2020 Spring Fudan University Data Mining Course HW by prof. Zhu Xuening. 复旦大学大数据学院2020年春季课程-数据挖掘（DATA620007）包含数据挖掘算法模型：Linear Regression Model、Logistic Regression Model、Linear Discriminant Analysis、K-Nearest Neighbour、Naive Bayes Classifier、Decision Tree Model、AdaBoost、Gradient Boosting Decision Tree(GBDT)、XGBoost、Random Forest Model、Support Vector Machine、Principal Component Analysis(PCA)

fudan-machinelearning icon fudan-machinelearning

2020 Spring Fudan University Machine Learning Course HW by prof. Chen Qin. 复旦大学大数据学院2020年春季课程-人工智能与机器学习（DATA620006）

learn_backtrader icon learn_backtrader

BackTrader中文教程笔记（by：量化投资与机器学习），系统性介绍Bactrader的特性、策略构建、数据结构、回测交易等，彻底掌握量化神器的使用方法。章节：介绍篇、数据篇、指标篇、交易篇、策略篇、可视化篇……（持续更新中）

webnotebook icon webnotebook

Notebook for Full Stack Developer. HTML5, CSS3, JavaScript, Node.js, Ajax, Axios, Express, Vue, React......

webpractice icon webpractice

A personal repo for practicing. HTML5, CSS3, JavaScript, Node.js, Ajax, Axios, Express, Vue, React

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