Mr.Tian's starred repositories

netsci-project

Network Analysis for Financial Markets

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LSTM-Stock-Prediction

Day-Trading algorithm using LSTM to predict intraday stock movement

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Qbot

[🔥updating ...] AI 自动量化交易机器人 AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant

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project-based-learning

Curated list of project-based tutorials

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pedquant

quant, financial data, economic data

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MarkowitzPortfolioOptimization

Computing a solution for the optimal mean-variance tradeoff (maximising Sharpe Ratio) of a portfolio according to MPT.

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pymarkowitz

Mean Variance (Markowitz) Portfolio Optimization and Beyond

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factor_attribution

Factor based portfolio risk decomposition using 8 factor model

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Portfolio-Optimization

Built a portfolio optimization algorithm to maximize expected returns on a combination of stocks using live feeds and historical data from yahoo finance using regression models, matrix transformations and principal component analysis. Designed a model to predict the performance of the portfolio based on multiple factors such as market returns, volatility, GDP and inflation

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MPT_BlackLitterman

Implementation of Modern Portfolio Theory and Black Litterman Model

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BlackLitterman

Implementation of the famous Black-Litterman model in Jupyter notebook

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Finance

150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data

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trading-strategy

Python framework for quantitative financial analysis and trading algorithms on decentralised exchanges

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Quantitative-Momentum

Quantitative Momentum Strategy Algorithm

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Momentum-Strategy

Quantitative Momentum - Investment Strategy inspired by Wesley Gray and Jack Vogel

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FinRL

FinRL: Financial Reinforcement Learning. 🔥

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ChatGPT

🔮 ChatGPT Desktop Application (Mac, Windows and Linux)

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GPy

Gaussian processes framework in python

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Canonical-Correlation-Analysis

A simple assignment applying Canonical Correlation Analysis method for two group of variables, diet and economic sector.

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multivariate-statistics

Case Study in ranking U.S. cities based on a single linear combination of rating variables. Dimensionality techniques used in the analysis are Principal Component Analysis (PCA), Factor Analysis (FA), Canonical Correlation Analysis (CCA)

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LDA-QDA

Implement LDA and QDA in R with iris and parkinson dataset.

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Regression_Classification

Linear, Ridge Regression, QDA, LDA

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Rstatistics

linear regression rstudio

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Machine-Learning-Models

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

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Machine-Learning-Projects

Machine Learning studies at Brandeis University, with my best friends Ran Dou, Tianyi Zhou, Dan Mduduzi, Siyan Lin.

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KNN_RStudio

Analysis of prostate cancer using KNN algorithm in RStudio

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kNN

kNN Algorithm implemented in RStudio

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kNN

机器学习实战

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