myvrml's repositories
awesome-quant
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
backtrader
Python Backtesting library for trading strategies
btgym
Scalable, event-driven, deep-learning-friendly backtesting library
Commodity-Channel-Index
My Final Project for Basic Algorithm and Programming
cvxportfolio
Portfolio optimization and simulation in Python
deepdow
Portfolio optimization with deep learning.
EchoStateNetworks
Materials related to the Medium article "Predicting Stock Prices with Echo State Networks".
Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction
Repository for Going Deeper with Convolutional Neural Network for Stock Market Prediction
hyperopt
Distributed Asynchronous Hyperparameter Optimization in Python
keras-gat
Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)
keras-tcn
Keras Temporal Convolutional Network.
multi-factor-gm-wind-joinquant
基于掘金+万得+聚宽的多因子策略开发框架
portfolioopt
Financial Portfolio Optimization Routines in Python
PredictingClosingPriceTomorrow
Predict the change in closing price from one trading day to the next into one of four bands for any stock using technical indicators and financial ratios as features.
Prediction-of-stock-prices-LSTM-and-NLP
Tomasz Słowik
pythondict-quant
Quant Examples Based on Backtrader.
qlib
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.
Reinforcement-learning-in-portfolio-management-
In this paper, we implement three state-of-art continuous reinforcement learning algorithms, Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO) and Policy Gradient (PG)in portfolio management.
Riskfolio-Lib
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
scikit-learn-doc-zh
:book: [译] scikit-learn（sklearn） 中文文档
SENN
Code implementation of "SENN: Stock Ensemble-based Neural Network for Stock Market Prediction using Historical Stock Data and Sentiment Analysis"
Sentiment-Analysis-in-Event-Driven-Stock-Price-Movement-Prediction
Use NLP to predict stock price movement associated with news
Stock-prediction-Dual-Attention-based-RNN-
Financial time series forecast using dual attention RNN
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
TD-seq
Backtrader TD Sequential
zipline
Zipline, a Pythonic Algorithmic Trading Library
zxpeter-stock_predict_machineLearning
针对沪深300指数的历史交易数据，通过机器学习的方法，预测股票的价格（涨跌概率），并借此来形成相应的交易策略。