Pinned Repositories
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.
trading_with_ta_backtesting
Trading backtesting with technical indicators
Asset-Portfolio-Management-usingDeep-Reinforcement-Learning-
This repository represents work in progress for the Worldquant University Capstone Project titled: Asset Portfolio Management using Deep Reinforcement Learning (DRL). The work presented explores the use of Deep Reinforcement Learning in dynamically allocating assets in a portfolio in order to solve the Tactical Asset Allocation (TAA) problem.
IndRNN_Theano_Lasagne
This code is to implement the IndRNN.
mlfinlab
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
QuantResearch
Quantitative analysis, strategies and backtests
Sector-Rotation-RNN
A simple, self-coded recurrent neural network that uses weekly changes in 10 major sector ETFs to predict which sectors will grow in the coming weeks.
Stock-Market-Trend-Analysis-Using-HMM-LSTM
Stock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory
StockSimilarity
Improve S&P 500 stock price prediction (random forest and gradient boosting trees) with time series similarity measurements: DTW, SAX, co-integration, Euclidean and Pearson.
WordFrequencyPython
Python code to find out most frequent words from different word lists
proxyanonymous's Repositories
proxyanonymous/QuantResearch
Quantitative analysis, strategies and backtests
proxyanonymous/Asset-Portfolio-Management-usingDeep-Reinforcement-Learning-
This repository represents work in progress for the Worldquant University Capstone Project titled: Asset Portfolio Management using Deep Reinforcement Learning (DRL). The work presented explores the use of Deep Reinforcement Learning in dynamically allocating assets in a portfolio in order to solve the Tactical Asset Allocation (TAA) problem.
proxyanonymous/WordFrequencyPython
Python code to find out most frequent words from different word lists
proxyanonymous/trading_with_ta_backtesting
Trading backtesting with technical indicators
proxyanonymous/yahooquery
Python wrapper for an unofficial Yahoo Finance API
proxyanonymous/Stock-Market-Trend-Analysis-Using-HMM-LSTM
Stock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory
proxyanonymous/mlfinlab
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
proxyanonymous/StockSimilarity
Improve S&P 500 stock price prediction (random forest and gradient boosting trees) with time series similarity measurements: DTW, SAX, co-integration, Euclidean and Pearson.
proxyanonymous/IndRNN_Theano_Lasagne
This code is to implement the IndRNN.
proxyanonymous/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.
proxyanonymous/Sector-Rotation-RNN
A simple, self-coded recurrent neural network that uses weekly changes in 10 major sector ETFs to predict which sectors will grow in the coming weeks.