wesley1001's repositories
ML-stock-prediction-models
使用机器学习进行股票预测并指导短线(预测未来3日股价)交易。
Quantitative-analysis
量化研究-券商金工研报复现
Stock-Market-Trend-Analysis-Using-HMM-LSTM
Stock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory
adaptive-asset-allocator-simulator
Simulates an adaptive asset allocation investment strategy over time
AutoTrader-1
A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.
Awesome-Trading-Algorithm
This algorithm takes a daily position on the SPY ETF by indirectly predicting the change in price through the put/call ratio. I do this by implementing machine learning techniques on Sofien Kaabar's put/call ratio trading strategy.
backtrader-pyqt-ui
Easy to use backtrader UI
CGM
Code for IJCAI 2021 main conference paper "Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling"
dlsa-public
Deep Learning Statistical Arbitrage
Hierarchical-Risk-Parity
Using Yahoo Finance and Hierarchical Risk Parity (Marcos López de Prado) to compute a portfolio of weights on South African equity shares
HIST
The source code and data of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".
HMMs_Stock_Market
Contains all code related to using HMMs to predict stock market prices.
june_applications_21
Skillset Challenge for the Apprenticeship Program, June 2021.
march_applications_21
Skillset Challenge for the Apprenticeship Program
MLFINLAB
public version of MLFINLAB from Hudson-Thames
momentum_trading_strategies
An application of high quality and low quality momentum trading on the S&P500, using the IEX Cloud API.
oct_applications
Applications to the apprenticeship program, October 2020.
pysystemtrade
Systematic Trading in python
QuantResearch
Quantitative analysis, strategies and backtests
sp500-stock-similarity-time-series
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.
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.
stockPriceDirectionPrediction
Determining stock price direction by using CNN on 1-D time series data encoded as 2-D Images
trading-rules-using-machine-learning
A financial trading method using machine learning.
Trend-Following-Strategies
Official Repository
tuneta
Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
zm_machine_learning_project
machine learning on tick stock data using idea from marcos lopez de prado's book