williamwongys Goto Github PK

followers: 0.0 following: 0.0 repos: 25.0 gists: 0.0

Name: William Wong

Type: User

Bio: Use ML to forecast prices Built ensemble model on various supervised training algos Built RL model based on DQN and A3C currently trying CNN-LSTM model

William Wong's Projects

advances-in-financial-machine-learning

Lectures of the Book "Advances in Financial Machine Learning" from Marcos Lopez de Prado

auto_ml

In this repository we test AutoML approaches for time-series forecasting

automatedstocktrading-deepq-learning

Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.

block-predict-based-on-news-a-

(公开新闻预测A股行业板块动向亚军源码)This is my first open Source for the competition Block Predict Based on News(https://www.kesci.com/home/competition/5cac39ea67205f002bdbf243) ,and fortunately which ranked the 2nd in the final round.Thanks to Kesci and Competetion Organizer .By the way ,I open my source code to help more for new guys to achieve more honor or make bigger progresses.All in one,Just Carry On.

cnn-rnn-bitcoin

Reusable CNN and RNN model doing time series binary classification

deep-learning-for-hackers

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

deep-reinforcement-stock-trading

A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.

deeplearning

Reinforcement Learning,NLP,VAE,CNN,Stock,Economic,Review,Quant

demand_forcasting_and_safety_stock_management

Demand forcasting using time series analysis and safety stock optimization to provide desired service level

financeops

Research in investment finance with Python Notebooks

fintech-2019-2020-ay1

In this project, we compared the impact of popular ML time series models (trees, prophet, LSTM, SVM) in stock price prediction and trend signal classification;

forecast-exchange-rate

中美汇率预测作业

hk_ipo_prediction

Predict first day performance of Hong Kong IPO stocks: A pipeline example of machine learning projects

marketvectors

Implementations for my blog post [here](https://medium.com/@TalPerry/deep-learning-the-stock-market-df853d139e02#.flflpo3xf)

practical-deep-learning-applied-to-time-series

Practical Deep Learning resources for Time series analysis and forecasting

predicting-loan-repayment-with-automated-feature-engineering-in-featuretools

通过Featuretools自动特征工程预测贷款偿还

revisit

A repository of customer revisit prediction research.

self-boosted-time-series-forecasting

Pytorch implementation of "Self-boosted Time-series Forecasting with Multi-task and Multi-view Learning" https://arxiv.org/pdf/1909.08181.pdf

stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

stock_a

「A股指数预测」深度学习量化应用

test-stock-prediction-algorithms

Use deep learning, genetic programming and other methods to predict stock and market movements

time-series-classification-and-clustering

Time series classification and clustering code written in Python.

time-series-forecasting-of-amazon-stock-prices-using-neural-networks-lstm-and-gan-

Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.

timeseries_seq2seq

This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.

trading-rules-using-machine-learning

This is my financial trading system using ML (Random forest & LSTM). Most of the methods are based on 'Advances in Financial Machine Learning' by Lopez de Prado.

williamwongys Goto Github PK

William Wong's Projects

Recommend Projects

Recommend Topics

Recommend Org