hyunjoon526 Goto Github PK

adv-alstm

Code for paper "Enhancing Stock Movement Prediction with Adversarial Training" IJCAI 2019

datascience-interview-questions

Datascience-Interview-Questions for Korean

estimate

hist

The source code and data of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".

hyunjoon526.github.io

master

This is the official code and supplementary materials for our AAAI-2024 paper: MASTER: Market-Guided Stock Transformer for Stock Price Forecasting. MASTER is a stock transformer for stock price forecasting, which models the momentary and cross-time stock correlation and guide feature selection with market information.

patchtst

An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730

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. An increasing number of SOTA Quant research works/papers are released in Qlib.

stock-prediction-deep-neural-learning

Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting

stock-prediction-models

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

stock-price-prediction-model

Stock Price prediction using news data. The datasets used consists news and stock price data from 2008 to 2016. The polarity(Subjectivity, Objectivity, Positive, Negative, Neutral) data is gathered from the news data and further used to predict stock prices. Achieved an accuracy of 94% using XGBoost.

stocknet-code

Code for stock movement prediction from tweets and historical stock prices.

stocknet-dataset

A comprehensive dataset for stock movement prediction from tweets and historical stock prices.

ta

Technical Analysis Library using Pandas and Numpy