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

Last update: Jan 03, 2023

Related tags

Data Visualization HIST

Overview

The HIST framework for stock trend forecasting

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

Environment

Install python3.7, 3.8 or 3.9.
Install the requirements in requirements.txt.

Install the Qlib and download the data:

# install Qlib from source
pip install --upgrade  cython
git clone https://github.com/microsoft/qlib.git && cd qlib
python setup.py install

# Download the stock features of Alpha360
python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/cn_data --region cn --version v2

Reproduce the stock trend forecasting results

git clone https://github.com/Wentao-Xu/HIST.git
cd HIST
mkdir output

Reproduce our HIST framework

# CSI 100
python learn.py --model_name HIST --data_set csi100 --hidden_size 128 --num_layers 2 --outdir ./output/csi100_HIST

# CSI 300
python learn.py --model_name HIST --data_set csi300 --hidden_size 128 --num_layers 2 --outdir ./output/csi300_HIST

Reproduce the baselines

# MLP on CSI 100
python learn.py --model_name MLP --data_set csi100 --hidden_size 512 --num_layers 3 --outdir ./output/csi100_MLP

# MLP on CSI 300
python learn.py --model_name MLP --data_set csi300 --hidden_size 512 --num_layers 3 --outdir ./output/csi300_MLP

LSTM

# LSTM on CSI 100
python learn.py --model_name LSTM --data_set csi100 --hidden_size 128 --num_layers 2 --outdir ./output/csi100_LSTM

# LSTM on CSI 300
python learn.py --model_name LSTM --data_set csi300 --hidden_size 128 --num_layers 2 --outdir ./output/csi300_LSTM

# GRU on CSI 100
python learn.py --model_name GRU --data_set csi100 --hidden_size 128 --num_layers 2 --outdir ./output/csi100_GRU

# GRU on CSI 300
python learn.py --model_name GRU --data_set csi300 --hidden_size 64 --num_layers 2 --outdir ./output/csi300_GRU

# SFM on CSI 100
python learn.py --model_name SFM --data_set csi100 --hidden_size 64 --num_layers 2 --outdir ./output/csi100_SFM

# SFM on CSI 300
python learn.py --model_name SFM --data_set csi300 --hidden_size 128 --num_layers 2 --outdir ./output/csi300_SFM

GATs

# GATs on CSI 100
python learn.py --model_name GATs --data_set csi100 --hidden_size 128 --num_layers 2 --outdir ./output/csi100_GATs

# GATs on CSI 300
python learn.py --model_name GATs --data_set csi300 --hidden_size 64 --num_layers 2 --outdir ./output/csi300_GATs

ALSTM

# ALSTM on CSI 100
python learn.py --model_name ALSTM --data_set csi100 --hidden_size 64 --num_layers 2 --outdir ./output/csi100_ALSTM

# ALSTM on CSI 300
python learn.py --model_name ALSTM --data_set csi300 --hidden_size 128 --num_layers 2 --outdir ./output/csi300_ALSTM

Transformer

# Transformer on CSI 100
python learn.py --model_name Transformer --data_set csi100 --hidden_size 32 --num_layers 3 --outdir ./output/csi100_Transformer

# Transformer on CSI 300
python learn.py --model_name Transformer --data_set csi300 --hidden_size 32 --num_layers 3 --outdir ./output/csi300_Transformer

ALSTM+TRA

We reproduce the ALSTM+TRA with its source code.

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

Related tags

Overview

The HIST framework for stock trend forecasting

Environment

Reproduce the stock trend forecasting results

Reproduce our HIST framework

Reproduce the baselines

Owner

Wentao Xu

股票行情实时数据接口-A股,完全免费的沪深证券股票数据-中国股市,python最简封装的API接口

kyle's vision of how datadog's python client should look

Create a table with row explanations, column headers, using matplotlib

paintable GitHub contribute table

Make visual music sheets for thatskygame (graphical representations of the Sky keyboard)

Library for exploring and validating machine learning data

Apache Superset is a Data Visualization and Data Exploration Platform

Streamlit-template - A streamlit app template based on streamlit-option-menu

OpenStats is a library built on top of streamlit that extracts data from the Github API and shows the main KPIs

cqMore is a CadQuery plugin based on CadQuery 2.1.

Create HTML profiling reports from pandas DataFrame objects

Interactive chemical viewer for 2D structures of small molecules

trade bot connected to binance API/ websocket.,, include dashboard in plotly dash to visualize trades and balances

Python implementation of the Density Line Chart by Moritz & Fisher.

SummVis is an interactive visualization tool for text summarization.

This is Pygrr PolyArt, a program used for drawing custom Polygon models for your Pygrr project!

An interactive dashboard built with python that enables you to visualise how rent prices differ across Sweden.

VDLdraw - Batch plot the log files exported from VisualDL using Matplotlib

Visualization Library

basemap - Plot on map projections (with coastlines and political boundaries) using matplotlib.