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

A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

A custom qq-plot for two sample data comparision

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

Area-weighted venn-diagrams for Python/matplotlib

A filler visualizer built using python

FURY - A software library for scientific visualization in Python

Multi-class confusion matrix library in Python

Show Data: Show your dataset in web browser!

GitHubPoster - Make everything a GitHub svg poster

SummVis is an interactive visualization tool for text summarization.

📊📈 Serves up Pandas dataframes via the Django REST Framework for use in client-side (i.e. d3.js) visualizations and offline analysis (e.g. Excel)

Domain Connectivity Analysis Tools to analyze aggregate connectivity patterns across a set of domains during security investigations

Graphing communities on Twitch.tv in a visually intuitive way

Attractors is a package for simulation and visualization of strange attractors.

Comparing USD and GBP Exchange Rates

eoplatform is a Python package that aims to simplify Remote Sensing Earth Observation by providing actionable information on a wide swath of RS platforms and provide a simple API for downloading and visualizing RS imagery

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

This is a sorting visualizer made with Tkinter.

CLAHE Contrast Limited Adaptive Histogram Equalization

Script to create an animated data visualisation for categorical timeseries data - GIF choropleth map with annotations.