/Dynamic-Stock-Co-Movement-Graphs-for-Stock-Predictions

Code for paper "Inductive Representation Learning on Dynamic Stock Co-Movement Graphs for Stock Predictions"

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

HAD-GNN

This repository contains the data and code for the paper "Inductive Representation Learning on Dynamic Stock Co-Movement Graphs for Stock Predictions". We are updating the code.

Datasets

This paper collected datasets from Yahoo! Finance for three major stock markets in the US, China, and Australia. The datasets "s&p500", "csi300", and "asx300" represent major companies in these market indices: Standard and Poor’s 500 (S&P 500), China Securities Index 300 (CSI 300), and Australian Securities Exchange 300 (ASX 300). In each dataset folder, there are two types of files for each dataset.

The file "./raw_data/stock_name.csv" contains the raw data for stock "stock_name" on the given period. The raw data includes five features: the opening price, high price, low price, closing price, and trading volume.

The file "date.csv" gives the data collection period.

The file "stock_symbols.csv" is the stock list of the corresponding market index.