research-article

Discovering the influences of the patent innovations on the stock market

Authors:

Jinchen HuoAuthors Info & Claims

Volume 59, Issue 3

https://doi.org/10.1016/j.ipm.2022.102908

Published: 01 May 2022 Publication History

Abstract

With the implementation of the innovation-driven development strategy, increasing technical innovations are patented by the individuals or the companies. As a form of intellectual properties, the patent has attracted attention from individuals and companies. Although there are some researches on the economic function of patent, few quantitative researches discuss on whether patents can work on the company stock market. To discover the relations between the company patents and the stock market, we explore a method to analyze the influence of patent activity on the company stock market. We collect the patent data and the stock data of listed companies, from which patent and market activities are extracted. By the recursive discrete wavelet transform, the patent and market activities are decomposed into multi-scale wavelets. These wavelets are fed into a patent and market activity based stock market trend prediction model, in which the influences of patent activity are analyzed. We compare our model with the state-of-the-art model on 4 measurements for 3 manufacturing datasets. The experimental results show that the patent activities have positive effect on market trend prediction in about 30% manufacturing listed companies and that the measurements of Shanghai/Shenzhen Stock Exchange often outperform that of USA in years 2016–2019 for the manufacturing listed companies.

Highlights

•

The patent and market activities based stock market trend prediction model includes a discrete wavelet transform method and a long-short-term memory based market trend prediction method.

•

The discrete wavelet transform method results in wavelet based representation of patent and market actives.

•

The long-short-term memory based market trend prediction method predicts market trend and analyzes the patent influence.

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Cited By

Liu WZhang YLuo XCao YGan KYe FTang WZhang M(2024)Patent transformation predictionInformation Processing and Management: an International Journal10.1016/j.ipm.2024.10387261:6Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1016/j.ipm.2024.103872
Liu HZhao TWang SLi X(2023)A stock rank prediction method combining industry attributes and price data of stocksInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10335860:4Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1016/j.ipm.2023.103358
Liu WLi SCao YWang Y(2023)Multi-task learning based high-value patent and standard-essential patent identification modelInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10332760:3Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1016/j.ipm.2023.103327

Index Terms

Discovering the influences of the patent innovations on the stock market
1. Applied computing
  1. Enterprise computing
  2. Law, social and behavioral sciences
    1. Economics
2. Information systems

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Information Processing and Management: an International Journal

Information Processing and Management: an International Journal Volume 59, Issue 3

May 2022

760 pages

ISSN:0306-4573

Issue’s Table of Contents

Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 May 2022

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Cited By

Liu WZhang YLuo XCao YGan KYe FTang WZhang M(2024)Patent transformation predictionInformation Processing and Management: an International Journal10.1016/j.ipm.2024.10387261:6Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1016/j.ipm.2024.103872
Liu HZhao TWang SLi X(2023)A stock rank prediction method combining industry attributes and price data of stocksInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10335860:4Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1016/j.ipm.2023.103358
Liu WLi SCao YWang Y(2023)Multi-task learning based high-value patent and standard-essential patent identification modelInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10332760:3Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1016/j.ipm.2023.103327

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