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Does Patent Help to Build Investment Portfolio of China A-Shares under China-US Trade Conflict?
- Source :
- Mathematical Problems in Engineering, Vol 2020 (2020)
- Publication Year :
- 2020
- Publisher :
- Hindawi Limited, 2020.
-
Abstract
- Patent, a legal representation of innovation achievement, is strongly meaningful for almost every country’s economic growth and technology development. China, the world’s no. 2 stock market, is the world’s largest patent application country. In this study, we observed 2,197 China-listed companies of Renminbi (RMB) common stocks (A-shares) from 2016 to 2018. The relationship among 570 valid patent indicators and financial indicators of the stock price, Return-on-Assets (ROA), and Return-on-Equity (ROE) was examined. We constructed patent leading indicators, patent kernel indicators, and patent prediction equations for predicting the stock price, ROA, and ROE using the Granger causality test and the dynamic time series forecast model. The stock performance of investment portfolios based on patent prediction equations was thoroughly discussed. We found that investment portfolios constructed by the higher predictive ROA, the higher predictive ROE, and the higher predictive stock price growth rate have better performance than the A-shares’ average. The underlying concept behind this study is that despite the overall economic environment fluctuation and the China-US trade conflict, the patent-based algorithm proposed was proved to be useful to discover good investment portfolios.
- Subjects :
- 050208 finance
Article Subject
Financial economics
General Mathematics
05 social sciences
General Engineering
Engineering (General). Civil engineering (General)
Patent application
Economic indicator
Granger causality
0502 economics and business
QA1-939
Renminbi
Economics
Common stock
Stock market
TA1-2040
China
Mathematics
050203 business & management
Stock (geology)
Subjects
Details
- ISSN :
- 15635147 and 1024123X
- Volume :
- 2020
- Database :
- OpenAIRE
- Journal :
- Mathematical Problems in Engineering
- Accession number :
- edsair.doi.dedup.....2163911bc25f337404004546b38a0eac
- Full Text :
- https://doi.org/10.1155/2020/7317480