Patent-Based Predictive Price-to-Earnings Ratio on Increasing Investment Performance of China Stock Market

Li, Zhaohui; Deng, GuangYun; Che, Hui-Chung

doi:10.1109/iscid51228.2020.00097

Cited by 7 publications

(5 citation statements)

References 15 publications

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“…As for the study about PE, Beaver and Morse found that PE ratios not only predicted future earning changes but also identified transitory aspects of current earnings [1]. Li, Deng and Che found the stock selection criteria by the higher predictive PE growth rate was useful to build valuable stock portfolios for Shenzhen Main Board with better performance than the market trend [2]. Tripathi and Aggarwal investigated the existence of value effects in the Indian stock market and compared various value stock portfolios and found that the value effect was significant on the basis of unadjusted and risk-adjusted returns.…”

Section: Introductionmentioning

confidence: 99%

Research on Stock Market Decision Making based on Price-to-Earnings Ratio–Taking Shenzhen stock as an example

Zhang

2024

SHS Web Conf.

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Taking Shenzhen stock as an example, this paper explores the opportunity for high returns in the stock market through the study of the price-to-earnings ratio, and finally determines the optimal stock market decision. By trying different numerical value on the price-to-earnings ratio and calculating the total return based on historical data, it is obtained that buying when the price-to-earnings ratio is lower than 156 and selling when it is higher than 224.5 can get the highest return. However, in the following general study of high-yield decisions, it is found that all decisions are concentrated in the rapid rise in stock prices caused by “reform cattle” in 2015 in China. Therefore, in order to study more general strategies, the scope and difference of price-to-earnings ratio are redrawn and two feasible decision-making methods are obtained: risk-averse decision-making and risk-preference decision-making. Both two decisions are suitable in a relatively stable stock market, and can earn almost the same profit theoretically, so investors can choose any of them based on their preferences.

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Section: Introductionmentioning

confidence: 99%

Research on Stock Market Decision Making based on Price-to-Earnings Ratio–Taking Shenzhen stock as an example

Zhang

2024

SHS Web Conf.

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“…They also proposed the patent prediction equations for quantitatively giving the predictive values of the aforementioned financial indicators. Chiu, Chen & Che (2020c, 2020d, 2020e, 2020f, 2021, Li, Deng & Che (2020a, 2020b, 2021 further studied the patent leading effect on various stock boards of China, proposed each stock board's patent prediction equations on the stock price, ROA, ROE, BPS, EPS, PB and PE, finally proposed patent based stock selection criteria to have stock portfolio performance surpassing the market trend. Tsai, Che & Bai (2021a, 2021b, 2021c, 2021d, 2021e, 2021f, 2022 discussed the relationship between various China patent indicators and the performance of China listed companies (A-shares).…”

Section: Introductionmentioning

confidence: 99%

Longer Patent Life Representing Higher Value? A Study on China Stock Market and China Patents

Tsai¹,

Che²,

Bai³

2022

Bulletin of Applied Economics

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By setting the market capitalization as the frame of patent value reference, twenty-two quarter’s market capitalization from 2016Q1 to 2021Q2 of China listed companies (A-shares) were collected. All valid patent data of three patent species including the invention grant, the utility model grant and the design grant, were retrieved for calculating the average patent life of each A-share. The variances of the market capitalization via different patent life groups were analyzed via ANOVA. The A-shares having invention grant’s patent lives above the general level usually showed higher market capitalization means than the A-shares having invention grant’s patent lives below the general level. The invention grants with longer patent life might be regarded as the patents of higher value. The utility model grants with longer patent life might not be regarded as the patents of higher value because of poor significance. The design grant’s patent life was a significant indicator for discriminating China A-share’s market capitalization, however, the optimal patent life were close to but not longer than four years. The longer patent life of the design grants was not regarded as higher value. JEL classification numbers: C38, C46, G11, G12. Keywords: patent, market capitalization, China A-share, patent life, ANOVA.

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“…The A-share sizes are quite different in these four stock boards. Chiu, Chen and Che (2020c, 2020d, 2020e, 2020f, 2021, Li, Deng and Che (2020a further studied the patent leading effect in each of the four stock boards, proposed the patent prediction equations for each stock board on the stock price, return-on-asset, return-on-equity, book-value-per-share, earnings-per-share, price-to-book and price-to-earnings, finally proposed patent based stock selection criteria to build stock portfolios having preferable performance. For improving the performance of stock portfolios, Tsai, Che and Bai (2022) applied AI approach via patent forward citations to select preferable stocks for each stock boards and clearly showed AI's superiority and limitation when using patent indicators.…”

Section: Introductionmentioning

confidence: 99%

“…Lai and Che (2009a, 2009b, 2009c gave a first start on using the drawing count of US patents by applied the drawing count as an indicator for quantitatively modeling damage awards of infringement lawsuits. Though the drawing count of China patents has been applied for quantitatively giving the predictive values of A-share's financial indicators (Chiu et al, 2020a(Chiu et al, , 2020b(Chiu et al, , 2020c(Chiu et al, , 2020d(Chiu et al, , 2020e, 2020f, 2021Li et al, 2020aLi et al, , 2020bLi et al, , 2021, however, the relationship between the drawing count and A-share's financial performance has not been discussed therein. Tsai, Che & Bai (2022f) focused on China invention publication patents, discussed the average drawing count per patent and the total drawing count, and found that the average drawing count of invention publications was not a good indicator for differentiating China A-share's stock rate of return, whereas the total drawing count of invention publications was a good indicator because the A-shares having higher total drawing counts of invention publications usually showed higher stock rates of return.…”

Section: Introductionmentioning

confidence: 99%

Industry Difference on Patent Drawing’s Capability for Differentiating Stock Rates of Return of Chinese Listed Companies in Non-Manufacturing Industry Sectors -- An Explore into Invention Publication Patents and Utility Model Grant Patents

Tsai¹,

Che²

2022

Bulletin of Applied Economics

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The industry difference on patent drawings of invention publications and utility model grants over top nine non-manufacturing industry sectors in China stock market was discussed via analysis of variation (ANOVA). Regarding patent drawing count’s capability for differentiating Chinese listed company’s stock rate of return, the invention publication and the utility model grant were different. The invention publication’s drawing count showed well capability for one industry sector, fair capability for two industry sectors, partial capability for one industry sector, weak capability for two industry sectors, and ineffective capability for three industry sectors; whereas the utility model grant’s drawing count showed partial capability for four industry sectors, weak capability for three industry sectors, and ineffective capability for two industry sectors. The patent drawing count of invention publications showed superior capability to those of utility model grants and invention grants. The higher patent counts of invention publications showed fairly connection with the capability, however, the higher patent counts of utility model grants showed weak connection with the capability. The higher stock rates of return also showed weak connection with the capability for either invention publications or utility model grants. Every non-manufacturing industry sector had its particularity. The industry difference among top nine non-manufacturing industry sectors in China stock market was distinct. JEL classification number: C38, C46, G11. Keywords: Patent, Invention publications, Utility model grants, ANOVA, Stock rate of return, Drawing count, Industry difference.

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Patent-Based Predictive Price-to-Earnings Ratio on Increasing Investment Performance of China Stock Market

Cited by 7 publications

References 15 publications

Research on Stock Market Decision Making based on Price-to-Earnings Ratio–Taking Shenzhen stock as an example

Research on Stock Market Decision Making based on Price-to-Earnings Ratio–Taking Shenzhen stock as an example

Longer Patent Life Representing Higher Value? A Study on China Stock Market and China Patents

Industry Difference on Patent Drawing’s Capability for Differentiating Stock Rates of Return of Chinese Listed Companies in Non-Manufacturing Industry Sectors -- An Explore into Invention Publication Patents and Utility Model Grant Patents

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