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Using Patent Drawings to Differentiate Stock Return Rate of China Listed Companies. A Study on China Patent Species of Invention Grant

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  • Chin-Yi Chen
  • Ching-Lin Chu
  • Hui-Chung Che
  • Hong-Wen Tsai
  • Bo Bai

Abstract

Patent is an important outcome of technological innovation. Though patent claim always caught attention when considering patent quality, it had to be supported by the drawings according to the patent examination criteria. However, patent drawing was seldom discussed. Based on the company integrated database, more than 50% of China listed companies of RMB common stocks (A-shares) from 2017Q1 to 2021Q4 were selected as effective samples. The effect of China invention grant patent’s drawing count for differentiating A-share’s stock return rate was thoroughly discussed via analysis of variation (ANOVA). The average drawing count of invention grants significantly increased over previous years. However, the total drawing count of invention grants was found to be an appropriate patent indicator for differentiating A-share’s stock return rate whereas the average drawing count of invention grants was not. The A-shares in the highest total drawing count groups of invention grants showed significantly higher stock return rate means while the A-shares in the lower total drawing count groups of invention grants showed significantly lower stock return rate means in most quarters from 2017 to 2021. The finding also proved that the patent quantity still mattered in China stock market.  JEL classification numbers: C38, C46, G11, G12.

Suggested Citation

  • Chin-Yi Chen & Ching-Lin Chu & Hui-Chung Che & Hong-Wen Tsai & Bo Bai, 2022. "Using Patent Drawings to Differentiate Stock Return Rate of China Listed Companies. A Study on China Patent Species of Invention Grant," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 12(3), pages 1-4.
    • Handle: RePEc:spt:admaec:v:12:y:2022:i:3:f:12_3_4
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    References listed on IDEAS

    as
    1. Liu, Qing & Qiu, Larry D., 2016. "Intermediate input imports and innovations: Evidence from Chinese firms' patent filings," Journal of International Economics, Elsevier, vol. 103(C), pages 166-183.
    2. Hong-Wen Tsai & Hui-Chung Che & Bo Bai, 2021. "Innovation Continuity as Indicator for Observing Stock Return Rate in China Stock Market," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(5), pages 1-2.
    3. Yu-Jing Chiu & Kuang-Chin Chen & Hui-Chung Che, 2020. "Does Patent Help to Build Investment Portfolio of China A-Shares under China-US Trade Conflict?," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-12, May.
    4. Dang, Jianwei & Motohashi, Kazuyuki, 2015. "Patent statistics: A good indicator for innovation in China? Patent subsidy program impacts on patent quality," China Economic Review, Elsevier, vol. 35(C), pages 137-155.
    5. Hong-Wen Tsai & Hui-Chung Che & Bo Bai, 2022. "Longer Patent Life Representing Higher Value? A Study on China Stock Market and China Patents," Bulletin of Applied Economics, Risk Market Journals, vol. 9(1), pages 115-136.
    6. Boeing, Philipp & Mueller, Elisabeth, 2019. "Measuring China's patent quality: Development and validation of ISR indices," China Economic Review, Elsevier, vol. 57(C).
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    More about this item

    Keywords

    Patent; ANOVA; Stock return rate; Drawing count; Invention grant.;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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