THE SIGNIFICANCE OF COMPANY INNOVATIVENESS FOR STOCK PRICE AND VOLATILITY
The aim of this paper was to determine whether company innovativeness is significant for the price and volatility of stocks. In modern business conditions, innovation is one of the foundations of business success because companies that innovate not only monitor changes in the environment but also ge...
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Published in: | Časopis za Ekonomiju i Tržišne Komunikacije Vol. 23; no. 1 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
01-06-2022
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Online Access: | Get full text |
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Summary: | The aim of this paper was to determine whether company innovativeness is significant for the price and volatility of stocks. In modern business conditions, innovation is one of the foundations of business success because companies that innovate not only monitor changes in the environment but also generate new revenue, open new markets, and so on, which significantly improves their position in relation to the competition. Exploring the significance of innovation for stock price movements can be important for understanding how the market reacts to innovation, but it can also motivate companies to invest more in innovation processes and the implementation of innovation activities. In the paper, the authors used a quantitative methodology based on a panel regression analysis of data collected from secondary sources for the period from 2005 to 2020. The research included eight of the most innovative companies ranked by the Boston Consulting Group. The results indicate that company innovativeness is statistically significant for average stock price and coefficients of variability. Given the important role that innovativeness plays in a company’s business, the results obtained can serve as guidelines for managers in charge of implementing innovation activities in companies, as well as investors and other relevant stakeholders. Recommendations for future research are aimed at expanding the model with additional variables, which could potentially increase the representativeness of the model, and testing existing models on other data sources. |
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ISSN: | 2232-8823 2232-9633 |
DOI: | 10.7251/EMC2201208K |