THE EFFECTS OS INNOVATION ON THE SYSTEMATIC RISK OF TECHNOLOGY COMPANIES LISTED ON THE S&P500
Keywords:
S&P500. Beta Coefficient. Volatility. Risk-return. Innovation.
Abstract
This research estimated the effect of innovation on the systematic risk coefficient of American technology companies listed on the S&P 500 index. This is a descriptive and quantitative study that covered 37 retail companies and 66 technology companies, analyzed between January 4, 2012, and December 30, 2022. The data regarding daily closing prices was collected from Yahoo Finance, and the information related to investments in R&D was obtained from Stock Analysis website. The following techniques were used: the correlation matrix, simple regression, the Student's t-test, the ARCH model for calculating volatilities, as well as a fixed effects panel model. The data was processed using the statistical software STATA 18. It was concluded that the beta coefficients of technology companies are positively and significantly influenced by investments in R&D, being 1.92 times higher than those of retail companies.
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References
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WANG, L.; BI, X. Risk assessment of knowledge fusion in an innovation ecosystem based on a GA-BP neural network. Cognitive Systems Research, v. 66, p. 201-210, 2021.
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ZACKS. Innovation, Buyouts & More to Fuel Consumer Staples Growth. Disponível em: https://www.nasdaq.com/articles/innovation-buyouts-more-to-fuel-consumer-staples-growth-2018-04-27 . Acesso em 18 mai 2023.
ASSAF NETO. A. Finanças corporativas e valor. São Paulo: Editora GEN, 2020.
AYINADDIS, S. G. Exploring firm-specific deterrents of innovation in micro and small enterprises in Ethiopia. Journal of Innovation and Entrepreneurship, v. 11, n. 1, p. 57, 2022.
BIØRN, E. Econometrics of panel data: Methods and applications. Oxford University Press, 2017.
BERK, J.; DEMARZO, P. Corporate Finance, Global Edition. Essex: Person Education Limited, 2019.
BOWERS, J.; KHORAKIAN, A. Integrating risk management in the innovation project. European Journal of innovation management, vol. 17, n. 1, pp. 25-40, 2014.
BROOKS, C. Introductory econometrics for finance. Cambridge university press, 2019.
BRYMAN, A.; BELL, E. Business Research Methods. 3.ed. New York: Oxford University Press, 2011.
CALDAS, A. V. S. et al. Os efeitos da Covid-19 sobre o desempenho das ações dos setores da B3. Contextus – Revista Contemporânea de Economia e Gestão, v. 19, n. 2, p. 15-28, 2021.
CASTELACCI, F. Innovation and the competitiveness oF industries: Comparing the mainstream and the evolutionary approaches. Technological Forecasting and Social Change, vol 75, pp. 984-1006, 2008.
CHOI, S.Y. Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic. Physica A: Statistical Mechanics and Its Applications, v. 574, p. 125988, 2021.
CORREIA, A. M. M.; GOMES, M. L. B.; DINIZ, L. L. Habitat’s of innovation in the knowledge economy: a comparative analysis of technology parks located in the Northeast region of Brazil. Independent Journal of Management & Production, vol. 4, n. 1, pp. 315-337, 2013.
DAMODARAN, A. Applied corporate finance. John Wiley & Sons, 2015.
DUONG, K. D. et al. How innovation and ownership concentration affect the financial sustainability of energy enterprises: evidence from a transition economy. Heliyon, v. 8, n. 9, 2022.
EUROPEAN COMMISSION. The potential of Market pull instruments for promoting innovation in environmental characteristics. Final Report, February, 2009.
FÁVERO, L.P. Métodos Quantitativos com Stata. São Paulo: GEN, 2014.
GOODELL, J. W.; HUYNH, T. L. D. Did Congress trade ahead? Considering the reaction of US industries to COVID-19. Finance Research Letters, v. 36, p. 101578, 2020.
GITMAN, L. J.; ZUTTER, C.J. Principles of managerial finance. 14th edition. Pearson Education, 2015.
HAMILTON, L. C. Statistics with Stata: version 12. Cengage Learning, 2012.
HIZAM-HANAFIAH, M.; SOOMRO, M. A. The situation of technology companies in industry 4.0 and the open innovation. Journal of open innovation: technology, market, and complexity, v. 7, n. 1, p. 34, 2021.
HORBACHENKO, S. A. et al. Innovative development of Ukraineﹸs economy. Financial and Credit Activity Problems of Theory and Practice, v. 3, n. 38, p. 390-396, 2021.
KITCHING, J.; BLACKBURN, R. A. Business strategies and performance during difficult economic conditions. Research Gate, Technical Report, outubro, 2009.
LABORDA, R.; OLMO, J.Volatility spillover between economic sectors in financial crisis prediction: Evidence spanning the great financial crisis and Covid-19 pandemic. Research in International Business and Finance, v. 57, p. 101402, 2021.
LLOYD, C. et al. COVID-19: A brief guide to circuit breakers and powers close the market. Alert Memorandum. Clearry Gottlieb Dteen & Hamilton LLP, 2020.
LU, M. Ranked: The Most Innovative Companies in 2023. Disponível em: https://www.visualcapitalist.com/most-innovative-companies-2023/ Acesso em 30 abr. 2024.
MARQUES, C. S.; FERREIRA, J. SME innovative capacity, competitive advantage and performance in a'Traditional'industrial region of Portugal. Journal of technology management & innovation, vol. 4, n. 4, pp. 53-68, 2009.
MARTINS, G. A.; THEÓPHILO, C. R. Metodologia da investigação científica para ciências sociais aplicadas. São Paulo: Atlas, 2009.
MEHMETOGLU, M.; JAKOBSEN, T. G. Applied Statistics Using Stata: A Guide for the Social Sciences . SAGE Publications. Edição do Kindle, 2017.
MENSI, W. et al. Dynamic frequency volatility spillovers and connectedness between strategic commodity and stock markets: US-based sectoral analysis. Resources Policy, v. 79, p. 102976, 2022.
OCDE/Eurostat (2018), Oslo Manual 2018: Guidelines for Collecting, Reporting and Using Data on Innovation, 4th Edition, The Measurement of Scientific, Technological and Innovation Activities, OCDE Publishing, Paris/Eurostat, Luxemburgo. https:// doi.org/ 10.1787/9789264304604-en.
PAGANO, M.; WAGNER, C.; ZECHNER, J. Disaster resilience and asset prices. Journal of Financial Economics, v. 150, n. 2, p. 103712, 2023.
PANTANO, E.; VIASSONE, M. Demand pull and technology push perspective in technology-based innovations for the points of sale: The retailers evaluation. Journal of Retailing and Consumer Services, v. 21, n. 1, p. 43-47, 2014.
PASTOR, L.; VERONESI, P. Technological revolutions and stock prices. The American Economic Review, vol. 99, n. 4, set., 2009.
PETRI, J. M. Proposta de um framework de avaliação de projetos de investimento em inovação tecnológica de startup. 2021. 143 p. Dissertação. (Mestrado em Engenharia de Produção e Sistemas) – Universidade Tecnológica Federal do Paraná. Pato Branco; 143 p. 2021.
PORTER, M. E.; RIVKIN, J.W. The Looming Challenge to U.S. Competitiviness. Disponível em: https://hbr.org/2012/03/the-looming-challenge-to-us-competitiveness Acesso em 28 abr. 2024,
ROSS, S. A. et al. Fundamentals of Corporate Finance. 10th Canadian ed. McGraw Hill, New York, 2019.
SAUNDERS, M; LEWIS, P.; THORNILL, A. Research Methods for Business Students. 8. ed. Harlow, England: Pearson Education, 2019.
SCHOPOHL, L.; WICHMANN, R.; BROOKS, C. Stata Guide to Accompany Introductory Econometrics for Finance. Cambridge University Press, 2019.
SCHUMPETER, J. A. Capitalism, Socialism and Democracy. George Allen & Unwin Ltda, London, 1976.
SHANKAR, Venkatesh et al. How technology is changing retail. Journal of Retailing, v. 97, n. 1, p. 13-27, 2021.
SINGH, A. G. Predictive Value of Estimated Beta. Westcliff International Journal of Applied Research,v. l. 5, No. 1. Fall 2021.
SMANIOTTO, Emanuelle; ZANI, João. Circuit breakers and volatility: Evidence from high frequency data on brazilian stock exchange. WFE Research Working Paper, 2020. Disponível em: https://www.researchgate.net/publication/342014244_Circuit_Breakers_and_Volatility_Evidence_from_High_Frequency_Data_on_Brazilian_Stock_Exchange . Acesso em 02 jun. 2024.
S&P 500. Components. Disponível em https://fknol.com/list/market-cap-sp-500-index-companies.php . Acesso em 02 de abril de 2022.
S&P 500. Market Cap of S&P 500 Index Constituents 2022. Disponível em: https://fknol.com/list/market-cap-sp-500-index-companies.php Acesso em 02 de abril de 2022.
STOCKEMER, D. Quantitative methods for the social sciences. A Practical Introduction with Examples in SPSS and Stata. Springer International Publishing, 2019.
TETİK, M.; CİĞEROĞLU, E. T.; YEŞİLDAĞ, E. Did 2008 Crisis Affect Systematic Risks of the Sectors? The Case of Turkey. Optimum Ekonomi ve Yönetim Bilimleri Dergisi, v. 7, n. 2, p. 581-592, 2020.
UMAIR, A. Top 20 Largest Consumer Staples Companies in the World. Disponível em: https://finance.yahoo.com/news/top-20-largest-consumer-staples-163350027.html. Acesso em 18 Jun, 2023.
VENKAIAH, V.; DRUCKER, P. Leadership in a globalised economic era: some perspectives and challenges. Department of Management Sciences, 2013. Disponível em: http://ms.rvrjcce.ac.in/6druckerlecture.pdf . Acesso em 02 de março de 2022.
WANG, L.; BI, X. Risk assessment of knowledge fusion in an innovation ecosystem based on a GA-BP neural network. Cognitive Systems Research, v. 66, p. 201-210, 2021.
WANG, W.; WANG, M; PAN, S. The Moderating Effect of R&D on Corporate Social Responsibility and Equity Financing Cost. International Review of Accounting, Banking & Finance, v. 14, n. 2, 2022.
Wolf V., Dobrucka R., Przekop R., Haubold St., 2021. Estratégias de inovação cooperativa – revisão e análise. Revista Científica de Logística. LogForum 17 (4), 477-484, http:// doi.org/ 10.17270/ J.LOG.2021.621.
ZACKS. Innovation, Buyouts & More to Fuel Consumer Staples Growth. Disponível em: https://www.nasdaq.com/articles/innovation-buyouts-more-to-fuel-consumer-staples-growth-2018-04-27 . Acesso em 18 mai 2023.
Published
2025-02-06
How to Cite
Silva Caldas, A. V., Oliveira Vieira, M., Barbosa de Queiroz, V., & Cabral Nogueira Lima, A. (2025). THE EFFECTS OS INNOVATION ON THE SYSTEMATIC RISK OF TECHNOLOGY COMPANIES LISTED ON THE S&P500. Caderno De Administração, 32(2), 116-139. https://doi.org/10.4025/cadadm.v32i2.73864
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