Antonio Pedro Soares Pinto
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Certification of Portuguese companies as an inducer of profitability: A panel data approach
Anabela Santos , Antonio Pedro Soares Pinto , Pedro Reis , Elisabete Neves doi: http://dx.doi.org/10.21511/ppm.20(4).2022.35Problems and Perspectives in Management Volume 20, 2022 Issue #4 pp. 465-482
Views: 331 Downloads: 68 TO CITE АНОТАЦІЯWith the globalization and internationalization of markets, companies need to be more competitive and offer high-quality guarantees to consumers, suppliers, banking institutions, and shareholders. Thus, the objective of this paper is to measure the impacts that these guarantees, analyzed through quality management, environmental management, and management of occupational health and safety standards, will have on the return on assets (ROA) of companies classified by sector of activity, considering each of the certifications individually and as a whole. The panel data approach methodology was used for 10 years in Portuguese-certified companies between 2010 and 2019. The Chow test, the Breusch-Pagan, and the Hausman test were applied to identify a more feasible model between the pooled OLS and the random or fixed effects model. Furthermore, the cluster-robust standard errors model was applied.
The results show the existence of synergies when adopting more than one certification to improve firm performance. Moreover, the single certification estimate by sector results are significant and can be positive drivers of profitability, but only for companies in the manufacturing industries related to natural resources. However, they trigger negative results in the accommodation, catering, and information and communication sectors.Acknowledgment
This paper is funded by National Funds through the FCT – Foundation for Science and Technology, I.P., within the scope of the project Refª UIDB/05583/2020. Furthermore, we would like to thank the Research Centre in Digital Services (CISeD) and the Instituto Politécnico de Viseu, for their support. -
The influence of consumer, manager, and investor sentiment on US stock market returns
Pedro Manuel Nogueira Reis , Antonio Pedro Soares Pinto , Andre Guimaraes doi: http://dx.doi.org/10.21511/imfi.22(1).2025.18Investment Management and Financial Innovations Volume 22, 2025 Issue #1 pp. 231-256
Views: 9 Downloads: 4 TO CITE АНОТАЦІЯThis study examines how consumer, investor, and manager sentiment explain US stock excess returns over 23 years. Its novelty resides in integrating the sentiments of three different types of economic and financial agents. It also performs a segmented temporal analysis using rolling window techniques, to assess sentiment’s impact across different time horizons. The empirical analysis utilizes the Paris-Winsten and Newey-West estimators, along with the ARMAX model to address autocorrelation and heteroscedasticity in linear regression, providing robust standard errors and reliable statistical inferences. The autoregressive moving average models estimate excess return based on the past values, shocks, and external variables. Combining the Fama-French five-factor model with the sentiment factor enriches the analysis. The study’s findings indicate that higher consumer optimism negatively impacts excess returns, as investors may anticipate a future decline in the stock market due to an existing overheated economy. Investor sentiment exhibits mixed behavior, where higher uncertainty may increase stock returns due to previous oversold markets creating opportunities for investors or due to the closing of short positions, which will also increase stock demand. It is also related to decreased stock returns depending on the proxy used. As for managers’ sentiment, this work did not demonstrate a relevant relationship between this sentiment and stock returns. The study also reveals that the importance of sentiment determinants of those three agents changes over time. The findings support behavioral models of asset pricing, which incorporate both market fundamentals and the psychological characteristics (sentiment) of different market participants.
Acknowledgments
This work is funded by National Funds through the FCT – Foundation for Science and Technology, I.P., within the scope of the project Ref. UIDB/05583/2020. Furthermore, we would like to thank the Research Centre in Digital Services (CISeD) and the Instituto Politécnico de Viseu for their support.
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