Pesquisa publicada na Revista FSA (Qualis B2). Autores: Daniel Christian Henrique - Prof. Adjunto do EPS/UFSC; Ivan Aune de Aguiar Filho - Bolsista de Extensão Probolsas; João Carlos Prats Ramos - Bolsista de Extensão Probolsas; Gabriel Dudena de Faria - Bolsista de Extensão Probolsas. A pandemia da covid-19 gerou sérios percalços financeiros e de saúde pública no mundo, aumentando a mortalidade e o desemprego, principalmente no primeiro ano de 2020, advindo dos lockdowns, assim como forçando 151 nações a criarem auxílios de renda emergenciais até o desenvolvimento e aplicação do ciclo vacinal completo. Ingressando no ano de 2022, houve uma volta à “normalidade”, mantendo-se um convívio com as novas variantes que até hoje rondam (com as atuais cepa Éris e Arcturus espalhando-se rapidamente pelo mundo). Este estudo, portanto, objetivou analisar o impacto que o número total de casos e de mortes gerados pela covid-19 ocasionou na variação da parcela da população que vive em extrema pobreza no mundo entre 2020 e 2022, assim como sua relação com as variações do Índice de Desenvolvimento Humano (IDH) e do PIB Per Capita dos países. Adicionalmente, este estudo é uma adaptação e evolução da pesquisa de Vitenu-Sackey e Barfi (2021) que analisou variáveis equivalentes, porém aplicadas somente aos meses iniciais da pandemia nos quais o mundo ainda se adaptava a esse novo contexto econômico, social e sanitário. Os dados foram obtidos no Our World In Data (2023), que coleta e organiza dados de fontes públicas de organizações mundiais de credibilidade, abordando dados do Banco Mundial, OMS e ONU. Como metodologia, optou-se nesta pesquisa pela geração de regressões com uso de Inteligência Artificial via uso de Machine Learning para melhor acuracidade dos coeficientes, do R2 e da normalidade dos resíduos, possibilitando uma análise mais assertiva.
Author: Lucas Johannes Silva. Advisor: Professor Daniel Christian Henrique. Final work for the undergratuation published in the UFSC Institutional Repository. The ice cream sector in Brazil has a strong growth potential, surpassing the Gross Domestic Product (GDP) growth projections for the coming years. Given these perspectives, the present study aims to carry out the economic-financial analysis for the opening of a new unit of a consolidated ice cream shop in Brasília. Five scenarios were analyzed with applications of uncertainty analysis, considering positive, moderate and negative variations in relation to factors such as rent increase, milk cost increase, GDP growth, climate change and rent increase combined with GDP growth . Taking into account the geopolitical and economic uncertainties, as well as the low probability of acceptable return for the new business, as well as the existence of several investment options that could guarantee returns above the basic interest rate with low risk, it was decided that it would not be feasible to start the new enterprise.
Author: Bianka Pisani de Souza. Advisor: Professor Daniel Christian Henrique. Final work for the undergratuation published in the Institutional Repository of UFSC. The scenario established in mid-2019, which established a pandemic state due to COVID-19, had a strong impact on the global economy, establishing new forms of consumption and significantly changing the consumer profile. For the textile sector, such changes were strongly felt and the perceived drop in revenues during the period was evident. The present work proposes to analyze revenue projections using different demand forecasting methods for different companies in the textile sector after the pandemic easing period. Short-term projections were analyzed using Machine Learning metrics and statistics for time series, considering that the models would make the necessary weights in view of the strong changes in net revenues that the pandemic period caused in the textile sector. It was adopted as a premise that at the time of data collection, the flexibility scenario would be associated with the active presence of Covid-19.
Author: Wesley Dias Oliveira. Advisor: Professor Dr. Daniel Christian Henrique. Final work for the undergratuation published in the Institutional Repository of UFSC. Driven by the opportunities for gains from the volatility of the speculative market, many investors seek to buy shares at the low to sell at the high, hoping to make gains in the near future. Imbued with this justification, the question is necessary: Is there a possible formation of the Overconfidence effect in the period of recovery of the IBOV index after the first months of the Covid-19 pandemic? To answer this questioning, it was necessary to use the method by Statman et al (2006).
Author: Danilo Ferreira Bento. Advisor: Professor Daniel Christian Henrique. Final work for the undergratuation published in the Institutional Repository of UFSC. Undergraduate courses in Production Engineering have a high dropout rate in Brazil and, even with the vertiginous expansion of on-site and distance courses in the last three decades, this rate has remained stable. In the case of this Course Completion Work, we seek to analyze qualitatively, through a literature review, and quantitatively, through logistic and multiple linear regressions implemented in R-Studio, the variables of this census that most contribute to the number of freshmen and graduates of national courses in Production Engineering, but also to verify which ones impact on blended courses in the face-to-face modality and on the use of accessibility materials (in Libras, Braille, digital and computer resources).
Author: Felipe Medeiros de Andrade. Advisor: Professor Daniel Christian Henrique. Final work for the undergratuation published in the Institutional Repository of UFSC. It is known that the current context generated by the pandemic has brought new challenges to the market, requiring a high capacity to adapt to this new reality, either by changing its processes or by viewing new opportunities. Therefore, the objective of this work was to identify and analyze the main strategic and economic factors that will influence the success of a new company focused on remote concierge services and e-commerce....
Authors: João Carlos Prats Ramos (Pibic Scholarship Holder) and Daniel Christian Henrique. Brazil has historically always been heavily dependent on exports of its agricultural and mineral commodities. This dependence leads to a constant analysis of the relationship between the country's macroeconomic variables in order to make possible predictions regarding their impact on the finances of companies in the B3 agribusiness segments...
Author: Felipe Vieira Leandro da Silva. Advisor: Professor Daniel Christian Henrique. Final work for the undergratuation published in the Institutional Repository of UFSC. At the end of 2019, the world economy was impacted by the COVID-19 pandemic and the commerce subsector was largely impacted by the closure of several commercial points and a strong migration of consumers to e-commerce. The present work proposes to apply different predictive methodologies in the main publicly traded companies in the trade subsector using the time series of net operating revenue taking into account the impact of the pandemic. The conclusion of this quantitative study is made by comparing the accuracy between the models.
Author: Christine Silva Saurin. Advisor: Prof. Daniel Christian Henrique. Third sector institutions, popularly called NGOs (non-governmental organizations), operate in the most diverse fields of work. Many arise from the government's inability to meet all social demands, giving space to the private sector to create initiatives to address social issues that they consider important, through private institutions that do not seek profit. However, even though the number of new NGOs has grown in recent years, the mortality rate is also high, around 70% in the first year of creation, especially due to failures in planning and financial management. One solution that some NGOs found to try to minimize this problem was to offer services or open small businesses that take advantage of the knowledge and skills of their employees ....
Author: João Marcos Seraphim Mello. Advisor: Professor Daniel Christian Henrique. Final work for the undergratuation published in the Institutional Repository of UFSC. This research suggests a different way from the traditional methodologies for portfolio formulation, using the AHP method as an aid in the formation of portfolios, for investors with knowledge of fundamental analysis. After the AHP tool was developed, through applied research data were collected from different investors and efficient portfolios and borders were elaborated through Economatica ....
Author: Pedro Augusto Dalinghaus dos Santos. Advisor: Professor Daniel Christian Henrique. Final work for the undergratuation published in the Institutional Repository of UFSC. The animal care segment is standing out due to its strong growth and apparently shielding it from crises. Recently, the sector absorbed the initial impact generated by the COVID-19 crisis, showing a very solid recovery and shooting 30%. In this context, this research aims to analyze the economic and financial viability of different investments, seeking to identify the most attractive for an investor to operate in this sector. For this, four alternatives of petshops were considered in which mutually exclusive analyzes were carried out in order to define which would be the best business model: Two traditional models focused on on-site service, differentiated by the service portfolio, a mobile model that performs all home care and a last alternative that allows on-site and home care upon reservation ....
By Daniel Christian Henrique and Jucemar Paes Neto (extension scholarship PROBOLSAS). Research published at the 7th Brazilian Meeting on Behavioral Finance and Economics at FGV. This research aimed to analyze the possibility of the Overconfidence Effect occurring during the coronavirus pandemic in the North American market, in which there was a drastic drop in the S&P 500 in the first month of virus spread in the country followed by a continuous increase in the index over the next five months. For this purpose, autoregressive vector methods were applied to ascertain whether the period of increase in the index was followed by an increase in its trading volume, denoting an excess of confidence or the occurrence of loss of confidence for the initial period of falling scores, with a consequent decrease in their negotiations.