Fintech vs. traditional financial services: how are investors reacting?

Detalhes bibliográficos
Autor(a) principal: Zhou Wenyi
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/23911
Resumo: Financial technology (fintech) has experienced dramatic growth in the 21st century while the traditional finance sector is facing challenges of innovative and convenient services brought by financial technology in the U.S after the 2008 crisis. This dissertation intends to study whether investors view U.S fintech differently from traditional finance under the influence of macroeconomic variables (total non-farm payroll, S&P500 index, the spread of 10-year and 2-year Government Bonds, and 3-month LIBOR). We establish multiple linear regression models for U.S fintech (the KFTX index as a representative) and traditional finance (represented by the S&P 500 Financials Services Select Sector Index) respectively to investigate the relationship between the above four macroeconomic variables from 2016 to 2020 and then obtain their comparative model by the difference between their log returns in empirical analysis. We observe that total non-farm payroll, and S&P 500 index are both statistically relevant in explaining the variations of the S&P 500 Financials Services Select Sector Index and the KFTX index while the S&P 500 Financials Services Select Sector Index is also influenced by the positive and statistically significant effects of 3-month LIBOR and the spread of 10-year and 2-year Government Bonds. In addition, we figure out that when 3-month LIBOR or 10-year and 2-year Government Bonds spread rises, investors are inclined to buy more traditional financial stock represented by the S&P 500 Financials Services Select Sector Index than the fintech assets represented by the KFTX index.
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spelling Fintech vs. traditional financial services: how are investors reacting?FintechTraditional financeMacroeconomic variablesMultiple linear regression methodFinanças tradicionaisVariáveis macroeconômicasMétodo de regressão linear múltiplaFinancial technology (fintech) has experienced dramatic growth in the 21st century while the traditional finance sector is facing challenges of innovative and convenient services brought by financial technology in the U.S after the 2008 crisis. This dissertation intends to study whether investors view U.S fintech differently from traditional finance under the influence of macroeconomic variables (total non-farm payroll, S&P500 index, the spread of 10-year and 2-year Government Bonds, and 3-month LIBOR). We establish multiple linear regression models for U.S fintech (the KFTX index as a representative) and traditional finance (represented by the S&P 500 Financials Services Select Sector Index) respectively to investigate the relationship between the above four macroeconomic variables from 2016 to 2020 and then obtain their comparative model by the difference between their log returns in empirical analysis. We observe that total non-farm payroll, and S&P 500 index are both statistically relevant in explaining the variations of the S&P 500 Financials Services Select Sector Index and the KFTX index while the S&P 500 Financials Services Select Sector Index is also influenced by the positive and statistically significant effects of 3-month LIBOR and the spread of 10-year and 2-year Government Bonds. In addition, we figure out that when 3-month LIBOR or 10-year and 2-year Government Bonds spread rises, investors are inclined to buy more traditional financial stock represented by the S&P 500 Financials Services Select Sector Index than the fintech assets represented by the KFTX index.A tecnologia financeira (fintech) experimentou um crescimento dramático no século 21, enquanto o setor financeiro tradicional está enfrentando desafios de serviços inovadores e convenientes trazidos pela tecnologia financeira nos EUA após a crise de 2008. Esta dissertação pretende estudar se os investidores veem a fintech dos EUA de forma diferente das finanças tradicionais sob a influência de variáveis macroeconômicas (folha de pagamento não agrícola total, índice S & P500, spread de títulos do governo de 10 e 2 anos e LIBOR de 3 meses). Estabelecemos vários modelos de regressão linear para fintech dos EUA (o índice KFTX como representante) e finanças tradicionais (representado pelo índice S&P 500 Financials Services Select Sector), respectivamente, para investigar a relação entre as quatro variáveis macroeconômicas acima de 2016 a 2020 e, em seguida, obter seu modelo comparativo pela diferença entre seus retornos de log na análise empírica. Observamos que o total da folha de pagamento não agrícola e o índice S&P 500 são estatisticamente relevantes para explicar as variações do S&P 500 Financials Services Select Sector Index e do índice KFTX, enquanto o S&P 500 Financials Services Select Sector Index também é influenciado pelo índice positivo e efeitos estatisticamente significativos da LIBOR de 3 meses e do spread dos títulos do governo de 10 e 2 anos. Além disso, descobrimos que quando o spread da LIBOR de 3 meses ou dos títulos do governo de 10 e 2 anos aumenta, os investidores tendem a comprar mais ações financeiras tradicionais representadas pelo S&P 500 Financials Services Select Sector Index do que os ativos fintech representados por o índice KFTX.2022-01-04T16:31:32Z2021-12-15T00:00:00Z2021-12-152021-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/23911TID:202829103engZhou Wenyiinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:38:41Zoai:repositorio.iscte-iul.pt:10071/23911Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:17:44.409101Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Fintech vs. traditional financial services: how are investors reacting?
title Fintech vs. traditional financial services: how are investors reacting?
spellingShingle Fintech vs. traditional financial services: how are investors reacting?
Zhou Wenyi
Fintech
Traditional finance
Macroeconomic variables
Multiple linear regression method
Finanças tradicionais
Variáveis macroeconômicas
Método de regressão linear múltipla
title_short Fintech vs. traditional financial services: how are investors reacting?
title_full Fintech vs. traditional financial services: how are investors reacting?
title_fullStr Fintech vs. traditional financial services: how are investors reacting?
title_full_unstemmed Fintech vs. traditional financial services: how are investors reacting?
title_sort Fintech vs. traditional financial services: how are investors reacting?
author Zhou Wenyi
author_facet Zhou Wenyi
author_role author
dc.contributor.author.fl_str_mv Zhou Wenyi
dc.subject.por.fl_str_mv Fintech
Traditional finance
Macroeconomic variables
Multiple linear regression method
Finanças tradicionais
Variáveis macroeconômicas
Método de regressão linear múltipla
topic Fintech
Traditional finance
Macroeconomic variables
Multiple linear regression method
Finanças tradicionais
Variáveis macroeconômicas
Método de regressão linear múltipla
description Financial technology (fintech) has experienced dramatic growth in the 21st century while the traditional finance sector is facing challenges of innovative and convenient services brought by financial technology in the U.S after the 2008 crisis. This dissertation intends to study whether investors view U.S fintech differently from traditional finance under the influence of macroeconomic variables (total non-farm payroll, S&P500 index, the spread of 10-year and 2-year Government Bonds, and 3-month LIBOR). We establish multiple linear regression models for U.S fintech (the KFTX index as a representative) and traditional finance (represented by the S&P 500 Financials Services Select Sector Index) respectively to investigate the relationship between the above four macroeconomic variables from 2016 to 2020 and then obtain their comparative model by the difference between their log returns in empirical analysis. We observe that total non-farm payroll, and S&P 500 index are both statistically relevant in explaining the variations of the S&P 500 Financials Services Select Sector Index and the KFTX index while the S&P 500 Financials Services Select Sector Index is also influenced by the positive and statistically significant effects of 3-month LIBOR and the spread of 10-year and 2-year Government Bonds. In addition, we figure out that when 3-month LIBOR or 10-year and 2-year Government Bonds spread rises, investors are inclined to buy more traditional financial stock represented by the S&P 500 Financials Services Select Sector Index than the fintech assets represented by the KFTX index.
publishDate 2021
dc.date.none.fl_str_mv 2021-12-15T00:00:00Z
2021-12-15
2021-10
2022-01-04T16:31:32Z
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