Does funding liquidity help predict U.S Dollar returns?

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Pedro Themido Pereira
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.14/29042
Resumo: Predicting the future value of an exchange rate has been a long-standing challenge in economics. There is still no evidence of any model or technique that has consistently been proven to beat the random walk model. The current objective of this thesis is to check if there is a liquidity channel tied to banking funding that allows us to explain some part of the performance of currency returns. The present analysis focuses on the paper “Risk Appetite and Exchange Rates” by Adrian et al. (2015) where it is claimed that there is a statistically significant relationship between banks’ funding capacities and changes in exchange rates. This relation seems to be more prominent for currencies of more developed countries. In my analysis, the liquidity aggregates (Commercial Paper and Repo) also display some explanatory power, though less than in Adrian et al. Importantly, however, I show that using linear time de-trending as the authors do presents stationarity problems for both liquidity aggregates, especially for Repo volume. The statistical inference of the OLS results is therefore limited. Moreover, in the fitted models, adding a dummy variable and a dummy variable with interactions with the two liquidity aggregates, as in Adrian et al. (2015), reduces the individual significance of the coefficients’ estimates for the liquidity variables. Overall, my analysis casts doubt on the results obtained in Adrian et al. (2015).
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spelling Does funding liquidity help predict U.S Dollar returns?Exchange ratesStationarityLiquidity fundingDomínio/Área Científica::Ciências Sociais::Economia e GestãoPredicting the future value of an exchange rate has been a long-standing challenge in economics. There is still no evidence of any model or technique that has consistently been proven to beat the random walk model. The current objective of this thesis is to check if there is a liquidity channel tied to banking funding that allows us to explain some part of the performance of currency returns. The present analysis focuses on the paper “Risk Appetite and Exchange Rates” by Adrian et al. (2015) where it is claimed that there is a statistically significant relationship between banks’ funding capacities and changes in exchange rates. This relation seems to be more prominent for currencies of more developed countries. In my analysis, the liquidity aggregates (Commercial Paper and Repo) also display some explanatory power, though less than in Adrian et al. Importantly, however, I show that using linear time de-trending as the authors do presents stationarity problems for both liquidity aggregates, especially for Repo volume. The statistical inference of the OLS results is therefore limited. Moreover, in the fitted models, adding a dummy variable and a dummy variable with interactions with the two liquidity aggregates, as in Adrian et al. (2015), reduces the individual significance of the coefficients’ estimates for the liquidity variables. Overall, my analysis casts doubt on the results obtained in Adrian et al. (2015).A previsão do valor futuro de uma taxa de câmbio é um desafio de há muito tempo no campo da economia. Ainda não há provas concretas de nenhum método que seja capaz de bater o random walk model, na previsão das taxas de câmbio futuras. O objectivo desta tese é analisar se existe algum liquidity channel relacionado com o mecanismo de financiamento dos bancos que ajude a explicar alguma parte da performance do retorno das moedas. A análise desta tese debruça-se sobre o paper “Risk Appetite and Exchange Rates” por Adrian et al. (2015), onde se afirma que existe uma relação estatisticamente significativa e positiva entre a capacidade de financiamento dos bancos e os retornos da moeda em que é denominado esse financiamento. Esta relação parece mais forte entre moedas de países desenvolvidos. Na minha análise, os agregados de liquidez (Papel Comercial e Repo) também revelam algum poder explicativo, ainda que este seja menor que aquele apresentado em Adrian et al. (2015). Digno de nota é que o método de de-trending (linear time de-trend), usado pelos autores, produz séries com problemas de estacionariedade, especialmente para o valor do Repo. A inferência estatística é portanto limitada. Além disso, nos modelos ajustados, usar uma dummy variable e uma dummy variable com interacções com os agregados de liquidez, como em Adrian et al. (2015), reduz a significância individual para as estimativas dos coeficientes das variáveis de liquidez. Em suma, o meu estudo levanta dúvidas sobre os resultados encontrados em Adrian et al. (2015).Albuquerque, Rui André Pinto deVeritati - Repositório Institucional da Universidade Católica PortuguesaRodrigues, Pedro Themido Pereira2019-12-23T12:47:06Z2019-05-022019-05-02T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.14/29042TID:202270769enginfo: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:RCAAP2023-07-12T17:34:34Zoai:repositorio.ucp.pt:10400.14/29042Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:23:18.638081Repositório 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 Does funding liquidity help predict U.S Dollar returns?
title Does funding liquidity help predict U.S Dollar returns?
spellingShingle Does funding liquidity help predict U.S Dollar returns?
Rodrigues, Pedro Themido Pereira
Exchange rates
Stationarity
Liquidity funding
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Does funding liquidity help predict U.S Dollar returns?
title_full Does funding liquidity help predict U.S Dollar returns?
title_fullStr Does funding liquidity help predict U.S Dollar returns?
title_full_unstemmed Does funding liquidity help predict U.S Dollar returns?
title_sort Does funding liquidity help predict U.S Dollar returns?
author Rodrigues, Pedro Themido Pereira
author_facet Rodrigues, Pedro Themido Pereira
author_role author
dc.contributor.none.fl_str_mv Albuquerque, Rui André Pinto de
Veritati - Repositório Institucional da Universidade Católica Portuguesa
dc.contributor.author.fl_str_mv Rodrigues, Pedro Themido Pereira
dc.subject.por.fl_str_mv Exchange rates
Stationarity
Liquidity funding
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Exchange rates
Stationarity
Liquidity funding
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description Predicting the future value of an exchange rate has been a long-standing challenge in economics. There is still no evidence of any model or technique that has consistently been proven to beat the random walk model. The current objective of this thesis is to check if there is a liquidity channel tied to banking funding that allows us to explain some part of the performance of currency returns. The present analysis focuses on the paper “Risk Appetite and Exchange Rates” by Adrian et al. (2015) where it is claimed that there is a statistically significant relationship between banks’ funding capacities and changes in exchange rates. This relation seems to be more prominent for currencies of more developed countries. In my analysis, the liquidity aggregates (Commercial Paper and Repo) also display some explanatory power, though less than in Adrian et al. Importantly, however, I show that using linear time de-trending as the authors do presents stationarity problems for both liquidity aggregates, especially for Repo volume. The statistical inference of the OLS results is therefore limited. Moreover, in the fitted models, adding a dummy variable and a dummy variable with interactions with the two liquidity aggregates, as in Adrian et al. (2015), reduces the individual significance of the coefficients’ estimates for the liquidity variables. Overall, my analysis casts doubt on the results obtained in Adrian et al. (2015).
publishDate 2019
dc.date.none.fl_str_mv 2019-12-23T12:47:06Z
2019-05-02
2019-05-02T00:00:00Z
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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