Essays on Financial Economics and Macroeconomics

dc.contributor.advisorTsiakas, Ilias
dc.contributor.authorZhang, Haibin
dc.date.accessioned2019-04-25T19:43:42Z
dc.date.available2019-04-25T19:43:42Z
dc.date.copyright2019-04
dc.date.created2019-04-17
dc.date.issued2019-04-25
dc.degree.departmentDepartment of Economics and Financeen_US
dc.degree.grantorUniversity of Guelphen_US
dc.degree.nameDoctor of Philosophyen_US
dc.degree.programmeEconomicsen_US
dc.description.abstractThis thesis, entitled Essays on Financial Economics and Macroeconomics, studies the interactions between real macroeconomics and financial variables. There is an emerging literature aims to investigate how can we reduce the impacts from the financial crisis by considering both macroeconomics and finance conditions together. For example, decision-makers should consider the financial market conditions first before policies are made. Meanwhile, the forecasting of short term financial variables' returns should take long term macroeconomic conditions into consideration. This has motivated us to explore further in the relationship between the macroeconomic factors and financial market conditions. In the first chapter, we examine the short-run and long-run dynamics of the correlation between exchange rate and commodity returns, and assess the extent to which the long-run correlation is determined by economic fundamentals. Our empirical analysis is based on the dynamic conditional correlation model with mixed data sampling (DCC-MIDAS) of Colacito, Engle and Ghysels (2011). This model provides a framework that captures the high-frequency relation between exchange rate and commodity returns as well as the low-frequency relation of volatility and correlation to economic fundamentals. Using both economic and statistical criteria, we find that the DCC-MIDAS\ model augmented with economic fundamentals performs better than competing models in sample and out of sample. In the second chapter, we investigate the direction of Granger causality between business and financial cycles. Our analysis is based on a vector autoregression model applied on mixed frequency data. This allows us to condition on data from higher frequency variables (such as monthly industrial production) and lower frequency variables (such as quarterly aggregate credit) in a way that avoids the effects on data aggregation. Our empirical investigation focuses on five industrialized countries: USA, Canada, UK, Germany and Japan. Firstly, we examine whether the monthly industrial production index causes quarterly aggregate credit or vice versa. Then, we determine the timing of when causality is statistically significant. We find that there is strong bidirectional causality between business and financial cycles. The timing of causality varies across countries, but for all countries, bidirectional causality is significant during the financial crisis. The third and final chapter, which is an extension of the second chapter, investigates the role of the US as a global leader. Specifically, by paring US with other country (i.e, Canada, UK, Germany and Japan), we examine whether the US industrial production or credit causes the industrial production or credit of the other countries. In addition, we investigate whether causality is affected by the nominal interest rate. Our main finding is that the US business cycle strongly causes the business cycles of Canada, the UK and Germany. Finally, there is strong evidence that causality tends to be significant when the US interest rate is higher.en_US
dc.identifier.urihttp://hdl.handle.net/10214/15911
dc.language.isoenen_US
dc.publisherUniversity of Guelphen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBusiness Cycleen_US
dc.subjectFinancial Cycleen_US
dc.subjectGranger Causalityen_US
dc.subjectExchange Rateen_US
dc.subjectCommoditiesen_US
dc.subjectDCC-MIDAS Modelen_US
dc.subjectMF-VAR Modelen_US
dc.subjectEconomic Fundamentalsen_US
dc.titleEssays on Financial Economics and Macroeconomicsen_US
dc.typeThesisen_US
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