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Essays on the volatility of macroeconomic and financial time series
dc.contributor.author | Yu, Wei-Choun | en_US |
dc.date.accessioned | 2009-10-06T17:48:51Z | |
dc.date.available | 2009-10-06T17:48:51Z | |
dc.date.issued | 2006 | en_US |
dc.identifier.other | b57820879 | en_US |
dc.identifier.other | 123035009 | en_US |
dc.identifier.other | Thesis 56562 | en_US |
dc.identifier.uri | http://hdl.handle.net/1773/7484 | |
dc.description | Thesis (Ph. D.)--University of Washington, 2006. | en_US |
dc.description.abstract | The essays are comprised of three chapters to investigate the structural changes and reasons of Japanese postwar macroeconomic dynamic, the structural changes and nature of exchange rate realized volatility, and the relationship between macroeconomic and financial market volatility, respectively. For each chapter, we apply advanced time-series econometrics techniques, including unknown structural break tests, Markov-switching model, long memory model, and factor model using principal component method to analyze a sequence of volatility issues with emphasis on output dynamics, monetary policy and financial market variables. In the first chapter, we exam the rising volatility of Japan's real output and its relationship with monetary policy. A few lessons we learn from Japan's case could be useful for most central bankers.In the second chapter, using high-frequency data, we explore the possibilities of structural changes and regime switching in the realized volatility of the Deutschemark/Dollar, Yen/Dollar and Yen/Deutschemark spot exchange rates with their observed long-memory property. We find the substantial reduction of persistence of realized volatility after removing the breaks and the VAR-RV-Break model provides the superior predictive ability compared to most of the forecasting models. However, the VAR-RV-I(d) long memory model is still the best forecasting model even when the true financial volatility series are created by structural breaks and we have little knowledge about break dates and size. In the third chapter, we find mixed evidence on volatility destabilization for the financial market. Twelve static factors and eight dynamic factors are calculated and explored from 140 time series data set in the U.S. | en_US |
dc.format.extent | v, 122 p. | en_US |
dc.language.iso | en_US | en_US |
dc.rights | Copyright is held by the individual authors. | en_US |
dc.rights.uri | en_US | |
dc.subject.other | Theses--Economics | en_US |
dc.title | Essays on the volatility of macroeconomic and financial time series | en_US |
dc.type | Thesis | en_US |
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Economics [179]