De Facto China Yuan Exchange Rate Regime and Fluctuation Estimation

This dissertation first adopts the exchange rate regression model for investigating the evolution of de facto CNY exchange rate regime after the China announced the currency reform. To simultaneously assess the volatility range of residuals in the regression model, that shows the deviation degree of...

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Main Author: Chen, Zili
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2014
Online Access:https://eprints.nottingham.ac.uk/27430/
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author Chen, Zili
author_facet Chen, Zili
author_sort Chen, Zili
building Nottingham Research Data Repository
collection Online Access
description This dissertation first adopts the exchange rate regression model for investigating the evolution of de facto CNY exchange rate regime after the China announced the currency reform. To simultaneously assess the volatility range of residuals in the regression model, that shows the deviation degree of the CNY fluctuation with respect to the basket currencies. Finally the dynamic VaRs of the CNY exchange rate is calculated based on the current exchange rate regime. The entire research process constitutes an inferential framework for estimating actual exchange rate regime and its risk. The main results are shown as follows. (1) In the nine years after the currency reform, the exchange rate regime of CNY was approximately pegged to USD all the time, and the CNY had slightly increased flexibility and slow appreciation during the second segment [2006-04-23, 2008-12-17] and the fourth segment [2010-06-21, 2014-08-15]. (2) Under current exchange rate regime, the 95% VaR by GARCH (1,1)-t model is the best risk estimate to describe the upper risk bound of residual series, and the 5% VaR by GARCH (1,1)-ged model the best risk estimate to describe the lower risk bound of residual series.
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spelling nottingham-274302018-01-22T22:13:36Z https://eprints.nottingham.ac.uk/27430/ De Facto China Yuan Exchange Rate Regime and Fluctuation Estimation Chen, Zili This dissertation first adopts the exchange rate regression model for investigating the evolution of de facto CNY exchange rate regime after the China announced the currency reform. To simultaneously assess the volatility range of residuals in the regression model, that shows the deviation degree of the CNY fluctuation with respect to the basket currencies. Finally the dynamic VaRs of the CNY exchange rate is calculated based on the current exchange rate regime. The entire research process constitutes an inferential framework for estimating actual exchange rate regime and its risk. The main results are shown as follows. (1) In the nine years after the currency reform, the exchange rate regime of CNY was approximately pegged to USD all the time, and the CNY had slightly increased flexibility and slow appreciation during the second segment [2006-04-23, 2008-12-17] and the fourth segment [2010-06-21, 2014-08-15]. (2) Under current exchange rate regime, the 95% VaR by GARCH (1,1)-t model is the best risk estimate to describe the upper risk bound of residual series, and the 5% VaR by GARCH (1,1)-ged model the best risk estimate to describe the lower risk bound of residual series. 2014-09-18 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/27430/1/CHEN_ZILI_dissertation.pdf Chen, Zili (2014) De Facto China Yuan Exchange Rate Regime and Fluctuation Estimation. [Dissertation (University of Nottingham only)] (Unpublished)
spellingShingle Chen, Zili
De Facto China Yuan Exchange Rate Regime and Fluctuation Estimation
title De Facto China Yuan Exchange Rate Regime and Fluctuation Estimation
title_full De Facto China Yuan Exchange Rate Regime and Fluctuation Estimation
title_fullStr De Facto China Yuan Exchange Rate Regime and Fluctuation Estimation
title_full_unstemmed De Facto China Yuan Exchange Rate Regime and Fluctuation Estimation
title_short De Facto China Yuan Exchange Rate Regime and Fluctuation Estimation
title_sort de facto china yuan exchange rate regime and fluctuation estimation
url https://eprints.nottingham.ac.uk/27430/