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On a Buffered Conditional Volatility Process

On a Buffered Conditional Volatility Process


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About the Book

This dissertation, "On a Buffered Conditional Volatility Process" by Pak-hang, Lo, 勞柏衡, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: The traditional threshold time series model is famous for its capability in capturing asymmetry. Regime switching takes place immediately when a certain variable crosses the threshold. However, this type of model may not be suitable for data which have no clear cut between regimes. A new generation of threshold type model, buffered time series model, is modified from the traditional threshold time series model. A buffer zone is introduced to replace the role of the threshold; regime switching will not take place within the buffer zone. The regime switching mechanism mimicks a climatological example and the buffered model may be suitable for data in which there is a region where the probabilistic structure of the data is insensitive to changes. Self-exciting buffered generalized autoregressive conditional heteroscedasticity (buffered GARCH) model is considered. Quasi-maximum likelihood is employed for parameter estimation. Strong consistency and asymptotic distributions are derived. Simulation experiments are carried out to verify the properties of the estimators. The buffered GARCH model is applied to two currency exchange rate data sets, US dollar to Moroccan dirham exchange rate and US dollar to Israeli new shekel exchange rate. At the same time, threshold GARCH model is also applied to the data sets in order to have comparison between the buffered GARCH model and threshold GARCH model. It is found that the buffered GARCH model beats the threshold GARCH model in terms of one information criterion, revealing that the buffered GARCH model may have advantage over the threshold GARCH model. DOI: 10.5353/th_b5177344 Subjects: Time-series analysis


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Product Details
  • ISBN-13: 9781361333303
  • Publisher: Open Dissertation Press
  • Publisher Imprint: Open Dissertation Press
  • Height: 279 mm
  • No of Pages: 118
  • Weight: 290 gr
  • ISBN-10: 1361333308
  • Publisher Date: 26 Jan 2017
  • Binding: Paperback
  • Language: English
  • Spine Width: 6 mm
  • Width: 216 mm


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