Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/20675
Title: A new hidden markov-switching volatility model.
Authors: Liu, Xin Yi.
Keywords: DRNTU::Social sciences
Issue Date: 2009
Source: Liu, X. Y. (2009). A new hidden markov-switching volatility model. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: The thesis proposes and applies a two-state hidden Markov-switching model for financial time series featured with periodic structure breaks in volatility. The expected return, volatility and state transition probability are determined by three link functions respectively, whose coefficients are further governed by the hidden state. The proposed model particularly emphasizes on the parallel structure of the two states. The parallel structure separates the INTER-state and INTRA-state dynamics, enhances greater transparency, balances the memory of both recent and distant history, provides more consistent economic implication, and greatly simplifies and stabilizes the EM algorithm. We further discuss its estimation, inference, standard errors of the parameter estimate, forecasting, model selection and implementation, especially our innovations in those issues. The Monte Carlo experiments suggest that the proposed estimation method is accurate and reliable, the choice of the initial state probability has little effect on proposed model, and the information matrix calculated numerically is stable and reliable.
URI: http://hdl.handle.net/10356/20675
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:HSS Theses

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