Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 63-64). Also available in electronic version. Access restricted to campus users.

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 37-39). Also available in electronic version. Access restricted to campus users.

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 76-80).

In financial markets, transaction durations refer to the duration time between two consecutive trades. It is common that more frequent trades are expected to be followed by shorter durations between consecutive transactions, while less frequent trades are expected to be followed by longer durations. Autoregressive conditional duration (ACD) model was developed to model transaction durations, based on the assumption that the expected average duration is dependent on the past durations. Empirically, transaction durations possess much longer memory than expected. The autocorrelation functions of durations decay slowly and are still significant after a large number of lags. Therefore, the fractionally integrated autoregressive conditional duration (FIACD) model was proposed to model this kind of long memory behavior. The ACD model possesses short memory as the dependence of the past durations will die out exponentially. The FIACD model possesses much longer memory as the dependence of the past durations will decay hyperbolically. However, the modeling result would be misleading if the actual dependence of the past durations decays between exponential rate and hyperbolic rate. Neither of these models can truly reveal the memory properties in this case. This thesis proposes a new duration model, named as the hyperbolic autoregressive conditional duration (HYACD) model, which combines the ACD model and the FIACD model into one. It possesses both short memory and long memory properties and allows the dependence of the past durations to decay between the exponential rate and the hyperbolic rate. It also indicates whether the dependence is close to short memory or long memory. The model is applied to the transaction data of AT&T and McDonald stocks traded on NYSE and statistically positive results are obtained when it is compared to the ACD model and the FIACD model. / published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

published_or_final_version / Statistics / Master / Master of Philosophy

Thesis (M. Phil.)--University of Hong Kong, 1994. / Includes bibliographical references (108-113).

published_or_final_version / Statistics / Doctoral / Doctor of Philosophy

Zhang Yuanxiu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 38-39). / Abstracts in English and Chinese.

Au Tsz-yin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 76-79). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Forecasting Time Series --- p.1 / Chapter 1.2 --- Importance of Multiple Forecasts --- p.2 / Chapter 1.3 --- Methodology of Forecasting for Autoregressive Models --- p.3 / Chapter 1.4 --- Bootstrap Approach --- p.9 / Chapter 1.5 --- Objectives --- p.12 / Chapter 2 --- "Bootstrapping Simultaneous Prediction Intervals, Case A: p known" --- p.15 / Chapter 2.1 --- TS Procedure --- p.16 / Chapter 2.2 --- CAO Procedure --- p.18 / Chapter 2.3 --- MAS Procedure --- p.20 / Chapter 3 --- "Bootstrapping Simultaneous Prediction Intervals, Case B: p unknown" --- p.24 / Chapter 3.1 --- TS Procedure --- p.25 / Chapter 3.2 --- CAO Procedure --- p.27 / Chapter 3.3 --- MAS Procedure --- p.28 / Chapter 4 --- Simulation Study --- p.29 / Chapter 4.1 --- Design of The Experiment --- p.29 / Chapter 4.2 --- Simulation Results --- p.33 / Chapter 5 --- A Real-Data Case --- p.36 / Chapter 5.1 --- Case A --- p.37 / Chapter 5.2 --- Case B --- p.42 / Chapter 6 --- Conclusion --- p.46 / Chapter A --- Tables of Simulation Results for Case A --- p.49 / Chapter B --- Tables of Simulation Results for Case B --- p.62 / Chapter C --- References --- p.76

Kong, Cheuk Kwan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 42-44). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Modelling Piecewise AR model --- p.4 / Chapter 2.1 --- Background --- p.4 / Chapter 2.2 --- Introduction to Auto-FARM --- p.5 / Chapter 2.3 --- Minimum Description Length --- p.6 / Chapter 2.4 --- Genetic Algorithm --- p.9 / Chapter 2.5 --- Reproduction Rules --- p.10 / Chapter 3 --- Bayesian-SCAD Approach --- p.14 / Chapter 3.1 --- Estimation via Penalty Function --- p.15 / Chapter 3.2 --- Introduction to SCAD --- p.17 / Chapter 3.3 --- Local Quadratic Approximation of SCAD --- p.20 / Chapter 3.4 --- Bayesian Formulation and GA Implementation --- p.22 / Chapter 4 --- Simulation Study --- p.25 / Chapter 4.1 --- Piecewise AR Process from Davis et al. (2006) --- p.25 / Chapter 4.2 --- Piecewise Seasonal AR Process --- p.29 / Chapter 5 --- Real Data Analysis --- p.33 / Chapter 5.1 --- Description and Source of Data --- p.33 / Chapter 5.2 --- Model Fitting --- p.36 / Chapter 5.3 --- Prediction Results --- p.39 / Chapter 6 --- Conclusion --- p.40 / Bibliography --- p.42