The first essay considers a dynamic non-stationary inventory problem in which replenishment is made in fixed lot sizes (e.g., in full truckloads or full containers). We consider two separate cases: one with exogenous pricing and the other with endogenous pricing. In the first case (exogenous pricing), we show that when the ordering cost contains only a variable component, the reorder-point lot-size policy or (r, Q) policy is optimal for both single-stage and multi-echelon inventory systems. In the presence of a fixed cost, we establish the optimality of batch based (s, S ) policies for the single-stage inventory system. In the second case (endogenous pricing), we show that when the demand function has the additive form and there is only a variable ordering cost, the (r,Q) list-price policy is optimal for the single-stage system, where inventory replenishment follows an (r,Q) policy and the optimal price in each period depends on the order-up-to level. / The second essay analyzes a periodic-review, stochastic, inventory-control system in which the fixed order-cost is a step function of the order size. In particular, if the order size is within a specified limit, C, then the setup cost is K1; otherwise it is K2, where K2 ≥ K1. This cost structure is motivated from some industrial applications and transportation/production contracts used in practice. Under the condition that K1 ≤ K 2 ≤ K1, we introduce a new concept called C - (K1 ≤ K 2) convexity, which enables us to partially characterize the structure of an optimal ordering policy. For the general condition K 1 ≤ K2 , the analysis is facilitated with a different notion called strong K-convexity. Based on this analysis, we provide a partial characterization of the optimal policy and construct an easy-to-implement heuristic method that has near-optimal performance in random test instances. Our study extends or redevelops (with different techniques) several existing results in the literature. / The third essay studies a firm's periodic-review production/inventory ordering decisions when the next period's setup cost depends on the quantity produced/ ordered in the current period. In particular, if the current period's production/order quantity exceeds a specified threshold value, the system starts the next period in a "warm" state and no fixed setup cost is incurred; otherwise the state is considered "cold" and a positive setup cost is required for production/ ordering. We develop a dynamic programming formulation of the problem and provide a partial characterization of the optimal policy under the assumption that the demands follow a Polya or Uniform distribution. We use the structural results to develop fairly simple heuristic policies, which perform highly effectively in our computational experiments. / With increased globalization and competition in the current market, supply chain has become longer and more complicated than ever before. An effective and efficient supply chain is crucial and essential to a successful firm. In a supply chain, inventories are a very important component as the investment in inventories is enormous. This dissertation consists of three essays related to stochastic inventory management. / Yang, Yi. / Adviser: Youhua Chen. / Source: Dissertation Abstracts International, Volume: 73-04, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 145-151). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

by Chen Xi. / "July 2000." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (p. 107-112). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

by Li Xia. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (p. 129-134). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web.

Gao, Fei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 52-53). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Option Pricing with GARCH --- p.1 / Chapter 1.2 --- Mean Reversion in GARCH --- p.3 / Chapter 1.3 --- Thesis Setting --- p.4 / Chapter 2 --- Literature Review --- p.5 / Chapter 2.1 --- GARCH Model --- p.5 / Chapter 2.2 --- Locally Risk-Neutral Valuation --- p.8 / Chapter 2.3 --- Conditional Esscher Transform --- p.9 / Chapter 3 --- The Model --- p.12 / Chapter 3.1 --- The Mean-Reverting GARCH Model --- p.12 / Chapter 3.2 --- The Characteristic Functions --- p.15 / Chapter 3.3 --- Identification of Pricing Measures --- p.21 / Chapter 3.3.1 --- Conditional Esscher Transform --- p.21 / Chapter 3.3.2 --- Our Proposed Change of Measure --- p.25 / Chapter 4 --- Option Pricing --- p.30 / Chapter 4.1 --- Fast Fourier Transform --- p.30 / Chapter 4.2 --- Option on Futures : --- p.32 / Chapter 4.3 --- Numerical Analysis --- p.35 / Chapter 5 --- Empirical Analysis - Application to the crude oil market --- p.37 / Chapter 5.1 --- Description of data --- p.37 / Chapter 5.2 --- Estimation --- p.38 / Chapter 5.3 --- Comparisons --- p.40 / Chapter 6 --- Summary and Future work --- p.42 / Chapter 7 --- Appendix --- p.43 / Bibliography --- p.52

Zhang Li. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 67-69). / Abstracts in English and Chinese. / Chapter 1 --- Introduction and Literature Review --- p.1 / Chapter 2 --- The Tracking Portfolio Models --- p.7 / Chapter 2.1 --- Problem Formulation --- p.8 / Chapter 2.2 --- Reformulation of Tracking Models --- p.12 / Chapter 2.3 --- A Stochastic LQ Control Approach --- p.13 / Chapter 3 --- Efficient Tracking: Deterministic Market Parameters --- p.16 / Chapter 3.1 --- Solution to Model I --- p.17 / Chapter 3.2 --- A Special Case of Model I --- p.23 / Chapter 3.3 --- Solution to Model II --- p.24 / Chapter 3.4 --- A Special Case of Model II: Mean-Variance Portfolio Selection --- p.32 / Chapter 3.5 --- Solution to Model III --- p.36 / Chapter 4 --- Efficient Tracking: Markov-Modulated Market Parameters --- p.41 / Chapter 4.1 --- Problem Formulation --- p.42 / Chapter 4.2 --- Solution to Model I with Regime Switching --- p.47 / Chapter 4.3 --- Solution to Model II with Regime Switching --- p.52 / Chapter 4.4 --- Solution to Model III with Regime Switching --- p.59 / Chapter 5 --- Conclusion --- p.64 / Bibliography --- p.66

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE. / Bibliography: leaves 170-173. / by Daniel Ocone. / Ph.D.

No description available.

Zheng, Fangbing. / "September 2010." / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 32-33). / Abstracts in English and Chinese.

Cheung, Man Wah. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 50-53). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Stochastic Stability --- p.2 / Chapter 1.2 --- Some Examples --- p.3 / Chapter 1.3 --- Our Main Focus --- p.5 / Chapter 1.4 --- Thesis Outline --- p.6 / Chapter 2 --- KMR's Approach and its Variations --- p.7 / Chapter 2.1 --- KMR's Approach --- p.7 / Chapter 2.2 --- Variations --- p.12 / Chapter 2.2.1 --- Bergin and Lipman (1996) --- p.12 / Chapter 2.2.2 --- Anderlini and Ianni (1996) --- p.12 / Chapter 2.2.3 --- Robson and Vega-Redondo (1996) --- p.13 / Chapter 2.2.4 --- Robles (1998) and Pak (2008) --- p.13 / Chapter 3 --- Mathematical Reviews on Nonstationary Markov Chain --- p.15 / Chapter 3.1 --- Ergodic Coefficient --- p.15 / Chapter 3.2 --- Weak Ergodicity --- p.16 / Chapter 3.3 --- Strong Ergodicity --- p.18 / Chapter 4 --- Existing Works on Time-Dependent Mutation Rates --- p.20 / Chapter 4.1 --- Model and Definitions --- p.20 / Chapter 4.2 --- Sufficient Condition for Weak Ergodicity --- p.23 / Chapter 4.3 --- Sufficient Condition for Strong Ergodicity --- p.24 / Chapter 5 --- Time-Dependent Mutations and Empirical Distribution --- p.26 / Chapter 5.1 --- Model --- p.28 / Chapter 5.2 --- Convergence of Empirical Distribution --- p.30 / Chapter 5.3 --- Proofs of Claims --- p.35 / Chapter 5.3.1 --- Proofs of Claims l(a)-(d) --- p.36 / Chapter 5.3.2 --- Proof of Claim 2 --- p.39 / Chapter 6 --- Open Problems --- p.42 / Chapter 6.1 --- Numerical Example and Simulations --- p.43 / Chapter 6.2 --- Numerical Results --- p.44 / Chapter 6.3 --- Other Discussions --- p.47 / Chapter 7 --- Conclusion --- p.48 / Bibliography --- p.50

Lo, Yu Wai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 66-70). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Literature Review --- p.8 / Chapter 2.1 --- Mean-reverting Model --- p.8 / Chapter 2.2 --- Volatility Smile --- p.11 / Chapter 2.3 --- Stochastic Volatility Model --- p.13 / Chapter 2.4 --- Multiscale Stochastic Volatility Model --- p.15 / Chapter 3 --- The Heston Stochastic Volatility --- p.17 / Chapter 3.1 --- The Model --- p.17 / Chapter 3.1.1 --- The Characteristic Function --- p.18 / Chapter 3.2 --- European Option Pricing --- p.24 / Chapter 3.2.1 --- Plain Vanilla Options --- p.25 / Chapter 3.2.2 --- Implied Volatility --- p.28 / Chapter 3.2.3 --- Other Payoff Functions --- p.30 / Chapter 3.3 --- Trinomial Tree: Exotic Option Pricing --- p.31 / Chapter 3.3.1 --- Sub-tree for the volatility --- p.33 / Chapter 3.3.2 --- Sub-tree for the asset --- p.34 / Chapter 3.3.3 --- Non-zero Correlation --- p.37 / Chapter 3.3.4 --- Calibration to Future prices --- p.38 / Chapter 3.3.5 --- Numerical Examples --- p.39 / Chapter 4 --- Multiscale Stochastic Volatility --- p.42 / Chapter 4.1 --- Model Settings --- p.42 / Chapter 4.2 --- Pricing --- p.44 / Chapter 4.3 --- Simulation studies --- p.54 / Chapter 5 --- Conclusion --- p.59 / Appendix --- p.61 / Chapter A --- Verifications --- p.61 / Chapter A.l --- Proof of Lemma 3.1.1 --- p.61 / Chapter B --- Black-Scholes Greeks --- p.64 / Bibliography --- p.66