by Cheung Wai-Lam, William. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1992. / Includes bibliographical references (leaves 93-96). / Chapter chapter 1: --- introduction / Chapter 1.1 --- INTRODUCTION --- p.1 / Chapter 1.2 --- OBJECTIVES AND SCOPE --- p.2 / Chapter 1.3 --- STRUCTURE OF REPORT --- p.3 / Chapter 1.4 --- CHAPTER SUMMARY --- p.5 / Chapter chapter 2: --- decision support systems (dss) / Chapter 2.1 --- THE DECISION MAKING PROCESS --- p.6 / Chapter 2.2 --- DEFINITION OF DSS --- p.8 / Chapter 2.3 --- STRUCTURE OF DSS --- p.12 / Chapter 2.3.1 --- Users --- p.12 / Chapter 2.3.2 --- Database --- p.12 / Chapter 2.3.3 --- Model Base --- p.14 / Chapter 2.4 --- CHAPTER SUMMARY --- p.15 / Chapter chapter 3: --- dss for stock evaluation / Chapter 3.1 --- STOCK VALUATION: CAPM vs APT --- p.16 / Chapter 3.2 --- DSS FOR STOCK INVESTMENT --- p.21 / Chapter 3.3 --- THE PROPOSED STOCK EVALUATION DSS --- p.23 / Chapter 3.4 --- CHAPTER SUMMARY --- p.26 / Chapter chapter 4: --- analyticheerarchy process (ahp) / Chapter 4.1 --- WHAT IS AHP --- p.27 / Chapter 4.2 --- AN EXAMPLE: PLANT LOCATION SELECTION --- p.27 / Chapter 4.3 --- COMPUTATION PROCESS OF AHP / Chapter 4.3.1 --- Notations --- p.35 / Chapter 4.3.2 --- Principal Eigenvector --- p.35 / Chapter 4.3.3 --- Eigenvalue --- p.36 / Chapter 4.3.4 --- Consistency Ratio --- p.36 / Chapter 4.4 --- CHAPTER SUMMARY --- p.37 / Chapter chapter 5: --- an ahp model for stock evaluation / Chapter 5.1 --- ALTERNATIVES FOR STOCK EVALUATION --- p.39 / Chapter 5.2 --- THE AHP MODEL FOR STOCK SELECTION --- p.41 / Chapter 5.3 --- EXPLANATIONS AND JUSTIFICATIONS FOR PROPOSED HIERARCHY --- p.43 / Chapter 5.3.1 --- Level1 --- p.45 / Chapter 5.3.2 --- Level2 --- p.45 / Chapter 5.3.3 --- Level3 --- p.46 / Chapter 5.3.4 --- Level4 --- p.48 / Chapter 5.3.5 --- Level5 --- p.49 / Chapter 5.3.6 --- Level6 --- p.60 / Chapter 5.4 --- CHAPTER SUMMARY --- p.61 / Chapter chapter 6: --- the development of iris: a prototype / Chapter 6.1 --- SYSTEM FLOWCHART --- p.63 / Chapter 6.2 --- PROGRAM SPECIFICATION --- p.65 / Chapter 6.2.1 --- File Maintenance Module --- p.65 / Chapter 6.2.2 --- Hierarchy Setup --- p.65 / Chapter 6.2.3 --- Eigenvector Computation --- p.67 / Chapter 6.2.4 --- Overall Weight Computation --- p.67 / Chapter 6.3 --- PROTOTYPE OPERATION --- p.67 / Chapter 6.4 --- CHAPTER SUMMARY --- p.79 / Chapter chapter 7: --- user evaluationof model and prototype / Chapter 7.1 --- METHODOLOGY OF EVALUATION --- p.82 / Chapter 7.1.1 --- Participants --- p.82 / Chapter 7.1.2 --- Stock Candidates --- p.83 / Chapter 7.1.3 --- Stock Data --- p.83 / Chapter 7.1.4 --- Process of Model and Prototype Evaluation --- p.84 / Chapter 7.2 --- FINDINGS --- p.85 / Chapter 7.2.1 --- Structure the Stock Evaluation Process --- p.86 / Chapter 7.2.2 --- Time-consuming --- p.87 / Chapter 7.2.3 --- The Consistency Ratio --- p.87 / Chapter 7.2.4 --- Reconsideration of Factors --- p.87 / Chapter 7.2.5 --- Precise Amount Available --- p.88 / Chapter 7.2.6 --- Users Forced to Considered All Factors --- p.88 / Chapter 7.3 --- CONCLUSION OF EVALUATION --- p.89 / Chapter 7.4 --- CHAPTER SUMMARY --- p.90 / Chapter chapter 8: --- summary and conclusion / Chapter 8.1 --- REPORT SUMMARY --- p.91 / Chapter 8.2 --- CONCLUSION --- p.91 / references --- p.93 / appendix --- p.97

The understanding of the emergent behaviour of complex systems is probably one of the most intriguing challenges in modern theoretical physics. In the present Thesis we use novel data analysis techniques and numerical simulations in order to shed some light on the fundamental mechanisms involved in their dynamics. We divide the main core of the research into three parts, each of which address a specific, and formally well defined, issue. In the first part, we study the processes of self - organization and herding in the evolution of the stock market. The data analysis, carried out over the fluctuations of several international indices, shows an avalanche - like dynamics characterized by power laws and indicative of a critical state. Further evidence of criticality relates to the behaviour of the price index itself. In this case we observe a power law decline with superimposed embedded log - periodic oscillations which are possibly due to an intrinsic discrete scale invariance. A stochastic cellular automata, instead, is used to mimic an open stock market and reproduce the herding behaviour responsible for the large fluctuations observed in the price. The results underline the importance of the largest clusters of traders which, alone, can induce a large displacement between demand and supply and lead to a crash. The second part of the Thesis focuses on the role played by the complex network of interactions that is created among the elementary parts of the system itself. We consider, in particular, the influence of the so - called " scale - free " networks, where the distribution of connectivity follows a power law, on the antiferromagnetic Ising model and on a model of stochastic opinion formation. Novel features, not encountered on regular lattices, have been pointed out. In the former case a spin glass transition at low temperatures is present while, in the latter, the turbulent - like behaviour emerging from the model is found to be particularly robust against the indecision of the agents. The last part is left for a numerical investigation of an extremal dynamical model for evolution / extinction of species. We demonstrate how the mutual cooperation between them comes to play a fundamental role in the survival probability : a healthy environment can support even less fitted species. / Thesis (Ph.D.)--School of Chemistry and Physics, 2006.

University of Macau / Faculty of Science and Technology / Department of Computer and Information Science

The understanding of the emergent behaviour of complex systems is probably one of the most intriguing challenges in modern theoretical physics. In the present Thesis we use novel data analysis techniques and numerical simulations in order to shed some light on the fundamental mechanisms involved in their dynamics. We divide the main core of the research into three parts, each of which address a specific, and formally well defined, issue. In the first part, we study the processes of self - organization and herding in the evolution of the stock market. The data analysis, carried out over the fluctuations of several international indices, shows an avalanche - like dynamics characterized by power laws and indicative of a critical state. Further evidence of criticality relates to the behaviour of the price index itself. In this case we observe a power law decline with superimposed embedded log - periodic oscillations which are possibly due to an intrinsic discrete scale invariance. A stochastic cellular automata, instead, is used to mimic an open stock market and reproduce the herding behaviour responsible for the large fluctuations observed in the price. The results underline the importance of the largest clusters of traders which, alone, can induce a large displacement between demand and supply and lead to a crash. The second part of the Thesis focuses on the role played by the complex network of interactions that is created among the elementary parts of the system itself. We consider, in particular, the influence of the so - called " scale - free " networks, where the distribution of connectivity follows a power law, on the antiferromagnetic Ising model and on a model of stochastic opinion formation. Novel features, not encountered on regular lattices, have been pointed out. In the former case a spin glass transition at low temperatures is present while, in the latter, the turbulent - like behaviour emerging from the model is found to be particularly robust against the indecision of the agents. The last part is left for a numerical investigation of an extremal dynamical model for evolution / extinction of species. We demonstrate how the mutual cooperation between them comes to play a fundamental role in the survival probability : a healthy environment can support even less fitted species. / Thesis (Ph.D.)--School of Chemistry and Physics, 2006.

The results from 17 new experiments and 19 previously reported experiments are compared in an investigation of call and continuous auctions. The call auction used is the computerized PLATO sealed bid/offer (SBO), uniform price auction. The continuous auction used is the PLATO double auction (DA), a computerized version of the "open outcry" double auction. The SBO call auction has temporal consolidation of market orders and has limited information about trading activity. The continuous DA auction is characterized by sequential bilateral trades, and trading information (bids, offers, and prices) is publicly displayed. The paper first explores the effect of multiple crossings per trading period in the SBO call auction. Next, a comparison of SBO and DA is made, based on market experiments using flow supply and demand schedules. The institutional comparison is then extended to experimental asset markets. The results imply the following. First, multiple calls per period increase the efficiency of the SBO call auction, relative to one call per period, but they also induce greater misrepresentation of costs and values in the first crossing each period. Buyers and sellers also withhold units from the first crossing in a further attempt to gain strategic advantage. However, neither the withholding nor the misrepresentation appears to have any substantial influence on price. Second, the SBO auction with two calls per period is as efficient as the DA auction. In markets with a random competitive equilibrium (CE) each period, the SBO auction does a better job than DA at tracking the random CE price. Thus the SBO auction is equally as efficient as the DA, and has the further attributes of lower price volatility and greater privacy. Third, in laboratory asset markets, the SBO auction exhibits price bubbles similar to those observed in DA markets. Price dynamics in the two institutions are comparable, despite the stark differences in order flow and information dissemination.