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Yang, Nian., Thesis (Ph.D.)--Chinese University of Hong Kong, 2013., Includes bibliographical references (leaves 95-100)., Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web., also in Chinese., http://library.cuhk.edu.hk/record=b5884377, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Ding, Yue., Thesis (Ph.D.)--Chinese University of Hong Kong, 2013., Includes bibliographical references., Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web., s also in Chinese., http://library.cuhk.edu.hk/record=b5884530, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Summary: The main objective of this thesis is to simulate, evaluate and discuss three standard methodologies of calculating Value-at-Risk (VaR) : Historical simulation, the Variance-covariance method and Monte Carlo simulations. Historical simulation is the most common nonparametric method. The Variance-covariance and Monte Carlo simulations are widely used parametric methods. This thesis defines the three aforementioned VaR methodologies, and uses each to calculate 1-day VaR for a hypothetical portfolio through MATLAB simulations. The evaluation of the results shows that historical simulation yields the most reliable 1-day VaR for the hypothetical portfolio under extreme market conditions. Finally, this paper concludes with a suggestion for further studies : a heavy-tail distribution should be used in order to imporve the accuracy of the results for the two parametric methods used in this study., by Kyong Chung., Thesis (M.S.)--Florida Atlantic University, 2012., Includes bibliography., Mode of access: World Wide Web., System requirements: Adobe Reader.

About the intraday volatility modeling, the limitations and potential problems of using Andersen & Bollerslev's approach are addressed and distinct modifications are proposed to tackle the corresponding issues. The first suggestion is about the utilization of the interaction between the intraday periodicity and the heteroskedasticity while the second is about the modified normalization for the estimation of the intraday periodicity., Furthermore, it is demonstrated that the inclusion of overnight variance can improve the prediction accuracy of the Chicago Board of options Exchange (CBOE) volatility indexes (VIX and VXD) under specific weight combinations. The findings contradict the common perception that overnight return does not contain useful information for daily volatility modeling., On the other hand, the third suggestion is about the inclusion of overnight information for the estimation of daily volatility. This study explores the possibility of incorporating the overnight variance indirectly through the use of linearly combined daily volatility estimators. The empirical results demonstrate that the inclusion of overnight variance can produce substantial influence when the minimum-variance constraints are relaxed. Besides, the influence is revealed to be not monotonic as an increase of the overnight proportion does not necessarily produce a larger influence., The proposed modifications are tested with different ARCH structures, including GARCH(1,1), FIGARCH(1,d,1) and HYGARCH(1,d,1), by using simulated data and market data. Apart from studying the 1-step-ahead out-of-sample performance, several multiple-step-ahead forecasting results are also addressed. Under the same level of model flexibility (parameterized portions), our proposed modifications always outperform the original method in both in-sample fitness and out-of-sample performance on various forecasting horizons., This research study investigates three new considerations for improving the performance of volatility modeling of financial returns. Two of them are related to the intraday volatility modeling and the other one is about the use of overnight information for daily volatility modeling., Chu, Chun Fai Carlin., Adviser: Kai Pui Lam., Source: Dissertation Abstracts International, Volume: 73-04, Section: A, page: ., Thesis (Ph.D.)--Chinese University of Hong Kong, 2011., Includes bibliographical references (leaves 180-186)., 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., also in Chinese., isbn: 9781267099303, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

General diffusion processes (GDP), or Ito's processes, are potential candidates for the modeling of asset prices, interest rates and other financial quantities to cope with empirical evidence. This thesis considers the applications of general diffusions in finance and potential extensions. In particular, we focus on financial problems involving (optimal) stopping times. A typical example is the valuation of American options. We investigate the use of Laplace-Carson transform (LCT) in valuing American options, and discuss its strengthen and weaknesses. Homotopy analysis from topology is then introduced to derive closed-form American option pricing formulas under GDP. Another example is taken from optimal dividend policies with bankruptcy procedures, which is closely related to excursion time and occupation time of a general diffusion. With the aid of Fourier transform, we further extend the analysis to the case of multi-dimensional GDP by considering the currency option pricing with mean reversion and multi-scale stochastic volatility., Zhao, Jing., Adviser: Hoi-Ying Wong., Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: ., Thesis (Ph.D.)--Chinese University of Hong Kong, 2010., Includes bibliographical references (leaves 97-105)., 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 Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web., also in Chinese., isbn: 9781124494357, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Chu, Ho., "December 2009.", Thesis (M.Phil.)--Chinese University of Hong Kong, 2010., Includes bibliographical references (p. 99-111)., s in English and Chinese., p.i, Acknowledgement --- p.iv, Chapter 1 --- Introduction --- p.1, Chapter 1.1 --- Overview of Mutual Fund Investment --- p.1, Chapter 1.2 --- Research Motivation --- p.4, Chapter 1.3 --- List of Contributions --- p.9, Chapter 1.4 --- Thesis Structure --- p.12, Chapter 2 --- Literature Review --- p.14, Chapter 2.1 --- Traditional Measurement Approaches --- p.14, Chapter 2.1.1 --- Jensen's Alpha --- p.16, Chapter 2.1.2 --- Treynor Index --- p.19, Chapter 2.1.3 --- Sharpe Ratio --- p.21, Chapter 2.1.4 --- Other Measures --- p.23, Chapter 2.1.4.1 --- M2 Measure --- p.23, Chapter 2.1.4.2 --- Multifactor Models --- p.25, Chapter 2.1.4.3 --- Morningstar's RAR --- p.27, Chapter 2.1.5 --- Shortcomings of Traditional Measures --- p.30, Chapter 2.2 --- Data Envelopment Analysis --- p.33, Chapter 2.2.1 --- Brief Introduction --- p.33, Chapter 2.2.2 --- Research Review on Fund Performance Mea-surement --- p.37, Chapter 2.2.3 --- Limitations of Basic DEA Models --- p.42, Chapter 3 --- DEA Methodology and Formulation --- p.47, Chapter 3.1 --- CCR and BCC Model --- p.48, Chapter 3.2 --- Problem of Slacks and DEA efficiency --- p.52, Chapter 3.3 --- Slacks-based Measure --- p.55, Chapter 3.4 --- Variables with Negative Values --- p.57, Chapter 3.5 --- Range Directional Measure --- p.59, Chapter 3.6 --- Modified Slacks-Based Measure --- p.62, Chapter 4 --- Empirical Study and Discussions --- p.65, Chapter 4.1 --- Data Source and Tools for Measurement --- p.65, Chapter 4.2 --- Model Variables Defined --- p.67, Chapter 4.3 --- Comparison of MSBM Performance Measure to Other Measures --- p.73, Chapter 4.4 --- Comparison of Hong Kong MPFs with Different Categories --- p.78, Chapter 5 --- Conclusions and Future Work --- p.90, Bibliography --- p.99, http://library.cuhk.edu.hk/record=b5894261, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Chung, Tsz Kin = 均值回復正態過程的雙撞擊時間分佈以及其在金融上的應用 / 鍾子健., Thesis submitted in: December 2008., Thesis (M.Phil.)--Chinese University of Hong Kong, 2009., Includes bibliographical references (leaves 101-105)., s in English and Chinese., Chung, Tsz Kin = Jun zhi hui fu zheng tai guo cheng de shuang zhuang ji shi jian fen bu yi ji qi zai jin rong shang de ying yong / Zhong Zijian., Chapter 1 --- Introduction --- p.1, Chapter 1.1 --- Overview --- p.1, Chapter 1.2 --- Mean-reverting lognormal (MRL) process --- p.3, Chapter 1.3 --- MRL-process and AR(l)-process --- p.5, Chapter 2 --- Double Hitting Time Distribution of a Mean-Reverting Log-normal Process --- p.8, Chapter 2.1 --- Introduction --- p.8, Chapter 2.2 --- Probability density function --- p.9, Chapter 2.3 --- Interpolation scheme - estimates and bounds --- p.12, Chapter 2.4 --- Multi-stage approximation scheme --- p.17, Chapter 2.5 --- Hitting time distribution and density --- p.19, Chapter 2.6 --- Numerical analysis --- p.20, Chapter 2.7 --- Appendix --- p.24, Chapter 2.7.1 --- Solving the Fokker-Planck equation --- p.24, Chapter 2.7.2 --- Probability density function associated with two piecewise-continuous boundaries --- p.27, Chapter 3 --- Pricing Exotic Options with Mean Reversion --- p.29, Chapter 3.1 --- Introduction --- p.29, Chapter 3.2 --- Barrier options --- p.30, Chapter 3.2.1 --- Double barrier options --- p.32, Chapter 3.2.2 --- Rebates --- p.33, Chapter 3.2.3 --- Numerical examples --- p.34, Chapter 3.3 --- Lookback options --- p.36, Chapter 3.3.1 --- Expected minimum and maximum --- p.37, Chapter 3.3.2 --- Standard lookback options --- p.41, Chapter 3.3.3 --- Fixed strike lookback options --- p.42, Chapter 3.3.4 --- Lookback spread option --- p.43, Chapter 3.3.5 --- Numerical examples --- p.43, Chapter 3.4 --- Sensitivity analysis --- p.46, Chapter 3.4.1 --- Analysis ´ؤ double knock-out call option --- p.47, Chapter 3.4.2 --- Analysis ´ؤ floating strike lookback put option --- p.52, Chapter 3.4.3 --- Analysis ´ؤ lookback spread option --- p.56, Chapter 3.4.4 --- Summary --- p.60, Chapter 3.5 --- Appendix --- p.61, Chapter 3.5.1 --- Closed-form price formula of the double knock-out call option --- p.61, Chapter 3.5.2 --- Derivations of lookback options --- p.63, Chapter 4 --- Using First-Passage-Time Density to Assess Realignment Risk of a Target Zone --- p.66, Chapter 4.1 --- Realignment risk of a target zone --- p.66, Chapter 4.1.1 --- Currency option market and target zone --- p.66, Chapter 4.1.2 --- First-Passage-Time approach --- p.67, Chapter 4.1.3 --- Option price and implied volatility --- p.69, Chapter 4.1.4 --- FPT density and realignment risk --- p.73, Chapter 4.2 --- The ERM crisis of 1992 --- p.74, Chapter 4.2.1 --- British pound (GBP) target zone --- p.74, Chapter 4.2.2 --- Italian lira (ITL) target zone --- p.81, Chapter 4.2.3 --- Summary --- p.85, Chapter 5 --- Market Expectation of Appreciation of the Renminbi --- p.87, Chapter 5.1 --- The Chinese Renminbi exchange rate system --- p.87, Chapter 5.2 --- First-Passage-Time approach --- p.90, Chapter 5.3 --- Estimations of expected maximum appreciation of Renminbi --- p.92, Chapter 5.4 --- Appendix --- p.99, Chapter 5.4.1 --- Derivations of the expected minimum and maximum --- p.99, Bibliography --- p.101, http://library.cuhk.edu.hk/record=b5896878, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Summary: Fads models for stocks under asymmetric information in a purely continuous(GBM) market were first studied by P. Guasoni (2006), where optimal portfolios and maximum expected logarithmic utilities, including asymptotic utilities for the informed and uninformed investors, were presented. We generalized this theory to Lâevy markets, where stock prices and the process modeling the fads are allowed to include a jump component, in addition to the usual continuous component. We employ the methods of stochastic calculus and optimization to obtain analogous results to those obtained in the purely continuous market. We approximate optimal portfolios and utilities using the instantaneous centralized and quasi-centralized moments of the stocks percentage returns. We also link the random portfolios of the investors, under asymmetric information to the purely deterministic optimal portfolio, under symmetric information., by Winston S. Buckley., Thesis (Ph.D.)--Florida Atlantic University, 2009., Bibliography: leaves 268-272.

Zhou, Tu., Thesis (M.Phil.)--Chinese University of Hong Kong, 2008., Includes bibliographical references (leaves 61-70)., s in English and Chinese., Chapter 1 --- Introduction --- p.0, Chapter 1.1 --- Motivation and Objective --- p.0, Chapter 1.2 --- Major Contribution --- p.2, Chapter 1.3 --- Thesis Organization --- p.4, Chapter 2 --- Measurement of Relationship between financial time series --- p.5, Chapter ´ب2.1 --- Linear Correlation --- p.5, Chapter 2.1.1 --- Pearson Correlation Coefficient --- p.6, Chapter 2.1.2 --- Rank Correlation --- p.6, Chapter 2.2 --- Mutual Information --- p.7, Chapter 2.2.1 --- Approaches of Mutual Information Estimation --- p.10, Chapter 2.3 --- Copula --- p.12, Chapter 2.4 --- Analysis from Experimental Data --- p.14, Chapter 2.4.1 --- Experiment 1: Nonlinearity --- p.14, Chapter 2.4.2 --- Experiment 2: Sensitivity of Outliers --- p.16, Chapter 2.4.3 --- Experiment 3: Transformation Invariance --- p.20, Chapter 2.5 --- Chapter Summary --- p.23, Chapter 3 --- Clustered Dynamic Conditional Correlation Model --- p.26, Chapter 3.1 --- Background Review --- p.26, Chapter 3.1.1 --- GARCH Model --- p.26, Chapter 3.1.2 --- Multivariate GARCH model --- p.29, Chapter 3.2 --- DCC Multivariate GARCH Models --- p.31, Chapter 3.2.1 --- DCC GARCH Model --- p.31, Chapter 3.2.2 --- Generalized DCC GARCH Model --- p.32, Chapter 3.2.3 --- Block-DCC GARCH Model --- p.32, Chapter 3.3 --- Clustered DCC GARCH Model --- p.34, Chapter 3.3.1 --- Minimum Distance Estimation (MDE) --- p.36, Chapter 3.3.2 --- Clustered DCC (CDCC) based on MDE --- p.37, Chapter 3.4 --- Clustering Method Selection --- p.40, Chapter 3.5 --- Model Estimation and Testing Method --- p.42, Chapter 3.5.1 --- Maximum Likelihood Estimation --- p.42, Chapter 3.5.2 --- Box-Pierce Statistic Test --- p.44, Chapter 3.6 --- Chapter Summary --- p.44, Chapter 4 --- Experimental Result and Applications on CDCC --- p.46, Chapter 4.1 --- Model Comparison and Analysis --- p.46, Chapter 4.2 --- Portfolio Selection Application --- p.50, Chapter 4.3 --- Value at Risk Application --- p.52, Chapter 4.4 --- Chapter Summary --- p.55, Chapter 5 --- Conclusion --- p.57, Bibliography --- p.61, http://library.cuhk.edu.hk/record=b5896838, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Yip Kin Fung., Thesis (M.Phil.)--Chinese University of Hong Kong, 2003., Includes bibliographical references (leaves 101-104)., s in English and Chinese., Chapter 1 --- Introduction --- p.1, Chapter 2 --- The Distribution of Fluctuations in Financial Data --- p.5, Chapter 2.1 --- Empirical Statistics --- p.5, Chapter 2.2 --- Data analyzed --- p.8, Chapter 2.3 --- Levy Distribution --- p.10, Chapter 2.4 --- Returns Distribution and Scaling Properties --- p.12, Chapter 2.5 --- Volatility Clustering --- p.19, Chapter 2.6 --- Conclusion --- p.21, Chapter 3 --- Models of Herd behaviour in Financial Markets --- p.22, Chapter 3.1 --- Cont and Bouchaud's model --- p.22, Chapter 3.2 --- The Model of Egiuluz and Zimmerman --- p.24, Chapter 3.3 --- EZ Model with Size-Dependent Dissociation Rates --- p.28, Chapter 3.4 --- Democratic and Dictatorship Self-Organized Model --- p.31, Chapter 3.5 --- Effect of Size-Dependent Fragmentation and Coagulation Prob- abilities --- p.33, Chapter 3.6 --- Extensions of EZ model --- p.35, Chapter 3.7 --- Conclusion --- p.39, Chapter 4 --- Review on the Minority Game(MG) --- p.42, Chapter 4.1 --- The Model and Results --- p.42, Chapter 4.2 --- Crowd-anticrowd Theory and Phase Transition --- p.46, Chapter 4.3 --- Market Efficiency --- p.48, Chapter 5 --- MG with biased strategy pool --- p.52, Chapter 5.1 --- The Model --- p.53, Chapter 5.2 --- Numerical Results and Discussion --- p.53, Chapter 5.3 --- Theory: MG with Biased Strategy Pool --- p.61, Chapter 5.4 --- Conclusion --- p.69, Chapter 6 --- MG with Randomly Participating Agents --- p.71, Chapter 6.1 --- The Model with One RPA --- p.71, Chapter 6.2 --- Results for q = 0.5 --- p.72, Chapter 6.3 --- Inefficiency and Success Rate --- p.76, Chapter 6.4 --- Results for q ≠ 0.5 --- p.82, Chapter 6.5 --- Many RPAs --- p.85, Chapter 6.6 --- Conclusion --- p.86, Chapter 7 --- A Model on Coupled Minority Games --- p.88, Chapter 7.1 --- The Model --- p.89, Chapter 7.2 --- Results and Discussion。 --- p.90, Chapter 7.3 --- Conclusion --- p.95, Chapter 8 --- Conclusion --- p.97, Bibliography --- p.101, Chapter A --- Solving Cluster Size distribution in EZ model --- p.105, http://library.cuhk.edu.hk/record=b5891443, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Yu Lian., Thesis (M.Phil.)--Chinese University of Hong Kong, 2003., Includes bibliographical references (leaves 81-84)., s in English and Chinese., Chapter 1 --- Introduction --- p.1, Chapter 2 --- Literature Review --- p.4, Chapter 3 --- An Index Tracking Model with Downside Chance Risk Mea- sure --- p.12, Chapter 3.1 --- Statement of the Model --- p.13, Chapter 3.2 --- Efficient Frontier --- p.16, Chapter 3.3 --- Application of the Downside Chance Index Tracking Model --- p.29, Chapter 3.4 --- Chapter Summary --- p.34, Chapter 4 --- Index Tracking Models with High Order Moment Downside Risk Measure --- p.35, Chapter 4.1 --- Statement of the Models --- p.35, Chapter 4.2 --- Mean-Downside Deviation Financial Index Tracking Model --- p.38, Chapter 4.3 --- Chapter Summary --- p.45, Chapter 5 --- Numerical Analysis --- p.45, Chapter 5.1 --- Data Analysis --- p.45, Chapter 5.2 --- Experiment Description and Discussion --- p.48, Chapter 5.2.1 --- Efficient Frontiers --- p.48, Chapter 5.2.2 --- Monthly Expected Rate of Return --- p.50, Chapter 5.3 --- Chapter Summary --- p.52, Chapter 6 --- Summary --- p.54, Chapter A --- List of Companies --- p.57, Chapter B --- Graphical Result of Section 5.2.1 --- p.61, Chapter C --- Graphical Result of Section 5.2.2 --- p.67, Chapter D --- Proof in Chapter 3 and Chapter4 --- p.73, Bibliography --- p.81, http://library.cuhk.edu.hk/record=b5891530, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Lim Sze Wah., Thesis (M.Phil.)--Chinese University of Hong Kong, 2002., Includes bibliographical references (leaves 71-73)., s in English and Chinese., Chapter 1 --- Introduction --- p.1, Chapter 2 --- A brief review on the basic minority game --- p.6, Chapter 2.1 --- Model --- p.7, Chapter 2.2 --- Results --- p.9, Chapter 2.3 --- Discussion --- p.11, Chapter 2.3.1 --- Bit-string Statistics and Market Efficiency --- p.11, Chapter 2.3.2 --- Crowds and Anticrowds Effect --- p.14, Chapter 2.3.3 --- Hamming Distance and Reduced Strategies Space --- p.15, Chapter 3 --- A brief review on existing variations on the minority game --- p.17, Chapter 3.1 --- Darwinism process and MG --- p.17, Chapter 3.2 --- Evolutionary MG (EMG) --- p.17, Chapter 3.3 --- Modified EMG (MEMG) --- p.18, Chapter 3.4 --- MG with arbitrary cutoff --- p.18, Chapter 3.5 --- Thermal MG (TMG) --- p.19, Chapter 3.6 --- Three-Sided MG --- p.19, Chapter 3.7 --- MG with variable payoffs --- p.19, Chapter 4 --- Minority game with varying number of participants --- p.21, Chapter 4.1 --- The modified MG --- p.22, Chapter 4.1.1 --- Model --- p.22, Chapter 4.1.2 --- Results --- p.23, Chapter 4.2 --- Mixed-population --- p.33, Chapter 4.2.1 --- Model --- p.33, Chapter 4.2.2 --- Results --- p.33, Chapter 4.2.3 --- Discussions --- p.37, Chapter 5 --- Minority game considering recent performance of strategies --- p.39, Chapter 5.1 --- The modified MG --- p.40, Chapter 5.1.1 --- Model --- p.40, Chapter 5.1.2 --- Results --- p.40, Chapter 5.2 --- Mixed-population --- p.46, Chapter 5.2.1 --- Model --- p.46, Chapter 5.2.2 --- Results --- p.47, Chapter 5.2.3 --- Discussions --- p.50, Chapter 6 --- Minority game combining both modifications --- p.52, Chapter 6.1 --- Model --- p.52, Chapter 6.2 --- Results --- p.53, Chapter 7 --- Conclusion --- p.68, Bibliography --- p.71, http://library.cuhk.edu.hk/record=b5891121, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

by Lo Ting Shek = 複雜適應系統中的個體為本模型 / 盧庭碩., Thesis (M.Phil.)--Chinese University of Hong Kong, 2000., Includes bibliographical references (leaves 105-107)., Text in English; abstracts in English and Chinese., by Lo Ting Shek = Fu za shi ying xi tong zhong de ge ti wei ben mo xing / Lu Tingshuo., Chapter 1 --- Introduction --- p.1, Chapter 2 --- Minority game --- p.9, Chapter 2.1 --- The model --- p.9, Chapter 2.2 --- Review on selected work on MG --- p.13, Chapter 2.2.1 --- Market efficiency and Phase transition --- p.13, Chapter 2.2.2 --- Crowd effect in MG --- p.17, Chapter 2.2.3 --- Hamming distance between strategies --- p.19, Chapter 2.2.4 --- Statistical mechanics of systems with heterogeneous agents --- p.21, Chapter 3 --- Theory of the minority game --- p.23, Chapter 3.1 --- Formalism --- p.23, Chapter 3.2 --- Discussion --- p.31, Chapter 4 --- Evolutionary Minority Game --- p.33, Chapter 4.1 --- Model --- p.33, Chapter 4.2 --- Results --- p.36, Chapter 4.3 --- Discussion --- p.38, Chapter 5 --- Theory of the Evolutionary Minority game --- p.43, Chapter 5.1 --- The theory of D'hulst and Rodgers [1] --- p.44, Chapter 5.1.1 --- Discussion on the D'hulst and Rodgers's theory --- p.51, Chapter 5.2 --- Theory of EMG [2] --- p.54, Chapter 5.2.1 --- Formalism --- p.55, Chapter 5.2.2 --- Results --- p.60, Chapter 5.2.3 --- Discussion --- p.66, Chapter 6 --- Evolutionary Minority Game with arbitrary cutoffs --- p.68, Chapter 6.1 --- Model --- p.68, Chapter 6.2 --- Results --- p.69, Chapter 6.3 --- Theory --- p.76, Chapter 6.4 --- Discussion --- p.85, Chapter 7 --- Evolutionary minority game with heterogeneous strategy distribution --- p.88, Chapter 7.1 --- Model --- p.89, Chapter 7.2 --- Results --- p.90, Chapter 7.3 --- Discussion --- p.99, Chapter 8 --- Conclusion --- p.103, http://library.cuhk.edu.hk/record=b5890318, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)