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91 
The information content of macroeconomic variables and industry specific financial ratios on stock prices: evidence from Hong Kong.January 2000 (has links)
by Au Wai Shan, Christine, Choi Wing Kam. / Thesis (M.B.A.)Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 8690). / ABSTRACT  p.ii / ACKNOWLEDGEMENT  p.iv / TABLE OF CONTENTS  p.v / LIST OF TABLES  p.vii / CHAPTER / Chapter I.  INTRODUCTION  p.1 / Chapter II.  LITERATURE REVIEW  p.3 / Chapter III.  METHODOLOGY  p.9 / Chapter 1  Source of Data and Company Information  p.9 / Chapter 1.1  Data on Security Prices and Macroeconomic Variables  p.9 / Chapter 1.2  Company Annual Reports  p.9 / Chapter 1.3  "Journals, Newspapers and Related Magazines"  p.10 / Chapter 2.  Selection of Company  p.10 / Chapter 3.  "Whatts PanEL,Data?"  p.10 / Chapter 3.1  Benefits of using Panel Data  p.11 / Chapter 3.2  Limitations of using Panel Data  p.12 / Chapter 4.  Multiple regression analysts  p.13 / Chapter 4.1  What is multiple regression model?  p.13 / Chapter 4.2  Assumptions of multiple regression  p.15 / Chapter 5.  FtnanctaL RatIo Analysts  p.16 / Chapter 6.  Economic Factor Analysis  p.19 / Chapter IV.  FINDINGS  p.20 / Chapter 1.  ResuLts of MULttpte Regression (By Individual Company) of the Stock Price and MacRoeconomtc factors  p.20 / Chapter 1.1  "R2, Coefficients of variables and Fstatistic"  p.20 / Chapter 1.2  Correlation Among the Macroeconomic Factors  p.23 / Chapter 2.  Results of MULTIpLe REgREssIons (By Sectors) of thE Stock Prtce and Financial Statement RatIos  p.24 / Chapter 2.1  "R2, Coefficients of variables and Fstatistic"  p.24 / Chapter 2.2  Correlation among the Microeconomic Factors  p.25 / Chapter V.  DISCUSSIONS  p.27 / Chapter 1.  Summary of findings  p.27 / Chapter 2.  Discusston of the impact of economic factors on the stock price  p.28 / Chapter 3.  "Dtscusston the impacts of ftnancial, statement ratios on the stock price"  p.29 / Chapter 4.  LImItattons on our model  p.31 / Chapter 4.1  Outlier Problems  p.31 / Chapter 4.2  Average stock price in the month of announcing annual reports  p.31 / Chapter 4.3  Using of annual data  p.32 / Chapter VI.  FURTHER DISCUSSION ON NOWADAYS PHENOMENA  p.33 / Chapter 1.  Greenspan's Theory  p.33 / Chapter 2.  ThE FEvER of Internet/ TEchnoLOgy/ConcEPt Stock  p.34 / Chapter VII.  RECOMMENDATIONS  p.35 / Chapter 1.  Other mEthodoLogIEs  p.35 / Chapter 2.  Other Ratios with same or similar meanings  p.36 / Chapter 3.  Other indices  p.37 / Chapter 4.  A new standard： sustatnaBILIty  p.37 / Chapter VIII.  CONCLUSION  p.39 / APPENDIX  p.40 / BIBLIOGRAPHY  p.86

92 
Fisher hypothesis, international stock return differentials and inflation differentials.January 2000 (has links)
Wu Haijun. / Thesis (M.Phil.)Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 4548). / Abstracts in English and Chinese. / Abstract  p.ii / Acknowledgement  p.iv / Chapter Chapter 1.  Introduction  p.1 / Chapter Chapter 2.  Literature Review  p.4 / Chapter 2.1.  The Fisher Hypothesis  p.4 / Chapter 2.2.  International Fisher Equation  p.11 / Chapter Chapter 3.  Theoretical Basis on The Link Between Stock Return Differential and Inflation Rate Differential  p.15 / Chapter Chapter 4.  Data Description  p.19 / Chapter Chapter 5.  Results  p.23 / Chapter 5.1.  Does The Generalized Fisher Hypothesis Hold In The Long Horizons  p.24 / Chapter 5.2.  Does International Fisher Equation Hold  p.29 / Chapter 5.3.  Can International Elements Account For The Failure of Fisher Hypothesis  p.36 / Chapter Chapter 6.  Conclusion  p.43 / Bibliography  p.45 / Appendix A  p.49 / Chapter A.1.  The link between interest rate differential and inflation rate differential  p.49 / Chapter A.2.  Instrumental Variable Estimation  p.53 / Appendix B  p.59 / Chapter B.1.  Hong Kong CPI(A) Source  p.59 / Chapter B.2.  Taiwan CPI Source  p.61 / LIST OF TABLES / Table 4.1: Data Description  p.21 / Table 4.2: Means and Standard Deviations of Inflation and Stock Returns  p.22 / Table 5.1: Shortterm (One Year) Test on Fisher Hypothesis on Stock Returns  p.26 / Table 5.2: Longterm (Five Years) Test on Fisher Hypothesis on Stock Returns  p.27 / Table 5.3: Longterm (Ten Years) Test on Fisher Hypothesis on Stock Returns  p.30 / Table 5.4: Shortterm (One Year) Test For International Fisher Equation on Stock Returns  p.33 / Table 5.5: Longterm (Five Years) Test For International Fisher Equation on Stock Returns  p.34 / Table 5.6: Longterm (Ten Years) Test For International Fisher Equation on Stock Returns  p.35 / Table 5.7: Testing Effects of International Elements on The Fisher Hypothesis  p.39 / Table 5.8: Regression Results For The Coefficients of Domestic Inflation With and Without International Elements  p.40

93 
Estimation of the beta aggregated structuralbreak model.January 2002 (has links)
Liu Guoxin. / Thesis (M.Phil.)Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 2425). / Abstracts in English and Chinese. / Chapter 1  Introduction  p.2 / Chapter 2  The Model  p.4 / Chapter 3  "Estimation of μ1 ,μ2 ,α and β"  p.7 / Chapter 4  Extension  p.9 / Chapter 5  Monte Carlo Simulation  p.11 / Chapter 5.1  "Case 1. a < 1, β < 1"  p.12 / Chapter 5.2  "Case 2. a > 1, β < 1"  p.12 / Chapter 5.3  "Case 3. a < 1,β > 1"  p.13 / Chapter 5.4  "Case 4. a > 1, β> 1"  p.13 / Chapter 6  Empirical Application  p.15 / Chapter 6.1  Model Construction  p.15 / Chapter 6.2  Estimation Results  p.15 / Chapter 6.2.1  1973Oil Crisis  p.16 / Chapter 6.2.2  1981 Oil Crisis  p.18 / Chapter 6.2.3  1991 Oil Crisis  p.20 / Chapter 7  Conclusion  p.23 / Chapter 8  Bibliography  p.24

94 
Pricing Americanstyle options by Monte Carlo method.January 2002 (has links)
by Wong Chi Yan. / Thesis (M.Phil.)Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 3839). / Abstracts in English and Chinese. / Chapter 1  Introduction  p.1 / Chapter 1.1  Introduction  p.1 / Chapter 1.2  Monte Carlo Method  p.2 / Chapter 1.3  Outline of Thesis  p.5 / Chapter 2  The Random Number Generators  p.7 / Chapter 2.1  Builtin Random Number Generating Functions  p.7 / Chapter 2.2  Linear Congruential Generators  p.8 / Chapter 3  Memory Reduction Methods  p.10 / Chapter 3.1  The FullStorage Method  p.10 / Chapter 3.2  The ForwardPath Method  p.12 / Chapter 3.3  The BackwardPath Method  p.14 / Chapter 4  The LeastSquares Method  p.17 / Chapter 5  Numerical Examples  p.28 / Chapter 6  Concluding Remarks  p.34 / Appendix  p.36 / Bibliography  p.38

95 
A numerical method for American option pricing under CEV model.January 2007 (has links)
Zhao Jing. / Thesis (M.Phil.)Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 7274). / Abstracts in English and Chinese. / Chapter 1  Introduction  p.1 / Chapter 2  The Constant Elasticity of Variance Model  p.6 / Chapter 2.1  The CEV Assumption  p.7 / Chapter 2.2  Properties of the CEV Model  p.9 / Chapter 2.3  Empirical Evidence and Theoretical Support  p.11 / Chapter 3  Option Pricing under CEV  p.14 / Chapter 3.1  The Valuation of European Options  p.14 / Chapter 3.2  The Valuation of American Options  p.17 / Chapter 3.3  "How ""far"" is Enough?"  p.19 / Chapter 4  The Proposed Artificial Boundary Approach  p.21 / Chapter 4.1  Standardized Form of the CEV Model  p.21 / Chapter 4.2  Exact Artificial Boundary Conditions  p.23 / Chapter 4.3  The Integral Kernels and Numerical Laplace Inversion  p.31 / Chapter 5  Numerical Examples  p.35 / Chapter 5.1  General Numerical Scheme  p.35 / Chapter 6  Homotopy Analysis Method  p.47 / Chapter 6.1  The FrontFixing Transformation  p.47 / Chapter 6.2  Homotopy Analysis Method  p.49 / Chapter 6.2.1  Zeroorder Deformation Equation  p.50 / Chapter 6.2.2  Highorder Deformation Equation  p.54 / Chapter 6.2.3  Pade Technique  p.57 / Chapter 6.3  Numerical Comparison  p.58 / Chapter 7  Conclusion  p.63 / Appendix  p.65 / Chapter A  The Valuation of Perpetual American Options  p.65 / Chapter B  "Derivation of G(Y,r) = Ls1 ((Y/a)vKv(Y)/sKv(sa)"  p.66 / Chapter C  Numerical Laplace Inversion  p.68 / Bibliography  p.72

96 
Market size, booktomarket equity and the crosssection of stock returns: an application of the multiplevariable threshold model. / Market size, booktomarket equity & the crosssection of stock returnsJanuary 2006 (has links)
Mak Wing Hei. / Thesis (M.Phil.)Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 5052). / Abstracts in English and Chinese. / ABSTRACT  p.1 / 摘要  p.2 / ACKNOWLEDGEMENTS  p.3 / TABLE OF CONTENTS  p.4 / Chapter CHAPTER 1  INTRODUCTION & LITERATURE REVIEW  p.6 / Chapter CHAPTER 2  DATA DESCRIPTION  p.12 / Chapter 2.1   Coverage and Sources  p.12 / Chapter 2.2   Match Accounting Data with Stock Returns  p.12 / Chapter 2.3   Selection Rule  p.13 / Chapter 2.4   Choice of the Threshold Variables Z  p.14 / Chapter CHAPTER 3  THE MODEL  p.15 / Chapter 3.1   Estimating excess returns & Betas  p.15 / Chapter 3.2  Estimating Threshold Effects  p.17 / Chapter 3.3   Testing the Number of Threshold Variables  p.19 / Chapter 3.4   Estimating Threshold values  p.21 / Chapter CHAPTER 4  PRELIMINARY OBSERVATIONS  p.21 / Chapter 4.1   Excess Returns  p.21 / Chapter 4.2   "Relationship between Beta, Market Size and BooktoMarket Equity"  p.24 / Chapter CHAPTER 5  ESTIMATION RESULTS OF THE THRESHOLD MODEL  p.35 / Chapter 5.1   Number of Threshold Variables  p.35 / Chapter 5.2  Threshold Value Estimates  p.39 / Chapter 5.3  The “and´ح case and “or´حcase  p.40 / Chapter 5.4   Comparison with OLS  p.45 / Chapter CHAPTER 6  CONCLUSION  p.48 / REFERENCES  p.50

97 
CEV asymptotics of American options. / Constant elasticity of variance asymptotics of American optionsJanuary 2013 (has links)
常方差彈性(CEV) 模型能夠刻畫波動率微笑的優點使之成為期權定價中的實用工具，然而它在應用到美式衍生工具時面臨分析上及計算上的挑戰。現行的解析方法是對代表著期權價格函數和其最佳履約曲線的自由邊界問題進行拉普拉斯卡森變換(LCT) ，繼而獲得在此變換下的解析解，可是此解含有合流超線幾何函數，使得它的數值計算在某些參數下顯得不穩定及低效。本文運用漸近法徹底解決美式期權在常方差彈性模型下的定價問題，並用永久性和限時性的美式看跌期權作為例子闡述所提出的方法。 / The constant elasticity of variance (CEV) model is a practical approach to option pricing by fitting to the implied volatility skew. Its application to Americanstyle derivatives, however, poses analytical and numerical challenges. By taking the Laplace Carson transform (LCT) to the freeboundary value problem characterizing the option value function and the early exercise boundary, the analytical result involves confluent hypergeometric functions. Thus, the numerical computation could be unstable and inefficient for certain set of parameter values. We solve this problem by an asymptotic approach to the American option pricing problem under the CEV model. We demonstrate the use of the proposed approach using perpetual and finitetime American puts. / Detailed summary in vernacular field only. / Pun, Chi Seng. / Thesis (M.Phil.)Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 3940). / Abstracts also in Chinese. / Chapter 1  Introduction  p.1 / Chapter 2  Problem Formulation  p.4 / Chapter 2.1  The CEV model  p.4 / Chapter 2.2  The freeboundary value problem  p.5 / Chapter 2.2.1  Perpetual American put  p.5 / Chapter 2.2.2  Finitetime American put  p.6 / Chapter 3  Asymptotic expansion of American put  p.8 / Chapter 3.1  Perpetual American put  p.8 / Chapter 3.2  Finitetime American put  p.16 / Chapter 4  Numerical examples  p.24 / Chapter 4.1  Perpetual American put  p.24 / Chapter 4.2  Finitetime American put  p.26 / Chapter 5  Conclusion  p.29 / Chapter A  Proof of Lemma 3.1  p.30 / Chapter B  Property of ak  p.32 / Chapter C  Explicit formulas for u₂(S)  p.34 / Chapter D  Closedform solutions  p.37 / Bibliography  p.40

98 
Fractional volatility models and malliavin calculus.January 2004 (has links)
Ng ChiTim. / Thesis (M.Phil.)Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 110114). / Abstracts in English and Chinese. / Chapter Chapter 1  Introduction  p.4 / Chapter Chapter 2  Mathematical Background  p.7 / Chapter 2.1  Fractional Stochastic Integral  p.8 / Chapter 2.2  Wick's Calculus  p.9 / Chapter 2.3  Malliavin Calculus  p.19 / Chapter 2.4  Fractional Ito's Lemma  p.27 / Chapter Chapter 3  The Fractional Black Scholes Model  p.34 / Chapter 3.1  Fractional Geometric Brownian Motion  p.35 / Chapter 3.2  Arbitrage Opportunities  p.38 / Chapter 3.3  Fractional Black Scholes Equation  p.40 / Chapter Chapter 4  Generalization  p.43 / Chapter 4.1  Stochastic Gradients of Fractional Diffusion Processes  p.44 / Chapter 4.2  An Example : Fractional Black Scholes Mdel with Varying Trend and Volatility  p.46 / Chapter 4.3  Generalization of Fractional Black Scholes PDE  p.48 / Chapter 4.4  Option Pricing Problem for Fractional Black Scholes Model with Varying Trend and Volatility  p.55 / Chapter Chapter 5  Alternative Fractional Models  p.59 / Chapter 5.1  Fractional Constant Elasticity Volatility (CEV) Models  p.60 / Chapter 5.2  Pricing an European Call Option  p.61 / Chapter Chapter 6  Problems in Fractional Models  p.66 / Chapter Chapter 7  Arbitrage Opportunities  p.68 / Chapter 7.1  Two Equivalent Expressions for Geometric Brownian Motions  p.69 / Chapter 7.2  Selffinancing Strategies  p.70 / Chapter Chapter 8  Conclusions  p.72 / Chapter Appendix A  Fractional Stochastic Integral for Deterministic Integrand  p.75 / Chapter A.1  Mapping from InnerProduct Space to a Set of Random Variables  p.76 / Chapter A.2  Fractional Calculus  p.77 / Chapter A.3  Spaces for Deterministic Functions  p.79 / Chapter Appendix B  Three Approaches of Stochastic Integration  p.82 / Chapter B.1  STransformation Approach  p.84 / Chapter B.2  Relationship between Three Types of Stochastic Integral  p.89 / Reference  p.90

99 
threefactor structural model of risky bonds and its applications. / 三因結構模型之公司債劵定價及其應用 / A threefactor structural model of risky bonds and its applications. / San yin jie gou mo xing zhi gong si zhai quan ding jia ji qi ying yongJanuary 2003 (has links)
Huang Ming Xi = 三因結構模型之公司債劵定價及其應用 / 黃銘浠. / Thesis (M.Phil.)Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 99102). / Text in English; abstracts in English and Chinese. / Huang Ming Xi = San yin jie gou mo xing zhi gong si zhai quan ding jia ji qi ying yong / Huang Mingxi. / Abstract  p.i / Acknowledgements  p.iii / Contents  p.iv / List of Figures  p.vii / List of Tables  p.xiii / Chapter Chapter 1.  Introduction  p.1 / Chapter Chapter 2.  Structural Models of Credit Pricing  p.3 / Chapter 2.1  Introduction  p.3 / Chapter 2.2  Merton's Model (1974)  p.4 / Chapter 2.2.1  The Framework of the Traditional Contingent Claims Analysis (CCA)  p.5 / Chapter 2.2.2  The Valuation of Corporate Bonds with BS Option Pric ing Theory  p.9 / Chapter 2.2.3  The Limitations of Traditional Contingent Claim Ap proach  p.12 / Chapter 2.3  "Shimko, Tejima and Deventer (1993)"  p.15 / Chapter 2.3.1  The Merton's Model in a Stochastic Interest Rate Frame work  p.15 / Chapter 2.4  Longstaff and Schwartz (1995)  p.17 / Chapter 2.4.1  A Structure Model of Early Default Mechanism and De viations from APR  p.17 / Chapter 2.5  Briys and de Varenne (1997)  p.21 / Chapter 2.5.1  A Structure Model of Stochastic Default Barrier  p.21 / Chapter 2.5.2  The Valuation of Risky ZeroCoupon Bonds  p.22 / Chapter 2.6  Stationaryleverageratio Models  p.25 / Chapter 2.6.1  Tauren (1999)  p.25 / Chapter 2.6.2  CollinDufresne and Goldstein (2001)  p.27 / Chapter 2.7  Summary  p.29 / Chapter Chapter 3.  The Valuation Framework of the Threefactor Model  p.32 / Chapter 3.1  Introduction  p.33 / Chapter 3.2  The Framework of the Threefactor Model  p.35 / Chapter 3.3  The Valuation of Risky Bonds  p.39 / Chapter 3.3.1  Imposing an Early Default Mechanism  p.42 / Chapter 3.3.2  Application: The Valuation of Probability of Default  p.45 / Chapter Chapter 4.  The Pricing Methodology of the Threefactor Model  p.46 / Chapter 4.1  Simplification of the Problem  p.47 / Chapter 4.2  Methodology of Upperlower Bound Scheme  p.48 / Chapter 4.2.1  Singlestage Approximation  p.48 / Chapter 4.2.2  Illustrative Examples  p.53 / Chapter 4.2.3  Multistage Approximation  p.54 / Chapter 4.2.4  Summary  p.58 / Chapter 4.2.5  Systematic Multistage Estimation of Bond Price  p.61 / Chapter 4.3  Estimation of Default Probability  p.63 / Chapter Chapter 5.  Numerical Results and Discussion  p.69 / Chapter 5.1  Initial Setting of Parameters  p.69 / Chapter 5.2  Numerical Results and Discussion  p.74 / Chapter Chapter 6.  Conclusion  p.89 / Appendix A. The Derivation of the ThreeFactor Model  p.91 / Bibliography  p.99

100 
A Monte Carlo Method for pricing American options.January 2003 (has links)
by Lam Wing Shan. / Thesis (M.Phil.)Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaf 41). / Abstracts in English and Chinese. / Chapter 1  Introduction  p.1 / Chapter 2  Background on Option Pricing  p.3 / Chapter 2.1  Financial options  p.3 / Chapter 2.1.1  Basic terms of options  p.3 / Chapter 2.1.2  Trading strategies  p.4 / Chapter 2.1.3  The Principle of no Arbitrage  p.5 / Chapter 2.1.4  Rational boundaries on Option Prices  p.5 / Chapter 2.1.5  American Options  p.6 / Chapter 2.1.6  PutCall Parity  p.7 / Chapter 2.2  BlackScholes equation  p.8 / Chapter 2.2.1  Derivation of BlackScholes equation  p.8 / Chapter 2.2.2  Solution to the BlackScholes equation  p.10 / Chapter 3  Review on Monte Carlo Method  p.15 / Chapter 3.1  Monte Carlo Simulation  p.15 / Chapter 3.2  Pricing an option using Monte Carlo Method  p.18 / Chapter 3.3  Antithetic Variates Method  p.21 / Chapter 4  Cell Partition Method  p.23 / Chapter 4.1  An Advantage of the Cell Partition Method  p.23 / Chapter 4.2  The Algorithm  p.24 / Chapter 5  Numerical Results  p.35 / Chapter 6  Conclusion  p.39 / Bibliography  p.41

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