Although the original intent of this study was to do a pre-and post-deregulation assessment of rail rates per ton-mile, the results using post-deregulation data show a significant decrease in rail rates between 1981 and 2000. While accounting for changes in shipment characteristics, savings for wheat, barley, com, oat, and soybean shippers were 63.80%, 69.17%, 49.07%, 67.97%, and 59.36%, respectively. Rate savings over time for an average 1981 shipment were 45%, 55%, 38%, 45%, and 36% for wheat, barley, com, oat, and soybean shippers, respectively. Analysis regarding the effects of deregulation of rail rates on com, soybean, and wheat on a regional basis shows that rail rates not only differ across commodities, but also among regions. In general, it was found that grain producers within regions that had higher levels of intermodal competition had lower rates than their counterparts with lower levels of intermodal competition. Distribution of benefits as a result of market-based pricing has varied among regions, and these variances are increasing over time.

Call number: LD2668 .T4 1955 S59 / Master of Science

No description available.

This study traces the annual average prices received per hundredweight for veal calves at the Chicago market and the annual average weekly earnings of employees in all manufacturing industries. The period of time covered by the study is 1900 to 1951.

by Wong Chi Yan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 38-39). / 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 --- Built-in 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 Full-Storage Method --- p.10 / Chapter 3.2 --- The Forward-Path Method --- p.12 / Chapter 3.3 --- The Backward-Path Method --- p.14 / Chapter 4 --- The Least-Squares Method --- p.17 / Chapter 5 --- Numerical Examples --- p.28 / Chapter 6 --- Concluding Remarks --- p.34 / Appendix --- p.36 / Bibliography --- p.38

Xu, Lin. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 128-131). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Zhao Jing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 72-74). / 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 Front-Fixing Transformation --- p.47 / Chapter 6.2 --- Homotopy Analysis Method --- p.49 / Chapter 6.2.1 --- Zero-order Deformation Equation --- p.50 / Chapter 6.2.2 --- High-order 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) = Ls-1 ((Y/a)vKv(Y)/sKv(sa)" --- p.66 / Chapter C --- Numerical Laplace Inversion --- p.68 / Bibliography --- p.72

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 --- Put-Call Parity --- p.7 / Chapter 2.2 --- Black-Scholes equation --- p.8 / Chapter 2.2.1 --- Derivation of Black-Scholes equation --- p.8 / Chapter 2.2.2 --- Solution to the Black-Scholes 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

Ren, You. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 48-51). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background of Option Pricing Theory --- p.1 / Chapter 1.2 --- American Option Pricing --- p.3 / Chapter 1.3 --- Numerical Approximation of American Option Price --- p.8 / Chapter 1.4 --- Statistical Issues --- p.12 / Chapter 1.4.1 --- Empirical Calibration --- p.13 / Chapter 2 --- Mixed Effects Model for American Option Prices --- p.16 / Chapter 2.1 --- Model --- p.16 / Chapter 2.2 --- Model Selection --- p.19 / Chapter 2.3 --- Empirical Bayes Prediction --- p.21 / Chapter 3 --- Simulation and Empirical Data --- p.22 / Chapter 3.1 --- Simulation --- p.22 / Chapter 3.1.1 --- Simulation of Stock Price Path and a Set of Options --- p.22 / Chapter 3.1.2 --- Training Mixed Effects Model --- p.27 / Chapter 3.1.3 --- Performance Measure and Prediction Result --- p.30 / Chapter 3.2 --- An Application to P&G American Options --- p.36 / Chapter 3.2.1 --- The Empirical Data and Setup --- p.36 / Chapter 3.2.2 --- Training Mixed Effects Option Pricing Model --- p.37 / Chapter 3.2.3 --- Performance Analysis --- p.41 / Chapter 4 --- Conclusion and Discussion --- p.46 / Bibliography --- p.48

Zhang, Wanqing. / Leaf 138 numbered in duplicate. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 138-143). / Abstracts in English and Chinese. / Abstract --- p.i / 摘要 --- p.ii / Acknowledgement --- p.iii / Table of Content --- p.iv / List of Tables --- p.vi / List of Figures / Chapter Chapter 1: --- Introduction --- p.1 / Chapter 1.1 --- An Overview of the Tourism Industry --- p.1 / Chapter 1.2 --- Research Motivation --- p.3 / Chapter 1.3 --- Outline --- p.8 / Chapter Chapter 2： --- Literature Review --- p.9 / Chapter Chapter 3： --- The Data and Methodology --- p.14 / Chapter 3.1 --- Dataset --- p.14 / Chapter 3.2 --- Methodology --- p.21 / Chapter Chapter 4： --- Empirical Evidence For Tourism Industry --- p.25 / Chapter 4.1 --- Hypothesis --- p.26 / Chapter 4.2 --- Evidence for the tourism stocks --- p.27 / Chapter 4.3 --- Decomposition of Returns --- p.42 / Chapter 4.4 --- Seasonality --- p.52 / Chapter Chapter 5： --- Empirical Evidence For The Market --- p.56 / Chapter 5.1 --- Momentum and reversal effect in general market --- p.57 / Chapter 5.1.1 --- Profitability and Return Performance --- p.57 / Chapter 5.1.2 --- Seasonality --- p.66 / Chapter 5.2 --- Tourism industry vs. General market --- p.70 / Chapter Chapter 6： --- Explaining The Momentum And Reversal Effect: Capital Asset Pricing Model --- p.73 / Chapter 6.1 --- Capmand three-factor model --- p.74 / Chapter 6.2 --- Evidence from tourism stocks --- p.86 / Chapter Chapter 7： --- Explaining The Momentum And Reversal Effect: Fundamentals --- p.92 / Chapter 7.1 --- Movements in fundamentals --- p.95 / Chapter 7.1.1 --- Fundamental hypothesis --- p.95 / Chapter 7.12 --- Movement in profits --- p.96 / Chapter 7.2 --- Using Logit Model To Explore Differences Between The Winner And The Loser Portfolio --- p.108 / Chapter 7.2.1 --- Induction of a binary choice approach- logit regression model --- p.108 / Chapter 7.2.2 --- MODEL I: Using changes in ROA --- p.113 / Chapter 7.2.3 --- MODEL II: Using coded Ret-ROA --- p.115 / Chapter 7.2.4 --- MODEL III: Multi-variable logistic regression --- p.118 / Chapter Chapter 8: --- The Price Impact Of Institutional Investors To Tourism Stocks --- p.120 / Chapter 8.1 --- Changes of institutional ownership in tourism stocks --- p.122 / Chapter 8.2 --- Regression Results --- p.126 / Chapter Chapter 9: --- Conclusion --- p.132 / Reference --- p.138