This dissertation consists of three essays. The first essay focuses on idiosyncratic volatility as a primary arbitrage cost for short sellers. Previous studies document (i) negative abnormal returns for high relative short interest (RSI) stocks, and (ii) positive abnormal returns for low RSI stocks. We examine whether these market inefficiencies can be explained by arbitrage limitations, especially firms' idiosyncratic risk. Consistent with limits to arbitrage hypothesis, we document an abnormal return of -1.74% per month for high RSI stocks (>=95th percentile) with high idiosyncratic volatility. However, for similar level of high RSI, abnormal returns are economically and statistically insignificant for stocks with low idiosyncratic volatility. For stocks with low RSI, the returns are positively related to idiosyncratic volatility. These results imply that idiosyncratic risk is a potential reason for the inability of arbitrageurs to extract returns from high and low RSI portfolios. The second essay investigates market efficiency in the absence of limits to arbitrage on short selling. Theoretical predictions and empirical results are ambiguous about the effect of short sale constraints on security prices. Since these constraints cannot be eliminated in equity markets, we use trades from futures markets where there is no distinction between short and long positions. With no external constraints on short positions, we document a weekend effect in futures markets which is a result of asymmetric risk between long and short positions around weekends. The premium is higher in periods of high volatility when short sellers are unwilling to accept higher levels of risk. On the other hand, riskiness of long positions does not seem to have a similar impact on prices. The third essay studies investor behaviors that generate mispricing by examining relationship between stock price and future returns. Based on traditional finance theory, valuation should not depend on nominal stock prices. However, recent literature documents that preference of retail investors for low price stocks results in their overvaluation. Motivated by this preference, we re-examine the relationship between stock price and expected return for the entire U.S. stock market. We find that stock price and expected returns are positively related if price is not confounded with size. Results in this paper show that, controlled for size, high price stocks significantly outperform low price stocks by an abnormal 0.40% per month. This return premium is attributed to individual investors' preference for low price stocks. Consistent with costly arbitrage, the return differential between high and low price stocks is highest for the stocks which are difficulty to arbitrage. The results are robust to price cut-off of $5, and in different sub-periods. / Ph. D.

The value-based approach to defining quality was used to investigate the value perceptions of softwood lumber treaters in the United States. Conjoint measurement techniques were used to estimate the trade-offs treaters make between quality enhancing attributes and price. Five intrinsic lumber attributes and five service attributes were chosen for inclusion in the study based on Hansen (1994) and personal interviews with treaters. Price was represented in the study relative to the current market price. Data were gathered in two stages through mail surveys of softwood lumber buyers at treating plants located in the United States. In the first stage, value ratings of 20 hypothetical combinations of lumber attributes and 20 hypothetical combinations of service attributes were obtained along with demographic information. In the second stage, value ratings of 20 hypothetical total products (combinations of both lumber and service attributes) were obtained. Utility functions for lumber value and service value were determined using ordinary least squares regression. Treaters gave the most importance to wane when evaluating the value of lumber packs. Price emerged as the second most important attribute in influencing treaters' perceptions of lumber value. Respondents considered the importance of the remaining lumber attributes in the following order: accuracy of grading, damage to lumber pack, and lumber straightness. A model to estimate the value of any combination of the attributes included in the study was developed. Simulation results suggest that treaters are willing to sacrifice $15.00 more per a thousand board feet for wane free lumber versus lumber with the maximum allowable wane. In the same fashion, respondents’ price sensitivity to other lumber attributes was determined. A service value utility function was developed based on the perceived value ratings. Price was the most important attribute in determining service value perceptions. Among all service attributes, lumber availability emerged as the most important. The second most important attribute in the determination of service value was reputation of the supplier. Respondents considered the supplier's ability to deliver lumber when promised as the third most important service attribute. The attributes, Supplier's ability to handle problems professionally and the ease with which supplier can be contacted by phone played a minor role in influencing service value. Based on the lumber value and service value analyses, lumber and service attributes were chosen for the final stage of data collection. Using a mail survey, perceived value ratings for hypothetical total products (lumber and service attributes) were obtained from the same respondents who provided data for the first stage of the analysis. Respondents in general, gave more importance to lumber quality than to service quality. Wane emerged as the most important attribute in influencing total product value. Price was considered to be the second most important attribute in the determination of perceived total product value. Respondents gave more importance to lumber availability than to reputation of the supplier while evaluating overall value. Accuracy of grading was considered to be the least important total product attribute. The results show that softwood lumber firms can differentiate themselves by providing wane free lumber and providing at least average service quality to their customers. The improved understanding of treaters’' needs and trade-offs should enable softwood lumber companies to plan the marketing strategies to achieve short- and long-term objectives while providing the most value to treaters. / Ph. D.

In the first essay, this thesis provides a new methodology for pricing the fixed income derivatives using the arbitrage-free Heath-Jarrow-Morton model (hereafter HJM model). While, most previous empirical implementations of HJM model like that by Amin and Morton (1994) are focused on one-factor model only, the essay attempts to extend the test to a two-factor model that could further capture the subtleties of the forward rate process. The two-factor Poisson-Gaussian version of HJM model derived by Das (1999) that incorporates a jump component as the second state variables is used to value the actively traded Eurodollar futures call option under the jump diffusion lattice. The one-factor and two-factor models are compared with five volatility functions to evaluate the degree of pricing improvement by the inclusion of one more state variable. / The essay also addresses the critical issues on the volatility structure of forward rates that affect the pricing performance of option under the HJM framework. Three new volatility specifications are constructed to estimate the traded options. The first volatility function is the humped & curvature adjusted model that allows for humped shape in volatility structure and better adjustment to the curvature of the term structure. The second is the humped & proportional model that exhibits humped volatility feature and is proportional to the forward rate. The third function is the linear exponential model that is extended from Vasicek's exponential model. They are compared with two other volatility structures developed by previous researchers on their pricing performances. The alternative models are examined from the perspectives of in-sample fit, out-of-sample pricing and hedging. / The second essay develops an approach for estimating the Value-at-Risk (hereafter VaR) with jumps using the Monte Carlo simulation method. It is by far the first paper to estimate VaR using the HJM model. The paper takes the framework of the Poisson Gaussian version of HJM model (hereafter, HJM jump-diffusion model) from Das (1999). The model is incorporated with a jump component to capture the kurtosis effect in the daily price changes. As a result, the HJM jump-diffusion model allows for the fat tailed and skewed distribution of return in most financial markets. The simulation process is expedited by using variance reduction method. The model is used for calculating the VaR of a portfolio consisting of the fixed income derivatives. The accuracy of the VaR estimates is examined statistically at the VaR at confidence level of both 95 and 99 percent. / This thesis is a collection of two essays that explore issues related to the pricing and the risk management of fixed income securities and derivatives in US markets. In the context of the pricing of derivatives, the arbitrage-free pricing approach is adopted. For the issue of risk management, the estimation of Value-at-Risk is presented. / by Ze-To Yau Man. / Source: Dissertation Abstracts International, Volume: 62-09, Section: A, page: 3138. / Supervisors: Jia He; Ying-foon Chow. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (p. 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 dissertations and theses, [200-] 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. / Abstracts in English and Chinese. / School code: 1307.

Kam Ying Chuen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 81-83). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Overview of Hong Kong Stock Market --- p.3 / Chapter 2.1 --- Stock Exchange of Hong Kong --- p.3 / Chapter 2.2 --- Hang Seng Index --- p.4 / Chapter 2.3 --- Influences of the United States --- p.5 / Chapter 2.4 --- Hong Kong Government's Intervention --- p.6 / Chapter 3 --- Literature Review --- p.8 / Chapter 3.1 --- Stable and Student t Distributions --- p.8 / Chapter 3.2 --- Generalized Distribution --- p.10 / Chapter 3.3 --- Socio-economic Model --- p.11 / Chapter 3.4 --- Extreme Value Analysis --- p.11 / Chapter 4 --- Methodology --- p.14 / Chapter 4.1 --- Homogeneous Model --- p.15 / Chapter 4.2 --- Inhomogeneous Model --- p.15 / Chapter 4.3 --- Model Validity --- p.16 / Chapter 4.3.1 --- Exceedance Rate --- p.17 / Chapter 4.3.2 --- Distribution of Excesses --- p.17 / Chapter 4.3.3 --- Independence --- p.18 / Chapter 5 --- Data --- p.19 / Chapter 5.1 --- Minute-by-minute Returns --- p.20 / Chapter 5.2 --- Daily returns --- p.21 / Chapter 5.3 --- Explanatory Variables for the Inhomogeneous Model --- p.21 / Chapter 6 --- Empirical Results: Minute-by-minute Returns --- p.24 / Chapter 6.1 --- Shape Parameter k --- p.24 / Chapter 6.2 --- Location Parameter μ --- p.25 / Chapter 6.3 --- Scale Parameter σ --- p.26 / Chapter 6.4 --- Conditional Scale Parameter ψ --- p.27 / Chapter 6.5 --- Specification Test --- p.29 / Chapter 7 --- Empirical Results: Daily Returns --- p.29 / Chapter 7.1 --- Homogeneous Model --- p.30 / Chapter 7.2 --- Inhomogeneous Model --- p.31 / Chapter 7.2.1 --- Constant Term --- p.32 / Chapter 7.2.2 --- Dow Jones Industrial Average Returns --- p.33 / Chapter 7.2.3 --- Volatility Indicators --- p.34 / Chapter 7.2.4 --- Monday Dummy --- p.35 / Chapter 7.2.5 --- Time Trend --- p.36 / Chapter 7.2.6 --- Duration Dummy --- p.37 / Chapter 7.2.7 --- Indicator for the Behavior of the Previous Trading Day --- p.38 / Chapter 8 --- Conclusion --- p.39

This thesis consists of three distinct parts. Part I introduces the basic concepts and the notion of general quadratic term structures (GQTS) essential in some of the following chapters. Part II focuses on credit risk models and Part III studies forward price term structure models using both the classical and the geometrical approach.  Part I is organized as follows. Chapter 1 is divided in two main sections. The first section presents some of the fundamental concepts which are a pre-requisite to the papers that follow. All of the concepts and results are well known and hence the section can be regarded as an introduction to notation and the basic principles of arbitrage theory. The second part of the chapter is of a more technical nature and its purpose is to summarize some key results on point processes or differential geometry that will be used later in the thesis. For finite dimensional factor models, Chapter 2 studies GQTS. These term structures include, as special cases, the affine term structures and Gaussian quadratic term structures previously studied in the literature. We show, however, that there are other, non-Gaussian, quadratic term structures and derive sufficient conditions for the existence of these GQTS for zero-coupon bond prices. On Part II we focus on credit risk models.   In Chapter 3 we propose a reduced form model for default that allows us to derive closed-form solutions for all the key ingredients in credit risk modeling: risk-free bond prices, defaultable bond prices (with and without stochastic recovery) and survival probabilities. We show that all these quantities can be represented in general exponential quadratic forms, despite the fact that the intensity of default is allowed to jump producing shot-noise effects. In addition, we show how to price defaultable digital puts, CDSs and options on defaultable bonds. Further on, we study a model for portfolio credit risk that considers both firm-specific and systematic risk. The model generalizes the attempt of Duffie and Garleanu (2001). We find that the model produces realistic default correlation and clustering effects. Next, we show how to price CDOs, options on CDOs and how to incorporate the link to currently proposed credit indices. In Chapter 4 we start by presenting a reduced-form multiple default type of model and derive abstract results on the influence of a state variable $X$ on credit spreads when both the intensity and the loss quota distribution are driven by $X$. The aim is to apply the results to a real life situation, namely, to the influence of macroeconomic risks on the term structure of credit spreads. There is increasing support in the empirical literature for the proposition that both the probability of default (PD) and the loss given default (LGD) are correlated and driven by macroeconomic variables. Paradoxically, there has been very little effort, from the theoretical literature, to develop credit risk models that would take this into account. One explanation might be the additional complexity this leads to, even for the ``treatable'' default intensity models. The goal of this paper is to develop the theoretical framework necessary to deal with this situation and, through numerical simulation, understand the impact of macroeconomic factors on the term structure of credit spreads. In the proposed setup, periods of economic depression are both periods of higher default intensity and lower recovery, producing a business cycle effect. Furthermore, we allow for the possibility of an index volatility that depends negatively on the index level and show that, when we include this realistic feature, the impacts on the credit spread term structure are emphasized. Part III studies forward price term structure models. Forward prices differ from futures prices in stochastic interest rate settings and become an interesting object of study in their own right. Forward prices with different maturities are martingales under different forward measures. This mathematical property implies that the term structure of forward prices is always linked to the term structure of bond prices, and this dependence makes forward price term structure models relatively harder to handle. For finite dimensional factor models, Chapter 5 applies the concept of GQTS to the term structure of forward prices. We show how the forward price term structure equation depends on the term structure of bond prices. We then exploit this connection and show that even in quadratic short rate settings we can have affine term structures for forward prices. Finally, we show how the study of futures prices is naturally embedded in the study of forward prices, that the difference between the two term structures may be deterministic in some (non-trivial) stochastic interest rate settings. In Chapter 6 we study a fairly general Wiener driven model for the term structure of forward prices. The model, under a fixed martingale measure, $\Q$, is described by using two infinite dimensional stochastic differential equations (SDEs). The first system is a standard HJM model for (forward) interest rates, driven by a multidimensional Wiener process $W$. The second system is an infinite SDE for the term structure of forward prices on some specified underlying asset driven by the same $W$. Since the zero coupon bond volatilities will enter into the drift part of the SDE for these forward prices, the interest rate system is needed as input to the forward price system. Given this setup, we use the Lie algebra methodology of Bj\o rk et al. to investigate under what conditions, on the volatility structure of the forward prices and/or interest rates, the inherently (doubly) infinite dimensional SDE for forward prices can be realized by a finite dimensional Markovian state space model. / Diss. Stockholm : Handelshögskolan, 2006

The issue of possibilities of real estate prices assessment for non-banking participants on financial market is solved in my Master’s thesis. The environment of non-banking participants on financial market is essentially defined here including description and division of it. In the survey there are the possibilities of real estate prices assessment together with the recommendation of the applicable methods. The practical part is included into my Master‘s thesis, too. The recommendation is applied here.

Thesis (MSc)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: We study Monte Carlo methods for pricing American options where the stock price dynamics follow exponential pure jump L évy models. Only stock price dynamics for a single underlying are considered. The thesis begins with a general introduction to American Monte Carlo methods. We then consider two classes of these methods. The fi rst class involves regression - we briefly consider the regression method of Tsitsiklis and Van Roy [2001] and analyse in detail the least squares Monte Carlo method of Longsta and Schwartz [2001]. The variance reduction techniques of Rasmussen [2005] applicable to the least squares Monte Carlo method, are also considered. The stochastic mesh method of Broadie and Glasserman [2004] falls into the second class we study. Furthermore, we consider the dual method, independently studied by Andersen and Broadie [2004], Rogers [2002] and Haugh and Kogan [March 2004] which generates a high bias estimate from a stopping rule. The rules we consider are estimates of the boundary between the continuation and exercise regions of the option. We analyse in detail how to obtain such an estimate in the least squares Monte Carlo and stochastic mesh methods. These models are implemented using both a pseudo-random number generator, and the preferred choice of a quasi-random number generator with bridge sampling. As a base case, these methods are implemented where the stock price process follows geometric Brownian motion. However the focus of the thesis is to implement the Monte Carlo methods for two pure jump L évy models, namely the variance gamma and the normal inverse Gaussian models. We first provide a broad discussion on some of the properties of L évy processes, followed by a study of the variance gamma model of Madan et al. [1998] and the normal inverse Gaussian model of Barndor -Nielsen [1995]. We also provide an implementation of a variation of the calibration procedure of Cont and Tankov [2004b] for these models. We conclude with an analysis of results obtained from pricing American options using these models. / AFRIKAANSE OPSOMMING: Ons bestudeer Monte Carlo metodes wat Amerikaanse opsies, waar die aandeleprys dinamika die patroon van die eksponensiële suiwer sprong L évy modelle volg, prys. Ons neem slegs aandeleprys dinamika vir 'n enkele aandeel in ag. Die tesis begin met 'n algemene inleiding tot Amerikaanse Monte Carlo metodes. Daarna bestudeer ons twee klasse metodes. Die eerste behels regressie - ons bestudeer die regressiemetode van Tsitsiklis and Van Roy [2001] vlugtig en analiseer die least squares Monte Carlo metode van Longsta and Schwartz [2001] in detail. Ons gee ook aandag aan die variansie reduksie tegnieke van Rasmussen [2005] wat van toepassing is op die least squares Monte Carlo metodes. Die stochastic mesh metode van Broadie and Glasserman [2004] val in die tweede klas wat ons onder oë neem. Ons sal ook aandag gee aan die dual metode, wat 'n hoë bias skatting van 'n stop reël skep, en afsonderlik deur Andersen and Broadie [2004], Rogers [2002] and Haugh and Kogan [March 2004] bestudeer is. Die reëls wat ons bestudeer is skattings van die grense tussen die voortsettings- en oefenareas van die opsie. Ons analiseer in detail hoe om so 'n benadering in die least squares Monte Carlo en stochastic mesh metodes te verkry. Hierdie modelle word geï mplementeer deur beide die pseudo kansgetalgenerator en die verkose beste quasi kansgetalgenerator met brug steekproefneming te gebruik. As 'n basisgeval word hierdie metodes geï mplimenteer wanneer die aandeleprysproses 'n geometriese Browniese beweging volg. Die fokus van die tesis is om die Monte Carlo metodes vir twee suiwer sprong L évy modelle, naamlik die variance gamma en die normal inverse Gaussian modelle, te implimenteer. Eers bespreek ons in breë trekke sommige van die eienskappe van L évy prossesse en vervolgens bestudeer ons die variance gamma model soos in Madan et al. [1998] en die normal inverse Gaussian model soos in Barndor -Nielsen [1995]. Ons gee ook 'n implimentering van 'n variasie van die kalibreringsprosedure deur Cont and Tankov [2004b] vir hierdie modelle. Ons sluit af met die resultate wat verkry is, deur Amerikaanse opsies met behulp van hierdie modelle te prys.

Thesis (MBA)--Stellenbosch University, 2000. / ENGLISH ABSTRACT: The price earnings multiple is a ratio of valuation and is published widely in the media as a comparative instrument of investment decisions. It is used to compare company valuation levels and their future growth/franchise opportunities. There have been numerous research studies done on the price earnings multiple, but no study has been able to design or derive a model to successfully predict the future price earnings multiple where the current stock price and following year-end earnings per share is used. The most widely accepted method of share valuation is to discount the future cash flows by an appropriate discount rate. Popular and widely used stock valuation models are the Dividend Discount Model and the Gordon Model. Both these models assume that future dividends are cash flows to the shareholder. Thomas K. Philips, the chief investment officer at Paradigm Asset Management in New York, constructed a valuation model at the end of 1999, which he published in The Journal of Portfolio Management. The model (Philips price earnings multiple model) was derived from the Dividend Discount Model and calculates an implied future price earnings multiple. The Philips price earnings multiple model includes the following independent variables: the cost of equity, the return on equity and the dividend payout ratio. Each variable in the Philips price earnings multiple model is a calculated present year-end point value, which was used to calculate the implied future price earnings multiple (present year stock price divided by following year-end earnings per share). This study used a historical five year (1995-2000) year-end data to calculate the implied and actual future price earnings multiple. Out of 225, Johannesburg Stock Exchange listed companies studied, only 36 were able to meet the criteria of the Philips price earnings multiple model. Correlation and population mean tests were conducted on the implied and constructed data sets. It proved that the Philips price earnings multiple model was unsuccesful in predicting the future price earnings multiple, at a statistical 0,20 level of significance. The Philips price earnings multiple model is substantially more complex than the Discount Dividend Model and includes greater restrictions and more assumptions. The Philips price earnings multiple model is a theoretical instrument which can be used to analyse hypothetical (with all model assumptions and restrictions having been met) companies. The Philips price earnings multiple model thus has little to no applicability in the practical valuation of stock price on Johannesburg Stock Exchange listed companies. / AFRIKAANSE OPSOMMING: Die prysverdienste verhouding is 'n waarde bepalingsverhouding en word geredelik gepubliseer in die media. Hierdie verhouding is 'n maatstaf om maatskappye se waarde vlakke te vergelyk en om toekomstige groei geleenthede te evalueer. Daar was al verskeie navorsingstudies gewy aan die prysverdiensteverhouding, maar nog geen model is ontwikkel wat die toekomstige prysverdiensteverhouding (die teenswoordige aandeelprys en toekomstige jaareind verdienste per aandeel) suksesvol kon modelleer nie. Die mees aanvaarbare metode vir waardebepaling van aandele is om toekomstige kontantvloeie te verdiskonteer teen 'n toepaslike verdiskonteringskoers. Van die vernaamste en mees gebruikte waardeberamings modelle is die Dividend Groei Model en die Gordon Model. Beide modelle gebruik die toekomstige dividendstroom as die toekomstige kontantvloeie wat uitbetaal word aan die aandeelhouers. Thomas K. Philips, die hoof beleggingsbeampte by Paradigm Asset Management in New York, het 'n waardeberamingsmodel ontwerp in 1999. Die model (Philips prysverdienste verhoudingsmodei) was afgelei vanaf die Dividend Groei Model en word gebruik om 'n geïmpliseerde toekomstige prysverdiensteverhouding te bereken. Die Philips prysverdienste verhoudingsmodel sluit die volgende onafhanklike veranderlikes in: die koste van kapitaal, die opbrengs op aandeelhouding en die uitbetalingsverhouding. Elke veranderlike in hierdie model is 'n berekende teenswoordige jaareinde puntwaarde, wat gebruik was om die toekomstige geïmpliseerde prysverdiensteverhouding (teenswoordige jaar aandeelprys gedeel deur die toekomstige verdienste per aandeel) te bereken. In hierdie studie word vyf jaar historiese jaareind besonderhede gebruik om die geïmpliseerde en werklike toekomstige prysverdiensteverhouding te bereken. Van die 225 Johannesburg Effektebeurs genoteerde maatskappye, is slegs 36 gebruik wat aan die vereistes voldoen om die Philips prysverdienste verhoudingsmodel te toets. Korrelasie en populasie gemiddelde statistiese toetse is op die berekende en geïmpliseerde data stelle uitgevoer en gevind dat die Philips prysverdienste verhoudingsmodel, teen 'n statistiese 0,20 vlak van beduidenheid, onsuksesvol was om die toekomstige prysverdiensteverhouding vooruit te skat. Die Philips prysverdienste verhoudingsmodel is meer kompleks as die Dividend Groei Model met meer aannames en beperkings. Die Philips prysverdienste verhoudingsmodel is 'n teoretiese instrument wat gebruik kan word om hipotetiese (alle model aannames en voorwaardes is nagekom) maatskappye te ontleed. Dus het die Philips prysverdienste verhoudingsmodel min tot geen praktiese toepassingsvermoë in die werkilke waardasie van aandele nie.

published_or_final_version / Urban Planning / Master / Master of Science in Urban Planning

Wong Hau Man, Ben. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 85-89). / Abstract / Acknowledgment / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Introduction to the Hang Seng Index Futures Market --- p.9 / Chapter Chapter 3. --- Dynamic Efficiency --- p.17 / Chapter 3.1 --- The Potential Lead/Lag Relationship between the Stock Index Futures price and the Stock Index --- p.18 / Chapter 3.2 --- Empirical Evidence of the Lead/Lag Relationship -the US experience --- p.20 / Chapter 3.3 --- Granger and Engle's Error-Correction Model --- p.21 / Chapter 3.4 --- Error-Correction Model for the Hang Seng Index Futures Price and Hang Seng Index --- p.25 / Chapter 3.5 --- Simultaneous Error-Correction Model --- p.30 / Chapter Chapter 4. --- Price Volatility --- p.38 / Chapter 4.1 --- Why Volatility Matters --- p.38 / Chapter 4.2a --- Theoretical Foundation of the relationship between Futures Trading and Cash Market Volatility --- p.39 / Chapter 4.2b --- Empirical Evidence of Futures Trading and Cash Market Volatility - the US experience --- p.40 / Chapter 4.3 --- The Schwert Estimation Method --- p.42 / Chapter 4.4 --- Hang Seng Index Volatility and Cash Market Trading Volume --- p.47 / Chapter 4.5 --- Hang Seng Index Volatility and Futures Trading Activities --- p.48 / Chapter 4.6 --- Hang Seng Index Volatility and Contract Life Cycle --- p.50 / Chapter Chapter 5. --- Margin Policy --- p.56 / Chapter 5.1 --- The Economic Role of Futures Margin --- p.57 / Chapter 5.2a --- Theoretical Foundation of the relationship between Margin Requirement and Futures Volatility --- p.58 / Chapter 5.2b --- Empirical Evidence of Margin Requirement and Price Volatility --- p.59 / Chapter 5.3 --- HSI Futures Margin Requirement and Probability of Exhaustion --- p.61 / Chapter 5.4 --- HSI Futures Margin Requirement and HSI Futures Volatility --- p.64 / Chapter 5.4a --- Event-Study Approach --- p.64 / Chapter 5.4b --- Alternative Method --- p.66 / Chapter 5.5 --- HSI Futures Leverage and Price Volatility --- p.70 / Chapter Chapter 6. --- Conclusions --- p.81 / REFERENCES --- p.85 / APPENDIX 1. - Data Description --- p.90 / APPENDIX 2. - FIGURES --- p.92 / Chapter - --- Figure 1. Trend of HSI from May 86 to Dec93 --- p.93 / Chapter - --- Figure 2. Trend of HSI Futures Price from May 86 to Dec93 --- p.94 / Chapter - --- Figure 3. Volatility of HSI from May 86 to Dec93 --- p.95 / Chapter - --- Figure 4. HSI Futures Margin and Futures Volatility (Futures volatility is measured in daily change in contracts value) --- p.96