Dissertations / Theses on the topic 'Options (Finance) – Prices – Mathematical models'
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Glover, Elistan Nicholas. "Analytic pricing of American put options." Thesis, Rhodes University, 2009. http://hdl.handle.net/10962/d1002804.
Full textLee, Mou Chin. "An empirical test of variance gamma options pricing model on Hang Seng index options." HKBU Institutional Repository, 2000. http://repository.hkbu.edu.hk/etd_ra/263.
Full textSong, Na, and 宋娜. "Mathematical models and numerical algorithms for option pricing and optimal trading." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50662168.
Full textpublished_or_final_version
Mathematics
Doctoral
Doctor of Philosophy
Zhao, Jing Ya. "Numerical methods for pricing Bermudan barrier options." Thesis, University of Macau, 2012. http://umaclib3.umac.mo/record=b2592939.
Full textDharmawan, Komang School of Mathematics UNSW. "Superreplication method for multi-asset barrier options." Awarded by:University of New South Wales. School of Mathematics, 2005. http://handle.unsw.edu.au/1959.4/30169.
Full textMimouni, Karim. "Three essays on volatility specification in option valuation." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103274.
Full textIn the second essay, we estimate the Constant Elasticity of Variance (CEV) model in order to study the level of nonlinearity in the volatility dynamic. We also estimate a CEV process combined with a jump process (CEVJ) and analyze the effects of the jump component on the nonlinearity coefficient. Estimation is performed using the particle filtering technique on a long series of S&P500 returns and on options data. We find that both returns data and returns-and-options data favor nonlinear specifications for the volatility dynamic, suggesting that the extensive use of linear models is not supported empirically. We also find that the inclusion of jumps does not affect the level of nonlinearity and does not improve the CEV model fit.
The third essay provides an empirical comparison of two classes of option valuation models: continuous-time models and discrete-time models. The literature provides some theoretical limit results for these types of dynamics, and researchers have used these limit results to argue that the performance of certain discrete-time and continuous-time models ought to be very similar. This interpretation is somewhat contentious, because a given discrete-time model can have several continuous-time limits, and a given continuous-time model can be the limit for more than one discrete-time model. Therefore, it is imperative to investigate whether there exist similarities between these specifications from an empirical perspective. Using data on S&P500 returns and call options, we find that the discrete-time models investigated in this paper have the same performance in fitting the data as selected continuous-time models both in and out-of-sample.
劉伯文 and Pak-man Lau. "Option pricing: a survey." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1994. http://hub.hku.hk/bib/B31977911.
Full textChan, Ka Hou. "European call option pricing under partial information." Thesis, University of Macau, 2017. http://umaclib3.umac.mo/record=b3691380.
Full textOagile, Joel. "Sequential Calibration of Asset Pricing Models to Option Prices." Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29840.
Full text蕭德權 and Tak-kuen Siu. "Risk measures in finance and insurance." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31242297.
Full textWang, Yintian 1976. "Three essays on volatility long memory and European option valuation." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102851.
Full textThe first essay presents a new model for the valuation of European options. In this model, the volatility of returns consists of two components. One of these components is a long-run component that can be modeled as fully persistent. The other component is short-run and has zero mean. The model can be viewed as an affine version of Engle and Lee (1999), allowing for easy valuation of European options. The model substantially outperforms a benchmark single-component volatility model that is well established in the literature. It also fits options better than a model that combines conditional heteroskedasticity and Poisson normal jumps. While the improvement in the component model's performance is partly due to its improved ability to capture the structure of the smirk and the path of spot volatility, its most distinctive feature is its ability to model the term structure. This feature enables the component model to jointly model long-maturity and short-maturity options.
The second essay derives two new GARCH variance component models with non-normal innovations. One of these models has an affine structure and leads to a closed-form option valuation formula. The other model has a non-affine structure and hence, option valuation is carried out using Monte Carlo simulation. We provide an empirical comparison of these two new component models and the respective special cases with normal innovations. We also compare the four component models against GARCH(1,1) models which they nest. All eight models are estimated using MLE on S&P500 returns. The likelihood criterion strongly favors the component models as well as non-normal innovations. The properties of the non-affine models differ significantly from those of the affine models. Evaluating the performance of component variance specifications for option valuation using parameter estimates from returns data also provides strong support for component models. However, support for non-normal innovations and non-affine structure is less convincing for option valuation.
The third essay aims to investigate the impact of long memory in volatility on European option valuation. We mainly compare two groups of GARCH models that allow for long memory in volatility. They are the component Heston-Nandi GARCH model developed in the first essay, in which the volatility of returns consists of a long-run and a short-run component, and a fractionally integrated Heston-Nandi GARCH (FIHNGARCH) model based on Bollerslev and Mikkelsen (1999). We investigate the performance of the models using S&P500 index returns and cross-sections of European options data. The component GARCH model slightly outperforms the FIGARCH in fitting return data but significantly dominates the FIHNGARCH in capturing option prices. The findings are mainly due to the shorter memory of the FIHNGARCH model, which may be attributed to an artificially prolonged leverage effect that results from fractional integration and the limitations of the affine structure.
Le, Truc. "Stochastic volatility models." Monash University, School of Mathematical Sciences, 2005. http://arrow.monash.edu.au/hdl/1959.1/5181.
Full textAu, Chi Yan. "Numerical methods for solving Markov chain driven Black-Scholes model." HKBU Institutional Repository, 2010. http://repository.hkbu.edu.hk/etd_ra/1154.
Full textWest, Lydia. "American Monte Carlo option pricing under pure jump levy models." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/79994.
Full textENGLISH 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.
Yiu, Fan-lai, and 姚勳禮. "Applicability of various option pricing models in Hong Kong warrants market." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B3126590X.
Full textWeng, Zuo Qiu. "Pricing discretely monitored barrier options via a fast and accurate FFT-based method." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2148272.
Full textU, Sio Chong. "The applications of Fourier analysis to European option pricing." Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b2148263.
Full textChu, Kut-leung, and 朱吉樑. "The CEV model: estimation and optionpricing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B4257500X.
Full textNg, Man Yun. "Quasi-Monte Carlo methods and their applications in high dimensional option pricing." Thesis, University of Macau, 2011. http://umaclib3.umac.mo/record=b2493256.
Full textLee, Tsz Ho. "High order compact scheme and its applications in computational finance." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2148266.
Full textLiu, Xin. "Fast exponential time integration scheme and extrapolation method for pricing option with jump diffusions." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2148264.
Full text高志強 and Chi-keung Anthony Ko. "A preliminary study of Hong Kong warrants using the Black-Scholesoption pricing model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1985. http://hub.hku.hk/bib/B31263227.
Full textLam, Yue-kwong, and 林宇光. "A revisit to the applicability of option pricing models on the Hong Kong warrants market after the stock option is introduced." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31267282.
Full textHuang, Ning Ying. "Numerical methods for early-exercise option pricing via Fourier analysis." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2148270.
Full textLee, Jinpyo. "A method for distribution network design and models for option-contracting strategy with buyers' learning." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/29620.
Full textCommittee Chair: Kleywegt, Anton J.; Committee Member: Ayhan, Hayriye; Committee Member: Dai, Jim; Committee Member: Erera, Alan; Committee Member: Ward, Amy R. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Cheng, Xin. "Three essays on volatility forecasting." HKBU Institutional Repository, 2010. http://repository.hkbu.edu.hk/etd_ra/1183.
Full textRich, Don R. "Incorporating default risk into the Black-Scholes model using stochastic barrier option pricing theory." Diss., This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-06062008-171359/.
Full textLee, Chi-ming Simon, and 李志明. "A study of Hong Kong foreign exchange warrants pricing using black-scholes formula." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1992. http://hub.hku.hk/bib/B3126542X.
Full textLi, Wen. "Numerical methods for the solution of the HJB equations arising in European and American option pricing with proportional transaction costs." University of Western Australia. School of Mathematics and Statistics, 2010. http://theses.library.uwa.edu.au/adt-WU2010.0098.
Full textBlix, Magnus. "Essays in mathematical finance : modeling the futures price." Doctoral thesis, Handelshögskolan i Stockholm, Finansiell Ekonomi (FI), 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-534.
Full textDiss. Stockholm : Handelshögskolan, 2004
Endekovski, Jessica. "Pricing multi-asset options in exponential levy models." Master's thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/31437.
Full textYuen, Fei-lung, and 袁飛龍. "Pricing options and equity-indexed annuities in regime-switching models by trinomial tree method." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B45595616.
Full textHao, Fangcheng, and 郝方程. "Options pricing and risk measures under regime-switching models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B4714726X.
Full textCheng, Lap-yan, and 鄭立仁. "Extension of price-trend models with applications in finance." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B37428408.
Full text任尚智 and Sheung-chi Phillip Yam. "Algebraic methods on some problems in finance." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B3122698X.
Full textMerino, Fernández Raúl. "Option Price Decomposition for Local and Stochastic Volatility Jump Diffusion Models." Doctoral thesis, Universitat de Barcelona, 2021. http://hdl.handle.net/10803/671682.
Full textEn aquesta tesi, s'estudia una descomposició del preu d'una opció per a models de volatilitat local i volatilitat estocàstica amb salts. D'una banda, generalitzem i estenem la descomposició d'Alòs per a ser utilitzada en una àmplia varietat de models com, per exemple, un model de volatilitat estocàstica general, un model de volatilitat estocàstica amb salts d'activitat finita o un model de volatilitat 'rough'. A més a més, veiern que en el cas dels models de volatilitat local, en particular, els models dependents del 'spot' s'ha d'utilitzar una nova fórmula de descomposició per a obtenir bons resultats numèrics. En particular, estudiem el model CEV. D'altra banda, observem que la fórmula d'aproximació es pot millorar utilitzant la formula de descomposició de forma recursiva. Mitjançant aquesta tècnica de descomposició, el preu d'una opció de compra es pot transformar en una formula tipus Taylor que conté una sèrie infinita de termes estocàstics. S'obtenen noves fórmules d'aproximació en el cas del model de Heston, trobant una millor aproximació.
En esta tesis, se estudia una descomposición del precio de una opción para los modelos de volatilidad local y volatilidad estocástica con saltos. Por un lado, generalizamos y ampliamos la descomposición de Alòs para ser utilizada en una amplia variedad de modelos como, por ejemplo, un modelo de volatilidad estocástica general, un modelo de volatilidad estocástica con saltos de actividad finita o un modelo de volatilidad 'rough'. Además, vemos que en el caso de los modelos de volatilidad local, en particular, los modelos dependientes del 'spot', se debe utilizar una nueva fórmula de descomposición para obtener buenos resultados numéricos. En particular, estudiamos el modelo CEV. Por otro lado, observamos que la fórmula de aproximación se puede mejorar utilizando la fórmula de descomposición de forma recursiva. Mediante esta técnica de descomposición, el precio de una opción de compra se puede transformar en una fórmula tipo Taylor que contiene una serie infinita de términos estocásticos. Se obtienen nuevas fórmulas de aproximación en el caso del modelo de Heston, encontrando una mejor aproximación.
Welihockyj, Alexander. "The cost of using misspecified models to exercise and hedge American options on coupon bearing bonds." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/20532.
Full textWei, Yong, and 卫勇. "The real effects of S&P 500 Index additions: evidence from corporate investment." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B4490681X.
Full textArroyo, Jorge M. "Money and the dispersion of relative prices in the drug and apparel industries." Thesis, Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/28574.
Full textNhongo, Tawuya D. R. "Pricing exotic options using C++." Thesis, Rhodes University, 2007. http://hdl.handle.net/10962/d1008373.
Full textChau, Irene. "An empirical comparison using both the term structure of interest rates and alternative models in pricing options on 90-day BAB futures." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 1999. https://ro.ecu.edu.au/theses/1207.
Full textGleeson, Cameron Banking & Finance Australian School of Business UNSW. "Pricing and hedging S&P 500 index options : a comparison of affine jump diffusion models." Awarded by:University of New South Wales. School of Banking and Finance, 2005. http://handle.unsw.edu.au/1959.4/22379.
Full textLi, Chao. "Option pricing with generalized continuous time random walk models." Thesis, Queen Mary, University of London, 2016. http://qmro.qmul.ac.uk/xmlui/handle/123456789/23202.
Full textYsusi, Mendoza Carla Mariana. "Estimation of the variation of prices using high-frequency financial data." Thesis, University of Oxford, 2005. http://ora.ox.ac.uk/objects/uuid:1b520271-2a63-428d-b5a0-e7e9c4afdc66.
Full textHoffmeyer, Allen Kyle. "Small-time asymptotics of call prices and implied volatilities for exponential Lévy models." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53506.
Full textGong, Ruoting. "Small-time asymptotics and expansions of option prices under Levy-based models." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44798.
Full text"American options pricing with mixed effects model." 2009. http://library.cuhk.edu.hk/record=b5894182.
Full textThesis (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
"Trading in options: an in-depth analysis." 1999. http://library.cuhk.edu.hk/record=b5889494.
Full textThesis (M.B.A.)--Chinese University of Hong Kong, 1999.
Includes bibliographical references (leaves 66-67).
ABSTRACT --- p.ii
TABLE OF CONTENTS --- p.ii
LIST OF TABLES --- p.vi
LIST OF EXHIBITS --- p.vii
PREFACE --- p.viii
ACKNOWLEDGMENTS --- p.x
Chapter
Chapter I. --- INTRODUCTION --- p.1
What is an Option? --- p.1
Options Market --- p.2
Uses of Options --- p.2
Value of Options --- p.3
Index Options --- p.4
Hang Seng Index Options --- p.4
Chapter II. --- BASIC PROPERTIES OF OPTIONS --- p.5
Assumptions --- p.5
Notation --- p.5
Option Prices at Expiration --- p.6
Call Option Prices at Expiration --- p.6
Put Option Prices at Expiration --- p.6
Upper Bounds for Option Prices --- p.6
Upper Bounds for Call Option Prices --- p.6
Upper Bounds for Put Option Prices --- p.6
Lower Bounds for European Option Prices --- p.7
Lower Bounds for European Call Option Prices --- p.7
Lower Bounds for European Put Option Prices --- p.8
Put-Call Parity --- p.8
Chapter III. --- FACTORS AFFECTING OPTION PRICES --- p.10
Price of Underlying Instrument --- p.10
Exercise Price of the Option --- p.10
Volatility of the Price of Underlying Instrument --- p.11
Time to Expiration --- p.11
Risk-free Rate --- p.11
Dividends --- p.12
Chapter IV. --- OPTION PRICING MODEL --- p.13
Assumptions --- p.13
The Price of Underlying Instrument Follows a Lognormal Distribution --- p.13
The Variance of the Rate of Return of Underlying Instrument is a Constant --- p.17
The Risk-free Rate is a Constant --- p.19
No Dividends are Paid --- p.20
There are No Transaction Costs and Taxes --- p.20
The Black-Scholes Option Pricing Model --- p.21
Notation --- p.21
The Formulas --- p.21
The Variables --- p.22
Properties of the Black-Scholes Formulas --- p.22
Implied Volatility --- p.23
Bias of the Black-Scholes Option Pricing Model --- p.26
Other Option Pricing Models。……………… --- p.27
Chapter V. --- SENSITIVITIES OF OPTION PRICE TO ITS FACTORS --- p.29
Delta --- p.29
Vega --- p.30
Theta --- p.31
Rho --- p.32
Gamma --- p.33
Managing the Change in the Value of Option --- p.34
Sensitivities of Portfolio Value to the Factors --- p.34
Chapter VI. --- TRADING STRATEGIES OF OPTIONS --- p.35
Methodology --- p.35
Limitations --- p.36
Basic Strategies --- p.37
Long Call --- p.37
Short Call --- p.39
Long Put --- p.40
Short Put --- p.42
Spread Strategies --- p.43
Money Spread --- p.43
Ratio Spread --- p.46
Box Spread --- p.46
Butterfly Spread --- p.46
Condor --- p.49
Calendar Spread --- p.49
Diagonal Spread --- p.52
Combination Strategies --- p.52
Straddle --- p.52
Strap --- p.54
Strip --- p.54
Strangle --- p.54
Selecting Trading Strategies Intelligently --- p.56
Chapter VII. --- CONCLUSIONS --- p.57
APPENDICES --- p.60
BIBLIOGRAPHY --- p.66
"Quanto options under double exponential jump diffusion." 2007. http://library.cuhk.edu.hk/record=b5893201.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2007.
Includes bibliographical references (leaves 78-79).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Background --- p.5
Chapter 2.1 --- Jump Diffusion Models --- p.6
Chapter 2.2 --- Double Exponential Jump Diffusion Model --- p.8
Chapter 3 --- Option Pricing with DEJD --- p.10
Chapter 3.1 --- Laplace Transform --- p.10
Chapter 3.2 --- European Option Pricing --- p.13
Chapter 3.3 --- Barrier Option Pricing --- p.14
Chapter 3.4 --- Lookback Options --- p.16
Chapter 3.5 --- Turbo Warrant --- p.17
Chapter 3.6 --- Numerical Examples --- p.26
Chapter 4 --- Quanto Options under DEJD --- p.30
Chapter 4.1 --- Domestic Risk-neutral Dynamics --- p.31
Chapter 4.2 --- The Exponential Copula --- p.33
Chapter 4.3 --- The moment generating function --- p.36
Chapter 4.4 --- European Quanto Options --- p.38
Chapter 4.4.1 --- Floating Exchange Rate Foreign Equity Call --- p.38
Chapter 4.4.2 --- Fixed Exchange Rate Foreign Equity Call --- p.40
Chapter 4.4.3 --- Domestic Foreign Equity Call --- p.42
Chapter 4.4.4 --- Joint Quanto Call --- p.43
Chapter 4.5 --- Numerical Examples --- p.45
Chapter 5 --- Path-Dependent Quanto Options --- p.48
Chapter 5.1 --- The Domestic Equivalent Asset --- p.48
Chapter 5.1.1 --- Mathematical Results on the First Passage Time of the Mixture Exponential Jump Diffusion Model --- p.50
Chapter 5.2 --- Quanto Lookback Option --- p.54
Chapter 5.3 --- Quanto Barrier Option --- p.57
Chapter 5.4 --- Numerical results --- p.61
Chapter 6 --- Conclusion --- p.64
Chapter A --- Numerical Laplace Inversion for Turbo Warrants --- p.66
Chapter B --- The Relation Among Barrier Options --- p.69
Chapter C --- Proof of Lemma 51 --- p.71
Chapter D --- Proof of Theorem 5.4 and 5.5 --- p.74
Bibliography --- p.78
"A numerical method for American option pricing under CEV model." 2007. http://library.cuhk.edu.hk/record=b5893177.
Full textThesis (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