Dissertations / Theses on the topic 'Options (Finance) – Valuation – Mathematical models'
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Mimouni, 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.
Dharmawan, 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 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.
Endekovski, Jessica. "Pricing multi-asset options in exponential levy models." Master's thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/31437.
Full textGlover, Elistan Nicholas. "Analytic pricing of American put options." Thesis, Rhodes University, 2009. http://hdl.handle.net/10962/d1002804.
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.
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Lee, 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 textZhao, Jing Ya. "Numerical methods for pricing Bermudan barrier options." Thesis, University of Macau, 2012. http://umaclib3.umac.mo/record=b2592939.
Full textCisneros-Molina, Myriam. "Mathematical methods for valuation and risk assessment of investment projects and real options." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491350.
Full textWelihockyj, 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 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 textMontsho, Obakeng Johannes. "Real options valuation for South African nuclear waste management using a fuzzy mathematical approach." Thesis, Rhodes University, 2013. http://hdl.handle.net/10962/d1003051.
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Nhongo, Tawuya D. R. "Pricing exotic options using C++." Thesis, Rhodes University, 2007. http://hdl.handle.net/10962/d1008373.
Full text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 textLe, Truc. "Stochastic volatility models." Monash University, School of Mathematical Sciences, 2005. http://arrow.monash.edu.au/hdl/1959.1/5181.
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 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 textCheng, Xin. "Three essays on volatility forecasting." HKBU Institutional Repository, 2010. http://repository.hkbu.edu.hk/etd_ra/1183.
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 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 textYiu, 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 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 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 textChavanasporn, Walailuck. "Application of stochastic differential equations and real option theory in investment decision problems." Thesis, University of St Andrews, 2010. http://hdl.handle.net/10023/1691.
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.
Huang, Ning Ying. "Numerical methods for early-exercise option pricing via Fourier analysis." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2148270.
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 textU, Sio Chong. "The applications of Fourier analysis to European option pricing." Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b2148263.
Full textMboussa, Anga Gael. "Calibration and Model Risk in the Pricing of Exotic Options Under Pure-Jump Lévy Dynamics." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/98030.
Full textAFRIKAANSE OPSOMMING : Die groeiende belangstelling in kalibrering en modelrisiko is ’n redelik resente ontwikkeling in finansiële wiskunde. Hierdie proefskrif fokusseer op hierdie sake, veral in verband met die prysbepaling van vanielje-en eksotiese opsies, en vergelyk die prestasie van verskeie Lévy modelle. ’n Nuwe metode om modelrisiko te meet word ook voorgestel (hoofstuk 6). Ons kalibreer eers verskeie Lévy modelle aan die log-opbrengs van die S&P500 indeks. Statistiese toetse en grafieke voorstellings toon albei aan dat suiwer sprongmodelle (VG, NIG en CGMY) die verdeling van die opbrengs beter beskryf as die Black-Scholes model. Daarna kalibreer ons hierdie vier modelle aan S&P500 indeks opsie data en ook aan "CGMY-wˆ ereld" data (’n gesimuleerde wÃłreld wat beskryf word deur die CGMY-model) met behulp van die wortel van gemiddelde kwadraat fout. Die CGMY model vaar beter as die VG, NIG en Black-Scholes modelle. Ons waarneem ook ’n effense verskil tussen die nuwe parameters van CGMY model en sy wisselende parameters, ten spyte van die feit dat CGMY model gekalibreer is aan die "CGMYwêreld" data. Versperrings-en terugblik opsies word daarna geprys, deur gebruik te maak van die gekalibreerde parameters vir ons modelle. Hierdie pryse word dan vergelyk met die "ware" pryse (bereken met die ware parameters van die "CGMY-wêreld), en ’n beduidende verskil tussen die modelpryse en die "ware" pryse word waargeneem. Ons eindig met ’n poging om hierdie modelrisiko te kwantiseer
ENGLISH ABSTRACT : The growing interest in calibration and model risk is a fairly recent development in financial mathematics. This thesis focussing on these issues, particularly in relation to the pricing of vanilla and exotic options, and compare the performance of various Lévy models. A new method to measure model risk is also proposed (Chapter 6). We calibrate only several Lévy models to the log-return of S&P500 index data. Statistical tests and graphs representations both show that pure jump models (VG, NIG and CGMY) the distribution of the proceeds better described as the Black-Scholes model. Then we calibrate these four models to the S&P500 index option data and also to "CGMY-world" data (a simulated world described by the CGMY model) using the root mean square error. Which CGMY model outperform VG, NIG and Black-Scholes models. We observe also a slight difference between the new parameters of CGMY model and its varying parameters, despite the fact that CGMY model is calibrated to the "CGMY-world" data. Barriers and lookback options are then priced, making use of the calibrated parameters for our models. These prices are then compared with the "real" prices (calculated with the true parameters of the "CGMY world), and a significant difference between the model prices and the "real" rates are observed. We end with an attempt to quantization this model risk.
Lee, 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 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.
Rich, 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 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 textDiallo, Ibrahima. "Some topics in mathematical finance: Asian basket option pricing, Optimal investment strategies." Doctoral thesis, Universite Libre de Bruxelles, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210165.
Full textIn Chapter 2, we concentrate upon the derivation of bounds for European-style discrete arithmetic Asian basket options in a Black and Scholes framework.We start from methods used for basket options and Asian options. First, we use the general approach for deriving upper and lower bounds for stop-loss premia of sums of non-independent random variables as in Kaas et al. [Upper and lower bounds for sums of random variables, Insurance Math. Econom. 27 (2000) 151–168] or Dhaene et al. [The concept of comonotonicity in actuarial science and finance: theory, Insurance Math. Econom. 31(1) (2002) 3–33]. We generalize the methods in Deelstra et al. [Pricing of arithmetic basket options by conditioning, Insurance Math. Econom. 34 (2004) 55–57] and Vanmaele et al. [Bounds for the price of discrete sampled arithmetic Asian options, J. Comput. Appl. Math. 185(1) (2006) 51–90]. Afterwards we show how to derive an analytical closed-form expression for a lower bound in the non-comonotonic case. Finally, we derive upper bounds for Asian basket options by applying techniques as in Thompson [Fast narrow bounds on the value of Asian options, Working Paper, University of Cambridge, 1999] and Lord [Partially exact and bounded approximations for arithmetic Asian options, J. Comput. Finance 10 (2) (2006) 1–52]. Numerical results are included and on the basis of our numerical tests, we explain which method we recommend depending on moneyness and time-to-maturity
In Chapter 3, we propose some moment matching pricing methods for European-style discrete arithmetic Asian basket options in a Black & Scholes framework. We generalize the approach of Curran M. (1994) [Valuing Asian and portfolio by conditioning on the geometric mean price”, Management science, 40, 1705-1711] and of Deelstra G. Liinev J. and Vanmaele M. (2004) [Pricing of arithmetic basket options by conditioning”, Insurance: Mathematics & Economics] in several ways. We create a framework that allows for a whole class of conditioning random variables which are normally distributed. We moment match not only with a lognormal random variable but also with a log-extended-skew-normal random variable. We also improve the bounds of Deelstra G. Diallo I. and Vanmaele M. (2008). [Bounds for Asian basket options”, Journal of Computational and Applied Mathematics, 218, 215-228]. Numerical results are included and on the basis of our numerical tests, we explain which method we recommend depending on moneyness and
time-to-maturity.
In Chapter 4, we use the stochastic dynamic programming approach in order to extend
Brennan and Xia’s unconstrained optimal portfolio strategies by investigating the case in which interest rates and inflation rates follow affine dynamics which combine the model of Cox et al. (1985) [A Theory of the Term Structure of Interest Rates, Econometrica, 53(2), 385-408] and the model of Vasicek (1977) [An equilibrium characterization of the term structure, Journal of Financial Economics, 5, 177-188]. We first derive the nominal price of a zero coupon bond by using the evolution PDE which can be solved by reducing the problem to the solution of three ordinary differential equations (ODE). To solve the corresponding control problems we apply a verification theorem without the usual Lipschitz assumption given in Korn R. and Kraft H.(2001)[A Stochastic control approach to portfolio problems with stochastic interest rates, SIAM Journal on Control and Optimization, 40(4), 1250-1269] or Kraft(2004)[Optimal Portfolio with Stochastic Interest Rates and Defaultable Assets, Springer, Berlin].
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
Cozma, Andrei. "Numerical methods for foreign exchange option pricing under hybrid stochastic and local volatility models." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:44a27fbc-1b7a-4f1a-bd2d-abeb38bf1ff7.
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 textWang, Wen-Kai. "Application of stochastic differential games and real option theory in environmental economics." Thesis, University of St Andrews, 2009. http://hdl.handle.net/10023/893.
Full textCalcraft, Peter James. "Two-pore channels and NAADP-dependent calcium signalling." Thesis, St Andrews, 2010. http://hdl.handle.net/10023/888.
Full textSewambar, Soraya. "The theory of option valuation." Thesis, 1992. http://hdl.handle.net/10413/7830.
Full textThesis (M.Sc.)-University of Natal, 1992.
Choi, Byeongwook. "Numerical methods for the valuation of American options under jump-diffusion processes." Thesis, 2002. http://wwwlib.umi.com/cr/utexas/fullcit?p3099434.
Full text"Dynamic options portfolio selection." 2003. http://library.cuhk.edu.hk/record=b5891531.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaves 58-59).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Overview --- p.1
Chapter 1.2 --- Organization Outline --- p.4
Chapter 2 --- Literature Review --- p.5
Chapter 2.1 --- Option --- p.5
Chapter 2.1.1 --- The definition of option --- p.5
Chapter 2.1.2 --- Payoff of Options --- p.6
Chapter 2.1.3 --- Black-Scholes Option Pricing Model --- p.7
Chapter 2.1.4 --- Binomial Model --- p.12
Chapter 2.2 --- Portfolio Theory --- p.15
Chapter 2.2.1 --- The Markowitz Mean-Variance Model --- p.15
Chapter 2.2.2 --- Multi-period Mean-Variance Formulation --- p.17
Chapter 3 --- Multi-Period Options Portfolio Selection Model with Guaran- teed Return --- p.20
Chapter 3.1 --- Problem Formulation --- p.20
Chapter 3.2 --- Solution Algorithm Using Dynamic Programming --- p.25
Chapter 3.3 --- Numerical Example --- p.27
Chapter 4 --- Mean-Variance Formulation of Options Portfolio --- p.36
Chapter 4.1 --- The Problem Formulation --- p.36
Chapter 4.2 --- Solution Algorithm Using Dynamic Programming --- p.39
Chapter 4.3 --- Numerical Example --- p.41
Chapter 5 --- Summary --- p.56
"A study on options hedge against purchase cost fluctuation in supply contracts." 2008. http://library.cuhk.edu.hk/record=b5893550.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2008.
Includes bibliographical references (leaves 44-48).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Motivation --- p.1
Chapter 1.2 --- Literature Review --- p.4
Chapter 1.2.1 --- Supply Contracts under Price Uncertainty --- p.5
Chapter 1.2.2 --- Dual Sourcing --- p.6
Chapter 1.2.3 --- Risk Aversion in Inventory Management --- p.6
Chapter 1.2.4 --- Hedging Operational Risk Using Financial Instruments --- p.7
Chapter 1.2.5 --- Financial Literature --- p.9
Chapter 1.3 --- Organization of the Thesis --- p.10
Chapter 2 --- A Risk-Neutral Model --- p.12
Chapter 2.1 --- Framework and Assumptions --- p.12
Chapter 2.2 --- "Price, Forward and Convenience Yield" --- p.14
Chapter 2.2.1 --- Stochastic Model of Price --- p.14
Chapter 2.2.2 --- Marginal Convenience Yield --- p.16
Chapter 2.3 --- Optimality Equations --- p.17
Chapter 2.4 --- The Structure of the Optimal Policy --- p.21
Chapter 2.4.1 --- One-period. Optimal Hedge Decision Rule --- p.21
Chapter 2.4.2 --- One-period Optimal Orderings Decision Rule --- p.23
Chapter 2.4.3 --- Optimal Policy --- p.24
Chapter 3 --- A Risk-Averse Model --- p.28
Chapter 3.1 --- Risk Aversion Modeling and Utility Function --- p.28
Chapter 3.2 --- Multi-Period Inventory Modelling --- p.31
Chapter 3.3 --- Exponential Utility Model --- p.33
Chapter 3.4 --- Optimal Ordering and Hedging Policy for Multi-Period Problem --- p.37
Chapter 4 --- Conclusion and Future Research --- p.40
Bibliography --- p.44
Chapter A --- Appendix --- p.49
Chapter A.l --- Notation --- p.49
Chapter A.2 --- K-Concavity --- p.50
"Fractional volatility models and malliavin calculus." 2004. http://library.cuhk.edu.hk/record=b5892022.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2004.
Includes bibliographical references (leaves 110-114).
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 --- Self-financing 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 Inner-Product 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 --- S-Transformation Approach --- p.84
Chapter B.2 --- Relationship between Three Types of Stochastic Integral --- p.89
Reference --- p.90
"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
"The value of put option to the newsvendor." 2003. http://library.cuhk.edu.hk/record=b5896094.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaves 66-69).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Notation and Model --- p.8
Chapter 2.1 --- Notation --- p.9
Chapter 2.2 --- Classical News vendor Model --- p.11
Chapter 2.3 --- The Price of the Put Option --- p.12
Chapter 2.4 --- Extended Models with the Option --- p.13
Chapter 3 --- Literature Review --- p.16
Chapter 4 --- Objective I ´ؤ Maximizing Expected Profit --- p.24
Chapter 4.1 --- Single Decision Variable Case: K = Q --- p.24
Chapter 4.2 --- Two Decision Variable Case: K ≤Q --- p.25
Chapter 4.3 --- Summary of the Chapter --- p.28
Chapter 5 --- Objective II ´ؤ Maximizing the Probability of Achieving A Target Profit --- p.30
Chapter 5.1 --- Single Decision Variable Case: K = Q --- p.30
Chapter 5.2 --- Two Decision Variable Case: K ≤ Q --- p.37
Chapter 5.3 --- Numerical Examples --- p.38
Chapter 5.4 --- Summary of the Chapter --- p.41
Chapter 6 --- Objective III ´ؤ Minimizing Profit Variance --- p.43
Chapter 6.1 --- Minimizing Profit Variance through R --- p.44
Chapter 6.2 --- Minimizing Profit Variance through K --- p.51
Chapter 6.2.1 --- Special Case R = s --- p.54
Chapter 6.3 --- Summary of the Chapter --- p.60
Chapter 7 --- Conclusion --- p.63
Bibliography --- p.69
"General diffusions: financial applications, analysis and extension." Thesis, 2010. http://library.cuhk.edu.hk/record=b6074923.
Full textZhao, 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.
Abstract also in Chinese.