Academic literature on the topic 'Options (Finance) – Valuation – Mathematical models'
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Journal articles on the topic "Options (Finance) – Valuation – Mathematical models"
Loerx, Andre, and Ekkehard W. Sachs. "Model Calibration in Option Pricing." Sultan Qaboos University Journal for Science [SQUJS] 16 (April 1, 2012): 84. http://dx.doi.org/10.24200/squjs.vol17iss1pp84-102.
Full textHUEHNE, FLORIAN. "DEFAULTABLE LÉVY LIBOR RATES AND CREDIT DERIVATIVES." International Journal of Theoretical and Applied Finance 10, no. 03 (May 2007): 407–35. http://dx.doi.org/10.1142/s0219024907004172.
Full textGiribone, Pier Giuseppe, and Roberto Revetria. "Certificate pricing using Discrete Event Simulations and System Dynamics theory." Risk Management Magazine 16, no. 2 (August 18, 2021): 75–93. http://dx.doi.org/10.47473/2020rmm0092.
Full textLORENZO, MERCURI. "PRICING ASIAN OPTIONS IN AFFINE GARCH MODELS." International Journal of Theoretical and Applied Finance 14, no. 02 (March 2011): 313–33. http://dx.doi.org/10.1142/s0219024911006371.
Full textCHU, CHI CHIU, and YUE KUEN KWOK. "VALUATION OF GUARANTEED ANNUITY OPTIONS IN AFFINE TERM STRUCTURE MODELS." International Journal of Theoretical and Applied Finance 10, no. 02 (March 2007): 363–87. http://dx.doi.org/10.1142/s0219024907004160.
Full textDassios, Angelos, and Shanle Wu. "Double-Barrier Parisian Options." Journal of Applied Probability 48, no. 01 (March 2011): 1–20. http://dx.doi.org/10.1017/s0021900200007592.
Full textDassios, Angelos, and Shanle Wu. "Double-Barrier Parisian Options." Journal of Applied Probability 48, no. 1 (March 2011): 1–20. http://dx.doi.org/10.1239/jap/1300198132.
Full textKamińska, Barbara. "Options in Corporate Finance Management." Przedsiebiorczosc i Zarzadzanie 15, no. 1 (January 1, 2014): 69–81. http://dx.doi.org/10.2478/eam-2014-0005.
Full textCiurlia, Pierangelo, and Andrea Gheno. "Pricing and Applications of Digital Installment Options." Journal of Applied Mathematics 2012 (2012): 1–21. http://dx.doi.org/10.1155/2012/584705.
Full textZEGHAL, AMINA BOUZGUENDA, and MOHAMED MNIF. "OPTIMAL MULTIPLE STOPPING AND VALUATION OF SWING OPTIONS IN LÉVY MODELS." International Journal of Theoretical and Applied Finance 09, no. 08 (December 2006): 1267–97. http://dx.doi.org/10.1142/s0219024906004037.
Full textDissertations / Theses on the topic "Options (Finance) – Valuation – Mathematical models"
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 textBooks on the topic "Options (Finance) – Valuation – Mathematical models"
Gibson, Rajna. Option valuation: Analyzing and pricing standardized option contracts. Genève: Georg, 1988.
Find full textOption valuation: Analyzing and pricing standardized option contracts. New York: McGraw-Hill, 1991.
Find full textOption valuation: An introduction to financial mathematics. Boca Raton: Taylor & Francis, 2012.
Find full textOption valuation in the presence of market imperfections. Frankfurt am Main: P. Lang, 1993.
Find full textAn introduction to financial option valuation: Mathematics, stochastics, and computation. New York: Cambridge University Press, 2004.
Find full text1957-, Srivastava Sanjay, ed. Option valuation and Option tutor. Cincinnati, Ohio: South-Western College, 1995.
Find full textJohn, O'Brien. Investments: A visual approach. Cincinnati, Ohio: South-Western Pub, 1995.
Find full textReal options valuation: The importance of interest rate modelling in theory and practice. 2nd ed. Heidelberg: Springer, 2010.
Find full textBeliefs-preferences gauge symmetry group and replication of contingent claims in a general market environment. Research Triangle Park, NC: IES Press, 1998.
Find full textTerm-structure models: A graduate course. Dordrecht: Springer, 2009.
Find full textBook chapters on the topic "Options (Finance) – Valuation – Mathematical models"
Eberlein, Ernst, Kathrin Glau, and Antonis Papapantoleon. "Analyticity of the Wiener–Hopf Factors and Valuation of Exotic Options in Lévy Models." In Advanced Mathematical Methods for Finance, 223–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18412-3_8.
Full textBordag, Ljudmila A. "On Option-Valuation in Illiquid Markets: Invariant Solutions to a Nonlinear Model." In Mathematical Control Theory and Finance, 71–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69532-5_5.
Full textBiancardi, Marta, and Giovanni Villani. "A Robustness Analysis of Least-Squares Monte Carlo for R&D Real Options Valuation." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 27–30. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05014-0_6.
Full textSmit, Han, and Thras Moraitis. "Option Games Valuation." In Playing at Acquisitions. Princeton University Press, 2015. http://dx.doi.org/10.23943/princeton/9780691140001.003.0006.
Full textDavis, Mark H. A. "3. The classical theory of option pricing." In Mathematical Finance: A Very Short Introduction, 30–60. Oxford University Press, 2019. http://dx.doi.org/10.1093/actrade/9780198787945.003.0003.
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