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Relevant bibliographies by topics / Binomial Pricing Model

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Academic literature on the topic 'Binomial Pricing Model'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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Journal articles on the topic "Binomial Pricing Model"

1

Breen, Richard. "The Accelerated Binomial Option Pricing Model." Journal of Financial and Quantitative Analysis 26, no. 2 (1991): 153. http://dx.doi.org/10.2307/2331262.

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Tian, Yisong ?Sam? "A flexible binomial option pricing model." Journal of Futures Markets 19, no. 7 (1999): 817–43. http://dx.doi.org/10.1002/(sici)1096-9934(199910)19:7<817::aid-fut5>3.0.co;2-d.

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Blake, D. "Option pricing models." Journal of the Institute of Actuaries 116, no. 3 (1989): 537–58. http://dx.doi.org/10.1017/s0020268100036696.

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Antoniou, I., V. V. Ivanov, and A. V. Kryanev. "On a Binomial Model of Option Pricing." Journal of Computational Methods in Sciences and Engineering 2, no. 1-2 (2002): 105–9. http://dx.doi.org/10.3233/jcm-2002-21-214.

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Yinghua, Li, and Li Xingsi. "Entropy Binomial Tree Model for Option Pricing." Applied Mathematics & Information Sciences 7, no. 1 (2013): 151–59. http://dx.doi.org/10.12785/amis/070118.

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Milanov, Krasimir, Ognyan Kounchev, Frank J. Fabozzi, Young Shin Kim, and Svetlozar T. Rachev. "A Binomial-Tree Model for Convertible Bond Pricing." Journal of Fixed Income 22, no. 3 (2012): 79–94. http://dx.doi.org/10.3905/jfi.2012.22.3.079.

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Costabile, Massimo, Ivar Massabó, and Emilio Russo. "An adjusted binomial model for pricing Asian options." Review of Quantitative Finance and Accounting 27, no. 3 (2006): 285–96. http://dx.doi.org/10.1007/s11156-006-9432-9.

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Xiao, Chang, and Jinsheng Zhou. "Pricing Mining Concessions Based on Combined Multinomial Pricing Model." Discrete Dynamics in Nature and Society 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/2196702.

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A combined multinomial pricing model is proposed for pricing mining concession in which the annualized volatility of the price of mineral products follows a multinomial distribution. First, a combined multinomial pricing model is proposed which consists of binomial pricing models calculated according to different volatility values. Second, a method is provided to calculate the annualized volatility and the distribution. Third, the value of convenience yields is calculated based on the relationship between the futures price and the spot price. The notion of convenience yields is used to adjust

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9

O. Osu, Bright, Samson O. Eggege, and Emmanuel J. Ekpeyong. "Application of Generalized Binomial Distribution Model for Option pricing." American Journal of Applied Mathematics and Statistics 5, no. 2 (2017): 62–71. http://dx.doi.org/10.12691/ajams-5-2-4.

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Liu, Jian, Weixing Wu, Jingfeng Xu, and Haijian Zhao. "An accurate binomial model for pricing American Asian option." Journal of Systems Science and Complexity 27, no. 5 (2014): 993–1007. http://dx.doi.org/10.1007/s11424-014-3271-x.

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Dissertations / Theses on the topic "Binomial Pricing Model"

1

Vestman, Jasmine. "Option pricing in the binomial model." Thesis, Uppsala universitet, Tillämpad matematik och statistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447428.

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Wolf, Diana Holmes. "Pricing American Options on Leveraged Exchange Traded Funds in the Binomial Pricing Model." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/723.

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This paper describes our work pricing options in the binomial model on leveraged exchange traded funds (ETFs) with three different approaches. A leveraged exchange traded fund attempts to achieve a similar daily return as the index it follows but at a specified positive or negative multiple of the return of the index. We price options on these funds using the leveraged multiple, predetermined by the leveraged ETF, of the volatility of the index. The initial approach is a basic time step approach followed by the standard Cox, Ross, and Rubinstein method. The final approach follows a differe

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3

Gu, Chenchen. "Option Pricing Using MATLAB." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/382.

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This paper describes methods for pricing European and American options. Monte Carlo simulation and control variates methods are employed to price call options. The binomial model is employed to price American put options. Using daily stock data I am able to compare the model price and market price and speculate as to the cause of difference. Lastly, I build a portfolio in an Interactive Brokers paper trading [1] account using the prices I calculate. This project was done a part of the masters capstone course Math 573: Computational Methods of Financial Mathematics.

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Sjödin, Elin. "Option Pricing in Discrete Time and Connections between the Binomial Model and Black-Scholes Model." Thesis, Uppsala universitet, Analys och sannolikhetsteori, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-253765.

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Stewart, Thomas Gordon. "Generalized Random Walks, Their Trees, and the Transformation Method of Option Pricing." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2608.pdf.

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Yang, Yuankai. "Pricing American and European options under the binomial tree model and its Black-Scholes limit model." Thesis, Linnéuniversitetet, Institutionen för matematik (MA), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-68264.

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We consider the N step binomial tree model of stocks. Call options and put options of European and American type are computed explicitly. With appropriate scaling in time and jumps, convergence of the stock prices and the option prices are obtained as N-> infinite. The obtained convergence is the Black-Scholes model and, for the particular case of European call option, the Black-Scholes formula is obtained. Furthermore, the Black-Scholes partial differential equation is obtained as a limit from the N step binomial tree model. Pricing of American put option under the Black-Scholes model is

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Pareja, Julian A. "Impact of the inclusion of stochastic and conditional volatility of a commodity in real options valuation using the binomial options pricing model." Doctoral thesis, Pontificia Universidad Católica del Perú, 2019. http://hdl.handle.net/20.500.12404/13834.

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In this dissertation it was described in detail the multiplicative quadrinomial tree numerical method with nonconstant volatility, based on a basis a proposal system of stochastic differential equations. The methodology allowed to estimate first, the value of the parameters based on an estimate conditional volatility process for a WTI oil commodity prices quoted in the Bloomberg platform, then they were derived and found their equivalent parameters in the proposed stochastic differential equations system, and finally the appropriate numerical method was constructed to include the volatility th

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Damberg, Petter, and Alexander Gullnäs. "Interest rate derivatives: Pricing of Euro-Bund options : An empirical study of the Black Derman & Toy model (1990)." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-24472.

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The market for interest rate derivatives has in recent decades grown considerably and the need for proper valuation models has increased. Interest rate derivatives are instruments that in some way are contingent on interest rates such as bonds and swaps and most financial transactions are in some way exposed to interest rate risk. Interest rate derivatives are commonly used to hedge this risk. This study focuses on the Black Derman & Toy model and its capability of pricing interest rate derivatives. The purpose was to simulate the model numerically using daily Euro-Bunds and options data t

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Coufalík, Jan. "Opční strategie a oceňování měnových opcí." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-199783.

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The aim of this diploma thesis is to analyze and implement selected option pricing models using statistical software. The first chapter introduces theoretical basics of options as financial instruments ideal for hedging and speculation. The second chapter constitutes the core part of this thesis since it unveils theoretical concepts of risk-neutral pricing and at the same time analyze some basic, as well as highly sophisticated option pricing models. In addition, each model is accompanied by a practical example of their effective implementation. The final chapter characterize the most widely u

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Pirozhkova, Daria. "Statistical models for an MTPL portfolio." Master's thesis, Vysoká škola ekonomická v Praze, 2017. http://www.nusl.cz/ntk/nusl-359373.

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In this thesis, we consider several statistical techniques applicable to claim frequency models of an MTPL portfolio with a focus on overdispersion. The practical part of the work is focused on the application and comparison of the models on real data represented by an MTPL portfolio. The comparison is presented by the results of goodness-of-fit measures. Furthermore, the predictive power of selected models is tested for the given dataset, using the simulation method. Hence, this thesis provides a combination of the analysis of goodness-of-fit results and the predictive power of the models.

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Books on the topic "Binomial Pricing Model"

1

Rajan, Raghuram. Pricing commodity bonds using binomial option pricing. International Economics Dept., the World Bank, 1988.

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2

Stochastic Calculus for Finance I: The Binomial Asset Pricing Model (Springer Finance). Springer, 2005.

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Book chapters on the topic "Binomial Pricing Model"

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Gianin, Emanuela Rosazza, and Carlo Sgarra. "Binomial Model for Option Pricing." In UNITEXT. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01357-2_3.

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Albrecher, Hansjoerg, Andreas Binder, Volkmar Lautscham, and Philipp Mayer. "The Binomial Option Pricing Model." In Compact Textbooks in Mathematics. Springer Basel, 2013. http://dx.doi.org/10.1007/978-3-0348-0519-3_5.

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Baaquie, Belal Ehsan. "Option Pricing and Binomial Model." In Mathematical Methods and Quantum Mathematics for Economics and Finance. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6611-0_9.

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4

Vassiliou, P.-C. G. "The No-Arbitrage Binomial Pricing Model." In Discrete-time Asset Pricing Models in Applied Stochastic Finance. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118557860.ch4.

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5

Shreve, Steven E. "The Binomial No-Arbitrage Pricing Model." In Stochastic Calculus for Finance I. Springer New York, 2005. http://dx.doi.org/10.1007/978-0-387-22527-2_1.

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6

Prigent, Jean-Luc, Olivier Renault, and Olivier Scaillet. "An Autoregressive Conditional Binomial Option Pricing Model." In Springer Finance. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-12429-1_17.

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Lee, Cheng-Few, John Lee, Jow-Ran Chang, and Tzu Tai. "Binomial Option Pricing Model Decision Tree Approach." In Essentials of Excel, Excel VBA, SAS and Minitab for Statistical and Financial Analyses. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-38867-0_25.

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Tapiero, Charles S., and Jiangyi Qi. "Financial Analytics and A Binomial Pricing Model." In Future Perspectives in Risk Models and Finance. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07524-2_8.

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9

Lee, Cheng-Few, Hong-Yi Chen, and John Lee. "The Binomial, Multinomial Distributions, and Option Pricing Model." In Financial Econometrics, Mathematics and Statistics. Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9429-8_12.

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10

Campolieti, Giuseppe, and Roman N. Makarov. "Replication and Pricing in the Binomial Tree Model." In Financial Mathematics, 2nd ed. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9780429503665-7.

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Conference papers on the topic "Binomial Pricing Model"

1

Wu, Qin, Min Wu, and Yunzhou Sun. "Analysis of software pricing based on binomial tree option pricing model." In 2020 International Conference on Information Science, Parallel and Distributed Systems (ISPDS). IEEE, 2020. http://dx.doi.org/10.1109/ispds51347.2020.00066.

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Li, Wei, and Liyan Han. "The Fuzzy Binomial Option Pricing Model under Knightian Uncertainty." In 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery. IEEE, 2009. http://dx.doi.org/10.1109/fskd.2009.252.

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3

Wang, Jin-feng, Yan An, Li-jie Feng, and Xin Wang. "Analysis on coal mine investment decision based on binomial tree pricing model." In EM2010). IEEE, 2010. http://dx.doi.org/10.1109/icieem.2010.5646405.

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Yongqing Shang, Zhen Wang, Qing Wang, and Lidong Zhong. "Notice of Retraction: Application of binomial option pricing model of forecasting oil price fluctuation." In 2010 IEEE International Conference on Advanced Management Science (ICAMS). IEEE, 2010. http://dx.doi.org/10.1109/icams.2010.5552960.

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Yen, Hui-Tzu, and Tyrone T. Lin. "Analysis of transnational joint venture decision evaluation on aesthetic medicine: Extended binomial options pricing model." In 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2016. http://dx.doi.org/10.1109/ieem.2016.7798138.

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Lu, Lijuan, Yunjiao Hu, and Rongxi Zhou. "The Binomial Option Pricing Models with Different Parameters." In 2011 Fourth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2011. http://dx.doi.org/10.1109/cso.2011.258.

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