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Relevant bibliographies by topics / Black–Scholes Option Pricing Model (OPM)

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Academic literature on the topic 'Black–Scholes Option Pricing Model (OPM)'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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Journal articles on the topic "Black–Scholes Option Pricing Model (OPM)"

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PARTHASARATHY, V. R. PERRY. "Managing uncertainty: A case for using real options with option pricing model (OPM) to evaluate capital investment." TAPPI Journal 12, no. 7 (2013): 69–77. http://dx.doi.org/10.32964/tj12.7.69.

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The pulp and paper industry relies heavily on the traditional discounted cash flow-based net present value (DCF-NPV) for making capital investment decisions. The deficiency of the DCF-NPV model is that it is static; once a pattern of cash flow is established, management does not have the option to change the direction when new information is available. However, flexibility to alter the investment decision is a powerful strategic and capital investment tool. Abundant research has established strong precedence for applications of “real options” in operational and strategic settings to provide us

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Li, Chenwei. "A Study of Option Pricing Models with Market Price Adjustments: Empirical Analysis Beyond the Black-Scholes Model." Advances in Economics, Management and Political Sciences 137, no. 1 (2024): 94–98. https://doi.org/10.54254/2754-1169/2024.18702.

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In 1973, Fischer Black and Myron Scholes unveiled the Black-Scholes option pricing model, a groundbreaking contribution that profoundly influenced the domain of option pricing theory. The introduction of the Black-Scholes pricing formula has garnered substantial acclaim across both academic and industrial spheres, leading to its widespread dissemination and application. This formula not only underscores its vital significance but also exemplifies its unique position as a cornerstone of financial theory, reshaping how options are valued and traded in markets worldwide. However, in the real fina

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ZHAO, JINSHI, and JIAZHEN HUO. "COORDINATION MECHANISM COMBINING SUPPLY CHAIN OPTIMIZATION AND RULE IN EXCHANGE." Asia-Pacific Journal of Operational Research 30, no. 05 (2013): 1350015. http://dx.doi.org/10.1142/s0217595913500152.

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There are two kinds of option pricing. The option pricing in exchange follows the Black–Scholes rule but does not consider the optimizing of supply chain. The traditional supply chain option contract can optimize supply chain but does not meet the Black–Scholes rule. We integrate the assumption of above two kinds of option pricing, and design a model to combine the Black–Scholes rule and traditional option contract of optimizing in a supplier-led supply chain. Our combined model can guide the enterprises to write or buy option considering both option pricing rule in financial market and the op

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Rani,, Dr Pushpa. "Analysis of Option Prices Using Black Scholes Model." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34488.

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A mathematical formula used in finance to calculate the theoretical price of an option and ascertain its option premium is known as the Black Scholes option pricing model, which aids option traders in making informed decisions. This article estimates the option premium of various call and put options using the Black Scholes Model. The three distinct option chains chosen for this essay are all Mid-Cap companies that are listed on the Indian National Stock Exchange. The companies are Suzlon Energy, Kalyan jewellers India, and Exide Industries Ltd. The analysis demonstrates that the options are e

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Lee, Eun-Kyung, and Yoon-Dong Lee. "Understanding Black-Scholes Option Pricing Model." Communications for Statistical Applications and Methods 14, no. 2 (2007): 459–79. http://dx.doi.org/10.5351/ckss.2007.14.2.459.

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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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Xiang, Shang. "Research on Option Pricing Method Based on the Black-Scholes Model." Economics and Management Innovation 2, no. 1 (2025): 69–77. https://doi.org/10.71222/k8mkc798.

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Option pricing is one of the core research topics in the field of financial engineering. As a classical option pricing method, the Black-Scholes model provides a significant foundation for both theory and practice in modern financial markets. This paper first elaborates on the theoretical foundation and mathematical derivation of the Black-Scholes model, analyzes its practical applications in option pricing, and explores its limitations, including the strict assumptions about market conditions and its applicability in environments with fluctuating volatility or sudden market jumps. To address

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Kim, Sol. "The Best Option Pricing Model for KOSPI 200 Weekly Options." Korean Journal of Financial Studies 51, no. 5 (2022): 499–521. http://dx.doi.org/10.26845/kjfs.2022.10.51.5.499.

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This study finds the best option pricing model for KOSPI 200 weekly options. It examines the in-sample pricing, out-of-sample pricing and hedging performances of the short-term options with a maximum maturity of seven days or less, which have not been analyzed in previous studies. The Black and Scholes (1973) model, Ad Hoc Black-Scholes model, and stochastic volatility and jumps models are compared. As a result, one of the Ad Hoc BlackScholes models, the absolute smile model using the strike price as an independent variable shows the best performance. However, its performance is not significan

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Yao, Yiyuan. "Prediction of Option Prices by BP Neural Network Based on Principal Component Analysis." Advances in Economics, Management and Political Sciences 118, no. 1 (2024): 289–98. https://doi.org/10.54254/2754-1169/2024.18633.

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Under the development of artificial intelligence, this paper adopts the neural network algorithm based on principal component analysis to perform data fitting and prediction on the option prices of Huaxia SSE 50ETF. It also compares the fitting and prediction accuracy of the traditional Black-Scholes option pricing, time series option pricing model and BP neural network algorithm based on principal component analysis for option prices. For the time series model, by analyzing the ACF and PACF figures, the research builds an ARIMA(2,2,0) model. For Black-Scholes model, the study utilizes the rel

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Chauhan, Arun, and Ravi Gor. "COMPARISON OF THREE OPTION PRICING MODELS FOR INDIAN OPTIONS MARKET." International Journal of Engineering Science Technologies 5, no. 4 (2021): 54–64. http://dx.doi.org/10.29121/ijoest.v5.i4.2021.203.

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  Black-Scholes option pricing model is used to decide theoretical price of different Options contracts in many stock markets in the world. In can find many generalizations of BS model by modifying some assumptions of classical BS model. In this paper we compared two such modified Black-Scholes models with classical Black-Scholes model only for Indian option contracts. We have selected stock options form 5 different sectors of Indian stock market. Then we have found call and put option prices for 22 stocks listed on National Stock Exchange by all three option pricing models. Finall

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Dissertations / Theses on the topic "Black–Scholes Option Pricing Model (OPM)"

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Яременко, Наталія Сергіївна, Наталья Сергеевна Яременко, Nataliia Serhiivna Yaremenko та С. О. Хайлук. "Сучасні моделі оцінки вартості банку і можливість їх застосування в Україні". Thesis, ВД «ІНЖЕК», 2010. http://essuir.sumdu.edu.ua/handle/123456789/59575.

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Saleh, Ali, and Ahmad Al-Kadri. "Option pricing under Black-Scholes model using stochastic Runge-Kutta method." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-53783.

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The purpose of this paper is solving the European option pricing problem under the Black–Scholes model. Our approach is to use the so-called stochastic Runge–Kutta (SRK) numericalscheme to find the corresponding expectation of the functional to the stochastic differentialequation under the Black–Scholes model. Several numerical solutions were made to study howquickly the result converges to the theoretical value. Then, we study the order of convergenceof the SRK method with the help of MATLAB.

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Hu, Junling. "Barrier Option Pricing under SABR Model Using Monte Carlo Methods." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/655.

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The project investigates the prices of barrier options from the constant underlying volatility in the Black-Scholes model to stochastic volatility model in SABR framework. The constant volatility assumption in derivative pricing is not able to capture the dynamics of volatility. In order to resolve the shortcomings of the Black-Scholes model, it becomes necessary to find a model that reproduces the smile effect of the volatility. To model the volatility more accurately, we look into the recently developed SABR model which is widely used by practitioners in the financial industry. Pricing a bar

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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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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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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/.

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Angeli, Andrea, and Cornelius Bonz. "Changes in the creditability of the Black-Scholes option pricing model due to financial turbulences." Thesis, Umeå University, Umeå School of Business, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-34873.

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<p>This study examines whether the performance of the Black-Scholes model to price stock index options is influenced by the general conditions of the financial markets. For this purpose we calculated the theoretical values of 5814 options (3366 put option price observations and 2448 call option price observations) under the Black-Scholes assumptions. We compared these theoretical values with the real market prices in order to put the degree of deviations in two different time windows built around the bankruptcy of Lehman Brothers (September 15th 2008) to the test. We find clear evidences to st

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Saleemi, Asima Parveen. "Finite Difference Methods for the Black-Scholes Equation." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-48660.

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Financial engineering problems are of great importance in the academic community and BlackScholes equation is a revolutionary concept in the modern financial theory. Financial instruments such as stocks and derivatives can be evaluated using this model. Option evaluation, is extremely important to trade in the stocks. The numerical solutions of the Black-Scholes equation are used to simulate these options. In this thesis, the explicit and the implicit Euler methods are used for the approximation of Black-scholes partial differential equation and a second order finite difference scheme is used

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Paulin, Carl, and Maja Lindström. "Option pricing models: A comparison between models with constant and stochastic volatilities as well as discontinuity jumps." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172226.

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The purpose of this thesis is to compare option pricing models. We have investigated the constant volatility models Black-Scholes-Merton (BSM) and Merton’s Jump Diffusion (MJD) as well as the stochastic volatility models Heston and Bates. The data used were option prices from Microsoft, Advanced Micro Devices Inc, Walt Disney Company, and the S&P 500 index. The data was then divided into training and testing sets, where the training data was used for parameter calibration for each model, and the testing data was used for testing the model prices against prices observed on the market. Calib

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Berta, Abaynesh. "Option Pricing using the Fast Fourier Transform Method." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-51058.

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The fast Fourier transform (FFT), even though it has been widely applicable in Physics and Engineering, it has become attractive in Finance as well for it’s enhancement of computational speed. Carr and Madan succeeded in implementing the FFT for pricing of an option. This project, inspired by Carr and Madan’s paper, attempts to elaborate and connect the various mathematical and theoretical concepts that are helpful in understanding of the derivation. Further, we derive the characteristic function of the risk neutral probability for the logarithmic terminal stock price. The Black-Scholes-Merton

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Books on the topic "Black–Scholes Option Pricing Model (OPM)"

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Chappell, David. On the derivation and solution of the Black-Scholes option pricing model: A step by step guide. University of Sheffield. School of Management and Economic Studies, 1987.

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Hallerbach, Winfried G. A simple approximation to the normal distribution function with an application to the Black & Scholes option pricing model. Rotterdam Institute for Business Economic Studies, Erasmus Universiteit, 1994.

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Butler, Cormac, Fairplace, and D. C. Black-Scholes Option Pricing Model. Financial Times Prentice Hall, 1998.

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Book chapters on the topic "Black–Scholes Option Pricing Model (OPM)"

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Pascucci, Andrea. "Black-Scholes model." In PDE and Martingale Methods in Option Pricing. Springer Milan, 2011. http://dx.doi.org/10.1007/978-88-470-1781-8_7.

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Franke, Jürgen, Wolfgang Karl Härdle, and Christian Matthias Hafner. "Black–Scholes Option Pricing Model." In Universitext. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54539-9_6.

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Borak, Szymon, Wolfgang Karl Härdle, and Brenda López Cabrera. "Black-Scholes Option Pricing Model." In Statistics of Financial Markets. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11134-1_6.

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Franke, Jürgen, Wolfgang Karl Härdle, and Christian Matthias Hafner. "Black–Scholes Option Pricing Model." In Universitext. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13751-9_6.

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Franke, Jürgen, Wolfgang Härdle, and Christian M. Hafner. "Black-Scholes Option Pricing Model." In Universitext. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-10026-4_6.

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Borak, Szymon, Wolfgang Karl Härdle, and Brenda López-Cabrera. "Black-Scholes Option Pricing Model." In Universitext. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33929-5_6.

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Franke, Jürgen, Wolfgang Karl Härdle, and Christian Matthias Hafner. "Black–Scholes Option Pricing Model." In Statistics of Financial Markets. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16521-4_6.

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Malliaris, A. G. "The Black-Scholes Option Pricing Model." In Financial Derivatives. John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118266403.ch26.

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Chan, Raymond H., Yves ZY Guo, Spike T. Lee, and Xun Li. "Black–Scholes–Merton Model for Option Pricing." In Financial Mathematics, Derivatives and Structured Products. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3696-6_11.

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Chan, Raymond H., Yves ZY Guo, Spike T. Lee, and Xun Li. "Black–Scholes–Merton Model for Option Pricing." In Financial Mathematics, Derivatives and Structured Products. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9534-9_14.

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Conference papers on the topic "Black–Scholes Option Pricing Model (OPM)"

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Shehi, Enkeleda. "Option Pricing Models: The Evolution of the Black-Scholes-Merton Model." In 10th International Scientific Conference ERAZ - Knowledge Based Sustainable Development. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2024. https://doi.org/10.31410/eraz.2024.157.

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This paper focuses on the development and impact of the Black- Scholes-Merton (Black-Scholes) model in mathematical finance. It begins with an overview of the Black-Scholes model, including its foundational assumptions, the Black-Scholes equation, and its formula for pricing European options. The paper discusses the model’s significant advantages, such as its ability to estimate market volatility and provide a self-replicating hedging strategy. It also addresses its limitations, including assumptions of constant volatility and perfect market conditions, which often do not align with real-world

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Huang, Wenli, Shenghong Li, and Songyan Zhang. "Pricing Perpetual American Option under the Fractional Black-Scholes Model." In 2010 3rd International Conference on Business Intelligence and Financial Engineering (BIFE). IEEE, 2010. http://dx.doi.org/10.1109/bife.2010.47.

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Takada, Hellinton Hatsuo, José de Oliveira Siqueira, Marcelo de Souza Lauretto, Carlos Alberto de Bragança Pereira, and Julio Michael Stern. "On the Black-Scholes European Option Pricing Model Robustness and Generality." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: Proceedings of the 28th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2008. http://dx.doi.org/10.1063/1.3039017.

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Hao, Minlei, and Ziyuan Yin. "Option pricing based on the Black-Scholes and the Heston model." In International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), edited by Yuanchang Zhong. SPIE, 2022. http://dx.doi.org/10.1117/12.2646649.

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Wróblewski, Marcin, and Andrzej Myślinski. "Non-linear Black-Scholes Option Pricing Model based on Quantum Dynamics." In 7th International Conference on Complexity, Future Information Systems and Risk. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0011066000003197.

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Edeki, S. O., O. O. Ugbebor, G. O. Akinlabi, and O. Gonzalez-Gaxiola. "Approximate solutions of a variable volatility driven black-scholes option pricing model." In 2017 2nd International Conference on Knowledge Engineering and Applications (ICKEA). IEEE, 2017. http://dx.doi.org/10.1109/ickea.2017.8169936.

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Sun, Mohan. "Genetic Algorithm and Black-Scholes Option Pricing Model in Patent Value Evaluation." In 2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS). IEEE, 2019. http://dx.doi.org/10.1109/icvris.2019.00074.

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Munoz Palma, Manuel, and Ezequiel Aviles Ochoa. "Incorporation of Fuzzy Logic to the Black-Scholes Model in Exchange Option Pricing." In Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support. Atlantis Press, 2013. http://dx.doi.org/10.2991/.2013.10.

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Cao, Yu, and Xinlun Ma. "Fixed Lookback Option Pricing Based on Black-Scholes Model and Monte-Carlo Simulation." In Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China. EAI, 2023. http://dx.doi.org/10.4108/eai.28-10-2022.2328424.

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Li, Lei. "The simulation of CSI 300 Index Option Pricing Based on Black-Scholes Model." In 2019 4th IEEE International Conference on Cybernetics (Cybconf). IEEE, 2019. http://dx.doi.org/10.1109/cybconf47073.2019.9436608.

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Reports on the topic "Black–Scholes Option Pricing Model (OPM)"

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Tirapat, Sunti. Risk-based deposit insurance : an application to Thailand. Chulalongkorn University, 2000. https://doi.org/10.58837/chula.res.2000.19.

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This paper investigates the application of option pricing to calculate the premium of deposit insurance in Thailand during 1992-1996 period. In addition to applying the traditional Black-Scholes model, the barrier model of Boyle and Lee (1994) is examined. The barrier model takes the management (owners) action into account: the management (owners) may have strong incentive to increase the volatility of the bank’s assets since this action in crease the value of their equity. As suggested by the stylized evidence, most financial institutions in Thailand were owned by “family” and there was inade

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