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Articoli di riviste sul tema "Option Pricing"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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1

Jensen, Bjarne Astrup, and Jørgen Aase Nielsen. "OPTION PRICING BOUNDS AND THE PRICING OF BOND OPTIONS." Journal of Business Finance & Accounting 23, no. 4 (1996): 535–56. http://dx.doi.org/10.1111/j.1468-5957.1996.tb01025.x.

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2

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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Abstract (sommario):

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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3

Li, Feng. "Option Pricing." Journal of Derivatives 7, no. 4 (2000): 49–65. http://dx.doi.org/10.3905/jod.2000.319134.

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4

Lord, Richard. "Option pricing." Journal of Banking & Finance 10, no. 1 (1986): 157–61. http://dx.doi.org/10.1016/0378-4266(86)90028-2.

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5

Mitra, Sovan. "Multifactor option pricing: pricing bounds and option relations." International Journal of Applied Decision Sciences 3, no. 1 (2010): 15. http://dx.doi.org/10.1504/ijads.2010.032238.

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6

Guo, Yuanyuan. "Comparative Analysis of the Application of Monte Carlo Model and BSM Model in European Option Pricing." BCP Business & Management 32 (November 22, 2022): 43–48. http://dx.doi.org/10.54691/bcpbm.v32i.2856.

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At present, the expansion of China's domestic options market brings positive factors and risks, and in order to avoid risks, it is crucial to choose a suitable model for option pricing. This article provides an example of an option for the underlying asset of the SSE 50 ETF. Using the BSM model and the Monte Carlo model for the selected option pricing, and comparing the actual option price. It is found that the pricing efficiency of the Monte Carlo model is higher than that of the BSM model when the number of simulations reaches 30,000 times in the call option, and there is little difference b

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7

Song, Peihang. "Research on the Development of Implied Volatility in Option Pricing." Advances in Economics, Management and Political Sciences 17, no. 1 (2023): 7–13. http://dx.doi.org/10.54254/2754-1169/17/20231048.

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Option, as an important financial derivative, has received more and more attention from investors in recent years. This paper includes three parts, the first part introduces the concept of options, including the birth and history of options, the trading of options, and different types of options. Then it discusses the history of option pricing and two typical and classic option pricing models and then introduces implied volatility. The second part of this paper introduces the specific development of the option pricing models, the correction process of option pricing models, and volatility mode

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8

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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9

Ryszard, Kokoszczyński, Sakowski Paweł, and Ślepaczuk Robert. "Which Option Pricing Model Is the Best? HF Data for Nikkei 225 Index Options." Central European Economic Journal 4, no. 51 (2019): 18–39. http://dx.doi.org/10.1515/ceej-2018-0010.

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Abstract In this study, we analyse the performance of option pricing models using 5-minutes transactional data for the Japanese Nikkei 225 index options. We compare 6 different option pricing models: the Black (1976) model with different assumptions about the volatility process (realized volatility with and without smoothing, historical volatility and implied volatility), the stochastic volatility model of Heston (1993) and the GARCH(1,1) model. To assess the model performance, we use median absolute percentage error based on differences between theoretical and transactional options prices. We

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10

Behera, Prashanta kumar, and Dr Ramraj T. Nadar. "Dynamic Approach for Index Option Pricing Using Different Models." Journal of Global Economy 13, no. 2 (2017): 105–20. http://dx.doi.org/10.1956/jge.v13i2.460.

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Option pricing is one of the exigent and elementary problems of computational finance. Our aims to determine the nifty index option price through different valuation technique.Â In this paper, we illustrate the techniques for pricing of options and extracting information from option prices. We also describe various ways in which this information has been used in a number of applications. When dealing with options, we inevitably encounter the Black-Scholes-Merton option pricing formula, which has revolutionized the way in which options are priced in modern time. Black and Scholes (1973) and Mer

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11

Dr., M. Tulasinadh* Dr.R. Mahesh. "THE GREEKS & BLACK AND SCHOLE MODEL" TO EVALUATE OPTIONS PRICING & SENSITIVITY IN INDIAN OPTIONS MARKET." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 4, no. 5 (2017): 74–78. https://doi.org/10.5281/zenodo.801245.

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Derivatives’ trading is a core part of the Indian Stock Market in the Current Scenario. Trading volumes in stock options have grown up tremendously during recent years. This also leads to be high volatility in the options prices Options Pricing is crucial factor for hedging and Speculative activities. Pricing plays a vital role for option writers. In this paper we have tried to find out the price of an option in the future and its sensitivity through the Greek & Black and Scholes Option pricing model. Many option traders rely on the “Greeks” to evaluate option positions and to determine op

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12

Shao, Zeyuan. "Pricing Technique for European Option and Application." Highlights in Business, Economics and Management 14 (June 12, 2023): 14–18. http://dx.doi.org/10.54097/hbem.v14i.8930.

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In financial mathematics, the pricing technique for derivatives is constantly debated. In this paper, the pricing technique of the European Option is mainly discussed, and the binomial tree (BN) model is first applied to the pricing process of European options. The previous results show that carbon credit index can be traded as an option, and BN model can correctly simulate the future price of call option constructed by consuming the carbon credit index. Secondly, the Black-Scholes (BN) model is also a crucial technique for pricing European options, and it is successfully applied to predicting

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13

Stamatopoulos, Nikitas, Daniel J. Egger, Yue Sun, et al. "Option Pricing using Quantum Computers." Quantum 4 (July 6, 2020): 291. http://dx.doi.org/10.22331/q-2020-07-06-291.

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We present a methodology to price options and portfolios of options on a gate-based quantum computer using amplitude estimation, an algorithm which provides a quadratic speedup compared to classical Monte Carlo methods. The options that we cover include vanilla options, multi-asset options and path-dependent options such as barrier options. We put an emphasis on the implementation of the quantum circuits required to build the input states and operators needed by amplitude estimation to price the different option types. Additionally, we show simulation results to highlight how the circuits that

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14

Li, Songsong, Yinglong Zhang, and Xuefeng Wang. "The Sunk Cost and the Real Option Pricing Model." Complexity 2021 (September 30, 2021): 1–12. http://dx.doi.org/10.1155/2021/3626000.

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Although the academic literature on real options has grown enormously over the past three decades, hitherto an accurate real option pricing model has not been developed for investment decision analyses. In this paper, we propose a real option pricing model based on sunk cost characteristics, which can estimate the value of real options more accurately. First, we explore the distinctive features that distinguish real options from financial options. The study shows that the distinguishing feature of the real options is the sunk cost, which does not exist in the financial options. Based on the su

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15

Bhat, Aparna, and Kirti Arekar. "Empirical Performance of Black-Scholes and GARCH Option Pricing Models during Turbulent Times: The Indian Evidence." International Journal of Economics and Finance 8, no. 3 (2016): 123. http://dx.doi.org/10.5539/ijef.v8n3p123.

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Exchange-traded currency options are a recent innovation in the Indian financial market and their pricing is as yet unexplored. The objective of this research paper is to empirically compare the pricing performance of two well-known option pricing models – the Black-Scholes-Merton Option Pricing Model (BSM) and Duan’s NGARCH option pricing model – for pricing exchange-traded currency options on the US dollar-Indian rupee during a recent turbulent period. The BSM is known to systematically misprice options on the same underlying asset but with different strike prices and maturities resulting in

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16

Hong, Jingqi. "Progress of the Study on the Models of Option Pricing." BCP Business & Management 39 (February 22, 2023): 147–53. http://dx.doi.org/10.54691/bcpbm.v39i.4057.

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Option pricing, a core part of options trading, has been fruitfully researched over the years. This article reviews the history of the emergence and advancement of option pricing in terms of a thorough classification of the widely used option pricing models and their empirical studies that follow. The three option pricing models are summarized, including the Black-Scholes pricing model, the tree diagram model, and the Monte Carlo simulation techniques, which have all represented significant progress in the field of option pricing theory. Moreover, the differences between various pricing models

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17

ALGHALITH, MOAWIA, CHRISTOS FLOROS, and THOMAS POUFINAS. "SIMPLIFIED OPTION PRICING TECHNIQUES." Annals of Financial Economics 14, no. 01 (2019): 1950003. http://dx.doi.org/10.1142/s2010495219500039.

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In this paper we provide alternative methods for pricing European and American call and put options. Our contribution lies in the simplification attempted in the models developed. Such simplification is feasible due to our observation that the value of the option can be derived as a function of the underlying stock price, strike price and time to maturity. This route is supported by the fact that both the risk-free rate and the volatility of the stock are captured by the move of the underlying stock price. Moreover, looking at the properties of the Brownian motion, widely used to map the move

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18

Amin, Kaushik. "Option Pricing Trees." Journal of Derivatives 2, no. 4 (1995): 34–46. http://dx.doi.org/10.3905/jod.1995.407926.

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19

Madan, Dilip B., and Wim Schoutens. "Conic Option Pricing." Journal of Derivatives 25, no. 1 (2017): 10–36. http://dx.doi.org/10.3905/jod.2017.25.1.010.

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20

Bieta, Volker, Udo Broll, and Wilfried Siebe. "Strategic Option Pricing." Economics and Business Review 6 (20), no. 3 (2020): 118–29. http://dx.doi.org/10.18559/ebr.2020.3.7.

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In this paper an extension of the well-known binomial approach to option pricing is presented. The classical question is: What is the price of an option on the risky asset? The traditional answer is obtained with the help of a replicating portfolio by ruling out arbitrage. Instead a two-person game from the Nash equilibrium of which the option price can be derived is formulated. Consequently both the underlying asset’s price at expiration and the price of the option on this asset are endogenously determined. The option price derived this way turns out, however, to be identical to the classical

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21

Carvalho, Vitor H., and Raquel M. Gaspar. "Relativistic Option Pricing." International Journal of Financial Studies 9, no. 2 (2021): 32. http://dx.doi.org/10.3390/ijfs9020032.

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The change of information near light speed, advances in high-speed trading, spatial arbitrage strategies and foreseen space exploration, suggest the need to consider the effects of the theory of relativity in finance models. Time and space, under certain circumstances, are not dissociated and can no longer be interpreted as Euclidean. This paper provides an overview of the research made in this field while formally defining the key notions of spacetime, proper time and an understanding of how time dilation impacts financial models. We illustrate how special relativity modifies option pricing a

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22

Wang, Tai-Ho. "Nonlinear Option Pricing." Quantitative Finance 15, no. 1 (2014): 19–21. http://dx.doi.org/10.1080/14697688.2014.931594.

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23

McCauley, J. L., G. H. Gunaratne, and K. E. Bassler. "Martingale option pricing." Physica A: Statistical Mechanics and its Applications 380 (July 2007): 351–56. http://dx.doi.org/10.1016/j.physa.2007.02.038.

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24

Bandi, Chaithanya, and Dimitris Bertsimas. "Robust option pricing." European Journal of Operational Research 239, no. 3 (2014): 842–53. http://dx.doi.org/10.1016/j.ejor.2014.06.002.

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25

Chalasani, P., S. Jha, and I. Saias. "Approximate Option Pricing." Algorithmica 25, no. 1 (1999): 2–21. http://dx.doi.org/10.1007/pl00009280.

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26

Lin, Yueh-Neng, and Chien-Hung Chang. "VIX option pricing." Journal of Futures Markets 29, no. 6 (2009): 523–43. http://dx.doi.org/10.1002/fut.20387.

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27

Husmann, Sven, and Neda Todorova. "CAPM option pricing." Finance Research Letters 8, no. 4 (2011): 213–19. http://dx.doi.org/10.1016/j.frl.2011.03.001.

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28

Ding, Ming, Jiaxin Liu, and Yuching Wu. "Pricing Chooser Option." Theoretical and Natural Science 107, no. 1 (2025): 220–26. https://doi.org/10.54254/2753-8818/2025.22645.

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Abstract (sommario):

With the rapid development of financial markets and the increasing diversification of investment instruments and choices, exotic derivatives like the Chooser option have emerged. This special type of option contract grants holders the right to choose whether the option is a put or a call at the selection date. This flexibility facilitates investors' hedging policies and diversification to spread risk and enhance returns. However, pricing it appropriately becomes a difficult task because of its complexity. This paper first aims to price the Chooser option in two ways: the N-period Binomial tree

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29

BRANGER, NICOLE, and CHRISTIAN SCHLAG. "OPTION BETAS: RISK MEASURES FOR OPTIONS." International Journal of Theoretical and Applied Finance 10, no. 07 (2007): 1137–57. http://dx.doi.org/10.1142/s0219024907004585.

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This paper deals with the problem of determining the correct risk measure for options in a Black–Scholes (BS) framework when time is discrete. For the purposes of hedging or testing simple asset pricing relationships previous papers used the "local", i.e., the continuous-time, BS beta as the measure of option risk even over discrete time intervals. We derive a closed-form solution for option betas over discrete return periods where we distinguish between "covariance betas" and "asset pricing betas". Both types of betas involve only simple Black–Scholes option prices and are thus easy to comput

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30

Visagie, Jaco. "On the interchangeability of barrier option pricing models." South African Statistical Journal 52, no. 2 (2018): 157–71. http://dx.doi.org/10.37920/sasj.2018.52.2.4.

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An important question when modelling option prices is which of the multitude of option pricing models to use. In this paper, the calculation of barrier option prices is considered. These exotic options are found in many financial markets the world over. It is demonstrated numerically that it is possible to replicate (with a high degree of accuracy) the barrier option prices obtained from one model by making use of a different model; these models are referred to as ‘interchangeable’. Tests for the interchangeability of barrier option pricing models are developed and applied. However, the tests

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31

Singh, Akash, Ravi Gor Gor, and Rinku Patel. "VALUATION OF EUROPEAN PUT OPTION BY USING THE QUADRATURE METHOD UNDER THE VARIANCE GAMMA PROCESS." International Journal of Engineering Science Technologies 4, no. 5 (2020): 1–5. http://dx.doi.org/10.29121/ijoest.v4.i4.2020.101.

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Dynamic asset pricing model uses the Geometric Brownian Motion process. The Black-Scholes model known as standard model to price European option based on the assumption that underlying asset prices dynamic follows that log returns of asset is normally distributed. In this paper, we introduce a new stochastic process called levy process for pricing options. In this paper, we use the quadrature method to solve a numerical example for pricing options in the Indian context. The illustrations used in this paper for pricing the European style option. We also try to develop the pricing formula for Eu

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32

Ross, Sheldon M., and J. George Shanthikumar. "PRICING EXOTIC OPTIONS." Probability in the Engineering and Informational Sciences 14, no. 3 (2000): 317–26. http://dx.doi.org/10.1017/s0269964800143037.

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We show that if the payoff of a European option is a convex function of the prices of the security at a fixed set of times, then the geometric Brownian motion risk neutral option price is increasing in the volatility of the security. We also give efficient simulation procedures for determining the no-arbitrage prices of European barrier, Asian, and lookback options.

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33

Yin, Xiaocui. "Correlation Financial Option Pricing Model and Computer Simulation under a Stochastic Interest Rate." Wireless Communications and Mobile Computing 2022 (August 10, 2022): 1–9. http://dx.doi.org/10.1155/2022/6745980.

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With the continuous expansion of the consumer interest rate market today, the risks brought by interest rate fluctuations have had a huge and far-reaching impact on the financial markets of many countries and it is becoming more and more important to simulate the pricing of financial options. In the traditional pricing model of financial options, the pricing standard of the pricing model is generally set as a financial product with random disturbance characteristics and the market price of its transaction does not follow the arbitrage principle of financial product pricing. It is easy to gener

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34

Ou, Shubin, and Guohe Deng. "Extremum Options Pricing of Two Assets under a Double Nonaffine Stochastic Volatility Model." Mathematical Problems in Engineering 2023 (February 1, 2023): 1–20. http://dx.doi.org/10.1155/2023/1165629.

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In this paper, we consider the pricing problem for the extremum options by constructing a double nonaffine stochastic volatility model. The joint characteristic function of the logarithm of two asset prices is derived by using the Feynman–Kac theorem and one-order Taylor approximation expansion. The semiclosed analytical pricing formulas of the European extremum options including option on maximum and option on minimum of two underlying assets are derived by using measure change technique and Fourier transform approach. Some numerical examples are provided to analyze the pricing results of ext

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35

DIA, BAYE M. "A REGULARIZED FOURIER TRANSFORM APPROACH FOR VALUING OPTIONS UNDER STOCHASTIC DIVIDEND YIELDS." International Journal of Theoretical and Applied Finance 13, no. 02 (2010): 211–40. http://dx.doi.org/10.1142/s0219024910005747.

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This paper studies the option pricing problem in a class of models in which dividend yields follow a time-homogeneous diffusion. Within this framework, we develop a new approach for valuing options based on the use of a regularized Fourier transform. We derive a pricing formula for European options which gives the option price in the form of an inverse Fourier transform and propose two methods for numerically implementing this formula. As an application of this pricing approach, we introduce the Ornstein-Uhlenbeck and the square-root dividend yield models in which we explicitly solve the prici

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36

Antwi Baafi, Joseph. "The Nexus Between Black-Scholes-Merton Option Pricing and Risk: A Case of Ghana Stock Exchange." Archives of Business Research 10, no. 5 (2022): 140–52. http://dx.doi.org/10.14738/abr.105.12350.

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Even though option pricing and its market activities are not new, in Ghana the idea of trading options is yet to be realized. One popular method in pricing options is known as Black-Scholes-Merton option pricing model. Even though option pricing activities are not currently happening on the Ghana Stock Exchange, authors looked at the possibilities and preparedness of the GES to start trading such financial instrument. The main objective of this study therefore was to know how Black-Scholes-Merton model could be used to help in appropriate option value and undertake a risk assessment of stocks

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37

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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DOKUCHAEV, NIKOLAI. "MULTIPLE RESCINDABLE OPTIONS AND THEIR PRICING." International Journal of Theoretical and Applied Finance 12, no. 04 (2009): 545–75. http://dx.doi.org/10.1142/s0219024909005348.

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We suggest a modification of an American option such that the option holder can exercise the option early before the expiration and can revert later this decision to exercise; it can be repeated a number of times. This feature gives additional flexibility and risk protection for the option holder. A classification of these options and pricing rules are given. We found that the price of some call options with this feature is the same as for the European call. This means that the additional flexibility costs nothing, similarly to the situation with American and European call options. For the mar

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Zeng, Xianglong. "Comparison of the Pricing Model for Different Types of options." BCP Business & Management 38 (March 2, 2023): 3337–42. http://dx.doi.org/10.54691/bcpbm.v38i.4295.

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Contemporarily, option is one of the widely used underlying assets to hedge the risks and construct portfolio in finance field. As a matter fact, with different regulations and trading rules of various transaction center around the world, there are plenty of types of options. On account of the differences in the trading rules, the option pricing models vary a lot. On this basis, this study will select three common types of options (i.e., European option, American option, and Asian Option) in order to detailly demonstrate the differences in the pricing. To be specific, the formulae as well as t

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Zhang, Yicheng. "Research on insurance pricing under option game based on Black-Scholes model." SHS Web of Conferences 208 (2024): 03005. https://doi.org/10.1051/shsconf/202420803005.

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The pricing of insurance products has always occupied a central position in the insurance business and has long been an important focus of academic research. With the development of theory, the combination of option theory and game theory provides a new analytical perspective for insurance pricing. Specifically, insurance can be viewed as a kind of option so that the strategies in option game theory can be applied to determine a reasonable premium level. In this context, this study aims to explore in depth how option game theory can be applied to the insurance pricing problem. First, this pape

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Gradojevic, Nikola, Dragan Kukolj, and Ramazan Gencay. "Clustering and Classification in Option Pricing." Review of Economic Analysis 3, no. 2 (2011): 109–28. http://dx.doi.org/10.15353/rea.v3i2.1458.

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This paper reviews the recent option pricing literature and investigates how clustering and classification can assist option pricing models. Specifically, we consider non-parametric modular neural network (MNN) models to price the S&P-500 European call options. The focus is on decomposing and classifying options data into a number of sub-models across moneyness and maturity ranges that are processed individually. The fuzzy learning vector quantization (FLVQ) algorithm we propose generates decision regions (i.e., option classes) divided by ‘intelligent’ classification boundaries. Such an ap

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Wang, Meini, Panjie Wang, and Yuyi Zhang. "An empirical study of down-and-out put option pricing based on Geometric Brownian Motion and Monte Carlo Simulation: evidence from crude oil and E-mini Nasdaq-100 futures." BCP Business & Management 26 (September 19, 2022): 804–9. http://dx.doi.org/10.54691/bcpbm.v26i.2041.

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Option, an instrument of significant financial values in the modern market, is of growing importance. In the case of pricing the option, pricing exotic option remains the problem, since none of the practical methods have been developed as a corresponding way of solution. In order to address the existing issue, this paper examines the feasibility of down-and-out put option pricing based on Geometric Brownian Motion and Monte-Carlo Simulation. Specifically, the stock prices will be calculated through the Geometric Brownian Motion certain while the underlying asset price and down-and-out put opti

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Lin, Wensheng. "Black-Scholes Model’s application in rainbow option pricing." BCP Business & Management 32 (November 22, 2022): 500–507. http://dx.doi.org/10.54691/bcpbm.v32i.2988.

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In this paper, we use excel as a tool to explore the pricing of rainbow options and their advantages based on the Black-Scholes Model. Two-color rainbow options are mainly explored in the paper, in which the underlying stocks are Apple and ExxonMobil. Simulating the price of two stocks is performed through Excel. Return on the corresponding European options and rainbow options is obtained after that. Next, the differences between the return on rainbow options and European options and pricing on rainbow option are analyzed. Finally, sensitivity analysis is carried out to further explore rainbow

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Yin, Zhao, and Chang Tan. "The Differential Algorithm for American Put Option with Transaction Costs under CEV Model." Journal of Systems Science and Information 2, no. 5 (2014): 401–10. http://dx.doi.org/10.1515/jssi-2014-0401.

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AbstractThis paper mainly studies the American put option pricing with transaction costs in the CEV process. The specific Crank-Nicolson form of numerical solution is obtained by the finite difference method. On this basis, Hong Kong stock CKH option is selected as the object to estimate option price. Finally, by comparing with the actual price, the American put option pricing model is verified as reasonable. This paper is significant to the rational pricing and the institutional construction of the upcoming stock options in mainland China.

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Liu, David, and An Wei. "Regulated LSTM Artificial Neural Networks for Option Risks." FinTech 1, no. 2 (2022): 180–90. http://dx.doi.org/10.3390/fintech1020014.

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This research aims to study the pricing risks of options by using improved LSTM artificial neural network models and make direct comparisons with the Black–Scholes option pricing model based upon the option prices of 50 ETFs of the Shanghai Securities Exchange from 1 January 2018 to 31 December 2019. We study an LSTM model, a mathematical option pricing model (BS model), and an improved artificial neural network model—the regulated LSTM model. The method we adopted is first to price the options using the mathematical model—i.e., the BS model—and then to construct the LSTM neural network for tr

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Singh, Vipul Kumar. "Pricing competitiveness of jump-diffusion option pricing models: evidence from recent financial upheavals." Studies in Economics and Finance 32, no. 3 (2015): 357–78. http://dx.doi.org/10.1108/sef-08-2012-0099.

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Purpose – The purpose of this paper is to investigate empirically the forecasting performance of jump-diffusion option pricing models of (Merton and Bates) with the benchmark Black–Scholes (BS) model relative to market, for pricing Nifty index options of India. The specific period chosen for this study canvasses the extreme up and down limits (jumps) of the Indian capital market. In addition, equity markets keep on facing high and low tides of financial flux amid new economic and financial considerations. With this backdrop, the paper focuses on finding an impeccable option-pricing model which

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Fabbiani, Emanuele, Andrea Marziali, and Giuseppe De Nicolao. "vanilla-option-pricing: Pricing and market calibration for options on energy commodities." Software Impacts 6 (November 2020): 100043. http://dx.doi.org/10.1016/j.simpa.2020.100043.

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Aljedhi, Reem Abdullah, and Adem Kılıçman. "Fractional Partial Differential Equations Associated with Lêvy Stable Process." Mathematics 8, no. 4 (2020): 508. http://dx.doi.org/10.3390/math8040508.

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In this study, we first present a time-fractional L e ^ vy diffusion equation of the exponential option pricing models of European option pricing and the risk-neutral parameter. Then, we modify a particular L e ^ vy-time fractional diffusion equation of European-style options. Further, we introduce a more general model based on the L e ^ vy-time fractional diffusion equation and review some recent findings associated with risk-neutral free European option pricing.

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Jin, Yunguo, and Shouming Zhong. "Pricing Spread Options with Stochastic Interest Rates." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/734265.

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Although spread options have been extensively studied in the literature, few papers deal with the problem of pricing spread options with stochastic interest rates. This study presents three novel spread option pricing models that permit the interest rates to be random. The paper not only presents a good approach to formulate spread option pricing models with stochastic interest rates but also offers a new test bed to understand the dynamics of option pricing with interest rates in a variety of asset pricing models. We discuss the merits of the models and techniques presented by us in some asse

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Martinkutė-Kaulienė, Raimonda. "EXOTIC OPTIONS: A CHOOSER OPTION AND ITS PRICING." Business, Management and Education 10, no. 2 (2012): 289–301. http://dx.doi.org/10.3846/bme.2012.20.

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Financial instruments traded in the markets and investors’ situation in such markets are getting more and more complex. This leads to more complex derivative structures used for hedging that are harder to analyze and which risk is harder managed. Because of the complexity of these instruments, the basic characteristics of many exotic options may sometimes be not clearly understood. Most scientific studies have been focused on developing models for pricing various types of exotic options, but it is important to study their unique characteristics and to understand them correctly in order to use

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