Pricing of Options Portfolio Based on Market Information Content

Subject Areas : Financial Knowledge of Securities Analysis

Mohsen rezaeeyan ¹ , narges yazdanian ² , alireza mirarab ³ , neda farahbakhsh ⁴

1 - Ph.D. Candidate Of Industrial Management -Financial Orientation. Roudehen Branch, Islamic Azad University, Roudehen, Iran
2 - Assistant Prof, Roudehen Branch. Islamic Azad University. Roudehen. Iran (Corresponding Arthur)
3 - Assistant Prof, Roudehen Branch. Islamic Azad University. Roudehen. Iran
4 - Assistant Prof, Roudehen Branch. Islamic Azad University. Roudehen. Iran

Received: 2022-08-03 Accepted : 2022-11-29 Published : 2023-07-23

Keywords: option pricing, Black-Scholes model, Information-Based Model,

Abstract :

Correct and fair options pricing has always been one of the challenges faced by financial researchers and investors. For this purpose, several models have been designed and tested for the pricing of option bonds. All these models have used the past information of the stock price for the pricing of the corresponding option, and the information content of the price from the index trend of market has not been paid attention to. In the current research, the option pricing model is evaluated based on the information content of the market index under the title of information-oriented model, and its performance is compared with the basic Black-Scholes model.The statistical population of the research includes the companies listed in Tehran Stock Exchange during the years 2016-2020, whose price and yield information along with market index values ​​were collected with monthly frequency during this period. To compare the fair valuation of options under the two methods of Black-Scholes and the proposed method of this research, first the stocks with information content from the market are identified through the estimation of the information transfer rate parameter, and then the value of the options for each share during a one-month maturity period is identified, and it was estimated based on two pricing models Black-Scholes and information-oriented.The results showed that the information-oriented model provided a more correct evaluation of the value of options and, therefore, provided a fairer valuation than the Black-Scholes model. According to the findings of the research, the ratio of profitable transactions under the information-oriented model was significantly larger than this ratio under the Black-Scholes model. The use of environmental and market information in the pricing of capital assets such as shares and options can significantly reduce the investment risk and provide higher profitability for investors.

References:

امجدیان، سیما (1396). برآورد شیب نوسانات ضمنی قرارداد اختیار معامله در سر رسیدهای کوتاه مدت به روش لوی، کارشناسی ارشد، دانشگاه آیت‌الله‌العظمی بروجردی (ره).

تقوی، امیرحسن (1396). مطالعه و بررسی ریسک ورشکستگی شرکتهای پذیرفته شده در بورس اوراق بهادار تهران با استفاده از مدلهای ارزشگذاری اختیار معامله مانع، کارشناسی ارشد، دانشگاه خوارزمی.

جنابی، امید (1398). شبیه سازی مونت کارلو جهت قیمت‌گذاری اوراق اختیار اروپایی تحت فرآیند پرش-انتشار، دکتری تخصصی، دانشگاه سیستان و بلوچستان.

لنگری، احسان (1397). اختیار معامله و ریسک در شرکت‌های پذیرفته‌شده در بورس اوراق بهادار تهران، کارشناسی ارشد، موسسه آموزش عالی حکیمان.

نام‌آور، فریبا (1393). بررسی قیمت‌گذاری اختیار اروپایی با نوسانات نرخ بهره در شرکت‌های پذیرفته شده در سازمان بورس اوراق بهادار، کارشناسی ارشد، دانشگاه علم و فرهنگ تهران.

نبوی چاشمی، سیدعلی؛ عبداللهی، فرهاد (1397). بررسی و مقایسه الگوهای سود اختیارمعاملات آسیایی، اروپایی و آمریکایی سهام در بورس اوراق بهادار تهران، مهندسی مالی و مدیریت اوراق بهادار، 34: 359-380.

یاوری، ساناز (1397). اختیار معامله، ریسک حقوق صاحبان سهام و ارزش‌گذاری تعدیلات ساختار سرمایه در شرکتهای پذیرفته شده در بورس اوراق بهادار تهران، کارشناسی ارشد، موسسه آموزش عالی حکیمان.

 

Aimi A., Diazzi L., Guardasoni C. (2018). Numerical pricing of geometric asian options with barriers. Math. Methods Appl. Sci., 41, 7510–7529.

Aimi A., Guardasoni C. (2021). Multi-Asset Barrier Options Pricing by Collocation BEM (with Matlab® Code)., Axioms, 10, 301.

Ballestra L. V., Cecere L. (2016). A fast numerical method to price American options under the Bates model, Computers & Mathematics with Applications, 72 (5), 1305–1319.

Carr P., Itkin A., Muravey D. (2020). Semi-closed form prices of barrier options in the time-dependent CEV and CIR models. J. Deriv., 28, 26–50.

Chen Y. (2017). Numerical Methods for Pricing Multi-Asset Options, Master Thesis, Department of Computer Science, University of Toronto.

Cuomo S., Di Lorenzo E., Di Somma V., Toraldo G. (2020). A sequential Monte Carlo approach for the pricing of barrier option under a stochastic volatility model. Electron. J. Appl. Stat. Anal., 13, 128–145.

Damircheli D., Bhatia M. (2019). Solution approaches and sensitivity analysis of variational inequalities, AIAA Scitech 2019 Forum, p. 0977.

Dar A. A. (2021). Comparison of European Option Pricing Models at Multiple Periods, Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics, 18-21.

Guillaume T. (2019). On the multidimensional Black Scholes partial differential equation. Ann. Oper. Res., 281, 229–251.

Haghi M., Mollapourasl R., Vanmaele M. (2018). An RBF–FD method for pricing American options under jump–diffusion models, Computers & Mathematics with Applications, 76 (10), 2434–2459.

Han, M., Wang, W. (2022). Option pricing with exchange rate risk under regime-switching multi-scale jump-diffusion models, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2022.2129992

Hull J. C. (2008). Options, Futures and Other Derivatives (7th Edition). Prentice Hall, 7 edition.

Ikamari C., Ngare P., Weke P. (2020). Multi-asset option pricing using an information-based model, Scientific African, Vol. 10, e00564.

Lars Kirkby J., Nguyen D., Nguyen D. (2020). A general continuous time Markov chain approximation for multi-asset option pricing with systems of correlated diffusion. Appl. Math. Comput., 386, 125472.

Niklasson V. (2018). Multi-Asset Options: A Numerical Study, Master Thesis, Department of Mathematical Sciences, Chalmers University of Technology.

Shreve S. E. (2004). Stochastic Calculus for Finance I. Springer-Verlag.

Wang X. (2020). Pricing options on the maximum or minimum of multi-assets under jump-diffusion processes, International Review of Economics & Finance, Vol. 70, 16-26.

Wilmott P. (2006). Paul Wilmott Introduces Quantitative Finance., vol. 1. John Wiley & Sons, 1 edition.

Zhao, K., Zhang, J., Liu, Q. (2022). Dual-Hybrid Modeling for Option Pricing of CSI 300ETF. Information, 13, 36.

Khraisha, T., Arthur, K. (2018). Can we have a general theory of financial innovation processes? A conceptual review, Financ. Innov., 4(4), 13-29.

Maruddani, D., Trimono, T. (2018). Modeling stock prices in a portfolio using multidimensional geometric Brownian motion, J. Phys. Conf., Ser. 1025.

Roul, P., Goura, V.M.K.P. (2020). A new higher order compact finite difference method for generalized black–scholes partial differential equation: European call option, J. Comput. Appl. Math., 363, 464–484.

Dhaene, J., Kukush, A., Linders, D. (2020). Comonotonic asset prices in arbitrage-free markets, J. Comput. Appl. Math., 364, 112310.

Cheung, K., Dhaene, J., Kukush, A., Linders, D. (2013). Ordered random vectors and equality in distribution, Scand. Actuarial J. (2013).

Macrina, A. (2006). An information-based framework for asset pricing: X-factor theory and its applications, PhD Thesis, King’s College London.