IDEAS home Printed from https://ideas.repec.org/a/pab/rmcpee/v34y2022i1p237-262.html
   My bibliography  Save this article

Estimación clásica y bayesiana de la volatilidad en el modelo de Black-Scholes
[Classical and Bayesian estimation of volatility in the Black-Scholes model]

Author

Listed:
  • Cangrejo Esquivel, Álvaro Javier

    (Universidad Surcolombiana (Colombia))

  • Tovar Cuevas, José Rafael

    (Universidad del Valle (Colombia))

  • García, Isabel Cristina

    (Pontificia Universidad Javeriana Cali (Colombia))

  • Manotas Duque, Diego Fernando

    (Universidad del Valle (Colombia))

Abstract

La valoración de opciones y en gran medida el mercado de derivados financieros requiere de una óptima estimación de la volatilidad, ya que justamente ésta es la variable que se negocia. Se presenta entonces una metodología estadística para la estimación del parámetro de volatilidad para un activo, usando métodos propios del enfoque Bayesiano. Para modelar el comportamiento natural del parámetro que representa la volatilidad en el modelo de Black-Scholes, se utilizan distribuciones de probabilidad de la familia Gama y la distribución Lévy Estándar. Los resultados obtenidos usando la metodología propuesta se contrastan con los obtenidos al estimar el parámetro desde el enfoque clásico donde se implementa el método de la Máxima Verosimilitud y la técnica Boostrap. Se logra evidenciar que el procedimiento de estimación desde el paradigma bayesiano, permitió obtener estimaciones del parámetro de volatilidad más ajustadas y precisas, cuando en la distribución de los retornos se consideran valores extremos. Estas características del estimador permiten que, al evaluar el precio de la opción, al utilizar el modelo de Black-Scholes, sea más próximo a lo que se espera que ocurra en el mercado financiero.

Suggested Citation

  • Cangrejo Esquivel, Álvaro Javier & Tovar Cuevas, José Rafael & García, Isabel Cristina & Manotas Duque, Diego Fernando, 2022. "Estimación clásica y bayesiana de la volatilidad en el modelo de Black-Scholes [Classical and Bayesian estimation of volatility in the Black-Scholes model]," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 34(1), pages 237-262, December .
  • Handle: RePEc:pab:rmcpee:v:34:y:2022:i:1:p:237-262
    DOI: https://doi.org/10.46661/revmetodoscuanteconempresa.5002
    as

    Download full text from publisher

    File URL: https://www.upo.es/revistas/index.php/RevMetCuant/article/view/5002/6355
    Download Restriction: no

    File URL: https://doi.org/10.46661/revmetodoscuanteconempresa.5002
    Download Restriction: no

    File URL: https://libkey.io/https://doi.org/10.46661/revmetodoscuanteconempresa.5002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Danielsson, Jon, 1994. "Stochastic volatility in asset prices estimation with simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 375-400.
    2. Rossetti, Nara & Seido , Marcelo & Faria , Jorge, 2017. "A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 22(42), pages 99-128.
    3. Robert C. Merton, 2005. "Theory of rational option pricing," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 8, pages 229-288, World Scientific Publishing Co. Pte. Ltd..
    4. Karolyi, G. Andrew, 1993. "A Bayesian Approach to Modeling Stock Return Volatility for Option Valuation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 579-594, December.
    5. Shu Wing Ho & Alan Lee & Alastair Marsden, 2011. "Use of Bayesian Estimates to determine the Volatility Parameter Input in the Black-Scholes and Binomial Option Pricing Models," JRFM, MDPI, vol. 4(1), pages 1-23, December.
    6. Nguyen, Van Bon, 2015. "Effects of fi scal defi cit and money M2 supply on inflation: Evidence from selected economies of Asia," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 20(38), pages 49-53.
    7. Darsinos, T. & Satchell, S.E., 2001. "Bayesian Analysis of the Black-Scholes Option Price," Cambridge Working Papers in Economics 0102, Faculty of Economics, University of Cambridge.
    8. Chen, Zhian & Du, Jinmin & Li, Donghui & Ouyang, Rui, 2013. "Does foreign institutional ownership increase return volatility? Evidence from China," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 660-669.
    9. Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
    10. Colm Kearney & Kevin Daly, 1998. "The causes of stock market volatility in Australia," Applied Financial Economics, Taylor & Francis Journals, vol. 8(6), pages 597-605.
    11. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    12. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
    13. Faisal Khan & Saif-Ur-Rehman Khan & Hashim Khan, 2016. "Pricing of Risk, Various Volatility Dynamics and Macroeconomic Exposure of Firm Returns: New Evidence on Age Effect," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 551-561.
    14. Mthuli Ncube & Stephen Satchell, 1997. "The Statistical Properties of the Black–Scholes Option Price," Mathematical Finance, Wiley Blackwell, vol. 7(3), pages 287-305, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    2. Darsinos, T. & Satchell, S.E., 2001. "Bayesian Analysis of the Black-Scholes Option Price," Cambridge Working Papers in Economics 0102, Faculty of Economics, University of Cambridge.
    3. Shu Wing Ho & Alan Lee & Alastair Marsden, 2011. "Use of Bayesian Estimates to determine the Volatility Parameter Input in the Black-Scholes and Binomial Option Pricing Models," JRFM, MDPI, vol. 4(1), pages 1-23, December.
    4. Hanno Gottschalk & Elpida Nizami & Marius Schubert, 2016. "Option Pricing in Markets with Unknown Stochastic Dynamics," Papers 1602.04848, arXiv.org, revised Jan 2017.
    5. Boyarchenko, Svetlana & Levendorskii[caron], Sergei, 2007. "Optimal stopping made easy," Journal of Mathematical Economics, Elsevier, vol. 43(2), pages 201-217, February.
    6. Robert C. Merton, 2006. "Paul Samuelson and Financial Economics," The American Economist, Sage Publications, vol. 50(2), pages 9-31, October.
    7. Ammann, Manuel & Kind, Axel & Wilde, Christian, 2003. "Are convertible bonds underpriced? An analysis of the French market," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 635-653, April.
    8. Kim, Amy M. & Li, Huanan, 2020. "Incorporating the impacts of climate change in transportation infrastructure decision models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 271-287.
    9. Bjork, Tomas, 2009. "Arbitrage Theory in Continuous Time," OUP Catalogue, Oxford University Press, edition 3, number 9780199574742.
    10. Jobst, Andreas A., 2014. "Measuring systemic risk-adjusted liquidity (SRL)—A model approach," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 270-287.
    11. Timothy Johnson, 2015. "Reciprocity as a Foundation of Financial Economics," Journal of Business Ethics, Springer, vol. 131(1), pages 43-67, September.
    12. Tabesh, Hamid, 1987. "Hedging price risk to soybean producers with futures and options: a case study," ISU General Staff Papers 1987010108000010306, Iowa State University, Department of Economics.
    13. Dapena, Jose Pablo, 2003. "On the Valuation of Companies with Growth Opportunities," Journal of Applied Economics, Universidad del CEMA, vol. 6(1), pages 1-24, May.
    14. Werry Febrianti & Kuntjoro Adji Sidarto & Novriana Sumarti, 2023. "The Combinational Mutation Strategy of Differential Evolution Algorithm for Pricing Vanilla Options and Its Implementation on Data during Covid-19 Pandemic," Papers 2301.09261, arXiv.org.
    15. Henry Lam & Zhenming Liu, 2014. "From Black-Scholes to Online Learning: Dynamic Hedging under Adversarial Environments," Papers 1406.6084, arXiv.org.
    16. Avinash & T. Mallikarjunappa, 2020. "Informational Role of Open Interest and Transaction Volume of Options: A Meta-Analytic Review," FIIB Business Review, , vol. 9(4), pages 275-285, December.
    17. Bettina Freitag & Lukas Häfner & Verena Pfeuffer & Jochen Übelhör, 2020. "Evaluating investments in flexible on-demand production capacity: a real options approach," Business Research, Springer;German Academic Association for Business Research, vol. 13(1), pages 133-161, April.
    18. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
    19. Lambrinoudakis, Costas & Skiadopoulos, George & Gkionis, Konstantinos, 2019. "Capital structure and financial flexibility: Expectations of future shocks," Journal of Banking & Finance, Elsevier, vol. 104(C), pages 1-18.
    20. Engstrom, Malin & Norden, Lars, 2000. "The early exercise premium in American put option prices," Journal of Multinational Financial Management, Elsevier, vol. 10(3-4), pages 461-479, December.

    More about this item

    Keywords

    ecuación diferencial estocástica; distribución previa; distribución posterior; estimación; volatilidad; bootstrap; valores extremos; hiperparámetros; elicitación; stochastic differential equation; previous distribution; posterior distribution; estimation; volatility; extreme values; hyperparameters; elicitation;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G1 - Financial Economics - - General Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pab:rmcpee:v:34:y:2022:i:1:p:237-262. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Publicación Digital - UPO (email available below). General contact details of provider: https://edirc.repec.org/data/dmupoes.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.