Skip to main content

Binomial Model for European Options

  • Chapter
  • First Online:

Part of the book series: Universitext ((UTX))

Abstract

For a large range of options such as the American options the boundary conditions of the Black-Scholes differential equation are too complex to solve analytically. Therefore, one relies on numerical price computation. The best known method is to approximate the stock price process by a discrete time stochastic process, or, as in the approach followed by Cox, Ross, Rubinstein, to model the stock price process as a discrete time process from the start. The binomial model is a convenient tool for pricing European options.

Binomialni model za europske opcijeNajveći je rizik ne riskirati!The greatest risk is not to take risk!

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Breiman, L. (1973). Statistics: With a view towards application. Boston: Houghton Mifflin Company.

    Google Scholar 

  • Cizek, P., Härdle, W., & Weron, R. (2011). Statistical tools in finance and insurance (2nd ed.). Berlin/Heidelberg: Springer.

    Google Scholar 

  • Feller, W. (1966). An introduction to probability theory and its application (Vol. 2). New York: Wiley.

    Google Scholar 

  • Franke, J., Härdle, W., & Hafner, C. (2011). Statistics of financial markets (3rd ed.). Berlin/ Heidelberg: Springer.

    Google Scholar 

  • Härdle, W., & Simar, L. (2012). Applied multivariate statistical analysis (3rd ed.). Berlin: Springer.

    Google Scholar 

  • Härdle, W., Müller, M., Sperlich, S., & Werwatz, A. (2004). Nonparametric and semiparametric models. Berlin: Springer.

    Google Scholar 

  • Harville, D. A. (2001). Matrix algebra: Exercises and solutions. New York: Springer.

    Google Scholar 

  • Klein, L. R. (1974). A textbook of econometrics (2nd ed., 488 p.). Englewood Cliffs: Prentice Hall.

    Google Scholar 

  • MacKinnon, J. G. (1991). Critical values for cointegration tests. In R. F. Engle & C. W. J. Granger (Eds.), Long-run economic relationships readings in cointegration (pp. 266–277). New York: Oxford University Press.

    Google Scholar 

  • Mardia, K. V., Kent, J. T., & Bibby, J. M. (1979). Multivariate analysis. Duluth/London: Academic.

    Google Scholar 

  • RiskMetrics. (1996). J.P. Morgan/Reuters (4th ed.). RiskMetricsTM.

    Google Scholar 

  • Serfling, R. J. (2002). Approximation theorems of mathematical statistics. New York: Wiley.

    Google Scholar 

  • Tsay, R. S. (2002). Analysis of financial time series. New York: Wiley.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Borak, S., Härdle, W.K., López-Cabrera, B. (2013). Binomial Model for European Options. In: Statistics of Financial Markets. Universitext. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33929-5_7

Download citation

Publish with us

Policies and ethics