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Scientific Annals of Economics and Business

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Stock Price Simulation Using Bootstrap and Monte Carlo

Martin Pažický
Published Online: 2017-08-01 | DOI: https://doi.org/10.1515/saeb-2017-0010


In this paper, an attempt is made to assessment and comparison of bootstrap experiment and Monte Carlo experiment for stock price simulation. Since the stock price evolution in the future is extremely important for the investors, there is the attempt to find the best method how to determine the future stock price of BNP Paribas′ bank. The aim of the paper is define the value of the European and Asian option on BNP Paribas′ stock at the maturity date. There are employed four different methods for the simulation. First method is bootstrap experiment with homoscedastic error term, second method is blocked bootstrap experiment with heteroscedastic error term, third method is Monte Carlo simulation with heteroscedastic error term and the last method is Monte Carlo simulation with homoscedastic error term. In the last method there is necessary to model the volatility using econometric GARCH model. The main purpose of the paper is to compare the mentioned methods and select the most reliable. The difference between classical European option and exotic Asian option based on the experiment results is the next aim of tis paper.

Keywords: European option; Asian Option; bootstrap; Monte Carlo; stock price simulation; modeling volatility


  • Andersen, T., Bollerslev, T., Diebold, F. X., and Vega, C., 2006. Real-time price discovery in global stock, bond and foreign exchange markets. Washington: Board of Governors of the Federal Reserve System (U.S.).Google Scholar

  • Bank for International Settlements, 2015. OTC derivatives statistics at end-June 2015 Statistical release. http://www.bis.org/publ/otc_hy1511.pdf.Google Scholar

  • BNP Paribas, 2016. How the bank is driving change. 2015 Annual Report, 63. https://group.bnpparibas/uploads/file/bnpp_ra_2015_en.pdf.Google Scholar

  • Bohdalová, M., 2006. Statistical Methods in Financial Services. (Dissertation Thesis), Comenius University, Bratislava.Google Scholar

  • Bohdalová, M., and Greguš, M., 2011. The identification of key market risk factors for a portfolio of EU bonds. Global business and economics anthology, 2(2), 470-477.Google Scholar

  • Bohdalová, M., and Greguš, M., 2012. Stochastic Analysis of the Financial Markets. Bratislava: Comenius University Press.Google Scholar

  • Bohdalová, M., and Šlahor, Ľ., 2008. Simulations of the correlated financial risk factors. Journal of Applied Mathematics, Statistics and Informatics, 4(1), 89-97.Google Scholar

  • Campbell, S. D., and Diebold, F. X., 2005. Stock returns and expected business conditions: Half a century of direct evidence. http://www.ssc.upenn.edu/~fdiebold/papers/paper70/cd3a.pdf.Google Scholar

  • Daly, K., Nielsen, A. E. B., and Oppenheimer, P., 2010. Finding fair value in global equities: Part II - Forecasting returns. Journal of Portfolio Management. http://www.iijournals.com/doi/pdfplus/10.3905/jpm.2010.36.3.056.CrossrefGoogle Scholar

  • Financeyahoo, 2017. California. 2017. from http://finance.yahoo.com/quote/BNP.F/history?period1=946681200&period2=1485730800&interval=1d&filter=history&frequency=1dGoogle Scholar

  • Franke, J., Härdle, W. K., and Hafner, C. M., 2008. Statistics of Financial Markets. Berlin, Heidelberg: Springer-Verlag. doi:CrossrefGoogle Scholar

  • Gujarati, D. N., and Porter, D. C., 2009. Basic Econometrics (5th ed.). Singapore: McGraw Hill.Google Scholar

  • Hull, J. C., 2012. Options, futures, and other derivatives (8th ed.). Boston: Prentice Hall.Google Scholar

  • Kenett, R. S., Rahav, E., and Steinberg, D. M., 2006. Bootstrap Analysis of Designed Experiments. Quality and Reliability Engineering International, 22(6), 659-667. doi:CrossrefGoogle Scholar

  • Lettau, M., and Ludvigson, S., 2001. Consumption, aggregate wealth, and expected stock returns. The Journal of Finance, LVI(3), 815-849.Google Scholar

  • Nnorges Bank Investment Management, 2012a. Economic Growth and Equity Returns. NBIM Discussion Note, 5. https://www.nbim.no/globalassets/documents/dicussionpaper/2012/discussionnote_5-12_final.pdf.Google Scholar

  • Nnorges Bank Investment Management, 2012b. Time-varying expected returns and investor heterogeneity: foundations for rebalancing. NBIM Discussion Note, 1. www.nbim.no/globalassets/documents/dicussion-paper/2012/discussionnote_1-12_v4.pdf.Google Scholar

  • Proksová, D., and Bohdalová, M., 2015. Bond yield spreads in the Eurozone. Analele ştiinţifice ale Universităţii "Al.I. Cuza" din Iaşi. Ştiinţe economice / Scientific Annals of the Alexandru Ioan Cuza University of Iasi. Economic Sciences, 62(2), 221-239. doi:CrossrefGoogle Scholar

  • Smith, J. P., and Beceren, M., 2011. The hidden driver of GEM. London: Deutsche Bank Global Markets Research.Google Scholar

  • Tsay, R. S., 2010. Analysis of Financial Time Series (3rd ed.). Chicago: John Wiley & Sons. doi:CrossrefGoogle Scholar

  • Verbeek, M., 2008. A Guide to Modern Econometrics (3rd ed.). West Sussex: John Wiley & Sons.Google Scholar

  • Wallick, D. W., Shanahan, J., Tasopoulos, C., and Yoon, J., 2012. The global case for strategic asset allocation. Vanguard research paper. https://institutional.vanguard.com/iam/pdf/VIPS_global_case.pdf.Google Scholar

About the article

Published Online: 2017-08-01

Published in Print: 2017-06-27

Citation Information: Scientific Annals of Economics and Business, Volume 64, Issue 2, Pages 155–170, ISSN (Online) 2501-3165, DOI: https://doi.org/10.1515/saeb-2017-0010.

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© 2017. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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