IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/83669.html

RBC LiONS™ S&P 500 Buffered Protection Securities (USD) Series 4 Analysis Option Pricing Analysis, Issuing Company Risk-hedging Analysis, and Recommended Investment Strategy

Author

Listed:
  • Tan, Zekuang

Abstract

This paper will compute the value of the RBC financial derivative-RBC LiONS™ S&P 500 Buffered Protection Securities (USD), Series 4 by utilizing the Black-Scholes Option Pricing Model. In order conduct a thorough analysis of the securities, the paper will compare the model value with the actual price at which the security was issued and the price at which it was traded. This model will help establish a recommended strategy for the issuing company to hedge the liability incurred by the security issued, and provide a possible hedging strategy for the investors.

Suggested Citation

  • Tan, Zekuang, 2017. "RBC LiONS™ S&P 500 Buffered Protection Securities (USD) Series 4 Analysis Option Pricing Analysis, Issuing Company Risk-hedging Analysis, and Recommended Investment Strategy," MPRA Paper 83669, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:83669
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/83669/1/MPRA_paper_83669.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. MacBeth, James D & Merville, Larry J, 1979. "An Empirical Examination of the Black-Scholes Call Option Pricing Model," Journal of Finance, American Finance Association, vol. 34(5), pages 1173-1186, December.
    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. Jurczenko, Emmanuel & Maillet, Bertrand & Negrea, Bogdan, 2002. "Revisited multi-moment approximate option pricing models a general comparison (Part 1)," LSE Research Online Documents on Economics 24950, London School of Economics and Political Science, LSE Library.
    2. Bianconi, Marcelo & MacLachlan, Scott & Sammon, Marco, 2015. "Implied volatility and the risk-free rate of return in options markets," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 1-26.
    3. Michael J. Dueker & Thomas W. Miller, 1996. "Market microstructure effects on the direct measurement of the early exercise premium in exchange-listed options," Working Papers 1996-013, Federal Reserve Bank of St. Louis.
    4. Charles J. Corrado & Tie Su, 1996. "Skewness And Kurtosis In S&P 500 Index Returns Implied By Option Prices," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 19(2), pages 175-192, June.
    5. Dong, Chaohua & Gao, Jiti, 2013. "Solving replication problems in a complete market by orthogonal series expansion," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 306-317.
    6. Henryk Gzyl & German Molina & Enrique ter Horst, 2009. "Assessment and propagation of input uncertainty in tree‐based option pricing models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 275-308, May.
    7. Christine A. Brown, 1999. "The Volatility Structure Implied by Options on the SPI Futures Contract," Australian Journal of Management, Australian School of Business, vol. 24(2), pages 115-130, December.
    8. Shih-Ping Feng, 2011. "The Liquidity Effect In Option Pricing: An Empirical Analysis," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 5(2), pages 35-43.
    9. Hsuan-Chu Lin & Ren-Raw Chen & Oded Palmon, 2016. "Explaining the volatility smile: non-parametric versus parametric option models," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 907-935, May.
    10. Trinidad Segovia, J.E. & Fernández-Martínez, M. & Sánchez-Granero, M.A., 2012. "A note on geometric method-based procedures to calculate the Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(6), pages 2209-2214.
    11. Patrick Asea & Mthuli Nube, 1997. "Heterogeneous Information Arrival and Option Pricing," UCLA Economics Working Papers 763, UCLA Department of Economics.
    12. R. L. Brown & T. J. Shevlin, 1983. "Stock Market Efficiency and Price Predictions Implicit in Option Trading," Australian Journal of Management, Australian School of Business, vol. 8(2), pages 71-93, December.
    13. Ming-Yuan Leon Li & Chun-Nan Chen, 2010. "Examining the interrelation dynamics between option and stock markets using the Markov-switching vector error correction model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(7), pages 1173-1191.
    14. Cornelis A. Los, 2004. "The Changing Concept of Financial Risk," Finance 0409034, University Library of Munich, Germany.
    15. repec:ags:aaea22:343544 is not listed on IDEAS
    16. David Edelman & Thomas Gillespie, 2000. "The Stochastically Subordinated Poisson Normal Process for Modelling Financial Assets," Annals of Operations Research, Springer, vol. 100(1), pages 133-164, December.
    17. Asea, Patrick K. & Ncube, Mthuli, 1998. "Heterogeneous information arrival and option pricing," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 291-323.
    18. Michael Weba, 2024. "Investment strategies based on forecasts are (almost) useless," Papers 2408.01772, arXiv.org.
    19. Eric Jacquier & Robert Jarrow, "undated". "Model Error in Contingent Claim Models (Dynamic Evaluation)," Rodney L. White Center for Financial Research Working Papers 7-96, Wharton School Rodney L. White Center for Financial Research.
    20. Kai-Li Wang & Mei-Ling Chen, 2007. "The dynamics in the spot, futures, and call options with basis asymmetries: an intraday analysis in a generalized multivariate GARCH-M MSKST framework," Review of Quantitative Finance and Accounting, Springer, vol. 29(4), pages 371-394, November.
    21. Barunik, Jozef & Barunikova, Michaela, 2015. "Revisiting the long memory dynamics of implied-realized volatility relation: A new evidence from wavelet band spectrum regression," FinMaP-Working Papers 43, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:83669. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.