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Long Memory Options: LM Evidence and Simulations

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  • Sutthisit Jamdee

    (Kent State University)

  • Cornelis A. Los

    (Kent State University)

Abstract

This paper demonstrates the impact of the observed financial market persistence or long term memory on European option valuation by simple simulation. Many empirical researchers have observed the non-Fickian degrees of persistence or long memory in the financial markets different from the Fickian neutral independence (i.i.d.) of the returns innovations assumption of Black-Scholes' geometric Brownian motion assumption. Moreover, Elliott and van der Hoek (2003) provide a theoretical framework for incorporating these findings into the Black- Scholes risk-neutral valuation framework. This paper provides the first graphical demonstration why and how such long term memory phenomena change European option values and provides thereby a basis for informed long term memory arbitrage. By using a simple mono-fractal Fractional Brownian motion, it is easy to incorporate the various degrees of persistence into the Black-Scholes pricing formula. Long memory options are of considerable importance in corporate remuneration packages, since stock options are written on a company's own shares for long expiration periods. It makes a significant difference in the valuation when an option is 'blue' or when it is 'red.' For a proper valuation of such stock options, the degrees of persistence of the companies' share markets must be precisely measured and properly incorporated in the warrant valuation, otherwise substantial pricing errors may result.

Suggested Citation

  • Sutthisit Jamdee & Cornelis A. Los, 2005. "Long Memory Options: LM Evidence and Simulations," Finance 0505003, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpfi:0505003
    Note: Type of Document - pdf; pages: 34. This paper has been presented at the International Conference on Risk Management and Quantitative Approaches in Finance, Gainesville, FL, April 6 - 8, 2005
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    2. Los, Cornelis A. & Tungsong, Satjaporn, 2008. "Investment Model Uncertainty and Fair Pricing," MPRA Paper 8859, University Library of Munich, Germany.
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    4. Kyaw, NyoNyo A. & Los, Cornelis A. & Zong, Sijing, 2006. "Persistence characteristics of Latin American financial markets," Journal of Multinational Financial Management, Elsevier, vol. 16(3), pages 269-290, July.
    5. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    6. Erdinc Akyildirim & Ahmet Goncu & Ahmet Sensoy, 2021. "Prediction of cryptocurrency returns using machine learning," Annals of Operations Research, Springer, vol. 297(1), pages 3-36, February.
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    More about this item

    Keywords

    Options; Long Memory; Persistence; Hurst Exponent; Identification; Simulation; Executive Remuneration;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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