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The Sum and Difference of Two Lognormal Random Variables

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  • C. F. Lo

Abstract

We have presented a new unified approach to model the dynamics of both the sum and difference of two correlated lognormal stochastic variables. By the Lie‐Trotter operator splitting method, both the sum and difference are shown to follow a shifted lognormal stochastic process, and approximate probability distributions are determined in closed form. Illustrative numerical examples are presented to demonstrate the validity and accuracy of these approximate distributions. In terms of the approximate probability distributions, we have also obtained an analytical series expansion of the exact solutions, which can allow us to improve the approximation in a systematic manner. Moreover, we believe that this new approach can be extended to study both (1) the algebraic sum of N lognormals, and (2) the sum and difference of other correlated stochastic processes, for example, two correlated CEV processes, two correlated CIR processes, and two correlated lognormal processes with mean‐reversion.

Suggested Citation

  • C. F. Lo, 2012. "The Sum and Difference of Two Lognormal Random Variables," Journal of Applied Mathematics, John Wiley & Sons, vol. 2012(1).
  • Handle: RePEc:wly:jnljam:v:2012:y:2012:i:1:n:838397
    DOI: 10.1155/2012/838397
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    References listed on IDEAS

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    1. Xin Gao & Hong Xu & Dong Ye, 2009. "Asymptotic Behavior of Tail Density for Sum of Correlated Lognormal Variables," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2009, pages 1-28, August.
    2. Moshe Arye Milevsky & Steven E. Posner, 1999. "Asian Options, The Sum Of Lognormals, And The Reciprocal Gamma Distribution," World Scientific Book Chapters, in: Marco Avellaneda (ed.), Quantitative Analysis In Financial Markets Collected Papers of the New York University Mathematical Finance Seminar, chapter 7, pages 203-218, World Scientific Publishing Co. Pte. Ltd..
    3. Dhaene, J. & Denuit, M. & Goovaerts, M. J. & Kaas, R. & Vyncke, D., 2002. "The concept of comonotonicity in actuarial science and finance: applications," Insurance: Mathematics and Economics, Elsevier, vol. 31(2), pages 133-161, October.
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    Cited by:

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    2. Yong-Ki Ma, 2021. "Correlated Log‐Normal Random Variables under a Multiscale Volatility Model," Advances in Mathematical Physics, John Wiley & Sons, vol. 2021(1).

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