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ROM Simulation with Rotation Matrices

Author

Listed:
  • Daniel Ledermann

    (ICMA Centre, Henley Business School, University of ReadingAuthor-Name: Carol Alexander
    ICMA Centre, Henley Business School, University of Reading)

Abstract

This paper explores the properties of random orthogonal matrix (ROM) simulation when the random matrix is drawn from the class of rotational matrices. We describe the characteristics of ROM simulated samples that are generated using random Hessenberg, Cayley and exponential matrices and compare the computational efficiency of parametric ROM simulations with standard Monte Carlo techniques.

Suggested Citation

  • Daniel Ledermann, 2011. "ROM Simulation with Rotation Matrices," ICMA Centre Discussion Papers in Finance icma-dp2011-06, Henley Business School, University of Reading.
    • Handle: RePEc:rdg:icmadp:icma-dp2011-06
    as

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    File URL: http://www.icmacentre.ac.uk/files/discussion-papers/DP2011-06.pdf
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    References listed on IDEAS

    as
    1. Blattberg, Robert C & Gonedes, Nicholas J, 1974. "A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices," The Journal of Business, University of Chicago Press, vol. 47(2), pages 244-280, April.
    2. Marsaglia, George & Tsang, Wai Wan & Wang, Jingbo, 2003. "Evaluating Kolmogorov's Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i18).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Computational efficiency; L matrices; Ledermann matrix; Random Orthogonal Matrix (ROM); Rotation matrix; Simulation;
    All these keywords.

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