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A computational investigation of the optimal Halton sequence in QMC applications

Author

Listed:
  • Bayousef Manal

    (Department of Computer Science, Florida State University, Tallahassee, FL 32306-4530, USA)

  • Mascagni Michael

    (Department of Computer Science, Florida State University, Tallahassee, FL 32306-4530; and National Institute of Standards and Technology, Gaithersburg, MD 20899, USA)

Abstract

We propose the use of randomized (scrambled) quasirandom sequences for the purpose of providing practical error estimates for quasi-Monte Carlo (QMC) applications. One popular quasirandom sequence among practitioners is the Halton sequence. However, Halton subsequences have correlation problems in their highest dimensions, and so using this sequence for high-dimensional integrals dramatically affects the accuracy of QMC. Consequently, QMC studies have previously proposed several scrambling methods; however, to varying degrees, scrambled versions of Halton sequences still suffer from the correlation problem as manifested in two-dimensional projections. This paper proposes a modified Halton sequence (MHalton), created using a linear digital scrambling method, which finds the optimal multiplier for the Halton sequence in the linear scrambling space. In order to generate better uniformity of distributed sequences, we have chosen strong MHalton multipliers up to 360 dimensions. The proposed multipliers have been tested and proved to be stronger than several sets of multipliers used in other known scrambling methods. To compare the quality of our proposed scrambled MHalton sequences with others, we have performed several extensive computational tests that use L2{L_{2}}-discrepancy and high-dimensional integration tests. Moreover, we have tested MHalton sequences on Mortgage-backed security (MBS), which is one of the most widely used applications in finance. We have tested our proposed MHalton sequence numerically and empirically, and they show optimal results in QMC applications. These confirm the efficiency and safety of our proposed MHalton over scrambling sequences previously used in QMC applications.

Suggested Citation

  • Bayousef Manal & Mascagni Michael, 2019. "A computational investigation of the optimal Halton sequence in QMC applications," Monte Carlo Methods and Applications, De Gruyter, vol. 25(3), pages 187-207, September.
    • Handle: RePEc:bpj:mcmeap:v:25:y:2019:i:3:p:187-207:n:2
    DOI: 10.1515/mcma-2019-2041
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    References listed on IDEAS

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    1. S. Ninomiya & S. Tezuka, 1996. "Toward real-time pricing of complex financial derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 3(1), pages 1-20.
    2. Chi, H. & Mascagni, M. & Warnock, T., 2005. "On the optimal Halton sequence," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 70(1), pages 9-21.
    3. Hofer, Roswitha, 2018. "Halton-type sequences in rational bases in the ring of rational integers and in the ring of polynomials over a finite field," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 143(C), pages 78-88.
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