ON SPREAD OPTION PRICING USING TWO-DIMENSIONAL FOURIER TRANSFORM

被引:8
|
作者
Alfeus, Mesias [1 ]
Schlogl, Erik [2 ,3 ]
机构
[1] Univ Technol Sydney, Sydney, NSW 2007, Australia
[2] Univ Technol Sydney, Quantitat Finance Res Ctr, 15 Broadway, Sydney, NSW 2007, Australia
[3] Univ Johannesburg, Dept Stat, Fac Sci, POB 524, ZA-2006 Auckland Pk, South Africa
关键词
Spread options; Fourier transform; numerical methods; two-dimensional Parseval's identity; FFTW;
D O I
10.1142/S0219024919500237
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Spread options are multi-asset options with payoffs dependent on the difference of two underlying financial variables. In most cases, analytically closed form solutions for pricing such payoffs are not available, and the application of numerical pricing methods turns out to be nontrivial. We consider several such nontrivial cases and explore the performance of the highly efficient numerical technique of Hurd & Zhou[(2010) A Fourier transform method for spread option pricing, SIAM J. Financial Math. 1(1), 142-157], comparing this with Monte Carlo simulation and the lower bound approximation formula of Caldana & Fusai[(2013) A general closed-form spread option pricing formula, Journal of Banking & Finance 37, 4893-4906]. We show that the former is in essence an application of the two-dimensional Parseval's Identity. As application examples, we price spread options in a model where asset prices are driven by a multivariate normal inverse Gaussian (NIG) process, in a three-factor stochastic volatility model, as well as in examples of models driven by other popular multivariate Levy processes such as the variance Gamma process, and discuss the price sensitivity with respect to volatility. We also consider examples in the fixed-income market, specifically, on cross-currency interest rate spreads and on LIBOR/OIS spreads.
引用
收藏
页数:20
相关论文
共 50 条
  • [21] Resonance lineshapes in two-dimensional Fourier transform spectroscopy
    Siemens, Mark E.
    Moody, Galan
    Li, Hebin
    Bristow, Alan D.
    Cundiff, Steven T.
    [J]. OPTICS EXPRESS, 2010, 18 (17): : 17699 - 17708
  • [22] An interactive tool to explore the two-dimensional Fourier transform
    Stoeger, B.
    [J]. ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES, 2022, 78 : E303 - E304
  • [23] THE NONLINEAR FOURIER TRANSFORM FOR TWO-DIMENSIONAL SUBCRITICAL POTENTIALS
    Music, Michael
    [J]. INVERSE PROBLEMS AND IMAGING, 2014, 8 (04) : 1151 - 1167
  • [24] Experimental consideration of two-dimensional Fourier transform spectroscopy
    Zhou, Liang
    Tian, Lie
    Zhang, Wen-kai
    [J]. CHINESE JOURNAL OF CHEMICAL PHYSICS, 2020, 33 (04) : 385 - 393
  • [25] Coherent two-dimensional Fourier transform infrared spectroscopy
    Khalil, M
    Demirdöven, N
    Tokmakoff, A
    [J]. ULTRAFAST PHENOMENA XIII, 2003, 71 : 583 - 585
  • [26] Windowed Fourier transform of two-dimensional quaternionic signals
    Bahri, Mawardi
    Hitzer, Eckhard S. M.
    Ashino, Ryuichi
    Vaillancourt, Remi
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2010, 216 (08) : 2366 - 2379
  • [27] Fast computation of the two-dimensional discrete Fourier transform
    Sundararajan, D
    Ahmad, MO
    [J]. PROCEEDINGS OF THE 39TH MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS I-III, 1996, : 759 - 762
  • [28] Femtosecond two-dimensional Fourier transform electronic spectroscopy
    Yetzbacher, Michael K.
    Smith, Eric Ryan
    Cho, Byungmoon
    Kitney, Katherine A.
    Jonas, David A.
    [J]. 2007 PACIFIC RIM CONFERENCE ON LASERS AND ELECTRO-OPTICS, VOLS 1-4, 2007, : 296 - 297
  • [29] Fast adaptive algorithm for two-dimensional Fourier transform
    Puchala, Dariusz
    Yatsymirskyy, Mykhaylo
    [J]. PRZEGLAD ELEKTROTECHNICZNY, 2007, 83 (10): : 43 - 46
  • [30] Lookback option pricing using the Fourier transform B-spline method
    Haslip, Gareth G.
    Kaishev, Vladimir K.
    [J]. QUANTITATIVE FINANCE, 2014, 14 (05) : 789 - 803