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Haar-wavelet based approximation for pricing American options under linear complementarity formulations

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dc.contributor.author Kumar, Devendra
dc.date.accessioned 2023-07-22T04:30:17Z
dc.date.available 2023-07-22T04:30:17Z
dc.date.issued 2020-10
dc.identifier.uri https://onlinelibrary.wiley.com/doi/full/10.1002/num.22568
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/10961
dc.description.abstract In this manuscript, we present a novel and highly accurate wavelet-based approximation technique to explore the sensitivities and value of American options diagnosed by linear complementarity problems. For a detailed analysis of such financially relevant problems, we transform the actual final value problem into a dimensionless initial value problem. To avoid the unacceptable large truncation error, the unbounded domain is trimmed into a bounded domain. A remarkable observation is that to investigate the various physical and numerical aspects of the options' sensitivities; the proposed scheme is efficient as it explicitly provides the numerical approximation of all the derivatives of the solution function. The multiresolution technique of the wavelets and the convergence of the proposed wavelet scheme are comprehensively analyzed. The wavelet analysis is accompanied by illustrative examples to demonstrate the proficiency and robustness of the present method coupled with graphical representations. It has been shown that the present method is efficient to solve free boundary problems. It is worthy to note that the highly accurate and promising computational results are enough to confirm the performance of the proposed method. The simulated results of options' Greeks analyzed and discussed have vast applications in different financial institutes and trading markets en_US
dc.language.iso en en_US
dc.publisher Wiley en_US
dc.subject Mathematics en_US
dc.subject Haar-wavelet en_US
dc.title Haar-wavelet based approximation for pricing American options under linear complementarity formulations en_US
dc.type Article en_US


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