Fast Fourier Transform of Multi-Assets Options under Economic Recession Induced Uncertainties

Bankole, Philip Ajibola and Ugbebor, Olabisi O. (2019) Fast Fourier Transform of Multi-Assets Options under Economic Recession Induced Uncertainties. American Journal of Computational Mathematics, 09 (03). pp. 143-157. ISSN 2161-1203

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Abstract

A Fast Fourier transform approach has been presented by Carr & Madan (2009) on a single underlying asset. In this current research paper, we present fast Fourier transform algorithm for the valuation of Multi-asset Options under Economic Recession Induced Uncertainties. The issue of multi-dimension in both finite and infinite case of Options is part of the focus of this research. The notion of economic recession was incorporated. An intuition behind the introduction of recession induced volatility uncertainty is revealed by huge volatility variation during the period of economic recession compared to the period of recession-free. Nigeria economic recession outbreak in 2016 and its effects on the uncertainty of the payoffs of Nigeria Stocks Exchange (NSE) among other investments was among the motivating factors for proposing economic recession induced volatility in options pricing. The application of the proposed Fast Fourier Transform algorithm in handling multi-assets options was shown. A new result on options pricing was achieved and capable of yielding efficient option prices during and out of recession. Numerical results were presented on assets in 3-dimensions as an illustration taking Black Scholes prices as a bench mark for method effectiveness comparison. The key findings of this research paper among other crucial contributions could be seen in computational procedure of options valuation in multi-dimensions and uncertainties in options payoffs under the exposure of economic recession.

Item Type: Article
Subjects: GO for STM > Mathematical Science
Depositing User: Unnamed user with email support@goforstm.com
Date Deposited: 22 Jun 2023 06:57
Last Modified: 02 Nov 2023 05:33
URI: http://archive.article4submit.com/id/eprint/1107

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