Pricing TARN Using a Finite Difference Method
Xiaolin Luo, Pavel Shevchenko

TL;DR
This paper introduces a finite difference scheme for pricing TARN options, offering a faster and more accurate alternative to Monte Carlo methods, especially for complex volatility models.
Contribution
The paper presents a novel finite difference approach for TARN option pricing, detailing implementation steps not previously available in literature.
Findings
Finite difference method can be an order of magnitude faster than Monte Carlo for TARN pricing.
Finite difference scheme provides more robust and accurate Greeks estimation.
Method performs well under constant, time-dependent, and local volatility models.
Abstract
Typically options with a path dependent payoff, such as Target Accumulation Redemption Note (TARN), are evaluated by a Monte Carlo method. This paper describes a finite difference scheme for pricing a TARN option. Key steps in the proposed scheme involve tracking of multiple one-dimensional finite difference solutions, application of jump conditions at each cash flow exchange date, and a cubic spline interpolation of results after each jump. Since a finite difference scheme for TARN has significantly different features from a typical finite difference scheme for options with a path independent payoff, we give a step by step description on the implementation of the scheme, which is not available in the literature. The advantages of the proposed finite difference scheme over the Monte Carlo method are illustrated by examples with three different knockout types. In the case of constant or…
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