Derivatives pricing using signature payoffs

2018-09-25

We introduce signature payoffs, a family of path-dependent derivatives that are given in terms of the signature of the price path of the underlying asset. We show that these derivatives are dense in the space of continuous payoffs, a result that is exploited to quickly price arbitrary continuous payoffs. This approach to pricing derivatives is then tested with European options, American options, Asian options, lookback options and variance swaps. As we show, signature payoffs can be used to price these derivatives with very high accuracy.

📄 PDF Abstract BibTeX arXiv:1809.09466

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Distributional Reinforcement Learning on Path-dependent Options

2025-07-16 · Ahmet Umur Özsoy

We reinterpret and propose a framework for pricing path-dependent financial derivatives by estimating the full distribution of payoffs using Distributional Reinforcement Learning (DistRL). Unlike traditional methods that…

Distributional Reinforcement Learning reinforcement-learning Reinforcement Learning Uncertainty Quantification

Rational Models for Inflation-Linked Derivatives

2018-01-26 · Henrik Dam, Andrea Macrina, David Skovmand, David Sloth

We construct models for the pricing and risk management of inflation-linked derivatives. The models are rational in the sense that linear payoffs written on the consumer price index have prices that are rational function…

Management

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Derivatives pricing using signature payoffs

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