This paper presents a new and flexible computational approach to derivative hedging. It is based on the use of least squares regression in order to compute the hedging portfolio. This nonparametric methodology can be readily applied to any derivative contract written on a single underlying risky asset in a complete market with continuous Markov price paths. We illustrate this technique computing sensitivities on plain vanilla and exotic options with both European and American exercise style. The achieved numerical accuracy is always comparable with the best simulation and semianalytic techniques presented in the literature. © 2004 Elsevier B.V. All rights reserved.

Hedging using simulation: A least squares approach

Tebaldi C.
2005

Abstract

This paper presents a new and flexible computational approach to derivative hedging. It is based on the use of least squares regression in order to compute the hedging portfolio. This nonparametric methodology can be readily applied to any derivative contract written on a single underlying risky asset in a complete market with continuous Markov price paths. We illustrate this technique computing sensitivities on plain vanilla and exotic options with both European and American exercise style. The achieved numerical accuracy is always comparable with the best simulation and semianalytic techniques presented in the literature. © 2004 Elsevier B.V. All rights reserved.
2005
Tebaldi, C.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/192744
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 6
social impact