eprintid: 739
rev_number: 12
eprint_status: archive
userid: 7
dir: disk0/00/00/07/39
datestamp: 2011-07-29 10:52:50
lastmod: 2011-08-04 07:29:05
status_changed: 2011-07-29 10:52:50
type: book_section
metadata_visibility: show
item_issues_count: 0
creators_name: Bemporad, Alberto
creators_name: Gabbriellini, Tommaso
creators_name: Puglia, Laura
creators_name: Bellucci, Leonardo
creators_id: alberto.bemporad@imtlucca.it
creators_id: 
creators_id: 
creators_id: 
title: Scenario-based stochastic model predictive control for dynamic option hedging
ispublished: pub
subjects: HB
subjects: QA
subjects: TJ
divisions: CSA
full_text_status: none
keywords: SMPC; dynamic option hedging; least squares problem; option pricing engine; scenario-based stochastic model predictive control; stochastic optimization problem; financial management; least squares approximations; optimisation;predictive control; pricing; stochastic systems
abstract: For a rather broad class of financial options, this paper proposes a stochastic model predictive control (SMPC) approach for dynamically hedging a portfolio of underlying assets. By employing an option pricing engine to estimate future realizations of option prices on a finite set of one-step-ahead scenarios, the resulting stochastic optimization problem is easily solved as a least-squares problem at each trading date with as many variables as the number of traded assets and as many constraints as the number of predicted scenarios. After formulating the dynamic hedging problem as a stochastic control problem, we test its ability to replicate the payoff at expiration date for plain vanilla and exotic options. We show not only that relatively small hedging errors are obtained in spite of price realizations, but also that the approach is robust with respect to market modeling errors.
date: 2010-12
date_type: published
publisher: IEEE
place_of_pub: Hilton Atlanta Hotel, Atlanta, December 15-17, 2010
pagerange: 6089 -6094
event_title: Decision and Control (CDC), 2010 49th IEEE Conference on
id_number: 10.1109/CDC.2010.5717004
refereed: TRUE
isbn: 978-1-4244-7745-6 
book_title: Decision and Control Conference
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5717004&isnumber=5716927
citation:   Bemporad, Alberto and Gabbriellini, Tommaso and Puglia, Laura and Bellucci, Leonardo  Scenario-based stochastic model predictive control for dynamic option hedging.   In:  Decision and Control Conference.   IEEE, Hilton Atlanta Hotel, Atlanta, December 15-17, 2010, 6089 -6094.  ISBN 978-1-4244-7745-6       (2010)