eprintid: 745
rev_number: 13
eprint_status: archive
userid: 7
dir: disk0/00/00/07/45
datestamp: 2011-07-29 11:00:09
lastmod: 2012-07-09 09:42:48
status_changed: 2012-07-09 09:42:48
type: book_section
metadata_visibility: show
item_issues_count: 0
creators_name: Bemporad, Alberto
creators_name: Puglia, Laura
creators_name: Gabbriellini, Tommaso
creators_id: alberto.bemporad@imtlucca.it
creators_id: 
creators_id: 
title: A stochastic model predictive control approach to dynamic option hedging with transaction costs
ispublished: pub
subjects: HG
subjects: QA
divisions: CSA
full_text_status: none
pres_type: paper
keywords: Contracts, Europe, Measurement uncertainty, Minimization, Portfolios, Predictive models, Stochastic processes.
abstract: This paper proposes a stochastic model predictive control (SMPC) approach to hedging derivative contracts (such as plain vanilla and exotic options) in the presence of transaction costs. The methodology is based on the minimization of a stochastic measures of the hedging error predicted for the next trading date. Three different measures are proposed to determine the optimal composition of the replicating portfolio. The first measure is a combination of variance and expected value of the hedging error, leading to a quadratic program (QP) to solve at each trading date; the second measure is the conditional value at risk (CVaR), a common index used in finance quantifying the average loss over a subset of worst-case realizations, leading to a linear programming (LP) formulation; the third approach is of min-max type and attempts at minimizing the largest possible hedging error, also leading to a (smaller scale) linear program. The hedging performance obtained by the three different measures is tested and compared in simulation on a European call and a barrier option.
date: 2011
date_type: published
publisher: IEEE
pagerange: 3862-3867
event_title: American Control Conference
event_location: San Francisco, USA
event_dates: June 29-July 01, 2011
event_type: conference
refereed: TRUE
isbn: 978-1-4577-0080-4
book_title: Proceedings of the American Control Conference (ACC), 2011
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5991205&isnumber=5989965
citation:   Bemporad, Alberto and Puglia, Laura and Gabbriellini, Tommaso  A stochastic model predictive control approach to dynamic option hedging with transaction costs.   In:  Proceedings of the American Control Conference (ACC), 2011.   IEEE, pp. 3862-3867.  ISBN 978-1-4577-0080-4      (2011)