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Optimal switching with applications ...

Ludkovski, Michael.

Optimal switching with applications to energy tolling agreements.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Optimal switching with applications to energy tolling agreements.
Author:	Ludkovski, Michael.
Description:	123 p.
Notes:	Adviser: Rene Carmona.
Notes:	Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1701.
Contained By:	Dissertation Abstracts International66-03B.
Subject:	Operations Research.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3169807
ISBN:	0542059878

Optimal switching with applications to energy tolling agreements.
Ludkovski, Michael.

Optimal switching with applications to energy tolling agreements. - 123 p.

Adviser: Rene Carmona.

Thesis (Ph.D.)--Princeton University, 2005.

Our main contribution is a new method of numerical solution based on Monte Carlo regressions. The scheme uses dynamic programming to simultaneously approximate the optimal switching times along all the simulated paths. Convergence analysis is carried out and numerical results are illustrated with a variety of concrete examples. We then benchmark and compare our scheme to alternative numerical methods. On a mathematical level, we contribute to the numerical analysis of reflected backward stochastic differential equations and quasi-variational inequalities. The final part of the dissertation proposes fruitful extensions to tackle other financial problems such as gas storage, exhaustible resources, hedging supply guarantees and energy risk management.

ISBN: 0542059878Subjects--Topical Terms:

227148
Operations Research.

Optimal switching with applications to energy tolling agreements.
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100 0 $a Ludkovski, Michael. $3 237502
245 1 0 $a Optimal switching with applications to energy tolling agreements.
300 $a 123 p.
500 $a Adviser: Rene Carmona.
500 $a Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1701.
502 $a Thesis (Ph.D.)--Princeton University, 2005.
520 # $a Our main contribution is a new method of numerical solution based on Monte Carlo regressions. The scheme uses dynamic programming to simultaneously approximate the optimal switching times along all the simulated paths. Convergence analysis is carried out and numerical results are illustrated with a variety of concrete examples. We then benchmark and compare our scheme to alternative numerical methods. On a mathematical level, we contribute to the numerical analysis of reflected backward stochastic differential equations and quasi-variational inequalities. The final part of the dissertation proposes fruitful extensions to tackle other financial problems such as gas storage, exhaustible resources, hedging supply guarantees and energy risk management.
520 # $a To overcome both of these limitations, we propose a new framework based on recursive optimal stopping. Our model demonstrates that the optimal dispatch policies can be described with the aid of 'switching boundaries', similar to standard American options. In turn, this provides new insight regarding the qualitative properties of the value function.
520 # $a We consider the problem of optimal switching with finite horizon. This special case of stochastic impulse control naturally arises during analysis of operational flexibility of exotic energy derivatives. The current practice for such problems relies on Markov decision processes that have poor dimension-scaling properties, or on strips of spark spread options that ignore the operational constraints of the asset.
590 $a School code: 0181.
650 # 0 $a Operations Research. $3 227148
650 # 0 $a Mathematics. $3 184409
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710 0 # $a Princeton University. $3 212488
773 0 # $g 66-03B. $t Dissertation Abstracts International
790 $a 0181
790 1 0 $a Carmona, Rene, $e advisor
791 $a Ph.D.
792 $a 2005
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