A Longstaff and Schwartz Approach to the Early Election Problem
Author(s) -
Elliot Tonkes,
Dharma Lesmono
Publication year - 2012
Publication title -
advances in decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.178
H-Index - 13
eISSN - 2090-3367
pISSN - 2090-3359
DOI - 10.1155/2012/287579
Subject(s) - optimal stopping , valuation (finance) , monte carlo method , computer science , democracy , mathematical economics , economics , politics , mathematical optimization , finance , mathematics , political science , statistics , law
In many democratic parliamentary systems, election timing is an important decision availed to governments according to sovereign political systems. Prudent governments can take advantage of this constitutional option in order to maximize their expected remaining life in power. The problem of establishing the optimal time to call an election based on observed poll data has been well studied with several solution methods and various degrees of modeling complexity. The derivation of the optimal exercise boundary holds strong similarities with the American option valuation problem from mathematical finance. A seminal technique refined by Longstaff and Schwartz in 2001 provided a method to estimate the exercise boundary of the American options using a Monte Carlo method and a least squares objective. In this paper, we modify the basic technique to establish the optimal exercise boundary for calling a political election. Several innovative adaptations are required to make the method work with the additional complexity in the electoral problem. The transfer of Monte Carlo methods from finance to determine the optimal exercise of real-options appears to be a new approach
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