A4 Conference proceedings

Developing a Decision Tree Block for the Exercise Boundary Fitting Method


Open Access publication

Publication Details
Authors: Kozlova Mariia, Lohrmann Christoph
Publication year: 2019
Language: English
Related Journal or Series Information: LUT Scientific and Expertise Publications : Tutkimusraportit - Research reports
Title of parent publication: NSAIS-ROW 2019 – Workshop on Adaptive and Intelligent Systems and Real Options
Volume number: 97
eISBN: 978-952-335-400-5
ISSN: 2243-3376
JUFO-Level of this publication: 0
Open Access: Open Access publication

Abstract

This extended abstract aims at developing a decision tree block for a real option model based on the exercise boundary fitting method. The method allows for multiple real options and multiple sources of uncertainty, while also complying with financial theory. When multiple real options are introduced, the decision tree that represents all the possible combinations of exercising the available options can become complex. It should be automated for the purpose of preserving flexibility of the model. And therefore, the whole process of decision tree construction should be generalized. This abstract presents the solution to this problem. With this development the real option model rises to a new level and enables wider variety of cases to be analyzed.


Last updated on 2020-17-01 at 14:54