Forecast of business performance using an agent-based model and its application to a decision tree Monte Carlo business valuation

Authored by Y Ikeda, O Kubo, Y Kobayashi

Date Published: 2004-12-01

DOI: 10.1016/j.physa.2004.06.093

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

The stochastic-agent-on-tree method for business valuation is proposed by applying the game theory to the agent-based model. The proposed method is reduced to the real option valuation method using approximations. Demand forecasting and business valuation for computer-related industries are investigated as a case study. (C) 2004 Elsevier B.V. All rights reserved.

Tags

Brownian motion Langevin Monte Carlo methods classical statistical mechanics decision theory and game theory etc.) particle dynamics stochastic analysis methods (Fokker-Planck