A parsimonious model for generating arbitrage-free scenario trees

Andrea Consiglio, Angelo Carollo, Stavros A. Zenios

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Simulation models of economic, financial and business risk factors are widely used to assess risks and support decision-making. Extensive literature on scenario generation methods aims at describing some underlying stochastic processes with the least number of scenarios to overcome the ‘curse of dimensionality’. There is, however, an important requirement that is usually overlooked when one departs from the application domain of security pricing: the no-arbitrage condition. We formulate a moment matching model to generate multi-factor scenario trees for stochastic optimization satisfying no-arbitrage restrictions with a minimal number of scenarios and without any distributional assumptions. The resulting global optimization problem is quite general. However, it is non-convex and can grow significantly with the number of risk factors, and we develop convex lower bounding techniques for its solution exploiting the special structure of the problem. Applications to some standard problems from the literature show that this is a robust approach for tree generation. We use it to price a European basket option in complete and incomplete markets.
Original languageEnglish
Pages (from-to)201-212
Number of pages12
JournalQuantitative Finance
Volume16
Publication statusPublished - 2016

All Science Journal Classification (ASJC) codes

  • Finance
  • General Economics,Econometrics and Finance

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