Arbeitspapier

Optimal stopping under ambiguity

We consider optimal stopping problems for ambiguity averse decision makers with multiple priors. In general, backward induction fails. If, however, the class of priors is time-consistent, we establish a generalization of the classical theory of optimal stopping. To this end, we develop first steps of a martingale theory for multiple priors. We define minimax (super)martingales, provide a Doob-Meyer decomposition, and characterize minimax martingales. This allows us to extend the standard backward induction procedure to ambiguous, time-consistent preferences. The value function is the smallest process that is a minimax supermartingale and dominates the payoff process. It is optimal to stop when the current payoff is equal to the value function. Moving on, we study the infinite horizon case. We show that the value process satisfies the same backward recursion (Bellman equation) as in the finite horizon case. The finite horizon solutions converge to the infinite horizon solution. Finally, we characterize completely the set of time-consistent multiple priors in the binomial tree. We solve two classes of examples: the so-called independent and indistinguishable case (the parking problem) and the case of American Options (Cox-Ross-Rubinstein model).

Sprache
Englisch

Erschienen in
Series: Working Papers ; No. 390

Klassifikation
Wirtschaft
Criteria for Decision-Making under Risk and Uncertainty
Optimization Techniques; Programming Models; Dynamic Analysis
Portfolio Choice; Investment Decisions
Thema
Optimal stopping
Ambiguity
Uncertainty aversion
Entscheidung bei Unsicherheit
Suchtheorie
Risikoaversion
Optionspreistheorie
Theorie

Ereignis
Geistige Schöpfung
(wer)
Riedel, Frank
Ereignis
Veröffentlichung
(wer)
Bielefeld University, Institute of Mathematical Economics (IMW)
(wo)
Bielefeld
(wann)
2007

Handle
URN
urn:nbn:de:hbz:361-10784
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Riedel, Frank
  • Bielefeld University, Institute of Mathematical Economics (IMW)

Entstanden

  • 2007

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