Regret minimization algorithms for pricing lookback options

Eyal Gofer, Yishay Mansour

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In this work, we extend the applicability of regret minimization to pricing financial instruments, following the work of [11]. More specifically, we consider pricing a type of exotic option called a fixed-strike lookback call option. A fixed-strike lookback call option has a known expiration time, at which the option holder has the right to receive the difference between the maximal price of a stock and some pre-agreed price. We derive upper bounds on the price of these options, assuming an arbitrage-free market, by developing two-way trading algorithms. We construct our trading algorithms by combining regret minimization algorithms and one-way trading algorithms. Our model assumes upper bounds on the absolute daily returns, overall quadratic variation, and stock price, otherwise allowing for fully adversarial market behavior.

Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 22nd International Conference, ALT 2011, Proceedings
Number of pages15
StatePublished - 2011
Event22nd International Conference on Algorithmic Learning Theory, ALT 2011 - Espoo, Finland
Duration: 5 Oct 20117 Oct 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6925 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference22nd International Conference on Algorithmic Learning Theory, ALT 2011


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