Buy low, sell high

Wouter Koolen; Vladimir Vovk

Buy low, sell high

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We consider online trading in a single security with the objective of getting rich when its price ever exhibits a large upcrossing without risking bankruptcy. We investigate payoff guarantees that are expressed in terms of the extremity of the upcrossings. We obtain an exact and elegant characterisation of the guarantees that can be achieved. Moreover, we derive a simple canonical strategy for each attainable guarantee.

Original language	English
Title of host publication	Proceedings of the Twenty Third International Conference on Algorithmic Learning Theory
Editors	Nader Bshouty, Gilles Stoltz, Nicolas Vayatis, Thomas Zeugmann
Place of Publication	Berlin
Publisher	Springer
Pages	335 - 349
Number of pages	15
Volume	7568
Publication status	Accepted/In press - 2012

Publication series

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer

Keywords

online investment
worst-case analysis
probability-free option pricing

The Decision Theory of Hiring and Firing Advisors
Vovk, V. (PI)
Dutch Research Council
1/02/11 → 31/01/13
Project: Research

Cite this

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title = "Buy low, sell high",

abstract = "We consider online trading in a single security with the objective of getting rich when its price ever exhibits a large upcrossing without risking bankruptcy. We investigate payoff guarantees that are expressed in terms of the extremity of the upcrossings. We obtain an exact and elegant characterisation of the guarantees that can be achieved. Moreover, we derive a simple canonical strategy for each attainable guarantee.",

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author = "Wouter Koolen and Vladimir Vovk",

year = "2012",

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volume = "7568",

series = "Lecture Notes in Artificial Intelligence",

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Buy low, sell high. / Koolen, Wouter; Vovk, Vladimir.
Proceedings of the Twenty Third International Conference on Algorithmic Learning Theory. ed. / Nader Bshouty; Gilles Stoltz; Nicolas Vayatis; Thomas Zeugmann. Vol. 7568 Berlin: Springer, 2012. p. 335 - 349 (Lecture Notes in Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Buy low, sell high

AU - Koolen, Wouter

AU - Vovk, Vladimir

PY - 2012

Y1 - 2012

N2 - We consider online trading in a single security with the objective of getting rich when its price ever exhibits a large upcrossing without risking bankruptcy. We investigate payoff guarantees that are expressed in terms of the extremity of the upcrossings. We obtain an exact and elegant characterisation of the guarantees that can be achieved. Moreover, we derive a simple canonical strategy for each attainable guarantee.

AB - We consider online trading in a single security with the objective of getting rich when its price ever exhibits a large upcrossing without risking bankruptcy. We investigate payoff guarantees that are expressed in terms of the extremity of the upcrossings. We obtain an exact and elegant characterisation of the guarantees that can be achieved. Moreover, we derive a simple canonical strategy for each attainable guarantee.

KW - online investment

KW - worst-case analysis

KW - probability-free option pricing

M3 - Conference contribution

VL - 7568

T3 - Lecture Notes in Artificial Intelligence

SP - 335

EP - 349

BT - Proceedings of the Twenty Third International Conference on Algorithmic Learning Theory

A2 - Bshouty, Nader

A2 - Stoltz, Gilles

A2 - Vayatis, Nicolas

A2 - Zeugmann, Thomas

PB - Springer

CY - Berlin

ER -

Buy low, sell high

Abstract

Publication series

Keywords

Projects

The Decision Theory of Hiring and Firing Advisors

Cite this