Growth Optimal Investment Strategy: The Impact of Reallocation Frequency and Heavy Tails

Author:

Bamberg G.1,Neuhierl A.2

Affiliation:

1. Universität Augsburg, Institut für Statistik and Mathematische Wirtschaftstheorie, Augsburg , Germany

2. Northwestern University – Kellogg School of Management, James L.Allen Center, Campus Dr, Evanston , United States of America

Abstract

Abstract The strategy to maximize the long-term growth rate of final wealth (maximum expected log strategy, maximum geometric mean strategy, Kelly criterion) is based on probability theoretic underpinnings and has asymptotic optimality properties. This article reviews the allocation of wealth in a two-asset economy with one risky asset and a risk-free asset. It is also shown that the optimal fraction to be invested in the risky asset (i) depends on the length of the basic return period and (ii) is lower for heavy-tailed log returns than for light-tailed log returns.

Publisher

Walter de Gruyter GmbH

Subject

Economics and Econometrics

Reference24 articles.

1. Asymptotic Optimality and Asymptotic Equipartition Properties of Log-Optimum Investment;Algoet;Annals of Probability,1988

2. Is Traditional Capital Market Theory Consistent with Fat-Tailed Log Returns?;Bamberg;Zeitschrift für Betriebswirtschaft,2002

3. On the Non-Existence of Conditional Value-at-risk Under Heavy Tails and Short Sales;Bamberg;OR Spectrum,2010

4. Treffen Investoren mit konstanter relativer Risikoaversion auch im Buy-and-Hold-Kontext myopische Portfolioentscheidungen?

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Interview mit Günter Bamberg;AStA Wirtschafts- und Sozialstatistisches Archiv;2018-11-23

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