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Benchmark-based deviation and drawdown measures in portfolio optimization

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journal contribution
posted on 2024-07-04, 10:19 authored by Michael Zabarankin, Bogdan Grechuk, Dawei Hao

Understanding and modeling of agent’s risk/reward preferences is a central problem in various applications of risk management including investment science and portfolio theory in particular. One of the approaches is to axiomatically define a set of performance measures and to use a benchmark to identify a particular measure from that set by either inverse optimization or functional dominance. For example, such a benchmark could be the rate of return of an existing attractive financial instrument. This work introduces deviation and drawdown measures that incorporate rates of return of indicated financial instruments (benchmarks). For discrete distributions and discrete sample paths, portfolio problems with such measures are reduced to linear programs and solved based on historical data in cases of a single benchmark and three benchmarks used simultaneously. The optimal portfolios and corresponding benchmarks have similar expected/cumulative rates of return in sample and out of sample, but the former are considerably less volatile.

History

Citation

Zabarankin, M., Grechuk, B. & Hao, D. Benchmark-based deviation and drawdown measures in portfolio optimization. Optim Lett (2024). https://doi.org/10.1007/s11590-024-02124-x

Author affiliation

College of Science & Engineering, Comp' & Math' Sciences

Version

  • VoR (Version of Record)

Published in

Optimization Letters

Publisher

Springer Science and Business Media LLC

issn

1862-4472

eissn

1862-4480

Acceptance date

2024-05-13

Copyright date

2024

Available date

2024-07-04

Language

en

Deposited by

Dr Bogdan Grechuk

Deposit date

2024-07-03

Rights Retention Statement

  • No

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