Benchmark-based deviation and drawdown measures in portfolio optimization
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-xAuthor affiliation
College of Science & Engineering, Comp' & Math' SciencesVersion
- VoR (Version of Record)
Published in
Optimization LettersPublisher
Springer Science and Business Media LLCissn
1862-4472eissn
1862-4480Acceptance date
2024-05-13Copyright date
2024Available date
2024-07-04Publisher DOI
Language
enPublisher version
Deposited by
Dr Bogdan GrechukDeposit date
2024-07-03Rights Retention Statement
- No