A General Framework for Portfolio Theory. Part II: drawdown risk measures
Stanislaus Maier-Paape, Qiji Jim Zhu
TL;DR
This paper introduces convex drawdown risk measures within a general portfolio theory framework, enabling the calculation of efficient portfolios constrained by drawdown risk, as an alternative to traditional measures like standard deviation.
Contribution
It develops new convex risk measures related to drawdown, expanding portfolio optimization methods beyond classical risk metrics.
Findings
Constructed convex drawdown risk measures.
Enabled portfolio optimization with drawdown constraints.
Provided practical methods for alternative risk assessment.
Abstract
The aim of this paper is to provide several examples of convex risk measures necessary for the application of the general framework for portfolio theory of Maier-Paape and Zhu, presented in Part I of this series (arXiv:1710.04579 [q-fin.PM]). As alternative to classical portfolio risk measures such as the standard deviation we in particular construct risk measures related to the current drawdown of the portfolio equity. Combined with the results of Part I (arXiv:1710.04579 [q-fin.PM]), this allows us to calculate efficient portfolios based on a drawdown risk measure constraint.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.