Mathematics and Financial Economics

, Volume 11, Issue 3, pp 275–297

Drawdown: from practice to theory and back again

Article

DOI: 10.1007/s11579-016-0181-9

Cite this article as:
Goldberg, L.R. & Mahmoud, O. Math Finan Econ (2017) 11: 275. doi:10.1007/s11579-016-0181-9
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Abstract

Maximum drawdown, the largest cumulative loss from peak to trough, is one of the most widely used indicators of risk in the fund management industry, but one of the least developed in the context of measures of risk. We formalize drawdown risk as Conditional Expected Drawdown (CED), which is the tail mean of maximum drawdown distributions. We show that CED is a degree one positive homogenous risk measure, so that it can be linearly attributed to factors; and convex, so that it can be used in quantitative optimization. We empirically explore the differences in risk attributions based on CED, Expected Shortfall (ES) and volatility. An important feature of CED is its sensitivity to serial correlation. In an empirical study that fits AR(1) models to US Equity and US Bonds, we find substantially higher correlation between the autoregressive parameter and CED than with ES or with volatility.

Keywords

Drawdown Conditional expected drawdown Deviation measure Risk attribution Serial correlation 

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Statistics and Economics, Center for Risk Management Research, and Consortium for Data Analytics in RiskUniversity of CaliforniaBerkeleyUSA
  2. 2.Faculty of Mathematics and StatisticsUniversity of St. GallenSt. GallenSwitzerland
  3. 3.Center for Risk Management ResearchUniversity of CaliforniaBerkeleyUSA

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