Drawdown: From Practice to Theory and Back Again
Journal
Mathematics and Financial Economics
ISSN
1862-9679
ISSN-Digital
1862-9660
Type
journal article
Date Issued
2017-06
Author(s)
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.
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
SEPS - Quantitative Economic Methods
Refereed
Yes
Publisher
Springer
Publisher place
Berlin
Volume
11
Number
3
Start page
275
End page
297
Division(s)
Eprints ID
251773
File(s)![Thumbnail Image]()
Name
drawdown2016_revised.pdf
Size
882.85 KB
Format
Adobe PDF
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