Cited by 24Stochastic processes and financial applicationsRisk and Portfolio OptimizationProbability and Risk Models

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The maximum drawdown of the Brownian motion

Magdon-Ismail, M., Atiya, A., Pratap, A., Abu-Mostafa, Y.·2003·2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.

Abstract

The MDD is defined as the maximum loss incurred from peak to bottom during a specified period of time. It is often preferred over some of the other risk measures because of the tight relationship between large drawdowns and fund redemptions. Also, a large drawdown can even indicate the start of a deterioration of an otherwise successful trading system, for example due to a market regime switch. Overall, the MDD is a very important risk measure. To be able to use it more insightfully, its analytical properties have to be understood. As a step towards this direction, we have presented in this article some analytic results that we have developed. We hope more and more results will come out from the research community analyzing this important measure.

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  1. 10.1214/aop/1176996041 · DOI
  2. 10.2307/3215274 · DOI

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    “…decline in portfolio value from its peak to its trough throughout the evaluation period, providing a measure for down-side risk: 2) It highlights the worst loss an investor could have faced and is commonly used to assess risk and volatility (Magdon-Ismail et al., 2004; Chekhlov et al., 2005).”

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Metadata

Authors
Magdon-Ismail, M., Atiya, A., Pratap, A., & Abu-Mostafa, Y.
Affiliations
  • Cairo University (EG)
  • California Institute of Technology (US)
Venue
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.
Publisher
IEEE
Published
2003-12-22
Pages
243-247
OpenAlex
W1890781297
Cited by
24
References
0
Citations by year
2023: 1 · 2021: 1 · 2020: 3 · 2019: 1 · 2018: 2 · 2017: 5 · 2015: 2 · 2014: 3 · 2013: 1
FWCI
1.83
Type
conference paper
Language
en
Open access
closed
Locations
  • IEEE Conference on Computational Intelligence for Financial Engineering & Economics (publishedVersion)
  • CaltechAUTHORS (California Institute of Technology) (submittedVersion)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Finance › Stochastic processes and financial applications
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Risk and Portfolio Optimization
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Probability and Risk Models
Keywords
maximum drawdown, Brownian motion, risk measures, fund redemptions, analytical results

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CoChat. (2026). Citation check: The maximum drawdown of the Brownian motion. https://app.cochat.ai/papers/10.1109/cifer.2003.1196267
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Magdon-Ismail, M., Atiya, A., Pratap, A., & Abu-Mostafa, Y. (2003). The maximum drawdown of the Brownian motion. 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. https://doi.org/10.1109/cifer.2003.1196267