JOURNAL ARTICLE

Strategic Discipline: How Asset Management Mirrors Military Operations.

  • Published In: Journal of Portfolio Management, 2025, v. 52, n. 1. P. 202 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Fabozzi, Frank J.; Stenholm, Caleb C. 3 of 3

Abstract

This article describes the operational parallels between asset management and military strategy, arguing that both fields demand clear mission objectives, disciplined execution, tactical flexibility, and resilience under pressure. Drawing from military doctrines such as the OODA loop and leadership practices at firms like Bridgewater Associates and JPMorgan Chase, the article shows how principles like mission clarity, intelligence gathering, resource deployment, and after-action reviews translate into successful portfolio management. It highlights the critical role of culture, emphasizing the need for trust, psychological resilience, and continuous learning to navigate volatile environments. The discussion also addresses the increasing importance of innovation and technological adaptation in maintaining competitive advantage amid evolving market risks and cyber threats. Incorporating examples from military training and from veterans who have transitioned into finance, the article outlines an operational framework asset managers can use to improve decision making, enhance organizational agility, and sustain long-term performance. Success in both fields ultimately rests on relentless preparation, smart adaptation, and the discipline to execute under uncertainty while staying true to the mission. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Portfolio Management. 2025/11, Vol. 52, Issue 1, p202
  • Document Type:Article
  • Subject Area:Military History and Science
  • Publication Date:2025
  • ISSN:0095-4918
  • DOI:10.3905/jpm.2025.1.769
  • Accession Number:189371012
  • Copyright Statement:Copyright of Journal of Portfolio Management is the property of With Intelligence Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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