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The Journal of Financial Data Science

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Article

Pest Control: Eliminating Nuisance Allocations through Empirical Asset Class Identification

Chao Ma, Brian Jacobsen and Wai Lee
The Journal of Financial Data Science Summer 2019, jfds.2019.1.006; DOI: https://doi.org/10.3905/jfds.2019.1.006
Chao Ma
is a global portfolio and quantitative strategist at Wells Fargo Investment Institute in St. Louis, MO
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Brian Jacobsen
is a senior investment strategist on the Multi-Asset Solutions team at Wells Fargo Asset Management in Menomonee Falls, WI
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Wai Lee
is the global head of research on the Multi-Asset Solutions team at Wells Fargo Asset Management in New York, NY
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Abstract

There is a seemingly infinite number of ways to partition the investment universe into asset categories. Too fine a partition can lead to very small allocations to certain categories in asset allocation models. When populating those categories with actual strategies, costs increase because due diligence and reporting are not costless activities. The right number of asset categories for building allocations should depend on balancing the marginal benefits and marginal costs of a finer partitioning of the investment universe. In this article, the authors use different machine learning techniques to help quantify these trade-offs. Two unsupervised learning techniques—exploratory factor analysis and hierarchical cluster analysis—are used to identify asset classes. A supervised learning technique—a regression tree—then is used to identify the most important basis for US equities, a specific asset class identified by the unsupervised learning techniques.

TOPICS: Big data/machine learning, security analysis and valuation, performance measurement

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The Journal of Financial Data Science: 3 (1)
The Journal of Financial Data Science
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Winter 2021
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Pest Control: Eliminating Nuisance Allocations through Empirical Asset Class Identification
Chao Ma, Brian Jacobsen, Wai Lee
The Journal of Financial Data Science Jun 2019, jfds.2019.1.006; DOI: 10.3905/jfds.2019.1.006

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Pest Control: Eliminating Nuisance Allocations through Empirical Asset Class Identification
Chao Ma, Brian Jacobsen, Wai Lee
The Journal of Financial Data Science Jun 2019, jfds.2019.1.006; DOI: 10.3905/jfds.2019.1.006
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  • Article
    • Abstract
    • ASSET CLASSES AND DIVERSIFICATION
    • EMPIRICALLY IDENTIFIED ASSET CLASSES
    • CONCLUSION
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  • Managing Editor’s Letter
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  • Portfolio Construction Using First Principles Preference Theory and Machine Learning
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