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Portfolio selection for individual passive investing
Author(s) -
Puelz David,
Hahn P. Richard,
Carvalho Carlos M.
Publication year - 2019
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.2483
Subject(s) - portfolio , selection (genetic algorithm) , automatic summarization , perspective (graphical) , passive management , construct (python library) , computer science , economics , actuarial science , business , finance , fund of funds , artificial intelligence , market liquidity , programming language
This paper considers passive fund selection from an individual investor's perspective. The growth of the passive fund market over the past decade is staggering. Individual investors who wish to buy these funds for their retirement and brokerage accounts have many options and are faced with a difficult selection problem. Which funds do they invest in, and in what proportions? We develop a novel statistical methodology to address this problem by adapting recent advances in posterior summarization. A Bayesian decision‐theoretic approach is presented to construct optimal sparse portfolios for individual investors over time.