Portfolio selection for individual passive investing

David Puelz, P. Richard Hahn, Carlos M. Carvalho

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
JournalApplied Stochastic Models in Business and Industry
DOIs
StateAccepted/In press - Jan 1 2019

Fingerprint

Portfolio Selection
Summarization
Proportion
Methodology
Portfolio selection
Investing
Individual investors
Market

Keywords

  • Bayesian methods
  • decision theory
  • model selection
  • portfolio selection

ASJC Scopus subject areas

  • Modeling and Simulation
  • Business, Management and Accounting(all)
  • Management Science and Operations Research

Cite this

Portfolio selection for individual passive investing. / Puelz, David; Hahn, P. Richard; Carvalho, Carlos M.

In: Applied Stochastic Models in Business and Industry, 01.01.2019.

Research output: Contribution to journalArticle

@article{64c612354703457cbce0a77e39bcf358,
title = "Portfolio selection for individual passive investing",
abstract = "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.",
keywords = "Bayesian methods, decision theory, model selection, portfolio selection",
author = "David Puelz and Hahn, {P. Richard} and Carvalho, {Carlos M.}",
year = "2019",
month = "1",
day = "1",
doi = "10.1002/asmb.2483",
language = "English (US)",
journal = "Applied Stochastic Models in Business and Industry",
issn = "1524-1904",
publisher = "John Wiley and Sons Ltd",

}

TY - JOUR

T1 - Portfolio selection for individual passive investing

AU - Puelz, David

AU - Hahn, P. Richard

AU - Carvalho, Carlos M.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - Bayesian methods

KW - decision theory

KW - model selection

KW - portfolio selection

UR - http://www.scopus.com/inward/record.url?scp=85073779965&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85073779965&partnerID=8YFLogxK

U2 - 10.1002/asmb.2483

DO - 10.1002/asmb.2483

M3 - Article

AN - SCOPUS:85073779965

JO - Applied Stochastic Models in Business and Industry

JF - Applied Stochastic Models in Business and Industry

SN - 1524-1904

ER -