Optimal buy-and-hold strategies for financial markets with bounded daily returns

Gen Huey Chen; Ming Yang Kao; Yuh Dauh Lyuu; Hsing Kuo Wong

doi:10.1137/S0097539799358847

Optimal buy-and-hold strategies for financial markets with bounded daily returns

Gen Huey Chen^*, Ming Yang Kao, Yuh Dauh Lyuu, Hsing Kuo Wong

^*Corresponding author for this work

Computer Science

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

Abstract

In the context of investment analysis, we formulate an abstract online computing problem called a planning game and develop general tools for solving such a game. We then use the tools to investigate a practical buy-and-hold trading problem faced by long-term investors in stocks. We obtain the unique optimal static online algorithm for the problem and determine its exact competitive ratio. We also compare this algorithm with the popular dollar averaging strategy using actual market data.

Original language	English (US)
Pages (from-to)	447-459
Number of pages	13
Journal	SIAM Journal on Computing
Volume	31
Issue number	2
DOIs	https://doi.org/10.1137/S0097539799358847
State	Published - 2001

Keywords

Balanced strategy
Buy-and-hold trading problems
Competitive analysis
Dollar averaging strategy
Linear programming
Minimax theorem
Online algorithms
Planning games
Zero-sum two-person games

ASJC Scopus subject areas

Computer Science(all)
Mathematics(all)

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10.1137/S0097539799358847

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abstract = "In the context of investment analysis, we formulate an abstract online computing problem called a planning game and develop general tools for solving such a game. We then use the tools to investigate a practical buy-and-hold trading problem faced by long-term investors in stocks. We obtain the unique optimal static online algorithm for the problem and determine its exact competitive ratio. We also compare this algorithm with the popular dollar averaging strategy using actual market data.",

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AB - In the context of investment analysis, we formulate an abstract online computing problem called a planning game and develop general tools for solving such a game. We then use the tools to investigate a practical buy-and-hold trading problem faced by long-term investors in stocks. We obtain the unique optimal static online algorithm for the problem and determine its exact competitive ratio. We also compare this algorithm with the popular dollar averaging strategy using actual market data.

KW - Balanced strategy

KW - Buy-and-hold trading problems

KW - Competitive analysis

KW - Dollar averaging strategy

KW - Linear programming

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KW - Online algorithms

KW - Planning games

KW - Zero-sum two-person games

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Optimal buy-and-hold strategies for financial markets with bounded daily returns

Abstract

Keywords

ASJC Scopus subject areas

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