Competitive Analysis of On-line Securities Investment

Based on the unidirectional conversion model, we investigate a practical buy-and-hold trading problem. This problem is useful for long-term investors, we use competitive analysis and game theory to design some trading rules in the securities markets. We present an online algorithm, Mixed Strategy, f...

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Published inAlgorithmic Applications in Management pp. 224 - 232
Main Authors Hu, Shuhua, Guo, Qin, Li, Hongyi
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN3540262245
9783540262244
ISSN0302-9743
1611-3349
DOI10.1007/11496199_25

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Abstract Based on the unidirectional conversion model, we investigate a practical buy-and-hold trading problem. This problem is useful for long-term investors, we use competitive analysis and game theory to design some trading rules in the securities markets. We present an online algorithm, Mixed Strategy, for the problem and prove its competitive ratio $1 + \frac{(n-1)t}{2}$ , where n is the trading horizon and t is the daily fluctuations of securities prices. The Dynamic-Mixed Strategy is also presented to further reduce the competitive ratio. An investing example is simulated with the Mixed Strategy and Dollar Average Strategy based on the actual market data.
AbstractList Based on the unidirectional conversion model, we investigate a practical buy-and-hold trading problem. This problem is useful for long-term investors, we use competitive analysis and game theory to design some trading rules in the securities markets. We present an online algorithm, Mixed Strategy, for the problem and prove its competitive ratio $1 + \frac{(n-1)t}{2}$ , where n is the trading horizon and t is the daily fluctuations of securities prices. The Dynamic-Mixed Strategy is also presented to further reduce the competitive ratio. An investing example is simulated with the Mixed Strategy and Dollar Average Strategy based on the actual market data.
Author Hu, Shuhua
Guo, Qin
Li, Hongyi
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  givenname: Hongyi
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  organization: Dept of Decision Sciences and Managerial Economics, The Chinese University of Hongkong, Hongkong, China
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Xu, Yinfeng
Zhu, Binhai
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Keywords Algorithmics
Markets
Conversion
Long term
Modeling
Mediation
Game theory
Daily
Securities trading
Economy
Mixed strategy
Mixed problem
Safety
Investment
Mathematical programming
Language English
License CC BY 4.0
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MeetingName AAIM 2005 : algorithmic applications in management (Xian, 22-25 June 2005)
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Notes Original Abstract: Based on the unidirectional conversion model, we investigate a practical buy-and-hold trading problem. This problem is useful for long-term investors, we use competitive analysis and game theory to design some trading rules in the securities markets. We present an online algorithm, Mixed Strategy, for the problem and prove its competitive ratio \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$1 + \frac{(n-1)t}{2}$\end{document}, where n is the trading horizon and t is the daily fluctuations of securities prices. The Dynamic-Mixed Strategy is also presented to further reduce the competitive ratio. An investing example is simulated with the Mixed Strategy and Dollar Average Strategy based on the actual market data.
Supported by NSF Grant No.70471035 and No.10371094.
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PublicationSeriesTitle Lecture Notes in Computer Science
PublicationSubtitle First International Conference, AAIM 2005, Xian, China, June 22-25, 2005. Proceedings
PublicationTitle Algorithmic Applications in Management
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Publisher Springer Berlin Heidelberg
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RelatedPersons Kleinberg, Jon M.
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Vardi, Moshe Y.
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Snippet Based on the unidirectional conversion model, we investigate a practical buy-and-hold trading problem. This problem is useful for long-term investors, we use...
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StartPage 224
SubjectTerms Algorithmics. Computability. Computer arithmetics
Applied sciences
Competitive Ratio
Computer science; control theory; systems
Exact sciences and technology
Mathematical programming
Online Algorithm
Operational research and scientific management
Operational research. Management science
Pure Strategy
Security Market
Static Algorithm
Theoretical computing
Title Competitive Analysis of On-line Securities Investment
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