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Competitive Analysis of On-line Securities Investment

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Algorithmic Applications in Management (AAIM 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3521))

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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.

Supported by NSF Grant No.70471035 and No.10371094.

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Author information

Authors and Affiliations

  1. School of Management, Xi’an Jiaotong University, Xi’an, China

    Shuhua Hu & Qin Guo

  2. Dept of Decision Sciences and Managerial Economics, The Chinese University of Hongkong, Hongkong, China

    Hongyi Li

Authors
  1. Shuhua Hu
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  2. Qin Guo
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  3. Hongyi Li
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Editor information

Editors and Affiliations

  1. IBM Almaden Research Center, 650 Harry Road, 95120, San Jose, CA,  

    Nimrod Megiddo

  2. The State Key Lab for Manufacturing Systems Engineering, 710049, Xi’an, P.R. China

    Yinfeng Xu

  3. Department of Computer Science, Montana State University, 59717, Bozeman, MT, USA

    Binhai Zhu

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© 2005 Springer-Verlag Berlin Heidelberg

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Hu, S., Guo, Q., Li, H. (2005). Competitive Analysis of On-line Securities Investment. In: Megiddo, N., Xu, Y., Zhu, B. (eds) Algorithmic Applications in Management. AAIM 2005. Lecture Notes in Computer Science, vol 3521. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11496199_25

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  • DOI: https://doi.org/10.1007/11496199_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26224-4

  • Online ISBN: 978-3-540-32440-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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