114,56 €
127,29 €
-10% with code: EXTRA
Online Algorithms for the Portfolio Selection Problem
Online Algorithms for the Portfolio Selection Problem
114,56
127,29 €
  • We will send in 10–14 business days.
Robert Dochow mathematically derives a simplified classification structure of selected types of the portfolio selection problem. He proposes two new competitive online algorithms with risk management, which he evaluates analytically. The author empirically evaluates online algorithms by a comprehensive statistical analysis. Concrete results are that follow-the-loser algorithms show the most promising performance when the objective is the maximization of return on investment and risk-adjusted pe…
  • Publisher:
  • Year: 2016
  • Pages: 185
  • ISBN-10: 3658135271
  • ISBN-13: 9783658135270
  • Format: 14.8 x 21 x 1.1 cm, softcover
  • Language: English
  • SAVE -10% with code: EXTRA

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Robert Dochow mathematically derives a simplified classification structure of selected types of the portfolio selection problem. He proposes two new competitive online algorithms with risk management, which he evaluates analytically. The author empirically evaluates online algorithms by a comprehensive statistical analysis. Concrete results are that follow-the-loser algorithms show the most promising performance when the objective is the maximization of return on investment and risk-adjusted performance. In addition, when the objective is the minimization of risk, the two new algorithms with risk management show excellent performance. A prototype of a software tool for automated evaluation of algorithms for portfolio selection is given.

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  • Author: Robert Dochow
  • Publisher:
  • Year: 2016
  • Pages: 185
  • ISBN-10: 3658135271
  • ISBN-13: 9783658135270
  • Format: 14.8 x 21 x 1.1 cm, softcover
  • Language: English English

Robert Dochow mathematically derives a simplified classification structure of selected types of the portfolio selection problem. He proposes two new competitive online algorithms with risk management, which he evaluates analytically. The author empirically evaluates online algorithms by a comprehensive statistical analysis. Concrete results are that follow-the-loser algorithms show the most promising performance when the objective is the maximization of return on investment and risk-adjusted performance. In addition, when the objective is the minimization of risk, the two new algorithms with risk management show excellent performance. A prototype of a software tool for automated evaluation of algorithms for portfolio selection is given.

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