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Recursive Portfolio Selection with Decision Trees

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Author Info
Anton Andriyashin
Wolfgang Härdle
Roman Timofeev

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Abstract

A great proportion of stock dynamics can be explained using publicly available information. The relationship between dynamics and public information may be of nonlinear character. In this paper we offer an approach to stock picking by employing so-called decision trees and applying them to XETRA DAX stocks. Using a set of fundamental and technical variables, stocks are classified into three groups according to the proposed position: long, short or neutral. More precisely, by assessing the current state of a company, which is represented by fundamental variables and current market situation, well reflected by technical variables, it is possible to suggest if the current market value of a company is underestimated, overestimated or the stock is fairly priced. The performance of the model over the observed period suggests that XETRA DAX stock returns can adequately be predicted by publicly available economic data. Another conclusion of this study is that the implied volatility variable, when included into the training sample, boosts the predictive power of the model significantly.

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Publisher Info
Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2008-009.

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Length: 27 pages
Date of creation: Jan 2008
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2008-009

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Related research
Keywords: CART; decision trees in finance; nonlinear decision rules; asset management; portfolio optimisation;

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Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Cizek, P. & Haerdle, W. & Spokoiny, V., 2007. "Adaptive Pointwise Estimation in Time-Inhomogeneous Time-Series Models," Discussion Paper 2007-35, Tilburg University, Center for Economic Research. [Downloadable!]
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  2. Ray-Bing Chen & Meihui Guo & Wolfgang Härdle & Shih-Feng Huang, 2008. "Independent Component Analysis Via Copula Techniques," SFB 649 Discussion Papers SFB649DP2008-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Enzo Giacomini & Wolfgang Härdle & Volker Krätschmer, 2008. "Dynamic Semiparametric Factor Models in Risk Neutral Density Estimation," SFB 649 Discussion Papers SFB649DP2008-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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  2. Nikolaus Hautsch & Dieter Hess & Christoph Müller, 2008. "Price Adjustment to News with Uncertain Precision," SFB 649 Discussion Papers SFB649DP2008-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
    Other versions:
  3. Viktor Winschel & Markus Krätzig, 2008. "JBendge: An Object-Oriented System for Solving, Estimating and Selecting Nonlinear Dynamic Models," SFB 649 Discussion Papers SFB649DP2008-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  4. Anton Andriyashin, 2008. "Stock Picking via Nonsymmetrically Pruned Binary Decision Trees," SFB 649 Discussion Papers SFB649DP2008-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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