TAILIEUCHUNG - Stock Picking via Nonsymmetrically Pruned Binary Decision Trees

Available-for-sale securities. Investments in debt securities that are classified as available for sale and equity securities that have readily determinable fair values that are classified as available for sale shall be measured subsequently at fair value in the statement of financial position. Unrealized holding gains and losses for available-for-sale securities (including those classified as current assets) shall be excluded from earnings and reported in other comprehensive income until realized except as indicated in the following sentence. All or a portion of the unrealized holding gain and loss of an available-for-sale security that is designated as being hedged in a fair. | SFB 649 Discussion Paper 2008-035 Stock Picking via Nonsymmetrically Pruned Binary Decision Trees Anton Andriyashin Humboldt-Universitat zu Berlin Germany This research was supported by the Deutsche Forschungsgemeinschaft through the SFB 649 Economic Risk . http ISSN 1860-5664 SFB 649 Humboldt-Universitat zu Berlin Spandauer StraBe 1 D-10178 Berlin SFB 6 4 9 E C O N O M I C R I S K B E R L I N Stock Picking via Nonsymmetrically Pruned Binary Decision Trees Anton V. Andriyashin CASE - Center for Applied Statistics and Economics Humboldt-Universitat zu Berlin Spandauer Strafie 1 10178 Berlin Germany Abstract Stock picking is the field of financial analysis that is of particular interest for many professional investors and researchers. In this study stock picking is implemented via binary classification trees. Optimal tree size is believed to be the crucial factor in forecasting performance of the trees. While there exists a standard method of tree pruning which is based on the cost-complexity tradeoff and used in the majority of studies employing binary decision trees this paper introduces a novel methodology of nonsymmetric tree pruning called Best Node Strategy BNS . An important property of BNS is proven that provides an easy way to implement the search of the optimal tree size in practice. BNS is compared with the traditional pruning approach by composing two recursive portfolios out of XETRA DAX stocks. Performance forecasts for each of the stocks are provided by constructed decision trees. It is shown that BNS clearly outperforms the traditional approach according to the backtesting results and the Diebold-Mariano test for statistical significance of the performance difference between two forecasting methods. JEL classification C14 C15 C44 C63 G12 Keywords decision tree stock picking pruning earnings forecasting data mining This paper was presented at the 20th Annual Australasian Finance and Banking Conference in Sydney Australia in .

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