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Ajouter au panierEtat : New. 2025th edition NO-PA16APR2015-KAP.
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Ajouter au panierEtat : New. SUPER FAST SHIPPING.
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Springer International Publishing AG, Cham, 2024
ISBN 10 : 3031620607 ISBN 13 : 9783031620607
Langue: anglais
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Ajouter au panierHardcover. Etat : new. Hardcover. This book develops a quantitative stock market investment methodology using financial indicators that beats the benchmark of S&P500 index. To achieve this goal, an ensemble of machine learning models is meticulously constructed, incorporating four distinct algorithms: support vector machine, k-nearest neighbors, random forest, and logistic regression. These models all make use of financial ratios extracted from company financial statements for the purposes of predictive forecasting. The ensemble classifier is subject to a strict testing of precision which compares it to the performance of its constituent models separately. Rolling window and cross-validation tests are used in this evaluation in order to provide a comprehensive assessment framework. A risk-off filter is developed to limit risk during uncertain market periods, and consequently to improve the Sharpe ratio of the model. The risk adjusted performance of the final model, supported by the risk-off filter, achieves a Sharpe ratio of 1.63 which surpasses both the models performance without the filter that delivers Sharpe ratio of 1.41 and the one from the S&P500 index of 0.80. The substantial increase in risk-adjusted returns is accomplished by reducing the models volatility from an annual standard of deviation of 15.75% to 11.22%, which represents an almost 30% decrease in volatility. The risk adjusted performance of the final model, supported by the risk-off filter, achieves a Sharpe ratio of 1.63 which surpasses both the models performance without the filter that delivers Sharpe ratio of 1.41 and the one from the S&P500 index of 0.80. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Edité par Springer, Springer Nature Switzerland, 2025
ISBN 10 : 3031620631 ISBN 13 : 9783031620638
Langue: anglais
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering.
Edité par Springer-Nature New York Inc, 2024
ISBN 10 : 3031620607 ISBN 13 : 9783031620607
Langue: anglais
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Ajouter au panierHardcover. Etat : Brand New. 82 pages. 9.44x6.61x9.69 inches. In Stock.
Edité par Springer, Berlin, Springer Nature Switzerland, Springer, 2024
ISBN 10 : 3031620607 ISBN 13 : 9783031620607
Langue: anglais
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Ajouter au panierBuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book develops a quantitative stock market investment methodology using financial indicators that beats the benchmark of S&P500 index. To achieve this goal, an ensemble of machine learning models is meticulously constructed, incorporating four distinct algorithms: support vector machine, k-nearest neighbors, random forest, and logistic regression. These models all make use of financial ratios extracted from company financial statements for the purposes of predictive forecasting. The ensemble classifier is subject to a strict testing of precision which compares it to the performance of its constituent models separately. Rolling window and cross-validation tests are used in this evaluation in order to provide a comprehensive assessment framework. A risk-off filter is developed to limit risk during uncertain market periods, and consequently to improve the Sharpe ratio of the model. The risk adjusted performance of the final model, supported by the risk-off filter, achieves a Sharpe ratio of 1.63 which surpasses both the model's performance without the filter that delivers Sharpe ratio of 1.41 and the one from the S&P500 index of 0.80. The substantial increase in risk-adjusted returns is accomplished by reducing the model's volatility from an annual standard of deviation of 15.75% to 11.22%, which represents an almost 30% decrease in volatility. 71 pp. Englisch.
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Ajouter au panierEtat : New. PRINT ON DEMAND.
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Ajouter au panierEtat : new. Questo è un articolo print on demand.
Edité par Springer, Springer Nature Switzerland Jun 2025, 2025
ISBN 10 : 3031620631 ISBN 13 : 9783031620638
Langue: anglais
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
EUR 149,79
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 84 pp. Englisch.
Edité par Springer, Berlin|Springer Nature Switzerland|Springer, 2024
ISBN 10 : 3031620607 ISBN 13 : 9783031620607
Langue: anglais
Vendeur : moluna, Greven, Allemagne
EUR 127,40
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book develops a quantitative stock market investment methodology using financial indicators that beats the benchmark of S&P500 index. To achieve this goal, an ensemble of machine learning models is meticulously constructed, incorporating four distin.
Edité par Springer, Springer Nature Switzerland Jun 2025, 2025
ISBN 10 : 3031620631 ISBN 13 : 9783031620638
Langue: anglais
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
EUR 149,79
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 84 pp. Englisch.