Tim oliver martens (12 risultati)

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Da: Books Puddle, Woodside, NY, U.S.A.Books Puddle
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Condizione: New. pp. 148.

Lingua: Tedesco
Editore: MWV Medizinisch Wissenschaftliche Verlagsgesellschaft, 2020
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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Paperback. Condizione: New. 1.

Lean-Exzellenz im OP Management: Effektive und effiziente Prozesse im OP
Angerer, Alfred/ Brand, Tim/ Gurnhofer, Ines/ Mattmann, Oliver/ Juchler, Isabelle/ Martens, Rutger
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 32,63
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Paperback. Condizione: Brand New. German language. 9.49x6.54x0.63 inches. In Stock.

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Da: preigu, Osnabrück, Germaniapreigu
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EUR 147,60
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Taschenbuch. Condizione: Neu. Seasonal Effects on Share Indices | An analysis with artificial neural networks | Tim-Oliver Martens | Taschenbuch | 148 S. | Englisch | 2015 | AV Akademikerverlag | EAN 9783639789287 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Lean-Exzellenz im OP Management
Angerer, Alfred|Brand, Tim|Gurnhofer, Ines|Mattmann, Oliver|Juchler, Isabelle|Martens, Rutger
Lingua: Tedesco
Editore: MWV Medizinisch Wissenschaftliche Verlagsges., 2020
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Der OP-Bereich ist als Herzstueck des Leistungsportfolios von zentraler Bedeutung fuer die Behandlungsqualitaet wie auch die wirtschaftlichen Ergebnisse des Krankenhauses. So steht auch der OP im Zentrum der Aufmerksamkeit bei der kontinuierlichen Optimierung .

Lingua: Tedesco
Editore: MWV Medizinisch Wissenschaftliche Verlagsgesellschaft, 2020
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- Prima edizione
Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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Paperback. Condizione: New. 1.

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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -No one can predict stock prices. However, there are many theories which imply that recurring seasonal effects could be used to determine the direction of share indices. Many traders have already heard the stock market adage: 'Sell in May and go away, but remember to come back in September'. What is with this adage really about, and are there other indications for the existence of recurring seasonal effects which could be used for respective trading strategies This book deals with eleven different recurring seasonal effects which are frequently referred to in academic writings as well. Artificial neural networks are used to identify these phenomena at eight different underlyings. For underlyings, where a phenomenon could be identified, a trading strategy based on the forecast of artificial neural networks is presented. These strategies use the respective effect to determine the direction of share indices. In order to compare the trading results a comparative strategy is used as a benchmark. It is shown how artificial neural networks could be used to identify recurring seasonal effects and how to create a trading position depending on the signal of these effects. 148 pp. Englisch.…

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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. 148.

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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - No one can predict stock prices. However, there are many theories which imply that recurring seasonal effects could be used to determine the direction of share indices. Many traders have already heard the stock market adage: 'Sell in May and go away, but remember to come back in September'. What is with this adage really about, and are there other indications for the existence of recurring seasonal effects which could be used for respective trading strategies This book deals with eleven different recurring seasonal effects which are frequently referred to in academic writings as well. Artificial neural networks are used to identify these phenomena at eight different underlyings. For underlyings, where a phenomenon could be identified, a trading strategy based on the forecast of artificial neural networks is presented. These strategies use the respective effect to determine the direction of share indices. In order to compare the trading results a comparative strategy is used as a benchmark. It is shown how artificial neural networks could be used to identify recurring seasonal effects and how to create a trading position depending on the signal of these effects.…

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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 148.

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Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Martens Tim-OliverTim-Oliver Martens, Master of Science, Major Finance: Studies of Economy Science at the Gottfried Wilhelm Leibniz University of Hannover, Germany. Consultant at PricewaterhouseCoopers, Frankfurt am Main, Germany. …

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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 147,60
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -No one can predict stock prices. However, there are many theories which imply that recurring seasonal effects could be used to determine the direction of share indices. Many traders have already heard the stock market adage: 'Sell in May and go away, but remember to come back in September'. What is with this adage really about, and are there other indications for the existence of recurring seasonal effects which could be used for respective trading strategies This book deals with eleven different recurring seasonal effects which are frequently referred to in academic writings as well. Artificial neural networks are used to identify these phenomena at eight different underlyings. For underlyings, where a phenomenon could be identified, a trading strategy based on the forecast of artificial neural networks is presented. These strategies use the respective effect to determine the direction of share indices. In order to compare the trading results a comparative strategy is used as a benchmark. It is shown how artificial neural networks could be used to identify recurring seasonal effects and how to create a trading position depending on the signal of these effects.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 148 pp. Englisch.…