This book helps to search a suitable model for the daily volume data series of Dhaka Stock Exchange (DSE) and to forecast the future outline. ML - ARCH (Marquardt) method has been used to build up the models for the volume data series by using statistical software's Eviews verson-5. Firstly, we fitted an ARIMA model and observed that there were present heteroskewdastic transactions. Then, we used different ARCH class volatility models but one of them we used intervention shock and selected the ARIMA with EGARCH model. Our findings established that ARIMA with EGARCH model comprises low residual variance and low forecast error for volume data and thus, the modeling concept used in this paper would be useful for the investors or researchers to resolve the future value of share volume.
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Ahammad Hossain,Lecturer, Department of Natural Science, Varendra University, Rajshahi, Bangladesh.Educational Background:M.Sc. in Statistics, University of Rajshahi, Rajshahi, Bangladesh
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book helps to search a suitable model for the daily volume data series of Dhaka Stock Exchange (DSE) and to forecast the future outline. ML - ARCH (Marquardt) method has been used to build up the models for the volume data series by using statistical software's Eviews verson-5. Firstly, we fitted an ARIMA model and observed that there were present heteroskewdastic transactions. Then, we used different ARCH class volatility models but one of them we used intervention shock and selected the ARIMA with EGARCH model. Our findings established that ARIMA with EGARCH model comprises low residual variance and low forecast error for volume data and thus, the modeling concept used in this paper would be useful for the investors or researchers to resolve the future value of share volume. 176 pp. Englisch. Bestandsnummer des Verkäufers 9783659683664
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hossain AhammadAhammad Hossain,Lecturer, Department of Natural Science, Varendra University, Rajshahi, Bangladesh.Educational Background:M.Sc. in Statistics, University of Rajshahi, Rajshahi, BangladeshThis book helps to search a. Bestandsnummer des Verkäufers 158223948
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Taschenbuch. Zustand: Neu. Volatility Analysis and Forecasting Volume Data of DSE | Ahammad Hossain (u. a.) | Taschenbuch | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659683664 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 113180100
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Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book helps to search a suitable model for the daily volume data series of Dhaka Stock Exchange (DSE) and to forecast the future outline. ML - ARCH (Marquardt) method has been used to build up the models for the volume data series by using statistical software's Eviews verson-5. Firstly, we fitted an ARIMA model and observed that there were present heteroskewdastic transactions. Then, we used different ARCH class volatility models but one of them we used intervention shock and selected the ARIMA with EGARCH model. Our findings established that ARIMA with EGARCH model comprises low residual variance and low forecast error for volume data and thus, the modeling concept used in this paper would be useful for the investors or researchers to resolve the future value of share volume.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 176 pp. Englisch. Bestandsnummer des Verkäufers 9783659683664
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book helps to search a suitable model for the daily volume data series of Dhaka Stock Exchange (DSE) and to forecast the future outline. ML - ARCH (Marquardt) method has been used to build up the models for the volume data series by using statistical software's Eviews verson-5. Firstly, we fitted an ARIMA model and observed that there were present heteroskewdastic transactions. Then, we used different ARCH class volatility models but one of them we used intervention shock and selected the ARIMA with EGARCH model. Our findings established that ARIMA with EGARCH model comprises low residual variance and low forecast error for volume data and thus, the modeling concept used in this paper would be useful for the investors or researchers to resolve the future value of share volume. Bestandsnummer des Verkäufers 9783659683664
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