Gaussian normal error assumption is a basic assumption for co-integration tests. Ordinary Least Squares (OLS) based regression techniques are also widely used together with the normality assumption. To consider the heavy-tailed structure observed in many economic and financial time series, new residual-based co-integration tests are developed and analyzed via Monte Carlo simulations. The new tests are based on Least Absolute Deviation (LAD) regressions, whose error structure follows the infinite-variance stable distribution. Empirical applications on Forward Rate Unbiasedness Hypothesis (FRUH) and Purchasing Power Parity (PPP) verify the need to make use of the infinite-variance stable distributions as the error distributions.
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Gaussian normal error assumption is a basic assumption for co-integration tests. Ordinary Least Squares (OLS) based regression techniques are also widely used together with the normality assumption. To consider the heavy-tailed structure observed in many economic and financial time series, new residual-based co-integration tests are developed and analyzed via Monte Carlo simulations. The new tests are based on Least Absolute Deviation (LAD) regressions, whose error structure follows the infinite-variance stable distribution. Empirical applications on Forward Rate Unbiasedness Hypothesis (FRUH) and Purchasing Power Parity (PPP) verify the need to make use of the infinite-variance stable distributions as the error distributions.
Fatma Özgü Serttaş was born in Ankara, Turkey and graduated from T.E.D Ankara College in 1995. She attended Bilkent University and received her B.A. in Economics in 2000 and her M.A. in Economics in 2002. She obtained her Ph.D. in Economics from Iowa State University in 2010. Currently, she is an Assistant Professor at Yıldırım Beyazıt University.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Gaussian normal error assumption is a basic assumption for co-integration tests. Ordinary Least Squares (OLS) based regression techniques are also widely used together with the normality assumption. To consider the heavy-tailed structure observed in many economic and financial time series, new residual-based co-integration tests are developed and analyzed via Monte Carlo simulations. The new tests are based on Least Absolute Deviation (LAD) regressions, whose error structure follows the infinite-variance stable distribution. Empirical applications on Forward Rate Unbiasedness Hypothesis (FRUH) and Purchasing Power Parity (PPP) verify the need to make use of the infinite-variance stable distributions as the error distributions. 152 pp. Englisch. Nº de ref. del artículo: 9783846547328
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Serttas Fatma OezgueFatma Oezgue Serttas was born in Ankara, Turkey and graduated from T.E.D Ankara College in 1995. She attended Bilkent University and received her B.A. in Economics in 2000 and her M.A. in Economics in 2002. She obtain. Nº de ref. del artículo: 5498229
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Gaussian normal error assumption is a basic assumption for co-integration tests. Ordinary Least Squares (OLS) based regression techniques are also widely used together with the normality assumption. To consider the heavy-tailed structure observed in many economic and financial time series, new residual-based co-integration tests are developed and analyzed via Monte Carlo simulations. The new tests are based on Least Absolute Deviation (LAD) regressions, whose error structure follows the infinite-variance stable distribution. Empirical applications on Forward Rate Unbiasedness Hypothesis (FRUH) and Purchasing Power Parity (PPP) verify the need to make use of the infinite-variance stable distributions as the error distributions.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 152 pp. Englisch. Nº de ref. del artículo: 9783846547328
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Gaussian normal error assumption is a basic assumption for co-integration tests. Ordinary Least Squares (OLS) based regression techniques are also widely used together with the normality assumption. To consider the heavy-tailed structure observed in many economic and financial time series, new residual-based co-integration tests are developed and analyzed via Monte Carlo simulations. The new tests are based on Least Absolute Deviation (LAD) regressions, whose error structure follows the infinite-variance stable distribution. Empirical applications on Forward Rate Unbiasedness Hypothesis (FRUH) and Purchasing Power Parity (PPP) verify the need to make use of the infinite-variance stable distributions as the error distributions. Nº de ref. del artículo: 9783846547328
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Taschenbuch. Condición: Neu. Infinite-Variance Stable Errors and Robust Estimation Procedures | A Monte Carlo Study with Empirical Applications | Fatma Özgü Sertta¿ | Taschenbuch | 152 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846547328 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Nº de ref. del artículo: 106706632
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