Sertta Fatma (7 results)

Condition: New. pp. 152.

Taschenbuch. Condition: 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.

Taschenbuch. Condition: 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.

Condition: New. Print on Demand pp. 152 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condition: New. PRINT ON DEMAND pp. 152.

Taschenbuch. Condition: 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.

Taschenbuch. Condition: 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.