Nonlinear Econometric Models
Informacje ogólne
Kod przedmiotu: | 230241-D |
Kod Erasmus / ISCED: |
11.2
|
Nazwa przedmiotu: | Nonlinear Econometric Models |
Jednostka: | Szkoła Główna Handlowa w Warszawie |
Grupy: |
Elective courses for AAB - masters Przedmioty kierunkowe do wyboru SMMD-ADA Przedmioty kierunkowe do wyboru SMMD-MIS |
Punkty ECTS i inne: |
3.00 (zmienne w czasie)
|
Język prowadzenia: | angielski |
Efekty uczenia się: |
Wiedza: Students should know: 1. what nonlinear econometric models are used to analyze problems in economics and finance and what methods are used to specify, estimate parameters and test the quality of nonlinear econometric models, 2. properties of estimators used for nonlinear models (NLS and ML methods) and how the maximum likelihood function is constructed for selected nonlinear models, 3. the optimization methods of the likelihood function and the sum of squared residuals and the econometric software and programming languages that are used to construct nonlinear econometric models. Umiejętności: Students should be able to: 1. analyze financial and economic developments using state-space models, switching regression models and other similar models, 2. estimate parameters of nonlinear models, test these models and select optimal specification of the model, 3. write a computer program to apply nonlinear econometric methods. Kompetencje społeczne: Students have the possibility to: 1. improve their skills in using the econometric software, 2. extend their knowledge of the econometric theory. |
Zajęcia w cyklu "Semestr letni 2024/25" (jeszcze nie rozpoczęty)
Okres: | 2025-02-15 - 2025-09-30 |
Przejdź do planu
PN WT ŚR CZ PT |
Typ zajęć: |
Laboratorium, 30 godzin
|
|
Koordynatorzy: | (brak danych) | |
Prowadzący grup: | (brak danych) | |
Lista studentów: | (nie masz dostępu) | |
Zaliczenie: |
Przedmiot -
Ocena
Laboratorium - Ocena |
|
Skrócony opis: |
The use of econometric models to explain nonlinear phenomena in economics and finance. Models with variable parameters, state-space models, state-space models with ARCH effects threshold regression, STAR, regime-switching models, neural networks - specification, estimation, verification. The use of econometric methods: Kalman filter, identification through heteroscedasticity. Theoretical foundations of nonlinear estimation. |
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Pełny opis: |
The main objective of the course is to familiarize students with the non-linear econometric models and modeling financial and economic phenomena. We will present models with variable parameters, state-space models, state-space models with ARCH effects threshold regressions, STAR models, regime-switching models, neural networks. Construction, estimation and verification of these models will be presented. The second objective is to present econometric software and programming languages - used to build and use nonlinear econometric models. |
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Literatura: |
Literatura podstawowa: J.D.Hamilton, Time Series Analysis, Princeton University Press 1994; artykuły z czasopism naukowych, wybrane przez wykładowcę. Literatura uzupełniająca: G.Chow, Ekonometria, PWN 1995; M.Osińska, Ekonometria finansowa, Polskie Wydawnictwo Ekonomiczne 2006, Warszawa; G.S.Maddala, Ekonometria, PWN 2006; Ch.Kim, Ch.Nelson, State-Space Models with Regime Switching, The MIT Press 1999; Ph.Frances, D.van Dijk, Non-linear time series models in empirical finance, Cambridge University Press 2006. |
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Uwagi: |
Kryteria oceniania: egzamin tradycyjny-pisemny: 50.00% inne: 50.00% |
Zajęcia w cyklu "Semestr zimowy 2024/25" (jeszcze nie rozpoczęty)
Okres: | 2024-10-01 - 2025-02-14 |
Przejdź do planu
PN WT ŚR CZ PT |
Typ zajęć: |
Laboratorium, 30 godzin
|
|
Koordynatorzy: | (brak danych) | |
Prowadzący grup: | (brak danych) | |
Lista studentów: | (nie masz dostępu) | |
Zaliczenie: |
Przedmiot -
Ocena
Laboratorium - Ocena |
|
Skrócony opis: |
The use of econometric models to explain nonlinear phenomena in economics and finance. Models with variable parameters, state-space models, state-space models with ARCH effects threshold regression, STAR, regime-switching models, neural networks - specification, estimation, verification. The use of econometric methods: Kalman filter, identification through heteroscedasticity. Theoretical foundations of nonlinear estimation. |
|
Pełny opis: |
The main objective of the course is to familiarize students with the non-linear econometric models and modeling financial and economic phenomena. We will present models with variable parameters, state-space models, state-space models with ARCH effects threshold regressions, STAR models, regime-switching models, neural networks. Construction, estimation and verification of these models will be presented. The second objective is to present econometric software and programming languages - used to build and use nonlinear econometric models. |
|
Literatura: |
Literatura podstawowa: J.D.Hamilton, Time Series Analysis, Princeton University Press 1994; artykuły z czasopism naukowych, wybrane przez wykładowcę. Literatura uzupełniająca: G.Chow, Ekonometria, PWN 1995; M.Osińska, Ekonometria finansowa, Polskie Wydawnictwo Ekonomiczne 2006, Warszawa; G.S.Maddala, Ekonometria, PWN 2006; Ch.Kim, Ch.Nelson, State-Space Models with Regime Switching, The MIT Press 1999; Ph.Frances, D.van Dijk, Non-linear time series models in empirical finance, Cambridge University Press 2006. |
|
Uwagi: |
Kryteria oceniania: egzamin tradycyjny-pisemny: 50.00% inne: 50.00% |
Zajęcia w cyklu "Semestr letni 2023/24" (zakończony)
Okres: | 2024-02-24 - 2024-09-30 |
Przejdź do planu
PN WT ŚR CZ PT |
Typ zajęć: |
Laboratorium, 30 godzin
|
|
Koordynatorzy: | (brak danych) | |
Prowadzący grup: | (brak danych) | |
Lista studentów: | (nie masz dostępu) | |
Zaliczenie: |
Przedmiot -
Ocena
Laboratorium - Ocena |
|
Skrócony opis: |
The use of econometric models to explain nonlinear phenomena in economics and finance. Models with variable parameters, state-space models, state-space models with ARCH effects threshold regression, STAR, regime-switching models, neural networks - specification, estimation, verification. The use of econometric methods: Kalman filter, identification through heteroscedasticity. Theoretical foundations of nonlinear estimation. |
|
Pełny opis: |
The main objective of the course is to familiarize students with the non-linear econometric models and modeling financial and economic phenomena. We will present models with variable parameters, state-space models, state-space models with ARCH effects threshold regressions, STAR models, regime-switching models, neural networks. Construction, estimation and verification of these models will be presented. The second objective is to present econometric software and programming languages - used to build and use nonlinear econometric models. |
|
Literatura: |
Literatura podstawowa: J.D.Hamilton, Time Series Analysis, Princeton University Press 1994; artykuły z czasopism naukowych, wybrane przez wykładowcę. Literatura uzupełniająca: G.Chow, Ekonometria, PWN 1995; M.Osińska, Ekonometria finansowa, Polskie Wydawnictwo Ekonomiczne 2006, Warszawa; G.S.Maddala, Ekonometria, PWN 2006; Ch.Kim, Ch.Nelson, State-Space Models with Regime Switching, The MIT Press 1999; Ph.Frances, D.van Dijk, Non-linear time series models in empirical finance, Cambridge University Press 2006. |
|
Uwagi: |
Kryteria oceniania: egzamin tradycyjny-pisemny: 50.00% inne: 50.00% |
Zajęcia w cyklu "Semestr zimowy 2023/24" (zakończony)
Okres: | 2023-10-01 - 2024-02-23 |
Przejdź do planu
PN WT ŚR CZ PT |
Typ zajęć: |
Laboratorium, 30 godzin
|
|
Koordynatorzy: | (brak danych) | |
Prowadzący grup: | (brak danych) | |
Lista studentów: | (nie masz dostępu) | |
Zaliczenie: |
Przedmiot -
Ocena
Laboratorium - Ocena |
|
Skrócony opis: |
The use of econometric models to explain nonlinear phenomena in economics and finance. Models with variable parameters, state-space models, state-space models with ARCH effects threshold regression, STAR, regime-switching models, neural networks - specification, estimation, verification. The use of econometric methods: Kalman filter, identification through heteroscedasticity. Theoretical foundations of nonlinear estimation. |
|
Pełny opis: |
The main objective of the course is to familiarize students with the non-linear econometric models and modeling financial and economic phenomena. We will present models with variable parameters, state-space models, state-space models with ARCH effects threshold regressions, STAR models, regime-switching models, neural networks. Construction, estimation and verification of these models will be presented. The second objective is to present econometric software and programming languages - used to build and use nonlinear econometric models. |
|
Literatura: |
Literatura podstawowa: J.D.Hamilton, Time Series Analysis, Princeton University Press 1994; artykuły z czasopism naukowych, wybrane przez wykładowcę. Literatura uzupełniająca: G.Chow, Ekonometria, PWN 1995; M.Osińska, Ekonometria finansowa, Polskie Wydawnictwo Ekonomiczne 2006, Warszawa; G.S.Maddala, Ekonometria, PWN 2006; Ch.Kim, Ch.Nelson, State-Space Models with Regime Switching, The MIT Press 1999; Ph.Frances, D.van Dijk, Non-linear time series models in empirical finance, Cambridge University Press 2006. |
|
Uwagi: |
Kryteria oceniania: egzamin tradycyjny-pisemny: 50.00% inne: 50.00% |
Właścicielem praw autorskich jest Szkoła Główna Handlowa w Warszawie.