Financial Econometrics I ( FAP, CIMA)
Informacje ogólne
Kod przedmiotu: | 222041-D |
Kod Erasmus / ISCED: |
11.2
|
Nazwa przedmiotu: | Financial Econometrics I ( FAP, CIMA) |
Jednostka: | Szkoła Główna Handlowa w Warszawie |
Grupy: |
Elective courses for FA - masters Elective courses for FAP - masters Elective courses for IMA - masters Elective courses for QEM - masters Przedmioty kierunkowe do wyboru SMMD-EKO Przedmioty kierunkowe do wyboru SMMD-FIR |
Punkty ECTS i inne: |
3.00 (zmienne w czasie)
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Język prowadzenia: | angielski |
Efekty uczenia się: |
Wiedza: 1. Describe areas of interest in financial econometrics. 2. Describe time-series characteristics of rates of return, their empirical distributions and distributions used for modeling the returns. 3. Express assumptions for the effective market hypothesis (EMH). Explain similarities and differences between basic forms of market effectiveness. Propose methods of testing the weak form of the effective market hypothesis (EMH). Give examples of anomalies in financial markets and propose methods to test those anomalies. 4. Understand the construction and nature of linear ARMA models of asset returns. Know a method of lag identification in ARMA models. 5. Interpret results from the unit root tests (the Dickey-Fuller test). 6. Characterize assumptions and the construction of CAPM models. Propose some extensions of the standard model specifications. Umiejętności: Student should be able to: 1. Perform a broad range of statistical analyses related to time series of asset returns. Interpret obtained results. Perform the ADF and KPSS tests. 2. Perform tests of the weak form of the efficient market hypothesis (EMH). 3. Identify the structure of an ARMA model using the Box-Jenkins approach. Estimate ARMA models and interpret the results. Verify quality of an ARMA model. 4. Estimate CAPM models and interpret estimation results. 5. Test co-integration relation between financial variables. Estimate and interpret the results. 6. Verify volatility clustering effect for asset returns. Select an appropriate specification of the GARCH model. Interpret and assess the quality of obtained results. Identify nonlinearities in the conditional variance equation of a GARCH model. Propose asymmetric GARCH specifications. Kompetencje społeczne: Ability to communicate in order to disseminate knowledge of financial econometrics Ability to cooperate in applying methods of financial econometrics |
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, 14 godzin
Wykład, 16 godzin
|
|
Koordynatorzy: | (brak danych) | |
Prowadzący grup: | Dobromił Serwa | |
Lista studentów: | (nie masz dostępu) | |
Zaliczenie: |
Przedmiot -
Ocena
Wykład - Ocena |
|
Skrócony opis: |
See semester study programme. |
|
Pełny opis: |
The main goal of the course is to present a basic range of econometric tools used in financial data modeling. Special attention will be paid to the concept of financial time series. The issues cover tools for testing the market efficiency hypothesis, building and estimation of univariate linear and non-linear models used for the description of conditional mean and variance of return time series, as well as methods of high frequency data modeling. Additional target of the lecture is to present empirical examples of the models with the application of selected econometric software packages. Financial econometrics is concerned with the application of quantitative methods in finance. The main aim of the course is to present econometric tools applied to description and forecasting of price and return time series of financial instruments and indices. These are often recorded at a very high frequency, are non-stationary, autocorrelated and characterized by a time-varying variance. The methods presented during the course serve as a starting point for more complex research, e.g., on financial efficiency, portfolio analysis, risk valuation or pricing of financial instruments. |
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Literatura: |
Literatura podstawowa: Zbigniew Krysiak, Financial Engineering in the Project Development, Warsaw School of Economics, June 2015; Roman Kozhan, Financial Econometrics With EViews, Roman Kozhan & Ventus Publishing, 2010; Zbigniew Krysiak, Portfolio Development at Risk, Warsaw School of Economics, June 2015; Literatura uzupełniająca: J.Brzeszczyński, R.Kelm, Ekonometryczne modele rynków finansowych, WIG Press, Warszawa 2002; J.Y.Campbell, A.W.Lo, A.C.MacKinlay, The Econometrics of Financial Markets, Princeton University Press, New Jersey 1997; E.Elton, M.Gruber, S.Brown, W.Goetzman, Modern Portfolio Theory and Investment Analysis, John Wiley&Sons 2007; J.D.Hamilton, Time Series Analysis, Princeton University Press 1994; M.Rubaszek, D.Serwa, W.Marcinkowska-Lewandowska (red. nauk.), Analiza kursu walutowego, Wyd. Beck, Warszawa 2009; R.S.Tsay, Analysis of Financial Time Series, Wiley 2005. G. Loeffler, P. Posch (2011), Credit Risk Modelling Using Excel and VBA with DVD, Wiley. Lando D. (2004) Credit risk modeling, Princeton Series in Finance. Matuszyk A. (2008) Credit scoring, CeDeWu. |
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Uwagi: |
Kryteria oceniania: egzamin testowy: 100.00% |
Zajęcia w cyklu "Semestr zimowy 2024/25" (w trakcie)
Okres: | 2024-10-01 - 2025-02-14 |
Przejdź do planu
PN WT ŚR CZ PT |
Typ zajęć: |
Laboratorium, 14 godzin
Wykład, 16 godzin
|
|
Koordynatorzy: | (brak danych) | |
Prowadzący grup: | (brak danych) | |
Lista studentów: | (nie masz dostępu) | |
Zaliczenie: |
Przedmiot -
Ocena
Wykład - Ocena |
|
Skrócony opis: |
See semester study programme. |
|
Pełny opis: |
The main goal of the course is to present a basic range of econometric tools used in financial data modeling. Special attention will be paid to the concept of financial time series. The issues cover tools for testing the market efficiency hypothesis, building and estimation of univariate linear and non-linear models used for the description of conditional mean and variance of return time series, as well as methods of high frequency data modeling. Additional target of the lecture is to present empirical examples of the models with the application of selected econometric software packages. Financial econometrics is concerned with the application of quantitative methods in finance. The main aim of the course is to present econometric tools applied to description and forecasting of price and return time series of financial instruments and indices. These are often recorded at a very high frequency, are non-stationary, autocorrelated and characterized by a time-varying variance. The methods presented during the course serve as a starting point for more complex research, e.g., on financial efficiency, portfolio analysis, risk valuation or pricing of financial instruments. |
|
Literatura: |
Literatura podstawowa: Zbigniew Krysiak, Financial Engineering in the Project Development, Warsaw School of Economics, June 2015; Roman Kozhan, Financial Econometrics With EViews, Roman Kozhan & Ventus Publishing, 2010; Zbigniew Krysiak, Portfolio Development at Risk, Warsaw School of Economics, June 2015; Literatura uzupełniająca: J.Brzeszczyński, R.Kelm, Ekonometryczne modele rynków finansowych, WIG Press, Warszawa 2002; J.Y.Campbell, A.W.Lo, A.C.MacKinlay, The Econometrics of Financial Markets, Princeton University Press, New Jersey 1997; E.Elton, M.Gruber, S.Brown, W.Goetzman, Modern Portfolio Theory and Investment Analysis, John Wiley&Sons 2007; J.D.Hamilton, Time Series Analysis, Princeton University Press 1994; M.Rubaszek, D.Serwa, W.Marcinkowska-Lewandowska (red. nauk.), Analiza kursu walutowego, Wyd. Beck, Warszawa 2009; R.S.Tsay, Analysis of Financial Time Series, Wiley 2005. G. Loeffler, P. Posch (2011), Credit Risk Modelling Using Excel and VBA with DVD, Wiley. Lando D. (2004) Credit risk modeling, Princeton Series in Finance. Matuszyk A. (2008) Credit scoring, CeDeWu. |
|
Uwagi: |
Kryteria oceniania: egzamin testowy: 100.00% |
Zajęcia w cyklu "Semestr letni 2023/24" (zakończony)
Okres: | 2024-02-24 - 2024-09-30 |
Przejdź do planu
PN WT ŚR CZ PT LAB
WYK
|
Typ zajęć: |
Laboratorium, 14 godzin
Wykład, 16 godzin
|
|
Koordynatorzy: | (brak danych) | |
Prowadzący grup: | Dobromił Serwa | |
Lista studentów: | (nie masz dostępu) | |
Zaliczenie: |
Przedmiot -
Ocena
Wykład - Ocena |
|
Skrócony opis: |
See semester study programme. |
|
Pełny opis: |
The main goal of the course is to present a basic range of econometric tools used in financial data modeling. Special attention will be paid to the concept of financial time series. The issues cover tools for testing the market efficiency hypothesis, building and estimation of univariate linear and non-linear models used for the description of conditional mean and variance of return time series, as well as methods of high frequency data modeling. Additional target of the lecture is to present empirical examples of the models with the application of selected econometric software packages. Financial econometrics is concerned with the application of quantitative methods in finance. The main aim of the course is to present econometric tools applied to description and forecasting of price and return time series of financial instruments and indices. These are often recorded at a very high frequency, are non-stationary, autocorrelated and characterized by a time-varying variance. The methods presented during the course serve as a starting point for more complex research, e.g., on financial efficiency, portfolio analysis, risk valuation or pricing of financial instruments. |
|
Literatura: |
Literatura podstawowa: Zbigniew Krysiak, Financial Engineering in the Project Development, Warsaw School of Economics, June 2015; Roman Kozhan, Financial Econometrics With EViews, Roman Kozhan & Ventus Publishing, 2010; Zbigniew Krysiak, Portfolio Development at Risk, Warsaw School of Economics, June 2015; Literatura uzupełniająca: J.Brzeszczyński, R.Kelm, Ekonometryczne modele rynków finansowych, WIG Press, Warszawa 2002; J.Y.Campbell, A.W.Lo, A.C.MacKinlay, The Econometrics of Financial Markets, Princeton University Press, New Jersey 1997; E.Elton, M.Gruber, S.Brown, W.Goetzman, Modern Portfolio Theory and Investment Analysis, John Wiley&Sons 2007; J.D.Hamilton, Time Series Analysis, Princeton University Press 1994; M.Rubaszek, D.Serwa, W.Marcinkowska-Lewandowska (red. nauk.), Analiza kursu walutowego, Wyd. Beck, Warszawa 2009; R.S.Tsay, Analysis of Financial Time Series, Wiley 2005. G. Loeffler, P. Posch (2011), Credit Risk Modelling Using Excel and VBA with DVD, Wiley. Lando D. (2004) Credit risk modeling, Princeton Series in Finance. Matuszyk A. (2008) Credit scoring, CeDeWu. |
|
Uwagi: |
Kryteria oceniania: egzamin testowy: 100.00% |
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, 14 godzin
Wykład, 16 godzin
|
|
Koordynatorzy: | (brak danych) | |
Prowadzący grup: | (brak danych) | |
Lista studentów: | (nie masz dostępu) | |
Zaliczenie: |
Przedmiot -
Ocena
Wykład - Ocena |
|
Skrócony opis: |
See semester study programme. |
|
Pełny opis: |
The main goal of the course is to present a basic range of econometric tools used in financial data modeling. Special attention will be paid to the concept of financial time series. The issues cover tools for testing the market efficiency hypothesis, building and estimation of univariate linear and non-linear models used for the description of conditional mean and variance of return time series, as well as methods of high frequency data modeling. Additional target of the lecture is to present empirical examples of the models with the application of selected econometric software packages. Financial econometrics is concerned with the application of quantitative methods in finance. The main aim of the course is to present econometric tools applied to description and forecasting of price and return time series of financial instruments and indices. These are often recorded at a very high frequency, are non-stationary, autocorrelated and characterized by a time-varying variance. The methods presented during the course serve as a starting point for more complex research, e.g., on financial efficiency, portfolio analysis, risk valuation or pricing of financial instruments. |
|
Literatura: |
Literatura podstawowa: Zbigniew Krysiak, Financial Engineering in the Project Development, Warsaw School of Economics, June 2015; Roman Kozhan, Financial Econometrics With EViews, Roman Kozhan & Ventus Publishing, 2010; Zbigniew Krysiak, Portfolio Development at Risk, Warsaw School of Economics, June 2015; Literatura uzupełniająca: J.Brzeszczyński, R.Kelm, Ekonometryczne modele rynków finansowych, WIG Press, Warszawa 2002; J.Y.Campbell, A.W.Lo, A.C.MacKinlay, The Econometrics of Financial Markets, Princeton University Press, New Jersey 1997; E.Elton, M.Gruber, S.Brown, W.Goetzman, Modern Portfolio Theory and Investment Analysis, John Wiley&Sons 2007; J.D.Hamilton, Time Series Analysis, Princeton University Press 1994; M.Rubaszek, D.Serwa, W.Marcinkowska-Lewandowska (red. nauk.), Analiza kursu walutowego, Wyd. Beck, Warszawa 2009; R.S.Tsay, Analysis of Financial Time Series, Wiley 2005. G. Loeffler, P. Posch (2011), Credit Risk Modelling Using Excel and VBA with DVD, Wiley. Lando D. (2004) Credit risk modeling, Princeton Series in Finance. Matuszyk A. (2008) Credit scoring, CeDeWu. |
|
Uwagi: |
Kryteria oceniania: egzamin testowy: 100.00% |
Właścicielem praw autorskich jest Szkoła Główna Handlowa w Warszawie.