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Магистратура 2016/2017

## Эконометрика (продвинутый уровень)

Статус: Курс обязательный (Финансы)
Направление: 38.04.08. Финансы и кредит
Когда читается: 1-й курс, 2-4 модуль
Преподаватели: Ёрмирзоев Мирзобобо, Захаров Игорь Юрьевич, Ожегов Евгений Максимович
Прогр. обучения: Финансы
Язык: русский
Кредиты: 7

### Программа дисциплины

#### Аннотация

The course «Advanced econometrics» is designed for first-year graduate master students following the program «Finance». Its main goal is to familiarize the students with advanced methods of econometric research, and their application to finance area using the appropriate software. The important accent is made on the selection of adequate econometric methods and program tools for the solution of research problems which could arise during the analysis of financial markets.

#### Цель освоения дисциплины

• Providing a theoretical knowledge about state-of-the-art econometrical methods of data analysis.
• Forming practical skills of application of econometrical methods.
• Developing of skills of work with specialized statistical software.

#### Результаты освоения дисциплины

• Students knows the theoretical base of econometrics and basic methods of analysis.
• Students knows and uses advanced econometric methods.
• Students knows main asset pricing models, could select and use the most appropriate method for analysis.

#### Содержание учебной дисциплины

• Classical linear regression model
1. Simple linear regression. Introduction. OLS and its key assumptions. Estimation of simple linear regression by OLS. The quality of model fitting. 2. Multiple linear regression. Multiple linear regression in scalar and matrix forms. The main properties of the model: unbiasedness, consistency and efficiency. Hypothesis checking, testing of coefficients and of linear restrictions. 3. Violation of assumptions in linear regression models. Multicollinearity. Heteroskedasticity. Autocorrelation. Incorrect specification in respect to variables, errors and model form. The White, Breusch-Pagan and Durbin-Watson tests. 4. Nonlinear models. Binary choice models. Multiple response models. Censored models. Selection bias.
• Microeconometrics models
5. Instrumental variables estimation. Endogeneity: causes and consequences. Methods of treating: IV, 2SLS, GMM. Instrumental variables: validity, relevance and their testing. 6. Panel data models. Panel structure of data. Fixed and random effects. Endogeneity in panel data. Hausman-Taylor model. Dynamic models. Arellano-Bond model. Mixed models.
• Estimation and testing of asset pricing models
7. Estimation and testing of CAPM. Economic and econometric assumptions of asset pricing models. Estimation of time-series regressions for returns of stock prices (TSR). Testing of joint hypotheses for all alpha coefficients in CAPM. Wald, LM, LR and GRS (Gibbons, Ross, Shanken) tests. Comparative analysis of the power of these tests. 8. Estimation and testing of multifactor models of asset pricing on cross-sections. Generalized Method of Moments (GMM). Application of GMM to analysis of stock returns if normality and heteroskedasticity assumptions are violated (TSR). Cross-sectional analysis of multifactor models of asset pricing (CSR). Fama-MacBeth methodology.

#### Элементы контроля

• Test 1
• Seminar activities 1
• Independent work 1
• Exam 1
• Test 2
• Seminar activities 2
• Independent work 2
• Exam 2
• Test 3
• Independent work 3
• Exam 3
• Seminar activities 3

#### Промежуточная аттестация

• Промежуточная аттестация (1 модуль)
0.4 * Exam 1 + 0.12 * Independent work 1 + 0.24 * Seminar activities 1 + 0.24 * Test 1
• Промежуточная аттестация (2 модуль)
0.4 * Exam 2 + 0.12 * Independent work 2 + 0.24 * Seminar activities 2 + 0.24 * Test 2
• Промежуточная аттестация (3 модуль)
0.13 * Exam 3 + 0.05 * Independent work 3 + 0.05 * Seminar activities 3 + 0.1 * Test 3 + 0.34 * Промежуточная аттестация (1 модуль) + 0.33 * Промежуточная аттестация (2 модуль)