Polina Pogorelova
- Senior Lecturer:Faculty of Economic Sciences / Department of Applied Economics
- Research Assistant:Laboratory of Stochastic Analysis and its Applications
- Polina Pogorelova has been at HSE University since 2019.
Education
- 2019
Master's in Economics
HSE University - 2016
Bachelor's in Applied Mathematics
Orenburg State University
Courses (2023/2024)
- Econometrics 1 (Advanced course) (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 1, 2 module)Rus
- Econometrics 2 (Advanced course) (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 3, 4 module)Rus
- Econometrics (Advanced Level) (Master’s programme; Faculty of Economic Sciences; 1 year, 3, 4 module)Rus
- Probability Theory and Statistics (Bachelor’s programme; Faculty of World Economy and International Affairs; 2 year, 1-3 module)Rus
- Past Courses
Courses (2022/2023)
- Econometrics 1 (Advanced course) (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 1, 2 module)Rus
- Econometrics 2 (Advanced course) (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 3, 4 module)Rus
- Econometrics (Advanced Level) (Master’s programme; Faculty of Economic Sciences; 1 year, 3, 4 module)Rus
- Financial Econometrics (Master’s programme; Faculty of Economic Sciences; 2 year, 2 module)Rus
- Финансовая эконометрика (Mago-Lego; 2 module)Rus
- Probability Theory and Statistics (Bachelor’s programme; Faculty of World Economy and International Affairs; 2 year, 1-3 module)Rus
Time Series Analysis (Master’s programme; Faculty of Economic Sciences; field of study "38.04.01. Экономика", field of study "38.04.01. Экономика"; 1 year, 3, 4 module)Rus
Courses (2021/2022)
- Econometrics (Bachelor’s programme; Faculty of World Economy and International Affairs; 3 year, 1-3 module)Rus
- Econometrics (Advanced Level) (Master’s programme; Faculty of Economic Sciences; 1 year, 3, 4 module)Rus
- Probability Theory and Statistics (Bachelor’s programme; Faculty of World Economy and International Affairs; 2 year, 1-3 module)Rus
Time Series Analysis (Master’s programme; Faculty of Economic Sciences; field of study "38.04.01. Экономика", field of study "38.04.01. Экономика"; 1 year, 3, 4 module)Rus
Time Series Analysis-1 (Master’s programme; Faculty of Economic Sciences; field of study "38.04.01. Экономика", field of study "38.04.01. Экономика"; 1 year, 3 module)Rus
Time Series Analysis-2 (Master’s programme; Faculty of Economic Sciences; field of study "38.04.01. Экономика", field of study "38.04.01. Экономика"; 1 year, 4 module)Rus
Courses (2020/2021)
- Econometrics (Bachelor’s programme; Faculty of World Economy and International Affairs; 3 year, 1-3 module)Rus
- Econometrics (Advanced Level) (Master’s programme; Faculty of Economic Sciences; 1 year, 3, 4 module)Rus
- Probability Theory and Statistics (Bachelor’s programme; Faculty of World Economy and International Affairs; 2 year, 1-3 module)Rus
Courses (2019/2020)
- Advanced Econometrics (Master’s programme; Faculty of Economic Sciences; 1 year, 3, 4 module)Rus
- Econometrics (Bachelor’s programme; Graduate School of Business; 2 year, 4 module)Rus
- Probability Theory and Statistics (Bachelor’s programme; Faculty of World Economy and International Affairs; 2 year, 1-3 module)Rus
Publications3
- Article Аганин А. Д., Маневич В. А., Пересецкий А. А., Погорелова П. В. Сравнение моделей прогноза волатильности криптовалют и фондового рынка // Экономический журнал Высшей школы экономики. 2023. Т. 27. № 1. С. 49-77. doi
- Article В. А. Маневич, А. А. Пересецкий, П. В. Погорелова Волатильность фондового рынка и волатильность криптовалют // Прикладная эконометрика. 2022. Т. 65. № 1. С. 65-76. doi
- Article Погорелова П. В., Пересецкий А. А. Выделение глобального стохастического тренда из несинхронных наблюдений волатильности финансовых индексов // Прикладная эконометрика. 2020. Т. 57. С. 53-71. doi
Conferences
- 2023Modern Econometric Tools and Applications – META2023 (Нижний Новгород). Presentation: Investigation of the impact of uncertainty indicators on Bitcoin volatility using ARDL model
- 2022
Modern Econometric Tools and Applications – META2022 (Нижний Новгород). Presentation: Comparison of GARCH and HAR models for realized volatility of Bitcoin and E-mini S&P 500
2nd International Conference on Econometrics and Business Analytics (iCEBA) (Ереван). Presentation: Comparison of GARCH and HAR models for realized volatility of Bitcoin and E-mini S&P 500
2nd International Conference on Econometrics and Business Analytics (iCEBA) (Ереван). Presentation: Comparison of GARCH and HAR models for realized volatility of Bitcoin and E-mini S&P 500
- 2020
IV Российский экономический конгресс (РЭК-2020) (Москва). Presentation: Выделение глобального стохастического тренда из несинхронных наблюдений волатильности финансовых индексов