Анализ временных рядов

2026/2027

Статус: Маго-лего

Кто читает: Банковский институт

Где читается: Банковский институт

Онлайн-часы: 20

Охват аудитории: для своего кампуса

Язык: русский

Кредиты: 3

Контактные часы: 8

Дополнительные материалы в LMS Задать вопрос

Аннотация

Time Series Analysis (Master level) is an elective course designed for the first year Master students of “Finantial Analytic” Program. This is an intermediate course of Time Series Theory for the students specializing in the field of Finance and Banking. The course is taught in English.The stress in the course is made on the sense of facts and methods of time series analysis. Conclusions and proofs are given for some basic formulas and models; this enables the students to understand the principles of economic theory. The main stress is made on the economic interpretation and applications of considered economic models.

Цель освоения дисциплины

The students should get acquainted with the main concepts of Time Series theory and methods of analysis.
Students should know how to use them in examining financial processes and should understand methods, ideas, results and conclusions that can be met in the majority of books and articles on economics and finance.
Students should master traditional methods of Time Series analysis, intended mainly for working with time series data.
Students should understand the differences between cross-sections and time series, and those specific economic problems, which occur while working with data of these types.

Планируемые результаты обучения

Understand trend-seasonal decomposition
Understand the ETS model and theta-model
Know how to do Box-Cox transformation
Build the ACF and PACF
Interpret the ARIMA models
Conduct stationarity tests
Know how to create predictors
Know the difference between the ARIMAX and ARDL model
Learn how to compare models
Learn how to handle missing data
Know how to detect anomalies
Learn about structural breaks

Содержание учебной дисциплины

Trend-seasonal decomposition and exponential smoothing models
ARIMA models
Time series forecasting
Pre-procssing data

Элементы контроля

Test 1
There are two graded online tests. Exact dates and time slots will be published in the LMS after confirmation of the official Module 3 timetable. The tests assess conceptual understanding, interpretation of statistical output, recognition of methodological errors, and basic numerical reasoning. Questions may include multiple-choice items, numerical answers, short code fragments, diagnostics, or AI-generated outputs that students must evaluate critically.
Test 2
There are two graded online tests. Exact dates and time slots will be published in the LMS after confirmation of the official Module 3 timetable. The tests assess conceptual understanding, interpretation of statistical output, recognition of methodological errors, and basic numerical reasoning. Questions may include multiple-choice items, numerical answers, short code fragments, diagnostics, or AI-generated outputs that students must evaluate critically.
Final Project
The final project is an individual applied forecasting exercise using a real economic or financial TS. The objective is to compare forecasting approaches based on predictive performance and to demonstrate that the complete analytical pipeline is methodologically valid, reproducible, and robust to key data and modeling choices.

Промежуточная аттестация

2026/2027 3rd module
0.25 * Test 1 + 0.5 * Final Project + 0.25 * Test 2

Список литературы

Авторы

Касьянова Ксения Александровна
Елизарова Ирина Николаевна
Кузюкова Юлия Игоревна

Программа дисциплины