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Regular version of the site
Master 2019/2020

Forecasting in Economics and Finance

Type: Elective course (Financial Analyst)
Area of studies: Finance and Credit
Delivered by: HSE Banking Institute
When: 1 year, 3 module
Mode of studies: Full time
Instructors: Ivan Stankevich
Master’s programme: Financial Analyst
Language: English
ECTS credits: 3

Course Syllabus

Abstract

The course is an introduction to main forecasting techniques used in economics and finance. It covers topics ranging from data collection and preparation to econometrics, general equilibrium and machine learning models used in forecasting. This course is mostly practical, not theoretical, so a significant amount of time will be devoted to application of the models discussed to real data.
Learning Objectives

Learning Objectives

  • The main aim of the course is to provide the students with understanding of how the forecasting is usually conducted. It includes both the ability to use and evaluate external forecasts and the ability to make forecasts themselves.
Expected Learning Outcomes

Expected Learning Outcomes

  • Students should be able to find the data they need, choose the model suitable to a certain problem, evaluate the forecasting performance of the model and interpret the results obtained. Apart from that, application of forecasting to decision-making process will be discussed.
Course Contents

Course Contents

  • • Sources of economic and financial data and external forecasts
  • • Main macroeconomic indicators
  • • Data collection and preparation, outliers, seasonal adjustment
  • • Measures of forecasting performance
  • • Time series econometrics models: stationary and non-stationary time series, ARIMA
  • • Vector autoregression, Bayesian Vector autoregression
  • • Macroeconomic models: general equilibrium models
  • • Basic machine learning techniques: LASSO, decision trees
  • • Overview of more advances econometric and machine learning tools
  • • Scenario forecasting
  • • Policy implications of forecasts
Assessment Elements

Assessment Elements

  • non-blocking essay
  • non-blocking final exam
    The exam is conducted in written form on the Zoom platform: the questions will be sent to the group e-mail, the students' answers are to be sent in PDF format on the lecturer's e-mail ivanstankevich0@gmail.com or istankevich@hse.ru. Web cameras should be activated all the time of the exam. Students can turn on the microphones if needed (e.g. to answer the questions about the structure of the exam) The Zoom conference will be activated 20 minutes prior to the scheduled starting time, all the students should be there by the beginning of the exam. The student's computer (tablets or smartphones are also allowed) should satisfy the following requirements: camera, microphone, support of Zoom. To participate in the exam the student should: come on time, keep the camera turned on during the exam. The exam is conducted in an open book format, so the students are allowed to use any printed, electronic or hand-written materials, but are not allowed to communicate with each other. Short-term loss of connection is under 3 minutes. Long-term loss of connection is more than 3 minutes. In case of long-term loss of connection the student is not allowed to continue the exam. The retake of the exam implies the use of a different set of questions.
Interim Assessment

Interim Assessment

  • Interim assessment (3 module)
    0.45 * essay + 0.55 * final exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Hassan S. Bakouch. (2007). Analysis of Integrated and Cointegrated Time Series with R by B. Pfaff. Journal of the Royal Statistical Society Series A, (2), 509. https://doi.org/10.1111/j.1467-985X.2007.00473_13.x

Recommended Additional Bibliography

  • Konstantinos Nikolopoulos, Waleed S. Alghassab, Konstantia Litsiou, & Stelios Sapountzis. (2019). Long-Term Economic Forecasting with Structured Analogies and Interaction Groups. Working Papers. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.p.bng.wpaper.19018
  • Mitchell, K., & Pearce, D. K. (2020). How Did Unconventional Monetary Policy Affect Economic Forecasts? Contemporary Economic Policy, 38(1), 206–220. https://doi.org/10.1111/coep.12440
  • Thanh, D. V. (2019). Macro-Econometric Model for Medium-Term Socio-Economic Development Planning in Vietnam. Part 2: Application of the Model. Economy of Region / Ekonomika Regiona, 15(3), 695–706. https://doi.org/10.17059/2019-3-6