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Regular version of the site

Quantitative Methods in Economics

2019/2020
Academic Year
ENG
Instruction in English
5
ECTS credits
Course type:
Compulsory course
When:
1 year, 1, 2 module

Course Syllabus

Abstract

No financial analysis is possible without use of quantitative methods, and mastering them is crucial to be able to keep focus on economic background of the problem rather than technicalities. Selection of efficient quantitative techniques, performance of correct calculations, and provision of adequate economic interpretation of the results, all are integral parts of investment decision-making process, both in corporate finance and at financial markets. The program presents the fundamentals of some quantitative techniques essential in financial analysis which would be further applied in many parts of the Financial Analyst program, including Corporate Finance, Financial Markets: Equities and Debt, Portfolio Management, Forecasting in Economics and Finance, Business Valuation, Venture Capital, Risk Management. The first part of the program covers the time value of money concepts and quantitative techniques applied in decision-making process in corporate finance and valuation of various financial instruments (stocks, bonds etc.), as well as probability approach to financial data analysis (risk, return etc.). The second part introduces statistical approach to financial analysis and decision-making, including estimation of investment risk and returns, testing related hypotheses and economic interpretation of the test results. The program is based on Chartered Financial Analyst (CFA) curriculum.
Learning Objectives

Learning Objectives

  • • to give students a comprehensive understanding of time value of money, probability, statistical, sampling, estimation and hypothesis testing concepts; • to develop students’ ability to apply quantitative techniques to the real-world economic cases; • to provide students with the ability to identify issues and assumptions underlying quantitative analysis.
Expected Learning Outcomes

Expected Learning Outcomes

  • On successful completion of the course, students should be able to: • solve time value of money problems and use it applications in equity, fixed income, and derivatives analysis; • use statistical methods as a powerful set of tools for analyzing data and draw conclusions; • understand and apply the probability tools needed to frame and address many real-world problems involving risk;
  • On successful completion of the course, students should be able to:• understand probability distributions and perform their investment uses; • apply sampling and use sample information to estimate the population parameters; • understand the framework of hypothesis testing and make judgements about the population in the basis of a sample analysis.
Course Contents

Course Contents

  • The time value of money, money market yields
  • Discounted cash flows applications, portfolio return management
  • Statistical concepts and market returns
  • Probability concepts, portfolio expected return and variance of return
  • Common probability distributions
  • Sampling and estimation
  • Hypothesis testing
Assessment Elements

Assessment Elements

  • non-blocking mid-term test
  • non-blocking homework
  • non-blocking final exam
Interim Assessment

Interim Assessment

  • Interim assessment (2 module)
    0.5 * final exam + 0.25 * homework + 0.25 * mid-term test
Bibliography

Bibliography

Recommended Core Bibliography

  • DeFusco, R. A., McLeavey, D. W., Pinto, J. E., & Runkle, D. E. (2015). Quantitative Investment Analysis (Vol. Third edition). Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1082450

Recommended Additional Bibliography

  • Principles of corporate finance, Brealey, R. A., 2011