Delivered at:: HSE Banking Institute

Course type:: Compulsory course

When:: 1 year, 1, 2 module

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

The course aims to provide students the quantitative skills, which are value to financial analysts in both an academic and vocational setting. In particular the course has the following 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

understand and apply the probability tools needed to frame and address many real-world problems involving risk;
understand probability distributions and perform their investment uses;
understand the framework of hypothesis testing and make judgements about the population in the basis of a sample analysis.
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
apply sampling and use sample information to estimate the population parameters

Course Contents

Week 1-2, Chapter 1
Week 3, Chapter 2
Week 4-5, Chapter 3: Probability concepts, portfolio expected return and variance of return
Week 6, Chapter 4: Common probability distributions
Week 7, Chapter 5: Sampling and estimation
Week 8, Chapter 6: Hypothesis testing

Assessment Elements

Graded week tests
Training Project
Training project is held at the end of week 3
Final Project
Final project is held at Week 9

Interim Assessment

2024/2025 2nd module
0.23 * Final Project + 0.72 * Graded week tests + 0.05 * Training Project

Bibliography

Recommended Core Bibliography

Frank J. Fabozzi, Sergio M. Focardi, & Petter N. Kolm. (2010). Quantitative Equity Investing : Techniques and Strategies. Wiley.
Richard A. DeFusco, Dennis W. McLeavey, Jerald E. Pinto, & David E. Runkle. (2007). Quantitative Investment Analysis: Vol. 2nd ed. Wiley.

Recommended Additional Bibliography

Richard Brealey, Stewart Myers, & Franklin Allen. (2020). ISE EBook Online Access for Principles of Corporate Finance: Vol. Thirteenth edition. McGraw-Hill Education.

Authors

Кузюкова Юлия Игоревна
ODINTSOVA ULYANA ALEKSANDROVNA
SHELIKE AYANA GEORGIEVNA
ELIZAROVA IRINA NIKOLAEVNA

Master of Finance

Quantitative Methods in Finance

Course Syllabus