July 12 – 23, 2021
Сombining financial econometrics and risk management, this course is meant to empower students with quantitative approaches and techniques to analyse investment and financial decisions.
Financial market generates vast amounts of data that can be informative for analysing decisions, forecasting crisis development, and evaluating risks. Covering a wide variety of topics in empirical corporate finance, such as asset pricing, portfolio analysis, volatility models, time series models, risk mature models, and others, the course will teach students how to apply quantitative methods to address practical financial applications and transform data into decision-relevant information. Students will also get the experience of using R and SPSS to build empirical models.
The course is taught by Vasilisa Makarova, Associate Professor, St. Petersburg School of Economics and Management, Department of Finance; Supervisor of the minor 'Personal and Behaviour Finance', Victor Krakovich, Senior Lecturer, St. Petersburg School of Economics and Management, Department of Finance, and Carlos Joaquin Rincon, MSc in Finance, HSE University; MSc. in Economics, Universidad de los Andes.
This course might be helpful to those who want to understand the logic of decision-making in finance. Predicting profitability and risks has become quite a challenge against the background of the pandemic, which does not allow forecasting a sustainable long-term result. In my section, we will focus on the sustainability of investment income, risk assessment, and investment asset classification.
In my part of the course, we will focus on risk management through optimal portfolio diversification with hedging strategies. We will apply techniques to determine optimal portfolios with a wide range of real-world assets, given the levels of risks in the global economy. We will also apply simple hedge strategies with option valuation models to ensure better protection of these portfolios
Why Choose This Course?
This course should be particularly useful for those students who are pursuing a career in business, finance, or financial economics, as well as those who are working on empirical research in the field of corporate finance.
- Parametric and nonparametric volatility measurement
- Mean-variance theory and portfolio optimization
- MVT alternatives (full scale, Black-litterman, Simplex method, Huang and Litzenberg)
- Binary probability models
- ARIMA-ARCH class models
- Other topics: on demand
Skills and Competences
Upon completing this course, students will acquire knowledge in the following topics:
- Pricing and analysing financial Instruments, including derivatives
- Analysing yield curves
- Portfolio analysis
- Estimating efficient portfolios and frontiers
- Modelling and predicting prices of financial assets
- Preparing and interpreting corporate financial information
Applicants should be familiar with financial math, time value of money, probability models, etc. The course is primarily aimed at senior bachelor's students, master's students, and young professionals.
The course includes lectures and seminars.
Individual project work which includes case study, problem solving, financial modeling, developing a presentation.
Final Grade Background
Students will be given four tasks (case study, problem solving, financial modeling, presentation). The final grade will be computed according to performance of each of the tasks. In order to complete the course students have to attend no less than 70% of classes.
Recommended Reading List
Fabozzi F.J., Markowitz H.M. (Eds.) The Theory and Practice of Investment Management- Asset Allocation, Valuation, Portfolio Construction, and Strategies