Our intensive modules are designed to boost your skills in specific areas of finance, with modules appropriate for current undergraduate students, prospective MSc students and those already working in industry.
The course combines theoretical and practical blocks, including team working, discussions and cases.
Portfolio Theory and Asset Management
Dr Natasha Todorovic, Senior Lecturer in Investment Management, City, University of London
Practical block (block to choose)
Matlab programming for finance
Dr Dirk Nitzsche, Senior Lecturer in Finance, Course Director for the Quants Masters Programmes, Associate Dean for International Relations, City, University of London
Applied Financial econometrics
Dr Anton Tichomirov, Expert in Financial Markets and risk Management, Associate Professor of SpbPU; Angi Skhvediani, Expert in econometrics, Leading lecturer of SPbPU
For successful mastery of the practical block, students do not need special skills in MatLab programming or Stata modeling.
You’ll also benefit from a social program that includes networking events to meet with fellow summer school students. We’ve designed the teaching schedule to give you the chance to explore this great city, and those nearby, at weekends.
Portfolio Theory and Asset Management (theoretical block)
Outline: This module is designed to introduce you to the key principles of the modern portfolio theory approach to investing and its implications on security selection and asset pricing. This module aims to introduce you to the theoretical background for the application of portfolio selection and asset pricing and accustom them with applying modern portfolio theory for the practice of investment management. Its main objective is to develop a good understanding of investment risk-return characteristics, the benefits of diversification, and the main equilibrium models for asset pricing. It also provides you with the skills required for security selection, portfolio construction and portfolio performance measurement.
Matlab Programming for Finance (elective course from the practical block)
Outline: Being able to perform some basic coding is becoming more and more important in the financial industry where R, Matlab and Python are widely used. Using those (sophisticated) programming languages allows to automate certain processes which helps for the analysis and decision making process and becomes one of those skills more and more analysts should have. Gaining some knowledge in any of those computer languages should allow someone to learn the syntax of other programmes which provides students with the skills to undertake more sophisticated analysis.
This module introduces Matlab programming to students without Matlab knowledge. To make programming more interesting and to demonstrate the relevance to finance, Matlab coding is taught using finance examples in the field of asset management, portfolio theory and valuation. Handling, manipulating and operating on matrices, writing and calling functions/procedures, using loops, conditional statements and optimisations are skills which need to be performed frequently by financial analysts. The finance examples are focusing on valuation (i.e. bond pricing, NPV), portfolio theory (i.e. efficient frontier), style analysis, estimation of factor models and simulations.
Applied Financial econometrics (elective course from the practical block)
Outline:This course provides overview of advanced financial econometrics techniques for analysis and modelling of time series data, such as prices, volatilities and return of the main cryptocurrencies, exchange or interest rates, share prices and etc. During this course we discuss briefly theory and foundations of econometrics and in depth specific modeling techniques of financial econometrics. Students will apply discussed techniques for analysis, modelling and forecasting key characteristics of financial data using STATA software. In addition, special attention will be paid to modelling relationships between several financial series. The knowledge and methods acquired in this course are particularly useful and sought after in the public/government and private/industry financial sectors. This module introduces Stata-modeling to students without Stata knowledge.