Perm State University Master in Finance & Information Technology (MiFIT)

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1 Perm State University Master in Finance & Information Technology (MiFIT) Page 1

2 Introduction Rapid changes in financial landscape demand finance professionals to double-quick develop practical solutions applying theoretical models to the real data. This requires deeper knowledge of modern day finance and most recent information technologies. To meet these demands the Chair of Information Systems and Mathematical Methods in Economics of Perm State University offers an Master in Finance and Information Technology (MiFIT) designed for students who wish to pursue a career in finance / IT. The MiFIT program an exciting learning environment that enables our students to develop systematic understanding of quantitative finance with the professional skills to apply IT within a financial institution. You will gain a command of analytical techniques in the relevant areas and an increased confidence in solving problems. Program is closely linked with PROGNOZ one of the largest IT developers in Russia recently named IT Company of the year 2010 and #1 Russian customized software developer. Master students will have a possibility to be involved in real projects in production. Fruitful research environment is created in the university Risk Lab, providing infrastructure for hi-tech financial engineering and risk management studies. The curriculum consists of three semesters of coursework followed by the writing of a Masters Thesis. The program starts each year (mid September) and interested persons need to apply for a place of study by the end of July. Graduates are well prepared to be employed within IT companies and financial institutions. Page 2

3 Main features Enrollment and costs: Accepted applicants will be enrolled as students at the Faculty of Economics, of the Perm State University. The tuition fee for the program is $1250 per semester (half year). An application fee might be changed. Curriculum summary: This specialized Master program offers its prospective students an advanced education in quantitative finance and information technology. Its Curriculum consists of a combination of mathematical methods in finance (econometrics, data mining, risk management, etc.) and IT courses (information systems, data management, etc.). Target participants and expected prerequisite knowledge: Graduates with (at least) a Bachelor degree (or equivalent) having a finance, economics and/or science background (mathematics, physics, engineering, computer science). Practitioners with a corresponding academic qualification, who feel that they need additional and more specialized training in quantitative finance and IT are mostly welcome. The candidates must exhibit a good knowledge of the English language, good intermediate knowledge of financial sciences as well as probability theory and statistics on a bachelor level. Every candidate who fulfils the requirements of the Admission rules is admitted to join the program. Language: The program is taught in English so that international as well as Russian participants can attend. Duration: The expected period of study is four semesters: 3 semesters of courses followed by the completion of a Master Thesis. The students have to achieve 120 ECTS in order to receive the degree "Master in Finance & Information Technology at Perm State University". Exchange programs: We welcome cooperation and exchange programs with other international universities offering similar programs. Page 3

4 Curriculum The program comprises 13 core courses and 10 elective courses*. Core courses: 1. Advanced macroeconomics 2. Advanced microeconomics 3. Advanced econometrics 4. Games theory 5. Quantitative research methods 6. Financial engineering I: Interest rates modeling 7. Operation research & Optimization 8. Financial markets modeling 9. Risk management 10. Data mining 11. Information systems 12. Data management 13. Advanced calculations in Excel Elective courses: 1. Hedge funds 2. Financial engineering II: Derivatives 3. Banks and banking supervision 4. Global business 5. Innovations & Start-ups 6. Object-oriented programming 7. Math applications 8. E-Commerce 9. Simulation & Copula theory 10. Time Series Analysis Each student needs to acquire at least 120 ECTS points as follows: 49 ECTS credit points from the core courses 12 ECTS credit points from the elective courses 59 ECTS credit points from the Master Thesis, Final exam and research activities. * The courses can be changed. Page 4

5 Core Courses Advanced Econometrics This course provides solid basis for econometrics research and includes foundations of hypothesis testing, regression analysis, misspecification tests, real-life problems solving. Financial engineering I The course Financial Engineering I: Interest Rates Models provides a basic framework for contemporary interest rate modeling and financial contracts pricing. Operation research & Optimization The rigorous, theoretical course on the operation research models and optimization techniques: linear and nonlinear programming, dynamical programming. Financial markets modeling The course is focused on financial market quantitative modeling including fundamental and technical analysis, bubble diagnostics, liquidity and market microstructure models. The course contains overview of current modeling practices and provides competence to design financial models. Risk management Course "Theory of risk and risk management models" involves the study of basic concepts and models for risk assessment with an emphasis on financial risks. The course contains overview of enterprise-wide risk management process and provides the practical approaches to design and analysis of current risk models in financial institutions and corporate sector, as well as regulation of risks, including Basel capital requirements. Data mining This course provides efficient techniques for multi-dimensional data analysis and classification, including factor analysis (principal components method), cluster analysis, Page 5

6 logit/probit regression as well as artificial intelligence methods such as fuzzy logic, neural networks and genetic algorithms. Information systems design Introductory course for information technologies and information systems architecture with emphasis on Business Intelligence and Decision support systems. Data management The course Data management is designed to train how to deal with your data using latterday techniques and strategies of data management, relational data base management systems, MS Excel Pivot tables and professional OLAP-systems. Students are proposed practical examples for all steps of data management from data extraction and loading to analytical processing. Advanced calculations in Excel The course will help to unveil the power of data processing MS Excel using statistics, solver, Visual basic macros and other features for Monte-Carlo simulation, derivatives pricing, Valueat-Risk calculations and other practical tasks. Elective Courses Hedge funds This course reviews cutting edge research on the fast growing hedge fund industry to provide a unified framework encompassing the different hedge fund strategies, performance, data biases, managerial risk-taking incentives, risk measures. Financial Engineering II This elective provides a rigorous conceptual framework for valuing and understanding the behavior of derivative instruments and their use in risk management. Page 6

7 Time Series Analysis An advanced statistical course on the analysis and forecasting of time series data. It covers nonstationarity, mean reversion, autocorrelation, cointegration, VECM and other topics. Banks and banking supervision Elective course on modeling banks and banking operations. Recent trends in Russian and international banking supervision are discussed. Global Business The focus of this course is the global economy and its components including world trade, capital flows, foreign exchange markets, etc. Innovations and Start-ups A case-based course on financing and marketing innovative entrepreneurial businesses and start-ups. Object oriented-programming This practical course gives an overview of modern programming approaches such as Java, C++, etc. You will learn how to fast create your application. Math Applications This elective is focused on study programming in popular mathematical environments such as Matlab and R. e-commerce The course is focused on e-commerce business planning, the information technologies such as Content management system (CMS), Customer relationship management (CRM), as well as marketing 2.0: blogging, social media marketing (SMM), search engine optimization (SEO), etc. The course is 100% practical. It is assumed that upon completion of the course, students will gain practical skills sufficient to run their own projects. Simulation & Copula theory The course is focused on the study of basic methods of Monte-Carlo simulation using copula and Bayesian data analysis, widely implemented in financial engineering to assess portfolio risk and price credit derivatives (CDO, MBS, etc.). The course contains overview of current modeling practices and provides competence to design models. Page 7

8 Teachers MiFIT 2011/2012 teachers: Prof. Dr. Fabrizio Lillo (University of Palermo, Italy / Santa Fe Institute, USA) Dr. Olga Kolokolova (Manchester School of Business, UK) Pankaj Kumar (IGIDR, India) Dr. Victor Laphin (Higher School of Economics, Russia) Dr. Vladimir Maksimov (ISMME) Dr. Bela Myznikova (ISMME) Dr. Vladimir Shishkin (ISMME) Dr. Sergey Ivliev (Prognoz Risk Lab) Dr. Dmitry Shultz (Prognoz) Dr. Konstantin Kuznetsov (Prognoz) And many others. Page 8

9 MiFIT Admissions Calendar 2011 Step Deadline Applications & Interviews June 1 August 5 Documents Submission June 1 August 5 Entrance Exam August 5 Admission Decision August 21 Teambuilding Session September Classes Start September 12 MiFIT Contact Information Sergey Ivliev, MiFIT Program Supervisor Phone: ivliev@prognoz.ru Natalia Frolova, ISMME chair Phone: nvf_psu@mail.ru Ksenia Kolesnikova, MiFIT Coordinator Phone: kolesnikova@prognoz.ru Zinaida Soroka, ISMME chair Phone: soroka@econ.psu.ru Page 9