Finance Corporate Finance Yrityksen rahoitus Code: LASK3047 Credit Units: 6 ETCS Time: Autumn semester, periods I-II. Content: Overview of corporate finance including valuation of stocks and bonds, capital budgeting, cost of capital, long-term financial policy and other topics in corporate finance. These include risk & return, capital budgeting, market efficiency, payout policy, capital structure, real options, risk management and corporate control & governance. Learning outcomes: A student will have a deep understanding and ability to solve comprehensive problems in various areas of corporate finance. Students are expected to learn to analyze a company s capital budgeting questions and long term financial policy needs, as well as other topics in the area of corporate finance. By the end of this course students should be able to connect the concept of present value to all major areas of finance (for example: value, risk & return, payout policy, financial analysis). The course will strengthen theoretical understanding of the subject and enhance the development of decision making and analytical and critical thinking skills. Teaching: Lectures and in-class exercises, problems and cases 44 h and 2 sets of exercises (separate from the lectures). Assessment: Exam and exercises. Literature: 1. Brealey, R. S. Myers F. Allen: Principles of Corporate Finance. McGraw-HilInc., Latest edition. 2. Material provided by the lecturer. Prerequisites: Bachelor-level knowledge of accounting and finance. Contact person: Dr. John Kihn Right to participate: Master s Degree students in Finance, Accounting and Auditing, and Business Law Investments Sijoitustoiminta Code: LASK3018 Credit Units: 8 ECTS Time: 1. year, autumn semester, periods II-III. Content: Financial markets and instruments, investment process and securities trading, asset allocation and diversification, market efficiency and stock returns anomalies, asset pricing models and security analysis, systemic risk and financial crises, term structure of interest rates, portfolio performance evaluation, investment stretagies and applied portfolio management,
Excel applications. Learning outcomes: After this course students are expected to have an in-depth understanding of security analysis, investment strategies and portfolio management. Students will also learn Excel applications within the context of asset allocation and diversification, security and portfolio analysis and asset pricing models. The course provides an opportunity to master the use of financial instruments through the StockTrak simulation assignment. By the end of the course students should also be able to evaluate general macroeconomic environment and apply this analysis within portfolio management framework. In addition, the course provides a general background for understanding the reasons for financial crises, the role of government and central bank on the financial markets and discusses important aspects in business ethics and corporate responsibility. The group assignment of the course will further develop analytical and critical thinking skills, improve decision making and problem solving skills as well as support general communication skills such as written and oral expression, and IT skills. Teaching: Lectures (30 h), exercises (4 h), Excel applications (4 h). Assessment: Exam and group assignment. Literature: 1. Bodie, Z., & Kane, A., & Marcus, A. (2009). Investments, 8th edition or later. 2. Bodie, Z. & Kane, A. & Marcus, A. (2011). Investments and Portfolio Management, Global Edition, 9 th edition. 3. Zimmermann, H., & Drobetz, W., & Oertmann, P., (2003). Global Asset Allocation, Wiley. 4. Selected research papers announced by the lecturers. Prerequisites: Corporate Finance course and bachelor-level knowledge of finance and accounting. Contact person: Assistant Professor Denis Davydov Right to participate: Master s Degree students in Finance Financial Derivatives and Risk Management Optiot, futuurit ja riskienhallinta Code: LASK3011 Credit Units: 8 ECTS Time: Autumn semester, period I. Content: Options and futures markets, option strategies and financial engineering, arbitrage pricing, binomial option pricing model, Black & Scholes model, alternative OPMs, implied volatilities, volatility smiles, management of market risk, empirical research. SAS and Excel VBA will be used for implementation of the methods discussed. Learning outcomes: By the end of this course students should be able to know different types of derivatives, derivative strategies, pricing of derivatives, and derivatives in risk management. Moreover, students should be acquainted with using the market prices of options to infer information (option implied information) and with essential calculation tools related to derivatives. SAS and Excel VBA is used for implementation of the methods discussed. The
program examples, reading assignments, in-class exercises and Stock Trak assignments will develop students skills of decision making and problem solving, and analytical and critical thinking and IT skills. Upon completion of the course a student will have developed the skills necessary to understand financial derivatives and derivatives markets and basics of the valuation of derivatives, run basic estimations related to derivatives, indentify problems in implementation of theoretical models and search individually solutions to possible problem, and deepen knowledge on derivatives and risk management individually by searching relevant scientific research articles. Teaching: Lectures, in-class group exercises, Stock Trak assignments 32 h. Assessment: Written examination, Stock Trak assignments Literature: Hull, John C.: Options, futures, and other derivatives, 7 th or later edition. Material provided by the lecturer. Prerequisites: Knowledge of the fundamentals of financial markets and principles of financial derivatives (e.g. Financial Derivatives). Contact person: Prof. Jussi Nikkinen Right to participate: Master s Degree students in Finance European Financial Markets Euroopan rahoitusmarkkinat Code: LASK3002 Credit Units: 5 ECTS Time: Spring semester, period III. Content: Introduction to financial markets, global financial crisis and the eurozone sovereign debt crisis, banking and financial regulation, terms structure of interest rates, European Central Bank and monetary policy. The course will also include topics related to emerging financial markets in Europe (introduction to emerging markets finance, financial integration, diversification with emerging markets, co-movement between emerging and developed European financial markets). Learning outcomes: By the end of this course students should be able to understand the factors causing the financial crisis and dynamics of the financial crisis in developed and emerging markets, know the functions of the European Central Bank, s understand monetary policy instruments and possess an insight into euro area monetary policy, understand the link between Euro interest and foreign exchange rates, understand the role of banking in the European financial mechanism, understand the concepts and current issues in banking regulation, and have a good understanding of the main topics in the area of emerging financial markets. The course will also support the development of students generic skills such as communication skills (written expression and oral expression), and analytical and critical thinking skills. Teaching: Lectures and group presentations 30 h. Assessment: Exam and written assignment. Literature: 1. Mishkin, F. S., Matthews, K. & Giuliodori, M. (2013). The Economics of Money,
Banking & Financial Markets. European edition. 2. Selected research papers announced by the lecturers. Prerequisites: A Bachelor s degree. Students should have basic knowledge in the main concepts of financial theory, such as interest rates, risk and return, discounting, and foreign exchange rates, and be familiar with the concept of capital markets Contact person: Dr. Vanja Piljak Right to participate: Master s Degree students in Finance and Economics Econometrics I Code: STAT2020 Credits: 5 ECTS Timing: fall 2015 Prerequisites: Elementary statistics and probability (Wooldridge, Appendix B), covering basic concepts of statistical inference (estimation and hypothesis testing, Wooldridge, Appendix C). Basic mathematics (Wooldridge, Appendix A) including, differentiation, integration, solving elementary differential equations, elasticity concept, and continuously compounded interest rate calculus. Working knowledge of basic matrix algebra (Wooldridge, Appendix D) is a benefit but not a prerequisite. Appendices of the Wooldridge s books are available in pdf-format at http://academic.cengage.com/resource_uploads/downloads/1408093758_415141.pdf Learning Outcomes: The student knows basics of empirical econometric research methods and approaches including types of econometric data, roles of variables, economic and econometric modeling, estimation, statistical inference, interpretation of estimation results, model checking and model evaluation, use of econometric models in practice. The course will develop students generic skills including basics of statistical modeling, communication of estimation results in economic terms, extracting relevant information from statistical software listings, and critical evaluation of empirical results. Content: Nature of econometrics and econometric data, simple regression model, multiple regression analysis, regression with qualitative information, heteroscedasticity, time series regression. Introduction to modern (econometric) software packages. Study Materials: Wooldridge, Jeffrey, M (2006), Introductory Econometrics-A Modern Approach, 3e, Thompson, South-West, chapters 1-12, Software: SAS, EViews, r. Teaching Methods: lectures 40 h, exercises 12 h, home page: http://lipas.uwasa.fi/~sip/teaching/ecm/lectures/index.html Modes of Study: exam Languages: English Grading: 1-5/fail Responsible Person: Seppo Pynnönen (www.uwasa.fi/~sip/) Teacher(s): Responsible Unit: Department of Mathematics and Statistics Additional Information: -
Econometrics II Code: STAT3090 Credits: 6 ECTS for PhD students (in particular economics) the course is possible to extend to 7 ECTS (7 op) with additional reading package described below Timing: spring (january-february) Prerequisites: basic Econometrics (STAT2020) and Mathematic Analysis (ORMS1010) recommended (including working knowledge in differentiation, integration, solving elementary differential equations, elasticity concept and continuously compounded interest rate calculus, and matrix algebra) Learning Outcomes: The student gains skills to use modern econometric tools applied in empirical finance and economics, the topics cover econometric applications in empirical asset pricing and analysis of financial time series including risk measurement, panel data econometrics and introduction to multivariate time series analysis (impulse responses, cointegration), the emphasis is in empirical modeling and interpretation of the results with real data examples. As generic skills the student learns to interpret empirical estimation results and the potential of solving complicated estimation and modeling problems with modern software such as R, SAS, Stata, or EViews.Content: financial and economic data, panel data models, financial econometrics (multivariate) time series models Study materials: (1) Wooldridge, Introductory Econometrics: A Modern Approach, Ch 13&14; (2) Enders, Applied Economic Time Series, Ch 5, Sec 5-9. Teaching Methods: lectures 42 h, demonstration 12 h (classes and notes in English) home page http://lipas.uwasa.fi/~sjp/teaching/ecmii/lectures/index.html) Modes of Study: exam Languages: English Grading: 1-5 or fail Responsible Person: Professor Seppo Pynnönen (www.uwasa.fi/~sjp/) Teacher(s): Seppo Pynnönen Responsible Unit: Department of Mathematics and Statistics Additional Information: course can be included to the minor in statistics/business mathematics Financial Time Series Analysis Code: STAT3100 Credits: 8 ECTS Timing: spring Prerequisites: Econometrics I Learning Outcomes: introduce the students to the latest in univariate time series methods and econometrics for analyzing quantitative financial information Content: the course covers both basic and advanced concepts of modern linear as well as nonlinear financial time series modeling, the focus is on the predictability of asset returns,
event study approaches, equilibrium models, modelling fixed income securities and termstructure models and microstructure issues Study materials: 1. MILLS, T. and R. Markellos (2008): The Econometric Modelling of Financial Time Series, Third Edition, Cambridge University Press 2. ALEXANDER, C(2008) Practical Financial Econometrics, Wiley 3. TAYLOR, S.J. (2005), Asset Price Dynamics, Volatility and Prediction, Princeton University Press, New York 4. additional reading package Teaching Methods: 42 h lectures Modes of Study: written examination + term paper (research proposal for Ph.D. students) Languages: English Grading: scale 1-5 or fail Responsible Person: Seppo Pynnönen and Johan Knif (Hanken) Teacher(s): Seppo Pynnönen Responsible Unit: Department of Mathematics and Statistics Additional Information: joint course with Hanken Vaasa course is arranged every second year, next time spring 2017