Econometrics and Operations Research (MSc) Vrije Universiteit Amsterdam - Fac. der Economische Wet. en Bedrijfsk. - M Econometrics and Operations

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1 Econometrics and Operations Research (MSc) Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Vrije Universiteit Amsterdam - - M Econometrics and Operations Research I

2 The Master's programme in Econometrics and Operations Research is an academic programme focusing on the development and application of quantitative methods for analysing economic issues in a broad sense. It is a successful preparation for a professional career in which mathematics, statistics and ICT are used in analysing and solving complex issues in general economics, and business and financial economics. Econometrists are also employed as experts in optimizing strategic and operational business processes like transport flows, stock management and operating systems. Econometrists can be found working at the central banks of Europe, at federal banks in the United States, at central government agencies and ministries, financial institutions, consultancy firms and in the majority of listed companies. The components of the Master's programme correspond closely with the department's research interests, which means that many of the latest scientific developments in areas like financial econometrics, logistics and game theory find their way directly into the teaching programme. Students also benefit from having the opportunity to study in small groups and work closely with the academic staff. Vrije Universiteit Amsterdam - - M Econometrics and Operations Research II

3 Inhoudsopgave M Econometrics - Ectrie and Math Ec 1 M Econometrics - No specialisation 2 M Econometrics - OR and Bus Ectr 3 Vak: Advanced Corporate Finance 3 Vak: Advanced Econometrics 4 Vak: Advanced Macroeconomics 6 Vak: Advanced Marketing Research 7 Vak: Asset Pricing 8 Vak: Asymptotic Statistics 10 Vak: Business Marketing 10 Vak: Caput Operation Research 11 Vak: Case Study 12 Vak: Combinatorial Optimization 13 Vak: Consumer Marketing 14 Vak: Corporate Finance 15 Vak: Data Mining Techniques 16 Vak: Derivatives and Asset Management 17 Vak: Distribution Logistics and Supply Chain Management 19 Vak: Empirical Finance and Security Analysis 20 Vak: Environmental Economics 21 Vak: Evolutionary Computing 22 Vak: Financial Markets and Institutions 23 Vak: Firm Behavior and Market Structures 25 Vak: Globalization, Growth and Development 26 Vak: Grondslagen waarschijnlijkheidsrekening 27 Vak: Instit Investments & ALM Vak: Investments 28 Vak: Labour Economics 29 Vak: Mathematical System Theory 31 Vak: Neurale Netwerken 32 Vak: Pension and Insurance Management 32 Vak: Regional and Urban Economics 33 Vak: Simulation and Stochastic Systems 34 Vak: Stochastic Optimization 35 Vak: Stochastic Processes for Finance 35 Vak: Strategic and Cooperative Decision Making 36 Vak: Thesis 37 Vak: Time Series Econometrics 37 Vak: Transport Economics 38 Vrije Universiteit Amsterdam - - M Econometrics and Operations Research III

4 M Econometrics - Ectrie and Math Ec Vakken: Naam Periode Credits Code Advanced Corporate Finance 6.0 E_FIN_ACF Advanced Econometrics Period 1, Period E_EORM_AECTR Advanced Macroeconomics Period E_EC_AMAEC Advanced Marketing Research Period E_MKT_AMR Asset Pricing 6.0 E_FIN_AP Asymptotic Statistics Semester X_ Business Marketing Period E_MKT_BM Caput Operation Research 6.0 E_EORM_COR Case Study Period E_EORM_CASE Combinatorial Optimization Period E_EORM_CO Consumer Marketing Period E_MKT_CM Corporate Finance Period E_FIN_CF Data Mining Techniques Period X_ Derivatives and Asset Management Empirical Finance and Security Analysis Period E_FIN_DAM Period E_FIN_EFSA Environmental Economics Period E_STR_EEC Financial Markets and Institutions Firm Behavior and Market Structures Globalization, Growth and Development Grondslagen waarschijnlijkheidsrekening Period E_FIN_FMI Period E_EC_FBMS Period E_EC_GGD Periode X_ Investments Period E_FIN_INV Labour Economics Period E_EC_LABEC Mathematical System Theory Regional and Urban Economics Simulation and Stochastic Systems Stochastic Processes for Finance Strategic and Cooperative Decision Making Period X_ Period E_STR_RUE Period E_EORM_SSS Periode X_ Period E_EORM_SCDM Thesis Periode 5, Periode E_EORM_THS Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 1 van 39

5 Time Series Econometrics Period E_EORM_TSE M Econometrics - No specialisation Vakken: Naam Periode Credits Code Advanced Corporate Finance 6.0 E_FIN_ACF Advanced Econometrics Period 1, Period E_EORM_AECTR Advanced Macroeconomics Period E_EC_AMAEC Advanced Marketing Research Period E_MKT_AMR Asset Pricing 6.0 E_FIN_AP Asymptotic Statistics Semester X_ Business Marketing Period E_MKT_BM Caput Operation Research 6.0 E_EORM_COR Case Study Period E_EORM_CASE Combinatorial Optimization Period E_EORM_CO Consumer Marketing Period E_MKT_CM Corporate Finance Period E_FIN_CF Data Mining Techniques Period X_ Derivatives and Asset Management Distribution Logistics and Supply Chain Management Empirical Finance and Security Analysis Period E_FIN_DAM Period E_BA_DLSCM Period E_FIN_EFSA Environmental Economics Period E_STR_EEC Evolutionary Computing Period X_ Financial Markets and Institutions Firm Behavior and Market Structures Globalization, Growth and Development Grondslagen waarschijnlijkheidsrekening Period E_FIN_FMI Period E_EC_FBMS Period E_EC_GGD Periode X_ Investments Period E_FIN_INV Labour Economics Period E_EC_LABEC Mathematical System Theory Period X_ Neurale Netwerken Periode X_ Pension and Insurance Management Regional and Urban Economics Period E_FIN_PIM Period E_STR_RUE Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 2 van 39

6 Simulation and Stochastic Systems M Econometrics - OR and Bus Ectr Period E_EORM_SSS Stochastic Optimization Period X_ Stochastic Processes for Finance Strategic and Cooperative Decision Making Periode X_ Period E_EORM_SCDM Time Series Econometrics Period E_EORM_TSE Transport Economics Period E_STR_TREC Vakken: Naam Periode Credits Code Advanced Econometrics Period 1, Period E_EORM_AECTR Asset Pricing 6.0 E_FIN_AP Caput Operation Research 6.0 E_EORM_COR Case Study Period E_EORM_CASE Combinatorial Optimization Period E_EORM_CO Data Mining Techniques Period X_ Derivatives and Asset Management Distribution Logistics and Supply Chain Management Advanced Corporate Finance Period E_FIN_DAM Period E_BA_DLSCM Environmental Economics Period E_STR_EEC Evolutionary Computing Period X_ Grondslagen waarschijnlijkheidsrekening Instit Investments & ALM 4.2 Periode X_ E_FIN_IIALM Investments Period E_FIN_INV Neurale Netwerken Periode X_ Pension and Insurance Management Simulation and Stochastic Systems Period E_FIN_PIM Period E_EORM_SSS Stochastic Optimization Period X_ Strategic and Cooperative Decision Making Period E_EORM_SCDM Thesis Periode 5, Periode E_EORM_THS Time Series Econometrics Period E_EORM_TSE Transport Economics Period E_STR_TREC Course code E_FIN_ACF () Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 3 van 39

7 prof. dr. ir. H.A. Rijken Achieve advanced knowledge in the theory and practice of corporate finance. The main objective is to fully understand theoretical concepts (their strengths and limitations) and to use these theoretical frameworks to solve in an effective way practical issues in corporate finance. After following this course, you: - understand basic Corporate Finance concepts, including their strengths and limitations - have the quantitative skills to apply these basic concepts - understand the interrelationship between various concepts and link them in a general framework - are able to apply this framework in real life cases This course elaborates on the course corporate finance in the bachelors program. The course has two focus areas: Corporate Security Design and Corporate (Financial) Risk Management We will start off with a short review of the theory of Modigliani and Miller. Within the framework of these concepts we will pay attention to the issues on capital structure from the perspective of both the equity holders and the debt holders. A range of corporate financing options, like subordinated bond, convertibles and corporate securitization, will be discussed. Thereafter we introduce comprehensively the concepts of the operational cash flow and the finance cash flow of a company. The added value of Corporate (Financial) Risk Management will be discussed from a cash flow perspective and a capital cost perspective. Links with Short Term Financial Management, Credit Risk Management and Value Based Management will be made. Substantial attention will be given to real life cases (agency questions and restructuring cases in practice) during the course. Lectures (2 times 2 hours per week) and working class written exam (70%) and two cases (30%) Entry requirements Corporate Finance 3.2 Advanced Econometrics Course code E_EORM_AECTR ( ) Period Period 1, Period 2 Credits 3.0 Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 4 van 39

8 dr. M. Ooms prof. dr. S.J. Koopman Lecture, Study Group To gain a profound and detailed understanding of advanced econometric theory and methods. By the end of this course, participants will: have detailed knowledge of - principles of econometric theory and practical methods at the graduate level - advanced statistical concepts used in econometric theory and their application in econometric modelling know how to - estimate and test both cross-section and time-series models - evaluate econometric procedures by means of simulation experiments - solve theoretical econometric exercises understand - the interplay between econometric techniques and modelling assumptions - the proofs of asymptotic properties of important estimators and test statistics have gained experience in - solving an econometric research questions as part of a group - presenting the solution to the class - discussing other groups' presentations Advanced Econometrics I The three main topics of this course are: - Nonlinear regression and generalised least squares, - Instrumental variable estimation, - Generalized methods of moments. This course recaps and extends undergraduate knowledge of econometric theory and methods at the graduate level, focussing on a number of selected methods and models. Estimators for both linear and non-linear models will be examined, including least-squares, and generalized methods of moments.. Point estimation as well as confidence interval estimation will be considered. For different estimators and test statistics the question is addressed of how exact, bootstrap or asymptotic inference can be conducted. Note: the econometrics programme is currently under revision. Some topics may change. Please consult the latest version of the online study guide. Advanced Econometrics II The three main topics in Advanced Econometrics II are maximum likelihood estimation, multivariate regression analysis and multivariate time Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 5 van 39

9 series analysis. The course recaps and extends undergraduate knowledge of econometric theory and methods at the graduate level, focussing on a number of selected methods and models. Estimators for both linear and non-linear models will be examined. Testing procedures that will take centre stage include Lagrange multiplier test as well as conditional moment tests. For all estimators and test statistics the question is addressed of how exact, bootstrap or asymptotic inference can be conducted. Note: the econometrics programme is currently under revision. Some topics may change. Please consult the latest version of the online study guide. lecture and tutorial Some lectures can be used for students to give presentations on selected topics. Written examination. There are two separate written exams for Advanced Econometrics I (period 1) and for Advanced Econometriecs II (period 2). Minimum required result for Advanced Econometrics I is 5.5 and for Advanced Econometrics II is 5.0. Total grade for the combined 6 ECTS version is the average of the two grades and must be at least 5.5 for a pass. The two partial grades are measured in one decimal point; the total grade is the rounded average of the two grades. Starting September 2010, the first part can be taken as a single elective course for 3 ECTS. Note: the econometrics programme is under revision. The examination format may change slightly. Please consult the latest version of the online study guide. Advanced Econometrics I and II: Davidson, R & J G. MacKinnon, Econometric Theory and Methods. OUP 2004, (compulsory). Advanced Econometrics II: Tsay, R., Analysis of Financial Time Series, John Wiley and Sons, 2005, Chapter 8 (parts). Other references: - Ruud, P A., An Introduction to Classical Econometric Theory. OUP, Hansen, B E, Econometrics. Manuscript, University of Wisconsin Current URL: Advanced Macroeconomics Course code E_EC_AMAEC ( ) Period Period 2 Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 6 van 39

10 prof. dr. E.J. Bartelsman prof. dr. E.J. Bartelsman Lecture The students will be able to actively read current literature and embark on their own research projects using the knowledge gained about the analytical, mathematical, and statistical tools of modern macroeconomics. The tools include dynamic optimization, signal extraction, Nash bargaining, and the basic building blocks of DSGE models. This course provides coverage at an advanced level of the building blocks of macro economics. Models of economic growth will be built up from inter- temporal optimisation decisions of firms and households. The basic model will be extended to take into account the effects on growth of investment in knowledge (R& D, education). Next, the course will present the tools of Real Business Cycle analysis and recent applications. Finally, the course will present the current state of work in New Keynesian economics and its implications for cyclical fluctuations, the functioning of the labor market and the conduct of monetary policy. lecture written interim examination plus problem sets. Romer, David Advanced Macro Economics. 3rd edition, McGraw Hill. Advanced Marketing Research Course code E_MKT_AMR ( ) Period Period 1 dr. L.J. Paas dr. L.J. Paas Lecture, Study Group - Obtain rigorous knowledge of the most important multivariate dataanalysis techniques used in marketing research - Applying multivariate data analysis techniques in SPSS and to interpreting the output Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 7 van 39

11 - Develop the ability to select the correct data analysis technique for a substantive problem and gain knowledge of important marketing applications Sound knowledge of marketing research and data analysis techniques is necessary for marketers working in either practice or academics. This course offers students thorough insight in the most important data analysis techniques. It also teaches them how to pursue the analyses in the statistical software package SPSS. Thereby, the course forms a preparation for the empirical research to be conducted for the Master's thesis. During the lectures at least the following techniques will be discussed: Factor analysis, scale construction, linear regression analysis, conjoint analysis, logistic regression, MANOVA, Multidimensional scaling, correspondence analysis and cluster analysis. The discussions concentrate on application of the techniques instead of technical details. Various practical marketing research examples will illustrate this application. During the tutorials, students will exercise the application of the techniques in SPSS and the interpretation of output, based on real- life data sets. lecture tutorial Lectures and tutorial. written interim examination 70 percent SPSS exam 30 percent Each to be completed with a minimum score of Hair Jr., Black, Babi &, Anderson, Multivariate Data Analysis. 7th edition. McGraw Hill, Pearson / Prentice Hall, Entry requirements Knowledge of SPSS and basic statistics Asset Pricing Course code E_FIN_AP () dr. F. Brevik This course aims to deepen your knowledge in the field of asset pricing and asset allocation. After completion of the course, you should: - Have a thorough understanding of how security prices are determined in financial markets, including equity and fixed income. - Understand and be able to apply optimal asset allocations for both Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 8 van 39

12 individual and institutional investors. - Acquire an academic and critical attitude towards competing technique in investment problems. - Be comfortable with doing advanced analyses in Software such as Microsoft Excel. Starting from basic (undergraduate) Investments knowledge, this course centers around the issues of asset pricing and asset allocation. In the first week we revisit the well known mean-variance framework and derive the standard CAPM in this set-up. In the second week we explore empirical deviations from the CAPM and discuss how these can be exploited. Here we also touch upon some issues related to behavioral finance. In the third week we study dynamic optimization. Dynamic programming is introduced by the example of pricing American options. We then use the same technique to solve for the optimal dynamic asset-allocation policy when investment opportunities are constant. In the forth week, we study variations in expected returns and link these to fundamental ratios. In the fifth week we explore how investors should exploit variations in expected returns and introduce the I-CAPM. Consumption based asset pricing is covered in the last week. Each of the 6 weeks of the course feature 4 hours of formal lectures and 2 hours of recitations. During recitations we will go through exercises to the topics covered in that week. The exercises are at the end of the relevant chapter of the lecture notes. Draft solutions will be posted on Blackboard after the recitations. In addition there are 3 group work assignments. The focus of these assignments is to apply the theoretical knowledge from class to real world problems using Excel or other software. In addition to gaining a deeper understanding of the topics in the course, the assignments will train you in quantitative computer skills you will need later in their career and prepare you for similar assignments in other courses and your thesis. For each assignment, you work in groups of three students. Assignments will be due at the end of the weeks 1, 3, and 5 of the term. To pass this course, you need a minimum final grade of 6.0 and a minimum grade on the written exam of 5.0. If you score less than 5.0 on the written exam, your final grade is equal to that grade. If you score 5.0 or higher, the final grade is given by: Final grade = 0.7*(Written exam grade) + 0.3*(Average assignment grade) - Lecture notes. - Selected research articles and news clippings. - [For background reading] Boadie, Kane, Markus: Investments (2008; MacGraw-Hill) Entry requirements You should be familiar with investments at the level of Bodie, Kane & Marcus, Investments. Undergraduate level knowledge of statistics and mathematics is also required (e.g., Berenson, Levine, Krehbiel: Basic Business Statistics; and Sydsaeter and Hammond (2006; Prentice Hall): Essential Mathematics for Economic Analysis, Sydsaeter, Hammond, Seierstad, and Strom (2005; Prentice Hall): Further mathematics for Economic Analysis (chapters 4 and 11)). Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 9 van 39

13 Recommended background knowledge You are expected to be very versatile in a relevant software package, such as Microsoft Excel (or any other similarly advance package) and use it to perform estimation and optimization. Core texts here are Benninga, Financial Modeling, or (more advanced) Jackson and Staunton, Advanced modeling in Finance using excel and VBA. Please note that the department will offer an advanced Excel course for Finance from August 29-September 2. Unless you already know how to perform optimizations and estimation in Excel and program VBA you should take this course. Remarks This course may have an in-depth empirical follow-up by choosing an appropriate Investments team-research-project during the January / February period. Asymptotic Statistics Vakcode X_ (400323) Periode Semester 1 Credits 8.0 Voertaal Engels Faculteit Faculteit der Exacte Wetenschappen Coördinator prof. dr. G.J.B. van den Berg Inhoud vak This course is part of the joint national master programme in mathematics. For schedules, course locations and course descriptions see Registration required via Business Marketing Course code E_MKT_BM ( ) Period Period 2 dr. E.A. Mooi dr. E.A. Mooi Lecture, Study Group Acquire knowledge of, and insight into, theories used in the field of business- to- business marketing. This course is targeted at the issues, challenges, and trends that organizations face when operating in business markets. This course provides insight into structural and process issues by which organizations cooperate or compete with other organizations and Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 10 van 39

14 discusses the theoretical and managerial implications of such behavior for marketing. Furthermore, some consideration will be given to intraorganizational issues. Specifically, the learning objectives involve the attainment of understanding of the concepts and theories used in business marketing through a selection of articles published in renowned academic journals. In addition, the course focus is on competence, e. g., the ability to effectively use and apply these concepts. The course will focus exclusively on business markets, and will address a wide variety of topics such as business relationships, outsourcing, branding, channels, negotiation, sales, and pricing. In addition, the course will introduce a number of recent developments in business marketing. Active participation of the students during discussions is required. Lectures and tutorials. written interim examination A set of articles published in top marketing journals, such as the Journal of Marketing. In addition, a few practically oriented papers, taken from journals such as Harvard Business review are included. All content will be made available on Blackboard. Entry requirements Students should have basic knowledge of marketing, including: - Bachelor Economie en bedrijfseconomie: Marketing Bachelor Bedrijfswetenschappen: Services Marketing - Pre- Master students: Marketing (and Thesis) Remarks The examination format is to be decided. Caput Operation Research Course code E_EORM_COR () dr. ir. R.A. Sitters In this course we will learn how to develop efficient algorithms for solving fundamental optimization problems with applications in routing, network design and scheduling. The objectives of the course are: - get to know models to capture different types of optimization problems (offline, online, distributed) - learn basic and advanced techniques to solve such optimization problems (primal-dual schema, randomized rounding, iterative rounding, potential functions, local search, etc.) - use these techniques to design efficient algorithms Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 11 van 39

15 - study the computational complexity of optimization problems Topics that will (probably) be covered in the course are: - Steiner network, facility location, scheduling problems, network routing, congestion games, network design - online algorithms, randomized algorithms, approximation algorithms, local search algorithms - computational complexity and hardness of approximation Lectures and tutorials; take-home assignments will be discussed biweekly written exam The material to be covered in class is based on the following books: - J. Kleinberg and E. Tardos, Algorithm Design, Addison-Wesley, N. Nisan, T. Roughgarden, E. Tardos, and V. V. Vazirani (Editors), Algorithmic Game Theory, Cambridge University Press, C. H. Papadimitriou and K. Steiglitz, Combinatorial Optimization; Algorithms and Complexity, Prentice-Hall, V. V. Vazirani, Approximation Algorithms, Springer, 1998 Entry requirements none Recommended background knowledge basic knowledge on algorithms, computational complexity and combinatorial optimization is advantageous (see, e.g., material covered in the bachelor course Combinatorial Optimization) Case Study Course code E_EORM_CASE ( ) Period Period 3 prof. dr. S.J. Koopman Practicing methods of econometrics and operational research using reallife case studies. Students can opt for three variants of this course: - Financial Econometrics, period 3, Koopman: This part focuses on the measurement and modelling of volatility in time series of financial returns. An introduction will be given of generalised autoregressive conditional heteroskedasticity (GARCH) models for the forecasting of volatility in daily (or lower frequency) financial returns. The Stochastic Volatility (SV) model is considered as an alternative approach that is more closely related to financial theory for option Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 12 van 39

16 pricing. The merits of both models will be investigated empirically using up-to-date financial time series. The final aim is to use the models for forecasting volatility and pricing options and other financial derivatives. Case-work is done in small groups and when a sufficiently large number of groups can be formed, a volatility forecast competition will be part of the course. - Applied Optimization, period 3, Gromicho: Participants who chose this variant will be trained in the design and implementation of advanced optimization algorithms which make use of proven optimization technology such as (integer) linear programming solvers. Examples include the generation of valid inequalities to strengthen formulations and lead to sophisticated branch and cut algorithms. After explaining how to implement such techniques in MatLab the participants will be asked to form small groups and focus on a specific hard problem with known benchmark instances and design and implement an exact algorithm for it. Their findings lead to a written essay. - Allocation Problems, period 3, Van der Laan: In this variant participants will be trained in solving real-life problems allocating costs or benefits of joint projects. The training concerns the formulation of the problem in a manageable quantitative model, to evaluate the theoretical properties of available solutions and their computational complexity, to select appropriate and computational tractable solutions, to develop a software tool for solving the problem, to carry out the required calculations and to report the results in an essay. Participants work on a real-life case in small groups of 2 or 3 students. Standard lectures will guide the student through the computational aspects of statistical estimation, simulation and optimisation methods. To gain further insights in the practical detail, computer programs for the implementation of some computer-intensive methods will be developed. lecture working group essay Selection of articles and papers Combinatorial Optimization Course code E_EORM_CO ( ) Period Period 1 prof. dr. L. Stougie prof. dr. L. Stougie Lecture Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 13 van 39

17 This course is an introduction into combinatorial optimization. It is algorithmically oriented. Theoretical correctness and running time analysis of algorithms is one of the main items of the course. The basis of computational complexity is studied in order to distinguish between well-solved and hard combinatorial optimisation problems. Efficient solution methods for well-solved problems and approximation methods for hard problems are studied. In the latter case, performance guarantees are derived. Goals for the students to achieve: - To acquire the skills for proving basic theorems in graph theory and combinatorial optimisation. - Be able to distinguish theoretically between easy and hard problems and prove some easy NP-hardness. - Learning a wide variety of combinatorial optimization models. - Learn efficient algorithms for general well-solved problems - Learn approximation techniques for computationally hard problems Combinatorial Optimization deals with situations where the best alternative has to be selected from a finite set. This may seem trivial. However, the number of elements may be huge, and it may be far from easy to find the best or even a good solution. A rich class of Combinatorial Optimisation problems comes from Graph and Network Optimisation. The course starts therefore with a quick introduction into graph theory. We start with studying Matching and Flow problems, proving properties that help to develop the algorithms with which to solve these problems efficiently. Specifically we determine the running time of the algorithms. We cover Combinatorial Optimization models, such as the Travelling Salesman Problem, Steiner Trees, Set Covering, etc., which are important for many practical problems related to transportation, telecommunication, production and activity planning. Then we study the foundations of the computational complexity theory to find out that not all combinatorial optimisation problems are efficiently solvable. Next to this insight, we use it to present a wide variety of Combintorial Optimisation problems. Approximation algorithms for computationally hard problems are the subject of the last part of the course. The design and performance analysis of such algorithms are central themes. As an example we study a general technique using ILP, LP-relaxations and rounding. written examination at the end of the course Papadimitriou, H. Christos & Steiglitz, Combinatorial Optimization (Algorithms And Complexity). Kenneth Dover Publications, 1999, ISBN paperback. Entry requirements Bedrijfseconometrie I, period 3.1 Consumer Marketing Course code E_MKT_CM ( ) Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 14 van 39

18 Period Period 2 dr. C.S. Noordhoff dr. C.S. Noordhoff Lecture, Study Group - Acquire knowledge of and insight into concepts and topics that are important to effective consumer marketing management (e. g., customer response to innovation, channel choice, co- creation, consumer decision making processes, and social influences). - Being able to analyze current and potential applications of consumer behavior and consumer psychology theories for developing marketing strategies. In the business world, the importance of what is known as 'customer focus' cannot be overstated. It is widely recognized as a key to success in the marketplace. This course provides insight into how consumers behave and discusses the theoretical and managerial implications of such behavior for firms. Specifically, the learning objectives involve the attainment of understanding of the concepts and theories of consumer marketing through selected articles. In addition, the course focuses on competence development, i. e., the ability to effectively use and apply these concepts in real- life cases. The course will focus exclusively on consumer markets and will address in greater depth a selection of consumer marketing concepts introduced in the Consumer Behavior course. In addition, the course will introduce a number of recent developments in consumer marketing. lecture Lectures and tutorials. written interim examination Articles (will be made available on Blackboard) Entry requirements Third- year courses Marketing 3. 1, Marketing Research and Research tutorial Marketing or equivalent. Corporate Finance Course code E_FIN_CF ( ) Period Period 2 Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 15 van 39

19 prof. dr. ir. H.A. Rijken prof. dr. ir. H.A. Rijken Lecture, Study Group Achieve advanced knowledge in the theory and practice of corporate finance. The main objective is to fully understand theoretical concepts (their strengths and limitations) and to use these theoretical frameworks to solve in an effective way practical issues in corporate finance. After following this course, you: - understand basic Corporate Finance concepts, including their strengths and limitations - have the quantitative skills to apply these basic concepts - understand the interrelationship between various concepts and link them in a general framework - are able to apply this framework in real life cases This course elaborates on the course corporate finance in the bachelors program. We will start off with a short review of the theory of Modigliani and Miller. Within the framework of these concepts we will pay attention to the issues on capital structure from the perspective of both the equity holders and the debt holders. A range of corporate financing options, like subordinated bond and convertibles, will be discussed. Thereafter we introduce comprehensively the concepts of the operational cash flow and the finance cash flow of a company. Short Term Financial Management, Risk Management, Credit Risk Management, Value Based Management and M&A issues are Corporate Finance topics which appear frequently in the news. Therefore substantial attention will be given to real life cases (agency questions and restructuring cases in practice) during the course. lecture working group written interim examination paper Entry requirements Corporate Finance 3.2 Data Mining Techniques Course code X_ (400108) Period Period 5 Faculteit der Exacte Wetenschappen dr. Z. Szlavik dr. Z. Szlavik Lecture Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 16 van 39

20 The aim of the course is that students acquire data mining knowledge and skills that they can apply in a business environment. How the aims are to be achieved: Students will acquire knowledge and skills mainly through the following: an overview of the most common data mining algorithms and techniques (in lectures), a survey of typical and interesting data mining applications, and practical assignments to gain "hands on" experience. The application of skills in a business environment will be simulated through various assignments of the course. The course will provide a survey of basic data mining techniques and their applications for solving real life problems. After a general introduction to Data Mining we will discuss some "classical" algorithms like Naive Bayes, Decision Trees, Association Rules, etc., and some recently discovered methods such as boosting, Support Vector Machines, and co-learning. A number of successful applications of data mining will also be discussed: marketing, fraud detection, text and Web mining, possibly bioinformatics. In addition to lectures, there will be an extensive practical part, where students will experiment with various data mining algorithms and data sets. The grade for the course will be based on these practical assignments (i.e., there will be no final examination). Lectures and compulsory practical work. Lectures are planned to be interactive: there will be small questions, one-minute discussions, following an algorithm on paper, looking for patterns in a dataset about you (!), filling in missing pieces in a table, coming up with a number of creative solutions to a small problem, etc. Practical assignments (i.e. there is no exam). There will be three assignments, some (parts) of these will be done individually, some in groups of two. There is a possibility to get a grade without doing these assignments: one (!) group can be selected (based on interviews conducted by the lecturer) to do a real research project instead (which - be warned - will most likely to involve more work, but it can also be more rewarding). Ian H. Witten, Eibe Frank, Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufman, (Second Edition) Additionally, a collection of articles in electronic form (BB). Entry requirements Kansrekening en Statistiek of Algemene Statistiek (knowledge of statistics and probabilities) or equivalent. Recommended: Machine Learning. Target group mbmi, mcs, mai, mbio Derivatives and Asset Management Course code E_FIN_DAM ( ) Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 17 van 39

21 Period Period 4 dr. M. Boes Lecture, Study Group In today s financial world, the role of derivatives gets increasingly important. Banks use them to manage their balance sheet and trading activities, corporate treasuries need them for mitigation of international trade risk, insurance companies actively apply them strategically to hedge long term interest rate exposures and pension funds use derivatives for protection against a shortfall in funding level. The last decade, derivatives trading worldwide has exploded to unprecedented levels. A thorough understanding of all aspects with respect to derivatives is indispensable for anyone pursuing a job in finance. This understanding can be achieved by: - knowing the different types of derivatives and understanding their possible applications - understanding and applying arbitrage free valuation techniques - understanding the product providers on the one hand and end users and the most relevant applications on the other hand - applying these products in economic simulations In this module, the following subjects will therefore be treated: - Interest rates, yield curve stripping, interest rate sensitivity, duration matching - Arbitrage Free Valuation of options (with emphasis on valuation techniques and market specific aspects such as implied volatility) - Greeks and hedging techniques - Financial Markets (liquidity, volume, different players and applications) - Application of derivatives by end users (e. g. hedging equity and interest rate risk for a pension fund) lecture The course spans a period of six weeks. Each week, there are four sessions of 45 minutes (dates and times to be announced), in which theory and exercises are mixed. Students are required to hand in three cases. The cases are mandatory and make up for 30 percent of the total result. The remaining 70 percent can be achieved via the written exam. written interim examination 70 percent case studies: 30 percent - Hull, John, Options, Futures and other Derivatives. 7th edition. - Selection of relevant articles Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 18 van 39

22 Entry requirements Students entering this course should be familiar with the basic corporate finance principles and techniques (e. g. Brealey & Myers, Principles of corporate finance. 2002) and investment management concepts (e. g. Bodie, Kane & Marcus, Investments. 1996). This also ensures a basic level of information on derivatives and pricing methodologies is already absorbed. Furthermore, basic knowledge of mathematics, linear algebra and statistics for finance bachelor programs is assumed, since these are important tools in finance. In the cases, the students are asked to develop computer code in VBA for Excel and/or MatLab. Distribution Logistics and Supply Chain Management Course code E_BA_DLSCM ( ) Period Period 1 dr. ir. S.L.J.M. de Leeuw Lecture, Seminar So far, the Bachelor courses have predominantly focused on decision problems within the context of an individual company. During the Masters courses, this context will be expanded to encompass multiple companies. The central theme is cooperation between shippers, customers and logistics service providers. The objective of this course is to introduce students to the topic of demand & supply chain management and to discuss relevant concepts to matching supply and demand in these chains. We will focus on demand driven Supply Chain Management. After an introduction to the concepts of SCM, we will discuss the design and implementation of SCM concepts taking into account the flow of information, money and materials across the supply chain. More specifically we will discuss: - Logistics network planning - Inventory management and forecasting - Supply contracts for strategic as well as commodity components - The value of information and the effective use of information in the supply chain - Supply chain integration - Centralized and decentralized distribution strategies. - Strategic alliances - Outsourcing, off-shoring, and procurement strategies - International supply chain management - Supply chain management and product design - Customer value. - Revenue management and pricing strategies. Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 19 van 39

23 In small groups, the students will work on an assignment for a selected supply chain. Additional relevant theory and literature has to be searched by the groups. written interim examination (60 percent) assignment (40 percent) - Kaminsky & Simchy-Levi, Designing and Managing the Supply Chain, concepts, strategies & case studies. 3rd ed., McGraw-Hill. - Electronic reader with selected articles Entry requirements - Logistics and Operations Research and Logistics and Information Systems - OR Service Logistics + Introduction to Transport, Distribution and Logistics All non-tscm students (including exchange students) need to contact the course coordinator first before being eligible to take part in the course. Empirical Finance and Security Analysis Course code E_FIN_EFSA ( ) Period Period 1 dr. R.G.W. Kraussl prof. dr. A. Lucas, dr. R.G.W. Kraussl Lecture This course offers students the opportunity to study advanced empirical research methods in finance. The objective is to increase the students' ability to understand and to apply empirical methods in finance. The course represents an integration of theory, methods and examples using EViews 6 to facilitate the practice of empirical finance. The aim of the course is to enable students to undertake their own quantitative research projects in practice. The course concentrates on the following issues: tests for information efficiency, market microstructure, credit risk, event study analysis, portfolio valuation, fixed incomes, ARCH and GARCH modeling and switching models. Teaching consists of lectures and both classroom discussions and computer exercises. Students are expected to actively participate in all classroom discussions. The purpose of the compulsory computer exercises is to give students the practical skills for solving empirical finance problems. Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 20 van 39

24 written interim examination Examination consists of two parts: a number of compulsory computer exercises (40 percent) and a final exam (60 percent). - Brooks, C., Introductory Econometrics for Finance. Cambridge, UK: Cambridge University Press, Additional literature will include a reading list of current articles Entry requirements Students should have a sound knowledge of introductory econometrics and statistics and be familiar with key concepts of corporate finance, investments and financial markets. - Anthony, M. & N.L. Biggs, Mathematics for Economics and Finance. Cambrige University Press, Berenson, M.L., D.M. Levine & T.C. Krehbiel, Basic Business Statistics - Concepts and Applications. 10th edition. Prentice Hall, Bodie, Z., A. Kane & A.J. Marcus, Investments. 7th ed.. McGraw-Hill, Brealey, R.A., S.C. Myers, & F. Allen, Principles of Corporate Finance. 9th edition. McGraw-Hill, Environmental Economics Course code E_STR_EEC ( ) Period Period 2 prof. dr. D.P. van Soest prof. dr. D.P. van Soest Lecture The aim of this course is to provide students with key insights regarding the nature of environmental problems and how environmental policy should be designed. This course consists of two parts. The first part comprises lectures by the teacher based on journal articles and on five chapters of an advanced textbook (Perman et al. ). The second part is devoted to group discussions based on readings of classical articles, which are presented by the students. The lectures offer a treatment of modern economic theories and methods to study the relationship between natural resources, environmental quality, economic structure, economic change, and environmental policy. The student is expected to develop a thorough understanding of relevant economic, environmental and ethical aspects, and of the link between theory, methods and empirical analysis. The approach sets the stage for the application of methods, such as modelling and valuation techniques. The following topics will be dealt with: Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 21 van 39

25 - biological and physical aspects of environmental processes and problems - (refresher in) welfare economics - environmental ethics - the economics of non- renewable and renewable resources - advanced topics in environmental policy theory (including instrument selection) - advanced theory and methods of monetary valuation of environmental change - models for the analysis of environmental policy In the second part of the course students give presentations on specific topics to be chosen by the group a list of key journal articles is available for each topic. After following this course, you: - have a profound understanding of the fundamental factors why environmental problems materialize (positive and negative externalities) - have a profound understanding about the strengths and weaknesses of the various environmental policy instruments (taxes, quotas, voluntary agreements) - have a good understanding about how and why the practice of environmental regulation may differ from the theoretically preferred design - have sharpened your economic reasoning and have improved your presentation skills. lecture written interim examination 60 percent presentation 30 percent class participation 10 percent - five chapters from Perman, P., Y. Ma, J. McGilvray and M. Common, Natural Resource & Environmental Economics. Addison Wesley, Longman Ltd, 3rd edition Additional articles from the Economics literature Evolutionary Computing Course code X_ (400111) Period Period 1 Faculteit der Exacte Wetenschappen prof. dr. A.E. Eiben prof. dr. A.E. Eiben Lecture Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 22 van 39

26 To learn about computational methods based on Darwinian principles of evolution. To illustrate the usage of such methods as problem solvers and as simulation, respectively modelling tools.to gain hands-on experience in performing experiments. The course is treating various algorithms based on the Darwinian evolution theory. Driven by natural selection (survival of the fittest), an evolution process is being emulated and solutions for a given problem are being "bred". During this course all "dialects" within evolutionary computing are treated (genetic algorithms, evolutiestrategieën, evolutionary programming, genetic programming, and classifier systems). Applications in optimisation, constraint handling and machine learning are discussed. Specific subjects handled include: various genetic structures (representations), selection techniques, sexual and asexual genetic operators, (self-)adaptivity. If time permits, subjects in Artificial Life and Artificial Societies, and Evolutionary Art will be handled. Hands-on-experience is gained by a compulsory pogramming assignment. Oral lectures and compulsory pogramming assignment. Written exam and pogramming assignment (weighted average). Eiben, A.E., Smith, J.E., Introduction to Evolutionary Computing. Springer, 2003 ISBN Slides available from Target group mbmi, mai, mcs, mpdcs Financial Markets and Institutions Course code E_FIN_FMI ( ) Period Period 4 dr. A.H. Siegmann prof. dr. A.F.P. Bakker, dr. A.H. Siegmann Lecture Well-functioning financial markets are key to the normal functioning of the economy, whereas financial institutions act as intermediaries to channel funds from savers/investors to borrowers/spenders. However, market efficiency should be seen as the exception rather than the norm. I.e., only in the absence of distorting factors can financial markets function properly. In many cases, regulation is necessary to clear the hurdles for an efficient allocation of prices and proper pricing of Vrije Universiteit Amsterdam - - M Econometrics and Operations Research Pagina 23 van 39