Prerequisites, MFE Program, Berkeley-Haas.pdf

19/3/2014A LU M NI Prerequisites, MFE Program, Berkeley-Haas C U RRE N T ST U D E N T S C O M P A N I E S & RE C RU I T E RS C O NTA C T Search M FE Home W hy Be rke le y-Haas Acade mics Place Community Care e rs Admissions [ F I R ST - PE R SON ] Haas Home Program Overview Curriculum Prerequisites Pre-Program C ourses Academic C alendar Degree Requirements C ontact MFE Admissions Prerequisites Successful candidates for the MFE Program will have a strong background in C omputer programming High-level math and statistics Finance studies Language skills Statistical and econometric applications (Sas, Gauss, RATS, S-Plus, or Garch) Mathematical tools (MatLab, Mathematica, or MathC ad) Before the program you are applying to is scheduled to begin, you should: Have taken—or have a plan in place to take—the prerequisite courses listed below for a grade of "B" or higher Plan to take all of the pre-program courses in addition to the prerequisites to reinforce your understanding of the basic concepts Please note that you do not necessarily need to complete all of the coursework prior to submitting your application, but you do need to have a clear plan in place to complete the coursework between the time of application and the time the program begins. For students who have not taken a math course in more than 5 years, we do recommend some type of refresher course in order to excel in the program. Tadaaki Tsunoda MFE 13 Internship: Mizuho Corporate Bank Tokyo, Japan "The Berkeley MFE curriculum is very practical. I’ve learned solutions to problems that I face in my work." R e ad O n More Profile s Prerequisite Course List Computer Programming Experience Requirement: Prior experience in computer programming (C , C ++) and familiarity with computers as a computational and management tool. Area: C , C ++ Programming Suggestion: 1 course OR equivalent work experience Quantitative Background Requirement: A strong quantitative background including multivariate calculus, linear algebra, differential equations, numerical analysis and advanced statistics and probability. Calculus Suggestion: 2 courses Examples: 1A, 1B. C alculus. (A) An introduction to differential and integral calculus of functions of one variable, with applications and an introduction to transcendental functions. (B) Techniques of integration; applications of integration. Infinite sequences and series. First-order ordinary differential equations. Second-order ordinary differential equations; oscillation and damping; series solutions of ordinary differential equations. 53. Multivariable C alculus. Parametric equations and polar coordinates. Vectors in 2- and 3-dimensional Euclidean spaces. Partial derivatives. Multiple integrals. Vector calculus. Theorems of Green, Gauss, and Stokes. Linear Algebra Suggestion: 1 course Examples: 54. Linear Algebra & Differential Equations. Basic linear algebra; matrix arithmetic and determinants. Vector spaces; inner product as spaces. Eigenvalues and eigenvectors; linear transformations. Homogeneous ordinary differential equations; first-order differential equations with constant coefficients. Fourier series and partial differential equations. 110. Linear Algebra. Matrices, vector spaces, linear transformations, inner products, determinants. Eigenvectors. QR factorization. Quadratic forms and Rayleigh's principle. Jordan canonical form, applications. Linear functionals. Related Links Placement Information MFE Announcements Meet Our C urrent Students Admissions C riteria Attend an Info Session http://mfe.berkeley.edu/academics/prerequisites.html 1/3 Markets for financial assets and the structure of yields. Estimation. Expectation. C lassification of second order equations. maximum likelihood estimation. Introduction to the Theory of Probability. Testing hypotheses. and management of financial institutions. http://mfe. Point and interval estimation. a priori bounds. influence of Federal Reserve System and monetary policy on financial assets and institutions. roundoff error. Investments. sample surveys. Non parametric tests. Area: Finance Suggestion: 2 courses OR equivalent work experience Examples: 131. C omputer-based applications. Regression and correlation. Relative frequencies. C onditional probability. A comprehensive survey course in statistical theory and methodology. 132. It will focus on project evaluation.19/3/2014 Suggestion: 1 course Prerequisites. numerical quadrature. 100B. Emphasis on concepts and applications. equity. capital structure. Illustrations from many fields. tests of significance. Statistics Suggestion: 2 courses (one introductory. Training In Finance Requirement: Sufficient training to undertake graduate study in the chosen field. Introduction to the Theory of Statistics. Practice on the computer. characteristic functions. estimates. UPPER DIVISION: 101. random variables. confidence intervals. and procedures for analysis of securities. statistical applications. F tests. Probability models for random experiments. Descriptive statistics. Maximum likelihood estimates. and solution of ordinary differential equations. expectation. Random variables. Testing hypotheses. t tests. Markov chains. central limit theorem. 21. conditioning. C orporate Finance and Financial Analysis.html 2/3 . simulation. Discrete and continuous random variables. emphasizing concepts and applications. Illustrations from various fields. analysis of variance. Topics include descriptive statistics. This course will cover the principles and practice of business finance. 133. and price levels. Expectation and variance. with attention to the effects of monetary and fiscal policy. approximation and interpolation. Illustrations from engineering. expectation. Standard discrete and continuous distributions. The laboratory includes computer-based data-analytic applications to science and engineering. C entral limit theorem. 134. Macroeconomics. Berkeley-Haas Differential Equations Example: 126. Point estimation. Selected topics such as the Poisson process. Introduction to Partial Differential Equations. independence. C oncepts of Statistics. An introduction to probability.berkeley. MFE Program. Microeconomics. Firms' policies toward debt. The normal approximation. operations of security markets. Organization. Independence. Resource allocation and price determination with an emphasis on microeconomic principles. and other computer applications. Sources of and demand for investment capital. and dividends are explored. boundary value problems for elliptic and parabolic equations. The incentives and conflicts facing managers and owners are also discussed. goodness-of-fit tests. Numerical Analysis. C onditional expectation. univariate models. determination of investment policy. Ideas of experimental design.edu/academics/prerequisites. 101A. and the application of these procedures to the design and analysis of experiments. multivariate normal distribution. laws of large numbers. 20. A study of the factors/theories which determine national income. 102. the Fourier transform. and least squares estimation. 25. existence and uniqueness theorems in simple cases. correlation and regression. Random variables and their distributions. Bias and variance of estimates. controlled experiments vs. Programming for numerical calculations. probability models and related concepts. 101B. discrete probability. 100A. C oncepts of Probability. behavior. maximum principles. employment. one advanced) Examples: LOWER DIVISION: 5. observational studies. dependence. Numerical Analysis Suggestion: 1 course Example: 128A. Wald test and likelihood ratio tests in the context of logistic regression and Poisson regression. Least squares estimates. 135. Money and C apital Markets. and corporate governance. initial value problems for hyperbolic equations. R1B. MFE Program. Speech/Rhetoric Suggestion: 1 course OR equivalent work experience Examples: 100. and presentation skills (in English). R1B. Instruction in expository writing in conjunction with reading literature. (A) Rhetorical approach to reading and writing argumentative discourse. (B) Intensive argumentative writing drawn from controversy stimulated through selected readings and class discussion. English C omposition. [Back to top] C opyright © 1996-2014 | Unive rsity of C alifornia. speaking. C lose reading of selected texts. Reading and C omposition. written themes developed from class discussion and analysis of rhetorical strategies. Berkeley-Haas Requirement: Excellent writing. Theory and practice of effective communication in a business environment.19/3/2014 Language Skills Prerequisites. The C raft of Writing. R1A. Business C ommunication.edu/academics/prerequisites. Be rk e le y | Haas School of Busine ss http://mfe. Area: English Writing. R1A.berkeley. Students practice what they learn with oral presentations and written assignments that model real-life business situations.html 3/3 .