학부
Appl Regr Analysis (STAT 512) (*석사 레벨)
Thorough applied course in regression and analysis of variance including experience with the SAS statistical software package. Topics include inference in simple and multiple linear regression, residual analysis, transformations, polynomial regression, model building with real data, and nonlinear regression. One-way and two-way analysis of variance, multiple comparisons, fixed and random factors, and analysis of covariance are covered. This course is not mathematically advanced, but covers a large volume of material. It requires calculus, and simple matrix algebra is helpful. This course is recommended for graduate students and for serious undergraduates from all areas.
회귀분석, ANOVA분석(1way, 2way), 다중회귀분석 학습 및 SAS로 구현 실습
A 4.0/4.0
Introduction To Statistics (STAT 350)
A data-oriented introduction to the fundamental concepts and methods of applied statistics. Exploratory analysis of data. Sample design and experimental design. Probability distributions and simulation. Sampling distributions. The reasoning of statistical inference. Confidence intervals and tests for one and two samples. Inference for contingency tables, regression, and correlation. Introduction to regression with several explanatory variables. Essential use is made of statistical software throughout. Intended primarily for students majoring in the mathematical sciences. For statistics majors and minors, credit should be allowed in no more than one of STAT 30100, 35000, 50100, and in no more than one of STAT 50300 and STAT 51100.
실증 분석, 확률 분포, 시뮬레이션, 통계적 추론, 회귀분석 등 학습
A+ 4.0/4.0
Statistical Theory (STAT 417) (*난이도 상)
mathematical theory of statistical inference, emphasizing inference for standard parametric families of distributions. Properties of estimators. Bayes and maximum likelihood estimation. Sufficient statistics. Properties of test of hypotheses. Distribution theory for common statistics based on normal distributions.
통계적 추론의 수학적 이론, 베이즈, 최우도 추정, 통계 분포 이론 등 수학
A 4.0/4.0
Foundations Analysis (MA341)
rigorous analysis, covering real numbers, sequences, series, continuous functions, differentiation, and Riemann integration
실수, 시퀀스, 시리즈, 연속 함수, 미분 및 Riemann 적분 실해석학 학습
A 4.0/4.0
Ord Differential Eqs (MA 366)
ordinary differential equations with emphasis on problem solving and applications. The one-hour computer lab will give students an opportunity for hands-on experience with both the theory and applications of the subject
미분방정식 및 dfield, pplane 실습
A 4.0/4.0
Topics Vector Calculus (MA 362)
Multivariate calculus; partial differentiation; implicit function theorems and transformations; line and surface integrals; vector fields; theorems of Gauss, Green, and Stokes.
다변량 미적분, 벡터, PDE, 가우스, 그린, Stokes 정리 수학
A 4.0/4.0
Linear Algebra II Appl (MA 353)
Factoring matrices, orthogonal projections (with application to least squares estimation), diagonalization and Jordan canonical form (with applications to Markov chains and systems of differential equations), Hermitian matrices, convexity (with application to linear programming). Emphasis on problem solving and applications from science, engineering, economics, or business.
This is a course focusing on rigorous proof and theoretical background for methods and results that appear in MA 351
Elementary Linear Algebra including:
1. Perform rigorous proofs using the definitions of vector space, subspace, linear combination of vectors, linear dependence and linear independence, bases and dimension.
2. Linear transformation and the null space and range of a linear transformation.
3. Understand elementary matrices and their use in describing the solution set of a system of linear equations.
4. Eigenvalues and eigenvectors, singular values and singular vectors.
5. Gram-Schmidt, least squares and related topics.
6. Abstract vectors, inner product spaces and related topics.
인수 분해 행렬, 최소 제곱 추정, 직교 프로젝션, 대학화 등 선형대수 학습
B 3.0/4.0
MFE 석사
금융해석학
확률이론, 브라우니안모션, 스토캐스틱 미적분학 등 학습
A 4.0/4.3
재무회계
This course builds a basic understanding of how information regarding a firm’s resources and obligations is conveyed to stockholders, creditors, financial analysts, government agencies and the general public. This course focuses on the form and content of corporate financial statements. Students learn the principles of revenue and expense recognition as well as the basic accounting for assets, liabilities, and equities. At the completion of the course, you should be able to:
n Understand the theory and implications of certain generally accepted accounting principles (GAAP),
n Identify various incentives that affect managers’ accounting choices, and
n Analyze economic events disclosed in corporate financial statements.
기업의 재무 제표 형식 및 내용 학습
A- 3.7/4.3
포트폴리오 최적화 및 운용
The purpose of this course is to introduce the modern theory and application of portfolio management techniques. We start by discussing the mean variance portfolio theory, including determination of opportunity set and calculation of the efficient frontier. Then we move on to modeling the correlation structure of security returns and selecting the optimum portfolio. Management of bond portfolios will also be discussed in the class, if time permits.
평균-분산 PF, 상관관계, efficient frontier, optimum PF 학습
B+ 3.3/4.3
전산금융
DB, SQL, 머신러닝 기법 통한 재무 데이터 처리 및 분석 모델링
A+ 4.3/4.3
보험과 위험의 원리
This course provides an introduction to different types of non-speculative risks faced by individuals and businesses along with possible alternative methods of treating such risks. We will examine the specific application of these methods with regards to life, health, property, and liability insurance contracts. First, we will gain a clear understanding of risk and the risk management process. Next, we will investigate the insurance industry from both an economic and regulatory perspective. Then we will study property and liability insurance contracts including auto insurance contracts. The ultimate section of the course will cover individual life and health insurance. Throughout the semester students will have the opportunity to demonstrate their understanding of current risk related topics through exams, participation, and homework assignments. This course is designed for non-majors as well as a foundation for more advanced risk management and insurance courses.
위험, 위험 관리, 손해보험, 생명보험 학습
A 4.0/4.3
금융 윤리와 사회 책임
CFA 기준으로 윤리 강령, 규제, 전문가 행위기준, 사례 분석
A+ 4.3/4.3
금융공학특강<금융CEO특강>
본 교과목에서는 학생들이 금융이론을 바탕으로 다양한 금융회사 (은행, 증권, 보험, 자산운용, 금융공기업 등) CEO들의 특강을 통해 이론이 어떻게 실무와 금융회사 경영에 적용되는지 이해하게 된다. 이를 통해 본 교과목의 목표는 금융회사에 진출해 경력을 개발하고자 하는 학생들이 더욱 구체적으로 각 분야에 대한 이해수준을 높이는 능력을 기르는데 있다. 학생들은 또한 본 교과목을 통해 금융CEO들의 회사경영에서의 여러 고민에 대해 청취하고 이를 해결하는데 함께 참여하게되어 향후 금융회사 경영자로서의 자질을 함양하는데 기초를 다지고자 한다.
금융회사 CEO들을 연사로 초청하여 각 분야에 대한 개론, 현황, 이슈 등 학습
A- 3.7/4.3
부동산투자론
This course covers the theory and practice of real estate investment decision making. While particular attention is given to the tools and techniques necessary to undertake real estate investment analysis for commercial properties, many of these same concepts can be readily applied within the residential marketplace. Particular attention is given to issues in urban economics, capital budgeting, real options, risk analysis, and income taxation which materially influence real estate investment decision making.
상업용 부동산에 대한 부동산 투자 분석, 자본 예산, 옵션, 위험 분석 및 소득세 학습
B+ 3.3/4.3
부동산 담보부 채권 및 기타 구조화 채권
This course studies debt secondary markets linked to real estate assets. These markets have become a key way to funding residential and commercial real estate. The recent financial crisis saw a sharp contraction of new issuance in some of these markets, although others, such as the agency MBS market, became even larger and more central to mortgage
On the debt side, we will analyze agency and non-agency mortgage-backed securities, as well as some related instruments, such as CMBS, CMOs, and CDOs. We will discuss the key factors that drive default risk and interest rate risk on commercial and residential mortgages, and learn the basic principles for the valuation of mortgage-backed securities, taking into account the value of the prepayment option embedded in such securities.
B+ 3.3/4.3
금융공학 연구방법1
Part I of this course, the research methods in financial engineering, reviews the popular methodologies in financial engineering research. At the beginning of the part I, each student will present his/her research plan as a proposal of research.
포트폴리오 전략, 수치해석학, 프라이싱 모델, 실증연구방법론
A- 3.7/4.3
금융프로그래밍
This course provides an introduction to the implementation of basic financial models using EXCEL functions, VBA (Visual Basic with Applications), R, and python. This course covers a number of topics including optimal portfolio, calculating beta, random number generation, stock price path, and Monte-Carlo simulation.
최적 포트폴리오 구성, 베타 계산, 난수 생성, 몬테카를로 시뮬레이션 학습(VBA, R)
A 4.0/4.3
사적시장에서의 투자기법
• Leverage buyouts (LBO), valuation and fund returns.
• Recent trend of LBO.
• Human element of private equity.
• Understand vocabulary of private equity and key industry facts
• Understand firm valuation process for LBO
• Understand how information asymmetry and moral hazard problem shape the compensation structure of private equity.
• Understand key research findings on the private equity industry.
사모펀드 이해, LBO 회사 평가 과정, 사모펀드의 도덕적 해이와 보상 구조 학습
A 4.0/4.3