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AMS 511, Foundation of Quantitative Finance 
Introduction to capital markets, securities pricing, and modern portfolio theory, including the organization and operation of securities market, the Efficient Market Hypothesis and its implications, the Capital Asset Pricing Model, the Arbitrage Pricing Theory, and more general factor models. Common stocks and their valuation, statistical analysis, and portfolio selection in a single-period, mean-variance context will be explored along with its solution as a quadratic program. Fixed income securities and their valuation, statistical analysis, and portfolio selection. Discussion of the development and use of financial derivatives. Introduction to risk neutral pricing, stochastic calculus, and the Black-Scholes Formula. Whenever practical, examples will use real market data. Numerical exercises and projects in a high-level programming environment will also be assigned.
Prerequisites:  AMS 510
3 credits, ABCF grading 
AMS 511 webpage 

AMS 512 Capital Markets and Portfolio Theory 
Development of capital markets and portfolio theory in both continuous time and multi-period settings. Utility theory and its application to the determination of optimal consumption and investment policies. Asymptotic growth under conditions of uncertainty. Applications to problems in strategic asset allocation over finite horizons and to problems in public finance. Whenever practical, examples will use real market data. Numerical exercises and projects in a high-level programming environment will also be assigned. 
Prerequisite:  AMS 511
3 credits, ABCF grading 
AMS 512 webpage 

AMS 513 Financial Derivatives and Stochastic Calculus 
Further development of derivative pricing theory including the use of equivalent martingale measures, the Girsanov Theorem, the Radon-Nikodym Derivative, and a deeper, more general understanding of the Arbitrage Theorem. Numerical approaches to solving stochastic PDEÕs will be further developed. Applications involving interest rate sensitive securities and more complex options will be introduced. Whenever practical, examples will use real market data. Numerical exercises and projects in a high-level programming environment will also be assigned. 
Prerequisite:  AMS 511
3 credits, ABCF grading 
AMS 513 webpage 

AMS 514 Computational Finance 
Review of foundations: stochastic calculus, martingales, pricing, and arbitrage. Basic principles of Monte Carlo and the efficiency and effectiveness of simulation estimators. Generation of pseudo- and quasi-random numbers with sampling methods and distributions. Variance reduction techniques such as control variates, antithetic variates, stratified and Latin hypercube sampling, and importance sampling. Discretization methods including first and second order methods, trees, jumps, and barrier crossings. Applications in pricing American options, interest rate sensitive derivatives, mortgage-backed securities and risk management. Whenever practical, examples will use real market data. Extensive numerical exercises and projects in a general programming environment will also be assigned. 
Prerequisite:  AMS 512 and  AMS 513
3 credits, ABCF grading 
AMS 514 webpage 

AMS 515 Case Studies in Computational Finance II 
Actual applications of Quantitative Finance to problems of risk assessment, product design, portfolio management, and securities pricing will be covered. Particular attention will be paid to data collection and analysis, the design and implementation of software, and, most importantly, to differences that occur between Òtheory and practiceÓ in model application, and to the development of practical strategies for handling cases in which Òmodel failureÓ makes the naive use of quantitative techniques dangerous. Extensive use of guest lecturers drawn from the industry will be made. 
Prerequisite:  AMS 512 and  AMS 513
3 credits, ABCF grading 
AMS 515 webpage 

AMS 516, Statistical Methods in Finance
The course introduces statistical methodologies in quantitative finance. Financial applications and statistical methodologies are intertwined in all lectures. The course will cover regression analysis and applications to the Capital Asset Pricing Model and multifactor pricing models, principal components and multivariate analysis, statistical methods for financial time series; value at risk, smoothing techniques and estimation of yield curves, and estimation and modeling of volatilities.
3 credits, ABCF grading 
AMS 516 webpage 

AMS 517, Risk Management 
Quantitative methods for risk management problems including market risk, credit risk, operational risk and Basel II accord. Multivariate models; extreme value theory; structure and reduced-form models of default; and copula-based models.
Prerequisite:  AMS 511AMS 512, and  AMS 513
3 credits, ABCF grading 
AMS 517 webpage

AMS 518, Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization
The course provides a thorough treatment of advance risk measurement and portfolio optimization, extending the traditional approaches to these topics by combining distributional models with risk or performance measures into one framework. It focuses on, among others, the fundamentals of probability metrics and optimization, new approaches to portfolio optimization and a varierty of essential risk measures. Numerical exercises and projects in a high-level programming environment will be assigned. 
Prerequisite:  AMS 512 or instructor consent
Offered Fall semester 
3 credits, ABCF grading 
AMS 518 webpage

AMS 519, Internship in Quantitative Finance
Supervised internship in financial institution. Students will typically work at a trading desk, in an asset management group, or in a risk management group. Students will be supervised by a faculty member and a manager at their internship site. Written and oral reports will be made to both supervisors.
Offered every semester
3-6 credits, S/U Grading
AMS 519 webpage

AMS 522, Bayesian Methods in Finance
The course explores in depth the fundamentals of the Bayesian methodology and the use of the Bayesian theory in portfolio and risk management. It focuses on, among other topics incorporating the prior views of analysts and investors into the asset allocation process, estimating and predicting volatility, improving risk forecasts, and combining the conclusions of different models. Numerical exercises and projects in a high-level programming environment will be assigned.
Prerequisite:  AMS 512 or instructor consent
Offered Spring semester 
3 credits, ABCF grading
AMS 522 webpage 

AMS 523, Mathematics of High Frequency Finance
The course explores Elements of real and complex linear spaces. Fourier series and transforms, the Laplace transform and z-transform. Elements of complex analysis including Cauchy theory, residue calculus, conformal mapping and Möbius transformations. Introduction to convex sets and analysis in finite dimensions, the Legendre transform and duality. Examples are given in terms of applications to high frequency finance. 
Offered Fall semester
3 credits, ABCF grading
AMS 523 webpage

AMS 600, Socially Responsible Investing
Introduction to a scope of investments which are socially responsible because of the nature of the business the company conducts, including but not limited to: avoiding investment in companies that produce or sell addictive substances (like alcohol, gambling and tobacco) and seeking out companies engaged in environmental sustainability.
Prerequisite:  AMS 511
Course is cross-listed with MBA 581
Offered Fall semester
3 credits, ABCF grading
AMS 600 webpage

AMS 601, Risk Management and Business Risk Control in BRIC Countries
Introduction to the challenges and opportunities in investing in the BRIC countries, Brazil, Russia, India and China, with emphasis in the risk assessment, control and management.  Opportunities in investing in BRIC:  growth in infrastructure, middle class demand, educated cheap workforce, potential for outsourcing work, high risk/high reward.
Prerequisite:  AMS 511
Course is cross-listed with MBA 584
Offered Spring semester
3 credits, ABCF grading
AMS 601 webpage

 

 

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