# Course Descriptions

## Core MFM Courses

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FM 5111 Introduction to Financial Markets

This course is a survey of important elements of financial markets and setting the context to the program. Topics include Complete vs incomplete markets, financial institutions, traded instruments, elements of accounting, arbitrage, Fundamental Theorem of Asset Pricing, Credit, Investment and Risk Management.

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FM 5121 Mathematics for Finance

This course establishes the mathematical foundation needed for modeling in finance, with focus on probability, statistics, stochastic processes, linear algebra and more.

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FM 5151 Financial Modeling I: Python

** **This course establishes the basic principles of Financial Modeling. Topics include different kinds of models (e.g. descriptive vs explanatory, statistical vs structural, etc.), foundational models used in finance (binomial, lognormal, Gaussian, etc.) and their applications (stocks, interest rates, commodities, etc.). Python will be used extensively to illustrate the models and construct Monte Carlo simulations. This course will therefore also serve as an introduction to the use of Python in finance.

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FM 5101 Current Events in Finance

This seminar course focuses on gathering current information on analyzing the effect of local and global happenings on the behavior of the financial markets. Students will use concepts from other courses to interpret weekly market events and present to the class.

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FM 5212 Continuous Time Finance

A course on Stochastic Calculus - based modeling in finance, focusing on the Black-Scholes model and its extensions.

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FM 5222 Statistical Methods in Finance

A course on Statistical methods used in the analysis of financial markets data. It will cover topics such as Bayesian statistics, Linear and non-linear regression, Markov Chain Monte Carlo, Copulas and Time-series analysis, and their applications to financial data.

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FM 5252 Financial Modeling II: Numerical Methods and Simulations

Monte Carlo simulations and elements of scientific computing as tools in modeling. Course will cover Monte Carlo methods as a key technique to develop and assess models and therefore will spend considerable time on the interpretation of model output.

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FM 5202 Ethics in Finance

This Seminar is formatted as a case study, focusing on financial law, regulation and ethics. Students will analyze various financial decisions and discuss cases that exhibit ethical challenges, such as conflict of interests. Discussion will be conducted in small groups and summarized as a presentation to the whole group.

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FM 5323 Data Science and Machine Learning in Finance

This course introduces the basic principles underlying Data Science and Machine Learning, focusing on their applications in finance. Topics include: understanding data, EDA, various types of Machine Learning problems (e.g. classification, regression, recommendation, etc.), various algorithmic approaches (GLMs, Trees, Neural Networks, etc.), model selection, limitations of ML models, and issues in their implementations.

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FM 5343 Quantitative Risk Management

Topics include: Taxonomies of Risk, Measures of Risk, Risk Modeling and Risk Mitigation strategies. Additionally, the role and purpose of Risk Management will be discussed

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FM 5353 Software Development in Finance

This class introduces the toolset of a compiled language and principles of object-oriented programming. Databases are introduced and data models related to finance applications are explored. Projects are sourced from applied finance problems and are implemented with a focus on performance and common practices in professional software development.

## Elective MFM Courses

The list of electives is expanding and will be periodically updated. Stay tuned!

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FM 5422 Quantitative Hedge Fund Strategies

A practical course exposing students to a variety of trading strategies used in Hedge Funds.

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FM 5462 Market Microstructure

This elective focuses on the stylized facts in market microstructure and its application in algorithmic trading. In order to deal with the vast amount of real time streaming data in algorithmic trading, students will learn how to use KDB+ (a time series database) and its language q (a vectorized functional language).

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FM 5443 Credit Risk Models

This course will focus on the basic kinds of credit models (structural, intensity, etc.), and their applications. Both individual credit and portfolio level approaches will be considered.

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FM 5411 Fixed Income Market

This elective on fixed income markets expands on the basic concepts in the core curriculum and provides students a deeper understanding of this market through a hands-on approach.

## FQF Courses

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FM 5001 Preparation for Financial mathematics I - FM 5002 Preparation for Financial mathematics II

This is a two-semester sequence designed to mainly build a solid foundation in mathematical theory of probability, and develop graduate level mathematical thinking and problem solving skills. The curriculum over the course of two semesters is focusing on calculus based probability (single variable in FM 5001and multi-variable in FM 5002), along with refreshing and strengthening knowledge and skills in some key topics used in financial modeling such as linear algebra, differential equations (including an introduction to partial differential equations), basic numerical methods and multivariable calculus. Towards the end of the sequence there will be a short introduction to mathematical statistics and to stochastic processes (random walks and Brownian Motion).

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FM 5111 Introduction to Financial Markets

This course is a survey of important elements of financial markets and setting the context to the program. Topics include Complete vs incomplete markets, financial institutions, traded instruments, elements of accounting, arbitrage, Fundamental Theorem of Asset Pricing, Credit, Investment and Risk Management.

###
+
FM 5151 Financial Modeling I: Python

This course establishes the basic principles of Financial Modeling. Topics include different kinds of models (e.g. descriptive vs explanatory, statistical vs structural, etc.), foundational models used in finance (binomial, lognormal, Gaussian, etc.) and their applications (stocks, interest rates, commodities, etc.). Python will be used extensively to illustrate the models and construct Monte Carlo simulations. This course will therefore also serve as an introduction to the use of Python in finance.

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FM 5252 Financial Modeling II: Numerical Methods and Simulations

Monte Carlo simulations and elements of scientific computing as tools in modeling. Course will cover Monte Carlo methods as a key technique to develop and assess models and therefore will spend considerable time on the interpretation of model output.