Financial Engineering, M.S. | NYU Tandon School of Engineering

Financial Engineering, M.S.

On Campus

Financial Engineering

The priority application deadline is December 15, 2019. 

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Sophisticated modeling and information technology now dominate the financial world. The theories and the practice of Finance are challenged today by complex financial and global systems and by dynamically changing regulatory environments and politics. A global world in transition creates both opportunities and challenges for financial engineers to adapt theoretical and financial constructs into profitable and innovative opportunities by creating innovative, custom-designed instruments in the marketplace.

At the NYU School of Engineering, we train our students to do exactly that: to engineer the future of finance and transform financial theory into practice. The MS in Financial Engineering program furnishes students with foundational knowledge in financial concepts. This knowledge then becomes a springboard to specialized fields where students can apply concepts to everything from derivatives risk finance to financial IT and algorithmic trading on Big Data.

The program allows students to select courses from the following focus areas:

  • Corporate Finance and Financial Markets
  • Computational Finance
  • Technology and Algorithmic Finance
  • Risk Finance

About the Program

The Department receives a large number of applications every year. To be considered for admission into the MS in Financial Engineering program, students must have a Bachelor’s Degree from an accredited institution and proven proficiency in:

  • Linear Algebra
  • Probability Theory
  • Multivariable Calculus (Advanced)
  • Applied Statistics
  • Computer Programming

Applicants must submit official transcripts from each institution attended as well as GRE test scores. Note that the average Quant GRE score of accepted students in Fall 2019 was 169.2/170.

 When applicable, applicants must also demonstrate English language proficiency to be determined by the TOEFL score.

The FRE department does not accept change-of-major requests. In all instances, students must formally apply to the program. Applicants must have demonstrated proficiency in the mathematical areas listed to be considered for admission. The Department offers both an online and an on-campus bootcamp during the summer before formal coursework starts. For program highlights and a video regarding further details on FRE admissions requirements, visit our Prospective Students page.


Contact the Graduate Center for questions about the application process, application status or to talk to an admissions counselor:

Office of Graduate Enrollment Management and Admissions
NYU Tandon School of Engineering
6 MetroTech Center
Brooklyn, NY 11201
engineering.gradinfo@nyu.edu
Phone: 646.997.3182
Fax: 646.997.3624


Contact the Department of Finance and Risk Engineering with your academic questions, e.g., courses and curricula.

Department of Finance and Risk Engineering
NYU Tandon School of Engineering
1 MetroTech Center North, 10th floor
Brooklyn, NY 11201
engineering.fre@nyu.edu
Tel: 646.997.3279
Fax: 646.997.3355


Curriculum

Students enrolled full-time will complete the program in 4 semesters (May) although some may accelerate the course load and graduate within 3 semesters. Our program also offers flexibility to attend part-time and extend the number of semesters.

To earn a Master of Science in Financial Engineering, students must complete 33 credits to qualify for graduation. The structure of the program is as follows:

  • Bootcamp of 0 credits
  • 5 core courses, each 3 credits
  • Focus area and general elective courses within FRE and closely related fields personalized by the student, totaling 13.5 credits
  • 1 required applied lab worth 1.5 credits
  • 1 capstone experience of 3 credits
    Read the Capstone Guidelines (PDF)
  • Capstone assessment of 0 credits
  • Bloomberg certification of 0 credits
  • Total # of credits: 33

 

The program allows students to select courses from the following focus areas:

  • Corporate Finance and Financial Markets
  • Computational Finance
  • Technology and Algorithmic Finance
  • Risk Finance

Students must also complete the Bloomberg Essentials Online Training Program and earn the Acknowledgement of Completion to qualify for graduation. The Department will support your efforts to complete the training program by providing many Bloomberg terminals and laboratory assistants to answer your questions. This is a zero-credit requirement, listed as FRE 5500.

Graduate students enrolled in other NYU graduate programs may request enrollment in FRE courses for up to 6 credits per semester with the approval of their graduate program advisor. Undergraduate students are not allowed to take courses in the MS in Financial Engineering program, except for those in a combined BS/MS program. It is the students’ responsibility to consult with their academic advisor if the courses they plan to take satisfy degree requirements in their program, and to obtain approval to enroll in Financial Engineering courses via the FRE cross-registration form available in the Student Resources page. Please review the NYU cross-school registration policy prior to submitting cross-registration requests.


CORE COURSES (15 CREDITS)

Required Courses:

3 Credits Introduction to Derivative Securitites FRE-GY6073
This course explains in detail various models and methods for pricing and hedging derivatives including: European, American, exotic options, swaps, and convertible bonds. Presentation is done using equity, interest rate, and volatility derivative products. A short introduction to computational methods necessary for pricing derivatives is provided.
Prerequisites: Matriculation into MS Financial Engineering or permission of the department.
3 Credits Quantitative Methods in Finance FRE-GY6083
This course focuses on quantitative methods and financial modeling. Probability theory, stochastic processes and optimization are studied and applied to a broad variety of financial problems and their derivatives. Topics include probability spaces; conditional probability; densities; distributions; density estimators; multivariate probability; moment-generating functions; random walks; Markov processes; Poisson processes; and the Brownian-motion process.
Prerequisite: Students are expected to know calculus and elementary probability and Graduate Standing
3 Credits Valuation for Financial Engineering FRE-GY6103
This course introduces financial engineers to robust risk-based valuation methods in discrete and continuous time. This includes four major applications: cash flows, traded derivative contracts, nontraded and embedded derivatives, and corporate assets & liabilities.
- “Cash flows” refers to risk-free and risky payments or expenditures.
- “Traded derivatives” include a high level treatment of forward contracts and the most commonly traded option contracts.
- “Nontraded and embedded derivatives” refer to contingent cash flows created in the normal processes of contracting and asset management
- “Corporate assets” refer to claims to cash flows owned and managed by corporations
- “Corporate liabilities” refers to corporate-issued securities or other payment obligations incurred by corporations.
Prerequisite: Graduate Standing

Two of the following three courses:

3 Credits Financial Economics FRE-GY6023
This course provides a rigorous introduction to the principles and application of the theory of financial economics. Following a review of foundational theories of markets and competition, this course covers the following areas: certainty and perfect capital markets, the institutional setting of financial economics, risk and contingent claims theory, and capital market imperfections and the limits to arbitrage that these impose on financial systems.
Prerequisite: Graduate Standing
3 Credits Financial Risk Management FRE-GY6123
This course introduces the techniques and problems of Financial Risk Management and Asset Pricing. It emphasizes risk finance and attitudes; Value at Risk; risk measurement principles; valuation and expected utility and their relevance in the valuation and the pricing of financial investments; insurance; management of derivatives; and risk management. Throughout, risk-management application problems are explored., The course introduces and focuses on the fundamental principles of the Arrow-Debreu state preference theory used to price derivatives and other assets in complete markets. Risk neutral-Binomial models in option pricing; essential elements of Ito calculus; and the Black-Scholes model for pricing options are introduced and applied to practical financial decision making and risk management problems. Prerequisite: Graduate Standing
3 Credits Machine Learning in Financial Engineering FRE-GY7773
This course covers the theory of Machine Learning and its fundamental applications in the field of Financial Engineering. Supervised, unsupervised, and reinforcement learning paradigms are discussed.
Prerequisites: Matriculation into MS Financial Engineering or permission of the FRE department

 

FOCUS AREA AND GENERAL ELECTIVES (13.5 CREDITS) 

These include the guidance tracks Financial Markets and Corporate Finance, Computational Finance, Technology and Algorithmic Finance, and Risk Finance (Credit Risk, Financial Management, and Insurance). 

Students may choose from any FRE courses to fulfill these focus area and general elective requirements. They may also elect to register for up to three (3) classes (maximum of one per semester) at select schools/programs at NYU. Courses outside FRE must be approved by the MS Financial Engineering academic advisor. Students may only enroll for courses at other schools of NYU that are not offered at the School of Engineering. Please review the NYU cross-school registration policy prior to submitting cross-registration requests.

For a list of available electives, see the FRE Course Listings.

Please see the the drop downs below for more details on focus areas.

 

APPLIED LAB (1.5 CREDITS*)

Choose 1 lab from the following:

1.5 Credits Financial Software Laboratory FRE-GY6811
This course teaches students to use financial software tools commonly employed in industry. Examples include: @Risk, Yieldbook, Excel, R, and C++.
Prerequisites: Graduate Standing

1.5 Credits Financial Econometric Laboratory FRE-GY6821
This course teaches students to use Eviews and Stata.
Prerequisites: Graduate Standing
1.5 Credits Computational Finance Laboratory FRE-GY6831
The course introduces programming applications in financial modelling. Topics include variables, data types, input/output, plotting, selection statements, loop statements, functions, and classes, and implementation for Black-Scholes option pricing partial differential equation, Monte Carlo simulation, numerical methods for solving partial differential equations, and option pricing by Fourier transform.
1.5 Credits Financial Software Engineering Laboratory FRE-GY6861
This financial lab requires students to publicly participate in a large software project. This participation could take the form of contributing to an open-source financial software project with the contributions being accepted and committed to the main branch, or publishing a stand-alone library or package for a programming language commonly used in financial applications, or the development or updating of a brand-new industrial strength financial software application. As the students work on their project, this course will focus on important software engineering considerations specifically as they apply to the fast-paced world of financial projects, such as formalized procedures for revision control and bug tracking and other proven methods of software management in a fast-paced financial environment.
Prerequisite: Graduate Standing
1.5 Credits R in Finance FRE-GY6871
This course introduces the free programming language R and its many applications to finance including risk management, portfolio construction, strategy development and testing, and trading and execution. Topics covered include financial time series analysis, advanced risk tools, applied econometrics, portfolio management, and derivatives valuation. Students will be required to write some code in R every week.
Prerequisites: Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the Department & FRE-GY 6123 and FRE-GY 6083
3 Credits Financial Computing FRE-GY6883
This course covers programming applications to financial engineering, including C++ and Java and the various common development environments for them. Topics include structured and object-oriented programming in C++ with applications to binomial options pricing, multi-threaded programming in Java with applets and graphical interfaces with applications to risk measurement tools, data-based manipulation and programming in SQL and standard database access libraries with applications to historical financial data series retrieval and management, and other advanced programming concepts important for financial engineering such as numerical techniques, trading systems, and large-scale software design.
Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the Department.

*For FRE-GY 6883, 1.5 credits count as lab and 1.5 credits as elective.

Note: Waivers are possible.

 

REQUIRED CERTIFICATION (0 CREDITS)

Bloomberg Certification FRE-GY5500
This course tracks the requirement for the self-paced, self-taught Bloomberg certification to be completed through a Bloomberg terminal.
Prerequisite: Graduate Financial Risk Engineering students only

 

CAPSTONE (3 CREDITS)

Choose 1 capstone option:

I. INTERNSHIP

1.5 Credits Financial Engineering Capstone: Internship FRE-GY7021
In this course, the Career Development Office helps the student secure an internship. Students work under faculty supervision. However, the course is intended to be largely self-directed within the guidelines established by the supervising faculty member. A paper based on the internship work is required.
Prerequisites: This course should be taken after the student has successfully completed two Semesters and earned at least 18 credits. Prerequisites vary depending on the student’s track, the nature of the internship and Graduate Standing.

Minimum 240 hours per semester; FRE-GY7021 must be taken twice in order to fulfill the capstone requirement; 1 report to the faculty is required

II. PROJECT

3 Credits Financial Engineering Capstone: Project FRE-GY7043
In this project course, students work with faculty on proprietary or non-proprietary research projects. Generally, students work under faculty supervision. However, the course is intended to be largely self-directed within the guidelines established by the supervising faculty member. A significant written research component is required.
Prerequisites: This course should be taken after the student has successfully completed two Semesters and has earned at least 18 credits. Prerequisites vary depending on the student’s track, the nature of the project to be undertaken, and Graduate Standing.

Project under faculty supervision

III. THESIS

3 Credits MS Thesis in Finance & Risk Engineering FRE-GY9973
In this research course, students undertake proprietary or non-proprietary research and write a thesis-type research paper. Generally, students work under faculty supervision. However, the course is intended to be largely self-directed within guidelines established by the supervising faculty member.
Prerequisites: Graduate Standing. This course should be taken during the student’s final semester. Prerequisites vary depending on the student’s track and the nature of the thesis project.

IV. SPECIAL TOPICS

3.00 credits (two courses of 1.5 credit each or a single 3.00 credit course) of courses marked “topics” or “special topics” in the FRE section of the school course catalog, with a capstone paper submitted to the capstone advisor.

In addition, please see the Capstone Procedures and Requirements (PDF).

 

CAPSTONE ASSESSMENT (0 CREDITS)

Capstone Assessment FRE-GY5990
The Master of Science in Financial Engineering program offers four types of Capstone experiences to its graduate students: theses, projects, special topics, and internships. This Capstone Assessment will serve as a centralized measure for the various types of Capstone experiences to identify whether students have successfully completed this experience and garner feedback about graduating students' skills and professional readiness. Note: course should be completed during final semester of studies.
Prerequisites: FRE-GY 9973 or FRE-GY 7021 (taken two times for a total of 3 credits) or FRE-GY 7043 or two special topics courses of 1.5 credits each, with a capstone papers submitted to the faculty.


Corporate Finance and Financial Markets

Corporate Finance and Financial Markets focuses on how to structure, value, market and apply complex financial products in expanding global financial markets. You will learn to wield sophisticated trading and risk management strategies and engineer solutions to the host of financial problems faced by today’s institutions. As a student, you will learn a diverse array of skills to prepare you for wide-ranging positions in corporate financial analysis, financial planning, financial consulting, asset management, management consulting, private equity value creation and global financial advisory and foreign exchange trading.

Graduates of Corporate Finance and Financial Markets are expected to seek positions in financial management groups, on trading and arbitrage desks, in product structuring groups, in derivatives groups, in investment banking departments and in the information-technology firms that support the trading operations of financial institutions.


Curriculum Requirements:

  • 5 core courses, each 3 credits totaling 15 credits
  • Focus area and general elective courses within FRE and closely related fields personalized by the student, totaling 13.5 credits
  • 1 required applied lab worth 1.5 credits
  • 1 capstone experience of 3 credits
  • Capstone assessment (0 credits)
  • Bloomberg Certification (0 credits)

Total # of credits: 33

Highly Recommended Course:

  • Advanced Valuation Theory FRE-GY6273, 3 Credits

Consider the following courses to build an area of personal strength in Financial Markets and Corporate Finance.

  • Money, Banking and Financial Markets FRE-GY6031, 1.5 Credits
  • Extreme Risk Analytics FRE-GY6041, 1.5 Credits
  • Financial Econometrics FRE-GY6091, 1.5 Credits
  • Investment Banking and Brokerage FRE-GY6111, 1.5 Credits
  • Financial Market Regulation FRE-GY621, 1.5 Credits
  • Applied Derivative Contracts FRE-GY6291, 1.5 Credits
  • Econometrics and Time Series Analysis FRE-GY6351, 1.5 Credits
  • Corporate and Financial Strategy FRE-GY6361, 1.5 Credits
  • Contract Economics FRE-GY6371, 1.5 Credits
  • Mergers & Acquisitions FRE-GY6391, 1.5 Credits
  • Fixed Income Securities and Interest Rate Derivatives FRE-GY6411, 1.5 Credits
  • Behavioral Finance FRE-GY6451, 1.5 Credits
  • Credit Risk & Financial Risk Management FRE-GY6491, 1.5 Credits
  • Asset-backed Securities and Securitization FRE-GY6571, 1.5 Credits
  • Global Finance FRE-GY6671, 1.5 Credits
  • Quantitative Portfolio Management FRE-GY6711, 1.5 Credits
  • Selected Topics in Financial Engineering FRE-GY6951, 1.5 Credits
  • Algorithmic Portfolio Management FRE-GY7241, 1.5 Credits
  • Topics in Finance and Financial Markets I FRE-GY7801, 1.5 Credits
  • Topics in Risk Finance I FRE-GY7821, 1.5 Credits
  • Topics in Financial and Risk Engineering I FRE-GY7831, 1.5 Credits
  • Topics in Financial and Risk Engineering 2 FRE-GY7851, 1.5 Credits

Recommended Lab:

  • Financial Econometric Laboratory FRE-GY6821, 1.5 Credits

Computational Finance

Computational Finance emphasizes both financial quantitative theory and practice, bridging the two and using both the fundamental concepts of finance and the stochastic and optimization methods and software in finance. This focus is meant for those individuals with a strong desire to become quantitative financial managers or to pursue applied finance research interests in cutting-edge investment science, trading and in financial risk management. Techniques such as quantitative finance, financial econometrics, stochastic modeling, simulation and optimization are part of a set of financial tools applied to the many problems of derivatives and options finance, arbitrage trading algorithms, asset pricing, credit risk and credit derivatives, developing new derivative products and the many areas where quant finance has a contribution to make.

Graduates of Computational Finance will be qualified to work in pricing financial risk and their management, in credit risk and their derivatives, in cutting-edge institutions, in quant hedge funds and in research and advanced product development departments of financial and consulting firms. Graduates of Risk Finance will have the qualification and abilities to become responsible specialists for positions in finance, credit granting firms, banks and insurance companies, as well as obtain the knowledge needed to face the upcoming complex problems arising by the increased use and centrality of financial insurance products (contributing to the development of complex financial products and a convergence) of finance and insurance. The complementary actuarial profession is a discipline that uses tools from statistics, probability theory and finance to analyze and solve practical problems in insurance and financial risk management. Actuaries assemble and analyze data to estimate the probability and likely cost of an event such as death, sickness, injury, disability or loss of property. Courses in risk finance provide the background for the first four actuarial examinations supervised by the Society of Actuaries and the Casualty Actuarial Society and cover additional educational experience requirements.


Curriculum Requirements:

  • 5 core courses, each 3 credits totaling 15 credits
  • Focus area and general elective courses within FRE and closely related fields personalized by the student, totaling 13.5 credits
  • 1 required applied lab worth 1.5 credits
  • 1 capstone experience of 3 credits
  • Capstone assessment (0 credits)
  • Bloomberg Certification (0 credits)

Total # of credits: 33

Highly Recommended Course:

Options Pricing & Stochastic Calculus FRE-GY6233, 3 Credits

Consider the following courses to build an area of personal strength in Computational Finance.

  • Extreme Risk Analytics FRE-GY6041, 1.5 Credits
  • Numerical & Simulation Techniques in Finance FRE-GY6251, 1.5 Credits
  • Dynamic Assets and Options Pricing FRE-GY6311, 1.5 Credits
  • Financial Risk Management and Optimization FRE-GY6331, 1.5 Credits
  • Econometrics and Time Series Analysis FRE-GY6351, 1.5 Credits
  • Credit Risk & Financial Risk Management FRE-GY6491, 1.5 Credits
  • Quantitative Portfolio Management FRE-GY6711, 1.5 Credits
  • Selected Topics in Financial Engineering FRE-GY6961, 1.5 Credits
  • Special Topics in Financial Engineering FRE-GY6971, 1.5 Credits
  • Statistical Arbitrage FRE-GY7121, 1.5 Credits
  • Topics in Risk Finance I FRE-GY7821, 1.5 Credits
  • Topics in Financial and Risk Engineering I FRE-GY7831, 1.5 Credits
  • Topics in Financial and Risk Engineering 2 FRE-GY7851, 1.5 Credits

Recommended Labs (1.5 credits*):

  • Computational Finance Laboratory FRE-GY6831, 1.5 Credits
  • Financial Computing FRE-GY6883, 3 Credits

*FRE-GY 6883 counts both as a lab (1.5 credits) and as an elective (1.5 credits), totaling 3 credits.


Technology and Algorithmic Finance

Graduates of Technology and Algorithmic Finance are actively involved in the development and implementation of the entire spectrum of algorithmic trading strategies, software applications, databases and networks used in modern financial services firms. The techniques it applies bridge computer science and finance to prepare graduate to participate in large-scale and mission-critical projects. Applications include high frequency finance, behavioral finance, agent-based modeling and algorithmic trading and portfolio management.

Upon graduation, students of Technology and Algorithmic Finance will have developed software projects ranging from behavioral models to bespoke derivative valuations to financial trading, information management and tools and financial platforms. Students would be familiar with the use and role of technology in front, middle, and back offices; common trading strategies and how to implement and back-test them; and how to create new models and build new useful tools quickly.


Curriculum Requirements:

  • 5 core courses, each 3 credits totaling 15 credits
  • Focus area and general elective courses within FRE and closely related fields personalized by the student, totaling 13.5 credits
  • 1 required applied lab worth 1.5 credits
  • 1 capstone experience of 3 credits
  • Capstone assessment (0 credits)
  • Bloomberg certification (0 credits)

Total # of credits: 33

Highly Recommended Course:

Foundations of Financial Technology FRE-GY6153, 3 Credits

Consider the following courses to build an area of personal strength in Technology and Algorithmic Finance.

  • Extreme Risk Analytics FRE-GY6041, 1.5 Credits
  • Clearing and Settlement and Operational Risk FRE-GY6131, 1.5 Credits
  • Numerical & Simulation Techniques in Finance FRE-GY6251, 1.5 Credits
  • Behavioral Finance FRE-GY6451, 1.5 Credits
  • Derivatives Algorithms FRE-GY6511, 1.5 Credits
  • Financial Computing FRE-GY6883, 1.5 Credits
  • Statistical Arbitrage FRE-GY7121, 1.5 Credits
  • Forensic Financial Technology and Regulatory Systems FRE-GY7211, 1.5 Credits
  • Big Data in Finance FRE-GY7221, 1.5 Credits
  • Algorithmic Portfolio Management FRE-GY7241, 1.5 Credits
  • Algorithmic Trading & High-frequency Finance FRE-GY7251, 1.5 Credits
  • News Analytics & Strategies FRE-GY7261, 1.5 Credits
  • Topics in Finance and Financial Markets I FRE-GY7801, 1.5 Credits
  • Topics in Risk Finance I FRE-GY7821, 1.5 Credits
  • Topics in Financial and Risk Engineering I FRE-GY7831, 1.5 Credits
  • Topics in Financial and Risk Engineering 2 FRE-GY7851, 1.5 Credits

Recommended Labs (1.5 credits*):

  • R in Finance FRE-GY6871, 1.5 Credits
  • Financial Computing FRE-GY6883, 3 Credits

*FRE-GY 6883 counts both as a lab (1.5 credits) and as an elective (1.5 credits), totaling 3 credits.


Risk

Risk presents a comprehensive approach to managing risk in the context of globalized markets, financial compliance, multi-dimensional regulatory environments and industry convergence across the financial spectrum. This specialization will prepare you for a challenging career in risk finance, insurance, credit risk and derivatives or financial risk management.

Challenges faced by practitioners of risk include:

  1. Managing financial, extreme and cyber risks in an era of uncertainty and global markets in turmoil and out of equilibrium.
  2. Developing financial products that are robust and anti-fragile to value risks and allow the safe transfer and the securitization of risks to better access financial liquidity and financial risk exchanges.  Both, optional financial products such as credit derivatives and financial insurance products are introduced, priced and managed to prevent financial losses and to hedge trading bets.
  3. Corporate Finance Risk Management, embedded in financial risk management of banks and other industrial and financial institutions.
  4. Financial regulation to better comprehend the complexity and complying to multiple regulation agencies as well as global regulation currently at the forefront of financial authorities.
  5. Financial Analytics to better measure risks, price and manage trading risks in an environment where stealth trading, high frequency trading, uncertainty and multi-agents finance prevail.  In such an environment a greater appreciation of out-of-equilibrium (incomplete) finance, statistical tools, big-data finance and financial technology to track, assess and control become essential tools to engineer financial risk management.
  6. Market Risk Analytics in banks, investment management firms and hedge funds.
  7. Operational Risk Management to implement the company’s operational risk framework.
  8. Quantitative Model Risk and model validation including the implementation process, reviewing model standards, assessing risk mitigation policies and monitoring risk events.

The job opportunities open to graduates in Risk are expanding and may include jobs in Credit Risk, Derivatives and Management in Loan Firms and Banks, Insurance and their use of financial Instruments, Regulation, within Agencies with responsibilities over Financial Institutions

(such as the Treasury-The OCC, The SEC, etc.  As well as Compliance Management, in particular in the Banking sector, in Hedge Funds and in numerous Regulated Institutions, Investment and Hedge funds and Corporate Financial Risk Management.


Curriculum Requirements:

  • 5 core courses, each 3 credits totaling 15 credits
  • Focus area and general elective courses within FRE and closely related fields personalized by the student, totaling 13.5 credits
  • 1 required applied lab worth 1.5 credits
  • 1 capstone experience of 3 credits
  • Capstone assessment (0 credits)
  • Bloomberg Certification (0 credits)

Total # of credits: 33

Consider the following courses to build an area of personal strength in Technology and Algorithmic Finance.

  • Extreme Risk Analytics FRE-GY6041, 1.5 Credits
  • Insurance Finance and Actuarial Science FRE-GY6051, 1.5 Credits
  • Financial Econometrics FRE-GY6091, 1.5 Credits
  • Clearing and Settlement and Operational Risk FRE-GY6131, 1.5 Credits
  • Static and Dynamic Hedging FRE-GY6141, 1.5 Credits
  • Financial Market Regulation FRE-GY6211, 1.5 Credits
  • Actuarial Models FRE-GY6223, 3 Credits
  • Applied Derivative Contracts FRE-GY6291, 1.5 Credits
  • Financial Risk Management and Optimization FRE-GY6331, 1.5 Credits
  • Econometrics and Time Series Analysis FRE-GY6351, 1.5 Credits
  • Fixed Income Securities and Interest Rate Derivatives FRE-GY6411, 1.5 Credits
  • Credit Risk & Financial Risk Management FRE-GY6491, 1.5 Credits
  • Market Risk Management and Regulation FRE-GY6731, 1.5 Credits
  • Sp Tpc in Applied Credit Derivatives & Securitization FRE-GY6941, 1.5 Credits
  • Special Topics in Financial Engineering FRE-GY6971, 1.5 Credits
  • Topics in Risk Finance I FRE-GY7821, 1.5 Credits

Various special topics courses, as offered, including:

  • Extreme Risk &  Fractional Finance
  • Financial Cyber Risks Management
  • Topics in Real Time Trading & Risk Management   
  • Topics in Financial Risk Management    
  • Topics in Advanced Credit Risk and Derivatives   
  • Topics in Actuarial and Insurance Finance  
  • Topics in Financial Analytics and Big Data     
  • Topics in Financial Regulation and Compliance
  • Financial Risk Management and Incomplete Markets
  • Financial Risk Measurement 

Recommended Labs (1.5 credits*):

  • Students must choose one lab from the following:
  • Financial Software Laboratory FRE-GY6811, 1.5 Credits
  • Financial Econometric Laboratory FRE-GY6821, 1.5 Credits
  • Computational Finance Laboratory FRE-GY6831, 1.5 Credits
  • Financial Software Engineering LaboratoryFRE-GY6861, 1.5 Credits
  • R in Finance FRE-GY6871, 1.5 Credits
  • Financial Computing FRE-GY6883, 3 Credits

*Please note: for FRE-GY 6883, 1.5 credits count as lab and 1.5 credits as elective.