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Program Description

The graduate program in statistics and biostatistics offers a master of science concentration in financial statistics and risk management (FSRM). This program is designed to meet the growing demand for financial statistics and risk management professionals.

Financial statistics is one of the emerging frontiers of statistics. As modern information technologies relentlessly generate voluminous and complex financial data, statistical theory and methodology have become indispensable to the financial industry. Statistical approaches based on empirical data have imposed themselves as a new generation of tools for arbitrage opportunities, performance predictions, risk exposure evaluation and management, portfolio management, asset evaluations, and the devising of novel financial products.

Risk management is an increasingly important subject in financial, industrial and regulatory sectors, in light of the global economy and the proliferation of innovative and complex risk management products. A successful risk management system incorporates expert knowledge from statistics, mathematics, finance, actuarial science, and computer science. Due to the interdisciplinary nature of the subject, it requires a special approach toward the training of the next generation of experts and leaders.

The FSRM program is designed to provide its graduates with a deep understanding of the nature of uncertainty, financial risks, and statistical properties of financial markets; a broad knowledge of established regulatory guidelines in risk management; strong technical skills for asset and portfolio analysis, risk evaluation, and management; and necessary communication and leadership skills for a successful career in financial statistics and risk management.

Students are encouraged to seek summer internships in the financial industry. A report on a suitable summer internship project can serve as the basis for the master's degree essay.

Students may pursue the degree full time or part time. Full-time students can complete the degree in three semesters and part-time students must complete their degree within five years. The minimum cumulative grade-point average required for graduation is 3.0 (B) for all courses taken at Rutgers after admission to the FSRM program.

It also is possible to apply for admission to FSRM as a nondegree student. As many as 12 credits of coursework taken as a nondegree student can count toward the degree if the student is subsequently admitted to the degree program.

Requirements

The requirements for the master degree in the FSRM program include completing 10 courses for a total of 30 course credits and an approved master degree essay. Among the 10 courses, eight are required courses and two are electives. Students may choose one of two tracks in the program: financial statistics or financial risk management. There is significant overlap in courses required for the two tracks.

Read more at: http://www.fsrm.rutgers.edu/program/reqs#ixzz1a276FHG4.

Required Courses for Financial Statistics Track:

FSRM 16:958:582� Methods and Theory of Probability with Financial Applications

FSRM 16:958:583� Methods of Statistical Inference with Financial Applications

FSRM 16:958:563� Regression Analysis in Finance

FSRM 16:958:565� Financial Time Series Analysis

Finance 22:390:589:61� Foundations of Finance (special section for FSRM)

FSRM 16:958:535� Advanced Statistical Methods in Finance

FSRM 16:958:587� Advanced Simulation Methods for Finance

FSRM 16:958:588� Financial Data Mining

Required Courses for Financial Risk Management Track:

FSRM 16:958:582� Methods and Theory of Probability with Financial Applications

FSRM 16:958:583� Methods of Statistical Inference with Financial Applications

FSRM 16:958:563� Regression Analysis in Finance

FSRM 16:958:565� Financial Time Series Analysis

Finance 22:390:589:61� Foundations of Finance (special section for FSRM)

FSRM 16:958:536� Financial Risk Evaluation and Management

FSRM 16:958:587� Advanced Simulation Methods for Finance

Finance 22:390:610� Risk Management and Insurance

Elective Courses:

Statistics 16:960:542� Life Data Analysis

Statistics 16:960:554� Applied Stochastic Processes

Statistics 16:960:567� Applied Multivariate Analysis

Computer Science 16:198:443� Advanced Programming for Financial�Applications (special section for FSRM)

Computer Science 16:198:513� Design and Analysis of Data Structures and�Algorithms I

Computer Science 16:198:514� Design and Analysis of Data Structures and Algorithms II

Computer Science 16:198:515� Programming Languages and Compilers I

Computer Science 16:198:516� Programming Languages and Compilers II

Computer Science 16:198:527� Computer Methods for Partial Differential Equations

Mathematics 16:642:623� Computational Finance

Mathematics 16:642:624� Credit Risk Modeling

Mathematics 16:642:625� Portfolio Theory and Applications

Electrical and Computer Engineering 16:332:503� Programming Methodology�for Finance

Economics 16:220:501� Microeconomics I

Economics 16:220:502� Microeconomics II

Economics 16:220:504� Macroeconomics I

Economics 16:220:505� Macroeconomics II

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