Financial Risk Modeling

Financial Risk Modeling 

taught by Huybert Groenendaal and Greg Nolder


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Aim of Course:

This online course, "Financial Risk Modeling" will cover the most important principles, techniques and tools in Financial Quantitative Risk Analysis. The course has been developed to effectively combine theoretical sessions with classroom examples and exercises in order to provide students with a comprehensive analysis of Monte Carlo techniques. In addition to discussions of recent innovations in the application of Monte Carlo methods, the course will cover many practical examples, case studies and interactive sessions.

The course will also get the participants comfortable with risk analysis modeling environments (in this case ModelRisk with the Insurance and Finance Module within Excel, but the lessons and techniques apply equally well to other modeling environments). Finally, the course will also cover common mistakes and how to avoid them.

This course may be taken individually (one-off) or as part of a certificate program.
Course Program:

WEEK 1: Introduction

  • Introduction to quantitative risk analysis and Monte Carlo
    • Core ideas of risk analysis
    • What is a probability distribution
    • How scenarios are generated, outputs produced and analyzed, why it works
  • Distributions
    • Most common univariate distributions in finance
    • Introduction to statistical descriptors-mean,mode,standard deviation,skewness,kurtosis
    • Example financial model and exercise

Stochastic Time Series

  • Trend, volatility, seasonality, autocorrelaton, cyclicity, mean reversion
  • GBM, +mean reversion, jump diffusioin, both, seasonality
  • Autoregressive models: ARCH, GARCH, EGARCH, APARCH
  • Markov chains
  • Multi-variate time series
  • Discussion of attributes and application of different stochastic time series
  • Example model and exercise

How to Deal with Correlations

  • Rank order
  • Covariance measures
  • Copulas
  • Example model and exercise

WEEK 4: Model Fitting and Conclusion

  • Fitting distributions, time series and copulas to historical data
    • Distributions (MLE)
    • Time series (MLE)
    • Copulas (MLE)
    • Fit comparisons with information criteria (i.e. AIC, SIC, HQIC)
    • Example model and exercise
  • Emphasis on examples model and practical case
    • VAR, expected shortfall examples
    • Some time series examples (including fitting to past financial datasets)
    • Analyzing correlations between stochastic variables, fitting copulas and applying then in a simulation model
    • Basel II example with operational risk
    • Markov Chain model example (for modeling credit portfolios)


Homework in this course consists of short answer questions to test concepts, guided data analysis problems using software, and guided data modeling problems using software.

In addition to assigned readings, this course also has supplemental readings available online, and an end of course data modeling project.

Financial Risk Modeling

Who Should Take This Course:
Anyone in investment banking, asset/investment/fund mangement, merchant banking, insurance companies, software/technology, government/public body and academia with an interest in applying quantitative probablilistic techniques in the fields of finance and insurance.
  • Risk Simulation and Queueing
  • All models are developed using Excel and ModelRisk. It is therefore essential that all participants be proficient in Excel, including the use of Excel functions.
Organization of the Course:

This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Options for Credit and Recognition:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
  1. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. Certificate - You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. CEUs and/or proof of completion - You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course,  CEU's and a record of course completion will be issued by The Institute, upon request.
  4. Other options - Specializations, INFORMS CAP recognition, and academic (college) credit are available for some courses

Specializations are an easy way for you to demonstrate mastery of a specific skill in statistics and analytics. This course is part of the Optimization Specialization which discusses linear programming, nonlinear programming, network flow, decision analysis, queuing, simulation.  Take any three of the four courses on this topic (this course, plus the courses listed to the right under "related courses," not including conferences).  For savings, use the promo code "optimize-specialization" and register for all three courses at once for  $1197 ($399 per course, not combinable with other tuition savings).  If you register for all four, you'll still receive the discounted rate.

College credit:
Financial Risk Modeling has been evaluated by the American Council on Education (ACE) and is recommended for the graduate degree category, 3 semester hours in finance or econometrics. Note: The decision to accept specific credit recommendations is up to each institution. More info here.

This course is also recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam, and can help CAP® analysts accrue Professional Development Units to maintain their certification .
Course Text:

Course participants will be provided with weekly digital reading material, as well as the required course text once enrolled in the course. Though completely optional and not required, the following texts are recommended as additional resources  that will give more in-depth understanding of the model as well as instruction for building good and practical models.

Practical Spreadsheet Risk Modeling for Management by Lehman, Groenendaal and Nolder, from CRC Press. This textbook is intended for those new to risk analysis. It features case studies and real world examples and is bundled with a 120 day license for ModelRisk.  It can be ordered directly from the publisher; use promo code 194CM for a 20% discount.

Risk Analysis: A Quantitiative Guide, 3rd Edition by David Vose, from Wiley. This new edition includes more than 150 example models in Excel and 400 illustrations as well as a 90 day license of ModelRisk.

Course illustrations and homework assignments will use ModelRisk, the Monte Carlo simulation and financial risk analysis tool from Vose Software. A limited time free trial license of will be provided to all course participants at the start of the course.


To be scheduled.

Financial Risk Modeling


To be scheduled.

Course Fee: $589

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