Financial Risk Modeling
Dr. Huybert GroenendaalAim of Course:
This course 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 Crystal Ball with Excel, but the lessons and techniques apply equally well to other modeling environments). The course will finally also cover common mistakes and how to prevent making them.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.For those enrolled in a Program of Advanced Statistical Studies, this is a required or elective course in the following Programs:
- Statistics in Business & Marketing - elective
Course Program:
The course is structured as followsSESSION 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
- 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
- Rank order
- Covariance measures
- Copulas
- Example model and exercise
- 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)
The Instructor:
Dr. Huybert Groenendaal is a Partner at Vose Consulting. For over two decades, Vose Consulting has provided clients worldwide with the highest quality risk analysis techniques and methods. Dr. Groenendaal helps and consults clients in industry and government on projects that include financial investment evaluations, project risk analysis, forecasting, operations, transportation logistics, epidemiology and more. A list of past experience and clients of Vose Consulting can be found here. Dr. Groenendaal also organizes and teaches "Quantitative Risk Analysis", "Project Risk Analysis", and "Corporate Risk Analysis" courses and workshops worldwide and has taught on risk analysis in the executive MBA program of the University of Texas at Dallas.Organization of the Course:
The course takes place over the internet, at statistics.com. 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. The course is scheduled to take place over 4 weeks, and typically requires 15 hours per week. 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 and work through exercises. Discussion among participants is encouraged. The instructor will provide answers and comments.Certificates and Grades:
You may be interested only in learning the material presented, and not be concerned with grades or certificates. Or you may be enrolled in a statistics.com Program in Advanced Statistical Studies that requires demonstration of proficiency in the subject, in which case your work will be assessed for purposes of issuing a grade. Or you may require only a "Certificate of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's). As you begin the class, you will be asked to specify your category.Credit:
This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a certificate will be issued by statistics.com, upon request.Dates:
Oct. 30 - Nov. 27, 2009Click here to be notified of future course offerings.
Participants gain access to the online materials on the first day of the course, and typically spend about 15 hours per week (at their convenience). You retain full access to course materials, including discussion board, for two weeks after the course closing date.
Level:
intermediate/advancedPrerequisite:
The equivalent of Introduction to Statistics 1: Inference for a Single Variable, and Introduction to Statistics 2: Working with Bivariate Data (and, if necessary before these courses, Introduction to Statistics for Beginners or Survey of Statistics for Beginners). All models are developed using Excel, Crystal Ball and ModelRisk for Insurance and Finance. It is therefore essential that all participants are reasonably proficient in Excel. Furthermore, some basic understanding of risk anaylsis is required, akin to the "Introduction to Quantitative Risk Analysis" course.Course Text:
Course Text: Course participants will be provided with weekly digital reading material, as well as the required course text. This text is available online at click here. If you have any problems viewing the text email info {at} vosesoftware.com. Note that this training package/online book is separate from the two (free) course software packages (see note about Crystal Ball below). There is also an optional recommended text, for those needing to retain a reference book after the course: Risk Analysis: A Quantitiative Guide by David Vose, from Wiley. Wiley typically offers statistics.com customers up to 15% discount on this book (and all other statistics titles): enter the code aff15 in the Promotion Code field when prompted during checkout and click the Apply Discount button. (If you are located in Asia, the web procedure for your location may not accept this discount -- try calling your regional Wiley representative.)Software:
Course illustrations and homework assignments will use ModelRisk for Insurance and Finance, the financial risk analysis tool made by Vose Software (www.vosesoftware.com) together with Crystal Ball (r), the risk analysis and simulation Excel add-in made by Oracle (www.crystaball.com). A limited time free demo license of both ModelRisk for Insurance and Finance and of Crystal Ball will be provided to all course participants at the start of the course.Registration:
Register Online - $469Register Online (academic) - $369 (you must be affiliated with a college, university or high school)
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.
Note: Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.
| © statistics.com 2004-2009 | Privacy Policy | Contact Us |