Financial Risk Modeling

Financial Risk Modeling 

taught by Huybert Groenendaal and Greg Nolder

 

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.

After completing this course, you will be able to:

  • Specify how a probability distribution is used in a financial model simulation
  • Characterize the different components of a time series (trend, seasonality, autocorrelation, volatility, mean reversion)
  • Fit various autoregressive models (ARCH, GARCH, more)
  • Use Markov chains in simulations
  • Work with multi-variate time series
  • Determine the correlation structure in time series
  • Fit appropriate probability distributions to historical data, and assess the fit (AIC, etc.)
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


WEEK 2:
Stochastic Time Series

  • Trend, volatility, seasonality, autocorrelaton, cyclicity, mean reversion
  • GBM, +mean reversion, jump diffusion, 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


WEEK 3:
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:

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.
Level:
intermediate/advanced
Prerequisite:
  • 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:
Options for Credit and Recognition:

Specialization:
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 Statistics.com 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.

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.

Software:
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.
Instructor(s):

Dates:

June 14, 2019 to July 12, 2019 June 12, 2020 to July 10, 2020

Financial Risk Modeling

Instructor(s):

Dates:
June 14, 2019 to July 12, 2019 June 12, 2020 to July 10, 2020

Course Fee: $589

Do you meet course prerequisites? What about book & software? (Click here to learn more)

We have flexible policies to transfer to another course, or withdraw if necessary (modest fee applies)

Group rates: Click here to get information on group rates. 

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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