Financial Risk Modeling

Some time ago, Facebook announced that it would acquire Instagram, a photo sharing service, for $1 billion.  Facebook's analysis (its shareholders must hope) would have generated a range of potential valuations and how likely they were, factoring in uncertainties about how fast the user base will grow, how fast photo uploads will grow, what the advertising volume will be, how advertising can be priced, and more.

Estimates like this are arrived at via risk simulation to attach probabilities to sequences of potential outcomes and values.  Learn how to conduct and analyze such simulations in Huybert Groenendaal's "Financial Risk Modeling," an online course at Statistics.com.

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. Finally, the course will also cover common mistakes and how to avoid them.  The software used is ModelRisk, an Excel add-in; a license will be provided for the duration of the course. For more details please visit at http://www.statistics.com/financialrisk.

Aim 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 ModelRisk with the Insurance and Finance Module within Excel, but the lessons and techniques apply equally well to other modeling environments).

Who can take this course:

Anyone in investment banking, asset / investment / fund management, merchant banking, insurance companies, software / technology, government/public body and academia with an interest in applying quantitative probabilistic techniques in the fields of finance and insurance.

Course Program:

Course outline: The course is structured as follows

SESSION 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

SESSION 2: 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

SESSION 3: How to Deal with Correlations

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

SESSION 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)

Huybert Groenendaal is a Managing Partner at EpiX Analytics, which specializes in risk analysis and modeling techniques for clients around the world.  He consults on a broad range of projects that include forecasting, financial risk analysis, project costs estimation, valuation, portfolio evaluation in fields such as pharmaco-economics, epidemiology, inventory optimization, mining and transportation. Dr. Groenendaal teaches risk analysis in the executive MBA program at the Leeds School of Business, University of Colorado at Denver and at the school of Management at the University of Texas at Dallas.

Greg Nolder is a risk analyst with experience in computer hardware, pharmaceuticals, banking, finance, construction, mining, oil & gas, chemicals, consumer packaged goods, transportation and engineering. Of particular interest are systems involving stochastic optimization, general QRA and applying analytics to amateur and professional sports.

You will be able to ask questions and exchange comments with the instructors via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune (www.c-elt.com).

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com