Applied Monte Carlo Simulation in Finance

2 Day Workshop
(Workshop is not being offered at this time)

Qualifies for Continuing Education Credits:

• NASBA CPE - 19.2
• CFA CE - 16
• ACCA CPD

Who Should Attend?

What will you get out of this Workshop?

• Gain a detailed understanding of Monte Carlo simulation and its application to financial problems

• Understand the general simulation framework, interpretation, analysis of results, strengths and weaknesses

• Learn about the practical application of the Monte Carlo simulation to financial problems such as Value-at-Risk and portfolio selection

• Practical Excel implementations that delegates will be able to reference after the workshop

Content

Attendees need to bring their own laptops. Vose Consulting will provide download links to have Model Risk software trial license, which will be used during the course.

The course will also feature a guest speaker to attend the course and teach practical application of Monte Carlo Simulation in Finance.

Practical and Hands-on Delegate Participation

During the intensive and interactive workshop, the course leaders will cover and practice several examples, including a selection from the following according to participants’ interest

• Some time-series examples (including fitting to past financial datasets)
• Analyzing correlations between stochastic variables, fitting copulas and applying them in a simulation model
• Insurance aggregate portfolios
• Basel II example with operational risk
• Markov Chain model example (for modeling credit portfolios)
• VAR, expected shortfall examples
• Analysis and simulation of extremes using order statistics techniques

Overview of Monte Carlo

1. What is a distribution
2. How scenarios are generated?
3. What outputs are produced?
4. How do you analyze the data?
5. Why it works

Distributions

1. Most common univariate distributions in finance and insurance
2. The stochastic processes behind them
3. Example model and group exercise

Aggregate distributions

1. By Monte Carlo simulation
2. By construction: Panjer, De Pril, FFT
3. Method of moments (MoM) approximations
4. Correlating aggregate variables

Stochastic time series

1. Trend, volatility, seasonality, autocorrelation, cyclicity, mean reversion
2. GBM, + mean reversion, jump diffusion, both, seasonality
3. Autoregressive models: ARCH, GARCH, EGARCH, APARCH
4. Markov chains
5. Discussion of attributes and application of different stochastic time-series
6. Example model and group exercise

How to deal with correlations

1. Rank order
2. Covariance measures
3. Copulas
4. Example model and group exercise

Fitting

1. Distributions (MLE, MoM)
2. Time-series (MLE)
3. Copulas (MLE)
4. Fit comparisons with information criteria (i.e. AIC, SIC, HQIC)
5. Example model and group exercise

Insurance risk

1. Premium determination
2. Ruin and depletion models

Good modeling practices, common mistakes and how to avoid them

1. Common mistakes with aggregate distributions
2. Representing uncertainty twice
3. Example models and group discussion

Attendees are requested to ensure that they bring their fully charged laptops, with the following applications included

1. MS Excel
2. a trial or full license of @RISK (standard or above, see www.palisade.com)
3. a trial or full license of ‘ModelRisk for Insurance and Finance’ (see www.vosesoftware.com).

Please note there are a number of exercises and practical examples throughout the course. GARP will not be able to provide laptops for these exercises.