New Dates to be Announced

Monte Carlo simulation continues to be the preferred tool for stress testing a business under risk. Simulation is experiencing a renewed interest by effective decision makers, due to the perception of increased risk in business and the widespread availability of computers. The power of Excel can be extended to develop and use Monte Carlo simulation models for making better business and policy decisions.

Simulation and Econometric Models for Probabilistic Forecasting and Risk Analysis is a three day workshop designed to teach analysts, who are familiar with Excel and basic statistics, (a) how to develop probabilistic forecasts, (b) simulate multivariate probability distributions, (c)develop a business model in Excel, (d) how to incorporate risk and probabilistic forecasts into business models to analyze alternative risky scenarios, and (e) how to use the risk ranking tools included in Simetar to rank risky scenarios. Dr. Richardson uses more than a dozen in-class exercises so the participants can gain valuable hands-on experience analyzing data, estimating parameters for probability distributions, simulating random variables, building and validating simulation models, and ranking risky alternatives using state-of-the-arts decision analysis techniques.

Simetar©, Simulation & Econometrics to Analyze Risk, is an Excel add-in designed, developed, and used by Richardson, Schumann, and Feldman at Texas A&M University to facilitate developing, validating, and using complex stochastic simulation models in Excel for decision making. Simetar provides menu driven dynamic functions for econometric data analysis, parameter estimation, probabilistic forecasting, simulation of univariate and multivariate random variables, validation/hypothesis testing, graphical display of risk results, and ranking risky scenarios using alternative utility functions. A free copy of the Simetar Users Manual and a trial copy of Simetar are available by contacting Simetar, Inc. at [email protected] or by going to the Simetar web site at www.simetar.com

Dr. Richardson and his associates are in high demand to teach simulation modeling workshops to risk analysts around the world, teaching more than 30 workshops in the past 10 years. Past participants are applying their new risk analysis skills at government agencies, universities, research centers, consulting firms, and private businesses around the world.

The registration fee for the Workshop is $1,450 and includes a Single User License for Simetar. The registration fee for owners of a Simetar license is $1,050.

College Station is about 90 miles from the Austin, Texas airport and about 90 miles from the Houston Intercontinental airport. All major airlines service the Austin and Houston airports.

If you have problems making accomodation reservations, contact us at [email protected]

Day 1: Simetar Tools for Data Analysis, Statistics, Regression, and Simulation of Random Variables – 8:00-5:00
• Introduction to risk analysis and simulation
• Data analysis tools in Simetar
• Forecasting with econometric and times series tools in Simetar
• Simulating univariate random variables
• Steps for developing stochastic simulation models
• Steps for developing probabilistic forecasting models using regression, moving averages, exponential smoothing, and seasonal/cyclical analysis
• Simulating business risk
• Graphical tools for displaying simulation results

Day 2: Simulating Correlated Random Variables and Statistical Tests for Model Validation – 8:00-5:00
• Parameter estimation for univariate distributions and picking the best distribution for simulating a random variable
• Simulating multivariate probability distributions for normal and non-normal probability distributions using Simetar
• Statistical tests and tools in Simetar for validating random values generated for univariate and multivariate probability distributions

Day 3: Determining the Best Risky Alternative and Applications of Simulation to Business and Policy Decisions – 8:00-12:00
• Scenario and sensitivity analysis under risk
• Analyzing simulation results to determine the best risky alternative using interactive graphical and quantitative analysis tools in Simetar
• Last three hours are for discussing advanced simulation topics, from the following list:
o Project management, financial risk analysis, bid analysis,
o Capital investment analysis: net present value and benefit/cost,
o Stochastic programming and optimal control theory,
o Probabilistic forecasting, inter-temporal correlation,
o Portfolio analysis, inventory management, time series analysis,
o Insurance premium estimation, logit and probit regression,
o Bootstrap simulation for estimating confidence intervals in regression, and
o Methods for dealing with large multivariate probability distributions.

Participants receive a copy of the latest Simetar, the Simetar User’s Manual, Dr Richardson’s Simulation text, “Simulation for Applied Risk Management,” and a copy of the workshop overheads. A jump drive with more than 100 demonstration programs and copies of all in-class problems covered in the Workshop will also be provided to the participants.

Participants will complete more than 20 in-class problems. Over the course of the workshop participants will experience the full cycle of model design, parameter estimation, forecasting, simulation of random variables, model validation, programming and validating pro forma financial statements, and ranking risky scenarios for decision making. Through the in-class problems, participants learn how to apply the workshop principles and Simetar to build and use a simulation model for decision making. To facilitate learning, each person must have their own micro computer running Microsoft Windows 2010 or higher with Excel (2010, 2013, or 2016).

If you are interested in attending the Workshop on Simulation and Econometric Models for Probabilistic Forecasting and Risk Analysis, please contact James Richardson at [email protected] to register.

Topics Covered During Days 1 and 2

Overview and Introduction
Introduction to Statistics and Simetar
Simetar Tools for Data Analysis
Simetar Tools for Regression and Forecasting
Univariate Distributions and their Simulation
Univariate Parameter Estimation
Picking the Best Distribution
Steps for Model Development
Steps for Probabilistic Forecasting
Stochastic Simulation
Simulating Business Risks
Multivariate Probability Distributions
Model Validation

Topics Covered During Day 3 

Scenario Analysis
Sensitivity Analysis
Ranking Risky Scenarios
Developing CDFs, PDFs, and Other Risk Charts
Presenting Simulation Results
Develop a complete simulation model from the ground up

Advanced Multiple Regression: df Betas, Logit, and Probit
Business Decision Models
Project Management
Developing Bids Under Risk
Project Feasibility
Inventory Management
Capital Investment Analysis
Probabilistic Forecasting
Portfolio Analysis Under Risk
Futures and Options for Risk Management
Financial Risk Management
Product Adoption
Inter-Temporal Correlation
Optimal Control
Bootstrap Sampling and Regression
Simulation and Insurance Premiums
Simulating Farm Program Payments
Times Series Model Estimation and Forecasting
Methods for simulating very large multivariate probability distributions
Simetar Installation