KEYNOTE: Modelling Uncertainty: The Good,The Bad & The Ugly

Dr. Dale F Cooper
Broadleaf Capital International

Modelling uncertainty is difficult. Tools like @RISK are easy to use, but getting reliable and justifiable outcomes takes more than a good tool. This talk will address some of the modelling pitfalls we see in our risk consulting activities, explore how and why they arise, and suggest some solutions. The focus will be on the way models are intended to support decision making and their effectiveness in doing this.

Overview of @RISK 5.0 and DecisionTools Suite 5.0
Sam McLafferty
Palisade Corporation

This major upgrade to @RISK and the DecisionTools Suite is driven by the latest innovations in the field and by customer input, as well as attention to the improvements with Excel 2007. Sam will highlight the most prevalent of the new software innovations, including a tour of the stunning new @RISK user interface that is completely integrated into the spreadsheet environment. The discussion will also address how @RISK 5.0 is designed to better meet the needs of corporate-wide sharing, and how it offers more robust analyses.

Building a Better Process to Support Executive Decision Making

Jay Horton
Strategis Partners

Many senior executives know only two degrees of probability, zero and one, while business analysts know every degree of probability except zero and one. So how do we bridge the knowledge gap? Quantitative decision support software and techniques have gone through a remarkable development over the past 20 years. However this has not necessarily led to sustained improvements in the quality of decision making in companies that have adopted these tools. Jay’s talk will draw upon his 20 years of experience consulting to senior executives on business decisions to explain how you can build a better process to support executive decision making. This involves understanding of the realities of how organisations make decisions, anticipating the needs of the decision maker, and overcoming inherent biases in decision making.


@RISK 5.0 Advanced Topics Discussion

Sam McLafferty
Palisade Corporation

Have questions after seeing the overview of the all-new @RISK 5.0? Want to know how @RISK 5.0 can apply to your specific modelling issues? Or, do you just simply want to learn more about @RISK 5.0 than we had time to cover in the overview? This session will cover more advanced features of @RISK 5.0 and provides a forum for questions and answers.

Modeling Correlation and VAR of Swaps

Dr. Nitin Singh
Indian Institute of Management Indore

Industry Focus: Finance
Product Focus: @RISK, StatTools

This presentation will show how swap was valued and how the volatility of swap was measured through simulation using @RISK. We have also proceeded to perform initial diagnostics on time series data and computed variance-covariance matrix using StatTools. As a spin-off, we learned how volatility of swap depends on the variance-covariance structure of the zero prices. We begin the analysis by estimating zero-coupon bond prices: First we consider cash flows of the swap in different time periods. Next, we value the swap by computing the present value of each leg and taking the difference between two values. The value of the floating leg is determined since the next floating coupon is known and we dealt with generic interest-rate swap. The present value of the floating-leg is calculated by pricing the swap over time. Thereafter, VAR is calculated using simulation by @RISK. We find cumulative probability for each change in Call Value and compute VAR for a 99% confidence level. Interestingly, we find that volatility of swap and VAR depends on the variance-covariance matrix of the zero prices.

Modelling Sheep Population and Wool Production in Australia

Kimbal Curtis
Department of Agriculture and Food, Western Australia

Industry Focus: Agriculture
Product Focus: NeuralTools, @RISK

Many business planning decisions are based on forecasts of future industry conditions. The sheep and wool industry in Australia and the down stream wool processors around the world are no different. A key input to their decision making is a forecast of expected wool production, and as Australia dominates the supply of traded raw wool, Australian forecasts are of utmost importance.

Single point forecasts do not assist businesses to assess risk forcing contingencies to be adopted. Provision of confidence limits allows assessment of both lower and higher than expected production.

This presentation will outline a simplified deterministic flock demographic model of the Australian sheep population. The process undertaken to convert it to a stochastic model capable of improving forecasts will be described. Sensitivity analyses were used to identify which inputs to vary, and where most effort should be applied in collecting reliable input statistics.

Real Options Valuation in Property Leases and Deriving Value from Inherent Volatility

Dr. Colin Beardsley
Risk-Return Solutions Pty Limited

Industry Focus: Real Estate
Product Focus: @RISK

Real options analysis draws from financial markets by developing a framework for valuing flexibility in decision making which adds to traditional discounted cash flow (DCF) methodology. This case study uses @RISK Monte Carlo simulation to value the real options inherent in long term property leases and how volatility can increase real estate value.

Real-World Applications of NeuralTools

Kimbal Curtis and Mark Meurisse

NeuralTools is a powerful Excel add-in that uses neural network technology to make powerful predictions in any spreadsheet model.  The presenters will cover three specific real-world case studies where NeuralTools has been used effectively: in business, in medicine, and in disaster response. 

Kimbal Curtis will discuss how NeuralTools predicted the market price of wool for the Western Australia Department of Agriculture.  Mark Meurisse will cover the use of NeuralTools for cardiovascular disease risk assessment.  He will also describe how NeuralTools was used to predict call volume for a disaster response center after Hurricane Katrina.

Risk Analyses on a Wind Farm Project

William Zhu
WEL Networks Ltd

Industry Focus: Energy
Product Focus: @RISK, PrecisionTree

A wind power generation project is valuated based on Discounted Free Cash Flow (DFCF) method. Key risk factors, including revenue associated (e.g., the amount of electricity generated by wind and electricity spot prices), capital expenditure associated (e.g., the NZ exchange rate linked to the imported wind turbines), and operating expenditure associated (e.g., CPI and PPI fluctuation), are identified. By utilising @RISK software, the model discusses the following issues in detail:

  • Distributions for the key input factors are fitted (especially for wind speed, electricity spot prices, and NZ exchange rates)
  • Correlation constraints are added for some of the risk factors to capture the inter-relationships among them
  • Both deterministic and stochastic sensitivity analyses are compared and discussed
  • Different scenarios are investigated by using advanced @RISK techniques (including goal seek, stress, and sequential analyses)
  • The scenario results are summarized by using a simple decision tree diagram.

This model uses Excel Macros, which incorporates numerous @RISK functions, to display the results and plot the graphs, so that users can run the model smoothly with little @RISK knowledge. It is also easy to convert this case study into a general business valuation model with minor modification.

Some Challenges and Solutions in the Application of Monte Carlo Risk Modelling to Health Risk Assessment in the Water Industry

Dr. David Roser
University of New South Wales, Centre for Water and Waste Technology

Industry Focus: Environment
Product Focus: @RISK

Quantitative risk techniques such as quantitative microbial risk assessment ( QMRA) are being increasingly applied to environmental and health impact/risk assessment. The introduction of QMRA is being driven by new inter/national guidelines, the availability of modelling tools like @RISK, and the need for assessments to account for the variability and uncertainty in environmental data such as water quality measurements. The CWWT uses QMRA to support its water and waste management projects and has found that QMRA risk modelling has a range of benefits. It facilitates an ‘holistic’ integration of hazard, dose response, and exposure pathway assessments central to health risk characterisation. Hazard ‘Exposure Pathway’ construction with QMRA in mind leads automatically to the identification of essential submodel inputs and major data gaps, and hence priorities for new experimental work and literature searches.

CWWT has constructed large numbers of models varying slightly but significantly in their assumptions, necessitating the development of ‘metamodelling’ and rigorous data management. Simulation of the impacts of infrequent ‘hazardous events’ has at times been impractical because of the large numbers of simulations required. And the visual complexity of CWWT models makes communication of modelling details to senior managers challenging. This presentation will outline how we have undertaken health risk modelling with @RISK using QMRA and water industry examples.  We will discuss its strengths and identify how to address the above constraints both in model construction and using @RISK.


Bridging Analytics & Decision Making

Jay Horton
Strategis Partners

This roundtable forum is a wide-ranging, speakeasy discussion among participants interested in gaining greater insight into the human processes involved with using data to make decisions. The discussion may range from model development to presentation. Facilitating the discussion is Jay Horton, widely acclaimed as an expert in the field of organisational strategy.

Practical Business Applications for Real Options

Dr. Colin Beardsley
Risk-Return Solutions Pty Limited

This forum is a wide-ranging, speakeasy session among participants interested in the valuation techniques of and approaches to real options analysis. Attendees may broach this topic from any angle of their choosing, e.g., research and development, mergers and acquisitions, property leasing, or licensing to name a few. Facilitating the discussion is Dr. Colin Beardsley, widely acclaimed as an expert in the field.


DecisionTools Suite Refresher
Mark Meurisse
Palisade Asia-Pacific

This presentation will show you how to integrate the elements of the DecisionTools Suite into a complete risk program. PrecisionTree will help identify the model and decision analysis that needs to be done, as well as provide an efficient and effective way of presenting the results. We will use TopRank to set us on the right path to creating a probabilistic model out of a deterministic one. @RISK (including BestFit and RISKview) adds the uncertainty to the model and runs the Monte Carlo simulations required for effective risk analysis. RISKOptimizer produces the values for decision variables in your model optimise your required outcome.

Introduction to @RISK 5.0
Rishi Prabhakar and Mark Meurisse
Palisade Asia-Pacific

Try @RISK 5.0 yourself!  This hands-on introduction will briefly recap the main benefits and uses of risk analysis before walking you through key new features in @RISK 5.0.  You will experience the all-new interface as you define distributions, compare distributions using overlays, fit distributions to data, and correlate input distributions.  See firsthand how large models can be simplified by combining distributions in a new @RISK function.  Add distributions to and draw distributions from the new @RISK Library.  Define Six Sigma properties in your outputs.  Review and edit your entire model in the new @RISK Model window.  Swap distributions out for non-@RISK users using the new Function Swap feature, edit your model, and swap them back in again.  Simulate in the new Demo Mode  and watch all charts, thumbnails, and reports update in real time.  View results using the new graphing engine, Scatter Plots, Box Whisker Plots, and Tornado Regression – Mapped Value charts.  Store simulation results in the @RISK Library or your workbook.  There is so much to see, we’ll cover as much as time permits.

Introduction to Evolver/RISKOptimizer

Rishi Prabhakar
Palisade Asia-Pacific

Evolver and RISKOptimizer use powerful genetic algorithms to perform optimisation in Microsoft Excel. RISKOptimizer builds on traditional optimisation by adding Monte Carlo simulation to account for uncertain, uncontrollable factors in your optimisation problem. This session introduces you to these powerful tools, showing you how to set up a model, define constraints within the model, and ultimately arrive at the optimal outcome. Examples including resource allocation, budgeting, and scheduling will be included.


Introduction to NeuralTools and StatTools

Rishi Prabhakar
Palisade Asia-Pacific

In this session we will learn how to use Palisade’s two data analysis tools: NeuralTools and StatTools.

NeuralTools imitates brain functions in order to “learn” the structure of your data. Once NeuralTools understands the data, it can take new inputs and make intelligent predictions. The new predictions are based on the patterns in known data, and offer uncanny accuracy. NeuralTools can automatically update predictions when input data changes, and it can even be combined with Palisade’s Evolver or Excel’s Solver to optimise tough decisions and achieve desired goals.

StatTools is a Microsoft Excel statistics add-in. This session will cover how to perform the most common statistical tests, and will include topics such as: Statistical Inference, Forecasting, Data Management, Summary Analyses, and Regression Analysis.

Introduction to PrecisionTree 5.0

Mark Meurisse
Palisade Asia-Pacific

This presentation combines an introduction of the enhanced user interface, tighter Excel integration, and new features of PrecisionTree 5.0, with demonstrations of how PrecisionTree can be used to analyse various problems in decision analysis.

Oil, Gas, and Mining Applications of the DecisionTools Suite

Mark Meurisse
Palisade Asia-Pacific

This session will focus on demonstrating or building basic oil and gas modelling applications using @RISK and PrecisionTree. Models in the areas of reserves estimation, portfolio modelling, production decline modeling, and drill testing will be covered.

Project Management Applications of @RISK and @RISK for Project

Mark Meurisse
Palisade Asia-Pacific

Project management applications of risk and decision analysis using palisade tools spans across industries, as well as across commercial and government sectors. This session will present key applications which are common to project management interests regardless of discipline. Core models of cost estimation and scheduling will be presented as well as a look into considerations such as phasing and real options in project management.

Selecting the Right Distribution
Rishi Prabhakar
Palisade Asia-Pacific

How often have you looked at the palette of distributions in @RISK and related tools and wondered which one you should use? A crucial aspect of risk modeling is the selection of the appropriate distribution to use to represent key uncertain variables. @RISK offers a wealth of probability distributions – some are very intuitive like the Uniform and Triangular, others are somewhat familiar to anyone with a scientific, engineering, or finance background, like the Normal and Lognormal. However, many of the other distributions offered in @RISK give us access to sophisticated probability thinking that can greatly extend and simplify your risk models.

This session will explain, in simple terms and illustrated with example models, the thinking behind the most powerful distributions, what they model, and how they can be put to use in your risk analyses.




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