Decision Making Under Uncertainty

How is quantitative modelling applied to today's risk analysis problems in finance, insurance, oil and gas, manufacturing, and more? Monte Carlo Simulation is the key.  In this blog, we'll discuss the latest tips and techniques to help you judge which risks to take and which to avoid, allowing for the best decision making under uncertainty.

The legacy of apartheid in South Africa has left much of the country without basic services such as housing, water and electricity. The government initiatives in place to tackle the issue do not have enough resource to meet the scale of the need so commercial finance programmes will play a key role in delivering these services.  But poor planning without enough information makes it difficult to recoup the costs of a project, thereby making it unattractive to potential commercial financers – in other words, ‘unbankable’.  

For example, an engineer might design a high-specification water system.  However, the focus on design may make it over-complex and therefore expensive – with the end result that it does not meet the needs of the community, the government or the financing organisation.

Bigen Africa, a consulting company that describes itself as a ‘development activist’, tackles this issue with risk analysis.  It uses @RISK as a tool to enable it to identify, manage and mitigate the risk associated with each project and ensure it attracts funding and is successful.

@RISK risk modeling software helps Bigen Africa to understand and demonstrate that it is the number and type of houses that drives the demand for services, where this demand is, what it will be in the future and who will use the services.  It forms the basis of engineering / planning, the financial risk analysis model, the revenue model and strategy, affordability analysis and the integration between the services (housing, roads, solid waste, water, sanitation, electricity, etc).

@RISK provides the level of detail that banks require before making a decision on whether to finance a project.  At the same time, the methodology benefits from simplicity and is easily understood by the wider audience involved in the project but not necessarily familiar with the specific concept of demand risk.

» Case Study: Bigen Africa uses @RISK to encourage funding for basic community services in South Africa

Join us this Thursday, April 26, 2012, for a free live webcast entitled, "Multi-Dimensional Project Portfolio Optimization and @RISK" to be presented by Eric Torkia.

Many speak of organizational alignment, but how many tell you how to do it? Others present only the financial aspects of portfolio optimization but abstract from how this enables the organization to meets its business objectives.  We are going to present a practical method that enables organizations to quickly build and optimize a portfolio of initiatives based on multiple quantitative and qualitative dimensions: Revenue Potential, Value of Information, Financial & Operational Viability and Strategic Fit.
         
This free live webcast is going to present these approaches and how they can be combined to improve both tactical and strategic decision making. We will also cover how this approach can dramatically improve organizational focus and overall business performance.

We will discuss these topics as well as present practical models and applications using @RISK.

Discussion Topics

•     Optimization Basics
  • Typical Optimization Applications
  • What is non-linear stochastic optimization
  • Objectives and constraints - things to know about optimization
•     Quick Overview of Portfolio Theory
  • Overview of conventional portfolio methods (financial, strategic, IT...).
  • Markowitz and the efficient frontier
  • Viability/Fit method
•     Optimizing with value of information and other critical dimensions
  • What is value of information (VOI)
  • How can VOI and portfolio methods be used to improve decision-making
  • How does the VOI impact portfolio decisions
•     Building and running the model
  • Overview of the components of the portfolio model
  • Run a quick optimizations using different dimensions and discuss results
  • Questions and Answer Period

Eric Torkia MASc is a senior management consultant/trainer and business analyst.  He has collaborated with some of the world's most recognized organizations to ensure the optimal design and delivery of enterprise systems, analytics as well as new forecasting and decision making processes.

Eric combines a unique set of skills and competencies revolving around performance, risk and change management to bring about durable business performance improvements.

• Financial and project based valuations
• Project Risk Analysis on 1+ billion dollar projects
• Performance Management business analysis and consulting
• Spreadsheet Modeling and VBA automation for simulation, forecasting and optimization
• Change Management consulting and training and instructional design relating to the adoption and implementation of enterprise analytics

Eric’s academic background includes a Master’s degree in information systems management from the University of Québec in Montreal as well as a BBA in international marketing and management from Northwood University Florida.

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When you think of heating sources, what comes to mind? For most Americans, oil, electricity and gas are the obvious choices. What about wood pellets? Wood-burning heat sources often conjure up images seen on “Little House on the Prairie”. However, in Europe wood  pellets are in high demand as a home-heating option. Besides being more efficient and less taxing on the environment, European regulations encourage the use of carbon-neutral sources. This is great news for U.S. wood-pellet producers, who expect to see a sharp demand for their product over the next decade.

FutureMetrics is one of the leading domestic experts in the economics of the production and use of renewable bioenergy. They, along with their partner Innovative Natural Resource Solutions, formed a new company, FutureEnergy Partners, to focus on the economics and risk of wood pellet production. Using @RISK, they performed risk analysis simulations to address some very critical concerns regarding the bright future of wood-pellet production:

• How much wood is required to operate a wood-powered plant and produce the appropriate amount of wood pellets to keep up with demand?
• How do they hedge their prices against global wood prices in a fashion that will allow them to turn a profit?

In a very informative case study, FutureMetrics shared its use of Monte Carlo simulation to answer both of those questions and secure a bright (and warm) future for U.S. wood pellet producers. It will be interesting to see if the U.S. moves towards alternate heating sources, such as wood pellets. If so, we’re sure @RISK can offer the kind of clear risk analysis necessary to make it both possible and profitable.
 

» Case Study: Futuremetrics Uses @RISK to Hedge Wood Prices in Production of Burning Wood Pellets

Beta 2 of Palisade’s new DecisionTools Suite 6.0 risk and decision analysis software is now available for download. Beta 2 includes the new time series simulation feature in @RISK 6.0, which allows you to model and simulate values that change over time. This is particularly useful in financial modeling and portfolio simulation.

» Download the DecisionTools Suite 6.0 Beta 2

Other key features of @RISK 6.0 include:

• Crystal Ball model converter
• Integration with Microsoft Project for simulation of Project schedules
• Easier-to-understand double-sided tornado
• Better distribution fitting

The DecisionTools Suite 6.0 is offers new versions of all products in the Suite: @RISK, PrecisionTree, TopRank, NeuralTools, StatTools, RISKOptimizer and Evolver.

» Complete list of new features
 

As every risk manager knows, however good a risk-based model, the validity of the forecasts it makes is dependent upon the quality of the input data.  One approach to obtaining assurance that forecasts from Monte Carlo analysis are realistic is to measure the capability of the risk management process that has been used to produce risk models.

The Project Risk Maturity Model (RMM) performs this measurement and has been demonstrated to help produce risk models that result in realistic forecasts (including models using Palisade’s risk analysis software, @RISK).

For example, the UK’s Ministry of Defence (MoD) equipment projects include the development and manufacture of new military equipment for the UK’s Army, Royal Navy and Royal Air Force.  Risk is often increased on these large and complex projects by objectives that tend to push the limits of technical feasibility. As a result, the MoD is highly committed to its project risk management process.  

However, in 2001, the MoD recognised that too many of its projects ran late and over budget.  It traced this to over-optimistic risk analysis forecasts in the early stages, leading to projects passing approval points without adequate scrutiny. This realisation prompted the MoD to invest in the Project RMM.  As a result, risk models used for project approvals became more reliable and realistic.

This is useful insight for @RISK users, because it enables them to check that the process used to develop their input data has been good enough to support their model.  As a result they can be confident of their predictions – regardless of the industry in which they operate.

For those who want to find out more, further details about the Project Risk Maturity Model and its lead developer, Martin Hopkinson, are in the case study on our website.
 

In a blog post last October, ‘Mixing business with biofuels’, we looked at how Sark7 uses Palisade’s DecisionTools Suite to build the business case for biofuel projects, with the overall aim of making these more attractive to potential investors.

Energy and Environmental Management magazine picked up on the topic, with the result that Scott Mongeau of Sark7 features on the site discussing the issue.

The premise of Scott’s article (and the Sark7 case study featured on our website) is that in order to attract funding, sustainable energy projects need to take a holistic approach that address a fundamental principle of finance.  So, rather than looking at potential profit in isolation, they must balance the highest profit that can be gained for the lowest aggregate risk exposure across integrated implementation, technical, economic and financial aspects.

Achieving this requires intensive computer-based modelling and simulation to enable in-depth decision-making insight, and Scott discusses how the various elements of the DecisionTools Suite are ideal tools with which to do that.  The full piece is available to read here: http://www.eaem.co.uk/opinions/mixing-business-biofuels

Scott Mongeau is following up this work with a presentation at this year’s European User Conference.  Here he will talk about using the DecisionTools Suite to conduct in-depth analysis that separates the hype from the tangible economic value-driven factors needed to ‘green light’ Smart City initiatives.

Craig Ferri
EMEA Managing Director of Risk & Decision Analysis

The pros and cons of energy systems have never been as critical as they are today. Energy sources, irrespective of how “green” they may or may not be, present associated risks: financial, environmental, personal, etc. Traditional thinking just assumes that “green-equals-good”, but there are strong considerations which must be applied when harnessing something as powerful as energy.  This is exactly what the international risk assessment organization, Der Norske Veritas (DNV) set out to discover.

Founded in 1864, DNV’s original mission was to inspect and evaluate the technical condition of Norwegian merchant vessels. Today, DNV assesses project risk across a number of industries, like rail transportation, healthcare, telecommunication and food and beverage companies. For its energy systems project, DNV utilized Monte Carlo simulation to identify environmental and financial risk factors of non-traditional (wind and solar) and traditional (nuclear waste storage, oil and gas and CO2 recycling) energy systems. Utilizing @RISK’s triangular distribution in its projection models, DNV uncovered some very interesting findings.

This research offered the energy industry a real world-examination of how to operate with risk and highlighted a key facet of DNV’s mission: Assessing risk doesn’t mean eliminating it (that’s unrealistic, if not impossible). Rather, assessing risk incorporates an honest look at factors that may do harm, determining their probability and constructing a business model that minimizes the potential impact those factors can have. We, at Palisade couldn’t agree more. We’re excited to be associated with DNV and the work they do to make the energy industry — and many others — safer for all.

» Read the complete case study about DNV's use of Palisade risk analysis solutions

Craig Ferri
EMEA Managing Director of Risk & Decision Analysis

Dr. Jose A. Briones of SpyroTek Performance Solutions recently gave a Palisade webcast presentation, using the success of Apple’s iPad as a working example, in "Use of @RISK for Quantifying Uncertainty in Innovation Project Management."

Product innovation has been described as the way out of today’s difficult business environment. However, the rate of success of development projects — in particular white space or disruptive innovation projects — remains too low.

The analysts at SpyroTek believes that a reason for the low success rate of development projects is the erroneous application of analysis methods designed for incremental innovation, such as NPV and DCF, to projects with high levels of uncertainty.

In the presentation, Jose discusses the use of @RISK and Probabilistic Decision Analysis in the management of innovation projects with high levels of uncertainty. Probabilistic decision analysis, when combined with the right management processes like Discovery Driven Planning, is a very effective approach to evaluate and manage the risk and potential of innovation projects.

» Watch "Use of @RISK for Quantifying Uncertainty in Innovation Project Management"
» View related slides from Dr. Briones

Join us this Thursday, Janurary 12, 2012, for a free live webcast entitled, "Refining the Business Case for Sustainable Energy Projects Using @RISK and PrecisionTree: A Biofuel Plant Case Study" to be presented by Scott Mongeau.

The sustainable energy industry sits at the nexus of growth and change: the popular groundswell for ‘green initiatives’, ongoing debates concerning global warming / climate change, fickle government incentives, the quest for renewable and alternative sources, expansion in developing economies, and the rapid emergence of new technologies. Sustainable energy industry sectors such as biofuel, solar, wind power each have unique selling points as well as practical challenges.  Across the board, profit margins are uncertain and tight, demanding detailed analysis and complex business cases.  Palisade's DecisionTools Suite is an ideal vehicle for conducting the deep risk analysis needed to separate the hype and ‘wishful vibes’ from the real risks and tangible profit cases needed to ‘green light’ sustainability projects.

Sustainable energy’s central competitor and sometimes partner, the petroleum majors, have distinct advantages, having established, streamlined supply chains and being embedded into the global economy.  However, traditional petroleum exploration is going to increasingly extreme and risky lengths to locate and exploit new reserves (i.e. Athabasca Oil Sands, deep sea drilling, project development in politically unstable regions).  The petroleum majors are dedicated users of the Palisade DecisionTools Suite to make their increasingly complex and risky business cases.

This free live webcast asserts that an energy development ‘risk / reward parity’ level is growing between new petroleum exploration and production and sustainable energy initiatives.  The presentation uses a biofuel plant case study as an example of how a profitable business case can be made for a sustainable energy project using techniques commonly applied in petroleum exploration and engineering initiatives.  The biofuel industry is expected to multiply its production by a factor of 50 by 2020.  The uncertainties of government subsidy, tax credits, and loan guarantees are crucial to meeting biofuel profit margins. Stochastic statistical analysis greatly improves the ability to pinpoint risk and to identify mitigation strategies. The case study uses @RISK to model biofuel project NPV, Evolver to suggest plant optimization strategies, and PrecisionTree to guide strategic decision making. The approaches presented have promise as a due-diligence tool for prospective sustainability entrepreneurs, investors, project managers, and firms. 

Scott Mongeau is Lead Consultant and Founder of Biomatica BV (biomatica.com), a niche consultancy specializing in biotechnology industry risk management. Scott has over a decade of experience in biotech, including key positions at Genentech Inc. related to risk management. He currently consults for several biofuel start-up initiatives and completed his thesis on biofuel project risk management. In addition to consulting, Scott is a part-time PhD researcher in the Executive Doctorate Program at Nyenrode Business University in the Netherlands. He holds a Global Executive MBA (OneMBA) and Masters in Financial Management (MFM) from the Erasmus Rotterdam School of Management (RSM). Additionally, he holds a Certificate in Finance from University of California at Berkeley, a Masters in Communication from the University of Texas at Austin, and a Graduate Degree in Applied Information Systems Management from the Royal Melbourne Institute of Technology as a Rotary Ambassadorial Scholar. Having lived and worked in a number of countries, Scott is an American citizen and currently consults and conducts research from his office in Leiden, Netherlands.

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Creating a feasible budget is never easy, but it’s even more challenging during questionable economic times. That was the case for the Arc of Yates, an amazing organization in New York State that provides a wide array of services for individuals with developmental disabilities in Yates County.  For many non-profit organizations, funding often comes from local, state and federal sources. Given the current economic climate, Arc of Yates was faced with the prospect of slashed budgets on every governmental level, effectively leaving the organization with a fraction of the funding they have enjoyed previously.

With uncertainties as to where that funding would originate, Arc of Yates utilized risk analysis software @RISK to explore which areas of funding were most likely to be affected. Using probability distributions, Arc of Yates could forecast what portion of the current budget stream may not be available over the next three years. Subsequently, the organization could develop strategies to explore alternative means of funding. Now Arc of Yates has a clear plan of action to meet upcoming budgets for the foreseeable future.

We think Arc of Yates’ use of @RISK is a great example of how Monte Carlo Simulation can empower organizations and lessen the concerns and uncertainties that accompany a struggling economy. Knowing where potential shortfalls may occur offers decision-makers the foresight and flexibility to stay in front of budgetary gaps. On a personal level, it’s great to know that we were able---in some small way---to further the effort of a truly fantastic organization.

» Arc of Yates case study
» Take a look at the great work Arc of Yates is doing.

Randy Heffernan
VP, Palisade Corporation

Join us this Thursday, November 10, 2011, for a free live webcast entitled, "Petroleum Resource Evaluation Using @RISK" to be presented by Dr. Ronald Brimhall.

This free live webcast contains instructions and demonstrations for using @RISK risk simulation software to examine net present value economic analyses for a petroleum resource. In this case, the asset is a low pressure gas reservoir. The main applications of @RISK cover in detail the spectrum of petroleum engineering analyses – rock and fluid properties, reservoir volumetrics, material balance, analogy, decline curve, and net present value. Microsoft Excel statistics spreadsheets with @RISK are the primary analysis tools. Basic principles are emphasized with the understanding that fundamentals may be applied to the entire spectrum of reservoir oil and natural gas assets in cases where variability and uncertainty in all relevant parameters are important.

Variability in rock properties are demonstrated by analysis of electric logs, Variability in original gas is place in demonstrated by comparing volumetric analysis and material balance for generalized reservoir (includes water influx and water production). Application of decline curve analysis with uncertainty in decline rate is applied to NPV analysis. A result of reserves determinations and NPV is compared with an alternative investment opportunity.

Dr. Brimhall’s experience covers 50 years in industry and in academia. He was part of the Petroleum Engineering Faculty at Texas A&M University, and maintained a professional practice related to formation evaluations, resource evaluations, log and pressure transient analyses, production operations for oil, natural gas and groundwater, as well as environmental and resource assessments for subsurface operations in energy and groundwater resources. His past project management experience includes business development as well as proper utilization of environment & natural resources.

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» View archived webcasts

Join us this Wednesday, October 19, 2011, for a free live webcast entitled "Modeling Oil & Gas Risk Problems using The DecisionTools Suite" to be presented by Rishi Prabhakar.

In today’s industry getting oil and gas safely and efficiently to the surface is a significant challenge. Oil & Gas problems and decisions are beset by uncertainty in all areas: production forecasting, reserves estimation, calculating exponential decline, scheduling, etc. There are many complex options for strategy and operations. The DecisionTools Suite has been used successfully throughout the entire value chain in the Oil & Gas industry.  This webcast will feature some of the common problems and solutions addressed effectively by the DecisionTools Suite.

Rishi brings a broad range of experience and expertise to the Palisade team. He has worked in and consulted to the energy industry, telecommunications, scientific research, banking and finance with an emphasis on operational risk and Basel II. Rishi has expert skills in the areas of statistical analysis, simulation, time series forecasting, risk/capital modelling, extreme value theory, survey design and analysis. He holds a BSc Mathematics from the University of Technology, Sydney.

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While it is accepted wisdom that the world needs to increase its focus on sustainable energy, there is still much dispute about whether initiatives of this kind are financially viable.

Sark7 is a specialist consultancy that aims to bridge the gap between populist enthusiasm surrounding ‘green’ initiatives and the intensive financial risk analysis demanded by capital investors and participants. It uses Palisade’s DecisionTools Suite to develop profitable business cases for sustainable energy projects. In effect, these act as due-diligence tools for prospective sustainability entrepreneurs, investors, project managers, providers and organisations.

Taking a biofuel plant as an example (but stressing that the techniques used are equally applicable to sustainable energy initiatives such as wind or solar energy), Sark7 uses various components of Palisade’s DecisionTools Suite to demonstrate viability. @RISK models the biofuel project’s Net Present Value (NPV), PrecisionTree informs strategic scenario decision-making and Evolver suggests plant optimisation strategies.

The premise is simple: Sark7 believes that environmental experts and enthusiasts need to be realistic about whether their proposal is financially viable if they are going to attract the funds that will make it a reality. Palisade’s risk analysis tools provide the language that is familiar to the financial world, as a result of which the project is more likely to receive funding. Sustainability criteria can therefore be met at the same time as providing investors with a risk-balanced return - so everyone wins.

» Read the full case study

Understanding how to use Monte Carlo simulation to account for risk in decision-making is quickly becoming a required skill for today’s business leaders, says Asher Drory, Adjunct Professor of Finance at University of Toronto’s Rotman School of Management.

“Many leading corporations are now using Monte Carlo simulation in their business cases,” Professor Drory says. “Students who want a leg up with such corporations should seek out all opportunities to get experience in working with Monte Carlo simulation.”

In his Financial Management course, Drory uses @RISK to teach some 200 graduate students each year how to use Monte Carlo simulation in analyzing working capital and capital budgeting decisions. Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probabilities that will occur for any choice of action.

For example, Drory's classes use @RISK and Monte Carlo simulation to look at:

• How forecasts of financial statements are needed to determine future funding requirements in working capital decisions.
• How forecasts of future free cash flows are required and risk must be assessed in capital budgeting analysis.

Separately, Drory and his students use Palisade’s PrecisionTree software in modeling decision tree analysis for new product development. The students have access to the entire DecisionTools Suite which is loaded on all of the computers in the Rotman Finance Laboratory.

“All key financial decisions such as investing, operating and financing decisions can benefit from Monte Carlo simulation,” says Prof. Drory, who has taught at the University of Toronto for 21 years. “I ran across @RISK about 5 years ago when I was looking for PC-based Monte Carlo simulation tools. @RISK has a straightforward and easy-to-use interface.”

» More about Professor Asher Drory
» More about @RISK

For their capstone design projects, undergraduate mining engineering students at Missouri University of Science and Technology develop “real-world” solutions. So, Dr. Samuel Frimpong provides his students with real-world tools, including Palisade’s @RISK software.

Similarly, he uses @RISK to help graduate students undertake research projects in geology and geological engineering, mining and petroleum engineering.

Dr. Frimpong says the risk analysis software helps students with risk modeling for everything from investment to production. Projects might include production forecasting, reserve estimation, exponential decline, and other key areas. @RISK also helps students understand stochastic processes – how random events can affect engineering phenomena over time.

“@RISK offers a comprehensive package for simulating stochastic processes defined by parametric probability and statistics,” says Dr. Frimpong, who has been teaching at the Rolla, Mo.-based university for more than 6 years. “The Excel environment also makes @RISK user-friendly.”

He also praised the software’s “efficient pre-simulation definition of input variables and post-simulation results.”

Dr. Frimpong says he has been using @RISK since his time at University of Alberta, Edmonton, Canada, where he completed his PhD in 1992 and later served as an associate professor of mining engineering.

A native of Ghana, Dr. Frimpong holds several patents in the area of oil sands extraction and is a noted expert in mine design, mineral economics, modeling methods and operations research.

» More about Dr. Samuel Frimpong
» More about @RISK

Join us this Thursday, October 6, 2011, for a free live webcast entitled, "Modeling Behavior Using @RISK and PrecisionTree: Why probability estimates aren’t always what they seem," to be presented by Christopher Brand.

Over the past three decades, behavioral economists and psychologists have gathered a significant amount of evidence suggesting that most people find it surprisingly difficult to make accurate judgments about probabilities. This is a cause for concern in real-world decisions, which normally involve at least some degree of risk and uncertainty. Even more troubling are the consequences for long-term decisions, in which it is necessary to account for multiple possible sequences of events; if each event includes an erroneous prior probability judgment, this will have the effect of multiplying the overall error in the decision.

This free live webcast will discuss some examples of probabilistic decision making where intuitions and judgments are regularly incorrect -- such as the Monty Hall problem, the base rate fallacy, and the conjunction fallacy -- and demonstrate these cases via implementation within @RISK risk analysis software, and PrecisionTree decision trees modeling software. Furthermore, the presentation will also explain how models of behavior during decision making can be developed using Palisade software.

Chris Brand is an Associate at Captum Capital Limited, where he provides consulting and training services to early stage life science companies in the behavioral aspects of business development. He is also a PhD student at Birkbeck, London University where he is active in the psychology of decision making. Chris holds an MSc in Cognitive and Decision Sciences from University College, London, an MA in Philosophy from the University of York and a BSc in Philosophy and Psychology from the University of Keele.

» Register now (FREE)
» View archived webcasts

Calum Turvey, W.I. Myers Professor of Agricultural Finance, uses @RISK in his Risk Simulation and Optimization course. Offered by the Charles H. Dyson School of Applied Economics and Management at Cornell University, Risk Simulation and Optimization is in its second year and has now become a regular course offering, with roughly 45 students per semester. @RISK is used to evaluate problems of finance, including capital budgeting, investments, random walks, derivatives pricing and real options. Dr. Turvey was first exposed to Palisade’s tools when they were in their infancy: “If I recall, I was customer number 100 in 1987 when @RISK was introduced as a Lotus 1-2-3 application, and have used it ever since.”

On the importance of exposing his students to @RISK, Dr. Turvey explains, “Students of finance are largely taught finance from the view of certainty. Adjustments are made in the standard investment model to adjust for risk, but these are generally not insightful. Risk assessment using probabilities is confined to simple decision trees. What we do in this course is take the standard textbook in finance, and chapter by chapter we convert everything to a probability model, starting with coordinated financial statements to investigate cash flow risk and on to NPV applications. On the derivatives side, I show how Monte Carlo simulation can be used to replicate options prices, and how Monte Carlo simulation can be used to price exotic options.”

Calum Turvey received his PhD from Purdue University in 1988, after which he joined the faculty of Agricultural Economics and Business at the University of Guelph, obtaining the rank of professor, until 2002. In 2002, he joined the faculty of Cornell’s Department of Agricultural, Food and Resource Economics as professor and director of the Food Policy Institute and Chair from 2003-2005. In 2005, he joined the Department of Applied Economics and Management as the W.I. Myers Professor of Agricultural Finance. He is the editor of “Agricultural Finance Review” and conducts research in the area of agricultural finance, risk management and agricultural policy.

» Dr. Calum Turvey’s work, on SSRN
» More about @RISK

The @RISK — Excel Reports command selects reports to be generated on the active simulation results, or the current model definition.

A variety of different pre-built simulation reports are available directly in Excel at the end of a simulation. The Quick Report is a report on simulation results designed for printing. This report contains a single page report for each output in a simulation. The other available reports, starting with Input Results Summary, contain the same information as the equivalent report in the Results Summary Window or other Report windows.

You can also use template sheets to create your own custom simulation report. Simulation statistics and graphs are placed in a template using @RISK statistics functions (such as RiskMean) or the graphing function RiskResultsGraph When a statistics function or graphing function is located in a template sheet, the desired statistics and graphs are then generated at the end of a simulation in a copy of the template sheet when you choose the Template Sheets option in the Excel Reports dialog. The original template sheet with the @RISK functions remains intact for use in generating reports from your next simulation.

» Read more about generating @RISK reports in Excel
» View a short video demonstrating reports in Excel  
» Download the example file Template.xls to see how to set up your own report

What do banks, bond-rating agencies and homeowners in places like Las Vegas have in common? They all grossly misjudged risk and, as a result, made bad decisions during the recent housing bubble.

That’s why Dr. Arnoldo Camacho, a professor at the highly regarded INCAE Business School in Alajuela, Costa Rica, incorporates Palisade’s @RISK software in his MBA courses – Finance I, and Financial Institutions and Capital Markets.

“The Finance course focuses on the creation of value through efficient decision making, which involves risk analysis,” says Dr. Camacho, who has taught at INCAE for 22 years. “In the Financial Institutions and Capital Markets courses, an in depth analysis of credit risk requires the estimation of the probability of default of issuers of debt.

“In both courses, @RISK is used for simulation and sensitivity analysis.”

Camacho was introduced to @RISK through INCAE, where his courses attract typically attract 60 to 65 students.

When asked why it is important to expose his students to @RISK, Camacho says, “It is easy to handle, and it allows students to move from uncertainty to risk analysis, which requires critical thinking.”

» More about Dr. Arnoldo Camacho
» More about @RISK