Are you confident of the risks you face in the way you perform portfolio allocation?

To ignore the effects of uncertainty in a portfolio allocation means to potentially expose your organization and clients to unnecessary risk and potential failure. Yet that is exactly what professionals do when they use Microsoft® Excel® without additional analytical support. In traditional spreadsheet analysis, you are forced to rely on best-guess or average values even when you know that inputs such as individual returns and inflation or volatility and are uncertain and uncontrollable.

Whether you're trying to optimize a portfolio of projects, securities, equity funds, or stocks, you need to account for the uncertainties in your financial models. No matter what risks you face, Crystal Ball software can help you find the specific solution for your needs.

Crystal Ball is a Microsoft® Excel®-based suite of analytical tools that includes Monte Carlo simulation, optimization, and forecasting. With little effort, you can apply these advanced analytical techniques to your new or existing spreadsheets to create more accurate cost and financial predictions and better informed business decisions.

Today, Crystal Ball is the tool chosen by more than 85% of the Fortune 500. Companies such as Sprint, Pillsbury, and Boeing rely on Crystal Ball to manage risk and make more informed business and strategic decisions. Common applications include the optimization of project and R&D portfolios, analysis of energy asset portfolios, and estimating loan portfolio funding options.

> Learn how Crystal Ball is used for financial planning

Key features of interest to your industry include sensitivity analysis, correlation, historical data fitting, trend charts, optimization, and efficient frontier. The sensitivity analysis helps you to understand which of the uncertain inputs are most critical and drive the uncertainty of your planning model. Correlation lets you link uncertain inputs and account for their positive or negative dependencies. If historical information does exist, the data fitting feature will calculate the probabilities around data such as investment returns. If historical data does exist, the data fitting feature will compare the data to the distribution algorithms and calculate the best possible fit and parameters for your data.

Trend charts allow you to visually analyze how the uncertainty around a portfolio grows and varies over time. Optimization helps determine optimal decision choices to maximize or minimize your goals (e.g., maximize the return on a portfolio of assets), and efficient frontier runs multiple optimizations to determine the best balance of risk and reward for a particular problem or portfolio.

LEARN MORE ABOUT CRYSTAL BALL FOR PORTFOLIO OPTIMIZATION AND ALLOCATION

This page offers links to a growing number of resources, including recorded Web seminars, articles, white papers, case studies, and example models. Additionally, you can view a list of common uses and examples reported directly from customers using Crystal Ball. You can also download a free trial version of Crystal Ball to see how it can help improve your business forecasts and decisions!

RECORDED WEB SEMINARS

Choose Wisely: Apply Project Selection and Optimization Models to Product Development and R&D Portfolios Learn how Project Selection and Optimization Models reveal the real-time risk adjusted value of the project pipeline and provide the clear and accurate data that is necessary to make highly informed decisions. Presented by Tom Hambleton, an independent Technology and Innovation Strategy consultant Recorded April 4, 2006	View recording Download files
Developing a Strong Energy Asset Portfolio Using the “Efficient Frontier” Approach Explore how to develop a strong energy asset portfolio with a case study on power plants. The case study illustrates implementation of the “efficient frontier” approach to portfolio development. Presented by Jim Letzelter, Partner, with Webb, Scott & Quinn Recorded January 18, 2006	View recording Download files
Portfolios Optimisation in Oil & Gas: An Analysis of Risk and Real Options and Their Contribution to Efficient Capital Allocation Review an optimised portfolio of capital projects and examine the sources of systematic and unsystematic risk. We will see how this can help in our funding decisions and the different impacts on the portfolio and its risk/return characteristics. Presented by Dave Hammal of Crystal Ball Recorded June 6, 2007	View recording Download files
Riesgos en Proyectos de Inversión: Cómo Enfrentarlo Aprende a utilizar la metodología más poderosa para analizar riesgos en proyectos de inversión utilizando Crystal Ball, el software líder a nivel mundial para aplicaciones que incluyen incertidumbre, variabilidad y riesgo. Presented by Eduardo Herrera, Presidente Ejecutivo de CIDEM Recorded March 9, 2006	View recording Download files

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WHITE PAPERS & ARTICLES

Advanced Project Portfolio Selection Methods By Jay April, Fred Glover, James P. Kelly, and Manuel Laguna, OptTek Systems, Inc (on the Financial Engineering News Web site)	Download
An Application of Portfolio Optimization with Risk Assessment To E&P Projects By Juan Marcelo Antelo Rodriguez, Petrobras Bolivia, Economic Engineer	Download
Optimizing the Growth Portfolio of a Diversified Mining Company By Thomas de Lange, Manager Strategy, Kumba Resources	Download
Selecting Winning Projects By Thomas Pyzdek (Six Sigma and Beyond column for Quality Digest, August 2000) (Six Sigma Partner)	Download
A "Top Down" Approach for Modern Portfolio Theory to Oil and Gas Property Investment By Dr. Frank Moseley, North Dakota University - Minot	Download
Using Simulation to Estimate Loan Portfolio Funding Requirements By Jonathon W. Albright, Senior Vice President and Finance Director at Bank One Card Services (on the Financial Engineering News Web site)	Download

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CASE STUDIES

Portfolio Optimization For ProVise Management Group, Crystal Ball is the Key to Optimizing Portfolio Profit	Download

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EXAMPLE MODELS

Portfolio Allocation (Part 1) Detail: This portfolio allocation model, used in our basic optimization tutorial, requires you to define decision variables and run OptQuest to determine an optimal investment strategy. The model uses standard deviation to limit risk. Includes optimizations setting file. Portfolio Allocation - Revisited (Part 2) Detail: This model is the same as above, but now the decision variables are already defined. Combines several objective functions into one multiobjective using special Crystal Ball functions and uses the Arbitrage Pricing Theory for incorporating risk. Includes optimizations setting file. Portfolio Allocation - Revisited EF (Part 3) Detail: Same as Portfolio Allocation, but with decision variables already defined. This example is used to show the use of the Efficient Frontier feature in OptQuest. Includes optimizations setting file.	For: Crystal Ball & OptQuest Level: Simple Download     Download     Download
Portfolio Optimization From: Stephen G. Powell and Kenneth R. Baker, Dartmouth College Detail: This application is excerpted from The Art of Modeling with Spreadsheets, Stephen G. Powell and Kenneth R. Baker, John Wiley and Sons, 2004. The objective of this model is to formulate an investment portfolio that has an attractive average return with low risk. In general, these goals conflict: high mean return is usually associated with high risk. This model discusses multiple approaches to portfolio allocation, including a simple deterministic assessment, simulation using Crystal Ball, and optimization using OptQuest.	Download For: Crystal Ball & OptQuest Level: Simple
Portfolio Without Market Correlation Detail: This model was developed for a client who is retiring and requires yearly cash income from her investment. The amount of the investment, income required per year, and anticipated inflation rate are entered by the user. In addition, the desired asset allocation is entered. The model will simulate the return of the portfolio using normal distributions based on the historical mean and standard deviation of each asset class. The balance at the end of Year 2000 and Year 2009 along with the simple average return are forecasted. These forecast will allow the user to analyze the risk and return of the portfolio.	Download For: Crystal Ball & OptQuest Level: Simple
Project Portfolio Selection Detail: The problem is to determine which projects to select to maximize the total expected profit while staying within the budget limitation. Complicating this decision is the fact that both the expected revenue and success rates are highly uncertain. Includes optimizations setting file. Uses binary decision variables for Yes/No decisions and uses the certainty statistic for optimizing the values observed between two endpoints.	Download For: Crystal Ball & OptQuest Level: Simple
Simulating the risk of a credit portfolio using Expected Loss (EL) From: Johannes Ritter, Solution Matrix Europe Detail: How do changes in Default Probability (PD), Loss Given Default (LGD) and Exposure at Default (EAD) affect the Expected Loss (EL)? Qualitative differences in loan management and credit rating can have great impacts on Expected Loss and therefore on capital requirements. Risk Management constantly tries to improve the quality of the input variables in order to more accurately assess the underlying risk of the bank's business. This model identifies the quantitative impacts of such improvements. It is also possible to quantify the impacts of negative developments.	Download For: Crystal Ball Level: Simple-Moderate

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COMMON USES & EXAMPLES

The following examples were provided by our customers and represent only some of the potential corporate finance applications for Crystal Ball.

• Assess investment opportunities in various business sectors
• DCF analysis
• Determining Risk in investments in the wind power and renewable energy industries
• Evaluation of capital investment proposals, acquisitions, and new business startups
• Evaluate equity option prices and refine financial market models
• Evaluate investment opportunity for private equity funds
• Evaluating investment options
• Feasibility studies on capital investments
• Financial market analysis, risk analysis, forecasting etc.
• Find optimal asset allocation for variety of asset classes
• Interest Rate Risk Management
• Model and drive financially sound marketing and business decisions
• Model complicated securities and investment strategies
• Optimisation of investments across different asset classes
• Option and asset pricing
• Options and derivative modeling
• Portfolio analysis, fund risk characteristics, market analysis
• Real options analysis
• Risk models for retirement plans
• Stock performance projections

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