|
 |
| |
| |
| FINANCIAL PLANNING |
When clients want to understand the risks and rewards of
investing, what do you tell them?
- Can you show them graphs and charts that explain what
happens to their portfolio in a bear market?
- Can you give them a probability based on historical
data that they will not lose their hard earned nest egg?
- Can you tell a retiring couple how much they can withdraw
each year while still maintaining their original investment?
- Can you optimize their portfolio based on their risk
tolerance?
With the recent
volatility in the stock market, are you confident of the
risks you face in your financial planning? If not, then you
need to turn to Crystal Ball®.
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 financial planning spreadsheets to create more accurate financial forecasts and help your clients with better informed financial decisions. |
|
. 
In traditional financial analysis - not using Monte Carlo simulation - you rely on linear analysis where uncertain and uncontrollable variables such as life expectancy and investment returns are treated as known, static values.
Future deviations from those assumptions means a revision of the plan, and if the client has already taken significant actions based on the original plan, such as retiring early or making large gifts to family members or charity, the client's financial security could be put at risk.
By adding stochastic analysis with Crystal Ball, you can see how the plan will succeed or fail in thousands of possible financial futures, create a confidence level for the client, and allow your clients to decide, based on their own risk tolerance, whether the confidence level is acceptable. You can then tailor and optimize the plan to the client’s desired confidence level.
Key
features of interest to your industry include sensitivity
analysis, correlation, historical data fitting, and trend charts. 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. Trend charts allow you to visually analyze how the uncertainty around a portfolio grows and varies over time. The Professional Edition includes time-series forecasting
and optimization, which can help to maximize portfolio return
and protect the long and short term value of a client's
portfolio.
LEARN MORE ABOUT CRYSTAL BALL FOR FINANCIAL PLANNING
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!
"My customers are absolutely satisfied with
the work performed for them using Crystal Ball. It has
saved putting money in unprofitable ventures."
-- Aziz U. Rahman, Credit and Financial Risk
Consultant, Financial Consultants International |
|

RECORDED WEB SEMINARS
 |
The Next Generation of Financial Planning
Demonstrates the use of Crystal Ball software in a series of financial planning applications, including how to project probabilities of future wealth, incorporating all tangible assets as well as financial assets that include stock options, restricted stock, qualified and non qualified accounts, etc.
Presented by Mike Patton, Principal of Integrity Wealth Management, LLC
Recorded September 19, 2007
|
View recording
Download files
|
 |
Advising with Confidence - Using Stochastic Analysis in Financial Planning
Learn how Bank of America applies stochastic analysis that allows the planner to test and visualize thousands of possible outcomes to better tailor the client's plan.
Presented by Terence Condren, Director of Planning Solutions at the Bank of America Private Bank
Recorded August 18, 2005
|
View recording
Download files |
 |
Top
|

WHITE PAPERS & ARTICLES
 |
A Better Way to Size Up Your Nest Egg,'' Monte Carlo'' models
simulate all kinds of scenarios
By Christopher Farrell (On the BusinessWeek Web site) |
Download |
 |
Advising with Confidence: Using Stochastic Analysis in Financial Planning
By Terence D. Condren, Bank of America Private Bank
 |
Download |
 |
Commerce, Enterprise Use Simulated Planning Programs
By Anne Lindner (On the St. Louis Business
Journal Web site) |
Download |
 |
Financial Planning for Worst Case Scenarios
By Huybert Groenendaal and F. J. Zagmutt (Written for Risk Management Magazine) |
Download |
 |
Live Well—Die Broke
By John M. Charnes, Professor, University of Kansas; Howard Marmorstein, Professor, University of Miami; Tom Robinson, Professor, University of Miami
 |
Download |
 |
Monte Carlo simulation: Model calculates probability of estate plan's worth
By Susan Deutschle (For Business First Web site) |
Download |
 |
The Next Generation of Financial Planning
Michael J. Patton, Personal CFO, Integrity Wealth Management, LLC
 |
Download
|
 |
| Will Your Clients
Accept a 50/50 Chance of Meeting Their Financial Objectives? |
Download |
 |
Top
|

CASE STUDIES
 |
Ryan Beck & Co.
Crystal Ball Services Helps This Regional Investment Bank and Brokerage Firm Forecast Future Stock Performance |
Download
|
 |
ProVise Management
Group
For ProVise Management Group, Crystal Ball is the Key to
Optimizing Portfolio Profit |
Download
|
 |
Top
|

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) (D)
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) (D)
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 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
|
 |
Top
|

COMMON USES & EXAMPLES
The following examples were provided by our customers and represent
only some of the potential financial planning applications for
Crystal Ball.
- Analysis of new business financial plan
- Assess investment opportunities in various business sectors
- Assessing retirement plan returns based on variable levels
of risk tolerance
- Determining the best set of investments
- Evaluate equity option prices and refine financial market models
- Evaluate investment opportunity for private equity funds
- Evaluating the current and future positions of employer granted
options
- Forecasting and Predicting impact of product sales growth and decline
- Headcount planning and break-even analysis
- Maximizing client's portfolio returns
- Monte Carlo simulation for newly formed hedge funds
- Planning an estate
Top
|

TEXTBOOKS
Top
|
| FINANCIAL PLANNING - Partners
and Toolkits |
Decisioneering is pleased to partner with companies that incorporate
Crystal Ball into their existing software toolkits.
Advisor Series
Convergence for Asset Liability Management (ALM)
Enteract
|
ADVISOR SERIES |
SRC Software's Advisor Series is a full-featured financial
planning and performance management application that provides
the ultimate in system flexibility and modeling sophistication.
The Advisor Series covers the complete range of planning and analytic
functions for the enterprise, including budgeting, forecasting,
payroll planning, consolidations and financial reporting.
SRC's solutions include Decisioneering's CB Predictor and help
enterprises reduce planning cycle times, model complex scenarios
and generate more reliable plans and reports. This ultimately
leads to faster, better decisions, improved performance and a
higher enterprise value.
The Advisor Series is made up of several software modules that
can be implemented as a fully integrated solution or as stand-alone
applications:
- Budget Advisor, a user-definable solution for
budget preparation, forecasting and analysis
- Payroll Planner, providing detailed payroll planning
at the individual employee or job code level
- Information Advisor, a robust solution for consolidations,
financial reporting and ad hoc analysis
See
our press release about SRC and Decisioneering
Click here to learn more about the Advisor Series of products
Back to Top
|
CONVERGENCE FOR ASSET LIABILITY
MANAGEMENT (ALM) |
BancWare Convergence: The Asset/Liability Management Solution
BancWare's Convergence for ALM gives you the power to make informed
decisions, the ability to identify profit opportunities, and the
knowledge to help minimize risk exposure in an increasingly competitive
market. Convergence for ALM is a powerful computational engine
that uses advanced financial algorithms to perform financial calculations,
including market value, convexity, income simulation, cash flows
and cash flow schedules, amortization schedules, funds transfer
pricing, and duration.
Convergence for ALM helps you:
Back to Top
|
ENTERACT |
CCH
INCORPORATED (CCH), a leading provider of financial and estate
planning information and software, has integrated OCB's Monte
Carlo simulation capabilities into the latest release of its CCH
Enteract financial-planning software.
CCH Enteract is an integrated planning system designed to let
financial planners immediately and interactively see how changes
in client data affect planning scenarios. OCB gives CCH Enteract
the power to clearly demonstrate the percentage chance a client
will have of meeting a particular goal while also communicating
the probability of falling short.
See our press release
on CCH's Enteract
Click here to learn more about CCH's Enteract
Back to Top
|
|
|
|
| |
|
|