Better Forecasting by Projecting Ranges of Outcomes (Course Id 2539)

• Who is this course for?
  This course is designed for anyone needing Continuing Professional Education (CPE), including CPAs, accountants, and other finance professionals seeking to enhance their forecasting and risk analysis skills.

• What is this course about or what problem does this course solve?
  The course addresses the challenge of traditional financial forecasting by teaching participants how to incorporate probability analysis and project ranges of outcomes instead of relying solely on single-point estimates.

• How can the knowledge from this course be used?
  Participants can apply probabilistic modeling, including Monte Carlo simulations and visual tools like S-curves and flying bars, to create more robust financial forecasts and better manage uncertainty and risk.

• Why is this course important to a CPA, Accountant, or IRS Enrolled Agent?
  Understanding and modeling risk and uncertainty in financial projections is crucial for informed decision-making, a core responsibility for CPAs and finance professionals.

• When is this course relevant or timely?
  Released in 2025, this course is timely for professionals looking to modernize their forecasting techniques and align with current best practices in financial analysis.

• How is a course like this consumed or used?
  This is a self-paced, text-based QAS self-study course that includes reading materials, review questions, and a final exam, accessible entirely online with no additional materials required.

This course provides a practical framework for incorporating probability analysis into your financial projections, equipping you with the tools and techniques to make more informed and robust financial forecasts. By incorporating probability analysis into your financial projections, you can better understand and manage risk to make more informed decisions.

Accounting is the language of business. Statistics is the language of uncertainty and risk. Financial analysts and decision-makers must speak both accounting and statistics; otherwise, we ignore uncertainty and risk.

This is a very high-level overview of probabilistic analysis. I'll focus more on concepts than calculations. My hope is that these concepts improve your company's understanding and measurement of uncertainty so that you can make better decisions.

In most forecasts and budgets, great effort is spent on determining the "right input number" or a few "right numbers" for the projection model. The assumption is that if we get the right inputs, we'll get the right output. In stochastic analysis, the model inputs are a range of numbers with assumptions about how those numbers are distributed throughout that range. Projections that provide ranges of outcomes and probabilities of those outcomes give us a much more complete picture of an uncertain and risky future.

The first lesson explores the benefits of probabilistic analysis. The second lesson briefly covers a few basic statistics concepts. We'll then look at S-curves and flying bars. These are ways to display a range of data. Next is an overview of Monte Carlo simulation. We'll then explore the implementation process for simulation analysis.

NASBA QAS - Text - NASBA Registry - 2539

Course Learning Objectives

• Recall the definitions of possibility and probability
• Identify key aspects of distribution curves and flying bar charts
• Recognize methods and tools for probabilistic modeling

Chapter 1 - Better Forecasting by Projecting Ranges of Outcomes

Thinking Probabilistically

Statistics Basics

S-Curves and Flying Bars

Monte Carlo Simulation

Implementing Simulation Analysis

Key Takeaways

Review Questions

Glossary