Financial Statement Modeling

2024 Curriculum CFA Program Level II Corporate Finance

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Introduction

Financial statement modeling is a key step in the process of valuing companies and the securities they have issued. We focus on how analysts use industry information and corporate disclosures to forecast a company’s future financial results.

An effective financial statement model must be based on a thorough understanding of a company’s business, management, strategy, external environment, and historical results. Thus, an analyst begins with a review of the company and its environment—its industry, key products, strategic position, management, competitors, suppliers, and customers. Using this information, an analyst identifies key revenue and cost drivers and assesses the likely impact of relevant trends, such as economic conditions and technological developments. An analyst’s understanding of the fundamental drivers of the business and assessment of future events provide the basis for forecast model inputs. In other words, financial statement modeling is not merely a quantitative or accounting exercise, it is the quantitative expression of an analyst’s expectations for a company and its competitive environment.

We begin our discussion with an overview of developing a revenue forecast. We then describe the general approach to forecasting each of the financial statements and demonstrate the construction of a financial statement model, including forecasted revenue, income statements, balance sheets, and statements of cash flows. Then, we describe five key behavioral biases that influence the modeling process and strategies to mitigate them. We turn to several important topics on the effects of micro- and macroeconomic conditions on financial statement models: the impact of competitive factors on prices and costs, the effects of inflation and deflation, technological developments, and long-term forecasting considerations. The reading concludes with a summary.

Most of the examples and exhibits used throughout the reading can be downloaded as a Microsoft Excel workbook. Each worksheet in the workbook is labeled with the corresponding example or exhibit number in the text.

Learning Outcomes

The member should be able to:

compare top-down, bottom-up, and hybrid approaches for developing inputs to equity valuation models;
compare “growth relative to GDP growth” and “market growth and market share” approaches to forecasting revenue;
evaluate whether economies of scale are present in an industry by analyzing operating margins and sales levels;
demonstrate methods to forecast cost of goods sold and operating expenses;
demonstrate methods to forecast nonoperating items, financing costs, and income taxes;
describe approaches to balance sheet modeling;
demonstrate the development of a sales-based pro forma company model;
explain how behavioral factors affect analyst forecasts and recommend remedial actions for analyst biases;
explain how competitive factors affect prices and costs;
evaluate the competitive position of a company based on a Porter’s five forces analysis;
explain how to forecast industry and company sales and costs when they are subject to price inflation or deflation;
evaluate the effects of technological developments on demand, selling prices, costs, and margins;
explain considerations in the choice of an explicit forecast horizon; and
explain an analyst’s choices in developing projections beyond the short-term forecast horizon.

Summary

Industry and company analysis are essential tools of fundamental analysis. The key points include the following:

Analysts can use a top-down, bottom-up, or hybrid approach to forecasting income and expenses. Top-down approaches usually begin at the level of the overall economy. Bottom-up approaches begin at the level of the individual company or unit within the company (e.g., business segment). Time-series approaches are considered bottom-up, although time-series analysis can be a tool used in top-down approaches. Hybrid approaches include elements of top-down and bottom-up approaches.
In a “growth relative to GDP growth” approach to forecasting revenue, the analyst forecasts the growth rate of nominal GDP and industry and company growth relative to GDP growth.
In a “market growth and market share” approach to forecasting revenue, the analyst combines forecasts of growth in particular markets with forecasts of a company’s market share in the individual markets.
Operating margins that are positively correlated with sales provide evidence of economies of scale in an industry.
Some balance sheet line items, such as retained earnings, flow directly from the income statement, whereas accounts receivable, accounts payable, and inventory are closely linked to income statement projections.
A common way to model working capital accounts is to use efficiency ratios.
Return on invested capital (ROIC), defined as net operating profit less adjusted taxes divided by the difference between operating assets and operating liabilities, is an after-tax measure of profitability. High and persistent levels of ROIC are often associated with having a competitive advantage.
Competitive factors affect a company’s ability to negotiate lower input prices with suppliers and to raise prices for products and services. Porter’s five forces framework can be used as a basis for identifying such factors.
Inflation (deflation) affects pricing strategy depending on industry structure, competitive forces, and the nature of consumer demand.
When a technological development results in a new product that threatens to cannibalize demand for an existing product, a unit forecast for the new product combined with an expected cannibalization factor can be used to estimate the impact on future demand for the existing product.
Factors influencing the choice of the explicit forecast horizon include the projected holding period, an investor’s average portfolio turnover, the cyclicality of an industry, company-specific factors, and employer preferences.
Key behavioral biases that influence analyst forecasts are overconfidence, illusion of control conservatism, representativeness, and confirmation bias.

3.25 PL Credit

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