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LM07 Company Analysis: Forecasting 2025 Level I Notes © IFT. All rights reserved 1 LM07 Company Analysis: Forecasting 1. Introduction ........................................................................................................................................................... 2 2. Forecast Objects, Principles, and Approaches .......................................................................................... 2 3. Forecasting Revenues ........................................................................................................................................ 4 4. Forecasting Operating Expenses and Working Capital ......................................................................... 6 5. Forecasting Capital Investments and Capital Structure ....................................................................... 8 6. Scenario Analysis ................................................................................................................................................. 9 Summary ...................................................................................................................................................................12 Required disclaimer: IFT is a CFA Institute Prep Provider. Only CFA Institute Prep Providers are permitted to make use of CFA Institute copyrighted materials which are the building blocks of the exam. We are also required to create / use updated materials every year and this is validated by CFA Institute. Our products and services substantially cover the relevant curriculum and exam and this is validated by CFA Institute. In our advertising, any statement about the numbers of questions in our products and services relates to unique, original, proprietary questions. CFA Institute Prep Providers are forbidden from including CFA Institute official mock exam questions or any questions other than the end of reading questions within their products and services. CFA Institute does not endorse, promote, review or warrant the accuracy or quality of the product and services offered by IFT. CFA Institute®, CFA® and “Chartered Financial Analyst®” are trademarks owned by CFA Institute. © Copyright CFA Institute Version 1.0
LM07 Company Analysis: Forecasting 2025 Level I Notes © IFT. All rights reserved 2 1. Introduction This learning module covers:  What to forecast, approaches to forecasting, and selecting a forecast horizon.  Forecasting particular items: revenues; operating expenses and working capital; capital investments and capital structure.  Use of scenario analysis in considering multiple outcomes. 2. Forecast Objects, Principles, and Approaches What to Forecast? Analysts can focus on different forecast objects such as:  Drivers of financial statement lines: This concept was covered in the previous learning module. The net sales for Warehouse Club Inc were analyzed using two bottom-up drivers: the average number of stores opened and the average net sales per store. Net sales can be forecasted by forecasting these drivers individually and multiplying them. The advantage of this approach is that it improves the explanatory value of the forecast and may also improve accuracy.  Individual financial statement lines: Instead of forecasting drivers, we can directly forecast individual financial statement lines. This approach is often used for lines without clear drivers, for less-material items, and for items that the analyst does not have a perspective on. For example: amortization expense, analysts may use the estimate provided by the management or simply assume that the quantity will remain the same in future periods.  Summary measures: This includes items like free cash flow, earning per share, and total assets. The advantage of using these as forecast objects is efficiency. The disadvantage is reduced transparency, which makes it difficult to audit the forecast. This method is best suited when the summary measure is stable and predictable, or when issuer disclosures are severely restricted.  Ad hoc objects: This includes items that may not have been reported on previous financial statements. Examples include the outcomes of a significant legal proceeding, a government regulatory action, a tax dispute, or a natural disaster. An analyst’s choice of forecast object depends on available information, efficiency, accuracy, explanatory value, and verifiability. Focus on Objects That Are Regularly Disclosed CFAI recommends using forecast objects that are either regularly disclosed or can be directly calculated using what is regularly disclosed.
LM07 Company Analysis: Forecasting 2025 Level I Notes © IFT. All rights reserved 3 Non-regularly disclosed information can be used to supplement forecasts but is problematic for direct use because forecasts cannot be confirmed in a timely manner. CFAI also cautions against overly complex models, because they require more forecasts and take more time to update, often with no improvement in accuracy. Forecast Approaches For any object there are four general forecast approaches:  Historical results (assume past is precedent): This approach uses past observed or calculated values as a forecast. This is an easy to implement approach and may be appropriate for companies operating in industries where the industry structure is not expected to change. The approach can also be used to forecast objects that are not material or that the analyst does not hold an opinion on. The approach is less appropriate for companies in cyclical industries because the future period could be at a different point in the business cycle.  Historical Base Rates and Convergence: This approach uses an industry or peer group average or median, calculated over a long time period as a “base rate” for forecasting where an object will converge to over time. This approach is more complex than the previous approach because analyst discretion is required to select the object, the sample to calculate the base rate, and a time frame for convergence to the base rate. The approach may be appropriate for companies operating in well established industries such as banks, airlines, retailers etc. It is less appropriate for companies in changing or new industries.  Management guidance: A company's management may publicly announce earnings, revenue, and other targets for the next quarter, year, or longer (known as management guidance or simply guidance). This guidance is often provided as a range (e.g. sales growth of 3%-5%) and is based on many sub-forecasts and assumptions by the management about macroeconomic growth, cost inflation, market share changes, exchange rates etc. Using guidance for forecasts may be appropriate when management has demonstrated a track record of reliable estimates.  Analyst’s discretionary forecasts: All other forecast approaches can be grouped under this category. This can include approaches based on surveys, quantitative models, probability distributions, and other unobservable inputs. Discretionary forecasts approaches are commonly used for companies in cyclical industries, companies that have no comparables, or companies undergoing a fundamental change like a shift in the competitive or regulatory environment. An analyst’s choice of forecast approach depends on the company’s industry structure, sensitivity to the business cycle, and business model, as well as the reliability and availability of information.
LM07 Company Analysis: Forecasting 2025 Level I Notes © IFT. All rights reserved 4 Selecting a Forecast Horizon The forecast time horizon is determined by the investment strategy for which the security is being considered, the cyclicality of the industry, company-specific factors, and the preferences of the analyst's employer. Long-term fund managers may focus their forecasting primarily on the next three to five years, whereas shorter-term managers may focus more on the next one or two quarters. 3. Forecasting Revenues Forecast Objects for Revenues Revenues can be forecasted using a top-down or bottom-up approach. Common top-down forecast objects include “growth relative to GDP growth” and “market growth and market share”. Growth relative to GDP growth approach: In this approach, we first forecast the growth rate of nominal GDP. We then forecast the company’s revenue growth relative to GDP growth. For example, we can assume that the company’s revenue will grow at a rate of 150 bps above the nominal GDP growth rate. The forecast may also be in relative terms. For example, if we forecast that the GDP will grow at 4%, and we believe that the company’s revenue will grow at a 20% faster rate, then the forecasted increase in the company’s revenue is 4% x (1 + 0.20) = 4.8%. Market growth and market share: In this approach, we combine forecasts of growth in particular markets with forecasts of a company’s market share. For example, assume Tesla is expected to maintain a market share of 1% in the automobile market. If the automobile market is expected to grow to $30 billion in annual revenue, then Tesla’s annual revenue is forecasted to grow to 1% * $30 billion = $300 million. Examples of bottom-up drivers for revenue forecast include:  Volumes and average selling price: Volumes and prices of the company’s products are forecasted separately and multiplied to get a revenue forecast. For example: The revenues for a mutual fund can be forecasted based on the AUM and management fee rates.  Product-line or segment revenues: Forecasts for individual products, product or business lines, geographic areas, or reporting segments are made and then aggregated into a total revenue forecast.  Capacity-based measure: For example, a retailer’s revenue may be forecasted based on same-store sales growth and sales related to new stores.  Return or yield based measure: Forecasts based on balance sheet accounts. For example, a bank’s interest revenue can be calculated as loans multiplied by the