5.7 Company Analysis: Forecasting Flashcards
The final component of an analyst’s report is to
develop a projection of the company’s financial performance over a specified horizon
What to Forecast?
Common forecast objects include:
Drivers of financial statement lines
Individual financial statement lines
Summary measures
Ad hoc objects
Drivers of financial statement lines
These include top-down and/or bottom-up factors that have a strong relationship with major performance metrics such as sales, COGS, and SG&A expenses
Drivers provide explanatory power that can help improve a forecast’s credibility and accuracy.
Individual financial statement lines
For items that are less material and/or lack clear drivers, an analyst may defer to estimates provided by management or assume a linear trend.
An outside analyst may lack access to the information needed to provide a better estimate of items such as depreciation or other current assets.
Summary measures
Forecasting a high-level summary measure (e.g., earnings per share) is appropriate if the metric is relatively stable and predictable.
While this approach is less transparent than a projection of a company’s complete set of financial statements, it may be the only option available when the company is not required to issue public financial disclosures.
Ad hoc objects
These include items that have not yet appeared on a company’s historical financial statements, such as an anticipated write-down of an asset that the company is currently carrying at its historical value.
Analysts may also forecast the financial impact of ad hoc events such as natural disasters and legal proceedings.
Forecast Approaches
Company forecasts are typically developed using one (or a combination of) the following approaches:
- Historical Results: Assume past is precedent
- Historical Base Rates and Convergence
- Management Guidance
- Analyst’s Discretionary Forecast
Historical Results: Assume past is precedent
why is this kind of a flawed method?
When a company operates in a cyclical industry, forecasts based on the assumption that the past is precedent may be appropriate for a multi-year forecast, but this approach is less appropriate if the forecast is for a specific year.
This approach is also inappropriate for a company that is implementing a significant change to its business model or experiencing a significant structural change in its competitive environment.
normalized earnings
a company’s expected profit in equilibrium economic conditions with no impact from unusual or temporary factors such as mergers, restructurings, or changes in strategy.
better with longer time frames
ecause the terminal value can be a substantial proportion of a company’s overall valuation, it is important for analysts to adhere to the following guidelines:
Projected free cash flows should be normalized to mitigate the impact of temporary macroeconomic or company-specific factors.
The assumed terminal growth rate must be consistent with macroeconomic reality (i.e., a company cannot grow faster than the overall economy in perpetuity) and may differ significantly from the company’s historical growth rate. Estimates of terminal value are heavily influenced by the growth rate assumption, so this input must reflect a realistic assessment of the conditions that a company is likely to encounter in the future.
Forecasts can be skewed by inflection points that mark a structural change in the business cycle or the company’s life cycle. Inflection points can be difficult to predict because they are often driven by relatively unpredictable factors such as technological change.
Valuations are inherently uncertain. Disruptive events (e.g., financial crises) significantly impact all companies, even those with solid business models, particularly if they have high levels of operating and financial leverage.
Forecasts of company performance typically begin with a
projection of top line revenue, which can be done using either a top-down or bottom-up approach
Top-down Approaches to Modeling Revenue
Revenue can be modeled with growth relative to GDP growth. Alternatively, the analyst can forecast revenues at the industry level and then extrapolate based on a company’s market share
Commonly used top-down revenue forecasting methods include:
Growth relative to GDP growth
Market growth and market share
Bottom-up Approaches to Modeling Revenue
Bottom-up revenue forecasts begin within the individual company and then arrive at an aggregate amount based on estimates for each business segment, product line, or geographical source
Examples of bottom-up revenue modeling methods include:
Volume and average sale price
Product-line or segment revenues
Capacity-based measures
Returns- or yield-based measures
