Book 3_FinAn_READING-40_INTRODUCTION-TO-FINANCIAL-STATEMENT-MODELING Flashcards
Developing sales-based pro forma financial statements
Step 1: Estimate revenue growth and future expected revenue.
Step 2: Estimate COGS.
Step 3: Estimate SG&A.
Step 4: Estimate financing costs.
Step 5: Estimate income tax expense and cash taxes, taking into account changes in deferred tax items.
Step 6: Model the balance sheet based on items that flow from the income statement and estimates for important working capital accounts.
Step 7: Use historical depreciation and capital expenditures to estimate future capital expenditures and net PP&E for the balance sheet.
Step 8: Use the completed pro forma income statement and balance sheet to construct a pro forma cash flow statement.
Behavioral factors may affect analyst’s forecasts:
- Overconfidence bias
- Illusion of control bias
- Conservatism bias or anchoring
- Representativeness bias
- Confirmation bias
Porter’s five forces
- less (more) pricing power when the threat of substitute products is high (low) and switching costs are low (high).
- less (more) pricing power when the intensity of industry rivalry is high (low).
- Pressure on input costs is higher when the bargaining power of suppliers is high.
- less pricing power when the bargaining power of customers is high.
- more pricing power when the threat of new entrants is low.
Vertically integrated companies
are likely to be less affected by increasing input costs.
The effect on sales of increasing product prices to reflect higher COGS
- depend on the elasticity of demand for the products
- and on the timing and amount of competitors’ price increases.
The forecast horizon for a buy-side analyst
may be the expected holding period for a stock.
The forecast horizon for highly cyclical companies
should include the middle of a cycle so that the analyst can forecast normalized earnings.
Earnings projections over a forecast period
based on the historical average growth rate of revenue over the previous economic cycle.
Overconfidence bias
too much faith in one’s own work. Analysts may underestimate their forecasting errors;
Illusion of control bias
- overestimating what an analyst can control and trying to control things an analyst cannot control
- This bias is manifested in two primary ways: seeking “expert” opinions to justify a forecast, and making a model more complex (e.g., by including more independent variables)
Conservatism bias
This is also called anchoring, where the analyst makes only small adjustments to their prior forecasts when new information becomes available
Representativeness bias
- a tendency to rely on known classifications
- Sometimes, new information may only be superficially similar to a known classification but may be better viewed from a fresh perspective
Confirmation bias
Confirmation bias causes an analyst to seek out (or pay attention to) data that affirms their earlier convictions, and to disregard or underestimate information that calls those opinions into question