Financial Statement Forecast Models in Equity Valuation

This module forecasts financial statements and derives cash flows from that forecast, letting an analyst assume separate drivers for revenue, expenses, investment, and financing rather than one overall growth rate. Valuations built this way are called disaggregated valuation models.

FCFF under this approach is built from underlying drivers:

• Revenue — total addressable market, market share, segment sales, demand trends
• Expenses — pricing power, materials and labor costs, cost efficiencies and margins
• Assets — asset growth and efficiency, working capital, gross fixed investment
• Financing — debt/equity mix, after-tax cost of debt, cost of equity, debt tenor and type

Extended over a multi-year horizon, this FCFF forecast can be used two ways:

Present value (DCF):

$$ {IV}_t = \sum_{i=1}^{n} \frac{ {FCFF}_{t+i}}{(1+ {WACC})^i} + \frac{E(P_{t+n})}{(1+ {WACC})^n} $$

Relative value (EV/FCFF):

$$ {IV}_t = {FCFF}_{t+1} \times {EV\ Multiplet} $$

where:

$$ {{EV \text{ Multiple}}_t} = \frac{ {EV}_{t+i}}{ {FCFF}_{t+i}} $$

A disaggregated model also typically yields revenue and/or EBITDA forecasts, which, paired with an appropriate peer multiple, give the terminal value \(E(P_{t+n})\), discussed later.

1. Rationale for Disaggregated Models

Disaggregated valuation models translate an analyst’s narrative about a company’s future into an estimate of firm or equity value through underlying value drivers. Rather than assuming a single aggregate growth rate for cash flows, these models allow an analyst to make separate assumptions about revenue growth, profit margins, asset investment, and financing activities.

Disaggregated models are appropriate whenever cash flow components are expected to grow at different rates over time. When an analyst assumes varying growth rates across income statement and balance sheet components, the resulting overall cash flow growth rate differs from that of any individual component.

For example, consider a mature firm with stable earnings growth but an expected increase in its dividend payout ratio due to fewer profitable investment opportunities. A disaggregated model explicitly captures this narrative: dividends per share grow faster than earnings per share during the period when the payout ratio increases. A constant-growth model assuming a stable payout ratio would miss this effect entirely.

When to use disaggregated models:

1. When revenue, expenses, and investment exhibit different growth trajectories
2. When the company’s capital structure or dividend policy is expected to change
3. When the analyst wants to communicate specific assumptions underlying the valuation
4. When scenario analysis requires flexibility in modifying individual model inputs

2. Construction of Disaggregated Models

Model construction begins with gathering historical financial statements and making any necessary adjustments for different accounting standards or policy choices. The analyst then determines the appropriate level of detail based on the value drivers most relevant to the company.

The simplest FCFF forecast combines expected net operating profit after taxes (NOPAT) with net investment.

NOPAT equals revenue less cost of goods sold (COGS), selling, general, and administrative expenses (SG&A), and depreciation and amortization (D&A), all after tax:

$$ {NOPAT} = [ \text{Revenue} – \text{COGS} – {SG\&A} – {D\&A}](1 – t) $$

where \(t\) is the firm’s tax rate.

Net investment consists of the change in working capital plus the change in net long-term assets:

$$ {\text{Net investment} }= \text{Working capital} + \text{Net long – term assets} $$

A more detailed NOPAT projection can break this down further into separate forecasts of revenues, COGS, additional operating expenses (such as SG&A and depreciation), and the tax rate.

Areas of Focus

Exhibit 1: Key Modeling Areas

$$
\begin{array}{l|l}
\textbf{Area} & \textbf{Purpose} \\
\hline
\text{Revenue} & \text{Forecast future sales using historical, bottom-up, or top-down approaches.} \\ \hline
\text{Expenses/Profit Margins} & \text{Project costs and profitability drivers} \\ \hline
\text{Asset Growth & Efficiency} & \text{Model working capital and long-term asset investment} \\ \hline
\text{Financing} & \text{Determine how growth is funded through debt, equity, or internal cash.} \\
\end{array}
$$

Revenue Model Construction

1. Historical Revenue Model

For mature companies with established products and stable competitive environments, past revenue growth provides a reasonable basis for projections. This approach works well for firms with predictable demand and limited growth prospects.

2. Bottom-Up Revenue Model

This approach forecasts revenue based on fundamental units of business activity:

• Unit sales \(\times\) price per unit
• Capacity-based measures (e.g., available seat-kilometers for airlines)
• Same-store sales growth for retail chains
• Subscriber growth and average revenue per user for subscription-based businesses

3. Top-Down Revenue Model

This approach starts with overall market size projections and applies the company’s expected market share:

• Project total market demand (units \(\times\) price)
• Estimate the company’s market share percentage
• Calculate revenue as market size \(\times\) market share

Expense or Profit Model Construction

1. Historical Expense Model

Regression analysis can estimate the relationship between expense growth and revenue growth:

$$ \text{Change in expense} = a + b \times (\text{Change in revenue}) $$

The intercept term (\(a\)) captures fixed costs, while the slope coefficient (\(b\)) measures how expenses vary with revenue changes.

2. Itemization of Economically Significant Expenses

For certain industries, significant expenses may not be shown separately in standardized financial statements. An analyst may need to access as-reported financial statements or annual report disclosures to model items like:

• Labor costs
• Raw materials or fuel costs
• Research and development expenses
• Selling and distribution costs

3. Direct Profit Margin Assumptions

An analyst may directly assume changes in gross or operating profit margins. This approach implies specific growth rates for underlying expenses. For example, if revenue grows at \(10\%\) and gross margin improves from \(60\%\) to \(62\%\), COGS must grow at a rate below \(10\%\).

Asset Model Construction

Asset models provide the foundation for estimating cash outflows for investing as part of the free cash flow calculation.

Historical Asset Models

Regression analysis can estimate the relationship between asset growth and revenue growth:

$$ \text{Change in asset line item}_t=a+b \times {\%\text{Change in revenue}}_r $$

When assets and revenues grow at the same rate, asset turnover ratios remain constant. However, some companies require disproportionate investment to support growth, while others achieve growth with relatively less investment.

Itemized Asset Model Forecasts

Balance sheet projections estimate investment spending by assuming that changes in operating asset and liability accounts represent uses or sources of cash:

• Operating assets that involve cash payments should be projected to grow
• Non-operating assets (e.g., marketable securities) should not be forecast to grow unless capturing changes in cash
• Goodwill impairments reflecting market value changes (not cash changes) should not be modeled as cash flows

Financing Model Construction

Financing requirements must be estimated to project FCFE accurately. The financing needs calculation follows this process:

Step 1: Forecast operating assets to obtain expected changes

Step 2: Forecast non-debt liabilities to obtain expected changes

Step 3: Forecast retained earnings changes by deducting dividends from net income

$$ \text{Financing Needs} = \Delta \text{Operating Assets} – \Delta \text{Non-Debt Liabilities} – \Delta \text{Retained Earnings} $$

Interpretation:

• Positive financing need \(\rightarrow\) Company requires external debt or equity
• Negative financing need \(\rightarrow\) Company generates surplus cash

Allocating Financing Needs

$$
\begin{array}{l|l}
\textbf{Financing Need > 0 (Additional Capital Needed)} & \textbf{Financing Need < 0 (Excess Cash Available)} \\ \hline \text{Cash: May be used as a source of capital} & \text{Cash: May be added to cash balance} \\\hline \text{Debt: May be issued (check debt ratio)} & \text{Debt: May be repaid (check debt ratio)} \\\hline \text{Equity: May be issued (if track record exists)} & \text{Equity: May be returned via repurchases or dividends} \\ \end{array} $$

3. Uses of Financial Statement Models in Equity Valuation

Financial statement models serve multiple purposes in equity valuation:

1. Estimating Intrinsic Value: Disaggregated models produce forecasted free cash flows that feed into present-value models or relative-valuation multiples. Projected FCFF can be used in discounted cash flow analysis, while projected income measures can support terminal value estimation.
2. Updating Valuations with New Information: As companies file quarterly or semi-annual financial reports, models are updated to reflect new information. Changes in observable variables (e.g., revenue growth, profit margins) can be directly compared to share price movements.
3. Scenario and What-If Analysis: Disaggregated models allow analysts to test alternative assumptions about:
   • Revenue growth under different economic conditions
   • Cost structure responses to volume changes (fixed vs. variable costs)
   • Investment requirements under different growth scenarios
   • Financing choices and their impact on cash flows
4. Capturing Complex Cost Structures: Unlike constant-growth models, disaggregated models can incorporate the effects of fixed versus variable costs. A company with high fixed costs experiences amplified changes in profit margins during cyclical swings: sharp margin improvements in growth periods and losses during downturns.

Example: Dividend Payout Policy in a Disaggregated Model

An analyst values a mature utility company using a dividend discount model. The company historically paid \(50\%\) of earnings as dividends. The analyst expects earnings per share (EPS) growth to decline from \(10\%\) to \(4\%\) over five years. The analyst assumes the dividend payout ratio will increase from \(50\%\) to \(70\%\) over this period as investment opportunities diminish.

$$
\begin{array}{c|c|c|c|c|c}
\textbf{Year} & \textbf{EPS Growth} & \textbf{Payout Ratio} & \textbf{EPS} & \textbf{DPS} & \textbf{DPS Growth} \\
\hline
0 & – & 50.0\% & 2.00 & 1.00 & – \\\hline
1 & 10.0\% & 50.0\% & 2.20 & 1.10 & 10.0\% \\\hline
2 & 10.0\% & 50.0\% & 2.42 & 1.21 & 10.0\% \\\hline
3 & 8.5\% & 55.0\% & 2.63 & 1.45 & 19.8\% \\\hline
4 & 6.0\% & 62.5\% & 2.78 & 1.74 & 20.0\% \\\hline
5 & 4.0\% & 70.0\% & 2.89 & 2.02 & 16.1\% \\
\end{array}
$$

Observation:

DPS growth exceeds EPS growth in Years 3–5 because the rising payout ratio offsets the slowing EPS growth. A constant-growth model with a fixed \(50\%\) payout ratio would have produced DPS growth equal to EPS growth, underestimating the cash flows available to shareholders.

Question

A disaggregated valuation model is most appropriate when:

1. all cash flow components are expected to grow at the same rate.
2. cash flows are expected to remain constant over the forecast horizon.
3. different cash flow components are expected to grow at different rates.

Solution

The correct answer is C.

A disaggregated model is most appropriate when cash flow components are expected to grow at differing rates. This allows the analyst to model revenue, expenses, assets, and financing separately, producing an overall cash flow growth rate that reflects the combined effect of these varying assumptions.

A is incorrect. When all components grow at the same rate, a simpler constant-growth model produces comparable results. The disaggregated approach offers no advantage in this scenario.

B is incorrect. With zero growth for all components, cash flow remains constant. Both disaggregated and constant-growth models yield identical results, making the disaggregated approach unnecessary.