VALUE LINE PUBLISHING,
OCTOBER 2002

Teaching Note

This case follows the performance-review and financial-statement-forecasting decisions of a Value Line analyst for the retail-building-supply industry in October 2002. The case contrasts the strong operating performance of Home Depot with the strong stock-market performance of Lowe’s. Students examine a financial-ratio analysis for Home Depot that acts as a template to generate a comparable ratio analysis for Lowe’s. The students’ ratio analysis is designed to build intuition with respect to interpreting individual ratios as well as ratio inter-relationships (e.g., the DuPont framework). The historical-performance comparison suggests that investors are skeptical of the ability …show more content…
Shareholders appear to have lost confidence that Home Depot can maintain its profit-and-growth trajectory. Some evidence of the company’s faltering performance lies in its lower existing-store growth. Given the magnitude of Home Depot’s retail space, investors may question the ability of the chain to find new markets.

The bottom line: manager performance is best measured by the impact on future cash flow. The historical-ratio analysis is helpful to the extent it can predict future performance. This theme sets the stage for the forecasting discussion.

2. How does the Home Depot forecasting model work? Why do we use ratios to forecast financial statements?

The instructor can ask the students to walk through the mechanics of the model, focusing on the 2002 forecast. Discussion on the use of ratios can highlight the importance of maintaining sensible relationships across line items. The discussion should also highlight that financial analysts find it easier to forecast ratios than to forecast expressly the line items themselves because such ratios as margins or turnover have economic meaning.

The instructor may also want to draw attention to the organization of the model. The assumptions drive the financial forecast by referencing the relevant cells. By putting the assumptions all at the top of the model, the analyst can also easily alter the assumptions and measure the impact.

3. How