Financial Statement Analysis*Financial Forecasting

FIN 419

Prepared by Jean Claude Rwubahuka

Email: jcrwubahuka@sfb.ac.rw

Definitions Financial Planning (Financial Statement

Forecasting): Using the understanding of the financial system

to project sales, income and assets needed based on production and marketing strategies.

Assessing operating cash flows to determine financial resources needed.

Planning sources of any additional funds. Managing cash to repay investors.

Planning - Step 1: Sales Forecast All profit and resource (balance sheet)

forecasts are based on the sales forecast. This is probably the most difficult step. Should be based on marketing strategy,

estimates of market share, economic forecasts, etc.

Planning - Step 1: Sales Forecast One major reason for forecasting financial

statements is to plan for cash needs. Therefore it is absolutely critical that seasonal factors are taken into consideration.

Regression can be used to estimate future sales. There are better methods available, but this is the

only one with which you are likely to be familiar.

Planning - Step 1: Sales Forecast The first step in running a time-series

regression is collecting the quarterly sales. There are two sources for quarterly sales data:

The 10-k usually contains quarterly operating information for the last two years.

If that doesn’t work, you can get the sales off the 10-Q reports (quarterly financial statements). There is no 4th quarter 10-Q, back out fourth quarter

using the annual data in the 10-k

Planning - Step 1: Sales Forecast Collect five years of quarterly sales data, and

order them from oldest to most current. Because sales are what we want to predict, we

will use them as our dependent (response) variable.

The only independent (predictor) variables we will use are time and season. Time will indicate how many quarters have

lapsed. Season is a set of indicator (dummy) variables.

Planning - Step 1: Sales Forecast

Quarter Sales Time 1st Qtr 2nd Qtr 3rd Qtr1999 1st Qtr 13,622,730 1 1 0 0

2nd Qtr 23,200,428 2 0 1 03rd Qtr 34,458,907 3 0 0 14th Qtr 26,817,119 4 0 0 0

2000 1st Qtr 15,131,033 5 1 0 02nd Qtr 23,114,100 6 0 1 03rd Qtr 37,230,069 7 0 0 14th Qtr 27,753,785 8 0 0 0

2001 1st Qtr 16,063,895 9 1 0 02nd Qtr 22,006,132 10 0 1 03rd Qtr 38,490,267 11 0 0 14th Qtr 26,759,512 12 0 0 0

2002 1st Qtr 13,749,588 13 1 0 02nd Qtr 19,194,071 14 0 1 03rd Qtr 30,453,543 15 0 0 14th Qtr 25,561,519 16 0 0 0

2003 1st Qtr 13,754,941 17 1 0 02nd Qtr 21,863,148 18 0 1 03rd Qtr 41,349,824 19 0 0 14th Qtr 29,196,840 20 0 0 0

For Rocky Shoe & Boot Company the data look like this:

Planning - Step 1: Sales Forecast We will be using Excel’s regression function. Make sure your copy of Excel has the Analysis

Toolpak added-in. To check, click on the Tools menu.

One option on that menu should be Data Analysis. If that option is there then you are good to go. If not you will have to add it in.

Planning - Step 1: Sales Forecast If Data Analysis is not under the Tools menu,

then choose Add-Ins from the Tools menu. Then click on both Analysis Tool-Paks. Then click OK

Now we should be ready to conduct a regression analysis.

Planning - Step 1: Sales Forecast Under the Tools menu, choose Data Analysis.

From the dialog box, choose regression. This will bring up another dialog box.

Using the box next to the Y-Range, highlight the Sales data you collected.

Using the box next to the X-Range, highlight the time, and seasonal variables you created. Both of these ranges should cover just as many rows!!

Tell Excel where to put the output and click OK.

Planning - Step 1: Sales Forecast Our model in our example has been set up to

forecast sales as a function of time, and season: Sales = constant + slope1*time + slope2*Qtr1 +

slope3*Qtr2 + slope4*Qtr3

For any quarter in the future, we will only need to forecast the time variable and the set of indicator variables to get a sales forecast.

Planning - Step 1: Sales Forecast The forecasts based on this model can be

found in a spreadsheet. Based on the regression output, the seasons

are statistically significant, but time is not. Meaning, there is a seasonal component to their

sales. However, sales do not appear to grow over time.

Planning - Step 1: Sales Forecast

$0

$5,000,000

$10,000,000

$15,000,000

$20,000,000

$25,000,000

$30,000,000

$35,000,000

$40,000,000

$45,000,000

1999 2000 2001 2002 2003 2004 2005 2006

AcutalEstimated

Planning - Step 2: Project Income Start from the sales forecasts Identify those lines of the income statement

that depend on sales (are variable) and those that don’t (are fixed).

Project all lines based on estimates of sales. Using the 10-Q, regression can be used to

estimate the variable/fixed components of costs as a function of sales.

Planning - Step 2: Project Income To empirically model fixed versus variable

costs, use the following regression equation: y = fixed portion + variable portion (sales) To estimate the fixed and variable portions, use

the regression modeling functions as described earlier. The y variable is the subject cost. The x variable is the sales. Excel will estimate the fixed/variable coefficients.

Planning - Step 2: Project Income In each case, use the statistical tests to assess

whether a relationship exists between the cost and sales. If there isn’t a relationship, assume it to be a

relatively fixed cost. After using regression, use your head to come

up with the final estimates, which can be vastly different from the regression estimates.

Planning - Step 2: Project Income After you have projected all lines of the

income statement, assess the dividend policy of the company. Do they declare a fixed amount as dividends? Do they declare a proportion of earnings as

dividends? Then project the dividends declared based on

their past behavior.