Financial Statement Analysis *Financial Forecasting

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Presentation transcript:

Financial Statement Analysis *Financial Forecasting 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 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

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.