CHAPTER 5

FINANCIAL FORECASTING

FINANCIAL FORECASTING

• Percent of Sales Method

• Linear Trend Extrapolation

• Regression Analysis

PERCENT OF SALES METHOD

A. PERCENT OF SALES METHOD

• Simplest forecasting method

• Forecasting the income statement and balance sheet items as percentages of sales forecast

• Sales forecast is assumed to be given

PERCENT OF SALES METHOD

1. Forecasting Income Statement

2. Forecasting Assets on Balance Sheet

3. Forecasting Liabilities on Balance Sheet

4. Discretionary Financing

PERCENT OF SALES METHOD

1. Forecasting Income Statement

- Use Common-Size Income Statement

- Determine items that will change with sales:

i. Cost of Goods Sold

ii. Selling and G&A Expenses (maybe)

- Assume that the sales forecast is given

PERCENT OF SALES METHOD

2. Forecasting Assets on Balance Sheet

• We can not use common-size balance sheet for forecasting assets

• Decide on the Assets that may change with Sales:– Cash Balance – Accounts Receivable– Inventory– Plant and Equipment:– Accumulated Depreciation

PERCENT OF SALES METHOD

3. Forecasting Liabilities on Balance Sheet• We need to categorize liabilities into two groups:

a) Spontaneous Sources of Financing

Arise in ordinary course of business, change with sales

Example: Accounts Payable, Other Current Liabilities

b) Discretionary Sources of Financing

These sources of financing requires great effort. Involve upper-level management decisions. Do not change with sales.

Example: Bonds, Bank loans, Common and Preferred Stock

PERCENT OF SALES METHOD

• Accounts Payable and Other Current Liabilities– Change with sales

• Retained Earnings– Previous year level + Additions in this year (from

Income Statement

• Other Items of Liability Section– Assume same level as previous year

PERCENT OF SALES METHOD

4. Discretionary Financing• Balance sheet plug:

Total Assets – Total Liability and Owner’s Equity

• A negative value forecasts a surplus of discretionary financing

• A positive value, forecasts a deficit of discretionary financing, and means that more discretionary funds will be needed.

LINEAR TREND EXTRAPOLATION

B. LINEAR TREND EXTRAPOLATION• In the percent of sales method, we assumed that you are

given the sales forecast.• Assume that you are not given the sales forecast but you

have to do it yourself• TREND function of Excel

TREND(Known_Y’s, Known_X’s, New_X’s, Constant)Y is the variable we want to forecast (dependent variable)(in our example

it is Sales)X is the variable we use to forecast Y (independent variable) (in our

example, it is Years)New_X is the new variable value to forecast Y Constant is a TRUE/FALSE variable. If you want an intercept, write True,

else write False.

Adding a Trendline to the Chart• Double Click the X-Y scatter chart, click on

the plot and right click the mouse

Choose Insert Trendline from the menu• Displaying the Trend Equation

- Right click the mouse on the trendline, choose Format Trendline, go to Options tab select Display Equation on the Chart -

REGRESSION ANALYSIS

C. REGRESSION ANALYSIS

Regression analysis is the method used to fit the best line to a data set

The best line is the line that minimizes the sum of squared errors. The errors are the difference between the actual data point and the one predicted by the model.

REGRESSION ANALYSIS

• Example:

Suppose you want to buy a Yahoo stock, and you want to know how the stock price moves with the market

You want to explain the return on Yahoo stock by the return on S&P 500 index

REGRESSION ANALYSIS

• First, you should collect data on the returns of Yahoo and S&P 500.

• Enter these data on Excel (Most probably, the data you found will be price data)

• Find the returns

Return = (Price Now) / (Price one period ago) - 1

• Note after finding the first returns of S&P 500, and Yahoo, drag the formulas to other cells

REGRESSION ANALYSIS

• Select the return range of S&P 500 and Yahoo, go to Chart Wizard, and create a Scatter Plot, choose Use 1st Column as X data, so S&P 500 returns will be on the X-axis, and Yahoo returns will be on the Y axis

REGRESSION ANALYSIS

• Analyzing the relation between the returns of Yahoo and S&P 500 from the Scatter diagram is a little difficult. You can possibly detect a vague positive relation between the Yahoo and S&P 500 returns.

• You can add a trend line in the chart to help you see the linear relation.

REGRESSION ANALYSIS

• Regression Equation:

You want to explain the returns of Yahoo in relation to the returns of S&P 500. Similar to the Linear Trend Equation the equation is as follows:

Yahoo Return = a + b*(S&P500 return) + e

REGRESSION ANALYSIS

Here Yahoo returns is the dependent variable that we want to explain

S&P500 returns is the independent variable we use to explain Yahoo returns

a is the intercept of the regression equation

b is the slope of regression equation

e is the error term: Error between the actual data and the fitted data

REGRESSION ANALYSIS

• Regression Analysis Using Excel

- Go to Tools Menu, click on Data Analysis

- Select Regression

- When the regression dialog box appears,

Enter the range which covers Yahoo Returns in the Input Y Range (Y is our dependent variable)

Enter the range which covers S&P500 Returns in the Input X Range (X is our dependent variable)

REGRESSION ANALYSIS

- If labels are included in the entered range in X and Y values, check the Label box

- Tell Excel to form a sheet for the regression results. To do this

Select New Worksheet Ply, and in the right box enter a name for sheet e.g.; Yahoo vs. S&P500

-Press OK

REGRESSION ANALYSIS

- Regression results will appear in the Yahoo vs. S&P500 sheet

- Look at the coefficients

Intercept is:

Slope is S&P500:

So,

Yahoo Return = ______ + _______*S&P500 return

REGRESSION ANALYSIS

- Interpretation of Regression OutputsP-value: The probability of observing a co-efficient at least this

magnitude if there were no relations between the dependent variable and the independent variables we observe.

Would a small p-value be a strong or weak evidence of a relation?

R-square: How much of the variation of the dependent variable is explained by the regression equation?

A larger R-square indicates better ability for the independent variables to explain the variations in Y.

REGRESSION ANALYSIS

• Typically, there are two steps involved in regression forecast.– Model estimation– Predictions with estimated parameters and new

values of the independent variables