Chapter 6 Financial Forecasting

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Financial Management Oxford Fajar Sdn. Bhd. (008974-T) 2010


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Chapter 6

Financial Forecasting


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Learning Objectives

At the end of this chapter, you should be able to:

Explain the purpose and importance of financialforecasting

Identify and explain the various forecasting techniques Prepare various budgets for a particular scenario in a

firm

Prepare proforma financial statements

Provide suggestions as to the alternatives available toa firm when it faces cash shortfalls

Explain the limitation of the percent of sales forecastmethod


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Introduction

Forecasting represents an integral part of anyplanning process that is undertaken by all firms.

Firms must make decisions today that will affect the

firm in the future. It means thinking in advance about the future, and

being able to devise alternative actions that can beimplemented.

It represents the firms ability to respond to eventsthat present itself in the future.


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Types of Forecasts


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Time-series Models

Predict the future by using historical data

Moving average

Assumes that market demands stay fairly steadyover time as it smoothes out variations

Four-month moving average is found by summing

up the demand during the past four months anddividing it by four


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With each passing month, the most recent monthsdata is added to the sum of the previous threemonths data, and the oldest months data isdropped

This enables the smoothening out of short-termirregularities in the data series

Moving average F =t+1 A + A + + At t-1 t-n+1n

Time-series Models (cont.)


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Exponential smoothing

Formula:

New forecast = Last periods forecast + (Last

periods actual value Last periods forecast) The latest estimate is equal to the previous

estimate, but adjusted by a fraction of the error

The smoothing constant is given by , which can be

increased to give more weight to recent data ordecreased to give more weight to past data.



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Trend projections

Attempt to fit a trend line to a series of historicaldata points

Projects the line into the future for medium- to long-range forecasts

Decomposition

Involves breaking down past data into components

and then projecting the data forward. Fourcomponents:

a) Trendgradual upward or downward movement of thedata over time



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b) Seasonalitypattern of demand fluctuation above orbelow the trend line that occurs every year

c) Cyclespatterns in the data that occur every several

years, which are usually tied into the business cycled) Random variationsthese are blips in the data

caused by chance and unusual circumstances nodiscernible patterns



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Causal Models

Identify and incorporate variables or factors thatmight influence the quantity being forecasted, intothe forecasting model

Regression analysisfor single factor modelsThe basic model is: y = a + bx

where:


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Multiple regression analysisfor multi-factormodels.

Given by the equation:

y = a + b1x1 + b2x2 + b3x3 +

Causal Models (cont.)


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Qualitative Models

Incorporate factors that are either judgemental orsubjective into the forecasting model

Delphi methodallows experts to make forecasts;

involves decision-makers, staff personnel andrespondents

Jury of executive opinionmakes use of opinions ofa small group of high-level managers. Then, using

statistical models, a forecast figure is obtained


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Qualitative Models (cont.)

Sales force compositeeach salesperson is asked toprovide estimates of what sales he or she is likely toachieve or what sales may be generated in a particularlocation or region under that particular sales persons

responsibility. These forecasts are then compiled andgrouped together, at branch, district, regional, nationallevel, geographic regions and international levels

Consumer market surveyinputs from customers or

potential customers are solicited regarding their futurepurchasing plans. Used when a firm seeks to launch anew product, i.e. market research as to a productsdesirability and the potential purchase pattern ofindividuals


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Sales Forecasts

Represent the firms estimate of the productquantity that the firm expects to sell in the future

Lengths of Time for Sales Forecasting

The farther into the future the firm projects, thegreater will be the uncertainties:

i) Short-range forecastsfewer than 3 months

ii) Intermediate forecasts3months to 2 years

iii) Long-range forecastsmore than two years


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Sales Budget

Shows the quantity of each product that the firmplans to sell and the intended selling price

Provides predictions of the total revenue (usually bymonth) from which cash receipts from customersmay be estimated

Provides the basic data for preparing budgets forproduction costs, and also for selling, distributionand administrative expenses


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Components in ProformaFinancial Statements

Proforma Income Statement

Proforma Statement of Financial Position

Proforma Cash Flow Statement

Others different types of budgets include the following: Cash budget

Sales budget

Production budget

Stock budget Purchasing budget

Labour budget


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Percent of Sales ForecastingMethod

The percent of sales forecasting formula is given asfollows:

Additional

financingneeded

Required

increase inassets

Increase

inliabilities

Increase in

retainedearnings

=

(AFN) = (A/S)gS (L/S)gS [ P(1+g)S D ]


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Percent of Sales ForecastingMethod (cont.)

(AFN) = (A/S)gS (L/S)gS [ P(1+g)S D ]

Where:

AFN = additional financing needed

A/S = typical ratio of quantity of assets to sales achieved (Thisindicates the increase in assets required per Ringgit ofincreased sales)

L/S = typical ratio of liabilities to sales achieved (This indicatesthe increase in liabilities per Ringgit of increased sales)

S = current year salesG = forecast growth in sales

P = net profit margin on sales

D = cash dividends to be paid


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Suggested Steps when there isa Forecast Shortfall of Funds

Obtaining new financing

Reducing assets balance

Increasing liabilities balance Reducing the sales growth rate

Reducing the amount of dividends to be paid


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Limitations of the Per Cent ofSales Forecasting Method

It provides reasonable estimation only whenasset requirements and financing sourcescan be assumed to be a constant percentageof sales

It assumes that there is a straight line ordirect proportion relationship between theforecast item and sales

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Chapter 6 Financial Forecasting