chapter 6 financial forecasting
TRANSCRIPT
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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.
Time-series Models (cont.)
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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
Time-series Models (cont.)
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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
Time-series Models (cont.)
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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