methods of financial forecasting (including both qualitative & quantitative)

1. FINANCIAL FORECASTING
&PLANNING
SUBMITTED BY
INDU NATH JHA
ANKIT KUMAR
MAYANK KUMAR
POOJA SINGH
ANJALI SINGH

2. WHAT IS FINANCIAL FORECASTING?
 It is a Part of Planning process.
 They are inferences as to what the future may be.
 One of the key aspects of organizational management and is critical to the success
of all businesses
 Based on:
i. Economic assumptions (interest rate, inflation rate, growth rate and so on).
ii. Sales forecast.
iii. Pro forma statements of Income account and Balance sheet.
iv. Asset requirements.
v. Financing plan.
vi. Cash Budget

3. TYPES OF FINANCIAL FORECASTING
There are a number of methods that can be used to develop a
financial forecast.
These methods fall into two general categories
i. Qualitative Methods
ii. Quantitative Methods

4. QUALITATIVE METHODS
1. Executive Opinion:
The expert opinions of key personnel of various departments are gathered to arrive at
future predictions.
 The management team makes revisions in the resulting forecast, based on their
expectations.
2. Sales force Polling:
Companies believe that salespersons have close contact with the consumers
They could provide significant insights regarding customer behavior.
 The estimates are derived based on the average of sales force polling.

5. QUALITITAVIE METHODS…
3. Delphi Method:
A series of questionnaires are prepared and answered by a group of experts, who are kept
separate from each other.
On the basis of result of first questionnaire, a second questionnaire is prepared
This second document is again presented to the experts, who are then asked to reevaluate
their responses to the first questionnaire
This process continues until the researchers have a narrow shortlist of opinions.

6. QUALITATIVE METHODS…
4. Scenario Writing:
In this method, the forecaster generates different outcomes based
on diverse starting criteria.
The management team decides on the most likely outcome from
the numerous scenarios presented

7. QUANTITATIVE METHODS
1. Regression Analysis
Regression analysis is widely used for prediction and forecasting.
It is analysis of average relationship between two or more variables.
In this method basically there are two type of variables
i. Dependent Variable
ii. Independent Variable
 Basically it helps one understand how the typical value of the dependent variable
changes when any one of the independent variables is varied, while the other
independent variables are held fixed

8. Regression analysis…
 Let ‘x’ be the independent variable, then the line of regression can be given by,
y = a+bx
Now we have to find the best possible value of a & b.
 Line of Regression of x on y (by regression coefficient method):
𝑥 − 𝑥= 𝑟
𝜕𝑦
𝜕𝑥
(𝑦 − 𝑦)

9. Regression analysis….
Co-efficient of line of regression:
The slope of line of regression is called its ‘Co-efficient’, denoted by “b”
Since there ere two line of regression ‘y on x’ and ‘x on y’, there are two co-efficient,
denoted by,
&
𝑏 𝑦𝑥=𝑟
𝜕𝑦
𝜕𝑥
𝑏 𝑥𝑦= 𝑟
𝜕𝑦
𝜕𝑥

10. 2. Time series analysis:
It consist statistical data which are collected, recorded & observed over successive
interval of time.
More clearly it can be defined as successive observation of given phenomenon over a
period of time.
Components affect the result of time series are:
i. Secular Trend (T):
it shows the direction of the series in a long period of time. Effect of trend is gradual, but
extends more or less consistently throughout the entire period of time.
ii. Cyclic Fluctuation (C):
these are the fluctuations as a result of business cycles and are generally referred to as long
term movements that represent consistently recurring rises.

11. Components affecting time series….
iii. Seasonal Fluctuations (S):
• these are of short duration occurring in a regular sequence at specific intervals of
time.
• These fluctuations are the result of changing season.
iv. Irregular Fluctuations (I):
• Also known as “Random Fluctuations”
• These variations are take place in a completely unpredictable fashion

12. Time series analysis…
• For analysis of the time series, we usually have two models,
i. Multiplicative Model:
ii. Additive Model:
Y*= Observed values of time series
Y*= T×C×S×I
Y= T+C+S+I

13. 3. Proforma financial analysis:
• Proforma statements use sales figures and costs from the previous two to
three years after excluding certain one-time costs.
• This method is mainly used in mergers and acquisitions.
• Also in cases where a new company is forming and statements are needed
to request capital from investors.
• Pro forma Income Statement. (Represents the operational plan for the
whole organization.)

14. PREPARATION OF PRO FORMA INCOME STATEMENTS
Percent of Sales Method
• Assumes that future relationship between various elements of
cost to sales will be similar to their historical relationships.
• These cost ratios are generally based on the average of previous
two or three years.
• For example, Cost of Goods sold may be expressed as a
percentage of Sales.

15. 2. BUDGETED EXPENSE METHOD.
• Estimate the value of each item on the basis of expected
developments in the future period for which the pro forma P&L
a/c is being prepared.
• Calls for greater effort on the part of Management, since they
have to define the likely happenings.

16. 3. COMBINATION METHOD
• Neither the Percent of sales method nor the Budgeted expense
method should be used in isolation.
• A combination of both methods work best.
• Items which have stable relationship to sales can be forecasted using
the Percent of sales method.
• For items where the future is likely to be very different from the past,
budgeted expense method can be used.

17. PROFORMA INCOME
STATEMENTActual figures
for Quarter
31-3-2006
Assumptions Proforma for
the qr ended
30-6-2006
1.No.of units
sold
2.Net Sales
3.Cost of Goods
sold:
4.Labour
5. Materials
6.Distribution
cost
7. Overhead
8. Total
9. Ratio of CGS
to Sales.
10. Gross Profit
11. GP Margin
14000
140000
100%
22960
25256
4592
61992
114800
82.0%
25200
18%
Sales decline 30%
due to low
demand.
No change in
Product mix.
20% of Cost of
good
22% of COG
4% of COG
54% of COG
Increase by 1.5%
9800
98000
100%
16366
18002.6
3273.2
44188.2
81830
83.5%
16170
16.5%

18. CONTD.
Actuals Assumption Proforma
12. Expenses:
13. Selling
Expenses
14. Admin.
Expense
15. Others
16.Total
17. Operating
Profit
18. Interest
19. Depreciation
20.PBT
21. Tax @ 30%
22.Net Income
23.Dividends
24.Retained
earnings.
25. Cash flow
after
dividends.
8250
4450
Nil
12700
12500
2500
2000
7000
2100
4900
900
4000
6000
A drop of Rs.
750 .
A drop of Rs.
850
Rs.2000 only
No dividends
Carried to B/s.
Retained
earning +
Depreciation
7500
3600
Nil
11100
5070
2000
2000
1070
321
749
0
749
2749