qt project report
TRANSCRIPT
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ASIAN BUSINESS SCHOOL
PROJECT FOR
QUANTITATIVES TECHNIQUESTOPIC
QUANTITATIVES TCHNIQUES IN BUSINESS SCENARIO
SUBMITTED TO: Mrs.Rupali Mishra Nigam
SUBMITTED BY:Ritika Raj,Vandana Soni, Prabin Kr. Singh
COURSE: PGDM+MEDIA MGMT.
1st
Semester
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CERTIFICATION
This is to certify that this project of quantitative techniques on topic ofUSE OF
QT IN BUSINESS SCENARIO is a bonafide research work carried out by
Ritika Raj,Vandana Soni and Prabin Kr. Singh students of ABS,PGDM 1st
semester.
Signature of faculty
(Mrs. Rupali Mishra Nigam)
Dean, Signature
(Dr. Latika Sahni)
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ACKNOWLEDGEMENT
The completion of any project is not complete without thanking the people behind the
venture & this project is no exception. Racing against the time & fast approachingdeadlines, the fact that I am able to successfully complete the project just in time would
not have been possible without the help and support of many people. Their constant
guidance & encouragement coupled with my commitment were the cornerstones for the
successful completion of the project.
It gives us immense pleasure t acknowledgement the teachers whose help gave the needed
confidence, enthusiasm, and perseverance. I express my gratitude to my teacher Mrs.
Rupali Mishra Nigam maam for providing the excellent guidance and opportunities to
complete this project. I express my thanks to respected Prof. Dr. Latika Sahni, Dean,
Asian Business School (ABS) Noida, for extending her support.
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EXECUTIVE SUMMARY
In the project the researcher made an effort to know how quantitative techniques can be
used in business. The respective work helped us in gaining knowledge regarding the use of
quantitative techniques.
We analyzed all financial data thoroughly.
Further, We also came to know about the types of business situations in which qt can be
used.
The objective of this project is to study & analyze the types of business situations and the
prospective of the study of quantitative techniques in business scenario.
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TABLE OF CONTENTS
(1)The Need Of Quantitative Techniques in Business decisions With Examples.
(1.1) 1st
situation
(1.2) 2nd situation
(1.3) 3rd situation
(2)Use of pictorial representation of data with examples.
(3)How pictorial representation of data helps to analyze business situations?
(4)BIBLIOGRAPHY
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Project On Quantitative Techniques
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Quantitative Techniques in BusinessIn the business world and in every aspect of life quantitative techniques are used
o assist in decision making.
Why?
Unlike classroom there is no enough information available in the real life situations
also to make correct decisions.
Therory1
(1)Seasonal variation is a component of a time series which is defined as the repetitive and
predictable movement around the trend line in one year or less. It is detected by measuring the quantity of
interest for small time intervals, such as days, weeks, months or quarters.
Organizations facing seasonal variations, like the motor vehicle industry, are often interested in
knowing their performance relative to the normal seasonal variation. The same applies to the
ministry of employment which expects unemployment to increase in June because recentgraduates are just arriving into the job market and schools have also been given a vacation for
the summer. That unemployment increased as predicted is a moot point, the relevant factor is
whether the increase is more or less than expected.
Organizations affected by seasonal variation need to identify and measure this seasonality to helpwith planning for temporary increases or decreases in labor requirements, inventory, training,periodic maintenance, and so forth. Apart from these considerations, the organizations need to
know if the variations they have experienced has been more or less would be expected given the
usual seasonal variations
Reasons for studying seasonal variation
There are several main reasons for studying seasonal variation:
The description of the seasonal effect provides a better understanding of theimpact this component has upon a particular series.
After establishing the seasonal pattern, methods can be implemented to eliminate
it from the time-series to study the effect of other components such as cyclical and
irregular variations. This elimination of the seasonal effect is referred to asdepersonalizing or seasonal adjustment of data.
To project the past patterns into the future knowledge of the seasonal variations is
a must for the prediction of the future trends.
http://en.wikipedia.org/wiki/Time_serieshttp://en.wikipedia.org/wiki/Linear_regressionhttp://en.wikipedia.org/wiki/Seasonalityhttp://en.wikipedia.org/wiki/Frequencyhttp://en.wikipedia.org/w/index.php?title=Deseasonalizing&action=edit&redlink=1http://en.wikipedia.org/wiki/Seasonal_adjustmenthttp://en.wikipedia.org/wiki/Seasonal_adjustmenthttp://en.wikipedia.org/w/index.php?title=Deseasonalizing&action=edit&redlink=1http://en.wikipedia.org/wiki/Frequencyhttp://en.wikipedia.org/wiki/Seasonalityhttp://en.wikipedia.org/wiki/Linear_regressionhttp://en.wikipedia.org/wiki/Time_series -
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Assumptions
A decision maker or analyst can make one of the following assumptions when treating theseasonal component:
The impact of the seasonal component is constant from year to year.
The seasonal effect is changing slightly from year to year.
The impact of the seasonal influence is changing dramatically.
Seasonal Index
Seasonal variation is measured in terms of an index, called a seasonal index. It is an average thatcan be used to compare an actual observation relative to what it would be if there were no
seasonal variation. An index value is attached to each period of the time series within a year.This implies that if monthly data are considered there are 12 separate seasonal indices, one for
each month. There can also be a further 4 index values for quarterly data. The following methodsuse seasonal indices to measure seasonal variations of a time-series data.
Method of simple averages Ratio to trend method Ratio-to-moving average me Link relatives method
EXAMPLE
Heavy discount ,promotion drive up sales:-After 3 months of sluggish growth,diwali has
lit up the retail market with customer durables, goods and automobiles companies predicting a crack in
season.Traditionallly the best time for retail sentiment, marketers were apprehensive about whether
macro-economic factors would dampen demand this year. The good news :Consumers are flocking
back to showrooms albeit lured by big discount and promotions.
http://en.wikipedia.org/w/index.php?title=Seasonal_index&action=edit&redlink=1http://en.wikipedia.org/wiki/Trend_estimationhttp://en.wikipedia.org/wiki/Moving_averagehttp://en.wikipedia.org/wiki/Moving_averagehttp://en.wikipedia.org/wiki/Trend_estimationhttp://en.wikipedia.org/w/index.php?title=Seasonal_index&action=edit&redlink=1 -
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Therory2
CYCLIC VARIATIONSCycle refers to recurrent variations in time series
Cyclical variations usually last longer than a yearCyclic fluctuations/variations are long term
movements that represent consistently recurring rises and declines in activity.BUSINESS CYCLE
Consists of 4 phases: prosperity decline depressions, recovery
purpose
(a)Measures of past cyclical behavior
(b)Forecasting
(c)Useful in formulating policies in business
EXAMPLE
ONGC net profit vaults 60% in Q2:-oil and gas company on 4 nov Friday posted a 60% jump
in et profit in second quarter ending September 0 on the back of higher crude price and reduced
subsidy outgo.the company reported a profit of Rs.862 cr. against Rs. 5389 cr. in the year ago
period.The company sells crude oil to state refiners at a discount to help compensate them partly losses
incurred on selling prices at government capped prices.The net profit would been higher by Rs. 3322
cr but for fuel subsidy payout,chairman Vasudeva said.
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Therory3
Sampling methodsWithin any of the types of frame identified above, a variety of sampling methods can be
employed, individually or in combination. Factors commonly influencing the choice between
these designs include:
Nature and quality of the frame
Availability of auxiliary information about units on the frame
Accuracy requirements, and the need to measure accuracy
Whether detailed analysis of the sample is expected
Cost/operational concerns
Simple random sampling
In a simple random sample ('SRS') of a given size, all such subsets of the frame are given anequal probability. Each element of the frame thus has an equal probability of selection: the frame
is not subdivided or partitioned. Furthermore, any givenpairof elements has the same chance ofselection as any other such pair (and similarly for triples, and so on). This minimises bias and
simplifies analysis of results. In particular, the variance between individual results within the
sample is a good indicator of variance in the overall population, which makes it relatively easy to
estimate the accuracy of results.
However, SRS can be vulnerable to sampling error because the randomness of the selection mayresult in a sample that doesn't reflect the makeup of the population. For instance, a simplerandom sample of ten people from a given country will on average produce five men and five
women, but any given trial is likely to overrepresent one sex and underrepresent the other.
Systematic and stratified techniques, discussed below, attempt to overcome this problem byusing information about the population to choose a more representative sample.
SRS may also be cumbersome and tedious when sampling from an unusually large targetpopulation. In some cases, investigators are interested in research questions specific to subgroups
of the population. For example, researchers might be interested in examining whether cognitive
ability as a predictor of job performance is equally applicable across racial groups. SRS cannot
accommodate the needs of researchers in this situation because it does not provide subsamples ofthe population. Stratified sampling, which is discussed below, addresses this weakness of SRS.
Simple random sampling is always an EPS design, but not all EPS designs are simple random
sampling.
EXAMPLE
http://en.wikipedia.org/wiki/Simple_random_samplehttp://en.wikipedia.org/wiki/Simple_random_sample -
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If the desired parameter is the mean annual salary of the income earning residents of a
particular county, a sample of 200 of these residents could be obtained and the annual salary
of each resident (element) in the sample could be determined and the mean annual salary of
the sample residents. If the sample is drawn in a random fashion from a frame, or list, of the
entire population, and if we use correct statistical techniques, the sample mean annual salary
(a statistic) may be a good estimate of the true mean annual salary (a parameter) of all the
residents of this county.
A population includes all the elements of interest. We use the term element to represent each
individual unit of a group in which we have interest.
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How do we use pictorial representation of data? with
examples.
Many people ask how many graphs or charts they should have in their business plans. As
with most other business planning questions, the answer is it depends.
There are many forms of representing data graphically:-They are
Bar graphs
Line Graph
Histogram
Frequency polygon
Pie chart
Radar
Waterfall model graph
Area Chart
Polar graph
Some are illustriated below:-
REPRESENTATION OF DATA
Besides the tabular form, the data may also be presented in some graphic or diagrammatic
form.The transformation of data through visual methods like graphs, diagrams, maps and charts is
called representation of data.The need of representing data graphically:Graphics, such as maps, graphs and diagrams, are used to represent large volume of data.They are necessary:
If the information is presented in tabular form or in a descriptive record, it becomesdifficult to draw results.
Graphical form makes it possible to easily draw visual impressions of data.
The graphic method of the representation of data enhances our understanding.
It makes the comparisons easy.
Besides, such methods create an imprint on mind for a longer time.
It is a time consuming task to draw inferences about whatever is being presented innongraphical form.
It presents characteristics in a simplified way.
These makes it easy to understand the patterns of population growth, distribution andthe density, sex ratio, agesex composition, occupational structure, etc.
General Rules for Drawing Graphs, Diagrams and Maps
1. Selection of a Suitable Graphical MethodEach characteristic of the data can only be suitably represented by an appropriate graphical
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method. For example,
mperature or growth of population between differentperiods in time line graph are used.
of the crop
producing areas are shown by dot maps.
Thus, it is necessary and important to select suitable graphical method to represent data.
2. Selection of Suitable ScaleEach diagram or map is drawn to a scale which is used to measure the data. The scale must
cover the entire data that is to be represented. The scale should neither be too large nor too
small.3. Design
The diagram or map should have following design:
iagram/map must be clear and include -
o The name of the area,
o Reference year of the data used ando The caption of the diagram.
Types of DiagramsThe diagrams and the maps is of following types:
(i) O ne-dimensional diagrams such as line graph, poly graph, bar diagram, histogram,
age, sex, pyramid, etc.;(ii) T wo-dimensional diagram such as pie diagram and rectangular diagram;
(iii) T hree-dimensional diagrams such as cube and spherical diagrams.
The most commonly drawn diagrams and maps are:
Line graphs
Bar diagrams
Pie diagram
Wind rose and star diagram
Flow Charts
1. Line GraphThe line graphs are usually drawn to represent the time series data related to the
temperature, rainfall, population growth, birth rates and the death rates.Construction of a Line Graph
1st step: Round the data to be shown upto the 1 digit of even numbers.
2nd step: Draw X and Y-axis. Mark the time series variables (years/months) on the X axis andthe data quantity/value to be plotted on Y axis.
3rd step: Choose an appropriate scale to show data and label it on Y-axis. If the data involves
a negative figure then the selected scale should also show it.
4th step: Plot the data to depict year/month-wise values according to the selected scale on Yaxis,mark the location of the plotted values by a dot and join these dots by a free hand drawn
line.
Example 1: Construct a line graph to represent the data
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2. PolygraphPolygraph is a line graph in which two or more than two variables are shown on a same
diagram by different lines. It helps in comparing the data. Examples which can be shown aspolygraph are:
in different states or countries in one diagram.
Construction of a Polygraph
All steps of construction of polygraph are similar to that of line graph. But different lines are
drawn to indicate different variables.
Example 2: Construct a polygraph to compare the variables.
3. Bar DiagramIt is also called a columnar diagram. The bar diagrams are drawn through columns of equal
width. Following rules were observed while constructing a bar diagram:
(a) The width of all the bars or columns is similar.(b) All the bars should are placed on equal intervals/distance.
(c) Bars are shaded with colours or patterns to make them distinct and attractive.
Three types of bar diagrams are used to represent different data sets:
agram
Simple Bar Diagram
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A simple bar diagram is constructed for an immediate comparison. It is advisable to arrange
the given data set in an ascending or descending order and plot the data variablesaccordingly. However, time series data are represented according to the sequencing of the
time period.
Example 3: Construct a simple bar diagram.
Construction Steps:
Draw X and Y-axes on a graph paper. Take an interval and mark it on Y-axis to plot data.
Divide X-axis into equal parts to draw bars. The actual values will be plotted according to theselected scale.
4. Line and Bar GraphThe line and bar graphs as drawn separately may also be combined to depict the data relatedto some of the closely associated characteristics such as the climatic data of mean monthly
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temperatures and rainfall.
Example 4: Construct a Line and bar Graph.Construction:
(a) Draw X and Y-axes of a suitable length and divide X-axis into parts to show months in ayear.
(b) Select a suitable scale with equal intervals on the Y-axis and label it at its right side.
(c) Similarly, select a suitable scale with equal intervals on the Y-axis and label at its left side.(d) Plot data using line graph and columnar diagram.
S u r y a v e e r S i n g h Page
5. Multiple Bar Diagram
Multiple bar diagrams are constructed to represent two or more than two variables for the
purpose of comparison. For example, a multiple bar diagram may be constructed to showproportion of males and females in the total, rural and urban population or the share of canal,
tube well and well irrigation in the total irrigated area in different states.Construction
(a) Mark time series data on X-axis and variable data on Y-axis as per the selected scale.
(b) Plot the data in closed columns.
Example 5: Construct a Multiple bar Diagram.
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6. Compound Bar DiagramWhen different components are grouped in one set of variable or different variables of one
component are put together, their representation is made by a compound bar diagram. In this
method, different variables are shown in a single bar with different rectangles.
Construction(a) Arrange the data in ascending or descending order.
(b) A single bar will depict the set of variables by dividing the total length of the bar as perpercentage.
7. Pie DiagramPie diagram is another graphical method of the representation of data. It is drawn to depictthe total value of the given attribute using a circle. Dividing the circle into correspondingdegrees of angle then represent the sub sets of the data. Hence, it is also called as DividedCircle Diagram. The angle of each variable is calculated using the following formulae.If data is given in percentage form, the angles are calculated using the given formulae.=Value of given states/total value of states
It is given in percentage form,the angles are calculated using the formula=
Percentage of x X 360/100Calculation of Angles
(a) Arrange the data on percentages in an ascending order.(b) Calculate the degrees of angles for showing the given values
(b) It could be done by multiplying percentage with a constant of 3.6 as derived by dividing
the total number of degrees in a circle by 100, i. e. 360/100.
(c) Plot the data by dividing the circle into the required number of divisions to show the sharedifferent regions/countries
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Construction
(a) Select a suitable radius for the circle to be drawn. A radius of 3, 4 or 5 cm may be chosenfor the given data set.
(b) Draw a line from the centre of the circle to the arc as a radius.
(c) Measure the angles from the arc of the circle for each category of vehicles in an ascending
order clock-wise, starting with smaller angle.(d) Complete the diagram by adding the title, sub title, and the legend. The legend mark be
chosen for each variable/category and highlighted by distinct shades/colours.
Precautions(a) The circle should neither be too big to fit in the space nor too small to be illegible.
(b) Starting with bigger angle will lead to accumulation of error leading to the plot of the
smaller angle difficult.
8. Flow Maps/ChartFlow chart is a combination of graph and map. It is drawn to show the flow of commodities or
people between the places of origin and destination. It is also called as Dynamic Map.
Transport map, which shows number of passengers, vehicles, etc., is the best example of aflow chart. These charts are drawn using lines of proportional width. Many government
agencies prepare flow maps to show density of the means of transportation on differentroutes.
The flow maps/ charts are generally drawn to represent two the types of data as given below:
1. The number and frequency of the vehicles as per the direction of their movement2. The number of the passengers and/or the quantity of goods transported.
Requirements for the Preparation of a Flow Map:
(a) A route map depicting the desired transport routes along with the connecting stations.
(b) The data pertaining No. of trains of selected routes of to the flow of goods, Delhi andadjoining areas services, number of vehicles, etc., along with the point of origin and
destination of the movements.
(c) The selection of a scale through which the data related to the quantity of passengers and
goods or the number of vehicles is to be represented.
Construction
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(a) Take an outline map of Delhi and adjoining areas in which railway line and the nodal
stations are depicted.(b) Select a scale to represent the number of trains. Here, the maximum number is 50 and the
minimum is 6. If we select a scale of 1cm = 50 trains, the maximum and minimum numbers
will be represented by a strip of 10 mm and 1.2 mm thick lines respectively on the map.
(c) Plot the thickness of each strip of route between the given rail route.(d) Draw a terraced scale as legend and choose distinct sign or symbol to show the nodal
points (stations) within the strip.
Flow Map of Train movements in and around Delhi.
ge 2
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Q3 How pictorial representation of data help to analyze business
situations?
A picture is worth a thousand words." This is certainly true when you're presenting and
explaining data. You can provide tables setting out the figures, and you can talk about
numbers, percentages, and relationships forever. However, the chances are that your point
will be lost if you rely on these alone. Put up a graph or a chart, and suddenly everything
you're saying makes sense!
Observations about Gold ETFs - 1
Based on the above chart, we can make the following observations:
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Gold ETFs in India have performed exceptionally well when the market has fallen as
shown by the green line (an over performance of 15.52% in 3 months).
However, Gold ETFs in India tend to underperform the Sensex ( 9.18% in 1 month)
during the bull run in the stock market. (In India, gold ETFs are recently launched.
Therefore, up to 6 months performance is compared.)
Observations about Gold ETFs - 2 Over the period of 6 months (2nd August 2007 - 5th February 2008)
Asset Class 2nd August 2007 5th February 2008 Absolute
Gain% Gain
Equity (Sensex) Rs 100,000 Rs 124,540 Rs 24,540 24.54%
Gold (Gold ETFs) Rs 100,000 Rs 129,920 Rs 29,920 29.92%
Absolute Out performance (Gold ETFs over Sensex) Rs 5,380 5.38%
Therefore, following are the important points:
Gold proves out to be a secure asset class at the time of market downfall
In last 6 months, though the market moved northwards most of the time, a steep fall in
January pulled down the aggregate returns with a higher percentage.
An investor would have gained Rs 5380 more if invested in Gold ETFs and not in
Sensex. This is due to exceptionally good performance of Gold ETFs in India in Jan 08even though this asset class was under performing during Oct-Dec 07
Facts about Gold ETFs During the Jan 08 market fall
During the market fall last month, the indices (Sensex and Nifty) have seen a steep fall ofapprox. (-9.78%) and (-12.60%). Following this fall, equity diversified funds have also
seen a downtrend of around (-15.67%) on an average.
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Contrary to this, Gold ETFs have delivered positive returns and also over performed the
equity indices .
Gold ETFs have returned approx. 3.77% in the month of January when the markets have
shown negative sentiments.
iTrust Observations
Gold ETF is an advisable asset class that can be a part of investor's portfolio to add to thediversification. These are low cost instruments and highly transparent.
Specially with the negative sentiments in today's market, gold is a secure asset class.
This asset class can bring stability and security in a well diversified portfolio.
Disclaimer
The information contained herein, together with all estimates and computations, if any, can
change due to legislative, regulatory or market forces. This document does not purport to be asolicitation of any advice pertaining to any tax or any other matter. Recipients are advised to
consult their tax advisor / insurance agent / investment advisor / bank, and study / evaluate the
facts of the matter and other information available before using the information provided in thisresponse.
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BIBLIOGRAPHY
1.www.google.com
2.www.wikipedia.com
3.Hindustan Times
4.Times Of India