Trend analysis is a technique used in technical analysis to forecast future stock movements by evaluating historical performance data. It involves comparing time periods, geographic areas, and organizational performance, and employs methods such as moving averages and least squares for data analysis. This approach is essential for competitive intelligence, allowing businesses to make informed decisions that enhance revenue from core customers.

2. • A trend analysis is an aspect of
technical analysis that tries to
predict the future movement of a
stock based on past data.
• Trend analysis is based on the
idea that what has happened in
the past gives traders an idea of
what will happen in the future.

3. • Definition in concise oxford dictionary which is that a
trend is “a general direction and tendency”
• A trend analysis is a method of analysis that allows
traders to predict what will happen with a stock in the
future. Trend analysis is based on historical data about
the stock's performance given the overall trends of
the market and particular indicators within the market.

4. • A trader may be able to match purchases and sales of
particular stocks, maximizing his or her potential for profits.
• trend analysis establishes the pattern for elements in the
financial statement over a period and will give an indication
of grey areas in the financial statement.
• evaluate company performance over a period of time.
• Comparing one time period to another time period.
• Comparing one geographic area to another
• Making future projection.
• Comparing with other organizations.

5. ….
• Trend Analysis is essential for a firm's competitive
intelligence program.
• The ability to accurately gauge customers' response to
changes in business and other environmental
parameters is a powerful competitive advantage.
• Trend Analysis Methods allow business users to make
analytical decisions about those business processes that
maximize revenue from core customers.

6. •Free hand graphical method
•Semi average method
•Moving average method
•Least square method for trend

7. • Under this method, the values of a time series are
plotted on a graph paper in the form of a historigram.
For this, the time variable is shown on the horizontal
axis, the value variable on the vertical axis, and the dots
are plotted on the graph paper at the intersecting points
of the time and value variables. After this, a curve is
drawn with free hand through the plotted dots in such a
manner that it represents the general tendency of the
time series, and eliminates all its other components viz:
seasonal, cyclical and irregular ones.

8. • From the following data, fit a free hand smooth curve
and forecast the trend values thereby.
• Graphic representation of the trend line relating to the
production of Peddy by the method of free hand curve.

9. • This method is sometimes employed when a line appears to
be an inadequate explanation of the trend. According to this
method, the original data are divided into two equal parts
and the values of each part are then summed up and
averaged.The average of each part is centered in the period
of the time of the part from which it has been calculated and
then plotted on a graph.Then a straight line is drawn to pass
through the plotted points.This line constitutes the semi-
average trend line.
• When the number of years is odd, the middle year is not
considered while dividing the data into two equal parts and
obtaining the average.

10. 65+80+100+70+80+110
6
=84.16
115+130+90+100+150+160
6
=124.16
years commodity
1992 65
1993 80
1994 100
1995 70
1996 80
1997 110
1998 115
1999 130
2000 90
2001 100
2002 150
2003 160

11. • In statistics a moving average (rolling average or
running average) is a calculation to analyze data points
by creating series of averages of different subsets of the
full data set. It is also called a moving mean (MM)
or rolling mean and is a type of finite impulse response
filter.

12. Years Price Average Average
1960 5
1961 7 21 7
1962 9 28 9.3
1963 12 32 10.6
1964 11 34 11
1965 10 29 9.6
1966 8 30 10
1967 12 33 11
1968 13 42 14
1969 17 49 16.3
1970 19 30 16.6
1971 14 46 15.3
1972 13 39 13
1973 12 40 13.34
1974 15

13. • The least squares method is a form of mathematical
regression analysis that finds the line of best fit for a
dataset, providing a visual demonstration of the
relationship between the data points. Each point of data
is representative of the relationship between a known
independent variable and an unknown dependent
variable.

14. Year PriceY X x2 XY yc = a+bx Index
Value
1951 107 0 0 0 108+2*0 108
1952 110 1 1 110 108+2*1 110
1953 114 2 4 228 108+2*2 112
1954 114 3 9 342 108+2*3 114
1955 115 4 16 460 108+2*4 116
560 10 30 1140 560
• Linear least squares regression has earned its
place as the primary tool for process modelling
because of its effectiveness and completeness.