Monday, October 7, 2019

Business data analysis Essay Example | Topics and Well Written Essays - 1000 words

Business data analysis - Essay Example They try to elaborate the rate at which the stock values are found to be varying over time. Seasonal variations Seasonal variations have very important implications for the policies which define the functioning of a company. Rise and fall in stock prices often classify the boom and recessive periods of a company respectively. When stock prices rise, the companies generally are found to increase their employee wages and hire more employees as the production rises. They are generally predicted through figuring out the differences between the predicted trend line and the actual observations, for each individual period. Averaging over the differences throughout an entire year leads to the calculation of seasonal variations for each month in any year (Hargreaves, 1994, p. 154). Stock prices for Deutsche Bank are estimated to be reaching a peak during the fourth month of every year while it faces a recession during the tenth month of every year. Hence, the company might be regarded to be u ndergoing a period of boom during the second quarter of every year and a depression during the fourth quarter. However, when these seasonal variation statistics are compared with the actual monthly differences in the trend calculations and actual observations, the readings were found to be much different. The following graph depicts the comparative readings of differences between actual and trend observations. ... On the other hand, recession is actually experienced during the beginning of second quarter as against the seasonal variations calculated. However, it is not repeated for each and every year, as is found for the year 2002. In the year 2002, the actual seasonal variations are found to be coinciding with the calculated ones even though the readings do not match each other. The only factor which seems to correspond with each other is the direction of trend. If actual stock price values are being counted for, as the diagram alongside depicts, it would show that the correspondence between actual trend and estimated one is rarely found for the span of 10 years. In fact, the diagram suggests the absence of any hard-core seasonal fluctuation as such. The actual detrended line indicates the period between 2002 and 2004 as well as that between 2009 and 2010 to be under recession while that between 2006 and 2008 to be a period of boom. On the other hand, seasonal variation statistics show that regular cycle of booms and recessions are found to characterise every year. However, a point to be taken a note of in this regard is that even when the company, i.e., Deutsche Bank undergoes a whole period of boom or recession as such, there exists small fluctuations during the same. Hence, predictions about seasonal variations are likely to match during some years. Even when a company is experiencing a period of boom or recession, there could be ups and downs in business which symbolise seasonal variations, which actually is a short run phenomenon. However, there might also be another reason behind the lack of compatibility between the estimated trends and the actual adjusted closing price of the stocks of Deutsche Bank. As the diagram produced

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