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PREDICTIBILITY OF RETURNS ON MICROSOFT STOCK PRICE
Ziqian Zhu
MSc Mathematical Finance
Queen Mary University of London
13/04/2015
The aim of this article is to investigate the dynamic behavior of daily returns of Microsoft stock prices from 21/03/2005 to 21/03/2015, which are downloaded from the NASDAQ website and include 2514 observations
Microsoft is an American multinational corporation that develops, manufactures, licenses, supports and sells computer software, consumer electronics and personal computers and services. Standard and Poor’s and Moody’s have both given a AAA rating to Microsoft, whose assets were valued at $41 billion on November 14, 2014 as compared to only $8.5 billion in unsecured debt and*…show more content…*

This means that the null hypothesis about normality can be rejected and daily stock prices are not normally distributed. Histogram 1 II. Stationarity of Microsoft daily stock prices and daily returns As the stationarity of stock prices can strongly influences its behavior and properties and the use of non-stationary data can lead to spurious regressions, thus test of stationarity is more than necessary in research of daily stock prices. I applied Augmented Dickey-Fuller test here to check for unit root. The results for the daily stock prices appear as in Table 1. Table 1 The value of the test statistic and the relevant critical values given the type of test equation and sample size, are given in the first panel of the output above. Clearly, the test statistic is -1.261047 that is not more negative than the critical value, so the null hypothesis of a unit root in the stock price series cannot be rejected. Since one of the independent variables in this regression is non-stationary, it is not appropriate to examine the coefficient standard errors or their t-ratios in the test regression. Now repeat all of the test for first difference of the daily stock prices. The output appear as in the following Table 2. Table 2 The test statistic is -34.10940 which is more negative than the critical value and hence

This means that the null hypothesis about normality can be rejected and daily stock prices are not normally distributed. Histogram 1 II. Stationarity of Microsoft daily stock prices and daily returns As the stationarity of stock prices can strongly influences its behavior and properties and the use of non-stationary data can lead to spurious regressions, thus test of stationarity is more than necessary in research of daily stock prices. I applied Augmented Dickey-Fuller test here to check for unit root. The results for the daily stock prices appear as in Table 1. Table 1 The value of the test statistic and the relevant critical values given the type of test equation and sample size, are given in the first panel of the output above. Clearly, the test statistic is -1.261047 that is not more negative than the critical value, so the null hypothesis of a unit root in the stock price series cannot be rejected. Since one of the independent variables in this regression is non-stationary, it is not appropriate to examine the coefficient standard errors or their t-ratios in the test regression. Now repeat all of the test for first difference of the daily stock prices. The output appear as in the following Table 2. Table 2 The test statistic is -34.10940 which is more negative than the critical value and hence

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