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A normal distribution can be used to describe how sample characteristics or events relate to each other. The distribution can be “used to predict and adjust for a wide range of financial goals by optimizing financial decision-making by applying and graphically mapping financial data into a distribution set of variables” (“The use of normal distribution in finance”, 2011). Under the normal distribution curve (bell curve), data is distributed around the mean or expected value. A low standard deviation indicates that the data points tend to be close to the mean of the data set, while a high standard deviation indicates that the data points are spread out over a wider range of values. Thus, determining if certain financial events are normally distributed can be useful because those events may be more likely to follow probabilistic patterns in the future.
Normal distributions can be used in finance to:
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Determine probability of financial events
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Compare financial events and/or products
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Assist in risk assessment
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Forecast return on investment (ROI)
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Present data in an easy-to-understand format
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Measure accuracy of statistical information through statistical analysis of the distribution
Financial economists often track monthly stock returns and look to determine if they are normally distributed. We are going to return to the Dow Jones Industrial Average. Using the information, you have learned about the normal curve and Z score, make probability statements about future returns of the Dow Jones Industrial Average, and defend your projections.
Go to
The Wall Street Journal
website
and use the historical tool to calculate the mean and standard deviation for the month of August 2017 for your projections.