# Volume Moving Average Research Paper

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Volume Moving Average (VMA) Volume Moving Average, as the name indicates, is a moving average of the volume rather than the price. VMA represents the average volume over a specified period of time and can be used to chart a stock, ETF or index for a period as short as a few minutes to as long as many years. By smoothing out individual surges in the volume activity, VMA allows you to see the general trends and volume patterns of a stock or index. A longer period VMA (aka Slow VMA - a larger number for the period) is often used to highlight long-term surges in volume. Significant volume surges sometimes precede long-term trend reversals. A shorter-period VMA (aka Fast VMA - a smaller number for the period) is often used to highlight short-term…show more content…
The result is the volume moving average of the security over that time period. Calculation V = Previous Day's Volume N = Time Period For example, to calculate a volume moving average for IBM on an intraday 5 min 2 day chart with 10 being the period: 1. Locate the actual point that you would like to calculate. 2. Add the previous 10 days' total volume (Time Period = 10). 3. Divide that sum by the actual time period (10). 4. That will result in the Volume Moving Average for that particular point. Note: When adding VMA as a new study, it will default to the first window with a Volume study already in place. However, if a Volume study does not exist, a new sub window will be added with a Volume study and the VMA study. The default time period for a VMA is 10. Descriptive Statistics Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of…show more content…
In a research study we may have lots of measures. Or we may measure a large number of people on any measure. Descriptive statistics help us to simplify large amounts of data in a sensible way. Each descriptive statistic reduces lots of data into a simpler summary. For instance, consider a simple number used to summarize how well a batter is performing in baseball, the batting average. This single number is simply the number of hits divided by the number of times at bat (reported to three significant digits). A batter who is hitting .333 is getting a hit one time in every three at bats. One batting .250 is hitting one time in four. The single number describes a large number of discrete events. Or, consider the scourge of many students, the Grade Point Average (GPA). This single number describes the general performance of a student across a potentially wide range of course