Introduction
Standard deviation - a statistical term, which is a good indicator of variability. It measures how widely values (for example, closing prices) are scattered from the mean value. Dispersion is the difference between the actual value, for example, closing prices and the average of closing prices. The greater the difference between prices and average closing price, the higher will be the standard deviation and the higher the variability. The closer in price to the average closing price, the lower the standard deviation and lower volatility.
Calculation
To calculate the 20-periodnogo standard deviation, the following steps:
1. Calculated a simple average of the closing prices, that is, summed up the last 20 closing prices and divide by 20.
2. For each period, subtracted the average of the closing prices of the actual closing prices. This gives us the deviation for each period.
3. Square deviation calculated for each period.
4. Summed values of the squares of deviations of each period.
5. Sum of squared deviations is divided by the number of periods (in our example - 20).
6. The standard deviation equals the square root of this value.
20-periodnoe The standard deviation for the above data is equal to 6.787. Please note that this is one of the versions of the standard deviation. There are different types of computing the standard deviation used in statistics, but this version is best suited for technical analysis, as all input data are known in advance.
Examples
The schedule below shows how the standard deviation may change over time.
After long periods of consolidation, standard deviation (or variability) decreased. Please note that in late December share trading in a narrow range and volatility dropped. Later, in mid-March, the action is also traded in a narrow range and variability also decreased. When the campaign started to grow in the second half of March, the variability also increased.
Shares "Amazon", which is in a similar price range as the stock "IBM", has a higher standard deviation. By the end of December, standard deviation was in the region of 7.5. With the decline in year-end standard deviation increased from 7 to values above 12.5. Subsequently, it fell to 2.5 in two weeks. Since then it has to align approximately 5. It was quite changeable market, and it could earn much more than the market shares of "IBM". The higher the volatility of certain market-based instruments, the more opportunities to earn in the trade for him.
The use of graphics programs
The standard deviation can be constructed on the graph, using the width of the indicator Bollindzhera in most graphics programs. Since the width of Bollindzhera forms two standard deviations above and below the moving average, the installation of "0.5" in the second box would be to divide the bandwidth Bollindzhera two, which is identical to the construction of one standard deviation.
Standard deviation - a statistical term, which is a good indicator of variability. It measures how widely values (for example, closing prices) are scattered from the mean value. Dispersion is the difference between the actual value, for example, closing prices and the average of closing prices. The greater the difference between prices and average closing price, the higher will be the standard deviation and the higher the variability. The closer in price to the average closing price, the lower the standard deviation and lower volatility.
CalculationTo calculate the 20-periodnogo standard deviation, the following steps:
1. Calculated a simple average of the closing prices, that is, summed up the last 20 closing prices and divide by 20.
2. For each period, subtracted the average of the closing prices of the actual closing prices. This gives us the deviation for each period.
3. Square deviation calculated for each period.
4. Summed values of the squares of deviations of each period.
5. Sum of squared deviations is divided by the number of periods (in our example - 20).
6. The standard deviation equals the square root of this value.
20-periodnoe The standard deviation for the above data is equal to 6.787. Please note that this is one of the versions of the standard deviation. There are different types of computing the standard deviation used in statistics, but this version is best suited for technical analysis, as all input data are known in advance.
Examples
The schedule below shows how the standard deviation may change over time.
After long periods of consolidation, standard deviation (or variability) decreased. Please note that in late December share trading in a narrow range and volatility dropped. Later, in mid-March, the action is also traded in a narrow range and variability also decreased. When the campaign started to grow in the second half of March, the variability also increased.
Shares "Amazon", which is in a similar price range as the stock "IBM", has a higher standard deviation. By the end of December, standard deviation was in the region of 7.5. With the decline in year-end standard deviation increased from 7 to values above 12.5. Subsequently, it fell to 2.5 in two weeks. Since then it has to align approximately 5. It was quite changeable market, and it could earn much more than the market shares of "IBM". The higher the volatility of certain market-based instruments, the more opportunities to earn in the trade for him.The use of graphics programs
The standard deviation can be constructed on the graph, using the width of the indicator Bollindzhera in most graphics programs. Since the width of Bollindzhera forms two standard deviations above and below the moving average, the installation of "0.5" in the second box would be to divide the bandwidth Bollindzhera two, which is identical to the construction of one standard deviation.Forex Magazine
based on stockcharts.com
based on stockcharts.com
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