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Typical price is the average value of daily prices, and can be used as a filter to help identify trends. It is also used as a daily average price which is very useful if you want a more simple view of prices. Financial interpretation:This indicator is a good solution if we want to exchange a stock chart with a single line chart, and the indicator will merely calculate the daily average of Hi, Low and Close prices. Calculation: The Typical price is calculated using the following formula: 
Typical price is a daily average of high, low and close prices.
Median prices are mid-point values of daily prices, and therefore can be used as a filter to help identify trends. They are also used as a daily average price which is very useful if you want a more simple "view" of prices. Financial Interpretation: This indicator is good solution if we want to replace a stock chart with a single line chart. The Median Price is merely the daily average of Hi and Low prices. Calculation: The Median price is calculated using the following formula: 
Median price is the daily average of high and low prices.
The Weighted Close formula calculates the average value of daily prices. The only difference between Typical Price and the Weighted Close is that the closing price has extra weight, and is considered the most important price. The Weighted Close can be used as a filter for identifying trends, and can also be used as a daily average price, which is very useful if you want a more simple view of prices. Financial Interpretation: This indicator is a good solution if we want to exchange a stock chart with a single line chart. The Weighted Close indicator merely calculates the daily weighted average of Hi, Low and Close prices. Calculation: The Weighted Close is calculated using the following formula: 
Weighted Close is a daily weighted average of high, low and close prices.
A Simple Moving Average is an average of data calculated over a period of time. The moving average is the most popular price indicator used in technical analyses. This average can be used with any price including the Hi, Low, Open, or Close, and can be applied to other indicators too. A moving average smoothens a data series, which is very important in a volatile market as it helps to identify significant trends. ADstock has four types of moving averages including Simple, Exponential, Triangular, and Weighted. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Moving Average is used to compare a security's prices with it's moving average. The most important element used in calculating the moving average is a time period, which should be equal to the observed market cycle. The moving average is a lagging indicator, and will always be behind the price. When the price is following a trend the moving average is very close to the security's price. When a price is going up, the moving average will probably stay down due to the influence of the historical data. Calculation: The moving average is calculated using the following formula: 
In the previous formula the n-value represents a time period. The most common time periods are: 10 Days, 50 Days and 200 Days. A moving average moves because as each new data point is added the oldest data point is dropped. A simple moving average gives equal weight to each data point price.
An Exponential Moving Average is an average of data calculated over a period of time where the most recent days are given more weight. The exponential moving average can be used with any price including a: Hi, Low, Open, and Close, or it could be applied to other indicators. An Exponential Moving average smoothens a data series, which is very important in a volatile market as it helps to remove excess data noise so that significant trends can be identified. ADstock has four types of moving averages: Simple, Exponential, Triangular, and Weighted. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Exponential Moving Average is used to compare a value with it's exponential moving average. The exponential moving average gives more influence to prices that are more recent, and because of this weighting mechanism, the moving average will follow prices much faster then a simple moving average. The most important element used in calculating the moving average is the time period used. This time period should be equal to the market cycle observed. The time period influences the percentage which will be used as a weight for the most recent periods. The Exponential moving average is a lagging indicator, and as such will always trail price. When the price is following a trend, then the exponential moving average will be very close to the price. When a price is going up, then the exponential moving average will most likely fall below the price. This is because of the influence from the historical data. Calculation: To recalculate an Exponential Moving Average you have to find a percentage which can be applied to the most recent days. The percentage could be determined using a time period: 
A Triangular Moving Average is an average of data calculated over a period of time, where the middle portion of data has the most weight. The Triangular Moving Average can be used with any price including the Hi, Low, Open, or Close, and can be applied to other indicators too. The Triangular Moving Average smoothens a data series, which is very important in a volatile market as it helps to identify significant trends more easily. ADstock has four types of moving averages including a Simple, Exponential, Triangular, and Weighted average. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Triangular moving average is used to compare values with their Triangular moving average, where the Triangular moving average gives more influence to the middle portion of the data. The most important element used in calculating the moving average is a time period, which should be equal to the observed market cycle. The Triangular moving average is a lagging indicator, and will always be behind the price. The triangular moving average is calculated as a simple moving average of a simple moving average (represents double smoothing), and because of this is a very slow indicator. When the price is following a trend the Triangular moving average is very close to the price. When a price is increasing the Triangular moving average usually stays down because of the influence of the historical data. Calculation: To recalculate a Triangular moving average we have to find a middle of the time periods which are used for calculation. This middle point will be calculated differently if the number of periods (i.e. data points) is odd or even. The triangular moving average will be calculated using a simple moving average for the middle point twice (Moving average of the moving average).
A Weighted Moving Average is an average of data calculated over a period of time, where greater weight is attached to the most recent data. The Weighted Moving Average can be used with any price including the Hi, Low, Open, or Close price, and can be applied to other indicators as well. The Weighted Moving Average smoothens a data series, which is important in a volatile market, as it helps to identify trends much more easily. Weighting is calculated from a sum of days. ADstock has four types of moving averages including Simple, Exponential, Triangular, and Weighted. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Weighted moving average is used to compare a value with it's Weighted moving average, and gives more influence for recent data and less influence for past data. The most important element used in calculating the moving average is a time period, which should be equal to the observed market cycle. The Weighted moving average is lagging indicator, and will always be behind the price. When the price is following a trend the Weighted moving average is very close to the price. When a price is increasing the Weighted moving average most likely will stay down because of the influence of the historical data. Calculation: The Weighted movi ng average is calculated using a sum of indexes of time periods (data points). Weight for every period is calculated as "index / (Number of data points)". The following table demonstrates how to calculate a 5 days weighted moving average: | Day | 1 | 2 | 3 | 4 | 5 | | Weight (Day Index/Sum of Indexes) | 1/15 | 2/15 | 3/15 | 4/15 | 5/15 | | Price | 32 | 21 | 24 | 11 | 16 | | Weighted Value (Weight*Price) | 2.133 | 2.8 | 4.8 | 2.933 | 5.333 | | 5 Day Weighted Moving Average (Sum of previous 5 weighted values) | | | | | 18 |
Envelopes are plotted above and below a moving average using a specified percentage as the shift. The envelopes indicator is used to create signals for buying and selling, and the percentage to be used for calculating the envelopes is specified by the user. This percentage should depend on the volatility of the market (the higher the market volatility, the higher the percentage should be). Financial Interpretation: The Envelopes indicator can be used with other indicators to generate signals for buying and selling. The percentage which is used for calculating the envelopes is specified by the user and depends on the volatility of the market. If the market is more volatile the percentage should be higher. A price is in an up-trend when it stays above the moving average and is in a down-trend when it stays below the moving average. Calculation: The first step is to find the Moving Average, and the second step is to shift the moving average up and down a specified percentage.
Bollinger Bands are indicators that are plotted at standard deviation levels above, and below a simple moving average. Since standard deviation is a measure of volatility, a large standard deviation indicates a volatile market, and a smaller standard deviation indicates a calmer market. Bollinger Bands are a good way to compare volatility against relative price levels, over a period of time. The Period is the time period used when displaying Bollinger Bands. Financial interpretation: Bollinger Bands can be used with other indicators to generate signals for buying and selling. They can also be used to find a period with overbought and oversold levels. The narrowing of the Bollinger Bands increases the probability of a sharp breakout in prices. The longer prices remain within the narrow bands, the more likely a price breakout will occur. Calculation: The first step in calculating the Bollinger Bands is to find the simple moving average. 
The upper and lower Bollinger Bands are calculated by determining a simple moving average, and then adding/subtracting a specified number of standard deviations from the simple moving average to calculate the upper and lower bands. 
In the above formulas, D represents the number of standard deviations applied to the Bollinger Bands indicator.
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Typical price is the average value of daily prices, and can be used as a filter to help identify trends. It is also used as a daily average price which is very useful if you want a more simple view of prices. Financial interpretation:This indicator is a good solution if we want to exchange a stock chart with a single line chart, and the indicator will merely calculate the daily average of Hi, Low and Close prices. Calculation: The Typical price is calculated using the following formula:
Typical price is a daily average of high, low and close prices.
Median prices are mid-point values of daily prices, and therefore can be used as a filter to help identify trends. They are also used as a daily average price which is very useful if you want a more simple "view" of prices. Financial Interpretation: This indicator is good solution if we want to replace a stock chart with a single line chart. The Median Price is merely the daily average of Hi and Low prices. Calculation: The Median price is calculated using the following formula:
Median price is the daily average of high and low prices.
The Weighted Close formula calculates the average value of daily prices. The only difference between Typical Price and the Weighted Close is that the closing price has extra weight, and is considered the most important price. The Weighted Close can be used as a filter for identifying trends, and can also be used as a daily average price, which is very useful if you want a more simple view of prices. Financial Interpretation: This indicator is a good solution if we want to exchange a stock chart with a single line chart. The Weighted Close indicator merely calculates the daily weighted average of Hi, Low and Close prices. Calculation: The Weighted Close is calculated using the following formula:
Weighted Close is a daily weighted average of high, low and close prices.
A Simple Moving Average is an average of data calculated over a period of time. The moving average is the most popular price indicator used in technical analyses. This average can be used with any price including the Hi, Low, Open, or Close, and can be applied to other indicators too. A moving average smoothens a data series, which is very important in a volatile market as it helps to identify significant trends. ADstock has four types of moving averages including Simple, Exponential, Triangular, and Weighted. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Moving Average is used to compare a security's prices with it's moving average. The most important element used in calculating the moving average is a time period, which should be equal to the observed market cycle. The moving average is a lagging indicator, and will always be behind the price. When the price is following a trend the moving average is very close to the security's price. When a price is going up, the moving average will probably stay down due to the influence of the historical data. Calculation: The moving average is calculated using the following formula:
In the previous formula the n-value represents a time period. The most common time periods are: 10 Days, 50 Days and 200 Days. A moving average moves because as each new data point is added the oldest data point is dropped. A simple moving average gives equal weight to each data point price.
An Exponential Moving Average is an average of data calculated over a period of time where the most recent days are given more weight. The exponential moving average can be used with any price including a: Hi, Low, Open, and Close, or it could be applied to other indicators. An Exponential Moving average smoothens a data series, which is very important in a volatile market as it helps to remove excess data noise so that significant trends can be identified. ADstock has four types of moving averages: Simple, Exponential, Triangular, and Weighted. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Exponential Moving Average is used to compare a value with it's exponential moving average. The exponential moving average gives more influence to prices that are more recent, and because of this weighting mechanism, the moving average will follow prices much faster then a simple moving average. The most important element used in calculating the moving average is the time period used. This time period should be equal to the market cycle observed. The time period influences the percentage which will be used as a weight for the most recent periods. The Exponential moving average is a lagging indicator, and as such will always trail price. When the price is following a trend, then the exponential moving average will be very close to the price. When a price is going up, then the exponential moving average will most likely fall below the price. This is because of the influence from the historical data. Calculation: To recalculate an Exponential Moving Average you have to find a percentage which can be applied to the most recent days. The percentage could be determined using a time period:
A Triangular Moving Average is an average of data calculated over a period of time, where the middle portion of data has the most weight. The Triangular Moving Average can be used with any price including the Hi, Low, Open, or Close, and can be applied to other indicators too. The Triangular Moving Average smoothens a data series, which is very important in a volatile market as it helps to identify significant trends more easily. ADstock has four types of moving averages including a Simple, Exponential, Triangular, and Weighted average. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Triangular moving average is used to compare values with their Triangular moving average, where the Triangular moving average gives more influence to the middle portion of the data. The most important element used in calculating the moving average is a time period, which should be equal to the observed market cycle. The Triangular moving average is a lagging indicator, and will always be behind the price. The triangular moving average is calculated as a simple moving average of a simple moving average (represents double smoothing), and because of this is a very slow indicator. When the price is following a trend the Triangular moving average is very close to the price. When a price is increasing the Triangular moving average usually stays down because of the influence of the historical data. Calculation: To recalculate a Triangular moving average we have to find a middle of the time periods which are used for calculation. This middle point will be calculated differently if the number of periods (i.e. data points) is odd or even. The triangular moving average will be calculated using a simple moving average for the middle point twice (Moving average of the moving average).
A Weighted Moving Average is an average of data calculated over a period of time, where greater weight is attached to the most recent data. The Weighted Moving Average can be used with any price including the Hi, Low, Open, or Close price, and can be applied to other indicators as well. The Weighted Moving Average smoothens a data series, which is important in a volatile market, as it helps to identify trends much more easily. Weighting is calculated from a sum of days. ADstock has four types of moving averages including Simple, Exponential, Triangular, and Weighted. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Weighted moving average is used to compare a value with it's Weighted moving average, and gives more influence for recent data and less influence for past data. The most important element used in calculating the moving average is a time period, which should be equal to the observed market cycle. The Weighted moving average is lagging indicator, and will always be behind the price. When the price is following a trend the Weighted moving average is very close to the price. When a price is increasing the Weighted moving average most likely will stay down because of the influence of the historical data. Calculation: The Weighted movi ng average is calculated using a sum of indexes of time periods (data points). Weight for every period is calculated as "index / (Number of data points)". The following table demonstrates how to calculate a 5 days weighted moving average: | Day | 1 | 2 | 3 | 4 | 5 | | Weight (Day Index/Sum of Indexes) | 1/15 | 2/15 | 3/15 | 4/15 | 5/15 | | Price | 32 | 21 | 24 | 11 | 16 | | Weighted Value (Weight*Price) | 2.133 | 2.8 | 4.8 | 2.933 | 5.333 | | 5 Day Weighted Moving Average (Sum of previous 5 weighted values) | | | | | 18 |
Envelopes are plotted above and below a moving average using a specified percentage as the shift. The envelopes indicator is used to create signals for buying and selling, and the percentage to be used for calculating the envelopes is specified by the user. This percentage should depend on the volatility of the market (the higher the market volatility, the higher the percentage should be). Financial Interpretation: The Envelopes indicator can be used with other indicators to generate signals for buying and selling. The percentage which is used for calculating the envelopes is specified by the user and depends on the volatility of the market. If the market is more volatile the percentage should be higher. A price is in an up-trend when it stays above the moving average and is in a down-trend when it stays below the moving average. Calculation: The first step is to find the Moving Average, and the second step is to shift the moving average up and down a specified percentage.
Bollinger Bands are indicators that are plotted at standard deviation levels above, and below a simple moving average. Since standard deviation is a measure of volatility, a large standard deviation indicates a volatile market, and a smaller standard deviation indicates a calmer market. Bollinger Bands are a good way to compare volatility against relative price levels, over a period of time. The Period is the time period used when displaying Bollinger Bands. Financial interpretation: Bollinger Bands can be used with other indicators to generate signals for buying and selling. They can also be used to find a period with overbought and oversold levels. The narrowing of the Bollinger Bands increases the probability of a sharp breakout in prices. The longer prices remain within the narrow bands, the more likely a price breakout will occur. Calculation: The first step in calculating the Bollinger Bands is to find the simple moving average.
The upper and lower Bollinger Bands are calculated by determining a simple moving average, and then adding/subtracting a specified number of standard deviations from the simple moving average to calculate the upper and lower bands.
In the above formulas, D represents the number of standard deviations applied to the Bollinger Bands indicator.
See General Help section for details
Select an Overlay Indicator and click ? Button to display Help
Typical price is the average value of daily prices, and can be used as a filter to help identify trends. It is also used as a daily average price which is very useful if you want a more simple view of prices. Financial interpretation:This indicator is a good solution if we want to exchange a stock chart with a single line chart, and the indicator will merely calculate the daily average of Hi, Low and Close prices. Calculation: The Typical price is calculated using the following formula:
Typical price is a daily average of high, low and close prices.
Median prices are mid-point values of daily prices, and therefore can be used as a filter to help identify trends. They are also used as a daily average price which is very useful if you want a more simple "view" of prices. Financial Interpretation: This indicator is good solution if we want to replace a stock chart with a single line chart. The Median Price is merely the daily average of Hi and Low prices. Calculation: The Median price is calculated using the following formula:
Median price is the daily average of high and low prices.
The Weighted Close formula calculates the average value of daily prices. The only difference between Typical Price and the Weighted Close is that the closing price has extra weight, and is considered the most important price. The Weighted Close can be used as a filter for identifying trends, and can also be used as a daily average price, which is very useful if you want a more simple view of prices. Financial Interpretation: This indicator is a good solution if we want to exchange a stock chart with a single line chart. The Weighted Close indicator merely calculates the daily weighted average of Hi, Low and Close prices. Calculation: The Weighted Close is calculated using the following formula:
Weighted Close is a daily weighted average of high, low and close prices.
A Simple Moving Average is an average of data calculated over a period of time. The moving average is the most popular price indicator used in technical analyses. This average can be used with any price including the Hi, Low, Open, or Close, and can be applied to other indicators too. A moving average smoothens a data series, which is very important in a volatile market as it helps to identify significant trends. ADstock has four types of moving averages including Simple, Exponential, Triangular, and Weighted. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Moving Average is used to compare a security's prices with it's moving average. The most important element used in calculating the moving average is a time period, which should be equal to the observed market cycle. The moving average is a lagging indicator, and will always be behind the price. When the price is following a trend the moving average is very close to the security's price. When a price is going up, the moving average will probably stay down due to the influence of the historical data. Calculation: The moving average is calculated using the following formula:
In the previous formula the n-value represents a time period. The most common time periods are: 10 Days, 50 Days and 200 Days. A moving average moves because as each new data point is added the oldest data point is dropped. A simple moving average gives equal weight to each data point price.
An Exponential Moving Average is an average of data calculated over a period of time where the most recent days are given more weight. The exponential moving average can be used with any price including a: Hi, Low, Open, and Close, or it could be applied to other indicators. An Exponential Moving average smoothens a data series, which is very important in a volatile market as it helps to remove excess data noise so that significant trends can be identified. ADstock has four types of moving averages: Simple, Exponential, Triangular, and Weighted. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Exponential Moving Average is used to compare a value with it's exponential moving average. The exponential moving average gives more influence to prices that are more recent, and because of this weighting mechanism, the moving average will follow prices much faster then a simple moving average. The most important element used in calculating the moving average is the time period used. This time period should be equal to the market cycle observed. The time period influences the percentage which will be used as a weight for the most recent periods. The Exponential moving average is a lagging indicator, and as such will always trail price. When the price is following a trend, then the exponential moving average will be very close to the price. When a price is going up, then the exponential moving average will most likely fall below the price. This is because of the influence from the historical data. Calculation: To recalculate an Exponential Moving Average you have to find a percentage which can be applied to the most recent days. The percentage could be determined using a time period:
A Triangular Moving Average is an average of data calculated over a period of time, where the middle portion of data has the most weight. The Triangular Moving Average can be used with any price including the Hi, Low, Open, or Close, and can be applied to other indicators too. The Triangular Moving Average smoothens a data series, which is very important in a volatile market as it helps to identify significant trends more easily. ADstock has four types of moving averages including a Simple, Exponential, Triangular, and Weighted average. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Triangular moving average is used to compare values with their Triangular moving average, where the Triangular moving average gives more influence to the middle portion of the data. The most important element used in calculating the moving average is a time period, which should be equal to the observed market cycle. The Triangular moving average is a lagging indicator, and will always be behind the price. The triangular moving average is calculated as a simple moving average of a simple moving average (represents double smoothing), and because of this is a very slow indicator. When the price is following a trend the Triangular moving average is very close to the price. When a price is increasing the Triangular moving average usually stays down because of the influence of the historical data. Calculation: To recalculate a Triangular moving average we have to find a middle of the time periods which are used for calculation. This middle point will be calculated differently if the number of periods (i.e. data points) is odd or even. The triangular moving average will be calculated using a simple moving average for the middle point twice (Moving average of the moving average).
A Weighted Moving Average is an average of data calculated over a period of time, where greater weight is attached to the most recent data. The Weighted Moving Average can be used with any price including the Hi, Low, Open, or Close price, and can be applied to other indicators as well. The Weighted Moving Average smoothens a data series, which is important in a volatile market, as it helps to identify trends much more easily. Weighting is calculated from a sum of days. ADstock has four types of moving averages including Simple, Exponential, Triangular, and Weighted. The most important difference between the above moving averages is how they weight their datapoints. Financial Interpretation: The Weighted moving average is used to compare a value with it's Weighted moving average, and gives more influence for recent data and less influence for past data. The most important element used in calculating the moving average is a time period, which should be equal to the observed market cycle. The Weighted moving average is lagging indicator, and will always be behind the price. When the price is following a trend the Weighted moving average is very close to the price. When a price is increasing the Weighted moving average most likely will stay down because of the influence of the historical data. Calculation: The Weighted movi ng average is calculated using a sum of indexes of time periods (data points). Weight for every period is calculated as "index / (Number of data points)". The following table demonstrates how to calculate a 5 days weighted moving average: | Day | 1 | 2 | 3 | 4 | 5 | | Weight (Day Index/Sum of Indexes) | 1/15 | 2/15 | 3/15 | 4/15 | 5/15 | | Price | 32 | 21 | 24 | 11 | 16 | | Weighted Value (Weight*Price) | 2.133 | 2.8 | 4.8 | 2.933 | 5.333 | | 5 Day Weighted Moving Average (Sum of previous 5 weighted values) | | | | | 18 |
Envelopes are plotted above and below a moving average using a specified percentage as the shift. The envelopes indicator is used to create signals for buying and selling, and the percentage to be used for calculating the envelopes is specified by the user. This percentage should depend on the volatility of the market (the higher the market volatility, the higher the percentage should be). Financial Interpretation: The Envelopes indicator can be used with other indicators to generate signals for buying and selling. The percentage which is used for calculating the envelopes is specified by the user and depends on the volatility of the market. If the market is more volatile the percentage should be higher. A price is in an up-trend when it stays above the moving average and is in a down-trend when it stays below the moving average. Calculation: The first step is to find the Moving Average, and the second step is to shift the moving average up and down a specified percentage.
Bollinger Bands are indicators that are plotted at standard deviation levels above, and below a simple moving average. Since standard deviation is a measure of volatility, a large standard deviation indicates a volatile market, and a smaller standard deviation indicates a calmer market. Bollinger Bands are a good way to compare volatility against relative price levels, over a period of time. The Period is the time period used when displaying Bollinger Bands. Financial interpretation: Bollinger Bands can be used with other indicators to generate signals for buying and selling. They can also be used to find a period with overbought and oversold levels. The narrowing of the Bollinger Bands increases the probability of a sharp breakout in prices. The longer prices remain within the narrow bands, the more likely a price breakout will occur. Calculation: The first step in calculating the Bollinger Bands is to find the simple moving average.
The upper and lower Bollinger Bands are calculated by determining a simple moving average, and then adding/subtracting a specified number of standard deviations from the simple moving average to calculate the upper and lower bands.
In the above formulas, D represents the number of standard deviations applied to the Bollinger Bands indicator.
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The Average True Range is an indicator that measures commitment, and compares the range between the High, Low and Close prices. This indicator was developed by J. Welles Wilder. Financial Interpretation: High Average True Range values often occur at market bottoms due to extensive panic sell. Low Average true range values are characteristic with market tops. Calculation: To find the Average True Range it is first necessary to find the True Range. Finding the True range is done in this manner: True Range = MAX( |High(today) - Low(today)|, |Close(yesterday) - High(today)|, |Close(yesterday) - Low(today)|) The Average True range is calculated as a Simple Moving Average of True Range.
The Commodity Channel Index compares prices with their moving averages. If the Commodity channel index is high, it means that a price is higher than its moving average, which is an indicator that the security is overbought. If the Commodity channel index is low, it means that a price is lower than its moving average, which is an indicator that the security is oversold. Financial interpretation: The Commodity channel index could be used as an overbought/oversold indicator or for divergence. If the Commodity channel index is high it means that a price is higher than its moving average which is an indicator that security is overbought. If the Commodity channel index is low it means that a price is lower than its moving average, which is an indicator that security is oversold. If the commodity channel index is above 100 it means that security is overbought. If the commodity channel index is below -100 it means that security is oversold. Calculation : The Commodity Channel index is calculated using following algorithm: 1. Calculate typical price:
TP = (High+Low+Close) / 3 2. Calculate Simple Moving Average of the TP (SMATP):
SMATP=SMA(TP) 3. Calculate Mean Deviation:  4. Calculate Commodity Channel Index: 
The Detrended Price Oscillator attempts to remove trend from prices. By comparing the closing price or any other price with it's moving average, the Detrended Price Oscillator eliminates cycles that are longer than the moving average. Financial Interpretation: The Detrended price oscillator is used to remove long cycles from a trend. When a price is detrended using the detrended price oscillator, cycles and overbought/oversold levels can be identified more easily. The principal is similar to using longer length technical indicators compared to shorter length technical indicators. Calculation: The Detrended Price Oscillator is calculated in the following way: - The first step is to create a simple moving average ( MA ) using n periods.
- 2. Calculate the Detrended Price Oscillator using the Close price and Moving Average:
DPO = Close – (MA((n/2)+1)) where MA((n/2)+1) means moving average (n/2)+1 days ago.
The Mass Index is used to predict trend reversal by comparing the difference, and range between High and Low prices. If the Mass Index increases, the range between High and low increases. If the Mass Index decreases, the range between High and Low decreases. Financial Interpretation: The most significant pattern to watch for is the "reversal bulge", will occur when a 25 day period Mass Index rises above 27 and falls back below 26.5. If the moving average of prices is going down and a reversal bulge has occurred it is signal for buying. If the moving average of prices is going up and a reversal bulge has occurred it is signal for selling. Calculation: The Mass Index is calculated using following formula:  Where EMA is Exponential Moving Average calculated using the AveragePeriod parameter.
The MACD (Moving Average Convergence/Divergence) indicator compares the two moving averages of prices. The MACD is used with a 9-day Exponential Moving average as a signal that indentifies buying or selling moments. This indicator was developed by Gerald Appel. Financial Interpretation: The MACD indicator should be used with a 9-day Exponential Moving Average as its Signal Line. The time to sell is when the MACD indicator falls below its signal line. Similarly, the time to buy is when the MACD indicator is higher than its signal line. When the MACD rises it means that security could be overbought. When the MACD diverges from prices this could be a sign that the current trend is close to being finished. Calculation : The MACD is calculated as a distance between a Short and a Long Exponential Moving Average.
The Performance indicator compares a current Close (or any other price) with the first Close value (from the first time period ). This indicator shows the degree of a change in a price Financial Interpretation: The performance chart shows how much a Close price (or any other price) changes from the price in the first period. This indicators shows the difference as a percentage (e.g. if a performance indicator value is -20 then the Close price has fallen -20%). Calculation : The Performance indicator is calculated using following formula: 
The Rate of Change indicator is very similar to the Performance indicator, where the Performance indicator compares the first price with current price while the Rate of Change compares a specified Close price with the current price. This formula is used for both prices and volume. Financial Interpretation: The Rate of Change chart shows how much the Close price has changed for a specified period, and shows the differences as percentages. If a performance indicator value is -20 then the Close price has fallen -20%. This indicator can be used for Volume and all prices. Calculation: The Rate of Change indicator is calculated using following formula: 
The Relative Strength Index is a momentum oscillator that compares upward movements of the Close price with downward movements, and results in values that range from 0 to 100. The Relative Strength index was developed by J. Welles Wilder. Financial Interpretation: The Relative Strength Index is useful for detecting Movement which is not readily apparent, and also as a Reversal signal using Divergence between the RSI and price (an RSI above 70 or below 30 warns of coming reversals). The Relative Strength Index is smoother than the Rate of Change. Calculation: The Relative Strength index is calculated using following algorithm: 1. Average Upward Price Move = EMA( Sum of all upward movements in Closing price ) 2. Average Downward Price Move = EMA( Sum of all downward movements in Closing price ) 3. Calculate Relative Strength (RS): RS = Average Upward Price Move / Average Downward Price Move 4. Calculate the Relative Strength Index (RSI): RSI = 100 - 100 / ( 1 + RS )
Standard Deviation is used to indicate volatility, and measures the difference between values, like closing price, and their moving average. The larger the difference, the higher the Standard Deviation and volatility. The smaller the difference, the lower the Standard Deviation and volatility. Financial Interpretation: When the close price is stable the Standard Deviation is low, but if the close price changes dramatically, then there will be a high Standard Deviation present. Market tops are usually accompanied by a high Standard Deviation, which indicates volatility. Market bottoms are usually accompanied by a low Standard Deviation. Calculation: The Standard deviation is calculated using following formula:  SMA - Simple Moving Average n - Number of Time Periods
When there is an upward trend in the market place, there is also a tendency for the closing price to be very close to that day's high. During a downward trend in the market there is a tendency for the closing price to be closer to the low price. The Stochastic Indicator helps to find trend reversals by searching for a period of time when the closing prices are close to the price lows in an upward market trend, or when closing prices are close to the price highs in a downward market trend. This formula has two output values: %K - Simple Stochastic Indicator and %D - Smoothed Stochastic Indicator (Moving Average of %K). Financial Interpretation: The Stochastic indicator value is always between 0 and 100, and is represented as a percentage. If the value is above 80 then the price is closing near the high. If the value is below 20 then the price is closing near its low. The %D line is more important than %K line, and the %K line changes direction before the %D line. When the %D line changes direction prior to the %K line, a slow and steady reversal is usually indicated. If both the %K and %D lines change direction and the %K line (the FastLine™) changes direction and approaches the %D line but does not cross it then this is a good confirmation of the prior reversal stability. Calculation: The Stochastic indicator is calculated on the following way: %K = ( Today's Close - LL ) / ( HH - LL ) * 100
LL = Lowest Low price in PeriodK
HH = Highest High price in PeriodK
%D is calculated as a Moving Average of %K for PeriodD.
The TRIX indicator formula is based on a triple moving average of the closing price. Its purpose is to eliminate short cycles. This indicator keeps the closing price in trends that are shorter than the specified period. Financial Interpretation: The TRIX indicator is designed to remove short and not very important cycles. With triple exponential smoothing TRIX filters out all cycles shorter than the specified number of periods. The TRIX should be also used together with its Moving Average. When the TRIX rises above its Moving Average it is a buying signal. When the TRIX falls below its Moving Average it is a selling signal. The turning points can be identified by using divergence between the security and the TRIX. Calculation: The TRIX indicator is calculated using the following formula: 1. EMA1 = EMA( Close )
2. EMA2 = EMA( EMA1 )
3. EMA3 = EMA( EMA2 )
4. TRIX = ( EMA3 [today] - EMA3 [yesterday] ) / EMA3 [yesterday]
Where:
EMA - Exponential Moving Average
The Volatility Chaikins indicator measures the difference between High and Low prices, and is used to indicate tops or bottoms of the market. This formula was developed by Marc Chaikin. Financial Interpretation: If the volatility (the difference between High and Low prices) is high it could indicate a market top (high market activity). If the volatility is low it could indicate a market bottom (low market activity). Calculation: Volatility Chaikins is calculated using the following formulas:  
William's %R is a momentum indicator, and is used to measure overbought, or oversold levels. This indicator is very similar to the Stochastic %K indicator, except that Williams %R is always a negative value between 0 and -100. This indicator was developed by Larry Williams. Financial Interpretation: This formula is very similar to the Stochastic Indicator formula, the difference being that William's %R is plotted on a negative scale and does not use internal smoothing. The value for the William's %R indicator is always between 0 and -100, and is represented as a percentage. If the value is below -80 then the price is closing near the high price. If the value is above -20 then the price is closing near its low. Calculation: The William's %R indicator is calculated on the following way: %R = (( HH - Today's Close ) / ( HH - LL )) * -100
where:
LL = Lowest Low price in Period
HH = Highest High price in Period
Select an Underneath Study and click ? Button to display Help
The Average True Range is an indicator that measures commitment, and compares the range between the High, Low and Close prices. This indicator was developed by J. Welles Wilder. Financial Interpretation: High Average True Range values often occur at market bottoms due to extensive panic sell. Low Average true range values are characteristic with market tops. Calculation: To find the Average True Range it is first necessary to find the True Range. Finding the True range is done in this manner: True Range = MAX( |High(today) - Low(today)|, |Close(yesterday) - High(today)|, |Close(yesterday) - Low(today)|) The Average True range is calculated as a Simple Moving Average of True Range.
The Commodity Channel Index compares prices with their moving averages. If the Commodity channel index is high, it means that a price is higher than its moving average, which is an indicator that the security is overbought. If the Commodity channel index is low, it means that a price is lower than its moving average, which is an indicator that the security is oversold. Financial interpretation: The Commodity channel index could be used as an overbought/oversold indicator or for divergence. If the Commodity channel index is high it means that a price is higher than its moving average which is an indicator that security is overbought. If the Commodity channel index is low it means that a price is lower than its moving average, which is an indicator that security is oversold. If the commodity channel index is above 100 it means that security is overbought. If the commodity channel index is below -100 it means that security is oversold. Calculation : The Commodity Channel index is calculated using following algorithm: 1. Calculate typical price:
TP = (High+Low+Close) / 3 2. Calculate Simple Moving Average of the TP (SMATP):
SMATP=SMA(TP) 3. Calculate Mean Deviation: 4. Calculate Commodity Channel Index: 
The Detrended Price Oscillator attempts to remove trend from prices. By comparing the closing price or any other price with it's moving average, the Detrended Price Oscillator eliminates cycles that are longer than the moving average. Financial Interpretation: The Detrended price oscillator is used to remove long cycles from a trend. When a price is detrended using the detrended price oscillator, cycles and overbought/oversold levels can be identified more easily. The principal is similar to using longer length technical indicators compared to shorter length technical indicators. Calculation: The Detrended Price Oscillator is calculated in the following way: - The first step is to create a simple moving average ( MA ) using n periods.
- 2. Calculate the Detrended Price Oscillator using the Close price and Moving Average:
DPO = Close – (MA((n/2)+1)) where MA((n/2)+1) means moving average (n/2)+1 days ago.
The Mass Index is used to predict trend reversal by comparing the difference, and range between High and Low prices. If the Mass Index increases, the range between High and low increases. If the Mass Index decreases, the range between High and Low decreases. Financial Interpretation: The most significant pattern to watch for is the "reversal bulge", will occur when a 25 day period Mass Index rises above 27 and falls back below 26.5. If the moving average of prices is going down and a reversal bulge has occurred it is signal for buying. If the moving average of prices is going up and a reversal bulge has occurred it is signal for selling. Calculation: The Mass Index is calculated using following formula: Where EMA is Exponential Moving Average calculated using the AveragePeriod parameter.
The MACD (Moving Average Convergence/Divergence) indicator compares the two moving averages of prices. The MACD is used with a 9-day Exponential Moving average as a signal that indentifies buying or selling moments. This indicator was developed by Gerald Appel. Financial Interpretation: The MACD indicator should be used with a 9-day Exponential Moving Average as its Signal Line. The time to sell is when the MACD indicator falls below its signal line. Similarly, the time to buy is when the MACD indicator is higher than its signal line. When the MACD rises it means that security could be overbought. When the MACD diverges from prices this could be a sign that the current trend is close to being finished. Calculation : The MACD is calculated as a distance between a Short and a Long Exponential Moving Average.
The Performance indicator compares a current Close (or any other price) with the first Close value (from the first time period ). This indicator shows the degree of a change in a price Financial Interpretation: The performance chart shows how much a Close price (or any other price) changes from the price in the first period. This indicators shows the difference as a percentage (e.g. if a performance indicator value is -20 then the Close price has fallen -20%). Calculation : The Performance indicator is calculated using following formula:
The Rate of Change indicator is very similar to the Performance indicator, where the Performance indicator compares the first price with current price while the Rate of Change compares a specified Close price with the current price. This formula is used for both prices and volume. Financial Interpretation: The Rate of Change chart shows how much the Close price has changed for a specified period, and shows the differences as percentages. If a performance indicator value is -20 then the Close price has fallen -20%. This indicator can be used for Volume and all prices. Calculation: The Rate of Change indicator is calculated using following formula:
The Relative Strength Index is a momentum oscillator that compares upward movements of the Close price with downward movements, and results in values that range from 0 to 100. The Relative Strength index was developed by J. Welles Wilder. Financial Interpretation: The Relative Strength Index is useful for detecting Movement which is not readily apparent, and also as a Reversal signal using Divergence between the RSI and price (an RSI above 70 or below 30 warns of coming reversals). The Relative Strength Index is smoother than the Rate of Change. Calculation: The Relative Strength index is calculated using following algorithm: 1. Average Upward Price Move = EMA( Sum of all upward movements in Closing price ) 2. Average Downward Price Move = EMA( Sum of all downward movements in Closing price ) 3. Calculate Relative Strength (RS): RS = Average Upward Price Move / Average Downward Price Move 4. Calculate the Relative Strength Index (RSI): RSI = 100 - 100 / ( 1 + RS )
Standard Deviation is used to indicate volatility, and measures the difference between values, like closing price, and their moving average. The larger the difference, the higher the Standard Deviation and volatility. The smaller the difference, the lower the Standard Deviation and volatility. Financial Interpretation: When the close price is stable the Standard Deviation is low, but if the close price changes dramatically, then there will be a high Standard Deviation present. Market tops are usually accompanied by a high Standard Deviation, which indicates volatility. Market bottoms are usually accompanied by a low Standard Deviation. Calculation: The Standard deviation is calculated using following formula: SMA - Simple Moving Average n - Number of Time Periods
When there is an upward trend in the market place, there is also a tendency for the closing price to be very close to that day's high. During a downward trend in the market there is a tendency for the closing price to be closer to the low price. The Stochastic Indicator helps to find trend reversals by searching for a period of time when the closing prices are close to the price lows in an upward market trend, or when closing prices are close to the price highs in a downward market trend. This formula has two output values: %K - Simple Stochastic Indicator and %D - Smoothed Stochastic Indicator (Moving Average of %K). Financial Interpretation: The Stochastic indicator value is always between 0 and 100, and is represented as a percentage. If the value is above 80 then the price is closing near the high. If the value is below 20 then the price is closing near its low. The %D line is more important than %K line, and the %K line changes direction before the %D line. When the %D line changes direction prior to the %K line, a slow and steady reversal is usually indicated. If both the %K and %D lines change direction and the %K line (the FastLine™) changes direction and approaches the %D line but does not cross it then this is a good confirmation of the prior reversal stability. Calculation: The Stochastic indicator is calculated on the following way: %K = ( Today's Close - LL ) / ( HH - LL ) * 100
LL = Lowest Low price in PeriodK
HH = Highest High price in PeriodK
%D is calculated as a Moving Average of %K for PeriodD.
The TRIX indicator formula is based on a triple moving average of the closing price. Its purpose is to eliminate short cycles. This indicator keeps the closing price in trends that are shorter than the specified period. Financial Interpretation: The TRIX indicator is designed to remove short and not very important cycles. With triple exponential smoothing TRIX filters out all cycles shorter than the specified number of periods. The TRIX should be also used together with its Moving Average. When the TRIX rises above its Moving Average it is a buying signal. When the TRIX falls below its Moving Average it is a selling signal. The turning points can be identified by using divergence between the security and the TRIX. Calculation: The TRIX indicator is calculated using the following formula: 1. EMA1 = EMA( Close )
2. EMA2 = EMA( EMA1 )
3. EMA3 = EMA( EMA2 )
4. TRIX = ( EMA3 [today] - EMA3 [yesterday] ) / EMA3 [yesterday]
Where:
EMA - Exponential Moving Average
The Volatility Chaikins indicator measures the difference between High and Low prices, and is used to indicate tops or bottoms of the market. This formula was developed by Marc Chaikin. Financial Interpretation: If the volatility (the difference between High and Low prices) is high it could indicate a market top (high market activity). If the volatility is low it could indicate a market bottom (low market activity). Calculation: Volatility Chaikins is calculated using the following formulas:
William's %R is a momentum indicator, and is used to measure overbought, or oversold levels. This indicator is very similar to the Stochastic %K indicator, except that Williams %R is always a negative value between 0 and -100. This indicator was developed by Larry Williams. Financial Interpretation: This formula is very similar to the Stochastic Indicator formula, the difference being that William's %R is plotted on a negative scale and does not use internal smoothing. The value for the William's %R indicator is always between 0 and -100, and is represented as a percentage. If the value is below -80 then the price is closing near the high price. If the value is above -20 then the price is closing near its low. Calculation: The William's %R indicator is calculated on the following way: %R = (( HH - Today's Close ) / ( HH - LL )) * -100
where:
LL = Lowest Low price in Period
HH = Highest High price in Period
Select an Underneath Study and click ? Button to display Help
The Average True Range is an indicator that measures commitment, and compares the range between the High, Low and Close prices. This indicator was developed by J. Welles Wilder. Financial Interpretation: High Average True Range values often occur at market bottoms due to extensive panic sell. Low Average true range values are characteristic with market tops. Calculation: To find the Average True Range it is first necessary to find the True Range. Finding the True range is done in this manner: True Range = MAX( |High(today) - Low(today)|, |Close(yesterday) - High(today)|, |Close(yesterday) - Low(today)|) The Average True range is calculated as a Simple Moving Average of True Range.
The Commodity Channel Index compares prices with their moving averages. If the Commodity channel index is high, it means that a price is higher than its moving average, which is an indicator that the security is overbought. If the Commodity channel index is low, it means that a price is lower than its moving average, which is an indicator that the security is oversold. Financial interpretation: The Commodity channel index could be used as an overbought/oversold indicator or for divergence. If the Commodity channel index is high it means that a price is higher than its moving average which is an indicator that security is overbought. If the Commodity channel index is low it means that a price is lower than its moving average, which is an indicator that security is oversold. If the commodity channel index is above 100 it means that security is overbought. If the commodity channel index is below -100 it means that security is oversold. Calculation : The Commodity Channel index is calculated using following algorithm: 1. Calculate typical price:
TP = (High+Low+Close) / 3 2. Calculate Simple Moving Average of the TP (SMATP):
SMATP=SMA(TP) 3. Calculate Mean Deviation: 4. Calculate Commodity Channel Index:
The Detrended Price Oscillator attempts to remove trend from prices. By comparing the closing price or any other price with it's moving average, the Detrended Price Oscillator eliminates cycles that are longer than the moving average. Financial Interpretation: The Detrended price oscillator is used to remove long cycles from a trend. When a price is detrended using the detrended price oscillator, cycles and overbought/oversold levels can be identified more easily. The principal is similar to using longer length technical indicators compared to shorter length technical indicators. Calculation: The Detrended Price Oscillator is calculated in the following way: - The first step is to create a simple moving average ( MA ) using n periods.
- 2. Calculate the Detrended Price Oscillator using the Close price and Moving Average:
DPO = Close – (MA((n/2)+1)) where MA((n/2)+1) means moving average (n/2)+1 days ago.
The Mass Index is used to predict trend reversal by comparing the difference, and range between High and Low prices. If the Mass Index increases, the range between High and low increases. If the Mass Index decreases, the range between High and Low decreases. Financial Interpretation: The most significant pattern to watch for is the "reversal bulge", will occur when a 25 day period Mass Index rises above 27 and falls back below 26.5. If the moving average of prices is going down and a reversal bulge has occurred it is signal for buying. If the moving average of prices is going up and a reversal bulge has occurred it is signal for selling. Calculation: The Mass Index is calculated using following formula: Where EMA is Exponential Moving Average calculated using the AveragePeriod parameter.
The MACD (Moving Average Convergence/Divergence) indicator compares the two moving averages of prices. The MACD is used with a 9-day Exponential Moving average as a signal that indentifies buying or selling moments. This indicator was developed by Gerald Appel. Financial Interpretation: The MACD indicator should be used with a 9-day Exponential Moving Average as its Signal Line. The time to sell is when the MACD indicator falls below its signal line. Similarly, the time to buy is when the MACD indicator is higher than its signal line. When the MACD rises it means that security could be overbought. When the MACD diverges from prices this could be a sign that the current trend is close to being finished. Calculation : The MACD is calculated as a distance between a Short and a Long Exponential Moving Average.
The Performance indicator compares a current Close (or any other price) with the first Close value (from the first time period ). This indicator shows the degree of a change in a price Financial Interpretation: The performance chart shows how much a Close price (or any other price) changes from the price in the first period. This indicators shows the difference as a percentage (e.g. if a performance indicator value is -20 then the Close price has fallen -20%). Calculation : The Performance indicator is calculated using following formula:
The Rate of Change indicator is very similar to the Performance indicator, where the Performance indicator compares the first price with current price while the Rate of Change compares a specified Close price with the current price. This formula is used for both prices and volume. Financial Interpretation: The Rate of Change chart shows how much the Close price has changed for a specified period, and shows the differences as percentages. If a performance indicator value is -20 then the Close price has fallen -20%. This indicator can be used for Volume and all prices. Calculation: The Rate of Change indicator is calculated using following formula:
The Relative Strength Index is a momentum oscillator that compares upward movements of the Close price with downward movements, and results in values that range from 0 to 100. The Relative Strength index was developed by J. Welles Wilder. Financial Interpretation: The Relative Strength Index is useful for detecting Movement which is not readily apparent, and also as a Reversal signal using Divergence between the RSI and price (an RSI above 70 or below 30 warns of coming reversals). The Relative Strength Index is smoother than the Rate of Change. Calculation: The Relative Strength index is calculated using following algorithm: 1. Average Upward Price Move = EMA( Sum of all upward movements in Closing price ) 2. Average Downward Price Move = EMA( Sum of all downward movements in Closing price ) 3. Calculate Relative Strength (RS): RS = Average Upward Price Move / Average Downward Price Move 4. Calculate the Relative Strength Index (RSI): RSI = 100 - 100 / ( 1 + RS )
Standard Deviation is used to indicate volatility, and measures the difference between values, like closing price, and their moving average. The larger the difference, the higher the Standard Deviation and volatility. The smaller the difference, the lower the Standard Deviation and volatility. Financial Interpretation: When the close price is stable the Standard Deviation is low, but if the close price changes dramatically, then there will be a high Standard Deviation present. Market tops are usually accompanied by a high Standard Deviation, which indicates volatility. Market bottoms are usually accompanied by a low Standard Deviation. Calculation: The Standard deviation is calculated using following formula: SMA - Simple Moving Average n - Number of Time Periods
When there is an upward trend in the market place, there is also a tendency for the closing price to be very close to that day's high. During a downward trend in the market there is a tendency for the closing price to be closer to the low price. The Stochastic Indicator helps to find trend reversals by searching for a period of time when the closing prices are close to the price lows in an upward market trend, or when closing prices are close to the price highs in a downward market trend. This formula has two output values: %K - Simple Stochastic Indicator and %D - Smoothed Stochastic Indicator (Moving Average of %K). Financial Interpretation: The Stochastic indicator value is always between 0 and 100, and is represented as a percentage. If the value is above 80 then the price is closing near the high. If the value is below 20 then the price is closing near its low. The %D line is more important than %K line, and the %K line changes direction before the %D line. When the %D line changes direction prior to the %K line, a slow and steady reversal is usually indicated. If both the %K and %D lines change direction and the %K line (the FastLine™) changes direction and approaches the %D line but does not cross it then this is a good confirmation of the prior reversal stability. Calculation: The Stochastic indicator is calculated on the following way: %K = ( Today's Close - LL ) / ( HH - LL ) * 100
LL = Lowest Low price in PeriodK
HH = Highest High price in PeriodK
%D is calculated as a Moving Average of %K for PeriodD.
The TRIX indicator formula is based on a triple moving average of the closing price. Its purpose is to eliminate short cycles. This indicator keeps the closing price in trends that are shorter than the specified period. Financial Interpretation: The TRIX indicator is designed to remove short and not very important cycles. With triple exponential smoothing TRIX filters out all cycles shorter than the specified number of periods. The TRIX should be also used together with its Moving Average. When the TRIX rises above its Moving Average it is a buying signal. When the TRIX falls below its Moving Average it is a selling signal. The turning points can be identified by using divergence between the security and the TRIX. Calculation: The TRIX indicator is calculated using the following formula: 1. EMA1 = EMA( Close )
2. EMA2 = EMA( EMA1 )
3. EMA3 = EMA( EMA2 )
4. TRIX = ( EMA3 [today] - EMA3 [yesterday] ) / EMA3 [yesterday]
Where:
EMA - Exponential Moving Average
The Volatility Chaikins indicator measures the difference between High and Low prices, and is used to indicate tops or bottoms of the market. This formula was developed by Marc Chaikin. Financial Interpretation: If the volatility (the difference between High and Low prices) is high it could indicate a market top (high market activity). If the volatility is low it could indicate a market bottom (low market activity). Calculation: Volatility Chaikins is calculated using the following formulas:
William's %R is a momentum indicator, and is used to measure overbought, or oversold levels. This indicator is very similar to the Stochastic %K indicator, except that Williams %R is always a negative value between 0 and -100. This indicator was developed by Larry Williams. Financial Interpretation: This formula is very similar to the Stochastic Indicator formula, the difference being that William's %R is plotted on a negative scale and does not use internal smoothing. The value for the William's %R indicator is always between 0 and -100, and is represented as a percentage. If the value is below -80 then the price is closing near the high price. If the value is above -20 then the price is closing near its low. Calculation: The William's %R indicator is calculated on the following way: %R = (( HH - Today's Close ) / ( HH - LL )) * -100
where:
LL = Lowest Low price in Period
HH = Highest High price in Period
| S/No | | Trans Date | Close | Prev | Change | % Chg | Open | High | Low | Avg | Deals | Volume | Value |
| 1 |  | 11/06/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 20.00 | 155.00 |
| 2 | | 14/06/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 1,200.00 | 9,300.00 |
| 3 | | 17/06/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 6 | 22.00 | 170.50 |
| 4 | | 28/06/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 100.00 | 775.00 |
| 5 | | 29/06/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 250.00 | 1,937.50 |
| 6 | | 07/07/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 82.00 | 635.50 |
| 7 | | 09/07/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 267.00 | 2,069.25 |
| 8 | | 21/07/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 1,000.00 | 7,750.00 |
| 9 | | 22/07/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 100.00 | 775.00 |
| 10 | | 28/07/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 5 | 7,599.00 | 58,892.25 |
| 11 | | 29/07/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 1,000.00 | 7,750.00 |
| 12 | | 17/08/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 70.00 | 542.50 |
| 13 | | 18/08/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 139.00 | 1,077.25 |
| 14 | | 23/08/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 1 | 1,500.00 | 11,625.00 |
| 15 | | 31/08/2010 | 8.15 | 8.15 | 0.00 | 0.00 | 8.15 | 8.15 | 8.15 | 7.75 | 6 | 1,080.00 | 8,370.00 |
| 16 |  | 03/09/2010 | 7.75 | 8.15 | -0.40 | -4.91 | 7.75 | 7.75 | 7.75 | 7.75 | 1 | 210,000.00 | 1,627,500.00 |
| | | | | | | | | | | | |
224,429.00 | 1,739,324.75 |
|  | | Full Name | ALUMACO PLC | | Symbol | ALUMACO | | Sector | INDUSTRIAL/DOMESTIC PRODUCTS | | Address | 32, Creek Road, | | Apapa, | | | | Lagos | | Tel Nos | 234(0)01-5803270 - 4 | | Fax | 01-5870368 | | Email | alumaco@hyperia.com | | Web Site | | | Date Started | | | Date Listed | July, 1972. | | Year End | Dec 31st |
| | Outstanding Units of Shares | 75,600,000.00 | | Last Traded Date | 03/09/2010 | | Last Traded Price | 7.75 | | Technical Suspension | Y/N | | Most Current Annual PAT * | 89,797,000.00 | | Most Current Annual PAT ** | 89,797,000.00 | | Earning Per Share * | 1.19 | | Earning Per Share ** | 1.19 | | Sector's Average EPS * | 0.60 | | Sector's Average EPS ** | 1.14 | | Price Earning Ratio* | 6.52 | | Price Earning Ratio** | 6.52 | | Sector's Avg. P E Ratio * | 21.65 | | Sector's Avg. P E Ratio ** | 9.45 |
| | | | Directors |
| Alhaji (Dr.) Shehu A. Musa, CFR, GCON, Chairman | Chief Isaiah Olanrewaju Ajijola | Mr. Akinwande A. Akinola |
| Maj. Gen. Victor Omonigho Odeka (Rtd) | Mr. M. O. Lakanu GM/CEO) | |
|
| Secreatary |
| Marina Nominees Limited |
Registrar
| United Bank for Africa Plc. |
| |
|
Auditor |
| Akintola Willams Deloite (Chartered Accountants) |
|
Forecasting and Trend AnalysisIn Time Series analysis, it is assumed that the data consists of a systematic pattern, and also random noise that makes the pattern difficult to identify. Most time series analysis techniques use filtering to remove the data noise. Time Series analysis has two main goals: - Identifying the nature of a sequence of observations
- Predicting future values using historical observations (also known as forecasting)
There are two general components of Time series patterns: Trend and Seasonality. The trend is a linear or non-linear component, and does not repeat within the time range. The Seasonality repeats itself in systematic intervals over time. These two components are often both present in real data.Formula 3. or Trend AnalysisTrend analysis is a technique used to identify a trend component in time series data. In many cases data can be approximated by a linear function, but logarithmic, exponential, and polynomial functions can also be used. ADstock supports polynomial approximation, and also linear approximation - which is implemented as a special case of polynomial approximation. Regression AnalysisRegression analysis is the study of relationships among variables, and its purpose is to predict, or estimate, the value of one variable from the known values of other variables related to it. Any method of fitting equations to data may be called regression, and these equations are useful for making predictions, and judging the strength of relationships. Forecasting and extrapolation from present values to future values is not a function of regression analysis. To predict the future, time series analysis is used. To predict values it is necessary to find a predictive function that will minimize the sum of distances between each of the points, and the predictive function itself. The least-squares method is the most common function amongst the predictive functions, and it calculates the minimum average squared deviations between the points, and the estimated function. Financial Interpretation: Forecasting can be used with all Prices to estimate future values, but can also be used with volumes and other indicators. Calculation: To understand the least-square method let assume that all points (values) which are used as historical data to predict the future belong to the unknown function f(x). The main goal is to find function f(x) which is in many cases almost impossible, or to approximate the f(x) function with another function q(x). Now, if the q(x) function is the polynomial function,  Formula 7.  Formula 4.
To find coefficients of the polynomial it is necessary to find a minimum of the function defined in Formula 4.  
If the n value is equal to 2, the Q(x) polynomial will represent the linear function:Formula 6.
Solving the system of n+1 linear equations we will determine all coefficients defined in polynomial Q(X) (Formula 1.)
Now let's return to our point values and change the function f(x) with pairs of x and y values:
 k=0,1,2,...,n.k=0,1,2,...,n.k=0,1,2,...,n. Formula 5. which is equal to:   Formula 1.
the norm, or mean square error, will be a minimum: Formula 2.
Theorem 1. For each appropriate function f(x), there is a unique least squares polynomial approximation of degree at most n which minimizes Formula 2.
Lets define the function of n+1 variables: 
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