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Qema

Variety N-Tuple Moving Averages w/ Variety Stepping [Loxx]Variety N-Tuple Moving Averages w/ Variety Stepping is a moving average indicator that allows you to create 1- 30 tuple moving average types; i.e., Double-MA, Triple-MA, Quadruple-MA, Quintuple-MA, ... N-tuple-MA. This version contains 2 different moving average types. For example, using "50" as the depth will give you Quinquagintuple Moving Average. If you'd like to find the name of the moving average type you create with the depth input with this indicator, you can find a list of tuples here: Tuples extrapolated Due to the coding required to adapt a moving average to fit into this indicator, additional moving average types will be added as they are created to fit into this unique use case. Since this is a work in process, there will be many future updates of this indicator. For now, you can choose from either EMA or RMA. This indicator is also considered one of the top 10 forex indicators. See details here: forex-station.com Additionally, this indicator is a computationally faster, more streamlined version of the following indicators with the addition of 6 stepping functions and 6 different bands/channels types. STD-Stepped, Variety N-Tuple Moving Averages STD-Stepped, Variety N-Tuple Moving Averages is the standard deviation stepped/filtered indicator of the following indicator Last but not least, a big shoutout to @lejmer for his help in formulating a looping solution for this streamlined version. this indicator is speedy even at 50 orders deep. You can find his scripts here: www.tradingview.com How this works Step 1: Run factorial calculation on the depth value, Step 2: Calculate weights of nested moving averages factorial(depth) / (factorial(depth - k) * factorial(k); where depth is the depth and k is the weight position Examples of coefficient outputs: 6 Depth: 6 15 20 15 6 7 Depth: 7 21 35 35 21 7 8 Depth: 8 28 56 70 56 28 8 9 Depth: 9 36 34 84 126 126 84 36 9 10 Depth: 10 45 120 210 252 210 120 45 10 11 Depth: 11 55 165 330 462 462 330 165 55 11 12 Depth: 12 66 220 495 792 924 792 495 220 66 12 13 Depth: 13 78 286 715 1287 1716 1716 1287 715 286 78 13 Step 3: Apply coefficient to each moving average For QEMA, which is 5 depth EMA , the calculation is as follows ema1 = ta. ema ( src , length) ema2 = ta. ema (ema1, length) ema3 = ta. ema (ema2, length) ema4 = ta. ema (ema3, length) ema5 = ta. ema (ema4, length) In this new streamlined version, these MA calculations are packed into an array inside loop so Pine doesn't have to keep all possible series information in memory. This is handled with the following code: temp = array.get(workarr, k + 1) + alpha * (array.get(workarr, k) - array.get(workarr, k + 1)) array.set(workarr, k + 1, temp) After we pack the array, we apply the coefficients to derive the NTMA: qema = 5 * ema1 - 10 * ema2 + 10 * ema3 - 5 * ema4 + ema5 Stepping calculations First off, you can filter by both price and/or MA output. Both price and MA output can be filtered/stepped in their own way. You'll see two selectors in the input settings. Default is ATR ATR. Here's how stepping works in simple terms: if the price/MA output doesn't move by X deviations, then revert to the price/MA output one bar back. ATR The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period. Standard Deviation Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation. Adaptive Deviation By definition, the Standard Deviation (STD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis we usually use it to measure the level of current volatility . Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA , we can call it EMA deviation. And added to that, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting). The difference when compared to standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions. See how this compares to Standard Devaition here: Adaptive Deviation Median Absolute Deviation The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant. Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution. For this indicator, I used a manual recreation of the quantile function in Pine Script. This is so users have a full inside view into how this is calculated. Efficiency-Ratio Adaptive ATR Average True Range (ATR) is widely used indicator in many occasions for technical analysis . It is calculated as the RMA of true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range See how this compares to ATR here: ER-Adaptive ATR Mean Absolute Deviation The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation. This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life. For Pine Coders, this is equivalent of using ta.dev() Bands/Channels See the information above for how bands/channels are calculated. After the one of the above deviations is calculated, the channels are calculated as output +/- deviation * multiplier Signals Green is uptrend, red is downtrend, yellow "L" signal is Long, fuchsia "S" signal is short. Included: Alerts Loxx's Expanded Source Types Bar coloring Signals 6 bands/channels types 6 stepping types Related indicators 3-Pole Super Smoother w/ EMA-Deviation-Corrected Stepping STD-Stepped Fast Cosine Transform Moving Average ATR-Stepped PDF MA
Pine Script™ indicator
by loxx
1
STD-Stepped, Variety N-Tuple Moving Averages [Loxx]STD-Stepped, Variety N-Tuple Moving Averages is the standard deviation stepped/filtered indicator of the following indicator Variety N-Tuple Moving Averages is a moving average indicator that allows you to create 1- 30 tuple moving average types; i.e., Double-MA, Triple-MA, Quadruple-MA, Quintuple-MA, ... N-tuple-MA. This version contains 5 different moving average types including T3. A list of tuples can be found here if you'd like to name the order of the moving average by depth: Tuples extrapolated STD-Stepped, You'll notice that this is a lot of code and could normally be packed into a single loop in order to extract the N-tuple MA, however due to Pine Script limitations and processing paradigm this is not possible ... yet. If you choose the EMA option and select a depth of 2, this is the classic DEMA ; EMA with a depth of 3 is the classic TEMA , and so on and so forth this is to help you understand how this indicator works. This version of NTMA is restricted to a maximum depth of 30 or less. Normally this indicator would include 50 depths but I've cut this down to 30 to reduce indicator load time. In the future, I'll create an updated NTMA that allows for more depth levels. This is considered one of the top ten indicators in forex. You can read more about it here: forex-station.com How this works Step 1: Run factorial calculation on the depth value, Step 2: Calculate weights of nested moving averages factorial(nemadepth) / (factorial(nemadepth - k) * factorial(k); where nemadepth is the depth and k is the weight position Examples of coefficient outputs: 6 Depth: 6 15 20 15 6 7 Depth: 7 21 35 35 21 7 8 Depth: 8 28 56 70 56 28 8 9 Depth: 9 36 34 84 126 126 84 36 9 10 Depth: 10 45 120 210 252 210 120 45 10 11 Depth: 11 55 165 330 462 462 330 165 55 11 12 Depth: 12 66 220 495 792 924 792 495 220 66 12 13 Depth: 13 78 286 715 1287 1716 1716 1287 715 286 78 13 Step 3: Apply coefficient to each moving average For QEMA, which is 5 depth EMA , the caculation is as follows ema1 = ta. ema ( src , length) ema2 = ta. ema (ema1, length) ema3 = ta. ema (ema2, length) ema4 = ta. ema (ema3, length) ema5 = ta. ema (ema4, length) qema = 5 * ema1 - 10 * ema2 + 10 * ema3 - 5 * ema4 + ema5 Included: Alerts Loxx's Expanded Source Types Bar coloring Signals Standard deviation stepping
Pine Script™ indicator
by loxx
7
Variety N-Tuple Moving Averages [Loxx]Variety N-Tuple Moving Averages is a moving average indicator that allows you to create 1- 30 tuple moving average types; i.e., Double-MA, Triple-MA, Quadruple-MA, Quintuple-MA, ... N-tuple-MA. This version contains 5 different moving average types including T3. A list of tuples can be found here if you'd like to name the order of the moving average by depth: Tuples extrapolated You'll notice that this is a lot of code and could normally be packed into a single loop in order to extract the N-tuple MA, however due to Pine Script limitations and processing paradigm this is not possible ... yet. If you choose the EMA option and select a depth of 2, this is the classic DEMA; EMA with a depth of 3 is the classic TEMA, and so on and so forth this is to help you understand how this indicator works. This version of NTMA is restricted to a maximum depth of 30 or less. Normally this indicator would include 50 depths but I've cut this down to 30 to reduce indicator load time. In the future, I'll create an updated NTMA that allows for more depth levels. This is considered one of the top ten indicators in forex. You can read more about it here: forex-station.com How this works Step 1: Run factorial calculation on the depth value, Step 2: Calculate weights of nested moving averages factorial(nemadepth) / (factorial(nemadepth - k) * factorial(k); where nemadepth is the depth and k is the weight position Examples of coefficient outputs: 6 Depth: 6 15 20 15 6 7 Depth: 7 21 35 35 21 7 8 Depth: 8 28 56 70 56 28 8 9 Depth: 9 36 34 84 126 126 84 36 9 10 Depth: 10 45 120 210 252 210 120 45 10 11 Depth: 11 55 165 330 462 462 330 165 55 11 12 Depth: 12 66 220 495 792 924 792 495 220 66 12 13 Depth: 13 78 286 715 1287 1716 1716 1287 715 286 78 13 Step 3: Apply coefficient to each moving average For QEMA, which is 5 depth EMA, the caculation is as follows ema1 = ta.ema(src, length) ema2 = ta.ema(ema1, length) ema3 = ta.ema(ema2, length) ema4 = ta.ema(ema3, length) ema5 = ta.ema(ema4, length) qema = 5 * ema1 - 10 * ema2 + 10 * ema3 - 5 * ema4 + ema5 Included: Alerts Loxx's Expanded Source Types Bar coloring
Pine Script™ indicator
by loxx
4