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Median

MA VisualizerThe MA Visualizer is made up of 5 Moving Averages (MA) All MA change color when the price closes above or below the MA line. The background between the MA line and price will also change color, this creates the Visualizer. When two or more MA are selected the two visualizer's will combine and create a gradient effect. Each MA can be adjusted with 6 source selection's to choose from (SMA , EMA , WMA , HMA , RMA , WVMA). The Visualizer can be turned off while leaving the MA lines turned on and vice versa. Their is also a MA Cross indicator built-in.
Pine Script®指標
由Satosaur提供
11
Median Convergence DivergenceIntroduction The Median Convergence Divergence (MCD) is a derivative of the Moving Average Convergence Divergence (MACD). The difference is the change in the use of the measure of central tendency. In MACD, moving average (mean) is used, whereas, in MCD, the median is used instead. The purpose of using the median is to eliminate the outlying values, which would be calculated for a moving average. The outliers would affect the value of the moving average. For example: 3, 5, 7, 8, 5, 4, 2, 1, 6, 21, 8. The data set average is 6.3, whereas the median value is 5. There is a difference of about 23% in the example. The reason is the outlying value '21' in the data set. As the markets are volatile, outlying values can always emerge. A moving average will consider those values; on the other hand, the median will ignore. If the strategy calls for a tool to ignore the outliers, the Median Convergence Divergence would be a great centered oscillator. The default values have changed to suit the current trading days in a week. When the MACD was introduced, there would be six trading days in a week. Therefore, it used 12 (2 weeks), 26(4 weeks), and 9 ( 1.5 weeks). But now that there are five trading days per week. The default values are adapted to them. Feel free to change them as per your wish. Recommended Settings The current settings are set to be used for the Daily Time Frame: 5 day period for the fast line, a 20 day period for the slow line, and a 10 day period for the signal line. (5 days represent a trading week, 10 days is two weeks, and 20 days is 4 weeks or a month) For the weekly charts, use 4 week period for the fast line, 13 week period for the slow line, and 8 week period for the signal line. (4 weeks represent a month, 8 weeks is two months, and 13 weeks is 3 months or quarterly) And for monthly charts, use 3 month period for the fast line, 12 month period for the slow line, and 6 month period for the signal line. (3 months is quarterly, 6 months is bi-yearly, and 12 month is yearly) It'll be challenging to measure for intraday since there are many different timeframes within intraday. The settings mentioned above should also be customized as per the requirements of the trading strategy. Strategy The strategy application is the same as the MACD, i.e., Signal Line Crossovers, Zero Line Crossovers, and Divergence. Signal Line Crossovers: When the MCD line crosses above the Signal line, it's a bullish crossover. When the MCD line crosses below the Signal line, it's a bearish crossover. Zero Line Crossovers: It's a bullish crossover when the MCD line crosses above the Zero line. When the MCD line crosses below the Zero Line, it's a bearish crossover. Divergence: When price shows a lower low, but MCD shows a higher low, it's a bullish divergence. When the price shows a higher high but MCD shows a lower high, it's a bearish divergence. Using other indicators in conjunction with the Median Convergence Divergence is recommended to take entry and exit signals.
Pine Script®指標
由maksumit提供
18
vol_rangesThis script shows three measures of volatility: historical (hv): realized volatility of the recent past median (mv): a long run average of realized volatility implied (iv): a user-defined volatility Historical and median volatility are based on the EWMA, rather than standard deviation, method of calculating volatility. Since Tradingview's built in ema function uses a window, the "window" parameter determines how much historical data is used to calculate these volatility measures. E.g. 30 on a daily chart means the previous 30 days. The plots above and below historical candles show past projections based on these measures. The "periods to expiration" dictates how far the projection extends. At 30 periods to expiration (default), the plot will indicate the one standard deviation range from 30 periods ago. This is calculated by multiplying the volatility measure by the square root of time. For example, if the historical volatility (hv) was 20% and the window is 30, then the plot is drawn over: close * 1.2 * sqrt(30/252). At the most recent candle, this same calculation is simply drawn as a line projecting into the future. This script is intended to be used with a particular options contract in mind. For example, if the option expires in 15 days and has an implied volatility of 25%, choose 15 for the window and 25 for the implied volatility options. The ranges drawn will reflect the two standard deviation range both in the future (lines) and at any point in the past (plots) for HV (blue), MV (red), and IV (grey).
Pine Script®指標
由taylor_o提供
1
Weighted Harrell-Davis Quantile Estimator with AbsoluteDeviation QUANTILE ESTIMATORS Weighted Harrell-Davis Quantile Estimator with Absolute Deviation Fences. DISCLAIMER: The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets. The following indicator was made for NON LUCRATIVE ACTIVITIES and must remain as is, following TradingView's regulations. Use of indicator and their code are published for work and knowledge sharing. All access granted over it, their use, copy or re-use should mention authorship(s) and origin(s). WARNING NOTICE! THE INCLUDED FUNCTION MUST BE CONSIDERED FOR TESTING. The models included in the indicator have been taken from open sources on the web and some of them has been modified by the author, problems could occur at diverse data sceneries, compiler version, or any other externality. Purpose: Weighted Quantiles or <> are quite difficult to find on must systems, also it's non-weighted approach are rarely used to estimate the location parameter of price distribution WICH IS NOT NORMAL, all this in favour of it's non-robust counterpart, the Arithmetic rolling Mean or <> and it's weighted variants like the WMA, VWAP, etc. Also, a big drawback from this is that must statistics derived from Normal-Distribution parameter location (the Mean) definitely will not fit for an efficient, nor robust estimation for price distributions, so their moments like the standard deviation, kurtosis, skewness, etc. will not be the better tools to build derived algorithms or technical indicators among price/volume. In an effort searching better statistical tools for price distributions, I found the excellent work of Andrey Akinshin that took me to port some of their Math research contributions for the compute benchmarking field , and bring it here at the TradingView ecosystem to take a shot at the price distribution crazy fields. For a better detail of what the weighted Harrell-Davis Quantile Estimator can do, who better than drink directly from the source at References: References: Weighted Quantile Estimators. DoubleMAD outlier detector based on the Harrell-Davis quantile estimator. Unbiased median absolute deviation based on the Harrell-Davis quantile estimator. Quantile confidence intervals for weighted samples. Licensing: This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International Copyright (c) 2021 (CC BY-NC-SA 4.0) Copyright's & Mentions: The Gamma Functions & Beta Probability Density Functions C# implementations by the Math.NET Numerics, part of the Math.NET Project. The Regularized Incomplete (Left) Beta Function C# implementation by the SAMTools, htslib project. The Weighted Harrell-Davis Quantile estimator ; C# & R implementations by Andrey Akinshin. External PineScript code, methods, support & consultancy by @PineCoders staff with special mention for: + "ma sorter ('sort by array' example)- JD" by @Duyck. + Porting, mods, compilation and debugging for this script by @XeL_Arjona for the TradingView's @PineCoders community.
Pine Script®指標
由xel_arjona提供
40
Torben Median Evolved OscillatorExtending the Works of Torben Mogensen, on Torben Median Median Filtering is an important technique ! The median filter is a non-linear digital filtering technique, often used to remove noise from an image or signal. Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image). Median filtering is very widely used in digital image processing because, under certain conditions, it preserves edges while removing noise (but see the discussion below), also having applications in signal processing. Have taken two T-Medians #1 of Length 13 #2 of Length 55 The Indicator plots the Relationship projection of Medians with the Closing Price as an Area Chart Provision for Alerts You get > Green T-Median Alert > Red T-Median Alert Enjoy!
Pine Script®指標
由Ankit_1618提供
5
Torben Moving MedianThis method was pointed it out by Torben Mogensen. It is certainly not the fastest way of finding a median, but it has the very interesting property that it does not modify the input array when looking for the median. It becomes extremely powerful when the number of elements to consider starts to be large, and copying the input array may cause enormous overheads. For read-only input sets of several hundred megabytes in size, it is the solution of choice, also because it accesses elements sequentially and not randomly. Beware that it needs to read the array several times though: a first pass is only looking for min and max values, further passes go through the array and come out with the median in little more time. The number of iterations is probably O(log(n)), although I have no demonstration of that fact. What is Median Filtering Median filtering is a commonly used technique in signal processing. Typically used on signals that may contain outliers skewing the usual statistical estimators, it is usually considered too expensive to be implemented in real-time or CPU-intensive applications. Let us define the median of N numerical values by: The median of a list of N values is found by sorting the input array in increasing order, and taking the middle value. The median of a list of N values has the property that in the list there are as many greater as smaller values than this element. How To trade Trading is quite intuitive Buy when the Price breaks-out the price which breaked the Torben Moving Median
Pine Script®指標
由Ankit_1618提供
Percentile Nearest Rank Using Arrays [LuxAlgo]The new array feature is extremely powerful, as it will allow pinescript users to do more complex things, or compute existing calculations more efficiently, it will also be possible to shine some light to some already existing functions, one of them being percentile_nearest_rank . We have been working on this new feature with our pal alexgrover, and made this script which computes a rolling percentile using the nearest rank method. Settings Length: Window of the rolling percentile, determine the number of past data to be used. Percentage: Return the current value if Percentage % of the data fall below that value, the setting is in a range (0,100). Src: Input source of the indicator. Usage A rolling percentile can have many usages when it comes to technical analysis, this is due to its ability to return the value of three common rolling statistics, the rolling median, which can be obtained using a percentage equal to 50, the rolling maximum, obtained with a percentage equal to 100, and the rolling minimum, obtained with a percentage equal to 0. When we use our rolling percentile as a rolling median, we can obtain a robust estimation of the underlying trend in the price, while using it as a rolling maximum/minimum can allow us to determine if the market is trending, and at which direction. The rolling maximum/minimum is a rolling statistic used to calculate the well known stochastic oscillator and Donchian channel indicator. We can also compute rolling quartiles, which can be obtained using a percentage of 25 or 75, with one of 25 returning the lower quartile and 75 the upper quartile. In blue the upper rolling quartile (%75), in orange the lower rolling quartile (%25), both using a window size of 100. Details In order to compute a rolling percentile nearest rank, we must first take the most recent length closing prices, then order them in ascending order, we then return the value of the ordered observations at index (percentage/100*length) - 1 (we use - 1 because our array index starts at 0).
Pine Script®指標
由LuxAlgo提供
13
Spread by//Every spread & central tendency measure in 1 script with comfortable visualization, including scrips's status line. Spread measures: - Standard deviation (for most cases); - Average deviation (if there are extreme values); - GstDev - Geometric Standard Deviation (exclusively for Geometric Mean); - HstDev - Harmonic Deviation (exclusively for Harmonic Mean). These modified functions will calculate everything right, they will take source, length, AND basis of your choice, unlike the ones from TW. Central tendency measures: - Mean (if everything's cool & equal); - Median (values clustering towards low/high part of the rolling window); - Trimean (3/more distinguishable clusters of data); - Midhinhe (2 distinguishable clusters of data); - Geometric Mean ( |low.. ... ... .. .... ... . . . . . . . . . . . .high| this kinda data); <- Exp law - Harmonic Mean { |low. . . . . . . . . . . . . . .. . . .high| kinda data). <- Reciprocal law Listen: 1) Don't hesitate using Standard Deviation with non-mean, like "Midhinge Standard Devition", despite what ol' stats gurus gonna say, it works when it's appropriate; 2) Don't check log space while using Geometric Mean & Geometric Standard Deviation, these 2 implement log stuff by design, I mean unless u wanna make it double xd 3) You can use this script, modify it how you want, ask me questions whatever, just make money using it; 4) Use Midrange & Midpoints in tandem when data follows ~addition law (like this . . . . . . . . . . . . . . . . . . . . .). <- just addition law Look at the data, choose spread measure first, then choose central tendency measure, not vice versa. !!! Ain't gonna place ® sign on standard deviations like one B guy did in 1980s lmao, but if your wanna use Harmonic Deviations in science/write about/cite it/whatever, pls give me a lil credit at least, I've never seen it anywhere and unfortunately had to develop it by myself. it's useful when your data develops by reciprocals law (opposite to exponential). Peace TW
Pine Script®指標
由gorx1提供
19
Range identifier by medianThis study tries to highlight ranges as they are defined by TradingLatino TradingView user. The study uses median values. A range is defined as periods when the price does not move a lot. Its default values are aimed at BTCUSDT pair and 4h timeframe. HOW IT WORKS For each of the bars a '5' median is calculated based on the 'highest of open and close' For each of the bars a '5' median is calculated based on the 'lowest of open and close' Thanks to the desviation setting both medians have a tolerated maximum and a minimum Condition 1: The bar current 'highest of open and close' needs to be between the respective tolerated maximum and minimum Condition 2: The bar current 'lowest of open and close' needs to be between the respective tolerated maximum and minimum If both conditions are met then the bar is in a range SETTINGS Price range periods : How many previous periods are used to calculate the medians Price range maximum desviation (%) ( > 0 ): Maximum positive desviation for range detection Price range minimum desviation (%) ( > 0 ): Mininum negative desviation for range detection Desviations should be both of them a positive number WARNING Despite the name indicator does not identify the entire range. It identifies when you realise you are inside a range. E.g. If a range length is 8 periods length this range indicator will highlight only the last 6 periods of the range. USAGE If your strategy signals you an upwards trend then you might use this range detector to know when to exit your long position Why? Because most of the times the price is found to be in a range it goes down FEEDBACK 1 My former attempt on calculating ranges felt too much over complex that is why I decided to implement it with medians. It should be easier to modify if I want to desviation inputs to be calculated automatically in the future. I'm interested on different approaches on how to detect ranges. FEEDBACK 2 I have only used this identifier in BTCUSDT 4h timeframe. Feel free to comment down below with your suggested settings for your favourite pair and timeframe PINE SCRIPT TRICK This script simulates looping an string char by char in pine script.
Pine Script®指標
由ruckard提供
Rolling summaryStatistical methods based on mean cannot be effective all the time when attributed to financial data since it doesn't usually follow normal distribution, the data can be skewed or/and have extreme values which can be described as outliers. In order to deal with this problem it is appropriate to use median-based techniques. The most common one is called five-number summary/box plot, which plots median of the dataset, 25th (Q1) & 75th (Q3) percentiles (the medians of lower & upper parts of the original dataset divided by the original median), and whiskers calculated by taking range between Q1 and Q3, multiplying it by 1.5 and adding it to Q3 and subtracting it from Q1. The values which are outside the whiskers are considered outliers. Default settings of the script correspond to the classic box plot. Seven-number summary can be also plotted by this script, by turning on 4 additional percentiles/Bowley’s seven-figure summary by turning on first 2 additional percentiles and changing their values to 10 and 90 respectively. P.S.: Mean can be also turned in just to check the difference.
Pine Script®指標
由gorx1提供
11
Recursive Median Oscillator & Fisher Transforms RibbonThis is a composite indicator made up of: - modifided (rescaled) version of evergets version of recursive median oscillator. - 1996anoojpatels Futur modification of Ehlers Fisher Transform Ribbons Indicator I think Ehlers attempts to minimise latency in indicators are extremely valuable and some of my most use trading tools. Thanks to all the authors whose iterations keep moving these indicators toward perfection. Here is my contribution.
Pine Script®指標
由irenabyss提供
MCI and VCI - Modified CCI FormulasFor private peeps only - Takes a modified version of the CCI formula into 2 parts VCI - Volume Channel Index (Yellow Histogram) - Measures accurate accumulation and distribution levels and times MCI - Modified Channel Index - Measures (when compared to VCI) levels where clearly buys are interested vs not interested. Example: If VCI > MCI - Shows buyer's are more than interested in buying, you've either hit a bottom or heavy resistance if MCI > VCI - Show's buyer's aren't interested and will most likely result in a dump/lower price Great for monitoring accumulation and distribution, these auto buy and sells look for the transition points over 0, works on EVERY commodity/stock/FOREX/Crypto Results are from trading 1 BTC x25 leveraging. Not all trades will get in if put in at limit, but it does survive with profits after the massive 0.075 fee (results shown are after fees)
Pine Script®策略
由ericisom887提供
2