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loxxmas - moving averages used in Loxx's indis & stratsLibrary "loxxmas" TODO:loxx moving averages used in indicators kama(src, len, kamafastend, kamaslowend)   KAMA Kaufman adaptive moving average   Parameters:      src : float      len : int      kamafastend : int      kamaslowend : int   Returns: array ama(src, len, fl, sl)   AMA, adaptive moving average   Parameters:      src : float      len : int      fl : int      sl : int   Returns: array t3(src, len)   T3 moving average, adaptive moving average   Parameters:      src : float      len : int   Returns: array adxvma(src, len)   ADXvma - Average Directional Volatility Moving Average   Parameters:      src : float      len : int   Returns: array ahrma(src, len)   Ahrens Moving Average   Parameters:      src : float      len : int   Returns: array alxma(src, len)   Alexander Moving Average - ALXMA   Parameters:      src : float      len : int   Returns: array dema(src, len)   Double Exponential Moving Average - DEMA   Parameters:      src : float      len : int   Returns: array dsema(src, len)   Double Smoothed Exponential Moving Average - DSEMA   Parameters:      src : float      len : int   Returns: array ema(src, len)   Exponential Moving Average - EMA   Parameters:      src : float      len : int   Returns: array fema(src, len)   Fast Exponential Moving Average - FEMA   Parameters:      src : float      len : int   Returns: array hma(src, len)   Hull moving averge   Parameters:      src : float      len : int   Returns: array ie2(src, len)   Early T3 by Tim Tilson   Parameters:      src : float      len : int   Returns: array frama(src, len, FC, SC)   Fractal Adaptive Moving Average - FRAMA   Parameters:      src : float      len : int      FC : int      SC : int   Returns: array instant(src, float)   Instantaneous Trendline   Parameters:      src : float      float : alpha   Returns: array ilrs(src, int)   Integral of Linear Regression Slope - ILRS   Parameters:      src : float      int : len   Returns: array laguerre(src, float)   Laguerre Filter   Parameters:      src : float      float : alpha   Returns: array leader(src, int)   Leader Exponential Moving Average   Parameters:      src : float      int : len   Returns: array lsma(src, int, int)   Linear Regression Value - LSMA (Least Squares Moving Average)   Parameters:      src : float      int : len      int : offset   Returns: array lwma(src, int)   Linear Weighted Moving Average - LWMA   Parameters:      src : float      int : len   Returns: array mcginley(src, int)   McGinley Dynamic   Parameters:      src : float      int : len   Returns: array mcNicholl(src, int)   McNicholl EMA   Parameters:      src : float      int : len   Returns: array nonlagma(src, int)   Non-lag moving average   Parameters:      src : float      int : len   Returns: array pwma(src, int, float)   Parabolic Weighted Moving Average   Parameters:      src : float      int : len      float : pwr   Returns: array rmta(src, int)   Recursive Moving Trendline   Parameters:      src : float      int : len   Returns: array decycler(src, int)   Simple decycler - SDEC   Parameters:      src : float      int : len   Returns: array sma(src, int)   Simple Moving Average   Parameters:      src : float      int : len   Returns: array swma(src, int)   Sine Weighted Moving Average   Parameters:      src : float      int : len   Returns: array slwma(src, int)   linear weighted moving average   Parameters:      src : float      int : len   Returns: array smma(src, int)   Smoothed Moving Average - SMMA   Parameters:      src : float      int : len   Returns: array super(src, int)   Ehlers super smoother   Parameters:      src : float      int : len   Returns: array smoother(src, int)   Smoother filter   Parameters:      src : float      int : len   Returns: array tma(src, int)   Triangular moving average - TMA   Parameters:      src : float      int : len   Returns: array tema(src, int)   Tripple exponential moving average - TEMA   Parameters:      src : float      int : len   Returns: array vwema(src, int)   Volume weighted ema - VEMA   Parameters:      src : float      int : len   Returns: array vwma(src, int)   Volume weighted moving average - VWMA   Parameters:      src : float      int : len   Returns: array zlagdema(src, int)   Zero-lag dema   Parameters:      src : float      int : len   Returns: array zlagma(src, int)   Zero-lag moving average   Parameters:      src : float      int : len   Returns: array zlagtema(src, int)   Zero-lag tema   Parameters:      src : float      int : len   Returns: array threepolebuttfilt(src, int)   Three-pole Ehlers Butterworth   Parameters:      src : float      int : len   Returns: array threepolesss(src, int)   Three-pole Ehlers smoother   Parameters:      src : float      int : len   Returns: array twopolebutter(src, int)   Two-pole Ehlers Butterworth   Parameters:      src : float      int : len   Returns: array twopoless(src, int)   Two-pole Ehlers smoother   Parameters:      src : float      int : len   Returns: array
Libreria Pine Script®
di loxx
4
JCFBaux Volatility [Loxx]JCFBaux is a volatility indicator that is used to detect early volatility spikes. To be used in conjunction with other momentum indicators for confluence. A Jurik-filtered signal line is included to provide a cutoff for when volatility is low. The JCFBaux is also used to calculate Jurik's "Composite Fractal Behavior". This is a directionless indicator. Many advanced traders will use JCFBaux as a drop in replacement for ADX DI. What is Jurik Volty used in the Juirk Filter? One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive. What is the Jurik Moving Average? Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines. Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
Indicatore Pine Script®
di loxx
13
Adaptive Qualitative Quantitative Estimation (QQE) [Loxx]Adaptive QQE is a fixed and cycle adaptive version of the popular Qualitative Quantitative Estimation (QQE) used by forex traders. This indicator includes varoius types of RSI caculations and adaptive cycle measurements to find tune your signal. Qualitative Quantitative Estimation (QQE): The Qualitative Quantitative Estimation (QQE) indicator works like a smoother version of the popular Relative Strength Index (RSI) indicator. QQE expands on RSI by adding two volatility based trailing stop lines. These trailing stop lines are composed of a fast and a slow moving Average True Range (ATR). There are many indicators for many purposes. Some of them are complex and some are comparatively easy to handle. The QQE indicator is a really useful analytical tool and one of the most accurate indicators. It offers numerous strategies for using the buy and sell signals. Essentially, it can help detect trend reversal and enter the trade at the most optimal positions. Wilders' RSI: The Relative Strength Index ( RSI ) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements. Essentially RSI , when graphed, provides a visual mean to monitor both the current, as well as historical, strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period creating a reliable metric of price and momentum changes. Given the popularity of cash settled instruments (stock indexes) and leveraged financial products (the entire field of derivatives); RSI has proven to be a viable indicator of price movements. RSX RSI: RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurk RSX retains all the useful features of RSI , but with one important exception: the noise is gone with no added lag. Rapid RSI: Rapid RSI Indicator, from Ian Copsey's article in the October 2006 issue of Stocks & Commodities magazine. RapidRSI resembles Wilder's RSI , but uses a SMA instead of a WilderMA for internal smoothing of price change accumulators. VHF Adaptive Cycle: Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length. Band-pass Adaptive Cycle: Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode. There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility. We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal ; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month. When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth. Included: -Toggle on/off bar coloring -Customize RSI signal using fixed, VHF Adaptive, and Band-pass Adaptive calculations -Choose from three different RSI types Visuals: -Red/Green line is the moving average of RSI -Thin white line is the fast trend -Dotted yellow line is the slow trend Happy trading!
Indicatore Pine Script®
di loxx
4
Aroon Oscillator of Adaptive RSI [Loxx]Aroon Oscillator of Adaptive RSI uses RSI to calculate AROON in attempt to capture more trend and momentum quicker than Aroon or RSI alone. Aroon Oscillator of Adaptive RSI has three different types of RSI calculations and the choice of either fixed, VHF Adaptive, or Band-pass Adaptive cycle measures to calculate RSI. Arron Oscillator: The Aroon Oscillator was developed by Tushar Chande in 1995 as part of the Aroon Indicator system. Chande’s intention for the system was to highlight short-term trend changes. The name Aroon is derived from the Sanskrit language and roughly translates to “dawn’s early light.” The Aroon Oscillator is a trend-following indicator that uses aspects of the Aroon Indicator (Aroon Up and Aroon Down) to gauge the strength of a current trend and the likelihood that it will continue. Aroon oscillator readings above zero indicate that an uptrend is present, while readings below zero indicate that a downtrend is present. Traders watch for zero line crossovers to signal potential trend changes. They also watch for big moves, above 50 or below -50 to signal strong price moves. Wilders' RSI: The Relative Strength Index (RSI) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements. Essentially RSI, when graphed, provides a visual mean to monitor both the current, as well as historical, strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period creating a reliable metric of price and momentum changes. Given the popularity of cash settled instruments (stock indexes) and leveraged financial products (the entire field of derivatives); RSI has proven to be a viable indicator of price movements. RSX RSI: RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurk RSX retains all the useful features of RSI, but with one important exception: the noise is gone with no added lag. Rapid RSI: Rapid RSI Indicator, from Ian Copsey's article in the October 2006 issue of Stocks & Commodities magazine. RapidRSI resembles Wilder's RSI, but uses a SMA instead of a WilderMA for internal smoothing of price change accumulators. VHF Adaptive Cycle: Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length. Band-pass Adaptive Cycle Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode. There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility. We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal ; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month. When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth. Included: -Toggle on/off bar coloring -Customize RSI signal using fixed, VHF Adaptive, and Band-pass Adaptive calculations -Choose from three different RSI types Happy trading!
Indicatore Pine Script®
di loxx
Adaptive, Zero lag Schaff Trend Cycle [Loxx]TASC's March 2008 edition Traders' Tips includes an article by John ​Ehlers titled "Measuring Cycle Periods," and describes the use of bandpass filters to estimate the length, in bars, of the currently dominant price cycle. What are Dominant Cycles and Why should we use them? Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode. There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility. We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal ; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month. When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth. Indicator Features -Zero lag or Regular Schaff Trend Cycle calculation - Fixed or Band-pass Dominant Cycle for Schaff Trend Cycle MA period inputs -10 different moving average options for Zero lag calculations -Separate Band-pass Dominant Cycle calculations for both Schaff Trend Cycle and MA calculations - Slow-to-Fast Band-pass Dominant Cycle input to tweak the ratio of Schaff Trend Cycle MA input periods as they relate to each other
Indicatore Pine Script®
di loxx
5
Hybrid, Zero lag, Adaptive cycle MACD [Loxx]TASC's March 2008 edition Traders' Tips includes an article by John ​Ehlers titled "Measuring Cycle Periods," and describes the use of bandpass filters to estimate the length, in bars, of the currently dominant price cycle. What are Dominant Cycles and Why should we use them? Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode. There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility. We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month. When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth . Indicator Features -Zero lag or Regular MACD/signal calculation - Fixed or Band-pass Dominant Cycle for MACD and Signal MA period inputs -10 different moving average options for both MACD and Signal MA calculations -Separate Band-pass Dominant Cycle calculations for both MACD and Signal MA calculations - Slow-to-Fast Band-pass Dominant Cycle input to tweak the ratio of MACD MA input periods as they relate to each other
Indicatore Pine Script®
di loxx
3
TL WavesI created this indicator inspired by the miyuki waves indicator by eto_miyuki. In my indicator we have 17 types of moving averages which can be selected in the settings. It is a trend indicator, the base of the wave is a moving average and 4 Average True Range (ATR) Bands derived from the baseline are formed. There are also 3 moving averages in a guppy style, these 3 moving averages can also be configured. The moving average options are: SMA ---> Simple WMA ---> Weighted VWMA ---> Volume Weighted EMA ---> Exponential DEMA ---> Double EMA ALMA ---> Arnaud Legoux HMA ---> Hull MA SMMA ---> Smoothed LSMA ---> Least Squares KAMA ---> Kaufman Adaptive TEMA ---> Triple EMA ZLEMA ---> Zero Lag FRAMA ---> Fractal Adaptive VIDYA ---> Variable Index Dynamic Average JMA ---> Jurik Moving Average T3 ---> Tillson TRIMA ---> Triangular All settings are available for changing inputs.
Indicatore Pine Script®
di TL_ID
1
Support/Resistant Zone (Simple)The concepts of trading level support and resistance are undoubtedly two of the most highly discussed attributes of technical analysis. Support is a price level where a downtrend can be expected to pause due to a concentration of demand or buying interest. As the price of assets or securities drops, demand for the shares increases, thus forming the support line. Meanwhile, resistance zones arise due to selling interest when prices have increased. There are many ways to identify support and resistance zones. This indicator is a simple method to identify them. Support/Resistant zones will draw basing on the size of the wick for candles, which are Pivots High/Low before.
Indicatore Pine Script®
di TrendCrypto2022
11
CANDLE FILTER Todays scripts is based on my Pullback And Rally Candles with other meaningful candles such as Hammers and Dojis. You can choose which Candles to show on the cart and if you want to candles to appear above or below a moving average. If you follow my work, you may recognise some of these candles which I'm about to show you however these candles are 1) more refined and 2) has moving average filters. Ive included a D,6H,1H Candle in this script as on different timeframes - each swing low on average has a different amount of bars within the swing low / swing high so the DPB and RD will only work on the Daily //Pullback candle This candle is very powerful when used with simple Price Action such as Market Structure//Demand zones and support zones. (((((WORKS BEST IN UPTRENDS AND BOTTOM OF RANGES))))) Ive included a D,6H,1H Pullback Candle in this script as on different timeframes - each swing low on average has a different amount of bars within the swing low so the DPB will only work on the Daily //DAILY PULLBACK (Swing Traders) snapshot //4H PULLBACK (Swing Traders) snapshot - this signal will produce more signals due to the swing low filter on the 4H //1H PULLBACK snapshot - this signal has been refined due to too many candle displaying in weak areas !!!IF YOU DONT WANT TO USE PULLBACKS DURING DOWNTRENDS THEN USE THE EMA FILTER TO TURN OFF THE PULLBACKS WHEN PRICE IS BELOW THE MOVING AVERAGE!!! //Rally candle (My personal Favourite) (((((WORKS BEST IN DOWNTRENDS AND TOP OF RANGES))))) This candle is very powerful when used with simple Price Action such as Market Structure//Supply zones and Resistance zones. //DAILY RALLY(Swing Traders) snapshot //4H RALLY(Swing Traders) snapshot - this signal will produce more signals due to the swing high filter on the 4H !!!IF YOU DONT WANT TO USE RALLIES DURING UPTRENDSTHEN USE THE EMA FILTER TO TURN OFF THE RALLIES WHEN PRICE IS ABOVE THE MOVING AVERAGE!!! //POWERFUL DOJIS (INDECISION) snapshot We look for indecision in key areas to see if momentum is shifting. When combined with Pullbacks or Rallys - this will enhance the odds of a probably area. //HAMMERS snapshot //MOVING AVERAGES snapshot Short EMA = 50 Long EMA = 200 This filter can be used when the market is trending - look out for rejections off the moving averages Also you can chance the Short And Long EMA to choose which MA cross you want to use snapshot ALSO ALL THE CANDLES HAVE A ALERT CONDITIONS WHICH YOU CAN ACCESS - THIS WILL ALERT ANY CANDLE YOU CHOOSE Please leave a like/comment on this post as this is much appreciated....
Indicatore Pine Script®
di LuxTradeVenture
13
AMASling - All Moving Average Sling ShotThis indicator modifies the SlingShot System by Chris Moody to allow it to be based on 'any' Fast and Slow moving average pair. Open Long / Close Long / Open Short / Close Short alerts can be generated for automated bot trading based on the SlingShot strategy: • Conservative Entry = Fast MA above Slow MA, and previous bar close below Fast MA, and current price above Fast MA • Conservative Entry = Fast MA below Slow MA, and previous bar close above Fast MA, and current price below Fast MA • Aggressive Entry = Fast MA above Slow MA, and price below Fast MA • Aggressive Exit = Fast MA below Slow MA, and price above Fast MA Entries and exits can also be made based on moving average crossovers, I initially put this in to make it easy to compare to a more standard strategy, but upon backtesting combining crossovers with the SlingShot appeared to produce better results on some charts. Alerts can also be filtered to allow long deals only when the fast moving average is above the slow moving average (uptrend) and short deals only when the fast moving average is below the slow moving averages (downtrend). If you have a strategy that can buy based on External Indicators you can use the 'Backtest Signal' which plots the values set in the 'Long / Short Signals' section. The Fast, Slow and Signal Moving Averages can be set to: • Simple Moving Average (SMA) • Exponential Moving Average (EMA) • Weighted Moving Average (WMA) • Volume-Weighted Moving Average (VWMA) • Hull Moving Average (HMA) • Exponentially Weighted Moving Average (RMA) (SMMA) • Linear regression curve Moving Average (LSMA) • Double EMA (DEMA) • Double SMA (DSMA) • Double WMA (DWMA) • Double RMA (DRMA) • Triple EMA (TEMA) • Triple SMA (TSMA) • Triple WMA (TWMA) • Triple RMA (TRMA) • Symmetrically Weighted Moving Average (SWMA) ** length does not apply ** • Arnaud Legoux Moving Average (ALMA) • Variable Index Dynamic Average (VIDYA) • Fractal Adaptive Moving Average (FRAMA) 'Backtest Signal' and 'Deal State' are plotted to display.none, so change the Style Settings for the chart if you need to see them for testing. Yes I did choose the name because 'It's Amasling!'
Indicatore Pine Script®
di EltAlt
1
Rally HTF Candle (Candlestick Analysis) Guaranteed WinnersRally Candle will signal when price is at the end of a Rally to the upside and thus entering a balance phase in the market (works on all markets) This candle works very efficient when the market is either trending downwards or in range markets where price is at resistance. (i would avoid in uptrends but depends on the trader) Also we can expect this candle to form when price is overextended as the theory of this script is when there is a turning point in momentum - this candle will appear and we can look long from this signal. This candle will only work in Swing High areas and appear when below an moving average which can be changed in the settings. This candle will work only work pn the HTF as it provides very good rexpectancy whereas the LTF has a slightly less expectancy (i will be publishing an intraday Rally candle) This candle can be alerted to signal the Rally Candle when the bar is confirmed and not during. The way i trade this candle is 1) Candle signal must be in probably area to increase efficiency. 2) Enter on the second candle after candle IS CONFIRMED 3) Set stop loss below Rally Candle or use ATR value 4) Trade with the trend ie only Bearish price action 5) This candle can catch extreme points in the market ie this candle projected when ETH hit aths $4841 6) Trading with a confluence along with the Rally is better than solely trading this candle Please leave a comment. If we get to 100 likes i will publish the script.
Indicatore Pine Script®
di LuxTradeVenture
10
Pullback Candles (Candlestick Analysis) Guaranteed Winners!!!!Pullback Candle will signal when price is at the end of a pullback and entering a balance phase in the market (works on all markets) Also we can expect a Pullback Candle during flash crashes as the theory of this script is when there is a turning point in momentum - this candle will appear and we can look long from this signal. This candle will only work in Swing Low areas and appear when below an moving average which can be changed in the settings. This candle will work on all timeframes - HTF provided very good rexpectancy whereas the LTF has a slightly less expectancy. This candle can be alerted to signal the Pullback Candle when the bar is confirmed and not during. The way i trade this candle is 1) Candle signal must be in probably area to increase efficiency. 2) Enter on the second candle after candle IS CONFIRMED 3) Set stop loss below Pullback Candle or use ATR value 4) Trade with the trend ie only bullish price action 5) This candle can catch falling knifes - we had one on LUNA before the rally to $7.50 6) Trading with a confluence along with the Pullback is better than solely trading this candle Please leave a comment. If we get to 100 likes i will publish the script. Have a good weekend :)
Indicatore Pine Script®
di LuxTradeVenture
40
Any RibbonThis indicator displays a ribbon of two individually configured Fast and Slow and Moving Averages for a fixed time frame. It also displays the last close price of the configured time frame, colored green when above the band, red below and blue when interacting. A label shows the percentage distance of the current price from the band, (again red below, green above, blue interacting), when the price is within the band it will show the percentage distance from median of the band. The Fast and Slow Moving Averages can be set to: Simple Moving Average (SMA) Exponential Moving Average (EMA) Weighted Moving Average (WMA) Volume-Weighted Moving Average (VWMA) Hull Moving Average (HMA) Exponentially Weighted Moving Average (RMA) (SMMA) Linear regression curve Moving Average (LSMA) Double EMA (DEMA) Double SMA (DSMA) Double WMA (DWMA) Double RMA (DRMA) Triple EMA (TEMA) Triple SMA (TSMA) Triple WMA (TWMA) Triple RMA (TRMA) Symmetrically Weighted Moving Average (SWMA) ** length does not apply ** Arnaud Legoux Moving Average (ALMA) Variable Index Dynamic Average (VIDYA) Fractal Adaptive Moving Average (FRAMA) I wrote this script after identifying some interesting moving average bands with my AMACD indicator and wanting to see them on the price chart. As an example look at the interactions between ETHBUSD 4hr and the band of VIDYA 32 Open and VIDYA 39 Open. Or start from the good old BTC Bull market support band, Weekly EMA 21 and SMA 20 and see if you can get a better fit. I find the Double RMA 22 a better fast option than the standard EMA 21.
Indicatore Pine Script®
di EltAlt
Rally Candle (End Game ) 26/04/2022 Few Months ago I started wanted to code a candle which alerts me when a Rally may be over in Bearish Conditions and today I have created a candle which is 1. subjective but more importantly appears in areas where buying pressure is at either a climax or in the process of a decline and this is where the Rally Candle signals. This shows momentum may be shifting and these can provide some good entries. They will only working when price is below the 200ema and in overextended markets - VERY IMPORTANT!!! Works on all timeframe with HTF providing more price percentage than LTF They aren’t a specific candle size however they will repaint when we see 4 higher close candles followed by a candle which has closed lower than the previous 4th. //Candle Conditions This candle has to be in a swing high area to be valid and on 1H and 6H but the 1H will repaint a lot of candles so when we have a point system of +20 we can assume this setup is a good setup. //Candle Operators You can change the color of the bar to your liking There is a ema filter so if you want to candle to not show candles of the 50ema this operator will do the command. Please post requests and any potential implementations I could port to pine script. Hope you Enjoy :)
Indicatore Pine Script®
di LuxTradeVenture
2
AMACD - All Moving Average Convergence DivergenceThis indicator displays the Moving Average Convergane and Divergence ( MACD ) of individually configured Fast, Slow and Signal Moving Averages. Buy and sell alerts can be set based on moving average crossovers, consecutive convergence/divergence of the moving averages, and directional changes in the histogram moving averages. The Fast, Slow and Signal Moving Averages can be set to: Exponential Moving Average ( EMA ) Volume-Weighted Moving Average ( VWMA ) Simple Moving Average ( SMA ) Weighted Moving Average ( WMA ) Hull Moving Average ( HMA ) Exponentially Weighted Moving Average (RMA) ( SMMA ) Symmetrically Weighted Moving Average ( SWMA ) Arnaud Legoux Moving Average ( ALMA ) Double EMA ( DEMA ) Double SMA (DSMA) Double WMA (DWMA) Double RMA ( DRMA ) Triple EMA ( TEMA ) Triple SMA (TSMA) Triple WMA (TWMA) Triple RMA (TRMA) Linear regression curve Moving Average ( LSMA ) Variable Index Dynamic Average ( VIDYA ) Fractal Adaptive Moving Average ( FRAMA ) If you have a strategy that can buy based on External Indicators use 'Backtest Signal' which returns a 1 for a Buy and a 2 for a sell. 'Backtest Signal' is plotted to display.none, so change the Style Settings for the chart if you need to see it for testing.
Indicatore Pine Script®
di EltAlt
2
Adaptive Average Vortex Index [lastguru]As a longtime fan of ADX, looking at Vortex Indicator I often wondered, where is the third line. I have rarely seen that anybody is calculating it. So, here it is: Average Vortex Index - an ADX calculated from Vortex Indicator. I interpret it similarly to the ADX indicator: higher values show stronger trend. If you discover other interpretation or have suggestions, comments are welcome. Both VI+ and VI- lines are also drawn. As I use adaptive length calculation in my other scripts (based on the libraries I've developed and published), I have also included the possibility to have an adaptive length here, so if you hate the idea of calculating ADX from VI, you can disable that line and just look at the adaptive Vortex Indicator. Note that as with all my oscillators, all the lines here are renormalized to -1..1 range unlike the original Vortex Indicator computation. To do that for VI+ and VI- lines, I subtract 1 from their values. It does not change the shape or the amplitude of the lines. Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly). VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow) VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast) Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA Fractal Adaptation - based on FRAMA by John F. Ehlers MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong). The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers . I do not know, which combination works best, so you can experiment. If no Adaptation is selected ( None option), you can set Length directly. If an Adaptation is selected, then Cycle multiplier can be set. The oscillator also has the option to configure the internal smoothing function with Window setting. By default, RMA is used (like in ADX calculation). Fast Default option is using half the length for smoothing. Triangle , Hamming and Hann Window algorithms are some better smoothers suggested by John F. Ehlers. After the oscillator a Moving Average can be applied. The following Moving Averages are included: SMA , RMA, EMA , HMA , VWMA , 2-pole Super Smoother, 3-pole Super Smoother, Filt11, Triangle Window, Hamming Window, Hann Window, Lowpass, DSSS. Postfilter options are applied last: Stochastic - Stochastic Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic ) by John F. Ehlers Inverse Fisher Transform - Inverse Fisher Transform Noise Elimination Technology - a simplified Kendall correlation algorithm "Noise Elimination Technology" by John F. Ehlers Momentum - momentum (derivative) Except for Inverse Fisher Transform , all Postfilter algorithms can have Length parameter. If it is not specified (set to 0), then the calculated Slow MA Length is used. If Filter/MA Length is less than 2 or Postfilter Length is less than 1, they are calculated as a multiplier of the calculated oscillator length. More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
Indicatore Pine Script®
di lastguru
5
Adaptive MA constructor [lastguru]Adaptive Moving Averages are nothing new, however most of them use EMA as their MA of choice once the preferred smoothing length is determined. I have decided to make an experiment and separate length generation from smoothing, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. This indicator is based on my previously published public libraries and also serve as a usage demonstration for them. I will try to expand the collection (suggestions are welcome), however it is not meant as an encyclopaedic resource, so you are encouraged to experiment yourself: by looking on the source code of this indicator, I am sure you will see how trivial it is to use the provided libraries and expand them with your own ideas and combinations. I give no recommendation on what settings to use, but if you find some useful setting, combination or application ideas (or bugs in my code), I would be happy to read about them in the comments section. The indicator works in three stages: Prefiltering, Length Adaptation and Moving Averages. Prefiltering is a fast smoothing to get rid of high-frequency (2, 3 or 4 bar) noise. Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly). Chande (Price) - based on Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length Chande (Volume) - a variant of Chande's algorithm, where volume is used instead of price VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow) VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast) Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA Deviation Scaling - based on DSSS by John F. Ehlers Median Average - based on Median Average Adaptive Filter by John F. Ehlers Fractal Adaptation - based on FRAMA by John F. Ehlers MESA MAMA Alpha - based on MESA Adaptive Moving Average by John F. Ehlers MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers, but unlike Alpha calculation, this adaptation estimates cycle period Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong). The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers. I do not know, which combination works best, so you can experiment. Chande's Adaptations also have 3 additional parameters: SD Length (lookback length of Standard deviation), Smooth (smoothing length of Standard deviation) and Power (exponent of the length adaptation - lower is smaller variation). These are internal tweaks for the calculation. Length Adaptaton section offer you a choice of Moving Average algorithms. Most of the Adaptations are originally used with EMA, so this is a good starting point for exploration. SMA - Simple Moving Average RMA - Running Moving Average EMA - Exponential Moving Average HMA - Hull Moving Average VWMA - Volume Weighted Moving Average 2-pole Super Smoother - 2-pole Super Smoother by John F. Ehlers 3-pole Super Smoother - 3-pole Super Smoother by John F. Ehlers Filt11 -a variant of 2-pole Super Smoother with error averaging for zero-lag response by John F. Ehlers Triangle Window - Triangle Window Filter by John F. Ehlers Hamming Window - Hamming Window Filter by John F. Ehlers Hann Window - Hann Window Filter by John F. Ehlers Lowpass - removes cyclic components shorter than length (Price - Highpass) DSSS - Derivation Scaled Super Smoother by John F. Ehlers There are two Moving Averages that are drown on the chart, so length for both needs to be selected. If no Adaptation is selected ( None option), you can set Fast Length and Slow Length directly. If an Adaptation is selected, then Cycle multiplier can be selected for Fast and Slow MA. More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
Indicatore Pine Script®
di lastguru
9
MovingAveragesLibraryLibrary "MovingAveragesLibrary" This is a library allowing one to select between many different Moving Average formulas to smooth out any float variable. You can use this library to apply a Moving Average function to any series of data as long as your source is a float. The default application would be for applying Moving Averages onto your chart. However, the scope of this library is beyond that. Any indicator or strategy you are building can benefit from this library. You can apply different types of smoothing and moving average functions to your indicators, momentum oscillators, average true range calculations, support and resistance zones, envelope bands, channels, and anything you can think of to attempt to smooth out noise while finding a delicate balance against lag. If you are developing an indicator, you can use the 'ave_func' to allow your users to select any Moving Average for any function or variable by creating an input string with the following structure: var_name = input.string(, , ) Where the types of Moving Average you would like to be provided would be included in options. Example: i_ma_type = input.string(title = "Moving Average Type", defval = "Hull Moving Average", options = ) Where you would add after options the strings I have included for you at the top of the PineScript for your convenience. Then for the output you desire, simply call 'ave_func' like so: ma = ave_func(source, length, i_ma_type) Now the plotted Moving Average will be the same as what you or your users select from the Input. ema(src, len) Exponential Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. sma(src, len) Simple Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. rma(src, len) Relative Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. wma(src, len) Weighted Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. dv2(len) Donchian V2 function.   Parameters:      len : Lookback length to use.   Returns: Open + Close / 2 for the selected length. ModFilt(src, len) Modular Filter smoothing function.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: Float value. EDSMA(src, len) Ehlers Dynamic Smoothed Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: EDSMA smoothing. dema(x, t) Double Exponential Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: DEMA smoothing. tema(src, len) Triple Exponential Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: TEMA smoothing. smma(x, t) Smoothed Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: SMMA smoothing. vwma(x, t) Volume Weighted Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: VWMA smoothing. hullma(x, t) Hull Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: Hull smoothing. covwma(x, t) Coefficient of Variation Weighted Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: COVWMA smoothing. frama(x, t) Fractal Reactive Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: FRAMA smoothing. kama(x, t) Kaufman's Adaptive Moving Average.   Parameters:      x : Series to use ('close' is used if no argument is supplied).      t : Lookback length to use.   Returns: KAMA smoothing. donchian(len) Donchian Calculation.   Parameters:      len : Lookback length to use.   Returns: Average of the highest price and the lowest price for the specified look-back period. tma(src, len) Triangular Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: TMA smoothing. VAMA(src, len) Volatility Adjusted Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: VAMA smoothing. Jurik(src, len) Jurik Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: JMA smoothing. MCG(src, len) McGinley smoothing.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: McGinley smoothing. zlema(series, length) Zero Lag Exponential Moving Average.   Parameters:      series : Series to use ('close' is used if no argument is supplied).      length : Lookback length to use.   Returns: ZLEMA smoothing. xema(src, len) Optimized Exponential Moving Average.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      len : Lookback length to use.   Returns: XEMA smoothing. EhlersSuperSmoother(src, lower) Ehlers Super Smoother.   Parameters:      src : Series to use ('close' is used if no argument is supplied).      lower : Smoothing value to use.   Returns: Ehlers Super smoothing. EhlersEmaSmoother(sig, smoothK, smoothP) Ehlers EMA Smoother.   Parameters:      sig : Series to use ('close' is used if no argument is supplied).      smoothK : Lookback length to use.      smoothP : Smothing value to use.   Returns: Ehlers EMA smoothing. ave_func(in_src, in_len, in_type) Returns the source after running it through a Moving Average function.   Parameters:      in_src : Series to use ('close' is used if no argument is supplied).      in_len : Lookback period to be used for the Moving Average function.      in_type : Type of Moving Average function to use. Must have a string input to select the options from that MUST match the type-casing in the function below.   Returns: The source as a float after running it through the Moving Average function.
Libreria Pine Script®
di CrackingCryptocurrency
7
Renko Candles OverlayHello All, For long time I got many request for Renko Candles and now here it's, Renko Candles Overlay . I tried to make almost everything optional, so you can play with the options as you want. Let see the options: Method: the option for brick scaling method: ATR, ATR/2, ATR/4, Percent, Traditional - ATR Period: period for Average True Range and it's valid if the method is ATR - ATR/2 Period: period for Average True Range and it's valid if the method is ATR/2 - ATR/4 Period: period for Average True Range and it's valid if the method is ATR/4 - Traditional: User-defined brick size, it's valid if the method is Traditional - Percent: Percent of Close price, it's valid if the method is Percent if the method is not Traditional (fixed brick size) then Brick size is calculated/updated when new bricks added. so The box sizes may be different because of the calculation is dynamic. Levels & Lines for new Bricks: if you enable this option then the script shows the levels for new brick Change Bar Color: optionally the script changes the bar color by using direction of the bricks and some other options for coloring. The script shows the bricks for visible area, which is approximately 280 candles. so if you change the width and number of the bricks then number of bricks that is shown is adjusted automatically to fit the screen. you can see the examples below: The script shows the levels to new brick as a line and label: Because of real-time bar is not confirmed until the candle close, the script shows the bricks as Unconfirmed , and unconfirmed bricks shown in different color: You can change the width of the bricks (width is 10 in following example): Optionally candle colors are changde by the direction of the bricks: If you have any recommendation then please drop a comment under the script ;) Enjoy!
Indicatore Pine Script®
di LonesomeTheBlue
137
ATR TREXTry to visualize TREX method. -4 types of candle based on TR : 1. Spinning ( Candle < 0.8*ATR ) 2. Standard ( 0.8*ATR < Candle < 1.2*ATR ) 3. Long bar ( 1.2*ATR < Candle < 2.5*ATR ) 4. Spike ( 2.5*ATR < Candle ) ATR length is different base on FRACTAL timeframes. you can now find what is type of candle as colored ATR. -Time frames : 1 Min 5 Min 15 Min 1 Hour 4 Hour 1 Day 1 Week 1 Month I am working on TREX method and this indicator will change and improve . (V1.0) Br Amin
Indicatore Pine Script®
di Aminhd
MTF Market Structure Highs and LowsThe indicator marks the last fractal highs and lows (W,D,4H and 1H options) to help determine current market structure. The script was created to help with directional bias but also as a MTF visual aid for stop hunts/liquidity raids. Liquidity areas are where we assume trader's stop losses would be when buying or selling. Liquidity lies above and below swing points and institutions need liquidity to fill large orders. Monitor price action as it hits these areas for a potential reversal trade.
Indicatore Pine Script®
di geneclash
50