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Moving Average CandlesInspired by Ricardo Santos's " Multiple Moving Average Candle System V0" () This script plots 6 moving averages using the plotcandle function rather than the normal plot function. Result is a stylish indicator that shows moving average crossovers in a more visual way. Moving average type options available are , or Simple, Exponential, Hull, Relative, Volume Weighted, and Arnaud Legoux Moving Averages, Linear Regression Curve, and Median. Lengths for each can be set in settings along with selection specific parameters. Good for plotting/visualizing potential entry/exit points based on your preferred moving averages crossing over, or just as some eye candy.
Penunjuk Pine Script®
oleh EsIstTurnt
T3 Velocity Candles [Loxx]T3 Velocity Candles is a candle coloring overlay that calculates its gradient coloring using T3 velocity. What is the T3 moving average? Better Moving Averages Tim Tillson November 1, 1998 Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years. Introduction "Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done." This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced. "Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator. Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus. We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes: It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values. It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits. The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade! Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how: Two Interesting Moving Averages We will examine two benchmark moving averages based on Linear Regression analysis. In both cases, a Linear Regression line of length n is fitted to price data. I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data. We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA . Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present. However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line. These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot. A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2. Filter Techniques Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag. There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by: L' = L(time series) + L(time series - L(time series)) That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to: 2L-L(L) This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994). In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator. We will use these two techniques to construct our better moving average, after we explore the first one a little more closely. Fixing Overshoot An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2. Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once. This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible. The solution to the overshoot problem is to recall what we are doing with twicing: DEMA (n) = EMA (n) + EMA (time series - EMA (n)) The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block: EMA (n) + EMA (time series - EMA (n))*.7; This is algebraically the same as: EMA (n)*1.7-EMA( EMA (n))*.7; I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is: GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v, Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data: T3(n) = GD ( GD ( GD (n))) In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Penunjuk Pine Script®
oleh loxx
[HA] Heikin-Ashi Shadow Candles// For overlaying Heikin Ashi candles over basic charts, or for use in it's own panel as an oscillator. // Enjoy the visual cues of HA candles, without giving up price action awareness. // Good for learning and comparison. // Aug 11 2022 Release Notes: * Bugfix: Candle color was based on classic direction not HA direction (did not update cover photo). // Aug 12 2022 Release Notes: * Implemented true oscillator mode. Provided as separate plot (styles tab) or mode switch option (Inputs tab). TV gets spazzy with "styles tab" "default hidden" plots, and will reset them if any variables are modified that affect them (i.e. wick color override). Mode switch should be sufficient for both users. // Aug 21 2022 Republished because of typo in indicator name prevented search.
Penunjuk Pine Script®
oleh JollyWizard
1
RSI Precision Trend Candles [Loxx]RSI Precision Trend Candles is a candle coloring indicator that uses an average range algorithm to determine trend direction. The precision trend algorithm can be used on any calculated output to tease out interesting trend information. What is RSI? The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The indicator was developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, New Concepts in Technical Trading Systems. Included Bar coloring Signals Alerts Loxx's Expanded Source Types
Penunjuk Pine Script®
oleh loxx
3
3 Candle EngulfingThree Line Strike Candlestick Pattern (3 candle Engulfing pattern) to help you detect sniper entry point mostly for (forex) You can use this as an indicator to detect an entry point for your trade. Please cross-check the Macro and Micro trend and don't go against the trend. Also use other indicators to confirm your entry. You can set the engulfing minimum pips value (Default is set to 10 pips) How it works: Yellow candle with an up green triangle means a long entry White candle with a down green triangle means a short entry
Penunjuk Pine Script®
oleh moamenmostafa
2
Previous Close To Current High Percentage Per CandleGet the percentage of previous candle price to current high candle price. This script will make your life easier to get percentage without you calculating it. Hope you enjoy the tool and let me know if there is any feedback or improvement request. Thank you very much. :D -------------------------------- Formula: Previous To High Percentage Per Candle = (high - previous / previous) * 100% --------------------------------
Penunjuk Pine Script®
oleh StevannusLake
2
Reversal Candlestick Pattern With Trend IndentifierThis script help to identified popular candlestick pattern combined with trend identifier. Most script only focus on criteria of the pattern. Such as how much the length of the body compared to previous candle etc. Besides criteria of the candle, this script also considered the trend into the logic. For example bullish engulfing is a bullish reversal signal, which is only valid in a down trend. To identified trend, I'm using RSI. Normally, RSI less than 50 is considered a down trend, and RSI greater than 50 is considered up trend. In this script, you can customize the criteria of how much RSI is up trend and down trend. Default value RSI >= 55 is up trend, RSI <= 45 is down trend. Your feedback and suggestion is welcome. Supported pattern: White Marubozu (wm) Black Marubozu (bm) Hammer (h) Hanging Man (hm) Inverted Hammer (ih) Shooting Star (ss) Bullish Engulfing (e) Bearish Engulfing (e) Tweezer Bottom (tb) Tweezer Top (tt) Three White Soldiers (tws) Three Black Crows (tbc) Morning Star (ms) Evening Star (es) Three Inside Up (tiu) Three Inside Down (tid) Reference: babypips.com
Penunjuk Pine Script®
oleh flintlockwood
8
Rate of Change Candle Standardized (ROCCS)ROCCS is a standardized rate of change oscillator with "error bars". Rate of change helps traders gauge momentum in a market by comparing the current price with the price "n" periods ago. What makes this special is you get to see the momentum of the momentum via the candle view. The candle transformation utilizes a moving average to smooth the signal however this is only used for the close price. The high and low prices are not smoothed. The moving average has an adjustable period, and so does the standardization. I hope you can find great use in this upgraded roc indicator.
Penunjuk Pine Script®
oleh The_Peaceful_Lizard
5
Weekly Options Expiry CandleThis script shows weekly expiry candle on daily chart. In weekly expiry, week starts on Friday and end on next Thursday. How the candle is constructed: Open= Open price of Friday, if Friday is a holiday, next available open price High= Highest high price of Friday, Monday, Tuesday, Wednesday, Thursday Low= Lowest low price of Friday, Monday, Tuesday, Wednesday, Thursday Close=Close price of Thursday, if Thursday is a holiday, previously available close price I am very new to Pine script, so waiting for your comments and review.
Penunjuk Pine Script®
oleh tanayroy
11
Normailzed CandleThis indicator normalizes Day's candle with Open. Idea is to see the daily movement in the context of the Open of the Day. Larry Williams talks about Open being the most important price of the day. Hence, this indicator. The Green line is average Open-to-High for occurrences of Red days. The Red line is average Open-to-Low for occurrences of Green days. Average are not perfect calculations since occurrences(of Red or Green) will vary within the time-span used for averages. These can used to gauge likelihood of the intra-day price reversal. If the price exceeds green/red line, there is higher likelihood of the price closing above/below open. The blue lines are average Open-to-close for Green and Red occurrences. Be careful on days where consecutive 3rd Highest High or Lowest Low day is made and also on the next day after such day. Prices may turn direction at least for a short while. The precursor to this script of the Candle Infopanel script. That script was just numbers in panel and this is a graphical representation. I Some of the calculations from original script are commented here because it would make visuals clutters (and probably the left-out calculation are not critical to making trade decisions!)
Penunjuk Pine Script®
oleh Masa_1234
4