Get started

Bands and Channels

Improved Z-Score OverlayLast month I published an improved z-score script that goes underneath your chart, which helps to highlight overbought or oversold regimes. It is customizable, and allows changing the periods, whether smoothing capability is desired, whether to use simple or exponential moving averages, and which data source to use (open, high, low, close, ohlc4). Some individuals may find that it is most useful not only to have the z-score visible underneath their price chart, but have the sigma values clearly visible on the chart itself to determine overbought or oversold levels. Therefore, this improved z-score overlay script will place the centerline of price on the chart, and +3/+2/+1/0/-1/-2/-3 sigma. These can be disabled if some values do not want to be shown, and the colors / opacity can be changed. Additionally, you could also put this into a new pane below your chart and disable all of the +3 to -3 sigma values, and enable the "Z-Score" button. This will allow you to replicate the original Improved Z-Score Script. If anyone has questions or would like to have any improvements made, let me know :) - Jim Bosse
Pine Script™ indicator
by jlb05013
Kase Peak Oscillator w/ Divergences [Loxx]Kase Peak Oscillator is unique among first derivative or "rate-of-change" indicators in that it statistically evaluates over fifty trend lengths and automatically adapts to both cycle length and volatility. In addition, it replaces the crude linear mathematics of old with logarithmic and exponential models that better reflect the true nature of the market. Kase Peak Oscillator is unique in that it can be applied across multiple time frames and different commodities. As a hybrid indicator, the Peak Oscillator also generates a trend signal via the crossing of the histogram through the zero line. In addition, the red/green histogram line indicates when the oscillator has reached an extreme condition. When the oscillator reaches this peak and then turns, it means that most of the time the market will turn either at the present extreme, or (more likely) at the following extreme. This is both a reversal and breakout/breakdown indicator. Crosses above/below zero line can be used for breakouts/breakdowns, while the thick green/red bars can be used to detect reversals The indicator consists of three indicators: The PeakOscillator itself is rendered as a gray histogram. Max is a red/green solid line within the histogram signifying a market extreme. Yellow line is max peak value of two (by default, you can change this with the deviations input settings) standard deviations of the Peak Oscillator value White line is the min peak value of two (by default, you can change this with the deviations input settings) standard deviations of the PeakOscillator value The PeakOscillator is used two ways: Divergence: Kase Peak Oscillator may be used to generate traditional divergence signals. The difference between it and traditional divergence indicators lies in its accuracy. PeakOut: The second use is to look for a Peak Out. A Peak Out occurs when the histogram breaks beyond the PeakOut line and then pulls back. A Peak Out through the maximum line will be displayed magenta. A Peak Out, which only extends through the Peak Min line is called a local Peak Out, and is less significant than a normal Peak Out signal. These local Peak Outs are to be relied upon more heavily during sideways or corrective markets. Peak Outs may be based on either the maximum line or the minimum line. Maximum Peak Outs, however, are rarer and thus more significant than minimum Peak Outs. The magnitude of the price move may be greater following the maximum Peak Out, but the likelihood of the break in trend is essentially the same. Thus, our research indicates that we should react equally to a Peak Out in a trendy market and a Peak Min in a choppy or corrective market. Included: Bar coloring Alerts
Pine Script™ indicator
by loxx
6
Round Numbers and Quarter LevelsThis script is based on "Round Numbers Above and Below" by BitcoinJesus-Not-Roger-Ver, but unlike this script that only shows "Round Numbers" levels, my script also shows "Quarter Number" levels like 25 and 75 that are very important for those who follow the quarters theory. Also the original script doesn't have different colors for different levels while my script has different colors and different styles for every level, this way it will be much easyer to recognize the levels at first sight. Finally the origianl script only works with Forex while my script also works with indexes like SP500 and others. Round Numbers are very important psychological levels in trading but also quarters levels (25 and 75) have a huge importance, so I created this script that shows all these levels with different colors and different lines style. You can edit the color and the style of the lines as you wish and you can add all the levels you want. In 1 hour chart 4 levels is usually enough but if you watch a daily chart then 8 levels is way better. Features: Personalize color to 00 round levels Personalize color to 50 round levels Personalize color to Quarters levels Personalize line style to 00 round levels Personalize line style to 50 round levels Personalize line style to Quarters levels Choose number of lines above and below price level (4 is default)
Pine Script™ indicator
by bluebeardit
7
(Quartile Vol.; Vol. Aggregation; Range US Bars; Gaps) [Kioseff]Hello! This indicator is a multifaceted tool that's, hopefully, useful for price action and volume analysis. (This script makes use of the newly introduced "text_font" parameter) With this script you'll have access to: Range US Chart Volume Aggregation Chart Gaps Chart Volume by Quartile Consequently, you'll have access to: First Quartile Volume Threshold Second Quartile Volume Threshold Third Quartile Volume Threshold 90th Percentile Volume Threshold Fourth Quartile Volume Threshold Q2 - Q1 Dispersion Q3 - Q2 Dispersion Q4 - Q3 Dispersion Quartile Deviation Interquartile Range Avg. "n" bar return following "high" volume Avg. "n" bar positive return following "high" volume Avg. "n" bar negative following "high" volume # of Positive Returns Following a Gap # of Negative Returns Following a Gap # of Gaps # of Up Gaps # of Down Gaps Average # of bars to fill Up Gaps Average # of bars to dill Down Gaps Average Gap Up % increase Average Gap Down % decrease Cumulative % increase of all Up Gaps Cumulative % decrease of all Down Gaps Sort gaps by distance from price Hide gaps that price substantially deviates from (gaps will reappear when price trades near the gap) Segment Range US bars by date Manually configure Range US price thresholds Identify "congestion" areas with Range US bars Range US Levels that must be exceeded for a new Range US bar to produce Manually configure cumulative volume threshold for Volume Aggregation bars Segment Volume Aggregation bars by date Largest Volume Aggregation bar increases Largest Volume Aggregation bar decreases Calculate log returns after "high" volume sessions Quartile Volume The Quartile Volume portion of the script segments price/volume intervals by quartile. The image above shows features of the indicator. For statistics, the following metrics are recorded: First Quartile Second Quartile Third Quartile 90th Percentile Fourth Quartile Q2 - Q1 Dispersion Q3 - Q2 Dispersion Q4 - Q3 Dispersion Quartile Deviation Interquartile Range Color-coordinated price bars (by volume quartiles) The percent rank for the volume of the current bar Avg. "n" bar return following "high" volume Avg. "n" bar positive return following "high" volume Avg. "n" bar negative following "high" volume The script colors bars via gradient. By default, bars are colored lime when volume for the interval is "high" (exceeds upper quartile thresholds). The greener the bar, the higher the volume for the interval. Bars are colored red when volume for the interval is "low" (fails to exceed lower quartile thresholds). The redder the bar, the lower the volume for the interval. Naturally, brownish-colored bars reflect a volume interval that concluded near the median. The image above exemplifies the process. This feature might be useful to categorize / objectively define high-volume clusters, low-volume clusters, high-volume price moves, low-volume price moves, etc. For greater precision, you can select to color bars by volume quartile they belong to. The image above shows color-coordinated price bars. More details shown in the image. Additionally, you can select to plot the quartile/percentile that a price bar belongs to on the chart. The image above shows price bars numbered by the volume quartile they belong to. The script will distinguish successive 90th percentile violations, superimpose a linear regression channel atop the data sequence, and record pertinent statistics. The image above shows the process. Lastly, the user can plot an anchored VWAP using a built-in time function. The image above shows the anchored VWAP. Range US Chart A Range US chart operates irrespective of time and volume - simply - bars produce after a user-defined price move is achieved/exceeded in either direction. A range us chart produces “trend candles” and “reversal candles”. A reversal candle always moves against the most immediate bar; a trend candle always moves in favor of the most immediate bar. The user defines the dollar amount price must travel up/down for a trend candle to fulfill, and for a reversal candle to fulfill. Note: if a “down reversal” candle (red) Is produced, it’s impossible for the next candle to also be a down reversal candle - for the downside move to continue the criteria for a down trend candle must be fulfilled. Similarly, if an “up reversal” candle (green) Is produced, it’s impossible for the next candle to also be an up reversal candle - for the upside move to continue, the criteria for an uptrend trend candle must be fulfilled. Consequently, Range US bars frequently trade at the same level for extended periods. This is intentional, as this chart type is theorized to “filter noise” (whether Range US charts fulfill this theory is to your discretion). Lastly, if an up trend candle (green) is produced, the next candle cannot be up a reversal up candle - only a trend up candle or reversal down candle can produce - vice versa for a trend down candle (the subsequent candle cannot be a reversal down candle). In this sense, an uptrend continues on successive trend up candles; a down trend continues on successive trend down candles. The image above exemplifies Range US chart functionality. The lower-right stats table shows the requisite price move for a "Trend" candle to produce and for a "Reversal" candle to produce. The default settings for this chart time automatically calculate the required "Trend" candle price move and the required "Reversal" candle price move. However, both settings are configurable. The image above shows manually configured parameters for a trend bar and reversal bar to produce. This feature allows the user to replicate the Range US chart hosted on extrinsic charting platforms. However, please consider that this script does not use tick data; 1-minute OHLC data is used for calculations. Consequently, configuring the trend bar and reversal bar requirement too low may return inaccurate data. For instance, if you set trend candles to form after a $1 price move then trend candles will form if price moves up $1 from a green Range US bar or down $1 from a red Range US bar. This is sufficient for lower priced assets; however, if you were trading, for instance, Bitcoin - a $1 price move can happen numerous times in one minute. This script can’t plot bars and record data until a 1-minute bar closes and a new 1-minute bar opens. Further, if Bitcoin moves up $1 twenty times and down $1 twenty times in a 1-minute bar - your Range US chart will record such variations as one price move. This data is inaccurate and likely useless. To counter this quandary, a warning message will appear if you configure trend bar price moves or reversal bar price moves too low. The image above shows the concealable warning message. The image above is a flow diagram (made with shaky hands) illustrating the Range US bar formation process. A google search will return additional information on the Range US chart type. Volume Aggregation Bars TradingView user and member of the TradingView Discord server @ferreirajames informed me of the Volume Aggregation chart type. The user commented in the "Suggestions" channel for the TradingView Discord server asking for the Volume Aggregation chart type. As an interim fix, I tried my hand at recreating the process, which is available in this script. Similar to the Range US chart type, Volume Aggregation bars aren’t bound to a time-axis; the bars form after a user-defined, cumulative amount of volume is achieved or exceeded. Consequently, once the cumulative amount of volume is achieved or exceeded - a bar is produced at the corresponding price level. Underlying theory: The chat type is conducive to identifying price levels where traders are “trapped”. Whether the process adequately distinguishes this circumstance is to your discretion. The image above exemplifies the Volume Aggregation chart type. Regardless of the current price, Volume Aggregation bars for after a requisite amount of volume is achieved/exceeded. Tick data isn't used; therefore, remainder values are carry over. By default, the script automatically calculates a proportional cumulative volume total to dictate the formation of Volume Aggregation bars. However, the cumulative threshold is configurable. The image above shows Volume Aggregation bars forming subsequent a user-defined cumulative volume total being exceeded. Note: This chart type uses OHLC data from the timeframe of your chart. Therefore, for instance, setting the volume threshold too low will produce inaccurate, useless data. A warning message will appear for such occurrence. Gaps The indicator incorporates a "Gaps" chart type. The image above shows accompanying features. A list of all unfilled gaps is accessible - gaps for this list are sorted by distance from current price. Partially filled gaps are displayed in the corresponding gap box - the percentage amount the gap was filled is also displayed. Gap statistics show: # of Gaps # of Up Gaps # of Down Gaps Average # of bars to fill Up Gaps Average # of bars to dill Down Gaps Average Gap Up % increase Average Gap Down % decrease Cumulative % increase of all Up Gaps Cumulative % decrease of all Down Gaps Naturally, there may be gaps formed thousands of bars ago that aren't close to price. Showing these gaps on the chart will "scrunch" the y-axis and make prices indistinguishable. I've added a setting that allows the user to hide gaps that are "n" % away from the current price. The gap, if unfilled, will reappear when price trades within the user-defined percentage. The image above shows an example. There's an unfilled down gap that's "hidden" because the current price is a further % away from price than what I've specified in the settings (1%). When prices trade back within 1% of the gap - it will reappear. The image above shows the process in action. Prices moved back within 1% (can be any %) of the gap; therefore, it reappeared on the chart. You can also set the % distance a gap must achieve for it to be considered a gap, recorded and plotted. Additionally, you can select to "visualize" gaps. Similar to the Range US chart and the Volume Aggregation chart, this setting will bars reflecting the most recent sequence of gaps - date and percentage distance of the gap are superimposed atop the bar. Let me know if there's anything else you'd like included! Note: The initial compilation time for this script is.... high. However, once the script's compiled, calculation load times are quick and you can sift through assets and timeframes relatively quick. There's also a setting to "Improve Load Times" in the user-inputs table. This setting only improves the load times for post-compilation calculations and plots. The initial compilation load time is unchanged. Simply, once the indicator has "first loaded", all subsequent loads are quick. Thank you! (:
Editors' picks
Pine Script™ indicator
by KioseffTrading
30
T3 Striped [Loxx]Theory: Although T3 is widely used, some of the details on how it is calculated are less known. T3 has, internally, 6 "levels" or "steps" that it uses for its calculation. This version: Instead of showing the final T3 value, this indicator shows those intermediate steps. This shows the "building steps" of T3 and can be used for trend assessment as well as for possible support / resistance values. 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. Included Alerts Signals Bar coloring Loxx's Expanded Source Types
Pine Script™ indicator
by loxx
6
TriexDev - Liquidation Rekt LevelsTriexDev - Liquidation Rekt Levels TradingView Indicator A basic indicator which lets you see where positions will be liquidated. Each line is based on default leverage levels typically used for trading. (3x,5x,10x,25x,50x) Have a subtle 'label prompt' on the 3x - because I had noticed some people didn't understand what labels were in other indicators. In the settings: - There is an offset to adjust the levels horizontally, this is to help make it easier to track if the chart has hit liquidation positions. - You can change colours/opacity of the lines. - You can hide the 'Labels', and/or 'label prompt' - In the 'Style' tab you can hide individual levels. Inspired/initially based off 'Mex Rekt Level' I often have this added to my charts, and toggle visibility when I want to check the liq levels. GitHub Repo for tidier/more detailed documentation as it is updated.
Pine Script™ indicator
by Xeirt
1
Impatient TS VWAP BandsImpatient VWAP bands are based of Traderskew's VWAP bands but are for more impatient traders. Wicking or crossing down through the upper band indicates a good short trade entry for range-bound trading periods while wicking or crossing up through the lower band indicates a good long entry in range-bound conditions. By default, impatience is disabled. If it is turned on, adjusting impatience determines how quickly the bands approach price: higher impatience approaches price faster. Rebound indicates how far from price the bands bounce after hitting price.
Pine Script™ indicator
by Austimize
KT HMAOverview : This indicator is an experiment to combine one of the volatility concepts (ATR), weighted MA and price movements to help visualize current market condition. Red Band : ATR volatility bands with 2nd and 3rd standard deviation. Yellow Band : Moving Average band HMA : Green/Red >> Shows current trend. Using HMA to emphasize on recent price points rather than older one. ----------------- Disclaimer My Scripts/Indicators/Ideas/Systems including above ones are only for educational purposes. The information contained in the Scripts/Indicators/Ideas does not constitute financial advice or a solicitation to buy or sell any securities of any type. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Do not trade with capital that you can not afford to lose. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Pine Script™ indicator
by nik0580
VWAP BANDS [qrsq]Description This indicator is used to find support and resistance utilizing both buying and selling volume. It can be used on lower and higher time frames to understand where price is likely to reject or bounce. How it works Instead of calculating the VWAP using the total volume, this script estimates the buying/selling volume and respectively calculates their individual VWAP's. The standard deviations of these are then calculated to create the set of two bands. The top bands being the VWAP from buying volume and bottom bands are from selling volume, with the option to use a double band on either pair. How to use it I like to use the bands for LTF scalping as well as HTF swings, I also like to use it alongside my SMA VWAP BANDS. For scalping: I tend to use either the 5m or 15m TF I then set the indicator's TF to 1m I will take a scalp based on the bands confluence with other PA methods, if price is being either supported or rejected. For swings: I tend to use a variety of TFs, including: 30m, 1H, 4H, D I then set the indicator's TF to "Chart" I will take a swing based on the bands confluence with other PA methods, if price is being either supported or rejected. I also tend to use them on perpetual contracts as the volume seems to be more consistent and hence results in more accurate support and resistance.
Pine Script™ indicator
by qrsq
2
Multiple Daily SMA EMA on Intra 1min 5min 15min ChartsThis script is helping you auto plot daily SMA EMA and extensions when you are looking at intraday charts. The script is customizable where user can select which ever levels they are interested in viewing. These daily lines act as support and resistance levels for intraday The green line represent 20 EMA Daily The yellow line represent 50 SMA Daily The olive line represent 200 SMA Daily The red line is upper Bollinger Band Daily The black line is lower Bollinger Band Daily To help you understand which lines are what I would recommend you add this indicator and select "D" timeframe and then see which lines you would like to view for your 1min chart or 5 min chart you can customize from the setting options which plot color you would like to view.
Pine Script™ indicator
by beststockalert
2
PrasiGanFanFibntroduction This is a combination of Fibonacci and Gann fan /retracements. The script can automatically draw as many: Fibonacci Retracements Fibonacci Fan Gann Retracements Gann Fan as the user requires on the chart. Each level set or fan consists of 7 lines based on the most important ratios of Fibonacci/ Gann . Basics What are Fibonacci retracements? Fibonacci retracement levels are horizontal lines that indicate where support and resistance are likely to occur. They stem from Fibonacci’s sequence. Each level is associated with a percentage which is how much of a prior move the price has retraced. The Fibonacci retracement levels are 23.6%, 38.2%, 61.8%, and 78.6%. While not officially a Fibonacci ratio, 50% is also used. The indicator is useful because it can be drawn between any two significant price points, such as a high and a low. The indicator will then create the levels between those two points. What are Gann retracements? A developer of technical analysis and trading was W.D. Gann . Gann theory expects a normal retracement of 50 percent. This means that under normal selling pressure, the stock price will decline half the amount of its most recent rise, and vice versa. It also suggests that retracements occur at the halfway point of a move, such as 25 percent (half of 50 percent), 12.5 percent (half of 25 percent), and so on. What is Fibonacci fan? Fibonacci fan is a set of sequential trend lines drawn from a trough or peak through a set of points dictated by Fibonacci retracements. The first step to create it is to draw a trend line covering the local lowest and highest prices of a security. To reach retracement levels, the trader divides the difference in price at the low and high end by ratios determined by the Fibonacci series. The lines formed by connecting the starting point for the base trend line and each retracement level create the Fibonacci fan. What is Gann fan? A Gann fan consists of a series of lines called Gann angles. These angles are superimposed over a price chart to show potential support and resistance levels. The resulting image is supposed to help technical analysts predict price changes. Gann believed the 45-degree angle to be most important, but the Gann fan also draws angles at degrees like 75, 63.75, 26.25 and 15. The Gann fan originates at a low or high point. The resulting lines show areas of potential future support and resistance . The 45-degree line is known as the 1:1 line because the price will rise or fall at a 45-degree angle when the price moves up/down one unit for each unit of time. All other lines in the Gann fan are drawn above and below the 1:1 line. The other angles are associated with 2:1, 3:1, 4:1, 8:1 and 1:8, 1:4, 1:3, and 1:2 time-to-price moves. Challenges The most of the time I dedicated to writing this script has been spent on handling these problems: 1. Finding Local Highest/Lowest Prices In order to draw Fibonacci and Gann fan /retracements, it's necessary to find local highest and lowest price points (Extrema) on the chart. As this could be so challenging, most traders and coders draw the lines covering the low and high prices over a given period of time or a limited number of bars back instead. I already wrote an indicator using this approach (Auto Fibonacci Combo). In this new script I tried to find the exact highest and lowest prices based on this idea that: if a high point is formed lower than previous high which was after a lowest point, then that previous one was the local highest point, and vice versa if a low point is formed higher than previous low which was after a highest point, then that previous one was the local lowest point. So logically an extremum price on the chart won't be found until the next high/low point is formed. 2. Finding Proper Chart Scale for Gann Fan Based on the theory, Gann angles are sensitive to the chart price scale and in order to have the right angles, the chart must be made with the proper scale. J.A. Hyerczyk in his book "Pattern, Price & Time - Using Gann Theory in Technical Analysis" suggests that the easiest way to determine the scale of a market is by taking the difference between top-to-top and bottom-to-bottom and dividing it by the time it took the market to move from top to top and bottom to bottom. Thus on a properly constructed chart, the basic equation for calculating Gann angles is: Price * Time. 3. Drawing Fans and Relocating Fan Labels at Each New Bar in Pine (A Programming-Related Subject) To do this, I used linear equations and line slopes. Of course it was so complicated and exhausting, but finally I overcame that thanks to my genius cousin. Settings and Usage By default, the script shows detected extremum points plus 1 Fibonacci fan, 1 Gann fan , 1 set of Fibonacci retracements and no Gann retracements on the chart. All of these could be changed in the indicator settings beside the color and transparency of each line. Feel free to use this and send me your thoughts!
Pine Script™ indicator
by Prasi456
4
BBSS - Bollinger Bands Scalping SignalsModified Bollinger Bands Indicator Added: - color change divergence (green) and narrowing (red) of the upper and lower bands - color change of the moving average - upward trend (green) and downward trend (red) - the appearance of a potential signal for long and short positions when the candle closes behind the upper or lower bands. How to use the indicator: Long conditions: - the price breaks through the upper band - Bollinger bands are expanding and should be green - the mid-line is green - the trigger candle should be green Short conditions: - the price breaks through the lower band - Bollinger bands are expanding and should be red - the mid-line is red - the trigger candle should be red
Pine Script™ indicator
by berezitskysl
1