Ultimate RSI [LuxAlgo]The Ultimate RSI indicator is a new oscillator based on the calculation of the Relative Strength Index that aims to put more emphasis on the trend, thus having a less noisy output. Opposite to the regular RSI, this oscillator is designed for a trend trading approach instead of a contrarian one.
🔶 USAGE
While returning the same information as a regular RSI, the Ultimate RSI puts more emphasis on trends, and as such can reach overbought/oversold levels faster as well as staying longer within these areas. This can avoid the common issue of an RSI regularly crossing an overbought or oversold level while the trend makes new higher highs/lower lows.
The Ultimate RSI crossing above the overbought level can be indicative of a strong uptrend (highlighted as a green area), while an Ultimate RSI crossing under the oversold level can be indicative of a strong downtrend (highlighted as a red area).
The Ultimate RSI crossing the 50 midline can also indicate trends, with the oscillator being above indicating an uptrend, else a downtrend. Unlike a regular RSI, the Ultimate RSI will cross the midline level less often, thus generating fewer whipsaw signals.
For even more timely indications users can observe the Ultimate RSI relative to its signal line. An Ultimate RSI above its signal line can indicate it is increasing, while the opposite would indicate it is decreasing.
🔹 Smoothing Methods
Users can return more reactive or smoother results depending on the selected smoothing method used for the calculation of the Ultimate RSI. Options include:
Exponential Moving Average (EMA)
Simple Moving Average (SMA)
Wilder's Moving Average (RMA)
Triangular Moving Average (TMA)
These are ranked by the degree of reactivity of each method, with higher ones being more reactive (but less smooth).
Users can also select the smoothing method used by the signal line.
🔶 DETAILS
The RSI returns a normalized exponential average of price changes in the range (0, 100), which can be simply calculated as follows:
ema(d) / ema(|d|) × 50 + 50
where d represent the price changes. In order to put more emphasis on trends we can put higher weight on d . We can perform this on the occurrence of new higher highs/lower lows, and by replacing d with the rolling range instead (the rolling period used to detect the higher highs/lower lows is equal to the length setting).
🔶 SETTINGS
Length: Calculation period of the indicator
Method: Smoothing method used for the calculation of the indicator.
Source: Input source of the indicator
🔹 Signal Line
Smooth: Degree of smoothness of the signal line
Method: Smoothing method used to calculation the signal line.
Komut dosyalarını "luxalgo" için ara
Volume Profile (Maps) [LuxAlgo]The Pine Script® developers have unleashed "maps"!
Volume Profile (Maps) displays volume, associated with price, above and below the latest price, by using maps
The largest and second-largest volume is highlighted.
🔶 USAGE
The proposed script can highlight more frequent closing prices/prices with the highest volume, potentially highlighting more liquid areas. The prices with the highest associated volume (in red and orange in the indicator) can eventually be used as support/resistance levels.
Voids within the volume profile can highlight large price displacements (volatile variations).
🔶 CONCEPTS
🔹 Maps
A map object is a collection that consists of key - value pairs
Each key is unique and can only appear once. When adding a new value with a key that the map already contains, that value replaces the old value associated with the key .
You can change the value of a particular key though, for example adding volume (value) at the same price (key), the latter technique is used in this script.
Volume is added to the map, associated with a particular price (default close, can be set at high, low, open,...)
When the map already contains the same price (key), the value (volume) is added to the existing volume at the associated price.
A map can contain maximum 50K values, which is more than enough to hold 20K bars (Basic 5K - Premium plan 20K), so the whole history can be put into a map.
🔹 Visible line/box limit
We can only display maximum 500 line.new() though.
The code locates the current (last) close, and displays volume values around this price, using lines, for example 250 lines above and 250 lines below current price.
If one side contains fewer values, the other side can show more lines, taking the maximum out of the 500 visible line limitation.
Example (max. 500 lines visible)
• 100 values below close
• 2000 values above close
-> 100 values will be displayed below close
-> 400 remaining -> 400 values will be displayed above close
Pushing the limits even further, when ' Amount of bars ' is set higher than 500, boxes - box.new() - will be used as well.
These have a limit of 500 as well, bringing the total limit to 1000.
Note that there are visual differences when boxes overlap against lines.
If this is confusing, please keep ' Amount of bars ' at max. 500 (then only lines will be used).
🔹 Rounding function
This publication contains 2 round functions, which can be used to widen the Volume Profile
Round
• "Round" set at zero -> nothing changes to the source number
• "Round" set below zero -> x digit(s) after the decimal point, starting from the right side, and rounded.
• "Round" set above zero -> x digit(s) before the decimal point, starting from the right side, and rounded.
Example: 123456.789
0->123456.789
1->123456.79
2->123456.8
3->123457
-1->123460
-2->123500
Step
Another option is custom steps.
After setting "Round" to "Step", choose the desired steps in price,
Examples
• 2 -> 1234.00, 1236.00, 1238.00, 1240.00
• 5 -> 1230.00, 1235.00, 1240.00, 1245.00
• 100 -> 1200.00, 1300.00, 1400.00, 1500.00
• 0.05 -> 1234.00, 1234.05, 1234.10, 1234.15
•••
🔶 FEATURES
🔹 Adjust position & width
🔹 Table
The table shows the details:
• Size originalMap : amount of elements in original map
• # higher: amount of elements, higher than last "close" (source)
• index "close" : index of last "close" (source), or # element, lower than source
• Size newMap : amount of elements in new map (used for display lines)
• # higher : amount of elements in newMap, higher than last "close" (source)
• # lower : amount of elements in newMap, lower than last "close" (source)
🔹 Volume * currency
Let's take as example BTCUSD, relative to USD, 10 volume at a price of 100 BTCUSD will be very different than 10 volume at a price of 30000 (1K vs. 300K)
If you want volume to be associated with USD, enable Volume * currency . Volume will then be multiplied by the price:
• 10 volume, 1 BTC = 100 -> 1000
• 10 volume, 1 BTC = 30K -> 300K
Disabled
Enabled
🔶 DETAILS
🔹 Put
When the map doesn't contain a price, it will be added, using map.put(id, key, value)
In our code:
map.put(originalMap, price, volume)
or
originalMap.put(price, volume)
A key (price) is now associated with a value (volume) -> key : value
Since all keys are unique, we don't have to know its position to extract the value, we just need to know the key -> map.get(id, key)
We use map.get() when a certain key already exists in the map, and we want to add volume with that value.
if originalMap.contains(price)
originalMap.put(price, originalMap.get(price) + volume)
-> At the last bar, all prices (source) are now associated with volume.
🔹 Copy & sort
Next, every key of the map is copied and sorted (array of keys), after which the index (idx) is retrieved of last (current) price.
copyK = originalMap.keys().copy()
copyK.sort()
idx = copyK.binary_search_leftmost(src)
Then left and right side of idx is investigated to show a maximum amount of lines at both sides of last price.
🔹 New map & display
The keys (from sorted array of copied keys) that will be displayed are put in a new map, with the associated volume values from the original map.
newMap = map.new()
🔹 Re-cap
• put in original amp (price key, volume value)
• copy & sort
• find index of last price
• fetch relevant keys left/right from that index
• put keys in new map and fetch volume associated with these keys (from original map)
Simple example (only show 5 lines)
bar 0, price = 2, volume = 23
bar 1, price = 4, volume = 3
bar 2, price = 8, volume = 21
bar 3, price = 6, volume = 7
bar 4, price = 9, volume = 13
bar 5, price = 5, volume = 85
bar 6, price = 3, volume = 13
bar 7, price = 1, volume = 4
bar 8, price = 7, volume = 9
Original map:
Copied keys array:
Sorted:
-> 5 keys around last price (7) are fetched (5, 6, 7, 8, 9)
-> keys are placed into new map + volume values from original map
Lastly, these values are displayed.
🔶 SETTINGS
Source : Set source of choice; default close , can be set as high , low , open , ...
Volume & currency : Enable to multiply volume with price (see Features )
Amount of bars : Set amount of bars which you want to include in the Volume Profile
Max lines : maximum 1000 (if you want to use only lines, and no boxes -> max. 500, see Concepts )
🔹 Round -> ' Round/Step '
Round -> see Concepts
Step -> see Concepts
🔹 Display Volume Profile
Offset: shifts the Volume Profile (max. 500 bars to the right of last bar, see Features )
Max width Volume Profile: largest volume will be x bars wide, the rest is displayed as a ratio against largest volume (see Features )
Show table : Show details (see Features )
🔶 LIMITATIONS
• Lines won't go further than first bar (coded).
• The Volume Profile can be placed maximum 500 bar to the right of last price.
• Maximum 500 lines/boxes can be displayed
Machine Learning Regression Trend [LuxAlgo]The Machine Learning Regression Trend tool uses random sample consensus (RANSAC) to fit and extrapolate a linear model by discarding potential outliers, resulting in a more robust fit.
🔶 USAGE
The proposed tool can be used like a regular linear regression, providing support/resistance as well as forecasting an estimated underlying trend.
Using RANSAC allows filtering out outliers from the input data of our final fit, by outliers we are referring to values deviating from the underlying trend whose influence on a fitted model is undesired. For financial prices and under the assumptions of segmented linear trends, these outliers can be caused by volatile moves and/or periodic variations within an underlying trend.
Adjusting the "Allowed Error" numerical setting will determine how sensitive the model is to outliers, with higher values returning a more sensitive model. The blue margin displayed shows the allowed error area.
The number of outliers in the calculation window (represented by red dots) can also be indicative of the amount of noise added to an underlying linear trend in the price, with more outliers suggesting more noise.
Compared to a regular linear regression which does not discriminate against any point in the calculation window, we see that the model using RANSAC is more conservative, giving more importance to detecting a higher number of inliners.
🔶 DETAILS
RANSAC is a general approach to fitting more robust models in the presence of outliers in a dataset and as such does not limit itself to a linear regression model.
This iterative approach can be summarized as follow for the case of our script:
Step 1: Obtain a subset of our dataset by randomly selecting 2 unique samples
Step 2: Fit a linear regression to our subset
Step 3: Get the error between the value within our dataset and the fitted model at time t , if the absolute error is lower than our tolerance threshold then that value is an inlier
Step 4: If the amount of detected inliers is greater than a user-set amount save the model
Repeat steps 1 to 4 until the set number of iterations is reached and use the model that maximizes the number of inliers
🔶 SETTINGS
Length: Calculation window of the linear regression.
Width: Linear regression channel width.
Source: Input data for the linear regression calculation.
🔹 RANSAC
Minimum Inliers: Minimum number of inliers required to return an appropriate model.
Allowed Error: Determine the tolerance threshold used to detect potential inliers. "Auto" will automatically determine the tolerance threshold and will allow the user to multiply it through the numerical input setting at the side. "Fixed" will use the user-set value as the tolerance threshold.
Maximum Iterations Steps: Maximum number of allowed iterations.
Adaptive MACD [LuxAlgo]The Adaptive MACD indicator is an adaptive version of the popular Moving Average Convergence Divergence (MACD) oscillator, returning longer-term variations during trending markets and cyclic variations during ranging markets while filtering out noisy variations.
🔶 USAGE
The proposed oscillator contains all the elements within a regular MACD, such as a signal line and histogram. A MACD value above 0 would indicate up-trending variations, while a value under 0 would be indicating down-trending variations.
Just like most oscillators, our proposed Adaptive MACD is able to return divergences with the price.
As we can see in the image above ranging markets will make the Adaptive MACD more conservative toward more cyclical conservations, filtering out both noise and longer-term variations. However, when longer-term variations (such as in a trending market) are prominent the oscillator will conserve longer-term variations.
The R2 Period setting determines when trending/ranging markets are detected, with higher values returning indications for longer intervals.
The fast and slow settings will act similarly to the regular MACD, however, closer values will return more cyclical outputs.
The image above compares our proposed MACD (top) with a regular MACD (bottom), both using fast = 19 and slow = 20 .
🔶 DETAILS
It is common to be solely interested in the trend component when the market is trending, however, during a ranging market it is more common to observe a more prominent cyclical/noise component. We want to be able to preserve one of the components at the appropriate market conditions, however, the regular MACD lack the ability to preserve cyclical component with high accuracy.
The MACD is an IIR bandpass filter. In order to obtain a lower passband bandwidth and a more symmetrical magnitude response (which would allow to conserve more precise cyclical variations) we can directly change the system calculation:
y = (price - price ) × g + ((1 - a1) + (1 - a2)) × y - (1 - a1) × (1 - a2) × y
where:
a1 = 2/(fast + 1)
a2 = 2/(slow + 1)
g = a1 - a2
Using division instead of multiplication on the second feedback weight allows further weighting the 2 samples lagged output, returning a more desirable magnitude response with a higher degree of filtering on both ends of the spectrum as shown in the image below:
We are interested in conserving cycles during ranging markets, and longer-term variations during trending markets, we can do this by interpolating between our two filter coefficients:
α × + (1 - α) ×
where 1 > α > 0 . α is measuring if the market is trending or ranging, with values closer to 1 indicating a trending market. We see that for higher values of α the original coefficient of the MACD is used. The image below shows various magnitude responses given multiple values of α :
We use a rolling R-Squared as α , this measurement has the benefit of indicating if the market is trending or ranging, as well as being constrained within range (0, 1), and having a U-shaped distribution.
If you are interested to learn more about the MACD see:
🔶 SETTINGS
R2 Period: Calculation window of the R-Squared.
Fast: Fast period for the calculation of the Adaptive MACD, lower values will return more noisy results.
Slow: Slow period for the calculation of the Adaptive MACD, higher values will return result with longer-term conserved variations.
Signal: Period of the EMA applied to the Adaptive MACD.
SuperTrend AI (Clustering) [LuxAlgo]The SuperTrend AI indicator is a novel take on bridging the gap between the K-means clustering machine learning method & technical indicators. In this case, we apply K-Means clustering to the famous SuperTrend indicator.
🔶 USAGE
Users can interpret the SuperTrend AI trailing stop similarly to the regular SuperTrend indicator. Using higher minimum/maximum factors will return longer-term signals.
The displayed performance metrics displayed on each signal allow for a deeper interpretation of the indicator. Whereas higher values could indicate a higher potential for the market to be heading in the direction of the trend when compared to signals with lower values such as 1 or 0 potentially indicating retracements.
In the image above, we can notice more clear examples of the performance metrics on signals indicating trends, however, these performance metrics cannot perform or predict every signal reliably.
We can see in the image above that the trailing stop and its adaptive moving average can also act as support & resistance. Using higher values of the performance memory setting allows users to obtain a longer-term adaptive moving average of the returned trailing stop.
🔶 DETAILS
🔹 K-Means Clustering
When observing data points within a specific space, we can sometimes observe that some are closer to each other, forming groups, or "Clusters". At first sight, identifying those clusters and finding their associated data points can seem easy but doing so mathematically can be more challenging. This is where cluster analysis comes into play, where we seek to group data points into various clusters such that data points within one cluster are closer to each other. This is a common branch of AI/machine learning.
Various methods exist to find clusters within data, with the one used in this script being K-Means Clustering , a simple iterative unsupervised clustering method that finds a user-set amount of clusters.
A naive form of the K-Means algorithm would perform the following steps in order to find K clusters:
(1) Determine the amount (K) of clusters to detect.
(2) Initiate our K centroids (cluster centers) with random values.
(3) Loop over the data points, and determine which is the closest centroid from each data point, then associate that data point with the centroid.
(4) Update centroids by taking the average of the data points associated with a specific centroid.
Repeat steps 3 to 4 until convergence, that is until the centroids no longer change.
To explain how K-Means works graphically let's take the example of a one-dimensional dataset (which is the dimension used in our script) with two apparent clusters:
This is of course a simple scenario, as K will generally be higher, as well the amount of data points. Do note that this method can be very sensitive to the initialization of the centroids, this is why it is generally run multiple times, keeping the run returning the best centroids.
🔹 Adaptive SuperTrend Factor Using K-Means
The proposed indicator rationale is based on the following hypothesis:
Given multiple instances of an indicator using different settings, the optimal setting choice at time t is given by the best-performing instance with setting s(t) .
Performing the calculation of the indicator using the best setting at time t would return an indicator whose characteristics adapt based on its performance. However, what if the setting of the best-performing instance and second best-performing instance of the indicator have a high degree of disparity without a high difference in performance?
Even though this specific case is rare its however not uncommon to see that performance can be similar for a group of specific settings (this could be observed in a parameter optimization heatmap), then filtering out desirable settings to only use the best-performing one can seem too strict. We can as such reformulate our first hypothesis:
Given multiple instances of an indicator using different settings, an optimal setting choice at time t is given by the average of the best-performing instances with settings s(t) .
Finding this group of best-performing instances could be done using the previously described K-Means clustering method, assuming three groups of interest (K = 3) defined as worst performing, average performing, and best performing.
We first obtain an analog of performance P(t, factor) described as:
P(t, factor) = P(t-1, factor) + α * (∆C(t) × S(t-1, factor) - P(t-1, factor))
where 1 > α > 0, which is the performance memory determining the degree to which older inputs affect the current output. C(t) is the closing price, and S(t, factor) is the SuperTrend signal generating function with multiplicative factor factor .
We run this performance function for multiple factor settings and perform K-Means clustering on the multiple obtained performances to obtain the best-performing cluster. We initiate our centroids using quartiles of the obtained performances for faster centroids convergence.
The average of the factors associated with the best-performing cluster is then used to obtain the final factor setting, which is used to compute the final SuperTrend output.
Do note that we give the liberty for the user to get the final factor from the best, average, or worst cluster for experimental purposes.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Performance Memory: Determine the degree to which older inputs affect the current output, with higher values returning longer-term performance measurements.
From Cluster: Determine which cluster is used to obtain the final factor.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
QQE Weighted Oscillator [LuxAlgo]The QQE (Quantitative Qualitative Estimation) Weighted Oscillator improves on its original version by weighting the RSI based on the indications given by the trailing stop, requiring more effort in order for a cross with the trailing stop to occur.
🔶 USAGE
The QQE Weighted Oscillator is comprised of a smoothed RSI oscillator and a trailing stop derived from this same RSI. The oscillator can be used to indicate whether the market is overbought/oversold as well as an early indication of trend reversals thanks to the leading nature of the RSI.
Using higher Factor values will return a longer-term trailing stop.
Like with a regular RSI divergence can be indicative of a reversal.
Further weighting will control how much "effort" is required for the trailing stop to cross the RSI. For example. For example, an RSI above the trailing stop will require a higher degree of negative price variations in order for a potential cross to occur when using higher weights.
This can cause higher weightings to return more cyclical and smoother results.
🔶 SETTINGS
Length: Length of the RSI oscillator.
Factor: Multiplicative factor used for the trailing stop calculation.
Smooth: Degree of smoothness of the RSI oscillator.
Weight: Degree of weighting used for the RSI calculation.
Support & Resistance Dynamic [LuxAlgo]The Support & Resistance Dynamic indicator aims to return real-time predictive support and resistance zones that are relevant to a detected trend. This makes this indicator similar to our previously published Predictive Ranges indicator.
Users can additionally extend the most recent historical support and resistance zones.
🔶 USAGE
Hypothetical resistance levels in an up-trend or supports in a down-trend would tend to be broken more easily, as such the indicator primary objective is to return reliable real-time support and resistance levels by taking this into account.
When the market is up-trending the indicator will only return support zones, while a down-trending market will cause the indicator to only return resistance zones.
If the price significantly breaks a support/resistance, rendering it unreliable, it can be a sign of a potential reversal.
Users can return support/resistance levels/zones for shorter-term trends by reducing the Multiplicative Factor setting.
🔹 Extension
Users can extend past estimated support/resistance levels, the amount of extended levels is determined by the users. Certain levels can stay relevant in the future, and can also aid in measuring the significance of a breakout, with further past levels being reached being indicative of more significant trends.
🔶 DETAILS
To determine if the price is up-trending or down-trending in order to show either support or resistance, the same method used in the predictive ranges script is used. A central tendency is estimated, if price significantly deviates from it upward an uptrend is detected, else a significant deviation downward would indicate a downtrend.
The central tendency estimate is used for the construction of the support and resistance levels.
🔶 SETTINGS
Multiplicative Factor: Determines the frequency at which new supports/resistances are returned, with lower values returning more frequent levels/zones.
ATR Length: ATR averaging length used as deviation threshold for the central tendency estimate.
Extend Last: Determines the amount of most recent historical supports/resistances to extend to the latest bar.
Master Pattern [LuxAlgo]The Master Pattern indicator is derived from the framework proposed by Wyckoff and automatically displays major/minor patterns and their associated expansion lines on the chart.
Liquidity levels are also included and can be used as targets/stops. Note that the Liquidity levels are plotted retrospectively as they are based on pivots.
🔶 USAGE
The Master Pattern indicator detects contraction phases in the markets (characterized by a lower high and higher low). The resulting average from the latest swing high/low is used as expansion line. Price breaking the contraction range upwards highlights a bullish master pattern, while a break downward highlights a bearish master pattern.
During the expansion phase price can tend to be stationary around the expansion level. This phase is then often followed by the price significantly deviating from the expansion line, highlighting a markup phase.
Expansion lines can also be used as support/resistance levels.
🔹 Major/Minor Patterns
The script can classify patterns as major or minor patterns.
Major patterns occur when price breaks both the upper and lower extremity of a contraction range, with their contraction area highlighted with a border, while minor patterns have only a single extremity broken.
🔶 SETTINGS
Contraction Detection Lookback: Lookback used to detect the swing points used to detect the contraction range.
Liquidity Levels: Lookback for the swing points detection used as liquidity levels. Higher values return longer term liquidity levels.
Show Major Pattern: Display major patterns.
Show Minor Pattern: Display minor patterns.
HyperTrend [LuxAlgo]The HyperTrend indicator aims to provide a real-time estimate of an underlying linear trend in the price. Support and resistance extremities are constructed from this estimate which can provide trade opportunities within the overall trend.
Most tools that return lines on a chart are either subject to backpainting or repainting. We aimed to provide a reliable real-time method to estimate linear trends in the price, enhancing traders' decision making processes when it comes to trading trends in price, hence the term 'HyperTrend'.
🔶 USAGE
Users can use the HyperTrend to easily determine the trend direction in the price, with an average sloping upward indicating an uptrend, and an average sloping downward indicating a downtrend.
The channels upper extremity can act as a resistance, while the lower extremity can act as a support. Contact with candle wicks can signal timely reversals/retracements.
Using a higher "Multiplicative Factor" value will return less frequent new channels, and is suitable to analyze longer-term trends. The slope settings on the other end allow us to control the slope of the returned channels, with higher values returning flatter results (similar to our previously posted predictive ranges).
🔹 Channel Average
The channel average can return an estimate of the current (and future) trend in the price, the chart below shows an interval where a linear regression is displayed alongside the channel average:
Unlike the linear regression, the average does not have any lookahead bias, this of course comes at the price of accuracy in most cases.
Users can also use this average as a support or resistance. The breakout of a TC average that has been tested multiple times can be considered more significant in suggesting a trend reversal.
🔶 SETTINGS
Multiplicative Factor: Control the allowed degree of deviation of the price from the average line. Higher values will return less frequent new channels.
Slope: Controls the steepness of the returned lines. Higher values will return flatter results.
Width %: Width percentage of the channel. Lower results will return narrower channels.
Extrapolated Previous Trend [LuxAlgo]The Extrapolated Previous Trend indicator extrapolates the estimated linear trend of the prices within a previous interval to the current interval. Intervals can be user-defined.
🔶 USAGE
Returned lines can be used to provide a forecast of trends, assuming trends are persistent in sign and slope.
Using them as support/resistance can also be an effecting usage in case the trend in a new interval does not follow the characteristic of the trend in the previous interval.
The indicator includes a dashboard showing the degree of persistence between segmented trends for uptrends and downtrends. A higher value is indicative of more persistent trend signs.
A lower value could hint at an anti-persistent behavior, with uptrends over an interval often being followed by a down-trend and vice versa. We can invert candle colors to determine future trend direction in this case.
🔶 DETAILS
This indicator can be thought of as a segmented linear model ( a(n)t + b(n) ), where n is the specific interval index. Unlike a regular segmented linear regression model, this indicator is not subject to lookahead bias, coefficients of the model are obtained on previous intervals.
The quality of the fit of the model is dependent on the variability of its coefficients a(n) and b(n) . Coefficients being less subject to change over time are more indicative of trend persistence.
🔶 SETTINGS
Timeframe: Determine the frequency at which new trends are estimated.
ICT Silver Bullet [LuxAlgo]The ICT Silver Bullet indicator is inspired from the lectures of "The Inner Circle Trader" (ICT) and highlights the Silver Bullet (SB) window which is a specific 1-hour interval where a Fair Value Gap (FVG) pattern can be formed.
When a FVG is formed during the Silver Bullet window, Support & Resistance lines will be drawn at the end of the SB session.
There are 3 different Silver Bullet windows (New York local time):
The London Open Silver Bullet (3 AM — 4 AM ~ 03:00 — 04:00)
The AM Session Silver Bullet (10 AM — 11 AM ~ 10:00 — 11:00)
The PM Session Silver Bullet (2 PM — 3 PM ~ 14:00 — 15:00)
🔶 USAGE
The ICT Silver Bullet indicator aims to provide users a comprehensive display as similar as possible to how anyone would manually draw the concept on their charts.
It's important to use anything below the 15-minute timeframe to ensure proper setups can display. In this section, we are purely using the 3-minute timeframe.
In the image below, we can see a bullish setup whereas a FVG was successfully retested during the Silver Bullet session. This was then followed by a move upwards to liquidity as our target.
Alternatively, you can also see below a bearish setup utilizing the ICT Silver Bullet indicator outlined.
At this moment, the indicator has removed all other FVGs within the Silver Bullet session & has confirmed this FVG as the retested one.
There is also a support level marked below to be used as a liquidity target as per the ICT Silver Bullet concept suggests.
In the below chart we can see 4 separate consecutive examples of bullish & bearish setups on the 3-minute chart.
🔶 CONCEPTS
This technique can visualize potential support/resistance lines, which can be used as targets.
The script contains 2 main components:
• forming of a Fair Value Gap (FVG)
• drawing support/resistance (S/R) lines
🔹 Forming of FVG
1 basic principle: when a FVG at the end of the SB session is not retraced, it will be made invisible.
Dependable on the settings, different FVG's will be shown.
• 'All FVG': all FVG's are shown, regardless the trend
• 'Only FVG's in the same direction of trend': Only FVG's are shown that are similar to the trend at that moment (trend can be visualized by enabling ' Show ' -> ' Trend ')
-> only bearish FVG when the trend is bearish vs. bullish FVG when trend is bullish
• 'strict': Besides being similar to the trend, only FVG's are shown when the closing price at the end of the SB session is:
– below the top of the FVG box (bearish FVG)
– above bottom of the FVG box (bullish FVG)
• 'super-strict': Besides being similar to the trend, only FVG's are shown when the FVG box is NOT broken
in the opposite direction AND the closing price at the end of the SB session is:
– below bottom of the FVG box (bearish FVG)
– above the top of the FVG box (bullish FVG)
' Super-Strict ' mode resembles ICT lectures the most.
🔹 Drawing support/resistance lines
When the SB session has ended, the script draws potential support/resistance lines, again, dependable on the settings.
• Previous session (any): S/R lines are fetched between current and previous session.
For example, when current session is ' AM SB Session (10 AM — 11 AM) ', then previous session is
' London Open SB (3 AM — 4 AM) ', S/R lines between these 2 sessions alone will be included.
• Previous session (similar): S/R lines are fetched between current and previous - similar - session.
For example, when current session is ' London Open SB (3 AM — 4 AM)' , only S/R lines between
current session and previous ' London Open SB (3 AM — 4 AM) ' session are included.
When a new session starts, S/R lines will be removed, except when enabling ' Keep lines (only in strict mode) '
This is not possible in ' All FVG ' or ' Only FVG's in the same direction of trend ' mode, since the chart would be cluttered.
Note that in ' All FVG ' or ' Only FVG's in the same direction of trend ' mode, both, Support/Resistance lines will be shown,
while in Strict/Super-Strict mode:
• only Support lines will be shown if a bearish FVG appears
• only Resistance lines if a bullish FVG is shown
The lines will still be drawn the the end of the SB session, when a valid FVG appears,
but the S/R lines will remain visible and keep being updated until price reaches that line.
This publication contains a "Minimum Trade Framework (mTFW)", which represents the best-case expected price delivery, this is not your actual trade entry - exit range.
• 40 ticks for index futures or indices
• 15 pips for Forex pairs.
When on ' Strict/Super-Strict ' mode, only S/R lines will be shown which are:
• higher than the lowest FVG bottom + mTFW, in a bullish scenario
• lower than the highest FVG bottom - mTFW, in a bearish scenario
When on ' All FVG/Only FVG's in the same direction of trend ' mode, or on non-Forex/Futures/Indices symbols, S/R needs to be higher/lower than SB session high/low.
🔶 SETTINGS
(Check CONCEPTS for deeper insights and explanation)
🔹 Swing settings (left): Sets the length, which will set the lookback period/sensitivity of the Zigzag patterns (which directs the trend)
🔹 Silver Bullet Session; Show SB session: show lines and labels of SB session
Labels can be disabled separately in the ' Style ' section, color is set at the ' Inputs ' section.
🔹 FVG
– Mode
• All FVG
• Only FVG's in the same direction of trend
• Strict
• Super-Strict
– Colors
– Extend: extend till last bar of SB session
🔹 Targets – support/resistance lines
– Previous session (any): S/R lines fetched between current and previous SB session
– Previous session (similar): S/R lines fetched between current and previous similar SB session
– Colors
– Keep lines (only in strict mode)
🔹 Show
– MSS ~ Session: Show Market Structure Shift , only when this happens during a SB session
– Trend: Show trend (Zigzag, colored ~ trend)
Open Interest Chart [LuxAlgo]The Open Interest Chart displays Commitments of Traders %change of futures open interest , with a unique circular plotting technique, inspired from this publication Periodic Ellipses .
🔶 USAGE
Open interest represents the total number of contracts that have been entered by market participants but have not yet been offset or delivered. This can be a direct indicator of market activity/liquidity, with higher open interest indicating a more active market.
Increasing open interest is highlighted in green on the circular plot, indicating money coming into the market, while decreasing open interests highlighted in red indicates money coming out of the market.
You can set up to 6 different Futures Open interest tickers for a quick follow up:
🔶 DETAILS
Circles are drawn, using plot() , with the functions createOuterCircle() (for the largest circle) and createInnerCircle() (for inner circles).
Following snippet will reload the chart, so the circles will remain at the right side of the chart:
if ta.change(chart.left_visible_bar_time ) or
ta.change(chart.right_visible_bar_time)
n := bar_index
Here is a snippet which will draw a 39-bars wide circle that will keep updating its position to the right.
//@version=5
indicator("")
n = bar_index
barsTillEnd = last_bar_index - n
if ta.change(chart.left_visible_bar_time ) or
ta.change(chart.right_visible_bar_time)
n := bar_index
createOuterCircle(radius) =>
var int end = na
var int start = na
var basis = 0.
barsFromNearestEdgeCircle = 0.
barsTillEndFromCircleStart = radius
startCylce = barsTillEnd % barsTillEndFromCircleStart == 0 // start circle
bars = ta.barssince(startCylce)
barsFromNearestEdgeCircle := barsTillEndFromCircleStart -1
basis := math.min(startCylce ? -1 : basis + 1 / barsFromNearestEdgeCircle * 2, 1) // 0 -> 1
shape = math.sqrt(1 - basis * basis)
rad = radius / 2
isOK = barsTillEnd <= barsTillEndFromCircleStart and barsTillEnd > 0
hi = isOK ? (rad + shape * radius) - rad : na
lo = isOK ? (rad - shape * radius) - rad : na
start := barsTillEnd == barsTillEndFromCircleStart ? n -1 : start
end := barsTillEnd == 0 ? start + radius : end
= createOuterCircle(40)
plot(h), plot(l)
🔶 LIMITATIONS
Due to the inability to draw between bars, from time to time, drawings can be slightly off.
Bar-replay can be demanding, since it has to reload on every bar progression. We don't recommend using this script on bar-replay. If you do, please choose the lowest speed and from time to time pause bar-replay for a second. You'll see the script gets reloaded.
🔶 SETTINGS
🔹 TICKERS
Toggle :
• Enabled -> uses the first column with a pre-filled list of Futures Open Interest tickers/symbols
• Disabled -> uses the empty field where you can enter your own ticker/symbol
Pre-filled list : the first column is filled with a list, so you can choose your open interest easily, otherwise you would see COT:088691_F_OI aka Gold Futures Open Interest for example.
If applicable, you will see 3 different COT data:
• COT: Legacy Commitments of Traders report data
• COT2: Disaggregated Commitments of Traders report data
• COT3: Traders in Financial Futures report data
Empty field : When needed, you can pick another ticker/symbol in the empty field at the right and disable the toggle.
Timeframe : Commitments of Traders (COT) data is tallied by the Commodity Futures Trading Commission (CFTC) and is published weekly. Therefore data won't change every day.
Default set TF is Daily
🔹 STYLE
From middle:
• Enabled (default): Drawings start from the middle circle -> towards outer circle is + %change , towards middle of the circle is - %change
• Disabled: Drawings start from the middle POINT of the circle, towards outer circle is + OR -
-> in both options, + %change will be coloured green , - %change will be coloured red .
-> 0 %change will be coloured blue , and when no data is available, this will be coloured gray .
Size circle : options tiny, small, normal, large, huge.
Angle : Only applicable if "From middle" is disabled!
-> sets the angle of the spike:
Show Ticker : Name of ticker, as seen in table, will be added to labels.
Text - fill
• Sets colour for +/- %change
Table
• Sets 2 text colours, size and position
Circles
• Sets the colour of circles, style can be changed in the Style section.
You can make it as crazy as you want:
Support Resistance Classification (VR) [LuxAlgo]The Support Resistance Classification (VR) indicator shows SR levels on any chart's visible range using higher time-frame data (HTF). Levels are classified 1 through 10 based on their strength, with lower values indicating stronger support/resistance levels.
This indicator uses visible range functionality, whereas if you adjust your chart to show previous price data, the indicator may show new levels.
🔶 USAGE
Certain indicators on higher timeframes can provide longer term support/resistance levels on lower timeframes. Users can use the provided levels on a chart visible range and use them as reference for future support/resistance levels.
The classification algorithm measures the strength of a support/resistance level using the entire chart visible range and is in a range of 1 to 10, with higher values indicating a weaker support/resistance.
Supports/resistances highlighted by the indicator can be used for future applications by marking them on the chart (quickly done with alt + h).
🔶 DETAILS
All calculations are based on what you see on the Visible Chart, as such changing the chart will recalculate the indicator.
Since only Swings which are not broken are included, every break would exclude that swing. Therefore, even when 'value' is chosen at Settings ('Value'), breaks are always calculated on the entire line.
🔶 SETTINGS
Fade: After x breaks the line becomes invisible
Value:
value:
• SMA, upper/lower: the breaks are triggered on the moving average itself
• Fibonacci Pivot Point levels, Previous High, Previous Low: only last HTF values can be used for breaks
• Swings (see SWING SETTINGS)
line:
• SMA, upper/lower: the breaks are triggered on the entire line, based on its latest value
• Fibonacci Pivot Point Levels, Previous High, Previous Low: breaks are triggered on the entire line, based on its latest value
• Swings (see SWING SETTINGS)
🔹 Swing Settings
Swings are always calculated at current timeframe, setting a HTF is not applicable on Swings.
Left/Right: for Swing calculation ( pivothigh , pivotlow )
Show: enables you to see the pivot points
🔹 Set
N°: The concerning number
TYPE:
• SMA (Simple Moving Average)
• Previous High/Low
• Upper/Lower ( Bollinger Bands )
• Pivot Point levels : "Fibonacci"
LENGTH: sets the 'Number of bars', needed for calculations (applicable for SMA, upper/lower)
MULT: sets the 'Standard deviation factor' (only applicable for upper/lower - BB)
HTF: sets 'Higher Time Frame' (applicable for SMA, upper/lower, Previous High/Low, Fibonacci)
🔹 Show Values
You can make up to 5 values visible (if you want to check/verify), except for Swings (see SWING SETTINGS)
To do so, enable (A -> E), and choose the N° you want to see.
This also is a useful tool if you're not sure which value you want to set.
SMT Divergences [LuxAlgo]The SMT Divergences indicator highlights SMT divergences between the chart symbol and two user-selected tickers (ES and YM by default).
A dashboard returning the SMT divergences statistics is also provided within the settings.
🔶 SETTINGS
Swing Lookback: Calculation window used to detect swing points.
Comparison Ticker: If enabled, will detect SMT divergences between the chart prices and the prices of the selected ticker.
🔹 Dashboard
Show Dashboard: Displays statistics dashboard on the chart.
Location: Location of the dashboard on the chart.
Size: Size of the displayed dashboard.
🔶 USAGE
SMT Divergences are characterized by diverging swing points between two securities.
The detection of SMT Divergences is performed by detecting swing points using the user chart prices as well as the prices of the selected external tickers. If a swing point on the chart ticker is detected at the same time on external tickers, comparison is performed.
Due to the detection requiring swing point confirmation (3 candles by default), this indicator can better be used to study price behaviors on the occurrence of an SMT divergence.
The dashboard highlights the number of SMT divergences that occurred on a swing high and swing low between the chart ticker and the selected external tickers.
The returned percentage indicates the proportion of swing highs or swing lows that led to an SMT divergence.
Volume Profile Regression Channel [LuxAlgo]The Volume Profile Regression Channel calculates a volume profile from an anchored linear regression channel. Users can choose the starting and ending points for the indicator calculation interval.
Like a regular volume profile, a "line" of control (LOC), value area, and a developing LOC are displayed.
🔶 SETTINGS
Sections: The number of sections the linear regression channel is divided into for the calculation of the volume profile.
Width %: Determines the length of the profile within the channel relative to the channel length.
Value Area %: Highlights the sections starting from the POC whose accumulated volume is equal to the user-defined percentage of the total profile sections volume.
🔶 USAGES
Regular volume profiles are often constructed from a horizontal price area, this can allow highlighting price areas where most trading activity takes place.
However, when price is strongly trending a classical volume profile can sometimes be more uniform. This is where using an angled volume profile can be useful.
The line of control allows highlighting the section of the channel with the most accumulated volume, this line can be used as a potential future support/resistance. This is where an angled volume profile might be the most useful.
The developing LOC highlights the LOC location at a specific time within the profile (from left to right) and can sometimes provide an estimate of the underlying trend in the price.
🔶 DETAILS
To be computed the script requires a left and right chart time coordinates. When adding the script to their charts users can determine the left and right time coordinates by clicking on the chart.
The linear regression channel width is determined so that the channel precisely encompasses the whole price.
🔶 LIMITATIONS
Using a very large calculation interval can return timeouts. Users can reduce the calculation interval to fix that issue from occurring.
The amount of drawing objects that can be used is limited, as such using a high calculation interval can display an incomplete profile.
🔶 ACKNOWLEDGEMENTS
If you are interested in these types of scripts, @HeWhoMustNotBeNamed published a similar script where users can use a custom line angle. See his 'Angled Volume Profile' script from March 2023.
EquiVolume [LuxAlgo]EquiVolume is a charting method that aims to incorporate volume information to a candlestick chart. Volume is highlighted through the candle body width, with wider candles suggesting more significant volume.
Our script shows an EquiVolume chart for the visible chart range. Additionally regular volume can be plotted as a column plot with the column's width controlled by volume.
🔶 SETTINGS
🔹 Options
Chart: Shows candles with volume adjusted width.
Volume: Shows volume with volume adjusted width.
🔹 Intrabar Analysis
Enable/disable: When LTF is enabled, the script will calculate the % volume/candles in the same direction than current timeframe.
You can choose a LTF between 1 and 240 minutes.
Type %:
- Volume: sum of volume of all LTF candles, which are in the same direction.
- #bars: sum of all LTF candles, which are in the same direction.
🔹 Width Boxes (bars)
Minimum width: sets the minimum width of a box (candle/volume)
Maximum width: sets the maximum width of a box (candle/volume)
🔶 USAGE
This charting method makes it easier to spot large volume candles, against comparing candles to volume.
Another example:
Additionally, users can make the script perform an intrabar analysis on the chart candles, allowing to highlight bullish/bearish activity within a candle. The script can estimate bullish/bearish trading activity within a candle or simply use intrabar candle signs.
Example
- 15-minute candle is green
- 10 1-minute candles (LTF) IN that 15-minute candle are green -> 10/15 = 66,667%
-> The current 15-minute candle will be 66,667% filled with green color.
Note that the script will draw everything from last visible bar at the right to left, as such you can scroll backwards, and the script will show you the data of the visible chart.
Scrolling back will return the following result:
🔶 REMARKS
When the LTF is too far apart from current timeframe, you should get an error. To prevent this, the LTF will automatically rise, giving no error.
When this happens, the adjusted LTF will be displayed. Do note, due to a maximum available LTF data, sometimes boxes won't always be visible (since there is no LTF data anymore)
To solve this, just elevate your LTF:
When the set LTF is higher than current TF, you would normally get an error as well.
This script will automatically adjust the LTF to current TF, together with a visible warning (no error though).
Due to the inability to draw a line in the space between bars, sometimes a wick won't be placed exactly in the middle.
FVG Sessions [LuxAlgo]The FVG Sessions indicator highlights the first fair value gap of the trading session as well as the session range. Detected fair value gaps extend to the end of the trading session.
Alerts are included on the formation of a session fair value gap, price being within a session fair value gap, mitigations, and price crossing session fair value gaps average.
🔶 USAGE
Trader ICT states that the first fair value gap of the trading session can attract the most significant reaction. Having only one FVG per session allows users to further focus on that precise imbalance as well as external elements.
The mitigation of a fair value gap is clearly indicated on the chart with a more transparent color allowing users to see inverse FVGs.
Extending the fair value gaps allows the imbalance area to provide potential support and resistance.
Do note that this script should be used on intraday charts.
🔶 ALERTS
The script includes the following alerts:
🔹 Bullish/Bearish FVG
Alerts on the formation of the first bullish or bearish FVG of the session.
🔹 Bullish/Bearish FVG Mitigation
Alerts when the first bullish or bearish FVG of the session is mitigated.
🔹 Price Within FVG
Alerts when price is within the first bullish or bearish FVG area of the session.
🔹 Price Cross FVG Average
Alerts when price cross the average level of the first bullish or bearish FVG of the session.
Volume Profile Matrix [LuxAlgo]The Volume Profile Matrix indicator extends from regular volume profiles by also considering calculation intervals within the calculation window rather than only dividing the calculation window in rows.
Note that this indicator is subject to repainting & back-painting, however, treating the indicator as a tool for identifying frequent points of interest can still be very useful.
🔶 SETTINGS
Lookback: Number of most recent bars used to calculate the indicator.
Columns: Number of columns (intervals) used to calculate the volume profile matrix.
Rows: Number of rows (intervals) used to calculate the volume profile matrix.
🔶 USAGE
The Volume Profile Matrix indicator can be used to obtain more information regarding liquidity on specific time intervals. Instead of simply dividing the calculation window into equidistant rows, the calculation is done through a grid.
Grid cells with trading activity occurring inside them are colored. More activity is highlighted through a gradient and by default, cells with a color that are closer to red indicate that more trading activity took place within that cell. The cell with the highest amount of trading activity is always highlighted in yellow.
Each interval (column) includes a point of control which highlights an estimate of the price level with the highest traded volume on that interval. The level with the highest traded volume of the overall grid is extended to the most recent bar.
Range Sentiment Profile [LuxAlgo]The Range Sentiment Profile indicator is inspired from the volume profile and aims to indicate the degree of bullish/bearish variations within equidistant price areas inside the most recent price range.
The most bullish/bearish price areas are highlighted through lines extending over the entire range.
🔶 SETTINGS
Length: Most recent bars used for the calculation of the indicator.
Rows: Number of price areas the price range is divided into.
Use Intrabar: Use intrabar data to compute the range sentiment profile.
Timeframe: Intrabar data timeframe.
🔶 USAGE
This tool can be used to easily determine if a certain price area contain more significant bullish or bearish price variations. This is done by obtaining an estimate of the accumulation of all the close to open variations occurring within a specific profile area.
A blue range background indicates a majority of bullish variations within each area while an orange background indicates a majority of bearish variations within each area.
Users can easily identify the areas with the most bullish/bearish price variations by looking at the bullish/bearish maximums.
It can be of interest to see where profile bins might have no length, these can indicate price areas with price variations with alternating signs (bullish variations are followed by a bearish sign) and similar body. They can also indicate a majority of either bullish or bearish variations alongside a minority of more significant opposite variations.
These areas can also provide support/resistance, as such price entering these areas could reverse.
Users can obtain more precise results by allowing the profile to use intrabar data. This will change the calculation of the profile, see the details section for more information.
🔶 DETAILS
The Range Sentiment Profile's design is similar to the way a volume profile is constructed.
First the maximum/minimum values over the most recent Length bars are obtained, these define the calculation range of the profile.
The range is divided into Rows equidistant areas. We then see if price lied within a specific area, if it's the case we accumulate the difference between the closing and opening price for that specific area.
Let d = close - open . The length of the bin associated to a specific area is determined as follows:
length = Width / 100 * Area / Max
Where Area is the accumulated d within the area, and Max the maximum value between the absolute value of each accumulated d of all areas.
The percentage visible on each bin is determined as 100 multiplied by the accumulated d within the area divided by the total absolute value of d over the entire range.
🔹 Intrabar Calculation
When using intrabar data the range sentiment profile is calculated differently.
For a specific area and candle within the interval, the accumulated close to open difference is accumulated only if the intrabar candle of the user selected timeframe lies within the area.
This can return more precise results compared to the standard method, at the cost of a higher computation time.
Volume Forecasting [LuxAlgo]The Volume Forecasting indicator provides a forecast of volume by capturing and extrapolating periodic fluctuations. Historical forecasts are also provided to compare the method against volume at time t .
This script will not work on tickers that do not have volume data.
🔶 SETTINGS
Median Memory: Number of days used to compute the median and first/third quartiles.
Forecast Window: Number of bars forecasted in the future.
Auto Forecast Window: Set the forecast window so that the forecast length completes an interval.
🔶 USAGE
The periodic nature of volume on certain securities allows users to more easily forecast using historical volume. The forecast can highlight intervals where volume tends to be more important, that is where most trading activity takes place.
More pronounced periodicity will tend to return more accurate forecasts.
The historical forecast can also highlight intervals where high/low volume is not expected.
The interquartile range is also highlighted, giving an area where we can expect the volume to lie.
🔶 DETAILS
This forecasting method is similar to the time series decomposition method used to obtain the seasonal component.
We first segment the chart over equidistant intervals. Each interval is delimited by a change in the daily timeframe.
To forecast volume at time t+1 we see where the current bar lies in the interval, if the bar is the 78th in interval then the forecast on the next bar is made by taking the median of the 79th bar over N intervals, where N is the median memory.
This method ensures capturing the periodic fluctuation of volume.
Market Structure Trailing Stop [LuxAlgo]This script returns trailing stops on the occurrence of market structure (CHoCH/BOS labeling). Trailing stops are adjusted based on trailing maximums/minimums with the option for users to be able to control how quickly a trailing stop can converge toward the price.
🔶 SETTINGS
Pivot Lookback: Pivot length used for the detection of swing points.
Increment Factor %: Controls how fast trailing stops converge toward the price, with lower values returning slower converging trailing stops.
Reset Stop On: Determines if trailing stops are reset on CHoCH structure or all (CHoCH + BOS).
Show Structure: Determines if market structure is displayed.
🔶 USAGE
Trailing stops allow traders to protect them against downside risk while also guaranteeing a potential profit in case the market goes in the expected direction of the trade.
Users making use of market structure as a primary entry condition can benefit from having trailing stops based on these to either provide an additional exit condition or to provide points of support/resistance with the price.
Trailing stops can avoid being hit more frequently by using a lower Increment Factor % setting.
Finally, users can reset the trailing stop when any market structure is detected (or only on CHoCHs). Allowing trailing stops to reset on the detection of any market structure allows the indicator to return trailing stops closer to the price. CHoCH labels are highlighted as dashed lines while BOS labels are highlighted as dotted lines.
🔶 DETAILS
When a new structure (or only CHoCH if specified by the user) is detected, trailing stops will initially be set based on the maximum/minimum made on the previous trend. This will also set the trailing maximum/minimum to the current price value.
If an uptrend is detected (most recent market structure is bullish) then the trailing stop will increase if the trailing maximum increase, the increment is calculated as:
trailing stop = trailing stop + Increment Factor % of (trailing maximum - previous trailing maximum)
If a downtrend is detected (most recent market structure is bearish) then the trailing stop will decrease if the trailing minimum decrease, the decrement is calculated as:
trailing stop = trailing stop + Increment Factor % of (trailing minimum - previous trailing minimum)
ICT NWOG/NDOG & EHPDA [LuxAlgo]This indicator displays New Week/Day Opening Gaps alongside Event Horizon PD Arrays which were conceptualized by a trader, ICT.
🔶 SETTINGS
Show: Determines if new week opening gaps (NWOG) or new day opening gaps (NDOG) are shown.
Amount: Controls the amount of most recent NWOGs/NDOGs to display on the chart.
Show EHPDA: Displays Event Horizons PD arrays.
🔶 USAGE
New Week/Day Opening Gaps are generally used as potential support or resistance areas.
Trader ICT describes that under consolidating market conditions, price tends to revert towards the opening gap area. This is consistent with other analysis suggesting that price has a tendency to come back toward gaps, ultimately looking to fill them.
ICT also introduces a novel concept, the "Event Horizon PD Array" (EHPDA) which are intermediary levels constructed from the average between the neighboring NWOGs or NDOGs.
EHPDA's are described by ICT as levels that "will not allow price to escape to the NWOG that will create a surge towards the NWOG it got too "close" to but has not yet reached."
Order Blocks & Breaker Blocks [LuxAlgo]The Order Blocks & Breaker Blocks indicator detects order blocks that can be turned into breaker blocks on the chart automatically once mitigated.
Users can determine the amount of bullish and bearish order/breaker blocks that display on their chart from within the settings menu.
🔶 SETTINGS
Swing Lookback: Lookback period used for the detection of the swing points used to create order blocks.
Show Last Bullish OB: Number of the most recent bullish order/breaker blocks to display on the chart.
Show Last Bearish OB: Number of the most recent bearish order/breaker blocks to display on the chart.
Use Candle Body: Allows users to use candle bodies as order block areas instead of the full candle range.
🔹 Style
Show Historical Polarity Changes: Allows users to see labels indicating where a swing high/low previously occurred within a breaker block.
🔶 USAGE
We have published several scripts covering the detection of order blocks previously, however, the concept of breaker blocks was not yet introduced.
When price mitigates an order block, a breaker block is confirmed. We can eventually expect price to trade back to this breaker block offering a new trade opportunity.
We can see that this is similar to a change in polarity, where a support becomes a resistance after a breakout and vice versa.
This script highlights regular order blocks as solid extended areas on the chart and breaker blocks as dashed lines with dual-colored areas. The color change and dashed line starts at the location where the order block was mitigated.
Using a higher "Swing Lookback" setting will return longer term order/breaker blocks on the chart.
Users can optionally enable "Historical Polarity Changes" labels within the settings menu to see where breaker blocks might have provided an effective trade setup previously.
The "Historical Polarity Changes" setting is disabled by default & is most effective using replay mode as the labels are backpainted.
The order blocks & breaker blocks themselves can be used in real-time as they are detected based on the swing length & previous breaker blocks being mitigated.
