ORB Heikin Ashi SPY 5min Correlation StrategyOverview:
The ORB (Opening Range Breakout) strategy combined with Heikin Ashi candles and Relative Volume (RVOL) indicator aims to capitalize on significant price movements that occur shortly after the market opens. This strategy identifies breakouts above or below the opening range, using Heikin Ashi candles for smoother price visualization and RVOL to gauge the strength of the breakout.
Components:
Opening Range Breakout (ORB): The strategy starts by defining the opening range, typically the first few minutes of the trading session. It then identifies breakouts above the high or below the low of this range as potential entry points.
Heikin Ashi Candles: Heikin Ashi candles are used to provide a smoother representation of price movements compared to traditional candlesticks. By averaging open, close, high, and low prices of the previous candle, Heikin Ashi candles reduce noise and highlight trends more effectively.
Relative Volume (RVOL): RVOL compares the current volume of a stock to its average volume over a specified period. It helps traders identify abnormal trading activity, which can signal potential price movements.
Candle for correlation : In this case we are using SPY candles. It can also use different asset
Strategy Execution:
Initialization: The strategy initializes by setting up variables and parameters, including the ORB period, session timings, and Heikin Ashi candle settings.
ORB Calculation: It calculates the opening range by identifying the high and low prices during the specified session time. These values serve as the initial reference points for potential breakouts. For this we are looking for the first 30 min of the US opening session.
After that we are going to use the next 2 hours to check for breakout opportunities.
Heikin Ashi Transformation: Optionally, the strategy transforms traditional candlestick data into Heikin Ashi format for smoother visualization and trend identification.
Breakout Identification: It continuously monitors price movements within the session and checks if the current high breaches the ORB high or if the current low breaches the ORB low. These events trigger potential long or short entry signals, respectively.
RVOL Analysis: Simultaneously, the strategy evaluates the relative volume of the asset to gauge the strength of the breakout. A surge in volume accompanying the breakout confirms the validity of the signal. In this case we are looking for at least a 1 value of the division between currentVolume and pastVolume
Entry and Exit Conditions: When a breakout occurs and is confirmed by RVOL and is within our session time, the strategy enters a long or short position accordingly. It does not have a stop loss or a takie profit level, instead it will always exit at the end of the trading session, 5 minutes before
Position Sizing and Commissions: For the purpose of this backtest, the strategy allocated 10% of the capital for each trade and assumes a trading commission of 0.01$ per share ( twice the IBKR broker values)
Session End: At the end of the trading session, the strategy closes all open positions to avoid overnight exposure.
Conclusion:
The combination of ORB breakout strategy, Heikin Ashi candles, and RVOL provides traders with a robust framework for identifying and capitalizing on early trends in the market. By leveraging these technical indicators together, traders can make more informed decisions and improve the overall performance of their trading strategies. However, like any trading strategy, it's essential to backtest thoroughly and adapt the strategy to different market conditions to ensure its effectiveness over time.
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Auto-magnifier / quantifytools- Overview
Auto-magnifier shows a lower timeframe view of candles and volume bars inside any main timeframe candle by zooming into it. Candles and volume bars as they develop are shown chronologically from left to right. By default, magnifier is triggered when less than 3 candles are visible on the chart.
By default, 20 lower timeframe candles are displayed by splitting main timeframe into 20 parts. The amount of candles displayed is a target rate, meaning the script will use a lower timeframe that has the closest match to 20 candles and therefore will vary a bit. Users can override automatic timeframe calculation and opt in to display any specific lower timeframe or adjust amount of candles shown (e.g. 20 -> 30 candles) per each main timeframe candle.
Example
Main timeframe set to 30 minute, candles displayed set to 20 -> Magnifying using 2 minute candles (30 minute/20 candles = 1.5 min, rounded to 2 min)
Main timeframe set to 30 minute, override set to 5 minutes -> Displaying 5 minute candles
Size of volume bars is calculated using relative volume (volume relative to volume SMA20), lowest bar representing relative volume values of under or equal to 1x the moving average and from there onwards progressively growing.
- Limitations and considerations
Amount of candles shown might flow over from the background on smaller screen sizes, in which case you would want to decrease the amount shown. Opposite is true for bigger screens, this value can be increased as more candles fit.
This indicator involves a lot of tricks with text elements to make it work automatically by zooming in. Size of wicks, bodies and volume bars are calculated by adding more text elements on big candles and less text elements on smaller candles. This means the displayed candles won't be a 100% match, but a rather a fair representation of the view, e.g. candle is green = lower timeframe candle is green, candle has a big wick = lower timeframe candle has a big wick (but not a 100% match).
Example
Magnified lower timeframe chart vs. Actual lower timeframe chart
Most mismatch will be found on the price levels where lower timeframe candles are shown, which is sacrificed for the sake of getting a better readability on the overall shape of lower timeframe price action. Users can alternatively optimize calculations for more accuracy, giving a better representation of the price levels where candles truly originated. This typically comes with the cost of worse readability however.
Example
Optimized for readability vs. Optimized for accuracy
- Visuals
All visual elements are fully customizable.
Fair value bands / quantifytools— Overview
Fair value bands, like other band tools, depict dynamic points in price where price behaviour is normal or abnormal, i.e. trading at/around mean (price at fair value) or deviating from mean (price outside fair value). Unlike constantly readjusting standard deviation based bands, fair value bands are designed to be smooth and constant, based on typical historical deviations. The script calculates pivots that take place above/below fair value basis and forms median deviation bands based on this information. These points are then multiplied up to 3, representing more extreme deviations.
By default, the script uses OHLC4 and SMA 20 as basis for the bands. Users can form their preferred fair value basis using following options:
Price source
- Standard OHLC values
- HL2 (High + low / 2)
- OHLC4 (Open + high + low + close / 4)
- HLC3 (High + low + close / 3)
- HLCC4 (High + low + close + close / 4)
Smoothing
- SMA
- EMA
- HMA
- RMA
- WMA
- VWMA
- Median
Once fair value basis is established, some additional customization options can be employed:
Trend mode
Direction based
Cross based
Trend modes affect fair value basis color that indicates trend direction. Direction based trend considers only the direction of the defined fair value basis, i.e. pointing up is considered an uptrend, vice versa for downtrend. Cross based trends activate when selected source (same options as price source) crosses fair value basis. These sources can be set individually for uptrend/downtrend cross conditions. By default, the script uses cross based trend mode with low and high as sources.
Cross based (downtrend not triggered) vs. direction based (downtrend triggered):
Threshold band
Threshold band is calculated using typical deviations when price is trading at fair value basis. In other words, a little bit of "wiggle room" is added around the mean based on expected deviation. This feature is useful for cross based trends, as it allows filtering insignificant crosses that are more likely just noise. By default, threshold band is calculated based on 1x median deviation from mean. Users can increase/decrease threshold band width via input menu for more/less noise filtering, e.g. 2x threshold band width would require price to cross wiggle room that is 2x wider than typical, 0x erases threshold band altogether.
Deviation bands
Width of deviation bands by default is based on 1x median deviations and can be increased/decreased in a similar manner to threshold bands.
Each combination of customization options produces varying behaviour in the bands. To measure the behaviour and finding fairest representation of fair and unfair value, some data is gathered.
— Fair value metrics
Space between each band is considered a lot, named +3, +2, +1, -1, -2, -3. For each lot, time spent and volume relative to volume moving average (SMA 20) is recorded each time price is trading in a given lot:
Depending on the asset, timeframe and chosen fair value basis, shape of the distributions vary. However, practically always time is distributed in a normal bell curve shape, being highest at lots +1 to -1, gradually decreasing the further price is from the mean. This is hardly surprising, but it allows accurately determining dynamic areas of normal and abnormal price behaviour (i.e. low risk area between +1 and -1, high risk area between +-2 to +-3). Volume on the other hand is typically distributed the other way around, being lowest at lots +1 to -1 and highest at +-2 to +-3. When time and volume are distributed like so, we can conclude that 1) price being outside fair value is a rare event and 2) the more price is outside fair value, the more anomaly behaviour in volume we tend to find.
Viewing metric calculations
Metric calculation highlights can be enabled from the input menu, resulting in a lot based coloring and visibility of each lot counter (time, cumulative relative volume and average relative volume) in data window:
— Alerts
Available alerts are the following:
Individual
- High crossing deviation band (bands +1 to +3 )
- Low crossing deviation band (bands -1 to -3 )
- Low at threshold band in an uptrend
- High at threshold band in a downtrend
- New uptrend
- New downtrend
Grouped
- New uptrend or downtrend
- Deviation band cross (+1 or -1)
- Deviation band cross (+2 or -2)
- Deviation band cross (+3 or -3)
— Practical guide
Example #1 : Risk on/risk off trend following
Ideal trend stays inside fair value and provides sufficient cool offs between the moves. When this is the case, fair value bands can be used for sensible entry/exit levels within the trend.
Example #2 : Mean reversions
When price shows exuberance into an extreme deviation, followed by a stall and signs of exhaustion (wicks), an opportunity for mean reversion emerges. The higher the deviation, the more volatility in the move, the more signalling of exhaustion, the better.
Example #3 : Tweaking bands for desired behaviour
The faster the length of fair value basis, the more momentum price needs to hit extreme deviation levels, as bands too are moving faster alongside price. Decreasing fair value basis length typically leads to more quick and aggressive deviations and less steady trends outside fair value.
[blackcat] L1 Relative Strength Volume-Adjusted EMALevel 1
Background
Vitali Apirine proposed an idea of “Relative Strength Moving Averages, Part 2 (RS VA EMA)” on October 2022.
Function
Based on my understanding, Vitali combines the merits of RSI, volume and EMA to improve moving average performance. It takes the relative volume strength into account and includes a measurement between positive and negative volume flow in the calculation, which gives direction to the volume input. In details, volume is considered positive when the close is higher than the previous close and negative when the close is lower than the previous close. I used 2 period lagged signal as trigger so that the pair fast and slow lines can form golden cross and dead cross where entry signal can be produced.
Remarks
Feedbacks are appreciated.
Daily Volume, RVol, RRVol, and RS/RW LabelsHeads-up display of essential Real Day Trading criteria
Daily Volume
Relative Strength/Weakness
ATR 14 and ATR 14 percent of price
Relative Volume (RVol)
Relative Volume to SPY RVol (RRVol)
RSI true swingsRelative Strength Index (RSI) is being used by majority of the traders to get benefitted based on the swings. But these swings are hard to Identify.
This Indicator uses 4 major factors for finding the potential reversal points:
RSI Crossover or crossunder
Relative volume
Overall volume against the moving average volume
Relative closing of the candles
Size of the bars
Please read Instructions carefully before using this indicator
Recommended entry is the OHLC4 of the signal bars.
If signal bar is too large, try to enter in the retracement when another signal comes either through indicator or through types of bars
when signals comes opposite to the trend, then try to wait for the next signal of same type. This creates a RSI-price divergence in confirmation by volume price action
Timeframe can be of your choice
Recommended stoploss should be swing highs or lows
Relative VolatilityRelative volatility highlights large changes in price. This was designed to be used with my relative volume indicator so that traders can see the effect of volume on price action. It is also a good tool to analyse breakout patterns to identify best entry points and waves.
Above shows relative volatility and relative volume working together.
MACD, RSI, & RVOL Strategy
This strategy combines the use of MACD (12, 26, 9), RSI (14, 30, 70), and RVOL (14) to create Long Buy and Sell signals. This works well with many different time intervals but was developed with 15-minute intervals in mind.
Using MACD as a reference, the strategy identifies when the MACD line crosses over (a factor in a buy signal) and under (a factor in a Sell signal) the Signal line. This shows a shift in positive (cross over) and negative (cross under) of a security.
Using the Relative Strength Index ( RSI ) as an indicator, the strategy notices when the velocity and magnitude of the directional price movements cross over the Oversold signal (30) and crosses under the Overbought signal (70) as a factor in creating a Buy and Sell signal.
Using Relative Volume (RVOL) as an indicator, the strategy calculates when the current volume has crossed over the 2x average volume indicator over a given period and is then used as a factor in creating a Buy signal. RVOL is also used when the change in volume crosses under a set RVOL number (in this strategy, it is set to a RVOL of 5).
RVOL = Current Volume / Average Volume over a certain period
This strategy indicates a Buy signal when 2/3 conditions are met:
- RSI Cross Over the Over Sold signal (default 30)
- MACD Cross Over of Signal ( MACD > Signal)
- RVOL Cross Over of 2 (RVOL > 2)
This strategy indicates a Sell signal when 2/3 conditions are met:
- RSI Cross Under the Over Bought signal (default 70)
- MACD Cross Under of Signal ( MACD < Signal)
- RVOL Cross Under 5 (RVOL < 5)
Enjoy and leave feedback!
`security()` revisited [PineCoders]NOTE
The non-repainting technique in this publication that relies on bar states is now deprecated, as we have identified inconsistencies that undermine its credibility as a universal solution. The outputs that use the technique are still available for reference in this publication. However, we do not endorse its usage. See this publication for more information about the current best practices for requesting HTF data and why they work.
█ OVERVIEW
This script presents a new function to help coders use security() in both repainting and non-repainting modes. We revisit this often misunderstood and misused function, and explain its behavior in different contexts, in the hope of dispelling some of the coder lure surrounding it. The function is incredibly powerful, yet misused, it can become a dangerous WMD and an instrument of deception, for both coders and traders.
We will discuss:
• How to use our new `f_security()` function.
• The behavior of Pine code and security() on the three very different types of bars that make up any chart.
• Why what you see on a chart is a simulation, and should be taken with a grain of salt.
• Why we are presenting a new version of a function handling security() calls.
• Other topics of interest to coders using higher timeframe (HTF) data.
█ WARNING
We have tried to deliver a function that is simple to use and will, in non-repainting mode, produce reliable results for both experienced and novice coders. If you are a novice coder, stick to our recommendations to avoid getting into trouble, and DO NOT change our `f_security()` function when using it. Use `false` as the function's last argument and refrain from using your script at smaller timeframes than the chart's. To call our function to fetch a non-repainting value of close from the 1D timeframe, use:
f_security(_sym, _res, _src, _rep) => security(_sym, _res, _src )
previousDayClose = f_security(syminfo.tickerid, "D", close, false)
If that's all you're interested in, you are done.
If you choose to ignore our recommendation and use the function in repainting mode by changing the `false` in there for `true`, we sincerely hope you read the rest of our ramblings before you do so, to understand the consequences of your choice.
Let's now have a look at what security() is showing you. There is a lot to cover, so buckle up! But before we dig in, one last thing.
What is a chart?
A chart is a graphic representation of events that occur in markets. As any representation, it is not reality, but rather a model of reality. As Scott Page eloquently states in The Model Thinker : "All models are wrong; many are useful". Having in mind that both chart bars and plots on our charts are imperfect and incomplete renderings of what actually occurred in realtime markets puts us coders in a place from where we can better understand the nature of, and the causes underlying the inevitable compromises necessary to build the data series our code uses, and print chart bars.
Traders or coders complaining that charts do not reflect reality act like someone who would complain that the word "dog" is not a real dog. Let's recognize that we are dealing with models here, and try to understand them the best we can. Sure, models can be improved; TradingView is constantly improving the quality of the information displayed on charts, but charts nevertheless remain mere translations. Plots of data fetched through security() being modelized renderings of what occurs at higher timeframes, coders will build more useful and reliable tools for both themselves and traders if they endeavor to perfect their understanding of the abstractions they are working with. We hope this publication helps you in this pursuit.
█ FEATURES
This script's "Inputs" tab has four settings:
• Repaint : Determines whether the functions will use their repainting or non-repainting mode.
Note that the setting will not affect the behavior of the yellow plot, as it always repaints.
• Source : The source fetched by the security() calls.
• Timeframe : The timeframe used for the security() calls. If it is lower than the chart's timeframe, a warning appears.
• Show timeframe reminder : Displays a reminder of the timeframe after the last bar.
█ THE CHART
The chart shows two different pieces of information and we want to discuss other topics in this section, so we will be covering:
A — The type of chart bars we are looking at, indicated by the colored band at the top.
B — The plots resulting of calling security() with the close price in different ways.
C — Points of interest on the chart.
A — Chart bars
The colored band at the top shows the three types of bars that any chart on a live market will print. It is critical for coders to understand the important distinctions between each type of bar:
1 — Gray : Historical bars, which are bars that were already closed when the script was run on them.
2 — Red : Elapsed realtime bars, i.e., realtime bars that have run their course and closed.
The state of script calculations showing on those bars is that of the last time they were made, when the realtime bar closed.
3 — Green : The realtime bar. Only the rightmost bar on the chart can be the realtime bar at any given time, and only when the chart's market is active.
Refer to the Pine User Manual's Execution model page for a more detailed explanation of these types of bars.
B — Plots
The chart shows the result of letting our 5sec chart run for a few minutes with the following settings: "Repaint" = "On" (the default is "Off"), "Source" = `close` and "Timeframe" = 1min. The five lines plotted are the following. They have progressively thinner widths:
1 — Yellow : A normal, repainting security() call.
2 — Silver : Our recommended security() function.
3 — Fuchsia : Our recommended way of achieving the same result as our security() function, for cases when the source used is a function returning a tuple.
4 — White : The method we previously recommended in our MTF Selection Framework , which uses two distinct security() calls.
5 — Black : A lame attempt at fooling traders that MUST be avoided.
All lines except the first one in yellow will vary depending on the "Repaint" setting in the script's inputs. The first plot does not change because, contrary to all other plots, it contains no conditional code to adapt to repainting/no-repainting modes; it is a simple security() call showing its default behavior.
C — Points of interest on the chart
Historical bars do not show actual repainting behavior
To appreciate what a repainting security() call will plot in realtime, one must look at the realtime bar and at elapsed realtime bars, the bars where the top line is green or red on the chart at the top of this page. There you can see how the plots go up and down, following the close value of each successive chart bar making up a single bar of the higher timeframe. You would see the same behavior in "Replay" mode. In the realtime bar, the movement of repainting plots will vary with the source you are fetching: open will not move after a new timeframe opens, low and high will change when a new low or high are found, close will follow the last feed update. If you are fetching a value calculated by a function, it may also change on each update.
Now notice how different the plots are on historical bars. There, the plot shows the close of the previously completed timeframe for the whole duration of the current timeframe, until on its last bar the price updates to the current timeframe's close when it is confirmed (if the timeframe's last bar is missing, the plot will only update on the next timeframe's first bar). That last bar is the only one showing where the plot would end if that timeframe's bars had elapsed in realtime. If one doesn't understand this, one cannot properly visualize how his script will calculate in realtime when using repainting. Additionally, as published scripts typically show charts where the script has only run on historical bars, they are, in fact, misleading traders who will naturally assume the script will behave the same way on realtime bars.
Non-repainting plots are more accurate on historical bars
Now consider this chart, where we are using the same settings as on the chart used to publish this script, except that we have turned "Repainting" off this time:
The yellow line here is our reference, repainting line, so although repainting is turned off, it is still repainting, as expected. Because repainting is now off, however, plots on historical bars show the previous timeframe's close until the first bar of a new timeframe, at which point the plot updates. This correctly reflects the behavior of the script in the realtime bar, where because we are offsetting the series by one, we are always showing the previously calculated—and thus confirmed—higher timeframe value. This means that in realtime, we will only get the previous timeframe's values one bar after the timeframe's last bar has elapsed, at the open of the first bar of a new timeframe. Historical and elapsed realtime bars will not actually show this nuance because they reflect the state of calculations made on their close , but we can see the plot update on that bar nonetheless.
► This more accurate representation on historical bars of what will happen in the realtime bar is one of the two key reasons why using non-repainting data is preferable.
The other is that in realtime, your script will be using more reliable data and behave more consistently.
Misleading plots
Valiant attempts by coders to show non-repainting, higher timeframe data updating earlier than on our chart are futile. If updates occur one bar earlier because coders use the repainting version of the function, then so be it, but they must then also accept that their historical bars are not displaying information that is as accurate. Not informing script users of this is to mislead them. Coders should also be aware that if they choose to use repainting data in realtime, they are sacrificing reliability to speed and may be running a strategy that behaves very differently from the one they backtested, thus invalidating their tests.
When, however, coders make what are supposed to be non-repainting plots plot artificially early on historical bars, as in examples "c4" and "c5" of our script, they would want us to believe they have achieved the miracle of time travel. Our understanding of the current state of science dictates that for now, this is impossible. Using such techniques in scripts is plainly misleading, and public scripts using them will be moderated. We are coding trading tools here—not video games. Elementary ethics prescribe that we should not mislead traders, even if it means not being able to show sexy plots. As the great Feynman said: You should not fool the layman when you're talking as a scientist.
You can readily appreciate the fantasy plot of "c4", the thinnest line in black, by comparing its supposedly non-repainting behavior between historical bars and realtime bars. After updating—by miracle—as early as the wide yellow line that is repainting, it suddenly moves in a more realistic place when the script is running in realtime, in synch with our non-repainting lines. The "c5" version does not plot on the chart, but it displays in the Data Window. It is even worse than "c4" in that it also updates magically early on historical bars, but goes on to evaluate like the repainting yellow line in realtime, except one bar late.
Data Window
The Data Window shows the values of the chart's plots, then the values of both the inside and outside offsets used in our calculations, so you can see them change bar by bar. Notice their differences between historical and elapsed realtime bars, and the realtime bar itself. If you do not know about the Data Window, have a look at this essential tool for Pine coders in the Pine User Manual's page on Debugging . The conditional expressions used to calculate the offsets may seem tortuous but their objective is quite simple. When repainting is on, we use this form, so with no offset on all bars:
security(ticker, i_timeframe, i_source )
// which is equivalent to:
security(ticker, i_timeframe, i_source)
When repainting is off, we use two different and inverted offsets on historical bars and the realtime bar:
// Historical bars:
security(ticker, i_timeframe, i_source )
// Realtime bar (and thus, elapsed realtime bars):
security(ticker, i_timeframe, i_source )
The offsets in the first line show how we prevent repainting on historical bars without the need for the `lookahead` parameter. We use the value of the function call on the chart's previous bar. Since values between the repainting and non-repainting versions only differ on the timeframe's last bar, we can use the previous value so that the update only occurs on the timeframe's first bar, as it will in realtime when not repainting.
In the realtime bar, we use the second call, where the offsets are inverted. This is because if we used the first call in realtime, we would be fetching the value of the repainting function on the previous bar, so the close of the last bar. What we want, instead, is the data from the previous, higher timeframe bar , which has elapsed and is confirmed, and thus will not change throughout realtime bars, except on the first constituent chart bar belonging to a new higher timeframe.
After the offsets, the Data Window shows values for the `barstate.*` variables we use in our calculations.
█ NOTES
Why are we revisiting security() ?
For four reasons:
1 — We were seeing coders misuse our `f_secureSecurity()` function presented in How to avoid repainting when using security() .
Some novice coders were modifying the offset used with the history-referencing operator in the function, making it zero instead of one,
which to our horror, caused look-ahead bias when used with `lookahead = barmerge.lookahead_on`.
We wanted to present a safer function which avoids introducing the dreaded "lookahead" in the scripts of unsuspecting coders.
2 — The popularity of security() in screener-type scripts where coders need to use the full 40 calls allowed per script made us want to propose
a solid method of allowing coders to offer a repainting/no-repainting choice to their script users with only one security() call.
3 — We wanted to explain why some alternatives we see circulating are inadequate and produce misleading behavior.
4 — Our previous publication on security() focused on how to avoid repainting, yet many other considerations worthy of attention are not related to repainting.
Handling tuples
When sending function calls that return tuples with security() , our `f_security()` function will not work because Pine does not allow us to use the history-referencing operator with tuple return values. The solution is to integrate the inside offset to your function's arguments, use it to offset the results the function is returning, and then add the outside offset in a reassignment of the tuple variables, after security() returns its values to the script, as we do in our "c2" example.
Does it repaint?
We're pretty sure Wilder was not asked very often if RSI repainted. Why? Because it wasn't in fashion—and largely unnecessary—to ask that sort of question in the 80's. Many traders back then used daily charts only, and indicator values were calculated at the day's close, so everybody knew what they were getting. Additionally, indicator values were calculated by generally reputable outfits or traders themselves, so data was pretty reliable. Today, almost anybody can write a simple indicator, and the programming languages used to write them are complex enough for some coders lacking the caution, know-how or ethics of the best professional coders, to get in over their heads and produce code that does not work the way they think it does.
As we hope to have clearly demonstrated, traders do have legitimate cause to ask if MTF scripts repaint or not when authors do not specify it in their script's description.
► We recommend that authors always use our `f_security()` with `false` as the last argument to avoid repainting when fetching data dependent on OHLCV information. This is the only way to obtain reliable HTF data. If you want to offer users a choice, make non-repainting mode the default, so that if users choose repainting, it will be their responsibility. Non-repainting security() calls are also the only way for scripts to show historical behavior that matches the script's realtime behavior, so you are not misleading traders. Additionally, non-repainting HTF data is the only way that non-repainting alerts can be configured on MTF scripts, as users of MTF scripts cannot prevent their alerts from repainting by simply configuring them to trigger on the bar's close.
Data feeds
A chart at one timeframe is made up of multiple feeds that mesh seamlessly to form one chart. Historical bars can use one feed, and the realtime bar another, which brokers/exchanges can sometimes update retroactively so that elapsed realtime bars will reappear with very slight modifications when the browser's tab is refreshed. Intraday and daily chart prices also very often originate from different feeds supplied by brokers/exchanges. That is why security() calls at higher timeframes may be using a completely different feed than the chart, and explains why the daily high value, for example, can vary between timeframes. Volume information can also vary considerably between intraday and daily feeds in markets like stocks, because more volume information becomes available at the end of day. It is thus expected behavior—and not a bug—to see data variations between timeframes.
Another point to keep in mind concerning feeds it that when you are using a repainting security() plot in realtime, you will sometimes see discrepancies between its plot and the realtime bars. An artefact revealing these inconsistencies can be seen when security() plots sometimes skip a realtime chart bar during periods of high market activity. This occurs because of races between the chart and the security() feeds, which are being monitored by independent, concurrent processes. A blue arrow on the chart indicates such an occurrence. This is another cause of repainting, where realtime bar-building logic can produce different outcomes on one closing price. It is also another argument supporting our recommendation to use non-repainting data.
Alternatives
There is an alternative to using security() in some conditions. If all you need are OHLC prices of a higher timeframe, you can use a technique like the one Duyck demonstrates in his security free MTF example - JD script. It has the great advantage of displaying actual repainting values on historical bars, which mimic the code's behavior in the realtime bar—or at least on elapsed realtime bars, contrary to a repainting security() plot. It has the disadvantage of using the current chart's TF data feed prices, whereas higher timeframe data feeds may contain different and more reliable prices when they are compiled at the end of the day. In its current state, it also does not allow for a repainting/no-repainting choice.
When `lookahead` is useful
When retrieving non-price data, or in special cases, for experiments, it can be useful to use `lookahead`. One example is our Backtesting on Non-Standard Charts: Caution! script where we are fetching prices of standard chart bars from non-standard charts.
Warning users
Normal use of security() dictates that it only be used at timeframes equal to or higher than the chart's. To prevent users from inadvertently using your script in contexts where it will not produce expected behavior, it is good practice to warn them when their chart is on a higher timeframe than the one in the script's "Timeframe" field. Our `f_tfReminderAndErrorCheck()` function in this script does that. It can also print a reminder of the higher timeframe. It uses one security() call.
Intrabar timeframes
security() is not supported by TradingView when used with timeframes lower than the chart's. While it is still possible to use security() at intrabar timeframes, it then behaves differently. If no care is taken to send a function specifically written to handle the successive intrabars, security() will return the value of the last intrabar in the chart's timeframe, so the last 1H bar in the current 1D bar, if called at "60" from a "D" chart timeframe. If you are an advanced coder, see our FAQ entry on the techniques involved in processing intrabar timeframes. Using intrabar timeframes comes with important limitations, which you must understand and explain to traders if you choose to make scripts using the technique available to others. Special care should also be taken to thoroughly test this type of script. Novice coders should refrain from getting involved in this.
█ TERMINOLOGY
Timeframe
Timeframe , interval and resolution are all being used to name the concept of timeframe. We have, in the past, used "timeframe" and "resolution" more or less interchangeably. Recently, members from the Pine and PineCoders team have decided to settle on "timeframe", so from hereon we will be sticking to that term.
Multi-timeframe (MTF)
Some coders use "multi-timeframe" or "MTF" to name what are in fact "multi-period" calculations, as when they use MAs of progressively longer periods. We consider that a misleading use of "multi-timeframe", which should be reserved for code using calculations actually made from another timeframe's context and using security() , safe for scripts like Duyck's one mentioned earlier, or TradingView's Relative Volume at Time , which use a user-selected timeframe as an anchor to reset calculations. Calculations made at the chart's timeframe by varying the period of MAs or other rolling window calculations should be called "multi-period", and "MTF-anchored" could be used for scripts that reset calculations on timeframe boundaries.
Colophon
Our script was written using the PineCoders Coding Conventions for Pine .
The description was formatted using the techniques explained in the How We Write and Format Script Descriptions PineCoders publication.
Snippets were lifted from our MTF Selection Framework , then massaged to create the `f_tfReminderAndErrorCheck()` function.
█ THANKS
Thanks to apozdnyakov for his help with the innards of security() .
Thanks to bmistiaen for proofreading our description.
Look first. Then leap.
SCOTTGO - MOMO RVOL Trend Painter V2 (Elite Pro)SCOTTGO - MOMO RVOL Trend Painter V2 (Elite Pro)
This professional-grade trend-following indicator identifies high-probability "Elite" entry points by combining Relative Volume (RVOL) with strict trend alignment and momentum filters. It is designed to filter out market noise and highlight only the most significant institutional moves.
Core Features
Elite Signal Logic: Triggers only when high RVOL (default >2.0x) aligns with a confirmed trend (Price vs. VWAP & 9EMA) and positive momentum (RSI & MACD).
Dynamic Bar Coloring: Instantly paints bars Green (Bullish) or Red (Bearish) when all "Elite" criteria are met.
Smart Labeling: Labels are corner-anchored to the left of the signal bar. This prevents visual clutter and ensures labels never obstruct new price action.
Detailed Tooltips: Hover over any "Elite" flag to see a comprehensive breakdown of the specific metrics (RVOL value, Trend status, RSI, and MACD) that triggered the signal.
Key Components
RVOL Threshold: Adjustable sensitivity to volume spikes.
Trend Filter: Optional requirement for price to stay above/below VWAP and the 9EMA.
Momentum Filters: Integrated RSI and MACD confirmation to avoid "exhaustion" trades.
Visual Customization: Full control over label spacing, colors, and opacity.
How to use: Look for the ⭐ ELITE flags as confirmation for trend continuation or high-volume breakouts. Use the triangles for precise candle entry points.
Disclaimer: Technical analysis tools are for informational purposes only. Trading involves significant financial risk.
QuantCrawler 5m ORB Pro - Opening Range with Confluence FiltersThis indicator captures the 5-minute Opening Range and generates entry signals using a breakout-then-retest methodology. It includes optional confluence filters to refine entries and reduce false signals.
HOW IT WORKS
1. Captures the 5-minute Opening Range (high, low, midpoint) at your selected session open
2. Waits for price to break beyond OR high or low by your defined distance
3. After breakout, monitors for price to retest the OR midpoint
4. Signals LONG after bullish breakout + midpoint retest
5. Signals SHORT after bearish breakout + midpoint retest
6. Marks invalidated signals with (X) if price breaks through the opposite side
PRE-CONFIGURED SESSIONS
- NYSE - 9:30-9:35 ET
- CME - 8:30-8:35 CT
- London - 3:00-3:05 ET
- Asia - 7:00-7:05 PM ET
- Custom - Define your own session times and timezone
BREAKOUT DISTANCE OPTIONS
Choose between fixed points or percentage-based breakout threshold. Percentage mode automatically scales to the instrument price.
CONFLUENCE FILTERS
Optional filters to add confirmation before signals fire:
- VWAP - Long requires price above VWAP, short requires below
- EMA Slope - Confirms trend direction using 20-period EMA
- Volume - Requires relative volume above 1.5x average
- FVG - Requires a Fair Value Gap supporting trade direction
- ATR - Filters Opening Ranges that are abnormally small or large relative to ATR
When filters block a valid setup, the indicator displays a BLOCKED label so you can see what you missed and why.
STATUS BOX
Real-time display showing:
- Current trade state (Building OR, Watching, Awaiting Retest, Long/Short Active)
- OR High, Low, and Midpoint levels
- Active filters and block reasons
ALERTS
Built-in alerts for Long Entry, Short Entry, or Any Entry.
Ripster Clouds + Saty Pivot + RVOL + Trend1. Ripster EMA Clouds (local + higher timeframe)
Local timeframe (your chart TF):
Plots up to 5 EMA clouds (8/9, 5/12, 34/50, 72/89, 180/200 – configurable).
Each cloud is:
One short EMA and one long EMA.
A filled band between them.
Color logic:
Cloud is bullish when short EMA > long EMA (green/blue-ish tone).
Bearish when short EMA < long EMA (red/orange/pink tone).
You can choose:
EMA vs SMA,
Whether to show the lines,
Per-cloud toggles.
MTF Clouds:
Two higher-timeframe EMA clouds:
Cloud 1: 50/55
Cloud 2: 20/21
Computed on a higher TF (default D, but configurable).
Show as thin lines + transparent bands.
Used for:
Visual higher-TF trend,
Optional signal filter (MTF must agree for trades).
2. Saty Pivot Ribbon (time-warped EMAs)
This is basically your Saty Pivot Ribbon integrated:
Uses a “Time Warp” setting to overlay EMAs from another timeframe.
EMAs:
Fast, Pivot, Slow (defaults 8 / 21 / 34).
Clouds:
Fast cloud between fast & pivot EMAs.
Slow cloud between pivot & slow EMAs.
Bullish/bearish colors are distinct from Ripster colors.
Optional highlights:
Can highlight fast/pivot/slow lines separately.
Conviction EMAs:
13 and 48 EMAs (configurable).
When fast conviction EMA crosses over/under slow:
You get triangle arrows (bullish/bearish conviction).
Bias candles:
If enabled, candles are recolored based on:
Price vs Bias EMA,
Candle up/down/doji,
So you see bullish/bearish “bias” directly in candle colors.
3. DTR vs ATR panel (range vs average)
In a small table panel (bottom-center by default):
Computes higher-TF ATR (default 14, TF auto D/W/M, smoothing type selectable).
Measures current range (high–low) on that TF.
Displays:
DTR: X vs ATR: Y Z% (+/-Δ% vs prev)
Where:
Z% = current range / ATR * 100.
Δ% = change vs previous bar’s Z%.
Background color:
Greenish for low move (<≈70%),
Red for high move (≥≈90%),
Yellow in between,
Slightly dimmed when price is below bias EMA.
This tells you: “Is today an average, quiet, or explosive day compared to normal?”
4. SMA Divergence panel
Separate histogram & line panel:
Fast and slow SMAs (default 14 & 30).
Computes price divergence vs SMA in %:
% above/below slow SMA,
% above/below fast SMA.
Shows:
Slow SMA divergence as a semi-transparent column,
Fast SMA divergence as a solid column on top,
EMA of the slow divergence (trend line) colored:
Blue when rising,
Orange/red when falling.
Static upper/lower bands with fill, plus optional zero line.
This gives you a feel for how stretched price is vs its anchors.
5. RVOL table (relative volume)
Small 3×2 table (bottom-right by default):
Inputs:
Average length (default 50 bars),
Optionally show previous candle RVOL.
Calculates:
RVOL now = volume / avg(volume N bars) * 100,
RVOL prev,
RVOL momentum (now – prev) for data window only.
Table columns:
Candle Vol,
RVOL (Now),
RVOL (Prev).
Colors:
200% → “high RVOL” color,
100–200% → “medium RVOL” color,
<100% → “low RVOL” color,
Slightly dimmer if price is below bias EMA.
This is used both visually and optionally as a signal filter (e.g., only trade when RVOL ≥ threshold).
6. Trend Dashboard (Price + 34/50 + 5/12)
Top-right trend box with 3 rows:
Price Action row:
Uses either Bias EMA or custom EMA on close to say:
Bullish (close > trend EMA),
Bearish (close < trend EMA),
Flat.
Ripster 34/50 Cloud row:
Uses 34/50 EMAs: bullish if 34>50, bearish if 34<50.
Ripster 5/12 Cloud row:
Uses 5/12 EMAs: bullish if 5>12, bearish if 5<12.
Then it does a vote:
Counts bullish votes (Price, 34/50, 5/12),
Counts bearish votes,
Depending on mode:
Majority (2 of 3) or Strict (3 of 3).
Output:
Overall Bullish / Bearish / Sideways.
You also get an optional label on the chart like
Overall: Bullish trend with color, and an optional background tint (green/red for bull/bear).
7. VWAP + Buy/Sell Signals
VWAP is plotted as a white line.
Fast “trend” cloud mid: average of 5 & 12 EMAs.
Slow “trend” cloud mid: average of 34 & 50 EMAs.
Buy condition:
5/12 crosses above 34/50 (bullish cloud flip),
Price > VWAP,
Optional filter: MTF Cloud 1 bullish (50/55 on higher TF),
Optional filter: RVOL >= threshold.
Sell condition:
5/12 crosses below 34/50,
Price < VWAP,
Optional same filters but bearish.
When conditions are met:
Plots BUY triangle up below price (distinct teal/green tone).
Plots SELL triangle down above price (distinct magenta/orange tone).
Alert conditions are defined for:
BUY / SELL signals,
Overall Bullish / Bearish / Sideways change,
MTF Cloud 1 trend flips.
8. Data Window metrics
For easy backtesting / inspection via TradingView’s data window, it exposes:
DTR% (Current) and DTR% Momentum,
RVOL% (Now), RVOL% (Prev), RVOL% Momentum.
TL;DR – What does this script do for you?
It turns your chart into a multi-framework trend and momentum dashboard:
Ripster EMA clouds for short/medium trend & S/R.
Saty Ribbon for higher-TF pivot structure and conviction.
RVOL + DTR/ATR for context (is this a big and well-participated move?).
SMA divergence panel for overextension/stretch.
A compact trend table that tells you Price vs 34/50 vs 5/12 in one glance.
Buy/Sell markers + alerts when:
short-term Ripster trend (5/12) flips over/under medium (34/50),
price agrees with VWAP,
plus optional filters (MTF trend and / or RVOL).
Basically: it’s a trend + confirmation + context system wrapped into one indicator, with most knobs configurable in the settings.
Clean Industry DataClean Industry Data – Overview
Clean Industry Data is a utility tool designed to give traders an instant, structured view of key fundamental and volatility metrics directly on the chart. The script displays a compact, customizable information panel containing:
Industry & Sector
Market Cap and Free-Float Market Cap
Free-Float Percentage
Average Daily Rupee Volume
Relative Volume (R.Vol) based on daily volume
% from 10 / 21 / 50 EMAs (calculated on daily closes)
ADR (14-day) with threshold-based indicators
ATR (current timeframe) with colour-coded risk cues
All volume-based statistics are anchored to daily data, ensuring the values remain consistent across all timeframes. The display table supports flexible positioning, custom background/text colours, and adjustable text size.
This script is ideal for traders who want a quick, accurate snapshot of a stock’s liquidity, volatility, and broader classification — without digging through multiple menus or external sources.
Daily Pivot Breakout Strategy IndicatorTagline:
A pivot-based breakout system that identifies confirmed daily breakouts with momentum and volume filters, with precise entry timing across all timeframes.
How It Works:
This indicator detects strict pivot high breakouts on daily data, filtered by Rate of Change (ROC ≥30%) and Relative Volume (RVOL >1). It displays both the breakout confirmation signal and the next-day entry signal directly on your chart, regardless of timeframe.
Visual Signals:
Orange Pivot Line: The most recent confirmed pivot high (within 250-day lookback)
Day-0 Label (Teal): Appears on the breakout confirmation day (when price closes above daily pivot with filters met)
Entry Banner (Green): Appears on the next trading day at market open - your actual entry point
Cross-Timeframe Consistency:
Daily Chart: View the big picture - Day-0 on breakout bar, Entry on next bar
Any Timeframe: Logic remains consistent to daily pivots and data, signals adapt to show at the correct time
Built-in Alert Conditions:
5PivotBreakout_Scan (Day-0): Fires when breakout is confirmed. Use this for after-hours scanning to build watchlists of confirmed breakouts
5PivotBreakout_Strategy (Next): Fires at market open the next day. Use this to automate entries on confirmed breakouts
Typical Workflow:
Set up Day-0 alerts on your watchlist to catch breakouts as they happen
Review confirmed breakouts each evening
Set up Entry alerts on selected tickers to automate next-day execution (fires at market open)
Optional: Convert to strategy() for backtesting with custom exits (20% trail is good)
Key Features:
Strict pivot detection: No ties allowed - center must be highest point
Momentum filter: 100-day ROC ensures trending strength
Volume confirmation: 20-day RVOL validates participation
No repainting: Uses lookahead_off for realistic, tradeable signals
Customizable Inputs:
Pivot strength parameters (left/right bars)
Pivot lookback period
ROC period and minimum threshold
RVOL period
Toggle visibility of pivot line and labels
Note: This indicator is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always test thoroughly before live trading.
Opening Range Breakout with Multi-Timeframe Liquidity]═══════════════════════════════════════
OPENING RANGE BREAKOUT WITH MULTI-TIMEFRAME LIQUIDITY
═══════════════════════════════════════
A professional Opening Range Breakout (ORB) indicator enhanced with multi-timeframe liquidity detection, trading session visualization, volume analysis, and trend confirmation tools. Designed for intraday trading with comprehensive alert system.
───────────────────────────────────────
WHAT THIS INDICATOR DOES
───────────────────────────────────────
This indicator combines multiple trading concepts:
- Opening Range Breakout (ORB) - Customizable time period detection with automatic high/low identification
- Multi-Timeframe Liquidity - HTF (Higher Timeframe) and LTF (Lower Timeframe) key level detection
- Trading Sessions - Tokyo, London, New York, and Sydney session visualization
- Volume Analysis - Volume spike detection and strength measurement
- Multi-Timeframe Confirmation - Trend bias from higher timeframes
- EMA Integration - Trend filter and dynamic support/resistance
- Smart Alerts - Quality-filtered breakout notifications
───────────────────────────────────────
HOW IT WORKS
───────────────────────────────────────
OPENING RANGE BREAKOUT (ORB):
Concept:
The Opening Range is a period at the start of a trading session where price establishes an initial high and low. Breakouts beyond this range often indicate the direction of the day's trend.
Detection Method:
- Default: 15-minute opening range (configurable)
- Custom Range: Set specific session times with timezone support
- Automatically identifies ORH (Opening Range High) and ORL (Opening Range Low)
- Tracks ORB mid-point for reference
Range Establishment:
1. Session starts (or custom time begins)
2. Tracks highest high and lowest low during the period
3. Range confirmed at end of opening period
4. Levels extend throughout the session
Breakout Detection:
- Bullish Breakout: Close above ORH
- Bearish Breakout: Close below ORL
- Mid-point acts as bias indicator
Visual Display:
- Shaded box during range formation
- Horizontal lines for ORH, ORL, and mid-point
- Labels showing level values
- Color-coded fills based on selected method
Fill Color Methods:
1. Session Comparison:
- Green: Current OR mid > Previous OR mid
- Red: Current OR mid < Previous OR mid
- Gray: Equal or first session
- Shows day-over-day momentum
2. Breakout Direction (Recommended):
- Green: Price currently above ORH (bullish breakout)
- Red: Price currently below ORL (bearish breakout)
- Gray: Price inside range (no breakout)
- Real-time breakout status
MULTI-TIMEFRAME LIQUIDITY:
Two-Tier System for comprehensive level identification:
HTF (Higher Timeframe) Key Liquidity:
- Default: 4H timeframe (configurable to Daily, Weekly)
- Identifies major institutional levels
- Uses pivot detection with adjustable parameters
- Suitable for swing highs/lows where large orders rest
LTF (Lower Timeframe) Key Liquidity:
- Default: 1H timeframe (configurable)
- Provides precision entry/exit levels
- Finer granularity for intraday trading
- Captures minor swing points
Calculation Method:
- Pivot high/low detection algorithm
- Configurable left bars (lookback) and right bars (confirmation)
- Timeframe multiplier for accurate multi-timeframe detection
- Automatic level extension
Mitigation System:
- Tracks when levels are swept (broken)
- Configurable mitigation type: Wick or Close-based
- Option to remove or show mitigated levels
- Display limit prevents chart clutter
Asset-Specific Optimization:
The indicator includes quick reference settings for different assets:
- Major Forex (EUR/USD, GBP/USD): Default settings optimal
- Crypto (BTC/ETH): Left=12, Right=4, Display=7
- Gold: HTF=1D, Left=20
TRADING SESSIONS:
Four Major Sessions with Full Customization:
Tokyo Session:
- Default: 04:00-13:00 UTC+4
- Asian trading hours
- Often sets daily range
London Session:
- Default: 11:00-20:00 UTC+4
- Highest liquidity period
- Major institutional activity
New York Session:
- Default: 16:00-01:00 UTC+4
- US market hours
- High-impact news events
Sydney Session:
- Default: 01:00-10:00 UTC+4
- Earliest Asian activity
- Lower volatility
Session Features:
- Shaded background boxes
- Session name labels
- Optional open/close lines
- Session high/low tracking with colored lines
- Each session has independent color settings
- Fully customizable times and timezones
VOLUME ANALYSIS:
Volume-Based Trade Confirmation:
Volume MA:
- Configurable period (default: 20)
- Establishes average volume baseline
- Used for spike detection
Volume Spike Detection:
- Identifies when volume exceeds MA * multiplier
- Default: 1.5x average volume
- Confirms breakout strength
Volume Strength Measurement:
- Calculates current volume as percentage of average
- Shows relative volume intensity
- Used in alert quality filtering
High Volume Bars:
- Identifies bars above 50th percentile
- Additional confirmation layer
- Indicates institutional participation
MULTI-TIMEFRAME CONFIRMATION:
Trend Bias from Higher Timeframes:
HTF 1 (Trend):
- Default: 1H timeframe
- Uses EMA to determine intermediate trend
- Compares current timeframe EMA to HTF EMA
HTF 2 (Bias):
- Default: 4H timeframe
- Uses 50 EMA for longer-term bias
- Confirms overall market direction
Bias Classifications:
- Bullish Bias: HTF close > HTF 50 EMA AND Current EMA > HTF1 EMA
- Bearish Bias: HTF close < HTF 50 EMA AND Current EMA < HTF1 EMA
- Neutral Bias: Mixed signals between timeframes
EMA Stack Analysis:
- Compares EMA alignment across timeframes
- +1: Bullish stack (lower TF EMA > higher TF EMA)
- -1: Bearish stack (lower TF EMA < higher TF EMA)
- 0: Neutral/crossed
Usage:
- Filters false breakouts
- Confirms trend direction
- Improves trade quality
EMA INTEGRATION:
Dynamic EMA for Trend Reference:
Features:
- Configurable period (default: 20)
- Customizable color and width
- Acts as dynamic support/resistance
- Trend filter for ORB trades
Application:
- Above EMA: Favor long breakouts
- Below EMA: Favor short breakouts
- EMA cross: Potential trend change
- Distance from EMA: Momentum gauge
SMART ALERT SYSTEM:
Quality-Filtered Breakout Notifications:
Alert Types:
1. Standard ORB Breakout
2. High Quality ORB Breakout
Quality Criteria:
- Volume Confirmation: Volume > 1.2x average
- MTF Confirmation: Bias aligned with breakout direction
Standard Alert:
- Basic breakout detection
- Price crosses ORH or ORL
- Icon: 🚀 (bullish) or 🔻 (bearish)
High Quality Alert:
- Both volume AND MTF confirmed
- Stronger probability setup
- Icon: 🚀⭐ (bullish) or 🔻⭐ (bearish)
Alert Information Includes:
- Alert quality rating
- Breakout level and current price
- Volume strength percentage (if enabled)
- MTF bias status (if enabled)
- Recommended action
One Alert Per Bar:
- Prevents alert spam
- Uses flag system to track sent alerts
- Resets on new ORB session
───────────────────────────────────────
HOW TO USE
───────────────────────────────────────
OPENING RANGE SETUP:
Basic Configuration:
1. Select time period for opening range (default: 15 minutes)
2. Choose fill color method (Breakout Direction recommended)
3. Enable historical data display if needed
Custom Range (Advanced):
1. Enable Custom Range toggle
2. Set specific session time (e.g., 0930-0945)
3. Select appropriate timezone
4. Useful for specific market opens (NYSE, LSE, etc.)
LIQUIDITY LEVELS SETUP:
Quick Configuration by Asset:
- Forex: Use default settings (Left=15, Right=5)
- Crypto: Set Left=12, Right=4, Display=7
- Gold: Set HTF=1D, Left=20
HTF Liquidity:
- Purpose: Major support/resistance levels
- Recommended: 4H for day trading, 1D for swing trading
- Use as profit targets or reversal zones
LTF Liquidity:
- Purpose: Entry/exit refinement
- Recommended: 1H for day trading, 4H for swing trading
- Use for position management
Mitigation Settings:
- Wick-based: More sensitive (default)
- Close-based: More conservative
- Remove or Show mitigated levels based on preference
TRADING SESSIONS SETUP:
Enable/Disable Sessions:
- Master toggle for all sessions
- Individual session controls
- Show/hide session names
Session High/Low Lines:
- Enable to see session extremes
- Each session has custom colors
- Useful for range trading
Customization:
- Adjust session times for your broker
- Set timezone to match your location
- Customize colors for visibility
VOLUME ANALYSIS SETUP:
Enable Volume Analysis:
1. Toggle on Volume Analysis
2. Set MA length (20 recommended)
3. Adjust spike multiplier (1.5 typical)
Usage:
- Confirm breakouts with volume
- Identify climactic moves
- Filter false signals
MULTI-TIMEFRAME SETUP:
HTF Selection:
- HTF 1 (Trend): 1H for day trading, 4H for swing
- HTF 2 (Bias): 4H for day trading, 1D for swing
Interpretation:
- Trade only with bias alignment
- Neutral bias: Be cautious
- Bias changes: Potential reversals
EMA SETUP:
Configuration:
- Period: 20 for responsive, 50 for smoother
- Color: Choose contrasting color
- Width: 1-2 for visibility
Usage:
- Filter trades: Long above, Short below
- Dynamic support/resistance reference
- Trend confirmation
ALERT SETUP:
TradingView Alert Creation:
1. Enable alerts in indicator settings
2. Enable ORB Breakout Alerts
3. Right-click chart → Add Alert
4. Select this indicator
5. Choose "Any alert() function call"
6. Configure delivery method (mobile, email, webhook)
Alert Filtering:
- All alerts include quality rating
- High Quality alerts = Volume + MTF confirmed
- Standard alerts = Basic breakout only
───────────────────────────────────────
TRADING STRATEGIES
───────────────────────────────────────
CLASSIC ORB STRATEGY:
Setup:
1. Wait for opening range to complete
2. Price breaks and closes above ORH or below ORL
3. Volume > average (if enabled)
4. MTF bias aligned (if enabled)
Entry:
- Bullish: Buy on break above ORH
- Bearish: Sell on break below ORL
- Consider retest entries for better risk/reward
Stop Loss:
- Bullish: Below ORL or range mid-point
- Bearish: Above ORH or range mid-point
- Adjust based on volatility
Targets:
- Initial: Range width extension (ORH + range width)
- Secondary: HTF liquidity levels
- Final: Session high/low or major support/resistance
ORB + LIQUIDITY CONFLUENCE:
Enhanced Setup:
1. Opening range established
2. HTF liquidity level near or beyond ORH/ORL
3. Breakout occurs with volume
4. Price targets the liquidity level
Entry:
- Enter on ORB breakout
- Target the HTF liquidity level
- Use LTF liquidity for position management
Management:
- Partial profits at ORB + range width
- Move stop to breakeven at LTF liquidity
- Final exit at HTF liquidity sweep
ORB REJECTION STRATEGY (Counter-Trend):
Setup:
1. Price breaks above ORH or below ORL
2. Weak volume (below average)
3. MTF bias opposite to breakout
4. Price closes back inside range
Entry:
- Failed bullish break: Short below ORH
- Failed bearish break: Long above ORL
Stop Loss:
- Beyond the failed breakout level
- Or beyond session extreme
Target:
- Opposite end of opening range
- Range mid-point for partial profit
SESSION-BASED ORB TRADING:
Tokyo Session:
- Typically narrower ranges
- Good for range trading
- Wait for London open breakout
London Session:
- Highest volume and volatility
- Strong ORB setups
- Major liquidity sweeps common
New York Session:
- Strong trending moves
- News-driven volatility
- Good for momentum trades
Sydney Session:
- Quieter conditions
- Suitable for range strategies
- Sets up Tokyo session
EMA-FILTERED ORB:
Rules:
- Only take bullish breaks if price > EMA
- Only take bearish breaks if price < EMA
- Ignore counter-trend breaks
Benefits:
- Reduces false signals
- Aligns with larger trend
- Improves win rate
───────────────────────────────────────
CONFIGURATION GUIDE
───────────────────────────────────────
OPENING RANGE SETTINGS:
Time Period:
- 15 min: Standard for most markets
- 30 min: Wider range, fewer breakouts
- 60 min: For slower markets or swing trades
Custom Range:
- Use for specific market opens
- NYSE: 0930-1000 EST
- LSE: 0800-0830 GMT
- Set timezone to match exchange
Historical Display:
- Enable: See all previous session data
- Disable: Cleaner chart, current session only
LIQUIDITY SETTINGS:
Left Bars (5-30):
- Lower: More frequent, sensitive levels
- Higher: Fewer, more significant levels
- Recommended: 15 for most markets
Right Bars (1-25):
- Confirmation period
- Higher: More reliable, less frequent
- Recommended: 5 for balance
Display Limit (1-20):
- Number of active levels shown
- Higher: More context, busier chart
- Recommended: 7 for clarity
Extension Options:
- Short: Levels visible near formation
- Current: Extended to current bar (recommended)
- Max: Extended indefinitely
VOLUME SETTINGS:
MA Length (5-50):
- Shorter: More responsive to spikes
- Longer: Smoother baseline
- Recommended: 20 for balance
Spike Multiplier (1.0-3.0):
- Lower: More sensitive spike detection
- Higher: Only extreme spikes
- Recommended: 1.5 for day trading
MULTI-TIMEFRAME SETTINGS:
HTF 1 (Trend):
- 5m chart: Use 15m or 1H
- 15m chart: Use 1H or 4H
- 1H chart: Use 4H or 1D
HTF 2 (Bias):
- One level higher than HTF 1
- Provides longer-term context
- Don't use same as HTF 1
EMA SETTINGS:
Length:
- 20: Responsive, more signals
- 50: Smoother, stronger filter
- 200: Long-term trend only
Style:
- Choose contrasting color
- Width 1-2 for visibility
- Match your trading style
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BEST PRACTICES
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Chart Timeframe Selection:
- ORB Trading: Use 5m or 15m charts
- Session Review: Use 1H or 4H charts
- Swing Trading: Use 1H or 4H charts
Quality Over Quantity:
- Wait for high-quality alerts (volume + MTF)
- Avoid trading every breakout
- Focus on confluence setups
Risk Management:
- Position size based on range width
- Wider ranges = smaller positions
- Use stop losses always
- Take partial profits at targets
Market Conditions:
- Best results in trending markets
- Reduce position size in choppy conditions
- Consider session overlaps for volatility
- Avoid trading near major news if inexperienced
Continuous Improvement:
- Track win rate by session
- Note which confluence factors work best
- Adjust settings based on market volatility
- Review performance weekly
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PERFORMANCE OPTIMIZATION
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This indicator is optimized with:
- max_bars_back declarations for efficient processing
- Conditional calculations based on enabled features
- Proper memory management for drawing objects
- Minimal recalculation on each bar
Best Practices:
- Disable unused features (sessions, MTF, volume)
- Limit historical display to reduce rendering
- Use appropriate timeframe for your strategy
- Clear old drawing objects periodically
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EDUCATIONAL DISCLAIMER
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This indicator combines established trading concepts:
- Opening Range Breakout theory (price action)
- Liquidity level detection (pivot analysis)
- Session-based trading (time-of-day patterns)
- Volume analysis (confirmation technique)
- Multi-timeframe analysis (trend alignment)
All calculations use standard technical analysis methods:
- Pivot high/low detection algorithms
- Moving averages for trend and volume
- Session time filtering
- Timeframe security functions
The indicator identifies potential trading setups but does not predict future price movements. Success requires proper application within a complete trading strategy including risk management, position sizing, and market context.
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USAGE DISCLAIMER
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This tool is for educational and analytical purposes. Opening Range Breakout trading involves substantial risk. The alert system and quality filters are designed to identify potential setups but do not guarantee profitability. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results. Trading intraday breakouts requires experience and discipline.
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CREDITS & ATTRIBUTION
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ORIGINAL SOURCE:
This indicator builds upon concepts from LuxAlgo's-ORB
Liquidity Sniper V3 (ANTI-FAKEOUT)An advanced institutional trading indicator combining liquidity pool targeting, smart money concepts, and momentum-based entries with comprehensive risk management.
🎯 CORE FEATURES:
- Liquidity Sniper Module: Identifies and targets major liquidity pools (PDH/PDL, PWH/PWL, Equal Highs/Lows, HVN/LVN edges)
- Anti-Fakeout Stack: 10-layer confirmation system including VWAP reclaim, micro BOS, displacement, relative volume, and mitigation entries
- Momentum Engulf Add-On: Catches high-velocity impulsive moves with engulfing candles, volume spikes, and volatility breakouts
- GARCH Volatility Filter: Dynamic volatility analysis to avoid choppy conditions
- Multi-Timeframe Confirmation: Ensures alignment across timeframes before entries
📊 SIGNAL CLASSIFICATION:
- BEST (Green): Highest probability setups with all confirmations aligned - 6.0+ score
- BETTER (Medium Green): Strong setups with most confirmations - 4.5-6.0 score
- GOOD (Light Green): Valid setups with basic confirmations - 3.0-4.5 score
🔍 TRADE SCENARIOS:
S1: Liquidity Reversal - Sweeps + reversals at key levels with displacement
S2: Continuation - Trend following with VWAP mean reversion
S3: Mean Reversion - Extreme deviations (2σ+) with Fibonacci exhaustion
S4: Deep Sweep - 3σ sweeps at major liquidity with high confluence
⚡ MOMENTUM TRIGGERS:
- MET (Momentum Engulf): Bullish/bearish engulfing with 1.5x+ volume spike and ATR impulse
- VBT (Volatility Breakout): Range breakouts with sigma bursts and participation
🛡️ RISK MANAGEMENT:
- Dynamic TP/SL based on ATR, VWAP bands, and liquidity pools
- 3-tier targets (T1: VWAP, T2: Nearest pool, T3: 5R extension)
- Early invalidation tracking (0.5R movement monitoring)
- Minimum 2:1 RR requirement with cooldown periods
- RTH session filters and anti-spam protection
📈 TECHNICAL EDGE:
- SMT Divergence detection vs ES correlation
- CVD (Cumulative Volume Delta) divergence confirmation
- FVG (Fair Value Gap) and Order Block mitigation entries
- Equal highs/lows clustering analysis
- Volume profile HVN/LVN identification
⚙️ FULLY CUSTOMIZABLE:
All parameters adjustable including cooldowns, proximity thresholds, ATR multipliers, RR floors, and scenario weights.
Perfect for: ES/NQ futures, forex majors, and liquid stocks. Works on 1-15 min timeframes. Best results during NY session (9:35-11:00 AM & 1:30-3:30 PM ET).
Created for serious traders seeking institutional-grade edge with quantifiable risk/reward and high-probability setups
Ripster Labels + Air Gaps (v6)What it shows (on one chart)
EMA Clouds (current timeframe)
Plots EMA 8/12/21/34/50/200 with three cloud fills:
12–21 = “fast” cloud
34–50 = “mid” cloud
50–200 = “base” cloud
Cloud color: green when the faster EMA is above the slower (bullish), red/maroon/orange when below (bearish).
Toggle lines vs. clouds via A) EMA Clouds settings.
MTF Rails (higher-TF EMAs)
For three higher timeframes (defaults 30m / 60m / 240m), draws two EMAs each (defaults 34 & 50).
These are stepline-like rails you can visually use as higher-TF supports/resistances.
Configure in B) MTF Rails (turn on/off, change TFs/lengths/colors).
Relative Volume Box (RVol)
Small table (top-center) showing:
Candle Vol (formatted K/M/B if enabled)
RVol = current bar volume / SMA 20 of volume (as a %)
Color scale: blue (<100%), yellow (100–150%), red (>150%).
Settings in C) RVol Box.
DTR vs ATR Box
Daily True Range (DTR = day high − day low) vs ATR(14) on the daily timeframe, with DTR as % of ATR.
Placed at top-right; toggle in D) DTR/ATR Box.
Ripster Trend Label (10m 12/50)
Looks at a separate timeframe (default 10m): EMA 12 vs EMA 50.
Bottom-right table cell shows “10m Trend ↑/↓/Sideways” (green/red/gray).
Configure in E) Ripster Trend Labels (TF and lengths).
Air Gaps (single EMA per TF)
Three horizontal, auto-extending lines showing an EMA from 30m / 60m / 240m (default length 12).
“Air gaps” are the price spaces between these lines—often lighter-resistance zones for price.
Start point logic:
All Bars = draw from the chart’s left
Start of Day = draw from today’s first bar
Bars Offset = draw from N bars back (default 100)
Settings in F) Air Gaps (TFs, length, draw-from, bars-back).
Inputs & where to tweak
A) EMA Clouds
Show EMA Clouds: master toggle
Source: close (default)
Lengths: 8/12/21/34/50/200
Show EMA lines: toggle plotted lines (clouds remain)
B) MTF Rails
Show MTF Rails
TF1/TF2/TF3 (defaults 30/60/240)
EMA A/B (defaults 34/50)
C) RVol Box
Show box
Format as K/M/B: K=1e3, M=1e6, B=1e9
D) DTR/ATR Box
Show DTR/ATR
ATR len: default 14 (daily)
E) Ripster Trend Labels
Show labels
Trend TF: default 10 (10-minute)
Trend EMA Fast/Slow: default 12/50
F) Air Gaps
Show Air Gap lines
TF1/TF2/TF3 (30/60/240)
EMA length: default 12
Draw from: All Bars | Start of Day | Bars Offset
Bars back: used if Draw from = Bars Offset
How it makes decisions
Cloud bias = sign of (faster EMA − slower EMA) for each cloud pair.
Example: 12>21 → fast cloud is bullish (green); 34>50 → mid cloud bullish (teal).
10m trend label = sign of (EMA12−EMA50) on the Trend TF (default 10m).
RVol = volume / sma(volume, 20); formatted as a percent and color-coded.
Practical read of the screen
Fast cloud flips (12/21) often mark short-term momentum changes; mid cloud flips (34/50) reflect swing bias.
Air Gap lines from higher TFs frequently act as support/resistance. Larger spaces between lines = “air gaps” where price can move with less friction.
RVol color tells you how “real” a move is: red/yellow often confirms momentum; blue warns of thin/liquidy bars.
DTR vs ATR shows if today’s range is stretched vs recent norm.
Design choices (why your prior errors are gone)
Removed multiline ?: chains → replaced by if/else (Pine v6 is picky about line continuations).
Moved fill() calls outside of local if blocks (Pine limitation).
ta.change(time("D")) != 0 makes the if condition boolean.
Declared G_drawFrom / G_barsBack before startX() so identifiers exist.
Ross-Style Momentum — StudyRoss-Style Momentum — Study
This indicator is designed to identify high-probability breakout setups inspired by Ross Cameron’s momentum trading style. It combines multiple filters and confirmations to highlight strong long opportunities, while giving traders full control over visibility and thresholds.
Core Features:
Price Range Filter: Only signals when price is between a defined min/max range (ideal for small-cap momentum).
VWAP Alignment: Ensures trades are biased to the long side only when price is above VWAP (optional).
MACD Momentum Check: Requires a fresh MACD bullish crossover within a user-defined lookback.
RSI & ATR Filters: Prevents chasing overextended moves (RSI ceiling) and ignores low-volatility tickers (ATR floor).
Relative Volume (RVOL): Confirms unusual trading activity with minimum RVOL thresholds.
Breakout & Volume Spike: Detects flat-top/base breakouts with volume expansion.
Higher Lows Option: Optional requirement for a constructive higher-lows pattern before breakout.
Float Filter: User-provided float value to avoid large-float stocks if desired.
Visual Tools:
Optional VWAP, Base High/Low, and RVOL plots.
Long setup markers (green labels under qualifying bars).
Background highlight when all conditions align.
Real-time dashboard (top-right) showing pass/fail status of each filter.
Alerts:
Triggers an alert when a full long setup condition is met.
This study does not place trades; it is intended as a signal and confirmation tool for discretionary traders who want to visually validate Ross-style momentum breakout conditions.
Long Elite Squeeze (LES) — H.H 22 Lindsay (AI)LES (Long Elite Squeeze)
LES (Long Elite Squeeze) is a trading framework designed to capture the highest-probability long setups. It’s not just another signal script — it’s a structured system built to filter noise, manage risk, and keep you aligned with real momentum.
🔹 Core Logic
Breakout Confirmation – Ensures moves have structure, not just random spikes.
Relative Volume (RVOL) – Confirms participation and fuel behind the move.
RSI Alignment – Avoids overextended traps and fakeouts.
Squeeze Momentum – The backbone of LES. Signals fire only after a defined squeeze pattern shift (6+ dark green bars followed by a light green bar).
🔹 Trade Management Built In
Automated Sell Signals – Trigger on either:
2 consecutive dark green bars on Squeeze Momentum
WaveTrend cross down
(only valid after a Buy signal — no random shorts)
HUD Entry Checklist – Live conditions shown on chart.
Status Tracker HUD – Flips between “Waiting for Entry” and “In Trade” for clear context.
🔹 Flexibility
3 switchable squeeze versions (V1, V2, V3) for different market conditions.
Customizable EMA & ATR settings (with color options).
Session-aware logic — filter signals to prime trading hours.
🔹 Blueprint & Credits
LES is a fusion of proven concepts, standing on the shoulders of respected creators:
-Squeeze Momentum – LazyBear
-WaveTrend Oscillator – LazyBear
-Relative Volume – LonesomeTheBlue
Breakout/structural logic – refined from classic frameworks
Their work laid the foundation — LES expands and integrates them into a complete trading system.
⚡ Why LES Stands Out
LES wasn’t coded overnight. It’s the result of countless hours of live testing, rebuilding, and refining. Every feature earned its place by proving value in real trading, not theory.
LES is more than an indicator. It’s a disciplined framework — crafted to turn chaos into structure, randomness into probability, and noise into clarity.
⚠️ Disclaimer: This is a trading framework, not financial advice. Performance depends on trader discipline, risk management, and market conditions.
Alt Szn Oracle - Institutional GradeThe Alt Szn Oracle is a macro-level indicator built to help traders front-run altseason by tracking liquidity, dominance rotation, sentiment, and capital flows—all in one signal. It’s designed for those who don’t just chase pumps, but want to understand when the tide is turning and why. This tool doesn't predict specific coin breakouts—it tells you when the market as a whole is gearing up to rotate into higher beta assets like altcoins, including memes and microcaps.
The index consolidates ten macro inputs into a normalized, smoothed score from 0–100. These include Bitcoin and Ethereum dominance, ETH/BTC, altcoin market cap (Total3), relative volume flows, and stablecoin supply (USDT, USDC, DAI)—which act as proxies for risk-on appetite and dry powder entering the system. It also incorporates manually updated sentiment metrics from Google Trends and the Fear & Greed Index, giving it a behavioral edge that most indicators lack.
The logic is simple but powerful: when BTC dominance is falling, ETH/BTC is rising, altcoin volume increases relative to BTC/ETH, and stablecoins start moving—you're likely in the early innings of rotation. The index is also filtered through a volatility threshold and smoothed with an EMA to eliminate chop and fakeouts.
Use this indicator on macro charts like TOTAL3, TOTAL2, or ETHBTC to gauge market health, or overlay it on specific coins like PEPE, DOGE, or SOL to confirm if the tide is in your favor. Interpreting the score is straightforward: readings above 80 suggest euphoria and signal it’s time to de-risk, 60–80 indicates expansion and confirms altseason is underway, 40–60 is neutral, and 20–40 is a capitulation zone where smart money accumulates.
What sets this apart is that it doesn’t just track price—it reflects the flow of capital, the positioning of liquidity, and the sentiment of the crowd. Most altseason indicators are lagging, overfitted, or too simplistic. This one is modular, forward-looking, and grounded in real capital rotation theory.
If you're a trader who wants to time the cycle, not guess it, this is your tool. Refine it, fork it, or expand it to your niche—DeFi, NFTs, meme coins, or L1s. It’s a framework for reading the macro winds, not a signal service. Use it with discipline, and you’ll catch the wave while others drown in noise.
RVOL Effort Matrix💪🏻 RVOL Effort Matrix is a tiered volume framework that translates crowd participation into structure-aware visual zones. Rather than simply flagging spikes, it measures each bar’s volume as a ratio of its historical average and assigns to that effort dynamic tiers, creating a real-time map of conviction , exhaustion , and imbalance —before price even confirms.
⚖️ At its core, the tool builds a histogram of relative volume (RVOL). When enabled, a second layer overlays directional effort by estimating buy vs sell volume using candle body logic. If the candle closes higher, green (buy) volume dominates. If it closes lower, red (sell) volume leads. These components are stacked proportionally and inset beneath a colored cap line—a small but powerful layer that maintains visibility of the true effort tier even when split bars are active. The cap matches the original zone color, preserving context at all times.
Coloration communicates rhythm, tempo, and potential turning points:
• 🔴 = structurally weak effort, i.e. failed moves, fake-outs or trend exhaustion
• 🟡 = neutral volume, as seen in consolidations or pullbacks
• 🟢 = genuine commitment, good for continuation, breakout filters, or early rotation signals
• 🟣 = explosive volume signaling either climax or institutional entry—beware!
Background shading (optional) mirrors these zones across the pane for structural scanning at a glance. Volume bars can be toggled between full-stack mode or clean column view. Every layer is modular—built for composability with tools like ZVOL or OBVX Conviction Bias.
🧐 Ideal Use-Cases:
• 🕰 HTF bias anchoring → LTF execution
• 🧭 Identifying when structure is being driven by real crowd pressure
• 🚫 Fading green/fuchsia bars that fail to break structure
• ✅ Riding green/fuchsia follow-through in directional moves
🍷 Recommended Pairings:
• ZVOL for statistically significant volume anomaly detection
• OBVX Conviction Bias ↔️ for directional confirmation of effort zones
• SUPeR TReND 2.718 for structure-congruent entry filtering
• ATR Turbulence Ribbon to distinguish expansion pressure from churn
🥁 RVOL Effort Matrix is all about seeing—how much pressure is behind a move, whether that pressure is sustainable, and whether the crowd is aligned with price. It's volume, but readable. It’s structure, but dynamic. It’s the difference between obeying noise and trading to the beat of the market.
Hull Moving Average Adaptive RSI (Ehlers)Hull Moving Average Adaptive RSI (Ehlers)
The Hull Moving Average Adaptive RSI (Ehlers) is an enhanced trend-following indicator designed to provide a smooth and responsive view of price movement while incorporating an additional momentum-based analysis using the Adaptive RSI.
Principle and Advantages of the Hull Moving Average:
- The Hull Moving Average (HMA) is known for its ability to track price action with minimal lag while maintaining a smooth curve.
- Unlike traditional moving averages, the HMA significantly reduces noise and responds faster to market trends, making it highly effective for detecting trend direction and changes.
- It achieves this by applying a weighted moving average calculation that emphasizes recent price movements while smoothing out fluctuations.
Why the Adaptive RSI Was Added:
- The core HMA line remains the foundation of the indicator, but an additional analysis using the Adaptive RSI has been integrated to provide more meaningful insights into momentum shifts.
- The Adaptive RSI is a modified version of the traditional Relative Strength Index that dynamically adjusts its sensitivity based on market volatility.
- By incorporating the Adaptive RSI, the HMA visually represents whether momentum is strengthening or weakening, offering a complementary layer of analysis.
How the Adaptive RSI Influences the Indicator:
- High Adaptive RSI (above 65): The market may be overbought, or bullish momentum could be fading. The HMA turns shades of red, signaling a possible exhaustion phase or potential reversals.
- Neutral Adaptive RSI (around 50): The market is in a balanced state, meaning neither buyers nor sellers are in clear control. The HMA takes on grayish tones to indicate this consolidation.
- Low Adaptive RSI (below 35): The market may be oversold, or bearish momentum could be weakening. The HMA shifts to shades of blue, highlighting potential recovery zones or trend slowdowns.
Why This Combination is Powerful:
- While the HMA excels in tracking trends and reducing lag, it does not provide information about momentum strength on its own.
- The Adaptive RSI bridges this gap by adding a clear visual layer that helps traders assess whether a trend is likely to continue, consolidate, or reverse.
- This makes the indicator particularly useful for spotting trend exhaustion and confirming momentum shifts in real-time.
Best Use Cases:
- Works effectively on timeframes from 1 hour (1H) to 1 day (1D), making it suitable for swing trading and position trading.
- Particularly useful for trading indices (SPY), stocks, forex, and cryptocurrencies, where momentum shifts are frequent.
- Helps identify not just trend direction but also whether that trend is gaining or losing strength.
Recommended Complementary Indicators:
- Adaptive Trend Finder: Helps identify the dominant long-term trend.
- Williams Fractals Ultimate: Provides key reversal points to validate trend shifts.
- RVOL (Relative Volume): Confirms significant moves based on volume strength.
This enhanced HMA with Adaptive RSI provides a powerful, intuitive visual tool that makes trend analysis and momentum interpretation more effective and efficient.
This indicator is for educational and informational purposes only. It should not be considered financial advice or a guarantee of performance. Always conduct your own research and use proper risk management when trading. Past performance does not guarantee future results.
Candlestick DataCandlestick Data Indicator
The Candlestick Data indicator provides a comprehensive overview of key metrics for analyzing price action and volume in real-time. This overlay indicator displays essential candlestick data and calculations directly on your chart, offering an all-in-one toolkit for traders seeking in-depth insights.
Key Features:
Price Metrics: View the daily high, low, close, and percentage change.
Volume Insights: Analyze volume, relative volume, and volume buzz for breakout or consolidation signals.
Range Analysis: Includes closing range, distance from low of day (LoD), and percentage change in daily range expansion.
Advanced Metrics: Calculate ADR% (Average Daily Range %), ATR (Average True Range), and % from 52-week high.
Moving Averages: Supports up to four customizable moving averages (EMA or SMA) with distance from price.
Market Context: Displays the sector and industry group for the asset.
This indicator is fully customizable, allowing you to toggle on or off specific metrics to suit your trading style. Designed for active traders, it brings critical data to your fingertips, streamlining decision-making and enhancing analysis.
Perfect for momentum, swing, and day traders looking to gain a data-driven edge!
