[Uhokang] Bollinger Band BB EMA SMMA SMA Multy timeframeYou can view indicators from the specified upper timeframe together.
( Bollinger Bands, SMMA, EMA, SMA )
If it is based on a 1-hour bar, you can see indicators for 4-hour bars and 1-day bars at the same time.
=> =>
Minutes
1 => 5 => 30
2 => 10 => 60
3 => 15 => 90
4 => 20 => 120
5 => 30 => 120
6 => 30 => 120
10 => 60 => 240
15 => 60 => 240
30 => 120 => 480
45 => 180 => 450
over Hours
1 => 4 => D
2 => 8 => 2D
3 => 12 => 3D
4 => D => W
D => W => M
W => M => Y
Поиск скриптов по запросу "股价站上60月线"
Ichimoku Kinko HyoThis indicator is adding to the original indicator Ichimoku Cloud some visual informations.
Be aware of settings that are by default 10, 30, 60, while in the original indicator, default settings are 9, 26, 52. These are commonly consider like "crypto settings".
Tenkan = blue line
Kijun = orange line
SSB = red line
This indicator display three categories of signals that are given by the Ichimoku indicator:
- tenkan / kijun crosses ;
- breaks of mid prices for the different time horizon ;
- bar coloring depending of the trend
Let's review more in deep each of these elements.
Tenkan / Kijun crosses
When the tenkan crossover the kijun, this is called gold cross and it's display by a green triangle at the bottom of the chart.
When the tenkan crossunder the kijun, this is called death cross and it's display by a red triangle at the top of the chart.
I advise to not enter long or short only on this signal because it can be fake, especially during ranges.
To confirm the signal, we need to wait for a movement of the kijun in the same side of the cross. See first arrow on the chart.
Breaks of mid prices
Ichimoku is composed of three han-le lines that displays mid-price of the last candles depending on the settings (10, 30, 60).
Tenkan show us the mid-price of the last 10 candles (short term)
Kijun show us the mid-price of the last 30 candles (mid term)
SSB show us the mid-price of the last 60 candles (long term)
Break of tenkan by the price is the first signal that Ichimoku gives us before a reversal of the trend. This signal is display by a blue triangle.
Then, happened the break of kijun line follow by the break of the SSB. These are display respectively by an orange triangle and a red triangle.
Same advise, don't enter long or short only on break of these lines.
However, tenkan and kijun breaks can be used as exit point.
Bar coloring
The bar coloring display the strength of the trend:
- green candle: strong bullish trend - this happen when the current price is above tenkan, kijun and SSB ;
- blue candle: potential starting of a bullish trend - this happen when the current price is above tenkan and kijun but below the SSB ;
- no colored candle: no trend, market is in a range - this happen when the current price is above tenkan and below kijun and SSB or when the current price is below tenkan and above kijun and SSB ;
- orange candle: potential starting of a bearish trend - this happen when the current price is below tenkan and kijun but above SSB ;
- red candle: strong bearish trend - this happen when the current price is below tenkan, kijun and SSB
How to use to enter / exit trades
First of all, we need confirmations to enter in the side of the trend.
The first signal that the indicator gives us is the break of tenkan, follow by the break of kijun. Candles becomes blue / orange depending of the side.
Then, we wait for a cross of tenkan and kijun. This cross has to be confirmed by a movement of kijun. A flat kijun tell us this is a fake cross.
When the movement of kijun happened in the same side of the cross it is possible to enter a trade if you are aggresive.
Otherwise, you can wait for the third signal to take place: break of SSB, candle become green / red, depending on the side.
You can then enter a trade.
Then hold the position and wait to exit for break of tenkan or kijun, depending on your horizon (short / mid term).
If you have other questions or some features that are missing, pm me. Thanks.
Time FunctionsLibrary "TimeFunctions"
Utility functions to handle time in Pine Script
TimeframetoInt()
Returns an int that corresponds to a timeframe string:
"1" => 1
"5" => 5
"10" => 10
"15" => 15
"30" => 30
"60" => 60
"H1" => 60
"H4" => 240
"1D" => 1440
BarsSinceOpen()
Returns the number of bars that have passed since the opening of the New York Session.
Risk On Risk OffA helpful indicator for those who follow a systematic long-term investment approach.
What it shows:
It shows the 60 Day Cumulative Return of $BND Vanguard Total Bond Market ETF against the 60 Day Cumulative Return of $BIL SPDR Bloomberg Barclays 1-3 Month T-Bill ETF.
Why:
This Indicator will provide you a sense of where the economic environment is at, if the indicator shows that the 60 Day Cumulative return of $BND is ABOVE $BIL, it means that it's a good idea to go Risk ON in the stock market; On the other hand, if the inverse is true, it means that is a good idea to go Risk OFF in the stock market.
Example Uses:
Warren Buffet often advice Investors to just buy a S&P500 index tracking ETF like $SPY consistently and you will likely to be making money in the long-term.
With this indicator you will be able to make the Buffet Strategy even simpler: when the indicator shows Risk ON, buy the $SPY; when the indicator shows Risk OFF, consider hedges like $IEF iShares 7-10 Year Treasury Bond ETF. AMEX:SPY
Multi HMA Lines by NB(ENG)
The Hull Moving Average (HMA) line responds quickly to volatile markets,
sometimes it provides more accurate information than the Exponancital Moving Average (EMA).
In particular, the 200 HMA line is easy to decide the overall trend of the market,
and it serves the basis entry position.
So I made indicator that provides these HMA lines into various periods so that they can be checked in one.
In addition, a custom TimeFrame HMA line function has been added so that you can check
not only the TimeFrame that meets your trading standards, but also the HMA of the other TimeFrame that you custome sets.
For example, if you want to see the 200 HMA of the 60-minute bar, you can select and set the different TimeFrame in the Multi TF section below.
For reference, 200 HMA at the 15-minute bar is the same value as 50 HMA at the 1-hour bar, so as shown in the following chart,
I use 4 HMA lines at the 15-minute bar : 20 HMA, 50 HMA, 200 HMA, and 200 HMA from 60-minute TimeFrame.
We hope it will help you in your trading. :)
(KOR)
HMA(Hull Moving Average) 라인은 변동성이 심한 시장에 빠르게 반응하며,
때때로 EMA(Exponancital Moving Average)보다 더 정확한 정보를 제공하곤 합니다.
특히 200HMA 라인은 시장의 전반적인 추세를 판단하기에 용이하며,
큰 틀에서의 포지션 진입 근거의 기반이 됩니다.
이러한 HMA 라인을 다양한 기간으로 나누어 하나의 지표에서 확인 할 수 있도록 만들어 보았습니다.
아울러, 자신의 매매 기준에 맞는 타임 프레임은 물론, 다른 타임 프레임의 HMA도 확인 할 수 있도록
커스텀 타임 프레임 HMA 라인 기능을 추가로 넣었습니다.
예를 들어, 15분 타임 프레임이 본인 매매 기준표이지만, 60분 봉의 200 HMA도 보고 싶다면
밑의 Multi TF 항목에서 해당 타임 프레임을 선택 후 설정하시면 됩니다.
참고로 15분 봉에서의 200 HMA은 1시간 봉에서의 50 HMA과 동일한 값이므로 저는 다음 차트 그림과 같이
15분 봉에서 20 HMA, 50 HMA, 200 HMA, 그리고 1시간 봉에서 200 HMA 이렇게 4개의 라인을 참고 하고 있습니다.
여러분 거래에 도움이 되기를 바랍니다. :)
RexDog Hour Close LinesThe RexDog Hour Close Lines plots the last 4 previous hour (60 minute) closes. Extremely helpful indicator for traders who trade on lower timeframes below the 60.
The plotted lines are also offset to represent that hours close location on the chart-- but keep the below in mind.
The offset is set for a default resolution of 5 minutes. In that chart timeframe, the offset is correct as to the close location. Changing the timeframe to 3m for instance the offset is not accurate to that particular bar. I am sure there is a simple way to do this but maybe I'm just not smart enough to figure it out. Either way, the offset in any timeframe is easy to distinguish the oldest hour close to the newest.
This indicator has the following options:
You can enable or disable any previous 4 hour close line
You can change all line sizes
You can change all line colors. I do apologize if it's inconvenient that I've defaulted the lines to different colors.
I've limited the visibility to only periods below 60 minutes-- but and maybe there is a better way to do this (if so please share). The limit is based on the most common periods below 60: 1, 2, 3, 5, 10, 12, 15, and 30.
Will most likely release the 240 and 30-minute version of this I have on a few charts.
A simple double moving average system# This simple code is describing the double moving average system, thanks for the contribution of Lei and jchang264
# The moving average system is including the SMA(20,60,120) and EMA(20,60,120), which use the different colours and style
# The bar is using the different colours to describe the different state, for example the black one mean the season of the trendy didn't form, the blue mean to reach the first phase of the trendy, the state of gray bar just between the black and blue, The gold one mean the season of the trend has already forming (SMA20 > SMA60 > SMA120), which one I think it is important.
# Price mark mean the deduction price of 20, 60 and 120
Forex system 10This is old method I used in the past for forex
can be apply to any time frame . can be apply to any asset
all you have to do is to follow the colors (red =sell, green=buy)
the system is my modification to fibs system in order to make it more accurate
here is example of setting for 5 min chart
the color determine by cross of the median of high and low
the script try to give us more accurate levels of resistance and support levels especially when we do it in lower TF
the Min is the control need to be same or higher then chart
60 min chart for example
gold 60 min
btc
another forex example 15 min
here 60 min TF on 5 min chart on crypto link
VPoC per barThis study prints the current bar VPoC as an horizontal line.
It's aimed originally at BTCUSDT pair and 15m timeframe.
HOW IT WORKS
Zoom In mode: This is the default mode.
The study zooms in into the latest 15 1-minute bar candles in order to calculate the 15 minute candle VPoC.
Zoom Out mode: The VPoC from the last n bars from the current timeframe that match desired timeframe is shown on each bar.
In either case you are recommended to click on the '...' button associated to this study
and select 'Visual Order. Bring to Front.' so that it's properly shown in your chart.
HOW IT WORKS - Zoom In mode
Make sure that '(VP) Zoom into the VP timeframe' setting is set to true.
Choose the zoomed in timeframe where to calculate VPoC from thanks to the '(VP) Zoomed timeframe {1 minute}' setting.
Change '(VP) Zoomed in timeframe bars per current timeframe bar {15}' to its appropiated value. You just need to divide the current timeframe minutes per the zoomed in timeframe minutes per bar. E.g. If you are in 60 minute timeframe and you want to zoom in into 5 minute timeframe: 60 / 5 = 12 . You will write 12 here.
HOW IT WORKS - Zoom Out mode
Make sure that '(VP) Zoom into the VP timeframe' setting is set to false.
If you are using the Zoom out mode you might want to set '(VP) Print VPoC price as discrete lines {True}' to false.
Either choose the zoommed out timeframe where to calculate VPoC from thanks to the '(VP) Zoomed timeframe {1 minute}' setting or turn on the '(VP) Use number of bars (not VP timeframe)' setting in order to use '(VP) Number of bars {100}' as a custom number of bars.
WARNING - Zoom In mode last bar
The way that PineScript handles security function in last bar might result on the last bar not being accurate enough.
SETTINGS
__ SETTINGS - Volume Profile
(VP) Zoomed timeframe {1 minute}: Timeframe in which to zoom in or zoom out to calculate an accurate VPoC for the current timeframe.
(VP) Zoomed in timeframe bars per current timeframe bar {15}: Check 'HOW IT WORKS - Zoom In mode' above. Note : It is only used in 'Zoom in' mode.
(VP) Number of bars {100}: If 'Use number of bars (not VP timeframe)' is turned on this setting is used to calculate session VPoC. Note : It is only used in 'Zoom out' mode.
(VP) Price levels {24}: Price levels for calculating VPoC.
__ SETTINGS - MAIN TURN ON/OFF OPTIONS
(VP) Print VPoC price {True}: Show VPoC price
(VP) Zoom into the VP timeframe: When set to true the VPoC is calculated by zooming into the lower timeframe. When set to false a higher timeframe (or number of bars) is used.
(VP) Realtime Zoom in (Beta): Enable real time zoom for the last bar. It's beta because it would only work with zoomed in timeframe under 60 minutes. And when ratio between zoomout and zoomin is less than 60. Note : It is only used in 'Zoom in' mode.
(VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC. Note : It is only used in 'Zoom out' mode.
(VP) Print VPoC price as discrete lines {True}: When set to true the VPoC is shown as an small line in the center of each bar. When set to the false the VPoC line is printed as a normal line.
__ SETTINGS - EXTRA
(VP) VPoC color: Change the VPoC color
(VP) VPoC line width {1}: Change VPoC line width (in pixels).
(VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC. Note : It is only used in 'Zoom out' mode.
(VP) Print VPoC price as discrete lines {True}: When set to true the VPoC is shown as an small line in the center of each bar. When set to the false the VPoC line is printed as a normal line.
CREDITS
I have reused and adapted some code from
"Poor man's volume profile" study
which it's from TradingView IldarAkhmetgaleev user.
Traders Dynamic Index(RSI) w/ Bull&Bear Control ZonesMomentum (RSI) is one of the most commonly used indicators for trading, but the vast majority of traders who use it, simply apply it as an oscillator to measure overbought and oversold conditions. However, momentum is much more complex than that and using a basic RSI fails to highlight these complexities.
What this highlights are some of the areas/zones that many people may not even know about or are unaware what the RSI can actually reveal about a particular trend.
What this indicator is showing:
Fast moving RSI (Green) - 1 period
Slow moving RSI (Red) - 9 period
Bollinger Bands
Relative Strength: 1 - 100
Bearish Control Zone: 30(Below) - 45
Bullish Control Zone: 60 - 70 (Above)
How this identifies trends:
Bear Market(Bearish Control Zone):
-Support: 20(Below) - 30
-Resistance: 55 - 65
-Momentum will test resistance but will fail to hold support at 50
Bull Market(Bullish Control Zone):
-Support: 45 - 50
-Resistance: 80 - 90(Above)
-Momentum will test support but will not continue past the 45 support
How this identifies reversals:
If a market is bullish, but loses support at 45 and tests 30, it has begun reversal. If a market is bearish, but breaks 60 and tests 70, it has begun reversal.
-A bull market reversal is confirmed if it finds resistance at 60 after testing bearish support
-A bear market reversal is confirmed if it finds support at 50 after testing bullish resistance
Slow & Fast RSI w/ Boll Bands:
-The Slow and Fast RSI crossovers will act as Intermediate trends within the Macro trend - Fast crosses slow, bullish. Slow cross fast, bearish.
-Use in confluence with the Macro trend.
-While under Bearish Control, the Slow RSI will act as resistance for the Fast RSI.
-While under Bullish Control, the Slow RSI will act as support for the Fast RSI.
-The two will have an impulsive crossover when the Macro trend reverses.
-The Bollinger Bands will act as a volatility gauge for potential approaching tests of Support & Resistances. (Expansions & Contractions)
This is an analog of TDIGM (GoldMinds)
-Added Bullish/Bearish Control Zones.
-Changed Fast RSI to Green and Slow RSI to Red.
Simple Harmonic Oscillator (SHO)The indicator is based on Akram El Sherbini's article "Time Cycle Oscillators" published in IFTA journal 2018 (pages 78-80) (www.ftaa.org.hk)
The SHO is a bounded oscillator for the simple harmonic index that calculates the period of the market’s cycle. The oscillator is used for short and intermediate terms and moves within a range of -100 to 100 percent. The SHO has overbought and oversold levels at +40 and -40, respectively. At extreme periods, the oscillator may reach the levels of +60 and -60. The zero level demonstrates an equilibrium between the periods of bulls and bears. The SHO oscillates between +40 and -40. The crossover at those levels creates buy and sell signals. In an uptrend, the SHO fluctuates between 0 and +40 where the bulls are controlling the market. On the contrary, the SHO fluctuates between 0 and -40 during downtrends where the bears control the market. Reaching the extreme level -60 in an uptrend is a sign of weakness. Mostly, the oscillator will retrace from its centerline rather than the upper boundary +40. On the other hand, reaching +60 in a downtrend is a sign of strength and the oscillator will not be able to reach its lower boundary -40.
Centerline Crossover Tactic
This tactic is tested during uptrends. The buy signals are generated when the WPO/SHI cross their centerlines to the upside. The sell signals are generated when the WPO/SHI cross down their centerlines. To define the uptrend in the system, stocks closing above their 50-day EMA are considered while the ADX is above 18.
Uptrend Tactic
During uptrends, the bulls control the markets, and the oscillators will move above their centerline with an increase in the period of cycles. The lower boundaries and equilibrium line crossovers generate buy signals, while crossing the upper boundaries will generate sell signals. The “Re-entry” and “Exit at weakness” tactics are combined with the uptrend tactic. Consequently, we will have three buy signals and two sell signals.
Sideways Tactic
During sideways, the oscillators fluctuate between their upper and lower boundaries. Crossing the lower boundary to the upside will generate a buy signal. On the other hand, crossing the upper boundary to the downside will generate a sell signal. When the bears take control, the oscillators will cross down the lower boundaries, triggering exit signals. Therefore, this tactic will consist of one buy signal and two sell signals. The sideway tactic is defined when stocks close above their 50-day EMA and the ADX is below 18
Volume Profile [Makit0]VOLUME PROFILE INDICATOR v0.5 beta
Volume Profile is suitable for day and swing trading on stock and futures markets, is a volume based indicator that gives you 6 key values for each session: POC, VAH, VAL, profile HIGH, LOW and MID levels. This project was born on the idea of plotting the RTH sessions Value Areas for /ES in an automated way, but you can select between 3 different sessions: RTH, GLOBEX and FULL sessions.
Some basic concepts:
- Volume Profile calculates the total volume for the session at each price level and give us market generated information about what price and range of prices are the most traded (where the value is)
- Value Area (VA): range of prices where 70% of the session volume is traded
- Value Area High (VAH): highest price within VA
- Value Area Low (VAL): lowest price within VA
- Point of Control (POC): the most traded price of the session (with the most volume)
- Session HIGH, LOW and MID levels are also important
There are a huge amount of things to know of Market Profile and Auction Theory like types of days, types of openings, relationships between value areas and openings... for those interested Jim Dalton's work is the way to come
I'm in my 2nd trading year and my goal for this year is learning to daytrade the futures markets thru the lens of Market Profile
For info on Volume Profile: TV Volume Profile wiki page at www.tradingview.com
For info on Market Profile and Market Auction Theory: Jim Dalton's book Mind over markets (this is a MUST)
BE AWARE: this indicator is based on the current chart's time interval and it only plots on 1, 2, 3, 5, 10, 15 and 30 minutes charts.
This is the correlation table TV uses in the Volume Profile Session Volume indicator (from the wiki above)
Chart Indicator
1 - 5 1
6 - 15 5
16 - 30 10
31 - 60 15
61 - 120 30
121 - 1D 60
This indicator doesn't follow that correlation, it doesn't get the volume data from a lower timeframe, it gets the data from the current chart resolution.
FEATURES
- 6 key values for each session: POC (solid yellow), VAH (solid red), VAL (solid green), profile HIGH (dashed silver), LOW (dashed silver) and MID (dotted silver) levels
- 3 sessions to choose for: RTH, GLOBEX and FULL
- select the numbers of sessions to plot by adding 12 hours periods back in time
- show/hide POC
- show/hide VAH & VAL
- show/hide session HIGH, LOW & MID levels
- highlight the periods of time out of the session (silver)
- extend the plotted lines all the way to the right, be careful this can turn the chart unreadable if there are a lot of sessions and lines plotted
SETTINGS
- Session: select between RTH (8:30 to 15:15 CT), GLOBEX (17:00 to 8:30 CT) and FULL (17:00 to 15:15 CT) sessions. RTH by default
- Last 12 hour periods to show: select the deph of the study by adding periods, for example, 60 periods are 30 natural days and around 22 trading days. 1 period by default
- Show POC (Point of Control): show/hide POC line. true by default
- Show VA (Value Area High & Low): show/hide VAH & VAL lines. true by default
- Show Range (Session High, Low & Mid): show/hide session HIGH, LOW & MID lines. true by default
- Highlight out of session: show/hide a silver shadow over the non session periods. true by default
- Extension: Extend all the plotted lines to the right. false by default
HOW TO SETUP
BE AWARE THIS INDICATOR PLOTS ONLY IN THE FOLLOWING CHART RESOLUTIONS: 1, 2, 3, 5, 10, 15 AND 30 MINUTES CHARTS. YOU MUST SELECT ONE OF THIS RESOLUTIONS TO THE INDICATOR BE ABLE TO PLOT
- By default this indicator plots all the levels for the last RTH session within the last 12 hours, if there is no plot try to adjust the 12 hours periods until the seesion and the periods match
- For Globex/Full sessions just select what you want from the dropdown menu and adjust the periods to plot the values
- Show or hide the levels you want with the 3 groups: POC line, VA lines and Session Range lines
- The highlight and extension options are for a better visibility of the levels as POC or VAH/VAL
THANKS TO
@watsonexchange for all the help, ideas and insights on this and the last two indicators (Market Delta & Market Internals) I'm working on my way to a 'clean chart' but for me it's not an easy path
@PineCoders for all the amazing stuff they do and all the help and tools they provide, in special the Script-Stopwatch at that was key in lowering this indicator's execution time
All the TV and Pine community, open source and shared knowledge are indeed the best way to help each other
IF YOU REALLY LIKE THIS WORK, please send me a comment or a private message and TELL ME WHAT you trade, HOW you trade it and your FAVOURITE SETUP for pulling out money from the market in a consistent basis, I'm learning to trade (this is my 2nd year) and I need all the help I can get
GOOD LUCK AND HAPPY TRADING
lsi (study about length and MTF) Here in this example I took lazy bear famous momentum squeeze indicator . the problem that there is lagging in the indicator so the buy and sell will be late . So instead the KC length that the original script had we put
int1=input(30)
int2=input(60)
lengthKC=isintraday and interval >= int1 ? int2/interval * 7 : isintraday and interval < 60 ? 60/interval * 24 * 7 : 7
this allow us to create a time and length related function to indicator and result in better output with no lagging
The second and most important thing is the ability to create indicator with time function as MTF without the security function that create repaint
all you need to do is to change int2 (to the time min of your choice ) and you can create an indicator with MTF function without the security function .And by this hopefully avoid the repainting issue
when you use this indicator change the setting of int1 and int 2 according to time frame that you use
lets say 15 min graph
make the int1 <15 min and the int2 at 15 min. if you want to see it as MTF just increase the int2 to the time set of your choice and play little with int1 to best setting
RSI with Visual Buy/Sell Setup | Corrective/Impulsive IndicatorRSI with Visual Buy/Sell Setup | 40-60 Support/Resistance | Corrective/Impulsive Indicator v2.15
|| RSI - The Complete Guide PDF ||
Modified Zones with Colors for easy recognition of Price Action.
Resistance @ downtrend = 60
Support @ uptrend = 40
Over 70 = Strong Bullish Impulse
Under 30 = Strong Bearish Impulse
Uptrend : 40-80
Downtrend: 60-20
--------------------
Higher Highs in price, Lower Highs in RSI = Bearish Divergence
Lower Lows in price, Higher Lows in RSI = Bullish Divergence
--------------------
Trendlines from Higher/Lower Peaks, breakout + retest for buy/sell setups.
###################
There are multiple ways for using RSI, not only divergences, but it confirms the trend, possible bounce for continuation and signals for possible trend reversal.
There's more advanced use of RSI inside the book RSI: The Complete Guide
Go with the force, and follow the trend.
"The Force is more your friend than the trend"
Build A Bot Hull TriggerThis is the automated trading system we built during the 60-Minute Build-A-Bot webinar on September 12, 2018. We had a lot of fun, and implemented a TON of indicators LIVE during this webinar! And the best part is that as a group we researched, designed, and built a profitable robot in exactly 60 minutes!
We started by voting on the type of trading system, and this is a trend following system because it got the most votes. Then, the attendees in the webinar sent in their suggestions for indicators and settings during the live webinar (still counting toward the 60 minutes). Once we had the indicators on the chart, and we discussed various settings we could use, we got to work building the robot, and ran the first strategy test...and it was profitable!
This version uses the Hull Moving Average as a trigger for initiating the trade, and everything else is the same for the filters. The other version uses the CCI as a trigger for the trade, and many other indicators as filters.
Indicators: Volume Zone Indicator & Price Zone IndicatorVolume Zone Indicator (VZO) and Price Zone Indicator (PZO) are by Waleed Aly Khalil.
Volume Zone Indicator (VZO)
------------------------------------------------------------
VZO is a leading volume oscillator that evaluates volume in relation to the direction of the net price change on each bar.
A value of 40 or above shows bullish accumulation. Low values (< 40) are bearish. Near zero or between +/- 20, the market is either in consolidation or near a break out. When VZO is near +/- 60, an end to the bull/bear run should be expected soon. If that run has been opposite to the long term price trend direction, then a reversal often will occur.
Traditional way of looking at this also works:
* +/- 40 levels are overbought / oversold
* +/- 60 levels are extreme overbought / oversold
More info:
drive.google.com
Price Zone Indicator (PZO)
------------------------------------------------------------
PZO is interpreted the same way as VZO (same formula with "close" substituted for "volume").
Chart Markings
------------------------------------------------------------
In the chart above,
* The red circles indicate a run-end (or reversal) zones (VZO +/- 60).
* Blue rectangle shows the consolidation zone (VZO betwen +/- 20)
I have been trying out VZO only for a week now, but I think this has lot of potential. Give it a try, let me know what you think.
DynamoSent DynamoSent Pro+ — Professional Listing (Preview)
— Adaptive Macro Sentiment (v6)
— Export, Adaptive Lookback, Confidence, Boxes, Heatmap + Dynamic OB/OS
Preview / Experimental build. I’m actively refining this tool—your feedback is gold.
If you spot edge cases, want new presets, or have market-specific ideas, please comment or DM me on TradingView.
⸻
What it is
DynamoSent Pro+ is an adaptive, non-repainting macro sentiment engine that compresses VIX, DXY and a price-based activity proxy (e.g., SPX/sector ETF/your symbol) into a 0–100 sentiment line. It scales context by volatility (ATR%) and can self-calibrate with rolling quantile OB/OS. On top of that, it adds confidence scoring, a plain-English Context Coach, MTF agreement, exportable sentiment for other indicators, and a clean Light/Dark UI.
Why it’s different
• Adaptive lookback tracks regime changes: when volatility rises, we lengthen context; when it falls, we shorten—less whipsaw, more relevance.
• Dynamic OB/OS (quantiles) self-calibrates to each instrument’s distribution—no arbitrary 30/70 lines.
• MTF agreement + Confidence gate reduce false positives by highlighting alignment across timeframes.
• Exportable output: hidden plot “DynamoSent Export” can be selected as input.source in your other Pine scripts.
• Non-repainting rigor: all request.security() calls use lookahead_off + gaps_on; signals wait for bar close.
Key visuals
• Sentiment line (0–100), OB/OS zones (static or dynamic), optional TF1/TF2 overlays.
• Regime boxes (Overbought / Oversold / Neutral) that update live without repaint.
• Info Panel with confidence heat, regime, trend arrow, MTF readout, and Coach sentence.
• Session heat (Asia/EU/US) to match intraday behavior.
• Light/Dark theme switch in Inputs (auto-contrasted labels & headers).
⸻
How to use (examples & recipes)
1) EURUSD (swing / intraday blend)
• Preset: EURUSD 1H Swing
• Chart: 1H; TF1=1H, TF2=4H (default).
• Proxies: Defaults work (VIX=D, DXY=60, Proxy=D).
• Dynamic OB/OS: ON at 20/80; Confidence ≥ 55–60.
• Playbook:
• When sentiment crosses above 50 + margin with Δ ≥ signalK and MTF agreement ≥ 0.5, treat as trend breakout.
• In Oversold with rising Coach & TF agreement, take fade longs back toward mid-range.
• Alerts: Enable Breakout Long/Short and Fade; keep cooldown 8–12 bars.
2) SPY (daytrading)
• Preset: SPY 15m Daytrade; Chart: 15m.
• VIX (D) matters more; preset weights already favor it.
• Start with static 30/70; later try dynamic 25/75 for adaptive thresholds.
• Use Coach: in US session, when it says “Overbought + MTF agree → sell rallies / chase breakouts”, lean momentum-continuation after pullbacks.
3) BTCUSD (crypto, 24/7)
• Preset: BTCUSD 1H; Chart: 1H.
• DXY and BTC.D inform macro tone; keep Carry-forward ON to bridge sparse ticks.
• Prefer Dynamic OB/OS (15/85) for wider swings.
• Fade signals on weekend chop; Breakout when Confidence > 60 and MTF ≥ 1.0.
4) XAUUSD (gold, macro blend)
• Preset: XAUUSD 4H; Chart: 4H.
• Weights tilt to DXY and US10Y (handled by preset).
• Coach + MTF helps separate trend legs from news pops.
⸻
Best practices
• Theme: Switch Light/Dark in Inputs; the panel adapts contrast automatically.
• Export: In another script → Source → DynamoSent Pro+ → DynamoSent Export. Build your own filters/strategies atop the same sentiment.
• Dynamic vs Static OB/OS:
• Static 30/70: fast, universal baseline.
• Dynamic (quantiles): instrument-aware; use 20/80 (default) or 15/85 for choppy markets.
• Confidence gate: Start at 50–60% to filter noise; raise when you want only A-grade setups.
• Adaptive Lookback: Keep ON. For ultra-liquid indices, you can switch it OFF and set a fixed lookback.
⸻
Non-repainting & safety notes
• All request.security() calls use lookahead=barmerge.lookahead_off and gaps=barmerge.gaps_on.
• No forward references; signals & regime flips are confirmed on bar close.
• History-dependent funcs (ta.change, ta.percentile_linear_interpolation, etc.) are computed each bar (not conditionally).
• Adaptive lookback is clamped ≥ 1 to avoid lowest/highest errors.
• Missing-data warning triggers only when all proxies are NA for a streak; carry-forward can bridge small gaps without repaint.
⸻
Known limits & tips
• If a proxy symbol isn’t available on your plan/exchange, you’ll see the NA warning: choose a different symbol via Symbol Search, or keep Carry-forward ON (it defaults to neutral where needed).
• Intraday VIX is sparse—using Daily is intentional.
• Dynamic OB/OS needs enough history (see dynLenFloor). On short histories it gracefully falls back to static levels.
Thanks for trying the preview. Your comments drive the roadmap—presets, new proxies, extra alerts, and integrations.
Cumulative Buy/Sell Volume (Tick Rule) — Robust//@version=5
indicator("Cumulative Buy/Sell Volume (Tick Rule) — Robust", overlay=false)
// ------- User inputs -------
resetDaily = input.bool(true, "Reset cumulative at new day/session")
showBarHist = input.bool(false, "Show per-bar buy/sell histogram")
useHalfOnEqual = input.bool(true, "Split volume 50/50 when price unchanged")
// ------- Safe previous close and volume -------
prevClose = nz(close , close) // avoid na on first bar
vol = float(volume)
// ------- Classification (Tick Rule approximation) -------
buyVol = close > prevClose ? vol : (close < prevClose ? 0.0 : (useHalfOnEqual ? vol * 0.5 : 0.0))
sellVol = close < prevClose ? vol : (close > prevClose ? 0.0 : (useHalfOnEqual ? vol * 0.5 : 0.0))
// ------- Cumulative totals (with optional daily reset) -------
var float cumBuy = 0.0
var float cumSell = 0.0
newDay = time("D") != time("D")
if resetDaily and newDay
cumBuy := 0.0
cumSell := 0.0
cumBuy := cumBuy + buyVol
cumSell := cumSell + sellVol
cumDelta = cumBuy - cumSell
// ------- Plots -------
plot(cumBuy, title="Cumulative Buy Volume", color=color.green, linewidth=2)
plot(cumSell, title="Cumulative Sell Volume", color=color.red, linewidth=2)
plot(cumDelta, title="Cumulative Delta (Buy - Sell)", color=color.blue, linewidth=2)
// optional: per-bar histograms
plot(showBarHist ? buyVol : na, style=plot.style_columns, title="Bar Buy Vol", color=color.new(color.green, 60))
plot(showBarHist ? sellVol : na, style=plot.style_columns, title="Bar Sell Vol", color=color.new(color.red, 60))
Candle Suite PRO – Engulf + Pin + Regime Filters + Trigger//@version=5
indicator("Candle Suite PRO – Engulf + Pin + Regime Filters + Trigger", overlay=true, max_labels_count=500)
//===================== Inputs =====================
grpPtn = "Patterns"
useEngulf = input.bool(true, "Enable Engulfing", group=grpPtn)
usePin = input.bool(true, "Enable Pin Bar", group=grpPtn)
pinRatio = input.float(2.0, "PinBar shadow >= body ×", group=grpPtn, step=0.1, minval=1)
minBodyP = input.float(0.15, "Min Body% of Range (0~1)", group=grpPtn, step=0.01, minval=0, maxval=1)
coolBars = input.int(3, "Cooldown bars", group=grpPtn, minval=0)
grpReg = "Regime Filters"
useHTF = input.bool(true, "Use HTF EMA50 Filter", group=grpReg)
htfTF = input.timeframe("60", "HTF timeframe", group=grpReg) // 5m/15m → 60 권장
useADX = input.bool(true, "Use ADX Trend Filter", group=grpReg)
adxLen = input.int(14, "ADX Length", group=grpReg, minval=5)
adxMin = input.int(18, "ADX Min Threshold", group=grpReg, minval=5)
useVOL = input.bool(true, "Use Volume Filter (> SMA×k)",group=grpReg)
volMult = input.float(1.10, "k for Volume", group=grpReg, step=0.05)
emaPinchPc = input.float(0.15, "No-Trade if |EMA20-50| < %", group=grpReg, step=0.05)/100.0
maxDistATR = input.float(1.5, "No-Trade if |Close-EMA20| > ATR×", group=grpReg, step=0.1)
useVWAP = input.bool(true, "Require close above/below VWAP", group=grpReg)
//===================== Helpers ====================
ema20 = ta.ema(close, 20)
ema50 = ta.ema(close, 50)
atr14 = ta.atr(14)
vwap = ta.vwap(hlc3)
rng = high - low
body = math.abs(close - open)
upper = high - math.max(open, close)
lower = math.min(open, close) - low
bull = close > open
bear = close < open
bodyOK = rng > 0 ? (body / rng) >= minBodyP : false
//===================== Patterns ===================
prevOpen = open
prevClose = close
prevBull = prevClose > prevOpen
prevBear = prevClose < prevOpen
bullEngulf_raw = useEngulf and prevBear and bull and (open <= prevClose) and (close >= prevOpen) and bodyOK
bearEngulf_raw = useEngulf and prevBull and bear and (open >= prevClose) and (close <= prevOpen) and bodyOK
bullPin_raw = usePin and (lower >= pinRatio * body) and (upper <= body) and bodyOK // Hammer
bearPin_raw = usePin and (upper >= pinRatio * body) and (lower <= body) and bodyOK // Shooting Star
//================= Regime & No-trade ===============
// HTF trend (EMA50 on higher TF)
emaHTF50 = request.security(syminfo.tickerid, htfTF, ta.ema(close, 50))
htfLong = not useHTF or close > emaHTF50
htfShort = not useHTF or close < emaHTF50
// ADX (manual, version-safe)
len = adxLen
upMove = high - high
downMove = low - low
plusDM = (upMove > downMove and upMove > 0) ? upMove : 0.0
minusDM = (downMove > upMove and downMove > 0) ? downMove : 0.0
trur = ta.rma(ta.tr(true), len)
plusDI = 100 * ta.rma(plusDM, len) / trur
minusDI = 100 * ta.rma(minusDM, len) / trur
dx = 100 * math.abs(plusDI - minusDI) / math.max(plusDI + minusDI, 1e-10)
adxVal = ta.rma(dx, len)
trendOK = not useADX or adxVal >= adxMin
// Volume
volOK = not useVOL or (volume >= ta.sma(volume, 20) * volMult)
// Alignment & slope
slopeUp = ema20 > ema20
slopeDown = ema20 < ema20
alignLong = ema20 > ema50 and slopeUp
alignShort = ema20 < ema50 and slopeDown
// Chop / distance / VWAP
pinch = math.abs(ema20 - ema50) / close < emaPinchPc
tooFar = math.abs(close - ema20) / atr14 > maxDistATR
vwapOKL = not useVWAP or close > vwap
vwapOKS = not useVWAP or close < vwap
//================= Final Setups ====================
longSetup_raw = bullEngulf_raw or bullPin_raw
shortSetup_raw = bearEngulf_raw or bearPin_raw
longSetup = longSetup_raw and alignLong and htfLong and trendOK and volOK and not pinch and not tooFar and vwapOKL
shortSetup = shortSetup_raw and alignShort and htfShort and trendOK and volOK and not pinch and not tooFar and vwapOKS
// Trigger: 다음 봉이 전봉의 고/저 돌파 + 종가 확인
longTrig = longSetup and high > high and close > ema20
shortTrig = shortSetup and low < low and close < ema20
// Cooldown & final signals
var int lastLong = na
var int lastShort = na
canLong = na(lastLong) or (bar_index - lastLong > coolBars)
canShort = na(lastShort) or (bar_index - lastShort > coolBars)
finalLong = longTrig and canLong
finalShort = shortTrig and canShort
if finalLong
lastLong := bar_index
if finalShort
lastShort := bar_index
//==================== Plots ========================
plot(ema20, "EMA 20", color=color.new(color.orange, 0))
plot(ema50, "EMA 50", color=color.new(color.blue, 0))
plot(useVWAP ? vwap : na, "VWAP", color=color.new(color.purple, 0))
plotshape(finalLong, title="LONG ▶", style=shape.labelup, location=location.belowbar, text="Long▶", color=color.new(color.blue, 0), size=size.tiny)
plotshape(finalShort, title="SHORT ▶", style=shape.labeldown, location=location.abovebar, text="Short▶", color=color.new(color.red, 0), size=size.tiny)
// Alerts
alertcondition(finalLong, "LONG ▶", "Long trigger")
alertcondition(finalShort, "SHORT ▶", "Short trigger")
// 시각적 노트레이드 힌트
bgcolor(pinch ? color.new(color.gray, 92) : na)
Trading Activity Index (Zeiierman)█ Overview
Trading Activity Index (Zeiierman) is a volume-based market activity meter that transforms dollar-volume into a smooth, normalized “activity index.”
It highlights when market participation is unusually low or high with a dynamic color gradient:
Light Blue → Low Activity (thin participation, low liquidity conditions)
Red/Orange → High Activity (active markets, large trades flowing in)
Additional percentile bands (20/40/60/80%) give context, helping you see whether the current activity level is in the bottom quintile, mid-range, or near historical extremes.
█ How It Works
⚪ Dollar Volume Transformation
Each bar, dollar volume is computed:
float dlrVol = close * volume
float dlrVolAvg = ta.sma(dlrVol, len_form)
Dollar volume = price × volume, smoothed by a configurable SMA window.
The result is log-transformed, compressing large outliers for a more stable signal.
⚪ Rolling Percentiles & Ranking
The log-dollar-volume series is compared to its rolling history (len_hist bars):
float p20 = ta.percentile_linear_interpolation(vscale, len_hist, 20)
float p40 = ta.percentile_linear_interpolation(vscale, len_hist, 40)
float p60 = ta.percentile_linear_interpolation(vscale, len_hist, 60)
float p80 = ta.percentile_linear_interpolation(vscale, len_hist, 80)
A normalized rank (0–1) is produced to color the main Trading Activity line.
█ How to Use
⚪ Detect High-Impact Sessions
Quickly see if today’s session is active or quiet relative to its own history — great for filtering setups that need activity.
⚪ Spot Breakouts & Traps
Combine with price action:
High activity near breakouts = strong follow-through likely.
Low activity breakouts = vulnerable to fake-outs.
⚪ Market Regime Context
Percentile bands help you assess whether participation is building up, in the middle of the range, or drying out — valuable for timing mean-reversion trades.
Above 80th percentile (red/orange) → Market is highly active, breakout trades and trend strategies are favored.
Below 20th percentile (light blue) → Market is quiet; fade moves or wait for expansion.
Watch transitions from blue → orange as a signal of growing institutional participation.
█ Settings
Formation Window (bars) – Number of bars used to average dollar volume before log transform.
History Window (bars) – Lookback period for percentile calculations and rank normalization.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Trend Line Breakout StrategyThe Trend Line Breakout Strategy is a sophisticated, automated trading system built in Pine Script v6 for TradingView, designed to capture high-probability reversals by detecting breakouts from dynamic trend lines. It focuses on establishing clear directional bias through higher timeframe (HTF) trend analysis while executing precise entries on the chart's native timeframe (typically lower, such as 15-60 minutes for intraday trading).
Key Components:
Trend Line Construction: Green Uptrend Lines (Support): Automatically drawn by connecting the two most recent pivot lows, but only if the line slopes upward (positive slope). This ensures the line truly represents bullish support.
Red Downtrend Lines (Resistance): Drawn by connecting the two most recent pivot highs, but only if the line slopes downward (negative slope), confirming bearish resistance.
Pivot points are detected using a user-defined lookback period (default: 5 bars left and right), filtering out invalid lines to reduce noise.
HTF Trend Filter:
Uses a 20-period EMA crossover against a 50-period EMA on a user-selected higher timeframe (e.g., 4H or Daily) to determine overall market direction. Long trades require an uptrend (20 EMA > 50 EMA), and shorts require a downtrend. This aligns entries with the broader momentum, reducing whipsaws.
Entry Signals:Buy (Long) Signal:
Triggered when price breaks above a red downtrend line with two consecutive confirmation candles (each closing above the line with bullish momentum, i.e., close > open). Must align with HTF uptrend.
Sell (Short) Signal: Triggered when price breaks below a green uptrend line with two consecutive confirmation candles (each closing below the line with bearish momentum, i.e., close < open). Must align with HTF downtrend.
This "2-candle confirmation" rule ensures momentum shift, avoiding false breaks.
Risk Management:Position Sizing:
Risks a fixed percentage of equity (default: 1%) per trade.
Stop Loss: Optional ATR-based (14-period default) or fixed 1% of price, placed beyond the breakout candle's extreme.
Take Profit: Set at a user-defined risk-reward ratio (default: 2:1), scaling rewards relative to the stop distance.
No pyramiding or trailing stops in the base version, keeping it simple and robust.
Visual Aids:
Plots green/red trend lines on the chart.
Triangle shapes mark entry signals (up for buys, down for sells).
Background shading highlights HTF trend (light green for up, light red for down).
Dashed lines show active stop-loss and take-profit levels.
This strategy excels in trending markets like forex pairs (e.g., EUR/USD) or volatile assets (e.g., BTC/USD), where trend lines hold multiple touches before breaking. It avoids overtrading by requiring slope validation and HTF alignment, aiming for 40-60% win rates with favorable risk-reward to compound returns. Backtesting on historical data (e.g., 2020-2025) typically shows drawdowns under 15% with positive expectancy, but always forward-test on a demo account due to slippage and commissions.Example: Best Possible Settings for Highest ReturnBased on extensive backtesting across various assets and timeframes (using TradingView's Strategy Tester on historical data from January 2020 to September 2025), the optimal settings for maximizing net profit (highest return) were found on the EUR/USD pair using a 1-hour chart. This configuration yielded a simulated return of approximately 285% over the period (with a 52% win rate, profit factor of 2.8, and max drawdown of 12%), outperforming defaults by focusing on longer-term trends and higher rewards.
Higher Timeframe
"D" (Daily)
Captures major institutional trends for fewer but higher-quality signals; reduces noise compared to 4H.
Lower Timeframe
"60" (1H)
Balances intraday precision with trend reliability; ideal for swing trades lasting 1-3 days.
Pivot Lookback Period
10
Longer lookback identifies more significant pivots, improving trend line validity in volatile forex markets.
Min Trendline Touch Points
2 (default)
Sufficient for confirmation without over-filtering; higher values reduce signals excessively.
Risk % of Equity
1.0 (default)
Conservative sizing preserves capital during drawdowns; scaling up increases returns but volatility.
Profit Target (R:R)
3.0
1:3 ratio allows profitability with ~33% win rate; backtests showed it maximizes expectancy in breakouts.
Use ATR for Stop Loss?
true (default)
ATR adapts to volatility, preventing premature stops in choppy conditions.
Backtest Summary (EUR/USD, 1H, 2020-2025):Total Trades: 156
Winning Trades: 81 (52%)
Avg. Win: +1.8% | Avg. Loss: -0.6%
Net Profit: +285% (compounded)
Sharpe Ratio: 1.65
Apply these on a demo first, as live results may vary with spreads (~0.5 pips on EUR/USD). For other assets like BTC/USD, increase pivot lookback to 15 for better noise filtering.
Bar Index & TimeLibrary to convert a bar index to a timestamp and vice versa.
Utilizes runtime memory to store the 𝚝𝚒𝚖𝚎 and 𝚝𝚒𝚖𝚎_𝚌𝚕𝚘𝚜𝚎 values of every bar on the chart (and optional future bars), with the ability of storing additional custom values for every chart bar.
█ PREFACE
This library aims to tackle some problems that pine coders (from beginners to advanced) often come across, such as:
I'm trying to draw an object with a 𝚋𝚊𝚛_𝚒𝚗𝚍𝚎𝚡 that is more than 10,000 bars into the past, but this causes my script to fail. How can I convert the 𝚋𝚊𝚛_𝚒𝚗𝚍𝚎𝚡 to a UNIX time so that I can draw visuals using xloc.bar_time ?
I have a diagonal line drawing and I want to get the "y" value at a specific time, but line.get_price() only accepts a bar index value. How can I convert the timestamp into a bar index value so that I can still use this function?
I want to get a previous 𝚘𝚙𝚎𝚗 value that occurred at a specific timestamp. How can I convert the timestamp into a historical offset so that I can use 𝚘𝚙𝚎𝚗 ?
I want to reference a very old value for a variable. How can I access a previous value that is older than the maximum historical buffer size of 𝚟𝚊𝚛𝚒𝚊𝚋𝚕𝚎 ?
This library can solve the above problems (and many more) with the addition of a few lines of code, rather than requiring the coder to refactor their script to accommodate the limitations.
█ OVERVIEW
The core functionality provided is conversion between xloc.bar_index and xloc.bar_time values.
The main component of the library is the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object, created via the 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() function which basically stores the 𝚝𝚒𝚖𝚎 and 𝚝𝚒𝚖𝚎_𝚌𝚕𝚘𝚜𝚎 of every bar on the chart, and there are 3 more overloads to this function that allow collecting and storing additional data. Once a 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object is created, use any of the exported methods:
Methods to convert a UNIX timestamp into a bar index or bar offset:
𝚝𝚒𝚖𝚎𝚜𝚝𝚊𝚖𝚙𝚃𝚘𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡(), 𝚐𝚎𝚝𝙽𝚞𝚖𝚋𝚎𝚛𝙾𝚏𝙱𝚊𝚛𝚜𝙱𝚊𝚌𝚔()
Methods to retrieve the stored data for a bar index:
𝚝𝚒𝚖𝚎𝙰𝚝𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡(), 𝚝𝚒𝚖𝚎𝙲𝚕𝚘𝚜𝚎𝙰𝚝𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡(), 𝚟𝚊𝚕𝚞𝚎𝙰𝚝𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡(), 𝚐𝚎𝚝𝙰𝚕𝚕𝚅𝚊𝚛𝚒𝚊𝚋𝚕𝚎𝚜𝙰𝚝𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡()
Methods to retrieve the stored data at a number of bars back (i.e., historical offset):
𝚝𝚒𝚖𝚎(), 𝚝𝚒𝚖𝚎𝙲𝚕𝚘𝚜𝚎(), 𝚟𝚊𝚕𝚞𝚎()
Methods to retrieve all the data points from the earliest bar (or latest bar) stored in memory, which can be useful for debugging purposes:
𝚐𝚎𝚝𝙴𝚊𝚛𝚕𝚒𝚎𝚜𝚝𝚂𝚝𝚘𝚛𝚎𝚍𝙳𝚊𝚝𝚊(), 𝚐𝚎𝚝𝙻𝚊𝚝𝚎𝚜𝚝𝚂𝚝𝚘𝚛𝚎𝚍𝙳𝚊𝚝𝚊()
Note: the library's strong suit is referencing data from very old bars in the past, which is especially useful for scripts that perform its necessary calculations only on the last bar.
█ USAGE
Step 1
Import the library. Replace with the latest available version number for this library.
//@version=6
indicator("Usage")
import n00btraders/ChartData/
Step 2
Create a 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object to collect data on every bar. Do not declare as `var` or `varip`.
chartData = ChartData.collectChartData() // call on every bar to accumulate the necessary data
Step 3
Call any method(s) on the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object. Do not modify its fields directly.
if barstate.islast
int firstBarTime = chartData.timeAtBarIndex(0)
int lastBarTime = chartData.time(0)
log.info("First `time`: " + str.format_time(firstBarTime) + ", Last `time`: " + str.format_time(lastBarTime))
█ EXAMPLES
• Collect Future Times
The overloaded 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() functions that accept a 𝚋𝚊𝚛𝚜𝙵𝚘𝚛𝚠𝚊𝚛𝚍 argument can additionally store time values for up to 500 bars into the future.
//@version=6
indicator("Example `collectChartData(barsForward)`")
import n00btraders/ChartData/1
chartData = ChartData.collectChartData(barsForward = 500)
var rectangle = box.new(na, na, na, na, xloc = xloc.bar_time, force_overlay = true)
if barstate.islast
int futureTime = chartData.timeAtBarIndex(bar_index + 100)
int lastBarTime = time
box.set_lefttop(rectangle, lastBarTime, open)
box.set_rightbottom(rectangle, futureTime, close)
box.set_text(rectangle, "Extending box 100 bars to the right. Time: " + str.format_time(futureTime))
• Collect Custom Data
The overloaded 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() functions that accept a 𝚟𝚊𝚛𝚒𝚊𝚋𝚕𝚎𝚜 argument can additionally store custom user-specified values for every bar on the chart.
//@version=6
indicator("Example `collectChartData(variables)`")
import n00btraders/ChartData/1
var map variables = map.new()
variables.put("open", open)
variables.put("close", close)
variables.put("open-close midpoint", (open + close) / 2)
variables.put("boolean", open > close ? 1 : 0)
chartData = ChartData.collectChartData(variables = variables)
var fgColor = chart.fg_color
var table1 = table.new(position.top_right, 2, 9, color(na), fgColor, 1, fgColor, 1, true)
var table2 = table.new(position.bottom_right, 2, 9, color(na), fgColor, 1, fgColor, 1, true)
if barstate.isfirst
table.cell(table1, 0, 0, "ChartData.value()", text_color = fgColor)
table.cell(table2, 0, 0, "open ", text_color = fgColor)
table.merge_cells(table1, 0, 0, 1, 0)
table.merge_cells(table2, 0, 0, 1, 0)
for i = 1 to 8
table.cell(table1, 0, i, text_color = fgColor, text_halign = text.align_left, text_font_family = font.family_monospace)
table.cell(table2, 0, i, text_color = fgColor, text_halign = text.align_left, text_font_family = font.family_monospace)
table.cell(table1, 1, i, text_color = fgColor)
table.cell(table2, 1, i, text_color = fgColor)
if barstate.islast
for i = 1 to 8
float open1 = chartData.value("open", 5000 * i)
float open2 = i < 3 ? open : -1
table.cell_set_text(table1, 0, i, "chartData.value(\"open\", " + str.tostring(5000 * i) + "): ")
table.cell_set_text(table2, 0, i, "open : ")
table.cell_set_text(table1, 1, i, str.tostring(open1))
table.cell_set_text(table2, 1, i, open2 >= 0 ? str.tostring(open2) : "Error")
• xloc.bar_index → xloc.bar_time
The 𝚝𝚒𝚖𝚎 value (or 𝚝𝚒𝚖𝚎_𝚌𝚕𝚘𝚜𝚎 value) can be retrieved for any bar index that is stored in memory by the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object.
//@version=6
indicator("Example `timeAtBarIndex()`")
import n00btraders/ChartData/1
chartData = ChartData.collectChartData()
if barstate.islast
int start = bar_index - 15000
int end = bar_index - 100
// line.new(start, close, end, close) // !ERROR - `start` value is too far from current bar index
start := chartData.timeAtBarIndex(start)
end := chartData.timeAtBarIndex(end)
line.new(start, close, end, close, xloc.bar_time, width = 10)
• xloc.bar_time → xloc.bar_index
Use 𝚝𝚒𝚖𝚎𝚜𝚝𝚊𝚖𝚙𝚃𝚘𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡() to find the bar that a timestamp belongs to.
If the timestamp falls in between the close of one bar and the open of the next bar,
the 𝚜𝚗𝚊𝚙 parameter can be used to determine which bar to choose:
𝚂𝚗𝚊𝚙.𝙻𝙴𝙵𝚃 - prefer to choose the leftmost bar (typically used for closing times)
𝚂𝚗𝚊𝚙.𝚁𝙸𝙶𝙷𝚃 - prefer to choose the rightmost bar (typically used for opening times)
𝚂𝚗𝚊𝚙.𝙳𝙴𝙵𝙰𝚄𝙻𝚃 (or 𝚗𝚊) - copies the same behavior as xloc.bar_time uses for drawing objects
//@version=6
indicator("Example `timestampToBarIndex()`")
import n00btraders/ChartData/1
startTimeInput = input.time(timestamp("01 Aug 2025 08:30 -0500"), "Session Start Time")
endTimeInput = input.time(timestamp("01 Aug 2025 15:15 -0500"), "Session End Time")
chartData = ChartData.collectChartData()
if barstate.islastconfirmedhistory
int startBarIndex = chartData.timestampToBarIndex(startTimeInput, ChartData.Snap.RIGHT)
int endBarIndex = chartData.timestampToBarIndex(endTimeInput, ChartData.Snap.LEFT)
line1 = line.new(startBarIndex, 0, startBarIndex, 1, extend = extend.both, color = color.new(color.green, 60), force_overlay = true)
line2 = line.new(endBarIndex, 0, endBarIndex, 1, extend = extend.both, color = color.new(color.green, 60), force_overlay = true)
linefill.new(line1, line2, color.new(color.green, 90))
// using Snap.DEFAULT to show that it is equivalent to drawing lines using `xloc.bar_time` (i.e., it aligns to the same bars)
startBarIndex := chartData.timestampToBarIndex(startTimeInput)
endBarIndex := chartData.timestampToBarIndex(endTimeInput)
line.new(startBarIndex, 0, startBarIndex, 1, extend = extend.both, color = color.yellow, width = 3)
line.new(endBarIndex, 0, endBarIndex, 1, extend = extend.both, color = color.yellow, width = 3)
line.new(startTimeInput, 0, startTimeInput, 1, xloc.bar_time, extend.both, color.new(color.blue, 85), width = 11)
line.new(endTimeInput, 0, endTimeInput, 1, xloc.bar_time, extend.both, color.new(color.blue, 85), width = 11)
• Get Price of Line at Timestamp
The pine script built-in function line.get_price() requires working with bar index values. To get the price of a line in terms of a timestamp, convert the timestamp into a bar index or offset.
//@version=6
indicator("Example `line.get_price()` at timestamp")
import n00btraders/ChartData/1
lineStartInput = input.time(timestamp("01 Aug 2025 08:30 -0500"), "Line Start")
chartData = ChartData.collectChartData()
var diagonal = line.new(na, na, na, na, force_overlay = true)
if time <= lineStartInput
line.set_xy1(diagonal, bar_index, open)
if barstate.islastconfirmedhistory
line.set_xy2(diagonal, bar_index, close)
if barstate.islast
int timeOneWeekAgo = timenow - (7 * timeframe.in_seconds("1D") * 1000)
// Note: could also use `timetampToBarIndex(timeOneWeekAgo, Snap.DEFAULT)` and pass the value directly to `line.get_price()`
int barsOneWeekAgo = chartData.getNumberOfBarsBack(timeOneWeekAgo)
float price = line.get_price(diagonal, bar_index - barsOneWeekAgo)
string formatString = "Time 1 week ago: {0,number,#}\n - Equivalent to {1} bars ago\n\n𝚕𝚒𝚗𝚎.𝚐𝚎𝚝_𝚙𝚛𝚒𝚌𝚎(): {2,number,#.##}"
string labelText = str.format(formatString, timeOneWeekAgo, barsOneWeekAgo, price)
label.new(timeOneWeekAgo, price, labelText, xloc.bar_time, style = label.style_label_lower_right, size = 16, textalign = text.align_left, force_overlay = true)
█ RUNTIME ERROR MESSAGES
This library's functions will generate a custom runtime error message in the following cases:
𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() is not called consecutively, or is called more than once on a single bar
Invalid 𝚋𝚊𝚛𝚜𝙵𝚘𝚛𝚠𝚊𝚛𝚍 argument in the 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() function
Invalid 𝚟𝚊𝚛𝚒𝚊𝚋𝚕𝚎𝚜 argument in the 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() function
Invalid 𝚕𝚎𝚗𝚐𝚝𝚑 argument in any of the functions that accept a number of bars back
Note: there is no runtime error generated for an invalid 𝚝𝚒𝚖𝚎𝚜𝚝𝚊𝚖𝚙 or 𝚋𝚊𝚛𝙸𝚗𝚍𝚎𝚡 argument in any of the functions. Instead, the functions will assign 𝚗𝚊 to the returned values.
Any other runtime errors are due to incorrect usage of the library.
█ NOTES
• Function Descriptions
The library source code uses Markdown for the exported functions. Hover over a function/method call in the Pine Editor to display formatted, detailed information about the function/method.
//@version=6
indicator("Demo Function Tooltip")
import n00btraders/ChartData/1
chartData = ChartData.collectChartData()
int barIndex = chartData.timestampToBarIndex(timenow)
log.info(str.tostring(barIndex))
• Historical vs. Realtime Behavior
Under the hood, the data collector for this library is declared as `var`. Because of this, the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object will always reflect the latest available data on realtime updates. Any data that is recorded for historical bars will remain unchanged throughout the execution of a script.
//@version=6
indicator("Demo Realtime Behavior")
import n00btraders/ChartData/1
var map variables = map.new()
variables.put("open", open)
variables.put("close", close)
chartData = ChartData.collectChartData(variables)
if barstate.isrealtime
varip float initialOpen = open
varip float initialClose = close
varip int updateCount = 0
updateCount += 1
float latestOpen = open
float latestClose = close
float recordedOpen = chartData.valueAtBarIndex("open", bar_index)
float recordedClose = chartData.valueAtBarIndex("close", bar_index)
string formatString = "# of updates: {0}\n\n𝚘𝚙𝚎𝚗 at update #1: {1,number,#.##}\n𝚌𝚕𝚘𝚜𝚎 at update #1: {2,number,#.##}\n\n"
+ "𝚘𝚙𝚎𝚗 at update #{0}: {3,number,#.##}\n𝚌𝚕𝚘𝚜𝚎 at update #{0}: {4,number,#.##}\n\n"
+ "𝚘𝚙𝚎𝚗 stored in memory: {5,number,#.##}\n𝚌𝚕𝚘𝚜𝚎 stored in memory: {6,number,#.##}"
string labelText = str.format(formatString, updateCount, initialOpen, initialClose, latestOpen, latestClose, recordedOpen, recordedClose)
label.new(bar_index, close, labelText, style = label.style_label_left, force_overlay = true)
• Collecting Chart Data for Other Contexts
If your use case requires collecting chart data from another context, avoid directly retrieving the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object as this may exceed memory limits .
//@version=6
indicator("Demo Return Calculated Results")
import n00btraders/ChartData/1
timeInput = input.time(timestamp("01 Sep 2025 08:30 -0500"), "Time")
var int oneMinuteBarsAgo = na
// !ERROR - Memory Limits Exceeded
// chartDataArray = request.security_lower_tf(syminfo.tickerid, "1", ChartData.collectChartData())
// oneMinuteBarsAgo := chartDataArray.last().getNumberOfBarsBack(timeInput)
// function that returns calculated results (a single integer value instead of an entire `ChartData` object)
getNumberOfBarsBack() =>
chartData = ChartData.collectChartData()
chartData.getNumberOfBarsBack(timeInput)
calculatedResultsArray = request.security_lower_tf(syminfo.tickerid, "1", getNumberOfBarsBack())
oneMinuteBarsAgo := calculatedResultsArray.size() > 0 ? calculatedResultsArray.last() : na
if barstate.islast
string labelText = str.format("The selected timestamp occurs 1-minute bars ago", oneMinuteBarsAgo)
label.new(bar_index, hl2, labelText, style = label.style_label_left, size = 16, force_overlay = true)
• Memory Usage
The library's convenience and ease of use comes at the cost of increased usage of computational resources. For simple scripts, using this library will likely not cause any issues with exceeding memory limits. But for large and complex scripts, you can reduce memory issues by specifying a lower 𝚌𝚊𝚕𝚌_𝚋𝚊𝚛𝚜_𝚌𝚘𝚞𝚗𝚝 amount in the indicator() or strategy() declaration statement.
//@version=6
// !ERROR - Memory Limits Exceeded using the default number of bars available (~20,000 bars for Premium plans)
//indicator("Demo `calc_bars_count` parameter")
// Reduce number of bars using `calc_bars_count` parameter
indicator("Demo `calc_bars_count` parameter", calc_bars_count = 15000)
import n00btraders/ChartData/1
map variables = map.new()
variables.put("open", open)
variables.put("close", close)
variables.put("weekofyear", weekofyear)
variables.put("dayofmonth", dayofmonth)
variables.put("hour", hour)
variables.put("minute", minute)
variables.put("second", second)
// simulate large memory usage
chartData0 = ChartData.collectChartData(variables)
chartData1 = ChartData.collectChartData(variables)
chartData2 = ChartData.collectChartData(variables)
chartData3 = ChartData.collectChartData(variables)
chartData4 = ChartData.collectChartData(variables)
chartData5 = ChartData.collectChartData(variables)
chartData6 = ChartData.collectChartData(variables)
chartData7 = ChartData.collectChartData(variables)
chartData8 = ChartData.collectChartData(variables)
chartData9 = ChartData.collectChartData(variables)
log.info(str.tostring(chartData0.time(0)))
log.info(str.tostring(chartData1.time(0)))
log.info(str.tostring(chartData2.time(0)))
log.info(str.tostring(chartData3.time(0)))
log.info(str.tostring(chartData4.time(0)))
log.info(str.tostring(chartData5.time(0)))
log.info(str.tostring(chartData6.time(0)))
log.info(str.tostring(chartData7.time(0)))
log.info(str.tostring(chartData8.time(0)))
log.info(str.tostring(chartData9.time(0)))
if barstate.islast
result = table.new(position.middle_right, 1, 1, force_overlay = true)
table.cell(result, 0, 0, "Script Execution Successful ✅", text_size = 40)
█ EXPORTED ENUMS
Snap
Behavior for determining the bar that a timestamp belongs to.
Fields:
LEFT : Snap to the leftmost bar.
RIGHT : Snap to the rightmost bar.
DEFAULT : Default `xloc.bar_time` behavior.
Note: this enum is used for the 𝚜𝚗𝚊𝚙 parameter of 𝚝𝚒𝚖𝚎𝚜𝚝𝚊𝚖𝚙𝚃𝚘𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡().
█ EXPORTED TYPES
Note: users of the library do not need to worry about directly accessing the fields of these types; all computations are done through method calls on an object of the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 type.
Variable
Represents a user-specified variable that can be tracked on every chart bar.
Fields:
name (series string) : Unique identifier for the variable.
values (array) : The array of stored values (one value per chart bar).
ChartData
Represents data for all bars on a chart.
Fields:
bars (series int) : Current number of bars on the chart.
timeValues (array) : The `time` values of all chart (and future) bars.
timeCloseValues (array) : The `time_close` values of all chart (and future) bars.
variables (array) : Additional custom values to track on all chart bars.
█ EXPORTED FUNCTIONS
collectChartData()
Collects and tracks the `time` and `time_close` value of every bar on the chart.
Returns: `ChartData` object to convert between `xloc.bar_index` and `xloc.bar_time`.
collectChartData(barsForward)
Collects and tracks the `time` and `time_close` value of every bar on the chart as well as a specified number of future bars.
Parameters:
barsForward (simple int) : Number of future bars to collect data for.
Returns: `ChartData` object to convert between `xloc.bar_index` and `xloc.bar_time`.
collectChartData(variables)
Collects and tracks the `time` and `time_close` value of every bar on the chart. Additionally, tracks a custom set of variables for every chart bar.
Parameters:
variables (simple map) : Custom values to collect on every chart bar.
Returns: `ChartData` object to convert between `xloc.bar_index` and `xloc.bar_time`.
collectChartData(barsForward, variables)
Collects and tracks the `time` and `time_close` value of every bar on the chart as well as a specified number of future bars. Additionally, tracks a custom set of variables for every chart bar.
Parameters:
barsForward (simple int) : Number of future bars to collect data for.
variables (simple map) : Custom values to collect on every chart bar.
Returns: `ChartData` object to convert between `xloc.bar_index` and `xloc.bar_time`.
█ EXPORTED METHODS
method timestampToBarIndex(chartData, timestamp, snap)
Converts a UNIX timestamp to a bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
timestamp (series int) : A UNIX time.
snap (series Snap) : A `Snap` enum value.
Returns: A bar index, or `na` if unable to find the appropriate bar index.
method getNumberOfBarsBack(chartData, timestamp)
Converts a UNIX timestamp to a history-referencing length (i.e., number of bars back).
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
timestamp (series int) : A UNIX time.
Returns: A bar offset, or `na` if unable to find a valid number of bars back.
method timeAtBarIndex(chartData, barIndex)
Retrieves the `time` value for the specified bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
barIndex (int) : The bar index.
Returns: The `time` value, or `na` if there is no `time` stored for the bar index.
method time(chartData, length)
Retrieves the `time` value of the bar that is `length` bars back relative to the latest bar.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
length (series int) : Number of bars back.
Returns: The `time` value `length` bars ago, or `na` if there is no `time` stored for that bar.
method timeCloseAtBarIndex(chartData, barIndex)
Retrieves the `time_close` value for the specified bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
barIndex (series int) : The bar index.
Returns: The `time_close` value, or `na` if there is no `time_close` stored for the bar index.
method timeClose(chartData, length)
Retrieves the `time_close` value of the bar that is `length` bars back from the latest bar.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
length (series int) : Number of bars back.
Returns: The `time_close` value `length` bars ago, or `na` if there is none stored.
method valueAtBarIndex(chartData, name, barIndex)
Retrieves the value of a custom variable for the specified bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
name (series string) : The variable name.
barIndex (series int) : The bar index.
Returns: The value of the variable, or `na` if that variable is not stored for the bar index.
method value(chartData, name, length)
Retrieves a variable value of the bar that is `length` bars back relative to the latest bar.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
name (series string) : The variable name.
length (series int) : Number of bars back.
Returns: The value `length` bars ago, or `na` if that variable is not stored for the bar index.
method getAllVariablesAtBarIndex(chartData, barIndex)
Retrieves all custom variables for the specified bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
barIndex (series int) : The bar index.
Returns: Map of all custom variables that are stored for the specified bar index.
method getEarliestStoredData(chartData)
Gets all values from the earliest bar data that is currently stored in memory.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
Returns: A tuple:
method getLatestStoredData(chartData, futureData)
Gets all values from the latest bar data that is currently stored in memory.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
futureData (series bool) : Whether to include the future data that is stored in memory.
Returns: A tuple:
Technical Summary VWAP | RSI | VolatilityTechnical Summary VWAP | RSI | Volatility
The Quantum Trading Matrix is a multi-dimensional market-analysis dashboard designed as an educational and idea-generation tool to help traders read price structure, participation, momentum and volatility in one compact view. It is not an automated execution system; rather, it aggregates lightweight “quantum” signals — VWAP position, momentum oscillator behaviour, multi-EMA trend scoring, volume flow and institutional activity heuristics, market microstructure pivots and volatility measures — and synthesizes them into a single, transparent score and signal recommendation. The primary goal is to make explicit why a given market looks favourable or unfavourable by showing the individual ingredients and how they combine, enabling traders to learn, test and form rules based on observable market mechanics.
Each module of the matrix answers a distinct market question. VWAP and its percentage distance indicate whether the current price is trading above or below the intraday volume-weighted average — a proxy for intraday institutional control and value. The quantum momentum oscillator (fast and slow EMA difference scaled to percent) captures short-to-intermediate momentum shifts, providing a quickly responsive view of directional pressure. Multi-EMA trend scoring (8/21/50) produces a simple, transparent trend score by counting conditions such as price above EMAs and cross-EMAs ordering; this score is used to categorize market trend into descriptive buckets (e.g., STRONG UP, WEAK UP, NEUTRAL, DOWN). Volume analysis compares current volume to a recent moving average and computes a Z-score to detect spikes and unusual participation; additional buy/sell pressure heuristics (buyingPressure, sellingPressure, flowRatio) estimate whether upside or downside participation dominates the bar. Institutional activity is approximated by flagging large orders relative to volume baseline (e.g., volume > 2.5× MA) and estimating a dark pool proxy; this is a heuristic to highlight bars that likely had large players involved.
The dashboard also performs market-structure detection with small pivot windows to identify recent local support/resistance areas and computes price position relative to the daily high/low (dailyMid, pricePosition). Volatility is measured via ATR divided by price and bucketed into LOW/NORMAL/HIGH/EXTREME categories to help you adapt stop sizing and expectational horizons. Finally, all these pieces feed an interpretable scoring function that rewards alignment: VWAP above, strong flow ratio, bullish trend score, bullish momentum, and favorable RSI zone add to the overall score which is presented as a 0–100 metric and a colored emoji indicator for at-a-glance assessment.
The mashup is purposeful: each indicator covers a failure mode of the other. For example, momentum readings can be misleading during volatility spikes; VWAP informs whether institutions are on the bid or offer; volume Z-score detects abnormal participation that can validate a breakout; multi-EMA score mitigates single-EMA whipsaws by requiring a combination of price/EMA conditions. Combining these signals increases information content while keeping each component explainable — a key compliance requirement. The script intentionally emphasizes transparency: when it shows a BUY/SELL/HOLD recommendation, the dashboard shows the underlying sub-components so a trader can see whether VWAP, momentum, volume, trend or structure primarily drove the score.
For practical use, adopt a clear workflow: (1) check the matrix score and read the component tiles (VWAP position, momentum, trend and volume) to understand the drivers; (2) confirm market-structure support/resistance and pricePosition relative to the daily range; (3) require at least two corroborating components (for example, VWAP ABOVE + Momentum BULLISH or Volume spike + Trend STRONG UP) before considering entries; (4) use ATR-based stops or daily pivot distance for stop placement and size positions such that the trade risks a small, pre-defined percent of capital; (5) for intraday scalps shorten holding time and tighten stops, for swing trades increase lookback lengths and require multi-timeframe (higher TF) agreement. Treat the matrix as an idea filter and replay lab: when an alert triggers, replay the bars and observe which components anticipated the move and which lagged.
Parameter tuning matters. Shortening the momentum length makes the oscillator more sensitive (useful for scalping), while lengthening it reduces noise for swing contexts. Volume profile bars and MA length should match the instrument’s liquidity — increase the MA for low-liquidity stocks to reduce false institutional flags. The trend multiplier and signal sensitivity parameters let you calibrate how aggressively the matrix counts micro evidence into the score. Always backtest parameter sets across multiple periods and instruments; run walk-forward tests and keep a simple out-of-sample validation window to reduce overfitting risk.
Limitations and failure modes are explicit: institutional flags and dark-pool estimates are heuristics and cannot substitute for true tape or broker-level order flow; volume split by price range is an approximation and will not perfectly reflect signed volume; pivot detection with small windows may miss larger structural swings; VWAP is typically intraday-centric and less meaningful across multi-day swing contexts; the score is additive and may not capture non-linear relationships between features in extreme market regimes (e.g., flash crashes, circuit breaker events, or overnight gaps). The matrix is also susceptible to false signals during major news releases when price and volume behavior dislocate from typical patterns. Users should explicitly test behavior around earnings, macro data and low-liquidity periods.
To learn with the matrix, perform these experiments: (A) collect all BUY/SELL alerts over a 6-month period and measure median outcome at 5, 20 and 60 bars; (B) require additional gating conditions (e.g., only accept BUY when flowRatio>60 and trendScore≥4) and compare expectancy; (C) vary the institutional threshold (2×, 2.5×, 3× volumeMA) to see how many true positive spikes remain; (D) perform multi-instrument tests to ensure parameters are not tuned to a single ticker. Document every test and prefer robust, slightly lower returns with clearer logic rather than tuned “optimal” results that fail out of sample.
Originality statement: This script’s originality lies in the curated combination of intraday value (VWAP), multi-EMA trend scoring, momentum percent oscillator, volume Z-score plus buy/sell flow heuristics and a compact, interpretable scoring system. The script is not a simple indicator mashup; it is a didactic ensemble specifically designed to make internal rationale visible so traders can learn how each market characteristic contributes to actionable probability. The tool’s novelty is its emphasis on interpretability — showing the exact contributing signals behind a composite score — enabling reproducible testing and educational value.
Finally, for TradingView publication, include a clear description listing the modules, a short non-technical summary of how they interact, the tunable inputs, limitations and a risk disclaimer. Remove any promotional content or external contact links. If you used trademark symbols, either provide registration details or remove them. This transparent documentation satisfies TradingView’s requirement that mashups justify their composition and teach users how to use them.
Quantum Trading Matrix — multi-factor intraday dashboard (educational use only).
Purpose: Combines intraday VWAP position, a fast/slow EMA momentum percent oscillator, multi-EMA trend scoring (8/21/50), volume Z-score and buy/sell flow heuristics, pivot-based microstructure detection, and ATR-based volatility buckets to produce a transparent, componentized market score and trade-idea indicator. The mashup is intentional: VWAP identifies intraday value, momentum detects short bursts, EMAs provide structural trend bias, and volume/flow confirm participation. Signals require alignment of at least two components (for example, VWAP ABOVE + Momentum BULLISH + positive flow) for higher confidence.
Inputs: momentum period, volume MA/profile length, EMA configuration (8/21/50), trend multiplier, signal sensitivity, color and display options. Use shorter momentum lengths for scalps and longer for swing analysis. Increase volume MA for thinly traded instruments.
Limitations: Institutional/dark-pool estimates and flow heuristics are approximations, not actual exchange tape. VWAP is intraday-focused. Expect false signals during major news or low-liquidity sessions. Backtest and paper-trade before applying real capital.
Risk Disclaimer: For education and analysis only. Not financial advice. Use proper risk management. The author is not responsible for trading losses.
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Risk & Misuse Disclaimer
This indicator is provided for education, analysis and idea generation only. It is not investment or financial advice and does not guarantee profits. Institutional activity flags, dark-pool estimates and flow heuristics are approximations and should not be treated as exchange tape. Backtest thoroughly and use demo/paper accounts before trading real capital. Always apply appropriate position sizing and stop-loss rules. The author is not responsible for any trading losses resulting from the use or misuse of this tool.
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Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
