SUPeR TReND 2.718An evolved version of the classic Supertrend, SUPeR TReND 2.718 is built to deliver elegant, high-precision trend detection using Euler's constant (e = 2.718) as its default multiplier. Designed for clarity and visual flow, this indicator brings together smooth line work, intelligent color logic, and a minimalistic tally system that tracks trend persistence — all in a highly customizable, overlay-ready format.
Unlike traditional implementations, this version maintains line visibility regardless of fill opacity, ensuring crisp tracking even in complex environments. Ideal for traders who value both aesthetics and actionable structure.
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🔑 Key Features:
- 📐 ATR-based Supertrend with default multiplier = e (2.718)
- 📉 Dynamic trend line with optional fill beneath price
- ⏳ Trend duration tally label (count-only or full format)
- ⬆️ Higher-timeframe Supertrend overlay (optional)
- 🟢 Directional candle coloring for clarity
- 🟡 Subtle anchor line to guide perception without clutter
- ⚙️ PineScript v6 compliant, efficient and modular
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🧠 Interpretation Guide:
- The Supertrend line tracks trend support or resistance — beneath price in uptrends, above in downtrends.
- The shaded fill reflects direction with 70% transparency.
- The trend tally label counts how long the current trend has lasted.
- Candle colors confirm direction without overtaking price action.
- The optional HTF line shows higher-timeframe context.
- A soft yellow anchor line stabilizes the fill relationship without distraction.
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⚙️ Inputs & Controls:
- ✏️ ATR Length – Volatility lookback
- 🧮 Multiplier – Default = 2.718 (Euler's number)
- 🕰️ Higher Timeframe – Choose your bias frame
- 👁️ Show HTF / Main – Toggle each trend layer
- 🧾 Show Label / Simplify – Show trend duration, with or without arrows
- 🎨 Color Candles – Turn directional bar coloring on or off
- 🪄 Show Fill – Toggle the shaded visual rhythm
- 🎛️ All visuals use tuned colors and transparencies for clarity
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🚀 Best Practices:
- ✅ Works on any time frame; shines on 1h v. 1D
- 🔁 Use the HTF line for macro bias filtering
- 📊 Combine with volume or liquidity overlays for edge
- 🧱 Use as a structural base layer with minimalist stacks
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📈 Strategy Tips:
- 🧭 MTF Trend Alignment: Enable the HTF line to filter trades. If the HTF trend is up, only take longs on the lower frame, and vice versa.
- 🔁 Pullback Entries: During a strong trend, consider short-term dips below the Supertrend line as possible re-entry zones — only if HTF remains aligned.
- ⏳ Tally for Exhaustion: When the bar count exceeds 15+, look for confluence (volume divergence, key levels, reversal signals).
- ⚠️ HTF Flip + Extended Trend: When the HTF trend reverses while the main trend is extended, that may be a macro exit or fade signal.
- 🚫 Solo Mode: Disable HTF and use the main trend + tally as a standalone signal layer.
- 🧠 Swing Setup Friendly: Especially powerful on 1D or 1h in swing systems or trend-based grid strategies.
Komut dosyalarını "mtf" için ara
Supply & Demand Zones
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Supply and Demand Zones
This indicator displays valid Supply and Demand zones on any chart and timeframe, using dynamically updating visuals. Users can see the moment that zones become validated, used, and then invalidated during live sessions. It is sleek, lightweight, and offers a feature-rich settings panel that allows customization of how each element appears and functions. Zones can enhance the probability of successful trades by locating areas that are most likely to contain resting orders of Supply or Demand, which are needed for price reversals.
Disclaimer
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Like all indicators, this can be a valuable tool when incorporated into a comprehensive, risk-based trading system.
Supply and Demand is not the same thing as Support and Resistance.
Trading based on price hitting a zone without understanding which zones are of higher quality and which are of lower quality (only discernible with a trained human eye) will yield poor results.
Supply and Demand works well as a system and even better when added to an existing one. However, like all effective trading techniques, it requires diligent study, practice, and repetition to become proficient. This is an indicator for use with Supply and Demand concepts, not a replacement for learning them.
Features
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Once a valid candle sequence is confirmed, a box will appear that displays the zone over the precise zone range. At 50% zone penetration, a zone becomes used , and at 100% it becomes invalidated . Each of these zone classifications changes the behavior of the zone on the chart immediately. The settings panel offers custom colors for Supply , Demand , Used , and Invalidated zone types.
Borders : The subtle border colors can be changed or hidden.
Boxes or Bases : Advanced users can opt to hide zone boxes and instead display small, subtle tags over base candle groups. This allows for more customizable selection over what is displayed and how.
Max Zones and Hide Invalidated :
There are limitations on how many objects TradingView allows at once. Because of this, once zones go from used to invalidated , they are hidden (deleted) by default. This allows the zones index to be allocated to display more valid , usable zones instead. If a user prefers to keep invalidated zones visible, they can be enabled; however, this will result in showing more recent zones for fewer historical zones.
All zones share one pool, so if you allow fifty max zones, forty-five might be supply while five might be demand on a big sell-off trend. You will always see the most recent zones, regardless of type or status.
It’s up to you how much clutter you want on your screen and how much improved load time you want - but once loaded, zone creation and function are always instantaneous.
Load Time
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Load time refers to the time it takes from when you switch tickers or timeframes before the zones are displayed initially. There is zero lag in the dynamic function and minimal load time, regardless of settings. However, if you are a fine-tuner or multi-screener, the number of Max Zones displayed is the only major variable affecting load time.
I run everything at Max when I develop. When I trade, I run mine at 25 max zones because I change timeframes often and want a very quick display of zones when I do. I have invalidated hidden, and simply enable it if I want to check an old zone. This gives me more zones than I need and reduces the load time to right where I like it.
Thresholds
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It is recommended to leave these as the default.
Base Body Threshold : Determines the maximum ratio of a candle’s body to wick before invalidation. Default (50% or 0.5). A higher number loosens thresholds, resulting in more zones being displayed.
Unrequire 2nd FT if LO is Strong & Strength Multiplier :
The standard logic sequence requires two Follow-Through candles. Under some strong price movement, Leg-Out candles can make an explosive directional move from a base, making a convincing argument for supply and demand perfectly at work, if not for a single Follow-Through candle instead of two.
By enabling this feature, you can tell the script to ignore second Follow-Through candles, if and only if, the Leg-Out candle's range is (Strength) X the base range. exceeds the range of the Base by a factor of X (Strength). ie: At 5x, this would require a Leg-Out range to be 500% the range of the Base.
If enabled and the Leg-Out is not strong enough, the default logic kicks in, and a second follow-through candle will validate the zone as per usual. This loosens thresholds overall and should result in more zones.
Recommended Usage
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Form a thesis using your primary trend trading system (eg: Elliott Wave, Structure Reversal, TheStrat, et al) to identify locations of a pullback for a long or short entry.
Identify a pullback area using your system, then use this indicator to find a high-quality zone on your chosen timeframe.
Once located, draw your own channel over the indicator's zone box. Start on 1m, check for zones, 2m, 3m, and so on. When you see a zone you like, recreate it; thus, when finished, you can see every timeframe’s highest-quality zones that you created, regardless of what timeframe you switch to. Tip: Be selective
To make the process faster, save a channel design in settings for “Demand” and one for “Supply”, then you can quickly get through this process in less than a minute with practice.
Optional: Use additional methods (eg: Fibonacci retracements, Elliott Wave Theory, Anchored VWAPs) to find congruent confirmation.
Version 1.0
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No known bugs remain from the closed beta.
In Development
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Powerful combination zones occur when standard zone sequences are extended with additional levels of demand or supply by adding more conditionals to the state machine logic. Got this mostly working in a dev version and it adds minimal extra resources. Set aside to polish a clean standard 1.0 for release first, but now displaying these extended zones is my top priority for next version.
MTF support is essentially working in a dev copy, but adds resources. Not sure if it is in the spirit of price action being the primary focus of a chart for serious traders, rather than indicators. If there is demand for it, I'll consider it.
Additional Threshold Settings
Thanks!
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Thank you for your interest in my work. This was a personal passion project of mine, and I was delighted it turned out better than I hoped, so I decided to share it. If you have any comments, bugs, or suggestions, please leave them here, or you can find me on Twitter or Discord.
@ ContrarianIRL
Open-source developer for over 25 years
EMA 10/55/200 - LONG ONLY MTF (4h with 1D & 1W confirmation)Title: EMA 10/55/200 - Long Only Multi-Timeframe Strategy (4h with 1D & 1W confirmation)
Description:
This strategy is designed for trend-following long entries using a combination of exponential moving averages (EMAs) on the 4-hour chart, confirmed by higher timeframe trends from the daily (1D) and weekly (1W) charts.
🔍 How It Works
🔹 Entry Conditions (4h chart):
EMA 10 crosses above EMA 55 and price is above EMA 55
OR
EMA 55 crosses above EMA 200
OR
EMA 10 crosses above EMA 500
These entries indicate short-term momentum aligning with medium/long-term trend strength.
🔹 Confirmation (multi-timeframe alignment):
Daily (1D): EMA 55 is above EMA 200
Weekly (1W): EMA 55 is above EMA 200
This ensures that we only enter long trades when the higher timeframes support an uptrend, reducing false signals during sideways or bearish markets.
🛑 Exit Conditions
Bearish crossover of EMA 10 below EMA 200 or EMA 500
Stop Loss: 5% below entry price
⚙️ Backtest Settings
Capital allocation per trade: 10% of equity
Commission: 0.1%
Slippage: 2 ticks
These are realistic conditions for crypto, forex, and stocks.
📈 Best Used On
Timeframe: 4h
Instruments: Trending markets like BTC/ETH, FX majors, or growth stocks
Works best in volatile or trending environments
⚠️ Disclaimer
This is a backtest tool and educational resource. Always validate on demo accounts before applying to real capital. Do your own due diligence.
MA CloudThis indicator plots a Moving Average (MA) cloud with ultra-smooth visuals, designed to help traders identify trend direction, momentum, and volatility in a clear and intuitive way.
Features:
Multiple MA types: choose between EMA, SMA, WMA, or RMA
Adaptive cloud width: based on standard deviation of price to visualize volatility
Smoothing controls: post-processed smoothing gives a silky, curved appearance
Multi-Timeframe (MTF) support: default to chart timeframe, or override to any custom timeframe (e.g. 1H, 1D, etc.)
Custom styling: adjustable colours, line thickness, and cloud opacity
Use cases:
Quickly assess trend strength and direction
Use cloud thickness as a volatility proxy
Spot pullback entries during trending conditions
Combine with price action or support/resistance for confluence
Settings:
MA Type – select your preferred moving average method
MA Length – period for the average
Cloud Width Factor – adjusts the distance of the cloud edges
Smoothing Length – softens the output for a polished look
Timeframe – optional override to analyse data from a higher or lower timeframe
Double Bollinger Bands MTF and Price projectionI did this script because I wanted to project prices over future bars quickly because I am a options trader.
Options:
Time frame: Default is Chart
Some times I prefer using 15 m with period 200 on a daily chart in a fast moving market. But you can chose what suites you
BB inner deviation 1 is default
When BB inner deviation=1 the outer will be 2X if its 0.5 outer will be 1
Moving Average type : Default EMA
Project next bar in label Default is off
This will calculate a linear projection of price of each band for the number of bars requested and print them in the label. It does not plot the future values
Using: in a trending market the prices will be generally be between band1 and band 2
and other times between -band1 and +band1. The projection can assist in optimal option strategy. Also in a fast moving market I would use 10 period ema for accurate price projections and others 20
Air Gap MTF with alert settingsWhat it shows:
This indicator will show a horizontal line at a price where each EMAs are on on different time frames, which will remove the effort of having to flick through different time frames or look at different chart.
The lines itself will move in real time as price moves and therefore as the EMA values changes so no need to manually adjustment the lines.
How to use it:
The price gap between each of the lines are known as "air gaps", which are essentially zones price can move with less resistance. Therefore bigger the airgap there is more likely more movement in price.
In other words, where lines are can be a resistance (or support) and can expect price stagnation or rejection.
On the chart it is clear to see lines are acting as resistances/supports.
Key settings:
The time frame are fixed to: 30min, 1hr and 4hr. This cannot be changed as of now.
EMA values for each time frame are user changeable in the settings, and up to 4 different values can be chosen for each time frame. Default is 5,12,34 and 50 for each timeframe.
Line colour, thickness and style can be user adjusted. Start point for where line will be drawn can be changed in the settings, either: start of day, user defined start or across the chart. In case of user defined scenario user can input a number that specifies a offset from current candle.
Label colour, font, alignment, text size and text itself can be user adjusted in the settings. Price can be also displayed if user chooses to do so. Position of label (offset from current candle) is user specified and can be adjusted by the user.
Both the lines and labels can be turned off (both and individually), for each lines.
Alert Settings:
Manually, user can set alerts for when price crosses a specific line.
This can be done by:
right click on any of line
choose first option (add alert on...)
On the second option under condition, use the dropdown menu to choose the desired EMA/timeframe to set alert for.
Hit "create" at bottom right of option
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If anything is not clear please let me know!
Multi-Timeframe Liquidity Zones V6 (Table)Multi-Timeframe Liquidity Zones V6 (Table) Indicator: Functionality and Uses
Overview: The Multi-Timeframe Liquidity Zones V6 (Table) indicator is a technical analysis tool that highlights key volume-based support and resistance levels across multiple timeframes. It leverages volume profile concepts – specifically the Point of Control (POC) and Value Area High/Low (VAH/VAL) – to identify “liquidity zones” where trading activity was heaviest . Unlike a standard single-timeframe volume profile, this indicator compiles data from several timeframes (e.g. monthly, weekly, daily, intraday) and displays the results in a convenient table format on the chart. The goal is to give traders a consolidated view of important price levels (derived from volume concentrations) across different horizons, helping them plan trades with a broader market perspective.
Purpose and Functionality of the Indicator
Multi-Timeframe Analysis: The primary objective of this indicator is to simplify multi-timeframe analysis of volume distribution. Rather than manually checking volume profiles on separate charts for each timeframe, the tool automatically calculates the key levels for each selected timeframe and presents them together. This includes higher-level perspectives (like monthly or weekly volume hotspots) alongside shorter-term levels (daily or hourly), ensuring that traders don’t miss significant zones from any timeframe . By offering a broader perspective on support and resistance levels, multi-timeframe tools help improve risk management and signal confirmation , and this indicator is designed to provide that volume-based perspective at a glance.
Table Format Display: Multi-Timeframe Liquidity Zones V6 (Table) specifically presents the information as a table (as opposed to plotting lines on the chart). Each row in the table typically corresponds to a timeframe (for example, Monthly, Weekly, Daily, 4H, 1H, 30M, 15M), and the columns list the calculated POC, VAH, VAL, and possibly the average volume for that timeframe’s look-back period. By structuring the data in a table, traders can quickly read off the exact price levels of these liquidity zones without having to visually trace lines. This format makes it easy to compare levels across timeframes or note where multiple timeframes’ levels cluster near the same price – a sign of especially strong support/resistance. The indicator uses a user-defined number of bars or length of history for each timeframe to calculate these values (so you can adjust how far back it looks to define the volume profile for each period).
Objective: In summary, the functionality is geared toward identifying high-liquidity price zones across multiple time scales and presenting them clearly. These high-liquidity zones often coincide with areas where price reacts (stalls, reverses, or accelerates) because a lot of trading activity (hence, orders and volume) took place there in the past. The indicator’s objective is to alert the trader to those areas in advance. It effectively answers questions like: “Where are the major volume concentration levels on the 1-hour, daily, and weekly charts right now?” and “Are there overlapping volume-based support/resistance levels from different timeframes around the current price?” By compiling this information, the indicator helps traders incorporate context from multiple timeframes in their decision-making, without needing to flip through numerous charts.
Identifying Liquidity Zones with POC, VAH, and VAL
Liquidity Zones Defined: In market terms, a “liquidity zone” is an area of the chart where a significant amount of trading occurred, meaning high liquidity (many buyers and sellers exchanged volume there). These zones often act as support or resistance because past heavy trading indicates consensus or interest around those price levels. This indicator identifies liquidity zones through volume profile analysis on each timeframe’s recent price action. Essentially, it looks at the distribution of trading volume at different prices over the specified period and finds the value area – the range of prices that encompassed the majority of that volume (commonly around 70% of the total volume ). Within that value area, it pinpoints the Point of Control (POC), which is the single price level that had the highest traded volume (the peak of the volume profile) . The upper and lower boundaries of that high-volume range are marked as Value Area High (VAH) and Value Area Low (VAL) respectively . Together, the VAH and VAL define the liquidity zone where the market spent most of its time and volume, and POC highlights the most traded price in that zone.
• Point of Control (POC): The POC is the price level with the greatest volume traded for the given period. It represents the price at which the most liquidity was exchanged – effectively the market’s “center of gravity” for that timeframe’s trading activity . The indicator calculates the POC for each selected timeframe by scanning the volume at each price; the price with maximum volume is flagged as that timeframe’s POC. In the table, the POC might be highlighted or listed as a key level (sometimes traders color-code it or mark it for emphasis). Because so many positions were opened or closed at the POC, it often serves as a strong support/resistance. For example, if price falls to a major POC from above, traders expect buyers may step in there (since it was a popular buy/sell level historically), potentially causing a bounce. Conversely, if price breaks through a POC decisively, it may signal a significant shift in market acceptance.
• Value Area High (VAH) and Low (VAL): The VAH and VAL are the price boundaries of the value area, which is typically defined to contain about 70% of the total traded volume for the period . In other words, between VAH and VAL is where the “bulk” of trading occurred, and outside this range is where relatively less volume traded. The indicator derives VAH/VAL by accumulating volume from the highest-volume price (POC) outward until ~70% of volume is covered (this is a common method for volume profile value area). VAH is the top of this high-volume region and VAL is the bottom. These levels are important because they often act like support/resistance boundaries: when price is inside the value area, it’s in a high-liquidity zone and tends to oscillate between VAH and VAL; when price moves above VAH or below VAL, it’s leaving the high-volume zone, which can indicate a potential trend or imbalance (price entering a lower-liquidity area where it might move faster until finding the next liquidity zone). Traders watch VAH/VAL for signs of rejection or acceptance: for instance, a price rally that falters at VAH suggests that level is acting as resistance (sellers defending that high-volume area), whereas if price pushes above VAH, it may continue until the next timeframe’s zone or until it finds new interest. The Multi-Timeframe Liquidity Zones V6 indicator gives the VAH and VAL for each timeframe, essentially mapping out the upper and lower bounds of key liquidity zones at those scales.
How the Indicator Identifies These: Under the hood, the indicator likely uses historical price and volume data for each timeframe’s lookback window. For each timeframe (say the last 20 weekly bars for a weekly profile, last 100 daily bars for a daily profile, etc.), it constructs a volume profile (a histogram of volume at each price). From that distribution, it finds the POC (highest volume bin) and calculates VAH/VAL around it. The output is a set of numbers (price levels) that mark where those zones lie. In practice, if using the Lines version of this indicator, those levels are drawn as horizontal lines on the chart and labeled by timeframe (e.g., a line at 1.2345 labeled “D POC” for Daily POC) . In the Table version, those values are instead listed in text form. Either way, the identification process is the same – it’s finding the high-volume price regions on each timeframe and calling them out. By doing this for multiple timeframes concurrently, the indicator reveals how these liquidity zones from different periods relate to each other. For example, you might discover that a daily-chart value area overlaps with a weekly-chart POC, creating a particularly strong zone of interest. This kind of insight is hard to get from a single timeframe analysis alone.
Volume Profile Data Across Multiple Timeframes
Multiple Timeframes in One View: One of the biggest advantages of this indicator is the ability to see volume profile information from various timeframes side by side. Traders often perform multiple timeframe analysis to get a fuller picture — for instance, checking monthly or weekly levels for long-term context while planning a trade on a 4-hour chart. This indicator automates that process for volume-based levels. The table will typically list each chosen timeframe (which could be preset or user-selected). For each timeframe, you get the POC, VAH, VAL, and possibly an average volume metric. The “average volume” likely refers to the average volume per bar or the average volume traded over the profile’s duration for that timeframe, which gives a sense of how significant that period’s activity is. For example, a weekly profile might show an average volume of say 500k per week, versus a daily profile average of 80k per day – indicating the scale of trading on weekly vs daily. High average volume on a timeframe means its liquidity zones were formed with a lot of participation, possibly making them more reliable support/resistance. By comparing these, traders can gauge which timeframes had unusually high or low activity recently. The table format makes such comparisons straightforward.
Identification of Confluence: Because all the data is presented together, traders can quickly spot confluence or overlaps between timeframes. If two different timeframes show liquidity zones at similar price levels, that price becomes extremely noteworthy. For instance, suppose the indicator shows: a 1-hour POC at 1.1300, a 4-hour VAL at 1.1280, and a daily VAL at 1.1290. These are all in a tight range – effectively indicating a multi-timeframe liquidity zone around 1.1280–1.1300. A trader seeing this cluster in the table will recognize that as a strong support area, since multiple profiles from intraday to daily all suggest heavy trading interest there. Similarly, overlaps of VAH (resistance zone) from different timeframes could signal a strong ceiling. The multi-timeframe view prevents a trader from, say, going long into a major weekly POC above, or shorting when there’s a huge monthly value-area low just below – situations where awareness of higher timeframe volume structure can make the difference between a good and bad trade.
User Customization: The indicator is flexible in that you can typically adjust which timeframes to include and how many bars to use for each timeframe’s calculation. For example, one might configure it to calculate monthly levels using the past 12 monthly bars (1 year of data), weekly levels using the past 20 weeks, daily using 100 days, etc., depending on preference. By tuning the “bars count” or period length , the trader can focus on recent liquidity zones or incorporate more history if desired. Shorter lookback might catch more recent shifts in volume distribution (important if the market structure changed recently), while longer lookback gives more established levels. This customization ensures the indicator’s output can be tailored to different trading styles (short-term vs swing vs long-term investing). Regardless of settings, the multi-timeframe table allows simultaneous visibility of the chosen timeframes’ volume landscape. This comprehensive view is the core strength: it consolidates data that normally requires flipping through multiple charts.
Using the Liquidity Zones Data for Trading Decisions
Traders can use the information from the MTF Liquidity Zones V6 (Table) indicator in several practical ways to enhance their decision-making:
• Identify Support and Resistance: Each liquidity zone acts as a potential support or resistance area. For example, if the table shows a daily VAH at a certain level above the current price, that level might serve as resistance if the price rallies up to it (since it marks the top of a high-volume region where sellers might step in). Conversely, a weekly VAL below current price could act as support on a dip. By noting these levels in the table, a trader planning an entry or exit can anticipate where the price might stall or reverse. Essentially, you get a map of high-interest price levels from different timeframes, which you can mark on your trading chart for guidance.
• Plan Entries and Exits Around Key Levels: Many traders incorporate volume profile levels into their strategies, for instance: buying near VAL (betting that the value area will hold and price will revert upward), or selling/shorting near VAH (expecting the top of value to hold as resistance), or trading breakouts when price moves outside the value area. With the multi-timeframe table, one can refine these tactics by also considering higher timeframe levels. Suppose you see that on the 1-hour chart the price is just above its 1H POC, but the table indicates that just slightly above, there’s also the daily POC. You might delay a long entry until price clears that daily POC, because that could be a stronger intraday barrier. Or if you intend to take profit on a long trade, you might choose a target just below a weekly VAH since price may struggle to climb past that on the first attempt. The indicator thus acts as a guide for precision in entry/exit decisions, aligning them with where liquidity is high.
• Gauge Trend Strength and Directional Bias: By observing where current price is relative to these volume zones, traders can infer certain market conditions. For instance, if price is trading above the VAH of multiple timeframes’ value areas, it suggests the market is in a more bullish or overextended territory (price accepted above prior value), whereas if price is below multiple VALs, it’s in bearish or undervalued territory relative to recent history. If the price stays around a POC, it indicates consolidation or equilibrium (market comfortable at that price). Traders can use this context for bias – e.g., if price is above the weekly VAH, you might lean bullish but watch for potential pullbacks to that VAH level (now a support). If price is below the monthly VAL, you might avoid longs until it re-enters that value area. In essence, the liquidity zones provide context of value vs. price: is price trading within the high-volume areas (implying range-bound behavior) or outside them (implying a breakout or trending move)? This can prevent chasing trades at poor locations.
• Combine with Other Indicators/Analysis: It’s generally advised to not use any single indicator in isolation, and this holds true here. The liquidity zones from this indicator are best used alongside price action or other technical signals for confirmation . For example, if a bullish candlestick reversal pattern forms right at a confluence of a 4H VAL and Daily POC, that’s a stronger buy signal than the pattern alone. Or if an oscillator shows overbought exactly as price hits a weekly VAH, it adds conviction to a possible short. The indicator’s table basically gives you a shortlist of critical price levels; you can then watch how price behaves at those levels (via candlesticks, order flow, etc.) to make the final trade decision. Traders might set alerts for when price approaches one of the listed levels, or they might drop down to a lower timeframe to fine-tune an entry once a key zone is reached. By integrating this volume-based insight with trend analysis, chart patterns, or momentum indicators, one can make more informed and high-probability decisions rather than trading in the dark.
• Risk Management and Stop Placement: High-liquidity zones can also inform stop-loss placement. Ideally, you want your stop on the other side of a strong support/resistance. If you go long near a VAL, you might place your stop just below the VAL (since a move beyond that suggests the high-volume zone didn’t hold). If you short near a VAH, a stop just above the VAH or POC could be logical. Moreover, if multiple timeframes show overlapping zones, a stop beyond all of them could be even safer (albeit at the cost of a wider stop). The indicator helps identify those spots. It also warns you of where not to put a stop – for example, placing a stop-loss right at a POC might be unwise because price could gravitate to that POC repeatedly (due to its magnetic effect as a high-volume price). Instead, a trader might choose a stop beyond the far side of the value area. By using the table’s information, you can align your risk management with areas of high liquidity, reducing the chance of being whipsawed by normal volatility around heavily traded levels .
Benefits of the Multi-Timeframe Liquidity Zones Indicator
Using the Multi-Timeframe Liquidity Zones V6 (Table) indicator offers several key benefits for traders, ultimately aiming to streamline analysis and improve decision quality:
• Consolidated Key Levels: It provides a clear, consolidated view of crucial volume-driven levels from multiple timeframes all at once . This saves time and ensures you always account for major support/resistance zones that come from higher or lower timeframe volume clusters. You won’t accidentally overlook a significant weekly level while focused on a 15-minute chart, for example.
• Enhanced Multi-Timeframe Insight: By aligning information from long-term and short-term periods, the indicator helps traders see the “bigger picture” while still operating on their preferred timeframe. This multi-scale awareness can improve trade timing and confidence. You’re effectively doing multi-timeframe analysis with volume profiles in an efficient manner, which can confirm or caution your trade ideas (e.g., a trend looks strong on the 1H, but the table shows a huge monthly VAH just overhead – a reason to be cautious or take profit early).
• Improved Decision Making and Precision: Knowing where liquidity zones lie allows for more precise entries, exits, and stop placements. Traders can make informed decisions such as waiting for a pullback to a value area before entering, or taking profits before price hits a major POC from a higher timeframe. These decisions are grounded in objectively important price levels, potentially leading to higher probability trades and better risk-reward setups. It essentially enhances your strategy by adding a layer of volume context – you’re trading with an awareness of where the market’s interest is heaviest.
• Volume-Based Confirmation: Price alone can sometimes be deceptive, but volume tells the true story of participation. The liquidity zones indicator provides volume-based confirmation of support/resistance. If a price level is identified by this tool, it’s because significant volume happened there – adding weight to that level’s importance. This can help filter out false support/resistance levels that aren’t backed by volume. In other words, it highlights high-quality levels that many traders (and possibly institutions) have shown interest in.
• Adaptable to Different Trading Styles: Whether one is a scalper looking at intraday (15M, 5M charts) or a swing trader focusing on daily/weekly, the indicator can be configured to those needs. You choose which timeframes and how much data to consider. This means the concept of liquidity zones can be applied universally – from spotting intraday pivot levels with volume, to seeing long-term value zones on an investment. The consistent methodology of POC/VAH/VAL across scales provides a common framework to analyze any market and timeframe.
• Informed Risk Management: As discussed, the knowledge of multi-timeframe volume zones aids in risk management. By placing stops beyond major liquidity areas or avoiding trades that run into strong volume walls, traders can reduce the likelihood of whipsaw losses. It’s an extra layer of defense to ensure your trade plan accounts for where the market has historically found lots of interest (hence likely friction). This level of informed planning can be the difference between a well-managed trade and an avoidable loss.
In conclusion, the Multi-Timeframe Liquidity Zones V6 (Table) indicator serves as a powerful analytical aid, giving traders a structured view of where price is likely to encounter support or resistance based on volume concentrations across timeframes. Its functionality centers on identifying those liquidity zones (via POC, VAH, VAL) and presenting them in an easy-to-read format, while its ultimate purpose is to help traders make more informed decisions. By integrating this tool into their workflow, traders can more confidently navigate price action, knowing the objective volume-based landmarks that lie ahead. Remember that while these volume levels often coincide with strong S/R zones, it’s best to use them in conjunction with other technical or fundamental analysis for confirmation . When used appropriately, the indicator can streamline multi-timeframe analysis and enhance your overall trading strategy , giving you an edge in identifying where the market’s liquidity (and opportunity) resides.
real_time_candlesIntroduction
The Real-Time Candles Library provides comprehensive tools for creating, manipulating, and visualizing custom timeframe candles in Pine Script. Unlike standard indicators that only update at bar close, this library enables real-time visualization of price action and indicators within the current bar, offering traders unprecedented insight into market dynamics as they unfold.
This library addresses a fundamental limitation in traditional technical analysis: the inability to see how indicators evolve between bar closes. By implementing sophisticated real-time data processing techniques, traders can now observe indicator movements, divergences, and trend changes as they develop, potentially identifying trading opportunities much earlier than with conventional approaches.
Key Features
The library supports two primary candle generation approaches:
Chart-Time Candles: Generate real-time OHLC data for any variable (like RSI, MACD, etc.) while maintaining synchronization with chart bars.
Custom Timeframe (CTF) Candles: Create candles with custom time intervals or tick counts completely independent of the chart's native timeframe.
Both approaches support traditional candlestick and Heikin-Ashi visualization styles, with options for moving average overlays to smooth the data.
Configuration Requirements
For optimal performance with this library:
Set max_bars_back = 5000 in your script settings
When using CTF drawing functions, set max_lines_count = 500, max_boxes_count = 500, and max_labels_count = 500
These settings ensure that you will be able to draw correctly and will avoid any runtime errors.
Usage Examples
Basic Chart-Time Candle Visualization
// Create real-time candles for RSI
float rsi = ta.rsi(close, 14)
Candle rsi_candle = candle_series(rsi, CandleType.candlestick)
// Plot the candles using Pine's built-in function
plotcandle(rsi_candle.Open, rsi_candle.High, rsi_candle.Low, rsi_candle.Close,
"RSI Candles", rsi_candle.candle_color, rsi_candle.candle_color)
Multiple Access Patterns
The library provides three ways to access candle data, accommodating different programming styles:
// 1. Array-based access for collection operations
Candle candles = candle_array(source)
// 2. Object-oriented access for single entity manipulation
Candle candle = candle_series(source)
float value = candle.source(Source.HLC3)
// 3. Tuple-based access for functional programming styles
= candle_tuple(source)
Custom Timeframe Examples
// Create 20-second candles with EMA overlay
plot_ctf_candles(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 20,
timezone = -5,
tied_open = true,
ema_period = 9,
enable_ema = true
)
// Create tick-based candles (new candle every 15 ticks)
plot_ctf_tick_candles(
source = close,
candle_type = CandleType.heikin_ashi,
number_of_ticks = 15,
timezone = -5,
tied_open = true
)
Advanced Usage with Custom Visualization
// Get custom timeframe candles without automatic plotting
CandleCTF my_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 30
)
// Apply custom logic to the candles
float ema_values = my_candles.ctf_ema(14)
// Draw candles and EMA using time-based coordinates
my_candles.draw_ctf_candles_time()
ema_values.draw_ctf_line_time(line_color = #FF6D00)
Library Components
Data Types
Candle: Structure representing chart-time candles with OHLC, polarity, and visualization properties
CandleCTF: Extended candle structure with additional time metadata for custom timeframes
TickData: Structure for individual price updates with time deltas
Enumerations
CandleType: Specifies visualization style (candlestick or Heikin-Ashi)
Source: Defines price components for calculations (Open, High, Low, Close, HL2, etc.)
SampleType: Sets sampling method (Time-based or Tick-based)
Core Functions
get_tick(): Captures current price as a tick data point
candle_array(): Creates an array of candles from price updates
candle_series(): Provides a single candle based on latest data
candle_tuple(): Returns OHLC values as a tuple
ctf_candles_array(): Creates custom timeframe candles without rendering
Visualization Functions
source(): Extracts specific price components from candles
candle_ctf_to_float(): Converts candle data to float arrays
ctf_ema(): Calculates exponential moving averages for candle arrays
draw_ctf_candles_time(): Renders candles using time coordinates
draw_ctf_candles_index(): Renders candles using bar index coordinates
draw_ctf_line_time(): Renders lines using time coordinates
draw_ctf_line_index(): Renders lines using bar index coordinates
Technical Implementation Notes
This library leverages Pine Script's varip variables for state management, creating a sophisticated real-time data processing system. The implementation includes:
Efficient tick capturing: Samples price at every execution, maintaining temporal tracking with time deltas
Smart state management: Uses a hybrid approach with mutable updates at index 0 and historical preservation at index 1+
Temporal synchronization: Manages two time domains (chart time and custom timeframe)
The tooltip implementation provides crucial temporal context for custom timeframe visualizations, allowing users to understand exactly when each candle formed regardless of chart timeframe.
Limitations
Custom timeframe candles cannot be backtested due to Pine Script's limitations with historical tick data
Real-time visualization is only available during live chart updates
Maximum history is constrained by Pine Script's array size limits
Applications
Indicator visualization: See how RSI, MACD, or other indicators evolve in real-time
Volume analysis: Create custom volume profiles independent of chart timeframe
Scalping strategies: Identify short-term patterns with precisely defined time windows
Volatility measurement: Track price movement characteristics within bars
Custom signal generation: Create entry/exit signals based on custom timeframe patterns
Conclusion
The Real-Time Candles Library bridges the gap between traditional technical analysis (based on discrete OHLC bars) and the continuous nature of market movement. By making indicators more responsive to real-time price action, it gives traders a significant edge in timing and decision-making, particularly in fast-moving markets where waiting for bar close could mean missing important opportunities.
Whether you're building custom indicators, researching price patterns, or developing trading strategies, this library provides the foundation for sophisticated real-time analysis in Pine Script.
Implementation Details & Advanced Guide
Core Implementation Concepts
The Real-Time Candles Library implements a sophisticated event-driven architecture within Pine Script's constraints. At its heart, the library creates what's essentially a reactive programming framework handling continuous data streams.
Tick Processing System
The foundation of the library is the get_tick() function, which captures price updates as they occur:
export get_tick(series float source = close, series float na_replace = na)=>
varip float price = na
varip int series_index = -1
varip int old_time = 0
varip int new_time = na
varip float time_delta = 0
// ...
This function:
Samples the current price
Calculates time elapsed since last update
Maintains a sequential index to track updates
The resulting TickData structure serves as the fundamental building block for all candle generation.
State Management Architecture
The library employs a sophisticated state management system using varip variables, which persist across executions within the same bar. This creates a hybrid programming paradigm that's different from standard Pine Script's bar-by-bar model.
For chart-time candles, the core state transition logic is:
// Real-time update of current candle
candle_data := Candle.new(Open, High, Low, Close, polarity, series_index, candle_color)
candles.set(0, candle_data)
// When a new bar starts, preserve the previous candle
if clear_state
candles.insert(1, candle_data)
price.clear()
// Reset state for new candle
Open := Close
price.push(Open)
series_index += 1
This pattern of updating index 0 in real-time while inserting completed candles at index 1 creates an elegant solution for maintaining both current state and historical data.
Custom Timeframe Implementation
The custom timeframe system manages its own time boundaries independent of chart bars:
bool clear_state = switch settings.sample_type
SampleType.Ticks => cumulative_series_idx >= settings.number_of_ticks
SampleType.Time => cumulative_time_delta >= settings.number_of_seconds
This dual-clock system synchronizes two time domains:
Pine's execution clock (bar-by-bar processing)
The custom timeframe clock (tick or time-based)
The library carefully handles temporal discontinuities, ensuring candle formation remains accurate despite irregular tick arrival or market gaps.
Advanced Usage Techniques
1. Creating Custom Indicators with Real-Time Candles
To develop indicators that process real-time data within the current bar:
// Get real-time candles for your data
Candle rsi_candles = candle_array(ta.rsi(close, 14))
// Calculate indicator values based on candle properties
float signal = ta.ema(rsi_candles.first().source(Source.Close), 9)
// Detect patterns that occur within the bar
bool divergence = close > close and rsi_candles.first().Close < rsi_candles.get(1).Close
2. Working with Custom Timeframes and Plotting
For maximum flexibility when visualizing custom timeframe data:
// Create custom timeframe candles
CandleCTF volume_candles = ctf_candles_array(
source = volume,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 60
)
// Convert specific candle properties to float arrays
float volume_closes = volume_candles.candle_ctf_to_float(Source.Close)
// Calculate derived values
float volume_ema = volume_candles.ctf_ema(14)
// Create custom visualization
volume_candles.draw_ctf_candles_time()
volume_ema.draw_ctf_line_time(line_color = color.orange)
3. Creating Hybrid Timeframe Analysis
One powerful application is comparing indicators across multiple timeframes:
// Standard chart timeframe RSI
float chart_rsi = ta.rsi(close, 14)
// Custom 5-second timeframe RSI
CandleCTF ctf_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 5
)
float fast_rsi_array = ctf_candles.candle_ctf_to_float(Source.Close)
float fast_rsi = fast_rsi_array.first()
// Generate signals based on divergence between timeframes
bool entry_signal = chart_rsi < 30 and fast_rsi > fast_rsi_array.get(1)
Final Notes
This library represents an advanced implementation of real-time data processing within Pine Script's constraints. By creating a reactive programming framework for handling continuous data streams, it enables sophisticated analysis typically only available in dedicated trading platforms.
The design principles employed—including state management, temporal processing, and object-oriented architecture—can serve as patterns for other advanced Pine Script development beyond this specific application.
------------------------
Library "real_time_candles"
A comprehensive library for creating real-time candles with customizable timeframes and sampling methods.
Supports both chart-time and custom-time candles with options for candlestick and Heikin-Ashi visualization.
Allows for tick-based or time-based sampling with moving average overlay capabilities.
get_tick(source, na_replace)
Captures the current price as a tick data point
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
na_replace (float) : Optional - Value to use when source is na
Returns: TickData structure containing price, time since last update, and sequential index
candle_array(source, candle_type, sync_start, bullish_color, bearish_color)
Creates an array of candles based on price updates
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
sync_start (simple bool) : Optional - Whether to synchronize with the start of a new bar
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of Candle objects ordered with most recent at index 0
candle_series(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides a single candle based on the latest price data
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: A single Candle object representing the current state
candle_tuple(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides candle data as a tuple of OHLC values
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Tuple representing current candle values
method source(self, source, na_replace)
Extracts a specific price component from a Candle
Namespace types: Candle
Parameters:
self (Candle)
source (series Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
na_replace (float) : Optional - Value to use when source value is na
Returns: The requested price value from the candle
method source(self, source)
Extracts a specific price component from a CandleCTF
Namespace types: CandleCTF
Parameters:
self (CandleCTF)
source (simple Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
Returns: The requested price value from the candle as a varip
method candle_ctf_to_float(self, source)
Converts a specific price component from each CandleCTF to a float array
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
Returns: Array of float values extracted from the candles, ordered with most recent at index 0
method ctf_ema(self, ema_period)
Calculates an Exponential Moving Average for a CandleCTF array
Namespace types: array
Parameters:
self (array)
ema_period (simple float) : Period for the EMA calculation
Returns: Array of float values representing the EMA of the candle data, ordered with most recent at index 0
method draw_ctf_candles_time(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar time coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using time-based x-coordinates
method draw_ctf_candles_index(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar index coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using index-based x-coordinates
method draw_ctf_line_time(self, source, line_size, line_color)
Renders a line representing a price component from the candles using time coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_time(self, line_size, line_color)
Renders a line from a varip float array using time coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_index(self, source, line_size, line_color)
Renders a line representing a price component from the candles using index coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
method draw_ctf_line_index(self, line_size, line_color)
Renders a line from a varip float array using index coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots tick-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots tick-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots time-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots time-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_candles(source, candle_type, sample_type, number_of_ticks, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, enable_ema, line_width, ema_color, use_time_indexing)
Unified function for plotting candles with comprehensive options
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Optional - Type of candle chart to display
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
ema_period (simple float) : Optional - Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
enable_ema (bool) : Optional - Whether to display the EMA overlay
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with optional EMA overlay
ctf_candles_array(source, candle_type, sample_type, number_of_ticks, number_of_seconds, tied_open, bullish_color, bearish_color)
Creates an array of custom timeframe candles without rendering them
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to create (candlestick or Heikin-Ashi)
sample_type (simple SampleType) : Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of CandleCTF objects ordered with most recent at index 0
Candle
Structure representing a complete candle with price data and display properties
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
candle_color (series color) : Color to use when rendering the candle
ready (series bool) : Boolean indicating if candle data is valid and ready for use
TickData
Structure for storing individual price updates
Fields:
price (series float) : The price value at this tick
time_delta (series float) : Time elapsed since the previous tick in milliseconds
series_index (series int) : Sequential index identifying this tick
CandleCTF
Structure representing a custom timeframe candle with additional time metadata
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
open_time (series int) : Timestamp marking when the candle was opened (in Unix time)
time_delta (series float) : Duration of the candle in milliseconds
candle_color (series color) : Color to use when rendering the candle
Bias TableOverview
The Bias Table Indicator is a multi-timeframe analysis tool designed to provide a quick sentiment overview across multiple timeframes. It combines signals from Moving Averages (MAs) and Oscillators to determine market bias, helping traders make more informed decisions.
Key Features
✔ Multi-Timeframe Analysis (MTF) – Displays market bias across up to five timeframes.
✔ Customizable Signals – Choose whether bias is based on Moving Averages (MAs), Oscillators, or a combination of both.
✔ Visual Table Format – The indicator presents the bias as a color-coded table in the bottom-right corner of the chart for quick reference.
✔ Adjustable Colors & Display Settings – Users can customize colors for different sentiment states (Strong Buy, Buy, Neutral, Sell, Strong Sell).
How It Works
Bias Calculation: The indicator evaluates market conditions using preset values (which can be replaced with actual logic) to determine sentiment for each timeframe.
Multi-Timeframe Support: The table can display bias from hourly to monthly timeframes, giving traders a broader view of market conditions.
Customizable Signals: Users can filter the table to show bias based only on MAs, Oscillators, or a combination of both.
Interpreting the Table
📊 Timeframes: The leftmost column shows selected timeframes (e.g., 1H, 4H, 1D, 1W, 1M).
📈 Signal Columns:
MAs – Bias based on Moving Averages.
Oscillators – Bias based on momentum indicators like RSI, Stochastics, etc.
All – A combined bias based on both MAs & Oscillators.
🚦 Color-Coded Ratings:
🔵 Strong Buy – High bullish strength.
🔹 Buy – Moderate bullish sentiment.
⚪ Neutral – No clear trend.
🔸 Sell – Moderate bearish sentiment.
🔴 Strong Sell – High bearish strength.
Best Used For:
📈 Trend Confirmation: Validate signals from your primary strategy.
⏳ Multi-Timeframe Analysis: See whether short-term and long-term trends align.
⚡ Quick Sentiment Check: Get a high-level view of market conditions without analyzing multiple indicators separately.
Customization Options:
Select which timeframes to include in the table.
Choose whether to base bias on MAs, Oscillators, or both.
Adjust colors for each signal type.
Multi-Timeframe MACD Strategy ver 1.0Multi-Timeframe MACD Strategy: Enhanced Trend Trading with Customizable Entry and Trailing Stop
This strategy utilizes the Moving Average Convergence Divergence (MACD) indicator across multiple timeframes to identify strong trends, generate precise entry and exit signals, and manage risk with an optional trailing stop loss. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trade accuracy, reduce exposure to false signals, and capture larger market moves.
Key Features:
Dual Timeframe Analysis: Calculates and analyzes the MACD on both the current chart's timeframe and a user-selected higher timeframe (e.g., Daily MACD on a 1-hour chart). This provides a broader market context, helping to confirm trends and filter out short-term noise.
Configurable MACD: Fine-tune the MACD calculation with adjustable Fast Length, Slow Length, and Signal Length parameters. Optimize the indicator's sensitivity to match your trading style and the volatility of the asset.
Flexible Entry Options: Choose between three distinct entry types:
Crossover: Enters trades when the MACD line crosses above (long) or below (short) the Signal line.
Zero Cross: Enters trades when the MACD line crosses above (long) or below (short) the zero line.
Both: Combines both Crossover and Zero Cross signals, providing more potential entry opportunities.
Independent Timeframe Control: Display and trade based on the current timeframe MACD, the higher timeframe MACD, or both. This allows you to focus on the information most relevant to your analysis.
Optional Trailing Stop Loss: Implements a configurable trailing stop loss to protect profits and limit potential losses. The trailing stop is adjusted dynamically as the price moves in your favor, based on a user-defined percentage.
No Repainting: Employs lookahead=barmerge.lookahead_off in the request.security() function to prevent data leakage and ensure accurate backtesting and real-time signals.
Clear Visual Signals (Optional): Includes optional plotting of the MACD and Signal lines for both timeframes, with distinct colors for easy visual identification. These plots are for visual confirmation and are not required for the strategy's logic.
Suitable for Various Trading Styles: Adaptable to swing trading, day trading, and trend-following strategies across diverse markets (stocks, forex, cryptocurrencies, etc.).
Fully Customizable: All parameters are adjustable, including timeframes, MACD Settings, Entry signal type and trailing stop settings.
How it Works:
MACD Calculation: The strategy calculates the MACD (using the standard formula) for both the current chart's timeframe and the specified higher timeframe.
Trend Identification: The relationship between the MACD line, Signal line, and zero line is used to determine the current trend for each timeframe.
Entry Signals: Buy/sell signals are generated based on the selected "Entry Type":
Crossover: A long signal is generated when the MACD line crosses above the Signal line, and both timeframes are in agreement (if both are enabled). A short signal is generated when the MACD line crosses below the Signal line, and both timeframes are in agreement.
Zero Cross: A long signal is generated when the MACD line crosses above the zero line, and both timeframes agree. A short signal is generated when the MACD line crosses below the zero line and both timeframes agree.
Both: Combines Crossover and Zero Cross signals.
Trailing Stop Loss (Optional): If enabled, a trailing stop loss is set at a specified percentage below (for long positions) or above (for short positions) the entry price. The stop-loss is automatically adjusted as the price moves favorably.
Exit Signals:
Without Trailing Stop: Positions are closed when the MACD signals reverse according to the selected "Entry Type" (e.g., a long position is closed when the MACD line crosses below the Signal line if using "Crossover" entries).
With Trailing Stop: Positions are closed if the price hits the trailing stop loss.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to assess its performance and optimize parameters for different assets and timeframes.
Example Use Cases:
Confirming Trend Strength: A trader on a 1-hour chart sees a bullish MACD crossover on the current timeframe. They check the MTF MACD strategy and see that the Daily MACD is also bullish, confirming the strength of the uptrend.
Filtering Noise: A trader using a 15-minute chart wants to avoid false signals from short-term volatility. They use the strategy with a 4-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and enables the trailing stop loss. As the price rises, the trailing stop is automatically adjusted upwards, protecting profits. The trade is exited either when the MACD reverses or when the price hits the trailing stop.
Disclaimer:
The MACD is a lagging indicator and can produce false signals, especially in ranging markets. This strategy is for educational and informational purposes only and should not be considered financial advice. Backtest and optimize the strategy thoroughly, combine it with other technical analysis tools, and always implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Multi-Timeframe EMA [TradeWithRon]Multi-Timeframe EMA Indicator
This indicator displays an Exponential Moving Average (EMA) from a higher timeframe on a lower timeframe chart. The EMA is a type of moving average that gives more weight to recent prices, making it more responsive to price changes compared to a Simple Moving Average (SMA). By overlaying a higher timeframe EMA on a lower timeframe chart, you can gain insights into the broader trend while analyzing price action at a more granular level.
🔶 FEATURES
* 5 MTF EMA with price and timeframe labels
* Smoothing: Alter the smoothness of the back-end EMA calculations.
* VWAP
Why Use EMA
Trend Identification: When the price is above the EMA, it suggests an uptrend, while a price below the EMA indicates a downtrend. The steeper the slope of the EMA, the stronger the trend.
Crossovers : A common strategy is to look for crossovers, such as when a short-term EMA crosses above a long-term EMA, signaling a potential buying opportunity (bullish crossover), or when a short-term EMA crosses below a long-term EMA, signaling a potential selling opportunity (bearish crossover).
Support and Resistance : EMAs can act as dynamic support and resistance levels. In an uptrend, the price may bounce off the EMA as support, while in a downtrend, it can act as resistance.
Convergence and Divergence: Traders look for divergences between price and the EMA to spot potential trend reversals. For example, if price makes a new high but the EMA doesn't, it could signal weakening momentum.
Overall, the EMA helps traders follow the market trend, spot potential reversals, and make more informed trading decisions.
After EMA Crosses you may experience A MSS, CISD, SFP. You can use all of these as confluence for a higher probability trade. This is a good way to capitalize on a trade
Another Case
How I Personally Use It:
Shortest EMA ( Example: 10 EMA ) = Entry
Middle EMA ( Example: 50 EMA ) = Short Term Support / Resistance
Longest EMA ( Example: 100 EMA ) = Long Term Support / Resistance
• WARNING
- If your MAIN chart TimeFrame its lower than ( selected TimeFrame ) the Table will not display signals
- Historical Data Unavailable for this resolution is under 2 minute chart, So you will have to use 2 minute and higher
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (Tradewithron) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Long-Only MTF EMA Cloud StrategyOverview:
The Long-Only EMA Cloud Strategy is a powerful trend-following strategy designed to help traders identify and capitalize on bullish market conditions. By utilizing an Exponential Moving Average (EMA) Cloud, this strategy provides clear and reliable signals for entering long positions when the market trend is favorable. The EMA cloud acts as a visual representation of the trend, making it easier for traders to make informed decisions. This strategy is ideal for traders who prefer to trade in the direction of the trend and focus exclusively on long positions.
Key Features:
EMA Cloud:
The strategy uses two EMAs (short and long) to create a dynamic cloud.
The cloud is bullish when the short EMA is above the long EMA, indicating a strong upward trend.
The cloud is bearish when the short EMA is below the long EMA, indicating a downward trend or consolidation.
Long Entry Signals:
A long position is opened when the EMA cloud turns bullish, which occurs when the short EMA crosses above the long EMA.
This crossover signals a potential shift in market sentiment from bearish to bullish, providing an opportunity to enter a long trade.
Adjustable Timeframe:
The EMA cloud can be calculated on the same timeframe as the chart or on a higher/lower timeframe for multi-timeframe analysis.
This flexibility allows traders to adapt the strategy to their preferred trading style and time horizon.
Risk Management:
The strategy includes adjustable stop loss and take profit levels to help traders manage risk and lock in profits.
Stop loss and take profit levels are calculated as a percentage of the entry price, ensuring consistency across different assets and market conditions.
Alerts:
Built-in alerts notify you when a long entry signal is generated, ensuring you never miss a trading opportunity.
Alerts can be customized to suit your preferences, providing real-time notifications for potential trades.
Visualization:
The EMA cloud is plotted on the chart, providing a clear visual representation of the trend.
Buy signals are marked with a green label below the price bar, making it easy to identify entry points.
How to Use:
Add the Script:
Add the script to your chart in TradingView.
Set EMA Lengths:
Adjust the Short EMA Length and Long EMA Length in the settings to suit your trading style.
For example, you might use a shorter EMA (e.g., 21) for more responsive signals or a longer EMA (e.g., 50) for smoother signals.
Choose EMA Cloud Resolution:
Select the EMA Cloud Resolution (timeframe) for the cloud calculation.
You can choose the same timeframe as the chart or a different timeframe (higher or lower) for multi-timeframe analysis.
Adjust Risk Management:
Set the Stop Loss (%) and Take Profit (%) levels according to your risk tolerance and trading goals.
For example, you might use a 1% stop loss and a 2% take profit for a 1:2 risk-reward ratio.
Enable Alerts:
Enable alerts to receive notifications for long entry signals.
Alerts can be configured to send notifications via email, SMS, or other preferred methods.
Monitor and Trade:
Monitor the chart for buy signals and execute trades accordingly.
Use the EMA cloud as a visual guide to confirm the trend direction before entering a trade.
Ideal For:
Trend-Following Traders: This strategy is perfect for traders who prefer to trade in the direction of the trend and capitalize on sustained price movements.
Long-Only Traders: If you prefer to focus exclusively on long positions, this strategy provides a clear and systematic approach to identifying bullish opportunities.
Multi-Timeframe Analysts: The adjustable EMA cloud resolution allows you to analyze trends across different timeframes, making it suitable for both short-term and long-term traders.
Risk-Averse Traders: The inclusion of stop loss and take profit levels helps manage risk and protect your capital.
BRT CHARTS MTFDescription of the Indicator
This indicator is designed to visualize and analyze price movements across multiple timeframes simultaneously. It displays candles from selected time intervals directly on the current chart, allowing traders to quickly assess market conditions without switching between different timeframes. This is particularly useful for traders who use multi-timeframe analysis to make trading decisions.
Key Features of the Indicator:
1. Displaying Candles from Multiple Timeframes:
- The indicator allows you to select three timeframes (e.g., 1 hour, 4 hours, and 1 day) and displays their candles on the current chart. This helps to see the overall market picture without switching between charts.
- Candles are displayed as vertical columns, each containing the body and wicks (shadows) of the candle. The colors of the candles (green for bullish and red for bearish) are customizable.
2. Dynamic Updates:
- The indicator automatically updates the candles as new data arrives, allowing you to track market changes in real time.
3. Customizable Number of Candles:
- The user can choose how many candles to display for each timeframe (default is 4 candles). This allows the indicator to be adapted to individual needs.
4. Range Display (High/Low):
- The indicator can show High and Low levels for each timeframe, helping to identify key support and resistance levels.
- It is also possible to display the Mid level (average between High and Low), which can be useful for identifying consolidation zones.
5. Data Table:
- The indicator supports displaying a table with key levels (High, Low, Mid) for each timeframe. The table can be placed in any corner of the chart, and its size and text/background colors are customizable.
6. Flexible Appearance Settings:
- The user can customize the colors of the candles, their wicks, High/Low/Mid levels, as well as the placement of the columns on the chart.
How the Indicator Helps in Trading:
- Multi-Timeframe Analysis: The indicator allows you to analyze multiple timeframes simultaneously, helping to better understand the overall trend and find entry points. For example, if the trend is bullish on the daily timeframe and there is a correction on the hourly timeframe, this could be a good opportunity to buy.
- Identifying Key Levels: Displaying High, Low, and Mid levels helps quickly identify support and resistance zones, which is useful for setting stop-loss and take-profit levels.
- Time-Saving: The indicator eliminates the need to switch between timeframes, speeding up the analysis and decision-making process.
- Visual Clarity: Visualizing candles from different timeframes on a single chart makes analysis more convenient and intuitive.
Example Use Cases:
1. Trend Trading: If a clear uptrend is visible on the daily timeframe and a correction is occurring on the hourly timeframe, you can look for buy opportunities near support levels.
2. Range Trading: If the price is moving sideways across all timeframes, you can use High and Low levels to trade from the boundaries of the range.
3. Identifying Reversal Points: If the price approaches a key resistance level on the higher timeframe and a bearish candle forms on the lower timeframe, this could be a signal to sell.
Conclusion:
This indicator is a powerful tool for traders who use multi-timeframe analysis. It helps quickly assess market conditions, identify key levels, and make informed trading decisions. Thanks to its flexible settings, the indicator can be adapted to any trading style and visualization preferences.
1H/3m Concept [RunRox]🕘 1H/3m Concept is a versatile trading methodology based on liquidity sweeps from fractal points identified on higher timeframes, followed by price reversals at these key moments.
Below, I will explain this concept in detail and provide clear examples demonstrating its practical application.
⁉️ WHAT IS A FRACTALS?
In trading, a fractal is a technical analysis pattern composed of five consecutive candles, typically highlighting local market turning points. Specifically, a fractal high is formed when a candle’s high is higher than the highs of the two candles on either side, whereas a fractal low occurs when a candle’s low is lower than the lows of the two adjacent candles on both sides.
Traders use fractals as reference points for identifying significant support and resistance levels, potential reversal areas, and liquidity zones within price action analysis. Below is a screenshot illustrating clearly formed fractals on the chart.
📌 ABOUT THE CONCEPT
The 1H/3m Concept involves marking Higher Timeframe (HTF) fractals directly onto a Lower Timeframe (LTF) chart. When a liquidity sweep occurs at an HTF fractal level, we remain on the same LTF chart (since all HTF fractals are already plotted on this lower timeframe) and wait for a clear Market Structure Shift (MSS) to identify our potential entry point.
Below is a schematic illustration clearly demonstrating how this concept works in practice.
Below is another 💡 real-chart example , showing liquidity in the form of a 1H fractal, swept by a rapid impulse move. Immediately afterward, a clear Market Structure Shift (MSS) occurs, signaling a potential entry point into the trade.
Another example is shown below, where we see our hourly fractal, from which price clearly reacts, providing an opportunity to search for an entry point.
As illustrated on the chart, the fractal levels from the higher timeframe are clearly displayed, but we’re working directly on the 5-minute chart. This allows us to remain on one timeframe without needing to switch back and forth between charts to spot such trading setups.
🔍 MTF FRACTALS
This concept can be applied across various HTF-LTF timeframe combinations. Although our examples illustrate 1H fractals used on a 5-minute chart, you can effectively utilize many other timeframe combinations, such as:
30m HTF fractals on 1m chart
1H HTF fractals on 3m chart
4H HTF fractals on 15m chart
1D HTF fractals on 1H chart
The key idea behind this concept is always the same: identify liquidity at fractal levels on the higher timeframe (HTF), then wait for a clear Market Structure Shift (MSS) on the lower timeframe (LTF) to enter trades.
⚙️ SETTINGS
🔷 Trade Direction – Select the preferred trading direction (Long, Short, or Both).
🔷 HTF – Choose the higher timeframe from which fractals will be displayed on the current chart.
🔷 HTF Period – Number of candles required on both sides of a fractal candle (before and after) to confirm fractal formation on the HTF.
🔷 Current TF Period – Sensitivity to the impulse that sweeps liquidity, used for identifying and forming the MSS line.
🔷 Show HTF – Enable or disable displaying HTF fractal lines on your chart. You can also customize line style and color.
🔷 Max Age (Bars) – Number of recent bars within which fractals from the selected HTF will be displayed.
🔷 Show Entry – Enable or disable displaying the MSS line on the chart.
🔷 Enable Alert – Activates TradingView alerts whenever the MSS line is crossed.
You can also enable 🔔 alerts, which notify you whenever price crosses the MSS line. This significantly simplifies the process of identifying these setups on your charts. Simply configure your preferred timeframes and wait for notifications when the MSS line is crossed.
🔶 We greatly appreciate your feedback and suggestions for improving the indicator!
SuperTrend'ed Fibos - DolphinTradeBot
Overwiev
This indicator aims to assist in taking trades at relatively low price levels in the direction of the main trend and capturing profits at potential reversal points.
What is it for !
The indicator simply performs its calculations by using two multitimeframe SuperTrend indicators, Fibonacci levels, and pivot points. The reason for using MTF in both SuperTrend indicators is that the lengths of the levels are relatively limited, so it allows for a more detailed analysis on lower timeframes.
How is it work
When both the HTF SuperTrend and the main SuperTrend indicators are in the same direction,
For Uptrend:
Once the main SuperTrend line is violated it barcolor and draws the basic Fibonacci levels between the pivot high point and the SuperTrend line within the trend region . The TakeProfit level is drawn at a distance multiplied by the TakeProfit Multiplier, between the lowest and highest points of the level. When the main trend reverses or the TakeProfit level is violated, it stops drawing.
For Downtrend:
Once the main SuperTrend line is violated it barcolor and draws the basic Fibonacci levels between the pivot low point and the SuperTrend line within the trend region . The TakeProfit level is drawn at a distance multiplied by the TakeProfit Multiplier, between the lowest and highest points of the level. When the main trend reverses or the TakeProfit level is violated, it stops drawing.
How to Use:
To prevent the line thickness from being displayed on the screen, the indicator shows the direction of the HTF SuperTrend indicator by coloring the background. In the settings section, you can adjust:
TakeProfit Multiplier
Fibonacci line colors
HTF SuperTrend activation
HTF SuperTrend settings
Main SuperTrend settings
Fibonacci levels
Custom alert activation
Custom alert level
Alarm Section
By default, the indicator gives an alert when a level is formed or violated. Additionally, if you want to set an alert for a specific level, you can activate the Custom Alert option and choose your desired level.
Order Blocks-[B.Balaei]Order Blocks -
**Description:**
The Order Blocks - indicator is a powerful tool designed to identify and visualize Order Blocks on your chart. Order Blocks are key levels where significant buying or selling activity has occurred, often acting as support or resistance zones. This indicator supports multiple timeframes (MTF), allowing you to analyze Order Blocks from higher timeframes directly on your current chart.
**Key Features:**
1. **Multi-Timeframe Support**: Choose any timeframe (e.g., Daily, Weekly) to display Order Blocks from higher timeframes.
2. **Customizable Sensitivity**: Adjust the sensitivity to detect more or fewer Order Blocks based on market conditions.
3. **Bullish & Bearish Order Blocks**: Clearly distinguishes between bullish (green) and bearish (red) Order Blocks.
4. **Alerts**: Get notified when price enters a Bullish or Bearish Order Block zone.
5. **Customizable Colors**: Personalize the appearance of Order Blocks to match your chart style.
**How to Use:**
1. Add the indicator to your chart.
2. Select your desired timeframe from the "Multi-Timeframe" settings.
3. Adjust the sensitivity and colors as needed.
4. Watch for Order Blocks to form and use them as potential support/resistance levels.
**Ideal For:**
- Swing traders and position traders looking for key levels.
- Traders who use multi-timeframe analysis.
- Anyone interested in understanding market structure through Order Blocks.
**Note:**
This indicator is for educational and informational purposes only. Always conduct your own analysis before making trading decisions.
**Enjoy trading with Order Blocks - !**
