ICT Donchian Smart Money Structure (Expo)█ Concept Overview
The Inner Circle Trader (ICT) methodology is focused on understanding the actions and implications of the so-called "smart money" - large institutions and professional traders who often influence market movements. Key to this is the concept of market structure and how it can provide insights into potential price moves.
Over time, however, there has been a notable shift in how some traders interpret and apply this methodology. Initially, it was designed with a focus on the fractal nature of markets. Fractals are recurring patterns in price action that are self-similar across different time scales, providing a nuanced and dynamic understanding of market structure.
However, as the ICT methodology has grown in popularity, there has been a drift away from this fractal-based perspective. Instead, many traders have started to focus more on pivot points as their primary tool for understanding market structure.
Pivot points provide static levels of potential support and resistance. While they can be useful in some contexts, relying heavily on them could provide a skewed perspective of market structure. They offer a static, backward-looking view that may not accurately reflect real-time changes in market sentiment or the dynamic nature of markets.
This shift from a fractal-based perspective to a pivot point perspective has significant implications. It can lead traders to misinterpret market structure and potentially make incorrect trading decisions.
To highlight this issue, you've developed a Donchian Structure indicator that mirrors the use of pivot points. The Donchian Channels are formed by the highest high and the lowest low over a certain period, providing another representation of potential market extremes. The fact that the Donchian Structure indicator produces the same results as pivot points underscores the inherent limitations of relying too heavily on these tools.
While the Donchian Structure indicator or pivot points can be useful tools, they should not replace the original, fractal-based perspective of the ICT methodology. These tools can provide a broad overview of market structure but may not capture the intricate dynamics and real-time changes that a fractal-based approach can offer.
It's essential for traders to understand these differences and to apply these tools correctly within the broader context of the ICT methodology and the Smart Money Concept Structure. A well-rounded approach that incorporates fractals, along with other tools and forms of analysis, is likely to provide a more accurate and comprehensive understanding of market structure.
█ Smart Money Concept - Misunderstandings
The Smart Money Concept is a popular concept among traders, and it's based on the idea that the "smart money" - typically large institutional investors, market makers, and professional traders - have superior knowledge or information, and their actions can provide valuable insight for other traders.
One of the biggest misunderstandings with this concept is the belief that tracking smart money activity can guarantee profitable trading.
█ Here are a few common misconceptions:
Following Smart Money Equals Guaranteed Success: Many traders believe that if they can follow the smart money, they will be successful. However, tracking the activity of large institutional investors and other professionals isn't easy, as they use complex strategies, have access to information not available to the public, and often intentionally hide their moves to prevent others from detecting their strategies.
Instantaneous Reaction and Results: Another misconception is that market movements will reflect smart money actions immediately. However, large institutions often slowly accumulate or distribute positions over time to avoid moving the market drastically. As a result, their actions might not produce an immediate noticeable effect on the market.
Smart Money Always Wins: It's not accurate to assume that smart money always makes the right decisions. Even the most experienced institutional investors and professional traders make mistakes, misjudge market conditions, or are affected by unpredictable events.
Smart Money Activity is Transparent: Understanding what constitutes smart money activity can be quite challenging. There are many indicators and metrics that traders use to try and track smart money, such as the COT (Commitments of Traders) reports, Level II market data, block trades, etc. However, these can be difficult to interpret correctly and are often misleading.
Assuming Uniformity Among Smart Money: 'Smart Money' is not a monolithic entity. Different institutional investors and professional traders have different strategies, risk tolerances, and investment horizons. What might be a good trade for a long-term institutional investor might not be a good trade for a short-term professional trader, and vice versa.
█ Market Structure
The Smart Money Concept Structure deals with the interpretation of price action that forms the market structure, focusing on understanding key shifts or changes in the market that may indicate where 'smart money' (large institutional investors and professional traders) might be moving in the market.
█ Three common concepts in this regard are Change of Character (CHoCH), and Shift in Market Structure (SMS), Break of Structure (BMS/BoS).
Change of Character (CHoCH): This refers to a noticeable change in the behavior of price movement, which could suggest that a shift in the market might be about to occur. This might be signaled by a sudden increase in volatility, a break of a trendline, or a change in volume, among other things.
Shift in Market Structure (SMS): This is when the overall structure of the market changes, suggesting a potential new trend. It usually involves a sequence of lower highs and lower lows for a downtrend, or higher highs and higher lows for an uptrend.
Break of Structure (BMS/BoS): This is when a previously defined trend or pattern in the price structure is broken, which may suggest a trend continuation.
A key component of this approach is the use of fractals, which are repeating patterns in price action that can give insights into potential market reversals. They appear at all scales of a price chart, reflecting the self-similar nature of markets.
█ Market Structure - Misunderstandings
One of the biggest misunderstandings about the ICT approach is the over-reliance or incorrect application of pivot points. Pivot points are a popular tool among traders due to their simplicity and easy-to-understand nature. However, when it comes to the Smart Money Concept and trying to follow the steps of professional traders or large institutions, relying heavily on pivot points can create misconceptions and lead to confusion. Here's why:
Delayed and Static Information: Pivot points are inherently backward-looking because they're calculated based on the previous period's data. As such, they may not reflect real-time market dynamics or sudden changes in market sentiment. Furthermore, they present a static view of market structure, delineating pre-defined levels of support and resistance. This static nature can be misleading because markets are fundamentally dynamic and constantly changing due to countless variables.
Inadequate Representation of Market Complexity: Markets are influenced by a myriad of factors, including economic indicators, geopolitical events, institutional actions, and market sentiment, among others. Relying on pivot points alone for reading market structure oversimplifies this complexity and can lead to a myopic understanding of market dynamics.
False Signals and Misinterpretations: Pivot points can often give false signals, especially in volatile markets. Prices might react to these levels temporarily but then continue in the original direction, leading to potential misinterpretation of market structure and sentiment. Also, a trader might wrongly perceive a break of a pivot point as a significant market event, when in fact, it could be due to random price fluctuations or temporary volatility.
Over-simplification: Viewing market structure only through the lens of pivot points simplifies the market to static levels of support and resistance, which can lead to misinterpretation of market dynamics. For instance, a trader might view a break of a pivot point as a definite sign of a trend, when it could just be a temporary price spike.
Ignoring the Fractal Nature of Markets: In the context of the Smart Money Concept Structure, understanding the fractal nature of markets is crucial. Fractals are self-similar patterns that repeat at all scales and provide a more dynamic and nuanced understanding of market structure. They can help traders identify shifts in market sentiment or direction in real-time, providing more relevant and timely information compared to pivot points.
The key takeaway here is not that pivot points should be entirely avoided or that they're useless. They can provide valuable insights and serve as a useful tool in a trader's toolbox when used correctly. However, they should not be the sole or primary method for understanding the market structure, especially in the context of the Smart Money Concept Structure.
█ Fractals
Instead, traders should aim for a comprehensive understanding of markets that incorporates a range of tools and concepts, including but not limited to fractals, order flow, volume analysis, fundamental analysis, and, yes, even pivot points. Fractals offer a more dynamic and nuanced view of the market. They reflect the recursive nature of markets and can provide valuable insights into potential market reversals. Because they appear at all scales of a price chart, they can provide a more holistic and real-time understanding of market structure.
In contrast, the Smart Money Concept Structure, focusing on fractals and comprehensive market analysis, aims to capture a more holistic and real-time view of the market. Fractals, being self-similar patterns that repeat at different scales, offer a dynamic understanding of market structure. As a result, they can help to identify shifts in market sentiment or direction as they happen, providing a more detailed and timely perspective.
Furthermore, a comprehensive market analysis would consider a broader set of factors, including order flow, volume analysis, and fundamental analysis, which could provide additional insights into 'smart money' actions.
█ Donchian Structure
Donchian Channels are a type of indicator used in technical analysis to identify potential price breakouts and trends, and they may also serve as a tool for understanding market structure. The channels are formed by taking the highest high and the lowest low over a certain number of periods, creating an envelope of price action.
Donchian Channels (or pivot points) can be useful tools for providing a general view of market structure, and they may not capture the intricate dynamics associated with the Smart Money Concept Structure. A more nuanced approach, centered on real-time fractals and a comprehensive analysis of various market factors, offers a more accurate understanding of 'smart money' actions and market structure.
█ Here is why Donchian Structure may be misleading:
Lack of Nuance: Donchian Channels, like pivot points, provide a simplified view of market structure. They don't take into account the nuanced behaviors of price action or the complex dynamics between buyers and sellers that can be critical in the Smart Money Concept Structure.
Limited Insights into 'Smart Money' Actions: While Donchian Channels can highlight potential breakout points and trends, they don't necessarily provide insights into the actions of 'smart money'. These large institutional traders often use sophisticated strategies that can't be easily inferred from price action alone.
█ Indicator Overview
We have built this Donchian Structure indicator to show that it returns the same results as using pivot points. The Donchian Structure indicator can be a useful tool for market analysis. However, it should not be seen as a direct replacement or equivalent to the original Smart Money concept, nor should any indicator based on pivot points. The indicator highlights the importance of understanding what kind of trading tools we use and how they can affect our decisions.
The Donchian Structure Indicator displays CHoCH, SMS, BoS/BMS, as well as premium and discount areas. This indicator plots everything in real-time and allows for easy backtesting on any market and timeframe. A unique candle coloring has been added to make it more engaging and visually appealing when identifying new trading setups and strategies. This candle coloring is "leading," meaning it can signal a structural change before it actually happens, giving traders ample time to plan their next trade accordingly.
█ How to use
The indicator is great for traders who want to simplify their view on the market structure and easily backtest Smart Money Concept Strategies. The added candle coloring function serves as a heads-up for structure change or can be used as trend confirmation. This new candle coloring feature can generate many new Smart Money Concepts strategies.
█ Features
Market Structure
The market structure is based on the Donchian channel, to which we have added what we call 'Structure Response'. This addition makes the indicator more useful, especially in trending markets. The core concept involves traders buying at a discount and selling or shorting at a premium, depending on the order flow. Structure response enables traders to determine the order flow more clearly. Consequently, more trading opportunities will appear in trending markets.
Structure Candles
Structure Candles highlight the current order flow and are significantly more responsive to structural changes. They can provide traders with a heads-up before a break in structure occurs
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. 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.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
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Adjusted OBVThis script shows On-Balance Volume adjusted for volume weighted candle body size.
This means that the wick lengths, body length, and sell/buy pressure are calculated into percentages of volume that contributed to each.
The body volume is the accumulatively tracked across candles to give a more accurate On-Balance Volume that has been traded to achieve the current price over time.
The script output is in Orange and for comparison the original technical OBV is in Blue.
As this is my first script, I hope to update it to include a 'buy' and 'sell' pressure gauge to perhaps turn this from a mere indicator into potentially a bit more predictive.
In the meantime, it should be useful for tracking OBV for other uses in a more accurate and less volatile way.
Compare Crypto Bollinger Bands//This is not financial advice, I am not a financial advisor.
//What are volatility tokens?
//Volatility tokens are ERC-20 tokens that aim to track the implied volatility of crypto markets.
//Volatility tokens get their exposure to an asset’s implied volatility using FTX MOVE contracts.
//There are currently two volatility tokens: BVOL and IBVOL.
//BVOL targets tracking the daily returns of being 1x long the implied volatility of BTC
//IBVOL targets tracking the daily returns of being 1x short the implied volatility of BTC.
/////////////////////////////////////////////////////////////////
CAN USE ON ANY CRYPTO CHART AS BINANCE:BTCUSD is still the most dominant crypto, positive volatility for BTC is positive for all.
/////////////////////////////////////////////////////////////////
//The Code.
//The blue line (ChartLine) is the current chart plotted on in Bollinger
//The red line (BVOLLine) plots the implied volatility of BTC
//The green line (IBVOLLine) plot the inverse implied volatility of BTC
//The orange line (TOTALLine) plots how well the crypto market is performing on the Bolling scale. The higher the number the better.
//There are 2 horizontal lines, 0.40 at the bottom & 0.60 at the top
/////////To Buy
//1. The blue line (ChartLine) must be higher than the green line (IBVOLLine)
//2. The green line (IBVOLLine) must be higher than the red line (BVOLLine)
//3. The red line (BVOLLine) must be less than 0.40 // This also acts as a trendsetter
//4. The orange line (TOTALLine) MUST be greater than the red line. This means that the crypto market is positive.
//5.IF THE BLUE LINE (ChartLine) IS GREATER THAN THE ORANGE LINE (TOTALLine) IT MEANS YOUR CRYPTO IS OUTPERFOMING THE MARKET {good for short term explosive bars}
//6. If the orange line (TOTALLine) is higher than your current chart, say BTCUSD. And BTC is going up to. It just means BTC is going up slowly. it's fine as long as they are moving in the same position.
//5. I use this on the 4hr, 1D, 1W timeframes
///////To Exit
//1.If the blue line (ChartLine) crosses under the green line (IBVOLLine) exit{ works best on 4hr,1D, 1W to avoid fakes}
//2.If the red line crosses over the green line when long. {close positions, or watch positions} It means negative volatility is wining
RedK Compound Ratio Moving Average (CoRa_Wave)
Compound Ratio Weighted Average (CoRa_Wave) is a moving average where the weights increase in a "logarithmically linear" way - from the furthest point in the data to the current point - the formula to calculate these weights work in a similar way to how "compound ratio" works - you start with an initial amount, then add a consistent "ratio of the cumulative prior sum" each period until you reach the end amount. The result is, the "step ratio" between the weights is consistent - This is not the case with linear-weights moving average (WMA), or EMA
- for example, if you consider a Weighted Moving Average (WMA) of length 5, the weights will be (from the furthest point towards the most current) 1, 2, 3, 4, 5 -- we can see that the ratio between these weights are inconsistent. in fact, the ratio between the 2 furthest points is 2:1, but the ratio between the most recent points is 5:4 -- the ratio is inconsistent, and in fact, more recent points are not getting the best weights they should/can get to counter-act the lag effect. Using the Compound ratio approach addresses that point.
a key advantage here is that we can significantly reduce the "tail weight" - which is "relatively" large in other MAs and would be main cause for lag - giving more weights to the most recent data points - and in a way that is consistent, reliable and easy to "code"
- the outcome is, a moving average line that suffers very little lag regardless of the length, and that can be relied on to track the price movements and swings closely.
other features:
===============
- An accelerator, or multiplier, has been added to further increase the "aggressiveness" of the moving average line, giving even more weights to the more recent points - the multiplier will have more effect between 1 and 5, then will have a diminishing effect after that - note that a multiplier of 0 (which effectively causes a comp. ratio of 0 to be applied) will produce a Simple Moving Average line :)
- We also added the ability to use an "automatic smoothing" mechanism, that user can over-ride by manually choosing how much smoothing is used. This gives more flexibility to how we can leverage this Moving Average in our charting.
- User can also select the Resolution and Source price for the CoRa_Wave. by default, they will be set to "same as chart" and hlc3
here are the formulas for our Compound Ratio moving average:
Compound Weight ratio r = (A/P)^1/t - 1
Weight at time t A = P(1 + r)^t
= Start_val * (1 + r) ^ index
index in the above formula is 0 for the furthest point out
Here's how CoRa_Wave compares to other common moving averages all set to the same length (20)
Proposed Usage
- CoRa_Wave can be used for any scenarios where we need a moving average that closely tracks the price, trend, swings with high responsiveness and little lag
- MA Cross-over scenarios - against another CoRa_Wave or any other MA
- below is a quick example scenario for how to utilize 2 CoRa_Wave lines of same length (one for open and one for closing price) to track swings and trends
- get as creative as you need :)
Code is commented - please feel free to leverage or customize further as you need.
👉 if you are interested in other moving averages i posted before, please check out the FiMA and the v_Wave ...
Perfect MA Touch – Full Setup 1,3,5,7,8,9 v2This indicator helps you track a precise candle countdown from a moving average touch, labeling key bars (1, 3, 5, 7, 8, 9) for timing entries and momentum setups — with optional coloring, alerts, and full customization.
What It Detects
1. MA Touch Trigger
The sequence starts when any selected moving average (up to 6 MAs, customizable) is touched by the candle's high/low range.
This "perfect touch" initiates the count and labels that candle as "1".
2. Candle Number Labels
After a perfect MA touch:
Candle 1 = the bar that touches the MA
Candle 3 = two bars after Candle 1
Candle 5 = the fifth bar after the touch
Candle 7 = third bar after Candle 5
Candle 8 = fourth bar after Candle 5
Candle 9 = fifth bar after Candle 5
It creates a time-based sequence you can use to anticipate reactions or momentum shifts.
3. Customization
You can:
Choose between EMA or SMA for each MA (6 total)
Set custom lengths for each MA (9, 20, 50, 100, 150, 200)
Choose which candle numbers (1, 3, 5, 7, 8, 9) to highlight
Pick font size and label color
4. Highlighting and Alerts
Highlight candles (with color) when certain bars (like 3, 5, 7) print
Alerts are available for all tracked bars (1, 3, 5, 7, 8, 9)
Use Case Example
Let’s say you want to enter trades on the 3rd candle after a perfect MA touch:
You set the script to highlight candle 3.
When a candle hits your chosen MA (say EMA 9), it’s labeled “1”.
Two bars later, bar 3 appears — giving you a timed signal to enter if price behavior aligns.
This method is especially useful when paired with:
Volume confirmation
Breakout or reversal patterns
Support/resistance or order block zones
Metaplanet MSW Strike LevelsMetaplanet Moving Strike Warrant (MSW) Price Tracker
This indicator displays Metaplanet's actual Moving Strike Warrant pricing schedule with real-time strike price visualization. It shows the exact strike prices that determine warrant exercise values based on Metaplanet's official MSW terms.
Key Features:
Current Period: Strike locked at ¥1,649 from June 24th through July 1st, 2025
Automatic Updates: Starting July 2nd, strike prices re-evaluate every 3 trading days using 3-day SMA of closing prices
Visual Strike Lines: Yellow horizontal lines show active MSW strike prices for each period
Background Signals: Light green when price is above strike (favorable), light red when below
Information Panel: Orange table displays current strike price and next evaluation date
Evaluation Markers: Orange/yellow dots mark re-evaluation dates
How It Works:
The indicator follows Metaplanet's official MSW schedule, automatically calculating new strike prices every 3 trading days based on the 3-day simple moving average of previous closing prices. This helps warrant holders track exercise opportunities and understand the dynamic pricing mechanism.
Perfect MA Touch – Full Setup 1,3,5,7,8,9This indicator helps you track a precise candle countdown from a moving average touch, labeling key bars (1, 3, 5, 7, 8, 9) for timing entries and momentum setups — with optional coloring, alerts, and full customization.
What It Detects
1. MA Touch Trigger
The sequence starts when any selected moving average (up to 6 MAs, customizable) is touched by the candle's high/low range.
This "perfect touch" initiates the count and labels that candle as "1".
2. Candle Number Labels
After a perfect MA touch:
Candle 1 = the bar that touches the MA
Candle 3 = two bars after Candle 1
Candle 5 = the fifth bar after the touch
Candle 7 = third bar after Candle 5
Candle 8 = fourth bar after Candle 5
Candle 9 = fifth bar after Candle 5
It creates a time-based sequence you can use to anticipate reactions or momentum shifts.
3. Customization
You can:
Choose between EMA or SMA for each MA (6 total)
Set custom lengths for each MA (9, 20, 50, 100, 150, 200)
Choose which candle numbers (1, 3, 5, 7, 8, 9) to highlight
Pick font size and label color
4. Highlighting and Alerts
Highlight candles (with color) when certain bars (like 3, 5, 7) print
Alerts are available for all tracked bars (1, 3, 5, 7, 8, 9)
Use Case Example
Let’s say you want to enter trades on the 3rd candle after a perfect MA touch:
You set the script to highlight candle 3.
When a candle hits your chosen MA (say EMA 9), it’s labeled “1”.
Two bars later, bar 3 appears — giving you a timed signal to enter if price behavior aligns.
This method is especially useful when paired with:
Volume confirmation
Breakout or reversal patterns
Support/resistance or order block zones
Liquidity Hunter HeatmapLiquidity Hunter (GPS Companion Tool)
Liquidity Hunter is a specialized script designed to help traders visualize and track potential liquidation zones, clusters, and imbalance traps in real-time. It is particularly useful for scalpers and short-term traders who rely on liquidity sweeps, stop hunts, and reversion plays.
This tool does not replicate open-source liquidation trackers. Instead, it uses a proprietary combination of volume surges, candle displacement, VWAP deviation, and high-timeframe wicks to infer areas of trapped traders and display them with clear, color-coded markers.
Key Features:
• Real-Time Liquidation Estimates: Detects where major stop losses (and potential liquidations) may have occurred, based on proprietary volume + price action logic.
• Cluster Strength Bubbles: Visual bubbles (scaled by cluster size) show where liquidations are stacking. Purple for bearish, white for bullish — intensity reflects strength.
• Pre-Liquidation Warning Zones: Highlights areas where price is likely to sweep liquidity before reversing, helping traders avoid chasing moves.
• Dollar-Based Labels (Optional): Displays the estimated value liquidated, helping traders size the significance of a move (e.g., $8.4M).
• Minimal Clutter Mode: Designed for intraday clarity — hides excess lines and uses bubbles, not shapes, for cleaner visualization.
Trend Flow Trail [AlgoAlpha]OVERVIEW
This script overlays a custom hybrid indicator called the Money Flow Trail which combines a volatility-based trend-following trail with a volume-weighted momentum oscillator. It’s built around two core components: the AlphaTrail—a dynamic band system influenced by Hull MA and volatility—and a smoothed Money Flow Index (MFI) that provides insights into buying or selling pressure. Together, these tools are used to color bars, generate potential reversal markers, and assist traders in identifying trend continuation or exhaustion phases in any market or timeframe.
CONCEPTS
The AlphaTrail calculates a volatility-adjusted channel around price using the Hull Moving Average as the base and an EMA of range as the spread. It adaptively shifts based on price interaction to capture trend reversals while avoiding whipsaws. The direction (bullish or bearish) determines both the band being tracked and how the trail locks in. The Money Flow Index (MFI) is derived from hlc3 and volume, measuring buying vs selling pressure, and is further smoothed with a short Hull MA to reduce noise while preserving structure. These two systems work in tandem: AlphaTrail governs directional context, while MFI refines the timing.
FEATURES
Dynamic AlphaTrail line with regime switching logic that controls directional bias and bar coloring.
Smoothed MFI with gradient coloring to visually communicate pressure and exhaustion levels.
Overbought/oversold thresholds (80/20), mid-level (50), and custom extreme zones (90/10) for deeper signal granularity.
Built-in take-profit signal logic: crossover of MFI into overbought with bullish AlphaTrail, or into oversold with bearish AlphaTrail.
Visual fills between price and AlphaTrail for clearer confirmation during trend phases.
Alerts for regime shifts, MFI crossovers, trail interactions, and bar color regime changes.
USAGE
Add the indicator to any chart. Use the AlphaTrail plot to define trend context: bullish (trailing below price) or bearish (trailing above). MFI values give supporting confirmation—favor long setups when MFI is rising and above 50 in a bullish regime, and shorts when MFI is falling and below 50 in a bearish regime. The colored fills help visually track strength; sharp changes in MFI crossing 80/20 or 90/10 zones often precede pullbacks or reversals. Use the plotted circles as optional take-profit signals when MFI and trend are extended. Adjust AlphaTrail length/multiplier and MFI smoothing to better match the asset’s volatility profile.
VWAP Supply & Demand Zones PRO**Overview:**
This script represents a major evolution of the original "VWAP Supply and Demand Zones" indicator. Initially created to explore price interaction with VWAP, it has now matured into a robust and feature-rich tool for identifying high-probability zones of institutional buying and selling pressure. The update introduces volume and momentum validation, dynamic zone management, alert logic, and a visual dashboard (HUD) — all designed for improved precision and clarity. The structural improvements, anti-repainting logic, and significant added utility warranted releasing this as a new script rather than a minor update.
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### What It Does:
This indicator dynamically detects **supply and demand zones** using VWAP-based logic combined with **volume** and **momentum confirmation**. When price crosses VWAP with strength, it identifies the potential zone of excess demand (below VWAP) or supply (above VWAP), marking it visually with colored regions on the chart.
Each zone is extended for a user-defined duration, monitored for touch interactions (tests), and tracked for possible breaks. The script helps traders interpret price behavior around these institutional zones as either **reversal** opportunities or **continuation** confirmation depending on context and strategy preference.
---
### How It Works:
* **VWAP Basis**: Zones are anchored at VWAP at the time of a significant cross.
* **Volume & Momentum Filters**: Crosses are only considered valid if backed by above-average volume and notable price momentum.
* **Zone Drawing**: Validated supply and demand zones are drawn as boxes on the chart. Each is extended forward for a customizable number of bars.
* **Touch Counting**: Zones track the number of price touches. Alerts are issued after a user-defined number of tests.
* **Break Detection**: If price closes significantly beyond a zone boundary, the zone is marked as broken and visually dimmed.
* **Visual Dashboard (HUD)**: A compact real-time HUD displays VWAP value, active zone counts, and current market bias.
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### How to Use It:
**Reversal Trading:**
* Look for price **rejecting** a zone after touching it.
* Use rejection candles or secondary indicators (e.g., RSI divergence) to confirm.
* These setups may offer low-risk entries when price respects the zone.
**Continuation Trading:**
* A **break of a zone** suggests strong directional bias.
* Use confirmed zone breaks to enter in the direction of momentum.
* Ideal in trending environments, especially with high volume and ATR movement.
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### Key Inputs:
* **VWAP Length**: Moving VWAP period (default: 20)
* **Zone Width %**: Percentage size of zone buffer (default: 0.5%)
* **Min Touches**: How many times price must test a zone before alerts trigger
* **Zone Extension**: How far into the future zones are projected
* **Volume & ATR Filters**: Ensure only strong, valid crossovers create zones
---
### Alerts:
You can enable alerts for:
* **New zone creation**
* **Zone tests (after minimum touch count)**
* **Zone breaks**
* **VWAP crosses**
* **Active presence inside a zone (entry conditions)**
These alerts help automate market monitoring, making it suitable for discretionary or systematic workflows.
---
### Why It's a New Script:
This is not a cosmetic update. The internal logic, signal generation, filtering methodology, visual engine, and UX framework have been entirely rebuilt from the ground up. The result is a highly adaptive, precision-oriented tool — appropriate for intraday scalpers and swing traders alike. It goes far beyond the original in terms of functionality and reliability, justifying a fresh release.
---
### Suitable Markets and Timeframes:
* Works across all liquid markets (crypto, equities, futures, forex)
* Best used on timeframes where volume data is stable (5m and above recommended)
* Recalibrate inputs for optimal detection across instruments
Trend Matrix Multi-Timeframe Dashboard(TechnoBlooms)Trend Matrix Multi-Timeframe Dashboard is a Minimalist Multi-Timeframe Trend Analyzer with Smart Indicator Integration. Trend Matrix MTF Dashboard is a clean, efficient, and visually intuitive trend analyzer built for traders who value simplicity without compromising on technical depth.
This dashboard empowers you to track trend direction across multiple timeframes using a curated set of powerful technical indicators—all from one compact visual panel. The design philosophy is simple: eliminate clutter, highlight trend clarity, and accelerate your decision-making process.
Key Features
✅ Minimalist Design with Maximum Insight
A compact dashboard view designed for clean charts and focused trading
Optimized layout shows everything you need—nothing you don’t
✅ Multi-Timeframe Access at a Glance
Instantly read the trend direction of selected indicators on multiple timeframes (e.g., 15m, 1h, 4h, 1D)
Customize the timeframe stack to fit scalping, intraday, swing, or positional strategies
✅ Robust Technical Indicators Built In
Each one is hand-picked for trend reliability:
MACD – Momentum and crossover confirmation
RSI – Overbought/oversold and directional shift
EMA – Dynamic support/resistance and trend bias
Bollinger Bands – Volatility structure and trend containment
PVT – Volume-Weighted Trend Confirmation
Supertrend – Price-following trend tracker
✅ Live Updates & Lightweight Performance
Built to update efficiently on every bar close
Minimal performance impact even with multiple timeframes active
By offering multi-timeframe (MTF) access to proven trend-following indicators, Trend Matrix helps you confidently align with the market’s dominant direction—without jumping between charts or analyzing indicators one by one.
This indicator offers customizable settings. The trader can choose the input parameters timeframes as per the choice.
Trend Matrix Multi-Timeframe Dashboard helps traders to identify trend based on technical indications. Trader can refer this while taking trading decisions.
🧠 Ideal For
Scalpers who need higher timeframe confirmation
Swing traders identifying clean entries aligned with the macro trend
Trend followers seeking clarity before committing capital
Price action & SMC traders validating market structure setups
Beginners who want a high-level trend guide without messy indicators
VNIndex Over 6.5% Downside Drop Indicator with TableOverview: The VNIndex 6.5% Downside Drop Indicator is a powerful tool designed to help traders and investors identify significant market drops on the VNIndex (or any other asset) based on a 6.5% downside threshold. This Pine Script® indicator automatically detects when the price of an asset drops by more than 6.5% within a single day, and visually marks those events on the chart.
Key Features:
6.5% Downside Drop Detection: Automatically calculates the daily percentage drop and identifies when the price falls by more than 6.5%.
Table Display: Displays the dates and corresponding percentage drops of all identified instances in a convenient table at the bottom right of the chart.
Markers: Red down-pointing markers are plotted above bars where the price drop exceeds the 6.5% threshold, making it easy to spot critical drop events at a glance.
Easy-to-Read Table: The table lists the date and drop percentage, updating dynamically as new drops are detected. This allows for easy tracking of significant downside moves over time.
How to Use:
Install the Script: Add this indicator to your TradingView chart.
Monitor Price Drops: The indicator will automatically detect when the price drops by over 6.5% from the previous close and display a marker on the chart and the table in the bottom right corner.
View the Table: The table displays the date and the percentage drop of each detected event, making it easy to track past significant moves.
Alerts: You can set an alert for 6.5% drops to receive notifications in real-time.
Customization Options:
The drop percentage threshold (6.5%) can be adjusted in the script to fit other market conditions or assets.
The table can be resized or styled based on user preference for better visibility.
Why Use This Indicator? This indicator is perfect for traders looking to spot large, significant price movements quickly. Large downside drops can signal potential market reversals or trading opportunities, and this tool helps you track such events effortlessly. Whether you're monitoring the VNIndex or any other asset, this indicator provides crucial insights into volatile price action, helping you make more informed decisions.
Open Source License: This indicator is open source and free to use under the Mozilla Public License 2.0. You are welcome to modify, distribute, and contribute to the project.
Contributions: Feel free to contribute improvements, fixes, or new features by creating a pull request. Let’s collaborate to make this indicator even better for the community!
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
Multi-Timeframe VWAP Master ProThe Multi-Timeframe VWAP Suite is a comprehensive and highly customizable indicator designed for traders who rely on Volume-Weighted Average Price (VWAP) across multiple timeframes and periods. This tool provides a complete suite of VWAP calculations, including daily, weekly, monthly, quarterly, yearly, and custom VWAPs, allowing traders to analyze price action and volume trends with precision. Whether you're a day trader, swing trader, or long-term investor, this indicator offers unparalleled flexibility and depth for your trading strategy.
Multi-Timeframe VWAPs:
Daily, Weekly, Monthly, Quarterly, and Yearly VWAPs: Track VWAP across various timeframes to identify key support and resistance levels.
Customizable Timeframes: Use the SMA timeframe input to adjust the period for moving averages and other calculations.
Previous Period VWAPs:
Previous Daily, Weekly, Monthly, and Quarterly VWAPs: Analyze historical VWAP levels to understand past price behavior and identify potential reversal zones.
Previous Year Quarterly VWAPs: Compare current price action to VWAP levels from specific quarters of the previous year.
Custom VWAPs:
Custom Start Date and Timeframe: Define your own VWAP periods by specifying a start date and timeframe, allowing for tailored analysis.
Dynamic Custom VWAP Calculation: Automatically calculates VWAP based on your custom inputs, ensuring flexibility for unique trading strategies.
Seasonal and Yearly VWAPs:
April, July, and October VWAPs: Analyze seasonal trends by tracking VWAP levels for specific months.
Yearly VWAP: Get a broader perspective on long-term price trends with the yearly VWAP.
SMA Integration:
SMA Overlay: Combine VWAP analysis with a Simple Moving Average (SMA) for additional confirmation of trends and reversals.
Customizable SMA Length and Timeframe: Adjust the SMA settings to match your trading style and preferences.
User-Friendly Customization:
Toggle Visibility and Labels: Easily enable or disable the display of specific VWAPs and their labels to keep your chart clean and focused.
Color Customization: Each VWAP line and label is color-coded for easy identification and can be customized to suit your preferences.
Dynamic Labeling:
Automatic Labels: Labels are dynamically placed on the last bar, providing clear and concise information about each VWAP level.
Customizable Label Text: Labels include detailed information, such as the timeframe or custom period, for quick reference.
Flexible Timeframe Detection:
Automatic Timeframe Detection: The indicator automatically detects new days, weeks, months, and quarters, ensuring accurate VWAP calculations.
Support for Intraday and Higher Timeframes: Works seamlessly on all chart timeframes, from 1-minute to monthly charts.
Previous Year Quarterly VWAPs:
Q1, Q2, Q3, Q4 VWAPs: Compare current price action to VWAP levels from specific quarters of the previous year.
User-Selectable Year: Choose the year for which you want to calculate previous quarterly VWAPs.
Persistent Monthly VWAPs:
Option to Persist Monthly VWAPs Year-Round: Keep monthly VWAP levels visible even after the month ends for ongoing analysis.
Comprehensive Analysis: Combines multiple VWAP timeframes and periods into a single tool, eliminating the need for multiple indicators.
Customizable and Flexible: Tailor the indicator to your specific trading strategy with customizable timeframes, periods, and settings.
Enhanced Decision-Making: Gain deeper insights into price action and volume trends across different timeframes, helping you make more informed trading decisions.
Clean and Organized Charts: Toggle visibility and labels to keep your chart clutter-free while still accessing all the information you need.
Ideal For:
Day Traders: Use daily and intraday VWAPs to identify intraday support and resistance levels.
Swing Traders: Analyze weekly and monthly VWAPs to spot medium-term trends and reversals.
Long-Term Investors: Leverage quarterly and yearly VWAPs to understand long-term price behavior and key levels.
Seasonal Traders: Track April, July, and October VWAPs to capitalize on seasonal trends.
The Multi-Timeframe VWAP Suite is a powerful and versatile tool for traders of all styles and timeframes. With its comprehensive suite of VWAP calculations, customizable settings, and user-friendly design, it provides everything you need to analyze price action and volume trends with precision and confidence. Whether you're looking to fine-tune your intraday strategy or gain a broader perspective on long-term trends, this indicator has you covered.
Kalman Filter Trend BreakersThe Kalman filter is a recursive algorithm developed in 1960 by Rudolf E. Kálmán, a Hungarian-American engineer and mathematician, that provides optimal estimates of a system's state by combining noisy measurements with a predictive model. It is widely used in control systems, signal processing, and finance for tracking and forecasting.
In trading, KF might be a good replacement for a moving average, as it reacts to price changes in a different way. Not only it follows price direction, but can also track the velocity of price change. This specific behaviour of KF is used in this indicator to track changes in trends.
Trend is characterized by price moving directionally, however, any trend comes to pause or complete stop and reversal, as the price changes more slowly (a trend fades into a sideways movement for a while) or the price movement changes direction, thus making a reversal.
This indicator detects the points where such changes occur (trend breaker points), and produces signals, which serve as points of current trend pausing or reversing. By applying different settings for KF calculation, you can produce less or more signals that indicate change in trend character, and either detect only significant trends changes, or less and shorter trends changes as well.
The signals do not differentiate the exact type of a trend change (it can be a brief trend pause followed by a continuation, as well as a complete reversal). However, once you are in a trend, the significant velocity change indicates a change in trend structure. In this sense, trend breaker signals should not be followed blindly, and can be used only as trend (and subsequently, position) exit confirmations, but not the entry contrarian confirmations.
For better visual representation, you can use chart signals attached to bars, and additionally paint a vertical gradient at each signal which shows significant trend deceleration.
Kalman filter calculations used in this indicator are partially based on an open-source code from @loxx which was published in 2022 as Kalman filter overlay .
WD Gann: Close Price X Bars Ago with Line or Candle PlotThis indicator is inspired by the principles of WD Gann, a legendary trader known for his groundbreaking methods in time and price analysis. It helps traders track the close price of a security from X bars ago, a technique that is often used to identify key price levels in relation to past price movements. This concept is essential for Gann’s market theories, which emphasize the relationship between time and price.
WD Gann’s analysis often revolved around specific numbers that he considered significant, many of which correspond to squared numbers (e.g., 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400, 441, 484, 529, 576, 625, 676, 729, 784, 841, 900, 961, 1024, 1089, 1156, 1225, 1296, 1369, 1444, 1521, 1600, 1681, 1764, 1849, 1936). These numbers are believed to represent natural rhythms and cycles in the market. This indicator can help you explore how past price levels align with these significant numbers, potentially revealing key price zones that could act as support, resistance, or reversal points.
Key Features:
- Historical Close Price Calculation: The indicator calculates and displays the close price of a security from X bars ago (where X is customizable). This method aligns with Gann's focus on price relationships over specific time intervals, providing traders with valuable reference points to assess market conditions.
- Customizable Plot Type: You can choose between two plot types for visualizing the historical close price:
- Line Plot: A simple line that represents the close price from X bars ago, ideal for those who prefer a clean and continuous representation.
- Candle Plot: Displays the close price as a candlestick chart, providing a more detailed view with open, high, low, and close prices from X bars ago.
- Candle Color Coding: For the candle plot type, the script color-codes the candles. Green candles appear when the close price from X bars ago is higher than the open price, indicating bullish sentiment; red candles appear when the close is lower, indicating bearish sentiment. This color coding gives a quick visual cue to market sentiment.
- Customizable Number of Bars: You can adjust the number of bars (X) to look back, providing flexibility for analyzing different timeframes. Whether you're conducting short-term or long-term analysis, this input can be fine-tuned to suit your trading strategy.
- Gann Method Application: WD Gann's methods involved analyzing price action over specific time periods to predict future movements. This indicator offers traders a way to assess how the price of a security has behaved in the past in relation to a chosen time interval, a critical concept in Gann's theories.
How to Use:
1. Input Settings:
- Number of Bars (X): Choose the number of bars to look back (e.g., 100, 200, or any custom period).
- Plot Type: Select whether to display the data as a Line or Candles.
2. Interpretation:
- Using the Line plot, observe how the close price from X bars ago compares to the current market price.
- Using the Candles plot, analyze the full price action of the chosen bar from X bars ago, noting how the close price relates to the open, high, and low of that bar.
3. Gann Analysis: Integrate this indicator into your broader Gann-based analysis. By looking at past price levels and their relationship to significant squared numbers, traders can uncover potential key levels of support and resistance or even potential reversal points. The historical close price can act as a benchmark for predicting future market movements.
Suggestions on WD Gann's Emphasis in Trading:
WD Gann’s trading methods were rooted in several key principles that emphasized the relationship between time and price. These principles are vital to understanding how the "Close Price X Bars Ago" indicator fits into his overall analysis:
1. Time Cycles: Gann believed that markets move in cyclical patterns. By studying price levels from specific time intervals, traders can spot these cycles and predict future market behavior. This indicator allows you to see how the close price from X bars ago relates to current market conditions, helping to spot cyclical highs and lows.
2. Price and Time Squaring: A core concept in Gann’s theory is that certain price levels and time periods align, often marking significant reversal points. The squared numbers (e.g., 1, 4, 9, 16, 25, etc.) serve as potential key levels where price and time might "square" to create support or resistance. This indicator helps traders spot these historical price levels and their potential relevance to future price action.
3. Geometric Angles: Gann used angles (like the 45-degree angle) to predict market movements, with the belief that prices move at specific geometric angles over time. This indicator gives traders a reference for past price levels, which could align with key angles, helping traders predict future price movement based on Gann's geometry.
4. Numerology and Key Intervals: Gann paid particular attention to numbers that held significance, including squared numbers and numbers related to the Fibonacci sequence. This indicator allows traders to analyze price levels based on these key numbers, which can help in identifying potential turning points in the market.
5. Support and Resistance Levels: Gann’s methods often involved identifying levels of support and resistance based on past price action. By tracking the close price from X bars ago, traders can identify past support and resistance levels that may become significant again in future market conditions.
Perfect for:
Traders using WD Gann’s methods, such as Gann angles, time cycles, and price theory.
Analysts who focus on historical price levels to predict future price action.
Those who rely on numerology and geometric principles in their trading strategies.
By integrating this indicator into your trading strategy, you gain a powerful tool for analyzing market cycles and price movements in relation to key time intervals. The ability to track and compare the historical close price to significant numbers—like Gann’s squared numbers—can provide valuable insights into potential support, resistance, and reversal points.
Disclaimer:
This indicator is based on the methods and principles of WD Gann and is for educational purposes only. It is not intended as financial advice. Trading involves significant risk, and you should not trade with money that you cannot afford to lose. Past performance is not indicative of future results. The use of this indicator is at your own discretion and risk. Always do your own research and consider consulting a licensed financial advisor before making any investment decisions.
Higher Time Frame Support/Resistance [BigBeluga]The Higher Time Frame Support/Resistance indicator is a tool designed to display pivot points derived from higher timeframes on your current chart. These pivot points are calculated based on the highs and lows of price action in different timeframes, and the indicator draws horizontal lines to represent these levels. These lines act as potential support and resistance zones, giving traders key market levels that may influence future price movement.
Each pivot line is color-coded and labeled with its price value and the timeframe it originates from. This allows traders to clearly differentiate between the significance of the levels based on their timeframe. For example, weekly pivot levels may represent stronger, more long-term support and resistance, while hourly pivots offer more immediate, short-term levels to watch.
🔵 IDEA
The Higher Time Frame Support/Resistance indicator is designed to simplify the process of tracking key support and resistance levels across multiple timeframes. Pivot points, which represent turning points in the market, are essential for identifying areas where price might reverse or break out. By displaying these levels from higher timeframes directly on the current chart, traders can quickly identify and react to critical areas in the market without needing to switch between different timeframe charts.
The indicator labels each pivot point with the specific timeframe it comes from (e.g., 4H, 1D, 1W), making it easy for traders to assess the relative strength of each level. Stronger levels from higher timeframes are likely to act as more significant barriers or support zones, while lower timeframe levels can be used for more precise entries and exits.
🔵 KEY FEATURES
Pivot Levels from Multiple Timeframes:
The indicator calculates pivot highs and lows from various higher timeframes (e.g., 4H, 1D, 1W) and plots these levels on the current chart. These pivot points are represented by horizontal lines that extend across the chart, serving as potential support and resistance zones.
Color-Coded Support and Resistance Lines:
Each pivot level is color-coded based on its timeframe, helping traders quickly differentiate between short-term and long-term support and resistance. This visual aid simplifies the analysis and allows for a clearer understanding of key market levels.
Price Labels and Timeframe Information:
In addition to the pivot lines, the indicator displays labels at each level with the corresponding price and timeframe. For example, a label may show "D Pivot High" followed by the exact price. This helps traders understand the origin and significance of each line, allowing for more informed trading decisions.
Labels up and down mark highs and lows from higher timeframes:
Pivot Shadows for Enhanced Clarity:
The indicator can also draw shadow lines that represent the pivot points but with increased transparency. These shadows allow traders to keep track of previous pivots without cluttering the chart with too many solid lines. The width and transparency of these shadows can be customized in the settings.
🔵 HOW TO USE
🔵 CUSTOMIZATION
Timeframes and Pivot Length: Customize which higher timeframes (e.g., 4H, 1D, 1W) you want to display pivot levels from. Adjust the pivot length to control how sensitive the indicator is in detecting market highs and lows.
Line Style and Colors: Adjust the line style (solid, dashed, dotted) and colors for each timeframe to match your personal preference or chart theme. This customization helps in maintaining a clear and visually appealing chart.
Shadow Line Width and Transparency: Control the width and transparency of the shadow pivot lines to reduce chart clutter while still keeping track of key historical levels.
Dynamic Market Correlation Analyzer (DMCA) v1.0Description
The Dynamic Market Correlation Analyzer (DMCA) is an advanced TradingView indicator designed to provide real-time correlation analysis between multiple assets. It offers a comprehensive view of market relationships through correlation coefficients, technical indicators, and visual representations.
Key Features
- Multi-asset correlation tracking (up to 5 symbols)
- Dynamic correlation strength categorization
- Integrated technical indicators (RSI, MACD, DX)
- Customizable visualization options
- Real-time price change monitoring
- Flexible timeframe selection
## Use Cases
1. **Portfolio Diversification**
- Identify highly correlated assets to avoid concentration risk
- Find negatively correlated assets for hedging strategies
- Monitor correlation changes during market events
2. Pairs Trading
- Detect correlation breakdowns for potential trading opportunities
- Track correlation strength for pair selection
- Monitor technical indicators for trade timing
3. Risk Management
- Assess portfolio correlation risk in real-time
- Monitor correlation shifts during market stress
- Identify potential portfolio vulnerabilities
4. **Market Analysis**
- Study sector relationships and rotations
- Analyze cross-asset correlations (e.g., stocks vs. commodities)
- Track market regime changes through correlation patterns
Components
Input Parameters
- **Timeframe**: Custom timeframe selection for analysis
- **Length**: Correlation calculation period (default: 20)
- **Source**: Price data source selection
- **Symbol Selection**: Up to 5 customizable symbols
- **Display Options**: Table position, text color, and size settings
Technical Indicators
1. **Correlation Coefficient**
- Range: -1 to +1
- Strength categories: Strong/Moderate/Weak (Positive/Negative)
2. **RSI (Relative Strength Index)**
- 14-period default setting
- Momentum comparison across assets
3. **MACD (Moving Average Convergence Divergence)**
- Standard settings (12, 26, 9)
- Trend direction indicator
4. **DX (Directional Index)**
- Trend strength measurement
- Based on DMI calculations
Visual Components
1. **Correlation Table**
- Symbol identifiers
- Correlation coefficients
- Correlation strength descriptions
- Price change percentages
- Technical indicator values
2. **Correlation Plot**
- Real-time correlation visualization
- Multiple correlation lines
- Reference levels at -1, 0, and +1
- Color-coded for easy identification
Installation and Setup
1. Load the indicator on TradingView
2. Configure desired symbols (up to 5)
3. Adjust timeframe and calculation length
4. Customize display settings
5. Enable/disable desired components (table, plot, RSI)
Best Practices
1. **Symbol Selection**
- Choose related but distinct assets
- Include a mix of asset classes
- Consider market cap and liquidity
2. **Timeframe Selection**
- Match timeframe to trading strategy
- Consider longer timeframes for strategic analysis
- Use shorter timeframes for tactical decisions
3. **Interpretation**
- Monitor correlation changes over time
- Consider multiple timeframes
- Combine with other technical analysis tools
- Account for market conditions and volatility
Performance Notes
- Calculations update in real-time
- Resource usage scales with number of active symbols
- Historical data availability may affect initial calculations
Version History
- v1.0: Initial release with core functionality
- Multi-symbol correlation analysis
- Technical indicator integration
- Customizable display options
Future Enhancements (Planned)
- Additional technical indicators
- Advanced correlation algorithms
- Enhanced visualization options
- Custom alert conditions
- Statistical significance testing
Adaptive EMA with ATR and Standard Deviation [QuantAlgo]Adaptive EMA with ATR and Standard Deviation by QuantAlgo 📈✨
Introducing the Adaptive EMA with ATR and Standard Deviation , a comprehensive trend-following indicator designed to combine the smoothness of an Exponential Moving Average (EMA) with the volatility adjustments of Average True Range (ATR) and Standard Deviation. This synergy allows traders and investors to better identify market trends while accounting for volatility, delivering clearer signals in both trending and volatile market conditions. This indicator is suitable for traders and investors seeking to balance trend detection and volatility management, offering a robust and adaptable approach across various asset classes and timeframes.
💫 Core Concept and Innovation
The Adaptive EMA with ATR and Standard Deviation brings together the trend-smoothing properties of the EMA and the volatility sensitivity of ATR and Standard Deviation. By using the EMA to track price movements over time, the indicator smooths out minor fluctuations while still providing valuable insights into overall market direction. However, market volatility can sometimes distort simple moving averages, so the ATR and Standard Deviation components dynamically adjust the trend signals, offering more nuanced insights into trend strength and reversals. This combination equips traders with a powerful tool to navigate unpredictable markets while minimizing false signals.
📊 Technical Breakdown and Calculations
The Adaptive EMA with ATR and Standard Deviation relies on three key technical components:
1. Exponential Moving Average (EMA): The EMA forms the base of the trend detection. Unlike a Simple Moving Average (SMA), the EMA gives more weight to recent price changes, allowing it to react more quickly to new data. Users can adjust the length of the EMA to make it more or less responsive to price movements.
2. Standard Deviation Bands: These bands are calculated from the standard deviation of the EMA and represent dynamic volatility thresholds. The upper and lower bands expand or contract based on recent price volatility, providing more accurate signals in both calm and volatile markets.
3. ATR-Based Volatility Filter: The Average True Range (ATR) is used to measure market volatility over a user-defined period. It helps refine the trend signals by filtering out false positives caused by minor price swings. The ATR filter ensures that the indicator only signals significant market movements.
⚙️ Step-by-Step Calculation:
1. EMA Calculation: First, the indicator calculates the EMA over a specified period based on the chosen price source (e.g., close, high, low).
2. Standard Deviation Bands: Then, it computes the standard deviation of the EMA and applies a multiplier to create upper and lower bands around the EMA. These bands adjust dynamically with the level of market volatility.
3. ATR Filtering: In addition to the standard deviation bands, the ATR is applied as a secondary filter to help refine the trend signals. This step helps eliminate signals generated by short-term price spikes or corrections, ensuring that the signals are more reliable.
4. Trend Detection: When the price crosses above the upper band, a bullish trend is identified, while a move below the lower band signals a bearish trend. The system accounts for both the standard deviation and ATR bands to generate these signals.
✅ Customizable Inputs and Features
The Adaptive EMA with ATR and Standard Deviation provides a range of customizable options to fit various trading/investing styles:
📈 Trend Settings:
1. Price Source: Choose the price type (e.g., close, high, low) to base the EMA calculation on, influencing how the trend is tracked.
2. EMA Length: Adjust the length to control how quickly the EMA reacts to price changes. A shorter length provides a more responsive EMA, while a longer period smooths out short-term fluctuations.
🌊 Volatility Controls:
1. Standard Deviation Multiplier: This parameter controls the sensitivity of the trend detection by adjusting the distance between the upper and lower bands from the EMA.
2. TR Length and Multiplier: Fine-tune the ATR settings to control how volatility is filtered, adjusting the indicator’s responsiveness during high or low volatility phases.
🎨 Visualization and Alerts:
1. Bar Coloring: Select different colors for uptrends and downtrends, providing a clear visual cue when trends change.
2. Alerts: Set up alerts to notify you when the price crosses the upper or lower bands, signaling a potential long or short trend shift. Alerts can help you stay informed without constant chart monitoring.
📈 Practical Applications
The Adaptive EMA with ATR and Standard Deviation is ideal for traders and investors looking to balance trend-following strategies with volatility management. Key uses include:
Detecting Trend Reversals: The dynamic bands help identify when the market shifts direction, providing clear signals when a trend reversal is likely.
Filtering Market Noise: By applying both Standard Deviation and ATR filtering, the indicator helps reduce false signals during periods of heightened volatility.
Volatility-Based Risk Management: The adaptability of the bands ensures that traders can manage risk more effectively by responding to shifts in volatility while keeping focus on long-term trends.
⭐️ Comprehensive Summary
The Adaptive EMA with ATR and Standard Deviation is a highly customizable indicator that provides traders with clearer signals for trend detection and volatility management. By dynamically adjusting its calculations based on market conditions, it offers a powerful tool for navigating both trending and volatile markets. Whether you're looking to detect early trend reversals or avoid false signals during periods of high volatility, this indicator gives you the flexibility and accuracy to improve your trading and investing strategies.
Note: The Adaptive EMA with ATR and Standard Deviation is designed to enhance your market analysis but should not be relied upon as the sole basis for trading or investing decisions. Always combine it with other analytical tools and practices. No statements or signals from this indicator constitute financial advice. Past performance is not indicative of future results.
Price & Volume Breakout Fibonacci Probability [TradeDots]📝 OVERVIEW
The "Price & Volume Breakout Fibonacci Probability" indicator is designed to detect the probability of the maximum run-up and drawdown of each breakout trade on an asset, assisting traders in optimizing their take profit and stop loss strategies.
🧮 CALCULATIONS
The algorithm detects price and volume breakouts to activate the Fibonacci levels displayed on the chart. It calculates these levels using the period pivot high and low, with the close price of the breakout bar as the reference price.
The indicator then forward-tests within an user-selected number of bars, detecting the maximum run-up and drawdown during that period. Consequently, it calculates the probability of the price hitting either side of the Fibonacci levels, showing the likelihood of reaching take profit and stop loss targets for each breakout trade.
📊 EXAMPLE
The above example shows two breakout trades, circled within the yellow rectangle zone.
The first trade has a maximum run-up above the +0.382 Fibonacci level zone and a maximum drawdown below the -0.618 Fibonacci level zone.
When the price reaches the maximum run-up, it only has a ~45% probability of moving further upward into the last two zones (25% + 19.44%). This indicates that setting a take profit at a higher level may have less than a 50% chance of success.
Conversely, when the price reaches its maximum drawdown, there is only an ~8% probability of moving further downward into the last drawdown zone. This could indicate a potential reversal.
⚙️ SETTINGS
Breakout Condition: Determines the type of breakout condition to track: "Price", "Volume", "Price & Volume".
Backtest Period: The maximum run-up and drawdown are detected within this bar period.
Price Breakout Period: Specifies the number of bars the price needs to break out from.
Volume Breakout Period: Specifies the number of bars the volume needs to break out from.
Trendline Confirmation: Confirms that the close price needs to be above the trendline.
📈 HOW TO USE
By understanding the probabilities of price movements to both the upside and downside, traders can set take profit and stop loss targets with greater accuracy.
For instance, placing a stop loss order below the zone with the highest probability minimizes the chances of being stopped out of a profitable trade. Conversely, setting a take profit target at the zone with the highest probability increases the win rate.
Additionally, if the price breaches multiple Fibonacci levels during the breakout period, it may indicate an abnormal state, signaling a potential reversal or pullback. This can help traders exit trades in a timely manner.
Traders can adjust their take profit and stop loss levels based on their individual risk tolerance.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Normalized and Smoothed Cumulative Delta for Top 5 NASDAQ StocksThis script is designed to create a TradingView indicator called **"Normalized and Smoothed Cumulative Delta for Top 5 NASDAQ Stocks."** The purpose of this indicator is to track and visualize the cumulative price delta (the change in price from one period to the next) for the top five NASDAQ stocks: Apple Inc. (AAPL), Microsoft Corporation (MSFT), Alphabet Inc. (GOOGL), Amazon.com Inc. (AMZN), and Meta Platforms Inc. (FB).
### Key Features of the Script:
1. **Ticker Selection**:
- The script focuses on the top five NASDAQ stocks by automatically setting their tickers.
2. **Price Data Retrieval**:
- It fetches the closing prices for each of these stocks using the `request.security` function for the current timeframe.
3. **Delta Calculation**:
- The script calculates the delta for each stock, which is simply the difference between the current closing price and the previous closing price.
4. **Cumulative Delta Calculation**:
- It calculates the cumulative delta for each stock by adding the current delta to the previous cumulative delta. This helps track the total change in price over time.
5. **Summing and Smoothing**:
- The cumulative deltas for all five stocks are summed together.
- The script then applies an Exponential Moving Average (EMA) with a period of 5 to smooth the summed cumulative delta, making the indicator less sensitive to short-term fluctuations.
6. **Normalization**:
- To ensure the cumulative delta is easy to interpret, the script normalizes it to a range of 0 to 1. This is done by tracking the minimum and maximum values of the smoothed cumulative delta and scaling the data accordingly.
7. **Visualization**:
- The normalized cumulative delta is plotted as a smooth line, allowing users to see the overall trend of the cumulative price changes for the top five NASDAQ stocks.
- A horizontal line is added at 0.5, serving as a midline reference, which can help traders quickly assess whether the normalized cumulative delta is above or below its midpoint.
### Usage:
This indicator is particularly useful for traders and investors who want to monitor the aggregated price movements of the top NASDAQ stocks, providing a high-level view of market sentiment and trends. By smoothing and normalizing the data, it offers a clear and concise visualization that can be used to identify potential market turning points or confirm ongoing trends.
Red Candles with Green Precedent
**Title**: Red Candles with Green Precedent Indicator
**Description**:
This TradingView indicator is designed to help traders identify potential reversal or continuation patterns based on the appearance of consecutive red candles following a green candle. The script marks a region starting from a green candle that precedes at least four consecutive red candles, extending a box forward for a predefined number of bars to analyze the continuation of the trend.
**Key Features**:
- **Consecutive Red Candles Detection**: The indicator counts consecutive red candles that close lower than they open.
- **Initial Green Candle Identification**: Identifies the last green candle before a series of red candles begins. This green candle must close higher than it opens.
- **Visual Box Extension**: Creates a visual box from the open to the high of the green candle and extends it forward to highlight the period of interest.
- **Dynamic Box Termination**: Optionally terminates the box early if a significant green candle appears within the extension period, suggesting a potential reversal.
**Usage**:
1. **Setup**: Apply the indicator to any chart in TradingView. Adjust the number of consecutive red candles to track based on your trading strategy.
2. **Interpretation**: A visual green box will appear when the criteria are met. This box helps focus on the price action following a potentially significant green candle. Traders should watch for price actions within and around the box to make informed decisions.
3. **Alerts**: Consider setting alerts for when a new box is created or when a significant green candle forms that might terminate the box early, indicating potential market movements.
**Suitable for**: This indicator is suitable for traders looking for visual cues about potential bearish exhaustion or the setup for a bullish reversal, particularly in volatile markets.
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Feel free to customize the description and features according to any additional details or personal insights you might want to include based on your trading experience or the specific behaviors of the markets you track.
**Disclaimer**:
This script is provided as a tool for trading analysis and is not intended to be used as the sole basis for any trading decisions. While this indicator aims to identify potential trading opportunities, its effectiveness can depend on market conditions and individual trading strategies. Users should conduct their own research and consult with professional advisors before making any investment decisions. The creator of this script assumes no responsibility for any potential financial losses incurred from using this indicator. Trading in financial markets involves risk, and it is possible to lose more than your initial investment.
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Day/Week/Month Metrics (Zeiierman)█ Overview
The Day/Week/Month Metrics (Zeiierman) indicator is a powerful tool for traders looking to incorporate historical performance into their trading strategy. It computes statistical metrics related to the performance of a trading instrument on different time scales: daily, weekly, and monthly. Breaking down the performance into daily, weekly, and monthly metrics provides a granular view of the instrument's behavior.
The indicator requires the chart to be set on a daily timeframe.
█ Key Statistics
⚪ Day in month
The performance of financial markets can show variability across different days within a month. This phenomenon, often referred to as the "monthly effect" or "turn-of-the-month effect," suggests that certain days of the month, especially the first and last days, tend to exhibit higher than average returns in many stock markets around the world. This effect is attributed to various factors including payroll contributions, investment of monthly dividends, and psychological factors among traders and investors.
⚪ Edge
The Edge calculation identifies days within a month that consistently outperform the average monthly trading performance. It provides a statistical advantage by quantifying how often trading on these specific days yields better returns than the overall monthly average. This insight helps traders understand not just when returns might be higher, but also how reliable these patterns are over time. By focusing on days with a higher "Edge," traders can potentially increase their chances of success by aligning their strategies with historically more profitable days.
⚪ Month
Historically, the stock market has exhibited seasonal trends, with certain months showing distinct patterns of performance. One of the most well-documented patterns is the "Sell in May and go away" phenomenon, suggesting that the period from November to April has historically brought significantly stronger gains in many major stock indices compared to the period from May to October. This pattern highlights the potential impact of seasonal investor sentiment and activities on market performance.
⚪ Day in week
Various studies have identified the "day-of-the-week effect," where certain days of the week, particularly Monday and Friday, show different average returns compared to other weekdays. Historically, Mondays have been associated with lower or negative average returns in many markets, a phenomenon often linked to the settlement of trades from the previous week and negative news accumulation over the weekend. Fridays, on the other hand, might exhibit positive bias as investors adjust positions ahead of the weekend.
⚪ Week in month
The performance of markets can also vary within different weeks of the month, with some studies suggesting a "week of the month effect." Typically, the first and the last week of the month may show stronger performance compared to the middle weeks. This pattern can be influenced by factors such as the timing of economic reports, monthly investment flows, and options and futures expiration dates which tend to cluster around these periods, affecting investor behavior and market liquidity.
█ How It Works
⚪ Day in Month
For each day of the month (1-31), the script calculates the average percentage change between the opening and closing prices of a trading instrument. This metric helps identify which days have historically been more volatile or profitable.
It uses arrays to store the sum of percentage changes for each day and the total occurrences of each day to calculate the average percentage change.
⚪ Month
The script calculates the overall gain for each month (January-December) by comparing the closing price at the start of a month to the closing price at the end, expressed as a percentage. This metric offers insights into which months might offer better trading opportunities based on historical performance.
Monthly gains are tracked using arrays that store the sum of these gains for each month and the count of occurrences to calculate the average monthly gain.
⚪ Day in Week
Similar to the day in the month analysis, the script evaluates the average percentage change between the opening and closing prices for each day of the week (Monday-Sunday). This information can be used to assess which days of the week are typically more favorable for trading.
The script uses arrays to accumulate percentage changes and occurrences for each weekday, allowing for the calculation of average changes per day of the week.
⚪ Week in Month
The script assesses the performance of each week within a month, identifying the gain from the start to the end of each week, expressed as a percentage. This can help traders understand which weeks within a month may have historically presented better trading conditions.
It employs arrays to track the weekly gains and the number of weeks, using a counter to identify which week of the month it is (1-4), allowing for the calculation of average weekly gains.
█ How to Use
Traders can use this indicator to identify patterns or trends in the instrument's performance. For example, if a particular day of the week consistently shows a higher percentage of bullish closes, a trader might consider this in their strategy. Similarly, if certain months show stronger performance historically, this information could influence trading decisions.
Identifying High-Performance Days and Periods
Day in Month & Day in Week Analysis: By examining the average percentage change for each day of the month and week, traders can identify specific days that historically have shown higher volatility or profitability. This allows for targeted trading strategies, focusing on these high-performance days to maximize potential gains.
Month Analysis: Understanding which months have historically provided better returns enables traders to adjust their trading intensity or capital allocation in anticipation of seasonally stronger or weaker periods.
Week in Month Analysis: Identifying which weeks within a month have historically been more profitable can help traders plan their trades around these periods, potentially increasing their chances of success.
█ Settings
Enable or disable the types of statistics you want to display in the table.
Table Size: Users can select the size of the table displayed on the chart, ranging from "Tiny" to "Auto," which adjusts based on screen size.
Table Position: Users can choose the location of the table on the chart
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. 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.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
