Uptrick: Bullish/Bearish Signal DetectorDetailed Explanation of the "Uptrick: Bullish/Bearish Signal Detector" Script
The "Uptrick: Bullish/Bearish Signal Detector" script is a sophisticated tool designed for the TradingView platform, leveraging Pine Script version 5. This script is crafted to enhance traders' ability to identify bullish (buy) and bearish (sell) signals directly on their trading charts. By combining the power of the MACD (Moving Average Convergence Divergence) and RSI (Relative Strength Index) indicators, this script provides a unique and efficient method for detecting potential trading opportunities. Below is an in-depth exploration of its purpose, features, and functionality.
Purpose
The primary purpose of this script is to assist traders in identifying potential entry and exit points in the market by signaling bullish and bearish conditions. This automated detection helps traders make more informed decisions without the need to manually analyze complex indicators. By overlaying signals directly on the price chart, the script allows for quick visual identification of market trends and reversals.
Uniqueness
What sets this script apart is its dual use of MACD and RSI indicators. While many trading strategies might rely on a single indicator, combining MACD and RSI enhances the reliability of the signals by filtering out false positives. The script not only identifies trends but also adds a layer of confirmation through the RSI, which measures the speed and change of price movements.
Inputs and Features
Customizable Label Appearance:
The script allows users to customize the appearance of the labels that indicate bullish and bearish signals. Users can set their preferred colors for the labels and the text, ensuring that the signals are easily distinguishable and aesthetically pleasing on their charts.
MACD Calculation:
The script calculates the MACD line and signal line using user-defined input values for the fast length, slow length, and signal length. The MACD histogram, which is the difference between the MACD line and the signal line, is used to determine the momentum of the market.
RSI Calculation:
The RSI is calculated using a user-defined input length. The RSI helps in identifying overbought or oversold conditions, which are crucial for confirming the strength of the trend detected by the MACD.
Bullish and Bearish Conditions:
The script defines bullish conditions as those where the MACD histogram is positive and the RSI is above 50. Bearish conditions are defined where the MACD histogram is negative and the RSI is below 50. This combination of conditions ensures that signals are generated based on both momentum and relative strength, reducing the likelihood of false signals.
Label Plotting:
The script plots labels on the chart to indicate bullish and bearish signals. When a bullish condition is met, and the previous signal was not bullish, a "LONG" label is plotted. Similarly, when a bearish condition is met, and the previous signal was not bearish, a "SHORT" label is plotted. This feature helps in clearly marking the points of interest for traders, making it easier to spot potential trades.
Tracking Previous Signals:
To avoid repetitive signals, the script keeps track of the last signal. If the last signal was bullish, it avoids plotting another bullish signal immediately. The same logic applies to bearish signals. This tracking ensures that signals are spaced out and only significant changes in market conditions are highlighted.
How It Works
The script operates in a loop, processing each bar (or candlestick) on the chart as new data comes in. It calculates the MACD and RSI values for each bar and checks if the current conditions meet the criteria for a bullish or bearish signal. If a signal is detected and it is different from the last signal, a label is plotted on the chart at the current bar's price level. This real-time processing allows traders to see the signals as they form, providing timely insights into market movements.
Practical Application
For practical use, a trader would add this script to their TradingView chart. They can customize the input parameters for the MACD and RSI calculations to fit their trading strategy or preferred settings. Once added, the script will automatically analyze the price data and start plotting "LONG" and "SHORT" labels based on the detected signals. Traders can then use these labels to make decisions on entering or exiting trades, adjusting their strategy as necessary based on the signals provided.
Conclusion
The "Uptrick: Bullish/Bearish Signal Detector" script is a powerful tool for any trader looking to leverage technical indicators for better trading decisions. By combining MACD and RSI, it offers a robust method for detecting market trends and potential reversals. The customizable features and real-time signal plotting make it a versatile and user-friendly addition to any trading toolkit. This script not only simplifies the process of technical analysis but also enhances the accuracy of trading signals, thereby potentially increasing the trader's success rate in the market.
Cerca negli script per "track"
ATH Distance HeatmapThe "ATH Distance Heatmap" is a powerful visualization tool designed for traders and investors who seek to quickly assess the relative performance of assets against their All-Time Highs (ATH). By mapping the percentage distance of current prices from their historical peaks, this script provides a unique perspective on market sentiment, potential recovery opportunities, and overvaluation risks.
Key Features:
Visual Clarity: Utilize a color-coded heatmap to instantly recognize which assets are near or far from their ATHs. Colors transition smoothly from cool to warm tones, indicating smaller to larger distances respectively.
Real-Time Updates: The script updates dynamically with live market data, ensuring you have the most current information at your fingertips.
Versatile Application: Whether you're tracking stocks, cryptocurrencies, commodities, or indices, the "ATH Distance Heatmap" adapts to a wide array of assets, making it a versatile tool for your trading arsenal.
Insightful Analysis: Beyond mere visualization, this tool can help identify potential buying opportunities in assets that are significantly below their ATHs, or highlight caution for those nearing their peaks.
How to Use:
Configure Your Assets: Start by selecting the assets you wish to track. The script can be customized to monitor a broad market range or a specific segment.
Interpret the Colors: Use the color gradient to gauge the distance of each asset from its ATH. Cooler colors indicate assets closer to their ATH, while warmer colors highlight those further away.
Ideal for:
Traders looking for a quick visual guide to market trends and asset performance.
Investors aiming to capitalize on recovery opportunities or to evaluate entry and exit points.
Market analysts interested in a concise overview of asset health relative to historical performance.
FlexiSuperTrend - Strategy [presentTrading]█ Introduction and How it is Different
The "FlexiSuperTrend - Strategy" by PresentTrading is a cutting-edge trading strategy that redefines market analysis through the integration of the SuperTrend indicator and advanced variance tracking.
BTC 6H L/S
This strategy stands apart from conventional methods by its dynamic adaptability, capturing market trends and momentum shifts with increased sensitivity. It's designed for traders seeking a more responsive tool to navigate complex market movements.
Local
█ Strategy, How It Works: Detailed Explanation
The "FlexiSuperTrend - Strategy" employs a multifaceted approach, combining the adaptability of the SuperTrend indicator with variance tracking. The strategy's core lies in its unique formulation and application of these components:
🔶 SuperTrend Polyfactor Oscillator:
- Basic Concept: The oscillator is a series of SuperTrend calculations with varying ATR lengths and multipliers. This approach provides a broader and more nuanced perspective of market trends.
- Calculation:
- For each iteration, `i`, the SuperTrend is calculated using:
- `ATR Length = indicatorLength * (startingFactor + i * incrementFactor)`.
- `Multiplier = dynamically adjusted based on market conditions`.
- The SuperTrend output for each iteration is compared with the indicator source (like hlc3), and the deviation is recorded.
SuperTrend Calculation:
- `Upper Band (UB) = hl2 + (ATR Length * Multiplier)`
- `Lower Band (LB) = hl2 - (ATR Length * Multiplier)`
- Where `hl2` is the average of high and low prices.
Deviation Calculation:
- `Deviation = indicatorSource - SuperTrend Value`
- This value is calculated for each SuperTrend setting in the oscillator series.
🔶 Indicator Source (`hlc3`):
- **Usage:** The strategy uses the average of high, low, and close prices, providing a balanced representation of market activity.
🔶 Adaptive ATR Lengths and Factors:
- Dynamic Adjustment: The strategy adjusts the ATR length and multiplier based on the `startingFactor` and `incrementFactor`. This adaptability is key in responding to changing market volatilities.
- Equation: ATR Length at each iteration `i` is given by `len = indicatorLength * (startingFactor + i * incrementFactor)`.
incrementFactor - 1
incrementFactor - 2
🔶 Normalization Methods:
Purpose: To standardize the deviations for comparability.
- Methods:
- 'Max-Min': Scales the deviation based on the range of values.
- 'Absolute Sum': Uses the sum of absolute deviations for normalization.
Normalization 'Absolute Sum'
- For 'Max-Min': `Normalized Deviation = (Deviation - Min(Deviations)) / (Max(Deviations) - Min(Deviations))`
- For 'Absolute Sum': `Normalized Deviation = Deviation / Sum(Absolute(Deviations))`
🔶 Trading Logic:
The strategy integrates the SuperTrend indicator, renowned for its effectiveness in identifying trend direction and reversals. The SuperTrend's incorporation enhances the strategy's ability to filter out false signals and confirm genuine market trends. * The SuperTrend Toolkit is made by @QuantiLuxe
- Long Entry Conditions: A buy signal is generated when the current trend, as indicated by the SuperTrend Polyfactor Oscillator, turns positive.
- Short Entry Conditions: A sell signal is triggered when the current trend turns negative.
- Entry and Exit Strategy: The strategy opens or closes positions based on these signals, aligning with the selected trade direction (long, short, or both).
█ Trade Direction
The strategy is versatile, allowing traders to choose their preferred trading direction: long, short, or both. This flexibility enables traders to tailor their strategies to their market outlook and risk appetite.
█ Usage
The FlexiSuperTrend strategy is suitable for various market conditions and can be adapted to different asset classes and time frames. Traders should set the strategy parameters according to their risk tolerance and trading goals. It's particularly useful for capturing long-term movements, ideal for swing traders, yet adaptable for short-term trading strategies.
█ Default Settings
1. Trading Direction: Choose from "Long", "Short", or "Both" to define the trade type.
2. Indicator Source (HLC3): Utilizes the HLC3 as the primary price reference.
3. Indicator Length (Default: 10): Influences the moving average calculation and trend sensitivity.
4. Starting Factor (0.618): Initiates the ATR length, influenced by Fibonacci ratios.
5. Increment Factor (0.382): Adjusts the ATR length incrementally for dynamic trend tracking.
6. Normalization Method: Options include "None", "Max-Min", and "Absolute Sum" for scaling deviations.
7. SuperTrend Settings: Varied ATR lengths and multipliers tailor the indicator's responsiveness.
8. Additional Settings: Features mesh style plotting and customizable colors for visual distinction.
The default settings provide a balanced approach, but users are encouraged to adjust them based on their individual trading style and market analysis.
lib_retracement_patternsLibrary "lib_retracement_patterns"
types and functions for XABCD pattern detection and plotting
method set_tolerances(this, tolerance_Bmin, tolerance_Bmax, tolerance_Cmin, tolerance_Cmax, tolerance_Dmin, tolerance_Dmax)
sets tolerances for B, C and D retracements. This creates another Pattern instance that is set as tolerances field on the original and will be used for detection instead of the original ratios.
Namespace types: Pattern
create_config(pattern_line_args, pattern_point_args, name_label_args, retracement_line_args, retracement_label_args, line_args_Dtarget, line_args_completion, line_args_tp1, line_args_tp2, line_args_sl, label_args_completion, label_args_tp1, label_args_tp2, label_args_sl, label_terminal, label_terminal_up_char, label_terminal_down_char, color_bull, color_bear, color_muted, fill_opacity, draw_point_labels, draw_retracements, draw_target_range, draw_levels, hide_shorter_if_shared_legs_greater_than_max, hide_engulfed_pattern, hide_engulfed_pattern_of_same_type, hide_longer_pattern_with_same_X, mute_previous_pattern_when_next_overlaps, keep_failed_patterns)
method direction(this)
Namespace types: Match
method length(this)
return the length of this pattern, determined by the distance between X and D point
Namespace types: Match
method height(this)
return the height of this pattern, determined by the distance between the biggest distance between A/C and X/D
Namespace types: Match
method is_forming(this)
returns true if not complete, not expired and not invalidated
Namespace types: Match
method tostring(this)
return a string representation of all Matches in this map
Namespace types: Match
method tostring(this)
Namespace types: map
remove_complete_and_expired(this)
method add(this, item)
Namespace types: map
method is_engulfed_by(this, other)
checks if this Match is engulfed by the other
Namespace types: Match
method update(tracking_matches, zigzag, patterns, max_age_idx, detect_dir, pattern_minlen, pattern_maxlen, max_sub_waves, max_shared_legs, max_XB_BD_ratio, debug_log)
checks this map of tracking Matches if any of them was completed or invalidated in
Namespace types: map
method mute(this, mute_color, mute_fill_color)
mute this pattern by making it all one color (lines and labels, for pattern fill there's another)
Namespace types: Match
method mute(this, mute_color, mute_fill_color)
mute all patterns in this map by making it all one color (lines and labels, for pattern fill there's another)
Namespace types: map
method hide(this)
hide this pattern by muting it with a transparent color
Namespace types: Match
method reset_styles(this)
reset the style of a muted or hidden match back to the preset configuration
Namespace types: Match
method delete(this)
remove the plot of this Match from the chart
Namespace types: Match
method delete(this)
remove all the plots of the Matches in this map from the chart
Namespace types: map
method draw(this)
draw this Match on the chart
Namespace types: Match
method draw(this, config, all_patterns, debug_log)
draw all Matches in this map, considering all other patterns for engulfing and overlapping
Namespace types: map
method check_hide_or_mute(this, all, config, debug_log)
checks if this pattern needs to be hidden or muted based on other plotted patterns and given configuration
Namespace types: Match
method add_if(id, item, condition)
convenience function to add a search pattern to a list, only if given condition (input.bool) is true
Namespace types: Pattern
Pattern
type to hold retracement ratios and tolerances for this pattern, as well as targets for trades
Config
allows control of pattern plotting shape and colors, as well as settings for hiding overlapped patterns etc.
Match
holds all information on a Pattern and a successful match in the chart. Includes XABCD pivot points as well as all Line and Label objects to draw it
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!
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 ...
Discord Levels (Label Toggle)This indicator is designed to streamline your multi-asset level tracking by displaying custom price levels directly on your chart for up to eight different stocks. It allows you to define key support, resistance, and moving average levels, enhancing your analysis across various instruments.
Key Features:
Multi-Stock Level Display: Track important levels for up to 8 distinct stock symbols simultaneously.
Customizable Level Inputs: Define all your desired price levels using a simple space-separated string for each stock.
Intelligent Color-Coding: Levels are automatically color-coded for quick identification based on the associated notes in your input string:
White Line: Standard price levels (e.g., 123.45).
Yellow Line: Levels designated as 200 Daily EMA (e.g., 18.70=daily 200 ema).
Blue Line: Levels designated as 50 Daily EMA (e.g., 18.70=daily 50 ema).
Gray Line: Levels designated as 34 Daily EMA (e.g., 18.70=daily 34 ema).
Green Line: Levels designated as 9 Daily EMA (e.g., 18.70=daily 9 ema).
Red Line: Critical or Cautionary levels (e.g., 9.00=cautionary).
Dynamic Label Positioning: Price labels are displayed next to the lines, dynamically positioned to the right of the current bar (30 bars offset) for optimal visibility across different timeframes.
Global Label Toggle: Easily enable or disable all price labels from the indicator's settings.
How to Use:
Input Stock Symbol: For each slot (Stock 1 to Stock 8) you wish to use, enter the exact TradingView symbol (e.g., AAPL, MSFT, TSLA).
Input Levels String: In the corresponding "Levels" input field, enter your desired price levels separated by spaces.
Basic Level: Just enter the number (e.g., 12.34).
Levels with Notes: Use the format PRICE=NOTE for specific annotations (e.g., 18.70=daily 200 ema, 9.00=cautionary).
Supported Notes for Automatic Coloring: daily 200 ema, daily 50 ema, daily 34 ema, daily 9 ema, cautionary, critical. (Case-insensitive)
Manage Slots: If you need to track more than 8 stocks, simply clear the symbol and levels for an old stock and use that slot for your new entry.
This indicator is a powerful tool for traders who rely on fixed price levels and moving averages across multiple securities, providing clear visual cues without cluttering your main chart analysis.
Weekend Trap
Weekend Trap Indicator
A comprehensive weekend range analysis tool designed to identify and track low-liquidity weekend price movements with advanced market maker detection.
What is the Weekend Trap?
The Weekend Trap refers to price ranges established during low-liquidity weekend periods (Saturday 5:00 AM to Monday 5:00 AM Perth time) when institutional trading is minimal.
Key Features
📊 Weekend Range Detection
Automatically identifies weekend periods based on Perth timezone
Creates visual rectangles showing weekend high/low ranges
Displays 50% midline for key pivot levels
Configurable range cutoff (default: Sunday 3:00 PM)
🎯 Advanced Market Maker Detection
PVSRA-style volume analysis for institutional activity identification
4-color coding system:
🟢 Lime: 200% Bull volume (Peak volume + bullish candle)
🔴 Red: 200% Bear volume (Peak volume + bearish candle)
🔵 Blue: 150% Bull volume (Rising volume + bullish candle)
🟣 Fuchsia: 150% Bear volume (Rising volume + bearish candle)
Weighted volume calculation for better peak detection
Circles positioned above bars for clear visualization
📈 Range Analytics
Clean range labels showing:
Absolute price range
Percentage movement
Historical analysis with configurable lookback period
Current weekend tracking with real-time updates
Settings Overview
Core Settings
Weeks to Backtest (1-52): Number of completed weekends to display
Show Weekend Trap Rectangles: Toggle rectangle visibility
Use Wicks for Rectangle Height: Include wicks vs. body-only ranges
Sunday Range Cutoff Hour: When to stop updating weekend range
Visual Customization
Rectangle colors and borders
Market maker marker sizes (tiny to large)
PVSRA color scheme for different volume levels
Label display options
Market Maker Detection
Automatic PVSRA analysis during weekend periods
150% threshold: Volume ≥ 150% of 10-period average
200% threshold: Volume ≥ 200% of average OR weighted volume peak
Real-time detection with immediate visual feedback
How to Use
Add to your chart (works on any timeframe, recommended: 1H-4H)
Set your preferred lookback period (default: 4 weeks)
Observe weekend ranges and note market maker activity
Monitor volume spikes indicated by colored circles
Analysis Applications
Weekend Range Analysis
Identify price ranges during low-liquidity periods
Track historical weekend price movements
Analyze range size and frequency patterns
Market Maker Detection
Identify institutional accumulation/distribution
Spot manipulation during low-liquidity periods
Analyze volume patterns and anomalies
Historical Pattern Recognition
Weekend range comparison across multiple periods
Multiple timeframe analysis capability
Volume pattern identification
Technical Details
Timezone: Australia/Perth (GMT+8)
Weekend Period: Saturday 5:00 AM → Monday 5:00 AM
Volume Analysis: 10-period moving average baseline
Weighted Volume: Volume × (High - Low) for peak detection
Object Management: Automatic cleanup based on lookback period
Best Practices
Use on liquid markets (major forex pairs, crypto, indices)
Adjust lookback period based on analysis timeframe
Monitor during Asia-Pacific trading hours for best results
Consider fundamental events that may affect weekend gaps
Credits
Volume analysis inspired by PVSRA (Price Volume Spread Range Analysis) methodology for institutional activity detection.
This indicator is designed for educational and analysis purposes.
ICT All in One by GtraderICT All-in-One by GTrader – Description
This indicator is designed for traders who follow ICT or Smart Money Concepts. It helps you visualize key market sessions, time-based price levels, and structured macro behaviors in one clean and customizable tool.
The Killzone feature automatically draws session boxes for Asia, London, and New York (including AM, Lunch, and PM sessions). Each box can show the session name, high and low pivots, and can be customized with different colors, transparency levels, and labels.
You can also add horizontal lines at important times like the daily open or New York open. Up to five session open lines can be defined, each with customizable styles, colors, and optional text labels.
In addition, the indicator lets you display vertical time markers. These lines help you track key intraday moments such as killzone entries or important session changes. You can enable up to four of these, each with its own settings.
One of the most powerful features is the macro session tracker. This creates boxes during specific time windows where price action is monitored. It automatically draws the top and bottom price levels during that session and updates them live. It supports up to five macros and works best on lower timeframes like 1-minute, 3-minute, and 5-minute charts.
The entire script respects your selected timezone, so all sessions and times are adjusted accordingly. Everything is customizable—from label sizes and colors to how many days of drawings are shown on your chart.
This script is ideal for traders who rely on time-of-day behavior, structured price action, and ICT methodologies.
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.
---
### 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.
---
### 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.
---
### 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.
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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
