Timed Ranges [mktrader]The Timed Ranges indicator helps visualize price ranges that develop during specific time periods. It's particularly useful for analyzing market behavior in instruments like NASDAQ, S&P 500, and Dow Jones, which often show reactions to sweeps of previous ranges and form reversals.
### Key Features
- Visualizes time-based ranges with customizable lengths (30 minutes, 90 minutes, etc.)
- Tracks high/low range development within specified time periods
- Shows multiple cycles per day for pattern recognition
- Supports historical analysis across multiple days
### Parameters
#### Settings
- **First Cycle (HHMM-HHMM)**: Define the time range of your first cycle. The duration of this range determines the length of all subsequent cycles (e.g., "0930-1000" creates 30-minute cycles)
- **Number of Cycles per Day**: How many consecutive cycles to display after the first cycle (1-20)
- **Maximum Days to Display**: Number of historical days to show the ranges for (1-50)
- **Timezone**: Select the appropriate timezone for your analysis
#### Style
- **Box Transparency**: Adjust the transparency of the range boxes (0-100)
### Usage Example
To track 30-minute ranges starting at market open:
1. Set First Cycle to "0930-1000" (creates 30-minute cycles)
2. Set Number of Cycles to 5 (will show ranges until 11:30)
3. The indicator will display:
- Range development during each 30-minute period
- Visual progression of highs and lows
- Color-coded cycles for easy distinction
### Use Cases
- Identify potential reversal points after range sweeps
- Track regular time-based support and resistance levels
- Analyze market structure within specific time windows
- Monitor range expansions and contractions during key market hours
### Tips
- Use in conjunction with volume analysis for better confirmation
- Pay attention to breaks and sweeps of previous ranges
- Consider market opens and key session times when setting cycles
- Compare range sizes across different time periods for volatility analysis
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GANN Level (Salil Sir)GANN Level Indicator Description
This Pine Script calculates and plots Gann Levels based on a user-defined price input. It creates horizontal lines at key support and resistance levels derived from the input price, applying Gann's theory of market structure. The levels are dynamically calculated and squared for enhanced precision.
Key Features:
Manual Price Input:
The user inputs a round off of square root of base price (Manual_Input), which serves as the foundation for calculations.
Support and Resistance Levels:
Six resistance levels (R1 to R6) and six support levels (S1 to S6) are calculated by incrementing or decrementing the base price in steps of 0.25.
Squared Levels:
Each level is squared (level^2) to align with Gann's mathematical principles.
Visualization:
All levels, including the base price squared (GANN), are plotted as horizontal dotted lines:
Black Line: Base price squared (Gann Level).
Green Lines: Resistance levels.
Red Lines: Support levels.
Purpose:
The indicator helps traders identify potential support and resistance zones based on Gann's methodology, providing a mathematical framework for decision-making.
Usage:
Adjust the Manual Price in the settings to the desired value.
Observe the plotted levels for key support and resistance zones on the chart.
Use these levels to make informed trading decisions or to validate other indicators.
Multi Timeframe Market Formation [LuxAlgo]The Multi Timeframe Market Formation tool allows traders to analyze up to 6 different timeframes simultaneously to discover their current formation, S/R levels and their degree of synchronization with the current chart timeframe. Multi timeframe analysis made easy.
🔶 USAGE
By default, the tool displays the chart's timeframe formation plus up to 5 other formations on timeframes higher than the one in the chart.
When the chart formation is synchronized with any enabled timeframe formation, the tool displays labels and a trailing channel, it uses a gradient by default, so the more timeframes are synchronized, the more visible the labels and the trailing channel are.
All timeframes enabled in the settings panel must be higher than the chart timeframe, otherwise the tool will display an error message.
🔹 Formations
A formation is a market structure defined by a lower and an upper boundary (also known as support & resistance).
Each formation has a different symbol and color to identify it at a glance.
It helps traders to know the current market behavior and the tool displays up to 5 of them.
BULLISH (green ▲): higher high and higher low
BEARISH (red ▼): lower high and lower low
CONTRACTION (orange ◀): lower high and higher low
EXPANSION (blue ▶): higher high and lower low
SIDEWAYS (yellow ◀): Any that does not fit with the others
🔹 Multi Timeframe Formations
The tool displays up to 6 different timeframe formations, the chart timeframe plus 5 more configurable from the settings panel.
Each of them has an upper and lower limit, a timeframe, a color and an icon.
If a bound level is shared by more than one formation, the timeframes and symbols are displayed on the same line.
These are significant levels shared by different timeframes and traders need to be aware of them.
🔹 Sync With Chart Timeframe
If the current formation on the chart timeframe is in sync with any of the timeframes enabled in the settings panel, the tool will display this on the chart.
The more timeframes are in sync, the more they are visible, providing a clear visual representation of the common market behavior on multiple timeframes at the same time.
🔶 SETTINGS
Formation size: Size of market formations on the chart timeframe
🔹 Timeframes
TF1 to TF5: Activate/deactivate timeframe, set size of market formation and activate/deactivate high and low levels
🔹 Style
Show Labels: Enable/Disable Timeframe Sync Labels
Transparency Gradient: Enable/Disable Transparency Gradient
Show Trailing Channel | Multiplier: Enable/Disable Trailing Channel and set multiplier
Color for each formation
ELC Indicator**ELC Indicator – Enigma Liquidity Concept**
The ELC Indicator is a cutting-edge tool designed for traders who want to leverage price action and liquidity concepts for high-precision trading opportunities. Unlike conventional indicators that rely purely on trend-following or oscillatory methods, ELC incorporates a unique combination of market structure, Fibonacci retracement levels, and dynamic EMA filtering to detect key buy and sell zones. This original approach helps traders capture the most relevant market movements and anticipate potential reversals with higher confidence.
---
### **What the ELC Indicator Does**
The primary goal of the ELC Indicator is to identify liquidity zones and plot Fibonacci-based levels around detected buy or sell signals. It continuously monitors price action to identify instances where significant liquidity grabs occur, signaled by breakouts beyond recent highs or lows. Once a signal is detected, the indicator plots horizontal lines at key Fibonacci ratios (0%, 25%, 50%, 75%, 100%, 120%, and 180%) to give traders a clear visual framework for potential retracement or extension levels.
Additionally, the indicator includes a dynamic EMA filter, which ensures that buy signals are only triggered when the price is above the EMA and sell signals when the price is below the EMA. This filtering mechanism helps reduce false signals in choppy markets and aligns trades with the broader trend direction.
---
### **Key Features**
1. **Buy & Sell Signals**
- Buy signals are generated when a liquidity grab occurs below the previous low, and the closing price is above the candle body midpoint and the EMA.
- Sell signals are triggered when a liquidity grab occurs above the previous high, and the closing price is below the candle body midpoint and the EMA.
- Visual cues are provided via small upward (green) and downward (red) triangles on the chart.
2. **Fibonacci Levels**
- For each buy or sell signal, the indicator plots multiple horizontal lines at key Fibonacci levels. These levels can help traders set realistic profit targets and stop-loss levels.
- The plotted lines can be customized in terms of style (solid, dotted, dashed) and color (buy and sell line colors).
3. **Dynamic EMA Filtering**
- A customizable EMA filter is integrated into the logic to align trades with the prevailing trend.
- The EMA length is adjustable, allowing traders to fine-tune the indicator based on their trading style and market conditions.
4. **Alert System**
- Alerts can be enabled for both buy and sell signals, ensuring traders never miss an opportunity even when away from the screen.
- Alerts are triggered once per bar, ensuring timely notifications without excessive noise.
5. **Customizable Signal Visibility**
- Traders can toggle the visibility of the last 9 buy and sell signals. When this option is disabled, only the most recent signal is displayed, helping to declutter the chart.
---
### **How to Use the ELC Indicator**
- **Trend Following**: The ELC Indicator works well in trending markets by filtering signals based on the EMA direction. Traders can use the plotted Fibonacci levels to enter trades, set profit targets, and manage risk.
- **Reversal Trading**: The liquidity grab detection mechanism allows traders to capture potential market reversals. By waiting for price retracements to key Fibonacci levels after a signal, traders can enter trades with a favorable risk-to-reward ratio.
- **Scalping & Day Trading**: With its ability to plot key intraday levels and generate real-time alerts, the ELC Indicator is particularly useful for scalpers and day traders looking to exploit short-term market inefficiencies.
---
### **Concepts Underlying the Calculations**
1. **Liquidity Grabs**: The ELC Indicator’s core logic is based on detecting instances where the market moves beyond a recent high or low, triggering a liquidity grab. This often signals a potential reversal or continuation, depending on broader market conditions.
2. **Fibonacci Ratios**: Once a signal is detected, key Fibonacci levels are plotted to provide traders with actionable zones for trade entries, profit targets, or stop-loss placements.
3. **EMA Filtering**: The EMA acts as a dynamic trend filter, ensuring that signals are aligned with the dominant market direction. This reduces the likelihood of entering trades against the prevailing trend.
---
### **Why ELC is Unique**
The ELC Indicator stands out by combining multiple powerful trading concepts—liquidity, Fibonacci ratios, and EMA filtering—into a single tool that provides actionable and visually intuitive information. Unlike traditional trend-following indicators that lag behind price action, ELC proactively identifies key market turning points based on liquidity events. Its customizable features, real-time alerts, and comprehensive plotting of Fibonacci levels make it a versatile tool for traders across various styles and timeframes.
Whether you're a scalper looking for intraday opportunities or a swing trader aiming to capture larger moves, the ELC Indicator offers a robust framework for identifying and executing high-probability trades.
---
### **How to Get Started**
1. Add the ELC Indicator to your chart.
2. Customize the EMA length, line colors, and style based on your preference.
3. Enable alerts to receive real-time notifications of buy and sell signals.
4. Use the plotted Fibonacci levels to plan your trade entries, profit targets, and stop-loss levels.
5. Combine the signals from ELC with your existing market analysis for optimal results.
---
This unique approach makes the ELC Indicator a valuable tool for traders seeking precision, clarity, and consistency in their trading decisions.
Support Resistance Major/Minor [TradingFinder] Market Structure🔵 Introduction
Support and resistance levels are key concepts in technical analysis, serving as critical points where prices pause or reverse due to the interaction of supply and demand. These foundational elements in price action and classical technical analysis assist traders in understanding market behavior and making better trading decisions.
Support levels are zones where demand is strong enough to prevent further price declines, while resistance levels act as barriers that hinder price increases.
Support and resistance levels are divided into two main types: static and dynamic. Static levels are fixed horizontal lines on charts, formed based on historical price points, and are crucial due to repeated price reactions in these areas.
Dynamic levels, on the other hand, move with market trends and are often identified using tools like moving averages and trendlines. These levels are particularly useful for analyzing dynamic trends and identifying potential reversal points in financial markets.
The importance of support and resistance in technical analysis lies in their ability to pinpoint price reversal or continuation points. Professional traders use these levels to determine optimal entry and exit points and combine them with tools such as Fibonacci retracements or moving averages for precise strategies.
Detailed analysis of price behavior at these levels provides insights into trend strength and the likelihood of price breaks or reversals. By understanding these concepts, technical analysts can forecast future price movements and optimize their trading decisions using tools such as indicators and price action. Support and resistance levels, as a cornerstone of technical analysis, form the foundation for many trading strategies.
🔵 How to Use
The Static Support and Resistance Indicator is a vital tool for identifying significant price zones in financial markets. It automatically detects major and minor support and resistance levels in both short-term and long-term intervals, enabling traders to analyze price behavior accurately and develop optimal entry and exit strategies.
🟣 Major Long-Term Support and Resistance
Major Long-Term Support : The lowest price points recorded over long-term intervals that prevent further declines.
Major Long-Term Resistance : The highest price points in long-term intervals that limit further price increases.
🟣 Minor Long-Term Support and Resistance
Minor Long-Term Support : Temporary halts in price decline within a downtrend over long-term intervals.
Minor Long-Term Resistance : Short-term zones within long-term intervals where prices react negatively in an uptrend.
🟣 Major Short-Term Support and Resistance
Major Short-Term Support : The lowest price points in short-term intervals that act as barriers against sharp price drops.
Major Short-Term Resistance : The highest points in short-term intervals that prevent further price surges.
🟣 Minor Short-Term Support and Resistance
Minor Short-Term Support : Temporary halts in price decline within short-term downtrends.
Minor Short-Term Resistance : Zones where price reacts quickly and reverses in short-term uptrends.
🔵 Settings
Long Term S&R Pivot Period : Defines the interval for identifying long-term support and resistance levels (default: 21).
Short Term S&R Pivot Period : Defines the interval for identifying short-term support and resistance levels (default: 5).
🟣 Long-Term Lines
Major Line Display : Enable/disable major long-term lines.
Minor Line Display : Enable/disable minor long-term lines.
Major Line Colors : Green for support, red for resistance (long-term major levels).
Minor Line Colors : Light green for support, light red for resistance (long-term minor levels).
Major Line Style : Choose between solid, dotted, or dashed lines for major long-term levels.
Minor Line Style : Choose between solid, dotted, or dashed lines for minor long-term levels.
Major Line Width : Adjust the thickness of major long-term lines.
Minor Line Width : Adjust the thickness of minor long-term lines.
🟣 Short-Term Lines
Major Line Display : Enable/disable major short-term lines.
Minor Line Display : Enable/disable minor short-term lines.
Major Line Colors : Gray-green for support, gray-red for resistance (short-term major levels).
Minor Line Colors : Dark green for support, dark red for resistance (short-term minor levels).
Major Line Style : Choose between solid, dotted, or dashed lines for major short-term levels.
Minor Line Style : Choose between solid, dotted, or dashed lines for minor short-term levels.
Major Line Width : Adjust the thickness of major short-term lines.
Minor Line Width : Adjust the thickness of minor short-term lines.
🔵 Conclusion
Static support and resistance levels are among the most critical tools in technical analysis, helping traders identify key reversal or continuation points.
This indicator simplifies and enhances the analysis process by automatically detecting major and minor levels in both short-term and long-term intervals. It allows traders to customize settings to suit their trading strategies and analyze different market levels effectively.
Using this indicator improves price action analysis, enhances market understanding, and identifies trading opportunities. Applicable to all trading styles, from day trading to long-term investing, it is an essential tool for technical analysis.
Combining this indicator with other tools like trendlines, Fibonacci retracements, and moving averages enables comprehensive analysis and allows traders to navigate financial markets with greater confidence.
Real-Time HTF Volume Footprint [BigBeluga]Real-time HTF Volume Footprint Profile is designed to provide a comprehensive view of higher timeframe volume profiles on your current chart. It overlays critical volume information from larger timeframes (like daily, weekly, or monthly) onto lower timeframe charts, helping you spot significant levels where volume is concentrated, acting as potential support or resistance.
🔵 Key Features:
HTF High and Low Zones: The indicator highlights the high and low of the chosen higher timeframe with clear zones, marking them with boxes. These zones help you see the broader market structure at a glance.
Volume Profile within HTF Range: Each higher timeframe range displays a volume profile, showing the distribution of volume at each price level. The most-traded price is highlighted in blue, known as the Point of Control (POC), indicating the price level with the highest activity.
Dynamic POC Option: Activate Dynamic POC to observe how the Point of Control shifts over time, giving insight into changing market interests and potential price direction.
Timeframe Flexibility: Select from daily, weekly, and monthly ranges (and more) to overlay their footprint profiles on your lower timeframe chart. This helps you tailor the indicator to the trading horizon that suits your strategy.
Info Table: Table shows a traders which timeframe is selected with last high and low of the selected timeframe
Visual Clarity with Custom Colors: The indicator uses subtle fills and distinct colors to ensure volume profile data integrates seamlessly into your chart without overwhelming other indicators or price data.
🔵 When to Use:
The HTF Volume Footprint Profile is essential for traders who want to bridge the gap between high-timeframe and intraday analysis. By visualizing HTF volume distribution on lower timeframes, this tool helps you:
Spot potential liquidity zones where price might react.
Identify support and resistance levels within HTF ranges.
Monitor PoC shifts that indicate changes in market behavior.
Track how current price aligns with significant volume clusters, providing a clear edge for volume-based strategies.
This indicator empowers traders to analyze lower timeframes with the context of higher timeframe volume profiles, providing a solid basis for identifying critical support and resistance levels shaped by large volume clusters. Whether you’re looking to spot liquidity zones or align your trades with broader market trends, HTF Volume Footprint Profile equips you with a strategic view.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Crypto Sectors Performance [Daveatt]IMPORTANT
⚠️ This script must be used on the Daily timeframe only.
OVERVIEW
This indicator brings the powerful sector analysis capabilities from velo.xyz/market's
Sector Performance chart to TradingView.
It enables traders to track and compare performance across the crypto market's major sectors, providing essential insights for sector rotation strategies and market analysis.
CALCULATION METHOD
The indicator calculates performance across six key crypto sectors: DeFi, Gaming, Layer 1s, Layer 2s, AI, and Memecoins.
For each sector, it computes a rolling percentage performance by averaging the performance of multiple representative tokens.
All sector performances are rebased to 0% at the start of each period, making relative comparisons clear and intuitive.
VISUALIZATION MODES
The script features two distinct visualization methods:
Plots Mode:
Displays continuous performance lines for each sector over time, ideal for tracking relative strength trends and sector momentum. Each sector has its own color-coded line with performance values clearly marked.
Bars Mode:
Presents current sector performance as vertical bars, offering an immediate visual comparison of sector gains and losses.
The bars are color-coded and labeled with exact percentage values for precise analysis.
For the "Bars Mode", I used the box.new() function
SECTOR COMPOSITION
Each sector comprises carefully selected representative tokens:
- DeFi: AAVE, 1INCH, JUP, MKR, UNI
- Gaming: GALA, AXS, RONIN, SAND
- Layer 1: BTC, ETH, AVAX, APT, SOL, BNB, SUI
- Layer 2: ARB, OP, ZK, POL, STRK, MNT
- AI: FET, NEAR, RENDER, TAO
- Memecoins: PEPE, BONK, SHIB, DOGE, WIFU, POPCAT
PERFORMANCE TRACKING
The indicator implements a rolling window approach for performance calculations.
Starting from 0% at the beginning of each period, it tracks relative performance with positive values indicating outperformance and negative values showing underperformance.
Multiple timeframe options (1W, 1M, 3M, 6M, and 1Y) allow for both short-term and long-term analysis.
APPLICATIONS
This tool proves invaluable for:
- Sector rotation analysis
- Identifying trending sectors
- Comparing relative strength
- Gauging market sentiment
- Understanding market structure through sector performance
Thanks for reading and for the support
Daveatt
Order blocksHi all!
This indicator will show you found order blocks that can be used as supply or demand. It's my take on trying to create good order blocks and I hope it makes sense.
First off I suggest to verify the current trend before using an order block. This can be done in a variety of ways, one way could be to use my other script "Market structure" () which I use and suggest.
You can configure the indicator to behave differently depending on settings. These are the settings available:
• The order blocks created can be found in any higher timeframe defined in "Timeframe"
• The number of active order blocks are defined in "Count". If an order block is found the earliest order block will be replaced
• You can choose the type of order blocks that are found ("Bullish", "Bearish " or "Both") in "Type"
• The old order blocks can be kept if "Keep history" is checked
• Order blocks that are found are not removed when mitigated (entered) but when a new one appears. They can be removed when they are broken by price if "Remove broken zones" are checked
There is also a setting section called "Requirements" that defines what is required for an order block to be created. These are the settings:
• "Take out"
Check this if you want the base of the order block (the candle where the zone is drawn from (high and low)) to have to take out the previous candle (be higher or lower depending if the order block is bullish or bearish).
• "Consecutive rising/falling"
Each following candle in the reaction (the 3 reaction candles) needs to reach higher or lower (depending on bullish or bearish). Check this if you want that to be true.
• "Reaction"
Some sort of reaction is needed from the 3 candles creating the order block. This reaction is based on the value of the Average True Length (ATR) of length 14. You can here define a factor of the value from the ATR that these 3 candles needs to move in price. A higher need for a reaction (higher factor of the ATR) will create lesser zones. You can also choose to show this limit with the checkbox.
• "Fair Value Gap"
The reaction needs to create a gap (imbalance) in price. This gap is known as a "Fair Value Gap" and is created when the last candle's wick does not meet with the base candle's wick. Check this if you want this to be needed.
After these settings you can also choose the colors of the created zones. The ones that are active (called "Zones"), the ones that are replaced ("Replaced zones") and the ones that are broken ("Broken zones") (if this is enabled in "Remove broken zones").
I'm using my library "Touched" to be able to show you labels when the order blocks have a retest, false breakout and breakout. These labels can be hidden if you disable the labels under the style tab in the indicator settings.
The concept of order blocks is widely used among traders and can provide you with good supply or demand zones. I hope that this indicator makes sense.
My todo-list has a few things, but top of that list is adding alerts for zone interactions or creations. Please feel free to say what you want to be coded!
The order blocks in the publication chart are found in weekly timeframe but are shown on the daily timeframe. Other than that the image shows you zones from the default settings (which are based on the daily timeframe).
Best of luck trading!
[Stuppieeeeeee] - Multiple vertical timeframes linesEnhance your trading experience with this intuitive indicator that displays vertical lines on your chart to mark the start of new bars in higher timeframes. Whether you're analyzing on a 5-minute chart or any other lower timeframe, this tool helps you visualize when significant periods begin on larger scales like hourly, daily, or even monthly charts.
Key Features:
Multiple Timeframes Supported: Choose from 5 minutes, 15 minutes, 1 hour, 4 hours, 12 hours, daily, weekly, and monthly timeframes to display vertical lines.
Customizable Appearance: Personalize each set of lines by adjusting their colors, including transparency levels, line styles (solid, dashed, dotted), and widths to suit your preferences and enhance visibility.
Automatic Visibility Management: The indicator intelligently hides lines for timeframes that are equal to or lower than your current chart timeframe, keeping your chart clean and focused.
Future Projection: Not only does it mark the start of current higher timeframe bars, but it also projects lines into the near future. This feature allows you to anticipate upcoming significant time intervals, aiding in better planning and decision-making.
Layer Control: You have the ability to control which lines appear above others. By adjusting the drawing order and using transparency settings, you ensure that all important lines are visible without cluttering your chart.
Benefits:
Enhanced Multi-Timeframe Analysis: Quickly identify when higher timeframe bars start while analyzing lower timeframe charts, helping you align your trades with significant market movements.
Improved Market Structure Understanding: Visual cues from the vertical lines aid in recognizing patterns and trends that span across different timeframes.
Strategic Planning: Anticipate key time intervals with future projection lines, allowing you to prepare for potential market shifts.
How to Use:
Apply the Indicator:
Add the indicator to your TradingView chart as you would with any other tool.
It's most effective when used on lower timeframe charts (like 5-minute or 15-minute charts) to display lines from higher timeframes.
Customize Settings:
Open the indicator's settings panel.
For each timeframe, adjust the line color, style, width, and transparency to your liking.
Set the transparency to allow underlying lines to show through if desired.
Interpret the Lines:
Vertical lines will appear at the start of new bars for the higher timeframes you've selected.
Use these visual markers to inform your entry and exit points, aligning them with larger market movements.
Pay attention to future lines to anticipate upcoming periods of interest.
Notes:
Performance Considerations: Displaying a large number of lines may impact chart performance. If you notice any lag, consider reducing the number of active timeframes or increasing line transparency.
TradingView Limitations: Be aware that TradingView limits the number of drawing objects on a chart. The indicator is designed to manage this, but extremely long timeframes or high bar counts might affect its operation.
Fibonacci Levels Strategy with High/Low Criteria-AYNETThis code represents a TradingView strategy that uses Fibonacci levels in conjunction with high/low price criteria over specified lookback periods to determine buy (long) and sell (short) conditions. Below is an explanation of each main part of the code:
Explanation of Key Sections
User Inputs for Higher Time Frame and Candle Settings
Users can select a higher time frame (timeframe) for analysis and specify whether to use the "Current" or "Last" higher time frame (HTF) candle for calculating Fibonacci levels.
The currentlast setting allows flexibility between using real-time or the most recent closed higher time frame candle.
Lookback Periods for High/Low Criteria
Two lookback periods, lowestLookback and highestLookback, allow users to set the number of bars to consider when finding the lowest and highest prices, respectively.
This determines the criteria for entering trades based on how recent highs or lows compare to current prices.
Fibonacci Levels Configuration
Fibonacci levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, and 100%) are configurable. These are used to calculate price levels between the high and low of the higher time frame candle.
Each level represents a retracement or extension relative to the high/low range of the HTF candle, providing important price levels for decision-making.
HTF Candle Calculation
HTF candle data is calculated based on the higher time frame selected by the user, using the newbar check to reset htfhigh, htflow, and htfopen values.
The values are updated with each new HTF bar or as prices move within the same HTF bar to track the highest high and lowest low accurately.
Set Fibonacci Levels Array
Using the calculated HTF candle's high, low, and open, the Fibonacci levels are computed by interpolating these values according to the user-defined Fibonacci levels.
A fibLevels array stores these computed values.
Plotting Fibonacci Levels
Each Fibonacci level is plotted on the chart with a different color, providing visual indicators for potential support/resistance levels.
High/Low Price Criteria Calculation
The lowest and highest prices over the specified lookback periods (lowestLookback and highestLookback) are calculated and plotted on the chart. These serve as dynamic levels to trigger long or short entries.
Trade Signal Conditions
longCondition: A long (buy) signal is generated when the price crosses above both the lowest price criteria and the 50% Fibonacci level.
shortCondition: A short (sell) signal is generated when the price crosses below both the highest price criteria and the 50% Fibonacci level.
Executing Trades
Based on the longCondition and shortCondition, trades are entered with the strategy.entry() function, using the labels "Long" and "Short" for tracking on the chart.
Strategy Use
This strategy allows traders to utilize Fibonacci retracement levels and recent highs/lows to identify trend continuation or reversal points, potentially providing entry points aligned with larger market structure. Adjusting the lowestLookback and highestLookback along with Fibonacci levels enables a customizable approach to suit different trading styles and market conditions.
ICT Setup 03 [TradingFinder] Judas Swing NY 9:30am + CHoCH/FVG🔵 Introduction
Judas Swing is an advanced trading setup designed to identify false price movements early in the trading day. This advanced trading strategy operates on the principle that major market players, or "smart money," drive price in a certain direction during the early hours to mislead smaller traders.
This deceptive movement attracts liquidity at specific levels, allowing larger players to execute primary trades in the opposite direction, ultimately causing the price to return to its true path.
The Judas Swing setup functions within two primary time frames, tailored separately for Forex and Stock markets. In the Forex market, the setup uses the 8:15 to 8:30 AM window to identify the high and low points, followed by the 8:30 to 8:45 AM frame to execute the Judas move and identify the CISD Level break, where Order Block and Fair Value Gap (FVG) zones are subsequently detected.
In the Stock market, these time frames shift to 9:15 to 9:30 AM for identifying highs and lows and 9:30 to 9:45 AM for executing the Judas move and CISD Level break.
Concepts such as Order Block and Fair Value Gap (FVG) are crucial in this setup. An Order Block represents a chart region with a high volume of buy or sell orders placed by major financial institutions, marking significant levels where price reacts.
Fair Value Gap (FVG) refers to areas where price has moved rapidly without balance between supply and demand, highlighting zones of potential price action and future liquidity.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The Judas Swing setup enables traders to pinpoint entry and exit points by utilizing Order Block and FVG concepts, helping them align with liquidity-driven moves orchestrated by smart money. This setup applies two distinct time frames for Forex and Stocks to capture early deceptive movements, offering traders optimized entry or exit moments.
🟣 Bullish Setup
In the Bullish Judas Swing setup, the first step is to identify High and Low points within the initial time frame. These levels serve as key points where price may react, forming the basis for analyzing the setup and assisting traders in anticipating future market shifts.
In the second time frame, a critical stage of the bullish setup begins. During this phase, the price may create a false break or Fake Break below the low level, a deceptive move by major players to absorb liquidity. This false move often causes smaller traders to enter positions incorrectly. After this fake-out, the price reverses upward, breaking the CISD Level, a critical point in the market structure, signaling a potential bullish trend.
Upon breaking the CISD Level and reversing upward, the indicator identifies both the Order Block and Fair Value Gap (FVG). The Order Block is an area where major players typically place large buy orders, signaling potential price support. Meanwhile, the FVG marks a region of supply-demand imbalance, signaling areas where price might react.
Ultimately, after these key zones are identified, a trader may open a buy position if the price reaches one of these critical areas—Order Block or FVG—and reacts positively. Trading at these levels enhances the chance of success due to liquidity absorption and support from smart money, marking an opportune time for entering a long position.
🟣 Bearish Setup
In the Bearish Judas Swing setup, analysis begins with marking the High and Low levels in the initial time frame. These levels serve as key zones where price could react, helping to signal possible trend reversals. Identifying these levels is essential for locating significant bearish zones and positioning traders to capitalize on downward movements.
In the second time frame, the primary bearish setup unfolds. During this stage, price may exhibit a Fake Break above the high, causing a brief move upward and misleading smaller traders into incorrect positions. After this false move, the price typically returns downward, breaking the CISD Level—a crucial bearish trend indicator.
With the CISD Level broken and a bearish trend confirmed, the indicator identifies the Order Block and Fair Value Gap (FVG). The Bearish Order Block is a region where smart money places significant sell orders, prompting a negative price reaction. The FVG denotes an area of supply-demand imbalance, signifying potential selling pressure.
When the price reaches one of these critical areas—the Bearish Order Block or FVG—and reacts downward, a trader may initiate a sell position. Entering trades at these levels, due to increased selling pressure and liquidity absorption, offers traders an advantage in profiting from price declines.
🔵 Settings
Market : The indicator allows users to choose between Forex and Stocks, automatically adjusting the time frames for the "Opening Range" and "Trading Permit" accordingly: Forex: 8:15–8:30 AM for identifying High and Low points, and 8:30–8:45 AM for capturing the Judas move and CISD Level break. Stocks: 9:15–9:30 AM for identifying High and Low points, and 9:30–9:45 AM for executing the Judas move and CISD Level break.
Refine Order Block : Enables finer adjustments to Order Block levels for more accurate price responses.
Mitigation Level OB : Allows users to set specific reaction points within an Order Block, including: Proximal: Closest level to the current price. 50% OB: Midpoint of the Order Block. Distal: Farthest level from the current price.
FVG Filter : The Judas Swing indicator includes a filter for Fair Value Gap (FVG), allowing different filtering based on FVG width: FVG Filter Type: Can be set to "Very Aggressive," "Aggressive," "Defensive," or "Very Defensive." Higher defensiveness narrows the FVG width, focusing on narrower gaps.
Mitigation Level FVG : Like the Order Block, you can set price reaction levels for FVG with options such as Proximal, 50% OB, and Distal.
CISD : The Bar Back Check option enables traders to specify the number of past candles checked for identifying the CISD Level, enhancing CISD Level accuracy on the chart.
🔵 Conclusion
The Judas Swing indicator helps traders spot reliable trading opportunities by detecting false price movements and key levels such as Order Block and FVG. With a focus on early market movements, this tool allows traders to align with major market participants, selecting entry and exit points with greater precision, thereby reducing trading risks.
Its extensive customization options enable adjustments for various market types and trading conditions, giving traders the flexibility to optimize their strategies. Based on ICT techniques and liquidity analysis, this indicator can be highly effective for those seeking precision in their entry points.
Overall, Judas Swing empowers traders to capitalize on significant market movements by leveraging price volatility. Offering precise and dependable signals, this tool presents an excellent opportunity for enhancing trading accuracy and improving performance
Range Detect SystemTechnical analysis indicator designed to identify potential significant price ranges and the distribution of volume within those ranges. The system helps traders calculate POC and show volume history. Also detecting breakouts or potential reversals. System identifies ranges with a high probability of price consolidation and helps screen out extreme price moves or ranges that do not meet certain volatility thresholds.
⭕️ Key Features
Range Detection — identifies price ranges where consolidation is occurring.
Volume Profile Calculation — indicator calculates the Point of Control (POC) based on volume distribution within the identified range, enhancing the analysis of market structure.
Volume History — shows where the largest volume was traded from the center of the range. If the volume is greater in the upper part of the range, the color will be green. If the volume is greater in the lower part, the color will be red.
Range Filtering — Includes multi-level filtering options to avoid ranges that are too volatile or outside normal ranges.
Visual Customization — Shows graphical indicators for potential bullish or bearish crossovers at the upper and lower range boundaries. Users can choose the style and color of the lines, making it easier to visualize ranges and important levels on the chart.
Alerts — system will notify you when a range has been created and also when the price leaves the range.
⭕️ How it works
Extremes (Pivot Points) are taken as a basis, after confirming the relevance of the extremes we take the upper and lower extremes and form a range. We check if it does not violate a number of rules and filters, perform volume calculations, and only then is the range displayed.
Pivot points is a built-in feature that shows an extremum if it has not been updated N bars to the left and N bars to the right. Therefore, there is a delay depending on the bars specified to check, which allows for a more accurate range. This approach allows not to make unnecessary recalculations, which completely eliminates the possibility of redrawing or range changes.
⭕️ Settings
Left Bars and Right Bars — Allows you to define the point that is the highest among the specified number of bars to the left and right of this point.
Range Logic — Select from which point to draw the range. Maximums only, Minimums only or both.
Use Wick — Option to consider the wick of the candles when identifying Range.
Breakout Confirmation — The number of bars required to confirm a breakout, after which the range will close.
Minimum Range Length — Sets the minimum number of candles needed for a range to be considered valid.
Row Size — Number of levels to calculate POC. *Larger values increase the script load.
% Range Filter — Dont Show Range is than more N% of Average Range.
Multi Filter — Allows use of Bollinger Bands, ATR, SMA, or Highest-Lowest range channels for filtering ranges based on volatility.
Range Hit — Shows graphical labels when price hits the upper or lower boundaries of the range, signaling potential reversal or breakout points.
Range Start — Show points where Range was created.
Linear Regression Channel UltimateKey Features and Benefits
Logarithmic scale option for improved analysis of long-term trends and volatile markets
Activity-based profiling using either touch count or volume data
Customizable channel width and number of profile fills
Adjustable number of most active levels displayed
Highly configurable visual settings for optimal chart readability
Why Logarithmic Scale Matters
The logarithmic scale option is a game-changer for analyzing assets with exponential growth or high volatility. Unlike linear scales, log scales represent percentage changes consistently across the price range. This allows for:
Better visualization of long-term trends
More accurate comparison of price movements across different price levels
Improved analysis of volatile assets or markets experiencing rapid growth
How It Works
The indicator calculates a linear regression line based on the specified period
Upper and lower channel lines are drawn at a customizable distance from the regression line
The space between the channel lines is divided into a user-defined number of levels
For each level, the indicator tracks either:
- The number of times price touches the level (touch count method)
- The total volume traded when price is at the level (volume method)
The most active levels are highlighted based on this activity data
Understanding Touch Count vs Volume
Touch count method: Useful for identifying key support/resistance levels based on price action alone
Volume method: Provides insight into levels where the most trading activity occurs, potentially indicating stronger support/resistance
Practical Applications
Trend identification and strength assessment
Support and resistance level discovery
Entry and exit point optimization
Volume profile analysis for improved market structure understanding
This Linear Regression Channel indicator combines powerful statistical analysis with flexible visualization options, making it an invaluable tool for traders and analysts across various timeframes and markets. Its unique features, especially the logarithmic scale and activity profiling, provide deeper insights into market behavior and potential turning points.
Multi Deviation VWAP [OmegaTools]The Multi Deviation VWAP is an original variation of the traditional VWAP indicator, designed to enhance your trading experience by providing more precise market insights. While the conventional VWAP calculates a single price level based on volume and price over a given period, the Multi Deviation VWAP goes a step further by introducing dynamic upper and lower bands that adapt to market conditions. These bands give traders a more comprehensive understanding of volatility and price action, making it an ideal tool for various trading strategies, especially for identifying potential price reversals or trend continuations.
Key Features:
Separate Calculation of Deviation Bands:
Unlike traditional VWAP bands, where both the upper and lower bands are symmetrically calculated using a single deviation value, the Multi Deviation VWAP calculates the deviations independently for the upper and lower bands. This allows for a more accurate reflection of market dynamics.
The upper deviation band is based on the average distance of closing prices above the VWAP, while the lower deviation band considers the average distance of closing prices below the VWAP.
This separation provides a more tailored approach, adapting to whether the market is showing bullish or bearish momentum, as opposed to a fixed, equal deviation in both directions.
Internal and External Bands:
Two sets of deviation bands are plotted: Internal Bands and External Bands, controlled by user inputs (factorone for internal and factortwo for external). These bands offer multiple levels of support and resistance based on market volatility.
The Internal Bands are closer to the VWAP and act as the first level of support/resistance, suitable for short-term or tighter trading ranges.
The External Bands are further from the VWAP and capture more significant market swings, useful for identifying larger trends or setting wider stop-losses.
Timeframe Flexibility:
The indicator allows traders to select the desired timeframe (1D by default) over which the VWAP and its deviation bands are calculated. This flexibility enables users to adapt the indicator to different trading styles, from intraday scalping to longer-term trend analysis.
Visual Enhancements:
Bullish and Bearish Colors: The bands are color-coded for quick visual interpretation. Bullish bands (lower deviations) are colored blue, while bearish bands (upper deviations) are colored red, making it easy to differentiate between market conditions at a glance.
Plot Fill: The area between the internal and external bands is shaded, providing clear visual zones of potential price containment, aiding in understanding the market structure and anticipating price movements.
How It Differs from a Standard VWAP:
Traditional VWAP provides a single price line that represents the volume-weighted average price over a given period, often used to identify general price trends.
In contrast, the Multi Deviation VWAP introduces upper and lower bands calculated separately based on price deviations above and below the VWAP, giving a more nuanced view of market volatility.
Symmetrical bands in traditional VWAP may not always accurately reflect the market's true behavior, especially in trending markets, where upward and downward price movements aren't always equal. By splitting the deviation calculations, this tool provides a more dynamic and realistic view of price action, adapting to whether the market is showing stronger upward or downward pressure.
Use Cases:
Trend Identification: The VWAP line acts as a central trend line, while the deviation bands offer levels of potential support and resistance. When price moves beyond the external bands, it may indicate overextension and potential reversal.
Volatility Trading: Traders can use the internal and external bands to set dynamic take-profit or stop-loss levels, allowing for flexible risk management depending on market conditions.
Range Trading: In consolidating markets, the Multi Deviation VWAP can help traders identify optimal buy and sell zones as the price oscillates between the upper and lower bands.
By incorporating independent deviation bands, this indicator provides traders with a more responsive tool that reflects market behavior more accurately, helping them make informed trading decisions with enhanced precision.
CANSLIM Screener [TrendX_]INTRODUCTION:
The CANSLIM investment strategy, developed by William J. O'Neil, is a powerful tool for identifying growth stocks that have the potential to outperform the market. TrendX has enhanced this approach with its unique indicators, making it easier for investors to assess stocks based on seven critical criteria.
➊ C: Current Quarterly EPS or PE with Growth Benchmark
The first criterion focuses on the Earnings Per Share (EPS) growth in the most recent quarter compared to previous quarters. A company should demonstrate significant EPS growth, ideally exceeding expectations and benchmarks within its industry.
➋ A: Average Annual EPS Growth with Growth Benchmark
This aspect evaluates a company's average annual EPS growth over the last three years. A consistent upward trend suggests that the company is effectively increasing its profitability. TrendX provides a customizable benchmark to help investors identify firms with sustainable growth trajectories.
➌ N: New Highs or New Product Development
TrendX interprets this criterion through an Annual Research & Development to Revenue Ratio (RNDR). A decreasing RNDR ratio may indicate that a company is finishing new products, which could lead to reduced revenue if product launches are unsuccessful.
➍ S: Supply and Demand
This component assesses supply and demand dynamics by analyzing the movement of Float Shares Outstanding. A decrease in float shares typically indicates higher demand for the stock, suggesting that the company is in good shape for future growth.
➎ L: Leader
TrendX employs comparative analysis between the Relative Strength Index (RSI) of a company and that of the overall market. If a company's RSI is higher than the market's, it signifies that the stock is leading rather than lagging.
➏ I: Institutional Sponsorship
Institutional sponsorship is gauged through the total dividends paid by a company. High dividend payouts can signal strong institutional interest, support and confidence in the company's future prospects.
➐ M: Market Direction
TrendX evaluates market direction by comparing a company's RSI against its Moving Average of RSI, along with utilizing Market Structure in Smart Money Concept indicator for alternative trend insights.
HOW TO USE
The TrendX CANSLIM indicator provides an evaluation score based on each of the seven criteria outlined above, which displays in a table containing:
Scoring System: Each letter in CANSLIM contributes to a total score out of 100%. A stock does not need to meet all seven criteria; achieving a score above 70% (5 out of 7) is generally considered indicative of a promising growth stock.
Screening Feature: The tool includes a screening feature that evaluates multiple stocks simultaneously, allowing investors to compare their CANSLIM scores efficiently. This feature streamlines identifying potential investment opportunities across various sectors.
DISCLAIMER
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur.
Therefore, one should always exercise caution and judgment when making decisions based on past performance.
FCNC SpreadTitle: FCNC Spread Indicator
Description:
The FCNC Spread Indicator is designed to help traders analyze the price difference (spread) between two futures contracts: the front contract and the next contract. This type of analysis is commonly used in futures trading to identify market sentiment, arbitrage opportunities, and potential roll yield strategies.
How It Works:
Front Contract: The front contract represents the futures contract closest to expiration, often referred to as the near-month contract.
Next Contract: The next contract is the futures contract that follows the front contract in the expiration cycle, typically the next available month.
Spread Calculation: frontContract - nextContract represents the difference between the price of the front contract and the next contract.
Positive Spread: A positive value means that the front contract is more expensive than the next contract, indicating backwardation.
Negative Spread: A negative value means that the front contract is cheaper than the next contract, indicating contango.
How to Use:
Input Selection: Select your desired futures contracts for the front and next contract through the input settings. The script will fetch and calculate the closing prices of these contracts.
Spread Plotting: The calculated spread is plotted on the chart, with color-coding based on the spread's value (green for positive, red for negative).
Labeling: The spread value is dynamically labeled on the chart for quick reference.
Moving Average: A 20-period Simple Moving Average (SMA) of the spread is also plotted to help identify trends and smooth out fluctuations.
Applications:
Trend Identification: Analyze the spread to determine market sentiment and potential trend reversals.
Divergence Detection: Look for divergences between the spread and the underlying market to identify possible shifts in trend or market sentiment. Divergences can signal upcoming reversals or provide early warning signs of a change in market dynamics.
This indicator is particularly useful for futures traders who are looking to gain insights into the market structure and to exploit differences in contract pricing. By providing a clear visualization of the spread between two key futures contracts, traders can make more informed decisions about their trading strategies.
Wyckoff Method IndicatorThe Wyckoff Method Market Cycle Indicator is a powerful tool designed to help traders identify the current market phase based on the principles of the Wyckoff Method. This indicator analyzes price action and volume patterns to determine whether the market is in an accumulation, markup, distribution, or markdown phase.
The Wyckoff Method, developed by Richard D. Wyckoff, is a time-tested approach to understanding market dynamics and identifying potential trading opportunities. By studying the interaction between price and volume, the Wyckoff Method aims to provide insight into the actions of market participants and the potential direction of the market.
This indicator automatically detects the key market phases as defined by the Wyckoff Method:
Accumulation: This phase occurs when large institutional investors are quietly accumulating positions, often leading to a period of consolidation with low volatility and decreasing volume.
Markup: Following the accumulation phase, the markup phase is characterized by a breakout above the accumulation range, accompanied by increasing volume. This indicates a potential bullish trend.
Distribution: After a significant price advance, the distribution phase emerges. It is marked by high volatility and increasing volume as large investors begin to distribute their holdings to the public.
Markdown: The markdown phase follows the distribution phase and is characterized by a breakdown below the distribution range, accompanied by increasing volume. This suggests a potential bearish trend.
The indicator plots the detected market phases on the chart using the following signals:
Green triangle pointing upwards: Accumulation phase
Blue triangle pointing downwards: Markup phase
Red triangle pointing downwards: Distribution phase
Orange triangle pointing upwards: Markdown phase
By utilizing this indicator, traders can gain valuable insights into the underlying market structure and make more informed trading decisions. However, it is important to note that the Wyckoff Method Market Cycle Indicator should be used in conjunction with other technical analysis tools and risk management strategies.
The indicator provides two input parameters:
Lookback Period: The number of bars used to calculate the volatility and determine the market phases. The default value is 50.
Volume Condition Multiple: The multiple used to compare the current volume with the volume of the lookback period. The default value is 2.
Traders can adjust these parameters to suit their specific trading style and the characteristics of the asset being analyzed.
Please note that this indicator is intended for educational and informational purposes only. It does not constitute financial advice. Always conduct your own analysis and exercise proper risk management when trading.
Happy trading!
Bilson Gann CountGann counting is a method for identifying swing points,trends, and overall market structure. It simplifies price action by drawing short trend lines that summarize moves.
There's essentially 4 types of bar/candle.
Up bar - Higher high and higher low than previous bar
Down bar - Lower high and lower low than previous bar
Inside bar - Lower high and higher low than previous bar
Outside bar - Higher high and lower low than previous bar
We use these determinations to decide how the trendline moves through the candles.
Up bars we join to the high, down bars we join to the low, inside bars are ignored.
There are other indicators that already exist which do this, the difference here is how we handle outside bars.
Other gann counting methods skip outside bars, this method determines how to handle the outside bar after the outside bar is broken.
examples
UP -> OUTSIDE -> UP = Outside bar treated as swing low
UP -> OUTSIDE -> DOWN = Outside bar treated as swing high
DOWN -> OUTSIDE -> UP = Outside bar treated as swing low
DOWN -> OUTSIDE -> DOWN = Outside bar treated as swing high
ATR Bands (Keltner Channel), Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of ATR Bands, candle wicks crossing the ATR upper and lower bands, and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from the lower band when using phi * multiplier
B2 Signal - Potential pivot up from the lower band when using 1/2 * multiplier
B3 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the upper band when using
S2 Signal - Potential pivot down from the upper band when using 1/2 * multiplier
S3 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional B1, B2, and S1, and S2 signals can be displayed that use the bands based on a multiplier that is half that of the primary one, and phi (0.618) times the primary multiplier as a way to quickly check for signals occurring along different, but related, bands.
Calculations
ATR Bands, or Keltner Channels, are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. ATR Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of ATRs to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of ATRs from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Settings
CHANNEL SETTINGS
Baseline EMA Period (Default: 21): Period length of the moving average basis line.
ATR Period (Default: 21): The number of periods over which the Average True Range (ATR) is calculated.
Basis MA Type (Default: SMA): The moving average type for the basis line.
Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
ADDITIONAL CHANNELS
Half of Multiplier Offset (Default: True): Toggles the display of the ATR bands that are set a distance of half of the ATR multiplier.
Quarter of Multiplier Offset (Default: false): Toggles the display of the ATR bands that are set a distance of one quarter of the ATR multiplier.
Phi (Φ) Offset (Default: false): Toggles the display of the ATR bands that are set a distance of phi (Φ) times the ATR multiplier.
WICK SETTINGS FOR CANDLE FILTERS
Wick Ratio for Bands (Default: 0.4): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.4): The ratio of wick size to total candle size for use at baseline.
Use Candle Body (rather than full candle size) (Default: false): Determines whether wick calculations use the candle body or the entire candle size.
VISUAL PREFERENCES - SIGNALS
Show Signals (Default: true): Allows signal labels to be shown.
Show Signals from 1/2 Band Offset (Default: false): Toggle signals originating from 1/2 offset upper and lower bands.
Show Signals from Phi (Φ) Band Offset (Default: false): Toggle signals originating from phi (Φ) offset upper and lower bands.
Show Baseline Signals (Default: false): Toggle Baseline signals.
VISUAL PREFERENCES - BANDS
Show ATR (Keltner) Bands (Default: true): Use a background color inside the Bollinger Bands.
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
Bollinger Band Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of Bollinger Bands, candle wicks crossing the upper and lower Bollinger Bands and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional, B1 and S1 signals can be displayed that use the baseline as the pivot level.
Settings
SIGNALS
Show Bollinger Band Signals (Default: True): Allows signal labels to be shown.
Hide Baseline Signals (Default: False): Baseline signals are on by default. This will turn them off.
Show Wick Signals (Defau
lt: True): Displays signals when wicking occurs.
BOLLINGER BAND SETTINGS
Period length for Bollinger Band Basis (Default: 21): Length of the Bollinger Band (BB) moving average basis line.
Basis MA Type (Default: SMA): The moving average type for the BB Basis line.
Source (Default: “close”): The source of time series data.
Standard Deviation Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
WICK SETTINGS FOR BOLLINGER BANDS
Wick Ratio for Bands (Default: 0.3): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.3): The ratio of wick size to total candle size for use at baseline.
WICK SETTINGS FOR CANDLE SIGNALS
Upper Wick Threshold (Default: 50): The percent of upper wick compared to the full candle size or candle body size.
Lower Wick Threshold (Default: 50): The percent of lower wick compared to the full candle size or candle body size.
Use Candle Body (Default: false): Toggles the use of the full candle size versus the candle body size when calculating the wick signal.
VISUAL PREFERENCES
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
Show Signals (Default: true): Toggle the Bollinger Band upper band, lower band, and baseline signals.
Show Bollinger Bands (Default: true): Show the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Calculations
Bollinger Bands are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. Bollinger Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of standard deviations to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of standard deviations from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
ICT Concept [TradingFinder] Order Block | FVG | Liquidity Sweeps🔵 Introduction
The "ICT" style is one of the subsets of "Price Action" technical analysis. ICT is a method created by "Michael Huddleston", a professional forex trader and experienced mentor. The acronym ICT stands for "Inner Circle Trader".
The main objective of the ICT trading strategy is to combine "Price Action" and the concept of "Smart Money" to identify optimal entry points into trades. However, finding suitable entry points is not the only strength of this approach. With the ICT style, traders can better understand price behavior and adapt their trading approach to market structure accordingly.
Numerous concepts are discussed in this style, but the key practical concepts for trading in financial markets include "Order Block," "Liquidity," and "FVG".
🔵 How to Use
🟣Order Block
Order blocks are a specific type of "Supply and Demand" zones formed when a series of orders are placed in a block. These orders could be created by banks or other major players. Banks typically execute large orders in blocks during their trading sessions. If they were to enter the market directly with a small quantity, significant price movements would occur before the orders are fully executed, resulting in less profit. To avoid this, they divide their orders into smaller, manageable positions. Traders should look for "buy" opportunities in "demand order blocks" areas and "sell" opportunities in "supply order blocks".
🟣Liquidity
These levels are where traders aim to exit their trades. "Market Makers" or smart money usually collects or distributes their trading positions near levels where many retail traders have placed their "Stop Loss" orders. When the liquidity resulting from these losses is collected, the price often reverses direction.
A "Stop Hunt" is a move designed to neutralize liquidity generated by triggered stop losses. Banks often use significant news events to trigger stop hunts and acquire the liquidity released in the market. If, for example, they intend to execute heavy buy orders, they encourage others to sell through stop hunts.
As a result, if there is liquidity in the market before reaching the order block region, the credibility of that order block is higher. Conversely, if liquidity is near the order block, meaning the price reaches the order block before reaching the liquidity area, the credibility of that order block is lower.
🟣FVG (Fair Value Gap)
To identify the "Fair Value Gap" on the chart, one must analyze candle by candle. Focus on candles with large bodies, examining one candle and the one before it. The candles before and after this central candle should have long shadows, and their bodies should not overlap with the body of the central candle. The distance between the shadows of the first and third candles is called the FVG range.
These zone function in two ways :
•Supply and Demand zone: In this case, the price reacts to these zone, and its trend reverses.
•Liquidity zone: In this scenario, the price "fills" the zone and then reaches the order block.
Important Note: In most cases, FVG zone with very small width act as supply and demand zone, while zone with a significant width act as liquidity zone, absorbing the price.
🔵 Setting
🟣Order Block
Refine Order Block : When the option for refining order blocks is Off, the supply and demand zones encompass the entire length of the order block (from Low to High) in their standard state and remain unaltered. On the option for refining order blocks triggers the improvement of supply and demand zones using the error correction algorithm.
Refine Type : The enhancement of order blocks via the error correction algorithm can be executed through two methods: Defensive and Aggressive. In the Aggressive approach, the widest possible range is taken into account for order blocks.
Show High Levels : If major high levels are to be displayed, set the option for showing high level to Yes.
Show Low Levels : If major low levels are to be displayed, set the option for showing low level to Yes.
Show Last Support : If showing the last support is desired, set the option for showing last support to Yes.
Show Last Resistance : If showing the last resistance is desired, set the option for showing last resistance to Yes.
🟣 FVG
FVG Filter : When FVG filtering is activated, the number of FVG areas undergoes filtration based on the specified algorithm.
FVG Filter Types :
1. Very Aggressive : Apart from the initial condition, an additional condition is introduced. For an upward FVG, the maximum price of the last candle should exceed the maximum price of the middle candle. Similarly, for a downward FVG, the minimum price of the last candle should be lower than the minimum price of the middle candle. This mode eliminates a minimal number of FVGs.
2. Aggressive : In addition to the conditions of the Very Aggressive mode, this mode considers the size of the middle candle; it should not be small. Consequently, a larger number of FVGs are eliminated in this mode.
3. Defensive : Alongside the conditions of the Very Aggressive mode, this mode takes into account the size of the middle candle, which should be relatively large with the majority of it comprising the body. Furthermore, to identify upward FVGs, the second and third candles must be positive, whereas for downward FVGs, the second and third candles must be negative. This mode filters out a considerable number of FVGs, retaining only those of suitable quality.
4. Very Defensive : In addition to the conditions of the Defensive mode, the first and third candles should not be very small-bodied doji candles. This mode filters out the majority of FVGs, leaving only the highest quality ones. Show Demand FVG: Enables the display of demand-related boxes, which can be toggled between off and on. Show Supply FVG: Enables the display of supply-related boxes along the path, which can also be toggled between off and on.
🟣 Liquidity
Statics Liquidity Line Sensitivity : A value ranging from 0 to 0.4. Increasing this value reduces the sensitivity of the "Statics Liquidity Line Detection" function and increases the number of identified lines. The default value is 0.3.
Dynamics Liquidity Line Sensitivity : A value ranging from 0.4 to 1.95. Increasing this value enhances the sensitivity of the "Dynamics Liquidity Line Detection" function and decreases the number of identified lines. The default value is 1.
Statics Period Pivot : Default value is set to 8. By adjusting this value, you can specify the period for static liquidity line pivots.
Dynamics Period Pivot : Default value is set to 3. By adjusting this value, you can specify the period for dynamic liquidity line pivots.
You can activate or deactivate liquidity lines as necessary using the buttons labeled "Show Statics High Liquidity Line," "Show Statics Low Liquidity Line," "Show Dynamics High Liquidity Line," and "Show Dynamics Low Liquidity Line".
BAERMThe Bitcoin Auto-correlation Exchange Rate Model: A Novel Two Step Approach
THIS IS NOT FINANCIAL ADVICE. THIS ARTICLE IS FOR EDUCATIONAL AND ENTERTAINMENT PURPOSES ONLY.
If you enjoy this software and information, please consider contributing to my lightning address
Prelude
It has been previously established that the Bitcoin daily USD exchange rate series is extremely auto-correlated
In this article, we will utilise this fact to build a model for Bitcoin/USD exchange rate. But not a model for predicting the exchange rate, but rather a model to understand the fundamental reasons for the Bitcoin to have this exchange rate to begin with.
This is a model of sound money, scarcity and subjective value.
Introduction
Bitcoin, a decentralised peer to peer digital value exchange network, has experienced significant exchange rate fluctuations since its inception in 2009. In this article, we explore a two-step model that reasonably accurately captures both the fundamental drivers of Bitcoin’s value and the cyclical patterns of bull and bear markets. This model, whilst it can produce forecasts, is meant more of a way of understanding past exchange rate changes and understanding the fundamental values driving the ever increasing exchange rate. The forecasts from the model are to be considered inconclusive and speculative only.
Data preparation
To develop the BAERM, we used historical Bitcoin data from Coin Metrics, a leading provider of Bitcoin market data. The dataset includes daily USD exchange rates, block counts, and other relevant information. We pre-processed the data by performing the following steps:
Fixing date formats and setting the dataset’s time index
Generating cumulative sums for blocks and halving periods
Calculating daily rewards and total supply
Computing the log-transformed price
Step 1: Building the Base Model
To build the base model, we analysed data from the first two epochs (time periods between Bitcoin mining reward halvings) and regressed the logarithm of Bitcoin’s exchange rate on the mining reward and epoch. This base model captures the fundamental relationship between Bitcoin’s exchange rate, mining reward, and halving epoch.
where Yt represents the exchange rate at day t, Epochk is the kth epoch (for that t), and epsilont is the error term. The coefficients beta0, beta1, and beta2 are estimated using ordinary least squares regression.
Base Model Regression
We use ordinary least squares regression to estimate the coefficients for the betas in figure 2. In order to reduce the possibility of over-fitting and ensure there is sufficient out of sample for testing accuracy, the base model is only trained on the first two epochs. You will notice in the code we calculate the beta2 variable prior and call it “phaseplus”.
The code below shows the regression for the base model coefficients:
\# Run the regression
mask = df\ < 2 # we only want to use Epoch's 0 and 1 to estimate the coefficients for the base model
reg\_X = df.loc\ [mask, \ \].shift(1).iloc\
reg\_y = df.loc\ .iloc\
reg\_X = sm.add\_constant(reg\_X)
ols = sm.OLS(reg\_y, reg\_X).fit()
coefs = ols.params.values
print(coefs)
The result of this regression gives us the coefficients for the betas of the base model:
\
or in more human readable form: 0.029, 0.996869586, -0.00043. NB that for the auto-correlation/momentum beta, we did NOT round the significant figures at all. Since the momentum is so important in this model, we must use all available significant figures.
Fundamental Insights from the Base Model
Momentum effect: The term 0.997 Y suggests that the exchange rate of Bitcoin on a given day (Yi) is heavily influenced by the exchange rate on the previous day. This indicates a momentum effect, where the price of Bitcoin tends to follow its recent trend.
Momentum effect is a phenomenon observed in various financial markets, including stocks and other commodities. It implies that an asset’s price is more likely to continue moving in its current direction, either upwards or downwards, over the short term.
The momentum effect can be driven by several factors:
Behavioural biases: Investors may exhibit herding behaviour or be subject to cognitive biases such as confirmation bias, which could lead them to buy or sell assets based on recent trends, reinforcing the momentum.
Positive feedback loops: As more investors notice a trend and act on it, the trend may gain even more traction, leading to a self-reinforcing positive feedback loop. This can cause prices to continue moving in the same direction, further amplifying the momentum effect.
Technical analysis: Many traders use technical analysis to make investment decisions, which often involves studying historical exchange rate trends and chart patterns to predict future exchange rate movements. When a large number of traders follow similar strategies, their collective actions can create and reinforce exchange rate momentum.
Impact of halving events: In the Bitcoin network, new bitcoins are created as a reward to miners for validating transactions and adding new blocks to the blockchain. This reward is called the block reward, and it is halved approximately every four years, or every 210,000 blocks. This event is known as a halving.
The primary purpose of halving events is to control the supply of new bitcoins entering the market, ultimately leading to a capped supply of 21 million bitcoins. As the block reward decreases, the rate at which new bitcoins are created slows down, and this can have significant implications for the price of Bitcoin.
The term -0.0004*(50/(2^epochk) — (epochk+1)²) accounts for the impact of the halving events on the Bitcoin exchange rate. The model seems to suggest that the exchange rate of Bitcoin is influenced by a function of the number of halving events that have occurred.
Exponential decay and the decreasing impact of the halvings: The first part of this term, 50/(2^epochk), indicates that the impact of each subsequent halving event decays exponentially, implying that the influence of halving events on the Bitcoin exchange rate diminishes over time. This might be due to the decreasing marginal effect of each halving event on the overall Bitcoin supply as the block reward gets smaller and smaller.
This is antithetical to the wrong and popular stock to flow model, which suggests the opposite. Given the accuracy of the BAERM, this is yet another reason to question the S2F model, from a fundamental perspective.
The second part of the term, (epochk+1)², introduces a non-linear relationship between the halving events and the exchange rate. This non-linear aspect could reflect that the impact of halving events is not constant over time and may be influenced by various factors such as market dynamics, speculation, and changing market conditions.
The combination of these two terms is expressed by the graph of the model line (see figure 3), where it can be seen the step from each halving is decaying, and the step up from each halving event is given by a parabolic curve.
NB - The base model has been trained on the first two halving epochs and then seeded (i.e. the first lag point) with the oldest data available.
Constant term: The constant term 0.03 in the equation represents an inherent baseline level of growth in the Bitcoin exchange rate.
In any linear or linear-like model, the constant term, also known as the intercept or bias, represents the value of the dependent variable (in this case, the log-scaled Bitcoin USD exchange rate) when all the independent variables are set to zero.
The constant term indicates that even without considering the effects of the previous day’s exchange rate or halving events, there is a baseline growth in the exchange rate of Bitcoin. This baseline growth could be due to factors such as the network’s overall growth or increasing adoption, or changes in the market structure (more exchanges, changes to the regulatory environment, improved liquidity, more fiat on-ramps etc).
Base Model Regression Diagnostics
Below is a summary of the model generated by the OLS function
OLS Regression Results
\==============================================================================
Dep. Variable: logprice R-squared: 0.999
Model: OLS Adj. R-squared: 0.999
Method: Least Squares F-statistic: 2.041e+06
Date: Fri, 28 Apr 2023 Prob (F-statistic): 0.00
Time: 11:06:58 Log-Likelihood: 3001.6
No. Observations: 2182 AIC: -5997.
Df Residuals: 2179 BIC: -5980.
Df Model: 2
Covariance Type: nonrobust
\==============================================================================
coef std err t P>|t| \
\------------------------------------------------------------------------------
const 0.0292 0.009 3.081 0.002 0.011 0.048
logprice 0.9969 0.001 1012.724 0.000 0.995 0.999
phaseplus -0.0004 0.000 -2.239 0.025 -0.001 -5.3e-05
\==============================================================================
Omnibus: 674.771 Durbin-Watson: 1.901
Prob(Omnibus): 0.000 Jarque-Bera (JB): 24937.353
Skew: -0.765 Prob(JB): 0.00
Kurtosis: 19.491 Cond. No. 255.
\==============================================================================
Below we see some regression diagnostics along with the regression itself.
Diagnostics: We can see that the residuals are looking a little skewed and there is some heteroskedasticity within the residuals. The coefficient of determination, or r2 is very high, but that is to be expected given the momentum term. A better r2 is manually calculated by the sum square of the difference of the model to the untrained data. This can be achieved by the following code:
\# Calculate the out-of-sample R-squared
oos\_mask = df\ >= 2
oos\_actual = df.loc\
oos\_predicted = df.loc\
residuals\_oos = oos\_actual - oos\_predicted
SSR = np.sum(residuals\_oos \*\* 2)
SST = np.sum((oos\_actual - oos\_actual.mean()) \*\* 2)
R2\_oos = 1 - SSR/SST
print("Out-of-sample R-squared:", R2\_oos)
The result is: 0.84, which indicates a very close fit to the out of sample data for the base model, which goes some way to proving our fundamental assumption around subjective value and sound money to be accurate.
Step 2: Adding the Damping Function
Next, we incorporated a damping function to capture the cyclical nature of bull and bear markets. The optimal parameters for the damping function were determined by regressing on the residuals from the base model. The damping function enhances the model’s ability to identify and predict bull and bear cycles in the Bitcoin market. The addition of the damping function to the base model is expressed as the full model equation.
This brings me to the question — why? Why add the damping function to the base model, which is arguably already performing extremely well out of sample and providing valuable insights into the exchange rate movements of Bitcoin.
Fundamental reasoning behind the addition of a damping function:
Subjective Theory of Value: The cyclical component of the damping function, represented by the cosine function, can be thought of as capturing the periodic fluctuations in market sentiment. These fluctuations may arise from various factors, such as changes in investor risk appetite, macroeconomic conditions, or technological advancements. Mathematically, the cyclical component represents the frequency of these fluctuations, while the phase shift (α and β) allows for adjustments in the alignment of these cycles with historical data. This flexibility enables the damping function to account for the heterogeneity in market participants’ preferences and expectations, which is a key aspect of the subjective theory of value.
Time Preference and Market Cycles: The exponential decay component of the damping function, represented by the term e^(-0.0004t), can be linked to the concept of time preference and its impact on market dynamics. In financial markets, the discounting of future cash flows is a common practice, reflecting the time value of money and the inherent uncertainty of future events. The exponential decay in the damping function serves a similar purpose, diminishing the influence of past market cycles as time progresses. This decay term introduces a time-dependent weight to the cyclical component, capturing the dynamic nature of the Bitcoin market and the changing relevance of past events.
Interactions between Cyclical and Exponential Decay Components: The interplay between the cyclical and exponential decay components in the damping function captures the complex dynamics of the Bitcoin market. The damping function effectively models the attenuation of past cycles while also accounting for their periodic nature. This allows the model to adapt to changing market conditions and to provide accurate predictions even in the face of significant volatility or structural shifts.
Now we have the fundamental reasoning for the addition of the function, we can explore the actual implementation and look to other analogies for guidance —
Financial and physical analogies to the damping function:
Mathematical Aspects: The exponential decay component, e^(-0.0004t), attenuates the amplitude of the cyclical component over time. This attenuation factor is crucial in modelling the diminishing influence of past market cycles. The cyclical component, represented by the cosine function, accounts for the periodic nature of market cycles, with α determining the frequency of these cycles and β representing the phase shift. The constant term (+3) ensures that the function remains positive, which is important for practical applications, as the damping function is added to the rest of the model to obtain the final predictions.
Analogies to Existing Damping Functions: The damping function in the BAERM is similar to damped harmonic oscillators found in physics. In a damped harmonic oscillator, an object in motion experiences a restoring force proportional to its displacement from equilibrium and a damping force proportional to its velocity. The equation of motion for a damped harmonic oscillator is:
x’’(t) + 2γx’(t) + ω₀²x(t) = 0
where x(t) is the displacement, ω₀ is the natural frequency, and γ is the damping coefficient. The damping function in the BAERM shares similarities with the solution to this equation, which is typically a product of an exponential decay term and a sinusoidal term. The exponential decay term in the BAERM captures the attenuation of past market cycles, while the cosine term represents the periodic nature of these cycles.
Comparisons with Financial Models: In finance, damped oscillatory models have been applied to model interest rates, stock prices, and exchange rates. The famous Black-Scholes option pricing model, for instance, assumes that stock prices follow a geometric Brownian motion, which can exhibit oscillatory behavior under certain conditions. In fixed income markets, the Cox-Ingersoll-Ross (CIR) model for interest rates also incorporates mean reversion and stochastic volatility, leading to damped oscillatory dynamics.
By drawing on these analogies, we can better understand the technical aspects of the damping function in the BAERM and appreciate its effectiveness in modelling the complex dynamics of the Bitcoin market. The damping function captures both the periodic nature of market cycles and the attenuation of past events’ influence.
Conclusion
In this article, we explored the Bitcoin Auto-correlation Exchange Rate Model (BAERM), a novel 2-step linear regression model for understanding the Bitcoin USD exchange rate. We discussed the model’s components, their interpretations, and the fundamental insights they provide about Bitcoin exchange rate dynamics.
The BAERM’s ability to capture the fundamental properties of Bitcoin is particularly interesting. The framework underlying the model emphasises the importance of individuals’ subjective valuations and preferences in determining prices. The momentum term, which accounts for auto-correlation, is a testament to this idea, as it shows that historical price trends influence market participants’ expectations and valuations. This observation is consistent with the notion that the price of Bitcoin is determined by individuals’ preferences based on past information.
Furthermore, the BAERM incorporates the impact of Bitcoin’s supply dynamics on its price through the halving epoch terms. By acknowledging the significance of supply-side factors, the model reflects the principles of sound money. A limited supply of money, such as that of Bitcoin, maintains its value and purchasing power over time. The halving events, which reduce the block reward, play a crucial role in making Bitcoin increasingly scarce, thus reinforcing its attractiveness as a store of value and a medium of exchange.
The constant term in the model serves as the baseline for the model’s predictions and can be interpreted as an inherent value attributed to Bitcoin. This value emphasizes the significance of the underlying technology, network effects, and Bitcoin’s role as a medium of exchange, store of value, and unit of account. These aspects are all essential for a sound form of money, and the model’s ability to account for them further showcases its strength in capturing the fundamental properties of Bitcoin.
The BAERM offers a potential robust and well-founded methodology for understanding the Bitcoin USD exchange rate, taking into account the key factors that drive it from both supply and demand perspectives.
In conclusion, the Bitcoin Auto-correlation Exchange Rate Model provides a comprehensive fundamentally grounded and hopefully useful framework for understanding the Bitcoin USD exchange rate.
