ass/dess dr ramy (8 Results)📌 Script Description for "ass/dess dr ramy (8 Results)"
This "ass/dess dr ramy (8 Results)" indicator in TradingView is designed to visualize different mathematical results based on the square root of a customizable number. The script takes an input value, calculates the square root, and then performs various arithmetic operations to generate multiple results. These results are plotted as horizontal lines on the chart to provide visual reference points.
🔍 Features
Custom Number Input
Users can input a custom number (e.g., 4.7 by default), and the script will compute the square root of this number.
Mathematical Calculations
After calculating the square root of the input number, the script performs the following operations:
Adding and subtracting different values (from 0.25 to 2).
Squaring the results of each of these operations.
Plotting Horizontal Lines
The computed results are then plotted as horizontal lines at different levels on the chart.
Different colors are used for each result to make them visually distinguishable:
Blue for ±2 results.
Green for ±1 results.
Red for ±0.25 results.
Orange for ±0.75 results.
Purple for ±1.25 results.
Yellow for ±0.5 results.
Fuchsia for ±1.5 results.
Teal for ±1.75 results.
⚙️ Parameters
Custom Number Input: Users can enter a custom number, which is used in the square root calculation.
The results are dynamically updated based on this custom number.
📝 Example Use Case
This script can be useful for traders who want to observe potential price levels or areas of support and resistance based on mathematical calculations that are derived from a single input.
The multiple levels plotted can act as dynamic reference points, which may assist in making technical analysis decisions.
Cicli
cycle144 dr ramy After Given Date📌 Description for Script Publishing
Cycle144 dr ramy After Given Date is a visual tool that highlights time-based cycles on the chart by marking specific candles that occur after a user-defined starting point.
🔹 How It Works:
You choose a specific date and time.
The script automatically identifies and labels the 18th, 36th, 54th, 72nd, 90th, 108th, 126th, and 144th candles after your selected date.
At each of those candles, the script:
Places a label (e.g., "18th Candle", "36th Candle", etc.).
Draws horizontal lines from the candle's high and low, extended to the right.
🔹 Purpose:
This indicator helps traders observe and analyze market behavior at regular cycle intervals after a significant date. It's useful for cycle-based strategies, time symmetry analysis, or just to visualize how price reacts at recurring time steps.
🛠️ No signals or strategies are included — this is a charting utility only.
Solar Cycle (SOLAR)SOLAR: SOLAR CYCLE
🔍 OVERVIEW AND PURPOSE
The Solar Cycle indicator is an astronomical calculator that provides precise values representing the seasonal position of the Sun throughout the year. This indicator maps the Sun's position in the ecliptic to a normalized value ranging from -1.0 (winter solstice) through 0.0 (equinoxes) to +1.0 (summer solstice), creating a continuous cycle that represents the seasonal progression throughout the year.
The implementation uses high-precision astronomical formulas that include orbital elements and perturbation terms to accurately calculate the Sun's position. By converting chart timestamps to Julian dates and applying standard astronomical algorithms, this indicator achieves significantly greater accuracy than simplified seasonal approximations. This makes it valuable for traders exploring seasonal patterns, agricultural commodities trading, and natural cycle-based trading strategies.
🧩 CORE CONCEPTS
Seasonal cycle integration: Maps the annual solar cycle (365.242 days) to a continuous wave
Continuous phase representation: Provides a normalized -1.0 to +1.0 value
Astronomical precision: Uses perturbation terms and high-precision constants for accurate solar position
Key points detection: Identifies solstices (±1.0) and equinoxes (0.0) automatically
The Solar Cycle indicator differs from traditional seasonal analysis tools by incorporating precise astronomical calculations rather than using simple calendar-based approximations. This approach allows traders to identify exact seasonal turning points and transitions with high accuracy.
⚙️ COMMON SETTINGS AND PARAMETERS
Pro Tip: While the indicator itself doesn't have adjustable parameters, it's most effective when used on higher timeframes (daily or weekly charts) to visualize seasonal patterns. Consider combining it with commodity price data to analyze seasonal correlations.
🧮 CALCULATION AND MATHEMATICAL FOUNDATION
Simplified explanation:
The Solar Cycle indicator calculates the Sun's ecliptic longitude and transforms it into a sine wave that peaks at the summer solstice and troughs at the winter solstice, with equinoxes at the zero crossings.
Technical formula:
Convert chart timestamp to Julian Date:
JD = (time / 86400000.0) + 2440587.5
Calculate Time T in Julian centuries since J2000.0:
T = (JD - 2451545.0) / 36525.0
Calculate the Sun's mean longitude (L0) and mean anomaly (M), including perturbation terms:
L0 = (280.46646 + 36000.76983T + 0.0003032T²) % 360
M = (357.52911 + 35999.05029T - 0.0001537T² - 0.00000025T³) % 360
Calculate the equation of center (C):
C = (1.914602 - 0.004817T - 0.000014*T²)sin(M) +
(0.019993 - 0.000101T)sin(2M) +
0.000289sin(3M)
Calculate the Sun's true longitude and convert to seasonal value:
λ = L0 + C
seasonal = sin(λ)
🔍 Technical Note: The implementation includes terms for the equation of center to account for the Earth's elliptical orbit. This provides more accurate timing of solstices and equinoxes compared to simple harmonic approximations.
📈 INTERPRETATION DETAILS
The Solar Cycle indicator provides several analytical perspectives:
Summer Solstice (+1.0): Maximum solar elevation, longest day
Winter Solstice (-1.0): Minimum solar elevation, shortest day
Vernal Equinox (0.0 crossing up): Day and night equal length, spring begins
Autumnal Equinox (0.0 crossing down): Day and night equal length, autumn begins
Transition rates: Steepest near equinoxes, flattest near solstices
Cycle alignment: Market cycles that align with seasonal patterns may show stronger trends
Confirmation points: Solstices and equinoxes often mark important seasonal turning points
⚠️ LIMITATIONS AND CONSIDERATIONS
Geographic relevance: Solar cycle timing is most relevant for temperate latitudes
Market specificity: Seasonal effects vary significantly across different markets
Timeframe compatibility: Most effective for longer-term analysis (weekly/monthly)
Complementary tool: Should be used alongside price action and other indicators
Lead/lag effects: Market reactions to seasonal changes may precede or follow astronomical events
Statistical significance: Seasonal patterns should be verified across multiple years
Global markets: Consider opposite seasonality in Southern Hemisphere markets
📚 REFERENCES
Meeus, J. (1998). Astronomical Algorithms (2nd ed.). Willmann-Bell.
Hirshleifer, D., & Shumway, T. (2003). Good day sunshine: Stock returns and the weather. Journal of Finance, 58(3), 1009-1032.
Hong, H., & Yu, J. (2009). Gone fishin': Seasonality in trading activity and asset prices. Journal of Financial Markets, 12(4), 672-702.
Bouman, S., & Jacobsen, B. (2002). The Halloween indicator, 'Sell in May and go away': Another puzzle. American Economic Review, 92(5), 1618-1635.
MVRV | Lyro RS📊 MVRV | Lyro RS is a powerful on-chain valuation tool designed to assess the relative market positioning of Bitcoin (BTC) or Ethereum (ETH) based on the Market Value to Realized Value (MVRV) ratio. It highlights potential undervaluation or overvaluation zones, helping traders and investors anticipate cyclical tops and bottoms.
✨ Key Features :
🔁 Dual Asset Support: Analyze either BTC or ETH with a single toggle.
📐 Dynamic MVRV Thresholds: Automatically calculates median-based bands at 50%, 64%, 125%, and 170%.
📊 Median Calculation: Period-based median MVRV for long-term trend context.
💡 Optional Smoothing: Use SMA to smooth MVRV for cleaner analysis.
🎯 Visual Threshold Alerts: Background and bar colors change based on MVRV position relative to thresholds.
⚠️ Built-in Alerts: Get notified when MVRV enters under- or overvalued territory.
📈 How It Works :
💰 MVRV Calculation: Uses data from IntoTheBlock and CoinMetrics to obtain real-time MVRV values.
🧠 Threshold Bands: Median MVRV is used as a baseline. Ratios like 50%, 64%, 125%, and 170% signal various levels of market extremes.
🎨 Visual Zones: Green zones for undervaluation and red zones for overvaluation, providing intuitive visual cues.
🛠️ Custom Highlights: Toggle individual threshold zones on/off for a cleaner view.
⚙️ Customization Options :
🔄 Switch between BTC or ETH for analysis.
📏 Adjust period length for median MVRV calculation.
🔧 Enable/disable threshold visibility (50%, 64%, 125%, 170%).
📉 Toggle smoothing to reduce noise in volatile markets.
📌 Use Cases :
🟢 Identify undervalued zones for long-term entry opportunities.
🔴 Spot potential overvaluation zones that may precede corrections.
🧭 Use in confluence with price action or macro indicators for better timing.
⚠️ Disclaimer :
This indicator is for educational purposes only. It should not be used in isolation for making trading or investment decisions. Always combine with price action, fundamentals, and proper risk management.
Bitcoin Power Law OscillatorThis is the oscillator version of the script. The main body of the script can be found here.
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift. This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula: log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support at point B(Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point D, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
Smoothed ROC Z-Score with TableSmoothed ROC Z-Score with Table
This indicator calculates the Rate of Change (ROC) of a chosen price source and transforms it into a smoothed Z-Score oscillator, allowing you to identify market cycle tops and bottoms with reduced noise.
How it works:
The ROC is calculated over a user-defined length.
A moving average and standard deviation over a separate window are used to standardize the ROC into a Z-Score.
This Z-Score is further smoothed using an exponential moving average (EMA) to filter noise and highlight clearer cycle signals.
The smoothed Z-Score oscillates around zero, with upper and lower bands defined by user inputs (default ±2 standard deviations).
When the Z-Score reaches or exceeds ±3 (customizable), the value shown in the table is clamped at ±2 for clearer interpretation.
The indicator plots the smoothed Z-Score line with zero and band lines, and displays a colored Z-Score table on the right for quick reference.
How to read it:
Values near zero indicate neutral momentum.
Rising Z-Scores towards the upper band suggest increasing positive momentum, possible market tops or strength.
Falling Z-Scores towards the lower band indicate negative momentum, potential bottoms or weakness.
The color-coded table gives an easy visual cue: red/orange for strong positive signals, green/teal for strong negative signals, and gray for neutral zones.
Use cases:
Identify turning points in trending markets.
Filter noisy ROC data for cleaner signals.
Combine with other indicators to time entries and exits more effectively.
S&P 500 Estimated PE (Sampled Every 4)📊 **S&P 500 Estimated PE Ratio (from CSV)**
This indicator visualizes the forward-looking estimated PE ratio of the S&P 500 index, imported from external CSV data.
🔹 **Features:**
- Real historical daily data from 2008 onward
- Automatically aligns PE values to closest available trading date
- Useful for macro valuation trends and long-term entry signals
📌 **Best for:**
- Investors interested in forward-looking valuation
- Analysts tracking over/undervaluation trends
- Long-term timing overlay on price action
Category: `Breadth indicators`, `Cycles`
Gold ValuationGold Value Index
The Gold Value Index (GVI) is a macro-driven oscillator that estimates the relative value of gold based on real-time movements in the US Dollar Index (DXY) and the 10-Year US Treasury Yield (US10Y). It helps traders contextualize gold’s price within broader macroeconomic pressure — identifying when gold may be over- or undervalued relative to these key drivers.
How It Works – Macro Inputs:
DXY (US Dollar Index): Typically moves inversely to gold. A rising dollar suggests downward pressure on gold value.
US10Y Yield: Higher yields increase the opportunity cost of holding gold, often leading to weaker gold prices.
Both inputs are Z-score normalized and inverted to reflect their typical negative correlation with gold. When combined, they form a single, scaled index from 0 (undervalued) to 100 (overvalued).
Why Use This Tool?
Gold reacts to macro forces as much as technical ones. The GVI blends these inputs into a clear, visual gauge to:
Anticipate mean-reversion setups.
Avoid emotionally-driven trades in extreme macro conditions.
Enhance timing by understanding gold's macro context.
Important Notes:
Data sources include ICEUS:DXY and TVC:US10Y via TradingView.
Code is protected — this is a private, invite-only script.
Simplified STH-MVRV + Z-ScoreSimplified Short Term Holder MVRV (STH-MVRV) + Z-Score Indicator
Description:
This indicator visualizes the Short Term Holder Market Value to Realized Value ratio (STH-MVRV) and its normalized Z-Score, providing insight into Bitcoin’s market cycle phases and potential overbought or oversold conditions.
How it works:
The STH-MVRV ratio compares the market value of coins held by short-term holders to their realized value, helping to identify periods of profit-taking or accumulation by these holders.
The indicator calculates three versions:
STH-MVRV (MVRV): Ratio of current MVRV to its 155-day SMA.
STH-MVRV (Price): Ratio of BTC price to its 155-day SMA.
STH-MVRV (AVG): Average of the above two ratios.
You can select which ratio to display via the input dropdown.
Threshold Lines:
Adjustable upper and lower threshold lines mark significant levels where market sentiment might shift.
The indicator also plots a baseline at 1.0 as a reference.
Z-Score Explanation:
The Z-Score is a normalized value scaled between -3 and +3, calculated relative to the chosen threshold levels.
When the ratio hits the upper threshold, the Z-Score approaches +2, indicating potential overbought conditions.
Conversely, reaching the lower threshold corresponds to a Z-Score near -2, signaling potential oversold conditions.
This Z-Score is shown in a clear table in the top right corner of the chart for easy monitoring.
Data Sources:
MVRV data is fetched from the BTC_MVRV dataset.
Price data is sourced from the BTC/USD index.
Usage:
Use this indicator to assess short-term holder market behavior and to help identify buying or selling opportunities based on extremes indicated by the Z-Score.
Combining this tool with other analysis can improve timing decisions in Bitcoin trading.
Simplified Hashrate Oscillator + Z-ScoreIndicator Description for TradingView
Simplified Hashrate Oscillator + Z-Score (SHO + Z)
This indicator analyzes the Bitcoin network's mining hashrate data by comparing short-term and long-term moving averages of the hashrate to create an oscillator that reflects changes in mining activity.
How it works:
The indicator calculates two Simple Moving Averages (SMAs) of the Bitcoin network hashrate — a short-term SMA (default 21 days) and a long-term SMA (default 105 days).
The difference between these two averages is normalized and expressed as a percentage, forming the Hashrate Oscillator line.
Two user-defined threshold lines (default ±7%) are plotted as upper and lower reference levels on the oscillator.
When the oscillator approaches these levels, it indicates potential extremes in mining activity.
Z-Score Explanation:
The Z-Score is a normalized measure that translates the oscillator's current value into a standardized scale roughly ranging from -2 to +2.
It shows how far the current hashrate oscillator value deviates from the user-defined thresholds.
A Z-Score near +2 means the oscillator is close to or above the upper threshold (possible overbought conditions).
A Z-Score near -2 means the oscillator is near or below the lower threshold (possible oversold conditions).
This helps users assess the relative strength or weakness of the mining hashrate movement in a normalized context.
Data Source:
The hashrate data is sourced daily from the Bitcoin network hashrate dataset provided by Quandl (QUANDL:BCHAIN/HRATE), a reliable blockchain data provider.
The indicator requests daily hashrate values and calculates SMAs accordingly.
How to use:
Watch the Hashrate Oscillator line for movements towards or beyond the threshold lines as signals of miner capitulation or recovery phases.
Use the Z-Score displayed in the table to quickly gauge how extreme the current reading is relative to set thresholds.
Adjust the short and long SMA periods and threshold lines to suit your preferred sensitivity and trading timeframe.
SP 500 PE Ratio (Loose Date Match)📈 **S&P 500 PE Ratio (from Excel Data)**
This custom indicator visualizes the historical S&P 500 Price-to-Earnings (PE) Ratio loaded from Excel. Each data point represents a snapshot of the market valuation at a specific time, typically on an annual or quarterly basis.
🔹 **What it does:**
- Plots the PE ratio values on the chart aligned with historical dates
- Uses stepwise or linear rendering to account for missing trading days
- Helps identify valuation cycles and extremes (e.g., overvalued vs undervalued)
🔍 **Use case:**
- Long-term market analysis
- Compare PE trends with price performance
- Spot long-term entry/exit zones based on valuation
🛠️ Future plans:
- Add value zone highlighting (e.g., PE > 30 = red, PE < 15 = green)
- Support for dynamic datasets (via Google Sheets or Notion)
Category: `Breadth indicators`, `Cycles`
💡 Source: Manually imported data (can be replaced with any custom macro data series)
TASC 2025.06 Cybernetic Oscillator█ OVERVIEW
This script implements the Cybernetic Oscillator introduced by John F. Ehlers in his article "The Cybernetic Oscillator For More Flexibility, Making A Better Oscillator" from the June 2025 edition of the TASC Traders' Tips . It cascades two-pole highpass and lowpass filters, then scales the result by its root mean square (RMS) to create a flexible normalized oscillator that responds to a customizable frequency range for different trading styles.
█ CONCEPTS
Oscillators are indicators widely used by technical traders. These indicators swing above and below a center value, emphasizing cyclic movements within a frequency range. In his article, Ehlers explains that all oscillators share a common characteristic: their calculations involve computing differences . The reliance on differences is what causes these indicators to oscillate about a central point.
The difference between two data points in a series acts as a highpass filter — it allows high frequencies (short wavelengths) to pass through while significantly attenuating low frequencies (long wavelengths). Ehlers demonstrates that a simple difference calculation attenuates lower-frequency cycles at a rate of 6 dB per octave. However, the difference also significantly amplifies cycles near the shortest observable wavelength, making the result appear noisier than the original series. To mitigate the effects of noise in a differenced series, oscillators typically smooth the series with a lowpass filter, such as a moving average.
Ehlers highlights an underlying issue with smoothing differenced data to create oscillators. He postulates that market data statistically follows a pink spectrum , where the amplitudes of cyclic components in the data are approximately directly proportional to the underlying periods. Specifically, he suggests that cyclic amplitude increases by 6 dB per octave of wavelength.
Because some conventional oscillators, such as RSI, use differencing calculations that attenuate cycles by only 6 dB per octave, and market cycles increase in amplitude by 6 dB per octave, such calculations do not have a tangible net effect on larger wavelengths in the analyzed data. The influence of larger wavelengths can be especially problematic when using these oscillators for mean reversion or swing signals. For instance, an expected reversion to the mean might be erroneous because oscillator's mean might significantly deviate from its center over time.
To address the issues with conventional oscillator responses, Ehlers created a new indicator dubbed the Cybernetic Oscillator. It uses a simple combination of highpass and lowpass filters to emphasize a specific range of frequencies in the market data, then normalizes the result based on RMS. The process is as follows:
Apply a two-pole highpass filter to the data. This filter's critical period defines the longest wavelength in the oscillator's passband.
Apply a two-pole SuperSmoother (lowpass filter) to the highpass-filtered data. This filter's critical period defines the shortest wavelength in the passband.
Scale the resulting waveform by its RMS. If the filtered waveform follows a normal distribution, the scaled result represents amplitude in standard deviations.
The oscillator's two-pole filters attenuate cycles outside the desired frequency range by 12 dB per octave. This rate outweighs the apparent rate of amplitude increase for successively longer market cycles (6 dB per octave). Therefore, the Cybernetic Oscillator provides a more robust isolation of cyclic content than conventional oscillators. Best of all, traders can set the periods of the highpass and lowpass filters separately, enabling fine-tuning of the frequency range for different trading styles.
█ USAGE
The "Highpass period" input in the "Settings/Inputs" tab specifies the longest wavelength in the oscillator's passband, and the "Lowpass period" input defines the shortest wavelength. The oscillator becomes more responsive to rapid movements with a smaller lowpass period. Conversely, it becomes more sensitive to trends with a larger highpass period. Ehlers recommends setting the smallest period to a value above 8 to avoid aliasing. The highpass period must not be smaller than the lowpass period. Otherwise, it causes a runtime error.
The "RMS length" input determines the number of bars in the RMS calculation that the indicator uses to normalize the filtered result.
This indicator also features two distinct display styles, which users can toggle with the "Display style" input. With the "Trend" style enabled, the indicator plots the oscillator with one of two colors based on whether its value is above or below zero. With the "Threshold" style enabled, it plots the oscillator as a gray line and highlights overbought and oversold areas based on the user-specified threshold.
Below, we show two instances of the script with different settings on an equities chart. The first uses the "Threshold" style with default settings to pass cycles between 20 and 30 bars for mean reversion signals. The second uses a larger highpass period of 250 bars and the "Trend" style to visualize trends based on cycles spanning less than one year:
Yield Curve Approximation
A yield curve is a graph that plots the yields (interest rates) of bonds with the same credit quality but different maturity dates. It helps investors understand the relationship between short-term and long-term interest rates.
🔹 Types of Yield Curves
1️⃣ Normal Yield Curve – Upward-sloping, indicating economic expansion.
2️⃣ Inverted Yield Curve – Downward-sloping, often a recession warning.
3️⃣ Flat Yield Curve – Suggests economic uncertainty or transition.
The yield curve is widely used to predict economic conditions and interest rate movements. You can learn more about it here. Would you like insights on how traders use the yield curve for investment decisions?
How to Trade Using This?
✅ If the yield curve is steepening (green) → Favor growth stocks, commodities, and high-risk assets.
✅ If the yield curve is flattening or inverting (red) → Consider bonds, defensive sectors, or hedging strategies.
✅ Pair with economic news and interest rate decisions to refine predictions.
Asia Session Range @mrxautrades🗺️ Asia Session Range by @mrxautrades
🚨 This script is closed-source because it implements a custom logic for session range visualization, deviation projections, and adaptive display based on chart timeframe. No other public script offers this exact functionality.
✅ What does this script do?
This indicator highlights the Asian session range and calculates dynamic extensions during the New York session open. It's designed for traders who rely on price action around key market sessions.
🔧 Unique Features (compared to existing scripts):
Timeframe-aware visibility: The script includes conditional logic to show or hide elements based on the chart timeframe (e.g., only visible on 60-minute or lower charts).
Automatic deviation levels: Calculates and plots extensions above/below the Asian range based on its size, offering projected support/resistance levels in real time.
Adaptive labels: Labels adjust dynamically to chart styling, with options for background, color, and visibility control.
⚙️ Customizable Inputs:
Asian and New York session times
Box, line, and label colors
Number and spacing of deviation levels
Line extension duration (in hours)
Label style: plain text or with background
🧠 Best suited for:
Breakout strategies based on the Asian session range
Using prior session levels as support/resistance
Intraday traders in Forex, indices, or crypto markets
Benner Cycles📜 Overview
The Benner Cycles indicator is a visually intuitive overlay that maps out one of the most historically referenced market timing models—Samuel T. Benner’s Cycles—directly onto your chart. This tool highlights three distinct types of market years: Panic, Peak, and Buy years, based on the rhythmic patterns first published by Benner in the late 19th century.
Benner's work is legendary among financial historians and cycle theorists. His original charts, dating back to the 1800s, remarkably anticipated economic booms, busts, and recoveries by following repeating year intervals. This modern adaptation brings that ancient rhythm into your TradingView workspace.
🔍 Background
Samuel T. Benner (1832–1913) was an Ohioan ironworks businessman and farmer who, after losing everything in the Panic of 1873, sought to uncover the secrets of economic cycles. His work led to the famous Benner's Cycle Chart, which forecasts business activity using repeatable intervals of panic, prosperity, and opportunity.
Benner’s method was based on a combination of numerological, agricultural, and empirical observations—not unlike early forms of technical and cyclical analysis. His legacy survives through a set of three rotating intervals for each market condition.
George Tritch was the individual responsible for preserving and publishing Samuel T. Benner’s economic cycle charts after Benner's death. While Benner was the original creator of the Benner Cycle, Tritch is known for reproducing and circulating the Benner chart in the early 20th century, helping it gain broader recognition among traders, economists, and financial historians.
🛠️ Features
Overlay Background Highlights shades the chart background to reflect the current year's cycle type
Configurable Year Range defines your own historical scope using Start Year and End Year
Fully Customizable Colors & Opacity
Live Statistics Table (optional) displays next projected Panic, Peak, and Buy years as well as current year’s market phase
Cycle Phase Logic (optional) prioritizes highlighting in order of Panic > Peak > Buy if overlaps occur
📈 Use Cases
Macro Timing Tool – Use the cycle phases to align with broader economic rhythms (especially useful for long-term investors or cycle traders).
Market Sentiment Guide – Panic years may coincide with recessions or major selloffs; Buy years may signal deep value or accumulation opportunities.
Overlay for Historical Studies – Perfect for comparing past major market movements (e.g., 1837, 1929, 2008) with their corresponding cycle phase. See known limitations below.
Forecasting Reference – Identify where we are in the repeating Benner rhythm and prepare for what's likely ahead.
⚠️ Limitations
❗ Not Predictive in Isolation: Use in conjunction with other tools.
❗ Calendar-Based Only: This indicator is strictly time-based and does not factor in price action, volume, or volatility.
❗ Historical Artifact, Not a Guarantee
❗ Data Availability: This indicator's historical output is constrained by the available price history of the underlying ticker. Therefore, it cannot display cycles prior to the earliest candle on the chart.
IB Range & Volume CalculatorIB Range & Volume Calculator - Summary
Overview
This indicator tracks and analyzes the Initial Balance (IB) period (first 30 minutes of trading from 8:30-9:00 AM Chicago time) by measuring both price range and trading volume. It compares today's values against a 30-day average, providing essential context for day traders and scalpers.
Key Features
Range Analysis
Automatically calculates high-low range during the Initial Balance period
Compares today's range with the 30-day historical average
Shows percentage difference from average with color coding (green for above average, red for below)
Volume Analysis
Tracks cumulative volume during the Initial Balance period
Calculates and displays 30-day volume average
Compares today's volume to the average with percentage difference
Visual Elements
Highlights all IB period candles with light blue background
Displays a fixed information panel in the upper right corner
Shows real-time status during the IB period ("In progress...")
Updates with final values once the IB period completes
Data Management
Maintains a rolling 30-day history of both range and volume data
Displays data collection progress (x/30 days)
Automatically resets calculations at the beginning of each new session
Trading Applications
This indicator is particularly valuable for:
Context-Based Trading Decisions
Compare today's market behavior to normal conditions
Adjust scalping targets based on relative volatility
Volume-Price Relationship Analysis
Identify unusual volume patterns that may precede significant moves
Validate price movements with corresponding volume confirmation
Trading Strategy Selection
High volume + high range: Momentum strategy opportunities
High volume + low range: Potential breakout setup
Low volume + high range: Possible fade/reversal opportunities
Low volume + low range: Range-bound scalping environment
5-Point Scalp Targeting
Determine if 5-point targets are aggressive or conservative for the day
Adapt stop levels based on relative volatility
Timing Optimization
Identify days with abnormal opening characteristics
Anticipate potential afternoon behavior based on IB patterns
The indicator provides essential context for rapid decision-making in fast-moving markets, helping traders calibrate their expectations and adapt their strategies to current market conditions.
Extended-hours Volume vs AVOL// ──────────────────────────────────────────────────────────────────────────────
// Extended-Hours Volume vs AVOL • HOW IT WORKS & HOW TO TRADE IT
// ──────────────────────────────────────────────────────────────────────────────
//
// ░ What this indicator is
// ------------------------
// • It accumulates PRE-MARKET (04:00-09:30 ET) and AFTER-HOURS (16:00-20:00 ET)
// volume on intraday charts and compares that running total with the stock’s
// 21-day average daily volume (“AVOL” by default).
// • Three live read-outs are shown in the data-window/table:
//
// AH – volume traded since the 16:00 ET close
// PM – volume traded before the 09:30 ET open
// Ext – AH + PM (updates in pre-market only)
// %AVOL – Ext ÷ AVOL × 100 (updates in pre-market)
//
// • It is intended for U.S. equities but the session strings can be edited for
// other markets.
//
// ░ Why it matters
// ----------------
// Big extended-hours volume almost always precedes outsized intraday range.
// By quantifying that volume as a % of “normal” trade (AVOL), you can filter
// which gappers and news names deserve focus *before* the bell rings.
//
// ░ Quick-start trade plan (educational template – tune to taste)
// ----------------------------------------------------------------
// 1. **Scan** the watch-list between 08:30-09:25 ET.
// ► Keep charts on 1- or 5-minute candles with “Extended Hours” ✔ checked.
// 2. **Filter** by `Ext` or `%AVOL`:
// – Skip if < 10 % → very low interest
// – Flag if 20-50 % → strong interest, Tier-1 candidate
// – Laser-focus if > 50 % → crowd favourite; expect liquidity & range
// 3. **Opening Range Breakout (long example)**
// • Preconditions: Ext ≥ 20 % & price above yesterday’s close.
// • Let the first 1- or 5-min bar complete after 09:30.
// • Stop-buy 1 tick above that bar (or pre-market high – whichever higher).
// • Initial stop below that bar low (or pre-market low).
// • First target = 1R or next HTF resistance.
// 4. **Red-to-Green reversal (gap-down long)**
// • Ext ≥ 30 % but pre-market gap is negative.
// • Enter as price reclaims yesterday’s close on live volume.
// • Stop under reclaim bar; scale out into VWAP / first liquidity pocket.
// 5. **Risk** – size so the full stop is ≤ 1 R of account. Volume fade or
// loss of %AVOL slope is a reason to tighten or exit early.
//
// ░ Tips
// ------
// • AVOL look-back can be changed in the input panel (21 days ⇒ ~1 month).
// • To monitor several symbols, open a multi-chart layout and sort your
// watch-list by %AVOL descending – leaders float to the top automatically.
// • Replace colour constants with hex if the namespace ever gets shadowed.
//
// ░ Disclaimer
// ------------
// For educational purposes only. Not financial advice. Trade your own plan.
//
// ──────────────────────────────────────────────────────────────────────────────
RSI Phan Ky FullThe RSI divergence indicator is like a magnifying glass that spots gaps between price swings and momentum. When price keeps climbing but RSI quietly sags, it’s a flashing U‑turn sign: the bulls are winded, and the bears are lacing up their boots. Flip it around—price is sliding yet RSI edges higher—and you’ve got bulls secretly stockpiling. Hidden divergences shore up the trend; regular divergences hint at a pivot. Blend those signals with overbought/oversold zones, support‑resistance, and volume, and RSI divergence turns into a radar that helps traders jump in with swagger and bail out just in time.
The Ultimate Buy and Sell Indicator: Unholy Grail Edition"You see, Watson, the market is not random—it simply whispers in a code too complex for the average trader. Lucky for you, I am not average."
They searched for the Holy Grail of trading for decades—promises, false prophets, and overpriced PDFs.
But they were all looking in the wrong place.
This isn’t a relic buried in the desert.
This is the Unholy Grail — a machine-forged fusion of logic, engineering, and tactical overkill .
Built by Sherlock Macgyver , this is not a mystical object. It’s a surveillance system for trend detection, signal validation, and precision entries .
⚠️ Important: This script draws its own candles.
To see it properly, disable regular candles by turning off "Body", "Wick" and "Border" colors.
🔧 What You’re Looking At
This overlay plots confirmed Buy/Sell signals , momentum-based “watch” zones , adaptive candle coloring , SuperTrend bias detection , dual Bollinger Bands , and a moving average ribbon .
It’s not “minimalist” —it’s comprehensive .
📍 Configuring the Tool: Follow the Breadcrumbs
Every setting includes a tooltip — read them . They're not filler. They explain exactly how each feature functions so you can dial this thing in like you're tuning a surveillance rig in a Cold War bunker .
If you skip them, you're walking blind in a minefield .
🕰️ Timeframes: The Signal Sweet Spot
Each asset has a tempo . You need to find the one where signals align with clarity —not chaos .
Start with 4H or 1H —work up or down from there.
Too many fakeouts? → Higher timeframe
Too slow? → Drop to 15m or 5m —but expect more noise and adjust settings accordingly.
The signals scale with time, but you must find the rhythm that best fits your asset—and your trading lifestyle .
♻️ RSI Cycle = Signal Sensitivity
This is the heart of the system . It controls how reactive the RSI engine is.
Adjust based on noise level and how often you can actually monitor your charts.
Short cycle (14–24): More signals, more speed, more noise
Longer cycle (36–64): Smoother entries, better for swing traders
Tip: If your signals feel too jittery, increase the cycle. If they lag too much, reduce it.
📉 SuperTrend: Your Trend Bias Compass
This isn’t your average SuperTrend. It adapts with RSI overlay logic and detects market “silence” via EMA compression— turning white right before the chaos . That said, you still control its aggression.
ATR Length = how many bars to average
ATR Factor = how tight or loose it hugs price
Lower = more sensitive (more trades, more noise)
Higher = confirmation only (fewer, but stronger signals)
Tweak until it feels like a sniper rifle.
No, you won’t get it perfect on the first try.
Yes, it’s worth it.
🛠️ Modular Signals: Why Things Fire (or Don’t)
Buy/Sell entries require conditions to align. The logic is modular, and that’s on purpose.
RSI signals only fire if RSI crosses its smoothed MA outside the dead zone and a “Watch” condition is active.
SuperTrend signals can be enabled to act on crossovers, optionally ignoring the Watch filter .
Watch conditions (colored squares) act as early recon and hint at possible upcoming trades.
Background color changes are “pre-signal warnings” and will repaint . Use them as leading signals, not gospel.
Want more trades? Loosen your filters .
Want sniper entries? Lock them down .
🌈 Candles and MAs: Visual Market Structure
Candles adapt in real-time to MA structure:
Green = bullish (above both fast/slow MAs)
Yellow = indecision (between)
Red = bearish (below both)
Buy/Sell signals override candles with bright orange and fuchsia —because subtlety doesn’t win wars .
You can also enable up to 8 customizable moving averages —great for confluence , trend confirmation , or just looking like a wizard .
🧠 Pro Usage Tips (TL;DR for Smart People):
Use tooltips in the settings menu —every toggle and slider is explained
Test timeframes until signal frequency and reliability match your goals
Adjust RSI cycle to reduce noise or speed up signals based on how frequently you trade
Tweak SuperTrend factor and ATR to fit volatility on your asset
Start with visual confirmation :
• Are watch signals lining up with trend zones?
• Are backgrounds firing before price moves?
• Are candle colors agreeing with signal direction?
📣 Alerts & Integration
Alerts are available for:
Buy/Sell entries (confirmed or advanced background)
Watch signals
Full band agreement (both Bollinger bands bullish or bearish)
Use these with webhook systems , bots , or your own trade journals .
Created by Sherlock Macgyver
Because sometimes the best trade…
is knowing exactly when not to take one.
SuperTrend CorregidoThis script implements a SuperTrend indicator based on the Average True Range (ATR). It is designed to help traders identify trend direction and potential buy/sell opportunities with visual signals on the chart.
🔧 Key Features:
ATR-Based Trend Detection: Calculates trend shifts using the ATR and a user-defined multiplier.
Buy/Sell Signals: Displays "Buy" and "Sell" labels directly on the chart when the trend changes direction.
Visual Trend Lines: Plots green (uptrend) and red (downtrend) SuperTrend lines to highlight the current market bias.
Trend Highlighting: Optionally fills the background to emphasize whether the market is in an uptrend or downtrend.
Customizable Settings:
ATR period and multiplier
Option to switch ATR calculation method
Toggle for signal visibility and trend highlighting
🔔 Alerts Included:
SuperTrend Buy Signal
SuperTrend Sell Signal
SuperTrend Direction Change
This indicator is useful for identifying entries and exits based on trend momentum and can be used across various timeframes.
MNQ-MES Hedge Protection Calculator by ATALLAMNQ-MES Hedge Protection Calculator - Summary
Purpose
This indicator provides real-time calculations for implementing a hedge strategy between MNQ (Micro E-mini Nasdaq-100) and MES (Micro E-mini S&P 500) futures contracts. It automatically determines the precise number of MES contracts needed to hedge a position in MNQ, based on current market prices and contract specifications.
Key Features
Real-time Hedge Ratio Calculation
Uses live market prices to calculate the optimal hedge ratio
Accounts for different point values ($2 for MNQ, $5 for MES)
Adjusts for beta differences between Nasdaq-100 and S&P 500
Flexible Position Management
Works for both long and short positions
Supports fractional contract amounts
Allows partial hedging (adjustable percentage)
User-Friendly Visual Interface
Clearly displays the exact number of MES contracts needed
Color-coded table showing position direction
Optional chart label with hedge summary
Practical Applications
Directional Risk Reduction: Maintain market exposure while reducing directional risk
Index Spread Trading: Capitalize on relative performance differences between indices
Portfolio Protection: Hedge existing positions in technology-heavy portfolios
Volatility Management: Reduce overall portfolio volatility while maintaining desired exposure
This indicator eliminates the complexity of manually calculating hedge ratios by providing instant, accurate, and visually clear instructions on how to implement an MNQ-MES hedge strategy based on current market conditions.
ICT-Elliott Hybrid Oscillator네이버 프리미엄 콘텐츠 > 재테크 사관학교 검색
This indicator uses Elliott Wave Theory and ICT (Inner Circle Trader) concepts to help easily and accurately predict when asset prices like cryptocurrencies or stocks will rise or fall.
📌 Easy Explanation of Terms
✅ What is Elliott Wave?
A theory stating that price movements follow a specific pattern (5 upward waves + 3 downward waves) repeatedly. Simply put, it's about repetitive cycles of rises and falls creating overall trends.
✅ What is ICT Theory?
A strategy that identifies optimal trading times by observing critical price areas traded by institutional investors (Order Blocks), imbalances in price (Fair Value Gaps - FVG), and major turning points (Break of Structure - BOS).
📈 Signals Provided by the Indicator
🔹 ① Pivot Highs & Lows
Red ▼: Short-term high (increased likelihood of price falling)
Green ▲: Short-term low (increased likelihood of price rising)
🔹 ② Fair Value Gap (FVG)
Green highlighted area: Zone where price is likely to rise again
Red highlighted area: Zone where price is likely to fall again
🔹 ③ Break of Structure (BOS)
Blue "BOS Up": Indicates a shift to an upward trend
Orange "BOS Down": Indicates a shift to a downward trend
⏳ Recommended Timeframe Combinations
| Major Trend (Basic Analysis) | Entry Point (Detailed Analysis) | Short-term Timing (Precision Analysis) |
| ---------------------------- | ------------------------------- | -------------------------------------- |
| 4-hour | 1-hour | 15-minute |
Use the 4-hour timeframe to gauge overall trends,
the 1-hour timeframe to pinpoint exact entry and exit points,
and the 15-minute timeframe for precise timing.
Include Source
🕯 Recommended Candle Patterns
* Pin Bar (Long wick candle) → Trend reversal signal
* Engulfing Candle (fully covering previous candle) → Strong trend reversal signal
* Hammer & Shooting Star (small body with a long wick) → Bullish or bearish reversal signal
* Doji (balance between buyers and sellers) → High potential for trend reversal
Multi-Index Gap Confluence Indicator by ATALLAOverview of the Multi-Index Gap Confluence Indicator
This indicator is designed to identify and highlight price gaps across multiple market indices and their related ETFs/futures. It specifically looks for:
True gaps (where there's no overlap between the current and previous bar's range)
Negative gaps (where only the candle bodies have no overlap, but wicks might)
The indicator has the capability to:
Visualize gaps on charts using colored rectangles
Compare gaps across up to 6 different symbols (3 ETFs and 3 futures)
Generate confluence signals when multiple symbols show gaps simultaneously
Customize appearance and detection parameters
Key Components
Gap Detection
The script distinguishes between:
True gaps: No overlap at all between current and previous bars
Negative gaps: Only the candle bodies have no overlap
Multi-Asset Comparison
The indicator can monitor gaps across six major market indices:
ETFs: QQQ (Nasdaq-100), SPY (S&P 500), and DIA (Dow Jones)
Futures: NQ1! (Nasdaq-100), ES1! (S&P 500), and YM1! (Dow Jones)
Confluence Detection
The script identifies when multiple assets display gaps simultaneously, with:
Configurable minimum threshold (default is 5 out of 6 assets)
Option to require both ETF and futures representation
A strong confluence signal when 5-6 assets show gaps
Customization Options
The indicator offers many parameters for customization:
Gap colors and opacity
Symbol selection and enablement
Confluence thresholds
Display options
Visual Elements
The indicator displays:
Colored rectangles highlighting gap areas
Optional up/down triangles for gap direction
A flag symbol for strong confluence signals (when 5-6 assets show gaps)
Labels listing which specific assets have gaps
Practical Use
This indicator appears designed for traders looking to identify potentially significant market moves by spotting when multiple major indices show price gaps simultaneously. The emphasis on "strong confluence" (5-6 assets showing gaps) suggests these are considered particularly noteworthy signals.
