Divergence Mucho Indicators v6 AlertsShows divergence for well known indicators. Allows option to create alert for 4 or more divergences signaling.
Ciclos
ICT Manipulation DetectorThis indicator detects ICT-style manipulations, liquidity sweeps (stop hunts), and Fair Value Gaps (FVG) automatically on the chart.
🔍 What It Does:
Identifies key highs and lows as liquidity zones.
Detects stop hunts above highs or below lows.
If the price move is large enough, marks it as a manipulation.
Highlights Fair Value Gaps (FVGs) where price might return.
Shows all events visually with boxes, lines, and alerts.
📌 Visuals:
🟩 Green box = Bullish manipulation → “DON’T SELL”
🟥 Red box = Bearish manipulation → “DON’T BUY”
🟨 Yellow dashed lines = Liquidity levels
🔼 / 🔽 Arrows = Sweeps without full manipulation
In short: It automatically detects and warns you of smart money manipulation based on ICT concepts.
D, W, M_CPR _ By VAZHGA VALAMUDAN SKcpr for daily, weekly, monthly levels and daily weekly monthly high low with ema 8,20,50,200"
Bitcoin Logarithmic Growth Curve 2025 Z-Score"The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
snapshot
snapshot
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns."
Now with Z-Score calculation for easy and constant valuation classification of Bitcoin according to this metric.
Created for TRW
Volume Cycle TrackerThis indicator measures the average bar-to-bar distance between recent high-volume candles, defined as candles with volume greater than its own 20-period SMA. The less frequent the high-volume candles, the higher the output value, helping visualize periods of reduced strong participation. It’s useful for identifying expansions and contractions in volume pressure without relying on raw volume bars. The values are smoothed to reduce noise. Can be used to filter out weak consolidations or spot re-accumulation zones.
Martin Strategy - No Loss Exit v3Martin Strategy1.0 Martin Strategy1.0 Martin Strategy1.0 Martin Strategy1.0 Martin Strategy1.0 Martin Strategy1.0
JADEVO I - Scaling Only (No SL) w/ Static Midpoint Alerthigh-precision, real-time trading indicator designed to capture powerful directional moves with minimal lag. Built for serious traders, this tool combines dynamic trend detection, smart entry logic, and customizable signal filtering to deliver reliable trade opportunities across any market or timeframe.
Key Features:
🧠 Adaptive Signal Engine: Filters out noise and highlights only the highest-probability setups.
🔁 Works on any timeframe and asset class (NQ, ES, FX, crypto, stocks).
🔥 Built-in alert conditions for Buy/Sell triggers, TP zones, and trend shifts.
🎯 Clean visual layout with optional overlays and labels.
⚙️ Fully customizable parameters for precision tuning.
Ideal for scalpers, intraday traders, and swing traders who demand consistent performance.
Join the Just.Trades community for access to advanced strategies, live signals, and automation tools.
Terminal de Estrategias PRO (MTF + Order Blocks)this is a new test for the implementation of functions on my app web for signals
Terminal de Estrategias PROim just testing this new script I just created for an strategy for an app
MANI SESSIONSOANDA:GBPUSD This indicator marks the opening times of the three main trading sessions — Asia, London, and New York — using vertical red dotted lines on the chart.
Each session is labeled with a minimal tag (“ASIA”, “LDN”, “NY”) displayed directly on the line for clean and unobtrusive reference.
All session times are based on the New York time zone and adjust automatically for each new day.
This tool helps intraday traders quickly identify session shifts, plan entries around high-volume hours, and stay locked into session-based strategy.
OANDA:GBPUSD
TOTAL3ES/ETH Mean ReversionTOTAL3ES/ETH Mean Reversion Indicator
Overview
The TOTAL3ES/ETH Mean Reversion indicator is a specialized tool designed exclusively for analyzing the ratio between TOTAL3 excluding stablecoins (TOTAL3ES) and Ethereum's market capitalization. This ratio provides crucial insights into the relative performance and valuation cycles between altcoins and ETH, making it an essential tool for cryptocurrency portfolio allocation and market timing decisions.
What This Indicator Measures
This indicator tracks the market cap ratio of all altcoins (excluding ETH and stablecoins) to Ethereum's market cap. When the ratio is:
Above 1.0 (Parity): Altcoins have a larger combined market cap than ETH
Below 1.0 (Parity): ETH's market cap exceeds the combined altcoin market cap
Key Features
Historical Context
Historical Range: 0.64 (July 2017 low) to 3.49 (all-time high)
Midpoint: 2.065 - the mathematical center of the historical range
Parity Line: 1.0 - the psychological level where altcoins = ETH market cap
Mean Reversion Zones
The indicator identifies extreme valuation zones based on historical data:
Upper Extreme Zone (~2.92 at 80% threshold): Suggests altcoins may be overvalued relative to ETH
Lower Extreme Zone (~1.21 at 80% threshold): Suggests altcoins may be undervalued relative to ETH
Visual Elements
Color-coded zones: Red shading for bearish reversion areas, green for bullish reversion areas
Multiple reference lines: Parity, midpoint, and historical extremes
Information table: Real-time metrics including current ratio, range position, and reversion pressure
Customizable display: Toggle zones, lines, and adjust transparency
How to Use This Indicator
Market Cycle Analysis
Extreme High Zone (Red): When ratio enters this zone, consider potential ETH outperformance
Extreme Low Zone (Green): When ratio enters this zone, consider potential altcoin season
Parity Crossovers: Monitor when ratio crosses above/below 1.0 for sentiment shifts
Portfolio Allocation Signals
High Ratio Values: May indicate overextended altcoin valuations relative to ETH
Low Ratio Values: May suggest undervalued altcoins relative to ETH
Midpoint Reversions: Historical tendency to revert toward the 2.065 midpoint
Alert Conditions
The indicator includes built-in alerts for:
Entering extreme high/low zones
Parity crossovers (above/below 1.0)
Mean reversion signals
Input Parameters
Display Settings
Show Reversion Zones: Toggle colored extreme zones on/off
Show Midpoint: Display the historical midpoint line
Show Parity Line: Show the 1.0 parity reference line
Zone Transparency: Adjust shaded area opacity (70-95%)
Calculation Settings
Reversion Strength Period: Moving average period for reversion calculations (10-50)
Extreme Threshold: Percentage of historical range defining extreme zones (0.5-1.0)
Information Table Metrics
The bottom-right table displays:
Current Ratio: Live TOTAL3ES/ETH value
Range Position: Current position within historical range (%)
From Parity: Distance from 1.0 parity level (%)
Reversion Pressure: Intensity of mean reversion forces (%)
Zone: Current market zone classification
Historical Range: Reference boundaries (0.64 - 3.49)
Midpoint: Historical center value
Important Notes
Chart Compatibility
Exclusively designed for CRYPTOCAP:TOTAL3ES/CRYPTOCAP:ETH
Built-in validation ensures proper chart usage
Will display error message if applied to incorrect charts
Trading Considerations
This is an analytical tool, not trading advice
Mean reversion is a tendency, not a guarantee
Consider multiple timeframes and confirmations
Factor in overall market conditions and trends
Risk Disclaimer
Past performance does not guarantee future results. Cryptocurrency markets are highly volatile and unpredictable. Always conduct your own research and consider your risk tolerance before making investment decisions.
Ideal Use Cases
Portfolio rebalancing between ETH and altcoins
Market cycle timing for position adjustments
Sentiment analysis of crypto market phases
Long-term allocation strategies based on historical patterns
Risk management through extreme zone identification
This indicator serves as a quantitative framework for understanding the cyclical relationship between Ethereum and the broader altcoin market, helping traders and investors make more informed allocation decisions based on historical valuation patterns.ons
- Factor in overall market conditions and trends
### Risk Disclaimer
Past performance does not guarantee future results. Cryptocurrency markets are highly volatile and unpredictable. Always conduct your own research and consider your risk tolerance before making investment decisions.
Parabolic SAR with Early Buy & MA-Based Exit Strategy📝 Strategy Description (Max SEO Impact)
This advanced Parabolic SAR-based trading strategy is designed to capture early trend reversals and exit intelligently using a dynamic moving average filter. It enters long trades when a PSAR reversal occurs, and exits only when the PSAR moves above price and the price falls below the 11-period SMA, helping avoid premature exits during volatile swings.
📌 Features:
• Custom Parabolic SAR calculation for refined trend tracking
• Background highlights during buy zones (SAR below price)
• Exit signals only when trend weakens (PSAR above + price under SMA)
• Red flag plotted on chart at exit bars for clear visual identification
• Works on all timeframes and instruments
Ideal for swing traders, trend followers, and strategy testers looking for smart PSAR-based entries with smoother exits.
Parabolic SAR with Early Buy & MA-Based Exit Strategy📝 Strategy Description (Max SEO Impact)
This advanced Parabolic SAR-based trading strategy is designed to capture early trend reversals and exit intelligently using a dynamic moving average filter. It enters long trades when a PSAR reversal occurs, and exits only when the PSAR moves above price and the price falls below the 11-period SMA, helping avoid premature exits during volatile swings.
📌 Features:
• Custom Parabolic SAR calculation for refined trend tracking
• Background highlights during buy zones (SAR below price)
• Exit signals only when trend weakens (PSAR above + price under SMA)
• Red flag plotted on chart at exit bars for clear visual identification
• Works on all timeframes and instruments
Ideal for swing traders, trend followers, and strategy testers looking for smart PSAR-based entries with smoother exits.
Parabolic SAR Strategy with MACD Confirmation & Trend Zone Highl📝 Description (SEO + Follower-Friendly):
🚀 Powerful Trend Strategy Using Parabolic SAR + MACD
This advanced Pine Script combines the classic Parabolic SAR trend-following system with MACD crossover confirmation, improving entry precision and filtering out false signals. The script also features:
✅ Dynamic trend zone background highlighting when SAR is below price
✅ MACD filter ensures trades align with market momentum
✅ Custom SAR logic with adaptive acceleration
✅ Clean visual SAR plots for easy trend tracking
✅ Fully backtestable with strategy.entry logic
🔎 Ideal for traders seeking early trend entries, momentum confirmation, and visual clarity.
📈 Works on all timeframes and pairs — perfect for swing traders, scalpers, and crypto enthusiasts.
💡 Use it as a base strategy or combine with your favorite indicators.
❤️ If you find this helpful, don't forget to like, comment, and follow for more premium strategies!
XRP Breathe Strategy Zones +🫁 XRP Breathe Strategy Zones
A time-based trading overlay designed specifically for XRPUSD.
This tool highlights weekly "Inhale" and "Exhale" phases based on a 20-day cycle of price action. It visually guides traders through expected accumulation and distribution zones, helping align trades with market rhythm.
🔹 Key Features:
Color-coded Inhale and Exhale phases
Critical price levels marked for support and resistance
Built-in signal arrows for trend confirmation
Perfect for swing traders and intraday strategists looking to trade XRP with more structure, timing, and confidence.
√ Square Root LevelsSquare Root - Based Levels Indicator
---------------------------------------------
This indicator plots key support and resistance levels based on the square root of price — a unique, mathematically-driven method rooted in price structure rather than traditional Fibonacci or percentage-based techniques.
Core Concept:
-----------------
Levels are calculated by applying the square root function to price, then multiplying or adding/subtracting scaled increments. This approach smooths volatility and reveals hidden levels of market significance that may not be visible with conventional tools.
Use Cases:
-------------
* Identify hidden support/resistance zones
* Time entries and exits based on price harmonics
* Complement other technical tools (like Fibonacci, Gann, or Pivot Points)
Customizable Settings:
----------------------------
* Base Price (Anchor)
* Increment/Multiplier
* Number of Levels
* Styling options for clean chart visuals
Whether you're a day trader or swing trader, this tool adds a mathematically unique perspective to your technical analysis.
Bitcoin: Pi Cycle Top & Bottom Indicator Z ScoreIndicator Overview
The Pi Cycle Top Indicator has historically been effective in picking out the timing of market cycle highs within 3 days.
It uses the 111 day moving average (111DMA) and a newly created multiple of the 350 day moving average, the 350DMA x 2.
Note: The multiple is of the price values of the 350DMA, not the number of days.
For the past three market cycles, when the 111DMA moves up and crosses the 350DMA x 2 we see that it coincides with the price of Bitcoin peaking.
It is also interesting to note that 350 / 111 is 3.153, which is very close to Pi = 3.142. In fact, it is the closest we can get to Pi when dividing 350 by another whole number.
It once again demonstrates the cyclical nature of Bitcoin price action over long time frames. However, in this instance, it does so with a high degree of accuracy over Bitcoin's adoption phase of growth.
Bitcoin Price Prediction Using This Tool
The Pi Cycle Top Indicator forecasts the cycle top of Bitcoin’s market cycles. It attempts to predict the point where Bitcoin price will peak before pulling back. It does this on major high time frames and has picked the absolute tops of Bitcoin’s major price moves throughout most of its history.
How It Can Be Used
Pi Cycle Top is useful to indicate when the market is very overheated. So overheated that the shorter-term moving average, which is the 111-day moving average, has reached an x2 multiple of the 350-day moving average. Historically, it has proved advantageous to sell Bitcoin around this time in Bitcoin's price cycles.
It is also worth noting that this indicator has worked during Bitcoin's adoption growth phase, the first 15 years or so of Bitcoin's life. With the launch of Bitcoin ETF's and Bitcoin's increased integration into the global financial system, this indicator may cease to be relevant at some point in this new market structure.
Added the Z-Score metric for easy classification of the value of Bitcoin according to this indicator.
Created for TRW
Inascript PRO (Elliott + TP System)Inascript PRO (Elliott + TP System) is an intraday strategy for gold (XAUUSD), based on simplified Elliott Wave logic.
It features 3 Take Profits, dynamic Stop Loss, break-even logic, and session filters (London & New York).
Precise alerts include entry, TP, and SL levels.
Developed by Inaskan for clean and smart intraday trading.
Investor Tool - Z ScoreThe Investor Tool is intended as a tool for long term investors, indicating periods where prices are likely approaching cyclical tops or bottoms. The tool uses two simple moving averages of price as the basis for under/overvalued conditions: the 2-year MA (green) and a 5x multiple of the 2-year MA (red).
Price trading below the 2-year MA has historically generated outsized returns, and signalled bear cycle lows.
Price trading above the 2-year MA x5 has been historically signalled bull cycle tops and a zone where investors de-risk.
Just like the Glassnode one, but here on TV and with StDev bands
Now with Z-SCORE calculation:
The Z-Score is calculated to be -3 Z at the bottom bands and 3 Z at the top bands
mean = (upper_sma + bottom_sma) / 2
bands_range = upper_sma - bottom_sma
stdDev = bands_range != 0 ? bands_range / 6 : 0
zScore = stdDev != 0 ? (close - mean) / stdDev : 0
Created for TRW
Bitcoin Cycle Master Z-ScoreThe "Bitcoin Cycle Master Z-Score" indicator is designed for in-depth, long-term analysis of Bitcoin's price cycles, using several key metrics to track market behavior and forecast potential price tops and bottoms. The indicator integrates multiple moving averages and on-chain metrics, offering a comprehensive view of Bitcoin’s historical and projected performance. Each of its components plays a crucial role in identifying critical cycle points.
The Z-Score is calculated between the 3 lower bands and the 2 upper bands
top_bands = (DeltaTop() + TerminalPrice())/2
bottom_bands = (BalancedPrice() + CVDD() + RealizedPrice())/3
The Z-Score is calculated to be -3 Z at the bottom bands and 3 Z at the top bands
mean = (top_bands + bottom_bands) / 2
bands_range = top_bands - bottom_bands
stdDev = bands_range != 0 ? bands_range / 6 : 0
zScore = stdDev != 0 ? (close - mean) / stdDev : 0
Created for TRW
Historical Year OverlayThis script allows you to simply source any historical calendar year and overlay it over any other year (usually a historical year overlaying a year in the future). It was made using an LLM for coding help and logic.
It is great for working out potential pivots and it also maps the previous profit/loss from the source year over the plot year so that we can see the connection to price levels throughout the plot year and also with the yearly close (we get a horizontal line for the close).
It uses the year open as a price reference to plot the P&L over the plot year (if use plot year option is selected).
if the year has not started yet you can use the "manual opening price" OR it will auto set to the current price (great for "replay mode", it will catch the actual opening price once it happens).
The settings are self explanatory. Choose a source year and plot year.
Choose a multiplier if you'd like (it simply multiplies the plot year P&L by that number; ie: 1 means the same as it was, 0.5 means half of what is was, 2 means 2x the source P&L)
The resolution is max default 50 line segments but you can simplify if you'd like.
I've released the code open-source so you can see what it is doing.
Please update it with all the enhancements you can think of.
Please let me know if you do this as I will be very interested!
