Crypto MACD SignalsUnlocking Enhanced Market Insights: A Next-Generation MACD Indicator for Cryptocurrency Trading
Introduction: Beyond Traditional MACD
In the vast landscape of technical analysis tools, the Moving Average Convergence Divergence (MACD) stands as one of the most ubiquitous and trusted momentum indicators. However, its classic formulation often leaves traders sifting through frequent crossovers, struggling to distinguish high-probability signals from market noise, especially in the volatile cryptocurrency markets. This script represents a significant evolution of the classic MACD, transforming it from a standalone oscillator into a comprehensive, multi-layered signal detection system. Its core originality lies not in reinventing the MACD calculation, but in augmenting it with proprietary filtering mechanisms, quantitative signal scoring, and visual prioritization to enhance decision clarity and timing.
Core Functionality: What It Does and How It Achieves It
This indicator, titled "Crypto MACD Signals," is a dedicated, non-overlay oscillator built for clarity and actionability. It performs three primary functions simultaneously:
Enhanced MACD Visualization: It plots the traditional MACD line, Signal line, and Histogram with a refined color scheme. The histogram is dynamically colored (blue for bullish, orange for bearish) but introduces a key innovation: the identification of "Huge" or "Anomalous" Bars. A bar is highlighted in bright white when its size exceeds twice the 20-bar Simple Moving Average of the absolute histogram values. This instantly draws attention to moments of exceptional momentum surge or capitulation, which often precede significant trend accelerations or reversals.
Context-Aware Signal Generation: Instead of marking every MACD line crossover, the script applies a crucial logical filter. It only plots a "BUY" signal (green upward triangle) when a bullish crossover occurs while the histogram is below the zero line. Conversely, a "SELL" signal (red downward triangle) is plotted only when a bearish crossover occurs while the histogram is above the zero line. This filter ensures signals are generated in the context of a potential trend reversal from an oversold or overbought state, rather than during the middle of a strong trend, dramatically increasing the signal's statistical edge. This aligns with a classic "Oscillator Reversal from Extremes" methodology within trend-following systems.
Real-Time Performance Dashboard: A fixed table in the top-right corner serves as a live statistical dashboard. It tracks and displays the total count of:
Generated Buy Signals
Generated Sell Signals
Total "Huge" Histogram Bars (both bullish and bearish)
This provides traders with an at-a-glance understanding of recent market activity—whether it has been signal-rich or quiet, and the frequency of high-momentum events—aiding in assessing the current market regime (e.g., trending vs. consolidating).
Implementation and Practical Usage
The indicator is designed for tactical swing trading and momentum-based intraday positioning in crypto assets. Its primary use case is for identifying "Pullback Entries within a Trend" and "Early Trend Reversal Confirmations."
For Trend-Following: A trader in an established uptrend would wait for a pullback that drives the MACD histogram negative. A subsequent bullish crossover that triggers a "BUY" signal, especially if accompanied by a "Huge" bullish histogram bar, offers a high-confidence entry point to re-join the trend.
For Counter-Trend/Reversal Scenarios (Scalping): The script is highly effective for a specific scalping technique: "Fading Extreme Momentum Exhaustion." A cluster of "Huge" bearish bars followed by a diminishing histogram and a bullish crossover signal can indicate selling exhaustion, presenting a short-term long scalp opportunity. The inverse applies for short scalps. The labels ("🔥") and arrows provide clear visual cues for these setups directly on the chart.
Workflow: Traders are advised to first observe the statistical table to gauge recent activity. Then, they should look for convergence between a filtered arrow signal (BUY/SELL) and the appearance of a "Huge" bar or a cluster of them. This multi-factor confirmation is the cornerstone of the strategy.
Underlying Philosophy and Calculation Logic
The script's intelligence is built on a layered philosophy of "Momentum Quantification and Contextual Validation."
Dynamic Thresholding for Anomalies: The "Huge Bar" detection does not use a fixed threshold. By comparing the current histogram value to a recent average of absolute momentum (ta.sma(math.abs(hist_line), 20)), it creates an adaptive, market-responsive benchmark. A bar that is 200% larger than recent average momentum is statistically anomalous, suggesting institutional-sized order flow or a major shift in sentiment. This is a direct application of statistical volatility band principles to momentum, not price.
Signal Filtering for Phase Alignment: The conditional logic for plotting arrows (bullish_cross and hist_line < 0) ensures the MACD crossover signal is aligned with the correct momentum phase of the market cycle. A buy signal is only valid if momentum (histogram) is coming from a "recharging" or bearish area (below zero), not when it's already extended above zero. This prevents buying at a peak and selling at a trough, which is a common pitfall of the raw indicator. This embodies the trading axiom: "Trade the turn, not the continuation."
Quantitative Self-Awareness: The integrated counter and dashboard represent a meta-analysis layer. It allows the tool to provide feedback on its own performance density. A market generating many signals might be choppy and range-bound, while a market with few signals but several "Huge Bars" might be in a strong, steady trend. This helps the trader select the appropriate strategy (trend riding vs. reversal scalping) for the current environment.
In essence, this script synthesizes several respected trading concepts: the core trend/momentum logic of MACD, the anomaly detection common to volatility-based indicators like Keltner Channels, and the signal-verification philosophy of multi-indicator systems—all packaged into a single, coherent, and visually intuitive tool specifically tuned for the unique amplitude and speed of cryptocurrency markets.
Search in scripts for "Cycle"
Bullish Divergence SMI Base & Trigger with ATR FilterDescription:
A bullish divergence indicator combining the Stochastic Momentum Index (SMI) and Average True Range (ATR) to pinpoint high-probability entries:
1. Base Arrow (Orange ▲):
• Marks every SMI %K / %D bullish crossover where %K < –70 (deep oversold)—the first half of the divergence setup.
• Each new qualifying crossover replaces the previous base, continuously “arming” the divergence signal.
• Configurable SMI lookbacks, oversold threshold, and a base timeout (default 100 days) to clear stale bases.
2. Trigger Arrow (Green ▲):
• Completes the bullish divergence: fires on the next SMI bullish crossover where %K > –60 and price has dropped below the base arrow’s close by at least N × ATR (default 1 × 14-day ATR).
• A dashed green line links the base and trigger to visually confirm the divergence.
• Resets after triggering, ready for a new divergence cycle.
Inputs:
• SMI %K Length, EMA Smoothing, %D Length
• Oversold Base Level (–70), Trigger Level (–60)
• ATR Length (14), ATR Multiplier (1.0)
• Base Timeout (100 days)
Ideal for any market, this study highlights genuine bullish divergences—oversold momentum crossovers that coincide with significant price reactions—before entering long trades.
IlluminateThe Illuminate script predicts the potential range of Bitcoin's top and bottom prices based on a logarithmic regression model, referencing Bitcoin's historical price trends and halvings. This script is designed to provide valuable insights into Bitcoin's price dynamics and long-term trends using principles derived from the "Bitcoin Law."
Key Features
Power Law Trend Lines
Primary Trend:
Projects the general growth trajectory of Bitcoin prices over time based on a logarithmic power law.
Resistance Line:
Identifies a potential upper limit of Bitcoin prices during market peaks.
Includes an offset trendline for an additional buffer zone.
Support Line:
Represents a possible bottom for Bitcoin prices during market downturns.
Offset trendlines highlight potential zones of price fluctuation near the support line.
Fill Zones:
Between resistance and offset: Semi-transparent Red.
Between support and offset: Semi-transparent Green/Blue.
Bitcoin Halving Events
Automatically marks significant Bitcoin halving dates with yellow vertical lines and labeled annotations.
Current and future halvings (approximate) are included.
Trending Phase Indication
A dynamic visual color fill highlights different phases of Bitcoin's price evolution based on a 4-year cycle.
Colors: Red, Green, Blue, Orange (indicating each phase).
"Trending Phase" label provides insight into the current phase.
Interactive Inputs
Show/Hide Resistance: Toggle resistance trend lines.
Show/Hide Support: Toggle support trend lines.
Show/Hide Halving Dates: Toggle visibility of halving annotations.
Customizable Parameters
Fine-tune parameters (A and n) for the main trend line to match your analysis needs.
How to Use
Overlay Analysis:
Add this script to your TradingView chart for direct overlay on Bitcoin's price data.
Interpret the Zones:
Use the resistance and support lines as potential upper and lower bounds for price movements.
Analyze fill zones for areas of likely price oscillation.
Halving Significance:
Observe price behavior before and after halving dates, which historically influence market trends.
Long-Term Perspective:
The model is optimized for long-term projections, making it suitable for strategic, rather than short-term, trading decisions.
Disclaimer:
This indicator is for educational purposes only and should not be used as investment advice. Always do your own research and consult with a financial advisor before making trading decisions.
Chuck Dukas Market Phases of Trends (based on 2 Moving Averages)This script is based on the article “Defining The Bull And The Bear” by Chuck Duckas, published in Stocks & Commodities V. 25:13 (14-22); (S&C Bonus Issue, 2007).
The article “Defining The Bull And The Bear” discusses the concepts of “bullish” and “bearish” in relation to the price behavior of financial instruments. Chuck Dukas explains the importance of analyzing price trends and provides a framework for categorizing price activity into six phases. These phases, including recovery, accumulation, bullish, warning, distribution, and bearish, help to assess the quality of the price structure and guide decision-making in trading. Moving averages are used as tools for determining the context preceding the current price action, and the slope of a moving average is seen as an indicator of trend and price phase analysis.
The six phases of trends
// Definitions of Market Phases
recovery_phase = src > ma050 and src < ma200 and ma050 < ma200 // color: blue
accumulation_phase = src > ma050 and src > ma200 and ma050 < ma200 // color: purple
bullish_phase = src > ma050 and src > ma200 and ma050 > ma200 // color: green
warning_phase = src < ma050 and src > ma200 and ma050 > ma200 // color: yellow
distribution_phase = src < ma050 and src < ma200 and ma050 > ma200 // color: orange
bearish_phase = src < ma050 and src < ma200 and ma050 < ma200 // color red
Recovery Phase : This phase marks the beginning of a new trend after a period of consolidation or downtrend. It is characterized by the gradual increase in prices as the market starts to recover from previous losses.
Accumulation Phase : In this phase, the market continues to build a base as prices stabilize before making a significant move. It is a period of consolidation where buying and selling are balanced.
Bullish Phase : The bullish phase indicates a strong upward trend in prices with higher highs and higher lows. It is a period of optimism and positive sentiment in the market.
Warning Phase : This phase occurs when the bullish trend starts to show signs of weakness or exhaustion. It serves as a cautionary signal to traders and investors that a potential reversal or correction may be imminent.
Distribution Phase : The distribution phase is characterized by the market topping out as selling pressure increases. It is a period where supply exceeds demand, leading to a potential shift in trend direction.
Bearish Phase : The bearish phase signifies a strong downward trend in prices with lower lows and lower highs. It is a period of pessimism and negative sentiment in the market.
These rules of the six phases outline the cyclical nature of market trends and provide traders with a framework for understanding and analyzing price behavior to make informed trading decisions based on the current market phase.
60-period channel
The 60-period channel should be applied differently in each phase of the market cycle.
Recovery Phase : In this phase, the 60-period channel can help identify the beginning of a potential uptrend as price stabilizes or improves. Traders can look for new highs frequently in the 60-period channel to confirm the trend initiation or continuation.
Accumulation Phase : During the accumulation phase, the 60-period channel can highlight that the current price is sufficiently strong to be above recent price and longer-term price. Traders may observe new highs frequently in the 60-period channel as the slope of the 50-period moving average (SMA) trends upwards while the 200-period moving average (SMA) slope is losing its downward slope.
Bullish Phase : In the bullish phase, the 60-period channel showing a series of higher highs is crucial for confirming the uptrend. Additionally, traders should observe an upward-sloping 50-period SMA above an upward-sloping 200-period SMA for further validation of the bullish phase.
Warning Phase : When in the warning phase, the 60-period channel can provide insights into whether the current price is weaker than recent prices. Traders should pay attention to the relationship between the price close, the 50-period SMA, and the 200-period SMA to gauge the strength of the phase.
Distribution Phase : In the distribution phase, traders should look for new lows frequently in the 60-period channel, hinting at a weakening trend. It is crucial to observe that the 50-period SMA is still above the 200-period SMA in this phase.
Bearish Phase : Lastly, in the bearish phase, the 60-period channel reflecting a series of lower lows confirms the downtrend. Traders should also note that the price close is below both the 50-period SMA and the 200-period SMA, with the relationship of the 50-period SMA being less than the 200-period SMA.
By carefully analyzing the 60-period channel in each phase, traders can better understand market trends and make informed decisions regarding their investments.
Color Agreement Aggregate (CAA)This indicator helps finding patterns within market structure in a highly intuitive manner.
It does this by painting a picture instead of presenting numerical values.
It greatly reduces noise in trend/structure analysis.
----- HOW TO USE IT -----
1) Zoom out of chart to get a clearer picture of overall color patterns.
2) Consider areas of intense reds and greens as areas of interest.
3) There is always a pattern of intense reds followed by intense greens. Consider this pattern as the start of a new cycle.
4) Key spikes and dips are shown when all 3 bands are matching of intense colors.
5) Turn on Precision in the Style tab to get more information on decisive spikes in price (See "Precision" below).
Reach (top band):
This is the fast and more volatile movement of the market. It shows the direction in which the recent price action is reaching towards.
Energy (middle band):
This is the medium speed of market movement. It shows the energy of the Reach and how influential it is to market change.
Frequent and intense change of color in this band can be a precursor of change within the Basis.
Basis (bottom band):
This is the slower, broader movement of the market. It is the basis on which the Reach and Energy sit on.
Intense colors in this band show major changes in price levels and market structure.
Precision:
Precision shows the weaker levels of colors. It does this by making bars in a band half its size.
For example, if there is a light green bar that is half, it means that the current bar is on the weaker level of the light green level.
Precision helps in identifying where there are influential moves in price action. Note, there will never be a half-sized bar in the highest and lowest levels.
This is because these levels are the limits and don't have a weaker half.
See notes in chart for more information. Note, you can turn off the labels in the Style tab.
----- HOW THIS INDICATOR IS ORIGINAL; WHAT IT DOES AND HOW IT DOES IT -----
This indicator has an original, unique ability to paint the overall market structure in a highly intuitive manner. It "paints" an image instead of showing numbers.
It does this by color-coding different levels of varying speeds of market movement. It then presents these levels as simple bars.
Finally, it stacks them all and creates an overall image of clear breaks and/or repeats within market structure.
This greatly reduces noise in pattern finding, finding breaks in market structure, and in confirming repeated patterns.
----- VERSION -----
The only significant information from this indicator are the colors themselves and the patterns, agreement, and aggregate of the colors.
This indicator does not provide any numerical information of the underlying, mathematical calculations.
The levels for the Reach are made by the KPAM; for the Energy, the CCI; and for the Basis, the RSI.
However, this indicator is not a variant, replacement, or presentation of the KPAM, CCI, or the RSI in any way, shape, or form -- this indicator does not present itself as such.
The 3 indicators are only useful to this indicator in as much as they are what the colors are derived from -- nothing more.
They are needed in order to obtain, visualize, and create the overall aggregate and agreement of colors.
Thus, the KPAM, CCI, and RSI cannot be adjust nor are they plotted. They are not, in any way, a focus of this indicator.
BTC ATH ROIThis indicator shows the ROI % of Bitcoin from when it passed its ATH of the previous bull cycle. I found it interesting that each time it crossed its ATH it took around 260-280 days to peak for each one. This bull run seems to follow between both of the previous bull runs including this recent dip.
There are a couple issues I want to fix but can't figure out:
1. You need to completely scroll out and move towards 2013 on the Daily chart for all 3 lines to show up. Would be nice to load all of that data at the start.
2. I can't query the value of the plots after they have been offset. This would be useful to create a prediction bias for the current plot so would could see where btc might go.
If you peeps know of a way to load all data or query plot values after offsets, please share. That would be awesome.
Ehler Stochastic Cyber Cycle Signals/AlertsThis script works based on @everget's version of Ehler Stochastic Cyber Cycle. Unlike @everget's work, my adaptation prints only crossovers into the chart that occur above or below the overbought/oversold zone.
You can find @everget's script with all related documentation here
I didn't change the calculation, I only reinvented how it is presented on the chart and added alerts.
5x Period Cycle SeasonalityShows the average from the last 5 periods for close price cycle. For example to see the annual seasonality of a stock for the last 5 years use on daily chart with the default setting of 252, the number of trading days in a year, approximately.
Multi-cycle EMA50 full-screen solid lineA small tool to help you check the price of EMA50 over multiple periods.
STIME3H Time High/Low Triangles (Correct Time • Wick/Body • Timezone Control)
This indicator plots 3-Hour (3H) High & Low levels using triangle markers, aligned to exact clock-based time blocks such as 00:00, 03:00, 06:00, 09:00, 12:00, 15:00, 18:00, 21:00.
It is designed for ICT / CRT / intraday traders who need precise session and time-cycle reference points without cluttering the chart.
🔹 Key Features
▲ High triangle & ▼ Low triangle for each 3-hour block
⏱ Correct time alignment using selectable timezones
🌍 Timezone dropdown
UTC
UTC-5 (Fixed)
New York (DST auto)
London (DST auto)
Tokyo
Custom timezone (IANA / Etc format)
🕒 Toggle individual times ON/OFF (00, 03, 06, 09, 12, 15, 18, 21)
📍 Triangles can touch candle wicks or bodies
🗂 Displays last 2 days by default (configurable)
🔠 Adjustable time text size (tiny → large)
🎨 Clean visuals, no background boxes, no repaint
Yen Carry Stress Badge Indicator Overview
This dashboard measures stress in the yen‑carry cycle using price‑based signals from FX, volatility, and global equity markets. Each component is scored based on its current condition, and the combined total reflects whether global markets are in a risk‑on expansion, transition phase, or risk‑off contraction.
Dashboard Components & Indication Levels
USDJPY Trend
Bullish (0 stress): USDJPY above 50‑day MA; yen weakening; carry trade stable
Bearish (1 stress): USDJPY below 50‑day MA; yen strengthening; unwind risk rising
JPY Volatility (ATR%)
Low (0 stress): ATR% < 0.8; stable FX environment
Medium (1 stress): ATR% 0.8–1.2; early instability
High (2 stress): ATR% > 1.2; elevated yen‑carry stress
VIX (Equity Volatility)
Low (0 stress): VIX < 18; calm markets
Medium (1 stress): VIX 18–25; rising uncertainty
High (2 stress): VIX > 25; risk‑off conditions
VWO Strength (Emerging Markets)
Strong (0 stress): VWO/VTI above 50‑day MA; EM participating; liquidity healthy
Weak (1 stress): VWO/VTI below 50‑day MA; EM lagging; early stress signal
VEA Strength (Developed Markets)
Strong (0 stress): VEA/VTI above 50‑day MA; broad global participation
Weak (1 stress): VEA/VTI below 50‑day MA; global breadth narrowing
Total Stress Score (0–10)
0–3: Low Stress (Risk‑On Expansion)
4–6: Moderate Stress (Transition Phase)
7–10: High Stress (Risk‑Off Contraction)
Intervalo de la confianza usando VWMA 5,10,14,55,90,200Varios Itervalos de Confianza usando VWMA
-LOS QUE MANIPULAN LOS MERCADOS, ES COMPRAR DONDE LA VOLATILIDAD ES BAJA, NO HAY RUIDO.
-DESPUES QUE COMPRAN, SU PROXIMO TRABAJO ES CREAR LA VARICIA=FOMO Y MANDAR UNA TARJETA DE INVITACION A LOS INVERSIONISTA MINORITARIOS.
-DESPUES QUE LOS MINORISTA ENTRAN EN CONFIANZA Y VARICIA-FOMO,VENDEN LOS QUE MANIPULAN LOS MERCADOS
-SU ULTIMA ETAPA ES VENDER MAS AGRESIVO PARA CREAR UN MIEDO=FUD Y DARLES EN EL CODO A LOS MINORISTAS PARA QUE SALGAN PERDIENDO.
ESTE CICLOS SE REPITE EN LOS MERCADOS.
Si las personas que operan los mercados tiene sintimentos donde el meido y la varicia entran en el juego de las inversiones y trade, entoces hay que medir como esta su miedo y varicia en diferentes temporaliades.
Que es mejor mediar esta varicia y miedo usando Intervalo de la Confianza usando el VWMA .
AHORA CON ESTA HERRAMIENTA
Ustedes solo tiene que encontrar como esta esta el FOMO o FUD en diferentes temporalidades.
Multiple Confidence Intervals Using VWMA
- Market manipulators buy where volatility is low and there is no noise.
- After they buy, their next step is to create volatility (FOMO) and send an invitation to retail investors.
- Once retail investors gain confidence and experience volatility (FOMO), the market manipulators sell.
- Their final stage is to sell more aggressively to create fear (FUD) and force retailers to lose money.
This cycle repeats itself in the markets. If people who trade the markets experience feelings where fear and greed come into play in their investments and trading, then it's necessary to measure how their fear and greed manifest across different timeframes.
What's the best way to measure this greed and fear using the Confidence Interval with the VWMA?
NOW WITH THIS TOOL
You only need to determine how FOMO or FUD manifests across different timeframes.
ETH Vol Breakout - NO ERROR VERSIONThis strategy examines the impact of Eth.d Vol on Ethereum price. Looking at ETHDVOL -60 (Support) and 78 (Resistance)—tell a very specific story - analyzing a High Volatility Regime.
The support level around 60 and resistance 78, tend to only occurs during Bull Runs or Market Crashes.
In the "Quiet Years", ETHDVOL rarely touched 60, let alone 78.
Trying to develop a strategy that is perfectly tuned for a Bull Market or a Crisis,
1. The "60 Floor" (Support)
Context: In a high-volatility regime, when ETHDVOL drops to 60, it indicates the market has "cooled off" just enough to reload leverage.
Historical Behavior (2021-2022 Context):
July 2021: After the May crash, ETHDVOL compressed down and found support at ~65.
Result: This marked the local bottom before the massive run-up to the November All-Time Highs ($4,800).
Outcome: Strong Buy Signal (Trend Continuation).
January 2022: ETHDVOL dropped to ~58-60 while price was hovering around $3,000.
Result: The floor broke, volatility spiked to 80+, and price crashed to $2,200.
Outcome: Trap / Warning Signal.
The Pattern: When Volatility hits 60 (Support), price is usually Coiling.
If Price is trending UP: This is a "dip buy" opportunity. The coil resolves upwards.
If Price is trending DOWN: This is the "calm before the flush." The coil resolves downwards.
2. The "78 Ceiling" (Resistance)
Context: 78 is an extreme reading. It represents panic (bottom) or euphoria (blow-off top).
Historical Behavior:
May 2021 (The Crash): ETHDVOL smashed through 78, peaking at 100+.
Price Action: Price collapsed from $4,000 to $1,700.
Signal: If Vol > 78, you are in a capitulation event. Buying spot here is usually profitable within 3-6 months (buying the blood).
November 2022 (FTX Collapse): ETHDVOL spiked to ~75-80.
Price Action: ETH hit $1,100 (Cycle Lows).
Signal: Hitting 78 marked the Absolute Bottom.
November 2021 (The Top): Interestingly, at the $4,800 price peak, Volatility was NOT at 78. It was lower (~60-70).
Insight: Bull market tops often happen on lower volatility than bear market bottoms.
Bitcoin Power Law Zones (Dunk)Introduction When viewed on a standard linear chart, Bitcoin’s long-term price action can appear chaotic and exponential. However, when analyzed through the lens of physics and network growth models, a distinct structure emerges.
This indicator implements the Bitcoin Power Law , a mathematical model that suggests Bitcoin’s price evolves in a straight line when plotted against time on a "log-log" scale. By calculating parallel bands around this regression line, we create a "Rainbow" of valuation zones that help investors visualize whether the asset is historically overheated, undervalued, or sitting at fair value.
The Math Behind the Model The Power Law dictates that price scales with time according to the formula: Price = A * (days since genesis)^b
This script uses the specific parameters popularized by recent physics-based analyses of the network: Slope (b): 5.78 (Representing the scaling law of the network adoption). Amplitude (A): 1.45 x 10^-17 (The intercept coefficient).
While simple moving averages react to price, this model is predictive based on time and network growth physics, providing a long-term "gravity" center for the asset.
Guide to the Valuation Zones
Upper Bands (Red/Orange): Extr. Overvalued, High Premium, Overvalued. Historically, these zones have marked cycle peaks where price moved too far, too fast ahead of the network's steady growth. The Baseline (Black Line): Fair Value. The mathematical mean of the Power Law. Price has historically oscillated around this line, treating it as a center of gravity. Lower Bands (Green/Blue): Undervalued, Discount, Deep Discount. These zones represent periods where the market price has historically lagged behind the network's intrinsic value, often marking accumulation phases.
Note: The lowest theoretical tiers ("Bitcoin Dead") have been trimmed from this chart to focus on relevant historical support levels.
How to Use Logarithmic Scale: You MUST set your chart to "Log" scale (bottom right of the TradingView window) for this indicator to function correctly. On a linear chart, the bands will appear to curve upwards aggressively; on a Log chart, they will appear as smooth, parallel channels. Timeframe: This is a macro-economic indicator. It is best viewed on Daily or Weekly timeframes. Overlay Labels: The indicator includes dynamic labels on the right-side axis, allowing you to instantly see the current price requirements for each valuation zone without manually tracing lines.
Credits This script is based on the Power Law theory popularized by Giovanni Santostasi and the original Corridor concepts by Harold Christopher Burger .
Disclaimer This tool is for educational and informational purposes only. It visualizes historical mathematical trends and does not constitute financial advice. Past performance of a model is not indicative of future results.
Further Reading
www.hcburger.com
giovannisantostasi.medium.com
Consolidation Tracker🧭 Consolidation Tracker — Visualize Market Reversals in Real Time
The Consolidation Tracker is a minimalist yet powerful tool designed to map the anatomy of market reversals and trend transitions. It highlights the structural evolution of price through four key phases, helping traders anticipate shifts with clarity and confidence.
🔄 The Four Stages of a Market Reversal:
Failure to Displace — Price fails to break beyond recent highs or lows, signaling potential exhaustion of the current trend.
Consolidation (CAMP) — A range-bound phase where price compresses between a dynamic high and low. These zones are shaded gray, representing indecision and balance.
Engulfing (ENGULF) — A decisive candle closes beyond the CAMP high or low, suggesting a directional shift. These are highlighted in orange.
Fair Value Gap (FVG) — A three-candle pattern forms a price imbalance. If this FVG also engulfs the CAMP range, it confirms the reversal and resets the CAMP. Bullish FVGs are shaded green, bearish FVGs in red.
🔁 From Reversal to Trend:
Once a reversal is confirmed via an FVG, the market often transitions into a trend cycle characterized by:
Displacement — Strong directional movement away from the prior range.
Fair Value Gaps — Continuation imbalances that offer high-probability entries on retracements.
🧠 How It Works:
The indicator dynamically tracks CAMP highs and lows, updating only when a candle engulfs the range or a valid FVG forms.
FVGs are detected when a three-candle sequence creates a gap between candle 2 and 0, and the middle candle (candle 1) breaks the CAMP boundary.
CAMP levels are plotted as horizontal lines, while background colors narrate the evolving structure in real time.
This tool is ideal for traders who value market structure, price efficiency, and narrative clarity. Whether you're anticipating reversals or riding trends, the Consolidation Tracker offers a clean, actionable lens into price behavior.
Predicted Funding RatesOverview
The Predicted Funding Rates indicator calculates real-time funding rate estimates for perpetual futures contracts on Binance. It uses triangular weighting algorithms on multiple different timeframes to ensure an accurate prediction.
Funding rates are periodic payments between long and short position holders in perpetual futures markets
If positive, longs pay shorts (usually bullish)
If negative, shorts pay longs (usually bearish)
This is a prediction. Actual funding rates depend on the instantaneous premium index, derived from bid/ask impacts of futures. So whilst it may imitate it similarly, it won't be completely accurate.
This only applies currently to Binance funding rates, as HyperLiquid premium data isn't available. Other Exchanges may be added if their premium data is uploaded.
Methods
Method 1: Collects premium 1-minunute data using triangular weighing over 8 hours. This granular method fills in predicted funding for 4h and less recent data
Method 2: Multi-time frame approach. Daily uses 1 hour data in the calculation, 4h + timeframes use 15M data. This dynamic method fills in higher timeframes and parts where there's unavailable premium data on the 1min.
How it works
1) Premium data is collected across multiple timeframes (depending on the timeframe)
2) Triangular weighing is applied to emphasize recent data points linearly
Tri_Weighing = (data *1 + data *2 + data *3 + data *4) / (1+2+3+4)
3) Finally, the funding rate is calculated
FundingRate = Premium + clamp(interest rate - Premium, -0.05, 0.05)
where the interest rate is 0.01% as per Binance
Triangular weighting is calculated on collected premium data, where recent data receives progressively higher weight (1, 2, 3, 4...). This linear weighting scheme provides responsiveness to recent market conditions while maintaining stability, similar to an exponential moving average but with predictable, linear characteristics
A visual representation:
Data points: ──────────────>
Weights: 1 2 3 4 5
Importance: ▂ ▃ ▅ ▆ █
How to use it
For futures traders:
If funding is trending up, the market can be interpreted as being in a bull market
If trending down, the market can be interpreted as being in a bear market
Even used simply, it allows you to gauge roughly how well the market is performing per funding. It can basically be gauged as a sentiment indicator too
For funding rate traders:
If funding is up, it can indicate a long on implied APR values
If funding is down, it can indicate a short on implied APR values
It also includes an underlying APR, which is the annualized funding rate. For Binance, it is current funding * (24/8) * 365
For Position Traders: Monitor predicted funding rates before entering large positions. Extremely high positive rates (>0.05% for 8-hour periods) suggest overleveraged longs and potential reversal risk. Conversely, extreme negative rates indicate shorts dominance
Table:
Funding rate: Gives the predicted funding rate as a percentage
Current premium: Displays the current premium (difference between perpetual futures price and the underlying spot) as a percentage
Funding period: You can choose between 1 hour funding (HyperLiquid usually) and 8 hour funding (Binance)
APR: Underlying annualized funding rate
What makes it original
Whilst some predicted funding scripts exist, some aren't as accurate or have gaps in data. And seeing as funding values are generally missing from TV tickers, this gives traders accessibility to the script when they would have to use other platforms
Notes
Currently only compatible with symbols that have Binance USDT premium indices
Optimal accuracy is found on timeframes that are 4H or less. On higher timeframes, the accuracy drops off
Actual funding rates may differ
Inputs
Funding Period: Choose between "8 Hour" (standard Binance cycle) or "1 Hour" (divides the 8-hour rate by 8 for granular comparison)
Plot Type: Display as "Funding Rate" (percentage per interval) or "APR" (annualized rate calculated as 8-hour rate × 3 × 365)
Table: Toggle the information table showing current funding rate, premium, funding period, and APR in the top-right corner
Positive Colour: Sets the colour for positive funding rates where longs pay shorts (default: #00ffbb turquoise)
Negative Colour: Sets the colour for negative funding rates where shorts pay longs (default: red)
Table Background: Controls the background colour and transparency of the information table (default: transparent dark blue)
Table Text Colour: Sets the colour for all text labels in the information table (default: white)
Table Text Size: Controls font size with options from Tiny to Huge, with Small as the default balance of readability and space
Super-Elliptic BandsThe core of the "Super-Elliptic Bands" indicator lies in its use of a super-ellipse mathematical model to create dynamic price bands around a central Simple Moving Average (SMA). Here's a concise breakdown of its essential components:
Central Moving Average (MA):
A Simple Moving Average (ta.sma(close, maLen)) serves as the baseline, anchoring the bands to the average price over a user-defined period (default: 50 bars).
Super-Ellipse Formula:
The bands are generated using the super-ellipse equation: |y/b| = (1 - |x/a|^p)^(1/p), where:
x is a normalized bar index based on a user-defined cycle period (periodBase, default: 64), scaled to range from -1 to +1.
a = 1 (fixed semi-major axis).
b is the volatility-based semi-minor axis, calculated as volRaw * mult, where volRaw comes from ta.stdev, ta.atr, or ta.tr (user-selectable).
p (shapeP, default: 2.0) controls the band shape:
p = 2: Elliptical bands.
p < 2: Pointier, diamond-like shapes.
p > 2: Flatter, rectangular-like shapes.
This formula creates bands that dynamically adjust their width and shape based on price volatility and a cyclical component.
enjoy....
Alt Szn Oracle - Institutional GradeThe Alt Szn Oracle is a macro-level indicator built to help traders front-run altseason by tracking liquidity, dominance rotation, sentiment, and capital flows—all in one signal. It’s designed for those who don’t just chase pumps, but want to understand when the tide is turning and why. This tool doesn't predict specific coin breakouts—it tells you when the market as a whole is gearing up to rotate into higher beta assets like altcoins, including memes and microcaps.
The index consolidates ten macro inputs into a normalized, smoothed score from 0–100. These include Bitcoin and Ethereum dominance, ETH/BTC, altcoin market cap (Total3), relative volume flows, and stablecoin supply (USDT, USDC, DAI)—which act as proxies for risk-on appetite and dry powder entering the system. It also incorporates manually updated sentiment metrics from Google Trends and the Fear & Greed Index, giving it a behavioral edge that most indicators lack.
The logic is simple but powerful: when BTC dominance is falling, ETH/BTC is rising, altcoin volume increases relative to BTC/ETH, and stablecoins start moving—you're likely in the early innings of rotation. The index is also filtered through a volatility threshold and smoothed with an EMA to eliminate chop and fakeouts.
Use this indicator on macro charts like TOTAL3, TOTAL2, or ETHBTC to gauge market health, or overlay it on specific coins like PEPE, DOGE, or SOL to confirm if the tide is in your favor. Interpreting the score is straightforward: readings above 80 suggest euphoria and signal it’s time to de-risk, 60–80 indicates expansion and confirms altseason is underway, 40–60 is neutral, and 20–40 is a capitulation zone where smart money accumulates.
What sets this apart is that it doesn’t just track price—it reflects the flow of capital, the positioning of liquidity, and the sentiment of the crowd. Most altseason indicators are lagging, overfitted, or too simplistic. This one is modular, forward-looking, and grounded in real capital rotation theory.
If you're a trader who wants to time the cycle, not guess it, this is your tool. Refine it, fork it, or expand it to your niche—DeFi, NFTs, meme coins, or L1s. It’s a framework for reading the macro winds, not a signal service. Use it with discipline, and you’ll catch the wave while others drown in noise.
BTC Transaction Indicator Name: "Bitcoin On-Chain Volume & Dynamic Parabolic Curve Signals"
Purpose:
This indicator is designed for Bitcoin traders and long-term holders. It combines the analysis of Bitcoin's on-chain transaction volume with price action to generate "Whale" and "Bear" signals. Additionally, it features a unique dynamic parabolic curve that acts as a visual support line, adapting its visibility based on price interaction with a key Exponential Moving Average (EMA).
Key Components:
On-Chain Volume Analysis:
Utilizes Estimated Transaction Volume (ETRAV) data from the Bitcoin blockchain.
Calculates fast and slow Simple Moving Averages (SMAs) of this volume.
Identifies volume trends (up/down) and significant volume increases/decreases.
Employs fixed thresholds (2,500,000 for low volume and 25,000,000 for high volume) to define key activity levels, similar to how historical on-chain analysis defined accumulation and distribution zones.
Price Action Analysis:
Calculates fast and slow SMAs of the price.
Detects price trends (up/down), recoveries, and declines based on these price SMAs.
"Whale" and "Bear" Signals:
Whale Signals (Buy-side): Generated when there's an upward volume trend, significant volume increase, and a downward price trend followed by price recovery. These indicate potential accumulation phases.
Bear Signals (Sell-side): Generated when there's a downward volume trend, significant volume decrease, and an upward price trend followed by price decline. These indicate potential distribution phases.
Visuals: Both types of signals are plotted as small, colored circles directly on the price chart, with corresponding text labels ("Whale," "Buy," "Bear," "Sell," "Price Recovering," "Price Declining").
Dynamic Parabolic Curve:
Concept: A green parabolic (exponential) curve that serves as a dynamic visual support line.
Activation: The curve starts drawing automatically only when the price crosses over the EMA 500 (Exponential Moving Average of 500 periods). The curve's starting point is set at a user-defined percentage below the EMA 500 value at that exact crossover point.
Visibility: The curve remains visible and continues its trajectory only as long as the price stays above the EMA 500.
Deactivation: The curve disappears instantly if the price falls below or equals the EMA 500. It will only reappear if the price crosses above the EMA 500 again.
Customization: The curve's steepness (Tasa Crecimiento Curva) and its initial distance from the EMA 500 (Inicio Curva % por debajo de EMA500) are adjustable.
Dynamic Label: A "Parabólico" text label is plotted near the center of the active curve segment, with an adjustable vertical offset to ensure it stays visually appealing below the curve.
What is PLOTTED on the chart:
The small, colored circle signals for Whale/Buy and Bear/Sell activity.
The green dynamic parabolic curve.
What is NOT PLOTTED:
EMA 200, EMA 500 lines (though they are calculated internally for logic).
Raw volume data or volume Moving Averages (these are only used for signal calculation, not plotted).
Ideal for:
Bitcoin traders and investors focused on long-term trends and cycle analysis, who want visual cues for accumulation/distribution phases based on on-chain activity, complemented by a unique, dynamically appearing parabolic support curve.
Important Notes:
Relies on the availability of external on-chain data (QUANDL:BCHAIN) within TradingView.
Functions best on a daily timeframe for optimal on-chain data relevance.
Global OECD CLI Diffusion Index YoY vs MoMThe Global OECD Composite Leading Indicators (CLI) Diffusion Index is used to gauge the health and directional momentum of the global economy and anticipate changes in economic conditions. It usually leads turning points in the economy by 6 - 9 months.
How to read: Above 50% signals economic expansion across the included countries. Below 50% signals economic contraction.
The diffusion index component specifically shows the proportion of countries with positive economic growth signals compared to those with negative or neutral signals.
The OECD CLI aggregates data from several leading economic indicators including order books, building permits, and consumer and business sentiment. It tracks the economic momentum and turning points in the business cycle across 38 OECD member countries and several other Non-OECD member countries.
Payday Anomaly StrategyThe "Payday Effect" refers to a predictable anomaly in financial markets where stock returns exhibit significant fluctuations around specific pay periods. Typically, these are associated with the beginning, middle, or end of the month when many investors receive wages and salaries. This influx of funds, often directed automatically into retirement accounts or investment portfolios (such as 401(k) plans in the United States), temporarily increases the demand for equities. This phenomenon has been linked to a cycle where stock prices rise disproportionately on and around payday periods due to increased buy-side liquidity.
Academic research on the payday effect suggests that this pattern is tied to systematic cash flows into financial markets, primarily driven by employee retirement and savings plans. The regularity of these cash infusions creates a calendar-based pattern that can be exploited in trading strategies. Studies show that returns on days around typical payroll dates tend to be above average, and this pattern remains observable across various time periods and regions.
The rationale behind the payday effect is rooted in the behavioral tendencies of investors, specifically the automatic reinvestment mechanisms used in retirement funds, which align with monthly or semi-monthly salary payments. This regular injection of funds can cause market microstructure effects where stock prices temporarily increase, only to stabilize or reverse after the funds have been invested. Consequently, the payday effect provides traders with a potentially profitable opportunity by predicting these inflows.
Scientific Bibliography on the Payday Effect
Ma, A., & Pratt, W. R. (2017). Payday Anomaly: The Market Impact of Semi-Monthly Pay Periods. Social Science Research Network (SSRN).
This study provides a comprehensive analysis of the payday effect, exploring how returns tend to peak around payroll periods due to semi-monthly cash flows. The paper discusses how systematic inflows impact returns, leading to predictable stock performance patterns on specific days of the month.
Lakonishok, J., & Smidt, S. (1988). Are Seasonal Anomalies Real? A Ninety-Year Perspective. The Review of Financial Studies, 1(4), 403-425.
This foundational study explores calendar anomalies, including the payday effect. By examining data over nearly a century, the authors establish a framework for understanding seasonal and monthly patterns in stock returns, which provides historical support for the payday effect.
Owen, S., & Rabinovitch, R. (1983). On the Predictability of Common Stock Returns: A Step Beyond the Random Walk Hypothesis. Journal of Business Finance & Accounting, 10(3), 379-396.
This paper investigates predictability in stock returns beyond random fluctuations. It considers payday effects among various calendar anomalies, arguing that certain dates yield predictable returns due to regular cash inflows.
Loughran, T., & Schultz, P. (2005). Liquidity: Urban versus Rural Firms. Journal of Financial Economics, 78(2), 341-374.
While primarily focused on liquidity, this study provides insight into how cash flows, such as those from semi-monthly paychecks, influence liquidity levels and consequently impact stock prices around predictable pay dates.
Ariel, R. A. (1990). High Stock Returns Before Holidays: Existence and Evidence on Possible Causes. The Journal of Finance, 45(5), 1611-1626.
Ariel’s work highlights stock return patterns tied to certain dates, including paydays. Although the study focuses on pre-holiday returns, it suggests broader implications of predictable investment timing, reinforcing the calendar-based effects seen with payday anomalies.
Summary
Research on the payday effect highlights a repeating pattern in stock market returns driven by scheduled payroll investments. This cyclical increase in stock demand aligns with behavioral finance insights and market microstructure theories, offering a valuable basis for trading strategies focused on the beginning, middle, and end of each month.
CRT AMD indicatorThis indicator is based on the Power of three (Accumulation Manipulation Distribution) Cycle, by marking the candle that Sweep the low or high of the previous candle and then closed back inside the range of the previous candle, indicating a possibility of a Manipulation or Reversal.
Combining the indicator with HTF Array and LTF Setup Entry will significantly improve the accuracy.
BTC x M2 Divergence (Weekly)### Why the "M2 Money Supply vs BTC Divergence with Normalized RSI" Indicator Should Work
IMPORTANT
- Weekly only indicator
- Combine it with BTC Halving Cycle Profit for better results
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator leverages the relationship between macroeconomic factors (M2 money supply) and Bitcoin price movements, combined with technical analysis tools like RSI, to provide actionable trading signals. Here's a detailed rationale on why this indicator should be effective:
1. **Macroeconomic Influence**:
- **M2 Money Supply**: Represents the total money supply, including cash, checking deposits, and easily convertible near money. Changes in M2 reflect liquidity in the economy, which can influence asset prices, including Bitcoin.
- **Bitcoin Sensitivity to Liquidity**: Bitcoin, being a digital asset, often reacts to changes in liquidity conditions. An increase in money supply can lead to higher asset prices as more money chases fewer assets, while a decrease can signal tightening conditions and lower prices.
2. **Divergence Analysis**:
- **Economic Divergence**: The indicator calculates the divergence between the percentage changes in M2 and Bitcoin prices. This divergence can highlight discrepancies between Bitcoin's price movements and broader economic conditions.
- **Market Inefficiencies**: Large divergences may indicate inefficiencies or imbalances that could lead to price corrections or trends. For example, if M2 is increasing (indicating more liquidity) but Bitcoin is not rising proportionately, it might suggest a potential upward correction in Bitcoin's price.
3. **Normalization and Smoothing**:
- **Normalized Divergence**: Normalizing the divergence to a consistent scale (-100 to 100) allows for easier comparison and interpretation over time, making the signals more robust.
- **Smoothing with EMA**: Applying Exponential Moving Averages (EMAs) to the normalized divergence helps to reduce noise and identify the underlying trend more clearly. This double-smoothed divergence provides a clearer signal by filtering out short-term volatility.
4. **RSI Integration**:
- **RSI as a Momentum Indicator**: RSI measures the speed and change of price movements, indicating overbought or oversold conditions. Normalizing the RSI and incorporating it into the divergence analysis helps to confirm the strength of the signals.
- **Combining Divergence with RSI**: By using RSI in conjunction with divergence, the indicator gains an additional layer of confirmation. For instance, a bullish divergence combined with an oversold RSI can be a strong buy signal.
5. **Dynamic Zones and Sensitivity**:
- **Good DCA Zones**: Highlighting zones where the divergence is significantly positive (good DCA zones) indicates periods where Bitcoin might be undervalued relative to economic conditions, suggesting good buying opportunities.
- **Red Zones**: Marking zones with extremely negative divergence, combined with RSI confirmation, identifies potential market tops or bearish conditions. This helps traders avoid buying into overbought markets or consider selling.
- **Peak Detection**: The sensitivity setting for detecting upside down peaks allows for early identification of potential market bottoms, providing timely entry points for traders.
6. **Visual Cues and Alerts**:
- **Clear Visualization**: The plots and background colors provide immediate visual feedback, making it easier for traders to spot significant conditions without deep analysis.
- **Alerts**: Built-in alerts for key conditions (good DCA zones, red zones, sell signals) ensure traders can act promptly based on the indicator's signals, enhancing the practicality of the tool.
### Conclusion
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator integrates macroeconomic data with technical analysis to offer a comprehensive view of Bitcoin's market conditions. By analyzing the divergence between M2 money supply and Bitcoin prices, normalizing and smoothing the data, and incorporating RSI for momentum confirmation, the indicator provides robust signals for identifying potential buying and selling opportunities. This holistic approach increases the likelihood of capturing significant market movements and making informed trading decisions.
