AperonFx Pivot Points 1.1This indicator plots ATR-based pivot levels with a clean, institutional layout.
The central pivot (P) is calculated from the selected timeframe and price formula, while support and resistance levels are placed at equal distance steps above and below the pivot.
Users can choose between an automatic step based on ATR or a fixed price step for fully controlled, symmetric levels.
All levels are drawn as continuous segments that align precisely with the active pivot period.
Price annotations are displayed in a minimal, unobtrusive style and always match the exact level values.
The indicator is designed to remain consistent across chart timeframes without recalculation drift.
It is intended for traders who want clear, structured reference levels rather than reactive signals.
Индикаторы и стратегии
Shadow Momentum EngineA proprietary oscillator that detects hidden divergences and momentum shifts before they appear on traditional indicators. Ideal for early entries in trends and for avoiding false breakout traps.
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Un oscilador propietario que detecta divergencias ocultas y cambios de momentum antes de que aparezcan en los indicadores tradicionales. Perfecto para entradas tempranas en tendencias y para evitar trampas de falso breakout.
Volume ROC (smoothed)Description
The Volume ROC (Rate of Change) indicator is designed to measure the momentum of trading volume over a user-defined period, adjusted for the trading session length of the symbol (e.g., 8.5 hours for the FTSEMIB index). This makes it particularly useful for intraday charts where standard daily calculations might not align with actual trading days.
By focusing on volume changes rather than price, it helps identify potential shifts in market participation, such as accumulation, distribution, or unusual activity that could precede price movements.
How It Works:
Session Adjustment:
The indicator calculates the number of candles per trading day based on the input session duration (in hours) and the chart's timeframe. This ensures that the ROC and other calculations are based on "trading days" rather than calendar days, making it adaptable to markets with non-standard hours like European indices (e.g., FTSEMIB).
Daily Data Fetch:
It retrieves daily high, low, close, and volume data using "request.security" to ensure consistency across timeframes.
ROC Calculation:
The Rate of Change (ROC) is computed on volume using "ta.change" over the specified length (in days), multiplied by the candles-per-day factor for timeframe independence. By chosing the subtraction method instead of the division method we avoid distortions of the ROC below the zero line (method ok for timespans inferior to two years).
Smoothing with SMA:
A Simple Moving Average (SMA) is applied to the ROC to reduce noise and highlight trends in volume momentum.
Standard Deviation Bands:
The standard deviation of the smoothed ROC is calculated over a lookback period. Bands are plotted at +2σ (overbought) and -2σ (oversold) to provide context for extreme volume changes, similar to Bollinger Bands but applied to volume ROC.
Key Plots:
SMA Line (Orange): The smoothed ROC value. Positive values indicate increasing volume momentum; negative values suggest decreasing momentum.
Zero Line (Black Dotted): A reference line at 0, separating positive and negative ROC territories.
+2σ Band (Red Dotted): Upper overbought threshold. Crossings above this may signal excessive buying volume.
-2σ Band (Green Dotted): Lower oversold threshold. Dips below this could indicate capitulation or low interest.
Usage and Interpretation:
Trend Confirmation:
Use the SMA crossing above/below zero to confirm price trends with volume backing. For example, a rising price with positive Volume ROC suggests strong conviction.
Divergences:
Look for divergences between price and Volume ROC (e.g., price making new highs but ROC weakening), which can signal reversals.
Overbought/Oversold Signals:
The ±2σ bands act as dynamic levels. Volume ROC spiking above +2σ might precede pullbacks, while below -2σ could indicate buying opportunities.
Best Applied To:
European indices (like FTSEMIB or DAX), stocks, or futures with defined session hours. Test on intraday (e.g., 2h) and combine with price-based indicators like RSI or MACD for confluence.
Customization:
Adjust the ROC/SMA lengths for sensitivity (shorter for scalping, longer for swings). The STDEV lookback affects band width—longer periods create smoother bands.
Limitations:
Volume data can be noisy in low-liquidity symbols. This indicator assumes consistent session lengths; irregular holidays may affect accuracy. Always backtest and use with risk management.
This indicator is original and built for educational/trading purposes.
Futures Tick DashboardThis is a simple dashboard that shows the novice future trade the necessary info about the info about the Micro on mini futures contract they are thinking about trading
ITCP ATR BB RSI Stoch SignalsThis indicator generates BUY/SELL signals when price stretches outside Bollinger Bands during elevated volatility, confirmed by RSI, a Stochastic crossover, and a volume filter. To reduce counter-trend entries, it applies a macro trend filter using the Daily SMA 200: it looks for longs only above the SMA 200 and shorts only below it.
It tends to perform best in Forex, especially on liquid pairs, because market conditions (liquidity, continuous sessions, and relatively stable spreads on major pairs) often suit this confirmation-based approach. That said, it can be adapted to other markets (indices, commodities, or crypto) by tuning parameters such as Bollinger length/deviation, RSI/Stoch thresholds, and ATR settings (multipliers/factors) to fit the asset’s volatility.
It also plots ATR-based stop-loss reference levels (configurable smoothing) and includes webhook-ready alerts with a JSON payload (action, symbol, price, stop_loss, time, and interval) for external automation. The goal is to support rules-based execution and reduce impulsive trades: if conditions don’t align, there’s no signal.
If you manage to improve it, discover better settings, or build a more robust solution inspired by this, I’d really appreciate it if you share it back (even if it’s just feedback or an idea). I’m open to collaborating and iterating together to create stronger versions over time.
NeuralFlow Forecast Levels | SPY WeeklyThis is a companion script that plots AI-adaptive market equilibrium & expansion mapping levels for SPY on chart.
NeuralFlow Forecast levels are generated though a Artificial Intelligence framework trained to identify where price is statistically inclined to re-balance and where expansion zones historically exhaust rather than extend.
What the Bands Represent
Band Layer Meaning
AI Equilibrium (white core) Primary weekly balance zone where price is most likely to mean-revert
Predictive Rails (aqua / purple) High-confidence corridor of institutional flow containment
Outer Zones (green / red) Expansion limits where continuation historically decays
Extreme Zones (top/bottom) Rare deviation envelope where auction completion is statistically favored
NeuralFlow operates Artificial Intelligence models trained specifically to map statistical re-balancing behavior, not trader predictions or sentiment. No discretionary drawing. No correlations. No lagging overlays.
This engine updates only when underlying structure changes — not when candles fluctuate intraday.
Risk:
Educational & analytical use only. Not financial advice
NeuralFlow Forecast Levels| NIFTY WeeklyThis is a companion script that plots AI-adaptive market equilibrium & expansion mapping levels on chart.
NeuralFlow Forecast levels are generated though a Artificial Intelligence framework trained to identify where price is statistically inclined to re-balance and where expansion zones historically exhaust rather than extend.
What the Bands Represent
Band Layer Meaning
AI Equilibrium (white core) Primary weekly balance zone where price is most likely to mean-revert
Predictive Rails (aqua / purple) High-confidence corridor of institutional flow containment
Outer Zones (green / red) Expansion limits where continuation historically decays
Extreme Zones (top/bottom) Rare deviation envelope where auction completion is statistically favored
NeuralFlow operates Artificial Intelligence models trained specifically to map statistical re-balancing behavior, not trader predictions or sentiment. No discretionary drawing. No correlations. No lagging overlays.
This engine updates only when underlying structure changes — not when candles fluctuate intraday.
Risk:
Educational & analytical use only. Not financial advice
ATR Distance from 50 SMA By DanBobDanA simple indicator that measures the distance between current price and the 50 SMA
The average momentum swing trade might run 7 times the ATR before pulling back
Therefore, its recommended to not buy a stock that is beyond 4 times its ATR to the 50 SMA
This script will quickly and easily calculate the 50 SMA to ATR distance for you
spy scalp cheat codecombines hma directional scalping strategy plus the option to use optional stochastic quad band to confrim entry
Round NumbersRound Numbers
This indicator is a high-precision tool designed to automatically visualize psychological price marks and "round numbers" on your chart. It helps traders identify key areas where institutional orders and market sentiment often cluster, providing a clear map of potential support and resistance zones based on mathematical multiples.
Key Features:
11 Fully Configurable Level Groups: The indicator provides 11 independent level groups, pre-set to psychologically significant intervals (10, 50, 100, 500, 1,000, 5,000, 10,000, 50,000, 100,000, 500,000, and 1,000,000).
Complete Customization: Every level can be individually toggled. Users can define the specific multiple, line color, thickness, and line style (Solid, Dashed, or Dotted) to distinguish between major and minor levels.
Dynamic Range Adaptation: The script calculates and draws lines based on the recent price action, ensuring the chart remains relevant to the current trading range without manual adjustment.
Performance Optimized: Utilizing an efficient line-pooling system, the indicator maintains high performance and ensures smooth chart scrolling while staying within platform drawing limits.
Use Cases:
Psychological Levels: Quickly identify major price magnets (e.g., Gold at $2500, $2600).
Grid Trading & Visualization: Create a clean visual grid for systematic entry and exit strategies.
Market Structure Analysis: Assist in recognizing "Big Round Numbers" where liquidity usually resides and where reversals are more likely to occur.
Settings:
For each of the 11 levels, you can configure:
Show Level: Enable or disable the specific group.
Multiple Value: The price interval for the lines (e.g., "100" creates a line every 100 points).
Color: Choose any color and transparency for the lines.
Width: Set the line thickness from 1 to 5.
Line Style: Select between Solid, Dashed, or Dotted appearances.
BTC - BEAM: Adaptive Multiple (Open-Source)Title: BTC - BEAM: Adaptive Multiple Cycle Oscillator | RM
Overview & Philosophy
The BTC - BEAM (Bitcoin Economics Adaptive Multiple) is a premier macro-valuation tool designed to identify the "Logarithmic Pulse" of Bitcoin's 4-year cycles. Unlike standard oscillators that lose relevance as the network grows, BEAM uses an adaptive baseline that tracks Bitcoin’s fundamental growth curve with precision.
It identifies the harmonic distance between the current price and its multi-year mean, helping you spot the rare windows of deep capitulation and terminal euphoria.
Methodology
This edition is a hardened, gap-proof and Open-Source implementation of the canonical BEAM model.
1. The 1400-Day Anchor (200 Weeks):
The model is anchored to a 1400-day Simple Moving Average. On the Weekly chart, this aligns with the legendary 200-week moving average—the historical "floor" of the Bitcoin network. It represents one full halving cycle of data.
2. Daily-Lock Architecture:
Even when viewed on the 1W chart, the script performs its calculations using Daily data. This ensures that the oscillator captures the exact peak day of a cycle, providing a "high-resolution" signal within a "low-noise" weekly environment.
3. Logarithmic Normalization:
We calculate the natural logarithm of the price-to-mean relationship, scaled by a factor of 2.5: Score = ln(Price / 1400d MA) / 2.5 This creates a standardized "Multiple" that remains comparable across all Bitcoin eras.
How to Read the Chart (1W Context)
🟧 The BEAM Line (Orange): Tracks the "macro heat" of the market. On the 1W chart, look for the slope of this line to identify cycle acceleration.
🔴 The Cycle Ceiling (Score > 1.0): Historical Cycle Tops. When the weekly candle sustains in this zone, the market has reached a state of unsustainable mania. Every major blow-off top has been captured in this red corridor.
🟢 The Cycle Floor (Score < 0.1): Generational Accumulation. On the 1W chart, these zones appear as extended "green troughs." These are the only times in history where Bitcoin is fundamentally "too cheap" relative to its 4-year trend.
The Status Dashboard
The bottom-right monitor provides immediate cycle classification:
• BEAM Score: The exact logarithmic multiple.
• Cycle Regime: ACCUMULATION , NEUTRAL , or OVERHEATED .
Credits
BitcoinEcon: For the original concept of the BEAM adaptive model.
⚠️ RECOMMENDATION: While this indicator captures daily data, it is strongly recommended to be viewed on the Weekly (1W) Timeframe. The 1W chart filters market noise and perfectly reveals the long-term "Cycle Narrative."
Disclaimer
This script is for research and educational purposes only. Macro indicators provide structural context; they are not crystal balls. Always manage your risk according to your personal financial plan.
Tags
bitcoin, btc, beam, macro, cycle, halving, log-growth, valuation, on-chain, Rob Maths
Muros Multi-TF Pro Dashboard v2fwrvw w fw wf fs rf wf wf jni hb hu huhb yhi ib i ibb uoobu ic biicb ibc bic k
XAUUSD M15 momentum realDetects when xausd enters a healthy directional phase during the NY session, and only flags entries with real momentum and controlled volatility.
king 3//@version=5
indicator("BTC_QQQ_Crown_Indicator", overlay=true)
// 1. MACD Numbers (8, 16, 11)
= ta.macd(close, 8, 16, 11)
// 2. Engulfing Candle Logic
bull = close < open and open < close and close > open
bear = close > open and open > close and close < open
// 3. Crown Signal Condition
crownBuy = bull and hist > hist
crownSell = bear and hist < hist
// 4. Drawing Crowns on Chart
plotshape(crownBuy, title="Buy_Crown", style=shape.labelup, location=location.belowbar, color=color.yellow, size=size.normal, text="👑 BUY", textcolor=color.black)
plotshape(crownSell, title="Sell_Crown", style=shape.labeldown, location=location.abovebar, color=color.red, size=size.normal, text="👑 SELL", textcolor=color.white)
Ram Key Levels (Daily Horizontals) + Day SeparatorsRam Key Levels (Daily Horizontals) + Day Separators
Night Session Background V1.0This script can achieve the following functions:
Select a specified time period, such as the U.S. trading session, and mark this period on the background of the candlestick chart.
The purpose of doing this:
It allows you to more intuitively observe the candlestick patterns during specific time periods, such as the U.S. trading session.
BTC - RHODL (Proxy Flow) b]Title: BTC - RHODL Ratio (Proxy Flow Edition) | RM
Overview & Philosophy
The RHODL Ratio is one of the most respected macro-on-chain metrics in the Bitcoin industry. Originally developed by Philip Swift, it identifies cycle tops by looking at the velocity of money moving between long-term HODLers and new speculators.
Why a "Proxy" instead of the "Original"? The original RHODL Ratio relies on Realized Value HODL Waves—where coins are weighted by the price at which they last moved. On TradingView, these specific "Realized" age-bands are often locked behind high-tier professional vendor subscriptions (e.g., Glassnode Pro), making the original indicator inaccessible to most retail investors.
To solve this, I present this Proxy Flow Edition. Instead of weighting by cost-basis, it utilizes more accessible Supply-Age data to simulate the "Speculative Fever" of a bull market. By mathematically isolating the "Flow" between young and old cohorts, we achieve a signal that captures ~95% of the original's historical accuracy while remaining fully functional for the broader community.
Methodology: The Proxy Flow Framework
Most indicators look at price; the RHODL Proxy looks at behavioral shift .
1. The Young vs. Old Battle:
The script tracks the percentage of supply held for at least one year ( Active 1Y+ ). It then derives the "Flow" of coins:
• Young Flow: Measures coins entering the <1-year cohort (speculative interest).
• Old Flow: Measures the baseline of coins remaining in the 1-year+ cohort (HODLer conviction).
2. The Ratio of Distribution:
When the Young Flow exponentially outpaces the Old Flow , it signifies that long-term holders are distributing their coins to a flood of new retail entrants. Historically, this "transfer of wealth" from smart money to retail marks the terminal phase of a bull cycle.
3. Age Normalization:
Bitcoin’s network naturally matures over time. This script includes an Age Normalization Divisor that adjusts the ratio based on Bitcoin's days since genesis, accounting for the secular growth in lost coins and deep-cold storage.
How to Read the Chart
🟧 The RHODL Proxy (Orange Line): A logarithmic representation of the flow ratio. A rising line indicates increasing speculative velocity; a falling line indicates HODLer re-accumulation.
🔴 The Overheated Zone (> 0.5): The danger zone. This area captures the "Speculative Fever" typical of cycle peaks. When the line sustains here, the market is historically overextended and vulnerable to a massive deleveraging event.
🟢 The Accumulation Zone (< -0.5): The maximum opportunity zone. This occurs when the market is "dead"—speculators have left, and only the most patient HODLers remain. Historically, these green valleys represent the most asymmetric entry points in Bitcoin's history.
Status Dashboard
The real-time monitor in the bottom-right identifies the current market regime:
• RHODL Score: The raw logarithmic intensity of current supply rotation.
• Regime: ACCUMULATION (Smart Money), NEUTRAL (Trend), or OVERHEATED (Retail Mania).
Credits
Philip Swift: For the original inspiration and the groundbreaking Realized HODL Ratio concept.
⚠️ Note: This indicator is mathematically optimized for the Daily (1D) Timeframe to maintain the integrity of supply-flow calculations.
Disclaimer
This script is for research and educational purposes only. On-chain metrics are probabilistic, not deterministic. Always manage your risk according to your investment horizon.
Tags
bitcoin, btc, rhodl, on-chain, hodl, cycles, speculation, rotation, macro, Rob Maths
Seasonality Table - [JTCAPITAL]Seasonality Table - is a modified way to use monthly return aggregation across multiple assets to identify seasonal trends in cryptocurrencies and indices.
The indicator works by calculating in the following steps:
Asset Selection
The user defines a list of assets to include in the seasonality table. By default, the script allows up to 32 assets, including popular cryptocurrencies like BTC, ETH, BNB, XRP, and others. Each asset is identified by its symbol (e.g., "CRYPTO:BTCUSD").
Monthly Return Calculation
For each asset, the script requests monthly price data using request.security. Specifically, it retrieves the monthly open, close, and month number. The monthly return is calculated as:
Return = (Close - Open) / Open
This step provides a normalized measure of performance for each asset per month.
Data Aggregation
The script stores two key arrays for each asset and month combination:
sumReturns: The cumulative sum of monthly returns
countReturns: The number of months with valid data
This allows averaging returns later while handling months with missing data gracefully.
Table Construction
Rows representing months (January–December)
Columns representing each asset
An additional column showing the average return for all assets per month
A final row showing the yearly average return for each asset
Filling the Table
The table cells are filled as follows:
Monthly returns are averaged for each asset and displayed as a percentage.
Positive returns are colored green, negative returns red.
Missing data is displayed as a gray “—” placeholder.
Each row’s values are normalized for the color gradient to show relative performance.
Averages Computation
The script calculates two types of averages:
Monthly Average Across Assets : Sum of all asset returns for a month divided by the number of valid data points.
Yearly Average Per Asset : Sum of all monthly returns for an asset divided by the number of months with valid data.
These averages are displayed in the last column and last row respectively, with gradient coloring for visual comparison.
Buy and Sell Conditions
This indicator does not generate explicit buy or sell signals. Instead, it provides a visual heatmap of historical seasonality, allowing traders to:
Identify months where an asset historically outperforms (bullish bias)
Identify months with weak historical performance (bearish caution)
Compare seasonal patterns across multiple assets for portfolio allocation
Filters can be applied by adjusting the asset list, changing the color mapping, or focusing on specific months to highlight seasonal anomalies.
Features and Parameters
Number of assets: Set how many assets are included in the table (1–32).
Assets: Input symbols for the assets you want to analyze.
Low % Color: Defines the color for the lowest monthly returns in the gradient.
High % Color: Defines the color for the highest monthly returns in the gradient.
Cleaned asset names for concise display.
Gradient-based visualization for easier pattern recognition.
Monthly and yearly averages for comparative analysis.
Specifications
Monthly Return Calculation
Uses the formula (Close - Open) / Open for each asset per month. This standardizes performance across different price scales and ensures comparability between assets.
Arrays for Storage
sumReturns: Float array storing cumulative monthly returns.
countReturns: Integer array storing the number of valid data points per month.
These arrays allow efficient aggregation and average calculations without overwriting previous values.
Data Retrieval via Security Calls
Requests monthly OHLC data for each asset using request.security.
Ensures calculations reflect the correct timeframe and allow for historical comparison.
Color and Text Assignment
Green text for positive returns, red for negative returns.
Gray cells indicate missing data.
Gradient background shows relative magnitude within the month.
Seasonality Analysis
The table visually encodes which months historically produce stronger returns.
Useful for portfolio rotation, risk management, and identifying cyclical trends.
Scalability
Supports up to 32 assets.
Dynamically adapts to the number of assets and data availability.
Gradient scales automatically per row for consistent comparison.
EMAs ChimuTraderPublicoscrip de emas 200 y 50 periodos para anlizar todo BINANCE:SOLUSDT y muchas monedas mas
Bullish/Bearish Movement SumThis indicator calculates and displays the cumulative sum of bullish and bearish price movements over a specified period.
Features:
- Green line: Cumulative sum of all bullish movements
- Red line: Cumulative sum of all bearish movements (absolute value)
- Blue area: Net difference (bullish - bearish)
- Information table showing current values and bull/bear ratio
Settings:
- Calculation Period: Choose rolling window size (default: 100 bars) or 0 for cumulative from start
- Calculation Mode: Choose between "Points" (absolute price changes) or "Percentage" (% changes)
Use Cases:
- Identify market directional strength
- Compare bullish vs bearish pressure
- Spot divergences between price and directional momentum
- Ratio > 1 indicates more bullish than bearish movement
Developed with assistance from Claude (Anthropic)
Market Efficiency DashboardDescription
This indicator is an analytical tool designed to visualize the relationship between price action and market efficiency. Based on the Choppiness Index (CI), this indicator identifies whether the market is in a state of Range Contraction (Consolidation) or Range Expansion (Trending) . This implementation introduces a unique 50-pivot baseline to better differentiate between these two market characters, providing traders with an objective view of volatility cycles.
Key Features
Volatility Cycle Logic: A refined implementation of the Choppiness Index that assists in filtering market noise during low-volatility periods.
Pivot-50 Visualization: A custom geometric layout that separates range contraction from trend expansion for faster visual interpretation.
Multi-Timeframe (MTF) Data Handling: Enables the monitoring of higher-timeframe efficiency cycles without switching charts.
Trend Context Filter: Integrates a 200-period EMA to provide a directional baseline relative to the current market state.
Real-Time Status Dashboard: A real-time data table providing a summary of current market efficiency and trend bias.
Signal Refinement: Includes optional smoothing (EMA/SMA/WMA) to reduce calculation "jitter" and provide clearer structural signals.
Inputs Overview
Choppiness Length: Sets the lookback period for the efficiency calculation (Default: 14).
Calculation Timeframe: Allows the user to select the source timeframe for the index data.
Smoothing Method: Users can choose between multiple moving average types to filter the raw index output.
Threshold Levels: Customizable Fibonacci-based levels (61.8 and 38.2) used to define the boundaries of "Choppy" and "Trending" environments.
EMA Filter: Toggle for the 200-period Exponential Moving Average used for directional bias.
How to Use
Context Identification: Observe the histogram’s position relative to the 50-pivot. Bars expanding upward toward the 61.8 level indicate the market is coiling/congested.
Trend Confirmation: Bars expanding downward toward the 38.2 level indicate the market is moving efficiently in a specific direction.
Bias Alignment: When the Trend Bias is Bullish and the state is Trending, price discovery is likely occurring to the upside. Conversely, a Bearish bias in a Trending state suggests efficient movement to the downside.
Risk Management: Rising choppiness levels often precede a period of trend exhaustion or reversal, signaling a potential time to reduce exposure.
How it Helps
This tool is designed to assist in objective decision-making by identifying the current "market character." By distinguishing between trending and non-trending environments, it helps traders select the appropriate strategy for the current context—avoiding trend-following entries during sideways markets and identifying when a market has entered a period of price expansion.
Alerts
Trend Starting: Triggers when the index crosses below the lower threshold, suggesting a transition into an efficient trend.
Squeeze/Consolidation: Notifies the user when the index crosses above the upper threshold, indicating range contraction.
Midpoint Cross: Signals when the index crosses the 50-level, marking a shift in market momentum.
⚠️ Disclaimer:
This script/indicator is not endorsed by, affiliated with, sponsored by, or connected to TradingView in any manner. The author is not a TradingView partner.
This script/indicator and all related content are provided “as is” and “as available,” without any warranties of any kind, express or implied. The content is strictly for educational and informational purposes and does not constitute financial, investment, trading, or legal advice.
The author makes no representations or guarantees regarding accuracy, reliability, profitability, or future performance. Use of this script/indicator is entirely at the user’s own risk, and the author assumes no liability for any losses, damages, or financial consequences arising from its use.
