HTF Live View - GSK-VIZAG-AP-INDIA📘 HTF Live View — GSK-VIZAG-AP-INDIA
🧩 Overview
The HTF Live View indicator provides a real-time visual representation of higher-timeframe (HTF) candle structures — such as 15min, 30min, 1H, 4H, and Daily — all derived directly from live 1-minute data.
This allows traders to see how higher timeframe candles are forming within the current session — without switching chart timeframes.
⚙️ Core Features
📊 Live Multi-Timeframe OHLC Tracking
Continuously calculates and displays Open, High, Low, and Close values for each key timeframe (15m, 30m, 1H, 4H, and Daily) based on the ongoing session.
⏱ Session-Aware Calculation
Automatically syncs with market hours defined by user-selected start and end times. Works across multiple timezones for global compatibility.
🕹 Visual Candle Representation
Draws mini-candles on the chart for each higher timeframe to represent their current body and wick — updated live.
Green body → bullish development
Red body → bearish development
📅 Informative Table Panel
Displays a summary table showing:
Timeframe label
Period (start–end time)
Live OHLC values
Color-coded close values
🌍 Timezone Support
Fully compatible with common regions such as Asia/Kolkata, New York, London, Tokyo, and Sydney.
🔧 User Inputs
Parameter Description
Market Start Hour/Minute Define session start time (default: 09:15)
Session End Hour/Minute Define market close (default: 15:30)
Timezone Select your preferred timezone for session alignment
💡 How It Works
The indicator uses a rolling OHLC calculation function that dynamically computes candle values based on elapsed session time.
Each timeframe (15m, 30m, 1H, 4H, and Daily) is built from 1-minute data to maintain precision even during intraday updates.
Both a visual representation (candles and wicks) and a data table (numeric summary) are displayed for clarity.
🧠 Use Cases
Monitor how HTF candles are forming live without switching chart intervals.
Understand intraday structure shifts (e.g., when 1H turns from red to green).
Confirm trend alignment across multiple timeframes visually.
Combine with your volume, delta, or liquidity tools for deeper confluence.
🪶 Signature
Developed by GSK-VIZAG-AP-INDIA
© prowelltraders — Educational and analytical use only.
⚠️ Disclaimer
This indicator is for educational and informational purposes only.
It does not provide financial advice or guaranteed trading results.
Always perform your own analysis before making investment decisions.
Statistics
Volume Sampled Supertrend [BackQuant]Volume Sampled Supertrend
A Supertrend that runs on a volume sampled price series instead of fixed time. New synthetic bars are only created after sufficient traded activity, which filters out low participation noise and makes the trend much easier to read and model.
Original Script Link
This indicator is built on top of my volume sampling engine. See the base implementation here:
Why Volume Sampling
Traditional charts print a bar every N minutes regardless of how active the tape is. During quiet periods you accumulate many small, low information bars that add noise and whipsaws to downstream signals.
Volume sampling replaces the clock with participation. A new synthetic bar is created only when a pre-set amount of volume accumulates (or, in Dollar Bars mode, when pricevolume reaches a dollar threshold). The result is a non-uniform time series that stretches in busy regimes and compresses in quiet regimes. This naturally:
filters dead time by skipping low volume chop;
standardizes the information content per bar, improving comparability across regimes;
stabilizes volatility estimates used inside banded indicators;
gives trend and breakout logic cleaner state transitions with fewer micro flips.
What this tool does
It builds a synthetic OHLCV stream from volume based buckets and then applies a Supertrend to that synthetic price. You are effectively running Supertrend on a participation clock rather than a wall clock.
Core Features
Sampling Engine - Choose Volume buckets or Dollar Bars . Thresholds can be dynamic from a rolling mean or median, or fixed by the user.
Synthetic Candles - Plots the volume sampled OHLC candles so you can visually compare against regular time candles.
Supertrend on Synthetic Price - ATR bands and direction are computed on the sampled series, not on time bars.
Adaptive Coloring - Candle colors can reflect side, intensity by volume, or a neutral scheme.
Research Panels - Table shows total samples, current bucket fill, threshold, bars-per-sample, and synthetic return stats.
Alerts - Long and Short triggers on Supertrend direction flips for the synthetic series.
How it works
Sampling
Pick Sampling Method = Volume or Dollar Bars.
Set the dynamic threshold via Rolling Lookback and Filter (Mean or Median), or enable Use Fixed and type a constant.
The script accumulates volume (or pricevolume) each time bar. When the bucket reaches the threshold, it finalizes one or more synthetic candles and resets accumulation.
Each synthetic candle stores its own OHLCV and is appended to the synthetic series used for all downstream logic.
Supertrend on the sampled stream
Choose Supertrend Source (Open, High, Low, Close, HLC3, HL2, OHLC4, HLCC4) derived from the synthetic candle.
Compute ATR over the synthetic series with ATR Period , then form upperBand = src + factorATR and lowerBand = src - factorATR .
Apply classic trailing band and direction rules to produce Supertrend and trend state.
Because bars only come when there is sufficient participation, band touches and flips tend to align with meaningful pushes, not idle prints.
Reading the display
Synthetic Volume Bars - The non-uniform candles that represent equal information buckets. Expect more candles during active sessions and fewer during lulls.
Volume Sampled Supertrend - The main line. Green when Trend is 1, red when Trend is -1.
Markers - Small dots appear when a new synthetic sample is created, useful for aligning activity cycles.
Time Bars Overlay (optional) - Plot regular time candles to compare how the synthetic stream compresses quiet chop.
Settings you will use most
Data Settings
Sampling Method - Volume or Dollar Bars.
Rolling Lookback and Filter - Controls the dynamic threshold. Median is robust to outliers, Mean is smoother.
Use Fixed and Fixed Threshold - Force a constant bucket size for consistent sampling across regimes.
Max Stored Samples - Ring buffer limit for performance.
Indicator Settings
SMA over last N samples - A moving average computed on the synthetic close series. Can be hidden for a cleaner layout.
Supertrend Source - Price field from the synthetic candle.
ATR Period and Factor - Standard Supertrend controls applied on the synthetic series.
Visuals and UI
Show Synthetic Bars - Turn synthetic candles on or off.
Candle Color Mode - Green/Red, Volume Intensity, Neutral, or Adaptive.
Mark new samples - Puts a dot when a bucket closes.
Show Time Bars - Overlay regular candles for comparison.
Paint candles according to Trend - Colors chart candles using current synthetic Supertrend direction.
Line Width , Colors , and Stats Table toggles.
Some workflow notes:
Trend Following
Set Sampling Method = Volume, Filter = Median, and a reasonable Rolling Lookback so busy regimes produce more samples.
Trade in the direction of the Volume Sampled Supertrend. Because flips require real participation, you tend to avoid micro whipsaws seen on time bars.
Use the synthetic SMA as a bias rail and trailing reference for partials or re-entries.
Breakout and Continuation
Watch for rapid clustering of new sample markers and a clean flip of the synthetic Supertrend.
The compression of quiet time and expansion in busy bursts often makes breakouts more legible than on uniform time charts.
Mean Reversion
In instruments that oscillate, faded moves against the synthetic Supertrend are easier to time when the bucket cadence slows and Supertrend flattens.
Combine with the synthetic SMA and return statistics in the table for sizing and expectation setting.
Stats table (top right)
Method and Total Samples - Sampling regime and current synthetic history length.
Current Vol or Dollar and Threshold - Live bucket fill versus the trigger.
Bars in Bucket and Avg Bars per Sample - How much time data each synthetic bar tends to compress.
Avg Return and Return StdDev - Simple research metrics over synthetic close-to-close changes.
Why this reduces noise
Time based bars treat a 5 minute print with 1 percent of average participation the same as one with 300 percent. Volume sampling equalizes bar information content. By advancing the bar only when sufficient activity occurs, you skip low quality intervals that add variance but little signal. For banded systems like Supertrend, this often means fewer false flips and cleaner runs.
Notes and tips
Use Dollar Bars on assets where nominal price varies widely over time or across symbols.
Median filter can resist single burst outliers when setting dynamic thresholds.
If you need a stable research baseline, set Use Fixed and keep the threshold constant across tests.
Enable Show Time Bars occasionally to sanity check what the synthetic stream is compressing or stretching.
Link again for reference
Original Volume Based Sampling engine:
Bottom line
When you let participation set the clock, your Supertrend reacts to meaningful flow instead of idle prints. The result is a cleaner state machine, fewer micro whipsaws, and a trend read that respects when the market is actually trading.
Options Position Size CalculatorOptions Position Size Calculator
Automate your options position sizing directly on the chart.
This indicator calculates the optimal number of options contracts to buy based on your risk management parameters, entry price, stop loss, and expected options decay.
📋 What It Does
Eliminates the need for external calculators by computing your position size directly on TradingView. Simply set your entry and stop loss prices, configure your risk parameters, and the indicator instantly shows you how many contracts to buy.
✨ Key Features
Visual Price Lines: Set entry and stop loss prices with draggable horizontal lines
Custom Loss Table: Input your own options loss percentages for distances from 0.1% to 1.5% (with interpolation between values)
Automatic Calculations: Calculates distance to stop loss, expected options loss, dollar risk, and final contract quantity
Live Display: All calculations shown in a clean info box on your chart
Accounts for Contract Multiplier: Correctly factors in the standard 100x options multiplier
🎯 How to Use
1. Configure Settings First
Add the indicator to your chart (set any initial prices when prompted)
Open indicator Settings (gear icon)
Enter your Portfolio Size (e.g., $10,000)
Set Risk Percentage (e.g., 2%)
Enter the Contract Price (the premium per contract, e.g., $1.50)
2. Fill Your Options Loss Table
This is crucial - you must input your own data
For each distance (0.1%, 0.2%, up to 1.5%), enter the expected % loss your options will suffer
Base this on your strategy (calls/puts), strike selection, and expiration
Use historical data from your trades or an options calculator
Example: If underlying moves 0.5% to your stop, your option might lose 30%
3. Set Entry & Stop Loss on Chart
Go back to indicator settings
Adjust Entry Price and Stop Loss Price to match your trade setup
The indicator calculates your position size instantly
4. Read Results
The indicator displays:
Distance to stop loss (%)
Expected options loss (%)
Dollar risk amount
CONTRACTS TO BUY - your position size
📊 Example
Portfolio: $10,000 | Risk: 2% | Entry: $150 | Stop: $149 (0.67% distance)
Expected loss: 38% | Contract price: $2.00
→ Buy 2 contracts
⚠️ Important
Your loss table values depend on your specific options strategy, strike, DTE, and IV
Different strategies require different loss tables
This is for educational purposes - always verify calculations
Never risk more than you can afford to lose
Made by traders, for traders. Trade safe, size smart.
Extreme Candle Pattern Visualizer🟠 OVERVIEW
This indicator compares the current candle's percentage change against historical data, then highlights past candles with equal or bigger magnitude of movement. Also, for all the highlighted past candles, it tracks how far price extends before recovering to its starting point. It also provides statistical context through percentile rankings.
IN SHORT: Quickly spot similar price movements in the past and understand how unusual the current candle is using percentile rankings.
🟠 CORE CONCEPT
The indicator operates on two fundamental principles:
1. Statistical Rarity Detection
The script calculates the percentage change (open to close) of every candle within a user-defined lookback period and determines where the current candle ranks in this distribution. A candle closing at -9% might fall in the bottom 5th percentile, indicating it's more extreme than 95% of recent candles. This percentile ranking helps traders identify statistically unusual moves that often precede reversals or extended trends.
2. Recovery Path Mapping
Once extreme candles are identified (those matching or exceeding the current candle's magnitude), the indicator tracks their subsequent price action. For bearish candles, it measures how far price dropped before recovering back to the candle's opening price. For bullish candles, it tracks how high price climbed before returning to the open. This reveals whether extreme moves typically extend further or reverse quickly.
🟠 PRACTICAL APPLICATIONS
Mean Reversion Trading:
Candles in extreme percentiles (below 10% or above 90%) often signal oversold/overbought conditions. The recovery lines show typical extension distances, helping traders set profit targets for counter-trend entries.
Momentum Continuation:
When extreme candles show small recovery percentages before price reverses back, it suggests strong directional momentum that may continue.
Stop Loss Placement:
Historical recovery data reveals typical extension ranges after extreme moves, informing more precise stop loss positioning beyond noise but before major reversals.
Pattern Recognition:
By visualizing how similar historical extremes resolved, traders gain context for current price action rather than trading in isolation.
🟠 VISUAL ELEMENTS
Orange Circles: Mark historical candles with similar or greater magnitude to current candle
Red Lines: Track downward extensions after bearish extreme candles
Green Lines: Track upward extensions after bullish extreme candles
Percentage Labels: Show exact extension distance from candle close to extreme point
Percentile Label: Color-coded box displaying current candle's statistical ranking
Hollow Candles: Background rendering for clean chart presentation
🟠 ORIGINALITY
This indicator uniquely combines statistical percentile analysis with forward-looking recovery tracking. While many indicators identify extreme moves, few show what happened next across multiple historical instances simultaneously. The dual approach provides both the "how rare is this?" question (percentile) and "what typically happens after?" answer (recovery paths) in a single visual framework.
MomentumQ Sector MatrixMomentumQ Sector Matrix — Multi-Timeframe & Sector Performance Dashboard
The MomentumQ Sector Matrix is a professional dashboard-style indicator designed to help traders quickly evaluate sector performance and momentum alignment across multiple timeframes.
It provides an instant visual snapshot of how each major U.S. sector is performing, helping traders identify strength, weakness, and rotation trends without switching between charts.
What It Does
MomentumQ Sector Matrix consolidates multi-timeframe return data (1-Month, 1-Week, and 1-Day) into a clean, color-coded table.
Each sector’s cell displays percentage performance, automatically colored green or red based on relative gains or losses.
This tool serves as a sector rotation map , letting traders:
Spot which parts of the market are leading or lagging
Track momentum alignment across monthly, weekly, and daily timeframes
Instantly identify broad market conditions (risk-on vs. risk-off)
Key Features
1. Multi-Timeframe Sector Overview
Displays percentage returns for major SPDR sectors on 1-Month, 1-Week, and 1-Day bases.
Toggle between Today and PrevD (previous day) return modes.
2. Adaptive Table Layout
Fully resizable — choose Small, Medium, or Large table sizes for the best fit on your chart.
Works seamlessly with both light and dark TradingView themes.
3. Light / Dark Mode Support
Switch between modes to automatically match your chart background.
4. Performance-Based Coloring
Green for positive returns, red for negative, gray for neutral.
Provides clear visual contrast even in compact layouts.
5. Instant Market Context
Gain quick insight into overall market strength or weakness.
Ideal for top-down analysis, ETF rotation strategies, and macro confirmation.
How to Use
Add the indicator to any chart (symbol-independent).
Choose your preferred table position and size in the settings panel.
Use 1M / 1W / 1D readings to align your trading bias with higher-timeframe context.
Why It’s Valuable
Consolidates sector analysis into a single, easy-to-read dashboard
Helps identify macro trends and sector leadership quickly
Supports both swing and intraday trading approaches
Complements existing momentum or regime-tracking systems
Disclaimer
This indicator is a technical analysis tool for educational and informational purposes only.
It does not constitute financial advice and does not guarantee profitability.
Always perform your own analysis and use proper risk management.
OOO Trade (By Bodinphat) V.2Description:
This indicator is an advanced trend-following system that combines multi-timeframe signals, order block zones (OB Zones), and precision-based metrics to help traders identify high-probability buy and sell opportunities.
It automatically analyzes EMA trends, RSI pullbacks, ADX strength, and volume confirmation to calculate a dynamic confidence score for both long and short directions.
The system also displays:
📊 Multi-Timeframe Trend Strip (M1 → D1) — showing each timeframe’s directional bias (Buy/Sell/Neutral).
🎯 OB Zones (Order Blocks) — highlights institutional demand (Bullish OB) and supply (Bearish OB) zones on the chart.
📋 Right-Side Info Panel — displays key metrics such as score, accuracy, SL/TP targets, and bias direction in real-time.
⚡ Session Filters — optional London/NY session filters for more accurate signal alignment.
This tool is ideal for traders who want to follow structured price action while maintaining a clear view of market strength and institutional zones.
It works best with XAUUSD, GBPUSD, and major indices on intraday or swing timeframes.
OOO Trade (By Bodinphat)Script Description (for TradingView Publish Page)
Description:
This indicator is an advanced trend-following system that combines multi-timeframe signals, order block zones (OB Zones), and precision-based metrics to help traders identify high-probability buy and sell opportunities.
It automatically analyzes EMA trends, RSI pullbacks, ADX strength, and volume confirmation to calculate a dynamic confidence score for both long and short directions.
The system also displays:
📊 Multi-Timeframe Trend Strip (M1 → D1) — showing each timeframe’s directional bias (Buy/Sell/Neutral).
🎯 OB Zones (Order Blocks) — highlights institutional demand (Bullish OB) and supply (Bearish OB) zones on the chart.
📋 Right-Side Info Panel — displays key metrics such as score, accuracy, SL/TP targets, and bias direction in real-time.
⚡ Session Filters — optional London/NY session filters for more accurate signal alignment.
This tool is ideal for traders who want to follow structured price action while maintaining a clear view of market strength and institutional zones.
It works best with XAUUSD, GBPUSD, and major indices on intraday or swing timeframes.
Disclaimer:
This indicator is for educational and informational purposes only.
It does not constitute financial advice. Please test thoroughly before using in live trading.
Michal D. Lagless Moving Average | MisinkoMasterThe 𝕸𝖎𝖈𝖍𝖆𝖑 𝕯. 𝕷𝖆𝖌𝖑𝖊𝖘𝖘 𝕸𝖔𝖛𝖎𝖓𝖌 𝕬𝖛𝖊𝖗𝖆𝖌𝖊 is my latest creation of a trend following tool, which is a bit different from the rest. By trying to de-lag the classical moving average, it gives you fast signals on changes in trend as fast as possible, keeping traders & investors always in check for potential risks they might want to avoid.
How does it work?
First we need to calculate lengths. The lengths are calcuted using a user defined input called the "Length Multiplier" and we of course need as well the length input too.
The indicator uses 10 lengths, 5 for an average price, 5 for median price.
The length for the average is the following:
length_2_avg = length_1_avg * length_multiplier
length_3_avg = length_2_avg * length_multiplier
...
and for the median lengths:
length_1_median = length_2_avg
length_2_median = length_3_avg
Here applies this rule
length_x_median < length_x_avg
This is intentional, and it is because the average is a little more reactive, while the median is a bit slower. To make up for the "slowness" of the median, we simple reduce the length of it a bit more than the average.
Now that we have our length we are ready to calculate averages and medians over their respective period. This is the a normal average from elementary school, nothing too fancy.
Now that we have all of them we match the pairs using another user defined input called "Median Weight" like so:
(Average_x * (2-median_weight) + Median_x * median_weight)/2
This gives more weight to the average (also due to the max value limit set to avoid breaking the fundational logic behind it).
After doing it to all the pairs we now average those pairs using another input called "Exponential Weight Multiplier".
The Exponential Weight Multiplier is used for weights which I will cover soon:
weight1 = weight
weight2 = weight * weight
weight3 = weight * weight * weight....
This is done until we have all the weights calculated
This gives exponentially more weight to the less lagging indicators, which is how we delag the indicator.
Then we sum all the pairs like so:
sum = pair1 * weight1 + pair2 * weight2 + pair3 * weight3 + pair4 * weight4 + pair5 * weight5
Then the sum is divided by the sum of weights, this results in us getting the final value.
Methodology & What is the actual point & how was it made?
I want to cover this one a bit deeper:
The methodology behind this was creating an indicator that would not be lagging, and would be able to avoid lag while not producing signals too often.
In many attempts in the first part, I tried using EMA, RMA, DEMA, TEMA, HMA, SMA and so on, but they were too noisy (except for SMA & RMA, but those had their flaws), so I tried the classical average taught in elementary school. This one worked better, but the noise was too high still after all this time. This made me include the median, which helped the noise, but made it far too lagging.
Here came the idea of making the median length lower and adding weights to counter the lag of the median, but it was still too lagging. This made me make the weights for lengths more exponential, while previously they were calculated using a little bit amplified sums that were alright, but nowhere near my desired result.
Using the new weights I got further, and after a bit of testing I was sattisfied with the results.
The logic for the trend was a big part in my development part, there were many I could think of, but not enough time to try them, so I stuck to the usual one, and I leave it up to YOU to beat my trend logic and get even better results.
Use Cases:
- Price/MA Crossovers
Simple, effective, useful
- Source for other indicators
This I tried myself, and it worked in a cool way, making the signals of for example RSI much smoother, so definitely try it out if you know how to code, or just simply put it in the source of the RSI.
- ROC
This trend logic stuck with me, I think you could find a way to make it good, but mainly for the people that can code in pine, trying out to combine the trend logic with ROC could work very well, do not sleep on it!
- Education
This concept is not really that complex, so for people looking for new ideas, inspiration, or just watching how trend following tools behave in general this is something that could benefit anyone, as the concept can be applied to ANYTHING, even the classical RSI, MACD, you could try even the Parabolic SAR, maybe STC or VZO, there is no limit to imagination.
- Strategy creation
Filtering this indicator with "and" conditions, or maybe even "or" or anything really could be very useful in a strategy that desires fast signals.
- Price Distance from bands
I noticed this while looking at past performance:
The stronger the trend the higher the distance from the Moving Average.
Final Notes
Watch out for mean reverting markets, as this is trend following you could get easily screwed in them.
Play around with this if it fits your desired outcome, you might find something I did not.
Hope you find it useful,
See you next time!
Stochastic %K Colored by VolumeDescription:
"Stochastic %K Colored by Volume is a technical indicator that combines the traditional Stochastic %K oscillator with volume-based coloring. It highlights periods of high, low, and neutral trading volume by changing the color of the %K line. Additionally, it identifies bullish and bearish divergences between price and the %K oscillator, helping traders spot potential reversals and trend changes. The indicator also includes key levels for overbought, oversold, and extreme zones to guide trading decisions."
Markov Chain Regime & Next‑Bar Probability Forecast✨ What it is
A regime-aware, math-driven panel that forecasts the odds for the very next candle. It shows:
• P(next r > 0)
• P(next r > +θ)
• P(next r < −θ)
• A 4-bucket split of next-bar outcomes (>+θ | 0..+θ | −θ..0 | <−θ)
• Next-regime probabilities: Calm | Neutral | Volatile
🧠 Why the math is strong
• Markov regimes: Markets cluster in volatility “moods.” We learn a 3-state regime S∈{Calm, Neutral, Volatile} with a transition matrix A, where A = P(Sₜ₊₁=j | Sₜ=i).
• Condition on the future state: We estimate event odds given the next regime j—
q_pos(j)=P(rₜ₊₁>0 | Sₜ₊₁=j), q_gt(j)=P(rₜ₊₁>+θ | Sₜ₊₁=j), q_lt(j)=P(rₜ₊₁<−θ | Sₜ₊₁=j)—
and mix them with transitions from the current (or frozen) state sNow:
P(event) = Σⱼ A · q(event | j).
This mixture-of-regimes view (HMM-style one-step prediction) ties next-bar outcomes to where volatility is likely headed.
• Statistical hygiene: Laplace/Beta smoothing, minimum-sample gating, and unconditional fallbacks keep estimates stable. Heavy computations run on confirmed bars; “Freeze at close” avoids intrabar flicker.
📊 What each value means
• Regime label & background: 🟩 Calm, 🟧 Neutral, 🟥 Volatile — quick read of market context.
• P(next r > 0): Directional tilt for the very next bar.
• P(next r > +θ): Odds of an outsized positive move beyond θ.
• P(next r < −θ): Odds of an outsized negative move beyond −θ.
• Partition row: Distributes next-bar probability across four intuitive buckets; they ≈ sum to 100%.
• Next Regime Probs: Likelihood of switching to Calm/Neutral/Volatile on the next bar (row of A for the current/frozen state).
• Samples row: How many next-bar samples support each next-state estimate (a confidence cue).
• Smoothing α: The Laplace prior used to stabilize binary event rates.
⚙️ Inputs you control
• Returns: Log (default) or %
• Include Volume (z-score) + lookback
• Include Range (HL/PrevClose)
• Rolling window N (transitions & estimates)
• θ as percent (e.g., 0.5%)
• Freeze forecast at last close (recommended)
• Display toggles (plots, partition, samples)
🎯 How to use it
• Volatility awareness & sizing: Rising P(next regime = Volatile) → consider smaller size, wider stops, or skipping marginal entries.
• Breakout preparation: Elevated P(next r > +θ) highlights environments where range expansion is more likely; pair with your setup/trigger.
• Defense for mean-reversion: If P(next r < −θ) lifts while you’re late long (or P(next r > +θ) lifts while late short), tighten risk or wait for better context.
• Calibration tip: Start θ near your market’s typical bar size; adjust until “>+θ” flags truly meaningful moves for your timeframe.
📝 Method notes & limits
Activity features (|r|, volume z, range) are standardized; only positive z’s feed the composite activity score. Estimates adapt to instrument/timeframe; rare regimes or small windows increase variance (hence smoothing, sample gating, fallbacks). This is a context/forecast tool, not a standalone signal—combine with your entry/exit rules and risk management.
🧩 Strategies too
We also develop full strategy versions that use these probabilities for entries, filters, and position sizing. Like this publication if you’d like us to release the strategy edition next.
⚠️ Disclaimer
Educational use only. Not financial advice. Markets involve risk. Past performance does not guarantee future results.
Opening Range Fibonacci Extensions (ATR Adjusted)this script displays daily, weekly, or monthly range extensions as a function of ATR in a Fibonacci retracement
Simple Custom Watermark & Symbol Info ジAdd a clean, configurable watermark to any chart. This lightweight indicator displays a custom name or brand plus optional symbol, timeframe, and current date in any corner of the chart. Perfect for traders, streamers, analysts, and content creators who want consistent chart branding, fast timestamps, or tidy screenshots.
Key features
Custom watermark text (brand, username, or logo text)
Toggle display of Symbol, Timeframe, and Date
Choose position: Top/Bottom × Left/Center/Right
Text color, background color (with alpha) and text size (small/normal/large)
Ultra-light, overlay-only — no chart clutter or extra objects
Why use it
Professionalize screenshots and shared charts with consistent branding
Add automatic timestamps to charts for auditability or content posts
Useful for streaming, educational content, reports, or trading journals
Minimal footprint keeps the chart readable while adding essential metadata
How traders use it
Add your name/handle for attribution on social posts
Show timeframe & symbol automatically when switching charts
Use date stamp for sessions, reports, and evidence of analysis timing
Built for clarity, speed, and clean visuals. Simple to configure — drop it on any chart and customize the watermark to match your workflow.
SJA WINFUT B3-10
INDICATOR FOR WINFUT B3 – 5-minute chart.
This indicator was designed to trade the Bovespa index futures contract (WINFUT) on the 5-minute chart.
It integrates technical analysis and macroeconomic context elements.
It combines several indicators in which the system calculates a score weighted by color and intensity for each indicator, generating a metric called “STRENGTH %,” which reflects the dominance of buyers (green), sellers (red), or sideways movement (orange) at the moment.
The calculation is adapted to market hours:
Between 9:00 a.m. and 9:59 a.m., it considers only the available indicators; after 10:00 a.m., it uses all data.
The panel displays real-time information, including divergences between strength and price, providing robust decision support for short-term operations on the mini index.
Buying trend.
The more green indicators (at the top of the panel) and dark blue indicators (at the bottom of the panel) and the higher the strength percentage, the greater the probability of buying.
Selling trend.
The more red indicators (at the top of the panel) and dark blue indicators (at the bottom of the panel) and the higher the strength percentage, the greater the probability of selling.
Translated with DeepL.com (free version)
SJA WINFUT B3-BRINDICATOR FOR WINFUT B3 – 5-minute chart.
This indicator was designed to trade the Bovespa index futures contract (WINFUT) on the 5-minute chart.
It integrates technical analysis and macroeconomic context elements.
It combines several indicators in which the system calculates a score weighted by color and intensity for each indicator, generating a metric called “STRENGTH %,” which reflects the dominance of buyers (green), sellers (red), or sideways movement (orange) at the moment.
The calculation is adapted to market hours:
Between 9:00 a.m. and 9:59 a.m., it considers only the available indicators; after 10:00 a.m., it uses all data.
The panel displays real-time information, including divergences between strength and price, providing robust decision support for short-term operations on the mini index.
Buying trend.
The more green indicators (at the top of the panel) and dark blue indicators (at the bottom of the panel) and the higher the strength percentage, the greater the probability of buying.
Selling trend.
The more red indicators (at the top of the panel) and dark blue indicators (at the bottom of the panel) and the higher the strength percentage, the greater the probability of selling.
Bollinger Bands %b Trend | DextraOverview
The Bollinger Bands %b Trend | Dextra is a custom technical indicator designed to enhance trend identification using the Bollinger Bands %b concept. This indicator calculates the percentage position of the price relative to the Bollinger Bands and uses customizable thresholds to determine bullish or bearish trends. It integrates dynamic candle coloring and a clear visual representation to assist traders in making informed decisions.
Key Features
- Bollinger Bands %b Calculation: Measures the price's position between the upper and lower Bollinger Bands as a percentage, providing a normalized view of overbought or oversold conditions.
- Trend Detection: Identifies uptrends and downtrends based on user-defined thresholds, offering a straightforward trend-following approach.
- Dynamic Candle Coloring: Colors candles according to the detected trend (green for uptrend, magenta for downtrend, gray for neutral), enhancing visual trend analysis.
- Customizable Parameters: Allows adjustment of length, standard deviation multiplier, and trend thresholds to suit various market conditions and trading styles.
How It Works
1. Bollinger Bands Calculation:
- The indicator uses an Exponential Moving Average (EMA) as the basis, calculated with a user-defined `length` (default 34).
- Upper and lower bands are derived by adding and subtracting a multiple of the standard deviation (`mult`, default 2.0) from the EMA.
- The %b value is computed as `(src - lower) / (upper - lower)`, where `src` is the price source (default `close`).
2. Trend Identification:
- An uptrend is detected when %b exceeds the `upperthreshold` (default 0.75).
- A downtrend is detected when %b falls below the `lowerthreshold` (default 0.26).
- The trend state is maintained until a new threshold condition is met.
3. Visualization:
- The %b line is plotted with a color reflecting the trend (green for uptrend, magenta for downtrend, gray for neutral).
- Horizontal dashed lines mark the uptrend and downtrend thresholds for reference.
- Candles are colored to match the trend, providing an overlay visualization on the price chart.
Customization Options
- Length: Adjust the EMA and standard deviation period (default 34, min 1).
- Source: Select the price data source for calculations (default `close`).
- StdDev: Set the standard deviation multiplier for band width (default 2.0, range 0.001 to 50).
- Uptrend Threshold: Define the %b level for uptrend detection (default 0.75, step 0.01).
- Downtrend Threshold: Define the %b level for downtrend detection (default 0.26, step 0.01).
Ideal Use Cases
- Trend Following: Perfect for traders seeking to capitalize on sustained price movements with clear entry and exit signals.
- Volatility Analysis: Useful for identifying periods of high or low volatility when combined with the %b positioning.
- Complementary Tool: Works well alongside momentum indicators (e.g., RSI) or volume-based tools to confirm trend strength.
#### Disclaimer
This indicator is provided for educational and informational purposes only. It is not intended to serve as financial advice or a guaranteed method for trading success. Trading involves significant risks, including the potential loss of capital. Users are solely responsible for their trading decisions and should conduct their own analysis and apply appropriate risk management strategies.
Notes
- Ensure your chart has sufficient historical data to reflect accurate Bollinger Bands calculations.
- Test the indicator on a demo account before using it in live trading to validate its performance with your preferred assets and timeframes.
This indicator is a versatile addition to any trader's toolkit, offering a blend of trend detection and visual clarity tailored to modern trading needs.
Swing Data - SimplifiedThe swing data indicator by jfsrev but simplified. Thank you jfsrev for your work!
CPR by VictorVCentral Pivot Range
Where price is vs CPR
Above TC: bullish bias; TC/BC act as support. Hold above TC → trend day likely.
Inside CPR (BC–TC): balanced/choppy; expect mean reversion between edges until a clean break.
Below BC: bearish bias; BC/TC act as resistance.
Width of the CPR
Narrow: energy coiled → higher chance of breakout/trend day.
Wide: balanced market → range-bound behavior more likely.
Shift vs yesterday
CPR shifted up: bullish undertone.
Shifted down: bearish undertone.
Overlapping: neutral/indecisive.
Intraday tells
Acceptance: Several candles holding outside BC/TC = expansion in that direction.
Rejection: Wicks through BC/TC that close back inside = likely fade back toward the opposite edge.
Pivot (P) magnet: On non-trend days, price often gravitates back to P.
Bitcoin Halving Cycle Strategy ProBitcoin Halving Cycle Strategy Pro - Advanced Market Cycle Analysis Tool
This professional indicator analyzes Bitcoin's 4-year halving cycles using precise mathematical calculations. It identifies bull and bear market phases based on 500 days before and 560 days after each halving event, providing traders with data-driven market cycle insights.
Key Features:
• Automatic Bull/Bear Market Zone Detection with color-coded areas
• Historical Halving Analysis (2012-2028) with future projections
• Live Performance Tracking during bull phases (returns, max drawdown)
• Customizable cycle parameters (days before/after halving)
• Interactive info table showing current cycle phase and metrics
• Visual timeline markers for halving dates and cycle boundaries
Perfect for long-term Bitcoin investors, cycle analysts, and traders who want to understand market psychology and timing based on historical halving patterns. Uses proven 1060-day cycle theory backed by empirical data.
Rebound Sigma Pro - IndicatorOverview
Rebound Sigma Pro is a mean-reversion indicator that detects statistically oversold conditions in trending markets.
It helps traders identify potential short-term rebounds based on momentum exhaustion and volatility-adjusted entry zones.
Concept
The indicator combines two quantitative components:
Short-term momentum to detect short-term exhaustion
Trend filter to ensure setups align with the long-term direction
When a stock in an uptrend becomes temporarily oversold, a limit-entry signal is plotted.
The trade is then tracked until short-term conditions normalize or a time-based exit occurs.
Visual Signals
Green Triangle: Suggests placing a limit order for the next session
Green Circle: Confirms entry was filled
Red Triangle: Signals an exit for the next session’s open
Orange Background: Pending order
Green Background: Position active
Red Background: Exit phase
Yellow Line: Entry reference price
User Inputs
Limit Entry (% below previous close) – Default 1 %
Use Limit Entry – Switch between limit or market entries
Enable Time Exit – Optional holding-period constraint
Maximum Holding Days
All other internal parameters (momentum length, filters) are pre-configured.
Alerts
Limit Order Signal: New setup detected
Entry Confirmed: Order filled
Exit Signal: Exit expected next day
Usage
Designed for liquid equities and ETFs
Works best in confirmed uptrends
Backtesting encouraged to adapt parameters per symbol and timeframe
Notes
Not an automated strategy; manual order execution required
Past behavior does not imply future performance
Always apply sound position sizing and risk management
Disclaimer
This indicator is provided for educational and analytical purposes only.
It does not constitute financial advice or performance assurance.
Uptrick: Relative Strength Rotation SystemIntroduction
The Uptrick: Relative Strength Rotation System is an indicator engineered to implement a regime-aware tactical allocation strategy across a predefined set of user-specified assets. It visualizes a simulated equity curve produced by a closed, managed rotation engine. The system is designed to identify relative strength relationships dynamically and rotate into stronger-performing assets, while offering an optional fallback into a defensive state when market conditions are deemed unfavorable by the logic.
Overview
This indicator allocates capital by continuously evaluating the relative strength between all asset pairs within the selected group. Unlike simplistic momentum models or rank-based selectors, this system uses internally calculated scores that compare each asset across multiple dimensions, forming a comprehensive decision matrix. These scores are evaluated through a regime-aware layer that determines whether the system should remain invested or move into an idle allocation. The rotation logic is implemented through a rebalancing structure that maintains exposure to a single asset at any time, or transitions into a fallback asset such as cash or PAXG based on internal conditions. Outputs include a dynamically colored equity curve, context-sensitive labels, and optional overlays comparing buy-and-hold performance of the selected assets.
Originality
The indicator utilizes a scoring matrix based on custom asset-to-asset comparative ratios, resulting in a relational framework that evaluates assets in the context of each other rather than in isolation. Each asset is analyzed through multiple statistical dimensions, including trend strength and normalized deviation using Z-score calculations. These metrics form the foundation of an adaptive matrix used to derive consensus leadership. A key differentiator lies in the optional routing of idle allocations to PAXG—a tokenized gold asset—offering a non-cash defensive alternative that introduces both diversification and risk modulation not typically seen in rotation models. The engine also includes an override layer that filters decisions through market state awareness, adding tactical discipline during ambiguous or bearish regimes. Taken together, these features form a self-contained rotation mechanism with multiple embedded controls and fallback logic, all of which are abstracted from the user.
Inputs and Features
Exponential Length (EMA Length)
Specifies the smoothing length used by one of the internal scoring models. Lower values allow for more responsive asset comparisons, while longer values smooth out short-term volatility in score changes.
Z Score
Controls the statistical lookback length used for normalized relative comparisons. This Z-score is a cornerstone of the system’s comparative matrix, standardizing inter-asset ratio behaviors to detect statistically significant deviations from recent behavior. It allows the rotation engine to isolate and prioritize sustained leadership across assets, regardless of price volatility.
Rebalance Every N Bars
Sets how frequently the system evaluates potential changes in leadership. This controls the cadence of reallocation and can be tuned for faster or slower responsiveness.
When Bearish / Neutral, go to
Lets the user select how the system behaves during non-confirmed or bearish conditions. It can either route to a flat cash-equivalent state or into a user-defined defensive asset (such as PAXG), introducing an added layer of optional protection.
Cash Filter
Activates an override that forces the system into an idle state during unfavorable market regimes, even if a leader is otherwise present. This regime-aware mechanism adds another layer of conditional control to mitigate exposure risk.
Start Date
Defines the point in history from which the equity simulation begins. All calculations and equity values prior to this point are excluded.
Asset Inputs (Asset 1 to Asset 4)
Allow the user to specify up to four assets to be evaluated within the rotation universe. These may include crypto, forex, or other tradable symbols supported by TradingView.
PAXG Fallback Asset
Specifies the asset used as a fallback when the idle state is active and the defensive mode is set to PAXG rather than cash.
Color Settings
Users can customize the chart color palette for each asset and idle condition for enhanced clarity.
HODL Curve Toggles
Enable buy-and-hold equity curves for each input asset to be plotted for direct performance comparison with the system’s output.
Simple Mode
Reduces visual noise by simplifying the chart’s appearance and removing optional elements.
Background Color and Shadow Equity Fill
Offer additional styling options that reflect the system's current allocation, enhancing chart readability.
COLORED EQUITY CURVE - PAXG
COLORED EQUITY CURVE - CASH
SYSTEM
Current System Text Color
Allows further customization of label text for visibility across different asset themes.
Summary
The Uptrick: Relative Strength Rotation System is a rotation engine that leverages a proprietary scoring matrix to simulate tactical asset allocation. It analyzes inter-asset behavior through pairwise ratio metrics and statistically normalized scoring methods, enabling it to identify leadership dynamics within a defined universe. The inclusion of PAXG as a defensive fallback, regime-aware cash filtering, and customizable rebalancing cadence gives the system adaptability beyond traditional relative strength models. Users are provided with transparent visual feedback through an equity curve, contextual labels, buy-and-hold overlays, and real-time equity statistics. The system is not designed to disclose its internal mechanics, but it enables full visualization of its output and decisions for comparative analysis.
Disclaimer
This script is intended solely for educational and informational purposes. It does not constitute financial advice, trading signals, or an offer to buy or sell any financial instrument. Trading and investing carry risk, and past performance does not guarantee future outcomes. Users should perform their own research and consult a licensed financial advisor before making trading decisions.
AlphaRadar - Market📊 ALPHARADAR - MARKET MONITOR
⚠️ IMPORTANT
🔴 This indicator MUST be used ONLY on DAILY (1D) timeframe. It will not work correctly on other timeframes.
Overview:
Real-time market and sector performance dashboard displaying major US indices and all 11 sector ETFs in a single, organized panel. Track market rotation and sector strength at a glance.
Features:
- Market Indices (4): SPY (S&P 500), QQQ (Nasdaq), IWM (Russell 2000), DIA (Dow Jones)
- Sector ETFs (11): Complete coverage of all US market sectors
- Performance Tracking: Day, 5D, 1M, 6M, and YTD returns
- Color-Coded: 🟢 Green (positive) / 🔴 Red (negative) for instant visual analysis
What You Can Track:
✅ Market breadth (all indices moving together vs divergence)
✅ Sector rotation (which sectors are leading/lagging)
✅ Risk-on vs Risk-off sentiment
✅ Short-term momentum (Day, 5D)
✅ Medium-term trends (1M, 6M)
✅ Year-to-date performance leaders
Market Sectors Included:
- XLC (Communication)
- XLY (Consumer Discretionary)
- XLP (Consumer Staples)
- XLE (Energy)
- XLF (Financials)
- XLV (Healthcare)
- XLI (Industrials)
- XLB (Materials)
- XLRE (Real Estate)
- XLK (Technology)
- XLU (Utilities)
How to Use:
🔍 Spot Market Rotation: Identify which sectors are outperforming
📈 Confirm Trends: All green = strong market, all red = market weakness
⚡ Find Opportunities: Rotate into leading sectors, avoid lagging ones
🎯 Risk Management: Divergence between indices = potential warning signal
Best For:
- Sector rotation strategies
- Market breadth analysis
- Swing trading
- Portfolio allocation decisions
- Daily market monitoring
Notes:
- Data updates in real-time during market hours
- All calculations based on daily closing prices
- Works with any chart symbol
- Free to use
🔔 Remember: Use DAILY (1D) charts only!
