FlowScape PredictorFlowScape Predictor is a non-repainting, regime-aware entry qualifier that turns complex market context into two readiness scores (Long & Short, each 0/25/50/75/100) and clean, confirmed-bar signals. It blends three orthogonal pillars so you act only when trend energy, momentum, and location agree:
Regime (energy): ATR-normalized linear-regression slope of a smooth HMA → EMA baseline, gated by ADX to confirm when pressure is meaningful.
Momentum (push): RSI slope alignment so price has directional follow-through, not just drift.
Structure (location): proximity to pivot-confirmed swings, scaled by ATR, so “ready” appears near constructive pullbacks—not mid-trend chases.
A soft ATR cloud wraps the baseline for context. A yellow Predictive Baseline extends beyond the last bar to visualize near-term trajectory. It is visual-only: scores/alerts never use it.
What you see
Baseline line that turns green/red when regime is strong in that direction; gray when weak.
ATR cloud around the baseline (context for stretch and pullbacks).
Scores (Long & Short, 0–100 in steps of 25) and optional “L/S” icons on bar close.
Yellow Predictive Baseline that extends to the right for a few bars (visual trajectory of the smoothed baseline).
The scoring system (simple and transparent)
Each side (Long/Short) sums four binary checks, 25 points each:
Regime aligned: trendStrong is true and LR slope sign favors that side.
Momentum aligned: RSI side (>50 for Long, <50 for Short) and RSI slope confirms direction.
Baseline side: price is above (Long) / below (Short) the baseline.
Location constructive: distance from the last confirmed pivot is healthy (ATR-scaled; not overstretched).
Valid totals are 0, 25, 50, 75, 100.
Best-quality signal: 100/0 (your side/opposite) on bar close.
Good, still valid: 75/0, especially when the missing block is only “location” right as price re-engages the cloud/baseline.
Avoid: 75/25 or any opposition > 0 in a weak (gray) regime.
The Predictive (Kalman) line — what it is and isn’t
The yellow line is a visual forward extension of the smoothed baseline to help you see the current trajectory and time pullback resumptions. It does not predict price and is excluded from scores and alerts.
How it’s built (plain English):
We maintain a one-dimensional Kalman state x as a smoothed estimate of the baseline. Each bar we observe the current baseline z.
The filter adjusts its trust using the Kalman gain K = P / (P + R) and updates:
x := x + K*(z − x), then P := (1 − K)*P + Q.
Q (process noise): Higher Q → expects faster change → tracks turns quicker (less smoothing).
R (measurement noise): Higher R → trusts raw baseline less → smoother, steadier projection.
What you control:
Lead (how many bars forward to draw).
Kalman Q/R (visual smoothness vs. responsiveness).
Toggle the line on/off if you prefer a minimal chart.
Important: The predictive line extends the baseline, not price. It’s a visual timing aid—don’t automate off it.
How to use (step-by-step)
Keep the chart clean and use a standard OHLC/candlestick chart.
Read the regime: Prefer trades with green/red baseline (trendStrong = true).
Check scores on bar close:
Take Long 100 / Short 0 or Long 75 / Short 0 when the chart shows a tidy pullback re-engaging the cloud/baseline.
Mirror the logic for shorts.
Confirm location: If price is > ~1.5 ATR from its reference pivot, let it come back—avoid chasing.
Set alerts: Add an alert on Long Ready or Short Ready; these fire on closed bars only.
Risk management: Use ATR-buffered stops beyond the recent pivot; target fixed-R multiples (e.g., 1.5–3.0R). Manage the trade with the baseline/cloud if you trail.
Best-practice playbook (quick rules)
Green light: 100/0 (best) or 75/0 (good) on bar close in a colored (non-gray) regime.
Location first: Prefer entries near the baseline/cloud right after a pullback, not far above/below it.
Avoid mixed signals: Skip 75/25 and anything with opposition while the baseline is gray.
Use the yellow line with discretion: It helps you see rhythm; it’s not a signal source.
Timeframes & tuning (practical defaults)
Intraday indices/FX (5m–15m): Demand 100/0 in chop; allow 75/0 when ADX is awake and pullback is clean.
Crypto intraday (15m–1h): Prefer 100/0; 75/0 on the first pullback after a regime turn.
Swing (1h–4h/D1): 75/0 is often sufficient; 100/0 is excellent (fewer but cleaner signals).
If choppy: raise ADX threshold, raise the readiness bar (insist on 100/0), or lengthen the RSI slope window.
What makes FlowScape different
Energy-first regime filter: ATR-normalized LR slope + ADX gate yields a consistent read of trend quality across symbols and timeframes.
Location-aware entries: ATR-scaled pivot proximity discourages mid-air chases, encouraging pullback timing.
Separation of concerns: The predictive line is visual-only, while scores/alerts are confirmed on close for non-repainting behavior.
One simple score per side: A single 0–100 readiness figure is easier to tune than juggling multiple indicators.
Transparency & limitations
Scores are coarse by design (25-point blocks). They’re a gatekeeper, not a promise of outcomes.
Pivots confirm after right-side bars, so structure signals appear after swings form (non-repainting by design).
Avoid using non-standard chart types (Heikin Ashi, Renko, Range, etc.) for signals; use a clean, standard chart.
No lookahead, no higher-timeframe requests; alerts fire on closed bars only.
Forecasting
Pi Cycle Top Indicator - mychaelgoPlots the original Pi Cycle Top moving averages and marks bars where the 111DMA is rising and crosses above the 350DMA×2, often coinciding with Bitcoin cycle peaks. Includes a label with the signal price.
FVG + Bank Level Targeting w/ Alert TriggerDescription:
FVG + Bank Level Targeting w/ Alert Trigger is an intraday trading tool that combines Fair Value Gap (FVG) detection with dynamic institutional targeting using prior-day, weekly, and monthly high/low "Bank Levels." When a Fair Value Gap is detected, the script projects a logical target using the closest bank level in price's direction, and visually extends that level on your chart.
This tool is designed to help traders anticipate where price is most likely to move after an FVG appears — and alert them when price breaks through key target zones.
How It Works:
* Bank Level Calculation:
The indicator calculates Daily, Weekly, and Monthly high and low levels from the previous bar of each respective timeframe.
These are optionally plotted on the chart with a slight tick offset to avoid overlap with price.
* FVG Detection:
Bullish FVGs are defined by a gap between the low of the current candle and the high two candles prior, with a confirming middle candle.
Bearish FVGs follow the reverse pattern.
Once detected, the script finds the nearest unbroken institutional level (Bank Level) in the direction of the FVG and anchors a target line at that price level.
* Target Line Projection:
The script draws a persistent horizontal line (not just a plotted value) at the selected bank level.
These lines automatically extend a set number of bars into the future for clarity and trade planning.
* Breakout Detection:
When price crosses above a Bull Target or below a Bear Target, the script triggers a breakout condition.
These breakouts are useful for trade continuation or reversal setups.
* Alerts:
Built-in alert conditions notify you in real time when price crosses above or below a target.
These can be used to set TradingView alerts for your preferred Futures symbols or intraday pairs.
Parameters:
Tick Offset Multiplier: Adds distance between price and plotted levels.
Show Daily/Weekly/Monthly Levels: Toggle for each institutional level group.
FVG Extend Right (bars): Controls how far the target lines extend into the future.
Color Controls: Customize colors for FVG fill and target lines.
Use Case:
This indicator is designed for traders who want to:
Trade continuation or reversal moves around institutional price zones
Integrate Fair Value Gap concepts with more logical, historically anchored price targets
Trigger alerts when market structure evolves around key levels
It is especially useful for intraday Futures traders on the 15-minute chart or lower, but adapts well to any instrument with strong reactionary behavior at prior session highs/lows.
Enhanced RSI KDE | Advanced FiltersThis is an enhanced version of the excellent RSI (Kernel Optimized) indicator originally created by @fluxchart. Full credit goes to fluxchart for the innovative KDE (Kernel Density Estimation) concept and the solid foundation that made this enhancement possible.
🙏 CREDITS & ACKNOWLEDGMENTS
Original Creator: @fluxchart - RSI (Kernel Optimized)
Original Concept: Kernel Density Estimation applied to RSI pivot analysis
Enhancement: Advanced filtering system and signal optimization- profitgang
License: Mozilla Public License 2.0
🚀 WHAT'S NEW IN THIS ENHANCED VERSION
Building upon fluxchart's brilliant KDE RSI foundation, this version adds:
🔥 Advanced Filtering System:
Multi-Timeframe Confluence - Confirms signals across higher timeframes
Volume Confirmation - Only signals on above-average volume
Volatility Range Filter - Avoids signals in choppy or extreme conditions
Trend Context Analysis - Considers overall market direction
Adaptive Pivot Detection - Adjusts sensitivity based on market volatility
🎯 Signal Quality Improvements:
Confluence Scoring - Each signal gets a quality score (1-6)
Label Cooldown System - Prevents chart clutter with smart spacing
Higher Activation Thresholds - More selective signal generation
Risk Management Integration - Auto stop-loss and take-profit levels
📊 Enhanced Dashboard:
Real-time filter status monitoring
KDE probability percentages
Confluence scores for both directions
Volume and volatility readings
⚙️ HOW IT WORKS
The indicator maintains fluxchart's core KDE methodology:
Collects RSI values at historical pivot points
Creates probability density functions using Gaussian/Uniform/Sigmoid kernels
Identifies high-probability zones for potential reversals
NEW: Multiple filters must align before generating signals, dramatically reducing false positives while maintaining the accuracy of high-probability setups.
🎛️ RECOMMENDED SETTINGS
Confluence Score: 5/6 (very selective)
Activation Threshold: Medium or High
Multi-Timeframe: Enabled with 2/2 alignment
Volume Filter: Enabled (1.5x threshold)
All other filters: Enabled for maximum quality
📈 BEST USE CASES
Swing Trading - Higher timeframe confirmation reduces whipsaws
Quality over Quantity - Fewer but much higher probability signals
Risk Management - Built-in stop/target levels for each signal
Multi-Asset Analysis - Works on stocks, crypto, forex, commodities
⚠️ IMPORTANT NOTES
This is a quality-focused indicator - expect fewer but better signals
Backtest thoroughly on your specific assets and timeframes
The original fluxchart indicator remains excellent for different trading styles
Consider this an alternative approach, not a replacement
🤝 COLLABORATION & FEEDBACK
Special thanks to @fluxchart for creating the original innovative KDE RSI concept. This enhancement wouldn't exist without that solid foundation.
Feel free to suggest improvements or share your results! The goal is to build upon great work in the community.
Bitcoin Expectile Model [LuxAlgo]The Bitcoin Expectile Model is a novel approach to forecasting Bitcoin, inspired by the popular Bitcoin Quantile Model by PlanC. By fitting multiple Expectile regressions to the price, we highlight zones of corrections or accumulations throughout the Bitcoin price evolution.
While we strongly recommend using this model with the Bitcoin All Time History Index INDEX:BTCUSD on the 3 days or weekly timeframe using a logarithmic scale, this model can be applied to any asset using the daily timeframe or superior.
Please note that here on TradingView, this model was solely designed to be used on the Bitcoin 1W chart, however, it can be experimented on other assets or timeframes if of interest.
🔶 USAGE
The Bitcoin Expectile Model can be applied similarly to models used for Bitcoin, highlighting lower areas of possible accumulation (support) and higher areas that allow for the anticipation of potential corrections (resistance).
By default, this model fits 7 individual Expectiles Log-Log Regressions to the price, each with their respective expectile ( tau ) values (here multiplied by 100 for the user's convenience). Higher tau values will return a fit closer to the higher highs made by the price of the asset, while lower ones will return fits closer to the lower prices observed over time.
Each zone is color-coded and has a specific interpretation. The green zone is a buy zone for long-term investing, purple is an anomaly zone for market bottoms that over-extend, while red is considered the distribution zone.
The fits can be extrapolated, helping to chart a course for the possible evolution of Bitcoin prices. Users can select the end of the forecast as a date using the "Forecast End" setting.
While the model is made for Bitcoin using a log scale, other assets showing a tendency to have a trend evolving in a single direction can be used. See the chart above on QQQ weekly using a linear scale as an example.
The Start Date can also allow fitting the model more locally, rather than over a large range of prices. This can be useful to identify potential shorter-term support/resistance areas.
🔶 DETAILS
🔹 On Quantile and Expectile Regressions
Quantile and Expectile regressions are similar; both return extremities that can be used to locate and predict prices where tops/bottoms could be more likely to occur.
The main difference lies in what we are trying to minimize, which, for Quantile regression, is commonly known as Quantile loss (or pinball loss), and for Expectile regression, simply Expectile loss.
You may refer to external material to go more in-depth about these loss functions; however, while they are similar and involve weighting specific prices more than others relative to our parameter tau, Quantile regression involves minimizing a weighted mean absolute error, while Expectile regression minimizes a weighted squared error.
The squared error here allows us to compute Expectile regression more easily compared to Quantile regression, using Iteratively reweighted least squares. For Quantile regression, a more elaborate method is needed.
In terms of comparison, Quantile regression is more robust, and easier to interpret, with quantiles being related to specific probabilities involving the underlying cumulative distribution function of the dataset; on the other expectiles are harder to interpret.
🔹 Trimming & Alterations
It is common to observe certain models ignoring very early Bitcoin price ranges. By default, we start our fit at the date 2010-07-16 to align with existing models.
By default, the model uses the number of time units (days, weeks...etc) elapsed since the beginning of history + 1 (to avoid NaN with log) as independent variable, however the Bitcoin All Time History Index INDEX:BTCUSD do not include the genesis block, as such users can correct for this by enabling the "Correct for Genesis block" setting, which will add the amount of missed bars from the Genesis block to the start oh the chart history.
🔶 SETTINGS
Start Date: Starting interval of the dataset used for the fit.
Correct for genesis block: When enabled, offset the X axis by the number of bars between the Bitcoin genesis block time and the chart starting time.
🔹 Expectiles
Toggle: Enable fit for the specified expectile. Disabling one fit will make the script faster to compute.
Expectile: Expectile (tau) value multiplied by 100 used for the fit. Higher values will produce fits that are located near price tops.
🔹 Forecast
Forecast End: Time at which the forecast stops.
🔹 Model Fit
Iterations Number: Number of iterations performed during the reweighted least squares process, with lower values leading to less accurate fits, while higher values will take more time to compute.
Wolf Exit Oscillator Enhanced
# Wolf Exit Oscillator Enhanced
## What it is (quick take)
**Wolf Exit Oscillator Enhanced** is a clean, rules-first **exit timing tool** built on the **True Strength Index (TSI)** with two optional safeguards:
1. **Signal-line crossover** (to avoid bailing on shallow dips), and
2. **EMA confirmation** (price-based “is the trend actually weakening/strengthening?” check).
Use it to standardize when you **take profits, cut losers, or scale out**—especially after momentum runs hot or cold.
> Works best **paired** with:
>
> * **ABS NR — Fail-Safe Confirm (v4.2.2)** for entries
> * **ABS Companion Oscillator — Trend / Exhaustion / New Trend** for trend/exhaustion context
---
## How to use it (operational workflow)
1. **Set your bands**
* `exitHigh` and `exitLow` mark “overcooked” zones on the TSI scale (default: +60 / –60).
* Above `exitHigh` = momentum stretched **up** (good place to **exit shorts** or **take long profits**).
* Below `exitLow` = momentum stretched **down** (good place to **exit longs** or **take short profits**).
2. **Choose strictness**
* **Base mode**: the moment TSI crosses out of a band, you get an exit signal.
* **Add Signal-Line Cross** (`enableSignalX = true`): require TSI to cross its signal in the same direction → **fewer, cleaner exits**.
* **Add EMA Filter** (`enableEMAFilter = true`): also require **price** to confirm (e.g., long exit only if price < EMA). This avoids bailing during healthy trends.
3. **Execute with structure**
* **Full exit** when a signal fires, or
* **Scale out** (e.g., 50% on first signal, remainder on trail/secondary signal), or
* **Move stop** to lock gains once an exit signal prints.
4. **Alerts**
* Set to **“Once per bar close”** to avoid intrabar flip-flop.
* Use the two provided alert names for automation (see “Alerts” below).
---
## Signals & visuals
* **TSI line** (solid) and **Signal line** (dashed) with optional **histogram** (TSI − Signal).
* **Horizontal bands** at `exitHigh` and `exitLow`.
* **Labels**:
* **Exit Long** appears when long-side momentum breaks down (below `exitLow`, plus any enabled filters).
* **Exit Short** appears when short-side momentum breaks down (above `exitHigh`, plus any enabled filters).
**Alerts (stable names):**
* **WolfExit — Exit Long**
* **WolfExit — Exit Short**
---
## Non-repainting behavior (what to expect)
* The oscillator is computed with **EMAs on current timeframe**—no higher-timeframe lookahead, no repaint.
* **Intrabar**: TSI/Signal can fluctuate; use **bar-close evaluation** (and alert setting “Once per bar close”) to lock signals.
* If you enable the EMA filter, that check is also evaluated at bar close.
---
## Every input explained (and how changing it alters behavior)
### Momentum engine (TSI)
* **TSI Long EMA Length (`tsiLongLen`, default 25)**
Higher = smoother, slower momentum; fewer signals. Lower = twitchier, more signals.
* **TSI Short EMA Length (`tsiShortLen`, default 13)**
Fine-tunes responsiveness on top of the long length. Lower short → snappier TSI.
* **TSI Signal Line Length (`tsisigLen`, default 7)**
Higher = slower signal line (harder to cross) → fewer signals. Lower = easier crosses → more signals.
### Thresholds (the bands)
* **Exit Threshold High (`exitHigh`, default +60)**
Raise to demand **stronger** overbought before signaling short exits / long profit-takes. Lower to trigger sooner.
* **Exit Threshold Low (`exitLow`, default −60)**
Raise (toward 0) to trigger **earlier** on longs; lower (more negative) to wait for deeper downside stretch.
### Confirmation layers
* **Require Signal Line Crossover (`enableSignalX`, default true)**
On = TSI must cross its signal (same direction as exit) → **filters out shallow wiggles**. Off = faster, more frequent exits.
* **Enable EMA Confirmation Filter (`enableEMAFilter`, default true)**
On = require **price < EMA** for **Exit Long** and **price > EMA** for **Exit Short**.
* **EMA Exit Confirmation Length (`exitEMALen`, default 50)**
Higher = **trendier** filter (harder to flip) → fewer exits; Lower = more reactive → more exits.
### Visuals
* **Show Histogram (`showHist`)**
On = quick visual for TSI–Signal spread (helps spot weakening momentum before a cross).
* **Plot Exit Signals (`showSignals`)**
Toggle labels if you only want the lines/bands with alerts.
---
## Tuning recipes (quick, practical)
* **Strong trend days (avoid premature exits)**
* Keep **`enableSignalX = true`** and **`enableEMAFilter = true`**
* Increase **`exitEMALen`** (e.g., 80)
* Consider raising **`exitHigh`** to 65–70 (and lowering **`exitLow`** to −65/−70)
* **Choppy/range days (exit faster, take the cash)**
* **`enableEMAFilter = false`** (don’t wait for price filter)
* **`enableSignalX`** optional; try off for quicker responses
* Bring bands closer to **±50** to take profits earlier
* **Scalping / lower timeframes**
* Shorten **TSI lengths** a bit (e.g., 21/9/5)
* Consider **`exitHigh=55 / exitLow=-55`**
* Keep **histogram on** to visualize momentum flip risk
* **Swing trading / higher timeframes**
* Lengthen **TSI** (e.g., 35/21/9) and **`exitEMALen`** (e.g., 100)
* Wider bands (±65 to ±75) to catch bigger moves before exiting
---
## Playbooks (how to actually trade it)
* **Entry from ABS NR FS, exit with Wolf**
* Take entries from **ABS NR — Fail-Safe Confirm** (triangle).
* Use **Wolf Exit** to scale out: 50% on first exit label, trail remainder with price/EMA or your stop logic.
* **Pyramid & protect**
* Add on re-accelerations (TSI pulls back toward zero without breaching the opposite band).
* The first **Exit** signal → take partial, raise stop to last higher low / lower high.
* **Mean-reversion fade management**
* When fading with ABS NR (KC band pokes + stretched |Z|), target the first opposite **Exit** signal as your “don’t overstay” cue.
---
## Suggested starting points
* **Day trading (5–15m):**
* TSI: **25 / 13 / 7** (default)
* Bands: **+60 / −60**
* Confirmations: **SignalX = on**, **EMA Filter = on**, **EMA Len = 50**
* Alerts: **Once per bar close**
* **Scalping (1–3m):**
* TSI: **21 / 9 / 5**
* Bands: **±55**
* Confirmations: **SignalX = on**, **EMA Filter = off** (optional for speed)
* **Swing (1h–D):**
* TSI: **35 / 21 / 9**
* Bands: **+65 / −65** (or ±70)
* Confirmations: **SignalX = on**, **EMA Filter = on**, **EMA Len = 100**
---
## Best-practice pairings
* **Entries:** **ABS NR — Fail-Safe Confirm (v4.2.2)**
* Take ABS triangles; let Wolf standardize exits so you’re not guessing.
* **Context:** **ABS Companion Oscillator**
* Prefer holding longer when the companion stays above (for longs) or below (for shorts) its neutral band and **no EXH tag** prints.
* If companion flags **EXH** against your position, tighten stops; Wolf’s next exit signal becomes high priority.
---
## Notes & disclaimers
* This is an **exit signal tool**, not a strategy or broker.
* Signals are strongest when aligned with your **entry logic** and a **risk framework** (position sizing, stops, partials).
* All evaluations are **current timeframe**; no higher-timeframe lookahead is used.
* Markets change—tune the bands and confirmations per symbol/timeframe.
---
**Tip:** Keep your alerts simple—one for **Exit Long**, one for **Exit Short**, **Once per bar close**. Use partial exits on the first signal, and let your stop/trailing logic handle the rest.
Squeeze Pro Alerts (Indicatore)This indicator is a breakout strategy that works like a compressed spring.
It first identifies periods of low market volatility (the "squeeze") and then signals when the price breaks out forcefully. To make the signals more reliable, it waits for a confirmation candle and uses filters like the trend on a higher timeframe.
The final result is a clear visual "BUY" or "SELL" signal on the chart, for which you can set up an alert.
ATAI Triangles — Volume-Based & Price Pattern Analysis (v1.01)ATAI Triangles — Volume-Based & Price Pattern Analysis (v1.01)
Overview
ATAI Triangles identifies two synchronized triangle structures — Hi-Lo-Hi (HLH) and Lo-Hi-Lo (LHL) — and analyzes them both geometrically and volumetrically. For each triangle, volume is split between its two legs (segments), providing interpretable insights into buyer vs seller activity along each path.
The idea is that certain geometric shapes, when paired with volume distribution on each leg, can reveal patterns worth exploring. Users are encouraged to share their observations and interpretations in the TradingView comments section so that more aspects of these triangle combinations can be discovered collectively.
Extra (for fun)
For a bit of entertainment, we’ve included a symbolic “hexagram” glyph that appears when both triangle types align in a particular way — it’s just a visual nod to geometry and has no predictive or trading value.
Interface & data clarity
- Inputs and parameters are organized by function (pattern geometry, volume analysis, visuals, HUD, labels).
- Each input includes tooltips explaining its purpose, units, and possible effects on calculations.
- All on-chart objects (polylines, labels, connectors) are named and colored to reflect their role, with volume values formatted in engineering notation (K, M, B).
- HUD columns and label texts use concise terms and consistent units, so that every displayed value is directly traceable to a calculation in the code.
- Daily and lower-timeframe volume series are clearly separated, with update logic documented to indicate intrabar provisional values vs finalized bar-close values.
Usage notes
Designed to be used alongside other indicators and chart tools for context; it is not a standalone signal generator.
All Buy/Sell volumes are absolute (non-negative); Δ = Buy − Sell.
Intrabar values update live and finalize at bar close (no repaint after close).
Disclaimer
For research, discussion, and educational purposes only. This is not financial advice and does not guarantee any outcome. Trade at your own risk.
Bot Scalping Camarilla Pivot (Sesuai TradingView)auto buy in S1,S2,S3, SL=S4, TP=R1
auto sell in R1,R2,R3, SL=R4, TP=S1
Multi - Timeframe 3 EMA Bull/Bear Table此指标是一个图标指标，适用于短线交易以及中线交易，它明确的显示出来了用EMA来表示方向指示，1分钟不可使用，此图表更新了多次以及修改了多次，在实际回测中有明显的提醒作用，不过多用于参考，不可作为主要指标使用，代码稍复杂如有加以改进的地方请提出，其中核心使用了EMA的20，50，200周期来作为参考，目的是能识别多周期和时间的方向指示，注意：此指标建议仅用于方向参考，不用于主要指标交易。
This indicator is a graphical indicator suitable for short-term and medium-term trading. It clearly shows the direction indicated by the EMA. It cannot be used for 1-minute intervals. This chart has been updated and modified multiple times, and it has a significant alerting effect in actual backtesting; however, it is mainly for reference and should not be used as the primary indicator. The code is somewhat complex, so please suggest improvements if there are any. The core uses the 20, 50, and 200 EMA periods as references, with the aim of identifying the direction indicators across multiple periods and timeframes. Note: This indicator is recommended only for directional reference and not for main indicator trading.
Bar TimeBar Time is a simple utility for traders who rely on backtesting, Bar Replay, and detailed price action analysis. It solves a common but frustrating problem: knowing the exact time of the bar you are looking at.
While most time indicators show your computer's live clock time, this tool displays the bar's own timestamp, perfectly synchronized with your chart's data and timezone.
Why Is This Important?
When you are deep in a Bar Replay session or analyzing a historical setup, the live clock is irrelevant. You need to know when that critical breakout or reversal candle actually happened. Was it during the pre-market? At the London open? In the last five minutes of the US session? This indicator provides that vital context instantly, without you needing to squint at the small print on the x-axis.
Key Use Cases
1. Mastering Bar Replay
As you click through bars in Replay mode, the displayed time updates with each new bar. This allows you to simulate a live trading session with full awareness of the time of day, helping you train your decision-making under more realistic conditions.
2. Analyzing Screener Signals
This is one of the most powerful uses. Imagine your screener finds a "BUY" signal on a stock from two bars ago. You switch to that stock's chart to investigate. Instead of hunting for the exact bar, this tool instantly shows you the date and time of the bar you are currently hovering over. It dramatically speeds up the workflow of moving from a screener alert to actionable analysis.
3. Detailed Price Action Study
Quickly identify key session timings, see how price reacts to news events at a specific time, or analyze intraday volume patterns with complete temporal clarity.
Features & Customization
The tool is designed to be lightweight, efficient, and fully customizable to match your charting environment.
Timezone-Aware Accuracy: Automatically detects your chart's timezone for a perfect match between the label and the x-axis.
Fully Customizable Position: Place the time display in any of nine screen positions (e.g., Top Left, Bottom Center) using a simple dropdown menu.
Custom Colors: Easily set the background and text colors to blend seamlessly with your chart's theme.
Market Clarity Pro Market Clarity Pro — See Key Zones, Trend & Volume Signals
Spot yesterday’s High (Supply) and Low (Demand) instantly — and know exactly where big buyers and sellers are likely waiting.
Red zones = strong selling pressure.
Green zones = strong buying pressure.
Plus, a built-in trend line keeps you trading in the right direction and away from sudden reversals.
You’ll also see:
🔴 Red arrow — not a sell signal, but a sign of heavy sellers stepping in, with volume confirmation and a candle breaking the previous one.
🔵 Blue arrow — not a buy signal, but a sign of strong buyers stepping in, with volume confirmation and a candle breaking the previous one.
These arrows highlight potential volume spikes and breakouts for confirmation only — you still confirm with the higher time frame for more market clarity.
Break above supply. Possible uptrend.
Break below demand. Possible downtrend.
📌 Before using this tool, watch the tutorial video to learn exactly how to apply it and how to spot profitable trades with confidence.
Quant Signals: Econophysics-based MomentumPhysical Momentum Switcher (p0 / p1 / p2 / p3)
This indicator implements a “physical momentum” concept from quantitative finance research, where momentum is defined similarly to physics:
Momentum (p) = Mass × Velocity
Instead of using only the standard cumulative return (classic momentum), it lets you switch between multiple definitions:
p0: Cumulative return over the lookback period (no mass, just price change).
p1: Sum of (mass × velocity) over the lookback period.
p2: Weighted average velocity = (Σ mass×velocity) ÷ (Σ mass).
p3: Sharpe-like momentum = average velocity ÷ volatility (massless).
Velocity can be measured as:
Log return: ln(Pt / Pt-1)
Normal return: (Pt / Pt-1 – 1)
Mass (for p1/p2) can be defined as:
Unit mass (1) — equal weighting, equivalent to traditional momentum.
Turnover proxy — Volume ÷ average volume over k bars.
Value turnover proxy — Dollar volume ÷ average dollar volume.
Inverse volatility — 1 ÷ return volatility over a specified period.
Features:
Switchable momentum definition, velocity type, and mass type.
Adjustable lookback (k) and smoothing period for the signal line.
Optional ±1σ display bands for quick overbought/oversold visual cues.
Alerts for crosses above/below zero or the signal line.
Table display summarizing current settings and values.
Typical uses:
Momentum trading: Buy when PM > 0 (or crosses above the signal), sell/short when PM < 0 (or crosses below).
Contrarian strategies: Reverse the logic when testing mean-reversion effects.
Cross-asset testing: Apply to different instruments to see which PM definition works best.
The Daily Bias Dashboard📜 Overview
This indicator is a powerful statistical tool designed to provide traders with a probable Daily Bias based on historical price action. It is built upon the concepts of Quarterly Theory, which divides the 24-hour trading day into 4 distinct sessions to analyze market behavior.
This tool analyzes how the market has behaved in the past to give you a statistical edge. It answers the question: "Based on the last X number of days, what is the most likely way the price will move during the Newyork AM & PM Sessions based on Asian & London Sessions?"
⚙️ How It Works
The indicator divides the 24-hour day (based on the America/New_York timezone) into two 12-hour halves:
First Half - 12 Hour Candle: The Accumulation/Manipulation or Asian/London Sessions (6 PM to 6 AM NY Time)
This period covers the Asian session and the start of the London session.
The indicator's only job here is to identify the highest high and lowest low of this 12-hour block, establishing the initial daily range.
Second Half - 12 Hour Candle: The Distribution/Continuation or NY AM/PM Sessions (6 AM to 6 PM NY Time)
This period covers the main London session and the full New York session.
The indicator actively watches to see if, and in what order, the price breaks out of the range established in Session 1 (FIrst Half of the day).
By tracking this behavior over hundreds of days, the indicator compiles statistics on four possible daily scenarios.
📊 The Four Scenarios & The Dashboard
The indicator presents its findings in a clean, easy-to-read dashboard, calculating the historical probability of each of the following scenarios:
↓ Low, then ↑ High: The price first breaks the low of Session 1 (often a liquidity sweep or stop hunt) before reversing to break the high of Session 1. This suggests a "sweep and reverse" bullish day.
↑ High, then ↓ Low: The price first breaks the high of Session 1 before reversing to break the low of Session 1. This suggests a "sweep and reverse" bearish day.
One-Sided Breakout: The price breaks only one of the boundaries (either the high or the low) and continues in that direction without taking the other side. This indicates a strong, trending day.
No Breakout (Inside Bar): The price fails to break either the high or the low of Session 1, remaining contained within its range. This indicates a day of consolidation and low volatility.
🧠 How to Use This Indicator
This is a confluence tool, not a standalone trading system. Its purpose is to help you frame a high-probability narrative for the trading day.
Establish a Bias: Start checking the dashboard at 06:00 AM Newyork time, which is the start of next half day trading session. If one scenario has a significantly higher probability (e.g., "One-Sided Breakout" at 89%), you have a statistically-backed directional bias in the direction of Breakout.
🔧 Features & Settings
Historical Days to Analyze: Set how many past days the indicator should use for its statistical analysis (default is 500).
Session Timezone : The calculation is locked to America/New_York as it is central to the Quarterly Theory concept, but this setting ensures correct alignment.
Dashboard Display: Fully customize the on-screen table, including its position and text size, or hide it completely.
⚠️ Important Notes
For maximum accuracy, use this indicator on hourly (H1) or lower timeframes.
The statistical probabilities are based on past performance and are not a guarantee of future results.
This tool is designed to sharpen your analytical skills and provide a robust, data-driven framework for your daily trading decisions. Use it to build confidence in your directional bias and to better understand the rhythm of the market.
Disclaimer: This indicator is for educational and informational purposes only and does not constitute financial advice. All trading involves risk.
XAUUSD 1H – FVG Buy/Sell Signals XAUUSD 1H – Fair Value Gap (FVG) Buy/Sell Signals (No Boxes)
What it is:
A clean, signal-only indicator for Gold on the 1-hour chart. It detects 3-bar Fair Value Gaps, waits for a deep retest, then confirms with strong candle structure + trend + ADX before printing a BUY/SELL arrow. No rectangles or clutter—just selective, high-quality signals.
Why it works:
Instead of chasing breakouts, the script hunts for imbalances (FVGs) where price often returns to “fair value.” It only fires when:
price revisits the gap by a configurable depth,
the candle closes beyond the far edge with a small buffer,
the candle body is ≥ ATR × K (confirms intent),
the broader trend (EMA-50/EMA-200) agrees, and
ADX (Wilder, manual) shows sufficient strength.
Key features
✅ Signal-only: arrows/labels—no boxes on chart.
✅ Deep retest logic (percentage of zone), not just a touch.
✅ Strong close filter (edge + buffer) + ATR body filter.
✅ Trend filter (EMA-50 vs EMA-200) to keep trades with the regime.
✅ ADX strength to avoid chop.
✅ One signal per zone (optional “delete on use”).
✅ Alerts for both BUY and SELL.
✅ Built for Pine v6, non-repainting logic on bar close.
Inputs you can tune
Min FVG size (pts) – ignore tiny gaps.
Retest depth (%) – how deep price must come back into the gap.
Close buffer (pts) – extra confirmation beyond zone edge.
Min body ≥ ATR× – candle strength requirement.
Min ADX – trend strength threshold.
Expire after X bars – keep zones fresh.
Delete zone after signal – true = one-shot signals.
How I use it
Apply to XAUUSD 1H.
Keep default filters for selective signals.
For more setups, lower Min FVG size or ADX and reduce retest depth; for stricter signals, do the opposite.
Combine with S/R or session timing (London/NY) for added confluence.
Notes
Signals are generated on bar close.
Designed for clarity and discipline—fewer, cleaner arrows over constant noise.
Works on other symbols/timeframes, but tuned for Gold 1H.
Tags: #XAUUSD #Gold #FVG #SmartMoney #1H #TrendFollowing #ADX #ATR #PineV6 #TradingView
Linh Index Trend & Exhaustion SuitePurpose: One overlay to judge trend, reversal risk, overextension, and volatility squeezes on indexes (built for VNINDEX/VN30, works on any symbol & timeframe).
What it shows
Trend state: Bull / Bear / Transition via 20/50/200 EMAs + slope check.
Overextension heatmap: Background paints when price is stretched vs the 20-EMA by ATR or % (you set the thresholds).
Squeeze detection:
Squeeze ON (yellow dot): Bollinger Bands (20,2) inside Keltner Channels (20,1.5).
Squeeze OFF + Release: White dot; script confirms direction only when close > BB upper (up) or close < BB lower (down).
52-week context: Distance to 52-week high/low (%).
Higher-TF alignment: Optional weekly trend reading shown on the label while you’re on the daily.
Anchored VWAP(s): Two optional AVWAPs from dates you choose (e.g., YTD open, last big gap/earnings).
Plots & labels
EMAs 20/50/200 (toggle on/off).
Optional BB & KC bands for diagnostics.
AVWAP #1 / #2 (optional).
Status label with: Trend, EMAs, Dist to 20-EMA (%, ATR), 52-week distances, HTF state.
Built-in alerts (set “Once per bar close”)
EMA10 ↔ EMA20 cross (early momentum shift)
EMA20 ↔ EMA50 cross (trend confirmation/negation)
Price ↔ EMA200 cross (long-term regime)
Squeeze Release UP / DOWN (BB breakout after squeeze)
Overextension Cool-off UP / DN (stretched vs 20-EMA + momentum rolling)
Near 52-week High (within your % threshold)
How to use (playbook)
Map regime: Prefer trades when Daily = Bull and HTF (Weekly) = Bull (shown on label).
Hunt expansion: Yellow → White dot and close beyond BB = fresh move.
Avoid chasing stretch: If background is painted (overextended vs 20-EMA), wait for a pullback or intraday base.
Locations matter: 52-week proximity + HTF Bull improves breakout quality.
Anchors: Add AVWAP from YTD open or last major gap to frame support/resistance.
Suggested settings
Overextension: ATR = 2.0, % = 4.0 to start; tune per index volatility.
Squeeze bands: BB(20,2) & KC(20,1.5) default are balanced; tighten KC (1.3) for more signals, widen (1.8) for fewer/higher quality.
Timeframes: Daily for signals, Weekly for bias. Optional 65-min for entries.
VN30 Effort-vs-Result Multi-Scanner — LinhVN30 Effort-vs-Result Multi-Scanner (Pine v5)
Cross-section scanner for Vietnam’s VN30 stocks that surfaces Effort vs Result footprints and related accumulation/distribution and volatility tells. It renders a ranked table (Top-N) with per-ticker signals and key metrics.
What it does
Scans up to 30 tickers (editable input.symbol slots) using one security() call per symbol → stays under Pine’s 40-call limit and runs reliably on any chart.
Scores each ticker by counting active signals, then ranks and lists the top names.
Optional metrics columns: zVol(60), zTR(60), ATR(20), HL/ATR(20).
Signals (toggleable)
Price/Volume – Effort vs Result
EVR Squeeze (stealth): z(Vol,60) > 4 & z(TR,60) < −0.5
5σ Vol, ≤1σ Ret: z(Vol,60) > 5 & |z(Return,60)| < 1
Wide Effort, Opposite Result: z(Vol,60) > 3 & close < open & z(CLV×Vol,60) > 1
Spread Compression, Heavy Tape: (H−L)/ATR(20) < 0.6 & z(Vol,60) > 3
No-Supply / No-Demand: close < close & range < 0.6×ATR(20) & vol < 0.5×SMA(20)
Momentum & Volatility
Vol-of-Vol Kink: z(ATR20,200) rising & z(ATR5,60) falling
BB Squeeze → Expansion: BBWidth(20) in low regime (z<−1.3) then close > upper band & z(Vol,60) > 2
RSI Non-Confirmation: Price LL/HH with RSI HL/LH & z(Vol,60) > 1
Accumulation/Distribution
OBV Divergence w/ Flat Price: OBV slope > 0 & |z(ret20,260)| < 0.3
Accumulation Days Cluster: ≥3/5 bars: up close, higher vol, close near high
Effort-Result Inversion (Down): big vol on down day then next day close > prior high
How to use
Set the timeframe (works best on 1D for EOD scans).
Edit the 30 symbol slots to your VN30 constituents.
Choose Top N, toggle Show metrics/Only matches and enable/disable scenarios.
Read the table: Rank, Ticker, (metrics), Score, and comma-separated Signals fired.
Method notes
Z-scores use a population-std estimate; CLV×Vol is used for effort/location.
Rolling counts avoid ta.sum; OBV is computed manually; all logic is Pine v5-safe.
Intraday-only ideas (true VWAP magnets, auction volume, flows, futures/options) are not included—Pine can’t cross-scan those datasets.
Disclaimer: Educational tool, not financial advice. Always confirm signals on the chart and with your process.
Ai buy and sell fundamental the Gk fundamental is a precision built market analysis tool designed yto help traders identify high probability
it uses a combination of market structure analysis, volatility tracking, and multi time frame confirmation to highlight possible trade opportunities
HOW IT WORKS
analyses momentum shift and structure breaks on the 2h chart for clearer direction
confirms potential entries by filtering market noise and using volatility directional filters
HOW TO USE apply 2h chart for primary direction
when signal appears allow 1 candle to close for confirmation
drop to lower time frame to lower time frame to refine entry if desired
always use proper risk management - no tool guarantees results
Comparaison DXY, VIX, SPX, DJI, GVZPine Script indicator compares the normalized values of DXY, VIX, SPX, DJI, and GVZ indices on a single scale from 0 to 100. Here's a breakdown of what it does:
Data Requests: Gets closing prices for:
US Dollar Index (DXY)
VIX Volatility Index
S&P 500 (SPX)
Dow Jones Industrial Average (DJI)
Gold Volatility Index (GVZ)
Normalization: Each index is normalized using a 500-period lookback to scale values between 0-100, making them comparable despite different price scales.
Visualization:
Plots each normalized index with distinct colors
Adds a dotted midline at 50 for reference
Uses thicker linewidth (2) for better visibility
Timeframe Flexibility: Works on any chart timeframe since it uses timeframe.period
This is useful for:
Comparing relative strength/weakness between these key market indicators
Identifying divergences or convergences in their movements
Seeing how different asset classes (currencies, equities, volatility) relate
You could enhance this by:
Adding correlation calculations between pairs
Including options to adjust the normalization period
Adding alerts when instruments diverge beyond certain thresholds
Including volume or other metrics alongside price
Quant Signals: Market Sentiment Monitor HUDWavelets & Scale Spectrum
This indicator is ideal for traders who adapt their strategy to market conditions — such as swing traders, intraday traders, and system developers.
Trend-followers can use it to confirm trending conditions before entering.
Mean-reversion traders can spot choppy markets where reversals are more likely.
Risk managers can monitor volatility shifts and regime changes to adjust position size or pause trading.
It works best as a market context filter — telling you the “weather” before you decide on the trade.
Wavelets are like tiny “measuring rulers” for price changes. Instead of looking at the whole chart at once, a wavelet looks at differences in price over a specific time scale — for example, 2 bars, 4 bars, 8 bars, and so on.
The scale spectrum is what you get when you measure volatility at several of these scales and then plot them against scale size.
If the spectrum forms a straight line on a log–log chart, it means price changes follow a consistent pattern across time scales (a power-law relationship).
The slope of that line gives the Hurst exponent (H) — telling you whether moves tend to persist (trend) or reverse (mean-revert).
The height of the line gives you the volatility (σ) — the average size of moves.
This approach works like a microscope, revealing whether the market’s behaviour is consistent across short-term and long-term horizons, and when that behaviour changes.
This tool applies a wavelet-based scale-spectrum analysis to price data to estimate three key market state measures inside a rolling window:
Hurst exponent (H) — measures persistence in price moves:
H > ~0.55 → market is trending (moves tend to continue).
H < ~0.45 → market is choppy/mean-reverting (moves tend to reverse).
Values near 0.5 indicate a neutral, random-walk-like regime.
Volatility (σ) — the average size of price swings at your chart’s timeframe, optionally annualized. Rising volatility means larger price moves, falling volatility means smaller moves.
Fit residual — how well the observed multi-scale volatility fits a clean power-law line. Low residual = stable behaviour; high residual = structural change (possible regime shift).
SKI FVG IndicatorIt uses ICT concepts and takes entries and exits. Identifies good FVG and shows an entry to buy or short and also exits at swing high or low , discount areas, primary areas, DOL (draw on liquidity)
Quant Signals: Entropy w/ ForecastThis is the first of many quantitative signals I plan to create for TV users.
Most technical analysis (TA) tools—like moving averages, oscillators, or chart patterns—are heuristic: they’re based on visually identifiable shapes, threshold crossovers, or empirically chosen rules. These methods rarely quantify the information content or structural complexity of market data. By quantifying market predictability before making a forecast, this method filters out noise and focuses your trading only during statistically favorable conditions—something traditional TA cannot objectively measure.
This MEPP-based approach is quantitative and model-free:
It comes from information theory and measures Shannon entropy rate to assess how predictable the market is at any moment.
Instead of interpreting price formations, it uses a data-compression algorithm (Lempel–Ziv) to capture hidden structure in the sequence of returns.
Forecasts are generated using a principle from statistical physics (Maximum Entropy Production), not historical chart patterns.
In short, this method measures the market's predictability BEFORE deciding a directional forecast is worth trusting. This tool is to inform TA traders on the market's current regime, whether it is smooth and predictable or it is volatile and turbulent.
Technical Introduction:
In information theory, Shannon entropy measures the uncertainty (or information content) in a sequence of data. For markets, the entropy rate captures how much new information price returns generate over time:
Low entropy rate → price changes are more structured and predictable.
High entropy rate → price changes are more random and unpredictable.
By discretizing recent returns into quartile-based states, this indicator:
Calculates the normalized entropy rate as a regime filter.
Uses MEPP to forecast the next state that maximizes entropy production.
Displays both the regime status (predictable vs chaotic) and the forecast bias (bullish/bearish) in a dashboard.
Measurements & How to Use Them
TLDR: HIGH ENTROPY -> information generation/market shift -> Don't trust forecast/strategy
1. H (bits/sym)
Shannon entropy rate of the last μ discrete returns, in bits per symbol (0–2).
Lower → more predictable; higher → more random.
Use as a raw measure of market structure.
2. H_max (log₂Ω)
Theoretical maximum entropy for Ω states. Here Ω = 4 → H_max = 2.0 bits.
Reference value for normalization.
3. Entropy (norm)
H / H_max, scaled between 0 and 1.
< 0.5–0.6 → predictable regime; > 0.6 → chaotic regime.
Main regime filter — forecasts are more reliable when below your threshold.
4. Regime
Label based on Entropy (norm) vs your entThresh.
LOW (predictable) = higher odds forecast will be correct.
HIGH (chaotic) = forecasts less reliable.
5. Next State (MEPP Forecast)
Discrete return state (1–4) predicted to occur next, chosen to maximize entropy production:
Large Down (strong bearish)
Small Down (mild bearish)
Small Up (mild bullish)
Large Up (strong bullish)
Use as your bias direction.
6. Bias
Simplified label from the Next State:
States 1–2 = Bearish bias (red)
States 3–4 = Bullish bias (green)
Align strategy direction with bias only in LOW regime.
