Institutional Signal Engine (ISE) 🧭 Overview
ISE is a multi-layer institutional trading system that combines trend, volatility, volume, and multi-timeframe logic into one advanced framework.
It identifies high-probability reversals, institutional accumulation/distribution phases, and Smart Buy/Sell setups confirmed by higher-timeframe filters.
The indicator integrates:
TSI–RSI–ATR dashboard (weekly basis)
Monthly trend filter (long-term direction)
A/D Line divergences and volume spikes on compression
Dynamic Sigma ±1…±4 volume bands (VWMA-based)
Smart visual signals, alerts, and real-time data tables
⚙️ Core Logic – Step by Step
1️⃣ Multi-Timeframe Engine
Calculates TSI, RSI, and ATR on the weekly timeframe to filter out short-term noise.
Uses a 10-period SMA on monthly close as long-term filter:
Above = monthly bullish bias
Below = monthly bearish bias
2️⃣ Weekly Trend Change Detection
A 10-bar SMA defines the weekly trend:
Green arrow “▲” = Bullish reversal
Red arrow “▼” = Bearish reversal
Automatic alerts are triggered when a reversal occurs.
3️⃣ Directional Score (0–100%)
A 4-factor composite score measures directional strength:
Component Weight Effect
TSI trend direction 25% Momentum bias
RSI above/below 50 25% Market strength
ATR above volatility threshold 25% Volatility confirmation
Monthly trend alignment 25% Institutional filter
Score ≥ 75% = strong institutional confirmation
Combined with monthly bias, this defines Smart Entry Zones
4️⃣ Institutional Module
🔸 A/D Line Divergences
Detects when volume flow diverges from price:
Price down + A/D up → bullish divergence (accumulation)
Price up + A/D down → bearish divergence (distribution)
🔸 Volume Spikes on Compression
Flags breakouts when price range contracts but volume surges sharply.
Indicates institutional activity and momentum expansion.
🔸 Smart Buy / Smart Sell Conditions
Smart signals appear only when all conditions align:
Divergence or volume spike,
Score ≥ 75%,
Monthly trend confirmation,
(Optional) Weekly trend reversal if enabled.
✅ Smart Buy (C) → Green triangle below bar
✅ Smart Sell (V) → Red triangle above bar
5️⃣ Advanced Visual Signals
Symbol Meaning Interpretation
▲ / ▼ Weekly trend reversal Direction change
🟢 C / 🔴 V Smart Buy / Smart Sell Institutional setup
🔵 / 🟠 Circles Ideal confirmed trades Retrospective validation
💠 Fuchsia Diamond Probable low Anticipated bullish reversal
↟ / ↡ RSI/SMA extreme cross Visual early warning
6️⃣ Sigma ±1..±4 Volume Bands (VWMA-70)
Based on Volume Weighted Moving Average (VWMA 70), not Bollinger.
Defines 4 upper and 4 lower Sigma levels relative to the current equilibrium (POC).
Acts as a probabilistic map of volume balance zones.
Labels display real-time price values for each band (auto-updated each bar).
7️⃣ Real-Time Information Tables
📋 Oscillator Table (Right side)
Displays the status of three oscillators:
Indicator Signal
Stochastic BUY / SELL / NEUTRAL
Fisher Transform BUY / SELL / NEUTRAL
Williams %R BUY / SELL / NEUTRAL
Colors: 🟢 = Buy, 🔴 = Sell, 🟠 = Neutral
📊 Volume Table (Top right)
Shows:
Volume Direction: buying / selling / neutral
Trend vs previous bar: increasing / decreasing / stable
Current vs previous volume values
🧠 How to Use and Interpret
🔹 Step 1 – Identify Context
Use the monthly filter and weekly arrows to determine the institutional direction.
📈 Both up = bullish environment
📉 Both down = bearish environment
Mixed = neutral / uncertain
🔹 Step 2 – Wait for Alignment
Trade only when Smart Signals appear in the same direction as the higher timeframe trend.
Green “C” = buy signal within bullish structure
Red “V” = sell signal within bearish structure
🔹 Step 3 – Confirm with Volumes and Sigma Bands
If price is near Sigma −2 / −3, expect potential rebound (buy zones).
If price is near Sigma +2 / +3, expect exhaustion (sell zones).
Strong volume spike + Smart signal = institutional confirmation
🔹 Step 4 – Manage Trades
Use weekly ATR or Sigma ±2 as volatility-based stop levels.
Exit on opposite Smart signal or trend reversal arrow.
📈 Interpretation Summary
Condition Meaning Bias
Green ▲ + Smart Buy + Score ≥75 Confirmed bullish reversal Long setup
Red ▼ + Smart Sell + Score ≥75 Confirmed bearish reversal Short setup
Fuchsia Diamond ⚡ Probable local bottom Early long opportunity
Narrow Sigma bands Compression → Pre-breakout Wait for expansion
Wide Sigma bands High volatility / exhaustion Avoid new entries
⚡ Summary
Aspect Description
Name Lanfranco Bilotti – Institutional Trading + Alert
Structure Multi-timeframe, multi-indicator system
Core Modules TSI, RSI, ATR, A/D Divergence, Volume Spike, Sigma Bands
Signals Smart Buy/Sell, Probable Low, Trend Arrows
Alerts Automatic weekly reversal alerts
Filters Weekly and monthly trend filters
Output Visual dashboard + dual data tables
Best timeframe Weekly or Daily (for institutional flow)
Main goal Detect institutional trend phases and confirm high-probability entries
💼 Trading Instructions (Usage Guide) !!!!
🔹 Step-by-Step Usage
1️⃣ Choose timeframe
Recommended use on Daily or Weekly charts.
Institutional alignment works best when Weekly = Monthly trend.
2️⃣ Identify market context
📈 Bullish environment: Monthly filter = UP and weekly arrow ▲
📉 Bearish environment: Monthly filter = DOWN and weekly arrow ▼
3️⃣ Wait for confirmation
Smart BUY (C) → appears only when volume, trend, and oscillators align.
Smart SELL (V) → confirmed institutional distribution setup.
4️⃣ Entry rules (example)
Long entry: when Smart BUY (C) appears and the current price is near Sigma −1 or −2.
Short entry: when Smart SELL (V) appears and the price is near Sigma +1 or +2.
5️⃣ Stop loss suggestion (statistical)
Use weekly ATR or next Sigma band as volatility-based stop.
Example: if entry at Sigma −1 → stop below Sigma −2.
6️⃣ Exit strategy
Exit when the opposite Smart Signal appears (C → V or V → C).
Or when a new weekly reversal arrow ▲ / ▼ is printed.
🔹 Interpretation Summary
Symbol Meaning Action Bias
▲ / ▼ Weekly trend reversal Confirms long / short bias
🟢 C Smart Buy Long entry zone
🔴 V Smart Sell Short entry zone
💠 Fuchsia Diamond Probable low Early long opportunity
↟ / ↡ RSI/SMA extreme Momentum exhaustion zone
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Trade only in the direction of the higher timeframe trend.
Smart BUY (C) → enter long when price is near Sigma −1 / −2 and monthly trend = UP.
Smart SELL (V) → enter short when price is near Sigma +1 / +2 and monthly trend = DOWN.
Exit on the opposite Smart signal or when a new weekly arrow ▲ / ▼ appears.
Use the weekly ATR or next Sigma band for stop-loss placement.
Always confirm signals at candle close.
Индикаторы и стратегии
Trend Direction (ZigZag)This indicator is designed to visually identify and label key market structure points—Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL)—using a ZigZag algorithm that efficiently tracks trend reversals and swing pivots. It overlays dynamic lines, labels, and color-coded bars directly onto your TradingView chart, making it ideal for traders seeking a clearer view of price structure for strategy development and confirmation.
What the Indicator Does
Automatically plots a ZigZag line following swing highs and lows, filtered by a customizable look-back length, helping to remove minor “noise” and highlight true structural pivots.
Labels each significant high or low as HH, HL, LH, or LL, enabling instant recognition of bullish or bearish market conditions.
Distinguishes structural shifts (“Break of Structure,” or BOS) with optional colored bar backgrounds for enhanced visual clarity when trends change.
Offers flexible controls over line color, width, label visibility and size, making it adaptable for different charting styles and timeframes.
Features and Customization
ZigZag Settings: Choose your preferred length and visual styling to fine-tune swing detection, with the ability to show or hide zigzag lines and adjust colors and thickness.
Labeling Structure: Toggle on/off the display of HH/HL/LH/LL labels, with customizable text size, helping you focus on the information relevant to your strategy.
Breakout Confirmation (Fib Factor): Integrates Fibonacci factor logic for validating when a breakout (BOS) should be recognized, giving added confidence in market turns.
Bar Coloring: Automatically paints bars to match current market bias (bullish or bearish), highlighting moments of structural change for quicker response.
How it Helps Traders
Clarifies Trend Structure: Makes it simple to distinguish trend direction and strength at a glance, improving timing and confidence in trade decisions.
Ideal for Strategy Building: Supports a variety of market-structure-based trading strategies, such as trend continuation, reversal setups, and breakout confirmations.
Saves Analysis Time: Automates the complex process of marking and tracking price swings, so you can focus on execution and risk management.
This indicator offers powerful market structure visualization and analysis, suited for all levels of traders and especially those who use price-action and swing-based systems (Supply & Demand).
Statistical Projection over N Days (drift + σ) – v1.2 [EN]🧭 Overview
“Statistical Projection over N Days (drift + σ)” is a quantitative forecasting model that estimates the expected future price range of any asset over a chosen horizon (default = 10 days).
It combines average drift (trend direction) and historical volatility (σ) to produce a probabilistic cone of future price movement.
The indicator displays:
a blue dashed line (expected price path),
1σ / 2σ deviation bands (volatility envelopes),
and a summary table with the key forecast values and expected return.
⚙️ Core Logic (Explained Simply)
The indicator analyses recent price behavior to estimate two key elements:
the average daily tendency of the market (called drift), and
the average daily variability (called volatility).
Here’s how it works, step by step:
Measures daily percentage changes (using logarithmic returns) to understand how much the price typically moves from one bar to the next.
It then calculates the average of those returns over a chosen historical window (for example, 70 bars).
If the average is positive → the market has a rising tendency (upward drift).
If the average is negative → the market tends to decline (downward drift).
At the same time, it computes the standard deviation of those returns — this shows how “wide” the movements are, i.e. how volatile the asset is.
Using these two measures — drift and volatility — it estimates where the price is statistically expected to move over the next N bars:
The mean projection (blue dashed line) represents the most likely price path.
The 1σ and 2σ lines (teal and gray) define confidence zones, where price is expected to remain about 68% and 95% of the time, respectively.
The model updates continuously with every new bar, recalculating both drift and volatility, so the projection cone expands, contracts, or changes direction depending on the latest market behavior.
📉 Interpretation of the Blue Line
The blue dashed line (pMean) is the statistical forecast path of price over the next N bars.
🔹 When the blue line is below the current price
The recent drift (average log return) is negative → the model expects a gradual decline.
Interpretation:
The prevailing statistical bias is bearish — the market is expected to move lower toward equilibrium.
🔹 When the blue line is above the current price
The recent drift is positive → the model expects a continued rise.
Interpretation:
The price is statistically likely to trend upward, maintaining momentum in the direction of the current drift.
🔹 When the blue line is sloping upward
The mean projection pMean is rising with each new bar.
Indicates positive drift → the average daily return is positive.
Interpretation:
The asset is in a growth phase; volatility bands act as potential expansion corridors.
🔹 When the blue line is sloping downward
The mean projection pMean decreases bar after bar.
Indicates negative drift → average daily return is negative.
Interpretation:
The asset is in a corrective or declining phase, with volatility determining potential drawdown limits.
🔹 When the blue line is flat
The drift (μ) is approximately zero.
Interpretation:
The model sees no directional bias; price equilibrium dominates.
Expect a sideways range unless new volatility (σ) expansion occurs.
📈 How to Read the Entire Projection
Blue dashed line → expected mean path (most probable price trajectory).
Teal lines (±1σ) → statistically normal range (≈68% of future outcomes).
Gray lines (±2σ) → extreme bounds (≈95% of outcomes).
Labels on the right show exact forecast prices for each band.
If the actual price moves outside the gray 2σ range →
→ it signals volatility breakout or regime shift, meaning the past volatility no longer explains the present movement.
🧮 Summary Table
Located at the top-right corner, it provides:
Field Description
Projection (days) Number of bars used for projection (h).
Anchor price Starting close used for forecast.
Mean target (h) Expected price after h bars (blue line endpoint).
1σ Band (↓ / ↑) 68% confidence interval.
2σ Band (↓ / ↑) 95% confidence interval.
Expected return Projected % change from current close to mean target.
Colors can be customized — for example:
white headers,
aqua for anchor price,
lime for target,
orange/red for σ bands,
yellow for expected return.
🧠 Practical Meaning
Blue Line State Interpretation Bias
Above price, rising Ongoing positive drift Bullish
Below price, falling Negative drift Bearish
Flat, near price Neutral drift Sideways
Steep slope Strong directional momentum Trend confirmation
Price > +2σ band Excess volatility / overextension Possible correction
Price < −2σ band Undervaluation or panic Reversion likely
⚡ Summary
Aspect Description
Purpose Statistical forecast of expected price range
Method Drift (μ) + Volatility (σ) from log returns
Outputs Mean projection (blue), 1σ & 2σ bands, expected return
Interpretation Directional bias from blue line and its slope
Recommended timeframe Daily
Best use Trend confirmation, probabilistic target estimation, volatility analysis.
Trade History Label Display On Chart (Copy-paste from Rakuten)Overview
This script automatically displays buy/sell labels on the chart simply by copying and pasting your trade history (execution records) exported from Rakuten Securities in Excel format.
It also automatically calculates the profit and loss for each trade.
Background
When reviewing one’s trades, manually matching the broker’s execution records — “date, time, symbol, number of shares, buy or sell” — with the exact points on the chart can be extremely time-consuming.
This is especially inefficient for day traders and scalpers, who may execute dozens of trades per day.
With this script, you can automatically display the entry (IN) and exit (OUT) points on your chart as labels.
It’s also useful when attaching charts to your trading notes or journals, as you can visually confirm exactly where you entered and exited, greatly speeding up the review process.
The script also supports multiple symbols.
Even if you paste a combined dataset containing trades for several stocks, only the trades for the currently displayed symbol will appear automatically.
This allows you to maintain a single master record and instantly visualize the relevant trades just by switching charts.
How to Use
1. Preparing your Excel data
(1)Export trade history
Export your trade history as a CSV file from Rakuten Securities MarketSpeed II, etc.
If you want to include detailed execution times (seconds), make sure to export the data on the same day.
If you export later as a batch, only the date will remain — the time information (hh:mm:ss) will be lost.
(2)Open and format in Excel
Always open the CSV file in Excel — not in Notepad.
If opened in Notepad, double quotes (") will be automatically added, which makes the script unable to recognize the data correctly.
If you need to include seconds in the execution date/time, set a custom format in Excel as follows:
yyyy/mm/dd hh:mm:ss
Copy the range from Execution Date (Column A) to Execution Price (Column L).
Do not include header rows.
Copy data only. Including the header line will cause parsing errors in the script.
(3)If you create a memo column
You can add a Memo column (Column M) next to the “Execution Price” column.
Anything written here (e.g., trade reasoning or notes) will appear on the chart labels.
If you add a memo column, copy the range from Execution Date (A) to Memo (M) when pasting into the script.
Again, copy only the data (not headers). Including column names will cause errors.
2. Paste data into TradingView
Open the script settings and paste the copied data into the text area labeled “Trade Data Paste Area.”
The script automatically parses the text and recognizes date, time, symbol, trade type, position type, credit type, quantity, price, and memo, displaying them as labels at the correct bar.
You can paste data for multiple stocks at once.
Only the rows matching the currently displayed chart’s symbol will be plotted.
3. Display settings (ON/OFF controls)
Each label element (credit type, position type, quantity, memo, etc.) can be turned ON/OFF individually in the script settings via checkboxes (input.bool).
If you’ve created a memo column, its content will also appear on the label.
4. Checking on the chart
Each trade’s entry and exit are shown directly above or below the relevant candlestick.
You can switch between daily and intraday timeframes for more detailed inspection.
Labels are color-coded (e.g., Buy / Sell / Settlement) for quick visual recognition.
When switching symbols, only the relevant trade labels for that symbol will automatically appear.
5. Notes
The script is designed for use on 1-minute to daily charts.
If there’s no matching candlestick for a given trade date/time, the label may not display correctly.
Data input is manual paste only (automatic import not supported).
CSV files must be edited in Excel. Other editors may alter the text format, causing parsing errors.
Due to Pine Script limitations, input.text_area can hold a maximum of 40,960 characters.
The script is tailored for Rakuten Securities’ export format.
Using data from other brokers may require aligning column structures.
If Rakuten changes its export format, the script may need adjustment.
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概要
このスクリプトは、楽天証券の約定履歴(取引記録)をExcelからコピーして貼り付けるだけで、チャート上に売買ラベルを自動表示するツールです。
また、各取引の損益も自動で計算されます。
背景
自分のトレードを振り返る際、証券会社の約定記録から「何月何日何時何分、どの銘柄を、何株、買った・売った」を確認して、チャート上の位置と突き合わせる作業は非常に時間がかかります。
特にデイトレードやスキャルピングをしていると、1日に数十件以上の約定が発生し、手動で位置を確認するのは非効率です。
このスクリプトを使えば、IN・OUTのタイミングをチャート上にラベルとして自動表示できます。
自分のトレードノート、トレード日記にチャート画像を貼り付ける際も利用 でき、チャートのどこでエントリー/決済したかを視覚的に確認できるため、振り返り作業が大幅に効率化されます。
また、 複数銘柄に対応しており、貼り付けたデータの中から現在表示中のチャート銘柄と一致する売買履歴だけを抽出・表示します。
これにより、複数銘柄分の約定記録を一括管理していても、チャートを切り替えるだけで該当銘柄の取引履歴を瞬時に可視化できます。
使用方法
1. Excelデータの準備
(1)約定履歴のエクスポート
楽天証券マーケットスピードⅡなどから約定履歴をCSV形式でエクスポートします。
約定の詳細な時刻(時分秒単位)データを取得したい場合は、必ず当日中にエクスポートしてください。後日まとめて過去分をエクスポートしても、日付までしか記録されず、時刻情報(hh:mm:ss)は失われます。
(2)Excelで開いて整形
CSVは必ずExcelで開いて編集してください。メモ帳で開くと "(ダブルクォーテーション) が自動的に付与され、スクリプトが正しく認識できません。
約定日の秒単位までを扱いたい場合は、Excelのセル書式設定を開き、「ユーザー定義」で次の形式を新規作成して適用します。書式を変更しないでコピーした場合は分までのデータとなり、スクリプトは00秒と認識します。
yyyy/mm/dd hh:mm:ss
約定日(A列)~約定単価(L列)までのデータ部分をコピーする。
※このとき、項目名(ヘッダー行)は含めず、データ部分のみをコピーしてください。項目名を含めるとスクリプトが誤認識してエラーになります
(3)メモ欄を作成する場合
約定単価の右隣の列(M列)を「メモ欄」として利用できます。ここにエントリー根拠など任意のメモを書いておくとラベル上でもメモを確認できます。
メモ欄を作成した場合は、約定日(A列)からメモ欄(M列)までをコピーして貼り付けてください。
※このとき、項目名(ヘッダー行)は含めず、データ部分のみをコピーしてください。項目名を含めるとスクリプトが誤認識してエラーになります。
2. データをTradingViewに貼り付ける
スクリプトの設定画面を開き、「取引データ貼り付け欄」にExcelからコピーしたデータをそのまま貼り付けます。
スクリプトが自動でテキストを解析し、日付・時刻・銘柄コード・取引区分・建玉区分・信用区分・数量・単価・メモなどを認識して、ラベルをチャート上に自動配置します。
複数銘柄のデータを一度に貼り付けても問題ありません。現在表示中のチャート銘柄と一致する行だけがラベルとして描画されます。
3. 表示設定(ON/OFF切り替え)
各表示要素(信用区分・建玉区分・数量・メモなど)は、設定画面のチェックボックス(input.bool)で個別に表示/非表示を切り替えられます。
メモ欄を作成している場合は、その内容もラベルに表示されます。
4. チャートでの確認
各取引のIN・OUTが、チャート上の該当バー(ローソク足)にラベルとして表示されます。
日足・分足を切り替えることで、より詳細なタイミングを確認できます。
ラベルは、買い(Buy)・売り(Sell)・返済などで色分けされ、視覚的に理解しやすい構成になっています。
チャートを銘柄ごとに切り替えるだけで、その銘柄の取引履歴のみが自動表示されます。
5. 注意点
このスクリプトは 1分足~日足 での使用を想定しています。データ上の日付や時刻に対応するローソク足が存在しない場合、ラベルを正しく表示できません。
データは手動貼り付け方式です。自動取得には対応していません。
Excel以外のアプリで開いたCSVは、文字列形式が変わるため解析できないことがあります。
Pineスクリプトの仕様上、テキストエリアには40,960文字までしか貼り付けできません。
楽天証券の出力フォーマットを想定しているため、他社形式を使う場合は列構成を揃える必要があります。
また、楽天証券の出力フォーマットが変更された場合は、正しく表示出来なります。
Symmetry Break Index | QRSymmetry Break Trend Scanner | QuantumResearch
What it does
This indicator detects trend regime shifts by measuring how persistently price deviates from its moving-average “symmetry.” It outputs a continuous Score and a binary Signal (Bullish / Bearish) when that score crosses user-defined thresholds:
Bullish (Long) when upside deviations dominate → sustained uptrend bias
Bearish (Short/Cash) when downside deviations dominate → sustained downtrend bias
It’s built for clarity and consistency: the plot is a single score with two horizontal decision lines so traders can quickly identify regime changes on a clean chart.
How it works (principle, not code)
Normalize price vs trend: Price is standardized against a moving average and its standard deviation to create a dimensionless “oscillator” series (how far above/below typical behavior price sits).
Symmetry count: For a user-defined range of reference levels, the script counts whether the standardized price is above or below each level. This builds a cumulative symmetry score: positive when upside presence is broad and persistent, negative when downside dominates.
Regime thresholds: Crossing the Uptrend Threshold or Downtrend Threshold flips the quantum state to Bullish or Bearish, minimizing noise compared with a single-level trigger.
This approach emphasizes persistence and breadth of deviation rather than one-off spikes, which can help filter chop.
Plots & visuals
Score (histogram/area fill): Positive area fills in the bullish color, negative area in the bearish color.
Zero line: Quick reference for balance between up/down deviations.
Two decision lines: Uptrend Threshold and Downtrend Threshold to mark regime flips.
Bar colors: Bars tint with the active regime (Bullish / Bearish) for fast reads.
Publish with a clean chart so the score and thresholds are clearly visible. Avoid extra indicators unless they are required and explained.
Inputs & customization
MA Length (default 40): Window for the baseline moving average and volatility. Shorter = more reactive; longer = smoother.
Source: Price input (e.g., close).
For Loop Range (Start / End, default −200…200): Breadth of reference levels in the symmetry count. Wider range = stronger smoothing and slower flips.
Uptrend / Downtrend Thresholds: Regime triggers. Tighten to react faster, widen to reduce whipsaws.
Color Mode: Choose a palette to match your chart.
Tip: Start with defaults, then tune MA Length and thresholds for your market/timeframe.
How to use it
Trend confirmation: Trade in the direction of the active regime; avoid counter-trend setups when the score is far beyond a threshold.
Risk controls: When the score retreats toward zero, consider reducing size or tightening stops—momentum is weakening.
Confluence: Combine with structure (S/R), volume, or volatility bands for entries/exits; the score provides context, not entries alone.
Originality & value
Unlike single-threshold oscillators, this method aggregates many standardized comparisons into one score, rewarding persistence and breadth of deviation. The result is a robust regime signal that tends to filter fleeting wiggles and highlight true symmetry breaks.
Limitations
Extremely range-bound markets can still produce false flips if thresholds are too tight.
Sudden volatility regime changes may require re-tuning MA Length or thresholds.
Standardization depends on the chosen window; there is no “one size fits all.”
Disclaimer
This tool is for research/education and is not financial advice. Markets involve risk, including loss of capital. Past performance does not predict or guarantee future results. Always test settings on your timeframe and use prudent risk management.
BTC Futures Open Interest 7-day Change | QRBitcoin Futures OI vs Price (7-Day)
What it is
This tool compares the 7-day momentum of Bitcoin perpetual futures Open Interest (OI) with the 7-day price change to classify market behavior into four intuitive regimes:
Leverage Rally (OI↑, Price↑) – positioning builds with rising price
Leveraged Sell-Off (OI↑, Price↓) – forced/short-term positioning into weakness
Deleveraging Sell-Off (OI↓, Price↓) – positions reduce while price falls
Spot Rally (OI↓, Price↑) – spot-led advance with lighter derivatives leverage
It is designed for BTC using the BINANCE:BTCUSD.P OI feed and a clean, self-contained visualization.
How it works (principle, not code)
OI Momentum: Calculates the 7-day Rate of Change (ROC) of BTC perpetual futures Open Interest.
Price Momentum: Calculates the 7-day ROC of the chart’s close.
Regime Logic: The sign of OI ROC and Price ROC determines the 4 regimes shown in the on-chart table label.
Volatility Context: A rolling standard deviation of OI ROC defines ±1σ and ±2σ bands. Bars are tinted when OI ROC exceeds ±2σ to highlight exceptional leverage shifts.
This is not a latency-sensitive microstructure model; it’s a context tool to see how derivatives positioning evolves relative to price.
Why it’s useful (originality & value)
Most OI overlays show a single line. This script adds:
a behavioral classifier (the 4 regimes) that’s immediately interpretable, and
adaptive σ-bands on OI momentum to distinguish routine leverage changes from abnormal expansions/flushes.
Together, they make it easier to read leverage cycles, spot rally quality, and identify riskier states (e.g., price up while OI surges vs. price up while OI fades).
What you see on the chart
Futures Open Interest (stepline) for BTC perpetuals (BINANCE:BTCUSD.P_OI).
OI ROC plot with zero line and ±1σ / ±2σ guides.
Bar tinting when OI ROC > +2σ (aggressive leverage build) or < −2σ (aggressive deleveraging).
Side table showing current OI ROC, Price ROC, and the regime label.
Note: If applied to a non-crypto symbol, OI will be suppressed and the script will warn that no OI data is available. It is intended for BTC.
Inputs & customization
Color mode: Choose among preset palettes to match your chart style.
(Other logic—lookbacks, σ-bands, and regime rules—are fixed to keep the reading consistent across users.)
How to use it
Confirm trends:
Leverage Rally with OI ROC above +1σ supports risk-on continuation.
Spot Rally can be constructive early in cycles, but be aware that OI can catch up quickly.
Caution in stress:
Leveraged Sell-Off often coincides with liquidation spikes and unstable conditions.
Deleveraging Sell-Off typically marks clearing phases; watch for stabilization as OI ROC returns toward 0.
Watch extremes:
±2σ moves in OI ROC are non-routine; combine with price structure, liquidations, and funding to refine decisions.
Use it as contextual confluence alongside your execution plan (levels, risk, and timeframe).
Chart-publishing guidance
Publish with a clean chart so the OI line, ROC bands, and regime label are easy to identify.
Avoid stacking unrelated indicators unless you explain why they are required to interpret the tool.
Limitations
OI feeds can vary by venue; this script uses Binance perpetual OI. Other venues may differ.
Short-term spikes (maintenance, outages, large block flows) can distort OI ROC for a few bars.
The σ-bands adapt to recent variability; regime persistence is more informative than a single spike.
Disclaimer
This script is for research and educational purposes only and is not financial advice. Trading involves risk, including loss of capital. Past performance does not predict or guarantee future results. Always validate on your timeframe and use robust risk management.
AASI | QRAASI | QR — Active Address Sentiment Index
What it is
AASI | QR is a market activity gauge that compares on-chain participation (Active Addresses) with price momentum. It highlights regimes where network usage accelerates/decelerates relative to price and uses adaptive bands to flag expansions that may precede trend continuation or fade. Designed for BTC (and any symbol with an “Active Addresses” feed), it provides clear, visual context rather than trade calls.
How it works (principle, not code)
Active Address Momentum (core signal)
The script measures the rate of change (ROC) of Active Addresses and builds dynamic, volatility-scaled bands around zero. When address momentum pushes into progressively higher (or lower) bands, it reflects broadening (or narrowing) participation.
Price Momentum Overlay (context)
A price ROC runs alongside address momentum so you can visually compare participation vs. price. This helps distinguish healthy trend strength (price rising with rising participation) from potential exhaustion (diverging behavior).
Adaptive Bands (regimes)
Bands (±1×, ±2×, ±3× of the dynamic scale) expand/contract with recent variability in address momentum. The background tint optionally highlights strong expansions:
• Upper expansions → potential risk-on phases
• Lower expansions → potential risk-off phases
No fixed overbought/oversold thresholds are hard-coded; the bands adapt to the current regime, which helps keep the tool relevant across market phases.
Why this is useful (originality & value)
Most momentum overlays watch price alone. AASI adds a behavioral layer by tracking how many participants are active while price moves. This helps:
Separate euphoric spikes (price up, participation flat/falling) from broad advance (price up, participation rising).
Spot early cooling (participation momentum fades before price) and late accelerations (fresh participation kick).
Maintain clarity via adaptive scaling, so signals don’t go “permanently stretched” in strong cycles.
What you see on the chart
Zero Baseline with three up/down bands (±1, ±2, ±3).
Active Address ROC (soft line, main signal).
Price ROC (overlay line for context).
Optional background tint when price ROC reaches the upper or lower adaptive zones.
Clean presentation: the script is self-contained and readable without other overlays.
Inputs & customization
Bands & Trend: toggle visibility of ±1/±2/±3 bands.
Active Address & Price: toggle the address ROC and price ROC plots.
Color Mode: switch palettes to match your layout.
Lookbacks: the internal dynamic scaling is derived from recent variability of address momentum (kept simple for usability).
How to use it
Confluence: Look for price ROC and address ROC moving in the same direction and entering higher bands → strengthens the risk-on case.
Divergence: Price pushing higher while address ROC stalls or falls toward lower bands → participation not confirming; be cautious.
Regime shifts: When address ROC crosses the zero line and sustains inside ±1/±2 bands, it often marks a state change (cooling → heating or vice-versa).
Combine responsibly: Use with your risk framework (position sizing, stops). AASI is context, not an auto-trader.
Scope & data notes
Designed for BTC with a GLASSNODE:BTC_ACTIVEADDRESSES series.
Can be applied to other assets only if a comparable “Active Addresses” feed exists for that symbol. If no feed is present, use price ROC alone just for context (reduced informational value).
The script relies on close-form series provided on TradingView; no external links or delegation required to interpret its purpose.
Chart-publishing guidance
Publish with a clean chart showing only AASI to keep outputs identifiable.
If you add drawings, use them strictly to illustrate where participation confirmed or diverged from price.
Limitations
On-chain participation data can be noisy around events, holidays, or network anomalies.
Adaptive bands reflect recent variability; sudden structural changes may require time to re-scale.
Not a buy/sell system; it’s a diagnostic layer for regime awareness and confirmation.
Disclaimer
This tool is for research and educational purposes only and is not financial advice. Trading and investing involve risk, including loss of capital. Past performance does not predict or guarantee future results. Always validate settings on your timeframe and use proper risk management.
Filter Signal 5🧭 Overview
“Filter Signal 5.0” is a professional confirmation and filtering tool designed to validate the true directional bias of any asset.
It combines price structure, volume dynamics, oscillator alignment, and multi-timeframe confirmation to detect high-probability directional setups while blocking false counter-trend signals.
The indicator calculates a directional score (0–4) based on the confluence of several technical conditions and displays both the current trend and the higher-timeframe trend in a compact on-chart dashboard.
⚙️ Core Logic
The indicator integrates four major analytical pillars:
Component Description Purpose
VWMA Trend Compares price to the Volume-Weighted Moving Average (VWMA 20). Detects the base trend (above = bullish, below = bearish).
Volume Flow Evaluates direction (buy/sell) and trend (rising/falling) of volume. Confirms institutional participation.
RSI Extreme Cross RSI crossing its SMA in extreme zones (<27 or >80). Identifies momentum reversals with statistical strength.
Oscillator Concordance Combines 3 signals (Stochastic, Fisher Transform, Williams %R). Measures broad technical consensus.
Each bullish or bearish confirmation adds +1 point to its respective score.
The final output is the comparison between scoreLong and scoreShort.
🧩 Multi-Timeframe Filter (MTF)
A higher-timeframe VWMA (e.g., Weekly or Monthly) is imported through request.security().
If the higher-timeframe trend is UP, bearish scores are suppressed.
If the higher-timeframe trend is DOWN, bullish scores are suppressed.
✅ This ensures entries are only taken in the direction of the dominant market trend.
🎯 Forecast Target System
Each new bar automatically generates a static forecast target (varip) based on the 10-bar average range:
If bullish → target = close + avgRange
If bearish → target = close − avgRange
This level is drawn as a yellow dashed line, providing a short-term statistical price projection.
🧮 Directional Logic Summary
Condition Weight Effect
Price > VWMA +1 Long Trend confirmation
Volume rising in buy candles +1 Long Institutional strength
RSI cross < 27 +1 Long Reversal signal
2 / 3 oscillators in buy mode +1 Long Statistical agreement
Mirror logic applies for short signals.
Final bias is determined by comparing total long vs short scores.
📊 Dashboard Information
Displayed at the bottom-left corner of the chart:
Field Meaning
📊 Trend Now Current directional bias (📈 UP / 📉 DOWN / ➡ NEUTRAL)
🎯 Forecast Target Predicted price level for the current bar
⏱ Filter MTF Higher timeframe used for filtering (e.g., W, 1M)
📐 Trend MTF Trend status of the higher timeframe
The dashboard updates dynamically on each bar close.
⚠️ Alerts
Two automatic alerts are available:
⚠️ Strong Buy: when scoreLong ≥ 3
⚠️ Strong Sell: when scoreShort ≥ 3
These appear only when at least three technical components agree.
📈 How to Use It
Load the indicator on your preferred asset and timeframe (recommended: Daily).
Set the higher timeframe filter (tf_selezione) → use “W” (Weekly) or “1M” (Monthly) for institutional alignment.
Wait for full confirmation:
Trend Now = 📈 UP and Trend MTF = 📈 UP → Long setup confirmed
Trend Now = 📉 DOWN and Trend MTF = 📉 DOWN → Short setup confirmed
Avoid trading when:
Trends are misaligned (different directions).
Score is < 2 / 4 (neutral zone).
🧠 Trading Logic Summary
Scenario Requirements Action
Long Setup Score ≥ 3 and MTF trend = UP Enter or hold long position
Short Setup Score ≥ 3 and MTF trend = DOWN Enter or hold short position
Neutral Mixed signals / MTF mismatch Stay flat – wait for breakout
🧮 Practical Example
When the daily timeframe prints 📈 Trend Now = UP, and the weekly filter shows 📐 Trend MTF = UP, the system has full alignment.
The yellow dashed line projects the short-term target for the move.
If volume direction and oscillators confirm, an alert “⚠️ Strong Buy” is automatically triggered.
✅ Ideal Usage
This indicator is designed to work together with Lanfranco’s other institutional models, such as:
TSI-RSI-ATR Dashboard → internal momentum and volatility,
Institutional Module / Smart Buy-Sell System → predictive divergence and volume compression,
Dynamic Price Targets / Sigma Bands → probabilistic price zones.
The “MTF Filter 4” acts as the final confirmation layer, the traffic-light system:
🟢 Green = confirmed direction,
🔴 Red = blocked signal,
🟠 Orange = neutral wait-state.
⚡ Summary
Type: Multi-factor signal confirmation tool
Core concept: Combine price + volume + oscillators + multi-timeframe filter
Best timeframe: Daily
Typical filter: Weekly or Monthly
Output: Directional bias, short-term forecast, institutional trend alignment
Chris Apriliony Trading StrategyStockSchool Following Trend
Uses the Moving Average (MA) method to identify short-term, medium-term, and long-term trends.
Trades are made only when all trends align in the same direction,
which is indicated by a green candle.
Chronos Reversal Labs🧬 Chronos Reversal Lab - Machine Learning Market Structure Analysis
OVERVIEW
Chronos Reversal Lab (CRL) is an advanced market structure analyzer that combines computational intelligence kernels with classical technical analysis to identify high-probability reversal opportunities. The system integrates Shannon Entropy analysis, Detrended Fluctuation Analysis (DFA), Kalman adaptive filtering, and harmonic pattern recognition into a unified confluence-based signal engine.
WHAT MAKES IT ORIGINAL
Unlike traditional reversal indicators that rely solely on oscillators or pattern recognition, CRL employs a multi-kernel machine learning approach that analyzes market behavior through information theory, statistical physics, and adaptive state-space estimation. The system combines these computational methods with geometric pattern analysis and market microstructure to create a comprehensive reversal detection framework.
HOW IT WORKS (Technical Methodology)
1. COMPUTATIONAL KERNELS
Shannon Entropy Analysis
Measures market uncertainty using information theory:
• Discretizes price returns into bins (user-configurable 5-20 bins)
• Calculates probability distribution entropy over lookback window
• Normalizes entropy to 0-1 scale (0 = perfectly predictable, 1 = random)
• Low entropy states (< 0.3 default) indicate algorithmic clarity phases
• When entropy drops, directional moves become statistically more probable
Detrended Fluctuation Analysis (DFA)
Statistical technique measuring long-range correlations:
• Analyzes price series across multiple box sizes (4 to user-set maximum)
• Calculates fluctuation scaling exponent (Alpha)
• Alpha > 0.5: Trend persistence (momentum regime)
• Alpha < 0.5: Mean reversion tendency (reversal regime)
• Alpha range 0.3-1.5 mapped to trading strategies
Kalman Adaptive Filter
State-space estimation for lag-free trend tracking:
• Maintains separate fast and slow Kalman filters
• Process noise and measurement noise are user-configurable
• Tracks price state with adaptive gain adjustments
• Calculates acceleration (second derivative) for momentum detection
• Provides cleaner trend signals than traditional moving averages
2. HARMONIC PATTERN DETECTION
Identifies geometric reversal patterns:
• Gartley: 0.618 AB/XA, 0.786 AD/XA retracement
• Bat: 0.382-0.5 AB/XA, 0.886 AD/XA retracement
• Butterfly: 0.786 AB/XA, 1.272-1.618 AD/XA extension
• Cypher: 0.382-0.618 AB/XA, 0.786 AD/XA retracement
Pattern Validation Process:
• Requires alternating swing structure (XABCD points)
• Fibonacci ratio tolerance: 0.02-0.20 (user-adjustable precision)
• Minimum 50% ratio accuracy score required
• PRZ (Potential Reversal Zone) calculated around D point
• Zone size: ATR-based with pattern-specific multipliers
• Active pattern tracking with 100-bar invalidation window
3. MARKET STRUCTURE ANALYSIS
Swing Point Detection:
• Pivot-based swing identification (3-21 bars configurable)
• Minimum swing size: ATR multiples (0.5-5.0x)
• Adaptive filtering: volatility regime adjustment (0.7-1.3x)
• Swing confirmation tracking with RSI and volume context
• Maintains structural history (up to 500 swings)
Break of Structure (BOS):
• Detects price crossing previous swing highs/lows
• Used for trend continuation vs reversal classification
• Optional requirement for signal validation
Support/Resistance Detection:
• Identifies horizontal levels from swing clusters
• Touch counting algorithm (price within ATR×0.3 tolerance)
• Weighted by recency and number of tests
• Dynamic updating as structure evolves
4. CONFLUENCE SCORING SYSTEM
Multi-factor analysis with regime-aware weighting:
Hierarchical Kernel Logic:
• Entropy gates advanced kernel activation
• Only when entropy < threshold do DFA and Kalman accelerate scoring
• Prevents false signals during chaotic (high entropy) conditions
Scoring Components:
ML Kernels (when entropy low):
• Low entropy + trend alignment: +3.0 points × trend weight
• DFA super-trend (α>1.5): +4.0 points × trend weight
• DFA persistence (α>0.65): +2.5 points × trend weight
• DFA mean-reversion (α<0.35): +2.0 points × mean-reversion weight
• Kalman acceleration: up to +3.0 points (scaled by magnitude)
Classical Technical Analysis:
• RSI oversold (<30) / overbought (>70): +1.5 points
• RSI divergence (bullish/bearish): +2.5 points
• High relative volume (>1.5x): +0-2.0 points (scaled)
• Volume impulse (>2.0x): +1.5 points
• VWAP extremes: +1.0 point
• Trend alignment (Kalman fast vs slow): +1.5 points
• MACD crossover/momentum: +1.0 point
Structural Factors:
• Near support (within 0.5 ATR): +0-2.0 points (inverse distance)
• Near resistance (within 0.5 ATR): +0-2.0 points (inverse distance)
• Harmonic PRZ zone: +3.0 to +6.0 points (pattern score dependent)
• Break of structure: +1.5 points
Regime Adjustments:
• Trend weight: 1.5× in trend regime, 0.5× in mean-reversion
• Mean-reversion weight: 1.5× in MR regime, 0.5× in trend
• Volatility multiplier: 0.7-1.3× based on ATR regime
• Theory mode multiplier: 0.8× (Conservative) to 1.2× (APEX)
Final Threshold:
Base threshold (default 3.5) adjusted by:
• Theory mode: -0.3 (APEX) to +0.8 (Conservative)
• Regime: +0.5 (high vol) to -0.3 (low vol or strong trend)
• Filter: +0.2 if regime filter enabled
5. SIGNAL GENERATION ARCHITECTURE
Five-stage validation process:
Stage 1 - ML Kernel Analysis:
• Entropy threshold check
• DFA regime classification
• Kalman acceleration confirmation
Stage 2 - Structural Confirmation:
• Market structure supports directional bias
• BOS alignment (if required)
• Swing point validation
Stage 3 - Trigger Validation:
• Engulfing candle (if required)
• HTF bias confirmation (if strict HTF enabled)
• Harmonic PRZ alignment (if confirmation enabled)
Stage 4 - Consistency Check:
• Anticipation depth: checks N bars back (1-13 configurable)
• Ensures Kalman acceleration direction persists
• Filters whipsaw conditions
Stage 5 - Structural Soundness (Critical Filter):
• Verifies adequate room before next major swing level
• Long signals: must have >0.25 ATR clearance to last swing high
• Short signals: must have >0.25 ATR clearance to last swing low
• Prevents trades directly into obvious structural barriers
Dynamic Risk Management:
• Stop-loss: Placed beyond last structural swing ± 2 ticks
• Take-profit 1: Risk × configurable R1 multiplier (default 1.5R)
• Take-profit 2: Risk × configurable R2 multiplier (default 3.0R)
• Confidence score: Calibrated 0-99% based on confluence + kernel boost
6. ADAPTIVE REGIME SYSTEM
Continuous market state monitoring:
Trend Regime:
• Kalman fast vs slow positioning
• Multi-timeframe alignment (optional HTF)
• Strength: ATR-normalized fast/slow spread
Volatility Regime:
• Current ATR vs 100-bar average
• Regime ratio: 0.7-1.3 typical range
• Affects swing size filtering and cooldown periods
Signal Cooldown:
• Base: User-set bars (1-300)
• High volatility (>1.5): cooldown × 1.5
• Low volatility (<0.5): cooldown × 0.7
• Post-BOS: minimum 20-bar cooldown enforced
FOUR OPERATIONAL MODES
CONSERVATIVE MODE:
• Threshold adjustment: +0.8
• Mode multiplier: 0.8×
• Strictest filtering for highest quality
• Recommended for: Beginners, large accounts, swing trading
• Expected signals: 3-5 per week (typical volatile instrument)
BALANCED MODE:
• Threshold adjustment: +0.3
• Mode multiplier: 1.0×
• Standard operational parameters
• Recommended for: General trading, learning phase
• Expected signals: 5-10 per week
APEX MODE:
• Threshold adjustment: -0.3
• Mode multiplier: 1.2×
• Maximum sensitivity, reduced cooldowns
• Recommended for: Scalping, high volatility, experienced traders
• Expected signals: 10-20 per week
INSTITUTIONAL MODE:
• Threshold adjustment: +0.5
• Mode multiplier: 1.1×
• Enhanced structural weighting, HTF emphasis
• Recommended for: Professional traders, swing positions
• Expected signals: 4-8 per week
VISUAL COMPONENTS
1. Fibonacci Retracement Levels
• Auto-calculated from most recent swing structure
• Standard levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%, 127.2%, 161.8%, 200%, 261.8%
• Key levels emphasized (50%, 61.8%, 100%, 161.8%)
• Color gradient from bullish to bearish based on level
• Automatic cleanup when levels are crossed
• Label intensity control (None/Fib only/All)
2. Support and Resistance Lines
• Dynamic horizontal levels from swing clusters
• Width: 2px solid lines
• Colors: Green (support), Red (resistance)
• Labels show price and level type
• Touch-based validation (minimum 2 touches)
• Real-time updates and invalidation
3. Harmonic PRZ Boxes
• Displayed around pattern completion (D point)
• Pattern-specific colors (Gartley: purple, Bat: orange, etc.)
• Box height: ATR-based zone sizing
• Score-dependent transparency
• 100-bar active window before removal
4. Confluence Boxes
• Appear when confluence ≥ threshold
• Yellow/orange gradient based on score strength
• Height: High to low of bar
• Width: 1 bar on each side
• Real-time score-based transparency
5. Kalman Filter Lines
• Fast filter: Bullish color (green default)
• Slow filter: Bearish color (red default)
• Width: 2px
• Transparency adjustable (0-90%)
• Optional display toggle
6. Signal Markers
• Long: Green triangle below bar (tiny size)
• Short: Red triangle above bar (tiny size)
• Appear only on confirmed signals
• Includes alert generation
7. Premium Dashboard
Features real-time metrics with visual gauges:
Layout Options:
• Position: 4 corners selectable
• Size: Small (9 rows) / Normal (12 rows) / Large (14 rows)
• Themes: Supreme, Cosmic, Vortex, Heritage
Metrics Displayed:
• Gamma (DFA - 0.5): Shows trend persistence vs mean-reversion
• TCI (Trend Strength): ATR-normalized Kalman spread with gauge
• v/c (Relative Volume): Current vs average with color coding
• Entropy: Market predictability state with gauge
• HFL (High-Frequency Line): Kalman fast/slow difference / ATR
• HFL_acc (Acceleration): Second derivative momentum
• Mem Bias: Net bullish-bearish confluence (-1 to +1)
• Assurance: Confidence × (1-entropy) metric
• Squeeze: Bollinger Band / Keltner Channel squeeze detection
• Breakout P: Probability estimate from DFA + trend + acceleration
• Score: Final confluence vs threshold (normalized)
• Neighbors: Active harmonic patterns count
• Signal Strength: Strong/Moderate/Weak classification
• Signal Banner: Current directional bias with emoji indicators
Gauge Visualization:
• 10-bar horizontal gauges (█ filled, ░ empty)
• Color-coded: Green (strong) / Gold (moderate) / Red (weak)
• Real-time updates every bar
HOW TO USE
Step 1: Configure Mode and Resolution
• Select Theory Mode based on trading style (Conservative/Balanced/APEX/Institutional)
• Set Structural Resolution (Standard for fast markets, High for balanced, Ultra/Institutional for swing)
• Enable Adaptive Filtering (recommended for all volatile assets)
Step 2: Enable Desired Kernels
• Shannon Entropy: Essential for predictability detection (recommended ON)
• DFA Analysis: Critical for regime classification (recommended ON)
• Kalman Filter: Provides lag-free trend tracking (recommended ON)
• All three work synergistically; disabling reduces effectiveness
Step 3: Configure Confluence Factors
• Enable desired technical factors (RSI, MACD, Volume, Divergence)
• Enable Liquidity Mapping for support/resistance proximity scoring
• Enable Harmonic Detection if trading pattern-based setups
• Adjust base confluence threshold (3.5 default; higher = fewer, cleaner signals)
Step 4: Set Trigger Requirements
• Require Engulfing: Adds precision, reduces frequency (recommended for Conservative)
• Require BOS: Ensures structural alignment (recommended for trend-following)
• Require Structural Soundness: Critical filter preventing traps (highly recommended)
• Strict HTF Bias: For multi-timeframe traders only
Step 5: Adjust Visual Preferences
• Enable/disable Fibonacci levels, S/R lines, PRZ boxes, confluence boxes
• Set label intensity (None/Fib/All)
• Adjust transparency (0-90%) for overlay clarity
• Configure dashboard position, size, and theme
Step 6: Configure Alerts
• Enable master alerts toggle
• Select alert types: Anticipation, Confirmation, High Confluence, Low Entropy
• Enable JSON details for automated trading integration
Step 7: Interpret Signals
• Wait for triangle markers (green up = long, red down = short)
• Check dashboard for confluence score, entropy, DFA regime
• Verify signal aligns with higher timeframe bias (if using HTF setting)
• Confirm adequate space to take-profit levels (no nearby structural barriers)
Step 8: Execute and Manage
• Enter at close of signal candle (or next bar open)
• Set stop-loss at calculated level (visible in alert if JSON enabled)
• Scale out at TP1 (1.5R default), trail remaining to TP2 (3.0R default)
• Exit early if entropy spikes >0.7 or DFA regime flips against position
CUSTOMIZATION GUIDE
Timeframe Optimization:
Scalping (1-5 minutes):
• Theory Mode: APEX
• Anticipation Depth: 3-5
• Structural Resolution: STANDARD
• Signal Cooldown: 8-12 bars
• Enable fast kernels, disable HTF bias
Day Trading (15m-1H):
• Theory Mode: BALANCED
• Anticipation Depth: 5-8
• Structural Resolution: HIGH
• Signal Cooldown: 12-20 bars
• Standard configuration
Swing Trading (4H-Daily):
• Theory Mode: INSTITUTIONAL
• Anticipation Depth: 8-13
• Structural Resolution: ULTRA or INSTITUTIONAL
• Signal Cooldown: 20-50 bars
• Enable HTF bias, strict confirmations
Market Type Optimization:
Forex Majors:
• All kernels enabled
• Harmonic patterns effective
• Balanced or Institutional mode
• Standard settings work well
Stock Indices:
• Emphasis on volume analysis
• DFA critical for regime detection
• Conservative or Balanced mode
• Enable liquidity mapping
Cryptocurrencies:
• Adaptive filtering essential
• Higher volatility regime expected
• APEX mode for active trading
• Wider ATR multiples for swing sizing
IMPORTANT DISCLAIMERS
• This indicator does not predict future price movements
• Computational kernels calculate probabilities, not certainties
• Past confluence scores do not guarantee future signal performance
• Always backtest on YOUR specific instruments and timeframes before live trading
• Machine learning kernels require calibration period (minimum 100 bars of data)
• Performance varies significantly across market conditions and regimes
• Signals are suggestions for analysis, not automated trading instructions
• Proper risk management (stops, position sizing) is mandatory
• Complex calculations may impact performance on lower-end devices
• Designed for liquid markets; avoid illiquid or gap-prone instruments
PERFORMANCE CONSIDERATIONS
Computational Intensity:
• DFA analysis: Moderate (scales with length and box size parameters)
• Entropy calculation: Moderate (scales with lookback and bins)
• Kalman filtering: Low (efficient state-space updates)
• Harmonic detection: Moderate to High (pattern matching across swing history)
• Overall: Medium computational load
Optimization Tips:
• Reduce Structural Analysis Depth (144 default → 50-100 for faster performance)
• Increase Calc Step (2 default → 3-4 for lighter load)
• Reduce Pattern Analysis Depth (8 default → 3-5 if harmonics not primary focus)
• Limit Draw Window (150 bars default prevents visual clutter on long charts)
• Disable unused confluence factors to reduce calculations
Best Suited For:
• Liquid instruments: Major forex, stock indices, large-cap crypto
• Active timeframes: 5-minute through daily (avoid tick/second charts)
• Trending or ranging markets: Adapts to both via regime detection
• Pattern traders: Harmonic integration adds geometric confluence
• Multi-timeframe analysts: HTF bias and regime detection support this approach
Not Recommended For:
• Illiquid penny stocks or micro-cap altcoins
• Markets with frequent gaps (stocks outside regular hours without gap adjustment)
• Extremely fast timeframes (tick, second charts) due to calculation overhead
• Pure mean-reversion systems (unless using CONSERVATIVE mode with DFA filters)
METHODOLOGY NOTE
The computational kernels (Shannon Entropy, DFA, Kalman Filter) are established statistical and signal processing techniques adapted for financial time series analysis. These are deterministic mathematical algorithms, not predictive AI models. The term "machine learning" refers to the adaptive, data-driven nature of the calculations, not neural networks or training processes.
Confluence scoring is rule-based with regime-dependent weighting. The system does not "learn" from historical trades but adapts its sensitivity to current volatility and trend conditions through mathematical regime classification.
SUPPORT & UPDATES
• Questions about configuration or usage? Send me a message on TradingView
• Feature requests are welcome for consideration in future updates
• Bug reports appreciated and addressed promptly
• I respond to messages within 24 hours
• Regular updates included (improvements, optimizations, new features)
FINAL REMINDERS
• This is an analytical tool for confluence analysis, not a standalone trading system
• Combine with your existing strategy, risk management, and market analysis
• Start with paper trading to learn the system's behavior on your markets
• Allow 50-100 signals minimum for performance evaluation
• Adjust parameters based on YOUR timeframe, instrument, and trading style
• No indicator guarantees profitable trades - proper risk management is essential
— Dskyz, Trade with insight. Trade with anticipation.
Smart Liquidity Zones v1 — for Gold only and for Trump🚀 Smart Liquidity Zones v1 – Fixed Filters + Stable Zones + Safe Stop
Designed exclusively for XAUUSD (Gold), this tool captures the true rhythm of liquidity hidden behind market volatility.
Originally engineered for the Trump-era gold movements, this version blends precision filtering, adaptive volatility logic, and secure dynamic stop levels — giving traders a structured edge in chaos.
💡 Whether you're scalping micro swings or analyzing multi-hour trends, the algorithm visualizes where the market’s liquidity traps lie — and how price reacts once those levels are engaged.
⚙️ Key Features
✨ Adaptive zone recognition system (smart filtering logic).
✨ Safe Stop framework with dynamic ATR buffer.
✨ Multi-layer filtering using candle, ATR, and volume behavior.
✨ Visual clarity with zone strength gradient for better risk reading.
✨ Auto-clean memory system for stable long sessions.
⚠️ Note: This tool is built exclusively for Gold traders (XAUUSD).
Optimized for 5m–1h charts. Works best during volatile sessions.
🧩 Settings Panel (Explained Without Revealing Logic)
🔹 Swing Length:
Controls how far the algorithm looks back to detect potential liquidity pivots.
(Higher = stronger zones, fewer signals.)
🔹 Extend To The Right:
How long the zone extends into the future — perfect for visual planning.
🔹 Zone Height:
Defines the visual range of each liquidity zone (recommended: 6.5 for Gold).
🔹 Min Distance Between Zones:
Prevents overlapping or cluttered zones to keep the chart clean.
🔹 Filters (ATR / Candle / Volume):
Three independent smart filters ensuring that only valid and powerful liquidity zones are drawn.
🔹 Dynamic Stop Buffer:
Automatically adjusts your safe stop level based on volatility (ATR).
🔹 Safe Stop Colors:
Customize visual clarity for stop levels — instantly spot your safety net.
⚡ Unique Concept
Built for traders who understand that liquidity is the market’s heartbeat,
and that true opportunity lies where stop hunts and smart money meet.
🟡 A smart visual system —
🔴 A safety layer for volatile times —
💰 And a nod to the wild gold markets during the Trump era.
📊 Recommended Use
Pair it with clean price action & structure.
Avoid indicator stacking — simplicity = power.
Gold (XAUUSD) only — this algorithm is not calibrated for forex pairs or crypto.
🔹 Best Settings for Gold:
Zone Height = 6.5
Swing Length = 10
Dynamic Stop Buffer = 0.5 ATR
Filters ON (ATR + Candle + Volume)
Quantum Reservoir Computing⚛ Quantum Reservoir Computing - Multi-Scale Market Analysis
OVERVIEW
This indicator combines three structural analysis kernels (Energy, Resonance, Topology) with a 6-spin reservoir computing network to provide multi-dimensional market state monitoring. It is designed to detect structural shifts, coherence alignment, and potential entry timing through visual analytics and optional signal markers.
WHAT MAKES IT ORIGINAL
Unlike single-indicator approaches, QRC fuses complementary analysis methods and uses a reservoir computing layer (coupled oscillator network) to capture temporal market structure. The system uses entropy-compensated signal logic to maintain directional alignment across kernels with inverted mathematical properties.
HOW IT WORKS (Technical Details)
1. ENERGY KERNEL
Measures compression state through two components:
• Entropy: Volatility-normalized return distribution, inverted (low volatility = high compression energy)
• ATR Compression: Short-period ATR divided by longer-period baseline ATR
• Final Energy: Weighted average of both components, ranging 0 to 1
2. RESONANCE KERNEL
Calculates cross-timeframe coherence using:
• 6 exponential moving averages (periods: 9, 14, 20, 30, 48, 84)
• Slope calculation for each EMA
• Amplitude weighting based on user-selected mode (Close/ATR/StDev)
• Coherence Index (CI): Measures directional agreement across all timeframes
• Mode Persistence: Stability of CI over 20 bars
3. TOPOLOGY KERNEL
Analyzes path geometry through:
• Turn density: Rate of price directional changes
• Curvature: Second-order price differences normalized by ATR
• Combined into a 0-1 topology change metric
4. RESERVOIR COMPUTING (6-Spin Network)
Six coupled state variables (spins) arranged in a ring topology:
• Drive signal combines directional consensus, price z-score, volume, and ATR regime
• Each spin updates via hyperbolic tangent activation with neighbor coupling
• Psi (Ψ): Coherence measure (average pairwise spin correlation)
• Spin Direction: Signed average of all spins
• Pulse detection: Positive changes in Ψ, z-scored to detect energy releases
5. FUSION & SCORING
• Magnitude: Weighted combination of all kernels (0 to 1 scale)
• Direction: Blend of EMA slope consensus, basis slope, and spin direction (-1 to 1)
• ScoreSigned: Direction multiplied by Magnitude (drives visuals)
• GateScore: Amplified score used only for signal threshold checks
• Heat: Entanglement measure combining Ψ, CI, and Magnitude
SIGNAL LOGIC (Important: Entropy-Compensated Inversion)
Because the entropy kernel naturally inverts (low volatility = bullish compression), signal logic compensates to maintain directional alignment:
• LONG signals fire when GateScore crosses below the short threshold (bearish GateScore + bullish structure)
• SHORT signals fire when GateScore crosses above the long threshold (bullish GateScore + bearish structure)
This inversion has been visually validated through metric plotting and maintains correct alignment with Resonance and Topology kernels.
Signal gates require:
• Two-of-three pass: CI ≥ minimum, Mode Persistence ≥ minimum, Ψ ≥ minimum
• Heat ≥ minimum threshold
• OR recent pulse window active (ΔΨ edge within N bars)
• Minimum bar spacing between signals (prevents clustering)
VISUAL COMPONENTS
1. Contained Ribbon (Recommended Mode)
• Center line: Basis EMA
• Edge: Positioned by ScoreSigned value
• Fill color: Green (bullish) or Red (bearish)
• Width: ATR-adaptive with configurable floor/ceiling
2. Quantum Aurora (Multi-Layer Energy Bands)
• 5-8 harmonic layers with phase-driven oscillations
• Colors shift with Heat level (cool blue at low Heat, warm orange/magenta at high Heat)
• Creates visual texture that reflects market state dynamics
3. Interference Mesh
• Subtle oscillating overlay modulated by CI and ScoreSigned
• Provides depth perception without visual clutter
4. Resonance Cloud
• Width proportional to Coherence Index
• Wide cloud = strong cross-timeframe alignment
• Narrow cloud = weak structural coherence
5. Energy Particles
• Floating micro-dots with density mapped to Magnitude
• Color-coded by Heat level (gold/cyan/gray)
• Provides continuous conviction feedback
6. Regime Atmosphere
• Background tint indicating market mode:
- Green: Coherent trend (CI>0.65, Ψ>0.55)
- Red: Choppy regime (CI<0.45, Ψ<0.40)
- Purple: Transition state
DASHBOARDS
1. Main Dashboard (Moveable, Resizable)
• Regime indicator with color-coded status
• Horizontal meter gauges for Ψ, CI, Heat, Magnitude
• Signal strength bars for Score and Gate
• Status indicators (dots) for ΔΨ, Heat, CI health
• Directional arrows and bars-since-signal counter
• Size options: Tiny, Small, Normal, Large
• Position: All four corners available
2. Heat HUD (Entanglement Matrix)
• Multi-row gradient display of last N bars (configurable 10-120)
• Metrics: Heat, Psi, CI, Magnitude, Pulse Z-score, Gate proximity
• Color-coded blocks show metric intensity over time
• Live footer with current values
• Resizable and moveable
HOW TO USE
Step 1: Monitor Regime and Structure
• Check Dashboard regime indicator (Trend/Chop/Transition)
• Observe Aurora flow (smooth = stable, erratic = unstable)
• Wide Resonance Cloud indicates strong multi-timeframe alignment
Step 2: Watch Entanglement Heat
• Heat HUD shows persistent structure as amber/red runs
• Green status dots indicate healthy metrics
• Rising Heat + rising Ψ suggests mode-locking
Step 3: Confirm Gate Conditions
• Dashboard displays effective thresholds (dynamically relaxed after dry periods)
• Two-of-three gate (CI/ModePersistence/Ψ) must pass OR recent pulse active
• Strength bars show conviction level
Step 4: Interpret Signals
• Enable "Show Diagnostic Plots" to verify metric behavior on your symbols
• Signals appear as tiny triangles (green below bars = long, red above = short)
• Best confluence: Heat rising + fresh pulse cluster + strong CI
Step 5: Risk Management
• Place stops beyond opposite ribbon edge plus 0.5 ATR buffer
• Trail stops following basis ± ATR fraction while Heat/Psi remain elevated
• Exit early if CI or Ψ collapse (status dots turn yellow/red)
CUSTOMIZATION
Extensive settings available:
• Core: EMA length, ATR length, pulse thresholds, heat minimum
• Signals: Mode (Aggressive/Normal/Conservative), thresholds, spacing, gain
• Visuals: Ribbon mode, Aurora layers, particle density, all show/hide toggles
• Dashboards: Size, position for both main dashboard and heat HUD
• Diagnostics: Optional metric plots for validation
IMPORTANT DISCLAIMERS
• This indicator does not predict future price movements
• Signals use entropy-compensated inversion (explained above); verify on your symbols
• Always backtest on your specific markets and timeframes before live trading
• Past performance does not guarantee future results
• Heavy visuals may impact performance on lower-end devices (use Performance toggles)
• Designed for liquid markets (major indices, forex, crypto); may underperform on illiquid symbols
• Complex system with learning curve; read full guide embedded in code
DIAGNOSTIC MODE
Enable "Show Diagnostic Plots" in settings to verify metric behavior:
• Heat, Psi, CI, Magnitude plotted in lower pane
• ScoreSigned and GateScore normalized to 0-1 scale
• Reference lines at 0.25, 0.5, 0.75 for threshold context
• Observe metric alignment with price action on YOUR symbols
METHODOLOGY NOTE
The "Quantum" terminology refers to the reservoir computing methodology (coupled oscillator network), not actual quantum mechanics. The 6-spin network uses hyperbolic tangent activation functions to model temporal market structure. This is a deterministic mathematical model, not a quantum computing system.
BEST SUITED FOR
• Liquid markets: Major indices (ES, NQ), forex majors (EUR/USD, GBP/USD), large-cap crypto (BTC, ETH)
• Timeframes: 5-minute through daily (works on all, but designed for intraday to swing)
• Trading styles: Structure-based entries, multi-timeframe confluence, visual state monitoring
• Experience level: Intermediate to advanced (complex system with learning curve)
PERFORMANCE CONSIDERATIONS
• Heavy calculations (6 spins, 6 EMAs, Aurora layers, particles) may lag on lower-end devices
• Use "Dashboard Size: Tiny" and reduce "Aurora Layers" to 2-3 for better performance
• Consider disabling "Energy Particles" on mobile devices
• Script is optimized with array capping and label recycling, but complexity remains high
SUPPORT & UPDATES
• Questions about usage or settings? Send me a message - I respond within 24 hours
• Feature requests are welcome for consideration in future updates
• Bug reports appreciated and addressed promptly
• Script will be maintained and updated as needed
FINAL REMINDERS
• This is an analytical tool, not a trading system
• Always backtest on YOUR symbols and timeframes before live use
• Use proper risk management - stops, position sizing, etc.
• Past performance does not guarantee future results
• Start with demo/paper trading to learn the system
— Dskyz, Trade with insight. Trade with anticipation.
Tether USDT DominanceThis indicator displays Tether (USDT) dominance as a MACD-style oscillator, using data from the CRYPTOCAP:USDT.D symbol. It includes:
MACD Line: Blue line showing the difference between fast and slow EMAs (default periods: 12/26).
Signal Line: Orange line as the SMA of the MACD (default period: 9).
Histogram: Columns with fading transparency—full color (green for positive, red for negative) when bars grow, semi-transparent when they shrink, indicating momentum changes.
Zero Line: Dotted gray line for reference.
Users can customize EMA and signal periods in the settings. Add to the bottom panel for crypto market analysis, where falling USDT dominance often signals altcoin rallies. Data fetched via TradingView's built-in security function. No alerts or trading signals included.
Overnight Range with Midline (RTH plots only)Overnight range: high and low with midline. Use it on ES, NQ, and Equity. Use for range or breakout.
CENDERE ALLTIMEWhat is CENDERE ALLTIME?
CENDERE ALLTIME is a sophisticated moving average crossover trading indicator that helps you identify buy and sell opportunities in the market. It compares two moving averages (fast and slow) and generates signals when they cross each other.
Key Features
✅ Flexible MA Selection - Choose from 8 different moving average types
✅ Automatic Backtesting - Test your strategy on historical data
✅ Signal Labels - Visual buy/sell signals with profit/loss percentages
✅ Optimization Engine - Finds the best MA combinations automatically
✅ Dual Statistics - View performance for both backtest period and all-time data
How It Works
The Strategy Logic
BUY Signal (Entry):
Triggers when the Fast MA crosses ABOVE the Slow MA
Entry price: Closing price of the signal candle
A blue label appears showing the entry price
SELL Signal (Exit):
Triggers when the Fast MA crosses BELOW the Slow MA
Exit price: Opening price of the signal candle
A green/red label appears showing exit price and profit/loss percentage
Settings Overview
1. MA Settings
Fast MA (Green Line by default)
Type: Choose from SMA, EMA, WMA, VWMA, RMA, HMA, DEMA, ALMA
Length: 10-100 bars (default: 20)
Color: Customizable
Slow MA (Red Line by default)
Type: Choose from SMA, EMA, WMA, VWMA, RMA, HMA, DEMA, ALMA
Length: 10-100 bars (default: 30)
Color: Customizable
💡 Tip: Fast MA should always be shorter than Slow MA for proper crossover signals.
2. Backtest Settings
Initial Capital: Starting amount for simulation (default: $1000)
Backtest Bar Count: Number of recent bars to test (default: 500)
3. Display Settings
Show MA Lines: Toggle visibility of moving average lines
Show Buy/Sell Signals: Toggle signal markers on chart
Show Optimization Table: Display best MA combinations
Show Labels: Toggle buy/sell price labels with P&L
4. Line Customization
Line Width: 1-5 pixels thickness
Line Style: Solid, Dashed, or Dotted
Reading the Signals
Buy Signal (Blue Label)
Example: 45.3
Appears below the candle
Shows the entry price (closing price)
Enter long position at this price
Sell Signal (Green/Red Label)
Example: 48.7
+7.52%
Appears above the candle
Top number: Exit price (opening price)
Bottom number: Profit/loss percentage
Green = Profit | Red = Loss
Understanding Statistics
The indicator tracks two sets of statistics:
Current Backtest Period
Tests only the last X bars (defined in settings)
Resets when you change the backtest period
Useful for recent performance analysis
All-Time Statistics
Tests from the beginning of available data
Never resets
Shows overall strategy performance
Key Metrics:
Total Return %: Overall profit/loss percentage
Win Rate: Percentage of profitable trades
Number of Trades: Total completed trades
Final Capital: Ending balance after all trades
Average Duration: Average bars held per trade
Optimization Feature
The indicator automatically tests 45 different MA combinations and ranks them by performance.
Tested Combinations:
Fast MA: 10, 20, 30, 40, 50, 60, 70, 80, 90
Slow MA: 20, 30, 40, 50, 60, 70, 80, 90, 100
Only valid pairs where Fast < Slow
How to Use:
Enable "Show Optimization Table" in settings
View the table showing top-performing combinations
Note the best Fast/Slow MA lengths
Manually adjust your MA settings to match the optimal values
Best Practices
For Beginners
Start with default settings (20/30 SMA)
Test on 500 bars to see recent performance
Look for combinations with high win rate (>50%)
Prefer strategies with reasonable trade frequency (not too many/few)
For Advanced Users
Experiment with different MA types (EMA for faster response, SMA for smoothness)
Test various timeframes (4H, 1D, 1W)
Combine with other indicators for confirmation
Consider market conditions (trending vs ranging)
Risk Management Tips
⚠️ Always use stop-losses (indicator doesn't include stops)
⚠️ Past performance doesn't guarantee future results
⚠️ Verify signals with volume and price action
⚠️ Start with small position sizes when live trading
Common MA Types Explained
TypeDescriptionBest ForSMASimple Moving AverageSmooth, reliable, general useEMAExponential MAFaster response, trending marketsWMAWeighted MARecent price emphasisVWMAVolume-Weighted MAVolume-based tradingRMARSI Moving AverageSmoothing volatilityHMAHull MAVery fast, reduced lagDEMADouble Exponential MAReduced lag, fast signalsALMAArnaud Legoux MASmooth with low lag
Troubleshooting
Problem: No signals appearing
Check if Fast MA < Slow MA in length
Increase backtest bar count
Verify indicator is applied correctly
Problem: Too many signals
Increase MA lengths (less sensitivity)
Try slower MA types (SMA instead of EMA)
Switch to higher timeframe
Problem: Labels overlapping
Reduce zoom level
Disable labels and use signal markers only
Adjust line width to make chart cleaner
SerenitySerenity: Find Serenity in Market Chaos
Every trader starts somewhere, often diving headfirst into the markets with charts cluttered by layers of lines, oscillators, and signals. It's easy to get caught up testing one approach after another—adding more tools, tweaking strategies, chasing the latest idea that promises clarity. The cycle repeats: overload the setup, second-guess every move, switch things up when results don't click right away. Over time, it becomes clear that jumping between setups rarely builds the consistency needed to navigate the ups and downs.
That's where the idea for Serenity came from—a way to step back from the noise and focus on a structured approach that encourages sticking to a plan and building consistency.
Built on the philosophy that no single perspective captures the full picture, Serenity offers two complementary views—Skye and Shade—to provide a more rounded interpretation of the market. Serenity’s logic builds on core market concepts—trend, momentum, and volume—combining them through carefully structured conditions that work across multiple timeframes. By focusing on where these elements align, it highlights key moments in the market while filtering out noise, providing clear and meaningful visual cues for analysis.
Skye focuses on faster-moving trends and momentum shifts, highlighting potential opportunities with a riskier, more agile approach. Shade takes a more conservative stance, emphasizing broader confirmations through volume and market structure. By integrating multiple timeframes and carefully crafted conditions, Serenity identifies key moments where price action, momentum, and market strength converge. Whether you're a scalper chasing quick moves, a day trader riding intraday waves, or a swing trader eyeing longer trends, Serenity adapts to any trading style, offering a flexible lens for both risk-tolerant and cautious approaches. Used together, Skye and Shade create a balanced view, filtering out distractions without overcomplicating the chart.
Even with its structure, Serenity remains a framework for interpretation—built on trend, momentum, and volume concepts that distill complex market movement into clear, visual markers like color shifts or highlighted zones. It’s a tool to see through the chaos, not a definitive answer.
Understanding Serenity’s Two Perspectives
Serenity is built around two complementary perspectives—Skye and Shade—each designed to interpret market behavior through a distinct lens. While they share the same foundation of trend, momentum, and volume analysis, they differ in speed, sensitivity, and purpose.
Skye
Skye focuses on the faster side of market behavior. It reacts quickly to changes in trend and momentum, making it well-suited for traders who prefer agility and earlier entries. Skye thrives in environments where price moves sharply and timing matters.
Its logic leans on short-term structure shifts, refined momentum cues, and cross-timeframe alignment to highlight areas where strength is building or fading. The perspective is intentionally more responsive—capturing movement before it’s fully confirmed, at the cost of increased sensitivity.
Shade
Shade takes a steadier, more measured approach. Where Skye seeks opportunity in early momentum, Shade looks for confirmation—aligning trend, volume, and structure to reinforce conviction.
It filters out minor fluctuations to focus on broader conditions, offering a cleaner perspective on established direction and underlying market strength. This makes it particularly suited for traders who value confirmation over speed—day traders looking for solid follow-through or swing traders aiming for consistency across larger moves.
Serenity’s Reversal Signals
In addition to its dual perspectives, Serenity provides two signal markers designed to highlight potential reversal areas:
Twilight Reversal
Twilight draws attention to areas where upward momentum might begin to build. It serves as a visual cue for zones where buying interest could be forming, helping you focus on potential opportunities for a positive shift in market behavior.
Eclipse Reversal
Eclipse highlights areas where downward pressure may be emerging. It marks zones where sellers could be gaining influence, guiding your attention to potential points where market strength may start to wane.
Together, these signals act as complementary tools to Skye and Shade, helping you interpret the market by showing areas where momentum could be shifting, all while keeping the chart clean and structured.
Flip to GreenPurpose:
This indicator applies a Lorentzian-distance–based machine-learning model to classify market conditions and highlight probable momentum shifts.
Where traditional indicators react to price movement, this one uses statistical pattern recognition to predict when momentum is likely to flip direction — the classic “flip to green” signal.
Concept:
Financial markets don’t move linearly; they bend and distort around major catalysts (news, FOMC meetings, earnings, etc.) in a way similar to how gravity warps space-time.
This indicator accounts for that distortion by measuring distance in Lorentzian space instead of the usual Euclidean space.
In simple terms: it adapts to volatility “warping,” allowing the model to detect structural momentum changes that normal math misses.
Core logic:
Imports two custom libraries:
MLExtensions for machine-learning utilities
KernelFunctions for advanced distance calculations
Computes relationships among multiple features (e.g., RSI, ADX, or other inputs).
Uses Lorentzian geometry to weight how recent price-time behavior influences current classification.
Outputs a visual “flip” cue when the probability of trend reversal exceeds threshold confidence.
Why it matters:
Most indicators measure what has already happened.
Lorentzian Classification attempts to capture what’s about to happen by comparing the present market state to a trained historical distribution under warped “price-time” geometry.
It’s particularly useful for spotting early accumulation or exhaustion zones before they become obvious on standard momentum tools.
Recommended use:
Run it as a background trend classifier or color overlay.
Combine it with volume-based confirmation tools (e.g., Dollar Volume Ownership Gauge) and structural analysis.
A “flip to green” suggests buyers are regaining control; a fade or flip to red implies control returning to sellers.
Dollar Volume Ownership GaugePurpose:
DVOG tracks the real money moving through a ticker by converting share volume into dollar volume (price × volume). It helps identify when institutional-sized players enter, defend, or unload positions — information that plain volume bars often hide.
How it works:
Each bar represents 4-minute aggregated dollar volume.
Green bars = moderate sponsorship ($400 K–$1 M per 4 min).
Red bars = heavy sponsorship ($1 M+ per 4 min).
Black bars = normal retail flow (under $400 K).
Optional horizontal guides mark both thresholds for quick reference.
Alerts:
Green Bar Alert: fires every time a bar exceeds $400 K, signaling fresh institutional activity.
Cross Alerts: trigger once when dollar volume crosses the $400 K or $1 M levels, perfect for automation or notifications.
Why it’s useful:
DVOG visually confirms when a breakout, knife-and-reclaim, or coil is being driven by real capital rather than low-liquidity noise.
It turns abstract volume into a direct measure of who’s actually in control.
Recommended use:
Run it in a separate pane below price. Combine with your normal structure analysis — higher lows, double bottoms, coils, etc. — and act only when structure and sponsorship line up.
🦊 Fox Trading Strategy Pro🧠 Description
The Fox Trading Strategy Pro is a fully automated Scalp or Swing strategy that intelligently detects market moves for getting the Pull-Back projects precise entry, stop loss, and take profit levels.
It’s designed for traders who want a complete trading system with clear structure, visual clarity, and instant alerts.
🔍 Core Features
🎯 Automated Entry Levels – Generates three entries (E1, E2, E3) and stop loss zones based on wave ratios.
💰 Target Mapping – Auto-draws up to six Take Profit levels (TP1–TP6) for precise trade management.
⚡ Real-Time Alerts – Get Trading-View alerts the moment price touches your entry levels.
🧩 Statistical Tracking – Tracks signal counts, TP hits, and stop loss events to measure performance.
🖼️ Clean Visuals – Entry, stop, and target lines with colored labels for quick analysis.
⚙️ Inputs & Customization
Adjustable precision and error tolerance .
Full color and line width control for personal chart style.
🚀 How It Works
Calculates and plots 3 entry levels + 1 stop loss.
Projects up to 6 take profit targets automatically.
Sends alerts when entry levels are reached.
Use it as a Swing or Scalp trading companion or as a signal generator for higher-timeframe confluences
Trading Toolbox by eXtylishThis indicator is an all-in-one "trading toolbox" designed for intraday price-action traders.
It combines many tools into one to keep your chart clean:
Key Levels: It automatically plots the Previous Day, Week, and Month Highs & Lows.
Session Ranges: It draws the Highs & Lows for the Asia, London, and New York sessions.
Smart Merging: Its best feature is combining nearby levels (e.g., if PDH and Asia High are at the same price) into a single line with a merged label (like "PDH & ASH").
Opening Range (ORB): It plots an opening range (e.g., first 5 mins) and includes an advanced Info Box that analyzes whether the opening's volatility and volume are high or low compared to average.
Trend Indicators: It includes configurable EMAs and VWAP.
HTF Candles: It displays a set of High Timeframe (e.g., 1-Hour) candles in an offset box on your chart for multi-timeframe analysis.
Topdown Jason IndicatorFramework: Multi-Timeframe Smart-Money-Concept (SMC) analysis
The Topdown Final Indicator is a fully dynamic, top-down market-structure tool that synchronizes higher-timeframe context (H4, H1, and Weekly) with precision M15 entry signals.
It was designed to replicate institutional “top-down” analysis — identifying high-probability setups by combining FVGs (Fair Value Gaps), fractal sweeps, and EMA trend alignment across multiple timeframes.
🔹 Core Features
H4 Fair Value Gap Detection
Automatically marks active bullish and bearish FVGs, with customizable extension and retention controls.
H1 Trend Filter (20/50 EMA)
Confirms directional bias based on EMA structure and dynamic spread filtering.
Optionally enforces directional confluence with the higher (weekly) trend.
M15 Precision Entry Logic
Executes simulated long or short entries when M15 EMA crossover aligns with armed FVGs and higher-timeframe trend conditions.
Smart EMA Visibility
The M15 EMAs automatically appear only when price enters an H4 FVG and the H1 trend confirms — and remain visible until the next EMA cross, visually guiding the active trade phase.
Risk Management Simulation
Dynamic Take-Profit and Stop-Loss projection
Optional 50% partial exits at 1R
Internal “virtual position” tracking for clean non-strategy visualization (no repainting)
Visual Management
Bullish / bearish FVG zones with adjustable colors
Optional H1 and M15 EMA overlays
Auto-cleaning of expired or irrelevant FVGs
Debug logs (optional) for real-time logic tracing