CRR - Smart Money Concept (Pro Expo)Detects Market Structure
Finds pivots using Structure Period.
Marks:
HH (Higher High), LH (Lower High)
HL (Higher Low), LL (Lower Low)
Can draw swing points at highs and lows.
Detects Structure Breaks
When the price breaks the last swing:
BMS (Break of Market Structure) → continuation.
ChoCH (Change of Character) → possible trend reversal.
Differentiates between strong and weak movements using filters.
Confirmation Filters (optional)
If useFilters is enabled, to validate breaks it uses:
ATR → the close must cross the level by at least atrMult * ATR.
Volume → the current volume must be > volMult * average volume.
MACD → in the direction of the break.
Gap → avoids some false breakouts due to gaps.
Internal Fibonacci Retracement of the Last Range
Draws 38.2%, 50%, and 61.8% between the last swing high and swing low.
Serves as internal bounce/discount/premium zones.
Current Range
Draws two dashed yellow lines:
Top: last swing High.
Bottom: last swing Low.
Shows you the range where the price is currently trading.
🧩 In short:
This script draws complete SMC structure (HH/HL/LL/LH + BMS + ChoCH), validates breakouts with ATR, volume, MACD, and gaps, and also displays internal Fibonacci retracement + current range, all automatically and cleanly.
指標和策略
CRR - Candlestick Pattern PRO + HUD Analyze each candlestick in detail:
Calculate:
Body size (bodyPct)
Upper wick (upPct)
Lower wick (lowPct)
Total range of the candlestick.
Detect important candlestick patterns:
Hammer
Inverted Hammer
Doji
Strong Bullish Candle
Strong Bearish Candle
Bullish Engulfing
Bearish Engulfing
Optional: Use the EMA 200 as a trend filter
If useTrend is enabled:
Above the EMA200 → “Trend: Bullish”
Below the EMA200 → “Trend: Bearish”
In between → “Trend: Sideways”
Color and mark the candlesticks:
If useColorCandles is active:
Color the candlestick according to the detected pattern.
If showLabels is active:
Write the name of the pattern above or below the candlestick (Hammer, Doji, Engulfing, etc.).
HUD in the upper right corner:
Name of the current pattern (or “None”).
Bias: bullish reversal, bearish reversal, momentum, indecision, etc.
EMA200 status (trend).
Candlestick body and wick percentages.
Pattern “Strength”: Low / Medium / High.
🧠 In simple terms:
This is a professional candlestick pattern radar, with colors, labels, and a HUD that tells you which pattern is present, what the trend is, and how strong the signal is.
CRR Auto 50% Candle A line at 50% of the candle
If a candle is larger than the minimum size you define (minSizePerc),
then calculate the midpoint of the candle (midLevel) and draw a horizontal line:
From the current candle to 44 bars to the right (or the number you choose).
Green if the candle is bullish, red if it is bearish.
2. Signal arrows
If it's a large bullish candle → green arrow pointing up with the text “50”.
If it's a large bearish candle → red arrow pointing down with the text “50”.
3. What is it for?
It marks the 50% level of important candles, which is often:
A mitigation zone.
A level where the price usually returns before continuing.
An institutional equilibrium point.
🧠 In simple terms:
It detects strong candles, draws their 50% level into the future, and marks them with arrows indicating whether they are bullish or bearish. Ideal for SMC.
CRR Nemesis Fear & Greed ProIt measures 4 market indicators:
ATR → volatility.
Relative Volume (rVOL) → whether there is more or less volume than average.
Price distance from the moving average (SMA 50) in ATR → how much the trend has extended.
Candlestick shape → size of the body and wicks (who is dominating, bulls or bears).
It calculates two scores (0–100):
Greed → when:
The candlestick is bullish,
The price is above the SMA 50 (uptrend),
There is a good body, good rVOL, the price is far from the average, high volatility,
A longer upper wick adds a little more.
Fear → when:
The candlestick is bearish,
The price is below the SMA 50 (downtrend),
Similarly: strong body, rVOL, distance from the average, volatility,
A longer lower wick adds a little more.
Both scores are smoothed with a 3-period EMA (greedSmoothed and fearSmoothed).
It determines the overall market sentiment (HUD):
ANGEL (greed dominates):
Greed ≥ 55 and Greed − Fear ≥ 10.
DEVIL (fear dominates):
Fear ≥ 55 and Fear − Greed ≥ 10.
If neither condition is met → NEUTRAL.
HUD on screen (table in the upper right corner):
Displays:
STATUS: ANGEL / DEVIL / NEUTRAL (with color).
FEAR: smoothed fear value.
GREED: smoothed greed value.
🧠 In simple terms:
It's a market sentiment engine: it combines volume, ATR, distance from the trend, and candlestick shape to tell you if the market is experiencing strong fear, strong greed, or is neutral, and displays it clearly in a HUD.
CRR - Gaps + FVG PROUses ATR
Calculates ATR and, with minAtrR, defines the minimum size for a GAP or FVG to be considered valid.
Detects and draws GAPs between candles
Bullish GAP: low > high (upward gap).
Bearish GAP: high < low (downward gap).
Draws a box between the previous and current candle.
The box can be extended to the right.
If the price fills the gap (touches it), and autoDelGap is active, the box is deleted (mitigated).
Only saves and manages the last bullish GAP and the last bearish GAP.
Detects and draws FVG (3-candle imbalance)
Bullish FVG: high < low → liquidity gap below.
Bearish FVG: low > high → liquidity gap above.
Draws a box for the gap between candle 2 and the current candle.
The box can be extended to the right.
When the price completely enters the zone (fills it), if autoDelFVG is active, the box is deleted (mitigated).
Only monitors the last bullish FVG and the last bearish FVG.
🧠 In simple terms:
It marks GAPs and FVG imbalance zones on the chart, extends them to the right, and automatically deletes them when the price mitigates/fills those zones.
CRR Birgua HUD (HH-HL / LL-LH)CRR Birgua HUD (HH-HL / LL-LH) essentially does three things:
Detects price structure using pivots.
Marks highs as:
HH = Higher High
LH = Lower High
Marks lows as:
HL = Higher Low
LL = Lower Low
It uses a pivot length (pivotLen, default 3) to find these turning points.
Measures the “Birgua” (impulse correction).
In a downtrend:
When an LH appears, it measures how much the retracement rose from the last low to that LH.
In an uptrend:
When an HL appears, it measures how much the retracement fell from the last high to that HL.
It calculates two things:
% correction (birgua_lastPct)
ATR multiples (birgua_lastAtrMult)
It only considers it “valid” if:
% correction ≥ birgua_minBirguaPc (e.g., 25%)
ATR multiple ≥ birgua_minAtrMult (e.g., 0.5)
If valid: it labels it with OK; otherwise: SMALL.
Creates a HUD and a “Birgua Score.”
Calculates a Birgua Score (0–100):
Starts at 50.
If the last Birgua was at an HL (strong bullish), it increases from 50.
If it was at an LH (strong bearish), it decreases from 50.
It can draw a line at the bottom with this score if you enable Show Birgua Score.
At the top of the screen, it displays a HUD with:
Direction: BULL (HL), BEAR (LH), or NEUTRAL.
B: XX.X% (Birgua percentage).
ATR: X.XX (ATR multiples).
Strength: Strong / Weak / N/A based on the minimums you defined.
🧠 Quick Use:
HL + strong Birgua → probable bullish continuation.
LH + strong Birgua → probable bearish continuation.
The HUD summarizes whether the last correction was strong or weak and on which side (bull or bear).
ICT Quant-Core: Liquidity Intelligence [Dual-Engine]🔥 THE ULTIMATE LIQUIDITY FILTERING ENGINE
Most SMC traders lose money because they "catch falling knives" on every local wick. This algorithm solves this problem by using DUAL-CORE logic and a signal quality scoring system.
This is no ordinary pivot indicator.
⚙️ HOW DOES IT WORK? (DUAL-CORE LOGIC)
The algorithm analyzes the market on two levels simultaneously:
1️⃣ MACRO CORE (Lookback 50 - "WHALE 🐋")
Tracks key levels from recent weeks/months.
This is where institutions build their positions.
Signals from this core have the highest priority (Score 10/10).
2️⃣ LOCAL CORE (Lookback 20 - "ROACH 🐟")
Tracks internal market structure and noise.
Signals are filtered by the Main Trend. If the trend is down, Local Longs are marked as "TRAP."
🧠 SMART FILTERS (QUANT LAYERS)
Instead of entering on every line touch, the script requires confirmation:
✅ RECLAIM LOGIC: Price must close back above/below the liquidity level (Swing Failure Pattern).
✅ RVOL FILTER: Requires relative volume > 1.2x the average (institutional track).
✅ SCORING SYSTEM (0-10): Each signal receives a score.
- 10/10: Macro Grab in line with the trend + high volume.
- 3/10: Local Grab against the trend (risky).
📊 ANALYTICAL DASHBOARD
In the lower right corner, you'll find the "Command Center":
- Trend Status (Distribution/Accumulation)
- Whale's Last Move (Price and Direction)
- Current Tactics (e.g., "Ignore Longs, Search for Shorts")
- Filter Status (RSI, Volume, Reclaim)
🚀 HOW TO USE IT?
1. Set the H4 timeframe.
2. Wait for a signal with a rating > 7/10.
3. Ignore "Fish/Local" signals (small icons) if they contradict the Dashboard color.
4. Entry occurs only after the candle closes (Reclaim).
NoProcess PivotsNoProcess Pivots
Visualize the structural framework of price action with NoProcess Pivots, a precision tool for multi-timeframe confluence trading.
Pivots are mathematically derived levels where price statistically finds support, resistance, or equilibrium. Institutional order flow respects these levels as key decision points where liquidity pools form and inefficiencies seek rebalancing.
NoProcess Pivots displays historical pivot ranges as period-bounded zones across Daily, Weekly, and Quarterly timeframes—allowing you to observe how price has respected or violated these levels over time. By projecting ±33% extensions beyond R1/S1, traders can identify targets, retracement levels, and key reversal points.
Cross-reference pivots across multiple timeframes to find confluence zones where Daily, Weekly, and Quarterly levels stack. These high-conviction areas offer the clearest setups for entries and exits.
Features:
Multi-timeframe pivots: Daily, Weekly, Quarterly
Historical levels with adjustable depth
Period-bounded zones
±33% extensions
Adaptive light/dark mode table
Real-time Δ PP percentage
Pivot cross alerts
Built for traders who respect the math behind the markets.
RiskCraft - Advanced Risk Management SystemRiskCraft – Risk Intelligence Dashboard
Trade like you actually respect risk
"I know the setup looks good… but how much am I actually risking right now?"
RiskCraft is an open-source Pine Script v6 indicator that keeps risk transparent directly on the chart. It is not a signal generator; it is a risk desk that calculates size, frames volatility, and reminds you when your behaviour drifts away from the plan.
Core utilities
Calculates professional-style position sizing in real time.
Reads volatility and market regime before position size is confirmed.
Adjusts risk based on the trader’s emotional state and confidence inputs.
Maps session risk across Asian, London, and New York hours.
Draws exactly one stop line and one target line in the preferred direction.
Provides rotating education tips plus contextual warnings when risk escalates.
It is intentionally conservative and keeps you in the game long enough for any separate entry logic to matter.
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Chart layout checklist
Use a clean chart on a liquid symbol (e.g., AMEX:SPY or major FX pairs).
Main RiskCraft dashboard placed on the right edge.
Session Risk box on the left with UTC time visible.
Floating risk badge above price.
Stop/target guide lines enabled.
Education panel visible in the bottom-right corner.
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1. On-chart components
Right-side dashboard : account risk %, position size/value, stop, target, risk/reward, regime, trend strength, emotional state, behavioural score, correlation, and preferred trade direction.
Session Risk box : highlights active session (Asian, London, NY), current UTC time, and risk label (High/Med/Low) per session.
Floating risk badge : keeps actual account risk percent visible with colour-coded wording from Ultra Cautious to Very Aggressive.
Stop/target lines : exactly one dashed stop and one dashed target aligned with the preferred bias.
Education panel : rotates core principles and AI-style warnings tied to volatility, risk %, and behaviour flags.
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2. Volatility engine – ATR with context 📈
atr = ta.atr(atrLength)
atrPercent = (atr / close) * 100
atrSMA = ta.sma(atr, atrLength)
volatilityRatio = atr / atrSMA
isHighVol = volatilityRatio > volThreshold
ATR vs ATR SMA shows how wild price is relative to recent history.
Volatility ratio above the threshold flips isHighVol , which immediately trims risk.
An ATR percentile rank over the last 100 bars indicates calm versus chaotic regimes.
Daily ATR sampling via request.security() gives higher time-frame context for intraday sessions.
When volatility spikes the script dials position size down automatically instead of cheering for maximum exposure.
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3. Market regime radar – Danger or Drift 🌊
ema20 = ta.ema(close, 20)
ema50 = ta.ema(close, 50)
ema200 = ta.ema(close, 200)
trendScore = (close > ema20 ? 1 : -1) +
(ema20 > ema50 ? 1 : -1) +
(ema50 > ema200 ? 1 : -1)
= ta.dmi(14, 14)
Regimes covered:
Danger : high volatility with weak trend.
Volatile : volatility elevated but structure still directional.
Choppy : low ADX and noisy action.
Trending : directional flows without extreme volatility.
Mixed : anything between.
Each regime maps to a 1–10 risk score and a multiplier that feeds the final position size. Danger and Choppy clamp size; Trending restores normal risk.
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4. Behaviour engine – trader inputs matter 🧠
You provide:
Emotional state : Confident, Neutral, FOMO, Revenge, Fearful.
Confidence : slider from 1 to 10.
Toggle for behavioural adjustment on/off.
Behind the scenes:
Each state triggers an emotional multiplier .
Confidence produces a confidence multiplier .
Combined they form behavioralFactor and a 0–100 Behavioural Score .
High-risk emotions or low conviction clamp the final risk. Calm inputs allow normal size. The dashboard prints both fields to keep accountability on-screen.
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5. Correlation guardrail – avoid stacking identical risk 📊
Optional correlation mode compares the active symbol to a reference (default AMEX:SPY ):
corrClose = request.security(correlationSymbol, timeframe.period, close)
priceReturn = ta.change(close) / close
corrReturn = ta.change(corrClose) / corrClose
correlation = calcCorrelation()
Absolute correlation above the threshold applies a correlation multiplier (< 1) to reduce size.
Dashboard row shows the live correlation and reference ticker.
When disabled, the row simply echoes the current symbol, keeping the table readable.
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6. Position sizing engine – heart of the script 💰
baseRiskAmount = accountSize * (baseRiskPercent / 100)
adjustedRisk = baseRiskAmount * behavioralFactor *
regimeAdjustment * volAdjustment *
correlationAdjustment
finalRiskAmount = math.min(adjustedRisk,
accountSize * (maxRiskCap / 100))
stopDistance = atr * atrStopMultiplier
takeProfit = atr * atrTargetMultiplier
positionSize = stopDistance > 0 ? finalRiskAmount / stopDistance : 0
positionValue = positionSize * close
Outputs shown on the dashboard:
Position size in units and value in currency.
Actual risk % back on account after adjustments.
Risk/Reward derived from ATR-based stop and target.
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7. Intelligent trade direction – bias without signals 🎯
Direction score ingredients:
EMA stack alignment.
Price versus EMA20.
RSI momentum relative to 50.
MACD line vs signal.
Directional Movement (DI+/DI–).
The resulting Trade Direction row prints LONG, SHORT, or NEUTRAL. No orders are generated—this is guidance so you only risk capital when the structure supports it.
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8. Stop/target guide lines – two lines only ✂️
if showStopLines
if preferLong
// long stop below, target above
else if preferShort
// short stop above, target below
Lines refresh each bar to keep clutter low.
When the direction score is neutral, no lines appear.
Use them as visual anchors, not auto-orders.
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9. Session Risk map – global volatility clock 🌍
Tracks Asian, London, and New York windows via UTC.
Computes average ATR per session versus global ATR SMA.
Labels each session High/Med/Low and colours the cells accordingly.
Top row shows the active session plus current UTC time so you always know the regime you are trading.
One glance tells you whether you are trading quiet drift or the part of the day that hunts stops.
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10. Floating risk badge – honesty above price 🪪
Text ranges from Ultra Cautious through Very Aggressive.
Colour matches the risk palette inputs (High/Med/Low).
Updates on the last bar only, keeping historical clutter off the chart.
Account risk becomes impossible to ignore while you stare at price.
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11. Education engine & warnings 📚
Rotates evergreen principles (risk 1–2%, journal trades, respect plan).
Triggers contextual warnings when volatility and risk % conflict.
Flags when emotional state = FOMO or Revenge.
Highlights sub-standard risk/reward setups.
When multiple danger flags stack, an AI-style warning overrides the tip text so you can course-correct before capital is exposed.
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12. Alerts – hard guard rails 🚨
Excessive Risk Alert : actual risk % crosses custom threshold.
High Volatility Alert : ATR behaviour signals danger regime.
Emotional State Warning : FOMO or Revenge selected.
Poor Risk/Reward Alert : risk/reward drops below your standard.
All alerts reinforce discipline; none suggest entries or exits.
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13. Multi-market behaviour 🕒
Intraday (1m–1h): session box and badge react quickly; ideal for scalpers needing constant risk context.
Higher time frames (1D–1W): dashboard shifts slowly, supporting swing planning.
Asset classes confirmed in validation: crypto majors, large-cap equities, indices, major FX pairs, and liquid commodities.
Risk logic is price-based, so it adapts across markets without bespoke tuning.
15. Key inputs & recommended defaults
Account Size : 10,000 (modify to match actual account; min 100).
Base Risk % : 1.0 with a Maximum Risk Cap of 2.5%.
ATR Period : 14, Stop Multiplier 2.0, Target Multiplier 3.0.
High Vol Threshold : 1.5 for ATR ratio.
Behavioural Adjustment : enabled by default; disable for fixed risk.
Correlation Check : optional; default symbol AMEX:SPY , threshold 0.7.
Display toggles : main dashboard, risk badge, session map, education panel, and stop lines can be individually disabled to reduce clutter.
16. Usage notes & limits
Indicator mode only; no automated entries or exits.
Trade history panel intentionally disabled (requires strategy context).
Correlation analysis depends on additional data requests and may lag slightly on illiquid symbols.
Session timing uses UTC; adjust expectations if you trade localized instruments.
HTF ATR sampling uses daily data, so bar replay on lower charts may show brief data gaps while HTF loads.
What does everyone think RISK really means?
Swing Data - ADR% / RVol / PVol / Float % / Avg $ Vol (Mod)Modified from this source code:
I have added the current bar DR so i can compare to ADR of the current bar to see if it is worth taking the trade for my bar-by-bar practice.
Quick too instead of having to measure it each time
BörsenampelThe “VIX/VVIX Traffic Light (Panel)” visualizes the current market risk as a simple traffic light (green / yellow / red) in the top‑right corner of the chart, based on the VIX and VVIX indices.
How it works
The script loads the VIX and VVIX indices via request.security and evaluates them using user‑defined threshold levels.
Green: VIX and VVIX are below their “green” thresholds, indicating a calm market environment and more risk‑on conditions.
Red: VIX and VVIX are above their “red” thresholds, signalling stress or panic phases with elevated risk.
Yellow: Transitional zone between the two extremes.
Chart display
A small panel with the title “Traffic Light” is shown in the upper‑right corner of the chart.
The central box displays the current status (“GREEN”, “YELLOW”, “RED”) with a matching background color.
Optionally, the current VIX and VVIX values are shown below the status.
Inputs and usage
Symbols for VIX and VVIX can be freely chosen (default: CBOE:VIX and CBOE:VVIX).
The green/red thresholds can be adjusted to fit personal volatility rules or different markets.
CRAZY RAY RAY - Dashboard 1-5-15-1D + SMC + Clock + Candles PRO OANDA:XAUUSD This script is essentially your institutional "nuclear power plant" for scalping and swing trading: it combines the 1-5-15-1D dashboard, SMC, PRO candles, money flow times, institutional filters, Bull/Bear 12C, Liquidity HUD, Fibo Move, and Target Trend with SL + 3 TPs into a single indicator. 1. Dashboard 1–5–15–1D (Central HUD)
Calculates across 4 timeframes: 1m, 5m, 15m, and 1D:
Trend with EMAs 15/30/200.
RSI (strength >50 buy, <50 sell).
MACD (crossover in favor or against).
For each timeframe it shows:
TREND → BULLISH / BEARISH / NEUTRAL.
ACTION → BUY / SELL / WAIT.
If all 4 timeframes align:
MODE = BULLISH BUY
MODE = BEARISH SELL
Filters and displays on the HUD if buys or sells are blocked by SMC context (BLOCKED BUY / BLOCKED SELL).
Also draws 2 simple moving averages on the chart:
SMA 20 white (you can use it as a micro-trend).
SMA 200 red (macro trend and institutional reference).
2. Real-Time Clock + Trading Hours
Calculates the real time for:
New York / Miami
London
Tokyo
using current time and real time zone.
Also calculates GMT time to know which session is dominant.
Marks your trading hours:
LONDON 3:00–5:30 (London time) → goodLondon
NY OPEN 8:30–10:00 (NY time) → goodNYOpen
ASIA 20:00–23:00 (Tokyo) → goodAsiaScalp
Displays a message on the HUD:
LONDON 3:00–5:30 (1–2 TRADES)
NY OPEN 8:30–10:00 (1 TRADE)
ASIA 20–23 (SCALP)
NO TRADE ROLL / DEAD / LATE
ONLY A+ SETUPS (when not in strong trading hours).
3. Institutional Power (volume + ATR + session)
Filter that evaluates whether the moment is institutional or retail:
Checks:
If you are in a strong trading session (London / NY). If the volume is above the average × multiplier.
If the ATR is above the average × multiplier.
If it passes the filters → INST ON, otherwise → RETAIL ZONE.
Used internally to block buys/sells and for the HUD.
4. Micro-signal “NO RETRACEMENT” on 1m (BUY SR / SELL SR)
On the 1-minute timeframe, it detects a very aggressive entry:
Clean trend (15/30/200 EMAs aligned).
Price crosses the 200 EMA.
MACD turns in favor.
Marks on the candle:
BUY SR (buys without retracement below the EMA200).
SELL SR (sales without retracement above the EMA200).
This state is also reflected in the HUD as the “SR” row.
5. SMC Block: HH/HL/LH/LL + BMS + ChoCH + Fibo + Zones
This is the SMC brain of the script:
Detects swings with pivots:
Paints HH, HL, LH, LL (if you activate showHHLL).
Marks BOS (break of structure).
Marks BMS and ChoCH (with strong or weak filter using ATR, volume, MACD, gaps).
Draws:
Internal Fibo of the last range (38–50–61).
Fibo entry zone 38–78% as a green discount/premium box.
Institutional mitigation zones (simple OB type green/red boxes).
Current range with dotted yellow lines.
Calculates logic for:
antiStupidBuy: blocks purchases when the context is very bearish (LL–LL–LH, bearish ChoCH, premium, EQH, etc.).
antiStupidSell: symmetrical for sales.
From this comes:
allowBuyInst
allowSellInst
buyBlockerOn / sellBlockerOn
buyTrapDetected (BUY SR signal but context blocks it → BUY TRAP).
All this feeds the HUD and institutional alerts.
6. PRO Candles (candlestick + smart color)
Candlestick pattern system:
Detects:
Hammer, Inverted Hammer. Doji.
Strong bullish/bearish candle.
Bullish/bearish engulfing.
Uses a trend EMA to determine if the pattern is with or against the trend.
Colors the candles according to the pattern (if you enable useColorCandles).
Defines texts:
patternText (pattern name).
biasText (reversal, momentum, indecision).
Updates the HUD with the current pattern (“CANDLE: Engulf Bull”, etc.).
7. Institutional PRO Combo + Reversals
Connects everything:
fullBuySetup:
allowBuyInst TRUE (SMC + Fibo + mitigation OK).
Institutional candles in favor (engulfing, hammer, etc.).
MultiTF aligned (1m, 5m in favor, 15/1D not strongly against).
Strong session (London or NY).
No blockages.
fullSellSetup: the same for sales.
Marks on the chart:
BUY PRO, SELL PRO.
BUY REV LL → reversal from a LL, at Fibo discount, with an institutional candle and above EMA200.
SELL REV HH → reversal from HH, at Fibo premium, with an institutional candle and below EMA200.
And generates alerts for all of this.
8. Dynamic Main HUD
On barstate.islast, updates the HUD:
Changes “BUY / SELL” to:
BUY BLOCK / SELL BLOCK when the context blocks that direction.
Writes:
Current candle pattern.
Time message.
Global status:
BUY TRAP ❌, BUY REV LL ✅, SELL REV HH ✅, BUY PRO ✅, SELL PRO ✅,
BUY BLOCK, SELL BLOCK, BUY/SELL OK.
9. Bull/Bear 12C HUD (Small right HUD)
12-confirmation bull/bear engine:
Calculates:
Sweep, 5th leg, mitigation, HL/LH, strong BOS.
Volume pattern (high-low-high).
ATR rising.
MACD crossover.
Liquidity.
Fear & Greed (SMA50).
Gap/imbalance. Bull/Bear 180 weak.
Count how many are ON:
bullScore /12
bearScore /12
Define a regime:
INSTITUTIONAL → many confirmations + rvol + ATR.
NORMAL
RETAIL
Show on right HUD:
List 1 to 12 with green/red dots BULL / BEAR.
Summary: “Regime: INSTITUTIONAL / NORMAL / RETAIL”.
10. Liquidity HUD XAU SCALP
Calculates RVOL, normalized ATR, spread vs ATR, current range vs average range.
Generates score and classifies:
LOW / MED / HIGH / INS.
Only moves up one level if you are in London/NY session (depending on sessions)
Volatility Risk PremiumTHE INSURANCE PREMIUM OF THE STOCK MARKET
Every day, millions of investors face a fundamental question that has puzzled economists for decades: how much should protection against market crashes cost? The answer lies in a phenomenon called the Volatility Risk Premium, and understanding it may fundamentally change how you interpret market conditions.
Think of the stock market like a neighborhood where homeowners buy insurance against fire. The insurance company charges premiums based on their estimates of fire risk. But here is the interesting part: insurance companies systematically charge more than the actual expected losses. This difference between what people pay and what actually happens is the insurance premium. The same principle operates in financial markets, but instead of fire insurance, investors buy protection against market volatility through options contracts.
The Volatility Risk Premium, or VRP, measures exactly this difference. It represents the gap between what the market expects volatility to be (implied volatility, as reflected in options prices) and what volatility actually turns out to be (realized volatility, calculated from actual price movements). This indicator quantifies that gap and transforms it into actionable intelligence.
THE FOUNDATION
The academic study of volatility risk premiums began gaining serious traction in the early 2000s, though the phenomenon itself had been observed by practitioners for much longer. Three research papers form the backbone of this indicator's methodology.
Peter Carr and Liuren Wu published their seminal work "Variance Risk Premiums" in the Review of Financial Studies in 2009. Their research established that variance risk premiums exist across virtually all asset classes and persist over time. They documented that on average, implied volatility exceeds realized volatility by approximately three to four percentage points annualized. This is not a small number. It means that sellers of volatility insurance have historically collected a substantial premium for bearing this risk.
Tim Bollerslev, George Tauchen, and Hao Zhou extended this research in their 2009 paper "Expected Stock Returns and Variance Risk Premia," also published in the Review of Financial Studies. Their critical contribution was demonstrating that the VRP is a statistically significant predictor of future equity returns. When the VRP is high, meaning investors are paying substantial premiums for protection, future stock returns tend to be positive. When the VRP collapses or turns negative, it often signals that realized volatility has spiked above expectations, typically during market stress periods.
Gurdip Bakshi and Nikunj Kapadia provided additional theoretical grounding in their 2003 paper "Delta-Hedged Gains and the Negative Market Volatility Risk Premium." They demonstrated through careful empirical analysis why volatility sellers are compensated: the risk is not diversifiable and tends to materialize precisely when investors can least afford losses.
HOW THE INDICATOR CALCULATES VOLATILITY
The calculation begins with two separate measurements that must be compared: implied volatility and realized volatility.
For implied volatility, the indicator uses the CBOE Volatility Index, commonly known as the VIX. The VIX represents the market's expectation of 30-day forward volatility on the S&P 500, calculated from a weighted average of out-of-the-money put and call options. It is often called the "fear gauge" because it rises when investors rush to buy protective options.
Realized volatility requires more careful consideration. The indicator offers three distinct calculation methods, each with specific advantages rooted in academic literature.
The Close-to-Close method is the most straightforward approach. It calculates the standard deviation of logarithmic daily returns over a specified lookback period, then annualizes this figure by multiplying by the square root of 252, the approximate number of trading days in a year. This method is intuitive and widely used, but it only captures information from closing prices and ignores intraday price movements.
The Parkinson estimator, developed by Michael Parkinson in 1980, improves efficiency by incorporating high and low prices. The mathematical formula calculates variance as the sum of squared log ratios of daily highs to lows, divided by four times the natural logarithm of two, times the number of observations. This estimator is theoretically about five times more efficient than the close-to-close method because high and low prices contain additional information about the volatility process.
The Garman-Klass estimator, published by Mark Garman and Michael Klass in 1980, goes further by incorporating opening, high, low, and closing prices. The formula combines half the squared log ratio of high to low prices minus a factor involving the log ratio of close to open. This method achieves the minimum variance among estimators using only these four price points, making it particularly valuable for markets where intraday information is meaningful.
THE CORE VRP CALCULATION
Once both volatility measures are obtained, the VRP calculation is straightforward: subtract realized volatility from implied volatility. A positive result means the market is paying a premium for volatility insurance. A negative result means realized volatility has exceeded expectations, typically indicating market stress.
The raw VRP signal receives slight smoothing through an exponential moving average to reduce noise while preserving responsiveness. The default smoothing period of five days balances signal clarity against lag.
INTERPRETING THE REGIMES
The indicator classifies market conditions into five distinct regimes based on VRP levels.
The EXTREME regime occurs when VRP exceeds ten percentage points. This represents an unusual situation where the gap between implied and realized volatility is historically wide. Markets are pricing in significantly more fear than is materializing. Research suggests this often precedes positive equity returns as the premium normalizes.
The HIGH regime, between five and ten percentage points, indicates elevated risk aversion. Investors are paying above-average premiums for protection. This often occurs after market corrections when fear remains elevated but realized volatility has begun subsiding.
The NORMAL regime covers VRP between zero and five percentage points. This represents the long-term average state of markets where implied volatility modestly exceeds realized volatility. The insurance premium is being collected at typical rates.
The LOW regime, between negative two and zero percentage points, suggests either unusual complacency or that realized volatility is catching up to implied volatility. The premium is shrinking, which can precede either calm continuation or increased stress.
The NEGATIVE regime occurs when realized volatility exceeds implied volatility. This is relatively rare and typically indicates active market stress. Options were priced for less volatility than actually occurred, meaning volatility sellers are experiencing losses. Historically, deeply negative VRP readings have often coincided with market bottoms, though timing the reversal remains challenging.
TERM STRUCTURE ANALYSIS
Beyond the basic VRP calculation, sophisticated market participants analyze how volatility behaves across different time horizons. The indicator calculates VRP using both short-term (default ten days) and long-term (default sixty days) realized volatility windows.
Under normal market conditions, short-term realized volatility tends to be lower than long-term realized volatility. This produces what traders call contango in the term structure, analogous to futures markets where later delivery dates trade at premiums. The RV Slope metric quantifies this relationship.
When markets enter stress periods, the term structure often inverts. Short-term realized volatility spikes above long-term realized volatility as markets experience immediate turmoil. This backwardation condition serves as an early warning signal that current volatility is elevated relative to historical norms.
The academic foundation for term structure analysis comes from Scott Mixon's 2007 paper "The Implied Volatility Term Structure" in the Journal of Derivatives, which documented the predictive power of term structure dynamics.
MEAN REVERSION CHARACTERISTICS
One of the most practically useful properties of the VRP is its tendency to mean-revert. Extreme readings, whether high or low, tend to normalize over time. This creates opportunities for systematic trading strategies.
The indicator tracks VRP in statistical terms by calculating its Z-score relative to the trailing one-year distribution. A Z-score above two indicates that current VRP is more than two standard deviations above its mean, a statistically unusual condition. Similarly, a Z-score below negative two indicates VRP is unusually low.
Mean reversion signals trigger when VRP reaches extreme Z-score levels and then shows initial signs of reversal. A buy signal occurs when VRP recovers from oversold conditions (Z-score below negative two and rising), suggesting that the period of elevated realized volatility may be ending. A sell signal occurs when VRP contracts from overbought conditions (Z-score above two and falling), suggesting the fear premium may be excessive and due for normalization.
These signals should not be interpreted as standalone trading recommendations. They indicate probabilistic conditions based on historical patterns. Market context and other factors always matter.
MOMENTUM ANALYSIS
The rate of change in VRP carries its own information content. Rapidly rising VRP suggests fear is building faster than volatility is materializing, often seen in the early stages of corrections before realized volatility catches up. Rapidly falling VRP indicates either calming conditions or rising realized volatility eating into the premium.
The indicator tracks VRP momentum as the difference between current VRP and VRP from a specified number of bars ago. Positive momentum with positive acceleration suggests strengthening risk aversion. Negative momentum with negative acceleration suggests intensifying stress or rapid normalization from elevated levels.
PRACTICAL APPLICATION
For equity investors, the VRP provides context for risk management decisions. High VRP environments historically favor equity exposure because the market is pricing in more pessimism than typically materializes. Low or negative VRP environments suggest either reducing exposure or hedging, as markets may be underpricing risk.
For options traders, understanding VRP is fundamental to strategy selection. Strategies that sell volatility, such as covered calls, cash-secured puts, or iron condors, tend to profit when VRP is elevated and compress toward its mean. Strategies that buy volatility tend to profit when VRP is low and risk materializes.
For systematic traders, VRP provides a regime filter for other strategies. Momentum strategies may benefit from different parameters in high versus low VRP environments. Mean reversion strategies in VRP itself can form the basis of a complete trading system.
LIMITATIONS AND CONSIDERATIONS
No indicator provides perfect foresight, and the VRP is no exception. Several limitations deserve attention.
The VRP measures a relationship between two estimates, each subject to measurement error. The VIX represents expectations that may prove incorrect. Realized volatility calculations depend on the chosen method and lookback period.
Mean reversion tendencies hold over longer time horizons but provide limited guidance for short-term timing. VRP can remain extreme for extended periods, and mean reversion signals can generate losses if the extremity persists or intensifies.
The indicator is calibrated for equity markets, specifically the S&P 500. Application to other asset classes requires recalibration of thresholds and potentially different data sources.
Historical relationships between VRP and subsequent returns, while statistically robust, do not guarantee future performance. Structural changes in markets, options pricing, or investor behavior could alter these dynamics.
STATISTICAL OUTPUTS
The indicator presents comprehensive statistics including current VRP level, implied volatility from VIX, realized volatility from the selected method, current regime classification, number of bars in the current regime, percentile ranking over the lookback period, Z-score relative to recent history, mean VRP over the lookback period, realized volatility term structure slope, VRP momentum, mean reversion signal status, and overall market bias interpretation.
Color coding throughout the indicator provides immediate visual interpretation. Green tones indicate elevated VRP associated with fear and potential opportunity. Red tones indicate compressed or negative VRP associated with complacency or active stress. Neutral tones indicate normal market conditions.
ALERT CONDITIONS
The indicator provides alerts for regime transitions, extreme statistical readings, term structure inversions, mean reversion signals, and momentum shifts. These can be configured through the TradingView alert system for real-time monitoring across multiple timeframes.
REFERENCES
Bakshi, G., and Kapadia, N. (2003). Delta-Hedged Gains and the Negative Market Volatility Risk Premium. Review of Financial Studies, 16(2), 527-566.
Bollerslev, T., Tauchen, G., and Zhou, H. (2009). Expected Stock Returns and Variance Risk Premia. Review of Financial Studies, 22(11), 4463-4492.
Carr, P., and Wu, L. (2009). Variance Risk Premiums. Review of Financial Studies, 22(3), 1311-1341.
Garman, M. B., and Klass, M. J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53(1), 67-78.
Mixon, S. (2007). The Implied Volatility Term Structure of Stock Index Options. Journal of Empirical Finance, 14(3), 333-354.
Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53(1), 61-65.
HTF Candles & Levels Visualizer - SRHTF Candles & Levels Visualizer is a clean higher‑timeframe visualization tool designed to complement any trading strategy by giving clear context of larger‑TF structure directly on your current chart. It plots the previous high and low for up to three user‑selectable timeframes, and draws them as extended levels with optional labels, making it easy to see where current price sits relative to key higher‑timeframe zones.
The script also renders compact proxy candles for each selected timeframe to the right of current price, so you can visually track HTF candle development without switching charts. Each HTF slot has independent settings: timeframe, color, number of displayed candles, and visibility toggles, along with global controls for line style, label size, candle spacing, and colors.
This tool does not generate trading signals; it focuses purely on multi‑timeframe context and market structure visualization to support your own entries, exits, and risk management.
AlphaTrend | APEX [Singularity]This is a customized Trend Tracer style system designed to capture high-quality moves while filtering out noise. It combines three core "Engines":
1. Kinetic Trend Engine (The "Ribbon")
Logic: Uses a Dual-ALMA Ribbon (Arnaud Legoux Moving Average).
Fast Line (Leader): Responsive, hugs price.
Slow Line (Laggard): Smooth, validates structure.
Signals: "BUY" and "SELL" labels trigger exactly when the ribbon twists (Crossover/Crossunder).
Filters:
Entropy & Hurst: Measures market chaos. The ribbon turns Gray/Faded during choppy conditions to warn against trading.
2. Flow Engine (Whale Validation)
Whale Volume: Checks for relative volume spikes (> 1.2x average) and Money Flow intensity.
Confirmation: Signals are stronger when accompanied by the Whale Icon (🐋), indicating institutional participation.
3. Liquidity Magnets (Targets)
Logic: Automatically detects recent Swing Highs and Lows.
Visuals: Dashed lines extend forward to act as dynamic Support/Resistance levels or Take Profit targets.
Behavior: Lines disappear when price tests (breaks) them, indicating "Liquidity Taken".
Visuals
Cloud: Dynamic Green/Red fill between the ribbon lines.
HUD: Heads-Up Display showing current Trend, Market State (Clean/Chop), Flow Status, and Active Magnets.
Labels: Clean "Tag" style labels for entry signa
Kurtosis with Skew Crossover Focused OscillatorDescription:
This indicator highlights Skewness/Kurtosis crossovers for short-term trading:
Green upward arrows: Skew crosses above Kurtosis → potential long signal.
Red downward arrows: Skew crosses below Kurtosis → potential short signal.
Yellow upward arrows: Extreme negative skew (skew ≤ -1.7) → potential oversold/reversal opportunity.
Oscillator Pane:
Orange = Skewness (smoothed)
Blue = Kurtosis (adjusted, smoothed)
Zero line = visual reference
Usage:
Primarily for 2–5 minute charts, highlighting statistical anomalies and potential short-term reversals that can be used in conjunction with OBV and/or CVD
Arrows signal potential entries based on skew/kurt dynamics.
Potential ideas???????
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Add Supporting Market Context
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Currently, signals are purely based on skew/kurt crossovers. Adding supporting indicators could improve reliability:
Volume / CVD: Identify when crossovers occur with real buying/selling pressure.
Wick Imbalance: Detect forced moves in price structure.
Volatility Regime (Parkinson / ATR): Filter signals during high volatility spikes or compressions.
Experimentation: Try weighting these supporting signals to dynamically confirm or filter skew/kurt crossovers and see if false signals decrease on 2–5 minute charts.
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Dynamic Thresholds & Scaling
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Right now, the extreme skew signal is triggered at a fixed level (skew ≤ -1.7). Future improvements could include:
Adaptive thresholds: Scale extreme skew levels based on recent standard deviation or intraday volatility.
Kurtosis thresholds: Introduce a cutoff for kurtosis to identify “fat-tail” events.
Experimentation: Backtest different adaptive thresholds for both skew and kurt, and see how it affects the precision vs. frequency of signals.
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Multi-Timeframe or Combined Oscillator
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Skew/kurt signals could be combined across multiple intraday timeframes (e.g., 1-min, 3-min, 5-min) to improve confirmation.
Create a composite oscillator that blends short-term and slightly longer-term skew/kurt values to reduce noise.
Experimentation: Compare a single timeframe approach vs multi-timeframe composite, and measure signal reliability and lag.
I'm leaving this open so anyone can experiment with it as this project may be on the backburner, but these are my thoughts so far
The Rumer's Box Theory“The Rumer's Box Theory” is a visual trading indicator that allows traders to quickly identify the previous daily candle’s high and low across any timeframe. It displays a purple box spanning the previous day’s high to low, with a blue horizontal line marking the 50% midpoint for quick reference. The settings also provide options to extend the box and midpoint line to the left, giving traders flexibility in how the indicator appears on the chart.
BLACK SWAN SWEEP (DANIELPEREZ)Crt de velas especificas después del sweep buscar la confirmación del order block para tomar una operacio .
Check specific candlesticks after the sweep to find order block confirmation before taking a trade.
Dynamic 15-Ticker Multi-Symbol Table 2025 EditionTitle:
Dynamic 15-Ticker Multi-Symbol Table 2025 Edition
Description:
This script provides a multi-ticker table for TradingView charts. It is fully open-source and free to use. The table displays up to 15 tickers, including SPY as the baseline symbol. The script updates in real-time on any timeframe.
Features:
SPY baseline: The first row always shows SPY for reference.
Custom tickers: Add up to 14 additional tickers via the input settings. Rows without tickers remain hidden.
Price and direction: Each ticker row displays the current price and an indicator of direction based on recent price movement.
RSI (14) indicator: Shows the current relative strength index value with a simple directional marker.
Volume formatting: Displays volume values in thousands, millions, or billions automatically. Volume change is indicated with directional markers.
Stable layout: The table uses alternating row colors for readability and maintains consistent row count without collapsing or disappearing rows.
Real-time updates: All displayed values refresh automatically on any chart timeframe.
How to use:
Add the script to your chart.
Enter your chosen tickers in the input settings. SPY will remain as the first ticker automatically.
Tickers not entered will remain hidden. When a ticker is removed, the row will be removed-dynamically.
Observe live prices, RSI values, and volume changes directly on your chart without switching symbols.
Additional notes:
The script is fully open-source; users are encouraged to modify or improve it.
No external links or references are required to understand its function.
This script does not repaint and does not require additional requests to update values.
The Rumer's Box Theory“The Rumer's Box Theory” is a visual trading indicator designed to help traders quickly identify the previous daily candle’s high and low ranges across all timeframes. The indicator draws a purple box spanning the previous day’s high to low, with a blue horizontal line at the 50% midpoint for easy reference.
DAILY AND WEEKLY MID LINESDAILY AND WEEKLY MID LINES INDICATOR
Description:
This indicator calculates and visualizes the dynamic midpoint (mid) of the current day and week in real-time. It provides traders with key reference levels based on developing price action.
Features:
Daily Mid Line:
Color: Orange
Thickness: 3 pixels
Style: Solid line
Updates: Automatically recalculates with each new candle
Calculation: Average of the day's highest high and lowest low from market open
Weekly Mid Line:
Color: Blue
Thickness: 3 pixels
Style: Dashed line
Updates: Continuously recalculates throughout the week
Calculation: Average of the week's highest high and lowest low from week start
How It Works:
At the start of each new trading day (00:00), the daily mid line resets and begins calculating from the first candle
At the start of each new trading week (typically Monday), the weekly mid line resets and begins fresh calculations
Both lines extend automatically to the right as new candles form
The lines are dynamic - they adjust as new highs/lows are made during the day/week
Trading Applications:
Support/Resistance Levels:
The mid lines act as natural equilibrium points where price may find temporary support or resistance
Daily mid can serve as intraday pivot, weekly mid as broader market balance point
Trend Analysis:
Price consistently above mid lines suggests bullish momentum
Price consistently below mid lines suggests bearish momentum
Relationship between daily and weekly mid lines shows multi-timeframe alignment
Entry/Exit Signals:
Price crossing above daily mid may indicate short-term bullish momentum
Price crossing below daily mid may indicate short-term bearish momentum
Weekly mid breaks can signal more significant trend changes
Market Context:
Distance between price and mid lines indicates market extremity
Steeper mid line slopes suggest stronger directional momentum
Flat mid lines suggest range-bound or consolidating markets
Confluence Trading:
Combine with other indicators (RSI, MACD, moving averages) for confirmation
Use as dynamic levels for stop-loss placement or take-profit targets
Best Practices:
More effective on higher timeframes (1H, 4H, Daily) for clearer signals
Works well in trending markets where mid lines act as moving support/resistance
Monitor for price rejection or acceptance at mid levels for trading decisions
Use in conjunction with volume analysis for confirmation
Psychological Significance:
Mid points often represent fair value areas where buyers and sellers find temporary equilibrium, making them natural decision points for market participants.
This indicator is particularly useful for day traders, swing traders, and position traders looking for dynamic, real-time reference points that adapt to current market conditions rather than relying on static historical levels.
ATR% Multiple from MA (with QQQ Reference)ATR% Multiple from MA (with QQQ Reference)
This indicator measures how extended a stock's price is from its moving average, normalized by volatility (ATR). It's useful for identifying overbought/oversold conditions and timing profit-taking.
How it works:
ATR% = ATR / Current Price (volatility as % of price)
% Gain From MA = How far price is from the moving average
ATR% Multiple From MA = % Gain From MA ÷ ATR%
Features:
Displays ATR% Multiple for the current symbol
Adds QQQ ATR% Multiple as a market benchmark reference
Shows % Gain From MA and ATR % for additional context
Customizable MA type (SMA, EMA, WMA, VWMA) and lengths
Usage:
Values of 7-10+ suggest taking partial profits (price is extended)
Negative values suggest oversold conditions
Compare your stock's extension to QQQ to gauge relative strength
Inspired by jfsrev's original ATR% Multiple from 50-MA concept, with added QQQ market reference:
ATR% Multiple from MA (with QQQ Reference)ATR% Multiple from MA (with QQQ Reference)
This indicator measures how extended a stock's price is from its moving average, normalized by volatility (ATR). It's useful for identifying overbought/oversold conditions and timing profit-taking.
How it works:
ATR% = ATR / Current Price (volatility as % of price)
% Gain From MA = How far price is from the moving average
ATR% Multiple From MA = % Gain From MA ÷ ATR%
Features:
Displays ATR% Multiple for the current symbol
Adds QQQ ATR% Multiple as a market benchmark reference
Shows % Gain From MA and ATR % for additional context
Customizable MA type (SMA, EMA, WMA, VWMA) and lengths
Usage:
Values of 7-10+ suggest taking partial profits (price is extended)
Negative values suggest oversold conditions
Compare your stock's extension to QQQ to gauge relative strength
Inspired by jfsrev's original ATR% Multiple from 50-MA concept, with added QQQ market reference:
