EMA Market Regime & Real-Time Candle Projection System📌 EMA Market Regime & Real-Time Candle Projection System
EMA Market Regime & Parabolic Projection is a real-time market structure system designed to anticipate candle behavior before it fully forms, by dynamically projecting price levels based on trend strength, acceleration, and market expansion.
Unlike traditional indicators that react after the candle closes, this system continuously adapts to live price data to provide early insight into bullish, bearish, parabolic, and exhaustion phases.
🔍 Core Concept
The system operates on four key dimensions:
Market Structure
Uses a fast and a slow EMA to determine the dominant market regime (bullish or bearish).
Directional Momentum
Measures EMA slope to confirm directional commitment.
Acceleration & Parabolic Detection
Identifies true parabolic movements through acceleration analysis, filtering out weak or range-bound price action.
Expansion Validation
Confirms that movements are supported by genuine market expansion, reducing false signals.
By combining these elements, the indicator projects a dynamic price level in real time, effectively drawing a forward-looking guide that adapts as each candle evolves.
🧠 Real-Time Candle Projection
The projected line represents a dynamic equilibrium level derived from EMA structure and acceleration.
This allows traders to:
Anticipate continuation vs exhaustion
Visualize momentum shifts before candle close
Read potential candle direction and strength in real time
The projection is non-repainting and updates tick-by-tick during the candle’s formation.
🎯 Market Regime Classification
The system automatically classifies the market into distinct states:
Bullish Trend – Positive structure with controlled momentum
Bearish Trend – Negative structure with controlled momentum
Parabolic Expansion – Accelerated trend with strong continuation potential
Parabolic Exhaustion – Loss of acceleration signaling potential reversal or pullback
Neutral / Range – Low momentum and low expansion (no-trade zone)
Each state is visually encoded using subtle, professional coloring, ensuring price candles always remain the primary focus.
🛡️ Professional-Grade Filters
Anti-range and anti-fake breakout filtering
Cooldown logic to prevent repetitive signals
Slope normalization relative to volatility
Designed to remain readable on M1–M5 scalping and higher timeframes
⚙️ Designed For
Scalping & Intraday Trading
Real-time decision-making
Trend continuation & exhaustion timing
Prop-firm and professional trading environments
This system is intended as a market structure and timing tool, not a signal spam indicator.
⚠️ Disclaimer
This indicator does not predict the future and does not provide guaranteed results. It is designed to assist discretionary traders by improving real-time market reading and execution timing.
지표 및 전략
AMT Structure: 80% Traverse, PD Levels & nPOCsHere is a clean, professional description formatted for the TradingView description box. It highlights the methodology (AMT/80% Rule), the specific features, and the credits.
Title: AMT Structure: 80% Traverse, PD Levels & nPOCs
Description:
This indicator is a comprehensive toolkit designed for futures traders utilizing Auction Market Theory (AMT) and Volume Profile strategies. It consolidates multiple scripts into a single, unified overlay to declutter your chart while providing essential structural references for the 80% Traverse setup, intraday context, and longer-term auction targets.
Key Features:
1. 80% Rule / Traverse Setup (Chart Champions Logic)
Automated RTH Open Detection: Hardcoded to the 08:30 AM CT Open to ensure accuracy for US Futures (ES/NQ) regardless of your chart's timezone settings.
Value Area Logic: Automatically calculates the Previous Day's Value Area High (VAH), Value Area Low (VAL), and Point of Control (POC).
Setup Detection: If the market opens outside of the previous day's value, the script highlights the Value Area in color (default: Purple), signaling that an 80% traverse (filling the value area) is structurally possible if price re-enters value.
Background Fill: Optional shading between VAH and VAL to clearly visualize the "playing field" for the traverse.
2. Auction Market Theory (AMT) Premarket Levels
Overnight High/Low: Automatically captures the highest and lowest prices traded during the overnight session (17:00 - 08:30 CT).
Breakout Alerts: Includes logic to detect and alert when these overnight levels are broken during the RTH session.
Auto-Cleanup: Lines can be set to auto-delete after a specified time (default: 60 mins into the session) to keep the chart clean after the Initial Balance (IB) period.
3. Structural Reference Levels
Previous Day Levels: Plots Previous Day High, Low, and Equilibrium (Midpoint) as standard reference lines.
Initial Balance (IB): Option to display the First Hour High and Low (08:30 - 09:30 CT) to assess day type (Neutral, Trend, Normal Variation, etc.).
RTH VWAP: An anchored VWAP that resets specifically at the RTH Open (08:30 CT), distinct from the standard 24-hour VWAP.
4. Naked Points of Control (nPOCs)
Multi-Timeframe Tracking: Tracks and plots Naked POCs for Daily, Weekly, and Monthly profiles.
Auto-Cleanup: Lines automatically delete themselves the moment price touches them, ensuring you only see untested levels.
Customization: Toggle each timeframe on/off individually.
Settings & Customization:
Global Offset: Move all text labels to the right with a single setting to prevent price action from obscuring text.
8:30 Open Offset: Independent offset for the Open label to distinguish it from other opening references.
Smart Coloring: Text labels automatically match their corresponding line colors for easy identification.
Modular Toggles: Every section (AMT, VWAP, PD Levels, CCV, nPOCs) can be turned on or off individually to suit your specific trading plan.
Usage: This tool is specifically tuned for ES and NQ futures trading but can be adapted for other instruments. It replaces the need for separate indicators for Overnight Highs/Lows, Previous Day Levels, and Volume Profile targeting.
Single Prints and Poor Highs/Lows [Real-Time]This indicator is designed for traders utilizing Auction Market Theory (AMT) who need real-time visibility into market structure inefficiencies. Unlike standard TPO tools that often wait for closed bars or finished sessions, this script builds a developing TPO profile tick-by-tick to identify Single Prints and Poor Highs/Lows the moment they form.
Key Features:
Real-Time Single Prints: Automatically detects and highlights areas of single-print inefficiencies (buying/selling tails) as they happen. These "ghost" boxes persist on the chart until price repairs (fills) them, acting as immediate targets or support/resistance zones.
Poor High/Low Detection: Strictly implements AMT logic to identify "unfinished" auctions. If a session extreme is formed by two or more TPO blocks (indicating a flat top/bottom rather than a rejection tail), it marks the level with a dotted line.
Repair Logic: Both Single Prints and Poor High/Low lines are dynamic. If price revisits and repairs the structure, the markers automatically vanish to keep your chart clean.
Session Control: Fully customizable RTH (Regular Trading Hours) session input (default 08:30–15:15) to ensure profiles are built on relevant liquidity.
Quantization: Adjustable "Ticks per Block" allowing you to tune the sensitivity of the TPO profile to different assets (ES, NQ, CL, etc.).
How It Works:
TPO Construction: The script breaks the session into 30-minute periods (configurable) and tracks price overlap.
Single Prints: When the market expands rapidly, leaving gaps in the profile (single TPO blocks), a box is drawn. If price trades back through this box, it deletes itself.
Poor Extremes: It monitors the current session High and Low. If the extreme price level has a TPO count of ≥ 2, it is flagged as "Poor." If the extreme is a single print (count = 1), it is considered a valid tail and left unmarked.
Settings:
RTH Session: Define your specific trading session time.
TPO Period: Default is 30 minutes (standard AMT).
Ticks per Block: Controls the vertical resolution of the TPO. (Higher values = coarser profile, Lower values = more precision).
Colors: Fully customizable colors for Live Prints, Historical Prints, and Poor High/Low lines.
Usage:
Use this tool to spot immediate structural targets. A Poor High often acts as a magnet for price to revisit and "repair," while Single Prints often defend as support/resistance on the first retest.
PEAD ScreenerPEAD Screener - Post-Earnings Announcement Drift Scanner
═══════════════════════════════════════════════════════════════
WHY EARNINGS ANNOUNCEMENTS CREATE OPPORTUNITY
═══════════════════════════════════════════════════════════════
The days immediately following an earnings announcement are among the noisiest periods for any stock. Within hours, the market must digest new information about a company's profits, revenue, and future outlook. Analysts scramble to update their models. Institutions rebalance positions. Retail traders react to headlines.
This chaos creates a well-documented phenomenon called Post-Earnings Announcement Drift (PEAD): stocks that beat expectations tend to keep rising, while those that miss tend to keep falling - often for weeks after the initial announcement. Academic research has confirmed this pattern persists across decades and markets.
But not every earnings surprise is equal. A company that beats estimates by 5 cents might move very differently than one that beats by 5 cents with unusually high volume, or one where both earnings AND revenue exceeded expectations. Raw numbers alone don't tell the full story.
═══════════════════════════════════════════════════════════════
HOW "STANDARDIZED UNEXPECTED" METRICS CUT THROUGH THE NOISE
═══════════════════════════════════════════════════════════════
This screener uses a statistical technique to measure how "surprising" a result truly is - not just whether it beat or missed, but how unusual that beat or miss was compared to the company's own history.
The core idea: convert raw surprises into Z-scores.
A Z-score answers the question: "How many standard deviations away from normal is this result?"
- A Z-score of 0 means the result was exactly average
- A Z-score of +2 means the result was unusually high (better than ~95% of historical results)
- A Z-score of -2 means the result was unusually low
By standardizing surprises this way, we can compare apples to apples. A small-cap biotech's $0.02 beat might actually be more significant than a mega-cap's $0.50 beat, once we account for each company's typical variability.
This screener applies this standardization to three dimensions: earnings (SUE), revenue (SURGE), and volume (SUV).
═══════════════════════════════════════════════════════════════
THE 9 SCREENING CRITERIA
═══════════════════════════════════════════════════════════════
─────────────────────────────────────────
1. SUE (Standardized Unexpected Earnings)
─────────────────────────────────────────
WHAT IT IS:
SUE measures how surprising an earnings result was, adjusted for the company's historical forecast accuracy.
Calculation: Take the earnings surprise (actual EPS minus analyst estimate), then divide by the standard deviation of past forecast errors. This uses a rolling window of the last 8 quarters by default.
Formula: SUE = (Actual EPS - Estimated EPS) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SUE > +2.0: Strongly positive surprise - earnings beat expectations by an unusually large margin. These stocks often continue drifting higher.
- SUE between 0 and +2.0: Modest positive surprise - beat expectations, but within normal range.
- SUE between -2.0 and 0: Modest negative surprise - missed expectations, but within normal range.
- SUE < -2.0: Strongly negative surprise - significant miss. These stocks often continue drifting lower.
For long positions, look for SUE values above +2.0, ideally combined with positive SURGE.
─────────────────────────────────────────
2. SURGE (Standardized Unexpected Revenue)
─────────────────────────────────────────
WHAT IT IS:
SURGE applies the same standardization technique to revenue surprises. While earnings can be manipulated through accounting choices, revenue is harder to fake - it represents actual sales.
Calculation: Take the revenue surprise (actual revenue minus analyst estimate), then divide by the standard deviation of past revenue forecast errors.
Formula: SURGE = (Actual Revenue - Estimated Revenue) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SURGE > +1.5: Strongly positive revenue surprise - the company sold significantly more than expected.
- SURGE between 0 and +1.5: Modest positive surprise.
- SURGE < 0: Revenue missed expectations.
The most powerful signals occur when BOTH SUE and SURGE are positive and elevated (ideally SUE > 2.0 AND SURGE > 1.5). This indicates the company beat on both profitability AND top-line growth - a much stronger signal than either alone.
When SUE and SURGE diverge significantly (e.g., high SUE but negative SURGE), treat with caution - the earnings beat may have come from cost-cutting rather than genuine growth.
─────────────────────────────────────────
3. SUV (Standardized Unexpected Volume)
─────────────────────────────────────────
WHAT IT IS:
SUV detects unusual trading volume after accounting for how volatile the stock is. More volatile stocks naturally have higher volume, so raw volume comparisons can be misleading.
Calculation: This uses regression analysis to model the expected relationship between price volatility and volume. The "unexpected" volume is the residual - how much actual volume deviated from what the model predicted. This residual is then standardized into a Z-score.
In plain terms: SUV asks "Given how much this stock typically moves, is today's volume unusually high or low?"
HOW TO INTERPRET:
- SUV > +2.0: Exceptionally high volume relative to the stock's volatility. This often signals institutional activity - big players moving in or out.
- SUV between +1.0 and +2.0: Elevated volume - above normal interest.
- SUV between -1.0 and +1.0: Normal volume range.
- SUV < -1.0: Unusually quiet - less activity than expected.
High SUV combined with positive price movement suggests accumulation (buying). High SUV combined with negative price movement suggests distribution (selling).
─────────────────────────────────────────
4. % From D0 Close
─────────────────────────────────────────
WHAT IT IS:
This measures how far the current price has moved from the closing price on its initial earnings reaction day (D0). The "reaction day" is the first trading day that fully reflects the earnings news - typically the day after an after-hours announcement, or the announcement day itself for pre-market releases.
Calculation: ((Current Price - D0 Close) / D0 Close) × 100
HOW TO INTERPRET:
- Positive values: Stock has gained ground since earnings. The higher the percentage, the stronger the post-earnings drift.
- 0% to +5%: Modest positive drift - earnings were received well but momentum is limited.
- +5% to +15%: Strong drift - buyers continue accumulating.
- > +15%: Exceptional drift - significant institutional interest likely.
- Negative values: Stock has given back gains or extended losses since earnings. May indicate the initial reaction was overdone, or that sentiment is deteriorating.
This metric is most meaningful within the first 5-20 trading days after earnings. Extended drift (maintaining gains over 2+ weeks) is a stronger signal than a quick spike that fades.
─────────────────────────────────────────
5. # Pocket Pivots
─────────────────────────────────────────
WHAT IT IS:
Pocket Pivots are a volume-based pattern developed by Chris Kacher and Gil Morales. They identify days where institutional buyers are likely accumulating shares without causing obvious breakouts.
Calculation: A Pocket Pivot occurs when:
- The stock closes higher than it opened (up day)
- The stock closes higher than the previous day's close
- Today's volume exceeds the highest down-day volume of the prior 10 trading sessions
The screener counts how many Pocket Pivots have occurred since the earnings announcement.
HOW TO INTERPRET:
- 0 Pocket Pivots: No detected institutional accumulation patterns since earnings.
- 1-2 Pocket Pivots: Some institutional buying interest - worth monitoring.
- 3+ Pocket Pivots: Strong accumulation signal - institutions appear to be building positions.
Pocket Pivots are most significant when they occur:
- Immediately following earnings announcements
- Near moving average support (10-day, 21-day, or 50-day)
- On above-average volume
- After a period of price consolidation
Multiple Pocket Pivots in a short period suggest sustained institutional demand, not just a one-day event.
─────────────────────────────────────────
6. ADX/DI (Trend Strength and Direction)
─────────────────────────────────────────
WHAT IT IS:
ADX (Average Directional Index) measures trend strength regardless of direction. DI (Directional Indicator) shows whether the trend is bullish or bearish.
Calculation: ADX uses a 14-period lookback to measure how directional (trending) price movement is. Values range from 0 to 100. The +DI and -DI components compare upward and downward movement.
The screener shows:
- ADX value (trend strength)
- Direction indicator: "+" for bullish (price trending up), "-" for bearish (price trending down)
HOW TO INTERPRET:
- ADX < 20: Weak trend - the stock is moving sideways, choppy. Not ideal for momentum trading.
- ADX 20-25: Trend is emerging - potentially starting a directional move.
- ADX 25-40: Strong trend - clear directional movement. Good for momentum plays.
- ADX > 40: Very strong trend - powerful move in progress, but may be extended.
The direction indicator (+/-) tells you which way:
- "25+" means ADX of 25 with bullish direction (uptrend)
- "25-" means ADX of 25 with bearish direction (downtrend)
For post-earnings plays, ideal setups show ADX rising above 25 with positive direction, confirming the earnings reaction is developing into a sustained trend rather than a one-day spike.
─────────────────────────────────────────
7. Institutional Buying PASS
─────────────────────────────────────────
WHAT IT IS:
This proprietary composite indicator detects patterns consistent with institutional accumulation at three stages after earnings:
EARLY (Days 0-4): Looks for "large block" buying on the earnings reaction day (exceptionally high volume with a close in the upper half of the day's range) combined with follow-through buying on the next day.
MID (Days 5-9): Checks for sustained elevated volume (averaging 1.5x the 20-day average) combined with positive drift and consistent upward price movement (more up days than down days).
LATE (Days 10+): Detects either visible accumulation (positive drift with high volume) OR stealth accumulation (positive drift with unusually LOW volume - suggesting smart money is quietly building positions without attracting attention).
HOW TO INTERPRET:
- Check mark/value of '1': Institutional buying pattern detected. The stock shows characteristics consistent with large players accumulating shares.
- X mark/value of '0': No institutional buying pattern detected. This doesn't mean institutions aren't buying - just that the typical footprints aren't visible.
A passing grade here adds conviction to other bullish signals. Institutions have research teams, information advantages, and long time horizons. When their footprints appear in the data, it often precedes sustained moves.
Important: This is a pattern detection tool, not a guarantee. Always combine with other analysis.
─────────────────────────────────────────
8. Strong ATR Drift PASS
─────────────────────────────────────────
WHAT IT IS:
This measures whether the stock has drifted significantly relative to its own volatility. Instead of asking "did it move 10%?", it asks "did it move more than 1.5 ATRs?"
ATR (Average True Range) measures a stock's typical daily movement. A volatile stock might move 5% daily, while a stable stock might move 0.5%. Using ATR normalizes for this difference.
Calculation:
ATR Drift = (Current Close - D0 Close) / D0 ATR in dollars
The indicator passes when ATR Drift exceeds 1.5 AND at least 5 days have passed since earnings.
HOW TO INTERPRET:
- Check mark/value of '1': The stock has drifted more than 1.5 times its average daily range since earnings - a statistically significant move that suggests genuine momentum, not just noise.
- X mark/value of '0': The drift (if any) is within normal volatility bounds - could just be random fluctuation.
Why wait 5 days? The immediate post-earnings reaction (days 0-2) often includes gap fills and noise. By day 5, if the stock is still extended beyond 1.5 ATRs from the earnings close, it suggests real buying pressure, not just a reflexive gap.
A passing grade here helps filter out stocks that "beat earnings" but haven't actually moved meaningfully. It focuses attention on stocks where the market is voting with real capital.
─────────────────────────────────────────
9. Days Since D0
─────────────────────────────────────────
WHAT IT IS:
Simply counts the number of trading days since the earnings reaction day (D0).
HOW TO INTERPRET:
- Days 0-5 (Green): Fresh earnings - the information is new, institutional repositioning is active, and momentum trades are most potent. This is the "sweet spot" for PEAD strategies.
- Days 6-10 (Neutral): Mid-period - some edge remains but diminishing. Good for adding to winning positions, less ideal for new entries.
- Days 11+ (Red): Extended period - most of the post-earnings drift has typically played out. Higher risk that momentum fades or reverses.
Research shows PEAD effects are strongest in the first 5-10 days after earnings, then decay. Beyond 20-30 days, the informational advantage of the earnings surprise is largely priced in.
Use this to prioritize: focus on stocks with strong signals that are still in the early window, and be more selective about entries as days accumulate.
═══════════════════════════════════════════════════════════════
PUTTING IT ALL TOGETHER
═══════════════════════════════════════════════════════════════
You can use this screener in the chart view or in the Screener.
One combination of the above filters to develop a shortlist of positive drift candidates may be:
- SUE > 2.0 (significant earnings beat)
- SURGE > 1.5 (significant revenue beat)
- Positive % From D0 Close (price confirming the good news)
- Institutional Buying PASS (big players accumulating)
- Strong ATR Drift PASS (statistically significant movement)
- Days Since D0 < 10 (still in the active drift window)
No single indicator is sufficient. The power comes from convergence - when multiple independent measures all point the same direction.
═══════════════════════════════════════════════════════════════
SETTINGS
═══════════════════════════════════════════════════════════════
Key adjustable parameters:
- SUE Method: "Analyst-based" uses consensus estimates; "Time-series" uses year-over-year comparison
- Window Size: Number of quarters used for standardization (default: 8)
- ATR Drift Threshold: Minimum ATR multiple for "strong" classification (default: 1.5)
- Institutional Buying thresholds: Adjustable volume and CLV parameters
═══════════════════════════════════════════════════════════════
DISCLAIMER
═══════════════════════════════════════════════════════════════
This screener is a research tool, not financial advice. Past patterns do not guarantee future results. Always conduct your own due diligence and manage risk appropriately. Post-earnings trading involves significant uncertainty and volatility. The 'SUE' in this indicator does not represent a real person; any similarity to actual Sue's (or Susans for that matter) living or dead is quite frankly ridiculous, not to mention coincidental.
EMA Cross BUY SELL
ema1Length = input.int(10, "EMA1 Periyodu")
ema2Length = input.int(20, "EMA2 Periyodu")
emaLineWidth = input.int(3, "EMA Çizgi Kalınlığı", minval=1, maxval=10)
bgTransparency = input.int(85, "Arka Plan Saydamlığı", minval=0, maxval=100)
ema1 = ta.ema(close, ema1Length)
ema2 = ta.ema(close, ema2Length)
longSignal = ta.crossover(ema1, ema2)
shortSignal = ta.crossunder(ema1, ema2)
var int trend = 0
trend := longSignal ? 1 : shortSignal ? -1 : trend
barcolor(trend == 1 ? color.green : trend == -1 ? color.red : na)
bgcolor(trend == 1 ? color.new(color.green, bgTransparency) : trend == -1 ? color.new(color.red, bgTransparency) : na)
plot(ema1, color=trend == 1 ? color.green : trend == -1 ? color.red : color.gray, linewidth=emaLineWidth, title="EMA1")
plot(ema2, color=trend == 1 ? color.green : trend == -1 ? color.red : color.gray, linewidth=emaLineWidth, title="EMA2")
plotshape(longSignal, title="Al Ok", style=shape.triangleup, location=location.belowbar, color=color.green, size=size.large)
plotshape(shortSignal, title="Sat Ok", style=shape.triangledown, location=location.abovebar, color=color.red, size=size.large)
EMA Color Buy/Sell
indicator("EMA Color & Buy/Sell Signals", overlay=true, max_lines_count=500, max_labels_count=500)
EMA
emaShortLen = input.int(9, "Kısa EMA")
emaLongLen = input.int(21, "Uzun EMA")
EMA
emaShort = ta.ema(close, emaShortLen)
emaLong = ta.ema(close, emaLongLen)
EMA renkleri (trend yönüne göre)
emaShortColor = emaShort > emaShort ? color.green : color.red
emaLongColor = emaLong > emaLong ? color.green : color.red
EMA
plot(emaShort, color=emaShortColor, linewidth=3, title="EMA Short")
plot(emaLong, color=emaLongColor, linewidth=3, title="EMA Long")
buySignal = ta.crossover(emaShort, emaLong)
sellSignal = ta.crossunder(emaShort, emaLong)
plotshape(buySignal, title="Buy", location=location.belowbar, color=color.lime, style=shape.triangleup, size=size.large)
plotshape(sellSignal, title="Sell", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.large)
barcolor(close > open ? color.new(color.green, 0) : color.new(color.red, 0))
var line buyLine = na
var line sellLine = na
if buySignal
buyLine := line.new(bar_index, low, bar_index, high, color=color.lime, width=2)
if sellSignal
sellLine := line.new(bar_index, high, bar_index, low, color=color.red, width=2)
EMA Color Cross + Trend Arrows V6//@version=5
indicator("EMA Color Cross + Trend Arrows V6", overlay=true, max_bars_back=500)
// === Inputs ===
fastLen = input.int(9, "Hızlı EMA")
slowLen = input.int(21, "Yavaş EMA")
// === EMA Hesapları ===
emaFast = ta.ema(close, fastLen)
emaSlow = ta.ema(close, slowLen)
// Trend Yönü
trendUp = emaFast > emaSlow
trendDown = emaFast < emaSlow
// === Çizgi Renkleri ===
lineColor = trendUp ? color.new(color.green, 0) : color.new(color.red, 0)
// === EMA Çizgileri (agresif kalın) ===
plot(emaFast, "Hızlı EMA", lineColor, 4)
plot(emaSlow, "Yavaş EMA", color.new(color.gray, 70), 2)
// === Ok Sinyalleri ===
buySignal = ta.crossover(emaFast, emaSlow)
sellSignal = ta.crossunder(emaFast, emaSlow)
// Büyük Oklar
plotshape(buySignal, title="AL", style=shape.triangleup, color=color.green, size=size.large, location=location.belowbar)
plotshape(sellSignal, title="SAT", style=shape.triangledown, color=color.red, size=size.large, location=location.abovebar)
// === Trend Bar Color ===
barcolor(trendUp ? color.green : color.red)
Basit BUY SELL//@version=5
indicator("Basit Yeşil Al - Kırmızı Sat", overlay=true)
// Mum renkleri
yesil = close > open
kirmizi = close < open
// Yeşil mumda AL oku
plotshape(yesil, title="AL", location=location.belowbar, color=color.lime, style=shape.triangleup, size=size.large, text="AL")
// Kırmızı mumda SAT oku
plotshape(kirmizi, title="SAT", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.large, text="SAT")
Renkli Parabolic SAR - Sade Versiyon//@version=5
indicator("Renkli Parabolic SAR - Sade Versiyon", overlay=true)
// === PSAR Ayarları ===
psarStart = input.float(0.02, "PSAR Başlangıç (Step)", step=0.01)
psarIncrement = input.float(0.02, "PSAR Artış (Increment)", step=0.01)
psarMax = input.float(0.2, "PSAR Maksimum (Max)", step=0.01)
// === PSAR Hesaplama ===
psar = ta.sar(psarStart, psarIncrement, psarMax)
// === Trend Tespiti ===
bull = close > psar
bear = close < psar
// === Renk Ayarları ===
barColor = bull ? color.new(color.green, 0) : color.new(color.red, 0)
psarColor = bull ? color.green : color.red
bgColor = bull ? color.new(color.green, 90) : color.new(color.red, 90)
// === Mum ve PSAR ===
barcolor(barColor)
plotshape(bull, title="PSAR Bull", location=location.belowbar, style=shape.circle, size=size.tiny, color=color.green)
plotshape(bear, title="PSAR Bear", location=location.abovebar, style=shape.circle, size=size.tiny, color=color.red)
// === Arka Plan ===
bgcolor(bgColor)
// === Al / Sat Sinyalleri ===
buySignal = ta.crossover(close, psar)
sellSignal = ta.crossunder(close, psar)
plotshape(buySignal, title="AL", location=location.belowbar, style=shape.triangleup, size=size.large, color=color.lime)
plotshape(sellSignal, title="SAT", location=location.abovebar, style=shape.triangledown, size=size.large, color=color.red)
// === Alarm Koşulları ===
alertcondition(buySignal, title="AL Sinyali", message="Parabolic SAR Al Sinyali")
alertcondition(sellSignal, title="SAT Sinyali", message="Parabolic SAR Sat Sinyali")
Initial Balance with AlertsThis indicator is a comprehensive tool for Auction Market Theory (AMT) practitioners who rely on the Initial Balance (IB) to determine the day's likely structure. It automatically plots the High and Low of the opening session (user-definable) and extends those levels to provide key support and resistance zones for the remainder of the trading day.
Unlike standard IB indicators, this script features Smart Alerts that are time-filtered. You can define a specific "Active Alert Window" (e.g., RTH only) to ensure you are notified of breakouts during key hours, while avoiding spam notifications during overnight or low-volume sessions.
Key Features:
1. Customizable Initial Balance
Flexible Session: Define the exact start and end time for your IB calculation (Default: 08:30–09:30).
Visual Clarity: Plots IB High, IB Low, and the 50% Midpoint with fully customizable line styles, colors, and widths.
2. Smart Time-Filtered Alerts
Breakout Detection: Triggers an alert when price crosses above the IB High or below the IB Low.
Session Filter: Includes a unique "Allowed Alert Time" input. Alerts will only fire if the breakout happens within this window (Default: 08:30–15:00), preventing unwanted notifications during overnight chop.
3. Advanced Extensions & Targets
Extensions: Option to display multiples of the IB range (2x, 3x) to serve as statistical targets for trend days.
Intermediate Levels: Option to display half-step extensions (e.g., 1.5x) for tighter scalping targets.
4. IB Delta Analytics Dashboard
Context is Key: An optional on-screen dashboard tracks the size of the Initial Balance over the last 20 days.
Sentiment: Automatically categorizes today's IB as "Huge," "Medium," or "Small" compared to the 20-day average. This helps you anticipate if the day is likely to be a "Range Day" (Large IB) or a "Trend Day" (Small IB).
Settings Overview:
Calculation Period: The time used to measure the high and low (e.g., first 60 mins).
Allowed Alert Time: The window during which alerts are active.
Show Extra Levels: Toggles the 2x and 3x extensions.
Fill IB Areas: Adds a background color to the opening range for better visibility.
Delta Analytics: Toggles the statistics table on/off.
Author's Instructions
How to Configure the Time Settings: This script uses two distinct time inputs to give you maximum control:
"Calculation period": This is when the script measures the High and Low.
Example: 0830-0930 (The first hour of the NYSE session).
"Allowed Alert Time (RTH)": This is when the script is allowed to send you alerts.
Example: 0830-1500 (The full trading day).
Why this matters: If price breaks the IB High at 18:00 (during the overnight session), the script will ignore it if your alert time ends at 15:00. This saves you from waking up to low-probability signals.
Setting Up Alerts: To activate the alerts, add the indicator to your chart, click the "Alerts" button (clock icon) in the top toolbar, select this indicator from the "Condition" list, and choose "Any alert() function call".
Disclaimer: This tool is for informational purposes only. Past performance does not guarantee future results.
Custom Monthly Volume Profile [Multi-Timeframe]This indicator renders a high-precision Monthly Volume Profile designed for intraday traders and practitioners of Auction Market Theory. Unlike standard volume profiles, this script utilizes Multi-Timeframe (MTF) data request capability to build the profile from lower timeframe data (e.g., 5-minute bars) while displaying it on your trading timeframe.
This tool is optimized to keep your chart clean while providing critical developing levels (POC, VAH, VAL) and historical context from the previous month.
Key Features:
1. Dynamic "Auto-Scaling" Width One of the biggest issues with monthly profiles is visual clutter.
Early Month: The profile starts wide (default 10% width) so you can clearly see the developing structure when data is scarce.
Late Month: As volume accumulates, the profile automatically shrinks (scales down to 2% width) to prevent the histogram from obscuring price action.
Note: This can be toggled off for a static width.
2. Developing & Static Levels
Current Month: Displays real-time Developing Point of Control (dPOC), Value Area High (dVAH), and Value Area Low (dVAL).
Previous Month: Automatically locks in the levels from the previous month at the close, providing immediate support/resistance references for the new month.
3. Time-Filtered Alerts Avoid waking up to notifications during low-volume overnight sessions. This script includes a Session Filter (Default: 0830-1500).
Alerts for crossing POC, VAH, or VAL will only trigger if the price cross occurs within the user-defined time window.
4. Calculation Precision
Multi-Timeframe Data: The profile is built using lower timeframe data (Input: Calculation Precision) rather than just the current chart bars. This ensures the Volume Profile shape remains accurate even when viewing higher timeframes.
Row Size: Fully adjustable "Tick/Row Size" to control the resolution of the volume buckets.
Settings Overview:
Calculation Precision: Determine the granularity of the data (e.g., "5" for 5-minute data).
Row Size: Controls vertical resolution (Lower = higher detail).
Value Area %: Standard 70% default, fully adjustable.
Auto-Width: Set the Start % (Day 1) and End % (Day 31).
Alerts: Toggle Current or Previous month alerts and define the active time session.
Visual Customization:
Customize colors for the Histogram (Value Area vs. Outer Area).
Customize line width and colors for POC, VAH, and VAL.
Supports Right or Left alignment.
Disclaimer: This tool is for informational purposes only. Past performance and volume levels do not guarantee future price action.
Heikin-Ashi Bar & Line with Signals//@version=6
indicator("Heikin-Ashi Bar & Line with Signals", overlay=true)
// Heikin-Ashi hesaplamaları
var float haOpen = na // İlk değer için var kullanıyoruz
haClose = (open + high + low + close) / 4
haOpen := na(haOpen) ? (open + close)/2 : (haOpen + haClose )/2
haHigh = math.max(high, haOpen, haClose)
haLow = math.min(low, haOpen, haClose)
// Renkler
haBull = haClose >= haOpen
haColor = haBull ? color.new(color.green, 0) : color.new(color.red, 0)
// HA Barları
plotcandle(haOpen, haHigh, haLow, haClose, color=haColor, wickcolor=haColor)
// HA Line
plot(haClose, title="HA Close Line", color=color.yellow, linewidth=2)
// Trend arka planı
bgcolor(haBull ? color.new(color.green, 85) : color.new(color.red, 85))
// Al/Sat sinyalleri
longSignal = haBull and haClose > haOpen and haClose < haOpen
shortSignal = not haBull and haClose < haOpen and haClose > haOpen
plotshape(longSignal, title="Al Sinyali", style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small)
plotshape(shortSignal, title="Sat Sinyali", style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small)
Gamma & Volatility Levels [Pro]General Purpose
This indicator analyzes volatility levels and expected price movements, combining gamma concepts (financial options) with volatility analysis to identify support and resistance zones.
Main Components
High Volatility Level (HVL): Calculates a volatility level based on the simple moving average (SMA) of the price plus one standard deviation. This level is represented by an orange line showing where volatility is concentrated.
Expected Movement (Movimiento Esperante): Uses the Average True Range (ATR) multiplied by an adjustable factor to project potential upward and downward movement ranges from the current price. It is drawn in green (upward) and red (downward).
Gamma Levels (Nivelas Gamma): Identifies two key levels: the call resistance (highest high of the last 50 periods) in blue, and the put support (lowest low) in purple. These are based on recent extreme prices.
Additional Information: The indicator calculates the percentage distance between the current price and the HVL, displaying it in a label.
Visual Elements
Colored lines on the chart for each level.
Labels with exact values next to each line.
A table in the upper right corner summarizing all calculated values.
Options to show or hide each element according to preference.
This is a useful tool for traders who work with options or seek to identify levels of extreme volatility and dynamic support/resistance zones.
7/19 EMA Crossover Alertsaskl hasodidu fuasdo asdfasdfiu sdfiuyiodafugoasdf fa sgyu dsgasdo asfo o asdf
Position Trdaing Lines (2 entries + live PnL)Position Trading Lines (2 entries + live PnL) is a utility script designed to visually manage a manual position on the chart, with clear TP/SL levels and real-time profit & loss.
The script does not place orders. It is meant to help you simulate / track an existing or planned position.
Features
• Up to 2 trades on the same symbol
• Each trade has:
• Direction: Long / Short
• Position size (lot)
• Entry price
• Take Profit (T.Profit) price
• Stop Loss (S.Loss) price
• Entry shift in bars from the last candle (to align with past or future entries)
• Visual lines on the price chart
• Horizontal line at the entry price
• Horizontal line at Take Profit
• Horizontal line at Stop Loss
• Informative labels
• Entry label showing: direction, size and @ entry price
• TP and SL labels showing:
• T.Profit / S.Loss
• position size
• @ price
• estimated PnL at that level
• If both trades share the same TP or SL price, a single combined label is shown with the total size and total PnL.
• Commissions
• Global commission input (percentage over notional).
• Commission is included in all PnL calculations.
• Live PnL label
• Real-time combined PnL of the active trades, updated on the last bar.
• Color changes with sign (green for profit, red for loss).
• Selective PnL for Trade 2
• Trade 2 has a switch: “Count PnL in total”.
• You can keep Trade 2 visible on the chart but exclude it from the combined PnL until it is actually active.
This tool is useful for discretionary traders who want a clean visual representation of their position, R:R, and projected outcomes directly on the chart, without relying on the broker’s position panel.
Neosha Concept V4 (NY Time)
Imagine the financial market as a huge ocean. Millions of traders throw orders into it every second. But beneath all the noise, there is a powerful current that quietly controls where the waves move. That current is not a person, not a trader, and not random—it is an algorithm.
This algorithm is called the Interbank Price Delivery Algorithm (IPDA).
Think of it as the “navigation system” that guides price through the market.
IPDA has one job:
to move prices in a way that keeps the market efficient and liquid.
To do this, it constantly looks for two things:
1. Where liquidity is hiding
Liquidity is usually found above highs and below lows—where traders place stop losses. The algorithm moves price there first to collect that liquidity.
2. Where price became unbalanced
Sometimes price moves too fast and creates gaps or imbalances. IPDA returns to those areas later to “fix” the missing orders.
Once you start looking at the charts with this idea in mind, everything makes more sense:
Why price suddenly spikes above a high and crashes down
Why big moves leave gaps that price later fills
Why the market reverses right after taking stops
Why trends begin only after certain levels are hit
These are not accidents.
They are the algorithm doing its job.
Price moves in a repeating cycle:
Gather liquidity
Make a strong move (displacement)
Return to fix inefficiency
Deliver to the next target
Most beginners only see the candles.
But once you understand IPDA, you see the intention behind the candles.
Instead of guessing where price might go, you begin to understand why it moves there.
And once you understand the “why,” your trading becomes clearer, calmer, and far more accurate.
MNQ Pro Scalping | SMA20 + VWAP Color //@version=5
TIFFANY//@version=5
indicator("MNQ Pro Scalping | SMA20 + VWAP Color + ATR SLTP + Fake Breakout", overlay=true)
// ===== INPUTS =====
smaLen = input.int(20, "SMA Length")
atrLen = input.int(14, "ATR Length")
slMult = input.float(1.0, "SL = ATR x", step=0.1)
tpMult = input.float(1.5, "TP = ATR x", step=0.1)
showNY = input.bool(true, "Only New York Session (09:30–16:00 ET)")
// ===== NY SESSION FILTER =====
inNY = not showNY or time(timeframe.period, "0930-1600")
// ===== SMA 20 =====
sma20 = ta.sma(close, smaLen)
smaColor = close > sma20 ? color.green : color.red
plot(sma20, "SMA 20", color=smaColor, linewidth=2)
// ===== VWAP (COLOR CHANGE) =====
vwapVal = ta.vwap(hlc3)
vwapColor = close > vwapVal ? color.green : color.red
plot(vwapVal, "VWAP", color=vwapColor, linewidth=2)
// ===== ATR =====
atr = ta.atr(atrLen)
// ===== CROSS CONDITIONS =====
crossUp = ta.crossover(close, sma20)
crossDown = ta.crossunder(close, sma20)
// ===== VALID TRADE CONDITIONS =====
longCond = crossUp and close > vwapVal and inNY
shortCond = crossDown and close < vwapVal and inNY
// ===== ATR SL / TP LEVELS =====
longSL = close - atr * slMult
longTP = close + atr * tpMult
shortSL = close + atr * slMult
shortTP = close - atr * tpMult
// ===== PLOT SL / TP WHEN SIGNAL =====
plot(longCond ? longSL : na, "Long SL", color=color.red, style=plot.style_linebr)
plot(longCond ? longTP : na, "Long TP", color=color.green, style=plot.style_linebr)
plot(shortCond ? shortSL : na, "Short SL", color=color.red, style=plot.style_linebr)
plot(shortCond ? shortTP : na, "Short TP", color=color.green, style=plot.style_linebr)
// ===== FAKE BREAKOUT DETECTION =====
// Giá cắt SMA nhưng đóng nến quay ngược lại
fakeUp = ta.crossover(high, sma20) and close < sma20
fakeDown = ta.crossunder(low, sma20) and close > sma20
plotshape(fakeUp and inNY, title="Fake Up", style=shape.xcross, location=location.abovebar, color=color.red, size=size.small)
plotshape(fakeDown and inNY, title="Fake Down", style=shape.xcross, location=location.belowbar, color=color.green, size=size.small)
// ===== SIGNAL SHAPES =====
plotshape(longCond, title="LONG", style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small)
plotshape(shortCond, title="SHORT", style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small)
// ===== ALERTS =====
alertcondition(longCond,
title="MNQ LONG – ATR Setup",
message="MNQ LONG: Cross ABOVE SMA20 | Above VWAP | ATR SL/TP valid")
alertcondition(shortCond,
title="MNQ SHORT – ATR Setup",
message="MNQ SHORT: Cross BELOW SMA20 | Below VWAP | ATR SL/TP valid")
alertcondition(fakeUp,
title="Fake Breakout UP",
message="WARNING: Fake breakout ABOVE SMA20")
alertcondition(fakeDown,
title="Fake Breakout DOWN",
message="WARNING: Fake breakout BELOW SMA20")
Trend zooming boxThis script clearly find trend.
You will be able to find areas where you get large impulsive moves in history easily. Not too much to describe.
SMA Cross PreventionTraditional MA crossover indicators are reactive — they tell you a cross happened after the fact.
This indicator is prescriptive — it tells you exactly what price action is required to prevent a cross from happening.
The Core Insight
When a fast MA is above a slow MA but they're converging, traders ask: "Will we get a death cross?"
This indicator answers a more useful question:
"What is the minimum price path required to prevent the cross?"
By treating the MA structure as a constraint and solving for the required input (future prices), we transform a lagging indicator into a forward-looking risk assessment tool.
MAJOR PA Zones + Structure + Targets (Gray/Purple)This script highlights major price-action structure (HH/HL/LH/LL), marks BOS/CHOCH events, and draws key supply/demand zones to help visualize trend shifts and potential targets.
RRE ZonesLine Creation: Each FVG box now has a corresponding dashed line drawn through its center:
Uses a dashed style for clear visibility
Matches the FVG color (with 30% transparency)
Extends to the right like the box
Width of 1 pixel
Synchronized Cleanup: When FVG boxes are removed (either by reaching max count or being filled by price), their corresponding center lines are also deleted automatically.
The center lines help you:
Quickly identify the 50% level of each FVG
Use it as a potential target or entry level
Better visualize the gap's midpoint for trading decisions
Density Zones (GM Crossing Clusters) + QHO Spin FlipsINDICATOR NAME
Density Zones (GM Crossing Clusters) + QHO Spin Flips
OVERVIEW
This indicator combines two complementary ideas into a single overlay: *this combines my earlier Geometric Mean Indicator with the Quantum Harmonic Oscillator (Overlay) with additional enhancements*
1) Density Zones (GM Crossing Clusters)
A “Density Zone” is detected when price repeatedly crosses a Geometric Mean equilibrium line (GM) within a rolling lookback window. Conceptually, this identifies regions where the market is repeatedly “snapping” across an equilibrium boundary—high churn, high decision pressure, and repeated re-selection of direction.
2) QHO Spin Flips (Regression-Residual σ Breaches)
A “Spin Flip” is detected when price deviates beyond a configurable σ-threshold (κ) from a regression-based equilibrium, using normalized residuals. Conceptually, this marks excursions into extreme states (decoherence / expansion), which often precede a reversion toward equilibrium and/or a regime re-scaling.
These two systems are related but not identical:
- Density Zones identify where equilibrium crossings cluster (a “singularity”/anchor behavior around GM).
- Spin Flips identify when price exceeds statistically extreme displacement from the regression equilibrium (LSR), indicating expansion beyond typical variance.
CORE CONCEPTS AND FORMULAS
SECTION A — GEOMETRIC MEAN EQUILIBRIUM (GM)
We define two moving averages:
(1) MA1_t = SMA(close_t, L1)
(2) MA2_t = SMA(close_t, L2)
We define the equilibrium anchor as the geometric mean of MA1 and MA2:
(3) GM_t = sqrt( MA1_t * MA2_t )
This GM line acts as an equilibrium boundary. Repeated crossings are interpreted as high “equilibrium churn.”
SECTION B — CROSS EVENTS (UP/DOWN)
A “cross event” is registered when the sign of (close - GM) changes:
Define a sign function s_t:
(4) s_t =
+1 if close_t > GM_t
-1 if close_t < GM_t
s_{t-1} if close_t == GM_t (tie-breaker to avoid false flips)
Then define the crossing event indicator:
(5) crossEvent_t = 1 if s_t != s_{t-1}
0 otherwise
Additionally, the indicator plots explicit cross markers:
- Cross Above GM: crossover(close, GM)
- Cross Below GM: crossunder(close, GM)
These provide directional visual cues and match the original Geometric Mean Indicator behavior.
SECTION C — DENSITY MEASURE (CROSSING CLUSTER COUNT)
A Density Zone is based on the number of cross events occurring in the last W bars:
(6) D_t = Σ_{i=0..W-1} crossEvent_{t-i}
This is a “crossing density” score: how many times price has toggled across GM recently.
The script implements this efficiently using a cumulative sum identity:
Let x_t = crossEvent_t.
(7) cumX_t = Σ_{j=0..t} x_j
Then:
(8) D_t = cumX_t - cumX_{t-W} (for t >= W)
cumX_t (for t < W)
SECTION D — DENSITY ZONE TRIGGER
We define a Density Zone state:
(9) isDZ_t = ( D_t >= θ )
where:
- θ (theta) is the user-selected crossing threshold.
Zone edges:
(10) dzStart_t = isDZ_t AND NOT isDZ_{t-1}
(11) dzEnd_t = NOT isDZ_t AND isDZ_{t-1}
SECTION E — DENSITY ZONE BOUNDS
While inside a Density Zone, we track the running high/low to display zone bounds:
(12) dzHi_t = max(dzHi_{t-1}, high_t) if isDZ_t
(13) dzLo_t = min(dzLo_{t-1}, low_t) if isDZ_t
On dzStart:
(14) dzHi_t := high_t
(15) dzLo_t := low_t
Outside zones, bounds are reset to NA.
These bounds visually bracket the “singularity span” (the churn envelope) during each density episode.
SECTION F — QHO EQUILIBRIUM (REGRESSION CENTERLINE)
Define the regression equilibrium (LSR):
(16) m_t = linreg(close_t, L, 0)
This is the “centerline” the QHO system uses as equilibrium.
SECTION G — RESIDUAL AND σ (FIELD WIDTH)
Residual:
(17) r_t = close_t - m_t
Rolling standard deviation of residuals:
(18) σ_t = stdev(r_t, L)
This σ_t is the local volatility/width of the residual field around the regression equilibrium.
SECTION H — NORMALIZED DISPLACEMENT AND SPIN FLIP
Define the standardized displacement:
(19) Y_t = (close_t - m_t) / σ_t
(If σ_t = 0, the script safely treats Y_t = 0.)
Spin Flip trigger uses a user threshold κ:
(20) spinFlip_t = ( |Y_t| > κ )
Directional spin flips:
(21) spinUp_t = ( Y_t > +κ )
(22) spinDn_t = ( Y_t < -κ )
The default κ=3.0 corresponds to “3σ excursions,” which are statistically extreme under a normal residual assumption (even though real markets are not perfectly normal).
SECTION I — QHO BANDS (OPTIONAL VISUALIZATION)
The indicator optionally draws the standard σ-bands around the regression equilibrium:
(23) 1σ bands: m_t ± 1·σ_t
(24) 2σ bands: m_t ± 2·σ_t
(25) 3σ bands: m_t ± 3·σ_t
These provide immediate context for the Spin Flip events.
WHAT YOU SEE ON THE CHART
1) MA1 / MA2 / GM lines (optional)
- MA1 (blue), MA2 (red), GM (green).
- GM is the equilibrium anchor for Density Zones and cross markers.
2) GM Cross Markers (optional)
- “GM↑” label markers appear on bars where close crosses above GM.
- “GM↓” label markers appear on bars where close crosses below GM.
3) Density Zone Shading (optional)
- Background shading appears while isDZ_t = true.
- This is the period where the crossing density D_t is above θ.
4) Density Zone High/Low Bounds (optional)
- Two lines (dzHi / dzLo) are drawn only while in-zone.
- These bounds bracket the full churn envelope during the density episode.
5) QHO Bands (optional)
- 1σ, 2σ, 3σ shaded zones around regression equilibrium.
- These visualize the current variance field.
6) Regression Equilibrium (LSR Centerline)
- The white centerline is the regression equilibrium m_t.
7) Spin Flip Markers
- A circle is plotted when |Y_t| > κ (beyond your chosen σ-threshold).
- Marker size is user-controlled (tiny → huge).
HOW TO USE IT
Step 1 — Pick the equilibrium anchor (GM)
- L1 and L2 define MA1 and MA2.
- GM = sqrt(MA1 * MA2) becomes your equilibrium boundary.
Typical choices:
- Faster equilibrium: L1=20, L2=50 (default-like).
- Slower equilibrium: L1=50, L2=200 (macro anchor).
Interpretation:
- GM acts like a “center of mass” between two moving averages.
- Crosses show when price flips from one side of equilibrium to the other.
Step 2 — Tune Density Zones (W and θ)
- W controls the time window measured (how far back you count crossings).
- θ controls how many crossings qualify as a “density/singularity episode.”
Guideline:
- Larger W = slower, broader density detection.
- Higher θ = only the most intense churn is labeled as a Density Zone.
Interpretation:
- A Density Zone is not “bullish” or “bearish” by itself.
- It is a condition: repeated equilibrium toggling (high churn / high compression).
- These often precede expansions, but direction is not implied by the zone alone.
Step 3 — Tune the QHO spin flip sensitivity (L and κ)
- L controls regression memory and σ estimation length.
- κ controls how extreme the displacement must be to trigger a spin flip.
Guideline:
- Smaller L = more reactive centerline and σ.
- Larger L = smoother, slower “field” definition.
- κ=3.0 = strong extreme filter.
- κ=2.0 = more frequent flips.
Interpretation:
- Spin flips mark when price exits the “normal” residual field.
- In your model language: a moment of decoherence/expansion that is statistically extreme relative to recent equilibrium.
Step 4 — Read the combined behavior (your key thesis)
A) Density Zone forms (GM churn clusters):
- Market repeatedly crosses equilibrium (GM), compressing into a bounded churn envelope.
- dzHi/dzLo show the envelope range.
B) Expansion occurs:
- Price can release away from the density envelope (up or down).
- If it expands far enough relative to regression equilibrium, a Spin Flip triggers (|Y| > κ).
C) Re-coherence:
- After a spin flip, price often returns toward equilibrium structures:
- toward the regression centerline m_t
- and/or back toward the density envelope (dzHi/dzLo) depending on regime behavior.
- The indicator does not guarantee return, but it highlights the condition where return-to-field is statistically likely in many regimes.
IMPORTANT NOTES / DISCLAIMERS
- This indicator is an analytical overlay. It does not provide financial advice.
- Density Zones are condition states derived from GM crossing frequency; they do not predict direction.
- Spin Flips are statistical excursions based on regression residuals and rolling σ; markets have fat tails and non-stationarity, so σ-based thresholds are contextual, not absolute.
- All parameters (L1, L2, W, θ, L, κ) should be tuned per asset, timeframe, and volatility regime.
PARAMETER SUMMARY
Geometric Mean / Density Zones:
- L1: MA1 length
- L2: MA2 length
- GM_t = sqrt(SMA(L1)*SMA(L2))
- W: crossing-count lookback window
- θ: crossing density threshold
- D_t = Σ crossEvent_{t-i} over W
- isDZ_t = (D_t >= θ)
- dzHi/dzLo track envelope bounds while isDZ is true
QHO / Spin Flips:
- L: regression + residual σ length
- m_t = linreg(close, L, 0)
- r_t = close_t - m_t
- σ_t = stdev(r_t, L)
- Y_t = r_t / σ_t
- spinFlip_t = (|Y_t| > κ)
Visual Controls:
- toggles for GM lines, cross markers, zone shading, bounds, QHO bands
- marker size options for GM crosses and spin flips
ALERTS INCLUDED
- Density Zone START / END
- Spin Flip UP / DOWN
- Cross Above GM / Cross Below GM
SUMMARY
This indicator treats the Geometric Mean as an equilibrium boundary and identifies “Density Zones” when price repeatedly crosses that equilibrium within a rolling window, forming a bounded churn envelope (dzHi/dzLo). It also models a regression-based equilibrium field and triggers “Spin Flips” when price makes statistically extreme σ-excursions from that field. Used together, Density Zones highlight compression/decision regions (equilibrium churn), while Spin Flips highlight extreme expansion states (σ-breaches), allowing the user to visualize how price compresses around equilibrium, releases outward, and often re-stabilizes around equilibrium structures over time.
Ultimate Reversion BandsURB – The Smart Reversion Tool
URB Final filters out false breakouts using a real retest mechanism that most indicators miss. Instead of chasing wicks that fail immediately, it waits for price to confirm rejection by retesting the inner band—proving sellers/buyers are truly exhausted.
Eliminates fakeouts – The retest filter catches only genuine reversions
Triple confirmation – Wick + retest + optional volume/RSI filters
Clear visuals – Outer bands show extremes, inner bands show retest zones
Works on any timeframe – From scalping to swing trading
Perfect for traders tired of getting stopped out by false breakouts.
Core Construction:
Smart Dynamic Bands:
Basis = Weighted hybrid EMA of HLC3, SMA, and WMA
Outer Bands = Basis ± (ATR × Multiplier)
Inner Bands = Basis ± (ATR × Multiplier × 0.5) → The "retest zone"
The Unique Filter: The Real Retest
Step 1: Identify an extreme wick touching the outer band
Step 2: Wait 1-3 bars for price to return and touch the inner band
Why it works: Most false breakouts never retest. A genuine reversal shows seller/buyer exhaustion by allowing price to come back to the "halfway" level.
Optional Confirmations:
Volume surge filter (default ON)
RSI extremes filter (optional)
Each can be toggled ON/OFF
How to Use:
Watch for extreme wicks touching the red/lime outer bands
Wait for the retest – price must return to touch the inner band (dotted line) within 3 bars
Enter on confirmation with built-in volume/RSI filters
Set stops beyond the extreme wick
