Optimized BTC Mean Reversion (RSI 20/65)📈 Optimized BTC Mean Reversion (RSI 20/65)
Optimized BTC Mean Reversion (RSI 20/65) is a rule-based trading strategy designed to capture mean-reversion moves in strong market structures, primarily optimized for Bitcoin, but adaptable to other liquid cryptocurrencies.
The strategy combines RSI extremes, Stochastic momentum, and EMA trend filtering to identify high-probability reversal zones while maintaining strict risk management.
🔍 Strategy Logic
This system focuses on entering trades when price temporarily deviates from equilibrium, while still respecting the broader trend.
✅ Long Conditions
RSI below 20 (oversold)
Stochastic below 25
Price trading above the 200 EMA (or within a controlled deviation)
Designed to buy sharp pullbacks in bullish conditions
❌ Short Conditions
RSI above 65 (overbought)
Stochastic above 75
Price trading below the 200 EMA
Designed to sell relief rallies in bearish conditions
🛡 Risk Management
Fixed Stop Loss: 4%
Fixed Take Profit: 6%
Risk/Reward: 1 : 1.5
No pyramiding (single position at a time)
Full equity position sizing (adjustable)
All exits are predefined at entry, ensuring consistency and emotional discipline.
📊 Indicators Used
200 EMA – Trend direction filter
RSI (14) – Mean-reversion trigger (20 / 65 levels)
Stochastic Oscillator – Momentum confirmation
👁 Visual Features
EMA plotted directly on chart
Real-time Stop Loss, Take Profit, and Entry Price lines
Clear long/short entry markers
Works on all timeframes (optimized for intraday and swing trading)
🔔 Alerts
Long entry alerts
Short entry alerts
(Perfect for automation or discretionary execution)
⚠️ Disclaimer
This strategy is intended for educational and research purposes only. Past performance does not guarantee future results. Always test on a demo account and adjust risk parameters to your own trading plan.
Chỉ báo và chiến lược
Relative Strength IndexRSI for indian market buy low and sell high.
rsi 3 low belo 15 buy and rsi high above 85 sell
Hammer Strategy (CLOSE ON NEXT BAR) [WORKING]Adjustable hammer and inverted hammer candle
Ham? INV? is the hammer
Entry on HAM, INV OR HAM?, INV? close next bar
RCI4linesRCI4lines plots four Rank Correlation Index (RCI) lines in a single panel to help you read momentum and trend conditions at a glance.
It shows two short-term RCIs (default: 7 and 9), a middle-term RCI (26), and a long-term RCI (52).
The script also draws shaded threshold zones between +80 to +95 and -80 to -95, making it easier to spot potential overbought / oversold areas and compare short-term moves with the bigger trend.
Useful for scalping to day trading, and for checking whether short-term momentum is aligned with mid/long-term direction.
SPX Master Levels & Correlations [Gemini] (v4.2)This will draw on your chart levels of SPX from other time frames low , high and ES
CRS (2 symbols: Ratio or Normalized) + InverseMade for Crosrate comparison By Leo Hanhart
This script is made to do a comparison between two assets under your current chart.
For example if you want to compare SPX over Growth ETF's Below a current asset to find momentum in your stock trading above it
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.
Golden Volume Lines📌 Golden Volume — Lines (Golden Team)
Golden Volume — Lines is an advanced volume-based indicator that detects Ultra High Volume candles using a statistical percentile model, then automatically draws and tracks key price levels derived from those candles.
The indicator highlights where real market interest and liquidity appear and shows how price reacts when those levels are broken.
🔍 How It Works
Volume Measurement
Choose between:
Units (raw volume)
Money (Volume × Average Price)
Average price can be calculated using HL2 or OHLC4.
Percentile-Based Classification
Volume is classified into:
Medium
High
Ultra High Volume
Thresholds are calculated using a rolling percentile window.
Ultra Volume candles are colored orange.
Dynamic High & Low Levels
For every Ultra Volume candle:
A High and Low dotted line is drawn.
Lines extend to the right until price breaks them.
Smart Line Break Detection (Wick-Based)
A line is considered broken when price wicks through it.
When a break occurs:
🟧 Orange line → broken by an Ultra Volume candle
⚪ White line → broken by a normal candle
The line stops exactly at the breaking candle.
🔔 Alerts
Alert on Ultra High Volume candles
Alert when a High or Low line is broken
Separate alerts for:
Break by Ultra Volume candle
Break by Normal candle
🎯 Use Cases
Breakout & continuation confirmation
Liquidity sweep detection
Volume-validated support & resistance
Market reaction after extreme participation
⚙️ Key Inputs
Volume display mode (Units / Money)
Percentile thresholds
Lookback window size
Maximum number of active Ultra levels
Optional dynamic alerts
⚠️ Disclaimer
This indicator is a volume and market structure tool, not a standalone trading system.
Always use proper risk management and additional confirmation.
VX-Session-Boxes-(AM/PM Split)(Customizable) by Ikaru-s-VX-Session-Boxes-(AM/PM Split) is a session-based visualization tool for TradingView that highlights major market sessions directly on the chart using dotted range boxes and an optional AM/PM split.
The indicator allows traders to visually separate market behavior across different sessions while keeping the chart clean and readable.
🔹 Key Features
Custom Session Definitions
Define up to 4 independent sessions using TradingView’s session format (HHMM-HHMM + weekdays).
Timezone-Aware
All sessions are calculated using a user-defined timezone (IANA or UTC offset), ensuring accurate session alignment across markets.
Dotted Session Boxes
Each session is drawn as a dotted box based on the session’s high/low range, providing a clear view of volatility and price structure.
AM / PM Split Visualization
Sessions can be visually split into AM and PM parts:
Separate box shading for AM and PM
Optional dotted vertical split line at the AM → PM transition (12:00 in the selected timezone)
Session Labels
Optional labels at the start of each session for quick identification (e.g. Sydney, Tokyo, London, New York).
Fully Customizable Visuals
Adjustable opacity, border width, and visibility toggles for boxes, split lines, and labels.
🔹 Use Cases
Session-based market analysis (Asia / London / New York)
Identifying session ranges and volatility expansion
Observing price behavior differences between AM and PM
Studying session transitions and liquidity shifts
🔹 Notes
Session boxes are based on session high and low, not full chart height.
AM/PM split is based on 12:00 (noon) in the selected timezone.
Designed for clarity and performance on intraday timeframes.
🔹 Compatibility
Pine Script® v6
Works on all intraday timeframes
Overlay indicator (draws directly on the price chart)
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.
Daily Vertical Linesadjust the time hour and minute base on ur timeframe.
please note that for asian beijing time you will need to deduct 1 hour
Relative Volume Bollinger Band %
The Relative Volume Bollinger Band % indicator is a powerful tool designed for traders seeking insights into volume, Bollinger band and relative strength dynamics. This indicator assesses the deviation of a security's trading volume relative to the Bollinger band % indicator and the RSI moving average. Together, these shed light on potential zones of interests where market shifts have a high probability of occurring.
Key Features:
Period: Tailor the indicator's sensitivity by adjusting the period of the smooth moving average and/or the period of the Bollinger band.
How it Works:
Moving Average Calculation: The script computes the simple moving average (SMA) of the relative strength over a defined period. When the higher SMA (orange line) is in the top grey zone, the security is in a zone where it has a high probability of becoming bullish. When the higher SMA is in the lower grey zone, the security is in a zone where it has a high probability of becoming bearish.
-Bollinger Band %: The script also computes the BB% which is primarily used to confirm overbought and oversold areas. When overbought, it turns white and remains white until the overbuying pressure is released indicating that the security is about to become bearish. The script indicates a bearish reversal when the BB% and RVOL bars are both red or when there are no more yellow RVOL bars, if present. When the BB% is<0 and rising, it will also appear white with yellow RVOL bars above. This is a good indication that bulls are beginning to enter buying positions. Confirmation here is indicated when the yellow RVOL bars change to green.
Relative Volume: The indicator then also normalizes the difference volume to indicate areas of high and low volatility. This shows where higher than normal volumes are being traded and can be used as a good indication of when to enter or exit a trade when the above criterions are met.
Visual Representation: The result is visually represented on the chart using columns. Bright green columns signify bullish relative volume values that are much greater than normal. Green columns signify bullish relative volume values that are significant. Red columns represent bearish values that are significant. Blue columns on the BB% indicator represent significant bullish buying in overbought areas. Red columns on the BB% indicator that are < 0 represent a bearish trend that is in an oversold area. This is there to prevent early entry into the market.
Enhancements:
Areas of Interest: Optionally, Areas of interest are represented by red, yellow and green circles on the higher SMA line, aiding in the identification of significant deviations.
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.
Pops Dividend 7-Day RadarHow traders use it as a strategy anyway 🧠
In real life, this becomes a manual or semi-systematic strategy:
Strategy logic (human-driven):
Scan for highest yield stocks
Filter for ex-date within 7 days
Apply technical rules (trend, EMAs, support)
Enter before ex-date
Exit:
Before ex-date (momentum run-up)
On ex-date
Or after dividend (reversion play)
Indicator’s role:
“Tell me when a stock qualifies so I can decide how to trade it.”
That’s exactly what this tool does.
How we could turn this into a strategy-style framework
Even though Pine won’t let us backtest dividends properly, we can:
Build a rules-based checklist (entry/exit rules)
Create alerts that behave like strategy triggers
Combine with:
EMA trend filters
Volume conditions
ATR-based exits
Label it as:
“Pops Dividend Capture Playbook” (manual execution)
This keeps it honest, legal, and reliable.
Bottom line
🧩 Indicator = what we built
📘 Strategy = how you trade it using the indicator
⚠️ TradingView limitations prevent a true dividend strategy backtest
Order Flow Analysis [Master Alert]This script is a custom modification of the original "Order Flow Analysis" indicator by kingthies.
I have taken the original code and engineered a "Master Alert" system into it. Here is the breakdown of what this specific script does:
1. The Core Purpose: "One Ring to Rule Them All"
In the original script, if you wanted to catch every move, you would have to set up separate alerts for Divergences, Absorptions, Crosses, etc. This modified script combines all 8 possible signals into a single "Master Trigger."
2. What triggers the Alert?
The alert will fire if ANY of the following 4 events happen on a candle:
Divergence (The Arrows):
Green Arrow: Price makes lower low, Pressure makes higher low (Bullish).
Red Arrow: Price makes higher high, Pressure makes lower high (Bearish).
Absorption (The Transparent Bars):
Bull Absorption: Huge volume + Price won't drop (Hidden Buying).
Bear Absorption: Huge volume + Price won't rise (Hidden Selling).
Zero Line Crosses (The Sentiment Flip):
Bull Cross: Pressure score flips from Negative to Positive.
Bear Cross: Pressure score flips from Positive to Negative.
Strong Zones (Turbo Mode):
Strong Bull: Pressure score breaks above +50.
Strong Bear: Pressure score breaks below -50.
3. How to Use It
Add the script to your chart.
Create an Alert.
Select "Order Flow Master" as the Condition.
Select "MASTER ALERT (All Signals)".
Now, you will get a notification for every single significant event this indicator detects, without needing multiple alert slots.
Range-Weighted Volatility (Comparable)I wrote an indicator to measure volatility inside a range. It’s extremely useful for choosing a trading pair for grid strategies, because it lets you quickly, easily, and fairly identify which asset is the volatility leader. It measures volatility “fairly” relative to the asset’s trading range, not just by absolute price changes.
For example: if an asset trades in a 50–100 range and over a week it moves many, many times between 52 and 98, then it’s highly volatile. But if another asset trades in a 50–1000 range and makes the same 52–98 moves, its volatility is actually low — because the “weight” of that movement relative to the full range is small. The indicator accounts for this “movement weight” relative to the range, then sums these weights into a single number. That number makes it easy to judge whether an asset is suitable for a grid strategy.
That’s exactly what grids need: not just high volatility, but high volatility within a narrow range.
Settings: the Window (bars) field defines how many bars are used to calculate volatility. On a 5-minute chart, one week is 2016 bars (2460/57). By default, the script calculates over 30 days on 5-minute charts. The script also allows you to set a second symbol for comparison, so you can see both results on the same chart.
Написал индикатор для определения волатильности в диапазоне, очень-очень полезно для выбора торговой пары на гриде, позволяет легко и быстро и честно определить лидера по волатильности, при этом определяет ее "честно", относительно торгового диапазона, а не просто изменения цены.
Например если актив торгуется в диапазоне 50-100 и за неделю много-много раз сходил 52-98, то это очень волатильный актив, и в то же время если актив торгуется в диапазоне 50-1000 и сходил так же 52-98, то это будет низко волатильный актив, т.е. учитывается "вес" движения относительно диапазона и данные "веса" суммируются в одну единую цифру по которой и можно оценивать насколько актив подходит под грид стратегию.
А ведь именно это для гридов и нужно, не просто высокая волатильность, а именно высокая волатильность в узком диапазоне.
Касательно настроек , в поле Windows (bars) задается количество баров по которым скрипт будет считать волатильность, на 5-ти минутки неделя это 2016 (24*60/5*7), стандартно скрипт считает за 30 дней на 5-ти минутки. + в самом скрипте можно указать вторую пару для сравнения чтоб на одном графике увидеть результат.
Breakout/Breakdown DetectorBreakout/Breakdown Detector - Quick Overview
What it does:
This indicator automatically identifies when price breaks through key support or resistance levels, signaling potential trading opportunities.
Key Features:
📈 Breakout Detection - Alerts when price breaks ABOVE resistance (bullish signal)
📉 Breakdown Detection - Alerts when price breaks BELOW support (bearish signal)
🔊 Volume Confirmation - Optionally requires high volume to confirm the break (filters false signals)
📊 Visual Signals - Shows green triangles (breakout) and red triangles (breakdown) on chart
🎨 Support/Resistance Lines - Automatically draws key levels based on recent price action
Settings You Can Adjust:
Lookback Period (default 20) - How many candles back to find support/resistance
Volume Multiplier (default 1.5x) - How much volume needed to confirm
Breakout Threshold (default 0.5%) - How far price must break through the level
How to Use:
Add to any chart (stocks, crypto, forex, etc.)
Green triangle below bar = BUY signal (breakout)
Red triangle above bar = SELL signal (breakdown)
Set alerts to get notified automatically
Perfect for: Swing traders, breakout traders, and anyone who wants to catch momentum moves early! 🚀
Impulse %Impulse % — Liquidation Cascade Detector (BTC · 1H)
Impulse % identifies sharp impulsive price moves and liquidation cascades by measuring how much a candle’s range deviates from its historical average in percent.
How it works
Calculates the candle range (in %) relative to price and compares it to the average over N periods.
When the range exceeds the upper band, an Impulse is detected.
Inside each 1H candle, the indicator checks lower timeframes (1m / 5m) to classify the impulse phases:
PANIC — the first minutes of a violent move (forced liquidations, stop hunts).
CAUTION (Cascade) — continuation and “cleanup” phase with elevated risk.
Determines whether the impulse is against the trend using EMA 50 / EMA 200 — the most dangerous scenario.
Highlights risk zones to protect positions and filter new entries.
What it’s for
Avoid entering during liquidation cascades.
Exit at break-even or partially take profit during risky phases.
Recommended Settings — BTC (1H)
Calculation
Calculation TF: (empty = current)
Average Mode: By N bars
N (bars): 100
Range Type: High–Low
Bands
Upper Band (% of average): 130
Lower Band: Auto (same %)
Cascade (First Minutes)
Enable Cascade Filter: ON
When to trigger safety: Only against trend
PANIC (minutes): 3
CAUTION (minutes after PANIC): 15
Trend (EMA)
Use EMA Trend: ON
Fast EMA: 50
Slow EMA: 200
Lower TF Detection
Lower TF: 1m (or 5m if you prefer smoother signals)
Visualization
Style: Columns
Show Bands: ON
Show Band Lines & Mean: ON
How to read it (BTC · 1H)
Purple (PANIC): first minutes of liquidation — do not enter.
Yellow (CAUTION): cascade phase — high risk, manage/exit.
Normal color: no active cascade — strategy allowed.
Best practice:
1m/5m → real-time cascade detection
1H → decision level
4H → market context
Double&Triple Pattern[TS_Indie]📌 Description – Double & Triple Pattern Indicator
The Double & Triple Pattern Indicator is developed to help traders systematically and clearly identify Double Top, Double Bottom, Triple Top, and Triple Bottom chart patterns.
⚙️ Core Logic & Working Mechanism
The Double & Triple Pattern Indicator is built on the concept of price swing formation, based on the logic of Trend Entry_0 , which focuses on structured market analysis and price action behavior.
The indicator detects three main swing points (Swing 1, Swing 2, and Swing 3). A Fibonacci Box is then created using Swing A and Swing B as reference points to define the swing detection zone.
When all three swings remain inside the defined Fibonacci Box, the structure is considered a valid Price Action setup.
The indicator then plots key lines on the chart:
➩ Break Line – used to confirm the signal (confirmation)
➩ Cancel Line – used to invalidate the price action if price moves against the conditions
➛ When price breaks the Break Line , the structure is confirmed and a Pending Order is placed at Swing B , with the Stop Loss set at Swing 1.
➛ If price breaks the Cancel Line first, the price action structure is immediately invalidated.
⚙️ Fibonacci Entry Zone & Change SL Settings
➩ When Fibo Entry Zone is set to 0, the Pending Order is placed directly at Swing B.
➩ When the value is greater than 0, the Pending Order is calculated using Fibonacci levels drawn from Swing B to the Stop Loss level.
➩ Change SL allows switching the Stop Loss reference between Swing 1 and Swing A.
⚙️ Min & Max Control for Swing Size : xATR
When enabling Control Size Swing : xATR , the indicator filters Swing B based on the defined Min and Max range.
This allows traders to selectively test larger or smaller swing-based price actions , depending on their trading strategy.
⭐ Pending Order Cancellation Conditions
A Pending Order will be canceled under the following conditions:
1.A new Price Action signal appears on either the Buy or Sell side.
2.When Time Session is enabled, the Pending Order is canceled once price exits the selected session.
🕹 Order Management Rule
When there is an active open position, the indicator restricts the creation of new Pending Orders to prevent overlapping positions.
💡 Double Pattern Example
💡 Triple Pattern Example
⚠️ Disclaimer
This indicator is designed for technical analysis purposes only and does not constitute investment advice.
Users should apply proper risk management and make decisions at their own discretion.
🥂 Community Sharing
If you find parameter settings that work well or produce strong statistical results, feel free to share them with the community so we can improve and develop this indicator together.
RS vs Indexes By Shashi MishraRS vs Indexes giving details about strength of the sripts against the TIDE which is indexes that you can follow , for example small cap index 100 / 250
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.
