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Absorption Range Ledger [JOAT]Absorption Range Ledger Introduction Absorption Range Ledger is an open-source range and participation overlay built to detect high-participation ranges, estimate internal bull-vs-bear ownership, track weighted equilibrium, and monitor whether the market is being absorbed, contained, reclaimed, or broken. It is designed for traders who want richer range context than a basic support/resistance box. The script identifies high-participation candles, merges overlapping activity into persistent range zones, tracks a weighted equilibrium line inside the zone, and then highlights whether that zone is acting as supportive absorption, resistant absorption, or a two-way transfer area. Optional TP/SL rails are created when weighted reclaims or range breaks occur on confirmed bars. Core Concepts 1. High Participation Detection The script compares current volume to a baseline moving average. When participation exceeds the threshold, the candle is eligible to build or extend an absorption range. 2. Range Merging New high-participation candles are merged into existing ranges when overlap conditions are satisfied. This creates broader institutional-style transfer zones rather than isolated candle markers. 3. Ownership Split Each active range tracks approximate bullish and bearish ownership internally. This is displayed visually using sub-boxes and summarized numerically in the dashboard. 4. Weighted Equilibrium A weighted equilibrium line is maintained inside the dominant active range. This level serves as a practical internal reference for reclaim and failure behavior. 5. Range Events The script distinguishes containment, weighted-line reclaims, and outright range breaks. These states are used for dashboard context and optional TP/SL scaffolding. Features High-participation range detection: Builds active ranges when volume exceeds the baseline threshold Range merging: Overlapping participation bars are combined into richer zones Bull/bear ownership split: Internal sub-boxes show approximate participation balance Weighted equilibrium line: A central reference inside the active range Dominant active range logic: Tracks the most relevant current range for context Range reclaim and break states: Distinguishes contained trade from directional escape Optional TP/SL ladder: Builds informational risk rails on confirmed reclaims and breaks Top-right dashboard: Shows state, active count, weighted level, balance, range width, and event condition How to Use This Indicator Step 1: Identify whether a dominant active range exists. Step 2: Check the ownership balance. Strong positive balance suggests bid-side absorption. Strong negative balance suggests offer-side absorption. Step 3: Watch how price behaves around the weighted equilibrium line. Reclaims and failures often provide better context than touching the raw box boundary alone. Step 4: Use confirmed breaks of the dominant range as state changes, not as guaranteed trend starts. Indicator Limitations Ownership balance is an internal estimate, not a true order-flow measurement Range merging depends on the chosen volume threshold and can be too broad or too narrow if poorly configured Old ranges expire by design and will not remain indefinitely on the chart The TP/SL ladder is informational and not an execution engine Originality Statement Absorption Range Ledger is original in the way it combines participation-based zone merging, internal ownership splitting, weighted equilibrium governance, and event-driven scaffolding into one open-source range tool. It is published as a contextual market-transfer indicator rather than a simple breakout box. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Participation, ownership, and absorption states are inferred from historical price and volume behavior and may not reflect future outcomes. Use independent analysis and risk management. -Made with passion by jackofalltrades
Pine Script® Indikator
von officialjackofalltrades
JOAT Pressure Composite [JOAT]JOAT Pressure Composite Introduction JOAT Pressure Composite is an open-source accumulation-distribution and participation oscillator built to measure whether buying or selling pressure is strengthening, weakening, rotating, or diverging from price. It is designed to expose internal sponsorship behind price movement rather than price movement alone. The script combines weighted close-location flow, relative-volume sponsorship, volume sigma, effort, efficiency, momentum bias, VWAP bias, and confirmed higher-timeframe context into one composite pressure model. The problem it solves is hidden participation. Price can rise on weak effort. Price can fall on poor sponsorship. Price can continue moving while internal pressure deteriorates. Pressure Composite tries to expose those changes earlier by measuring how much of the move is actually being sponsored by participation. The oscillator pane carries the composite, signal line, envelope, flow ribbon, and extreme states. At the same time, the indicator projects tailored information onto the main chart. Price divergence is labeled clearly. Expansion and absorption states are labeled directly on candles. Anchored VWAP and trend context are overlaid on price so the oscillator and chart remain connected. Core Concepts 1. Weighted Pressure Engine The base flow uses close-location value and weighted volume. closeLocationValue = (2.0 * close - low - high) / barRange weightedVolume = volume * sponsorshipFactor 2. Pressure Z-Score The raw pressure series is normalized with a Z-score. 3. Sigma and Effort Layers Volume sigma and effort help distinguish aggressive participation from ordinary rotation. 4. Efficiency Bias The script measures whether price is moving efficiently over the selected lookback. 5. VWAP Bias Distance from anchored VWAP is normalized in ATR terms. 6. Confirmed Divergence Logic Pivot-based divergence compares oscillator highs and lows to price highs and lows. 7. Expansion and Absorption Labels The chart prints Bid Expansion, Offer Expansion, Bull Absorption, and Bear Absorption labels directly on price. 8. Confirmed Higher-Timeframe Context The script pulls confirmed HTF composite states only. Features Composite pressure model: blends pressure, effort, sigma, efficiency, and VWAP bias Flow ribbon: shows whether pressure is widening or fading Envelope and extreme states: separates normal expansion from aggressive pressure Confirmed divergence detection: compares oscillator pivots to price pivots Clear divergence labeling: bullish and bearish pressure divergence is labeled directly on price Expansion / absorption labels: market states are marked on actual candles Anchored VWAP context: projected onto the chart for alignment Fast / slow trend context: price-side guides remain visible while using the oscillator Confirmed HTF states: non-repainting higher-timeframe pressure context No dashboard: information is pushed into the chart and oscillator instead of a table Input Parameters Composite Engine: Smoothing Type Flow Smoothing Normalization Length Relative Volume Baseline Relative Volume Boost Volume Sigma Length Effort Smoothing Efficiency Length Signal Length Envelope Length Envelope Multiplier Extreme Multiplier Pivot Length Divergence Scan ATR Length Qualification / Display: Use Trend Gate Trend Fast EMA Trend Slow EMA Use VWAP Gate Minimum Spread Show Histogram Show Signal Line Show Envelope Show Flow Ribbon Show Divergence Tint Price Bars Shade Momentum States Show Price Context Show Price Event Labels How to Use This Indicator Step 1: Read the composite vs signal relationship to judge widening or fading pressure. Step 2: Check whether the state is expansion or absorption. Step 3: Watch labeled divergences closely, especially after extension. Step 4: Use anchored VWAP and trend overlays to connect the oscillator back to price structure. Step 5: Use confirmed HTF context as a quality filter rather than a prediction tool. Indicator Limitations Divergences can persist before price responds Confirmed higher-timeframe context intentionally lags unfinished HTF candles Low-volume environments can flatten the composite even while price drifts Pressure quality does not guarantee immediate reversal or continuation Originality Statement This script is original in how it integrates weighted close-location flow, RVOL sponsorship, sigma, effort, efficiency, VWAP distance, confirmed HTF context, and direct price-chart state labeling into one coherent participation framework. The components are combined because they all address one question: how much real sponsorship exists behind current price movement. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Pressure readings and divergences do not guarantee reversal or continuation. Use the script as context and confirmation, not as a promise of outcome. Best Use Cases Measuring whether price movement is being sponsored by real participation Spotting divergence between price and internal pressure Reading expansion versus absorption conditions Combining participation context with VWAP and trend structure Interpretation Notes The strongest bullish pressure states usually include positive pressure, supportive spread, constructive effort, and favorable price context above value. The strongest bearish pressure states are the mirror image. Divergences are most useful when they appear after extension or at major contextual levels. Absorption labels should be treated as warnings that apparent directional continuation may be losing quality. Publication Notes This script is intended to be published with a clean chart where the oscillator, labeled divergence, and at least one price-context label are clearly visible. Because there is no dashboard, the publication image should make the chart-side annotations easy to read. Keep the chart clean so the viewer can immediately understand that the script links oscillator behavior back to price. -Made with passion by jackofalltrades\
Pine Script® Indikator
von officialjackofalltrades
Displacement Forge [JOAT]Displacement Forge Introduction Displacement Forge is an open-source order block detection engine built on Z-Score impulse analysis. It identifies statistically significant price displacements — moves that exceed a configurable standard deviation threshold relative to recent price change history — and marks the candle immediately preceding each displacement as an Order Block Zone. Order blocks represent the price ranges from which institutional order flow originates. Price regularly returns to these zones to fill remaining orders, and Displacement Forge identifies and tracks each one, monitors for zone reactions, and records cumulative rejection statistics. The problem order block analysis solves is entry precision. A trend bias tells you direction. An order block tells you at what price the institutions that created that trend loaded their positions. Returning to those prices to enter alongside institutional flow — rather than chasing moves already in progress — is the conceptual foundation Displacement Forge is built on. The Z-Score gate ensures only statistically significant displacements qualify, filtering out small impulses caused by normal market noise. Core Concepts 1. Z-Score Displacement Detection Rather than using fixed ATR multiples to define a "significant" move, Displacement Forge computes the Z-Score of each bar's price change relative to the rolling distribution of recent price changes. The Z-Score measures how many standard deviations the current move is from the recent mean: priceChg = close - close avgChg = ta.sma(priceChg, zscoreLen) stdChg = ta.stdev(priceChg, zscoreLen) zscore = stdChg > 0 ? (priceChg - avgChg) / stdChg : 0.0 A positive Z-Score above the threshold with a bullish candle close and a higher close than recent highs — filtered by an EMA and VWAP trend context — constitutes a bullish displacement impulse. A negative Z-Score below the negative threshold with a bearish close and lower-than-recent lows in the opposing trend context constitutes a bearish displacement impulse. 2. Order Block Zone Identification When a displacement impulse is detected, the indicator looks backward through the impulse lookback window for the last candle in the opposite direction — the candle just before the institutional move began. That candle's high and low define the order block zone. This captures the price range where institutional orders were being placed before the displacement candle consumed available liquidity: if bullImpulse for i = 1 to impulseLook if close < open // Last bearish candle before the impulse obLow := low obHigh := high break Each zone is drawn as a box on the chart using the pre-impulse candle's range. Bull order blocks are drawn with a bullish tint (price expected to react bullishly when revisited). Bear order blocks with a bearish tint. 3. EMA and VWAP Trend Filter Two independent trend filters gate displacement qualification. The EMA filter (200-period by default, configurable) requires bull displacements to occur above the EMA and bear displacements below it. The VWAP filter adds an intraday fair-value gate — bull displacements require price to be above the current VWAP, bear displacements require price to be below. Both filters can be independently enabled or disabled: bullImpulse = zscore > threshold and close > open and close > ta.highest(close, impulseLook) and (not useEma or close > ema200) and (not useVwap or close > ta.vwap) 4. Zone Reaction Detection and Rejection Counting Active order block zones are continuously monitored for price reactions. A bullish reaction occurs when the candle low touches or enters the bull zone range with a bullish close. A bearish reaction occurs when the high touches or enters the bear zone range with a bearish close. Each confirmed reaction increments the independent bull and bear rejection counters displayed in the dashboard: if ob.isBull and low <= ob.top and low >= ob.bottom and close > open bullReactionDetected := true totalBullRejections += 1 5. Zone Lifespan and Active Zone Management Each zone carries an age counter that increments bar by bar. Zones exceeding the maximum age (configurable) are automatically removed as inactive. The active zone count and total tested zone count are tracked and displayed in the dashboard, giving a running picture of how many zones are currently relevant versus how many have been tested and absorbed. Features Z-Score impulse gate: Displacement qualification based on standard deviations from the rolling price-change distribution, not arbitrary fixed thresholds Order block zone boxes: Pre-impulse candle ranges drawn as colored boxes on the chart for both bull and bear impulses EMA trend filter: Configurable EMA length gates displacement direction relative to long-term trend VWAP trend filter: Intraday VWAP provides a fair-value gate alongside the EMA for dual confirmation Zone reaction monitoring: Active zones continuously checked for price reactions with independent bull and bear rejection counters Zone age management: Configurable maximum zone age with automatic removal of expired zones Active and tested zone counts: Dashboard tracks how many zones are live versus how many have been tested Bull and bear rejection totals: Cumulative counts of all confirmed zone reactions by direction Displacement markers: Labeled arrows at each confirmed displacement bar (BULL DISP, BEAR DISP) with size and style differentiation Divergence detection: Z-Score divergence against price direction labeled (BULL DIV, BEAR DIV) and hidden divergence (H.BULL, H.BEAR) Institutional dashboard (top right): 13-row table with Z-Score, displacement state, OB reactions, active zone count, tested zone count, EMA and VWAP filter status Fully configurable: Z-Score length and threshold, impulse lookback, EMA length, VWAP toggle, zone max age, and zone visibility independently adjustable Alerts: Separate alertconditions for bullish and bearish displacement impulses Input Parameters Displacement Detection: Z-Score Length: Rolling window for mean and standard deviation calculation (default: 20) Z-Score Threshold: Standard deviation threshold for displacement qualification (default: 1.5) Impulse Lookback: Bars back to search for the pre-impulse order block candle (default: 5) Trend Filters: EMA Length: Trend EMA period (default: 200) Use EMA Filter toggle (default: enabled) Use VWAP Filter toggle (default: enabled) Zone Management: Max Zone Age (Bars): Maximum bar lifespan of active zones before automatic removal (default: 100) Show OB Zones toggle Display: Show Dashboard toggle Show Divergence Labels toggle Bullish and Bearish color inputs How to Use This Indicator Step 1: Identify the Current Z-Score and Displacement State The dashboard shows the live Z-Score value and displacement state (BULL IMPULSE, BEAR IMPULSE, or NEUTRAL). Use the Z-Score value as a real-time gauge of how statistically extreme the current price move is relative to recent history. Step 2: Locate Active Order Block Zones After any displacement, a colored box marks the pre-impulse candle range. These zones are the areas where institutional orders were accumulated before the move. The dashboard's Active Zones row shows how many live zones are currently on the chart. Step 3: Wait for Price to Return to a Zone When price retraces after a displacement and enters an active zone, watch for a reaction candle. A bullish close from within a bull zone or a bearish close from within a bear zone constitutes a zone reaction and increments the dashboard's rejection counter. Step 4: Apply EMA and VWAP Context The EMA filter status (ABOVE/BELOW) and VWAP filter status in the dashboard confirm whether the trend context supports the zone direction. An active bull zone with price above both the EMA and VWAP provides a higher-context long reaction than the same zone in a downtrend. Step 5: Observe Divergence Labels BULL DIV and BEAR DIV labels appear when the Z-Score diverges from price direction — Z-Score momentum and price momentum disagree. H.BULL and H.BEAR mark hidden divergence. These are secondary signals that may precede displacement reversals. Indicator Limitations The Z-Score is computed relative to the rolling price-change distribution of the configured lookback period. During regime changes or low-liquidity periods, the distribution can shift and cause the threshold to misfire Order block identification looks backward from the displacement bar. The pre-impulse candle selection is algorithmic — it finds the last opposite-direction candle within the lookback. In some impulse structures this may not match the manually identified order block Zone reaction detection requires the candle to touch the zone range in the same bar that a directional close occurs. Multi-bar zone entry sequences are not separately tracked The VWAP calculation resets at daily boundaries. On instruments that trade across midnight or on continuous futures contracts, the VWAP reset behavior may differ from expectations This indicator identifies order block zones and reactions. It does not generate trade entry signals, and zone reactions do not guarantee price continuation from the zone Originality Statement Displacement Forge is original in its application of Z-Score analysis to price change distribution as the gate for order block qualification, combined with a dual trend filter and automatic zone reaction monitoring with cumulative statistics. This indicator is published because: Using the rolling Z-Score of bar-by-bar price changes — rather than raw ATR multiples — to define what constitutes a statistically significant displacement provides an adaptive, distribution-aware threshold that adjusts to current volatility rather than using fixed values The pre-impulse candle lookback logic that identifies the order block as the last opposite-direction candle before the displacement provides a specific, repeatable rule for zone placement that eliminates the ambiguity of manual order block selection The dual trend filter combining a configurable EMA with VWAP — both independently togglable — provides layered directional context that single-MA systems do not offer Tracking cumulative bull and bear rejection counts alongside active and tested zone counts provides ongoing statistical feedback on how the order block zones are performing across the chart history Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Order block zones are identified using statistical and structural criteria but do not guarantee any particular price reaction when revisited. Z-Score thresholds are parameters that require adjustment to match specific instruments and timeframes. Past zone reactions do not guarantee future reactions. Always use proper risk management. The author is not responsible for any trading losses resulting from the use of this indicator. -Made with passion by jackofalltrades
Pine Script® Indikator
von officialjackofalltrades
2
Imbalance Zone Classifier [JOAT]Imbalance Zone Classifier Introduction The Imbalance Zone Classifier detects Fair Value Gaps (price imbalances where no two-sided auction occurred) and assigns each zone a 0–100 Strength Score based on four measurable factors: gap size relative to historical distribution, intrabar buy/sell volume composition, zone age, and mitigation status. Rather than drawing every FVG indiscriminately, this indicator filters by minimum score and renders only the zones most likely to attract institutional order flow on return visits. The core problem this solves: nearly every FVG tool draws every gap, producing charts saturated with dozens of overlapping boxes that cannot be prioritized. A 0.03% gap on declining volume is not equivalent to a 0.8% gap formed on explosive institutional buying. The Strength Score quantifies that difference, letting the trader focus on the handful of zones that genuinely matter. Core Concepts 1. Fair Value Gap Detection An FVG (also known as an inefficiency or price imbalance) occurs when three consecutive candles leave a price gap: // Bullish FVG: candle high is below candle low bool bull_fvg = high < low and close > open // Bearish FVG: candle low is above candle high bool bear_fvg = low > high and close < open Detection is confirmed on bar close — the gap is only registered after candle closes — ensuring no repainting. The zone boundaries are the candle high and candle low for a bullish FVG (and their inverses for bearish). 2. The 0–100 Strength Score Each FVG receives a composite score derived from four sub-scores: int vol_score = int(math.min(bull_pct / 0.7 * 50, 50)) // 0-50 pts int size_score = int(math.min(gap_rank * 0.35, 35)) // 0-35 pts int composite_score = vol_score + size_score // base // Age decay applied post-formation: score -= 1 per N bars Size Score (0–35 pts): The gap size as a percentage of price is ranked against the last 1000 bars using a percentile rank. A gap in the top 10% of historical size scores near maximum. A tiny gap scores near zero. Volume Score (0–50 pts): Lower-timeframe bars within the formation candle's time window are decomposed into buy and sell volume. A bullish FVG with 90% buy-side composition scores 50; one with 50% scores 25. Age Decay: Zones accumulate bar age. The score decays over time, reflecting that older unmitigated zones become less relevant. Zones below the minimum score threshold fade and are removed. 3. Lower-Timeframe Volume Decomposition Volume intelligence comes from requesting sub-bar data at the user-specified lower timeframe: array ltf_bull_vol = request.security_lower_tf("", i_ltf, (close > open ? volume : 0.0)) array ltf_bear_vol = request.security_lower_tf("", i_ltf, (close < open ? volume : 0.0)) float sum_bull_ltf = ltf_bull_vol.sum() float sum_bear_ltf = ltf_bear_vol.sum() float bull_pct = sum_bull_ltf / (sum_bull_ltf + sum_bear_ltf) This decomposes the FVG formation candle's volume into directional sub-bar composition — giving a precise measure of whether the gap was formed by institutional buying pressure or merely a thin-volume vacuum. 4. Mitigation Logic Zones are considered mitigated when price returns to the zone midpoint (or high/low depending on user setting). Mitigated zones do not disappear immediately — they change color and fade, providing a historical record. They are removed from the active list after a configurable bar count, and a counter increments in the dashboard. 5. Volume Bar Visualization Inside Zones Each zone renders a proportional buy/sell volume bar inside the zone body — a thin inner box whose right edge shows the bull/bear volume ratio. A zone with 80% buy volume renders its inner bar nearly full green. This gives an immediate visual indication of the composition without requiring the dashboard. Features Fair Value Gap Detection: Bullish and bearish FVGs confirmed on bar close, non-repainting 0–100 Strength Score: Composite score from gap size percentile rank and lower-timeframe volume composition Minimum Score Filter: Only zones above the threshold are rendered — keeps the chart clean LTF Volume Decomposition: True intrabar buy/sell ratio from lower-timeframe data Volume Bar Inside Zone: Proportional buy/sell bar rendered within each zone body Mitigation Tracking: Zones transition to faded color on mitigation; active vs mitigated count in dashboard Zone Extension: Unmitigated zones extend rightward automatically until price returns Age Decay: Score degrades over time, naturally purging stale zones below the threshold 9-Row Dashboard: Active bullish zones, active bearish zones, total mitigated, highest current score, session FVG count Alerts: Bullish FVG formed, bearish FVG formed, bullish FVG mitigated, bearish FVG mitigated Input Parameters FVG Detection: Detect Bullish FVGs: Toggle bullish imbalance detection (default: on) Detect Bearish FVGs: Toggle bearish imbalance detection (default: on) Minimum Strength Score (0–100): Filter threshold — only zones above this are shown (default: 25). Higher = fewer, stronger zones. Mitigation Source: close = mitigated when close crosses zone midpoint. high/low = wick breach removes the zone (default: close) Max Active Zones: Maximum simultaneous rendered zones (default: 12, range: 3–30) Volume Intelligence: LTF Resolution: Lower timeframe for intrabar volume decomposition (default: 1m) Visualization: Bullish / Bearish / Mitigated colors: Fully customizable Show Volume Bars Inside Zones: Display proportional buy/sell bar within each zone (default: on) Extend Unmitigated Zones: Extend zone boxes rightward until mitigation (default: on) Dashboard: Position: Top Right, Top Left, Bottom Right, Bottom Left (default: Top Right) How to Use This Indicator Step 1: Set the Minimum Score Start with the default score of 25. This filters out the weakest gaps while keeping meaningful zones. If the chart still shows too many zones, raise to 40–50. For maximum selectivity on higher timeframes, 60+ selects only the most institutionally significant gaps. Step 2: Read the Volume Bar Inside Each Zone A bullish FVG with a mostly green inner bar (80%+ buy volume) was formed by genuine institutional buying. One with a near-50% bar was formed in a thin, directionless push — much less likely to hold on retest. This distinction cannot be made from price action alone. Step 3: Trade the Retest Price frequently returns to fill FVG zones, particularly the highest-score zones. The midpoint of the zone (zone top + zone bottom / 2) is the primary retest level. Entry on a return to a high-score bullish FVG, with a stop below the zone low, is a clean risk-defined setup. Step 4: Monitor Mitigation Once a zone changes to the mitigated color, it no longer has predictive value as a support/resistance level — it has been filled. Remove it from your analysis. The dashboard count of mitigated zones tells you how efficiently the market is clearing imbalances. Originality Statement This indicator is original in its composite strength scoring system applied to Fair Value Gaps using lower-timeframe volume decomposition. Its publication is justified because: Gap size percentile rank against 1000-bar history normalizes the score across different instruments and timeframes — a 0.5% gap on EURUSD scores the same as a 0.5% gap on BTCUSD regardless of absolute price level Lower-timeframe volume decomposition provides true intrabar buy/sell composition of each FVG formation candle — a dimension of analysis unavailable from chart-timeframe OHLCV data alone The visual volume bar inside each zone encodes directional conviction directly within the zone's screen space, creating a two-dimensional information display (price level + volume direction) without additional panels Age decay combined with minimum score filtering creates a self-organizing, self-cleaning zone map that requires no manual zone management from the trader Limitations LTF volume requests add computation overhead. On 1-minute chart timeframes, requesting 1-minute LTF data is a no-op; the function falls back to chart-timeframe volume for those bars. The strength score is a relative ranking, not an absolute predictive probability. A score of 80 does not mean an 80% chance of holding — it means this zone is stronger than most, not that it is guaranteed to act as support or resistance. Mitigation is detected on bar close (or high/low depending on setting). Intrabar wicks that return to the zone but close outside it will not trigger mitigation in the default setting. The maximum zone count is a performance and visual constraint. On timeframes where FVGs form frequently, older lower-score zones are removed to stay within the limit. Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any instrument. All trading involves risk of loss. Fair Value Gap zones do not guarantee price reversal or support. Always use proper risk management. -Made with passion by jackofalltrades
Pine Script® Indikator
von officialjackofalltrades
1
Liquidity Contour Engine [JOAT] Liquidity Contour Engine Introduction Liquidity Contour Engine is an overlay indicator that identifies two distinct institutional price phenomena: liquidity sweeps at swing highs and lows, and order blocks formed before impulsive structural moves. Liquidity sweep zones mark levels where price reached beyond a prior swing, triggering stop orders, then reversed — the classic footprint of a sweep-and-reversal sequence. Order block zones mark the last opposing candle before a significant directional impulse, representing the area where a large position was initiated. The underlying premise is that institutions build and exit positions through order flow that leaves identifiable marks on the chart. A liquidity sweep is one such mark: price extending beyond a well-established swing level, clearing stops, then reversing. This behavior is not random — it reflects deliberate order accumulation at levels where retail stops cluster. Similarly, order blocks at the origin of impulsive moves may act as re-entry areas when price later returns to them. Core Concepts 1. Confirmed Swing Pivot Detection Swings are identified using ta.pivothigh and ta.pivotlow with a configurable lookback. All pivot detections are confirmed — offset by the lookback bars — meaning no repainting occurs. Only when sufficient bars have closed on both sides of a potential pivot is it registered. 2. Liquidity Sweep Detection A bullish sweep is confirmed when: price wicks below the most recent swing low by at least a configurable ATR multiple, and the bar closes back above that swing low. This captures the wick-past-and-close-back pattern that characterizes institutional accumulation at liquidity levels. A bearish sweep is the mirror condition at swing highs. Upon detection, a zone is created at the swept level, rendered as a dual-width line (thin solid + thick transparent shadow). Zones remain active until price sustains a close beyond the swept level by 0.5 ATR, at which point they convert to dotted lines (mitigated state). 3. Order Block Detection An order block is identified as the prior N candle(s) before a structural impulse. A bullish impulse is defined as a bar that closes above the most recent swing high. The order block is the last candle body before that impulse, rendered as a filled box from body open to the wick high. Mitigation occurs when price closes beyond the 50% level of the order block body, fading the box to indicate the zone has been traded through. 4. Zone Lifecycle Management The indicator uses arrays to track active zones and enforces a maximum count. When the maximum is exceeded, the oldest zone is removed from the chart. This prevents chart clutter while keeping the most recent and relevant zones visible. Features Liquidity Sweep Zones: Dual-width line rendering at swept swing levels, self-managing lifecycle Order Block Boxes: Filled zones at order block origin, with mitigation fading Swing Level Dotted Lines: Current swing high and low extensions as dotted reference lines 9-Row Dashboard: Sweep state, active zone counts, order block counts, last swing levels Configurable ATR Threshold: Adjusts how far price must reach beyond a swing to qualify as a sweep Max Zone Limit: Prevents chart clutter with configurable maximum active zone count Input Parameters Swing Lookback: Bars required each side for pivot confirmation (default: 8) Sweep ATR Threshold: Minimum sweep distance in ATR units (default: 0.3) Max Active Zones: Maximum concurrently displayed liquidity zones (default: 8) ATR Period: Period for ATR calculation (default: 14) Show Order Blocks: Toggle order block rendering OB Lookback: How many bars back to identify the order block candle (default: 3) How to Use This Indicator Sweep-and-Reverse Setups When a bullish sweep fires (price wicked below a swing low and closed back above), the zone represents the level where stops were taken. If price subsequently builds structure above that zone and delta pressure is positive, the setup is a potential long entry with the swept level as reference for the stop. Order Block Re-Tests When price returns to a bullish order block zone (shown in teal), it is revisiting the area where an institutional position was likely initiated. If the zone has not been mitigated (box remains filled), a reaction from that zone is plausible. A mitigated order block (faded) is a less reliable reference. Zone Confluence When a liquidity sweep zone and an order block coincide at the same price level, the confluence represents a stronger structural reference than either zone alone. Limitations Swing pivot confirmation introduces a bar lag equal to the lookback period. Sweeps and order blocks are identified after the fact, not in the moment they form Not every liquidity sweep produces a reversal. Price can continue through a swept level without reversing Order block identification is mechanical and cannot account for all institutional order placement strategies On higher timeframes, zones cover wider price ranges and may require adjustment of the ATR threshold Originality Statement The unified framework for tracking liquidity sweeps and order blocks within a single indicator with a shared zone lifecycle management system is the original design contribution. Zone mitigation logic that converts active zones to passive reference lines (rather than deleting them) preserves structural context while visually indicating that a zone's primary relevance has passed. The dual-width shadow line rendering for sweep zones provides depth that distinguishes them clearly from standard horizontal lines. Disclaimer This indicator is for educational and informational purposes only. Liquidity sweep detection describes a pattern in historical price data. Past occurrences of this pattern do not guarantee future reactions. Order blocks are hypothetical areas of interest, not confirmed institutional levels. Always use proper risk management. -Made with passion by officialjackofalltrades
Pine Script® Indikator
von officialjackofalltrades
Liquidity Zone Harvester [JOAT]Liquidity Zone Harvester Introduction Institutional order flow leaves footprints in market structure. When a large buyer or seller places a significant order, the execution of that order creates an imbalance between supply and demand at a specific price level — and markets frequently return to these levels to test whether the original interest remains. These price areas are commonly referred to as order blocks or liquidity zones, and they form one of the core concepts in institutional and Smart Money trading methodology. The Liquidity Zone Harvester is an automated order block detection and management system that identifies these zones using statistically validated momentum signals rather than arbitrary manual placement. Instead of drawing boxes wherever a trader's eye thinks supply or demand may exist, this indicator uses Z-score cumulative impulse detection to identify when directional momentum has reached statistically significant levels — and only then marks the most recent opposing-close candle as the source order block. Volume quality gates ensure that only high-participation impulses create zones, filtering out low-conviction moves that are less likely to represent genuine institutional activity. What sets this indicator apart from standard order block tools is what happens after zone creation. Every active zone is tracked through a dual-mechanism aging system. The Bayesian exponential decay model progressively reduces zone visual intensity over time with a configurable half-life, providing a continuous probability signal about zone freshness. Simultaneously, a Kaplan-Meier survival analysis engine — borrowed from medical statistics — estimates the probability that a given zone will survive future price tests, based on the historical survival rates of all previously observed zones in the training window. Each zone displays both its current age and its estimated survival probability directly on the chart, turning static boxes into dynamically updated probability estimates. Core Concepts 1. Z-Score Cumulative Impulse Detection Zone creation is triggered only when directional momentum reaches a statistically defined threshold. The system accumulates a running streak of directional closes — when consecutive bars close higher than their open, the bull accumulator grows; when consecutive bars close lower, the bear accumulator grows. The streak resets when direction reverses. This cumulative streak is then normalized against its own rolling mean and standard deviation, producing a Z-score that measures how unusual the current momentum streak is relative to recent history. cumBull := close > open ? nz(cumBull ) + (close - open) : 0 cumBear := close < open ? nz(cumBear ) + (open - close) : 0 zBull = (cumBull - ta.sma(cumBull, zLen)) / ta.stdev(cumBull, zLen) zBear = (cumBear - ta.sma(cumBear, zLen)) / ta.stdev(cumBear, zLen) bullEvent = ta.crossover(zBull, zThresh) and barstate.isconfirmed and volOK bearEvent = ta.crossover(zBear, zThresh) and barstate.isconfirmed and volOK When a bullEvent fires (bull Z-score crosses the threshold with volume confirmation), the system looks backward to find the most recent down-close candle — the last bar where sellers were dominant before the impulse began. This becomes the demand zone. Similarly, a bearEvent marks the most recent up-close candle as the supply zone. 2. Volume Quality Gate Not all Z-score impulses are created equal. An impulse that occurs on abnormally low volume represents weak conviction — possibly a thin-market price drift rather than genuine institutional momentum. The volume gate applies RSI to the volume series to normalize it against its own history. Only when volume RSI exceeds the configurable threshold is the volOK condition true, enabling zone creation. volRsi = ta.rsi(volume, 14) volOK = volRsi > volThresh This filter meaningfully reduces the number of zones created during low-participation conditions such as pre-market sessions, lunch hours, or holiday-period trading — precisely the times when order block levels are least likely to represent significant institutional interest. 3. Order Block Zone Construction When a signal event is confirmed, the most recent opposing candle is identified using ta.valuewhen(). For a bullEvent, the system finds the most recent bar where close was less than open (a down candle) — its high and low define the demand zone boundaries. For a bearEvent, it finds the most recent up candle — its high and low define the supply zone boundaries. A box object is created spanning from that historical bar to the current bar, with height defined by the candle's actual high-low range. lastDnHigh = ta.valuewhen(close < open, high, 0) lastDnLow = ta.valuewhen(close < open, low, 0) lastDnBar = ta.valuewhen(close < open, bar_index, 0) if bullEvent newBox = box.new(lastDnBar, lastDnHigh, bar_index, lastDnLow, ...) bullBoxes.push(newBox) 4. Overlap Prevention (f_no_overlap) To avoid cluttering the chart with redundant zones that occupy the same price territory, an overlap check function evaluates whether a proposed new zone overlaps with any existing zone of the same type. The function iterates over all existing bull or bear boxes and compares the new zone's top and bottom against each existing box's top and bottom. A guard condition (nBull > 0) prevents the iteration from running on an empty array, which would cause an index -1 crash. f_no_overlap(newTop, newBot, boxes) => noOverlap = true if boxes.size() > 0 for i = 0 to boxes.size() - 1 b = boxes.get(i) if newTop >= box.get_bottom(b) and newBot <= box.get_top(b) noOverlap := false noOverlap 5. Bayesian Exponential Decay Each zone's visual transparency is driven by an exponential decay function that represents the diminishing probability of zone relevance over time. The half-life parameter (default: 75 bars) defines how quickly a zone fades. At age 0, the zone is fully opaque. At age 75 bars, the zone is at 50% opacity. At age 150 bars, 25% opacity. This continuous decay — rather than a binary active/expired switch — provides an analog probability signal directly encoded in the zone's visual intensity. decayFactor = math.exp(-0.693 * age / halfLife) zoneAlpha = math.round(decayFactor * 200) box.set_bgcolor(b, color.new(zoneColor, 255 - zoneAlpha)) 6. Kaplan-Meier Survival Analysis The Kaplan-Meier estimator is a nonparametric statistical method originally developed to measure survival probabilities in clinical trial data. In this indicator, "survival" is defined as a liquidity zone remaining unmitigated (not breached by a closing price on two separate occasions). Each time a zone is mitigated, it is recorded as a "death event" at its current age. Zones that expire by age limit without mitigation are recorded as "censored events" — incomplete observations. The KM formula multiplies survival probabilities across all observed events up to a given age. // For each completed event (death at age t_i with n_i at-risk zones): S_t := S_t * (1.0 - d_i / n_i) // Product over all event times <= query age For each active zone, the indicator queries the KM estimate at the zone's current age and displays the result as a percentage label. A zone at age 40 showing "Age 40 | 72%" means that historically, 72% of zones survived to at least 40 bars without being mitigated — giving traders a quantitative assessment of how likely the zone is to hold on the next test. Features Z-Score Cumulative Impulse: Statistical momentum threshold using normalized cumulative directional streaks to gate zone creation. Volume Quality Gate: Volume RSI filter ensures only high-participation impulses create zones. Precise Order Block Identification: Most recent opposing candle (last down-close for bull event, last up-close for bear event) defines zone boundaries. Overlap Prevention: f_no_overlap function checks all existing zones before creating a new one, preventing chart clutter from redundant levels. Bayesian Exponential Decay: Zone opacity decays over time with configurable half-life, encoding freshness as a visual probability signal. Kaplan-Meier Survival Analysis: Medical-statistics survival estimator applied to zone longevity, displayed as a percentage probability label on each active zone. Dynamic Zone Extension: Box right edge extends to the current bar on every update, keeping zones visually connected to the present. Mitigation Tracking: Zones that are closed through twice are flagged as mitigated and removed, with the event recorded for KM analysis. Seven-Row Dashboard: Active demand count, active supply count, bull Z, bear Z, volume RSI, KM training size, and signal status. Two Alert Conditions: Zone created alert and zone rejection (price tests and bounces back) alert. Input Parameters Z-Score Settings: Z Lookback: Rolling window for Z-score normalization (default: 50) Z Threshold: Sigma level required to trigger an impulse event (default: 2.0) Volume Gate Settings: Volume RSI Period: RSI lookback for volume normalization (default: 14) Volume RSI Threshold: Minimum volume RSI for zone creation eligibility (default: 55) Zone Management Settings: Max Zone Age: Maximum bars a zone remains active before forced removal (default: 300) Mitigation Count: Number of closes through a zone required for mitigation (default: 2) Max Active Zones Per Side: Maximum simultaneous demand or supply zones displayed (default: 5) Decay Settings: Decay Half-Life: Number of bars at which zone opacity reaches 50% of initial value (default: 75) KM Settings: KM Training Window: Bar lookback for Kaplan-Meier training data collection (default: 500) Show Survival Labels: Toggle KM probability labels on active zones (default: true) Display Settings: Show Demand Zones: Toggle demand (bull) zone boxes (default: true) Show Supply Zones: Toggle supply (bear) zone boxes (default: true) Show Dashboard: Toggle the seven-row information table (default: true) How to Use This Indicator Step 1: Understand Zone Creation Conditions Zones are not created on every bar — they are created only when a statistically significant directional impulse (Z-score above threshold) occurs on above-average volume. This selectivity is intentional. In any given trading session, you will likely see only a few zone creation events, each backed by a genuine momentum surge that suggests institutional participation. When you see a new zone appear, note the Z-score values in the dashboard and the volume RSI reading — higher values on both indicate a stronger impulse and more confident zone placement. Step 2: Prioritize Fresh, High-Survival Zones Not all zones on the chart are equally relevant. A fresh zone (low age, full opacity) at a KM survival rate of 80% is a far stronger candidate for price reaction than an old zone (high age, near-transparent) at 30% survival probability. Use both the visual opacity and the KM label together: as a zone ages and fades, reduce your expectation that it will provide meaningful support or resistance. When price approaches a zone that is both visually fresh and shows high KM survival probability, the statistical expectation of reaction is at its highest. Step 3: Watch for Zone Rejection Alerts The zone rejection alert fires when price tests a zone (enters the box boundary) and then closes back away from it without mitigating it. This is the core trade setup: price returning to the institutional order block level, briefly penetrating it, and then reversing. The rejection alert provides a timely notification for potential entries in the direction of the original impulse that created the zone, with the zone's near boundary serving as the natural stop-loss reference. Step 4: Monitor KM Training Size for Statistical Validity The dashboard displays the KM training sample size — the number of completed zone events (both mitigated and aged-out) available for the survival analysis. With fewer than 10 training events, the KM estimate has high variance and should be treated as rough guidance. With 30 or more training events, the estimate becomes statistically stable. On instruments or timeframes where the indicator has run for extended periods, the KM estimates become increasingly reliable as the training dataset grows. Indicator Limitations The Z-score cumulative impulse and volume gate require sufficient chart history for the rolling normalization periods to be seeded. In the first Z-lookback bars of a new chart, zone creation signals may be less reliable as the mean and standard deviation are not yet fully established. Kaplan-Meier survival estimates are only as reliable as the training dataset. On instruments or timeframes that have not accumulated many completed zone events, the survival probabilities should be treated as rough estimates rather than statistically precise values. The mitigation definition (two closes through the zone) is a configurable approximation. In real order block theory, mitigation can be defined in several ways; this indicator's specific definition may not match every trader's conceptual framework. Zones are based on the most recent opposing candle at the time of the impulse event. In fast markets where multiple large candles cluster closely together, the marked candle may not represent the most significant institutional order location. This indicator requires volume data. On instruments where volume is unavailable or unreliable (some synthetic indices, certain forex pairs), the volume gate will not function as intended and should be disabled or its threshold lowered significantly. The exponential decay model assumes a constant half-life across all market conditions. In reality, zone relevance can be regime-dependent — a zone formed during a trending market may remain relevant longer than one formed during a range, or vice versa. Maximum active zones per side is a hard limit. If the limit is reached, new valid zone creation events will be rejected until an existing zone is mitigated or aged out. Originality Statement The Liquidity Zone Harvester is a genuinely original indicator that applies statistical and mathematical frameworks from outside the trading domain to a problem common in technical analysis. The Z-score cumulative impulse detection — using consecutive close-open accumulation normalized against rolling sma/stdev — as the primary trigger for order block marking is an original signal architecture. Most order block indicators use visual pattern matching (e.g., a large candle followed by a gap) rather than statistical significance thresholds. Applying the Kaplan-Meier survival estimator — a nonparametric method from biostatistics — to estimate the probability that a liquidity zone will survive future price tests is a novel application of medical statistics to market analysis. This provides a mathematically grounded probability estimate that no standard order block indicator offers. The Bayesian exponential decay applied to zone visual transparency — using a configurable half-life to continuously encode zone freshness as opacity — is an original visual design that treats zone relevance as a continuously diminishing probability rather than a binary active/inactive state. The overlap prevention function that iterates over all existing zone arrays before creating a new zone — with the index-crash guard for empty arrays — is a specific engineering solution to a concrete problem in box-based indicator design. The volume RSI quality gate, applied specifically to filter Z-score impulse events rather than as a standalone signal, is an original confluence filter design that specifically addresses the problem of thin-market false signals in order block detection. Disclaimer The Liquidity Zone Harvester is provided for educational and informational purposes only. It is a technical analysis tool and does not constitute financial advice. Liquidity zones and order blocks are analytical constructs; they do not guarantee price reactions. Past zone behavior as encoded in Kaplan-Meier estimates does not predict future zone performance. All trading involves risk of loss. Users are solely responsible for their own trading decisions. Please consider your individual risk tolerance and consult a licensed financial professional before engaging in any trading activity. -Made with passion by officialjackofalltrades
Pine Script® Indikator
von officialjackofalltrades
Syndicate Confluence [JOAT]Syndicate Confluence Introduction Syndicate Confluence is an open-source overlay indicator that unifies three independent analytical engines into a single spatially organized visual system. Engine 1 is an adaptive Kalman filter with a Supertrend ratchet trail — it classifies the macro directional regime and generates a triple-glow neon trail on the chart. Engine 2 is an institutional order block zone mapper — it identifies swing-pivot order blocks, classifies them by trading session, and renders them as persistent box-based zones with session-colored borders and labeled displacement ratios. Engine 3 is an HMA pressure trail paired with a custom volume-weighted MFI — it classifies each bar into bull pressure, bear pressure, or neutral states. The three-layer visual architecture ties all three engines together: an outer ATR cloud communicates the macro volatility context of the Kalman filter; a corridor fill between the Kalman Supertrend line and the HMA trail communicates whether both engines are aligned in the same direction; and a core gradient fill between the HMA trail and the candle mid-body communicates the intensity of the current pressure state. When all three layers are saturated in the same color, the confluence is at its strongest. When they are fragmented, the market is transitioning. The highest-confidence signal — the starred HC Long or HC Short label — fires only when a trail flip, Kalman direction, and order block proximity all coincide simultaneously. This triple-engine intersection is the indicator's primary setup, and the remaining visual layers exist to help traders evaluate whether conditions are building toward or away from that state. Core Concepts 1. Adaptive Kalman Regime Engine The Kalman filter maintains a running estimate and error variance. Each bar, the gain is computed as err / (err + noise), where noise = alpha * period. The estimate is updated toward close proportional to the gain, and the error variance self-adjusts — expanding when prediction is poor (high responsiveness), contracting when the filter tracks well (high smoothness). A Supertrend ratchet is applied to the Kalman value: ATR-scaled upper and lower bands drift with a direction-persistence rule — the upper band can only fall, the lower band can only rise. Direction flips when the Kalman value closes through the active band. Applying the ratchet to a Kalman-smoothed price removes the micro-fluctuations that cause excessive flips in price-based systems. 2. Session-Colored Order Block Zones When a swing pivot low is confirmed, the indicator searches back for the last bearish candle before the pivot. If the subsequent displacement exceeds ATR * dispMult, that candle becomes a bull order block. The zone is drawn at the candle's midpoint with ATR-scaled height. Zone border color is determined by the birth session: London = blue (#60a5fa), NY = pink (#f472b6), Asia = green (#34d399). The label shows type, session, displacement ratio (e.g., "▲ BULL LON 1.8x 5030.41"), and updates its x-position every bar to track the right edge of the chart. Border thickness scales with displacement ratio — zones from 2x+ displacement moves get thicker borders. 3. HMA Pressure Trail and Volume-Weighted MFI An HMA ratchet trail determines directional commitment. The custom volume-weighted MFI sums volume * hlc3 on rising bars (positive flow) and volume * hlc3 on falling bars (negative flow), normalizes with the RSI formula, and smooths with an HMA. Bull pressure is active when the trail is bullish AND the smoothed MFI exceeds the bull threshold. Bear pressure when trail is bearish AND MFI below the bear threshold. The pressure strength percentage tracks the rolling 50-bar proportion of bars spent in an active pressure state. 4. Three-Layer Visual Architecture Outer ATR Cloud: k_val ± cloudMult * ATR filled with directional color at near-full transparency — communicates macro volatility context and Kalman regime at a glance Corridor Fill: The zone between the Kalman Supertrend line and the HMA trail — fills cyan when both agree bullish, rose when both agree bearish, neutral gray when diverging. When the corridor narrows and both trails converge in the same direction, confluence is building Core Pressure Gradient: Between the HMA trail and the candle mid-body — transparent at the HMA, saturated at the body, colored by pressure state. Deep color indicates active, volume-backed directional pressure 5. Signal Hierarchy ★ HC Long / ★ HC Short: Trail flip + Kalman direction + OB proximity — the highest-confidence setup. Starred label with colored background Trail flip arrows: Triangle up/down when trail flips in Kalman direction with MFI above/below 50 — standard entry signal MFI cross-50 triangles: Small triangles on the Kalman trail when MFI crosses the 50 level in the trail direction — momentum regime shift marker TP labels: Fire when MFI reaches overbought or oversold extremes in the trail direction K▲ / K▼ labels: Mark the exact bar where the Kalman Supertrend direction flips Squeeze diamond / circle: Diamond on squeeze start, circle on squeeze release Volume impulse labels: "1.8x vol" label on high-volume directional bars above the configured multiple Proximity diamonds: Fire on the first bar where price enters the OB proximity buffer Features Adaptive Kalman Filter: Self-calibrating gain updates noise estimate each bar — faster during impulses, smoother during consolidation Supertrend Ratchet on Kalman: Direction-persistent bands applied to the filtered price — stable, low-whipsaw regime signal Triple-Layer Kalman Glow: Widths 9/5/2 with decreasing transparency create a neon halo effect on the Supertrend trail Outer ATR Volatility Cloud: Wide envelope around the Kalman value, gradient-filled by regime direction Corridor Fill (Kalman ST ↔ HMA Trail): The alignment region between both trails — fills directionally when confluent, neutral when diverging Core Pressure Gradient Fill: HMA-to-mid-body gradient colored by active pressure state Session-Colored OB Zone Borders: London blue / NY pink / Asia green borders encode session context directly in the zone visual OB Zone Labels: Type, session, displacement ratio, and price level — updated live at right chart edge ★ HC Long / HC Short Labels: Triple-confluence signal fired when trail flip, Kalman direction, and OB proximity align Trail Flip Arrows: Triangle up/down entry signals when trail flips in Kalman direction with MFI midline confirmation MFI Cross-50 Markers: Small triangles on the trail at momentum regime shifts TP Overbought/Oversold Labels: Fire at MFI extremes in trail direction K▲/K▼ Kalman Flip Labels: Pinpoint the exact bar of each Kalman regime change Squeeze Detection: Diamond on Kalman band compression start, circle on release K-Velocity Dots: Brightness-scaled dots on the trail communicating momentum acceleration Volume Impulse Labels: Ratio labels on high-volume directional bars Proximity Diamonds: Alert when price first enters the OB proximity buffer Regime Transition Circles: Fire at every Kalman regime change on the trail line Gradient Bar Coloring: Saturates with MFI intensity when Kalman and trail agree, fades to neutral otherwise 13-Row Dashboard: K-Regime, Trail, Pressure state, Zone proximity, Confluence, MFI, P-Strength %, Squeeze state, Band Width, Trend Bars, K-Velocity %, ATR 9 Alertconditions: Long/short signals, HC signals, TP signals, squeeze release, Kalman flips Input Parameters Regime Engine: Kalman Alpha: Base noise smoothing — lower = smoother, more lag (default 0.02) Kalman Beta: Error variance recovery rate (default 0.10) Kalman Period: Gain magnitude scaler (default 50) ST Factor: ATR multiplier for Supertrend bands on Kalman (default 1.5) ST ATR Length: ATR lookback for band calculation (default 10) Cloud ATR Width: Outer cloud multiplier (default 2.5) Squeeze Threshold %: Band width below this % of SMA triggers squeeze (default 80%) Zone Engine: Swing Length: Pivot confirmation lookback (default 5) OB Lookback: Bars searched for qualifying order block candle (default 20) Displacement ATR Mult: Minimum move to validate an OB (default 0.8) Zone ATR Width: Zone height as ATR fraction (default 0.75) Max Active OBs / Side: Oldest zones trimmed beyond this limit (default 8) Proximity Buffer (ATR): Approach detection radius (default 1.5) Momentum Engine: MFI Length: Volume-weighted money flow lookback (default 14) MFI Smooth: HMA smoothing on raw MFI (default 5) Trail HMA Length: HMA period for pressure trail (default 14) Trail ATR Mult: Trail band width (default 1.5) MFI Bull/Bear Thresholds: Pressure activation levels (default 58/42) Signals: TP Overbought / Oversold: MFI extremes for TP labels (default 78/22) Impulse Vol Multiplier: Volume multiple for impulse labels (default 1.5) How to Use This Indicator HC Signal Setup: The ★ HC Long / HC Short label is the primary setup. It fires when the trail flips in the Kalman direction while price is within proximity of an active order block. Enter on the labeled bar. Trail your stop at the HMA trail line. Look for the TP label or pressure state deactivation as an exit reference. Corridor Fill as Trend Quality Gauge: When the corridor between the Kalman trail and HMA trail is narrow and saturated with color, both trend systems are locked in the same direction — this is the highest-confidence trending condition. When the corridor is wide or neutral gray, the two systems are diverging — reduce size or wait for re-alignment. Reading the Signal Hierarchy: Start with the Kalman regime (K▲/K▼ label and trail color) for macro direction. Add the trail flip arrow for timing. Confirm with MFI cross-50 triangle. Check if an OB zone is nearby for HC bonus. Exit on TP label or when the corridor fill turns neutral. Squeeze Breakout Setup: When the golden diamond squeeze marker fires, the Kalman bands are compressing. Wait for the circle squeeze release marker. If the trail is aligned with the Kalman regime at release, the first trail flip after the release is a high-quality breakout entry. Indicator Limitations Order block detection requires a confirmed swing pivot, which in Pine Script v6 is offset by swingLen bars — zones are created after the fact relative to the actual pivot candle The corridor fill between the Kalman trail and HMA trail can produce wide fills on instruments with large spread between the two systems — this is informational, not a defect, but may visually dominate the chart on some timeframes HC signals require all three conditions simultaneously. On instruments with sparse order block formation, HC signals may be infrequent compared to standard trail flip arrows The volume-weighted MFI requires volume data. On instruments with unreliable volume reporting, the pressure engine may be less meaningful than on equities or futures Squeeze detection uses 80% of the 20-bar SMA as the threshold. On instruments that are persistently low-volatility, this threshold may trigger continuously — adjust the squeeze percentage parameter upward for such instruments Originality Statement This indicator is original in its three-engine confluence architecture, the corridor fill system between the Kalman Supertrend and HMA trail, and the session-colored OB zone integration with the starred HC signal. The publication is justified because: The corridor fill between the Kalman Supertrend trail and the HMA pressure trail creates a novel visual quality gauge — the width and saturation of the corridor communicates alignment strength between macro regime and near-term pressure in a single spatial layer Session-colored OB zone borders encode institutional session context directly into the zone visual without requiring a separate session indicator, making the chart self-contained for context-aware zone evaluation The HC signal requires three independent engine conditions to coincide: Kalman regime direction, trail flip timing, and OB proximity. This triple-gate structure is a more restrictive and higher-quality filter than any two-condition confluence approach The three-layer visual architecture (outer cloud, corridor fill, core pressure gradient) creates a spatially organized picture where the distance between layers communicates regime context, trail alignment, and pressure intensity at different spatial scales simultaneously The K-velocity dot brightness system embeds momentum acceleration directly into the trail visualization without requiring a separate panel — the trail itself communicates direction, state, and rate of change simultaneously Disclaimer This indicator is provided for educational and informational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument. Past performance of any pattern or signal does not guarantee future results. All trading involves substantial risk. Always use proper risk management and conduct your own independent analysis. — Made with passion by officialjackofalltrades
Pine Script® Indikator
von officialjackofalltrades
Vortex Nexus Alpha [JOAT]Vortex Nexus Alpha Strategy Introduction The Vortex Nexus Alpha Strategy is an advanced open-source algorithmic trading system that combines multi-dimensional signal generation, adaptive regime detection, and institutional-grade risk management into a unified execution framework. This strategy represents a complete trading system built from the ground up using proprietary mathematical models, fractal analysis, momentum tracking, and market microstructure intelligence. Unlike simple crossover strategies or single-indicator systems, Vortex Nexus Alpha synthesizes intelligence from five independent signal layers, each containing five distinct detection mechanisms, creating a 25-factor confluence scoring system that validates every trade entry. The strategy is designed for traders who understand that consistent profitability requires multi-dimensional analysis, adaptive positioning, and systematic risk management rather than relying on any single indicator or pattern. Why This Strategy Exists This strategy addresses the fundamental challenge of algorithmic trading: most systems over-optimize to historical data or rely on simplistic logic that fails in real market conditions. Vortex Nexus Alpha solves this through a knowledge-based architecture that doesn't depend on indicator mashups but instead builds intelligence from first principles: Volatility Expansion Engine: Measures market volatility through ATR percentile ranking and adapts position sizing and stop distances dynamically Price Efficiency Calculator: Quantifies how efficiently price moves using path length analysis, filtering choppy conditions Chaos Measurement System: Identifies market regime (directional, equilibrium, chaotic) using logarithmic range analysis Directional Conviction Tracker: Measures trend strength through ADX and directional movement indicators Adaptive Ribbon System: Multi-layer EMA ribbon that expands/contracts based on volatility and provides dynamic support/resistance Volume Pressure Analysis: Estimates buying/selling pressure through candle structure and wick analysis Gauss Smoothing Engine: 4th-order Gaussian filter that eliminates noise while preserving genuine price movements Fractal Efficiency Measurement: Logarithmic efficiency calculation that adapts Laguerre filtering for optimal lag reduction Laguerre Momentum Transform: Adaptive momentum oscillator that responds faster during efficient moves Temporal Flow Dynamics: Analyzes price flow direction, magnitude, and acceleration across multiple dimensions Pivot Structure Analysis: Detects market structure breaks and shifts using swing high/low analysis Order Block Detection: Identifies institutional positioning zones through volume-confirmed reversal patterns Imbalance Zone Mapping: Marks price gaps and inefficiencies that often get filled Each component contributes unique intelligence that validates or invalidates potential trade setups. The strategy requires minimum confluence scores before entering positions, ensuring that multiple independent systems agree on directional bias. Core Strategy Architecture 1. Volatility Expansion Engine The strategy begins with comprehensive volatility analysis: volatility = ta.atr(volatilityPeriod) volatilityPercent = (volatility / close) * 100 volatilityRank = ta.percentrank(volatilityPercent, 100) Volatility percentile ranking provides context for current volatility relative to recent history. This measurement drives multiple strategy decisions: - Position sizing: Higher volatility = smaller positions - Stop distance: Higher volatility = wider stops - Signal filtering: Extreme volatility (>80 percentile) triggers defensive mode The strategy adapts to volatility rather than using fixed parameters, ensuring it remains relevant across different market regimes. 2. Price Efficiency and Chaos Measurement The strategy calculates price efficiency to distinguish trending from ranging markets: priceMovement = math.abs(close - close ) pathLength = math.sum(math.abs(close - close ), efficiencyPeriod) efficiency = pathLength > 0 ? priceMovement / pathLength : 0 High efficiency (>0.6) indicates clean, directional movement suitable for trend-following. Low efficiency (<0.4) suggests choppy conditions where the strategy reduces activity or switches to mean-reversion logic. Chaos level is measured using logarithmic range analysis: rangeHigh = ta.highest(high, volatilityPeriod) rangeLow = ta.lowest(low, volatilityPeriod) atrSum = math.sum(ta.atr(1), volatilityPeriod) chaosLevel = 100 * math.log10(atrSum / (rangeHigh - rangeLow)) / math.log10(volatilityPeriod) High chaos (>60) triggers defensive positioning. Low chaos (<40) enables aggressive trend-following. 3. Directional Conviction System The strategy implements complete ADX analysis with directional indicators: = adx(14, 14) ADX above 25 indicates emerging directional conviction. Above 40 indicates dominant conviction. The strategy uses conviction strength to: - Filter entries: Minimum conviction threshold prevents trading in directionless markets - Size positions: Higher conviction = larger positions (within risk limits) - Set targets: Strong conviction enables wider profit targets The difference between bullForce and bearForce determines directional bias and validates signal direction. 4. Adaptive Ribbon System The strategy calculates 8 EMA layers with adaptive spacing: stepSize = (slowPeriod - fastPeriod) / (ribbonLayers - 1) ribbonLevel0 = ta.ema(close, fastPeriod) ribbonLevel7 = ta.ema(close, slowPeriod) Ribbon analysis provides: - Trend direction: Fast > slow = bullish, fast < slow = bearish - Trend strength: Wider ribbon = stronger trend - Dynamic support/resistance: Ribbon layers act as price magnets - Compression detection: Tight ribbon = energy buildup before breakout The strategy only takes long trades when price is above the ribbon and short trades when below, ensuring alignment with trend structure. 5. Volume Pressure Analysis The strategy estimates buying and selling pressure using candle structure: buyPressure = close > open ? volume * ((close - open + upperWick * 0.5) / barSpan) : close < open ? volume * ((upperWick + bodyMass * 0.3) / barSpan) : volume * 0.5 sellPressure = volume - buyPressure pressureDelta = buyPressure - sellPressure Pressure analysis validates signal direction: - Long signals require positive pressure delta - Short signals require negative pressure delta - Extreme pressure (>70% of volume) suggests potential exhaustion The strategy tracks cumulative pressure to identify accumulation and distribution phases. 6. Gauss Smoothing and Fractal Efficiency The strategy applies 4th-order Gaussian filtering to eliminate noise: gaussClose := math.pow(alpha, 4) * close + 4 * (1.0 - alpha) * nz(gaussClose ) - 6 * math.pow(1 - alpha, 2) * nz(gaussClose ) + 4 * math.pow(1 - alpha, 3) * nz(gaussClose ) - math.pow(1 - alpha, 4) * nz(gaussClose ) Fractal efficiency is calculated using logarithmic path measurement: fractalRatio = totalSpan > 0 ? math.log(rangeSum / totalSpan) / math.log(fractalSpan) : 0.0 fractalEfficiency = math.max(0, math.min(1, (fractalRatio + 1) / 2)) High fractal efficiency (>0.7) validates that momentum signals are backed by clean price action. 7. Laguerre Momentum Transform The strategy uses adaptive Laguerre filtering for momentum measurement: gamma = 0.7 * (1 - fractalEfficiency) + 0.1 * fractalEfficiency L0 := (1 - gamma) * gaussClose + gamma * nz(L0 ) L1 := -gamma * L0 + nz(L0 ) + gamma * nz(L1 ) L2 := -gamma * L1 + nz(L1 ) + gamma * nz(L2 ) L3 := -gamma * L2 + nz(L2 ) + gamma * nz(L3 ) cu = (L0 > L1 ? L0 - L1 : 0) + (L1 > L2 ? L1 - L2 : 0) + (L2 > L3 ? L2 - L3 : 0) cd = (L0 < L1 ? L1 - L0 : 0) + (L1 < L2 ? L2 - L1 : 0) + (L2 < L3 ? L3 - L2 : 0) laguerreValue = cu + cd != 0 ? 100 * (cu / (cu + cd)) : 50 fractalMomentum = (laguerreValue - 50) * (1 + fractalEfficiency) The adaptive gamma adjustment reduces lag during efficient moves and adds smoothing during choppy conditions. Fractal momentum above 20 validates bullish signals, below -20 validates bearish signals. 8. Temporal Flow Dynamics The strategy analyzes price flow across multiple dimensions: priceFlow = ta.ema(close, flowPeriod) - ta.ema(close, flowPeriod * 2) flowDir = priceFlow > 0 ? 1 : -1 flowMagnitude = math.abs(priceFlow) / volatility flowAccel = ta.change(priceFlow, 3) Flow analysis provides: - Flow direction: Confirms trend direction - Flow magnitude: Measures flow strength relative to volatility - Flow acceleration: Identifies momentum shifts The strategy requires flow alignment with signal direction for entry validation. 9. Market Structure Analysis The strategy tracks pivot highs and lows to identify structure breaks: pivotTop = ta.pivothigh(high, pivotSpan, pivotSpan) pivotBottom = ta.pivotlow(low, pivotSpan, pivotSpan) Structure breaks occur when: - Bullish: Price breaks above previous pivot high - Bearish: Price breaks below previous pivot low Structure shifts (change of character) occur when: - Bullish: Downtrend breaks above previous pivot high - Bearish: Uptrend breaks below previous pivot low The strategy gives bonus confluence points to signals that align with structure breaks or shifts. 10. Order Block and Imbalance Detection The strategy identifies institutional positioning zones: orderBlockBull = close < open and close > open and volume > avgVol * 1.2 orderBlockBear = close > open and close < open and volume > avgVol * 1.2 gapUp = low > high and (low - high ) > volatility * 0.3 gapDown = high < low and (low - high) > volatility * 0.3 Order blocks mark zones where institutions placed large orders. The strategy uses these as: - Entry zones: Look for entries near order blocks in trend direction - Stop placement: Place stops beyond order blocks for protection - Target zones: Opposite-direction order blocks become profit targets Imbalance zones (gaps) often get filled, providing mean-reversion opportunities. Multi-Dimensional Signal Generation The strategy generates signals through five independent layers, each containing five detection mechanisms: Layer 1: Rapid Scalp Signals (5 mechanisms) - Laguerre oversold + flow bullish + price above fast ribbon - Pressure index positive + flow reversal bullish - Momentum bullish + volume surge + price above mid ribbon - Strong bullish candle + ribbon bullish + pressure positive - Fractal momentum positive + flow acceleration positive + ribbon aligned Layer 2: Swing Position Signals (5 mechanisms) - Ribbon bullish + price above slow ribbon + bullish regime - Structure break bullish + momentum bullish - Order block bullish + flow bullish + conviction strong - Gap up + pressure extreme + ribbon aligned - Range breakout up + cumulative pressure positive + flow strong Layer 3: Momentum Continuation (5 mechanisms) - Fractal momentum extreme + ribbon bullish + conviction strong - Laguerre oversold + flow bullish + volume surge - Momentum extreme + fractal momentum positive + ribbon expanding - Extreme buy pressure + flow acceleration positive + bullish regime - Bull force > bear force + conviction strong + ribbon aligned Layer 4: Structure Confirmation (5 mechanisms) - Structure shift bullish + volume surge - Order block bullish + price above last pivot low + momentum bullish - Gap up + flow bullish + ribbon bullish - Structure break bullish + pressure extreme positive - Volume absorption + pressure positive + price above mid ribbon Layer 5: Confluence Boosters (5 mechanisms) - Ribbon tight + ribbon expanding + ribbon bullish + volume surge - Net flow positive + temporal force positive + bullish regime - Fractal efficiency high + Laguerre oversold + flow magnitude strong - Strong bullish candle + price above previous high + volume extreme - Velocity positive + flow bullish + ribbon power strong Each layer contributes 0 or 1 to the bull strength score. The strategy requires minimum confluence (default 2) before entering long positions. This multi-layer approach ensures that signals are validated across multiple independent dimensions. Risk Management System The strategy implements institutional-grade risk management: Position Sizing: - Risk percentage per trade (default 1% of equity) - Dynamic adjustment based on volatility percentile - Reduced sizing during high chaos or low efficiency Stop Loss Placement: stopLoss = close - (volatility * slMultiplier) - ATR-based stops that adapt to current volatility - Multiplier (default 1.5) provides breathing room - Stops placed beyond order blocks when possible Take Profit Targets: takeProfit = close + (volatility * slMultiplier * tpMultiplier) - Risk-reward ratio (default 2.5:1) - Adjusted based on conviction strength - Wider targets during strong conviction, tighter during weak Trailing Stop System: trailStop = close - (volatility * trailOffset) - Optional trailing stop (default enabled) - Offset (default 1.2x ATR) balances protection and breathing room - Activates after position moves into profit Visual Elements Adaptive Ribbon: Multi-layer EMA ribbon with gradient coloring showing trend direction and strength Entry Signals: Triangle shapes sized by signal strength (large for 5+ confluence, small for 2-3 confluence) Structure Markers: Lines and labels marking structure breaks, shifts, and order blocks Imbalance Boxes: Boxes marking price gaps and inefficiency zones Regime Background: Subtle background coloring showing current market regime Flow Background: Additional background layer showing flow direction Comprehensive Dashboard: 18-row intelligence panel showing position status, signal strength, regime, ribbon state, pressure, momentum, structure, flow, conviction, Laguerre, volume, volatility, trade statistics, and win rate The dashboard provides complete strategy intelligence with real-time metrics and performance tracking. Strategy Parameters Core Settings: Ultra-Aggressive Mode: Maximum trade frequency (default enabled) Min Signal Strength: Minimum confluence required (1-6, default 2) Risk %: Risk per trade as percentage of equity (0.5-5.0%, default 1.0%) TP Multiplier: Take profit as multiple of stop distance (1.0-10.0, default 2.5) SL Multiplier: Stop loss as multiple of ATR (0.5-5.0, default 1.5) Trailing Stop: Enable/disable trailing stop (default enabled) Trail Offset: Trailing stop distance as multiple of ATR (0.5-3.0, default 1.2) Advanced Parameters: Volatility Period: ATR calculation length (5-50, default 14) Efficiency Period: Price efficiency calculation period (5-100, default 20) Flow Period: Temporal flow analysis period (10-50, default 20) Ribbon Layers: Number of EMA layers (3-15, default 8) Fast Period: Fastest EMA period (2-20, default 5) Slow Period: Slowest EMA period (10-100, default 34) Visualization: Dashboard: Toggle metrics panel (default enabled) Entry Signals: Toggle signal shapes (default enabled) Regime Zones: Toggle background coloring (default enabled) Adaptive Ribbon: Toggle ribbon display (default enabled) How to Use This Strategy Step 1: Configure Risk Parameters Set risk percentage appropriate for your account size. 1% is conservative, 2% is moderate, 3%+ is aggressive. Never risk more than you can afford to lose on any single trade. Step 2: Select Minimum Signal Strength Default 2 provides balanced trade frequency and quality. Increase to 3-4 for higher quality but fewer trades. Decrease to 1 only in ultra-aggressive mode on highly liquid instruments. Step 3: Adjust Risk-Reward Ratio Default 2.5:1 provides good balance. Increase to 3-5:1 for swing trading. Decrease to 1.5-2:1 for scalping. Higher ratios require higher win rates to be profitable. Step 4: Enable/Disable Trailing Stops Trailing stops protect profits but can exit prematurely. Enable for trend-following, disable for mean-reversion. Adjust trail offset based on instrument volatility. Step 5: Monitor Dashboard Metrics Watch "POSITION" status, "BULL STR" and "BEAR STR" scores, "REGIME" classification, and "WIN RATE" percentage. These provide real-time strategy health assessment. Step 6: Backtest Thoroughly Test on at least 100 trades across different market conditions. Verify that win rate, profit factor, and drawdown meet your requirements. Adjust parameters if needed. Step 7: Forward Test on Demo Run strategy on demo account for at least 1 month before live trading. Verify that live performance matches backtest expectations. Monitor slippage and execution quality. Step 8: Start Small on Live Begin with minimum position sizes on live account. Gradually increase as confidence builds. Never risk more than 1-2% of account on any single trade initially. Best Practices Use on liquid instruments with tight spreads and reliable execution Backtest with realistic commission (0.1%) and slippage (2 ticks minimum) Test across multiple market conditions (trending, ranging, volatile, calm) Verify minimum 100 trades in backtest for statistical significance Monitor win rate - should be 45-60% for 2.5:1 risk-reward ratio Check profit factor - should be >1.5 for robust strategy Analyze maximum drawdown - should be <20% of account Review trade distribution - avoid over-concentration in specific periods Monitor signal strength distribution - most trades should be 3+ confluence Check regime alignment - strategy should perform in directional regimes Verify that losses are controlled - no single loss should exceed 2% of account Ensure adequate trade frequency - at least 2-3 trades per week on daily timeframe Combine with manual oversight - review signals before execution in early stages Use appropriate timeframe - 15m-1H for day trading, 4H-1D for swing trading Avoid trading during major news events unless specifically tested for that Keep detailed trade journal to identify patterns in wins and losses Strategy Limitations Algorithmic strategies cannot predict black swan events or unprecedented market conditions Backtested performance does not guarantee future results Slippage and commission in live trading may differ from backtest assumptions The strategy requires sufficient volatility - may underperform in extremely low volatility Signal generation depends on multiple calculations - computational lag possible on slow systems The strategy works best on trending instruments - may struggle in perpetual ranges Confluence scoring requires all components to be relevant - some may be less meaningful on certain instruments The strategy cannot account for fundamental catalysts or news events Trailing stops can exit prematurely during volatile but ultimately profitable moves The strategy requires adequate liquidity for execution at desired prices Parameter optimization can lead to overfitting - use walk-forward analysis The strategy shows what signals exist, not why - market context still matters Technical Implementation Built with Pine Script v6 using: Complete volatility expansion engine with ATR percentile ranking Price efficiency calculator using path length analysis Chaos measurement using logarithmic range calculations Full ADX implementation with directional indicators 8-layer adaptive EMA ribbon with volatility-based spacing Volume pressure estimation using candle structure analysis 4th-order Gaussian filter for noise elimination Fractal efficiency measurement using logarithmic path complexity Adaptive Laguerre transform with 4 cascading filter levels Temporal flow analysis with direction, magnitude, and acceleration Pivot-based market structure tracking Order block and imbalance zone detection 25-factor confluence scoring system across 5 signal layers Dynamic position sizing based on volatility and regime ATR-based stop loss and take profit calculations Optional trailing stop system with volatility adjustment Comprehensive dashboard with 18 metrics and performance tracking Alert system for all entry and exit signals The code is fully open-source with extensive comments explaining each component and signal generation logic. Originality Statement This strategy is original and represents a complete trading system built from proprietary knowledge rather than indicator mashups. The strategy is justified because: It synthesizes 13 independent analytical systems into a unified execution framework The 25-factor confluence scoring across 5 signal layers provides multi-dimensional validation Each component is built from first principles using mathematical models and market microstructure concepts The adaptive nature of the system (volatility, efficiency, regime) ensures relevance across market conditions Risk management is integrated at the core rather than added as an afterthought The strategy doesn't rely on any single indicator or pattern - it builds intelligence from multiple independent sources Fractal efficiency and Laguerre adaptation provide unique momentum measurement not found in standard systems Temporal flow analysis adds a dimension of price dynamics beyond simple trend following Market structure tracking provides context that pure indicator-based systems lack The comprehensive dashboard provides complete strategy intelligence and performance tracking The system is designed for real trading with realistic risk management, not just backtest optimization Each component contributes unique intelligence: volatility drives adaptation, efficiency filters conditions, chaos identifies regimes, conviction measures strength, ribbon provides structure, pressure shows order flow, Gauss filtering eliminates noise, fractal efficiency validates momentum, Laguerre provides adaptive momentum, flow tracks dynamics, structure provides context, order blocks mark zones, and confluence validates signals. The strategy's value lies in combining these complementary perspectives into a cohesive, adaptive trading system with institutional-grade risk management. Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors. Algorithmic trading strategies are tools for systematic execution, not guarantees of profit. Backtested performance does not guarantee future results. Past strategy performance does not predict future performance. Market conditions change, and strategies that worked historically may not work in the future. The signals generated are mathematical calculations based on current market data, not predictions of future price movement. High confluence scores, regime alignment, and structure breaks do not guarantee profitable trades. Users must conduct their own analysis and risk assessment before making trading decisions. Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this strategy. Users assume full responsibility for all trading decisions made using this tool. Thoroughly backtest and forward test any strategy before live trading. -Made with passion by officialjackofalltrades
Pine Script® Strategie
von officialjackofalltrades
Precision Pivot Confluence Engine [JOAT]Precision Pivot Confluence Engine Introduction The Precision Pivot Confluence Engine is an open-source technical indicator that combines Central Pivot Range (CPR) analysis with Smart Money Concepts (SMC), multi-oscillator divergence detection, and institutional order flow patterns. This mashup integrates multiple proven methodologies into a unified confluence system designed to identify high-probability trading zones where institutional and retail liquidity intersect. The indicator is built for traders who understand that no single signal provides consistent edge, but multiple confirming factors working together can significantly improve trade selection. By synthesizing CPR levels, Fair Value Gaps, Order Blocks, liquidity sweeps, and divergence patterns, this tool helps identify structural market inflection points. Chart showing CPR levels, FVG zones, Order Blocks, and divergence signals on 4H timeframe Why This Mashup Exists This indicator combines five distinct analytical frameworks that complement each other: CPR Analysis: Identifies key pivot levels where institutional algorithms and retail traders make decisions Smart Money Concepts: Tracks Fair Value Gaps, Order Blocks, and Breaker Blocks showing institutional positioning Divergence Detection: Uses RSI, MACD, and Stochastic RSI to identify momentum exhaustion Liquidity Analysis: Detects liquidity sweeps where stop hunts occur before reversals Volume Confirmation: Validates moves with volume analysis and delta calculations Each component addresses a different aspect of market structure. CPR provides static reference levels, SMC reveals dynamic institutional behavior, divergences show momentum shifts, liquidity sweeps identify stop hunts, and volume confirms genuine moves versus noise. Together, they create a multi-dimensional view of market conditions. Core Components Explained 1. Enhanced CPR System The Central Pivot Range system calculates Daily and Weekly pivot levels using the formula: Pivot = (High + Low + Close) / 3 BC (Bottom Central) = (High + Low) / 2 TC (Top Central) = (Pivot - BC) + Pivot The indicator analyzes CPR width to determine market regime: Narrow CPR (width < 0.5%): Indicates compression and potential breakout conditions Wide CPR (width > 1.5%): Suggests ranging market with less directional conviction Price position relative to CPR: Above both Daily and Weekly pivots = bullish structure, below = bearish structure CPR levels act as magnetic zones where price tends to react. The indicator tracks distance from pivots to identify overextension and mean reversion opportunities. 2. Smart Money Concepts Integration Fair Value Gaps (FVG): Bullish FVG occurs when current low > high from 2 bars ago, leaving an unfilled gap Bearish FVG occurs when current high < low from 2 bars ago The indicator calculates FVG size as percentage of price and filters for significant gaps (> 0.3%) to avoid noise. FVGs represent inefficient price delivery where institutions moved price quickly, often returning to fill these gaps later. Order Blocks (OB): Bullish OB: Two consecutive bearish candles followed by strong bullish candle with high volume Bearish OB: Two consecutive bullish candles followed by strong bearish candle with high volume Order Blocks mark the last opposite-direction move before a strong impulse, indicating where institutions accumulated or distributed positions. Breaker Blocks: Failed Order Blocks that get violated become Breaker Blocks, signaling potential trend reversal. The indicator tracks the last bullish and bearish OB levels and alerts when price breaks through them. Liquidity Sweeps: The indicator identifies when price briefly exceeds recent highs/lows (20-bar lookback) but closes back inside the range. These "stop hunts" often precede reversals as institutions trigger retail stops before moving price in the intended direction. Example showing FVG zones, Order Blocks, and liquidity sweep markers 3. Multi-Oscillator Divergence System The indicator simultaneously tracks divergences across three oscillators: RSI Divergence: Bullish: Price makes lower low, RSI makes higher low (momentum improving despite price weakness) Bearish: Price makes higher high, RSI makes lower high (momentum deteriorating despite price strength) MACD Divergence: Tracks histogram divergences using the same pivot-based logic Stochastic RSI Divergence: More sensitive than RSI, catches early momentum shifts The indicator uses a 5-bar pivot lookback to identify swing highs/lows and compares current pivots with previous pivots to detect divergences. When multiple oscillators show divergence simultaneously, it signals strong momentum exhaustion. 4. Volume Analysis Engine Volume MA Comparison: Identifies high volume (> 1.5x MA) and climax volume (> 3x MA) Volume Delta: Cumulative difference between buying volume (green candles) and selling volume (red candles) Delta Trend: Compares current delta to 20-period MA to identify institutional accumulation or distribution Volume Confirmation: Validates bullish moves with high volume + rising delta, bearish moves with high volume + falling delta 5. Confluence Scoring System The indicator calculates a real-time confluence score (0-100) by weighting each component: Confluence Score Components: - CPR Position: Up to 15 points (bullish above pivots, bearish below) - SMC Signals: Up to 10 points (FVG + OB + Breaker + Liquidity Sweeps) - Divergence: Up to 10 points (single oscillator = 5, multiple = 10) - Volume: Up to 10 points (confirmed volume = 7, climax = additional 3) - Trend Alignment: Up to 5 points (price vs key MAs) Scores above 70 indicate strong confluence for potential trades. The dashboard displays individual component scores for transparency. Visual Elements CPR Lines: Daily Pivot (yellow), TC/BC (yellow transparent), Weekly Pivot (yellow circles) FVG Boxes: Green boxes for bullish FVGs, red boxes for bearish FVGs Order Block Boxes: Solid green/red boxes marking institutional zones Breaker Block Labels: "BB" markers when Order Blocks fail Liquidity Sweep Labels: "LIQ" and "STRONG LIQ" positioned at sweep tips Divergence Labels: "D" markers at divergence pivot points Dashboard: Top-right table showing confluence score and component breakdown How Components Work Together The mashup creates a layered analysis approach: Layer 1 - Structure: CPR levels define key zones where reactions are likely Layer 2 - Institutional Behavior: SMC concepts show where smart money is positioned Layer 3 - Momentum: Divergences indicate when current trend is losing steam Layer 4 - Confirmation: Volume validates whether moves are genuine or false Layer 5 - Synthesis: Confluence score combines all factors into actionable signal Example scenario: Price approaches Daily Pivot (Layer 1) where a bullish Order Block exists (Layer 2), RSI shows bullish divergence (Layer 3), and volume delta is rising (Layer 4). The confluence score jumps to 85 (Layer 5), signaling high-probability long setup. Input Parameters CPR Settings: Show Daily CPR: Toggle daily pivot levels (default: enabled) Show Weekly CPR: Toggle weekly pivot levels (default: enabled) CPR Width Threshold: Defines narrow vs wide CPR (default: 0.5% / 1.5%) Smart Money Concepts: Show FVG: Display Fair Value Gap boxes (default: enabled) Show Order Blocks: Display Order Block boxes (default: enabled) Show Breaker Blocks: Display Breaker Block labels (default: enabled) Show Liquidity Sweeps: Display liquidity sweep markers (default: enabled) FVG Min Size: Minimum gap size to display (default: 0.3%) Lookback Bars: Bars to scan for liquidity levels (default: 20) Divergence Detection: Show Divergences: Toggle divergence labels (default: enabled) RSI Length: Period for RSI calculation (default: 14) Pivot Lookback: Bars for pivot detection (default: 5) Volume Analysis: Show Volume Analysis: Toggle volume indicators (default: enabled) Volume MA Length: Period for volume moving average (default: 20) High Volume Multiplier: Threshold for high volume (default: 1.5x) Climax Volume Multiplier: Threshold for climax volume (default: 3.0x) Display Options: Show Dashboard: Toggle confluence score table (default: enabled) Max FVG Boxes: Limit displayed FVG boxes (default: 20) Max OB Boxes: Limit displayed Order Block boxes (default: 15) Label Spacing: Minimum bars between labels to prevent overlap (default: 10-15) How to Use This Indicator Step 1: Identify Market Structure Check CPR position and width. Narrow CPR suggests breakout potential, wide CPR suggests range-bound conditions. Step 2: Look for SMC Confluence Identify FVGs, Order Blocks, and recent liquidity sweeps. These zones often provide high-probability entry areas. Step 3: Check for Divergences Look for divergence labels at swing points. Multiple oscillator divergences increase signal strength. Step 4: Confirm with Volume Ensure volume supports the move. Rising delta + high volume confirms bullish moves, falling delta + high volume confirms bearish moves. Step 5: Review Confluence Score Check the dashboard. Scores above 70 indicate strong confluence. Individual component scores show which factors are contributing. Step 6: Wait for Price Action Confirmation The indicator identifies zones and conditions, but wait for price action confirmation (candlestick patterns, breakouts, etc.) before entering trades. Best Practices Use on 15-minute to 4-hour timeframes for optimal signal quality Combine with proper risk management - indicator shows zones, not exact entries Pay attention to confluence score - higher scores generally indicate better setups Watch for FVG fills and Order Block retests as entry triggers Liquidity sweeps followed by reversal often provide excellent risk:reward entries Divergences work best when combined with SMC zones or CPR levels Volume confirmation is critical - avoid low-volume signals Indicator Limitations Does not provide exact entry/exit signals - requires trader interpretation Can generate false signals in choppy, low-volume conditions Multiple visual elements may clutter chart - adjust display settings as needed Divergences can persist longer than expected - price can continue trending despite divergence FVGs and Order Blocks don't always get retested - not every zone provides entry opportunity Confluence score is a guide, not a guarantee - high scores can still result in losing trades Requires understanding of SMC concepts and CPR analysis for effective use Performance varies across different markets and timeframes Technical Implementation Built with Pine Script v6 using: Custom CPR calculations with width analysis Box and label management with anti-overlap logic Persistent variables for tracking Order Blocks and Breaker Blocks Pivot-based divergence detection across multiple oscillators Volume delta calculation with cumulative tracking Real-time confluence scoring system Dynamic dashboard with component breakdown The code is fully open-source and can be modified to suit individual trading styles and preferences. Originality Statement This indicator is original in its integration approach. While individual components (CPR, FVG, Order Blocks, RSI divergence, volume analysis) are established concepts, this mashup is justified because: It synthesizes five distinct methodologies that address different market aspects The confluence scoring system provides quantitative measurement of setup quality Anti-overlap logic and timeframe-adaptive filtering reduce visual clutter Component integration creates layered analysis not available in individual indicators The combination helps identify zones where multiple institutional and technical factors align Each component contributes unique information: CPR provides static structure, SMC reveals dynamic institutional behavior, divergences show momentum shifts, liquidity analysis identifies stop hunts, and volume confirms genuine moves. The mashup's value lies in presenting these complementary perspectives simultaneously with a unified scoring system. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors. Technical indicators are tools for analysis, not crystal balls. Past performance and backtested results do not guarantee future performance. Market conditions change, and strategies that worked historically may not work in the future. The confluence score is a mathematical calculation based on current market data, not a prediction of future price movement. High confluence scores do not guarantee profitable trades. Users must conduct their own analysis and risk assessment before making trading decisions. Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool. -Made with passion by officialjackofalltrades
Pine Script® Indikator
von officialjackofalltrades
Z-EMA Fusion BandsDesigned with crypto markets in mind, particularly Bitcoin , it builds on the concept that the 1-Week 50 EMA often serves as a long-term bull/bear market threshold — an area where institutional bias, momentum shifts, and cyclical rotations tend to occur. 🔹 Core Components & Synergies: 1. 1W 50 EMA (Higher Timeframe) - This EMA is calculated on a weekly timeframe, regardless of your current chart. - In crypto, price above the 1W 50 EMA typically aligns with long-term bull market phases, while extended periods below can signify bearish macro structure. - The slope of the EMA is also analyzed to add directional confidence to trend strength. 2. ±1 Standard Deviation Bands - Surrounding the 50 EMA, these bands visualize normal price dispersion relative to trend. - When price consistently hugs or breaks outside these bands, it often reflects market expansion, volatility events, or mean-reversion opportunity. 3. Z-Score Gradient Fill - The area between the bands is filled using a Z-score-based gradient, which dynamically adjusts color based on how far price is from the EMA (in terms of standard deviations). - Color shifts from aqua (near EMA) to fuchsia (far from EMA) help you spot price compression, equilibrium, or overextension at a glance. - The fill also uses transparency scaling, making it fade as price stretches further, emphasizing the core structure. 4. Directional EMA Coloring - The EMA line itself is colored based on: - The slope of the EMA (rising/falling) - Whether the HTF candle is bullish or bearish - This provides intuitive color-coded confirmation of momentum alignment or potential exhaustion. 5. Price/EMA Divergence Detection - The script detects bullish and bearish divergence between price and the EMA (rather than using a traditional oscillator). - Bullish Divergence: Price makes a lower low, EMA makes a higher low. - Bearish Divergence: Price makes a higher high, EMA makes a lower high. - These signals often mark transitional zones where momentum fades before a trend reversal or correction. 📊 Suggested Uses: 🔸 Swing and Position Trading: - Use the 1W 50 EMA as a macro-trend anchor. - Stay long-biased when price is above with positive slope, and short-biased when below. - Consider entries near band edges for mean-reversion plays, especially if confluence forms with divergence signals. 🔸 Volatility-Based Filtering: - Use the Z-score fill to identify volatility compression (near EMA) or expansion (edge of bands). - Combine this with breakout strategies or dynamic position sizing. 🔸 Divergence Confirmation: - Combine divergence markers with HTF EMA slope for high-probability setups. - Bullish div + EMA flattening/rising can signal the start of accumulation after a macro dip. 🔸 Multi-Timeframe Analysis: - Works well as a structural overlay on intraday charts (1H, 4H, 1D). - Use this indicator to track long-term bias while executing lower timeframe trades. ⚠️ Disclaimer: This indicator is designed for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any asset. Always use proper risk management, and combine with your own analysis, tools, and strategy. Performance in past market conditions does not guarantee future results.
Pine Script® Indikator
von RWCS_LTD
Volumatic Fair Value Gaps [BigBeluga]🔵 OVERVIEW The Volumatic Fair Value Gaps indicator detects and plots size-filtered Fair Value Gaps (FVGs) and immediately analyzes the bullish vs. bearish volume composition inside each gap. When an FVG forms, the tool samples volume from a 10× lower timeframe , splits it into Buy and Sell components, and overlays two compact bars whose percentages always sum to 100%. Each gap also shows its total traded volume . A live dashboard (top-right) summarizes how many bullish and bearish FVGs are currently active and their cumulative volumes—offering a quick read on directional participation and trend pressure. 🔵 CONCEPTS FVGs (Fair Value Gaps) : Imbalance zones between three consecutive candles where price “skips” trading. The script plots bullish and bearish gaps and extends them until mitigated. Size Filtering : Only significant gaps (by relative size percentile) are drawn, reducing noise and emphasizing meaningful imbalances. // Gap Filters float diff = close > open ? (low - high ) / low * 100 : (low - high) / high *100 float sizeFVG = diff / ta.percentile_nearest_rank(diff, 1000, 100) * 100 bool filterFVG = sizeFVG > 15 Volume Decomposition : For each FVG, the indicator inspects a 10× lower timeframe and aggregates volume of bullish vs. bearish candles inside the gap’s span. 100% Split Bars : Two inline bars per FVG display the % Bull and % Bear shares; their total is always 100%. Total Gap Volume : A numeric label at the right edge of the FVG shows the total traded volume associated with that gap. Mitigation Logic : Gaps are removed when price closes through (or touches via high/low—user-selectable) the opposite boundary. Dashboard Summary : Counts and sums the active bullish/bearish FVGs and their total volumes to gauge directional dominance. 🔵 FEATURES Bullish & Bearish FVG plotting with independent color controls and visibility toggles. Adaptive size filter (percentile-based) to keep only impactful gaps. Lower-TF volume sampling at 10× faster resolution for more granular Buy/Sell breakdown. Per-FVG volume bars : two horizontal bars showing Bull % and Bear % (sum = 100%). Per-FVG total volume label displayed at the right end of the gap’s body. Mitigation source option : choose close or high/low for removing/invalidating gaps. Overlap control : older overlapped gaps are cleaned to avoid clutter. Auto-extension : active gaps extend right until mitigated. Dashboard : shows count of bullish/bearish gaps on chart and cumulative volume totals for each side. Performance safeguards : caps the number of active FVG boxes to maintain responsiveness. 🔵 HOW TO USE Turn on/off FVG types : Enable Bullish FVG and/or Bearish FVG depending on your focus. Tune the filter : The script already filters by relative size; if you need fewer (stronger) signals, increase the percentile threshold in code or reduce the number of displayed boxes. Choose mitigation source : close — stricter; gap is removed when a closing price crosses the boundary. high/low — more sensitive; a wick through the boundary mitigates the gap. Read the per-FVG bars : A higher Bull % inside a bullish gap suggests constructive demand backing the imbalance. A higher Bear % inside a bearish gap suggests supply is enforcing the imbalance. Use total gap volume : Larger totals imply more meaningful interest at that imbalance; confluence with structure/HTF levels increases relevance. Watch the dashboard : If bullish counts and cumulative volume exceed bearish, market pressure is likely skewed upward (and vice versa). Combine with trend tools or market structure for entries/exits. Optional: hide volume bars : Disable Volume Bars when you want a cleaner FVG map while keeping total volume labels and the dashboard. 🔵 CONCLUSION Volumatic Fair Value Gaps blends precise FVG detection with lower-timeframe volume analytics to show not only where imbalances exist but also who powers them. The per-gap Bull/Bear % bars, total volume labels, and the cumulative dashboard together provide a fast, high-signal read on directional participation. Use the tool to prioritize higher-quality gaps, align with trend bias, and time mitigations or continuations with greater confidence.
Pine Script® Indikator
von BigBeluga
16
Bull/Bear Ratio By Month Table [MsF]Japanese below / 日本語説明は英文の後にあります。 ------------------------- This is an indicator that shows monthly bull-bear ratio in a table. By specifying the start year and end year, the ratio will be calculated and showed based on the number of bullish and bearish lines in the monthly bar. It allows you to analyze the trend of each symbol and month (bullish / bearish). Up to 10 symbols can be specified. You can take monthly bull-bear ratio for the past 10 or 20 years on the web, but with this indicator, you can narrow it down to the period in which you want to see the symbols you want to see. It is very convenient because you can take statistics at will. Furthermore, if the specified ratio is exceeded, the font color can be changed to any color, making it very easy to read. === Parameter description === - From … Year of start of aggregation - To … Year of end of aggregation - Row Background Color … Row title background color - Col Background Color … Column title background color - Base Text Color … Text color - Background Color … Background Color - Border Color … Border Color - Location … Location - Text Size … Text Size - Highlight Threshold … Ratio threshold, and color - Display in counter? … Check if you want to show the number of times instead of the ratio ------------------------- 月別陰陽確率をテーブル表示するインジケータです。 開始年から終了年を指定することで、月足における陽線数および陰線数を元に確率を計算して表示します。 この機能により各シンボルおよび各月の特徴（買われやすい／売られやすい）を認識することができアノマリー分析が可能です。 シンボルは10個まで指定可能です。 過去10年、20年の月別陰陽確率は、Web上でよく見かけますが、このインジケータでは見たいシンボルを見たい期間に絞って、 自由自在に統計を取ることができるため大変便利です。 なお、指定した確率を上回った場合、文字色を任意の色に変更することができるため、大変見やすくなっています。 === パラメータの説明 === - From … 集計開始年 - To … 集計終了年 - Row Background Color … 行タイトルの背景色 - Col Background Color … 列タイトルの背景色 - Base Text Color … テキストカラー - Background Color … 背景色 - Border Color … 区切り線の色 - Location … 配置 - Text Size … テキストサイズ - Highlight Threshold … 色変更する確率の閾値、および色 - Display in counter? … 確率ではなく回数表示する場合はチェックする
Pine Script® Indikator
von Trader_Morry
Donchian Channels StrengthTL;DR - A different approach calculating strength based on Donchain channels My approach calculating strength by using the difference between price and donchain average. It is possible to use the highest/lowest value of a given source (like close) or to use the highest high/lowest low (by using the option 'include wicks') for the strength calculation I added multiple moving averages which can be used in the calculations incl. SMMA (RMA) which is used in RSI calculation and works best for me. Usage is similar to RSI: DC Strength oscillates between 0 and 100. Low values (<20) indicate a bearish situation while high values (>80) indicate bullish ones. Center line (50) crossings can also indicate a possible trend change.
Pine Script® Indikator
von Daniel_Ge
4
Bull Bear Power with Optional Normalization FunctionThis indicator is designed to provide traders with insights into market sentiment and potential trend reversals. This indicator enhances the traditional Bull Bear Power (BBP) by adding valuable visualizations and customization options to assist traders in making informed trading decisions. Indicator Overview: The NBBP indicator calculates Bull Bear Power, which measures the strength of bullish and bearish forces in the market. It does so by taking the difference between the high and the exponential moving average (EMA) of the closing price for a specified length. This raw BBP is represented on the chart as a line. Key Features: -- Zero Line : The NBBP indicator introduces a central reference line at zero. This line serves as a pivotal point for interpreting market sentiment. When the BBP line is above zero, it is colored green, indicating a predominance of bullish sentiment. Conversely, when the BBP line is below zero, it turns red, signaling a prevalence of bearish sentiment. This coloration helps traders quickly identify shifts in market sentiment. -- OPTIONAL Normalization Function : One of the standout features of the NBBP indicator is its optional normalization function. When activated in the settings menu, this function scales the BBP values from -1 to +1. This means that BBP values are adjusted to fit within a standardized range, making it easier for traders to compare sentiment across different timeframes or assets. Normalization is particularly valuable for identifying extreme sentiment conditions and potential reversals. -- Moving Average : To provide additional context and smooth out BBP fluctuations, the indicator includes an exponential moving average (EMA). The EMA of BBP is plotted on the chart as a white line. Traders can use this moving average to identify trends and potential trend reversals. -- Fill Between Lines : The indicator visually enhances the BBP by filling the area between the BBP line and the zero line with a translucent color. This fill helps traders visualize the strength and duration of bullish or bearish sentiment. Interpretation: -- BBP Line : Traders can assess the raw BBP line for shifts in sentiment. When the line crosses above zero, it may suggest a shift from bearish to bullish sentiment, potentially indicating a buying opportunity. Conversely, when the line crosses below zero, it may signal a shift from bullish to bearish sentiment, suggesting a potential selling opportunity. -- Normalization Function : The optional normalization function allows traders to gauge sentiment on a standardized scale. Values above 0 indicate bullish sentiment, while values below 0 suggest bearish sentiment. The closer the values are to their polar ends (-1 or +1), the stronger the sentiment. -- Moving Average : The EMA of BBP helps identify trends. When BBP crosses above the EMA, it may indicate a strengthening bullish trend, while a crossover below the EMA may suggest a bearish trend. Customization: The NBBP indicator provides traders with flexibility through customizable settings. Users can adjust the BBP length, EMA length, and choose to activate or deactivate the normalization function based on their trading preferences and strategy. Limitations: The NBBP indicator is most effective when used in conjunction with other technical analysis tools and market context. Traders should consider multiple factors when making trading decisions. Normalization function results may vary depending on the chosen length and market conditions. If the desired result is not achieved through default settings, try changing timeframes or toggling on/off the normalization function. Users should exercise caution and combine it with other indicators and analysis techniques. In conclusion, the NBBP indicator is a versatile tool that empowers traders to assess market sentiment, identify potential reversals, and follow trends. Its intuitive visualizations, normalization function, and customizable settings make it a valuable addition to any trader's toolkit.
Pine Script® Indikator
von LeafAlgo
2
Balance of Force (BOF)The script "Balance of Force" is an indicator that aims to provide insight into the bullish and bearish forces present in the market by analyzing the relationship between bullish and bearish true ranges. The indicator first calculates the bearish and bullish true ranges by taking the absolute difference between the open and close prices for each period and summing these values over a user-specified length. It then calculates the ratio of the bullish true range to the bearish true range and takes the natural logarithm of this value, resulting in the "bullish-bearish ratio". The script then calculates the standard deviation of this ratio over a user-specified length to create a measure of volatility. Using this deviation and the dominant cycle, it then applies an exponential moving average to smooth the ratio. The indicator plots the smoothed ratio, the raw ratio, and the deviation of the ratio multiplied by 1, 2 and 3 in addition to filling the area between the deviation multiplied by 3 and the log(1) with red and green. The user can use the indicator to identify potential bullish or bearish market conditions by analyzing the relationship between the smoothed ratio and the log(1) and the deviation of the ratio.
Pine Script® Indikator
von The_Peaceful_Lizard
Stock Market Emotion Index (SMEI)Implementation of Charlie Q. Yang's research paper “The stock market emotion index”, subtitle “A New Sentiment Measure Using Enhanced OBV and Money Flow Indicators”, (2007) where he combined “five simple emotion statistics” - Close Emotion Statistic (CES), Money Flow Statistic (MFS), Supply Demand Statistic (SDS), Relative Strength Statistic (RSS), and Psychological Level Statistic (PLS) - into one indicator. Quotations: “The index calculation is solely based on observed short term market volatility as reflected by each day’s trading volume, open, high, low, and close prices” “The basic premise of Dow theory is that the market discounts everything, including the emotions of all traders. The fundamentals of a company do not change suddenly when its daily stock price is fluctuating as driven by human emotions that are often irrational. However, over a longer time period, a company's fundamentals do change. Again, different types of human emotions, triggered by the flow of material events, are moving the stock price trend up or down. This paper summarizes the author’s attempt in understanding primary trend extent and duration by proposing a new sentiment measure using statistical analysis of stock market human emotion.” Even though “indicator is intended for identifying primary trend cycles that typically last one year or longer“ where Mr. Yang used a fixed averaging length of 260 days and only days as time frame, my implementation has been changed slightly to accommodate for all time frames and to adapt faster using shorter averaging (timeframe dependent). How to use it: Positive values indicating a bullish trend and negative values indicating a bearish trend. Background color is set to green or red accordingly. Positive and negative bar to bar changes are indicated with green and red to show bar to bar (ultra short term) trends. (No financial advise, use for testing purposed only)
Pine Script® Indikator
von Lantzwat
Tilson Bull-Bear-MarkerThe Tilson Bull-Bear marker is using 2 Tilson moving averages and their divergence to identify bull and bear trends and reversals (potential entry or exit points). How to use it: Fast T3 (thick line) above thin line / solid blue fill color = ongoing bull trend Slow T3 (thin line) above thick line / solid red fill color = ongoing bear trend Shrinking or expanding divergence between the lines = trend is getting hotter or cooling down Fast T3 (thick line) changes color from blue to red = potential trend reversal from bullish to bearish Fast T3 (thick line) changes color from red to blue = potential trend reversal from bearish to bullish (No financial advise, for testing purposes only)
Pine Script® Indikator
von Lantzwat
5
Combo 2/20 EMA & Bull And Bear Balance This is combo strategies for get a cumulative signal. First strategy This indicator plots 2/20 exponential moving average. For the Mov Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met. Second strategy This new indicator analyzes the balance between bullish and bearish sentiment. One can cay that it is an improved analogue of Elder Ray indicator. To get more information please see "Bull And Bear Balance Indicator" by Vadim Gimelfarb. WARNING: - For purpose educate only - This script to change bars colors.
Pine Script® Strategie
von HPotter
1
Trend ExplorerAre we in a bull or a bear market? From the technical analysis point of view, the answer is "It depends". It depends from the parameters of your indicator, the timeframe of the pair you are looking and the volatility of that specific market you are looking to. After I experimented with various trending indicators I decided to develop a framework that potentially could "embed" already existing logic from well known indicators (e.g. Supertrend OTT etc.). The most important part is that I managed to abstract that logic away and experiment even further to produce some more robust, market and timeframe resolution agnostic results. While at the same time I was able to switch between market and timeframe resolution specific configuration to take some decision. Finally, I decided to share this code with you folks! Developed this indicator "Trend Explorer" in an effort to make the aforementioned abstraction of all those trending indicators. The goal is to enable the user to explore and combine different approaches in order to create a more robust and market general/specific, timeframe resolution invariant/fluctuating and volatility auto/manual adjusted indicator according to his needs. The logic behind the abstraction is fairly simple. The trending indicator consists of two boundary lines the "bull trend low boundary" (green) and the "bear trend high boundary" (red). The indicator also has a control line (orange). Every time the control line crosses a boundary there is a trend reversal! The boundary lines are defined by the thresholds. To be more precise, boundaries are pulled upwards by thresholds (blue) during a bull market and downwards during a bear market. I challenge the user to experiment with the different ways of calculating the thresholds and the control. I am open to suggestions that might improve and extend the possibilities of this indicator. Any feedback, comments, general thoughts or bug reports are welcome. Why did I chose those defaults? For threshold calculation I chose MINMAX which calculates the local minimum and maximum using a sliding window. As far as I know it is not used in any existing trending indicator, but it seems reasonable for a trader to search for local min and max to make a decision. The width of the sliding window a.k.a the "period to remember" the local min and max is 30 days by default, just because I believe that for regular people it is a reasonable period of time to forget too. Also, compared to the SUBADD method MINMAX does not seem to lag behind, especially when using averages in the SUBADD mode. Moreover, I consider MINMAX to be more general than the margins used by the SUBADD since margins should be configured based on the underlying market volatility. For a source of min and max I chose the low and high values just because they are timeframe resolution invariant, meaning that they have the same (not exactly due to number precision and rounding, but very close) results for a single pair whether you use "4 hour" or "1 day" time interval! Another popular choice might be (close, close) since many traders wait for the daily candle to close in order to discard outliers. However, this approach is not resolution invariant and it depends from the time interval the user has selected. Do you have any interesting trending indicator you would like to see how it performs in this framework logic? Let me know! Do you have in mind any variation of Control or Thresholds calculation you would like to test? Please describe it in the comments below so I can add it in my implementation for you! Did you find any other bug or you experienced any strange behavior? PM me with a description of the bug, the trading pair the timeframe resolution the exact time (candle) and all the necessary configurations for this indicator so I can reproduce it on my machine! Please enjoy with caution, Jason
Pine Script® Indikator
von jason5480
12
Bull Bear Power1. Calculate * Base on RSI status in the same period of price bar, "Bull Bear Power" is counting number of bars moved above 70 then return result to "bull power" series, and counting number of bars moved below 30 then return result to "bear power" series. * By default RSI period is 2 and Bar period is 15. 2. Interface * Bull power: green columns. * Bear power: red columns. * Info Line: show info of RSI and Bull Bear Power - Bull Bear Power info: Period, Bull value, Bear value - RSI info: RSI value, RSI status: overbought (>70), oversold(<30), crossunder 70, crossover 30. 3. Trade: * Consider place Long oder when Bull power increase from below to above Bear power * Consider place Short oder when Bear power increase from below to above Bull power
Pine Script® Indikator
von inno14
4
[blackcat] L2 Bull Bear Convergence Divergence (BBCD)Level: 2 Background A bull market is gaining ground and is economically sound, while a bear market is declining and most stocks are depreciating. The actual origins of these terms are unclear, but one reason could be that bulls attack by pulling their horns up while bears attack by brushing their paws down. Function L2 Bull Bear Convergence Divergence (BBCD) disclose the convergence divergence of the bull bear as a market opinion indicator. It tells you the opinion of those who are directly involved with the markets. As a trader, understanding how the convergence divergence of the bull bear works can be of great help. I inherited the traditional MACD expression method, and added golden cross (yellow cross) and dead cross (fuchsia cross) prompts, as well as bottom divergence (lime cross) and top divergence (red cross) prompts. Key Signal bbd --> bull bear fast line bbdsupport --> bull bear slow line and support level bbdgx --> bull bear gold cross in yellow bbddx --> bull bear dead cross in fuchsia bbotdiverg --> bull bear bottom divergence alert in lime cross btopdiverg --> bull bear top divergence alert in red cross Pros and Cons Pros: 1. it can help to see the strength change of a trend in time 2. visual bottom and top divergence alerts are provided Cons: 1. it disclose the strength change better than price change Remarks Bull Bear Convergence Divergence (BBCD) is new. Readme In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts. The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works. Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element. Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level. Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated. Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop. Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Pine Script® Indikator
von blackcat1402
3