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Dynamic Support and Resistance with Trend Lines Dynamic Support and Resistance with Trend Lines (DSRTL) 1. Introduction & Methodology The DSRTL indicator is designed to provide a multidimensional analysis of market structure. Unlike traditional tools that rely solely on price pivots, this script combines Static Volume-based Zones with Dynamic Trend Lines to evaluate the price's position relative to critical market components. The S/R Identification Technique Instead of standard pivot points, DSRTL utilizes Volume Analysis to highlight areas of significant trader participation: - Strategy A: Matrix Climax: Identifies candles within the lookback period that are near price extremes (Highs/Lows) and coincide with significant buying or selling volume. - Strategy B: Volume Extremes: Detects candles with the absolute highest buy/sell volumes within the selected lookback window, creating extreme volume-based S/R zones. - Result: This creates Support/Resistance (S/R) zones that are validated by actual market activity, not just price geometry. Dynamic Trend Lines To complement the static zones, the indicator employs two adaptive channel methods: - Pivot Span: Connects recent significant pivots for a fast, reactive trend corridor. - 5-Point Channel: Segments the lookback period into 5 parts to perform a linear regression analysis, creating a stable and statistically significant channel. 2. Volume Calculation Methodology Accurate S/R detection requires distinguishing Buy Volume from Sell Volume. DSRTL offers two calculation modes: - Geometry (Source File): Estimates buy/sell volume based on the Close price's position relative to the High/Low of the candle. Note: This is an approximation that works on all plan types as it does not require intrabar data. - Intrabar (Precise): Analyzes historical lower-timeframe data (e.g., 15S) to calculate intrabar-based volume deltas with higher precision compared to the geometric method. Note: This offers superior accuracy. It requires access to historical intrabar data (depending on your plan limits). For the best analytical results, use this mode if available. 3. The Smart Matrix Engine (3D Analysis) The core of DSRTL is its dashboard, powered by the "Smart Matrix Engine." This engine evaluates the current price in a multi-layer market structure context (Static Volume Zones + Dynamic Channels + Volume Metrics).: A. S-State (Static): Where is the price relative to the Volume S/R zones? B. D-State (Dynamic): Where is the price relative to the Trend Channels? How to read the Matrix Map: The dashboard displays a 5x5 grid representing 25 possible market scenarios. - Rows (S1-S5): Represent the Static State (S1=Breakout, S3=Mid-Range, S5=Breakdown). - Columns (D1-D5): Represent the Dynamic State (D1=Overextended Up, D3=Neutral, D5=Overextended Down). - Active Cell: Marked with a dot, indicating the specific intersection of price action and market structure. 4. Matrix Interpretations (The 25 Scenarios) Below is the detailed logic for every possible state displayed on the dashboard, explaining the Title, Bias, and actionable Signal. Section I: S1 - Static Breakout (Price > Static Resistance) The price has cleared the static volume resistance zone. - S1 / D1: HYPER EXTENSION Bias: Extreme Bullish Signal: Caution: Exhaustion Risk. Trail stops tight. - S1 / D2: RESISTANCE CLASH Bias: Bullish Signal: Breakout confirmed but facing immediate dynamic resistance. - S1 / D3: CHANNEL BREAKOUT Bias: Strong Bullish Signal: Ideal Trend Continuation. Look to buy dips. - S1 / D4: SMART PULLBACK Bias: Bullish (Pullback) Signal: A pullback occurring after a breakout. Strong buy opportunity. - S1 / D5: CONFLICT (DIV) Bias: Conflict/Reversal Signal: Major Divergence. Static breakout is failing against dynamic structure. High Risk. Section II: S2 - Inside Static Resistance The price is currently testing the overhead resistance zone. - S2 / D1: WEAK SPIKE Bias: Neutral/Bullish Signal: Testing resistance, but short-term overextended. - S2 / D2: IRON FORTRESS (R) Bias: Rejection Risk Signal: Double Resistance (Static + Dynamic). High probability of rejection. - S2 / D3: TESTING RES Bias: Neutral Signal: Consolidating at resistance. Wait for a clear break or rejection. - S2 / D4: COMPRESSION (UP) Bias: Conflict (Squeeze) Signal: Squeezed between Static Resistance and Dynamic Support. Volatility imminent. - S2 / D5: RES vs DOWN-TREND Bias: Bearish Signal: Strong downtrend meeting static resistance. Potential Short entry. Section III: S3 - Mid-Range The price is floating between significant Static Support and Resistance. - S3 / D1: OVERBOUGHT RANGE Bias: Rejection Risk (OB) Signal: Overextended within the range. Potential fade (short). - S3 / D2: RANGE HIGH LIMIT Bias: Neutral/Bearish Signal: At the top of the dynamic channel. Look for rejection signs. - S3 / D3: NEUTRAL / CHOPPY Bias: Neutral Signal: Dead Center. Low probability environment. Avoid trading. - S3 / D4: RANGE DIP BUY Bias: Neutral/Bullish Signal: At the bottom of the dynamic channel. Look for bounce signs. - S3 / D5: WEAK RANGE (OS) Bias: Bounce Risk (OS) Signal: Oversold within the range. Potential fade (long). Section IV: S4 - Inside Static Support The price is currently testing the floor support zone. - S4 / D1: SUP vs UP-TREND Bias: Bullish Signal: Strong uptrend meeting static support. Potential Long entry. - S4 / D2: COMPRESSION (DN) Bias: Conflict (Squeeze) Signal: Squeezed between Static Support and Dynamic Resistance. Volatility imminent. - S4 / D3: TESTING SUPPORT Bias: Neutral Signal: Consolidating at support. Wait for a bounce or breakdown. - S4 / D4: IRON FLOOR (S) Bias: Bounce Risk Signal: Double Support (Static + Dynamic). High probability of a bounce. - S4 / D5: WEAK DIP Bias: Neutral/Bearish Signal: Testing support, but short-term oversold. Section V: S5 - Static Breakdown (Price < Static Support) The price has dropped below the static volume support zone. - S5 / D1: CONFLICT (DIV) Bias: Conflict/Reversal Signal: Major Divergence. Static breakdown is failing. High Risk. - S5 / D2: BEAR PULLBACK Bias: Bearish (Pullback) Signal: A pullback occurring after a breakdown. Strong selling opportunity. - S5 / D3: CHANNEL BREAKDOWN Bias: Strong Bearish Signal: Ideal Trend Continuation (Down). Sell rallies. - S5 / D4: SUPPORT CLASH Bias: Bearish Signal: Breakdown confirmed but facing immediate dynamic support. - S5 / D5: HYPER DROP (VOID) Bias: Extreme Bearish Signal: Caution: Climax risk. Trail stops for shorts. DISCLAIMER & EDUCATIONAL PURPOSE This indicator is strictly an educational tool designed to visualize complex market structure concepts. Its primary purpose is to help traders "bridge the gap" between academic theory and real-time market behavior by providing a visual representation of support, resistance, and volume dynamics. Please Note: 1. Not a Trading Strategy: This script is an analytical assistant, not a standalone "Black Box" trading system. It does not generate buy or sell signals that should be followed blindly. 2. No Financial Advice: The data provided by this tool is for informational purposes only. It is not a recommendation to buy or sell any asset. 3. Risk Warning: Trading involves significant risk. Always use your own judgment, perform your own technical analysis, and use proper risk management. Do not use this tool as the sole basis for your trading decisions. 4. Data Precision & Platform Limits: The "Intrabar (Precise)" calculation mode relies on high-resolution historical data to provide exact results. Access to this specific data depth depends entirely on your platform's subscription capabilities. If your plan does not support this level of historical intrabar data, the Precise mode may have limited coverage. In that case, you should switch to "Geometry" mode for a fully populated view.

Multi Timeframe Bollinger Bands Spectrum [Ata]Multi-Timeframe Bollinger Bands Spectrum Technical Overview This script integrates multi-timeframe volatility analysis with volume-derived order flow estimation. By combining Bollinger Bands (statistical deviation) with internal candle volume logic, the indicator qualifies price movements to differentiate between sustained trends, reversals, and exhaustion events. The system is designed to provide a structural context for price action, visualizing market regimes through a dual-zone spectrum and filtering signals based on the interaction between price location and specific volume thresholds. Core Logic & Calculation 1. Volume Decomposition Algorithm Instead of using total volume, the script estimates Buying Pressure vs. Selling Pressure based on the close position relative to the candle's High/Low range: - Buying Volume (vb): Increases as the close approaches the High. - Selling Volume (vs): Increases as the close approaches the Low. This logic allows the detection of directional flow even within standard volume bars. 2. Statistical Spectrum The indicator renders deviations from the Basis (SMA) as two distinct zones: - Bullish Zone (Blue): Price positioning between the Basis and Upper Band. - Bearish Zone (Red): Price positioning between the Basis and Lower Band. This structure is applied across multiple timeframes (overlay) to visualize the macro trend context without noise. 3. Non-Repainting Execution To ensure historical accuracy and reliability for backtesting, all higher-timeframe data is requested using "lookahead_off". Signals are confirmed only upon the closure of the respective timeframe's candle. Signal Definitions Signals are generated only when specific Volatility and Volume conditions intersect: Reversal Setups (Reaction to Liquidity) - WALL: Triggered when price rejects the Upper Band accompanied by Extreme Selling Volume (vs > Limit). This suggests active limit sell orders absorbing the rally. - FLOOR: Triggered when price rejects the Lower Band accompanied by Extreme Buying Volume (vb > Limit). This suggests active limit buy orders absorbing the drop. - ABSORP: Identifies absorption near the lower bands where selling pressure is met with passive buying (indicated by lower wicks and relative buy volume). Momentum Setups (Trend Continuation) - POWER: Validates a breakout above the Upper Band only if supported by Dominant Buying Volume and a strong candle body. - PANIC: Validates a breakdown below the Lower Band only if supported by Dominant Selling Volume. - TRAP: Marks failed breakouts where price exits the bands but volume analysis contradicts the move (e.g., low directional volume). Exhaustion Setups (Statistical Extremes) - CLIMAX/CRASH: Identifies anomalies where price deviates significantly from the mean (Extreme Deviation) or when volume reaches unsustainable levels relative to the average, often preceding a mean reversion. Input Parameters - Bollinger Logic: Configuration for Length and Standard Deviation Multiplier. - Volume Thresholds: Adjustable factors for Minimum Volume (Trend) and Extreme Volume (Reversal/Climax). - Timeframe Layers: Toggle visibility for up to 5 higher timeframes. - Theme: Adjusts label contrast for Dark/Light backgrounds. Disclaimer This indicator is strictly for analytical purposes. It provides a visualization of past market data based on statistical and volumetric formulas. Users should apply their own risk management protocols.

Smart Money Volume Matrix [Ata]Smart Money Volume Matrix The Smart Money Volume Matrix (SMV Matrix) is an advanced volume-spread analysis (VSA) dashboard and charting tool designed to identify significant market anomalies by analyzing the relationship between price extremes and volume flow. Unlike traditional indicators that rely solely on moving averages or oscillators, this tool performs a "Snapshot Analysis" of a defined lookback period (default: 100 bars) to rank price action based on Order Flow Dominance. It isolates the Top 10 Highest and Lowest Close prices and scrutinizes the volume behind them to categorize market sentiment into four distinct phases: Distribution, No Demand, Absorption, and Exhaustion. Core Logic & Methodology The script operates on a Zero-Lag Snapshot Engine. It does not print historical signals bar-by-bar; instead, it evaluates the current market structure relative to the recent history (Lookback Period). 1. Ranking Engine: The script scans the lookback period to find the Top 10 Highest Closes and Top 10 Lowest Closes. 2. Volume Classification: For each ranked bar, it calculates the "Intrabar Buy/Sell Volume" (or approximates it using candle geometry if Intrabar data is unavailable). 3. Dominance Detection: It compares Buying Volume vs. Selling Volume to determine who is in control at critical price levels. Signal Classifications (VSA Logic) The indicator generates labels on the chart and updates the dashboard table based on the following logic: 1. At Price Tops (Resistance Areas): - Distribution (Supply): High Price + High Total Volume + Sellers Dominant. Interpretation: Indicates heavy institutional selling into rising prices. Often precedes a reversal. - Buy Climax: High Price + High Total Volume + Buyers Dominant. Interpretation: Extreme buying frenzy. While bullish, it often marks a "trap" or temporary top due to exhaustion. - No Demand: High Price + Low Volume. Interpretation: Prices drifted higher but lack institutional participation. A sign of weakness. 2. At Price Bottoms (Support Areas): - Absorption: Low Price + High Total Volume + Buyers Dominant. Interpretation: Institutional money is absorbing selling pressure (passive buying). A strong sign of accumulation. - Panic Sell: Low Price + High Total Volume + Sellers Dominant. Interpretation: Extreme fear. High volume at lows typically indicates capitulation and potential hands-changing. - Exhaustion: Low Price + Low Volume. Interpretation: Selling pressure has dried up. The market may float upward due to lack of sellers. Key Features - Dashboard Matrix Table: Displays the exact Close Price, Buy/Sell Volume, and Market State (Group) for the Top 10 ranking bars. Smart Footer: Automatically detects the active "Resistance Zone" (derived from G1 Distribution levels) and "Support Zone" (derived from G3 Absorption levels) and reports the current price status relative to these zones (e.g., "Testing Resistance", "Breakout", "At Support"). - Smart Zones (Auto S/R): Automatically draws Support and Resistance boxes extending into the future based on the most significant volume clusters found in the rankings. Includes logic to detect "Flips" (e.g., when Support breaks, it is labeled as a flip to Resistance). - Average Trend Channels: Calculates a Linear Regression trend line based specifically on the coordinates of the Top 10 Highs and Top 10 Lows, providing a "Best Fit" channel for the current market structure. - Visual Clarity: Labels utilize a "Smart Stacking" algorithm to prevent overlap on the chart. Guide lines connect labels to their respective candles for precise identification. Settings & Configuration - Matrix Settings: Lookback Period (default 100 bars) and Top Rank Count. - Volume Engine: Choose between "Intrabar (Precise)" for accurate order flow or "Geometry (Approx)" for standard volume estimation. - Visuals: Toggle Table, Labels, Lines, Zones, and Trend Lines. Adjust transparency and font sizes. IMPORTANT NOTE ON SNAPSHOT LOGIC This indicator is designed as a Real-Time Dashboard. It continuously updates the "Top 10" list as new candles form. Therefore, a label that appears on a candle may disappear if that candle falls out of the Top 10 ranking or leaves the lookback window. This is intended behavior to ensure the chart always reflects the current most critical levels, rather than a historical record of past signals. It is best used for live market analysis rather than historical back testing. Disclaimer: This tool is for educational and analytical purposes only. Volume analysis is subjective and should be used in conjunction with other methods of technical analysis.

Trend Line Methods (TLM)Trend Line Methods (TLM) Overview Trend Line Methods (TLM) is a visual study designed to help traders explore trend structure using two complementary, auto-drawn trend channels. The script focuses on how price interacts with rising or falling boundaries over time. It does not generate trade signals or manage risk; its purpose is to support discretionary chart analysis. Method 1 – Pivot Span Trendline The Pivot Span Trendline method builds a dynamic channel from major swing points detected by pivot highs and pivot lows. • The script tracks a configurable number of recent pivot highs and lows. • From the oldest and most recent stored pivot highs, it draws an upper trend line. • From the oldest and most recent stored pivot lows, it draws a lower trend line. • An optional filled area can be drawn between the two lines to highlight the active trend span. As new pivots form, the lines are recalculated so that the channel evolves with market structure. This method is useful for visualising how price respects a trend corridor defined directly by swing points. Method 2 – 5-Point Straight Channel The 5-Point Straight Channel method approximates a straight trend channel using five key points extracted from a fixed lookback window. Within the selected window: • The window is divided into five segments of similar length. • In each segment, the highest high is used as a representative high point. • In each segment, the lowest low is used as a representative low point. • A straight regression-style line is fitted through the five high points to form the upper boundary. • A second straight line is fitted through the five low points to form the lower boundary. The result is a pair of straight lines that describe the overall directional channel of price over the chosen window. Compared to Method 1, this approach is less focused on the very latest swings and more on the broader slope of the market. Inputs & Menus Pivot Span Trendline group (Method 1) • Enable Pivot Span Trendline – Turns Method 1 on or off. • High trend line color / Low trend line color – Colors of the upper and lower trend lines. • Fill color between trend lines – Base color used to shade the area between the two lines. Transparency is controlled internally. • Trend line thickness – Line width for both high and low trend lines. • Trend line style – Line style (solid, dashed, or dotted). • Pivot Left / Pivot Right – Number of bars to the left and right used to confirm pivot highs and lows. Larger values produce fewer but more significant swing points. • Pivot Count – How many historical pivot points are kept for constructing the trend lines. • Lookback Length – Number of bars used to keep pivots in range and to extend the trend lines across the chart. 5-Point Straight Channel group (Method 2) • Enable 5-Point Straight Channel – Turns Method 2 on or off. • High channel line color / Low channel line color – Colors of the upper and lower channel lines. • Channel line thickness – Line width for both channel lines. • Channel line style – Line style (solid, dashed, or dotted). • Channel Length (bars) – Lookback window used to divide price into five segments and build the straight high/low channel. Using Both Methods Together Both methods are designed to visualise the same underlying idea: price tends to move inside rising or falling channels. Method 1 emphasises the most recent swing structure via pivot points, while Method 2 summarises the broader channel over a fixed window. When the Pivot Span Trendline corridor and the 5-Point Straight Channel boundaries align or intersect, they can highlight zones where multiple ways of drawing trend lines point to similar support or resistance areas. Traders can use these confluence zones as a visual reference when planning their own entries, exits, or risk levels, according to their personal trading plan. Notes • This script is meant as an educational and analytical tool for studying trend lines and channels. • It does not generate trading signals and does not replace independent analysis or risk management. • The behaviour of both methods is timeframe- and symbol-agnostic; they will adapt to whichever chart you apply them to.

Smart Money Dynamics Blocks - Pearson Matrix Smart Money Dynamics Blocks — Pearson Matrix A structural fusion of Prime Number Theory, Pearson Correlation, and Cumulative Delta Geometry. 1. Mathematical Foundation This indicator is built on the intersection of Prime Number Theory and the Pearson correlation coefficient, creating a structural framework that quantifies how price and time evolve together. Prime numbers — unique, indivisible, and irregular — are used here as nonlinear time intervals. Each prime length (2, 3, 5, 7, 11…97) represents a regression horizon where correlation is measured between price and time. The result is a multi-scale correlation lattice — a geometric matrix that captures hidden directional strength and temporal bias beyond traditional moving averages. 2. The Pearson Matrix Logic For every prime interval p, the indicator calculates the linear correlation: r_p = corr(price, bar_index, p) Each r_p reflects how closely price and time move together across a prime-defined window. All r_p values are then averaged to create avgR, a single adaptive coefficient summarizing overall structural coherence. - When avgR > 0.8 → strong positive correlation (labeled R+). - When avgR < -0.8 → strong negative correlation (labeled R−). This approach gives a mathematically grounded definition of trend — one that isn’t based on pattern recognition, but on measurable correlation strength. 3. Sequential Prime Slope and Median Pivot Using the ordered sequence of 25 prime intervals, the model computes sequential slopes between adjacent primes. These slopes represent the rate of change of structure between two prime scales. A robust median aggregator smooths the slopes, producing a clean, stable directional vector. The system anchors this slope to the 41-bar pivot — the median of the first 25 primes — serving as the geometric midpoint of the prime lattice. The resulting yellow line on the chart is not an ordinary regression line; it’s a dynamic prime-slope function, adapting continuously with correlation feedback. 4. Regression-Style Parallel Bands Around this prime-slope line, the indicator constructs parallel bands using standard deviation envelopes — conceptually similar to a regression channel but recalculated through the prime–Pearson matrix. These bands adjust dynamically to: - Volatility, via standard deviation of residuals. - Correlation strength, via avgR sign weighting. Together, they visualize statistical deviation geometry, making it easier to observe symmetry, expansion, and contraction phases of price structure. 5. Volume and Cumulative Delta Peaks Below the geometric layer, the indicator incorporates a custom lower-timeframe volume feed — by default using 15-second data (custom_tf_input_volume = “15S”). This allows precise delta computation between up-volume and down-volume even on higher timeframe charts. From this feed, the indicator accumulates delta over a configurable period (default: 100 bars). When cumulative delta reaches a local maximum or minimum, peak and trough markers appear, showing the precise bar where buying or selling pressure statistically peaked. This combination of geometry and order flow reveals the intersection of market structure and energy — where liquidity pressure expresses itself through mathematical form. 6. Chart Interpretation The primary chart view represents the live execution of the indicator. It displays the relationship between structural correlation and volume behavior in real time. Orange “R+” and blue “R−” labels indicate regions of strong positive or negative Pearson correlation across the prime matrix. The yellow median prime-slope line serves as the structural backbone of the indicator, while green and red parallel bands act as dynamic regression boundaries derived from the underlying correlation strength. Peaks and troughs in cumulative delta — displayed as numerical annotations — mark statistically significant shifts in buying and selling pressure. The secondary visualization (Prime Regression Concept) expands on this by illustrating how regression behavior evolves across prime intervals. Each colored regression fan corresponds to a prime number window (2, 3, 5, 7, …, 97), demonstrating how multiple regression lines would appear if drawn independently. The indicator integrates these into one unified geometric model — eliminating the need to plot tens of regression lines manually. It’s a conceptual tool to help visualize the internal logic: the synthesis of many small-scale regressions into a single coherent structure. 7. Interpretive Insight This model is not a prediction tool; it’s an instrument of mathematical observation. By translating price dynamics into a prime-structured correlation space, it reveals how coherence unfolds through time — not as a forecast, but as a measurable evolution of structure. It unifies three analytical domains: - Prime distribution — defines a nonlinear temporal architecture. - Pearson correlation — quantifies statistical cohesion. - Cumulative delta — expresses behavioral imbalance in order flow. The synthesis creates a geometric analysis of liquidity and time — where structure meets energy, and where the invisible rhythm of market flow becomes measurable. 8. Contribution & Feedback Share your observations in the comments: - The time gap and alternation between R+ and R− clusters. - How different timeframes change delta sensitivity or reveal compression/expansion. - Prime intervals/clusters that tend to sit near turning points or liquidity shifts. - How avgR behaves across assets or regimes (trending, ranging, high-vol). - Notable interactions with the parallel bands (touches, breaks, mean-revert). Your field notes help others read the model more effectively and compare contexts. Summary - Primes define the structure. - Pearson quantifies coherence. - Slope median stabilizes geometry. - Regression bands visualize deviation. - Cumulative delta locates imbalance. Together, they construct a framework where mathematics meets market behavior.

ATAI Volume Pressure Analyzer V 1.0 — Pure Up/Down ATAI Volume Pressure Analyzer V 1.0 — Pure Up/Down Overview Volume is a foundational tool for understanding the supply–demand balance. Classic charts show only total volume and don’t tell us what portion came from buying (Up) versus selling (Down). The ATAI Volume Pressure Analyzer fills that gap. Built on Pine Script v6, it scans a lower timeframe to estimate Up/Down volume for each host‑timeframe candle, and presents “volume pressure” in a compact HUD table that’s comparable across symbols and timeframes. 1) Architecture & Global Settings Global Period (P, bars) A single global input P defines the computation window. All measures—host‑TF volume moving averages and the half‑window segment sums—use this length. Default: 55. Timeframe Handling The core of the indicator is estimating Up/Down volume using lower‑timeframe data. You can set a custom lower timeframe, or rely on auto‑selection: ◉ Second charts → 1S ◉ Intraday → 1 minute ◉ Daily → 5 minutes ◉ Otherwise → 60 minutes Lower TFs give more precise estimates but shorter history; higher TFs approximate buy/sell splits but provide longer history. As a rule of thumb, scan thin symbols at 5–15m, and liquid symbols at 1m. 2) Up/Down Volume & Derived Series The script uses TradingView’s library function tvta.requestUpAndDownVolume(lowerTf) to obtain three values: ◉ Up volume (buyers) ◉ Down volume (sellers) ◉ Delta (Up − Down) From these we define: ◉ TF_buy = |Up volume| ◉ TF_sell = |Down volume| ◉ TF_tot = TF_buy + TF_sell ◉ TF_delta = TF_buy − TF_sell A positive TF_delta indicates buyer dominance; a negative value indicates selling pressure. To smooth noise, simple moving averages of TF_buy and TF_sell are computed over P and used as baselines. 3) Key Performance Indicators (KPIs) Half‑window segmentation To track momentum shifts, the P‑bar window is split in half: ◉ C→B: the older half ◉ B→A: the newer half (toward the current bar) For each half, the script sums buy, sell, and delta. Comparing the two halves reveals strengthening/weakening pressure. Example: if AtoB_delta < CtoB_delta, recent buying pressure has faded. [ 4) HUD (Table) Display /i] Colors & Appearance Two main color inputs define the theme: a primary color and a negative color (used when Δ is negative). The panel background uses a translucent version of the primary color; borders use the solid primary color. Text defaults to the primary color and flips to the negative color when a block’s Δ is negative. Layout The HUD is a 4×5 table updated on the last bar of each candle: ◉ Row 1 (Meta): indicator name, P length, lower TF, host TF ◉ Row 2 (Host TF): current ↑Buy, ↓Sell, ΔDelta; plus Σ total and SMA(↑/↓) ◉ Row 3 (Segments): C→B and B→A blocks with ↑/↓/Δ ◉ Rows 4–5: reserved for advanced modules (Wings, α/β, OB/OS, Top 5) Advanced Modules 5.1 Wings “Wings” visualize volume‑driven movement over C→B (left wing) and B→A (right wing) with top/bottom lines and a filled band. Slopes are ATR‑per‑bar normalized for cross‑symbol/TF comparability and converted to angles (degrees). Coloring mirrors HUD sign logic with a near‑zero threshold (default ~3°): ◉ Both lines rising → blue (bullish) ◉ Both falling → red (bearish) ◉ Mixed/near‑zero → gray Left wing reflects the origin of the recent move; right wing reflects the current state. 5.2 α / β at Point B We compute the oriented angle between the two wings at the midpoint B: β is the bottom‑arc angle; α = 360° − β is the top‑arc angle. ◉ Large α (>180°) or small β (<180°) flags meaningful imbalance. ◉ Intuition: large α suggests potential selling pressure; small β implies fragile support. HUD cells highlight these conditions. 5.3 OB/OS Spike OverBought/OverSold (OB/OS) labels appear when directional volume spikes align with a 7‑oscillator vote (RSI, Stoch, %R, CCI, MFI, DeMarker, StochRSI). ◉ OB label (red): unusually high sell volume + enough OB votes ◉ OS label (teal): unusually high buy volume + enough OS votes Minimum votes and sync window are user‑configurable; dotted connectors can link labels to the candle wick. 5.4 Top3 Volume Peaks Within the P window the script ranks the top three BUY peaks (B1–B3) and top three SELL peaks (S1–S3). ◉ B1 and S1 are drawn as horizontal resistance (at B1 High) and support (at S1 Low) zones with adjustable thickness (ticks/percent/ATR). ◉ The HUD dedicates six cells to show ↑/↓/Δ for each rank, and prints the exact High (B1) and Low (S1) inline in their cells. 6) Reading the HUD — A Quick Checklist ◉ Meta: Confirm P and both timeframes (host & lower). ◉ Host TF block: Compare current ↑/↓/Δ against their SMAs. ◉ Segments: Contrast C→B vs B→A deltas to gauge momentum change. ◉ Wings: Right‑wing color/angle = now; left wing = recent origin. ◉ α / β: Look for α > 180° or β < 180° as imbalance cues. ◉ OB/OS: Note labels, color (red/teal), and the vote count. ◉Top3: Keep B1 (resistance) and S1 (support) on your radar. Use these together to sketch scenarios and invalidation levels; never rely on a single signal in isolation. [ 7) Example Highlights (What the table conveys) /i] ◉ Row 1 shows the indicator name, the analysis length P (default 55), and both TFs used for computation and display. ◉ B1 / S1 blocks summarize each side’s peak within the window, with Δ indicating buyer/seller dominance at that peak and inline price (B1 High / S1 Low) for actionable levels. ◉ Angle cells for each wing report the top/bottom line angles vs. the horizontal, reflecting the directional posture. ◉ Ranks B2/B3 and S2/S3 extend context beyond the top peak on each side. ◉ α / β cells quantify the orientation gap at B; changes reflect shifting buyer/seller influence on trend strength. Together these visuals often reveal whether the “wings” resemble a strong, upward‑tilted arm supported by buyer volume—but always corroborate with your broader toolkit 8) Practical Tips & Tuning ◉ Choose P by market structure. For daily charts, 34–89 bars often works well. ◉ Lower TF choice: Thin symbols → 5–15m; liquid symbols → 1m. ◉ Near‑zero angle: In noisy markets, consider 5–7° instead of 3°. ◉ OB/OS votes: Daily charts often work with 3–4 votes; lower TFs may prefer 4–5. ◉ Zone thickness: Tie B1/S1 zone thickness to ATR so it scales with volatility. ◉ Colors: Feel free to theme the primary/negative colors; keep Δ<0 mapped to the negative color for readability. Combine with price action: Use this indicator alongside structure, trendlines, and other tools for stronger decisions. Technical Notes Pine Script v6. ◉ Up/Down split via TradingView/ta library call requestUpAndDownVolume(lowerTf). ◉ HUD‑first design; drawings for Wings/αβ/OBOS/Top3 align with the same sign/threshold logic used in the table. Disclaimer: This indicator is provided solely for educational and analytical purposes. It does not constitute financial advice, nor is it a recommendation to buy or sell any security. Always conduct your own research and use multiple tools before making trading decisions.

Price Statistical Strategy-Z Score V 1.01 Price Statistical Strategy – Z Score V 1.01 Overview A technical breakdown of the logic and components of the “Price Statistical Strategy – Z Score V 1.01”. This script implements a smoothed Z-Score crossover mechanism applied to the closing price to detect potential statistical deviations from local price mean. The strategy operates solely on price data (close) and includes signal spacing control and momentum-based candle filters. No volume-based or trend-detection components are included. Core Methodology The strategy is built on the statistical concept of Z-Score, which quantifies how far a value (closing price) is from its recent average, normalized by standard deviation. Two moving averages of the raw Z-Score are calculated: a short-term and a long-term smoothed version. The crossover between them generates long entries and exits. Signal Conditions Entry Condition: A long position is opened when the short-term smoothed Z-Score crosses above the long-term smoothed Z-Score, and additional entry conditions are met. Exit Condition: The position is closed when the short-term Z-Score crosses below the long-term Z-Score, provided the exit conditions allow. Signal Gapping: A minimum number of bars (Bars gap between identical signals) must pass between repeated entry or exit signals to reduce noise. Momentum Filter: Entries are prevented during sequences of three or more consecutively bullish candles, and exits are prevented during three or more consecutively bearish candles. Z-Score Function The Z-Score is calculated as: Z = (Close - SMA(Close, N)) / STDEV(Close, N) Where N is the base period selected by the user. Input Parameters Enable Smoothed Z-Score Strategy Enables or disables the Z-Score strategy logic. When disabled, no trades are executed. Z-Score Base Period Defines the number of bars used to calculate the simple moving average and standard deviation for the Z-Score. This value affects how responsive the raw Z-Score is to price changes. Short-Term Smoothing Sets the smoothing window for the short-term Z-Score. Higher values produce smoother short-term signals, reducing sensitivity to short-term volatility. Long-Term Smoothing Sets the smoothing window for the long-term Z-Score, which acts as the reference line in the crossover logic. Bars gap between identical signals Minimum number of bars that must pass before another signal of the same type (entry or exit) is allowed. This helps reduce redundant or overly frequent signals. Trade Visualization Table A table positioned at the bottom-right displays live PnL for open trades: Entry Price Unrealized PnL % Text colors adapt based on whether unrealized profit is positive, negative, or neutral. Technical Notes This strategy uses only close prices — no trend indicators or volume components are applied. All calculations are based on simple moving averages and standard deviation over user-defined windows. Designed as a minimal, isolated Z-Score engine without confirmation filters or multi-factor triggers.