Регистрация

Forecasting

Probability Grid [LuxAlgo]The Probability Grid tool allows traders to see the probability of where and when the next reversal would occur, it displays a 10x10 grid and/or dashboard with the probability of the next reversal occurring beyond each cell or within each cell. 🔶 USAGE By default, the tool displays deciles (percentiles from 0 to 90), users can enable, disable and modify each percentile, but two of them must always be enabled or the tool will display an error message alerting of it. The use of the tool is quite simple, as shown in the chart above, the further the price moves on the grid, the higher the probability of a reversal. In this case, the reversal took place on the cell with a probability of 9%, which means that there is a probability of 91% within the square defined by the last reversal and this cell. 🔹 Grid vs Dashboard The tool can display a grid starting from the last reversal and/or a dashboard at three predefined locations, as shown in the chart above. 🔶 DETAILS 🔹 Raw Data vs Normalized Data By default the tool displays the normalized data, this means that instead of using the raw data (price delta between reversals) it uses the returns between each reversal, this is useful to make an apples to apples comparison of all the data in the dataset. This can be seen in the left side of the chart above (BTCUSD Daily chart) where normalize data is disabled, the percentiles from 0 to 40 overlap and are indistinguishable from each other because the tool uses the raw price delta over the entire bitcoin history, with normalize data enabled as we can see in the right side of the chart we can have a fair comparison of the data over the entire history. 🔹 Probability Beyond or Within Each Cell Two different probability modes are available, the default mode is Probability Beyond Each Cell, the number displayed in each cell is the probability of the next reversal to be located in the area beyond the cell, for example, if the cell displays 20%, it means that in the area formed by the square starting from the last reversal and ending at the cell, there is an 80% probability and outside that square there is a 20% probability for the location of the next reversal. The second probability mode is the probability within each cell, this outlines the chance that the next reversal will be within the cell, as we can see on the right chart above, when using deciles as percentiles (default settings), each cell has the same 1% probability for the 10x10 grid. 🔶 SETTINGS Swing Length: The maximum length in bars used to identify a swing Maximum Reversals: Maximum number of reversals included in calculations Normalize Data: Use returns between swings instead of raw price Probability: Choose between two different probability modes: beyond and inside each cell Percentiles: Enable/disable each of the ten percentiles and select the percentile number and line style 🔹 Dashboard Show Dashboard: Enable or disable the dashboard Position: Choose dashboard location Size: Choose dashboard size 🔹 Style Show Grid: Enable or disable the grid Size: Choose grid text size Colors: Choose grid background colors Show Marks: Enable/disable reversal markers
Индикатор Pine Script®
от LuxAlgo
10
SMT Divergence ICT 02 [TradingFinder] Smart Money Technique SMC🔵 Introduction SMT Divergence (Smart Money Technique Divergence) is a price action-based trading concept that detects discrepancies in market behavior between two assets that are generally expected to move in the same direction. Rooted in ICT (Inner Circle Trader) methodology, this approach helps traders recognize subtle signs of market manipulation or imbalance, often ahead of traditional indicators. The core idea behind SMT divergence is simple: when two correlated instruments—such as currency pairs, indices, or assets from the same sector—start forming different swing points (highs or lows), this can reveal a lack of confirmation in the trend. Such divergence is often a precursor to a price reversal or pause in momentum. This technique works effectively across various markets including Forex, stocks, and cryptocurrencies. It’s particularly valuable when used alongside concepts like liquidity sweeps, market structure breaks (MSBs), or order block identification. In advanced use cases, Sequential SMT helps uncover patterns of alternating divergences across sessions, often signaling engineered liquidity traps before price reacts. When combined with the Quarterly Theory—which segments market behavior into Accumulation, Manipulation, Distribution, and Continuation/Reversal phases—traders gain insight not only into where divergence happens, but when it's most likely to be significant within the market cycle. Bullish SMT : Bullish SMT Divergence occurs when one asset prints a higher low while the correlated asset forms a lower low. This asymmetry often suggests that the downside move is losing strength, hinting at a potential bullish shift. Bearish SMT : Bearish SMT Divergence is formed when one asset creates a higher high, while the second asset fails to confirm by printing a lower high. This typically signals weakening bullish pressure and the possibility of a reversal to the downside. 🔵 How to Use The SMT Divergence indicator is designed to detect imbalances between two positively correlated assets—such as major currency pairs, indices, or commodities. These divergences often indicate early signs of market inefficiency or smart money manipulation and can help traders anticipate trend shifts with higher precision. Unlike traditional divergence indicators or earlier versions of this script, this upgraded version does not rely solely on consecutive pivot comparisons. Instead, it dynamically scans all available pivots within the chart to identify divergences at any structural level—major or minor—across the price action. This broader detection method increases the reliability and frequency of meaningful SMT signals. Moreover, when integrated with Sequential SMT logic, the indicator is capable of identifying multiple divergence sequences across sessions. These sequences often signal engineered liquidity traps and can be mapped within the Quarterly Theory framework, allowing traders to pinpoint not just the presence of divergence but also the phase of the market cycle it appears in (Accumulation, Manipulation, Distribution, or Continuation). 🟣 Bullish SMT Divergence This signal occurs when the primary asset forms a higher low, while the correlated asset forms a lower low. This pattern implies weakening bearish momentum and a potential shift to the upside. If the correlated asset breaks its previous low but the primary asset does not, this divergence suggests absorption of selling pressure and possible accumulation by smart money—making it a strong bullish signal, especially when aligned with a favorable market phase (e.g., the end of a manipulation phase in Q2). 🟣 Bearish SMT Divergence This signal occurs when the primary asset creates a higher high, while the correlated asset forms a lower high. This mismatch indicates fading bullish momentum and a potential reversal to the downside. If the correlated asset fails to confirm a breakout made by the main asset, the divergence may point to distribution or exhaustion. When seen within Q3 or Q4 phases of the Quarterly Theory, this pattern often precedes sharp declines or fake-outs engineered by smart money 🔵 Settings ⚙️ Logical Settings Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD). Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings. Activate Max Pivot Back : When enabled, limits the maximum number of past pivots to be considered for divergence detection. Max Pivot Back Length : Defines how many past pivots can be used (if the above toggle is active). Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared. Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated. 🎨 Display Settings Show Bullish SMT Line : Draws a line connecting the bullish divergence points. Show Bullish SMT Label : Displays a label on the chart when a bullish divergence is detected. Bullish Color : Sets the color for bullish SMT markers (label, shape, and line). Show Bearish SMT Line : Draws a line for bearish divergence. Show Bearish SMT Label : Displays a label when a bearish SMT divergence is found. Bearish Color : Sets the color for bearish SMT visual elements. 🔔 Alert Settings Alert Name : Custom name for the alert messages (used in TradingView’s alert system). Message Frequency : All : Every signal triggers an alert. Once Per Bar : Alerts once per bar regardless of how many signals occur. Per Bar Close : Only triggers when the bar closes and the signal still exists. Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC). Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals. Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals 🔵Conclusion The SMT Plus indicator offers a refined and powerful approach to detecting smart money behavior through divergence analysis between correlated assets. By removing the limitations of consecutive pivot comparisons and allowing for broader structural detection, it captures more accurate and timely signals that often precede major market moves. When paired with frameworks like Sequential SMT and the Quarterly Theory, the indicator not only highlights where divergence occurs, but also when in the market cycle it's most likely to matter. Its flexible settings, customizable visuals, and integrated alert system make it suitable for intraday scalpers, swing traders, and even long-term macro analysts. Whether you're using it as a standalone decision-making tool or combining it with other ICT concepts, SMT Plus gives you an edge in recognizing manipulation, timing reversals, and staying in sync with the real market narrative—not just the chart.
Индикатор Pine Script®
от TFlab
15
Sessions with Mausa session high/low tracker that draws flat, horizontal lines for Asia, London, and New York trading sessions. It updates those levels in real time during each session, locks them in once the session ends, and keeps them on the chart for context. At a glance, you always know: Where each session’s highs and lows were set Which session produced them (ASIA, LDN, NY labels float cleanly above the highs) When price is approaching or reacting to prior session levels 🔹 Use Cases: • Key Levels – See where Asia, London, or NY set boundaries, and watch how price respects or rejects them • Breakout Zones – Monitor when price breaks above/below session highs/lows • Session Structure – Know instantly if a move happened during London or NY without squinting at the clock • Backtesting – Keep historic session levels on the chart for reference — nothing gets deleted • Confluence – Align these levels with support/resistance, fibs, or liquidity zones Simple, visual, no distractions — just session structure at a glance.
Индикатор Pine Script®
от MausIncognito
EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection)EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection) 🚨 Main Utility: Early Squeeze Warning The primary function of this indicator is to warn traders early when the market is approaching a "squeeze"—a tightening condition that often precedes significant moves or regime shifts. By visually highlighting areas of increasing tension, it helps traders anticipate potential volatility and prepare accordingly. This is intended to be a statistically and psychologically grounded replacement of so-called "fib-time-zones," which are overly-deterministic and subjective. 📌 Overview The EMA-Based Squeeze Dynamics indicator projects future regime shifts (such as golden and death crosses) using exponential moving averages (EMAs). It employs historical interval data and current market conditions to dynamically forecast when the critical EMAs (50-period and 200-period) will reconverge, marking likely trend-change points. This indicator leverages two core ideas: Behavioral finance theory: Traders often collectively anticipate popular EMA crossovers, creating a self-fulfilling prophecy (normative social influence), similar to findings from Solomon Asch’s conformity experiments. Bayesian-like updates: It utilizes historical crossover intervals as a prior, dynamically updating expectations based on evolving market data, ensuring its signals remain objectively grounded in actual market behavior. ⚙️ Technical & Mathematical Explanation 1. EMA Calculations and Regime Definitions The indicator uses three EMAs: Fast (9-period): Represents short-term price movement. Medial (50-period): Indicates medium-term trend direction. Slow (200-period): Defines long-term market sentiment. Regime States: Bullish: 50 EMA is above the 200 EMA. Bearish: 50 EMA is below the 200 EMA. A shift between these states triggers visual markers (arrows and labels) directly on the chart. 2. Gap Dynamics and Historical Intervals At each crossover: The indicator records the gap (distance) between the 50 and 200 EMAs. It tracks the historical intervals between past crossovers. An Exponentially Weighted Moving Average (EWMA) of these intervals is calculated, weighting recent intervals more heavily, dynamically updating expectations. Important note: After every regime shift, the projected crossover line resets its calculation. This reset is visually evident as the projection line appears to move further away after each regime change, temporarily "repelled" until the EMAs begin converging again. This ensures projections remain realistic, grounded in actual EMA convergence, and prevents overly optimistic forecasts immediately after a regime shift. 3. Gap Momentum & Adaptive Scaling The indicator measures how quickly or slowly the gap between EMAs is changing ("gap momentum") and adjusts its forecast accordingly: If the gap narrows rapidly, a crossover becomes more imminent. If the gap widens, the next crossover is pushed further into the future. The "gap factor" dynamically scales the projection based on recent gap momentum, bounded between reasonable limits (0.7–1.3). 4. Squeeze Ratio & Background Color (Visual Cues) A "squeeze ratio" is computed when market conditions indicate tightening: In a bullish regime, if the fast EMA is below the medial EMA (price pulling back towards long-term support), the squeeze ratio increases. In a bearish regime, if the fast EMA rises above the medial EMA (price rallying into long-term resistance), the squeeze ratio increases. What the Background Colors Mean: Red Background: Indicates a bullish squeeze—price is compressing downward, hinting a bullish reversal or continuation breakout may occur soon. Green Background: Indicates a bearish squeeze—price is compressing upward, suggesting a bearish reversal or continuation breakout could soon follow. Opacity Explanation: The transparency (opacity) of the background indicates the intensity of the squeeze: High Opacity (solid color): Strong squeeze, high likelihood of imminent volatility or regime shift. Low Opacity (faint color): Mild squeeze, signaling early stages of tightening. Thus, more vivid colors serve as urgent visual warnings that a squeeze is rapidly intensifying. 5. Projected Next Crossover and Pseudo Crossover Mechanism The indicator calculates an estimated future bar when a crossover (and thus, regime shift) is expected to occur. This calculation incorporates: Historical EWMA interval. Current squeeze intensity. Gap momentum. A dynamic penalty based on divergence from baseline conditions. The "Pseudo Crossover" Explained: A key adaptive feature is the pseudo crossover mechanism. If price action significantly deviates from the projected crossover (for example, if price stays beyond the projected line longer than expected), the indicator acknowledges the projection was incorrect and triggers a "pseudo crossover" event. Essentially, this acts as a reset, updating historical intervals with a weighted adjustment to recalibrate future predictions. In other words, if the indicator’s initial forecast proves inaccurate, it recognizes this quickly, resets itself, and tries again—ensuring it remains responsive and adaptive to actual market conditions. 🧠 Behavioral Theory: Normative Social Influence This indicator is rooted in behavioral finance theory, specifically leveraging normative social influence (conformity). Traders commonly watch EMA signals (especially the 50 and 200 EMA crossovers). When traders collectively anticipate these signals, they begin trading ahead of actual crossovers, effectively creating self-fulfilling prophecies—similar to Solomon Asch’s famous conformity experiments, where individuals adopted group behaviors even against direct evidence. This behavior means genuine regime shifts (actual EMA crossovers) rarely occur until EMAs visibly reconverge due to widespread anticipatory trading activity. The indicator quantifies these dynamics by objectively measuring EMA convergence and updating projections accordingly. 📊 How to Use This Indicator Monitor the background color and opacity as primary visual cues. A strongly colored background (solid red/green) is an early alert that a squeeze is intensifying—prepare for potential volatility or a regime shift. Projected crossover lines give a dynamic target bar to watch for trend reversals or confirmations. After each regime shift, expect a reset of the projection line. The line may seem initially repelled from price action, but it will recalibrate as EMAs converge again. Trust the pseudo crossover mechanism to automatically recalibrate the indicator if its original projection misses. 🎯 Why Choose This Indicator? Early Warning: Visual squeeze intensity helps anticipate market breakouts. Behaviorally Grounded: Leverages real trader psychology (conformity and anticipation). Objective & Adaptive: Uses real-time, data-driven updates rather than static levels or subjective analysis. Easy to Interpret: Clear visual signals (arrows, labels, colors) simplify trading decisions. Self-correcting (Pseudo Crossovers): Quickly adjusts when initial predictions miss, maintaining accuracy over time. Summary: The EMA-Based Squeeze Dynamics Indicator combines behavioral insights, dynamic Bayesian-like updates, intuitive visual cues, and a self-correcting pseudo crossover feature to offer traders a reliable early warning system for market squeezes and impending regime shifts. It transparently recalibrates after each regime shift and automatically resets whenever projections prove inaccurate—ensuring you always have an adaptive, realistic forecast. Whether you're a discretionary trader or algorithmic strategist, this indicator provides a powerful tool to navigate market volatility effectively. Happy Trading! 📈✨
Индикатор Pine Script®
от garysebastianbrowniii
Half Causal EstimatorOverview The Half Causal Estimator is a specialized filtering method that provides responsive averages of market variables (volume, true range, or price change) with significantly reduced time delay compared to traditional moving averages. It employs a hybrid approach that leverages both historical data and time-of-day patterns to create a timely representation of market activity while maintaining smooth output. Core Concept Traditional moving averages suffer from time lag, which can delay signals and reduce their effectiveness for real-time decision making. The Half Causal Estimator addresses this limitation by using a non-causal filtering method that incorporates recent historical data (the causal component) alongside expected future behavior based on time-of-day patterns (the non-causal component). This dual approach allows the filter to respond more quickly to changing market conditions while maintaining smoothness. The name "Half Causal" refers to this hybrid methodology—half of the data window comes from actual historical observations, while the other half is derived from time-of-day patterns observed over multiple days. By incorporating these "future" values from past patterns, the estimator can reduce the inherent lag present in traditional moving averages. How It Works The indicator operates through several coordinated steps. First, it stores and organizes market data by specific times of day (minutes/hours). Then it builds a profile of typical behavior for each time period. For calculations, it creates a filtering window where half consists of recent actual data and half consists of expected future values based on historical time-of-day patterns. Finally, it applies a kernel-based smoothing function to weight the values in this composite window. This approach is particularly effective because market variables like volume, true range, and price changes tend to follow recognizable intraday patterns (they are positive values without DC components). By leveraging these patterns, the indicator doesn't try to predict future values in the traditional sense, but rather incorporates the average historical behavior at those future times into the current estimate. The benefit of using this "average future data" approach is that it counteracts the lag inherent in traditional moving averages. In a standard moving average, recent price action is underweighted because older data points hold equal influence. By incorporating time-of-day averages for future periods, the Half Causal Estimator essentially shifts the center of the filter window closer to the current bar, resulting in more timely outputs while maintaining smoothing benefits. Understanding Kernel Smoothing At the heart of the Half Causal Estimator is kernel smoothing, a statistical technique that creates weighted averages where points closer to the center receive higher weights. This approach offers several advantages over simple moving averages. Unlike simple moving averages that weight all points equally, kernel smoothing applies a mathematically defined weight distribution. The weighting function helps minimize the impact of outliers and random fluctuations. Additionally, by adjusting the kernel width parameter, users can fine-tune the balance between responsiveness and smoothness. The indicator supports three kernel types. The Gaussian kernel uses a bell-shaped distribution that weights central points heavily while still considering distant points. The Epanechnikov kernel employs a parabolic function that provides efficient noise reduction with a finite support range. The Triangular kernel applies a linear weighting that decreases uniformly from center to edges. These kernel functions provide the mathematical foundation for how the filter processes the combined window of past and "future" data points. Applicable Data Sources The indicator can be applied to three different data sources: volume (the trading volume of the security), true range (expressed as a percentage, measuring volatility), and change (the absolute percentage change from one closing price to the next). Each of these variables shares the characteristic of being consistently positive and exhibiting cyclical intraday patterns, making them ideal candidates for this filtering approach. Practical Applications The Half Causal Estimator excels in scenarios where timely information is crucial. It helps in identifying volume climaxes or diminishing volume trends earlier than conventional indicators. It can detect changes in volatility patterns with reduced lag. The indicator is also useful for recognizing shifts in price momentum before they become obvious in price action, and providing smoother data for algorithmic trading systems that require reduced noise without sacrificing timeliness. When volatility or volume spikes occur, conventional moving averages typically lag behind, potentially causing missed opportunities or delayed responses. The Half Causal Estimator produces signals that align more closely with actual market turns. Technical Implementation The implementation of the Half Causal Estimator involves several technical components working together. Data collection and organization is the first step—the indicator maintains a data structure that organizes market data by specific times of day. This creates a historical record of how volume, true range, or price change typically behaves at each minute/hour of the trading day. For each calculation, the indicator constructs a composite window consisting of recent actual data points from the current session (the causal half) and historical averages for upcoming time periods from previous sessions (the non-causal half). The selected kernel function is then applied to this composite window, creating a weighted average where points closer to the center receive higher weights according to the mathematical properties of the chosen kernel. Finally, the kernel weights are normalized to ensure the output maintains proper scaling regardless of the kernel type or width parameter. This framework enables the indicator to leverage the predictable time-of-day components in market data without trying to predict specific future values. Instead, it uses average historical patterns to reduce lag while maintaining the statistical benefits of smoothing techniques. Configuration Options The indicator provides several customization options. The data period setting determines the number of days of observations to store (0 uses all available data). Filter length controls the number of historical data points for the filter (total window size is length × 2 - 1). Filter width adjusts the width of the kernel function. Users can also select between Gaussian, Epanechnikov, and Triangular kernel functions, and customize visual settings such as colors and line width. These parameters allow for fine-tuning the balance between responsiveness and smoothness based on individual trading preferences and the specific characteristics of the traded instrument. Limitations The indicator requires minute-based intraday timeframes, securities with volume data (when using volume as the source), and sufficient historical data to establish time-of-day patterns. Conclusion The Half Causal Estimator represents an innovative approach to technical analysis that addresses one of the fundamental limitations of traditional indicators: time lag. By incorporating time-of-day patterns into its calculations, it provides a more timely representation of market variables while maintaining the noise-reduction benefits of smoothing. This makes it a valuable tool for traders who need to make decisions based on real-time information about volume, volatility, or price changes.
Индикатор Pine Script®
от The_Peaceful_Lizard
6
Sun Moon Conjunctions Trine Oppositions 2025this script is an astrological tool designed to overlay significant Sun-Moon aspect events for 2025 on a Bitcoin chart. It highlights key lunar phases and aspects—Conjunctions (New Moon) in blue, Squares in red, Oppositions (Full Moon) in purple, and Trines in green—using background colors and labeled markers. Users can toggle visibility for each aspect type and adjust label sizes via customizable inputs. The script accurately marks events from January through December 2025, with labels appearing once per event, making it a valuable resource for exploring potential correlations between lunar cycles and Bitcoin price movements.
Индикатор Pine Script®
от Dshergill
RVOL Effort Matrix💪🏻 RVOL Effort Matrix is a tiered volume framework that translates crowd participation into structure-aware visual zones. Rather than simply flagging spikes, it measures each bar’s volume as a ratio of its historical average and assigns to that effort dynamic tiers, creating a real-time map of conviction , exhaustion , and imbalance —before price even confirms. ⚖️ At its core, the tool builds a histogram of relative volume (RVOL). When enabled, a second layer overlays directional effort by estimating buy vs sell volume using candle body logic. If the candle closes higher, green (buy) volume dominates. If it closes lower, red (sell) volume leads. These components are stacked proportionally and inset beneath a colored cap line—a small but powerful layer that maintains visibility of the true effort tier even when split bars are active. The cap matches the original zone color, preserving context at all times. Coloration communicates rhythm, tempo, and potential turning points: • 🔴 = structurally weak effort, i.e. failed moves, fake-outs or trend exhaustion • 🟡 = neutral volume, as seen in consolidations or pullbacks • 🟢 = genuine commitment, good for continuation, breakout filters, or early rotation signals • 🟣 = explosive volume signaling either climax or institutional entry—beware! Background shading (optional) mirrors these zones across the pane for structural scanning at a glance. Volume bars can be toggled between full-stack mode or clean column view. Every layer is modular—built for composability with tools like ZVOL or OBVX Conviction Bias. 🧐 Ideal Use-Cases: • 🕰 HTF bias anchoring → LTF execution • 🧭 Identifying when structure is being driven by real crowd pressure • 🚫 Fading green/fuchsia bars that fail to break structure • ✅ Riding green/fuchsia follow-through in directional moves 🍷 Recommended Pairings: • ZVOL for statistically significant volume anomaly detection • OBVX Conviction Bias ↔️ for directional confirmation of effort zones • SUPeR TReND 2.718 for structure-congruent entry filtering • ATR Turbulence Ribbon to distinguish expansion pressure from churn 🥁 RVOL Effort Matrix is all about seeing—how much pressure is behind a move, whether that pressure is sustainable, and whether the crowd is aligned with price. It's volume, but readable. It’s structure, but dynamic. It’s the difference between obeying noise and trading to the beat of the market.
Индикатор Pine Script®
от TheLeadingIndicator
OBVX Conviction Bias🧮 The OBVX Conviction Bias overlay tracks the flow of directional volume using the classic On-Balance Volume calculation, then filters it through a layered moving average system to expose crowd commitment , pressure transitions , and momentum fatigue . The tool applies two smoothed averages to the OBV line—a fast curve and a longer-term baseline scaled using Euler’s constant (2.718)—and visualizes their relationship using a color-coded crossover ribbon and pressure fills. When used correctly, it reveals whether a move is being supported by meaningful volume, or whether the crowd is starting to disengage. 🚦 The core signal compares OBV to its fast moving average. When OBV climbs above the short average, it fills green—suggesting real directional effort. When OBV sinks below, the fill turns maroon—flagging fading conviction or pullback potential. A second fill between the short and long OBV moving averages captures the broader trend of volume intention. If the short is above the long, this space fills greenish, showing constructive pressure. If it flips, the fill fades red, signaling crowd hesitation, rotation, or early exhaustion. ⚖️ All smoothing is user-selectable, defaulting to VWMA for effort-sensitive structure. The long-term average is auto-scaled using the natural exponential multiplier (2.718), offering rhythm that reflects the curve of participation. OBVX Conviction Bias isn’t trying to predict—it’s trying to show you where the crowd is leaning , and whether that lean is gaining traction or losing strength. 🧐  Ideal Use-Cases: • Detect divergence between volume flow and price action • Confirm breakout validity with volume alignment • Fade breakouts where OBV fails to follow through • Time pullback entries when OBV pressure resumes in trend direction 🍷  Recommended Pairings: • ZVOL to measure whether volume is statistically significant or just noise (as shown) • RVOL Effort Matrix to validate crowd effort by tier and structure zone • SUPeR TReND 2.718 and/or MA Ribbons for directional confluence • ATR Turbulence to track volatility-phase alignment with volume intention
Индикатор Pine Script®
от TheLeadingIndicator
BeSight Mega SpotBeSight Mega Spot – Zone Based Price Grid Indicator สคริปต์นี้ถูกออกแบบมาเพื่อช่วยเทรดเดอร์มองเห็นโซนราคาสำคัญที่ราคาอาจเกิดปฏิกิริยา โดยอ้างอิงจากระดับราคาที่ลงท้ายด้วย 0 และ 5 (เช่น 1350, 1355, 1360 เป็นต้น) ซึ่งมักเป็นระดับที่มีการตั้งคำสั่งซื้อขายจำนวนมากในตลาด BeSight Mega Spot – Zone-Based Price Grid Indicator This indicator is designed to help traders visualize key price zones where the market often reacts, based on price levels ending with 0 or 5 (e.g., 1350, 1355, 1360). These levels are commonly used for pending orders, liquidity, or price clustering zones. It displays horizontal grid lines at fixed step intervals (default: every 5 points), covering the entire visible price range of the chart. Each price level is labeled for better clarity and planning. 🟦 Blue lines: Price levels ending in 0 ⬜ Gray lines: Price levels ending in 5 This tool is useful for identifying potential institutional behavior zones, price consolidation, accumulation/distribution areas, or psychological support/resistance levels. 🧠 Notes: - This indicator is not a buy/sell signal tool or predictive system. - It works best when used in conjunction with other technical tools such as Supply/Demand zones or Smart Money Concepts (SMC) analysis. - Compatible with all instruments: stocks, futures, forex, crypto, etc. ✅ How to use: 1. Add the indicator to your chart 2. Observe how price interacts with the 0/5 grid zones 3. Use the lines to assist with breakout, retest, or reversal planning 4. Combine with price action or other indicators for higher precision ✨ Developed by BeSight – A Community Of Traders --------------------------------------------------------------------------------------- อินดิเคเตอร์นี้จะแสดงเส้นแนวนอนแบบตาราง (Grid) ที่แบ่งช่วงราคาออกเป็นระยะ ๆ ตามค่าที่ผู้ใช้กำหนด เช่น ทุก ๆ 5 จุด และครอบคลุมช่วงราคาทั้งหมดของกราฟ โดยแสดงเป็นเส้นแบบ dotted พร้อมป้ายราคาเพื่อให้มองเห็นได้ชัดเจน 🟦 เส้นสีน้ำเงิน: แสดงระดับราคาที่ลงท้ายด้วย 0 ⬜ เส้นสีเทา: แสดงระดับราคาที่ลงท้ายด้วย 5 เหมาะสำหรับผู้ที่ต้องการดูโซนราคา "หยุดพัก / เก็บของ / เปิดโพซิชัน" ซึ่งอาจสะท้อนพฤติกรรมของผู้เล่นรายใหญ่หรือสถาบันในตลาด 🧠 ข้อควรรู้: - อินดิเคเตอร์นี้ไม่ได้บอกจุดเข้าเทรดหรือการคาดการณ์ แต่ช่วยในการวางแผนแนวรับ-แนวต้านร่วมกับเครื่องมือวิเคราะห์อื่น ๆ - รองรับทุกสินทรัพย์ที่มีหน่วยราคาคงที่ (หุ้น, ฟิวเจอร์ส, ฟอเร็กซ์, คริปโต ฯลฯ) ✅ วิธีใช้งาน: 1. เพิ่มอินดิเคเตอร์นี้ลงบนกราฟ 2. ใช้เส้น Grid เป็นแนวประกอบในการดูพฤติกรรมราคา เช่น การหยุดลง, การเบรกแนว, การกลับตัว 3. ผสมผสานกับโซน Demand/Supply หรือโซน SMC เพื่อความแม่นยำ ✨ พัฒนาโดย BeSight – คอมมูนิตี้ของเทรดเดอร์ตัวจริง
Индикатор Pine Script®
от BeSight
1
3SMA +30 Stan Weinstein +200WMA +alert-crossingIndicator Description: Stan Weinstein Strategy + Key Moving Averages 🔹 Introduction This indicator combines the Classic Stan Weinstein Strategy with a modern update based on the author’s latest recommendations. It includes key moving averages that help identify trends and potential entry or exit points in the market. 📊 Included Moving Averages (Fully Customizable) All moving averages in this indicator have modifiable parameters, allowing users to adjust values in the input settings. 1️⃣ 30-Week SMA (Stan Weinstein): A long-term trend indicator defining the asset’s main trend. 2️⃣ 40-Week SMA (Weinstein Update): An adjusted version recommended by the author in his recent updates. 3️⃣ 10-Day SMA: Displays short-term price action and helps confirm trend changes. 4️⃣ 100-Day SMA: A medium-term trend measure used by traders to assess trend strength. 5️⃣ 200-Day WMA (Weighted Moving Average): A very long-term indicator that filters market noise and confirms solid trends. 🔍 How to Interpret It ✔️ 30/40-Week SMA in an uptrend → Confirms an accumulation phase or an upward price trend. ✔️ Price above the 200-WMA → Indicates a strong and healthy long-term trend. ✔️ 10-SMA crossing other moving averages → Can signal an early entry or exit opportunity. ✔️ 100-SMA vs. 200-WMA → A breakout of the 100-SMA above the 200-WMA may signal a new bullish phase. 🚨 Built-in Alerts (Key Crossovers) The indicator includes automatic alerts to notify traders when key moving averages cross, allowing timely reactions: 🔔 10-SMA crossing the 40-SMA → Possible medium-term trend shift. 🔔 10-SMA crossing the 200-WMA → Confirmation of a stronger trend. 🔔 40-SMA crossing the 200-WMA → Long-term trend reversal signal. 💡 Customization: All moving average periods can be adjusted in the input settings, making the indicator flexible for different trading strategies.
Индикатор Pine Script®
от Magm7
Open Vertical Lines [TradeWithRon]This indicator allows traders to draw vertical lines manually or automatically based on the current or specified higher timeframes. It is a versatile tool designed to help users identify and mark significant changes in the market, such as new candle formations, based on a selected or auto-adjusted timeframe. Open Source Features: Timeframe Customization: Users can either manually specify a desired timeframe (e.g., 1-hour, 1-day, etc.) or enable the "Auto" feature, which automatically adjusts the timeframe based on the current chart's timeframe for better alignment with different trading strategies. Customizable Line Style: The vertical line can be drawn in three different styles: Solid, Dashed, or Dotted, giving users the flexibility to choose their preferred appearance for better chart readability. Line Color: Users can select the color of the vertical line with transparency options to match their chart's visual preferences. Auto Timeframe Adjustments: The "Auto Align" option dynamically adjusts the timeframe used for vertical lines depending on the chart's current timeframe. For example, if you’re using a lower timeframe (e.g., 5 minutes), the indicator will automatically switch to a higher timeframe (e.g., 1 hour or daily) to mark vertical lines, ensuring the lines correspond to higher timeframe price action. Vertical Line Placement: A vertical line is placed each time a new candle appears on the chart, marking key moments for the user to analyze market movements. This can be helpful for marking the start of new trading sessions or significant events in the market. How to Use: 1. Apply the indicator to your chart. 2. Configure the preferred timeframe settings (either fixed or auto-align). 3. Customize the line style and color according to your visual preference. 4. The indicator will automatically place vertical lines on the chart when a new candle is formed, based on your selected timeframe.
Индикатор Pine Script®
от yeahronc
AltSeasonality - MTFAltSeason is more than a brief macro market cycle — it's a condition. This indicator helps traders identify when altcoins are gaining strength relative to Bitcoin dominance, allowing for more precise entries, exits, and trade selection across any timeframe. The key for altcoin traders is that the lower the timeframe, the higher the alpha. By tracking the TOTAL3/BTC.D ratio — a real-time measure of altcoin strength versus Bitcoin — this tool highlights when capital is rotating into or out of altcoins. It works as a bias filter, helping traders avoid low-conviction setups, especially in chop or during BTC-led conditions. ________________________________________________________________________ It works well on the 1D chart to validate swing entries during strong altcoin expansion phases — especially when TOTAL3/BTC.D breaks out while BTCUSD consolidates. On the 4H or 1D chart, rising TOTAL3/BTC.D + a breakout on your altcoin = high-conviction setup. If BTC is leading, fade the move or reduce size. Consider pairing with the Accumulation - Distribution Candles, optimized for the 1D (not shown). 🔍 Where this indicator really excels, however, is on the 1H and 15M charts, where short-term traders need fast bias confirmation before committing to a move. Designed for scalpers, intraday momentum traders, and tactical swing setups. Use this indicator to confirm whether an altcoin breakout is supported by broad market flow — or likely to fail due to hidden BTC dominance pressure. ________________________________________________________________________ 🧠 How it works: - TOTAL3 = market cap of altcoins (excl. BTC + ETH) - BTC.D = Bitcoin dominance as % of total market cap - TOTAL3 / BTC.D = a normalized measure of altcoin capital strength vs Bitcoin - BTCUSD = trend baseline and comparison anchor The indicator compares these forces side-by-side, using a normalized dual-line ribbon. There is intentionally no "smoothing". When TOTAL3/BTC.D is leading, the ribbon shifts to an “altseason active” phase. When BTCUSD regains control, the ribbon flips back into BTC dominance — signaling defensive posture. ________________________________________________________________________ 💡 Strategy Example: On the 1H chart, a crossover into altseason → check the 15M chart for confirmation. Consider adding the SUPeR TReND 2.718 for confirmation (not shown). If both align, you have trend + flow confluence. If BTCUSD is leading or ribbon is mixed, reduce exposure or wait for confirmation. Further confirmation via Volume breakouts in your specific coin. ⚙️ Features: • MTF source selection (D, 1H, 15M) • Normalized ribbon (TOTAL3/BTC.D vs BTCUSD) • Cross-aware fill shading • Custom color and transparency controls • Optional crossover markers • Midline + zone guides (0.2 / 0.5 / 0.8)
Индикатор Pine Script®
от TheLeadingIndicator
Cz ASR indicatorAverage session range indicator built by me. Great tool to gauge volatility and intraday reversal zones. Great for FX as there is an included table that shows range in pips; however, this can be applied across all assets as a volatility measure. How it works: The script measures the range of sessions, including Asia, London, and New York. The lookback period could be adjusted so you can find what length works best and is most accurate. This is then averaged out to provide the ASR. This provides us with an upper and lower bound of which the price could potentially fluctuate in based on the past session ranges. I have also added the 50% ASR, which is also a super useful metric for reversals or continuations. There is also a configurable UTC so that you can adjust the indicator so it can accurately measure the range within certain sessions. Note - different session start and stop times vary from market to market. I have set the code to the standard forex market opens however, if you wish to change the time ,you are able to do so by editing the variables in the script Enjoy :)
Индикатор Pine Script®
от oh_my_liquidity
2
ATR - Asymmetric Turbulence Ribbon🧭 Asymmetric Turbulence Ribbon (ATR) The Asymmetric Turbulence Ribbon (ATR) is an enhanced and reimagined version of the standard Average True Range (ATR) indicator. It visualizes not just raw volatility, but the structure, momentum, and efficiency of volatility through a multi-layered visual approach. It contains two distinct visual systems: 1. A zero-centered histogram that expresses how current volatility compares to its historical average, with intensity and color showing speed and conviction 2. A braided ribbon made of dual ATR-based moving averages that highlight transitions in volatility behavior—whether volatility is expanding or contracting The name reflects its purpose: to capture asymmetric, evolving turbulence in market behavior, through structure-aware volatility tracking. _______________________________________________________________ 🔧 Inputs (Fibonacci defaults) ATR Length Lookback period for ATR calculation (default: 13) ATR Base Avg. Length Moving average period used as the zero baseline for histogram (default: 55) ATR ROC Lookback Number of bars to measure rate of change for histogram color mapping (default: 8) Timeframe Override Optionally calculate ATR values from a higher or fixed timeframe (e.g., 1D) for macro-volatility overlay Show Ribbon Fill Toggles colored fill between ATR EMA and HMA lines Show ATR MAs Toggles visibility of ATR EMA and HMA lines Show Crossover Markers Shows directional triangle markers where ATR EMA and HMA cross Show Histogram Toggles the entire histogram display _______________________________________________________________ 📊 Histogram Component: Volatility Energy Profile The histogram shows how far the current ATR is from its moving average baseline, centered around zero. This lets you interpret volatility pressure—whether it's expanding, contracting, or preparing to reverse. To complement this, the indicator also plots the raw ATR line in aqua. This is the actual average true range value—used internally in both the histogram and ribbon calculations. By default, it appears as a slightly thicker line, providing a clear reference point for comparing historical volatility trends and absolute levels. Use the baseline ATR to: - Compare real-time volatility to previous peaks or troughs - Monitor how ATR behaves near histogram flips or ribbon crossovers - Evaluate volatility phases in absolute terms alongside relative momentum The ATR line is particularly helpful for users who want to keep tabs on raw volatility values while still benefiting from the enhanced visual storytelling of the histogram and ribbon systems. Each histogram bar is colored based on the rate of change (ROC) in ATR: The faster ATR rises or falls, the more intense the color. Meanwhile, the opacity of each bar is adjusted by the effort/result ratio of the price candle (body vs. range), showing how much price movement was achieved with conviction. Color Interpretation: 🔴 Red Strong volatility expansion Market entering or deepening into a volatility burst Seen during breakouts, panic moves, or macro shock events Often accompanied by large real candle bodies 🟠 Orange Moderate volatility expansion Heating up phase, often precedes breakouts Common in strong trending environments Signals tightening before acceleration 🟡 Yellow Mild volatility increase Transitional state—energy building, not yet exploding Appears in early trend development or pullbacks 🟢 Green Mild volatility contraction ATR cooling off Seen during consolidation, reversion, or range balance Good time to assess upcoming directional setups 🔵 Aqua Moderate compression Volatility is clearly declining Signals consolidation within larger structure Pre-breakout zones often form here 🔵 Deep Blue Strong volatility compression Market is coiling or dormant Can signal upcoming squeeze or fade environment Often followed by sharp expansion Opacity scaling: Brighter bars = efficient, directional price action (strong bodies) Faded bars = indecision, chop, absorption, or wick-heavy structure Together, color and opacity give a 2D view of market volatility: Hue = the type and direction of volatility Opacity = the quality and structure behind it Use this to gauge whether volatility is rising with conviction, fading into neutrality, or compressing toward breakout potential. _______________________________________________________________ 🪡 Ribbon Component: Volatility Rhythm Structure The ribbon overlays two moving averages of ATR: EMA (yellow) – faster, more reactive HMA (orange) – smoother, more rhythmic Their relationship creates the ribbon logic: Yellow fill (EMA > HMA) Short-term volatility is increasing faster than the longer-term rhythm Signals active expansion and engagement Orange fill (HMA > EMA) Volatility is decaying or leveling off Suggests possible exhaustion, pullback, or range Crossover triangle markers (optional, off by default to avoid clutter) identify the moment of shift in volatility phase. The ribbon reflects the  shape of volatility over time—ideal for mapping cyclical energy shifts, transitional states, and alignment between current and average volatility. _______________________________________________________________ 📐 Strategy Application Use the Asymmetric Turbulence Ribbon to: - Detect volatility expansions before breakouts or directional runs - Spot compression zones that precede structural ruptures - Visually separate efficient moves from noisy market activity - Confirm or fade trade setups based on underlying energy state - Track the volatility environment across multiple timeframes using the override _______________________________________________________________ 🎯 Ideal Timeframes Designed to function across all timeframes, but particularly powerful on intraday to daily ranges (1H to 1D) Use the timeframe override to anchor your chart in higher-timeframe volatility context, like daily ATR behavior influencing a 1H setup. _______________________________________________________________ 🧬 Customization Tips - Increase ATR ROC Lookback for smoother color transitions - Extend ATR Base Avg Length for more macro-driven histogram centering - Disable the histogram for ribbon-only rhythm view - Use opacity and color shifts in the histogram to detect stealth energy builds - Align ATR phases with structure or order flow tools for high-quality setups
Индикатор Pine Script®
от TheLeadingIndicator
ATR and Moving AverageUsing ATR and Moving Average: A Technical Analysis Strategy The Average True Range (ATR) and the Moving Average are two important technical analysis tools that can be used together to identify trading opportunities in the market. In this article, we will explore how to use these two tools and how the crossover between them can indicate changes in the market. What is ATR? The Average True Range (ATR) is a measure of the volatility of an asset, which calculates the average true range of an asset over a period of time. The true range is the difference between the closing price and the opening price of an asset, or the difference between the closing price and the highest or lowest price of the day. ATR is an important measure of volatility, as it helps to identify the magnitude of price fluctuations of an asset. What is Moving Average? The Moving Average is a technical analysis tool that calculates the average price of an asset over a period of time. The Moving Average can be used to identify trends and price patterns, and is an important tool for traders. There are different types of Moving Averages, including the Simple Moving Average (SMA), the Exponential Moving Average (EMA), and the Weighted Moving Average (WMA). Crossover between ATR and Moving Average The crossover between ATR and Moving Average can be an important indicator of changes in the market. When ATR crosses above the Moving Average, it may indicate that the volatility of the asset is increasing and that the price may be about to rise. This occurs because ATR is increasing, which means that the true range of the asset is increasing, and the Moving Average is being surpassed, which means that the price is rising. On the other hand, when ATR crosses below the Moving Average, it may indicate that the volatility of the asset is decreasing and that the price may be about to fall. This occurs because ATR is decreasing, which means that the true range of the asset is decreasing, and the Moving Average is being surpassed, which means that the price is falling. Trading Strategies There are several trading strategies that can be used with the crossover between ATR and Moving Average. Some of these strategies include: Buying when ATR crosses above the Moving Average, with the expectation that the price will rise. Selling when ATR crosses below the Moving Average, with the expectation that the price will fall. Using the crossover between ATR and Moving Average as a filter for other trading strategies, such as trend analysis or pattern recognition. In summary, the crossover between ATR and Moving Average can be an important indicator of changes in the market, and can be used as a technical analysis tool to identify trading opportunities. However, it is important to remember that no trading strategy is foolproof, and that it is always important to use a disciplined approach and manage risk adequately.
Индикатор Pine Script®
от Guilherme-Bruno
Professional MSTI+ Trading Indicator"Professional MSTI+ Trading Indicator" is a comprehensive technical analysis tool that combines over 20 indicators to generate high-quality trading signals and assess market sentiment. The script integrates standard indicators (MACD, RSI, Bollinger Bands, Stochastic, Simple Moving Averages, and Volume Analysis) with advanced components (Squeeze Momentum, Fisher Transform, True Strength Index, Heikin-Ashi, Laguerre RSI, Hull MA) and further includes metrics such as ADX, Chaikin Money Flow, Williams %R, VWAP, and EMA for in-depth market analysis. Key Features: Multiple Presets for Different Trading Styles: Choose from optimal configurations like Professional, Swing Trading, Day Trading, Scalping, or Reversal Hunter. Note that the presets may not work perfectly on all pairs, and manual calibration might be required. This flexibility allows you to fine-tune the settings to align with your unique strategies and signals. Multi-Layered Signal Filtering: Filters based on trend, volume, and volatility help eliminate false signals, enhancing the accuracy of market entries. Comprehensive Fear & Greed Index: The indicator aggregates data from RSI, volatility, momentum, trend, and volume to gauge overall market sentiment, providing an additional layer of market context. Dynamic Information Panel: Displays detailed status updates for each component (e.g., MACD, RSI, Laguerre RSI, TSI, Fisher Transform, Squeeze, Hull MA, etc.) along with a visual strength bar that represents the intensity of the trading signal. Signal Generation: Buy and sell signals are generated when a predefined number of conditions are met and confirmed over multiple bars. These signals are clearly displayed on the chart with arrows, making it easier to spot potential entry and exit points. Alert Setup: Built-in alert conditions allow you to receive real-time notifications when trading signals are generated, helping you stay on top of market movements. "Professional MSTI+ Trading Indicator" is designed to enhance your trading strategy by providing a multi-faceted market analysis and an intuitive visual interface. While the presets offer a robust starting point, they may require manual calibration on certain pairs, giving you the flexibility to configure your own unique strategies and signals.
Индикатор Pine Script®
от mindmarket
1
Eclipse Dates IndicatorThis TradingView indicator displays vertical lines on eclipse dates from 1980 to 2030, with comprehensive filtering options for different types of eclipses. Features Date Range: Covers 221 eclipse events from 1980 to 2030 Eclipse Types: Filter by Solar and/or Lunar eclipses Eclipse Subtypes: Filter by Total, Partial, Annular, Penumbral, and Hybrid eclipses Year Range Selection: Focus on specific decades (1980-1990, 1990-2000, etc.) Visual Customization: Separate styling for Solar and Lunar eclipses Line Appearance: Customize color, style, and width Label Options: Show/hide labels with customizable appearance Eclipse Types Show Solar Eclipses: Toggle visibility of Solar eclipses Show Lunar Eclipses: Toggle visibility of Lunar eclipses Eclipse Subtypes Show Total Eclipses: Toggle visibility of Total eclipses Show Partial Eclipses: Toggle visibility of Partial eclipses Show Annular Eclipses: Toggle visibility of Annular eclipses Show Penumbral Eclipses: Toggle visibility of Penumbral eclipses Show Hybrid Eclipses: Toggle visibility of Hybrid eclipses Visual Settings Solar/Lunar Eclipse Line Color: Set the color for eclipse lines Solar/Lunar Eclipse Line Style: Choose between solid, dashed, or dotted lines Solar/Lunar Eclipse Line Width: Set the width of eclipse lines Solar/Lunar Label Text Color: Set the color for label text Solar/Lunar Label Background Color: Set the background color for labels General Settings Show Eclipse Labels: Toggle visibility of eclipse labels Label Size: Choose between tiny, small, normal, or large labels Extend Lines to Chart Borders: Toggle whether lines extend to chart borders Year Range: Filter eclipses by decade (1980-1990, 1990-2000, etc.) Usage Tips For optimal visualization, use daily or weekly timeframes When analyzing specific periods, use the Year Range filter To focus on specific eclipse types, use the type and subtype filters For cleaner charts, you can hide labels and only show lines Customize colors to match your chart theme Data Source Eclipse data is sourced from NASA's Five Millennium Catalog of Solar Eclipses and includes both solar and lunar eclipses from 1980 to 2030.
Индикатор Pine Script®
от justhahgao
Gold Futures vs Spot (Candlestick + Line Overlay)📝 Script Description: Gold Futures vs Spot This script was developed to compare the price movements between Gold Futures and Spot Gold within a specific time frame. The primary goals of this script are: To analyze the price spread between Gold Futures and Spot To identify potential arbitrage opportunities caused by price discrepancies To assist in decision-making and enhance the accuracy of gold market analysis 🔧 Key Features: Fetches price data from both Spot and Futures markets (from APIs or chart sources) Converts and aligns data for direct comparison Calculates the price spread (Futures - Spot) Visualizes the spread over time or exports the data for further analysis 📅 Date Created: 🧠 Additional Notes: This script is ideal for investors, gold traders, or analysts who want to understand the relationship between the Futures and Spot markets—especially during periods of high volatility. Unusual spreads may signal shifts in market sentiment or the actions of institutional players.
Индикатор Pine Script®
от SantaFX
1
Econometrica by [SS]This is Econometrica, an indicator that aims to bridge a big gap between the resources available for analysis of fundamental data and its impact on tickers and price action. I have noticed a general dearth of available indicators that offer insight into how fundamentals impact a ticker and provide guidance on how they these economic factors influence ticker behaviour. Enter Econometrica. Econometrica is a math based indicator that aims to co-integrate and model indicator price action in relation to critical economic metrics. Econometrica supports the following US based economic data: CPI Non-Farm Payroll Core Inflation US Money Supply US Central Bank Balance Sheet GDP PCE Let's go over the functions of Econometrica. Creating a Regression Cointegrated Model The first thing Econometrica does is creates a co-integrated regression, as you see in the main chart, predicting ticker value ranges from fundamental economic data. You can visualize this in the main chart above, but here are some other examples: SPY vs Core Inflation: BA vs PCE: QQQ vs US Balance Sheet: The band represents the anticipated range the ticker should theoretically fall in based on the underlying economic value. The indicator will breakdown the relationship between the economic indicator and the ticker more precisely. In the images above, you can see how there are some metrics provided, including Stationairty, lagged correlation, Integrated Correlation and R2. Let's discuss these very briefly: Stationarity: checks to ensure that the relationship between the economic indicator and ticker is stationary. Stationary data is important for making unbiased inferences and projections, so having data that is stationary is valuable. Lagged Correlation: This is a very interesting metric. Lagged correlation means whether there is a delay in the economic indicator and the response of the ticker. Typically, you will observed a lagged correlation between an economic indicator and price of a ticker, as it can take some time for economic changes to reach the market. This lagged correlation will provide you with how long it takes for the economic indicator to catch up with the ticker in months. Integrated Correlation: This metric tells you how good of a fit the regression bands are in relation to the ticker price. A higher correlation, means the model is better at consistent and accurate information about the anticipated range for the ticker in relation to the economic indicator. R2: Provides information on the variance and degree of model fit. A high R2 value means that the model is capable of explaining a large amount of variance between the economic indicator and the ticker price action. Explaining the Relationship Owning to the fact that the indicator is a bit on the mathy side (it has to be to do this kind of task), I have included ability for the indicator to explain and make suggestions based on the underlying data. It can assess the model's fit and make suggestions for tweaking. It can also explain the implications of the data being presented in the model. Here is an example with QQQ and the US Balance Sheet: This helps to simplify and interpret the results you are looking at. Forecasting the Economic Indicator In addition to assessing the economic indicator's impact on the ticker, the indicator is also capable of forecasting out the economic indicator over the next 25 releases. Here is an example of the CPI forecast: Overall use of the indicator The indicator is meant to bridge the gap between Technical Analysis and Fundamental Analysis. Any trader who is attune to fundamentals would benefit from this, as this provides you with objective data on how and to what extent fundamental and economic data impacts tickers. It can help affirm hypothesis and dispel myths objectively. It also omits the need from having to perform these types of analyses outside of Tradingview (i.e. in excel, R or Python), as you can get the data in just a few licks of enabling the indicator. Conclusion I have tried to make this indicator as user friendly as possible. Though it uses a lot of math, it is fairly straight forward to interpret. The band plotted can be considered the fair market value or FMV of the ticker based on the underlying economic data, provided the indicator tells you that the relationship is significant (and it will blatantly give you this information verbatim, you don't have to interpret the math stuff). This is US economic data only. It does not pull economic data from other countries. You can absolutely see how US economic data impacts other markets like the TSX, BANKNIFTY, NIFTY, DAX etc. but the indicator is only pulling US economic data. That is it! I hope you enjoy it and find this helpful! Thanks everyone and safe trades as always 🚀🚀🚀
Индикатор Pine Script®
от Steversteves
4