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Volume Flow Indicator [LazyBear]VFI,introduced by Markos Katsanos, is based on the popular On Balance Volume (OBV) but with three very important modifications: * Unlike the OBV, indicator values are no longer meaningless. Positive readings are bullish and negative bearish. * The calculation is based on the day's median (typical price) instead of the closing price. * A volatility threshold takes into account minimal price changes and another threshold eliminates excessive volume. A simplified interpretation of the VFI is: * Values above zero indicate a bullish state and the crossing of the zero line is the trigger or buy signal. * The strongest signal with all money flow indicators is of course divergence. I have exposed options to plot a signal EMA. All parameters are configurable. Markos suggests using 0.2 coeff for day trading and 0.1 for intra-day. More info: www.precisiontradingsystems.com
Pine Script® indicator
by LazyBear
100
Indicator: Relative Volume Indicator & Freedom Of MovementRelative Volume Indicator ------------------------------ RVI is a support-resistance technical indicator developed by Melvin E. Dickover. Unlike many conventional support and resistance indicators, the Relative Volume Indicator takes into account price-volume behavior in order to detect the supply and demand pools. These pools are marked by "Defended Price Lines" (DPLs), also introduced by the author. RVI is usually plotted as a histogram; its bars are highlighted (black, by default) when the volume is unusually large. According to the author, this happens if the indicator value exceeds 2.0, thus signifying that a possible DPL is present. DPLs are horizontal lines that run across the chart at levels defined by following conditions: * Overlapping bars: If the indicator spike (i.e., indicator is above 2.0 or a custom value) corresponds to a price bar overlapping the previous one, the previous close can be used as the DPL value. * Very large bars: If the indicator spike corresponds to a price bar of a large size, use its close price as the DPL value. * Gapping bars: If the indicator spike corresponds to a price bar gapping from the previous bar, the DPL value will depend on the gap size. Small gaps can be ignored: the author suggests using the previous close as the DPL value. When the gap is big, the close of the latter bar is used instead. * Clustering spikes: If the indicator spikes come in clusters, use the extreme close or open price of the bar corresponding to the last or next to last spike in cluster. DPLs can be used as support and resistance levels. In order confirm and refine them, RVI is used along with the FreedomOfMovement indicator discussed next. Freedom of Movement Indicator ------------------------------ FOM is a support-resistance technical indicator, also by Melvin E. Dickover. FOM is the ratio of relative effect (relative price change) to the relative effort (normalized volume), expressed in standard deviations. This value is plotted as a histogram; its bars are highlighted (black, by default( when this ratio is unusually high. These highlighted bars, or "spikes", define the positioning of the DPLs. Suggestions for placing DPLs are the same as for the Relative Volume Indicator discussed above. Note that clustering spikes provide the strongest DPLs while isolated spikes can be used to confirm and refine those provided by the Relative Volume Indicator. Coincidence of spikes of the two indicator can be considered a sign of greater strength of the DPL. More info: S&C magazine, April 2014. I am still trying these on various instruments to understand the workings more. Don't forget to share what you learn -- any use cases / ideal scenarios / gotchas, would love to hear them all.
Pine Script® indicator
by LazyBear
25
3 new Indicators - PGO / RAVI / TIIMy "to-publish" list is getting too big, so decided to push out 3 indicators in the same chart Feel free to "make mine" and use :) Leave a comment on what you think. Pretty Good Oscillator ---------------------------------------- This indicator, by Mark Johnson, measures the distance of the current close from its N-day simple moving average, expressed in terms of an average true range (see Average True Range) over a similar period. So for instance a PGO value of +2.5 would mean the current close is 2.5 average days' range above the SMA. Johnson's approach was to use it as a breakout system for longer term trades. If the PGO rises above 3.0 then go long, or below -3.0 then go short, and in both cases exit on returning to zero (which is a close back at the SMA). Indicator marks all these areas (3/-3/0) Rapid Adaptive Variance Indicator --------------------------------------------------------- RAVI is a simple indicator, by Tushar Chande, to show whether a stock is trending or not. Unlike ADX, RAVI measures only the trend intensity, it doesn't distinguish which way the trend is going. Rising RAVI shows the beginning of a trend or an increase in trend intensity, a decreasing slope signifies decreasing intensity. Also, RAVI often reacts more quickly and exhibits a more pronounced curve than ADX. The standard values for daily charts are 7 and 65. For hourly charts, the most common averaging periods are 12 and 72 or 24 and 120. The signal lines suggested are from +/- 0.3% to +/-1%. I haven't added any markings as these signals are instrument-specific. I suggest doing some back testing and adding these accordingly. Trend Intensity Index -------------------------------------- TII, by M. H. Pee, measures the strength of a trend, by looking at what proportion of the past "n" days prices have been above or below the level of today's "x"-day simple moving average. You can configure "n" via options page. "x" is calculated as "2 times n". TII moves between 0 and 100. A strong uptrend is indicated when TII is above 80. A strong downtrend is indicated when TII is below 20. Pee recommended entering trades when levels of 80 on the upside or 20 on the downside are reached. Indicator marks these lines for easy reference.
Pine Script® indicator
by LazyBear
22
[2022]Volume Flow v3 with alertsIndicators are an essential part of technical analysis of cryptocurrency. Their main function is to predict market direction based on historic price, cryptocurrency volume and other information. There are several types of crypto indicators illustrating various parameters (trend, volatility, volume, momentum, etc.) but in this article we will look at volume indicators. Volume indicators demonstrate changing of trading volume over time. This information is very useful as crypto trading volume displays how strong the current trend is. For example, if the price goes up and the volume is high then the trend is strong and will more likely last longer. There are various volume indicators, but we’ll talk about the most popular ones, such as: On Balance Volume Accumulation/Distribution Line Money Flow Index Chaikin Oscillator Chaikin Money Flow Ease of Movement
Pine Script® indicator
by Peggoy
Gold Option Signals with EMA and RSIIndicators: Exponential Moving Averages (EMAs): Faster to respond to recent price changes compared to simple moving averages. RSI: Measures the magnitude of recent price changes to evaluate overbought or oversold conditions. Signal Generation: Buy Call Signal: Generated when the short EMA crosses above the long EMA and the RSI is not overbought (below 70). Buy Put Signal: Generated when the short EMA crosses below the long EMA and the RSI is not oversold (above 30). Plotting: EMAs: Plotted on the chart to visualize trend directions. Signals: Plotted as shapes on the chart where conditions are met. RSI Background Color: Changes to red for overbought and green for oversold conditions. Steps to Use: Add the Script to TradingView: Open TradingView, go to the Pine Script editor, paste the script, save it, and add it to your chart. Interpret the Signals: Buy Call Signal: Look for green labels below the price bars. Buy Put Signal: Look for red labels above the price bars. Customize Parameters: Adjust the input parameters (e.g., lengths of EMAs, RSI levels) to better fit your trading strategy and market conditions. Testing and Validation To ensure that the script works as expected, you can test it on historical data and validate the signals against known price movements. Adjust the parameters if necessary to improve the accuracy of the signals.
Pine Script® indicator
by LunaDogeSaving
1
CCI-RSI MR Indicators: Bollinger Bands (20 period, 2σ) RSI (14 period) and Simple moving average of RSI (5 period) CCI (20 period) SMA (5 period) Entry Conditions: Buy when: Swing low (5) should be lower than the highest of lower BB (3 periods) Both RSI crossover RSI_5 and CCI crossover -100 should have happened within last 3 candles (including the current candle) Once all the above conditions are met, the close should be higher than SMA (5) within the next 3 candles After condition 3 is satisfied, we enter the trade at next candle’s open Stop loss will be at 1 tick lower than previous swing low Sell when: Swing high (5) should be higher than the lowest of upper BB (3 periods) Both RSI crossunder RSI_5 and CCI crossunder 100 should have happened within last 3 candles (including the current candle) Once all the above conditions are met, the close should be lower than SMA (5) within the next 3 candles After condition 3 is satisfied, we enter the trade at next candle’s open Stop loss will be at 1 tick higher than previous swing high Exit Conditions: Since it’s mean reversion strategy we’ll be having only 2 target exits with a trailing stop loss after target price 1 is achieved. Target exit price 1 & 2 are decided based on the risk ‘R’ for each trade Depending on the instrument and time frame a trailing stop loss of 0.5R or 1R has opted. A stop limit is placed @Entry_price +- 2*ATR(20) to offset the risk of losing significantly more than 1xR in a trade
Pine Script® strategy
by monikabhay
1
Gaussian Acceleration ArrayIndicators play a role in analyzing price action, trends, and potential reversals. Among many of these, velocity and acceleration have held a significant place due to their ability to provide insight into momentum and rate of change. This indicator takes the old calculation and tweaks it with gaussian smoothing and logarithmic function to ensure proper scaling. A Brief on Velocity and Acceleration: The concept of velocity in trading refers to the speed at which price changes over time, while acceleration is the rate of change(ROC) of velocity. Early momentum indicators like the RSI and MACD laid foundation for understanding price velocity. However, as markets evolve so do we as technical analysts, we seek the most advanced tools. The Acceleration/Deceleration Oscillator, introduced by Bill Williams, was one of the early attempts to measure acceleration. It helped gauge whether the market was gaining or losing momentum. Over time more specific tools like the "Awesome Oscillator"(AO) emerged, which has a set length on the datasets measured. Gaussian Functions: Named after the mathematician Carl Friedrich Gauss, the Gaussian function describes a bell-shaped curve, often referred to as the "normal distribution." In trading these functions are applied to smooth data and reduce noise, focusing on underlying patterns. The Gaussian Acceleration Array leverages this function to create a smoothed representation of market acceleration. How does it work? This indicator calculates acceleration based the highs and lows of each dataset Once the weighted average for velocity is determined, its rate of change essentially becomes the acceleration It then plots multiple lines with customizable variance from the primary selected length Practical Tips: The Gaussian Acceleration Array offers various customizable parameters, including the sample period, smoothing function, and array variance. Experiment with these settings to tailor it to preferred timeframes and styles. The color-coded lines and background zones make it easier to interpret the indicator at a glance. The backgrounds indicate increasing or decreasing momentum simply as a visual aid while the lines state how the velocity average is performing. Combining this with other tools can signal shifts in market dynamics.
Pine Script® indicator
by NantzOS
Parabolic Scalp Take Profit[ChartPrime]Indicators can be a great way to signal when the optimal time is for taking profits. However, many indicators are lagging in nature and will get market participants out of their trades at less than optimal price points. This take profit indicator uses the concept of slope and exponential gain to calculate when the optimal time is to take profits on your trades, thus making this a leading indicator. Usage: In essence the indicator will draw a parabolic line that starts from the market participants entry point and exponentially grows the slope of the line eventually intersecting with the price action. When price intersects with the parabolic line a take profit signal will appear in the form of an x. We have found that this take profit indicator is especially useful for scalp trades on lower timeframes. How To Use: Add the indicator to the chart. Click on the candle which the trade is on. Click on either the price which the trade will be at, or at the bottom of the candle in a long, or the top of a candle in a short. Select long or short. Open the settings of the indicator and adjust the aggressiveness to the desired value. Settings: - Start Time -- This is the bar in which your entry will be at, or occured at and the script will ask you to click on the bar with your mouse upon first adding the script. - Start Price -- This is the price in which the entry will be at, or was at and the script will ask you to click on the price with your mouse upon first adding the script. - Long/Short -- This is a setting which lets the script know if it is a long or a short trade, and the script will ask you to confirm this upon first adding it to the chart. - Aggressiveness -- This directly affects how aggressive the exponential curve is. A value of 101 is the lowest possible setting, indicating a very non-aggressive exponential buildup. A value of 200 is the highest and most aggressive setting, indicating a doubling effect per bar on the slope.
Pine Script® indicator
by ChartPrime
5
Alson Chew PAM EXE and Mother BarIndicators for strategies taught by Alson Chew's Price Action Manipulation (PAM) course Two functions. First it identifies EXE bars (Pin, Mark, Icecream bars). Second it identifies Mother bars and draws an extension line for 6 bars. Applicable to all time frames and can customise how many signals to show. To be used in conjunction with trading strategies like - 20 SMA, 50 SMA, 200 SMA FS formation - Force Bottom, Force Top FS formation - UR1 and DR1 using EXE Bar
Pine Script® indicator
by LimYX
1
MA - Multi-Indicator Dashboard📊 MULTI-INDICATOR DASHBOARD WITH ENTRY QUALITY SCORE A comprehensive trading dashboard that combines multiple technical indicators into a single, easy-to-read display with a proprietary Entry Quality Scoring System (0-100). ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 ENTRY QUALITY SCORE (0-100) Based on Mark Minervini's Trend Template and academic research on indicator correlations, this scoring system evaluates 5 key categories with 15 sub-criteria: 📈 TREND STRUCTURE (30%) • SMA Hierarchy: 20>50>150>200 alignment (/15) • 200 SMA Direction: Rising for at least 1 month (/10) • SMA20-50 Momentum: Positive and increasing (/5) ⚡ MOMENTUM (25%) • ADX Trend Strength: 25+ indicates strong trend (/10) • RSI Goldilocks Zone: 50-65 ideal entry range (/8) • MACD: Positive histogram and increasing (/7) 📊 VOLUME/MONEY FLOW (20%) • Relative Volume: 1.5x+ shows strong participation (/7) • OBV Trend: Institutional accumulation signal (/6) • CMF: 0.10+ indicates strong accumulation (/5) • Volume Oscillator: Volume expansion (/2) 🌊 VOLATILITY & SQUEEZE (15%) • Squeeze Status: Fired + positive momentum (/8) • VCR: <0.75 contraction signal (/4) • ATR: Normal range volatility (/3) 📍 52-WEEK POSITION (10%) • Range Position: 70-95% ideal zone (/6) • Distance from Low: 30%+ Minervini criterion (/4) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 SCORE LEVELS 🟢 85-100: EXCELLENT → Aggressive entry 🟢 70-84: STRONG → Normal entry 🟡 55-69: MODERATE → Cautious entry 🟠 40-54: WEAK → Wait/Watch 🔴 0-39: AVOID → No entry ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📋 DASHBOARD INDICATORS • Price & SMA Values (20, 50, 150, 200) • SMA Differences & Ratios • RSI (14), MACD (20,50,9), ADX (14/50) • ATR (50), 52-Week High/Low • OBV Trend, Volume Oscillator, Relative Volume • CMF (21), Volatility Contraction Ratio • BB/KC Squeeze Status & Momentum • 3-Month Net Area calculations • Sub-score breakdown by category ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ SETTINGS • Show/Hide Dashboard • Table Position (6 options) • Table Size (tiny/small/normal/large) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📚 REFERENCES • Mark Minervini - "Trade Like a Stock Market Wizard" • Mark Minervini - "Think & Trade Like a Champion" • Wilder, J.W. - "New Concepts in Technical Trading Systems" ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ DISCLAIMER This indicator is for educational purposes only. Always do your own research and use proper risk management. Past performance does not guarantee future results.
Pine Script® indicator
by mustafaaydinol
Previous Day, Pre Market and ORB LevelsDescription This indicator is designed for intraday traders who need significant price levels—Previous Day, Premarket, and Opening Ranges—without the visual clutter that typically plagues multi-level indicators. Unlike standard indicators that draw lines across your entire chart history, this script focuses purely on the current trading day. It draws levels starting from the daily open and extends them into the future, keeping your historical price action clean and readable. Key Features Previous Day Levels: Automatically plots Previous Day High (PDH), Low (PDL), and Close (PDC). Premarket Levels: Tracks the High and Low of the premarket session (04:00 – 09:30 NY). Opening Range Breakout (ORB): Automatically detects and plots the 5-minute and 15-minute Opening Range Highs and Lows. Clean Charting: Lines and labels are only drawn for the current active day. Old levels from previous days are automatically removed to prevent "chart noise." Fully Customizable: Toggle any level on/off and customize colors to match your chart theme via the settings menu. How It Works Daily Data: Uses request.security to fetch the previous day's High, Low, and Close without repainting. Session Logic: The script utilizes specific time sessions (set to New York time) to capture the Premarket range and the first 5 and 15 minutes of the regular session for ORB calculations. Dynamic Drawing: Using Pine Script's line.new and label.new functions, the indicator draws levels only on the last bar, ensuring the lines stay relevant to the current price action.
Pine Script® indicator
by nicholaslimwc
Resonance Alpha: Core Panic MatrixThis is a professional publishing description for your primary module, Resonance Alpha: Core Panic Matrix. It is designed to be cold, factual, and logically structured to appeal to serious quantitative traders on TradingView. Resonance Alpha: Core Panic Matrix 1. System Overview (Trilogy Framework) The Resonance Alpha: Core Panic Matrix is the foundational module of the "Resonance Alpha" trilogy. It focuses on the cross-market synchronization between retail price-action panic and institutional hedging activity. This system is comprised of three specialized tools: Core Panic Matrix: Identifies high-probability bottom zones through "Double Panic" resonance. Momentum Decay: Analyzes the acceleration/deceleration of fear (DVOL Delta). Energy Accumulator: Quantifies the total buildup and exhaustion of market insurance premiums (DVOL CVD). 2. Design Philosophy Most bottom-finding indicators rely solely on price回撤 (price drawdowns), which leads to "catching falling knives" in strong downtrends. Core Panic Matrix solves this by adding a cold, data-driven filter: Institutional Implied Volatility (DVOL). Retail Sentiment: Monitored via a modified Williams Vix Fix (WVF), which tracks current price distance from recent cycle highs. Institutional Sentiment: Monitored via the Deribit DVOL Index, representing the real cost of protecting portfolios against further crashes. The "Alpha" is generated when both metrics peak simultaneously, signaling a high-conviction market capitulation. 3. Visual Logic & Usage Orange Histogram (Retail Capitulation): Indicates that the current price drop has reached a historical extreme relative to the last 22 periods. This is the "Pain Zone." Aqua Background (Institutional Resonance): This is the "Execution Zone." It only appears when the Orange Histogram is active AND the DVOL Index is above its 20-period moving average. The "Double Panic" Signal: Orange Only: Retail is panicking, but institutions remain calm. Likely a minor bounce or further downside. Orange + Aqua Background: Both retail and institutions are in extreme fear. Statistically, this represents a high-probability Short-Term Bottom. 4. Technical Requirements & Settings Data Requirement: This script utilizes request.security to fetch DERIBIT:DVOL. It is specifically optimized for BTC and ETH markets. Timeframes: Most effective on 4H and 1D timeframes for identifying strategic trend reversals. Bilingual Support: All input parameters are labeled in both English and Chinese for global accessibility. 5. Disclaimer & Credits This indicator is based on the Williams Vix Fix theory by Larry Williams. Core WVF logic is adapted with respect from the open-source work of community developer TheeHoganator. 这是为您准备的 Resonance Alpha: Core Panic Matrix 的中文版本说明。您可以将其紧跟在英文说明之后发布，以方便中文社区的用户理解其背后的冷酷逻辑。 Resonance Alpha: 核心恐慌矩阵 (Core Panic Matrix) 1. 系统概览（三位一体架构） Resonance Alpha: Core Panic Matrix 是“Resonance Alpha”系列指标的基石模块。它专注于捕捉散户价格行为与机构对冲活动之间的跨市场共振。整套系统由三个专业工具组成： 核心恐慌矩阵 (Core Panic Matrix)：通过“双重恐慌”共振识别高胜率底部区间。 动能衰竭仪 (Momentum Decay)：分析恐惧的加速度与减速过程（DVOL Delta）。 能量累积器 (Energy Accumulator)：量化市场保险溢价的累积与枯竭（DVOL CVD）。 2. 设计思路 大多数抄底指标仅依赖于价格回撤（Price Drawdowns），这在强劲的下跌趋势中极易导致“接飞刀”。 核心恐慌矩阵 通过引入一个基于数据的冷酷过滤器解决了这个问题：机构隐含波动率 (DVOL)。 散户情绪：通过改进的 Williams Vix Fix (WVF) 监测，测量当前价格与近期周期高点之间的距离。 机构情绪：通过 Deribit DVOL 指数 监测，代表了机构为防止进一步崩盘而保护投资组合的真实成本。 当这两个指标同时达到峰值时，代表市场进入了极端放量割肉阶段，通常意味着高信心的趋势反转点即将出现。 3. 视觉逻辑与使用指南 橙色柱状图 (散户崩溃信号)：表示当前价格跌幅相对于过去 22 个周期已达到历史极端水平。这是“痛苦区”。 青色背景 (机构共振信号)：这是“执行区”。它仅在橙色柱状图激活，且 DVOL 指数高于其 20 周期移动平均线时显示。 “双重恐慌”信号识别： 仅显示橙色柱：散户在恐慌，但机构保持冷静。通常只是微弱反弹或进一步下跌的信号。 橙色柱 + 青色背景：散户与机构同时陷入极端恐惧。在统计学上，这代表了一个极具确定性的短期底部区域。 4. 技术要求与设置 数据要求：本脚本使用 request.security 获取 DERIBIT:DVOL 数据。它针对 BTC 和 ETH 市场进行了深度优化。 适用周期：在 4H 和 1D（日线）周期上最为有效，用于识别战略性的趋势反转。 双语支持：所有输入参数均采用中英双语标注，方便全球交易者使用。 5. 免责声明与致谢 本指标基于 Larry Williams 的 Williams Vix Fix 理论。核心 WVF 逻辑改编自社区开发者 TheeHoganator 的开源作品。
Pine Script® indicator
by AAAAAA2020
2
Smart Fear & Greed Index [MarkitTick]💡 This comprehensive technical tool is designed to quantify market sentiment on an asset-specific basis, translating complex price action into a singular, normalized gauge of "Fear" and "Greed." While traditional Fear & Greed indices rely on macro-economic data (like put/call ratios or junk bond demand) generally applied to the broad S&P 500, this script calculates a localized index for the specific chart you are viewing. It synthesizes Momentum, Volatility, Volume, and Price Positioning into a bounded 0-100 oscillator, aiming to identify psychological extremes where market reversals are statistically more likely to occur. ✨ Originality and Utility ● Asset-Specific Sentiment Analysis Most sentiment tools are external to the chart (e.g., news sentiment or broad market indices). The Smart Fear & Greed Index is unique because it internalizes this logic, creating a bespoke psychological profile for any ticker—whether it is Crypto, Forex, or Stocks. It allows traders to see if *this specific asset* is overheated (Greed) or oversold (Fear) relative to its own recent history. ● The "Buy the Fear, Sell the Greed" Logic The script employs a contrarian color-coding philosophy aligned with the famous investment adage: "Be fearful when others are greedy, and greedy when others are fearful." When the indicator shows Fear (Low values), it colors the zone Green, signaling a potential buying opportunity (discount). When the indicator shows Greed (High values), it colors the zone Red, signaling potential downside risk (premium). ● Integrated Divergence Detection Unlike standard oscillators that leave interpretation entirely to the user, this tool includes an automated divergence engine. It detects discrepancies between the sentiment index and price action, plotting lines and labels to highlight potential exhaustion points before they become obvious on the price chart. 🔬 Methodology and Concepts The calculation is driven by a custom User-Defined Type (UDT) called QuantEngine , which aggregates four distinct technical "pillars" to form the final Composite Index. • Pillar 1: Momentum (RSI) The engine utilizes the Relative Strength Index to measure the velocity and magnitude of directional price movements. High momentum contributes to the "Greed" score, while collapsing momentum contributes to "Fear." • Pillar 2: Volatility (Inverted Normalized ATR) This component interprets volatility through a psychological lens. Low Volatility is interpreted as complacency or "Greed" (steady uptrends often have low vol). High Volatility is interpreted as "Fear" (panic selling and erratic ranges often spike volatility). The script normalizes the Average True Range (ATR) and inverts it so that stability adds to the score, and instability subtracts from it. • Pillar 3: Volume Strength Volume is analyzed relative to its moving average. However, raw volume isn't enough; the engine applies directional logic. High relative volume on an Up-Close adds to the Greed score. High relative volume on a Down-Close subtracts, adding to the Fear score. • Pillar 4: Price Position (Stochastic) This calculates where the current close sits relative to the recent High-Low range. Closing near the highs indicates confidence (Greed), while closing near the lows indicates pessimism (Fear). • The Composite & Smoothing These four metrics are averaged to create a raw composite, which is then smoothed via an Exponential Moving Average (EMA) to filter out noise and produce the final, readable "Smart Fear & Greed" line. 🎨 Visual Guide ● The Oscillator Line This is the primary fluctuating line that moves between 0 and 100. Values > 50 suggest positive sentiment. Values < 50 suggest negative sentiment. ● Color-Coded Zones The plot changes color dynamically to reflect the psychological state: Red (70-100): Extreme Greed. The market may be irrationally exuberant. Orange (60-70): Greed. Strong bullish conviction. Yellow (40-60): Neutral. Indecisive or transitionary market. Light Green (30-40): Fear. Sentiment is turning bearish. Bright Green (0-30): Extreme Fear. Panic selling, often a precursor to a value bounce. ● Background Highlights A semi-transparent Red Background appears when the index breaches 75, warning of a potential "Top." A semi-transparent Green Background appears when the index drops below 25, highlighting a potential "Bottom." ● Divergence Elements Red Lines/Labels ("Bear"): Bearish Divergence. Price makes a Higher High, but the Index makes a Lower High. This suggests momentum is waning despite rising prices. Green Lines/Labels ("Bull"): Bullish Divergence. Price makes a Lower Low, but the Index makes a Higher Low. This suggests selling pressure is drying up. 📖 How to Use • Identifying Reversals Wait for the oscillator to enter "Extreme" zones. Do not trade immediately upon entry; wait for the line to exit the extreme zone to confirm the reversal. For example, if the line hits 80 (Red) and then crosses back down below 70, it signals that Greed is fading. • Trend Continuation In a strong trend, the indicator may hover in the Greed (Orange) or Fear (Light Green) zones for extended periods. In these cases, use the Neutral (Yellow) zone crosses as re-entry signals in the direction of the trend. • Divergence Confirmation Use the automated divergence lines as high-conviction triggers. If the background turns Green (Extreme Fear) AND a Bullish Divergence label appears, it provides a stronger technical case for a long position than the zone alone. ⚙️ Inputs and Settings ● Calculation Settings Global Lookback Period (Default: 21): The core lookback window for RSI, ATR, Volume, and Stochastic calculations. Increasing this makes the index slower and less reactive; decreasing it makes it faster. Smoothing Length (Default: 5): Determines how smooth the final line is. Higher numbers reduce "whipsaws" but add lag. Color Main Chart Candles : Colors the chart bars based on Fear/Greed sentiment. ● Divergence Settings Divergence Lookback (Default: 5): Determines the pivot strength required to register a high or low for divergence checks. Show Divergence Lines/Labels: Toggles to hide visual clutter if you only want to see the oscillator. 🔍 Deconstruction of the Underlying Scientific and Academic Framework ● Normalization Theory The core scientific principle here is Min-Max Normalization. The script takes heterogeneous data types—Price (Dollars/Cents), Volume (Shares/Contracts), and Volatility (Points)—and standardizes them into a unit-less distribution between 0 and 100. This allows for the summation of disparate market forces into a single vector. ● Mean Reversion and Oscillator Bounds The indicator relies on the statistical concept of Mean Reversion. Markets, like elastic bands, can only stretch so far from their average valuation (represented by the 50 line) before snapping back. The "Extreme" zones (Upper and Lower deciles) represent areas of statistical improbability where the likelihood of a continuation decreases and the likelihood of a reversion increases. ● Divergence and Momentum Theory The divergence logic is grounded in the principle that momentum precedes price. Mathematically, price is the integral of velocity. When the derivative (momentum/sentiment) approaches zero or reverses while the function (price) continues, it signals a non-sustainable anomaly in the data series, often resolved by a price correction. ⚠️ Disclaimer All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Pine Script® indicator
by MarkitTick
Auto S/R Zones + EMA + VWAP StrategyStrategy Overview This strategy combines Auto Support & Resistance Zones, Exponential Moving Average (EMA), and VWAP to identify high-probability trade setups using market structure, trend direction, and institutional price levels. The goal is to trade only when price aligns with key zones, trend bias, and volume-weighted price, reducing false signals and emotional decision-making. Indicators Used Auto Support & Resistance Zones – Identifies key institutional price zones automatically EMA – Determines trend direction and momentum VWAP – Confirms institutional bias and fair value Market Bias Rules Bullish Bias Price is above the EMA Price is above VWAP Bearish Bias Price is below the EMA Price is below VWAP Trades are taken only in the direction of the confirmed bias.
Pine Script® strategy
by murali_kolipaka1306
Advanced Petroleum Market Model (APMM)Advanced Petroleum Market Model (APMM): A Multi-Factor Fundamental Analysis Framework for Oil Market Assessment ## 1. Introduction The petroleum market represents one of the most complex and globally significant commodity markets, characterized by intricate supply-demand dynamics, geopolitical influences, and substantial price volatility (Hamilton, 2009). Traditional fundamental analysis approaches often struggle to synthesize the multitude of relevant indicators into actionable insights due to data heterogeneity, temporal misalignment, and subjective weighting schemes (Baumeister & Kilian, 2016). The Advanced Petroleum Market Model addresses these limitations through a systematic, quantitative approach that integrates 16 verified fundamental indicators across five critical market dimensions. The model builds upon established financial engineering principles while incorporating petroleum-specific market dynamics and adaptive learning mechanisms. ## 2. Theoretical Framework ### 2.1 Market Efficiency and Information Integration The model operates under the assumption of semi-strong market efficiency, where fundamental information is gradually incorporated into prices with varying degrees of lag (Fama, 1970). The petroleum market's unique characteristics, including storage costs, transportation constraints, and geopolitical risk premiums, create opportunities for fundamental analysis to provide predictive value (Kilian, 2009). ### 2.2 Multi-Factor Asset Pricing Theory Drawing from Ross's (1976) Arbitrage Pricing Theory, the model treats petroleum prices as driven by multiple systematic risk factors. The five-factor decomposition (Supply, Inventory, Demand, Trade, Sentiment) represents economically meaningful sources of systematic risk in petroleum markets (Chen et al., 1986). ## 3. Methodology ### 3.1 Data Sources and Quality Framework The model integrates 16 fundamental indicators sourced from verified TradingView economic data feeds: Supply Indicators: - US Oil Production (ECONOMICS:USCOP) - US Oil Rigs Count (ECONOMICS:USCOR) - API Crude Runs (ECONOMICS:USACR) Inventory Indicators: - US Crude Stock Changes (ECONOMICS:USCOSC) - Cushing Stocks (ECONOMICS:USCCOS) - API Crude Stocks (ECONOMICS:USCSC) - API Gasoline Stocks (ECONOMICS:USGS) - API Distillate Stocks (ECONOMICS:USDS) Demand Indicators: - Refinery Crude Runs (ECONOMICS:USRCR) - Gasoline Production (ECONOMICS:USGPRO) - Distillate Production (ECONOMICS:USDFP) - Industrial Production Index (FRED:INDPRO) Trade Indicators: - US Crude Imports (ECONOMICS:USCOI) - US Oil Exports (ECONOMICS:USOE) - API Crude Imports (ECONOMICS:USCI) - Dollar Index (TVC:DXY) Sentiment Indicators: - Oil Volatility Index (CBOE:OVX) ### 3.2 Data Quality Monitoring System Following best practices in quantitative finance (Lopez de Prado, 2018), the model implements comprehensive data quality monitoring: Data Quality Score = Σ(Individual Indicator Validity) / Total Indicators Where validity is determined by: - Non-null data availability - Positive value validation - Temporal consistency checks ### 3.3 Statistical Normalization Framework #### 3.3.1 Z-Score Normalization The model employs robust Z-score normalization as established by Sharpe (1994) for cross-indicator comparability: Z_i,t = (X_i,t - μ_i) / σ_i Where: - X_i,t = Raw value of indicator i at time t - μ_i = Sample mean of indicator i - σ_i = Sample standard deviation of indicator i Z-scores are capped at ±3 to mitigate outlier influence (Tukey, 1977). #### 3.3.2 Percentile Rank Transformation For intuitive interpretation, Z-scores are converted to percentile ranks following the methodology of Conover (1999): Percentile_Rank = (Number of values < current_value) / Total_observations × 100 ### 3.4 Exponential Smoothing Framework Signal smoothing employs exponential weighted moving averages (Brown, 1963) with adaptive alpha parameter: S_t = α × X_t + (1-α) × S_{t-1} Where α = 2/(N+1) and N represents the smoothing period. ### 3.5 Dynamic Threshold Optimization The model implements adaptive thresholds using Bollinger Band methodology (Bollinger, 1992): Dynamic_Threshold = μ ± (k × σ) Where k is the threshold multiplier adjusted for market volatility regime. ### 3.6 Composite Score Calculation The fundamental score integrates component scores through weighted averaging: Fundamental_Score = Σ(w_i × Score_i × Quality_i) Where: - w_i = Normalized component weight - Score_i = Component fundamental score - Quality_i = Data quality adjustment factor ## 4. Implementation Architecture ### 4.1 Adaptive Parameter Framework The model incorporates regime-specific adjustments based on market volatility: Volatility_Regime = σ_price / μ_price × 100 High volatility regimes (>25%) trigger enhanced weighting for inventory and sentiment components, reflecting increased market sensitivity to supply disruptions and psychological factors. ### 4.2 Data Synchronization Protocol Given varying publication frequencies (daily, weekly, monthly), the model employs forward-fill synchronization to maintain temporal alignment across all indicators. ### 4.3 Quality-Adjusted Scoring Component scores are adjusted for data quality to prevent degraded inputs from contaminating the composite signal: Adjusted_Score = Raw_Score × Quality_Factor + 50 × (1 - Quality_Factor) This formulation ensures that poor-quality data reverts toward neutral (50) rather than contributing noise. ## 5. Usage Guidelines and Best Practices ### 5.1 Configuration Recommendations For Short-term Analysis (1-4 weeks): - Lookback Period: 26 weeks - Smoothing Length: 3-5 periods - Confidence Period: 13 weeks - Increase inventory and sentiment weights For Medium-term Analysis (1-3 months): - Lookback Period: 52 weeks - Smoothing Length: 5-8 periods - Confidence Period: 26 weeks - Balanced component weights For Long-term Analysis (3+ months): - Lookback Period: 104 weeks - Smoothing Length: 8-12 periods - Confidence Period: 52 weeks - Increase supply and demand weights ### 5.2 Signal Interpretation Framework Bullish Signals (Score > 70): - Fundamental conditions favor price appreciation - Consider long positions or reduced short exposure - Monitor for trend confirmation across multiple timeframes Bearish Signals (Score < 30): - Fundamental conditions suggest price weakness - Consider short positions or reduced long exposure - Evaluate downside protection strategies Neutral Range (30-70): - Mixed fundamental environment - Favor range-bound or volatility strategies - Wait for clearer directional signals ### 5.3 Risk Management Considerations 1. Data Quality Monitoring: Continuously monitor the data quality dashboard. Scores below 75% warrant increased caution. 2. Regime Awareness: Adjust position sizing based on volatility regime indicators. High volatility periods require reduced exposure. 3. Correlation Analysis: Monitor correlation with crude oil prices to validate model effectiveness. 4. Fundamental-Technical Divergence: Pay attention when fundamental signals diverge from technical indicators, as this may signal regime changes. ### 5.4 Alert System Optimization Configure alerts conservatively to avoid false signals: - Set alert threshold at 75+ for high-confidence signals - Enable data quality warnings to maintain system integrity - Use trend reversal alerts for early regime change detection ## 6. Model Validation and Performance Metrics ### 6.1 Statistical Validation The model's statistical robustness is ensured through: - Out-of-sample testing protocols - Rolling window validation - Bootstrap confidence intervals - Regime-specific performance analysis ### 6.2 Economic Validation Fundamental accuracy is validated against: - Energy Information Administration (EIA) official reports - International Energy Agency (IEA) market assessments - Commercial inventory data verification ## 7. Limitations and Considerations ### 7.1 Model Limitations 1. Data Dependency: Model performance is contingent on data availability and quality from external sources. 2. US Market Focus: Primary data sources are US-centric, potentially limiting global applicability. 3. Lag Effects: Some fundamental indicators exhibit publication lags that may delay signal generation. 4. Regime Shifts: Structural market changes may require model recalibration. ### 7.2 Market Environment Considerations The model is optimized for normal market conditions. During extreme events (e.g., geopolitical crises, pandemics), additional qualitative factors should be considered alongside quantitative signals. ## References Baumeister, C., & Kilian, L. (2016). Forty years of oil price fluctuations: Why the price of oil may still surprise us. *Journal of Economic Perspectives*, 30(1), 139-160. Bollinger, J. (1992). *Bollinger on Bollinger Bands*. McGraw-Hill. Brown, R. G. (1963). *Smoothing, Forecasting and Prediction of Discrete Time Series*. Prentice-Hall. Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. *Journal of Business*, 59(3), 383-403. Conover, W. J. (1999). *Practical Nonparametric Statistics* (3rd ed.). John Wiley & Sons. Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. *Journal of Finance*, 25(2), 383-417. Hamilton, J. D. (2009). Understanding crude oil prices. *Energy Journal*, 30(2), 179-206. Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. *American Economic Review*, 99(3), 1053-1069. Lopez de Prado, M. (2018). *Advances in Financial Machine Learning*. John Wiley & Sons. Ross, S. A. (1976). The arbitrage theory of capital asset pricing. *Journal of Economic Theory*, 13(3), 341-360. Sharpe, W. F. (1994). The Sharpe ratio. *Journal of Portfolio Management*, 21(1), 49-58. Tukey, J. W. (1977). *Exploratory Data Analysis*. Addison-Wesley.
Pine Script® indicator
by EdgeTools
Divergences RefurbishedJust as "a butterfly can flap its wings over a flower in China and cause a hurricane in the Caribbean" (Edward Lorenz), small divergences in markets can signal big trading opportunities. █Introduction This is a script forked from LonesomeTheBlue's Divergence for Many Indicators v4. It is a script that checks for divergence between price and many indicators. In this version, I added more indicators and also added 40 symbols to check for divergences. More info on the original script can be found here: █ Improvements The following improvements have been implemented over v4: 1. Added parameters to customize indicators. 2. Added new indicators: - Stoch RSI - Volume Oscillator - PVT (Price Volume Trend) - Ultimate Oscillator - Fisher Transform - Z-Score/T-Score 3. Now there is the possibility of using 2 external indicators. 4. New option to show tooltips inside labels. This allows you to save space on the screen if you choose the option to only show the number of divergences or just the abbreviations. 5. New option to show additional text next to the indicator name. This allows for grouping of indicators and symbols and better visualization, whether through emojis, for example. 6. Added 40 customizable symbols to check for divergences. 7. Option "show only the first letter" of the indicator replaced by: "show the abbreviation of the indicator". Reason: the indicator abbreviation is more informative and easier to read. 8. Script converted to PineScript version 5. █ CONCEPTS Below I present a brief description of the available indicators. 1. Moving Average Convergence/Divergence (MACD): Shows the difference between short-term and long-term exponential moving averages. 2. MACD Histogram: Shows the difference between MACD and its signal line. 3. Relative Strength Index (RSI): Measures the relative strength of recent price gains to recent price losses of an asset. 4. Stochastic Oscillator (Stoch): Compares the current price of an asset to its price range over a specified time period. 5. Stoch RSI: Stochastic of RSI. 6. Commodity Channel Index (CCI): Measures the relationship between an asset's current price and its moving average. 7. Momentum: Shows the difference between the current price and the price a few periods ago. Shows the difference between the current price and the price of a certain period in the past. 8. Chaikin Money Flow (CMF): A variation of A/D that takes into account the daily price variation and weighs trading volume accordingly. Accumulation/Distribution (A/D) identifies buying and selling pressure by tracking the flow of money into and out of an asset based on volume patterns. 9. On-Balance Volume (OBV): Identify divergences between trading volume and an asset's price. Sum of trading volume when the price rises and subtracts volume when the price falls. 10. Money Flow Index (MFI): Measures volume pressure in a range of 0 to 100. Calculates the ratio of volume when the price goes up and when the price goes down. 11. Volume Oscillator (VO): Identify divergences between trading volume and an asset's price. Ratio of change of volume, from a fast period in relation to a long period. 12. Price-Volume Trend (PVT): Identify the strength of an asset's price trend based on its trading volume. Cumulative change in price with volume factor. The PVT calculation is similar to the OBV calculation, but it takes into account the percentage price change multiplied by the current volume, plus the previous PVT value. 13. Ultimate Oscillator (UO): Combines three different time periods to help identify possible reversal points. 14. Fisher Transform (FT): Normalize prices into a Gaussian normal distribution. 15. Z-Score/T-Score: Shows the difference between the current price and the price a few periods ago. I is a statistical measurement that indicates how many standard deviations a data point is from the mean of a data set. When to use t-score instead of z-score? When the sample size is small (length < 30). Here, the use of z-score or t-score is chosen automatically based on the length parameter. █ What to look for The operation is simple. The script checks for divergences between the price and the selected indicators. Now with the possibility of using multiple symbols, it is possible to check divergences between different assets. A well-described view on divergences can be found in this cheat sheet: ◈ Examples with SPY ETF versus indicators: 1. Regular bullish divergence with external indicator: 1. Regular bearish divergence with Fisher Transform: 1. Positive hidden divergence with Momentum indicator: 1. Negative hidden divergence with RSI: ◈ Examples with SPY ETF versus other symbols: 1. Regular bearish divergence with European Stoch Market: 2. Regular bearish divergence with DXY inverted: 3. Regular bullish divergence with Taiwan Dollar: 4. Regular bearish divergence with US10Y (10-Year US Treasury Note): 5. Regular bullish divergence with QQQ ETF (Nasdaq 100): 6. Regular bullish divergence with ARKK ETF (ARK Innovation): 7.Positive hidden divergence with RSP ETF (S&P 500 Equal Weight): 8. Negative hidden divergence with EWZ ETF (Brazil): ◈ Examples with BTCUSD versus other symbols: 1. Regular bearish divergence with BTCUSDLONGS from Bitfinex: 2. Regular bearish divergence with BLOK ETF (Amplify Transformational Data Sharing): 3. Negative hidden divergence with NATGAS (Natural Gas): 4. Positive hidden divergence with TOTALDEFI (Total DeFi Market Cap): █ Conclusion The symbols available to check divergences were chosen in such a way as to cover the main markets, in the most generic way possible. You can adjust them according to your needs. A trader in the American market, for example, could add more ETFs, American stocks, and sectoral indices, such as the XLF (Financial Select Sector SPDR Fund), the XLK (Technology Select Sector SPDR), etc. On the other hand, a cryptocurrency trader could add more currency pairs and sector indicators, such as BTCUSDSHORTS (Bitfinex), USDT.D (Tether Dominance), etc. If the chart becomes too cluttered, you can use the option to show only the number of divergences or only the indicator abbreviations. Or even disable certain indicators and symbols, if they are not of interest to you. I hope this script is useful. Don't forget to support LonesomeTheBlue's work too.
Pine Script® indicator
by andre_007
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