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SPY → ES 11 Levels with Labels📌 Description for SPY → ES 11-Level Converter (with Labels) This script converts important SPY options-based levels into their equivalent ES futures prices and plots them directly on the ES chart. Because SPY trades at a different price scale than ES, each SPY level is multiplied by a customizable ES/SPY ratio to project accurate ES levels. It is designed for traders who use SpotGamma, GEXBot, MenthorQ, Vol-trigger levels, or their own gamma/oi/volume models. 🔍 Features ✅ Converts SPY → ES using custom or automatic ratio Option to manually enter a ratio (recommended for accuracy) Or automatically compute ES/SPY from live prices ✅ Plots 11 major levels on the ES chart Each level can be individually turned ON/OFF: Call Wall Put Wall Volume Trigger Spot Price +Gamma Level –Gamma Level Zero Gamma Positive OI Negative OI Positive Volume Negative Volume All levels are drawn as clean horizontal lines using the converted ES value.
مؤشر Pine Script®
من ‎CarolClays‎
Kira EMA 9-21 + VWAP Buy/Sell🔥 KIRA MOMENTUM SETUP – BUY & SELL SYSTEM Simple • Powerful • Trend-Based ✅ BUY CONDITION 🟢 EMA 9 crosses ABOVE EMA 21 AND Price closes ABOVE VWAP 🔴 SELL CONDITION EMA 9 crosses BELOW EMA 21 AND Price closes BELOW VWAP 🚫 NO TRADE ZONE ❌ EMAs tangled ❌ Price chopping around VWAP 🎯 BEST TIMEFRAMES ✅ 5-Minute ✅ 15-Minute (Indices & highly liquid stocks) ⚠️ RISK RULE • Buy SL ➝ Below recent swing low • Sell SL ➝ Above recent swing high • Risk per trade ≤ 1%
مؤشر Pine Script®
من ‎kirainvestors‎
67Major Market Trading Hours New York Stock Exchange (NYSE) Open: 9:30 AM (ET) Close: 4:00 PM (ET) Pre-Market: 4:00 AM – 9:30 AM (ET) After Hours: 4:00 PM – 8:00 PM (ET) Nasdaq Open: 9:30 AM (ET) Close: 4:00 PM (ET) Pre-Market: 4:00 AM – 9:30 AM (ET) After Hours: 4:00 PM – 8:00 PM (ET) London Stock Exchange (LSE) Open: 8:00 AM (GMT) Close: 4:30 PM (GMT) Tokyo Stock Exchange (TSE) Open: 9:00 AM (JST) Lunch Break: 11:30 AM – 12:30 PM (JST) Close: 3:00 PM (JST) Hong Kong Stock Exchange (HKEX) Open: 9:30 AM (HKT) Lunch Break: 12:00 PM – 1:00 PM (HKT) Close: 4:00 PM (HKT) If you'd like anything bigger, bold, color‑coded, or reorganized, just tell me and I’ll adjust it!
مؤشر Pine Script®
من ‎nyzilakos‎
Adaptive Support & Resistance ProAdaptive Support & Resistance Pro – Description Adaptive Support & Resistance Pro is an advanced S/R tool designed to automatically identify key support and resistance zones based on a combination of RSI, CMO dynamics, and pivot logic. This indicator provides precise and reactive levels that form only when specific technical conditions are met, filtering out noise and delivering more reliable S/R signals. It is ideal for technical traders who want to understand where price naturally pauses, reverses, or consolidates—without the need to manually draw lines on every chart. 🔍 Key Features 1. Automatic Support & Resistance Detection The indicator uses: RSI (9) CMO logic based on HMA Pivot structure (len = 2) to generate valid Support and Resistance zones. A level is drawn only when all required conditions align, preventing false or weak signals. 2. Multi-Timeframe Analysis (MTF) You can view the chart on one timeframe (e.g., 5m) and display Support/Resistance levels from another timeframe (e.g., 1H, 4H, D) at the same time. This allows for: viewing higher-timeframe structures on lower charts, better planning of entries and exits, avoiding trades inside strong zones that may not be visible on the current timeframe. All of this is controlled through the input: S/R Timeframe 3. Adjustable Line Thickness (visual enhancement) Using the input: Line Width you can increase the thickness of support/resistance lines to: make important zones more visible, improve chart readability, emphasize S/R levels according to your visual preference. This is especially useful on fast markets (Forex, Crypto) and on higher timeframes where clarity of levels is essential. 4. Clear distinction between Support and Resistance Support lines have their own customizable color (default: green) Resistance lines have their own customizable color (default: red) You can freely adjust the colors to match your personal TradingView layout or theme. 5. Alerts (Notification System) The built-in alert: "New S/R line" triggers whenever a new support or resistance level is detected. This helps you: monitor important levels without constantly watching the chart, react quickly to new structure signals, stay aware of market changes in real time. 🎯 How to Use the Indicator Support levels often indicate potential reversals or long-entry opportunities. Resistance levels highlight areas where price may reverse downward or form short setups. The best performance is achieved when combining this indicator with: price action, EMA structure, confirmation zones, breakout logic, trend filters. MTF usage is highly recommended: Analyze higher-timeframe S/R while trading lower-timeframe setups. ⚠️ Disclaimer This indicator does not generate direct buy or sell signals. Its purpose is to assist in market analysis and highlight areas where price is likely to react. 📌 Conclusion Adaptive Support & Resistance Pro combines the strongest elements of automated S/R mapping: precision, reduced noise, multi-timeframe flexibility, and advanced logic based on RSI, CMO, and pivot structure. It is perfect for traders who want: clean and accurate S/R levels, higher-timeframe insight while trading lower charts, customizable and visually enhanced structure mapping.
مؤشر Pine Script®
من ‎Aleksin_Aleksandar‎
6
Bollinger Bands with ATR SL Hariss 369Bollinger Bands are a popular technical analysis tool developed by John Bollinger. They consist of three lines plotted on a price chart: Middle Band – a simple moving average (usually 20 periods). Upper Band – the middle band plus two standard deviations. Lower Band – the middle band minus two standard deviations. Key Features: Volatility Indicator: The bands expand when volatility increases and contract when volatility decreases. Trend Analysis: Prices near the upper band indicate overbought conditions, while prices near the lower band indicate oversold conditions. Trading Signals: Traders often look for price touches, breaks, or rebounds from the bands to identify potential entries or exits. To strengthen the trend quality RVOL has been considered. The ideal value of RVOL is 1.5 Higher Time Frame Trend filter gives trend clarity in higher time frame. One can select RVOL and HTF (Higher Time Frame) filter. Bollinger bands indicator is basically a trend following indicator. We should go with the trend rather book profit @1:1 or 1:2 basis. In that case we might miss the long trend. The middle band is generally considered as stop loss. However, ATR based stop loss has been designed in the script in order to capture the volatility in decent way. Break out signal is initiated on break out with volume taking higher time frame into consideration. One can use this indicator in any time frame and any class of asset. To filter higher time frame eg. entry / exit 5 min chart, 15m/1h can be taken as higher time frame, for 1h entry/ exit, 4h can be taken as higher time frame trend filter.
مؤشر Pine Script®
من ‎Hariss369‎
RSI Forecast Colorful [DiFlip]RSI Forecast Colorful Introducing one of the most complete RSI indicators available — a highly customizable analytical tool that integrates advanced prediction capabilities. RSI Forecast Colorful is an evolution of the classic RSI, designed to anticipate potential future RSI movements using linear regression. Instead of simply reacting to historical data, this indicator provides a statistical projection of the RSI’s future behavior, offering a forward-looking view of market conditions. ⯁ Real-Time RSI Forecasting For the first time, a public RSI indicator integrates linear regression (least squares method) to forecast the RSI’s future behavior. This innovative approach allows traders to anticipate market movements based on historical trends. By applying Linear Regression to the RSI, the indicator displays a projected trendline n periods ahead, helping traders make more informed buy or sell decisions. ⯁ Highly Customizable The indicator is fully adaptable to any trading style. Dozens of parameters can be optimized to match your system. All 28 long and short entry conditions are selectable and configurable, allowing the construction of quantitative, statistical, and automated trading models. Full control over signals ensures precise alignment with your strategy. ⯁ Innovative and Science-Based This is the first public RSI indicator to apply least-squares predictive modeling to RSI calculations. Technically, it incorporates machine-learning logic into a classic indicator. Using Linear Regression embeds strong statistical foundations into RSI forecasting, making this tool especially valuable for traders seeking quantitative and analytical advantages. ⯁ Scientific Foundation: Linear Regression Linear regression is a fundamental statistical method that models the relationship between a dependent variable y and one or more independent variables x. The general formula for simple linear regression is: y = β₀ + β₁x + ε where: y  = predicted variable (e.g., future RSI value) x  = explanatory variable (e.g., bar index or time) β₀ = intercept (value of y when x = 0) β₁ = slope (rate of change of y relative to x) ε   = random error term The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the RSI projection based on recent trends. ⯁ Least Squares Estimation To minimize the error between predicted and observed values, we use the formulas: β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²) β₀ = ȳ - β₁x̄ Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables. ⯁ Linear Regression in Machine Learning Linear regression is a foundational component of supervised learning. Its simplicity and precision in numerical prediction make it essential in AI, predictive algorithms, and time-series forecasting. Applying regression to RSI is akin to embedding artificial intelligence inside a classic indicator, adding a new analytical dimension. ⯁ Visual Interpretation Imagine a time series of RSI values like this: Time → RSI    → The regression line smooths these historical values and projects itself n periods forward, creating a predictive trajectory. This projected RSI line can cross the actual RSI, generating sophisticated entry and exit signals. In summary, the RSI Forecast Colorful indicator provides both the current RSI and the forecasted RSI, allowing comparison between past and future trend behavior. ⯁ Summary of Scientific Concepts Used Linear Regression: Models relationships between variables using a straight line. Least Squares: Minimizes squared prediction errors for optimal fit. Time-Series Forecasting: Predicts future values from historical patterns. Supervised Learning: Predictive modeling based on known output values. Statistical Smoothing: Reduces noise to highlight underlying trends. ⯁ Why This Indicator Is Revolutionary Scientifically grounded: Built on statistical and mathematical theory. First of its kind: The first public RSI with least-squares predictive modeling. Intelligent: Incorporates machine-learning logic into RSI interpretation. Forward-looking: Generates predictive, not just reactive, signals. Customizable: Exceptionally flexible for any strategic framework. ⯁ Conclusion By combining RSI and linear regression, the RSI Forecast Colorful allows traders to predict market momentum rather than simply follow it. It's not just another indicator: it's a scientific advancement in technical analysis technology. Offering 28 configurable entry conditions and advanced signals, this open-source indicator paves the way for innovative quantitative systems. ⯁ Example of simple linear regression with one independent variable This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables. ⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x) This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component. ⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models. ⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model. ⯁ Result of fitting a set of data points with a quadratic function This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line. ⯁ What Is RSI? The RSI (Relative Strength Index) is a technical indicator developed by J. Welles Wilder. It measures the velocity and magnitude of recent price movements to identify overbought and oversold conditions. The RSI ranges from 0 to 100 and is commonly used to identify potential reversals and evaluate trend strength. ⯁ How RSI Works RSI is calculated from average gains and losses over a set period (commonly 14 bars) and plotted on a 0–100 scale. It consists of three key zones: Overbought: RSI above 70 may signal an overbought market. Oversold: RSI below 30 may signal an oversold market. Neutral Zone: RSI between 30 and 70, indicating no extreme condition. These zones help identify potential price reversals and confirm trend strength. ⯁ Entry Conditions All conditions below are fully customizable and allow detailed control over entry signal creation. 📈 BUY 🧲 Signal Validity: Signal remains valid for X bars. 🧲 Signal Logic: Configurable using AND or OR. 🧲 RSI > Upper 🧲 RSI < Upper 🧲 RSI > Lower 🧲 RSI < Lower 🧲 RSI > Middle 🧲 RSI < Middle 🧲 RSI > MA 🧲 RSI < MA 🧲 MA > Upper 🧲 MA < Upper 🧲 MA > Lower 🧲 MA < Lower 🧲 RSI (Crossover) Upper 🧲 RSI (Crossunder) Upper 🧲 RSI (Crossover) Lower 🧲 RSI (Crossunder) Lower 🧲 RSI (Crossover) Middle 🧲 RSI (Crossunder) Middle 🧲 RSI (Crossover) MA 🧲 RSI (Crossunder) MA 🧲 MA (Crossover)Upper 🧲 MA (Crossunder)Upper 🧲 MA (Crossover) Lower 🧲 MA (Crossunder) Lower 🧲 RSI Bullish Divergence 🧲 RSI Bearish Divergence 🔮 RSI (Crossover) Forecast MA 🔮 RSI (Crossunder) Forecast MA 📉 SELL 🧲 Signal Validity: Signal remains valid for X bars. 🧲 Signal Logic: Configurable using AND or OR. 🧲 RSI > Upper 🧲 RSI < Upper 🧲 RSI > Lower 🧲 RSI < Lower 🧲 RSI > Middle 🧲 RSI < Middle 🧲 RSI > MA 🧲 RSI < MA 🧲 MA > Upper 🧲 MA < Upper 🧲 MA > Lower 🧲 MA < Lower 🧲 RSI (Crossover) Upper 🧲 RSI (Crossunder) Upper 🧲 RSI (Crossover) Lower 🧲 RSI (Crossunder) Lower 🧲 RSI (Crossover) Middle 🧲 RSI (Crossunder) Middle 🧲 RSI (Crossover) MA 🧲 RSI (Crossunder) MA 🧲 MA (Crossover)Upper 🧲 MA (Crossunder)Upper 🧲 MA (Crossover) Lower 🧲 MA (Crossunder) Lower 🧲 RSI Bullish Divergence 🧲 RSI Bearish Divergence 🔮 RSI (Crossover) Forecast MA 🔮 RSI (Crossunder) Forecast MA 🤖 Automation All BUY and SELL conditions can be automated using TradingView alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies. ⯁ Unique Features Linear Regression Forecast Signal Validity: Keep signals active for X bars Signal Logic: AND/OR configuration Condition Table: BUY/SELL Condition Labels: BUY/SELL Chart Labels: BUY/SELL markers above price Automation & Alerts: BUY/SELL Background Colors: bgcolor Fill Colors: fill Linear Regression Forecast Signal Validity: Keep signals active for X bars Signal Logic: AND/OR configuration Condition Table: BUY/SELL Condition Labels: BUY/SELL Chart Labels: BUY/SELL markers above price Automation & Alerts: BUY/SELL Background Colors: bgcolor Fill Colors: fill
مؤشر Pine Script®
من ‎DiFlip‎
2