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Volume Dominance (Multi-Timeframe)Volume dominance is a mathematical concept i invented by separating up volume and down volume, and replacing the opposing elements in the averaging arrays with zeroes. positive volume dominance is calculated by taking the average of volumes with a positive price direction over a period. for every volume with a negative price direction within the period, a zero is added to the averaging array. Dpv = sum(upVol + (dnVol * 0)) / length Dnv = sum(dnVol + (upVol * 0)) / length Dpv = Dominance of Positive volume Dnv = Dominance of Negative volume upVol = total volume of upward filtered candles within length array dnVol = total volume of downward filtered candles within length array the user can see positive and negative volume dominance and read the label at the end of the plot to see the breadth of the dominance gap. the user can select between using EMA and SMA to compute the dominance averages. when the yellow center line moves with the change of a dominance line, it indicates strong directional force.
Pine Script® göstergesi
Shaeroden tarafından
Nasdaq Market Direction ProbabilitiesA table in the bottom-left corner showing bullish, bearish, and neutral probabilities for Nasdaq market direction, calculated from weighted indicators (moving averages, RSI, volume trend, futures change, and sentiment). A label on the chart with a recommendation ("Long", "Short", or "Monitor") based on the highest probability. A histogram of the bullish probability in a separate pane. The probabilities update on each confirmed bar, using the chart’s timeframe (ideally 60 minutes).
Pine Script® göstergesi
EvilR8 tarafından
Ticker Industry and Competitor LookupThe Ticker Industry and Competitor Lookup is a comprehensive indicator that provides instant access to industry classification data and competitive intelligence for any ticker symbol. Built using the advanced SIC_TICKER_DATA library, this tool delivers professional-grade sector analysis with enterprise-level performance. It's a simple yet great tool for competitor research, sector studies, portfolio diversification, and investment decision-making. This indicator is a simple tool built on based on our SIC_TICKER_DATA library to demonstrate the use cases of the library. In this case, you enter a ticker and it displays the sector, SIC or Standard Industrial Classification which is a SEC identifier, and more importantly, the competitors that are listed to be in the exact same SIC by SEC. There isn't much to say about the indicator itself but we strongly recommend checking out the SIC_TICKER_DATA library we just published to learn more about the types of indicators you can build using it.
Pine Script® göstergesi
EdgeTerminal tarafından
PietasterThis Pine Script (v6) indicator plots a 111-day Simple Moving Average (SMA) and a 2 * 350-day SMA (equivalent to a 700-day SMA) for Bitcoin's price, displayed on any timeframe. It highlights crossover points with vertical lines: green for bullish crossovers (111-day MA crosses above 700-day MA) and purple for bearish crossovers (111-day MA crosses below 700-day MA). Vertical lines extend 50% above the highest price and 50% below the lowest price at the crossover, ensuring visibility through price action. Labels identify the moving averages for clarity.
Pine Script® göstergesi
bfrahm73 tarafından
SIC_TICKER_DATAThe SIC Ticker Data is an advanced and efficient library for ticker-to-industry classification and sector analysis. Built with enterprise-grade performance optimizations, this library provides instant access to SIC codes, industry classifications, and peer company data for comprehensive market analysis. Perfect for: Sector rotation strategies, peer analysis, portfolio diversification, market screening, and financial research tools. The simple idea behind this library is to pull any data related to SIC number of any US stock market ticker provided by SEC in order to see the industry and also see the exact competitors of the ticker. The library stores 3 types of data: SIC number, Ticker, and Industry name. What makes it very useful is that you can pull any one of this data using the other. For example, if you would like to know which tickers are inside a certain SIC, or what's the SIC number of a specific ticker, or even which tickers are inside a certain industry, you can use this library to pull this data. The idea for data inside this library is to be accessible in any direction possible as long as they're related to each other. We've also published a simple indicator that uses this library in order to demonstrate the inner workings of this library. The library stores thousands of tickers and their relevant SIC code and industry for your use and is constantly updated with new data when available. This is a large library but it is optimized to run as fast as possible. The previous unpublished versions would take over 40 seconds to load any data but the final public version here loads the data in less than 5 seconds. 🔍 Primary Lookup Functions createDataStore() Initialize the library with all pre-loaded data. store = data.createDataStore() getSicByTicker(store, ticker) Get SIC code for any ticker symbol. sic = data.getSicByTicker(store, "AAPL") // Returns: "3571" getIndustryByTicker(store, ticker) Get industry classification for any ticker. industry = data.getIndustryByTicker(store, "AAPL") // Returns: "Computer Hardware" getTickersBySic(store, sic) Get all companies in a specific SIC code. software = data.getTickersBySic(store, "7372") // Returns: "MSFT,GOOGL,META,V,MA,CRM,ADBE,ORCL,NOW,INTU" getTickersByIndustry(store, industry) Get all companies in an industry. retail = data.getTickersByIndustry(store, "Retail") // Returns: "AMZN,HD,WMT,TGT,COST,LOW" 📊 Array & Analysis Functions getTickerArrayBySic(store, sic) Get tickers as array for processing. techArray = data.getTickerArrayBySic(store, "7372") for i = 0 to array.size(techArray) - 1 ticker = array.get(techArray, i) // Process each tech company getTickerCountBySic(store, sic) Count companies in a sector (ultra-fast). pinescripttechCount = data.getTickerCountBySic(store, "7372") // Returns: 10 🎯 Utility Functions tickerExists(store, ticker) Check if ticker exists in database. exists = data.tickerExists(store, "AAPL") // Returns: true tickerInSic(store, ticker, sic) Check if ticker belongs to specific sector. isInTech = data.tickerInSic(store, "AAPL", "3571") // Returns: true 💡 Usage Examples Example 1: Basic Ticker Lookup // @version=6 import EdgeTerminal/SIC_TICKER_DATA/1 as data indicator("Ticker Analysis", overlay=true) store = data.createDataStore() currentSic = data.getSicByTicker(store, syminfo.ticker) currentIndustry = data.getIndustryByTicker(store, syminfo.ticker) if barstate.islast and currentSic != "NOT_FOUND" label.new(bar_index, high, syminfo.ticker + " SIC: " + currentSic + " Industry: " + currentIndustry) Example 2: Sector Analysis // @version=6 import EdgeTerminal/SIC_TICKER_DATA/1 as data indicator("Sector Comparison", overlay=false) store = data.createDataStore() // Compare sector sizes techCount = data.getTickerCountBySic(store, "7372") // Software financeCount = data.getTickerCountBySic(store, "6199") // Finance healthCount = data.getTickerCountBySic(store, "2834") // Pharmaceutical plot(techCount, title="Tech Companies", color=color.blue) plot(financeCount, title="Finance Companies", color=color.green) plot(healthCount, title="Health Companies", color=color.red) Example 3: Peer Analysis // @version=6 import EdgeTerminal/SIC_TICKER_DATA/1 as data indicator("Find Competitors", overlay=true) store = data.createDataStore() currentSic = data.getSicByTicker(store, syminfo.ticker) if currentSic != "NOT_FOUND" competitors = data.getTickersBySic(store, currentSic) peerCount = data.getTickerCountBySic(store, currentSic) if barstate.islast label.new(bar_index, high, "Competitors (" + str.tostring(peerCount) + "): " + competitors) Example 4: Portfolio Sector Allocation // @version=6 import EdgeTerminal/SIC_TICKER_DATA/1 as data indicator("Portfolio Analysis", overlay=false) store = data.createDataStore() // Analyze your portfolio's sector distribution portfolioTickers = array.from("AAPL", "MSFT", "GOOGL", "JPM", "JNJ") sectorCount = map.new() for i = 0 to array.size(portfolioTickers) - 1 ticker = array.get(portfolioTickers, i) industry = data.getIndustryByTicker(store, ticker) if industry != "NOT_FOUND" currentCount = map.get(sectorCount, industry) newCount = na(currentCount) ? 1 : currentCount + 1 map.put(sectorCount, industry, newCount) 🔧 Advanced Feature You can also bulk load data for large data sets like this: // Pre-format your data as pipe-separated string bulkData = "AAPL:3571:Computer Hardware|MSFT:7372:Software|GOOGL:7372:Software" store = data.createDataStoreFromBulk(bulkData)
Pine Script® kütüphanesi
EdgeTerminal tarafından
Fusion AI IndicatorWhat is Fusion AI? The Fusion AI Indicator blends three proven momentum & mean-reversion signals into a single composite “AI Score.” By normalizing and weighting EMA crossovers, RSI bias and MACD momentum, you get one clean line that captures multi-factor strength shifts in real time—plus optional price-chart arrows and built-in alerts. How it works Fast vs. Slow EMA (40%) (EMA(fastLen) – EMA(slowLen)) / EMA(slowLen) RSI Deviation (30%) (RSI(rsiLen) – 50) / 50 MACD Momentum (30%) (MACD.line – MACD.signal) / ATR(14) AI Score = 0.4 · EMA + 0.3 · RSI + 0.3 · MACD Thresholds Buy when AI Score crosses up through +Threshold Sell when it crosses down through –Threshold Default Inputs (tuned for balanced signals) Fast MA Length: 12 Slow MA Length: 26 RSI Length: 14 MACD Fast EMA: 12 MACD Slow EMA: 26 MACD Signal Smoothing: 9 AI Score Threshold: 0.30 Show Overlay Arrows: ✔️ Alert on Bar Close Only: ✔️ (You can lower Threshold toward 0.10–0.20 for more frequent signals in quieter markets.) Recommended Markets & Timeframes Bitcoin (BTCUSD) on 1 H, 4 H – captures crypto swings Ethereum (ETHUSD) on 1 H, 4 H AAPL, TSLA, SPY on 15 M, 1 H – ideal for intraday setups How to Add Alerts Add the indicator to your chart. Open Create Alert → Condition → Fusion AI Indicator with Alerts & Overlay → choose Buy Signal or Sell Signal. Set Frequency to Once per bar close (default) or Once per bar. Paste a custom message or use the default: “Fusion AI: Bullish crossover detected” “Fusion AI: Bearish crossunder detected” Usage Tips Combine with volume filters or support/resistance zones for higher-probability entries. Use the gradient-colored subchart to spot building momentum even before arrows appear. Back-test threshold levels per asset: volatility will dictate whether 0.30 is too loose or too tight. Enjoy smoother, multi-factor signals in one indicator—Fusion AI does the math so your eyes can focus on the trade.
Pine Script® göstergesi
FindBetterTrades tarafından
2
USDT + USDC DominanceUSDT and USDC Dominance: This refers to the combined market capitalization of Tether (USDT) and USD Coin (USDC) as a percentage of the total cryptocurrency market capitalization. It measures the proportion of the crypto market held by these stablecoins, which are pegged to the US dollar. High dominance indicates a "risk-off" sentiment, where investors hold stablecoins for safety during market uncertainty. A drop in dominance suggests capital is flowing into riskier assets like altcoins, often signaling a bullish market or the start of an "alt season."
Pine Script® göstergesi
cariste tarafından
Correlation Coefficient with MA & BB中文版介紹 相關係數、移動平均線與布林帶指標 (Correlation Coefficient with MA & BB) 這個 Pine Script 指標是一款強大的工具，旨在幫助交易者和投資者深入分析兩個市場標的之間的關係強度與方向，並結合移動平均線 (MA) 和布林帶 (BB) 來進一步洞察這種關係的趨勢和波動性。 無論您是想尋找配對交易機會、管理投資組合風險，還是僅僅想更好地理解市場動態，這個指標都能提供有價值的見解。 指標特色與功能： 動態相關係數計算： 您可以選擇任何您想比較的股票、商品或加密貨幣代號（例如，預設為 GOOG）。 指標會自動計算當前圖表（主數據源，預設為收盤價）與您指定標的之間的相關係數。 相關係數值介於 -1 (完美負相關) 至 1 (完美正相關) 之間，0 表示無線性關係。 視覺化呈現相關係數線，並標示 1、0、-1 參考水平線，同時填充完美相關區間，讓您一目了然。 特別之處：程式碼中包含了 ticker.modify，確保比較標的數據考慮了股息調整或延長交易時段，使相關性分析更加精準。 相關係數的移動平均線 (MA)： 為了平滑相關係數的短期波動，指標提供了多種移動平均線類型供您選擇，包括：SMA、EMA、WMA、SMMA。 您可以設定計算 MA 的週期長度（預設 20 週期）。 這條 MA 線有助於識別相關係數的長期趨勢，判斷兩者關係是趨於增強還是減弱。 相關係數的布林帶 (BB)： 將布林帶應用於相關係數，以衡量其波動性和相對高低水平。 中軌與您選擇的移動平均線保持一致。 上軌和下軌則根據相關係數的標準差和您設定的 Z 值（預設 2.0 倍標準差）動態調整。 布林帶可以幫助您識別相關係數何時處於極端水平，可能預示著未來會回歸均值。 如何運用這個指標？ 配對交易策略：當兩個通常高度相關的資產，其相關係數短期內顯著偏離平均水平（例如，一個資產價格上漲而另一個原地踏步），您可能可以考慮利用此「失衡」進行配對交易。 投資組合多元化：了解不同資產之間的相關性，有助於構建更穩健的投資組合，避免過度集中於同向變動的資產，有效分散風險。 市場趨勢洞察：透過觀察相關係數的趨勢和波動，您可以更好地理解不同市場板塊或資產類別之間的聯動性，為您的宏觀經濟分析提供數據支持。 請注意，相關性不等於因果性。使用此指標時，請結合您的整體交易策略、宏觀經濟分析以及其他技術指標進行綜合判斷。 English Version Introduction Correlation Coefficient with Moving Average & Bollinger Bands Indicator (Correlation Coefficient with MA & BB) This Pine Script indicator is a powerful tool designed to help traders and investors deeply analyze the strength and direction of the relationship between two market instruments. It integrates Moving Averages (MA) and Bollinger Bands (BB) to further insight into the trend and volatility of this relationship. Whether you're looking for pair trading opportunities, managing portfolio risk, or simply aiming to better understand market dynamics, this indicator can provide valuable insights. Indicator Features & Functionality: Dynamic Correlation Coefficient Calculation: You can select any symbol you wish to compare (e.g., default is GOOG), be it stocks, commodities, or cryptocurrencies. The indicator automatically calculates the correlation coefficient between the current chart (main data source, default is close price) and your specified symbol. Correlation values range from -1 (perfect negative correlation) to 1 (perfect positive correlation), with 0 indicating no linear relationship. It visually plots the correlation line, marks 1, 0, -1 reference levels, and fills the perfect correlation zone for clear visualization. Special Feature: The code includes ticker.modify, ensuring that the comparative symbol's data accounts for dividend adjustments or extended trading hours, leading to more precise correlation analysis. Moving Average (MA) for Correlation: To smooth out short-term fluctuations in the correlation coefficient, the indicator offers multiple MA types for you to choose from: SMA, EMA, WMA, SMMA. You can set the length of the MA period (default 20 periods). This MA line helps identify the long-term trend of the correlation coefficient, indicating whether the relationship between the two instruments is strengthening or weakening. Bollinger Bands (BB) for Correlation: Bollinger Bands are applied to the correlation coefficient itself to gauge its volatility and relative high/low levels. The middle band aligns with your chosen Moving Average. The upper and lower bands dynamically adjust based on the correlation coefficient's standard deviation and your set Z-score (default 2.0 standard deviations). Bollinger Bands can help you identify when the correlation coefficient is at extreme levels, potentially signaling a future reversion to the mean. How to Utilize This Indicator: Pair Trading Strategies: When two typically highly correlated assets show a significant short-term deviation from their average correlation (e.g., one asset's price rises while the other stagnates), you might consider exploiting this "imbalance" for pair trading. Portfolio Diversification: Understanding the correlation between different assets helps build a more robust investment portfolio, preventing over-concentration in co-moving assets and effectively diversifying risk. Market Trend Insight: By observing the trend and volatility of the correlation coefficient, you can better understand the联动 (interconnectedness) between different market sectors or asset classes, providing data support for your macroeconomic analysis. Please note that correlation does not imply causation. When using this indicator, combine it with your overall trading strategy, macroeconomic analysis, and other technical indicators for comprehensive decision-making.
Pine Script® göstergesi
ZhaoXianC tarafından
ADR TableTrack volatility and session momentum in real-time with customizable precision. Key Features: Average Daily Range (ADR): Configurable length (default 5 days), based on previous daily high–low ranges. Session Anchor Options: Choose anchor at 4 am NY, 6 pm NY, 9:30 am NY, 8:30 am NY, Previous Day Close, or Current Bar. Session Range & %ADR: Displays the real-time range from the chosen anchor, plus what percentage of ADR has been covered. High / Low Target Levels: Calculates ADR targets based on anchor: anchor ± ADR. Optional Target Lines: Draw horizontal lines for high and low targets across the session; customize color and width. Dynamic Table Display: User-selectable table size and text size (Tiny to Huge) for optimal readability. Robust Anchor Logic: Uses the first bar at-or-after anchor time each NY day, ensuring stability even on irregular intraday timeframes. How to Use Choose your anchor in settings. View ADR, session range (with %ADR), and target price levels in the top-right pane.Toggle High/Low lines to overlay targets on the chart. Adjust table and text size to match your workspace. Why It Matters Quickly assess where price stands relative to typical volatility. Easily identify intraday price exhaustion or breakout zones. Anchor flexibility enables use for both futures and equities, aligning with your trading session. Clean, professional display—no clutter, no guesswork.
Pine Script® göstergesi
OliverC-H tarafından
Economy RadarEconomy Radar — Key US Macro Indicators Visualized A handy tool for traders and investors to monitor major US economic data in one chart. Includes: Inflation: CPI, PCE, yearly %, expectations Monetary policy: Fed funds rate, M2 money supply Labor market: Unemployment, jobless claims, consumer sentiment Economy & markets: GDP, 10Y yield, US Dollar Index (DXY) Options: Toggle indicators on/off Customizable colors Tooltips explain each metric (in Russian & English) Perfect for spotting economic cycles and supporting trading decisions. Add to your chart and get a clear macro picture instantly!
Pine Script® göstergesi
Melatue tarafından
Kase Convergence Divergence [BackQuant]Kase Convergence Divergence The Kase Convergence Divergence is a sophisticated oscillator designed to measure directional market strength through the lens of volatility-adjusted log return structures. Inspired by Cynthia Kase’s work on statistical momentum and price projection ranges, this unique indicator offers a hybrid framework that merges signal processing, multi-length sweep logic, and adaptive smoothing techniques. Unlike traditional momentum oscillators like MACD or RSI, which rely on static moving average differences, KCD introduces a dual-process system combining: Kase-style statistical range projection (via log returns and volatility), A sweeping loop of lookback lengths for robustness, First and second derivative modes to capture both velocity and acceleration of price movement. Core Logic & Computation The KCD calculation is centered on two volatility-normalized transforms: KSDI Up: Measures how far the current high has moved relative to a past low, normalized by return volatility. KSDI Down: Measures how far the current low has moved relative to a past high, also normalized. For every length in a user-defined sweep range (e.g., 25–35), both KSDI_up and KSDI_dn are computed, and their maximum values across the loop are retained. The difference between these two max values produces the raw signal: KPO (Kase Projection Oscillator): Measures directional skew. KCD (Kase Convergence Divergence): Defined as KPO – MA(KPO) — similar in spirit to MACD but structurally different. Users can choose to visualize either the first derivative (KPO) , or the second derivative (KCD) , depending on market conditions or strategy style. Key Features ✅ Multi-Length Sweep Logic: Improves signal reliability by aggregating statistical range projections across a set of lookbacks. ✅ Advanced Smoothing Modes: Supports DEMA, HMA, TEMA, LINREG, WMA and more for dynamic adaptation. ✅ Dual Derivative Modes: Choose between speed (first derivative) or smoothness (second derivative) to fit your trading regime. ✅ Color-Encoded Signal Bands: Heatmap-style oscillator coloring enhances visual feedback on trend strength. ✅ Candlestick Painting: Optional bar coloring makes it easy to spot trend shifts on the main chart. ✅ Adaptive Fill Zones: Green and red fills between the oscillator and zero line help distinguish bullish and bearish regimes at a glance. Practical Applications 📈 Trend Confirmation: Use KCD as a secondary confirmation layer after breakout or pullback entries. 📉 Momentum Shifts: Crossover and crossunder of the zero line highlight potential regime changes. 📊 Strategy Filters: Incorporate into algos to avoid trendless or mean-reverting environments. 🧪 Derivative Switching: Flip between KPO and KCD modes depending on whether you want to measure acceleration or deceleration of price flow. Alerts & Signals Two built-in alerts help you catch regime shifts in real time: Long Signal: Triggered when the selected oscillator crosses above zero. Short Signal: Triggered when it crosses below zero. These events can be used to generate entries, exits, or trend validation cues in multi-layer systems. Conclusion The Kase Convergence Divergence goes beyond traditional oscillators by offering a volatility-normalized, derivative-aware signal engine with enhanced visual dynamics. Its sweeping architecture and dynamic fill logic make it especially powerful for identifying trending environments, filtering chop, and adding statistical rigor to your trading toolkit. Whether you’re a discretionary trader seeking precision, or a quant looking to model more robust return structures, KCD offers a creative yet analytically grounded solution.
Pine Script® göstergesi
BackQuant tarafından
Alma SD SuperTrend | OquantAlma SD SuperTrend | Oquant The "Alma SD SuperTrend | Oquant" is a trend-following indicator that integrates the Arnaud Legoux Moving Average (ALMA) with a SuperTrend calculation based on standard deviation (SD). Designed to quickly identify and follow market trends while reducing noise, this script provides buy and sell signals for traders across various assets and timeframes. This script offers a unique approach by combining ALMA with a SuperTrend framework that uses standard deviation instead of the traditional Average True Range (ATR). This implementation focuses on fast trend detection with minimized noise, making it suitable for trend-following or swing trading strategies. The script’s customizable parameters allow traders to adapt it to their preferred trading style. How It Works Arnaud Legoux Moving Average (ALMA): ALMA is an advanced moving average that applies a Gaussian filter to smooth price data, reducing market noise while preserving responsiveness to price changes. It uses three parameters: Length: Sets the lookback period for smoothing. Longer periods produce smoother results. Offset: Shifts the moving average toward recent prices. Higher offsets emphasize newer data for faster trend detection. Sigma controls the smoothness and lag of the Alma by adjusting the spread of the Gaussian distribution used in the calculation. Standard Deviation (SD) Calculation: The script calculates the standard deviation of the price over a specified period to measure volatility. SD measures how much the prices deviate from its mean, offering a statistical perspective on market volatility. This is used to create dynamic upper and lower bands around the ALMA line, adjusted by a user-defined factor. The bands expand in volatile markets and contract in stable conditions, helping in trend detection. SuperTrend Logic: The script generates a SuperTrend line that dynamically tracks market trends by switching between upper and lower volatility bands based on price movement. Here's how it works: The SuperTrend line is calculated using the ALMA (Arnaud Legoux Moving Average) as a baseline, with upper and lower bands created by adding and subtracting a multiple(Factor) of the standard deviation (SD) from the ALMA. When the price moves above the upper band, the SuperTrend line shifts to the lower band, indicating a bullish trend (potential buy signal). When the price falls below the lower band, the SuperTrend line switches to the upper band, signaling a bearish trend (potential sell signal). To avoid quick, unreliable changes, this script intelligently adjusts the SuperTrend bands for stability. While the SuperTrend line dynamically follows market movements, it's designed to hold at its previous level if the price doesn't cross a band or confirm a new trend direction. This approach ensures the SuperTrend quickly identifies and follows genuine market trends, providing clear signals while effectively reducing false alerts from short-term price swings. Differences from Traditional SuperTrend: Baseline: The traditional SuperTrend typically uses a hl2((high + low)/2)as its baseline, while this script employs ALMA for a smoother, noise-filtered trend foundation. Volatility Measure: Instead of ATR, this script uses standard deviation to calculate the bands. Standard deviation measures how much the prices vary or spread out from its mean. Visualization: The script plots the SuperTrend line, colors candles to match the trend, and fills the area between the price and the SuperTrend line for visual clarity, helping traders quickly identify trend direction and strength (green for bullish, purple for bearish). How to Use It Add to Chart: Apply the indicator to any market and timeframe. Interpret Signals: Green Line and Candles: Bullish trend (price above the SuperTrend line). Consider long entries. Purple Line and Candles: Bearish trend (price below the SuperTrend line). Consider short entries. Filled Area: The shaded area between price and the SuperTrend line highlights trend direction(green for bullish, purple for bearish). Adjust Inputs: Source: Select the price data to use (e.g., close, open, high, low). Factor: Adjusts band width. Higher values widen bands, reducing sensitivity. SD Length: Period for calculating standard deviation. Longer periods smooth volatility. ALMA Length: Period for ALMA. Longer periods increase smoothness. Alma Offset: Shift the moving average toward recent or older prices. Higher offsets emphasize newer data for faster trend detection. ALMA Sigma control the smoothness and lag of the Alma by adjusting the spread of the Gaussian distribution used in the calculation. Alerts This indicator includes optional built-in alert conditions that notify you when the signal crosses above 0 (long signal, price above upper band) or below 0 (short signal, price below lower band). Enable these alerts to get timely updates on potential trend shifts without constantly monitoring the chart. ⚠️ Disclaimer: This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
Pine Script® göstergesi
oquant tarafından
GOLD Auto-Alert Strategy [Enhanced+Signals+UT Bot]New Version The Indicator ✅ BUY Signal Triggers Only If: UT Buy signal flips (from down to up) ADX > Threshold → market has strength RSI is outside the 40–60 range Volume is spiking above 20-bar average × 1.2 EMA Fast > EMA Slow → uptrend confirmed Close > EMA Fast → price above short-term trend Bullish Engulfing candle 🔻 SELL Signal Triggers Only If: UT Sell signal flips (from up to down) ADX > Threshold → market has strength RSI is outside the 40–60 range Volume is spiking above average EMA Fast < EMA Slow → downtrend confirmed Close < EMA Fast → bearish structure Bearish Engulfing candle
Pine Script® göstergesi
aashiqasmr tarafından