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Spinn ATR tableThe table contains summary data on the ATR from different timeframes and for different periods. You can view both absolute values ​​and the percentage of the average price move to the current price. This data can be used to compare the ATR on different timeframes. And, most importantly, you can compare the ATR of different coins. In addition, the last column shows the average deviation of the ATR for each of the timeframes. You can compare these values ​​on different coins to determine which ones are more volatile . Note. Using the indicator on different timeframes may give slightly different values ​​due to the difference in the stored data for these timeframes. -- В таблице собраны сводные данные по ATR с разных таймфреймов и за разные периоды. Можно просматривать как абсолютные значения, так и процентное соотношение среднего хода цены к текущей цене. Эти данные можно использовать, чтобы сравнить ATR на разных таймфреймах. И, самое главное, можно сравнивать ATR разных монет. Кроме того, в последней колонке указано среднее отклонение ATR по каждому из таймфреймов. Можно сравнивать эти значения на разных монетах, чтобы определить - какие из них более волатильны . Примечание. Использование индикатора на разных таймфреймах может давать слегка разные значения из-за разницы в хранимых данных для этих таймфреймов.
Penunjuk Pine Script®
oleh Spinn29
1
Multiple Indicator 50EMA Cross AlertsHere’s a screener including Symbol, Price, TSI, and 50 ema cross in a table output. The 50 Exponential Moving Average is a trend indicator You can find bullish momentum when the 50 ema crossed over or a bearish momentum when the 50 ema crossed under we are looking to take advantage by trading the reversion of these trends. True strength index (TSI) is a trend momentum indicator Readings are bullish when the True Strength Index shows positive values Readings are bearish when the indicator displays negative values. When a value is above 20, we look for selling overbought opportunity and when the value is under 20, we look for buying oversold opportunity. You can select the pair of your choice in the settings. Make sure to create an alert and choose any alerts then an alert will trigger when a price cross under or cross over the 50 ema for every pair separately. This allow the user to verify if there is a trade set up or not. Disclaimer This post and the script don’t provide any financial advice.
Penunjuk Pine Script®
oleh F_rank_01
27
BTC Futures BasisShows various basis percentages in a table and plots historical basis. Also has an alert function for backwardation events. Useful for tracking bullish/bearish sentiment in BTC futures markets. *Currently displays March and June futures for the following exchanges: Bitmex, Binance, Deribit, Okex, and FTX Also displays CME Continuous Next Contract. All of the symbols are customizable. ----------- Market-wide backwardation usually occurs during a heavy sell-off (such as a liquidation cascade). **For getting alerts of backwardation events, I recommend creating an alert on the 1 minute chart with the condition "Any alert() function call". Alert level is customizable as well. ----------- *NOTE!! : Futures contracts expire (obviously), so the contract symbols will need to be updated periodically. I will try to keep them updated going into the future. **NOTE2!! : The alert() function does not track the CME contract. This is to avoid false triggers.
Penunjuk Pine Script®
oleh daylad
4
SPY Sub-Sector Daily Money Flow TableThis calculates the dollar volume per candlestick (2nd row) and cumulative (3rd row) of the entire trading day for each subsector of the SPY. The 'Total' column is the total of all the subsectors combined. It is calculated separately from SPY volume. The money flow is calculated with (open+close)/2 which means different timeframes yield different results and won't be especially accurate day-by-day. This is useful to quickly see rotation and possible divergences. Enjoy!
Penunjuk Pine Script®
oleh barnabygraham
6
[CLX][#01] Animation - Price Ticker (Marquee)This indicator displays a classic animated price ticker overlaid on the user’s current chart. It is possible to fully customize it or to select one of the predefined styles. A detailed description will follow in the next few days. Used Pinescript technics: - varip (view/animation) - tulip instance (config/codestructur) - table (view/position) By the way, for me, one of the coolest animated effects is by Duyck We hope you enjoy it! 🎉 CRYPTOLINX - jango_blockchained 😊👍 Disclaimer: Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely. The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script.
Penunjuk Pine Script®
oleh cryptolinx
2
MTF Price/Volume % [Anan]Hello friends, This is a multi-timeframe table with these features: Display price change percentage compared with the last timeframe candle close. Display price change percentage compared with the last timeframe candle close MA. Displays change percentage compared with the last timeframe candle volume. Displays change percentage compared with the last timeframe candle volume MA. Change type/length of MA for Price/Volume. Full control of Panel position and size. Full control of displaying any row or column.
Penunjuk Pine Script®
oleh Mohamed3nan
20
Average Daily Range TableThis is the last script to complete Vladimir Poltoratskiy's setup found in his books. Poltoratskiy argues that you should not take any fractal corridors higher than 50% of the Average Daily Range. To be honest, even 40% is a lot, because then, your target will be 160% ADR away from your entry and one "fracture" just can't be enough to predict moves this big. I chose a table to visually represent the indicator because it doesn't change its value during the day. It takes far less room on the chart. There are also two simple moving averages. You may use the as an indicator if the relative volatility as of late is extremely low and in that case, perhaps, expect an increase in the coming days. They are applied to the Average Daily Range, not one day range!
Penunjuk Pine Script®
oleh OrcChieftain
1
PAC newThis indicator will alert you when a candle goes above or below the price action channel (PAC) but only on the first or second candle after a colour change in candle. When price is above the price action channel that is a bullish sign, when price is below the PAC that is a bearish sign. The idea is that a sudden change in price is a cause to investigate further price action moving in that direction so the indicator aims to identify reversal Scalping strategy that works on 5 min chart and aims to gain 10 pips. Do not act on every signal. Further investigation is required, for example by looking at RSI oversolf and overbought levels. For example, at an oversold area, a buy signal is more valid
Penunjuk Pine Script®
oleh table47
Month/Month Percentage % Change, Historical; Seasonal TendencyTable of monthly % changes in Average Price over the last 10 years (or the 10 yrs prior to input year). Useful for gauging seasonal tendencies of an asset; backtesting monthly volatility and bullish/bearish tendency. ~~User Inputs~~ Choose measure of average: sma(close), sma(ohlc4), vwap(close), vwma(close). Show last 10yrs, with 10yr average % change, or to just show single year. Chose input year; with the indicator auto calculating the prior 10 years. Choose color for labels and size for labels; choose +Ve value color and -Ve value color. Set 'Daily bars in month': 21 for Forex/Commodities/Indices; 30 for Crypto. Set precision: decimal places ~~notes~~ -designed for use on Daily timeframe (tradingview is buggy on monthly timeframe calculations, and less precise on weekly timeframe calculations). -where Current month of year has not occurred yet, will print 9yr average. -calculates the average change of displayed month compared to the previous month: i.e. Jan22 value represents whole of Jan22 compared to whole of Dec21. -table displays on the chart over the input year; so for ES, with 2010 selected; shows values from 2001-2010, displaying across 2010-2011 on the chart. -plots on seperate right hand side scale, so can be shrunk and dragged vertically. -thanks to @gabx11 for the suggestion which inspired me to write this
Penunjuk Pine Script®
oleh twingall
10
Thirdeyechart Gold Simulation Final 2Gold Simulation – Final Version 2 (Safe/Unsafe Trade Detection) The Gold Simulation Final Version is a comprehensive TradingView indicator designed for traders who want an immediate understanding of gold market dynamics. This version monitors multiple XAU pairs simultaneously and integrates an advanced logic to detect Safe and Unsafe trade conditions in real time. Key features: Safe Trade: Indicates situations where market direction shows clear dominance and higher probability of trend continuity. Unsafe Trade: Highlights areas where price movement is uncertain or potentially volatile, signaling traders to be cautious. Multi-Timeframe Analysis: Calculates percentage changes across Weekly (W), Daily (D), 4-Hour (H4), and 1-Hour (H1), and combines them into a Total Average Trend Strength for a consolidated market view. Clean Visual Layout: All data is displayed in a solid boxed table, making trend strength, direction, and safety status immediately clear. Logic Overview Percent change per timeframe: pct_tf = ((close_tf - open_tf) / open_tf) * 100 Collect all timeframe values for each XAU pair: values = Total Average Strength: Total_Avg = sum(values) / 4 Safe/Unsafe conditions are determined by configurable thresholds comparing dominance between buyers and sellers across timeframes. This version helps traders quickly identify where trend is strong and stable versus where market conditions are uncertain, allowing better planning and risk management. Disclaimer This indicator is for educational and analytical purposes only. It does not provide financial or trading advice. Users are fully responsible for their own trading decisions, and markets carry risk. © 2025 Ajik Boy. All rights reserved. Redistribution or commercial use without permission is prohibited.
Penunjuk Pine Script®
oleh Spiderweb11
Thirdeyechart Gold Simulation FinalGold Simulation – Final Version (Safe/Unsafe Trade Detection) The Gold Simulation Final Version is a comprehensive TradingView indicator designed for traders who want an immediate understanding of gold market dynamics. This version monitors multiple XAU pairs simultaneously and integrates an advanced logic to detect Safe and Unsafe trade conditions in real time. Key features: Safe Trade: Indicates situations where market direction shows clear dominance and higher probability of trend continuity. Unsafe Trade: Highlights areas where price movement is uncertain or potentially volatile, signaling traders to be cautious. Multi-Timeframe Analysis: Calculates percentage changes across Weekly (W), Daily (D), 4-Hour (H4), and 1-Hour (H1), and combines them into a Total Average Trend Strength for a consolidated market view. Clean Visual Layout: All data is displayed in a solid boxed table, making trend strength, direction, and safety status immediately clear. Logic Overview Percent change per timeframe: pct_tf = ((close_tf - open_tf) / open_tf) * 100 Collect all timeframe values for each XAU pair: values = Total Average Strength: Total_Avg = sum(values) / 4 Safe/Unsafe conditions are determined by configurable thresholds comparing dominance between buyers and sellers across timeframes. This version helps traders quickly identify where trend is strong and stable versus where market conditions are uncertain, allowing better planning and risk management. Disclaimer This indicator is for educational and analytical purposes only. It does not provide financial or trading advice. Users are fully responsible for their own trading decisions, and markets carry risk. © 2025 Thirdeyechart. All rights reserved. Redistribution or commercial use without permission is prohibited.
Penunjuk Pine Script®
oleh Spiderweb11
Buy/Sell Signal v3 BTC/Gold Scalping Strategy - 5M 1H Timeframe Description Advanced trading indicator specifically designed for scalping BTC and Gold on 5-minute and 1-hour timeframes. It uses EMA crossovers with automatic risk management (Stop Loss and Take Profit) based on ATR. Main Features - Automatic entry signals: Identifies optimal buy and sell points based on EMA crossovers - Integrated risk management: Automatically calculates SL and TP according to your preferred risk/reward ratio - Smart invalidation: Cancels previous positions when a new opposite signal appears - Clear visualization: Horizontal lines showing entry, stop loss, and take profit in real time - Informative panel: Table with all information about the active position - Complete alert system: Notifications for entries, exits, and invalidations How It Works The indicator detects trend changes through the crossover of two EMAs: - Fast EMA (default 5 periods): Quickly responds to price changes - Slow EMA (default 13 periods): Filters market noise - BUY Signal: When the fast EMA crosses above the slow EMA - SELL Signal: When the fast EMA crosses below the slow EMA Risk Management - Stop Loss: Placed below/above the low/high of the entry candle, adjusted by ATR - Take Profit: Automatically calculated according to your configured R:R ratio (default 3:1) - Invalidation: If an opposite signal appears before TP or SL is hit, the position closes automatically Visual Elements - 🟢 BUY Label: Buy signal (lime green) - 🔴 SELL Label: Sell signal (red) - ⚠️ INV Icon: Invalidated entry (yellow) - 🎯 TP Icon: Take Profit reached (green) - ❌ SL Icon: Stop Loss triggered (red) - ⚪ White dotted line: Entry price - 🔴 Red line: Stop Loss level - 🟢 Green line: Take Profit level Recommended Settings For BTC: - Fast EMA: 5 - Slow EMA: 13 - ATR: 14 - SL Multiplier: 0.5 - Risk:Reward: 3.0 - Candle confirmation: Enabled For Gold (XAU/USD): - Fast EMA: 5 - Slow EMA: 13 - ATR: 14 - SL Multiplier: 0.4–0.6 (adjust depending on volatility) - Risk:Reward: 2.5–3.5 - Candle confirmation: Enabled Available Alerts 1. 🟢 BUY Signal: Triggered when a new buy opportunity appears 2. 🔴 SELL Signal: Triggered when a new sell opportunity appears 3. 🎯 Take Profit: Notifies when the profit target is reached 4. ❌ Stop Loss: Alerts when stop loss is triggered 5. ⚠️ Invalidated Entry: Alerts when a position is canceled by an opposite signal Important Notes - ⏰ Recommended timeframe: 5 minutes and 1 hour - 📊 Optimized assets: Bitcoin (BTC/USD) and Gold (XAU/USD), including Futures - ⚠️ No repaint*: Signals do not change once confirmed - 🎓 Educational use: Always perform your own analysis before trading - 💰 Capital management: Never risk more than 1–2% of your account per trade Customizable Parameters Indicators: - Fast EMA period (1–50) - Slow EMA period (1–50) - ATR period (1–50) - Stop Loss multiplier (0.1–5.0) - Risk:Reward ratio (1.0–10.0) - Candle confirmation (On/Off) EMA Visualization: - Show/Hide Fast EMA - Customizable Fast EMA color - Show/Hide Slow EMA - Customizable Slow EMA color How to Use 1. Add the indicator to your 5-minute chart 2. Adjust parameters according to your trading style 3. Set up alerts to receive notifications 4. Wait for clear BUY or SELL signals 5. Manage the trade following the SL and TP levels displayed Disclaimer: This indicator is a technical analysis tool. It does not constitute financial advice. Trading carries significant risks and you may lose your capital. Always trade responsibly with proper risk management.
Penunjuk Pine Script®
oleh kelfry98
Universal Ratio Trend Matrix [InvestorUnknown]The Universal Ratio Trend Matrix is designed for trend analysis on asset/asset ratios, supporting up to 40 different assets. Its primary purpose is to help identify which assets are outperforming others within a selection, providing a broad overview of market trends through a matrix of ratios. The indicator automatically expands the matrix based on the number of assets chosen, simplifying the process of comparing multiple assets in terms of performance. Key features include the ability to choose from a narrow selection of indicators to perform the ratio trend analysis, allowing users to apply well-defined metrics to their comparison. Drawback: Due to the computational intensity involved in calculating ratios across many assets, the indicator has a limitation related to loading speed. TradingView has time limits for calculations, and for users on the basic (free) plan, this could result in frequent errors due to exceeded time limits. To use the indicator effectively, users with any paid plans should run it on timeframes higher than 8h (the lowest timeframe on which it managed to load with 40 assets), as lower timeframes may not reliably load. Indicators: RSI_raw: Simple function to calculate the Relative Strength Index (RSI) of a source (asset price). RSI_sma: Calculates RSI followed by a Simple Moving Average (SMA). RSI_ema: Calculates RSI followed by an Exponential Moving Average (EMA). CCI: Calculates the Commodity Channel Index (CCI). Fisher: Implements the Fisher Transform to normalize prices. Utility Functions: f_remove_exchange_name: Strips the exchange name from asset tickers (e.g., "INDEX:BTCUSD" to "BTCUSD"). f_remove_exchange_name(simple string name) => string parts = str.split(name, ":") string result = array.size(parts) > 1 ? array.get(parts, 1) : name result f_get_price: Retrieves the closing price of a given asset ticker using request.security(). f_constant_src: Checks if the source data is constant by comparing multiple consecutive values. Inputs: General settings allow users to select the number of tickers for analysis (used_assets) and choose the trend indicator (RSI, CCI, Fisher, etc.). Table settings customize how trend scores are displayed in terms of text size, header visibility, highlighting options, and top-performing asset identification. The script includes inputs for up to 40 assets, allowing the user to select various cryptocurrencies (e.g., BTCUSD, ETHUSD, SOLUSD) or other assets for trend analysis. Price Arrays: Price values for each asset are stored in variables (price_a1 to price_a40) initialized as na. These prices are updated only for the number of assets specified by the user (used_assets). Trend scores for each asset are stored in separate arrays // declare price variables as "na" var float price_a1 = na, var float price_a2 = na, var float price_a3 = na, var float price_a4 = na, var float price_a5 = na var float price_a6 = na, var float price_a7 = na, var float price_a8 = na, var float price_a9 = na, var float price_a10 = na var float price_a11 = na, var float price_a12 = na, var float price_a13 = na, var float price_a14 = na, var float price_a15 = na var float price_a16 = na, var float price_a17 = na, var float price_a18 = na, var float price_a19 = na, var float price_a20 = na var float price_a21 = na, var float price_a22 = na, var float price_a23 = na, var float price_a24 = na, var float price_a25 = na var float price_a26 = na, var float price_a27 = na, var float price_a28 = na, var float price_a29 = na, var float price_a30 = na var float price_a31 = na, var float price_a32 = na, var float price_a33 = na, var float price_a34 = na, var float price_a35 = na var float price_a36 = na, var float price_a37 = na, var float price_a38 = na, var float price_a39 = na, var float price_a40 = na // create "empty" arrays to store trend scores var a1_array = array.new_int(40, 0), var a2_array = array.new_int(40, 0), var a3_array = array.new_int(40, 0), var a4_array = array.new_int(40, 0) var a5_array = array.new_int(40, 0), var a6_array = array.new_int(40, 0), var a7_array = array.new_int(40, 0), var a8_array = array.new_int(40, 0) var a9_array = array.new_int(40, 0), var a10_array = array.new_int(40, 0), var a11_array = array.new_int(40, 0), var a12_array = array.new_int(40, 0) var a13_array = array.new_int(40, 0), var a14_array = array.new_int(40, 0), var a15_array = array.new_int(40, 0), var a16_array = array.new_int(40, 0) var a17_array = array.new_int(40, 0), var a18_array = array.new_int(40, 0), var a19_array = array.new_int(40, 0), var a20_array = array.new_int(40, 0) var a21_array = array.new_int(40, 0), var a22_array = array.new_int(40, 0), var a23_array = array.new_int(40, 0), var a24_array = array.new_int(40, 0) var a25_array = array.new_int(40, 0), var a26_array = array.new_int(40, 0), var a27_array = array.new_int(40, 0), var a28_array = array.new_int(40, 0) var a29_array = array.new_int(40, 0), var a30_array = array.new_int(40, 0), var a31_array = array.new_int(40, 0), var a32_array = array.new_int(40, 0) var a33_array = array.new_int(40, 0), var a34_array = array.new_int(40, 0), var a35_array = array.new_int(40, 0), var a36_array = array.new_int(40, 0) var a37_array = array.new_int(40, 0), var a38_array = array.new_int(40, 0), var a39_array = array.new_int(40, 0), var a40_array = array.new_int(40, 0) f_get_price(simple string ticker) => request.security(ticker, "", close) // Prices for each USED asset f_get_asset_price(asset_number, ticker) => if (used_assets >= asset_number) f_get_price(ticker) else na // overwrite empty variables with the prices if "used_assets" is greater or equal to the asset number if barstate.isconfirmed // use barstate.isconfirmed to avoid "na prices" and calculation errors that result in empty cells in the table price_a1 := f_get_asset_price(1, asset1), price_a2 := f_get_asset_price(2, asset2), price_a3 := f_get_asset_price(3, asset3), price_a4 := f_get_asset_price(4, asset4) price_a5 := f_get_asset_price(5, asset5), price_a6 := f_get_asset_price(6, asset6), price_a7 := f_get_asset_price(7, asset7), price_a8 := f_get_asset_price(8, asset8) price_a9 := f_get_asset_price(9, asset9), price_a10 := f_get_asset_price(10, asset10), price_a11 := f_get_asset_price(11, asset11), price_a12 := f_get_asset_price(12, asset12) price_a13 := f_get_asset_price(13, asset13), price_a14 := f_get_asset_price(14, asset14), price_a15 := f_get_asset_price(15, asset15), price_a16 := f_get_asset_price(16, asset16) price_a17 := f_get_asset_price(17, asset17), price_a18 := f_get_asset_price(18, asset18), price_a19 := f_get_asset_price(19, asset19), price_a20 := f_get_asset_price(20, asset20) price_a21 := f_get_asset_price(21, asset21), price_a22 := f_get_asset_price(22, asset22), price_a23 := f_get_asset_price(23, asset23), price_a24 := f_get_asset_price(24, asset24) price_a25 := f_get_asset_price(25, asset25), price_a26 := f_get_asset_price(26, asset26), price_a27 := f_get_asset_price(27, asset27), price_a28 := f_get_asset_price(28, asset28) price_a29 := f_get_asset_price(29, asset29), price_a30 := f_get_asset_price(30, asset30), price_a31 := f_get_asset_price(31, asset31), price_a32 := f_get_asset_price(32, asset32) price_a33 := f_get_asset_price(33, asset33), price_a34 := f_get_asset_price(34, asset34), price_a35 := f_get_asset_price(35, asset35), price_a36 := f_get_asset_price(36, asset36) price_a37 := f_get_asset_price(37, asset37), price_a38 := f_get_asset_price(38, asset38), price_a39 := f_get_asset_price(39, asset39), price_a40 := f_get_asset_price(40, asset40) Universal Indicator Calculation (f_calc_score): This function allows switching between different trend indicators (RSI, CCI, Fisher) for flexibility. It uses a switch-case structure to calculate the indicator score, where a positive trend is denoted by 1 and a negative trend by 0. Each indicator has its own logic to determine whether the asset is trending up or down. // use switch to allow "universality" in indicator selection f_calc_score(source, trend_indicator, int_1, int_2) => int score = na if (not f_constant_src(source)) and source > 0.0 // Skip if you are using the same assets for ratio (for example BTC/BTC) x = switch trend_indicator "RSI (Raw)" => RSI_raw(source, int_1) "RSI (SMA)" => RSI_sma(source, int_1, int_2) "RSI (EMA)" => RSI_ema(source, int_1, int_2) "CCI" => CCI(source, int_1) "Fisher" => Fisher(source, int_1) y = switch trend_indicator "RSI (Raw)" => x > 50 ? 1 : 0 "RSI (SMA)" => x > 50 ? 1 : 0 "RSI (EMA)" => x > 50 ? 1 : 0 "CCI" => x > 0 ? 1 : 0 "Fisher" => x > x ? 1 : 0 score := y else score := 0 score Array Setting Function (f_array_set): This function populates an array with scores calculated for each asset based on a base price (p_base) divided by the prices of the individual assets. It processes multiple assets (up to 40), calling the f_calc_score function for each. // function to set values into the arrays f_array_set(a_array, p_base) => array.set(a_array, 0, f_calc_score(p_base / price_a1, trend_indicator, int_1, int_2)) array.set(a_array, 1, f_calc_score(p_base / price_a2, trend_indicator, int_1, int_2)) array.set(a_array, 2, f_calc_score(p_base / price_a3, trend_indicator, int_1, int_2)) array.set(a_array, 3, f_calc_score(p_base / price_a4, trend_indicator, int_1, int_2)) array.set(a_array, 4, f_calc_score(p_base / price_a5, trend_indicator, int_1, int_2)) array.set(a_array, 5, f_calc_score(p_base / price_a6, trend_indicator, int_1, int_2)) array.set(a_array, 6, f_calc_score(p_base / price_a7, trend_indicator, int_1, int_2)) array.set(a_array, 7, f_calc_score(p_base / price_a8, trend_indicator, int_1, int_2)) array.set(a_array, 8, f_calc_score(p_base / price_a9, trend_indicator, int_1, int_2)) array.set(a_array, 9, f_calc_score(p_base / price_a10, trend_indicator, int_1, int_2)) array.set(a_array, 10, f_calc_score(p_base / price_a11, trend_indicator, int_1, int_2)) array.set(a_array, 11, f_calc_score(p_base / price_a12, trend_indicator, int_1, int_2)) array.set(a_array, 12, f_calc_score(p_base / price_a13, trend_indicator, int_1, int_2)) array.set(a_array, 13, f_calc_score(p_base / price_a14, trend_indicator, int_1, int_2)) array.set(a_array, 14, f_calc_score(p_base / price_a15, trend_indicator, int_1, int_2)) array.set(a_array, 15, f_calc_score(p_base / price_a16, trend_indicator, int_1, int_2)) array.set(a_array, 16, f_calc_score(p_base / price_a17, trend_indicator, int_1, int_2)) array.set(a_array, 17, f_calc_score(p_base / price_a18, trend_indicator, int_1, int_2)) array.set(a_array, 18, f_calc_score(p_base / price_a19, trend_indicator, int_1, int_2)) array.set(a_array, 19, f_calc_score(p_base / price_a20, trend_indicator, int_1, int_2)) array.set(a_array, 20, f_calc_score(p_base / price_a21, trend_indicator, int_1, int_2)) array.set(a_array, 21, f_calc_score(p_base / price_a22, trend_indicator, int_1, int_2)) array.set(a_array, 22, f_calc_score(p_base / price_a23, trend_indicator, int_1, int_2)) array.set(a_array, 23, f_calc_score(p_base / price_a24, trend_indicator, int_1, int_2)) array.set(a_array, 24, f_calc_score(p_base / price_a25, trend_indicator, int_1, int_2)) array.set(a_array, 25, f_calc_score(p_base / price_a26, trend_indicator, int_1, int_2)) array.set(a_array, 26, f_calc_score(p_base / price_a27, trend_indicator, int_1, int_2)) array.set(a_array, 27, f_calc_score(p_base / price_a28, trend_indicator, int_1, int_2)) array.set(a_array, 28, f_calc_score(p_base / price_a29, trend_indicator, int_1, int_2)) array.set(a_array, 29, f_calc_score(p_base / price_a30, trend_indicator, int_1, int_2)) array.set(a_array, 30, f_calc_score(p_base / price_a31, trend_indicator, int_1, int_2)) array.set(a_array, 31, f_calc_score(p_base / price_a32, trend_indicator, int_1, int_2)) array.set(a_array, 32, f_calc_score(p_base / price_a33, trend_indicator, int_1, int_2)) array.set(a_array, 33, f_calc_score(p_base / price_a34, trend_indicator, int_1, int_2)) array.set(a_array, 34, f_calc_score(p_base / price_a35, trend_indicator, int_1, int_2)) array.set(a_array, 35, f_calc_score(p_base / price_a36, trend_indicator, int_1, int_2)) array.set(a_array, 36, f_calc_score(p_base / price_a37, trend_indicator, int_1, int_2)) array.set(a_array, 37, f_calc_score(p_base / price_a38, trend_indicator, int_1, int_2)) array.set(a_array, 38, f_calc_score(p_base / price_a39, trend_indicator, int_1, int_2)) array.set(a_array, 39, f_calc_score(p_base / price_a40, trend_indicator, int_1, int_2)) a_array Conditional Array Setting (f_arrayset): This function checks if the number of used assets is greater than or equal to a specified number before populating the arrays. // only set values into arrays for USED assets f_arrayset(asset_number, a_array, p_base) => if (used_assets >= asset_number) f_array_set(a_array, p_base) else na Main Logic The main logic initializes arrays to store scores for each asset. Each array corresponds to one asset's performance score. Setting Trend Values: The code calls f_arrayset for each asset, populating the respective arrays with calculated scores based on the asset prices. Combining Arrays: A combined_array is created to hold all the scores from individual asset arrays. This array facilitates further analysis, allowing for an overview of the performance scores of all assets at once. // create a combined array (work-around since pinescript doesn't support having array of arrays) var combined_array = array.new_int(40 * 40, 0) if barstate.islast for i = 0 to 39 array.set(combined_array, i, array.get(a1_array, i)) array.set(combined_array, i + (40 * 1), array.get(a2_array, i)) array.set(combined_array, i + (40 * 2), array.get(a3_array, i)) array.set(combined_array, i + (40 * 3), array.get(a4_array, i)) array.set(combined_array, i + (40 * 4), array.get(a5_array, i)) array.set(combined_array, i + (40 * 5), array.get(a6_array, i)) array.set(combined_array, i + (40 * 6), array.get(a7_array, i)) array.set(combined_array, i + (40 * 7), array.get(a8_array, i)) array.set(combined_array, i + (40 * 8), array.get(a9_array, i)) array.set(combined_array, i + (40 * 9), array.get(a10_array, i)) array.set(combined_array, i + (40 * 10), array.get(a11_array, i)) array.set(combined_array, i + (40 * 11), array.get(a12_array, i)) array.set(combined_array, i + (40 * 12), array.get(a13_array, i)) array.set(combined_array, i + (40 * 13), array.get(a14_array, i)) array.set(combined_array, i + (40 * 14), array.get(a15_array, i)) array.set(combined_array, i + (40 * 15), array.get(a16_array, i)) array.set(combined_array, i + (40 * 16), array.get(a17_array, i)) array.set(combined_array, i + (40 * 17), array.get(a18_array, i)) array.set(combined_array, i + (40 * 18), array.get(a19_array, i)) array.set(combined_array, i + (40 * 19), array.get(a20_array, i)) array.set(combined_array, i + (40 * 20), array.get(a21_array, i)) array.set(combined_array, i + (40 * 21), array.get(a22_array, i)) array.set(combined_array, i + (40 * 22), array.get(a23_array, i)) array.set(combined_array, i + (40 * 23), array.get(a24_array, i)) array.set(combined_array, i + (40 * 24), array.get(a25_array, i)) array.set(combined_array, i + (40 * 25), array.get(a26_array, i)) array.set(combined_array, i + (40 * 26), array.get(a27_array, i)) array.set(combined_array, i + (40 * 27), array.get(a28_array, i)) array.set(combined_array, i + (40 * 28), array.get(a29_array, i)) array.set(combined_array, i + (40 * 29), array.get(a30_array, i)) array.set(combined_array, i + (40 * 30), array.get(a31_array, i)) array.set(combined_array, i + (40 * 31), array.get(a32_array, i)) array.set(combined_array, i + (40 * 32), array.get(a33_array, i)) array.set(combined_array, i + (40 * 33), array.get(a34_array, i)) array.set(combined_array, i + (40 * 34), array.get(a35_array, i)) array.set(combined_array, i + (40 * 35), array.get(a36_array, i)) array.set(combined_array, i + (40 * 36), array.get(a37_array, i)) array.set(combined_array, i + (40 * 37), array.get(a38_array, i)) array.set(combined_array, i + (40 * 38), array.get(a39_array, i)) array.set(combined_array, i + (40 * 39), array.get(a40_array, i)) Calculating Sums: A separate array_sums is created to store the total score for each asset by summing the values of their respective score arrays. This allows for easy comparison of overall performance. Ranking Assets: The final part of the code ranks the assets based on their total scores stored in array_sums. It assigns a rank to each asset, where the asset with the highest score receives the highest rank. // create array for asset RANK based on array.sum var ranks = array.new_int(used_assets, 0) // for loop that calculates the rank of each asset if barstate.islast for i = 0 to (used_assets - 1) int rank = 1 for x = 0 to (used_assets - 1) if i != x if array.get(array_sums, i) < array.get(array_sums, x) rank := rank + 1 array.set(ranks, i, rank) Dynamic Table Creation Initialization: The table is initialized with a base structure that includes headers for asset names, scores, and ranks. The headers are set to remain constant, ensuring clarity for users as they interpret the displayed data. Data Population: As scores are calculated for each asset, the corresponding values are dynamically inserted into the table. This is achieved through a loop that iterates over the scores and ranks stored in the combined_array and array_sums, respectively. Automatic Extending Mechanism Variable Asset Count: The code checks the number of assets defined by the user. Instead of hardcoding the number of rows in the table, it uses a variable to determine the extent of the data that needs to be displayed. This allows the table to expand or contract based on the number of assets being analyzed. Dynamic Row Generation: Within the loop that populates the table, the code appends new rows for each asset based on the current asset count. The structure of each row includes the asset name, its score, and its rank, ensuring that the table remains consistent regardless of how many assets are involved. // Automatically extending table based on the number of used assets var table table = table.new(position.bottom_center, 50, 50, color.new(color.black, 100), color.white, 3, color.white, 1) if barstate.islast if not hide_head table.cell(table, 0, 0, "Universal Ratio Trend Matrix", text_color = color.white, bgcolor = #010c3b, text_size = fontSize) table.merge_cells(table, 0, 0, used_assets + 3, 0) if not hide_inps table.cell(table, 0, 1, text = "Inputs: You are using " + str.tostring(trend_indicator) + ", which takes: " + str.tostring(f_get_input(trend_indicator)), text_color = color.white, text_size = fontSize), table.merge_cells(table, 0, 1, used_assets + 3, 1) table.cell(table, 0, 2, "Assets", text_color = color.white, text_size = fontSize, bgcolor = #010c3b) for x = 0 to (used_assets - 1) table.cell(table, x + 1, 2, text = str.tostring(array.get(assets, x)), text_color = color.white, bgcolor = #010c3b, text_size = fontSize) table.cell(table, 0, x + 3, text = str.tostring(array.get(assets, x)), text_color = color.white, bgcolor = f_asset_col(array.get(ranks, x)), text_size = fontSize) for r = 0 to (used_assets - 1) for c = 0 to (used_assets - 1) table.cell(table, c + 1, r + 3, text = str.tostring(array.get(combined_array, c + (r * 40))), text_color = hl_type == "Text" ? f_get_col(array.get(combined_array, c + (r * 40))) : color.white, text_size = fontSize, bgcolor = hl_type == "Background" ? f_get_col(array.get(combined_array, c + (r * 40))) : na) for x = 0 to (used_assets - 1) table.cell(table, x + 1, x + 3, "", bgcolor = #010c3b) table.cell(table, used_assets + 1, 2, "", bgcolor = #010c3b) for x = 0 to (used_assets - 1) table.cell(table, used_assets + 1, x + 3, "==>", text_color = color.white) table.cell(table, used_assets + 2, 2, "SUM", text_color = color.white, text_size = fontSize, bgcolor = #010c3b) table.cell(table, used_assets + 3, 2, "RANK", text_color = color.white, text_size = fontSize, bgcolor = #010c3b) for x = 0 to (used_assets - 1) table.cell(table, used_assets + 2, x + 3, text = str.tostring(array.get(array_sums, x)), text_color = color.white, text_size = fontSize, bgcolor = f_highlight_sum(array.get(array_sums, x), array.get(ranks, x))) table.cell(table, used_assets + 3, x + 3, text = str.tostring(array.get(ranks, x)), text_color = color.white, text_size = fontSize, bgcolor = f_highlight_rank(array.get(ranks, x)))
Penunjuk Pine Script®
oleh InvestorUnknown
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