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Multi MA 10 Lines PRO (Custom Label + Crossover Icon)Multi MA 10 Lines PRO – 10 Custom MAs, Dynamic Labels & Persistent Crossover Symbols The ultimate professional Moving Average indicator — plot up to 10 fully customizable MAs (type, timeframe, color, width, style), display live price labels (value, % distance, or custom text), plus advanced ATR cross markers on every crossover (MA1/MA2). NEW: All MA crossovers are marked with persistent symbols (choose icon, color, size) — instantly spot every golden/death cross in your backtest! Complete flexibility for scalpers, swing traders, and serious strategists.
Wskaźnik Pine Script®
od MILO888
Nifty Futures vs ATM Option Candle Mismatch//@version=5 indicator("Nifty Futures vs ATM Option Candle Mismatch", overlay=true) // === Input symbols (modify these as needed) === niftySymbol = input.symbol("NSE:NIFTY1!", "Nifty Futures Symbol") atmOptionSymbol = input.symbol("NSE:NIFTY24JUN22400CE", "ATM Option Symbol") // Replace with real ATM symbol dynamically // === Get 5-min candles from both instruments === niftyClose = request.security(niftySymbol, "5", close) niftyOpen = request.security(niftySymbol, "5", open) optionClose = request.security(atmOptionSymbol, "5", close) optionOpen = request.security(atmOptionSymbol, "5", open) // === Determine candle color (green or red) === niftyGreen = niftyClose > niftyOpen optionGreen = optionClose > optionOpen // === Condition: Mismatch in candle direction === mismatch = (niftyGreen != optionGreen) // === Plot an icon or background when mismatch occurs === plotshape(mismatch, title="Mismatch Signal", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small) bgcolor(mismatch ? color.new(color.red, 85) : na, title="Mismatch Background")
Wskaźnik Pine Script®
od Athiral
Momentum Trend Bands (MTB)📌 What Is the Momentum Trend Bands (MTB) Indicator? The Momentum Trend Bands (MTB) is a custom-built trend detection indicator that blends momentum and volatility into a dynamic, visual system. Its core goal is to help traders identify the beginning and strength of a trend earlier than traditional tools like moving averages, while filtering out market noise. 🧠 What Is It Built On? The indicator is built on two foundational concepts: 1. Rate of Change (ROC): This measures the speed at which the price is moving. We use a fast and a slow version of ROC and then calculate their difference. This difference gives us a momentum signal — it shows whether the price is gaining upward or downward strength. 2. Standard Deviation (Volatility): This shows how much the price fluctuates. By calculating it over a certain period, we can measure market noise and filter out weak, insignificant moves that might otherwise cause false signals. Together, momentum shows direction, and volatility shows confidence. 🛠️ How Does It Work? • The core of the indicator is a smoothed momentum signal, representing the net difference between fast and slow momentum. • Around this signal, we build upper and lower bands — these are dynamic boundaries that expand or contract based on volatility. • When the momentum breaks above or below these bands, it signals a strong directional move — suggesting the start or continuation of a trend. The bands also serve a visual filter: • If momentum stays within the bands, it implies the market is consolidating or ranging. • When it exits the bands decisively, it implies strength in that direction. 📈 How to Use It? 1. Trend Entry: o When the momentum signal rises above the upper band, it suggests a strong bullish trend may be starting. o When the signal drops below the lower band, it indicates a bearish trend. 2. Stay Out of Chop: o If the signal moves sideways within the bands, it’s best to avoid trading — the market is likely consolidating or ranging. 3. Visual Confirmation: o The background color changes with the trend: green for bullish, red for bearish, gray for neutral. This makes it quick to read visually. 4. Signal Arrows: o Small up or down arrows appear when trends begin, serving as early entry points. ⚙️ What Kind of Market Does It Work Best In? • Trending Markets: MTB shines in markets with strong directional movement — whether up or down. It's designed to pick up momentum early and hold through trend continuation. • Volatile Instruments: The built-in volatility filter helps in markets like crypto or commodities where price action is fast and erratic. • Avoid Flat or Low-Volume Conditions: In sideways markets, MTB may stay gray or flip often — these are not ideal times to trade using this indicator alone. 💎 Why Is It Unique? Unlike many indicators that react slowly (like moving averages) or trigger too often (like raw momentum), MTB balances early detection with reliability. Its unique combination of: • ROC difference for directional intent, • Smoothing for signal clarity, • Bands scaled by volatility for robustness, …makes it stand apart from commonly available indicators on platforms like TradingView.
Wskaźnik Pine Script®
od SupertradeOfficial
VWAP + ADX Trend FilterVWAP + ADX Trend Identifier (Intraday)” 🔹 Description: Write a short, clear summary like: “This script combines VWAP and ADX to help identify intraday trend trades. Buy and sell signals appear when price crosses VWAP with ADX strength above a threshold, confirming directional bias.” You can also include: Best suited for NIFTY / BNIFTY Ideal timeframe: 5–15 min For educational or personal use 🔹 Visibility: Public: Anyone can find it on TradingView. Must follow Pine Script Publishing Rules. Invite-only: Useful if you want to share with selected people (like clients or premium users). Private: Only you can see and use it. 📌 Important Tips for Publishing:
Wskaźnik Pine Script®
od dhramendersingh01
NP Screener with Alerts For Nifty 50 [NITIN PADALE]//@version=6 indicator('NP Screener with Alerts For Nifty 50 ', overlay = true) //////////// // INPUTS // filter_enabled = input.bool(false, '', group = 'Filter', inline = 'Filter') filter_column = input.string('Price', title = 'Column', options = , group = 'Filter', inline = 'Filter') filter_from = input.float(-9999999, 'From', group = 'Filter', inline = 'Filter') filter_to = input.float(9999999, 'To', group = 'Filter', inline = 'Filter') // SMA rsi_len = input.int(14, title = 'RSI Length', group = 'Indicators') rsi_os = input.float(30, title = 'RSI Overbought', group = 'Indicators') rsi_ob = input.float(70, title = 'RSI Oversold', group = 'Indicators') // TSI tsi_long_len = input.int(25, title = 'TSI Long Length', group = 'Indicators') tsi_shrt_len = input.int(13, title = 'TSI Short Length', group = 'Indicators') tsi_ob = input.float(30, title = 'TSI Overbought', group = 'Indicators') tsi_os = input.float(-30, title = 'TSI Oversold', group = 'Indicators') // ADX Params adx_smooth = input.int(14, title = 'ADX Smoothing', group = 'Indicators') adx_dilen = input.int(14, title = 'ADX DI Length', group = 'Indicators') adx_level = input.float(40, title = 'ADX Level', group = 'Indicators') // SuperTrend sup_atr_len = input.int(10, 'Supertrend ATR Length', group = 'Indicators') sup_factor = input.float(3.0, 'Supertrend Factor', group = 'Indicators') ///////////// // SYMBOLS // u01 = input.bool(true, title = '', group = 'Symbols', inline = 's01') u02 = input.bool(true, title = '', group = 'Symbols', inline = 's02') u03 = input.bool(true, title = '', group = 'Symbols', inline = 's03') u04 = input.bool(true, title = '', group = 'Symbols', inline = 's04') u05 = input.bool(true, title = '', group = 'Symbols', inline = 's05') u06 = input.bool(true, title = '', group = 'Symbols', inline = 's06') u07 = input.bool(true, title = '', group = 'Symbols', inline = 's07') u08 = input.bool(true, title = '', group = 'Symbols', inline = 's08') u09 = input.bool(true, title = '', group = 'Symbols', inline = 's09') u10 = input.bool(true, title = '', group = 'Symbols', inline = 's10') s01 = input.symbol('HDFCBANK', group = 'Symbols', inline = 's01') s02 = input.symbol('ICICIBANK', group = 'Symbols', inline = 's02') s03 = input.symbol('RELIANCE', group = 'Symbols', inline = 's03') s04 = input.symbol('INFY', group = 'Symbols', inline = 's04') s05 = input.symbol('BHARTIARTL', group = 'Symbols', inline = 's05') s06 = input.symbol('LT', group = 'Symbols', inline = 's06') s07 = input.symbol('ITC', group = 'Symbols', inline = 's07') s08 = input.symbol('TCS', group = 'Symbols', inline = 's08') s09 = input.symbol('AXISBANK', group = 'Symbols', inline = 's09') s10 = input.symbol('SBIN', group = 'Symbols', inline = 's10') ////////////////// // CALCULATIONS // filt_col_id = switch filter_column 'Price' => 1 'RSI' => 2 'TSI' => 3 'ADX' => 4 'SuperTrend' => 5 => 0 // Get only symbol only_symbol(s) => array.get(str.split(s, ':'), 1) id_symbol(s) => switch s 1 => only_symbol(s01) 2 => only_symbol(s02) 3 => only_symbol(s03) 4 => only_symbol(s04) 5 => only_symbol(s05) 6 => only_symbol(s06) 7 => only_symbol(s07) 8 => only_symbol(s08) 9 => only_symbol(s09) 10 => only_symbol(s10) => na // for TSI double_smooth(src, long, short) => fist_smooth = ta.ema(src, long) ta.ema(fist_smooth, short) // ADX dirmov(len) => up = ta.change(high) down = -ta.change(low) plusDM = na(up) ? na : up > down and up > 0 ? up : 0 minusDM = na(down) ? na : down > up and down > 0 ? down : 0 truerange = ta.rma(ta.tr, len) plus = fixnan(100 * ta.rma(plusDM, len) / truerange) minus = fixnan(100 * ta.rma(minusDM, len) / truerange) adx_func(dilen, adxlen) => = dirmov(dilen) sum = plus + minus adx = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), adxlen) adx screener_func() => // RSI rsi = ta.rsi(close, rsi_len) // TSI pc = ta.change(close) double_smoothed_pc = double_smooth(pc, tsi_long_len, tsi_shrt_len) double_smoothed_abs_pc = double_smooth(math.abs(pc), tsi_long_len, tsi_shrt_len) tsi = 100 * (double_smoothed_pc / double_smoothed_abs_pc) // ADX adx = adx_func(adx_dilen, adx_smooth) // Supertrend = ta.supertrend(sup_factor, sup_atr_len) // Set Up Matrix screenerMtx = matrix.new(0, 6, na) screenerFun(numSym, sym, flg) => = request.security(sym, timeframe.period, screener_func()) arr = array.from(numSym, cl, rsi, tsi, adx, sup) if flg matrix.add_row(screenerMtx, matrix.rows(screenerMtx), arr) // Security call screenerFun(01, s01, u01) screenerFun(02, s02, u02) screenerFun(03, s03, u03) screenerFun(04, s04, u04) screenerFun(05, s05, u05) screenerFun(06, s06, u06) screenerFun(07, s07, u07) screenerFun(08, s08, u08) screenerFun(09, s09, u09) screenerFun(10, s10, u10) /////////// // PLOTS // var tbl = table.new(position.top_right, 6, 41, frame_color = #151715, frame_width = 1, border_width = 2, border_color = color.new(color.white, 100)) log.info(str.tostring(filt_col_id)) alert_msg = '' if barstate.islast table.clear(tbl, 0, 0, 5, 40) table.cell(tbl, 0, 0, 'Symbol', text_halign = text.align_center, bgcolor = color.gray, text_color = color.white, text_size = size.small) table.cell(tbl, 1, 0, 'Price', text_halign = text.align_center, bgcolor = color.gray, text_color = color.white, text_size = size.small) table.cell(tbl, 2, 0, 'RSI', text_halign = text.align_center, bgcolor = color.gray, text_color = color.white, text_size = size.small) table.cell(tbl, 3, 0, 'TSI', text_halign = text.align_center, bgcolor = color.gray, text_color = color.white, text_size = size.small) table.cell(tbl, 4, 0, 'ADX', text_halign = text.align_center, bgcolor = color.gray, text_color = color.white, text_size = size.small) table.cell(tbl, 5, 0, 'Supertrend', text_halign = text.align_center, bgcolor = color.gray, text_color = color.white, text_size = size.small) if matrix.rows(screenerMtx) > 0 for i = 0 to matrix.rows(screenerMtx) - 1 by 1 is_filt = not filter_enabled or matrix.get(screenerMtx, i, filt_col_id) >= filter_from and matrix.get(screenerMtx, i, filt_col_id) <= filter_to if is_filt if str.length(alert_msg) > 0 alert_msg := alert_msg + ',' alert_msg alert_msg := alert_msg + id_symbol(matrix.get(screenerMtx, i, 0)) rsi_col = matrix.get(screenerMtx, i, 2) > rsi_ob ? color.red : matrix.get(screenerMtx, i, 2) < rsi_os ? color.green : #aaaaaa tsi_col = matrix.get(screenerMtx, i, 3) > tsi_ob ? color.red : matrix.get(screenerMtx, i, 3) < tsi_os ? color.green : #aaaaaa adx_col = matrix.get(screenerMtx, i, 4) > adx_level ? color.green : #aaaaaa sup_text = matrix.get(screenerMtx, i, 5) > 0 ? 'Down' : 'Up' sup_col = matrix.get(screenerMtx, i, 5) < 0 ? color.green : color.red table.cell(tbl, 0, i + 1, id_symbol(matrix.get(screenerMtx, i, 0)), text_halign = text.align_left, bgcolor = color.gray, text_color = color.white, text_size = size.small) table.cell(tbl, 1, i + 1, str.tostring(matrix.get(screenerMtx, i, 1)), text_halign = text.align_center, bgcolor = #aaaaaa, text_color = color.white, text_size = size.small) table.cell(tbl, 2, i + 1, str.tostring(matrix.get(screenerMtx, i, 2), '#.##'), text_halign = text.align_center, bgcolor = rsi_col, text_color = color.white, text_size = size.small) table.cell(tbl, 3, i + 1, str.tostring(matrix.get(screenerMtx, i, 3), '#.##'), text_halign = text.align_center, bgcolor = tsi_col, text_color = color.white, text_size = size.small) table.cell(tbl, 4, i + 1, str.tostring(matrix.get(screenerMtx, i, 4), '#.##'), text_halign = text.align_center, bgcolor = adx_col, text_color = color.white, text_size = size.small) table.cell(tbl, 5, i + 1, sup_text, text_halign = text.align_center, bgcolor = sup_col, text_color = color.white, text_size = size.small) if str.length(alert_msg) > 0 alert(alert_msg, freq = alert.freq_once_per_bar_close)
Wskaźnik Pine Script®
od shaileshGole
EMA Crossover + SuperTrend Retest//@version=5 indicator("EMA Crossover + SuperTrend Retest", overlay=true) // Inputs for SuperTrend atrLength = input.int(10, "ATR Length", minval=1) Factor = input.float(3.0, "SuperTrend Multiplier", step=0.1) // Calculate EMAs ema13 = ta.ema(close, 13) ema50 = ta.ema(close, 50) ema200 = ta.ema(close, 200) // Calculate SuperTrend = ta.supertrend(Factor, atrLength) // Plot EMAs plot(ema13, "EMA 13", color=color.new(#FF6D00, 0)) plot(ema50, "EMA 50", color=color.new(#2962FF, 0)) plot(ema200, "EMA 200", color=color.new(#00BFA5, 0)) // Plot SuperTrend plot(supertrend, "SuperTrend", color=direction == 1 ? color.rgb(230, 13, 13) : color.rgb(17, 255, 0), linewidth=2) // Trend Conditions uptrendFilter = ema50 > ema200 and close > supertrend downtrendFilter = ema50 < ema200 and close < supertrend // Crossover Conditions with Trend Filter bullishCross = ta.crossover(ema13, ema50) and uptrendFilter bearishCross = ta.crossunder(ema13, ema50) and downtrendFilter // Retest Conditions (Both EMAs and SuperTrend) bullishRetest = bullishCross and (low <= ema50) and (low <= ema200) and (low <= supertrend) bearishRetest = bearishCross and (high >= ema50) and (high >= ema200) and (high >= supertrend) // Plot Signals plotshape(bullishRetest, "Bullish Signal", shape.triangleup, location.belowbar, color=color.green, size=size.small) plotshape(bearishRetest, "Bearish Signal", shape.triangledown, location.abovebar, color=color.red, size=size.small) // Alert Conditions alertcondition(bullishRetest, "Bullish Alert", "EMA13↑50 + Retest 50/200/SuperTrend") alertcondition(bearishRetest, "Bearish Alert", "EMA13↓50 + Retest 50/200/SuperTrend")
Wskaźnik Pine Script®
od kumarmailkumar89
SDCALibraryMy Valuation Library for mostly crypto currency use, but some can be applied to other assets. There are technical and on-chain indicator functions for use. Technical Indicators: 1. **drawdown_zscore** - **Summary**: Calculates the z-score of drawdowns over a specified lookback period. - **Inputs**: - `lookback_length` (int): Period for drawdown calculation. - `zScoreLen` (int): Length for z-score calculation. 2. **sharpe_zscore** - **Summary**: Computes the z-score of the Sharpe ratio using returns over a period and a smoothing length. - **Inputs**: - `length` (int): Period for returns calculation. - `smalen` (int): Smoothing length for returns. - `zScoreLen` (int): Length for z-score calculation. 3. **rsi_zscore** - **Summary**: Calculates the z-score of the Relative Strength Index (RSI) with smoothing. - **Inputs**: - `length` (int): Period for RSI calculation. - `smalen` (int): Smoothing length for RSI. - `zScoreLen` (int): Length for z-score calculation. 4. **DFATH_zscore** - **Summary**: Computes the z-score for a specific DFATH metric (details not specified). - **Inputs**: - `zScoreLen` (int): Length for z-score calculation. 5. **RTI_zscore** - **Summary**: Calculates the z-score of a trend indicator based on data count and sensitivity. - **Inputs**: - `trend_data_count` (int): Number of data points for trend analysis. - `trend_sensitivity_percentage` (int): Sensitivity threshold for trend detection. - `zScoreLen` (int): Length for z-score calculation. On-Chain (Crypto only, mostly BTC, ETH) 6. **SOPR_zscore** - **Summary**: Computes the z-score of Spent Output Profit Ratio (SOPR) for a specific coin. - **Inputs**: - `zScoreLen` (int): Length for z-score calculation. - `coin_sopr` (string): SOPR data for the specified coin. 7. **thermocap_zscore** - **Summary**: Calculates the z-score of the Thermocap metric using moving average and coin-specific data. - **Inputs**: - `ma_len` (int): Length of the moving average. - `ma_type` (string): Type of moving average. - `zScoreLen` (int): Length for z-score calculation. - `coin_index` (string): Coin index data. - `coin_blocks_mined` (string): Data on blocks mined for the coin. 8. **MVRV_zscore** - **Summary**: Computes the z-score of the Market Value to Realized Value (MVRV) ratio. - **Inputs**: - `zScoreLen` (int): Length for z-score calculation. - `coin_MC` (string): Market capitalization data. - `coin_MC_real` (string): Realized market capitalization data. 9. **supplyinprofit_zscore** - **Summary**: Calculates the z-score of the percentage of coin supply in profit or loss, optionally adjusted for alpha decay. - **Inputs**: - `isAlphaDecayAdjusted` (bool): Whether to apply alpha decay adjustment. - `zScoreLen` (int): Length for z-score calculation. - `coin_profit_address_percent` (string): Percentage of addresses in profit. - `coin_loss_address_percent` (string): Percentage of addresses in loss. 10. **realized_price_zscore** - **Summary**: Computes the z-score of the realized price based on realized market cap and supply. - **Inputs**: - `zScoreLen` (int): Length for z-score calculation. - `coin_MC_real` (string): Realized market capitalization data. - `coin_supply` (string): Coin supply data. 11. **CVVD_zscore** - **Summary**: Calculates the z-score of Cumulative Value Days Destroyed (CVVD) metric. - **Inputs**: - `zScoreLen` (int): Length for z-score calculation. - `coin_MC_real` (string): Realized market capitalization data. - `coin_total_volume` (string): Total volume data for the coin. 12. **NUPL_zscore** - **Summary**: Computes the z-score of Net Unrealized Profit and Loss (NUPL) metric. - **Inputs**: - `zScoreLen` (int): Length for z-score calculation. - `coin_MC` (string): Market capitalization data. - `coin_MC_real` (string): Realized market capitalization data.
Biblioteka Pine Script®
od QuantChook
Moving AveragesThis indicator allows you to seamlessly apply one or multiple moving averages simultaneously on your chart. You can easily select from predefined periods: 10, 20, 50, 100, and 200. It is pre-configured to use Exponential Moving Averages (EMA) by default, so there’s no need to input or adjust the type manually—just enable the ones you need and you're ready to go. Ideal for traders who rely on dynamic trend analysis and want a quick, clutter-free setup for multiple EMAs
Wskaźnik Pine Script®
od ChiragGoyal1
Quad Rotation - StochasticThis Indicator is a step up from the Triad Rotation Indicator previously made, as it has 4 Stochastic signals rather then 3. It can be used mainly to identify potential reversal periods. If the Instrument becomes overbought, or oversold with all 4 stochastics a horizontal highlight will appear, either green or red. Green indicates the instrument is oversold, and may reverse soon, meaning you should take a buying positions, and red indicates an overbought position, where you may want to sell due to a reversal downward. Additionally, you can set an alarm if all 4 stochastic indicators signal overbought or oversold. This will help reduce your need to watch each instrument, and reduce the likelihood of overtrading. If you have comments regarding this indicator, if you found it helpful, or would like other improvements feel free to email me. If you are looking for other custom indicators, also feel free to email me. Email: thejak77@aol.com. This is an email rarely monitored, so please be patient, thank you! All the best, and stay profitable!
Wskaźnik Pine Script®
od EmberJaxx77
Breakout Entry Signals//@version=5 indicator("Breakout Entry Signals", overlay=true) length = input.int(20, title="Breakout Period") highestHigh = ta.highest(high, length) lowestLow = ta.lowest(low, length) longCondition = close > highestHigh shortCondition = close < lowestLow plotshape(longCondition, location=location.belowbar, color=color.green, style=shape.triangleup, size=size.small) plotshape(shortCondition, location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small)
Wskaźnik Pine Script®
od IzzyDuhName
Double Inside Bar Alert (1-1 Only)Double Inside Bar Alert Indicator Stay ahead of breakout opportunities with our Double Inside Bar Alert Indicator. This tool automatically scans your watchlist and notifies you in real-time whenever a double inside bar pattern appears—an advanced price action setup known for signaling strong potential breakouts or reversals. Whether you’re a day trader or swing trader, this indicator helps you: Spot consolidation zones early before major price moves Receive instant alerts across your entire watchlist Filter noise and focus on high-probability chart setups Perfect for traders who rely on price action and want to catch momentum shifts as they form.
Wskaźnik Pine Script®
od mrf2rev
1
DJZS Session Tracker (PDT-Aligned)//@version=5 indicator("DJZS Session Tracker (PDT-Aligned)", overlay=true, max_lines_count=500) // Extract current date/time var int y = year(time) var int mo = month(time) var int d = dayofmonth(time) // Convert local session times (PDT = UTC-7) asia_start = timestamp("America/Los_Angeles", y, mo, d, 17, 0) asia_end = timestamp("America/Los_Angeles", y, mo, d + 1, 2, 0) london_start = timestamp("America/Los_Angeles", y, mo, d + 1, 0, 0) london_end = timestamp("America/Los_Angeles", y, mo, d + 1, 9, 0) ny_start = timestamp("America/Los_Angeles", y, mo, d + 1, 5, 0) ny_end = timestamp("America/Los_Angeles", y, mo, d + 1, 14, 0) in_session(start, end) => time >= start and time < end asia = in_session(asia_start, asia_end) london = in_session(london_start, london_end) ny = in_session(ny_start, ny_end) // Plot background for sessions bgcolor(asia ? color.new(color.aqua, 85) : na) bgcolor(london ? color.new(color.green, 85) : na) bgcolor(ny ? color.new(color.orange, 85) : na) // Track session highs/lows var float asiaHigh = na var float asiaLow = na var float londonHigh = na var float londonLow = na var float nyHigh = na var float nyLow = na if asia asiaHigh := na(asiaHigh) ? high : math.max(asiaHigh, high) asiaLow := na(asiaLow) ? low : math.min(asiaLow, low) else asiaHigh := na asiaLow := na if london londonHigh := na(londonHigh) ? high : math.max(londonHigh, high) londonLow := na(londonLow) ? low : math.min(londonLow, low) else londonHigh := na londonLow := na if ny nyHigh := na(nyHigh) ? high : math.max(nyHigh, high) nyLow := na(nyLow) ? low : math.min(nyLow, low) else nyHigh := na nyLow := na // Plot session highs/lows plot(asiaHigh, "Asia High", color=color.aqua, style=plot.style_linebr, linewidth=1) plot(asiaLow, "Asia Low", color=color.aqua, style=plot.style_linebr, linewidth=1) plot(londonHigh, "London High", color=color.green, style=plot.style_linebr, linewidth=1) plot(londonLow, "London Low", color=color.green, style=plot.style_linebr, linewidth=1) plot(nyHigh, "NY High", color=color.orange, style=plot.style_linebr, linewidth=1) plot(nyLow, "NY Low", color=color.orange, style=plot.style_linebr, linewidth=1)
Wskaźnik Pine Script®
od djzsx