ADX & DI (Modified to v5 by ChatGPT with Custom Colors & Levels)// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © RealKunalRajani
//@version=5
indicator("ADX and DI (v5 with Custom Colors & Levels)", overlay=false)
// Inputs
len = input.int(14, title="ADX Length")
// True Range
trueRange = math.max(math.max(high - low, math.abs(high - nz(close ))), math.abs(low - nz(close )))
// Directional Movements
dmPlus = (high - nz(high ) > nz(low ) - low) ? math.max(high - nz(high ), 0) : 0
dmMinus = (nz(low ) - low > high - nz(high )) ? math.max(nz(low ) - low, 0) : 0
// Smoothed values
smTR = 0.0
smTR := nz(smTR ) - (nz(smTR ) / len) + trueRange
smDMp = 0.0
smDMp := nz(smDMp ) - (nz(smDMp ) / len) + dmPlus
smDMm = 0.0
smDMm := nz(smDMm ) - (nz(smDMm ) / len) + dmMinus
// DI+ and DI-
DIplus = (smDMp / smTR) * 100
DIminus = (smDMm / smTR) * 100
// DX and ADX
DX = math.abs(DIplus - DIminus) / (DIplus + DIminus) * 100
ADX = ta.sma(DX, len)
// Plots with custom colors
plot(DIplus, color=color.green, title="DI+")
plot(DIminus, color=color.red, title="DI-")
plot(ADX, color=color.yellow, title="ADX")
// Custom Threshold Lines
hline(15, color=color.white, linestyle=hline.style_dashed, title="Threshold 1")
hline(20, color=color.white, linestyle=hline.style_dashed, title="Threshold 2")
אינדיקטורים ואסטרטגיות
Grok PHD Options put/call walls.Options put/call walls. Puts support, Calls resistance. Grok PHD Trading dot com.
Relative Volume (RVOL) + Average Volume [AZ]The script helps you instantly see whether today’s volume is unusual compared to the past (relative volume). It’s built for breakout/fakeout filters, like the 15-minute ORB strategy you’re running.
Technical Summary VWAP | RSI | VolatilityTechnical Summary VWAP | RSI | Volatility
The Quantum Trading Matrix is a multi-dimensional market-analysis dashboard designed as an educational and idea-generation tool to help traders read price structure, participation, momentum and volatility in one compact view. It is not an automated execution system; rather, it aggregates lightweight “quantum” signals — VWAP position, momentum oscillator behaviour, multi-EMA trend scoring, volume flow and institutional activity heuristics, market microstructure pivots and volatility measures — and synthesizes them into a single, transparent score and signal recommendation. The primary goal is to make explicit why a given market looks favourable or unfavourable by showing the individual ingredients and how they combine, enabling traders to learn, test and form rules based on observable market mechanics.
Each module of the matrix answers a distinct market question. VWAP and its percentage distance indicate whether the current price is trading above or below the intraday volume-weighted average — a proxy for intraday institutional control and value. The quantum momentum oscillator (fast and slow EMA difference scaled to percent) captures short-to-intermediate momentum shifts, providing a quickly responsive view of directional pressure. Multi-EMA trend scoring (8/21/50) produces a simple, transparent trend score by counting conditions such as price above EMAs and cross-EMAs ordering; this score is used to categorize market trend into descriptive buckets (e.g., STRONG UP, WEAK UP, NEUTRAL, DOWN). Volume analysis compares current volume to a recent moving average and computes a Z-score to detect spikes and unusual participation; additional buy/sell pressure heuristics (buyingPressure, sellingPressure, flowRatio) estimate whether upside or downside participation dominates the bar. Institutional activity is approximated by flagging large orders relative to volume baseline (e.g., volume > 2.5× MA) and estimating a dark pool proxy; this is a heuristic to highlight bars that likely had large players involved.
The dashboard also performs market-structure detection with small pivot windows to identify recent local support/resistance areas and computes price position relative to the daily high/low (dailyMid, pricePosition). Volatility is measured via ATR divided by price and bucketed into LOW/NORMAL/HIGH/EXTREME categories to help you adapt stop sizing and expectational horizons. Finally, all these pieces feed an interpretable scoring function that rewards alignment: VWAP above, strong flow ratio, bullish trend score, bullish momentum, and favorable RSI zone add to the overall score which is presented as a 0–100 metric and a colored emoji indicator for at-a-glance assessment.
The mashup is purposeful: each indicator covers a failure mode of the other. For example, momentum readings can be misleading during volatility spikes; VWAP informs whether institutions are on the bid or offer; volume Z-score detects abnormal participation that can validate a breakout; multi-EMA score mitigates single-EMA whipsaws by requiring a combination of price/EMA conditions. Combining these signals increases information content while keeping each component explainable — a key compliance requirement. The script intentionally emphasizes transparency: when it shows a BUY/SELL/HOLD recommendation, the dashboard shows the underlying sub-components so a trader can see whether VWAP, momentum, volume, trend or structure primarily drove the score.
For practical use, adopt a clear workflow: (1) check the matrix score and read the component tiles (VWAP position, momentum, trend and volume) to understand the drivers; (2) confirm market-structure support/resistance and pricePosition relative to the daily range; (3) require at least two corroborating components (for example, VWAP ABOVE + Momentum BULLISH or Volume spike + Trend STRONG UP) before considering entries; (4) use ATR-based stops or daily pivot distance for stop placement and size positions such that the trade risks a small, pre-defined percent of capital; (5) for intraday scalps shorten holding time and tighten stops, for swing trades increase lookback lengths and require multi-timeframe (higher TF) agreement. Treat the matrix as an idea filter and replay lab: when an alert triggers, replay the bars and observe which components anticipated the move and which lagged.
Parameter tuning matters. Shortening the momentum length makes the oscillator more sensitive (useful for scalping), while lengthening it reduces noise for swing contexts. Volume profile bars and MA length should match the instrument’s liquidity — increase the MA for low-liquidity stocks to reduce false institutional flags. The trend multiplier and signal sensitivity parameters let you calibrate how aggressively the matrix counts micro evidence into the score. Always backtest parameter sets across multiple periods and instruments; run walk-forward tests and keep a simple out-of-sample validation window to reduce overfitting risk.
Limitations and failure modes are explicit: institutional flags and dark-pool estimates are heuristics and cannot substitute for true tape or broker-level order flow; volume split by price range is an approximation and will not perfectly reflect signed volume; pivot detection with small windows may miss larger structural swings; VWAP is typically intraday-centric and less meaningful across multi-day swing contexts; the score is additive and may not capture non-linear relationships between features in extreme market regimes (e.g., flash crashes, circuit breaker events, or overnight gaps). The matrix is also susceptible to false signals during major news releases when price and volume behavior dislocate from typical patterns. Users should explicitly test behavior around earnings, macro data and low-liquidity periods.
To learn with the matrix, perform these experiments: (A) collect all BUY/SELL alerts over a 6-month period and measure median outcome at 5, 20 and 60 bars; (B) require additional gating conditions (e.g., only accept BUY when flowRatio>60 and trendScore≥4) and compare expectancy; (C) vary the institutional threshold (2×, 2.5×, 3× volumeMA) to see how many true positive spikes remain; (D) perform multi-instrument tests to ensure parameters are not tuned to a single ticker. Document every test and prefer robust, slightly lower returns with clearer logic rather than tuned “optimal” results that fail out of sample.
Originality statement: This script’s originality lies in the curated combination of intraday value (VWAP), multi-EMA trend scoring, momentum percent oscillator, volume Z-score plus buy/sell flow heuristics and a compact, interpretable scoring system. The script is not a simple indicator mashup; it is a didactic ensemble specifically designed to make internal rationale visible so traders can learn how each market characteristic contributes to actionable probability. The tool’s novelty is its emphasis on interpretability — showing the exact contributing signals behind a composite score — enabling reproducible testing and educational value.
Finally, for TradingView publication, include a clear description listing the modules, a short non-technical summary of how they interact, the tunable inputs, limitations and a risk disclaimer. Remove any promotional content or external contact links. If you used trademark symbols, either provide registration details or remove them. This transparent documentation satisfies TradingView’s requirement that mashups justify their composition and teach users how to use them.
Quantum Trading Matrix — multi-factor intraday dashboard (educational use only).
Purpose: Combines intraday VWAP position, a fast/slow EMA momentum percent oscillator, multi-EMA trend scoring (8/21/50), volume Z-score and buy/sell flow heuristics, pivot-based microstructure detection, and ATR-based volatility buckets to produce a transparent, componentized market score and trade-idea indicator. The mashup is intentional: VWAP identifies intraday value, momentum detects short bursts, EMAs provide structural trend bias, and volume/flow confirm participation. Signals require alignment of at least two components (for example, VWAP ABOVE + Momentum BULLISH + positive flow) for higher confidence.
Inputs: momentum period, volume MA/profile length, EMA configuration (8/21/50), trend multiplier, signal sensitivity, color and display options. Use shorter momentum lengths for scalps and longer for swing analysis. Increase volume MA for thinly traded instruments.
Limitations: Institutional/dark-pool estimates and flow heuristics are approximations, not actual exchange tape. VWAP is intraday-focused. Expect false signals during major news or low-liquidity sessions. Backtest and paper-trade before applying real capital.
Risk Disclaimer: For education and analysis only. Not financial advice. Use proper risk management. The author is not responsible for trading losses.
________________________________________
Risk & Misuse Disclaimer
This indicator is provided for education, analysis and idea generation only. It is not investment or financial advice and does not guarantee profits. Institutional activity flags, dark-pool estimates and flow heuristics are approximations and should not be treated as exchange tape. Backtest thoroughly and use demo/paper accounts before trading real capital. Always apply appropriate position sizing and stop-loss rules. The author is not responsible for any trading losses resulting from the use or misuse of this tool.
________________________________________
Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
RSI with Dual Smoothed MAs + Trend BackgroundRSI with two custom MAs (SMA, EMA, WMA, RMA, VWMA).
Slope-based MA coloring.
Background shading for quick trend confirmation.
ADR(20) % ValueDisplays the 20-day Average Daily Range (ADR) as a % of price, following the method popularized by Kristjan Qullamägi (Qullamaggie). The ADR value updates dynamically and is printed directly on the chart for quick reference.
Hurst Momentum Oscillator | AlphaNattHurst Momentum Oscillator | AlphaNatt
An adaptive oscillator that combines the Hurst Exponent - which identifies whether markets are trending or mean-reverting - with momentum analysis to create signals that automatically adjust to market regime.
"The Hurst Exponent reveals a hidden truth: markets aren't always trending. This oscillator knows when to ride momentum and when to fade it."
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📐 THE MATHEMATICS
Hurst Exponent (H):
Measures the long-term memory of time series:
H > 0.5: Trending (persistent) behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting behavior
Originally developed for analyzing Nile river flooding patterns, now used in:
Fractal market analysis
Network traffic prediction
Climate modeling
Financial markets
The Innovation:
This oscillator multiplies momentum by the Hurst coefficient:
When trending (H > 0.5): Momentum is amplified
When mean-reverting (H < 0.5): Momentum is reduced
Result: Adaptive signals based on market regime
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💎 KEY ADVANTAGES
Regime Adaptive: Automatically adjusts to trending vs ranging markets
False Signal Reduction: Reduces momentum signals in mean-reverting markets
Trend Amplification: Stronger signals when trends are persistent
Mathematical Edge: Based on fractal dimension analysis
No Repainting: All calculations on historical data
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📊 TRADING SIGNALS
Visual Interpretation:
Cyan zones: Bullish momentum in trending market
Magenta zones: Bearish momentum or mean reversion
Background tint: Blue = trending, Pink = mean-reverting
Gradient intensity: Signal strength
Trading Strategies:
1. Trend Following:
Trade momentum signals when background is blue (trending)
2. Mean Reversion:
Fade extreme readings when background is pink
3. Regime Transition:
Watch for background color changes as early warning
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🎯 OPTIMAL USAGE
Best Conditions:
Strong trending markets (crypto bull runs)
Clear ranging markets (forex sessions)
Regime transitions
Multi-timeframe analysis
Market Applications:
Crypto: Excellent for identifying trend persistence
Forex: Detects when pairs are ranging
Stocks: Identifies momentum stocks
Commodities: Catches persistent trends
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Developed by AlphaNatt | Fractal Market Analysis
Version: 1.0
Classification: Adaptive Regime Oscillator
Not financial advice. Always DYOR.
Combine two tickers OHLC bars with selectable sourcesCombines the bars of two chosen tickers, used to fix issues with split history, new ticker names
e.g. MYTIL went to LSE from ATHEX and changed ticker names but with "broken"/ split chart history. With this script you get the full history combined with the two tickers.
An SMA50 was used as an example of how this can be used with others custom indicators inside this script.
Recovery StrategyDescription:
The Recovery Strategy is a long-only trading system designed to capitalize on significant price drops from recent highs. It enters a position when the price falls 10% or more from the highest high over a 6-month lookback period and adds positions on further 2% drops, up to a maximum of 5 positions. Each trade is held for 6 months before exiting, regardless of profit or loss. The strategy uses margin to amplify position sizes, with a default leverage of 5:1 (20% margin requirement). All key parameters are customizable via inputs, allowing flexibility for different assets and timeframes. Visual markers indicate recent highs for reference.
How It Works:
Entry: Buys when the closing price drops 10% or more from the recent high (highest high in the lookback period, default 126 bars ~6 months). If already in a position, additional buys occur on further 2% drops (e.g., 12%, 14%, 16%, 18%), up to 5 positions (pyramiding).
Exit: Each trade exits after its own holding period (default 126 bars ~6 months), regardless of profit or loss. No stop loss or take-profit is used.
Margin: Uses leverage to control larger positions (default 20% margin, 5:1 leverage). The order size is a percentage of equity (default 100%), adjustable via inputs.
Visualization: Displays blue markers (without text) at new recent highs to highlight reference levels.
Inputs:
Lookback Period for High Peak (bars): Number of bars to look back for the recent high (default: 126, ~6 months on daily charts).
Initial Drop Percentage to Buy (%): Percentage drop from recent high to trigger the first buy (default: 10.0%).
Additional Drop Percentage to Buy (%): Further drop percentage to add positions (default: 2.0%).
Holding Period (bars): Number of bars to hold each position before selling (default: 126, ~6 months).
Order Size (% of Equity): Percentage of equity used per trade (default: 100%).
Margin for Long Positions (%): Percentage of position value covered by equity (default: 20%, equivalent to 5:1 leverage).
Usage:
Timeframe: Designed for daily charts (126 bars ~6 months). Adjust Lookback Period and Holding Period for other timeframes (e.g., 1008 hours for hourly charts, assuming 8 trading hours/day).
Assets: Suitable for stocks, ETFs, or other assets with significant price volatility. Test thoroughly on your chosen asset.
Settings: Customize inputs in the strategy settings to match your risk tolerance and market conditions. For example, lower Margin for Long Positions (e.g., to 10% for 10:1 leverage) to increase position sizes, but beware of higher risk.
Backtesting: Use TradingView’s Strategy Tester to evaluate performance. Check the “List of Trades” for skipped trades due to insufficient equity or margin requirements.
Risks and Considerations:
No Stop Loss: The strategy holds trades for the full 6 months without a stop loss, exposing it to significant drawdowns in prolonged downtrends.
Margin Risk: Leverage (default 5:1) amplifies both profits and losses. Ensure sufficient equity to cover margin requirements to avoid skipped trades or simulated margin calls.
Pyramiding: Up to 5 positions can be open simultaneously, increasing exposure. Adjust pyramiding in the code if fewer positions are desired (e.g., change to pyramiding=3).
Market Conditions: Performance depends on price drops and recoveries. Test on historical data to assess effectiveness in your market.
Broker Emulator: TradingView’s paper trading simulates margin but does not execute real margin trading. Results may differ in live trading due to broker-specific margin rules.
How to Use:
Add the strategy to your chart in TradingView.
Adjust input parameters in the settings panel to suit your asset, timeframe, and risk preferences.
Run a backtest in the Strategy Tester to evaluate performance.
Monitor open positions and margin levels in the Trading Panel to manage risk.
For live trading, consult your broker’s margin requirements and leverage policies, as TradingView’s simulation may not match real-world conditions.
Disclaimer:
This strategy is for educational purposes only and does not constitute financial advice. Trading involves significant risk, especially with leverage and no stop loss. Always backtest thoroughly and consult a financial advisor before using any strategy in live trading.
Trendlines with ATR flexabilityIndicator shows you the trendline with ability to sel up how far the pivot can be from a perverct pixel in percentage of ATR of current timeframe
Cruce TEMA SMMA con Alarma a 12 BarrasPROBANDO Una estrategia de 12 velas para la venta de xauusd en temporalidades de 1h a 1 minuto
Turnover// ========================================
// TURNOVER INDICATOR (成交额指标)
// ========================================
//
// This indicator calculates and displays the turnover (trading value) for each bar,
// which represents the total monetary value of shares traded during that period.
// Turnover = Volume × Price
//
// KEY FEATURES:
// • Multiple price basis options: VWAP (recommended for intraday) or HLC3 average
// • Visual representation with colored columns (red/green for down/up bars)
// • Moving average overlay to smooth turnover trends
// • Rolling sum calculation for cumulative turnover over specified periods
// • Fully customizable parameters for different trading strategies
//
// USE CASES:
// • Identify periods of high/low market activity and liquidity
// • Analyze institutional money flow and market participation
// • Spot potential breakout or reversal points based on turnover spikes
// • Compare relative trading interest across different timeframes
// • Monitor market strength during trend formations
//
// PARAMETERS:
// • Price Basis: Choose between VWAP (intraday focus) or HLC3 (daily+ timeframes)
// • Visual Options: Toggle MA, rolling sum, and color coding
// • Timeframe Flexibility: Adjust MA and sum periods for your analysis needs
//
// ========================================
5 EMA Close/Open Cross StrategyLong Entry - 5 EMA Close crossing above 5 EMA open
exit - 5 EMA Close crossing below 5 EMA open
Short entry - 5 EMA Close crossing below 5 EMA open
exit - 5 EMA Close crossing above 5 EMA open
Candle Range Theory: CRT, InsideBar-CRT + AlertDescription:
The Candle Range & Inside Bar CRTs indicator is a powerful tool designed for traders who want to analyze price action and make informed decisions based on candle range theories. This indicator automatically identifies key candle range patterns and inside bars, providing clear visual signals directly on your chart.
Key Features:
Candle Range Theory Detection: Automatically highlights candles based on range analysis, allowing traders to spot potential breakout or reversal points.
Inside Bar CRTs: Detects inside bars and marks them on the chart, helping traders identify consolidation periods and potential breakout opportunities.
Custom Alerts: Users can set alerts for specific candle range or inside bar events, ensuring they never miss a trade opportunity.
Visual Clarity: Clear markings and labels on the chart make it easy to interpret signals at a glance.
User-Friendly: Intuitive setup and customizable options to fit different trading styles and timeframes.
Use Cases:
Spotting breakout and reversal opportunities.
Identifying consolidation zones with inside bars.
Enhancing decision-making in swing, day, or scalping trading strategies.
Combining with other indicators or trading strategies for confirmation.
Alerts:
Set alerts for:
Candle range breakout
Inside bar formation
Any combination of candle range and inside bar signals
Stocks Multi-Indicator Alerts (cryptodaddy)//@version=6
// Multi-Indicator Alerts
// --------------------------------------------
// This script combines technical indicators and basic analyst data
// to produce composite buy and sell signals. Each block is heavily
// commented so future modifications are straightforward.
indicator("Multi-Indicator Alerts", overlay=true, max_labels_count=500)
//// === Daily momentum indicators ===
// Relative Strength Index measures price momentum.
rsiLength = input.int(14, "RSI Length")
rsi = ta.rsi(close, rsiLength)
// Money Flow Index incorporates volume to track capital movement.
// In Pine Script v6 the function only requires a price source and length;
// volume is taken from the built-in `volume` series automatically.
mfLength = input.int(14, "Money Flow Length")
mf = ta.mfi(hlc3, mfLength)
// `mfUp`/`mfDown` flag a turn in money flow over the last two bars.
mfUp = ta.rising(mf, 2)
mfDown = ta.falling(mf, 2)
//// === WaveTrend oscillator ===
// A simplified WaveTrend model produces "dots" indicating potential
// exhaustion points. Values beyond +/-53 are treated as oversold/overbought.
n1 = input.int(10, "WT Channel Length")
n2 = input.int(21, "WT Average Length")
ap = hlc3 // typical price
esa = ta.ema(ap, n1) // smoothed price
d = ta.ema(math.abs(ap - esa), n1) // smoothed deviation
ci = (ap - esa) / (0.015 * d) // channel index
tci = ta.ema(ci, n2) // trend channel index
wt1 = tci // main line
wt2 = ta.sma(wt1, 4) // signal line
greenDot = ta.crossover(wt1, wt2) and wt1 < -53
redDot = ta.crossunder(wt1, wt2) and wt1 > 53
plotshape(greenDot, title="Green Dot", style=shape.circle, color=color.green, location=location.belowbar, size=size.tiny)
plotshape(redDot, title="Red Dot", style=shape.circle, color=color.red, location=location.abovebar, size=size.tiny)
//// === Analyst fundamentals ===
// Fundamental values from TradingView's database. If a ticker lacks data
// these will return `na` and the related conditions simply evaluate false.
rating = request.financial(syminfo.tickerid, "rating", period="FY")
targetHigh = request.financial(syminfo.tickerid, "target_high_price", period="FY")
targetLow = request.financial(syminfo.tickerid, "target_low_price", period="FY")
upsidePct = (targetHigh - close) / close * 100
downsidePct = (close - targetLow) / close * 100
// `rating` comes back as a numeric value (1 strong sell -> 5 strong buy). Use
// thresholds instead of string comparisons so the script compiles even when
// the broker only supplies numeric ratings.
ratingBuy = rating >= 4 // buy or strong buy
ratingNeutralOrBuy = rating >= 3 // neutral or better
upsideCondition = upsidePct >= 2 * downsidePct // upside at least twice downside
downsideCondition = downsidePct >= upsidePct // downside greater or equal
//// === Daily moving-average context ===
// 50 EMA represents short-term trend; 200 EMA long-term bias.
ema50 = ta.ema(close, 50)
ema200 = ta.ema(close, 200)
longBias = close > ema200 // price above 200-day = long bias
momentumFavorable = close > ema50 // price above 50-day = positive momentum
//// === Weekly trend filter ===
// Higher timeframe confirmation to reduce noise.
weeklyClose = request.security(syminfo.tickerid, "W", close)
weeklyEMA20 = request.security(syminfo.tickerid, "W", ta.ema(close, 20))
weeklyRSI = request.security(syminfo.tickerid, "W", ta.rsi(close, rsiLength))
// Weekly Money Flow uses the same two-argument `ta.mfi()` inside `request.security`.
weeklyMF = request.security(syminfo.tickerid, "W", ta.mfi(hlc3, mfLength))
weeklyFilter = weeklyClose > weeklyEMA20
//// === Buy evaluation ===
// Each true condition contributes one point to `buyScore`.
c1_buy = rsi < 50 // RSI below midpoint
c2_buy = mfUp // Money Flow turning up
c3_buy = greenDot // WaveTrend oversold bounce
c4_buy = ratingBuy // Analyst rating Buy/Strong Buy
c5_buy = upsideCondition // Forecast upside twice downside
buyScore = (c1_buy?1:0) + (c2_buy?1:0) + (c3_buy?1:0) + (c4_buy?1:0) + (c5_buy?1:0)
// Require all five conditions plus trend filters and persistence for two bars.
buyCond = c1_buy and c2_buy and c3_buy and c4_buy and c5_buy and longBias and momentumFavorable and weeklyFilter and weeklyRSI > 50 and weeklyMF > 50
buySignal = buyCond and buyCond
//// === Sell evaluation ===
// Similar logic as buy side but inverted.
c1_sell = rsi > 70 // RSI above overbought threshold
c2_sell = mfDown // Money Flow turning down
c3_sell = redDot // WaveTrend overbought reversal
c4_sell = ratingNeutralOrBuy // Analysts neutral or still buy
c5_sell = downsideCondition // Downside at least equal to upside
sellScore = (c1_sell?1:0) + (c2_sell?1:0) + (c3_sell?1:0) + (c4_sell?1:0) + (c5_sell?1:0)
// For exits require weekly filters to fail or long bias lost.
sellCond = c1_sell and c2_sell and c3_sell and c4_sell and c5_sell and (not longBias or not weeklyFilter or weeklyRSI < 50)
sellSignal = sellCond and sellCond
// Plot composite scores for quick reference.
plot(buyScore, "Buy Score", color=color.green)
plot(sellScore, "Sell Score", color=color.red)
//// === Confidence table ===
// Shows which of the five buy/sell checks are currently met.
var table status = table.new(position.top_right, 5, 2, border_width=1)
if barstate.islast
table.cell(status, 0, 0, "RSI", bgcolor=c1_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 1, 0, "MF", bgcolor=c2_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 2, 0, "Dot", bgcolor=c3_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 3, 0, "Rating", bgcolor=c4_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 4, 0, "Target", bgcolor=c5_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 0, 1, "RSI>70", bgcolor=c1_sell?color.new(color.red,0):color.new(color.green,0))
table.cell(status, 1, 1, "MF down",bgcolor=c2_sell?color.new(color.red,0):color.new(color.green,0))
table.cell(status, 2, 1, "Red dot", bgcolor=c3_sell?color.new(color.red,0):color.new(color.green,0))
table.cell(status, 3, 1, "Rating", bgcolor=c4_sell?color.new(color.red,0):color.new(color.green,0))
table.cell(status, 4, 1, "Target", bgcolor=c5_sell?color.new(color.red,0):color.new(color.green,0))
//// === Alert text ===
// Include key metrics in alerts so the chart doesn't need to be opened.
buyMsg = "BUY: RSI " + str.tostring(rsi, "#.##") +
", MF " + str.tostring(mf, "#.##") +
", Upside " + str.tostring(upsidePct, "#.##") + "%" +
", Downside " + str.tostring(downsidePct, "#.##") + "%" +
", Rating " + str.tostring(rating, "#.##")
sellMsg = "SELL: RSI " + str.tostring(rsi, "#.##") +
", MF " + str.tostring(mf, "#.##") +
", Upside " + str.tostring(upsidePct, "#.##") + "%" +
", Downside " + str.tostring(downsidePct, "#.##") + "%" +
", Rating " + str.tostring(rating, "#.##")
// Alert conditions use static messages; dynamic data is sent via `alert()`
alertcondition(buySignal, title="Buy Signal", message="Buy conditions met")
alertcondition(sellSignal, title="Sell Signal", message="Sell conditions met")
if buySignal
alert(buyMsg, alert.freq_once_per_bar_close)
if sellSignal
alert(sellMsg, alert.freq_once_per_bar_close)
//// === Watch-out flags ===
// Gentle warnings when trends weaken but before full sell signals.
warnRSI = rsi > 65 and rsi <= 65
warnAnalyst = upsidePct < 2 * downsidePct and upsidePct > downsidePct
alertcondition(warnRSI, title="RSI Watch", message="RSI creeping above 65")
alertcondition(warnAnalyst, title="Analyst Watch", message="Analyst upside shrinking")
if warnRSI
alert("RSI creeping above 65: " + str.tostring(rsi, "#.##"), alert.freq_once_per_bar_close)
if warnAnalyst
alert("Analyst upside shrinking: up " + str.tostring(upsidePct, "#.##") + "% vs down " + str.tostring(downsidePct, "#.##") + "%", alert.freq_once_per_bar_close)
//// === Plot bias moving averages ===
plot(ema50, color=color.orange, title="EMA50")
plot(ema200, color=color.blue, title="EMA200")
//// === Cross alerts for context ===
goldenCross = ta.crossover(ema50, ema200)
deathCross = ta.crossunder(ema50, ema200)
alertcondition(goldenCross, title="Golden Cross", message="50 EMA crossed above 200 EMA")
alertcondition(deathCross, title="Death Cross", message="50 EMA crossed below 200 EMA")
NQ Open Playbook (with Toggles)marks out asain,london.ny high and lows on 4h,1h,15m simple little stradGY FOER BEGINERS TO GET A FEEL FOR THE MARKET.
SMC Pro (Wellington) v1.4.2This SMC indicator combines BOS/CHoCH, OBs, FVGs, liquidity, and Premium/Discount with confirmation on the 1H (EMA200).
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Stockbee Reversal BullishCustom indicator for identifying stocks that meet the Stockbee's Reversal Bullish criteria. This can be used as a standalone indicator or use it to screen for stocks in Pine Screener.
HOPE(EMA) ROPE(IC)Confucius say: Man at end of rope finds hope; man drunk on hope soon finds rope
-HaggisZero
عكفة الماكد المتقدمة - أبو فارس ©// 🔒 Advanced MACD Curve © 2025
// 💡 Idea & Creativity: Engineer Abu Elias
// 🛠️ Development & Implementation: Abu Fares
// 📜 All intellectual rights reserved - Copying, modifying, or redistributing is not permitted
// 🚫 Any attempt to tamper with this code or violate intellectual property rights is legally prohibited
// 📧 For inquiries and licensing: Please contact the developer, Abu Fares
dr.forexy strategy 1“Dear friends, please do not use this strategy on your own! This setup works best on the 5-minute timeframe. I hope it brings you great profits.”
