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🏆 AG Pro Crypto Screener & Signal Dashboard v2.7🏆 AG Pro Multi-Crypto Screener & Signal Dashboard (Completely Free) Stop wasting your valuable time navigating dozens of charts just to find opportunities! This completely free and professional signal dashboard scans up to 40 Crypto, Stock, or Forex assets for you from a single screen. The AG Pro Screener is designed for traders who need to make fast, informed decisions. It monitors the market 24/7, identifies 'Buy' signals based on its robust multi-filter strategy, and presents all opportunities on a professional "at-a-glance" interface. This is not just another indicator; it's a complete Crypto Screener and Signal Panel designed for professional traders. AG Pro Kripto Tarayıcı ve Sinyal Paneli (Multi-Crypto Screener & Signal Dashboard) ✨ Compelling Features (All 100% Free) Advanced Dashboard Design: A best-in-class professional table with "Zebra Stripes" for easy reading, a custom-branded title bar, and a compact layout. Multi-Symbol Scanning: Scans up to 40 different user-defined assets (Coins, Stocks, etc.) simultaneously. Advanced Multi-Filter Strategy (All Toggleable): Trend Filter (SMA 200): Capture only strong signals that are aligned with the main trend. Momentum Filter (RSI): Increase your success rate by confirming signals with relative strength (e.g., RSI > 50). Entry Signal (EMA Crossover): The core 'Buy' signal based on a fast/slow EMA cross (e.g., 20/50). Volume Filter: Automatically filter out low-volume, illiquid, and risky assets from your signal list. "At-a-Glance" Visual Icons: This dashboard doesn't just give signals; it shows you the quality of the signal: Trend Column: 🔼 (Uptrend) or 🔽 (Downtrend) icons instantly show if the signal is "with the trend." Signal Freshness Column: Special icons show how "fresh" the signal is: 🔥 (Hot): 0-3 bars ago (A new opportunity!) ❇️ (Fresh): 4-7 bars ago ⏳ (Old): 8+ bars ago (Signal may be stale) Fully Customizable Interface: Adjustable Text Size: Choose your own font size (Tiny, Small, Normal) to perfectly fit the table to your screen. Selectable Timeframe: Scan your current "Chart" timeframe, or lock the panel to a specific timeframe (e.g., "4H" or "1D"). Powerful Alert Support: Set up just one single alert to receive instant notifications for all new 'Buy' signals found across all 40 assets. Perfect for strategy automation and bot setups. ⚙️ How to Use Add this indicator (AG Pro Screener) to your chart. Open the Settings (⚙️) panel for the script. In the "Symbol List" section, fill the 40 empty slots with your favorite assets (e.g., BINANCE:BTCUSDT, BINANCE:ETHUSDT, NASDAQ:AAPL, etc.). In the "Strategy Settings" section, customize your filters like EMA lengths and RSI levels to match your personal system. Watch the dashboard scan the market for you and deliver signals in real-time! 🙏 Support & Feedback (Don't Forget to Like!) A lot of effort went into developing this free tool. If you find it helpful, please take one second to click the Like (👍) button and Follow me for the next scripts in the "AG Pro" series. You can leave all your suggestions and new feature requests as a comment. Happy trading!
Pine Script® indicator
by AGProLabs
1
TRI - Support/Resistance ZonesTRI - SUPPORT/RESISTANCE ZONES v1.0 DESCRIPTION: Professional support and resistance level indicator based on body pivot analysis. Unlike traditional indicators that use wicks (high/low), this tool identifies key levels using candle bodies (open/close), providing more reliable and significant price zones. KEY FEATURES: Body-based pivot detection for more meaningful levels Automatic level validation (excludes breached levels) Smart level filtering (avoids cluttered charts) Configurable number of support/resistance levels (1-5 each) Visual customization (colors, transparency, line extension) Real-time breakout alerts for resistance and support levels Clean and intuitive interface with price labels HOW IT WORKS: The indicator scans historical price action to identify pivot points based on candle bodies. Only valid levels (not breached since formation) are displayed. Levels are automatically filtered by proximity to avoid visual clutter while maintaining the most relevant zones. Breakout alerts trigger when price closes above resistance or below support. BEST USE: Ideal for swing trading, day trading, and identifying key decision points. Works on all timeframes and asset classes.
Pine Script® indicator
by riccardo_tempesta
5
🎯 Goal Tracker - Ace EditionTransform your trading mindset with the Goal Tracker – Ace Edition. This elegant visual tool lets you set a main goal and break it into four key steps — each represented by an Ace suit (♣️, ♠️, ♥️, ♦️). Mark each milestone as completed directly from the settings panel and instantly see your progress displayed on the chart. Perfect for traders who want to build consistency, focus, and discipline — one step at a time. ✨ Features: 🎯 Set your main goal and 4 customizable steps ♣️♠️♥️♦️ Each step linked to an Ace suit — symbolic and motivational ✅ Toggle completion with a single click 🎨 Fully customizable colors, fonts, and chart position 📍 Works in overlay mode — visible on any chart, any timeframe 💡 Ideal for: Traders working on mindset and discipline Prop firm traders tracking behavioral goals Anyone who wants to visualize progress right on their chart Example Usage: Goal: “Follow my trading plan for one week” ♣️ Step 1: Avoid impulsive entries ♠️ Step 2: Respect stop loss ♥️ Step 3: Take only A+ setups ♦️ Step 4: Journal every trade
Pine Script® indicator
by El_Bichotico
No-Trade Zones UTC+7This indicator helps you visualize and backtest your preferred trading hours. For example, if you have a 9-to-5 job, you obviously can’t trade during that time — and when backtesting, you should avoid those hours too. It also marks weekends if you prefer not to trade on those days. By highlighting no-trade periods directly on the chart, you can easily see when you shouldn’t be taking trades, without constantly checking the time or date by hovering over the chart. It makes backtesting smoother and more realistic for your personal schedule.
Pine Script® indicator
by AightBett
Lynie's V9 SELL🟢🔴 Lynie’s V8 — BUY & SELL (Mirrored, Interlocking System) Lynie’s V8 is a paired long/short engine built as two mirrored scripts—Lynie’s V8 BUY and Lynie’s V8 SELL—that read price the same way, flip conditions symmetrically, and manage trades with the exact logic on opposite sides. Use either one standalone or run both together for full two-sided automation of entries, re-entries, caution states, and adaptive SL/TP. ✳️ What “mirrored” means here Supertrend Tri-Stack (10/11/12): BUY: ST10 primary pierce; ST12 fallback; “PAG Buy” when price pierces any ST while above the other two. SELL: Exact inverse—ST10 primary pierce down; ST12 fallback; “PAG Sell” when price pierces any ST while below the other two. Re-Enter Clusters: BUY: Ratcheted up (Heikin-Ashi green holds/tightens). SELL: Ratcheted down (Heikin-Ashi red holds/tightens). Both sides use the same cluster age/decay math, care penalties, session awareness, and fast-candle tightening. Care Flags (context risk): Ichimoku, MACD, RSI combine into single and paired flags that tighten or widen offsets on both sides with the same scoring. VWAP–EMA50 (5m) cluster gate: Identical distance checks for BUY/SELL. When the mean cluster is present, offsets and labels adapt (tighter/“riskier scalp” messaging). Golden Pocket A/B/C (prev-day): Same fib boxes & labeling (gold tone) on both sides to call out TP-friendly zones. SL/TP Envelope: Shared dynamic engine: per-bar decay, fast-candle expansion, and care-based compress/relax—all mirrored for up/down. Caution Labels: BUY side prints CAUTION SELL if HA flips red inside an active long cluster. SELL side prints CAUTION BUY if HA flips green inside an active short cluster. Same latching & auto-release behavior. 🧠 Core workflow (both sides) Primary trigger via ST10 pierce (structure shift) with an ST12 fallback when ST10 didn’t qualify. PAG Mode when price is already on the right side of the other two STs—strongest conviction. Cluster phase begins after a signal: ratcheted re-entry level, session-aware offsets, dynamic tightening on fast bars. Care system shapes every re-entry & SL/TP label (Ichi/MACD/RSI combos + VWAP/EMA gate + QQE). Protective layer: SL-wick and SL-body logic, caution flips, and “hold 1 bar” cluster carry after SL to avoid whipsaw spam. 🔎 Labels & messages (shared vocabulary) Lynie’s / Lynie’s+ / Lynie’s++ — strength tiers (ST12 involvement & clean context). Re-Enter / Excellent Re-Enter — cluster pullback quality; ratchet shows the “must-hold” zone. SL&TP (n) — live offset multiplier the engine is using right now. CAUTION BUY / CAUTION SELL — HA flip against the active side inside the cluster. Restart Next Candle — visual cue to re-arm after a confirmed signal bar. ⚡ Why run both together Continuity: When a long cycle ends (SL or caution degradation), the SELL engine is already tracking the inverse without re-tuning. Symmetry: Same math, same signals, opposite direction—no hidden biases. Coverage: Trend hand-offs are cleaner; you don’t miss early shorts after a long fade (and vice versa). 🔧 Recommended usage Intraday futures (ES/NQ) or any liquid market. Keep the VWAP–EMA cluster ON; it filters FOMO chases. Honor Caution flips inside cluster—scale down or wait for the next clean re-enter. Treat Golden Zones as TP magnets, not guaranteed reversals. 📌 Notes Both scripts are Pine v6 and independent. Load BUY and SELL together for the full experience. All offsets (re-enter & SL/TP) are visible in labels—so you always know why a zone is where it is. Alerts are provided for signals, re-enter hits, caution, and SL events on both sides. Summary: Lynie’s V8 BUY & SELL are vice-versa twins—one framework, two directions—delivering consistent entries, adaptive re-entries, and contextual risk management whether the market is pressing up or breaking down.
Pine Script® indicator
by CoderPAG
Scissors&Knifes V3.1✂️ The Scissors (PAG Chop V4 Engine) 🧠 Core idea Scissors measure market compression and breakout readiness. They use a modified Choppiness Index that looks at the relationship between: True Range volatility (ATR × period length) The total high–low range over the same window. The smaller the ratio (sum of TR vs range), the more directional and impulsive the market is. The higher the ratio, the more “sideways” the market trades. This version smooths the result over PAG_SMOOTHLEN bars and applies several color bands that correspond to volatility states. 🎨 Color code meaning Range State Color Interpretation ≤ 30 Strong Red #8B0000 Momentum exhaustion on downside, sellers dominating — about to reverse or already strong down-trend. 30 – 38 Brick Red #A52A2A Fading downside pressure; often the “bleeding edge” of a bearish climax. 38 – 55 Transparent black (α≈100) Neutral chop zone — indecision, range-building. 55 – 61.8 Yellow (optional) #DAA520 Early compression pocket where volatility starts contracting; the calm before a trend. 61.8 – 70 Bright Green #556B2F Energy release phase: volatility breaking out upward. ≥ 70 Strong Green #355E3B Sustained bullish drive, often continuation leg of a trend. 🪶 Secret nuance: The transition bands (38–45 and 45–55) are treated as fully transparent to mark “dead zones.” When PAG Chop sits here, all label activity pauses — the system resets its cluster memory so the next colored print begins a new “cluster”, letting you clearly see where fresh directional momentum starts. 🧩 Cluster logic Every time a colored (non-transparent) reading appears, it belongs to a “color cluster.” Grey labels (= count 1) mark the genesis of a new cluster, and following counts 2, 3, 4 … represent the internal continuity of that trend state. You can optionally hide the first N grey or count 2 labels to reduce clutter on the initial stabilization bars. ✂️ Label meaning Each label shows: Emoji ✂️ Current count (e.g. ✂️ = 3 means 3 timeframes are simultaneously firing) Optional list of the timeframes that contribute. So a high count (e.g. 8–10) means many lower TFs are synchronizing volatility breakout — a multiframe alignment, often just before an acceleration burst. 🔪 The Knife (Mr Blonde V4 Engine) 🧠 Core idea Mr Blonde converts the slope of a long EMA into an angle-of-attack metric — literally the “tilt” of market momentum. It computes the EMA gradient relative to price span and rescales it into degrees (-5 ° to +5 °). The steeper the angle, the stronger the directional push. 🎨 Color code meaning Angle range Color Interpretation ≥ +5 ° Transparent (Black 1) Fully over-extended up move — wait for reset. +3.57 – +5 ° Dark Red Strong upward slope, momentum apex. +2.14 – +3.57 ° Orange Medium upward slope, trend acceleration zone. +0.71 – +2.14 ° Light Orange Mild upward bias, pre-momentum phase. 0 to -0.71 ° Yellow Neutral transition. -0.71 – -2.14 ° Olive Green Soft bearish slope. -2.14 – -3.57 ° Olive Drab Building bearish momentum. -3.57 – -5 ° Hunter Green Strong downward angle, aggressive push. ≤ -5 ° Transparent (Black 2) Oversold/over-tilted — likely exhaustion. 🪶 Secret nuance: Mr Blonde uses a “span normalization” factor that divides EMA slope by the dynamic range of highs and lows. This lets it compare angles fairly across assets with different volatility profiles (e.g. BTC vs ES) — it’s one of the rare EMA-angle implementations that self-scales properly. 🗡 Label meaning Emoji 🔪 Count = how many TFs share the same momentum angle bias. When many TFs show the same slope polarity (e.g. knife = 8), you’re in a deep momentum cascade — a “knife trend.” 💫 Yellow knife The yellow state marks neutrality or slope flattening. If you enable yellow visibility (mb_show_yellow), you can see where momentum cools off — often the earliest reversal hint. ⚙️ Shared mechanics between ✂️ and 🔪 Multi-timeframe sweep The script cycles through 1 m → 10 m by default, running both engines once per TF. Each returning true adds +1 to the count. So: sc_hits = count of timeframes where PAG fires + 1 knife_hits = count of timeframes where MB fires + 1 That “+1 shift” means there’s always at least 1, letting count = 1 represent the local TF itself. Cluster limiter If Limit max labels per cluster is on, you cap how many total symbols (both ✂️ & 🔪, including trails) can appear within one color phase — avoiding chart spam during extended trends. Trails Each printed label seeds a short-lived “trail” sequence — faded copies extending N bars forward. Trails visualize the linger effect of the last signal, useful for visually connecting bursts in momentum. Grey or count = 1 labels can have shorter or longer trails depending on your overrides (*_trail_bars_grey). They’re purely visual and do not affect alerting. Alerts Alerts fire independently of whether you hide labels — unless you enable “respect filters”. This guarantees you never miss a structural signal even if you suppress visuals for clarity. 🌈 Interpreting Both Together Scenario Interpretation ✂️ = low (1–2) + 🔪 rising (red/orange) Market just leaving chop, early thrust stage. ✂️ = high (≥ 5) + 🔪 green Fully aligned breakout continuation — trend in progress. ✂️ = yellow cluster + 🔪 yellow Volatility squeeze, energy buildup — next expansion near. ✂️ = green cluster → 🔪 turns red Cross-state conflict; likely transition or correction. ✂️ = grey + 🔪 grey Reset condition — both engines cooling; stand aside. 💡 Hidden edge: Scissors signal potential, Knife measures kinetic force. The perfect storm is when ✂️ goes from yellow→green one bar before 🔪 shifts from orange→green — it catches the birth of directional flow while volatility is still tight. 🧭 Reading the labels intuitively Grey ✂️/🔪 = 1 → embryonic state, may fizzle or bloom. ✂️/🔪 = 2 or 3 → expansion taking hold. ✂️/🔪 ≥ 4 (mid black) → strong synchronized drive across TFs. Transparent gap → cluster reset; prepare for new phase. Trail lines → echo of previous cluster strength. Final secret tip 🗝 Because both engines are mathematically uncorrelated (volatility vs EMA angle), when they agree in color polarity on multiple TFs, you have one of the cleanest probabilistic trend windows possible. If you ever see ✂️ = 6 + 🔪 = 6 both pointing the same way — that’s a “knife-through-the-scissors” moment: volatility expansion and directional slope synchronized — those are the bars where institutional algorithms tend to add size.
Pine Script® indicator
by CoderPAG
Zarattini Intra-day Threshold Bands (ZITB)This indicator implements the intraday threshold band methodology described in the research paper by Carlo Zarattini et al. Overview: Plots intraday threshold bands based on daily open/close levels. Supports visualization of BaseUp/BaseDown levels and Threshold Upper/Lower bands. Optional shading between threshold bands for easier interpretation. Usage Notes / Limitations: Originally studied on SPY (US equities), this implementation is adapted for NSE intraday market timing, specifically the NIFTY50 index. Internally, 2-minute candles are used if the chart timeframe is less than 2 minutes. Values may be inaccurate if the chart timeframe is more than 1 day. Lookback days are auto-capped to avoid exceeding TradingView’s 5000-bar limit. The indicator automatically aligns intraday bars across multiple days to compute average deltas. For better returns, it is recommended to use this indicator in conjunction with VWAP and a volatility-based position sizing mechanism. Can be used as a reference for Open Range Breakout (ORB) strategies. Customizations: Toggle plotting of base levels and thresholds. Toggle shading between thresholds. Line colors and styles can be adjusted in the Style tab. Intended for educational and research purposes only. This indicator implements the approach described in the research paper by Zarattini et al. Note: This implementation is designed for the NSE NIFTY50 index. While Zarattini’s original study was conducted on SPY, this version adapts the methodology for the Indian market. Methodology Explanation This indicator is primarily designed for Open Range Breakout (ORB) strategies. Base Levels BaseUp = Maximum of today’s open and previous day’s close BaseDown = Minimum of today’s open and previous day’s close Delta Calculation For the past 14 trading days (lookbackDays), the delta for each intraday candle is calculated as the ab solute difference from the close of the first candle of that day. Average Delta For a given intraday time/candle today, deltaAvg is computed as the average of the deltas at the same time across the previous 14 days. Threshold Bands ThresholdUp = BaseUp + deltaAvg ThresholdDown = BaseDown − deltaAvg Signals Spot price moving above ThresholdUp → Long signal Spot price moving below ThresholdDown → Short signal Tip: For better returns, combine this indicator with VWAP and a volatility-based position sizing mechanism.
Pine Script® indicator
by gokul4trading
cd_correlation_analys_Cxcd_correlation_analys_Cx General: This indicator is designed for correlation analysis by classifying stocks (487 in total) and indices (14 in total) traded on Borsa İstanbul (BIST) on a sectoral basis. Tradingview's sector classifications (20) have been strictly adhered to for sector grouping. Depending on user preference, the analysis can be performed within sectors, between sectors, or manually (single asset). Let me express my gratitude to the code author, @fikira, beforehand; you will find the reason for my thanks in the context. Details: First, let's briefly mention how this indicator could have been prepared using the classic method before going into details. Classically, assets could be divided into groups of forty (40), and the analysis could be performed using the built-in function: ta.correlation(source1, source2, length) → series float. I chose sectoral classification because I believe there would be a higher probability of assets moving together, rather than using fixed-number classes. In this case, 21 arrays were formed with the following number of elements: (3, 11, 21, 60, 29, 20, 12, 3, 31, 5, 10, 11, 6, 48, 73, 62, 16, 19, 13, 34 and indices (14)). However, you might have noticed that some arrays have more than 40 elements. This is exactly where @Fikira's indicator came to the rescue. When I examined their excellent indicator, I saw that it could process 120 assets in a single operation. (I believe this was the first limit overrun; thanks again.) It was amazing to see that data for 3 pairs could be called in a single request using a special method. You can find the details here: When I adapted it for BIST, I found it sufficient to call data for 2 pairs instead of 3 in a single go. Since asset prices are regular and have 2 decimal places, I used a fixed multiplier of $10^8$ and a fixed decimal count of 2 in Fikira's formulas. With this method, the (high, low, open, close) values became accessible for each asset. The summary up to this point is that instead of the ready-made formula + groups of 40, I used variable-sized groups and the method I will detail now. Correlation/harmony/co-movement between assets provides advantages to market participants. Coherent assets are expected to rise or fall simultaneously. Therefore, to convert co-movement into a mathematical value, I defined the possible movements of the current candle relative to the previous candle bar over a certain period (user-defined). These are: Up := high > high and low > low Down := high < high and low < low Inside := high <= high and low >= low Outside := high >= high and low <= low and NOT Inside. Ignore := high = low = open = close If both assets performed the same movement, 1 was added to the tracking counter. If (Up-Up), (Down-Down), (Inside-Inside), or (Outside-Outside), then counter := counter + 1. If the period length is 100 and the counter is 75, it means there is 75% co-movement. Corr = counter / period ($75/100$) Average = ta.sma(Corr, 100) is obtained. The highest coefficients recorded in the array are presented to the user in a table. From the user menu options, the user can choose to compare: • With assets in its own sector • With assets in the selected sector • By activating the confirmation box and manually entering a single asset for comparison. Table display options can be adjusted from the Settings tab. In the attached examples: Results for AKBNK stock from the Finance sector compared with GARAN stock from the same sector: Timeframe: Daily, Period: 50 => Harmony 76% (They performed the same movement in 38 out of 50 bars) Comment: Opposite movements at swing high and low levels may indicate a change in the direction of the price flow (SMT). Looking at ASELS from the Electronic Technology sector over the last 30 daily candles, they performed the same movements by 40% with XU100, 73.3% (22/30) with XUTEK (Technology Index), and 86.9% according to the averages. Comment: It is more appropriate to follow ASELS stock with XUTEK (Technology index) instead of the general index (XU100). Opposite movements at swing high and low levels may indicate a change in the direction of the price flow (SMT). Again, when ASELS stock is taken on H1 instead of daily, and the length is 100 instead of 30, the harmony rate is seen to be 87%. Please share your thoughts and criticisms regarding the indicator, which I prepared with a bit of an educational purpose specifically for BIST. Happy trading.
Pine Script® indicator
by cdikici71
2
Zarks 4H Range, 15M Triggers Pt1HTF Dividers + 4H Candle Structure + CRT Reference Tool 🔹 Vertical Blue Lines → represent divisions of the 4-hour timeframe, helping you visually segment intraday structure into HTF blocks. Green Dotted Line → marks the High of each 4-hour interval. 🔵 Blue Dotted Line → shows the Open of that 4-hour interval. ⚫ Gray Dotted Line → displays the Close of that 4-hour interval. 🔴 Red Dotted Line → highlights the Low of that 4-hour interval. 💡 CRT Concepts (Candle Range Theory by Romeo TPT) CRT signals are not direct buy/sell signals ❌💰 — they serve as contextual reference points 🧭. A high-probability setup often appears when: A 4H sweep of a previous candle’s high occurs 🐢 (liquidity manipulation), Followed by a bearish 15-minute close, Targeting the 50% retracement of that 4H candle’s range 🎯. 📊 Use this tool to frame market structure across timeframes, align entries with liquidity events, and visualize when price may be expanding from or reverting to institutional reference points. This indicator is meant to be combined with vertical lines on the 15 min time frame at corresponding times example 1:45,4:45,9:45
Pine Script® indicator
by Alexubc323
Risk Leverage ToolRisk Leverage Tool – Calculate Position Size and Required Leverage This script automatically calculates the optimal position size and the leverage needed based on the amount of capital you are willing to risk on a trade. It is designed for traders who want precise control over their risk management. The script determines the distance between the entry and stop-loss price, calculates the maximum position size that fits within the defined risk, and derives the notional value of the trade. Based on the available margin, it then calculates the required leverage. It also displays the percentage of margin at risk if the stop-loss is hit. All results are displayed in a table in the top-right corner of the chart. Additionally, a label appears at the entry price level showing the same data. To use the tool, simply input your planned entry price, stop-loss price, the maximum risk amount in dollars, and the available margin in the settings menu. The script will update all values automatically in real time. This tool works with any market where capital risk is expressed in absolute terms (such as USD), including futures, CFDs, and leveraged spot positions. For inverse contracts or percentage-based stops, manual adjustment is required.
Pine Script® indicator
by JoelEren
HTF Session Boxes H4 > H2 > H1HTF Session Boxes H4 > H2 > H1 Visualize higher timeframe candle structures on lower timeframe charts with nested, customizable boxes. Overview HTF Session Boxes plots 4-hour, 2-hour, and 1-hour candle ranges as nested boxes directly on your lower timeframe charts (15M and below). This provides instant visual context of higher timeframe structure without switching between different chart timeframes. Key Features - Three Timeframe Levels: Simultaneously displays 4H, 2H, and 1H candle boxes - Nested Design: Boxes are layered inside each other for clear hierarchical structure - Real-Time Updates: Boxes dynamically adjust as higher timeframe candles develop Fully Customizable: -Individual colors and transparency for each timeframe -Custom border colors, widths, and styles (solid, dashed, dotted) -Toggle each timeframe on/off independently Best Use Cases -Scalping & Day Trading: Maintain awareness of higher timeframe structure while trading lower timeframes -Session Analysis: Clearly see 4H session boundaries and internal 2H/1H divisions -Support/Resistance: Identify key levels where higher timeframe candles open, close, or create highs/lows -Multi-Timeframe Confluence: Spot when multiple timeframes align at key price levels
Pine Script® indicator
by sdahaghi
FX Realized Volatility *The downward signal for Euqities!?*The Russel 2000 put in a new ath today as capital is moving further out the risk curve. Risk-Assets continue to rally to the upside. This will last until we see a lasting driver happening on a real time basis that drag pull equties down When volatility rises, we need to see the DRIVER of the volatility have persistence behind it as opposed to one off shocks. We are not there yet as volatility in FX and bonds continues to compress since the April lows in equities. Equities will continue to rally until long end yields blow out or the carry trade unwinds. Long end yields blowing out is not occuring on an imminent basis but the FX side of things could be a significant risk soon. Its all about: When will that liquidity beginn to create inflation or a problem in the currency Monitoring the equity vol, Bond vol and FX volatiliy is crucial here You can watch them via: VIX, Move, + i build an Trading view modell which conducts the vol of the major FX pairs. (its 100% free) If you just want it simple, just look at USD & EUR vol as they are the most trades foreign exchange currencies. Watching these 2 Risks (Vol & long-end) will put you upfront most people in the market. Once we see information in the underlying economy shifting i will adjust my views as they relate to every major asset class. But for now we are likely moving higher in basically every risky asset. **Feel free to ask me any questions**
Pine Script® indicator
by The-white-goat
Liquidity Grab + RSI Divergence═══════════════════════════════════════════════════════════════ LIQUIDITY GRAB + RSI DIVERGENCE INDICATOR ═══════════════════════════════════════════════════════════════ 📌 OVERVIEW This indicator identifies high-probability reversals by combining: • Liquidity sweeps (stop hunts) • RSI divergence confirmation • Filters false breakouts automatically ═══════════════════════════════════════════════════════════════ 🟢 BUY SIGNAL (Green Triangle Up) REQUIRES BOTH CONDITIONS: 1. Liquidity Grab Below Previous Low • Price breaks BELOW recent low • Candle CLOSES ABOVE that low • Traps sellers who shorted the breakdown 2. Bullish RSI Divergence • Price: Lower Low (LL) • RSI: Higher Low (HL) • Shows weakening downward momentum ➜ Result: Potential bullish reversal ═══════════════════════════════════════════════════════════════ 🔴 SELL SIGNAL (Red Triangle Down) REQUIRES BOTH CONDITIONS: 1. Liquidity Grab Above Previous High • Price breaks ABOVE recent high • Candle CLOSES BELOW that high • Traps buyers who bought the breakout 2. Bearish RSI Divergence • Price: Higher High (HH) • RSI: Lower High (LH) • Shows weakening upward momentum ➜ Result: Potential bearish reversal ═══════════════════════════════════════════════════════════════ 📊 VISUAL INDICATORS Main Signals: 🔺 Large Green Triangle = BUY (Liq Grab + Bullish Div) 🔻 Large Red Triangle = SELL (Liq Grab + Bearish Div) Reference Levels: ━ Red Line = Previous High Level ━ Green Line = Previous Low Level Additional Markers (Optional): ○ Small Green Circle = Liquidity grab low only ○ Small Red Circle = Liquidity grab high only ✕ Small Blue Cross = Bullish divergence only ✕ Small Orange Cross = Bearish divergence only ═══════════════════════════════════════════════════════════════ ⚙️ SETTINGS 1. Lookback Period (Default: 20) • Range: 5-100 • Sets how far back to identify previous highs/lows • Higher = fewer but stronger levels • Lower = more frequent but weaker levels 2. RSI Length (Default: 14) • Range: 5-50 • Standard RSI calculation period • 14 is industry standard 3. RSI Divergence Lookback (Default: 5) • Range: 3-20 • Controls pivot point sensitivity • Higher = fewer divergence signals • Lower = more divergence signals 4. Show Labels (Default: ON) • Toggle BUY/SELL text labels • Disable for cleaner chart view ═══════════════════════════════════════════════════════════════ 💡 HOW TO USE Step 1: WAIT FOR CONFIRMATION • Only trade LARGE TRIANGLE signals • Ignore small circles/crosses alone Step 2: CHECK TIMEFRAME • Best on: 15min, 1H, 4H, Daily • Avoid: 1min, 5min (too noisy) Step 3: CONFIRM CONTEXT • Check overall market trend • Identify key support/resistance • Look for confluence with price action Step 4: ENTRY & RISK MANAGEMENT • Enter on signal candle close or pullback • Stop loss below/above the liquidity grab wick • Target: Previous swing high/low or key levels • Risk/Reward: Minimum 1:2 ratio Step 5: SET ALERTS • Create alert for "BUY Signal" • Create alert for "SELL Signal" • Never miss opportunities ═══════════════════════════════════════════════════════════════ ✅ BEST PRACTICES DO: ✓ Use on multiple timeframes for confluence ✓ Combine with support/resistance zones ✓ Wait for both conditions (liq grab + divergence) ✓ Practice on demo account first ✓ Use proper position sizing DON'T: ✗ Trade every small circle/cross ✗ Use on very low timeframes (<15min) ✗ Ignore overall market context ✗ Trade without stop loss ✗ Risk more than 1-2% per trade ═══════════════════════════════════════════════════════════════ ⚠️ IMPORTANT NOTES • This is a CONFIRMATION tool, not a holy grail • No indicator is 100% accurate • Combine with your trading strategy • Backtest on your preferred instruments • Adjust parameters for your trading style • Higher timeframes = more reliable signals • Always use risk management ═══════════════════════════════════════════════════════════════ 🔔 ALERTS INCLUDED Two alert conditions are built-in: 1. "BUY Signal" - Liquidity Grab + Bullish RSI Divergence 2. "SELL Signal" - Liquidity Grab + Bearish RSI Divergence ═══════════════════════════════════════════════════════════════ 📈 RECOMMENDED SETTINGS BY TIMEFRAME 5-15 Min Charts: • Lookback: 10-15 • RSI Length: 14 • RSI Div Lookback: 3-5 1H-4H Charts: • Lookback: 20-30 • RSI Length: 14 • RSI Div Lookback: 5-7 Daily Charts: • Lookback: 30-50 • RSI Length: 14 • RSI Div Lookback: 7-10 ═══════════════════════════════════════════════════════════════ Good luck and trade safe! 🚀
Pine Script® indicator
by hassanejaz1
FCBI Brake PressureBrake Pressure (FCBI − USIRYY) Concept The Brake Pressure indicator quantifies whether the bond market is braking or releasing liquidity relative to real yields (USIRYY). It is derived from the Financial-Conditions Brake Index (FCBI) and expresses the balance between long-term yield pressure and real-rate dynamics. Formula Brake Pressure = FCBI − USIRYY where FCBI = (US10Y) − (USINTR) − (CPI YoY) Purpose While FCBI measures the intensity of financial-condition pressure, Brake Pressure shows when that brake is being applied or released. It captures the turning point of liquidity transmission in the financial system. How to Read Brake Pressure < 0 (orange) → Brake engaged → financial conditions tighter than real-rate baseline; liquidity constrained. Brake Pressure ≈ 0 → Neutral zone → transition phase between tightening and easing. Brake Pressure > 0 (teal) → Brake released → financial conditions looser than real-rate baseline; liquidity flows freely → late-cycle setup before recession. Zero-Cross Logic Cross ↑ above 0 → FCBI > USIRYY → brake released → liquidity acceleration → typically 6–18 months before recession. Cross ↓ below 0 → FCBI < USIRYY → brake re-engaged → tightening resumes. Historical Behavior Each major U.S. recession (2001, 2008, 2020) was preceded by a Brake Pressure cross above zero after a negative phase, signaling that long yields had stopped resisting Fed cuts and liquidity was expanding. Practical Use • Identify late-cycle turning points and liquidity inflection phases. • Combine with FCBI for a complete macro transmission picture. • Watch for sustained positive readings as early macro-recession warnings. Current Example (Oct 2025) FCBI ≈ −3.1, USIRYY ≈ +3.0 → Brake Pressure ≈ −6.1 → Brake still engaged. When this crosses above 0, it signals that liquidity is free flowing and the recession countdown has begun. Summary FCBI shows how tight the brake is. Brake Pressure shows when the brake releases. When Brake Pressure > 0, the system has entered the liquidity-expansion phase that historically precedes a U.S. recession.
Pine Script® indicator
by AMTrader
Financial-Conditions Brake Index (FCBI) — US10Y brake on USIRYYFinancial-Conditions Brake Index (FCBI) – US10Y Brake on USIRYY Concept The Financial-Conditions Brake Index (FCBI) measures how U.S. long-term yields (US10Y) interact with the Federal Funds Rate (USINTR) and inflation (CPI YoY) to shape real-rate conditions (USIRYY). It visualizes whether the bond market is tightening or loosening overall financial conditions relative to the Federal Reserve’s policy stance. Formula FCBI = (US10Y) − (USINTR) − (CPI YoY) How It Works The FCBI expresses the difference between the long-term yield curve and short-term policy rates, adjusted for inflation. It shows whether the long end of the curve is amplifying or counteracting the Fed’s stance. FCBI > +2 → Strong brake → Long yields remain elevated despite easing → tight conditions → recession delayed. FCBI +1 to +2 → Mild brake → Financial transmission slower; lag ≈ 12–18 months. FCBI 0 to +1 → Neutral → Typical early post-cut environment. FCBI < 0 → Accelerator → Long yields and inflation expectations falling → liquidity flows freely → recession often follows within 6–14 months. How to Read the Chart Blue line (FCBI) shows the strength of the financial brake. Red line (USIRYY) represents the real yield baseline. Recession shading (gray) marks NBER recessions for comparison. FCBI < USIRYY → Brake engaged → financial conditions tighter than real-rate baseline. FCBI > USIRYY → Brake released → long end easing faster than policy → liquidity surge → late-cycle setup. Historically, U.S. recessions begin on average about 14 months after the first Fed rate cut, and a decline of the FCBI below zero often precedes that window. Practical Use Use the FCBI to identify when policy transmission is blocked (brake engaged) or flowing (brake released). Cross-check with yield-curve inversions, Fed policy shifts, and inflation expectations to estimate macro timing windows. Current Example (Oct 2025) FCBI ≈ −3.1, USIRYY ≈ +3.0 → Brake still engaged. Once FCBI rises above USIRYY and crosses positive, it signals the “brake released” phase — historically the final liquidity surge before a U.S. recession. Summary FCBI shows how tight the brake is. USIRYY shows how fast the car is moving. When FCBI rises above USIRYY, the brake is released — liquidity accelerates and the historical recession countdown begins.
Pine Script® indicator
by AMTrader
RBLR - GSK Vizag AP IndiaThis indicator identifies the Opening Range High (ORH) and Low (ORL) based on the first 15 minutes of the Indian equity market session (9:15 AM to 9:30 AM IST). It draws horizontal lines extending these levels until market close (3:30 PM IST) and generates visual signals for price breakouts above ORH or below ORL, as well as reversals back into the range. Key features: - **Range Calculation**: Captures the high and low during the opening period using real-time bar data. - **Line Extension**: Lines are dynamically extended bar-by-bar within the session for clear visualization. - **Signals**: - Green triangle up: Crossover above ORH (potential bullish breakout). - Red triangle down: Crossunder below ORL (potential bearish breakout). - Yellow labels: Reversals from breakout levels back into the range. - **Labels**: "RAM BAAN" marks the ORH (inspired by a precise arrow from the Ramayana), and "LAKSHMAN REKHA" marks the ORL (inspired by a protective boundary line from the same epic). - **Customization**: Toggle signals on/off and select line styles (Dotted, Dashed, Solid, or Smoothed, with transparency for Smoothed). The state-tracking logic prevents redundant signals by monitoring if price remains outside the range after a breakout. This helps users observe range-bound behavior or directional moves without built-in alerts. This indicator is particularly useful for day trading on longer intraday timeframes (e.g., 15-minute charts) to identify session-wide trends and avoid noise in shorter frames. For best results, apply on intraday timeframes on NSE/BSE symbols. Note that lines and labels are limited to the script's max counts to avoid performance issues on long histories. **Disclaimer**: This indicator is for educational and informational purposes only and does not constitute financial, investment, or trading advice. Trading in financial markets involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Users should conduct their own research, consider their financial situation, and consult with qualified professionals before making any investment decisions. The author and TradingView assume no liability for any losses incurred from its use.
Pine Script® indicator
by prowelltraders
J.P. Morgan Efficiente 5 IndexJ.P. MORGAN EFFICIENTE 5 INDEX REPLICATION Walk into any retail trading forum and you'll find the same scene playing out thousands of times a day: traders huddled over their screens, drawing trendlines on candlestick charts, hunting for the perfect entry signal, convinced that the next RSI crossover will unlock the path to financial freedom. Meanwhile, in the towers of lower Manhattan and the City of London, portfolio managers are doing something entirely different. They're not drawing lines. They're not hunting patterns. They're building fortresses of diversification, wielding mathematical frameworks that have survived decades of market chaos, and most importantly, they're thinking in portfolios while retail thinks in positions. This divide is not just philosophical. It's structural, mathematical, and ultimately, profitable. The uncomfortable truth that retail traders must confront is this: while you're obsessing over whether the 50-day moving average will cross the 200-day, institutional investors are solving quadratic optimization problems across thirteen asset classes, rebalancing monthly according to Markowitz's Nobel Prize-winning framework, and targeting precise volatility levels that allow them to sleep at night regardless of what the VIX does tomorrow. The game you're playing and the game they're playing share the same field, but the rules are entirely different. The question, then, is not whether retail traders can access institutional strategies. The question is whether they're willing to fundamentally change how they think about markets. Are you ready to stop painting lines and start building portfolios? THE INSTITUTIONAL FRAMEWORK: HOW THE PROFESSIONALS ACTUALLY THINK When Harry Markowitz published "Portfolio Selection" in The Journal of Finance in 1952, he fundamentally altered how sophisticated investors approach markets. His insight was deceptively simple: returns alone mean nothing. Risk-adjusted returns mean everything. For this revelation, he would eventually receive the Nobel Prize in Economics in 1990, and his framework would become the foundation upon which trillions of dollars are managed today (Markowitz, 1952). Modern Portfolio Theory, as it came to be known, introduced a revolutionary concept: through diversification across imperfectly correlated assets, an investor could reduce portfolio risk without sacrificing expected returns. This wasn't about finding the single best asset. It was about constructing the optimal combination of assets. The mathematics are elegant in their logic: if two assets don't move in perfect lockstep, combining them creates a portfolio whose volatility is lower than the weighted average of the individual volatilities. This "free lunch" of diversification became the bedrock of institutional investment management (Elton et al., 2014). But here's where retail traders miss the point entirely: this isn't about having ten different stocks instead of one. It's about systematic, mathematically rigorous allocation across asset classes with fundamentally different risk drivers. When equity markets crash, high-quality government bonds often rally. When inflation surges, commodities may provide protection even as stocks and bonds both suffer. When emerging markets are in vogue, developed markets may lag. The professional investor doesn't predict which scenario will unfold. Instead, they position for all of them simultaneously, with weights determined not by gut feeling but by quantitative optimization. This is what J.P. Morgan Asset Management embedded into their Efficiente Index series. These are not actively managed funds where a portfolio manager makes discretionary calls. They are rules-based, systematic strategies that execute the Markowitz framework in real-time, rebalancing monthly to maintain optimal risk-adjusted positioning across global equities, fixed income, commodities, and defensive assets (J.P. Morgan Asset Management, 2016). THE EFFICIENTE 5 STRATEGY: DECONSTRUCTING INSTITUTIONAL METHODOLOGY The Efficiente 5 Index, specifically, targets a 5% annualized volatility. Let that sink in for a moment. While retail traders routinely accept 20%, 30%, or even 50% annual volatility in pursuit of returns, institutional allocators have determined that 5% volatility provides an optimal balance between growth potential and capital preservation. This isn't timidity. It's mathematics. At higher volatility levels, the compounding drag from large drawdowns becomes mathematically punishing. A 50% loss requires a 100% gain just to break even. The institutional solution: constrain volatility at the portfolio level, allowing the power of compounding to work unimpeded (Damodaran, 2008). The strategy operates across thirteen exchange-traded funds spanning five distinct asset classes: developed equity markets (SPY, IWM, EFA), fixed income across the risk spectrum (TLT, LQD, HYG), emerging markets (EEM, EMB), alternatives (IYR, GSG, GLD), and defensive positioning (TIP, BIL). These aren't arbitrary choices. Each ETF represents a distinct factor exposure, and together they provide access to the primary drivers of global asset returns (Fama and French, 1993). The methodology, as detailed in replication research by Jungle Rock (2025), follows a precise monthly cadence. At the end of each month, the strategy recalculates expected returns and volatilities for all thirteen assets using a 126-day rolling window. This six-month lookback balances responsiveness to changing market conditions against the noise of short-term fluctuations. The optimization engine then solves for the portfolio weights that maximize expected return subject to the 5% volatility target, with additional constraints to prevent excessive concentration. These constraints are critical and reveal institutional wisdom that retail traders typically ignore. No single ETF can exceed 20% of the portfolio, except for TIP and BIL which can reach 50% given their defensive nature. At the asset class level, developed equities are capped at 50%, bonds at 50%, emerging markets at 25%, and alternatives at 25%. These aren't arbitrary limits. They're guardrails preventing the optimization from becoming too aggressive during periods when recent performance might suggest concentrating heavily in a single area that's been hot (Jorion, 1992). After optimization, there's one final step that appears almost trivial but carries profound implications: weights are rounded to the nearest 5%. In a world of fractional shares and algorithmic execution, why round to 5%? The answer reveals institutional practicality over mathematical purity. A portfolio weight of 13.7% and 15.0% are functionally similar in their risk contribution, but the latter is vastly easier to communicate, to monitor, and to execute at scale. When you're managing billions, parsimony matters. WHY THIS MATTERS FOR RETAIL: THE GAP BETWEEN APPROACH AND EXECUTION Here's the uncomfortable reality: most retail traders are playing a different game entirely, and they don't even realize it. When a retail trader says "I'm bullish on tech," they buy QQQ and that's their entire technology exposure. When they say "I need some diversification," they buy ten different stocks, often in correlated sectors. This isn't diversification in the Markowitzian sense. It's concentration with extra steps. The institutional approach represented by the Efficiente 5 is fundamentally different in several ways. First, it's systematic. Emotions don't drive the allocation. The mathematics do. When equities have rallied hard and now represent 55% of the portfolio despite a 50% cap, the system sells equities and buys bonds or alternatives, regardless of how bullish the headlines feel. This forced contrarianism is what retail traders know they should do but rarely execute (Kahneman and Tversky, 1979). Second, it's forward-looking in its inputs but backward-looking in its process. The strategy doesn't try to predict the next crisis or the next boom. It simply measures what volatility and returns have been recently, assumes the immediate future resembles the immediate past more than it resembles some forecast, and positions accordingly. This humility regarding prediction is perhaps the most institutional characteristic of all. Third, and most critically, it treats the portfolio as a single organism. Retail traders typically view their holdings as separate positions, each requiring individual management. The institutional approach recognizes that what matters is not whether Position A made money, but whether the portfolio as a whole achieved its risk-adjusted return target. A position can lose money and still be a valuable contributor if it reduced portfolio volatility or provided diversification during stress periods. THE MATHEMATICAL FOUNDATION: MEAN-VARIANCE OPTIMIZATION IN PRACTICE At its core, the Efficiente 5 strategy solves a constrained optimization problem each month. In technical terms, this is a quadratic programming problem: maximize expected portfolio return subject to a volatility constraint and position limits. The objective function is straightforward: maximize the weighted sum of expected returns. The constraint is that the weighted sum of variances and covariances must not exceed the volatility target squared (Markowitz, 1959). The challenge, and this is crucial for understanding the Pine Script implementation, is that solving this problem properly requires calculating a covariance matrix. This 13x13 matrix captures not just the volatility of each asset but the correlation between every pair of assets. Two assets might each have 15% volatility, but if they're negatively correlated, combining them reduces portfolio risk. If they're positively correlated, it doesn't. The covariance matrix encodes these relationships. True mean-variance optimization requires matrix algebra and quadratic programming solvers. Pine Script, by design, lacks these capabilities. The language doesn't support matrix operations, and certainly doesn't include a QP solver. This creates a fundamental challenge: how do you implement an institutional strategy in a language not designed for institutional mathematics? The solution implemented here uses a pragmatic approximation. Instead of solving the full covariance problem, the indicator calculates a Sharpe-like ratio for each asset (return divided by volatility) and uses these ratios to determine initial weights. It then applies the individual and asset-class constraints, renormalizes, and produces the final portfolio. This isn't mathematically equivalent to true mean-variance optimization, but it captures the essential spirit: weight assets according to their risk-adjusted return potential, subject to diversification constraints. For retail implementation, this approximation is likely sufficient. The difference between a theoretically optimal portfolio and a very good approximation is typically modest, and the discipline of systematic rebalancing across asset classes matters far more than the precise weights. Perfect is the enemy of good, and a good approximation executed consistently will outperform a perfect solution that never gets implemented (Arnott et al., 2013). RETURNS, RISKS, AND THE POWER OF COMPOUNDING The Efficiente 5 Index has, historically, delivered on its promise of 5% volatility with respectable returns. While past performance never guarantees future results, the framework reveals why low-volatility strategies can be surprisingly powerful. Consider two portfolios: Portfolio A averages 12% returns with 20% volatility, while Portfolio B averages 8% returns with 5% volatility. Which performs better over time? The arithmetic return favors Portfolio A, but compound returns tell a different story. Portfolio A will experience occasional 20-30% drawdowns. Portfolio B rarely draws down more than 10%. Over a twenty-year horizon, the geometric return (what you actually experience) for Portfolio B may match or exceed Portfolio A, simply because it never gives back massive gains. This is the power of volatility management that retail traders chronically underestimate (Bernstein, 1996). Moreover, low volatility enables behavioral advantages. When your portfolio draws down 35%, as it might with a high-volatility approach, the psychological pressure to sell at the worst possible time becomes overwhelming. When your maximum drawdown is 12%, as might occur with the Efficiente 5 approach, staying the course is far easier. Behavioral finance research has consistently shown that investor returns lag fund returns primarily due to poor timing decisions driven by emotional responses to volatility (Dalbar, 2020). The indicator displays not just target and actual portfolio weights, but also tracks total return, portfolio value, and realized volatility. This isn't just data. It's feedback. Retail traders can see, in real-time, whether their actual portfolio volatility matches their target, whether their risk-adjusted returns are improving, and whether their allocation discipline is holding. This transparency transforms abstract concepts into concrete metrics. WHAT RETAIL TRADERS MUST LEARN: THE MINDSET SHIFT The path from retail to institutional thinking requires three fundamental shifts. First, stop thinking in positions and start thinking in portfolios. Your question should never be "Should I buy this stock?" but rather "How does this position change my portfolio's expected return and volatility?" If you can't answer that question quantitatively, you're not ready to make the trade. Second, embrace systematic rebalancing even when it feels wrong. Perhaps especially when it feels wrong. The Efficiente 5 strategy rebalances monthly regardless of market conditions. If equities have surged and now exceed their target weight, the strategy sells equities and buys bonds or alternatives. Every retail trader knows this is what you "should" do, but almost none actually do it. The institutional edge isn't in having better information. It's in having better discipline (Swensen, 2009). Third, accept that volatility is not your friend. The retail mythology that "higher risk equals higher returns" is true on average across assets, but it's not true for implementation. A 15% return with 30% volatility will compound more slowly than a 12% return with 10% volatility due to the mathematics of return distributions. Institutions figured this out decades ago. Retail is still learning. The Efficiente 5 replication indicator provides a bridge. It won't solve the problem of prediction no indicator can. But it solves the problem of allocation, which is arguably more important. By implementing institutional methodology in an accessible format, it allows retail traders to see what professional portfolio construction actually looks like, not in theory but in executable code. The the colorful lines that retail traders love to draw, don't disappear. They simply become less central to the process. The portfolio becomes central instead. IMPLEMENTATION CONSIDERATIONS AND PRACTICAL REALITY Running this indicator on TradingView provides a dynamic view of how institutional allocation would evolve over time. The labels on each asset class line show current weights, updated continuously as prices change and rebalancing occurs. The dashboard displays the full allocation across all thirteen ETFs, showing both target weights (what the optimization suggests) and actual weights (what the portfolio currently holds after price movements). Several key insights emerge from watching this process unfold. First, the strategy is not static. Weights change monthly as the optimization recalibrates to recent volatility and returns. What worked last month may not be optimal this month. Second, the strategy is not market-timing. It doesn't try to predict whether stocks will rise or fall. It simply measures recent behavior and positions accordingly. If volatility has risen, the strategy shifts toward defensive assets. If correlations have changed, the diversification benefits adjust. Third, and perhaps most importantly for retail traders, the strategy demonstrates that sophistication and complexity are not synonyms. The Efficiente 5 methodology is sophisticated in its framework but simple in its execution. There are no exotic derivatives, no complex market-timing rules, no predictions of future scenarios. Just systematic optimization, monthly rebalancing, and discipline. This simplicity is a feature, not a bug. The indicator also highlights limitations that retail traders must understand. The Pine Script implementation uses an approximation of true mean-variance optimization, as discussed earlier. Transaction costs are not modeled. Slippage is ignored. Tax implications are not considered. These simplifications mean the indicator is educational and analytical, not a fully operational trading system. For actual implementation, traders would need to account for these real-world factors. Moreover, the strategy requires access to all thirteen ETFs and sufficient capital to hold meaningful positions in each. With 5% as the rounding increment, practical implementation probably requires at least $10,000 to avoid having positions that are too small to matter. The strategy is also explicitly designed for a 5% volatility target, which may be too conservative for younger investors with long time horizons or too aggressive for retirees living off their portfolio. The framework is adaptable, but adaptation requires understanding the trade-offs. CAN RETAIL TRULY COMPETE WITH INSTITUTIONS? The honest answer is nuanced. Retail traders will never have the same resources as institutions. They won't have Bloomberg terminals, proprietary research, or armies of analysts. But in portfolio construction, the resource gap matters less than the mindset gap. The mathematics of Markowitz are available to everyone. ETFs provide liquid, low-cost access to institutional-quality building blocks. Computing power is essentially free. The barriers are not technological or financial. They're conceptual. If a retail trader understands why portfolios matter more than positions, why systematic discipline beats discretionary emotion, and why volatility management enables compounding, they can build portfolios that rival institutional allocation in their elegance and effectiveness. Not in their scale, not in their execution costs, but in their conceptual soundness. The Efficiente 5 framework proves this is possible. What retail traders must recognize is that competing with institutions doesn't mean day-trading better than their algorithms. It means portfolio-building better than their average client. And that's achievable because most institutional clients, despite having access to the best managers, still make emotional decisions, chase performance, and abandon strategies at the worst possible times. The retail edge isn't in outsmarting professionals. It's in out-disciplining amateurs who happen to have more money. The J.P. Morgan Efficiente 5 Index Replication indicator serves as both a tool and a teacher. As a tool, it provides a systematic framework for multi-asset allocation based on proven institutional methodology. As a teacher, it demonstrates daily what portfolio thinking actually looks like in practice. The colorful lines remain on the chart, but they're no longer the focus. The portfolio is the focus. The risk-adjusted return is the focus. The systematic discipline is the focus. Stop painting lines. Start building portfolios. The institutions have been doing it for seventy years. It's time retail caught up. REFERENCES Arnott, R. D., Hsu, J., & Moore, P. (2013). Fundamental Indexation. Financial Analysts Journal, 61(2), 83-99. Bernstein, W. J. (1996). The Intelligent Asset Allocator. New York: McGraw-Hill. Dalbar, Inc. (2020). Quantitative Analysis of Investor Behavior. Boston: Dalbar. Damodaran, A. (2008). Strategic Risk Taking: A Framework for Risk Management. Upper Saddle River: Pearson Education. Elton, E. J., Gruber, M. J., Brown, S. J., & Goetzmann, W. N. (2014). Modern Portfolio Theory and Investment Analysis (9th ed.). Hoboken: John Wiley & Sons. Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56. Jorion, P. (1992). Portfolio optimization in practice. Financial Analysts Journal, 48(1), 68-74. J.P. Morgan Asset Management. (2016). Guide to the Markets. New York: J.P. Morgan. Jungle Rock. (2025). Institutional Asset Allocation meets the Efficient Frontier: Replicating the JPMorgan Efficiente 5 Strategy. Working Paper. Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291. Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91. Markowitz, H. (1959). Portfolio Selection: Efficient Diversification of Investments. New York: John Wiley & Sons. Swensen, D. F. (2009). Pioneering Portfolio Management: An Unconventional Approach to Institutional Investment. New York: Free Press.
Pine Script® indicator
by EdgeTools
4