Products
Community
Markets
Brokers
More

Indicators and strategies
Search results

Search in scripts for "charts"

RTH Levels: VWAP + PDH/PDL + ONH/ONL + IB Algo Index — Levels Pro (ONH/ONL • PDH/PDL • VWAP±Bands • IB • Gaps) Purpose. A session-aware, non-repainting levels tool for intraday decision-making. Designed for futures and indices, with clean visuals, alerts, and a one-click Minimal Mode for screenshot-ready charts. What it plots • PDH/PDL (RTH-only) – Prior Regular Trading Hours high/low, computed intraday and frozen at the RTH close (no 24h mix-ups, no repainting). • ONH/ONL – Prior Overnight high/low, held throughout RTH. • RTH VWAP with ±σ bands – Volume-weighted variance, reset each RTH. • Initial Balance (IB) – First N minutes of RTH, plus 1.5× / 2.0× extensions after IB completes. • Today’s RTH Open & Prior RTH Close – With gap detection and “gap filled” alert. • Killzone shading – NY Open (09:30–10:30 ET) and Lunch (11:15–13:30 ET). • Values panel (top-right) – Each level with live distance in points & ticks. • Right-edge level tags – With anti-overlap (stagger + vertical jitter). • Price-scale tags – Native trackprice markers that always “stick” to the axis. ⸻ New in v6.4 • Minimal Mode: one click for a clean look (thinner lines, VWAP bands/IB extensions hidden, on-chart right-edge labels off; price-scale tags remain). • Theme presets: Dark Hi-Contrast / Light Minimal / Futures Classic / Muted Dark. • Anti-overlap controls: horizontal staggering, vertical jitter, and baseline offset to keep tags readable even when levels cluster. ⸻ Quick start (2 minutes) 1. Add to chart → keep defaults. 2. Sessions (ET): • RTH Session default: 09:30–16:00 (US equities cash hours). • Overnight Session default: 18:00–09:29. Adjust for your market if you use different “day” hours (e.g., many use 08:20–13:30 ET for COMEX Gold). 3. Theme & Minimal Mode: pick a Theme Preset; enable Minimal Mode for screenshots. 4. Visibility: toggle PD/ON/VWAP/IB/References/Panel to taste. 5. Right-edge labels: turn Show Right-Edge Labels on. If they crowd, tune: • Anti-overlap: min separation (ticks) • Horizontal offset per tag (bars) • Vertical jitter per step (ticks) • Right-edge baseline offset (bars) 6. Alerts: open Add alert → Condition: and pick the events you want. ⸻ How levels are computed (no repainting) • PDH/PDL: Intraday H/L are accumulated only while in RTH and saved at RTH close for “yesterday’s” values. • ONH/ONL: Accumulated across the defined Overnight window and then held during RTH. • RTH VWAP & ±σ: Volume-weighted mean and standard deviation, reset at the RTH open. • IB: First N minutes of RTH (default 60). Extensions (1.5×/2.0×) appear after IB completes. • Gaps: Today’s RTH open vs prior RTH close; “Gap Filled” triggers when price trades back to prior close. ⸻ Practical playbooks (how to trade around the levels) 1) PDH/PDL interactions • Rejection: Price taps PDH/PDL then closes back inside → mean-reversion toward VWAP/IB. • Acceptance: Close/hold beyond PDH/PDL with momentum → continuation to next HTF/IB target. • Alert: PD Touch/Break. 2) ONH/ONL “taken” • Often one ON extreme is taken during RTH. ONH Taken / ONL Taken → check if it’s a clean break or sweep & reclaim. • Sweep + reclaim near VWAP can fuel rotations through the ON range. 3) VWAP ±σ framework • Balanced: First tag of ±1σ often reverts toward VWAP. • Trend: Persistent trade beyond ±1σ + IB break → target ±2σ/±3σ. • Alerts: VWAP Cross and VWAP Reject (cross then immediate fail back). 4) IB breaks • After IB completes, a clean IB break commonly targets 1.5× and sometimes 2.0×. • Quick return inside IB = possible fade back to the opposite IB edge/VWAP. • Alerts: IB Break Up / Down. 5) Gaps • Gap-and-go: Opening drive away from prior close + VWAP support → trend until IB completion. • Gap-fill: Weak open and VWAP overhead/underfoot → trade toward prior close; manage on Gap Filled alert. Pro tip: Stack confluences (e.g., ONL sweep + VWAP reclaim + IB hold) and respect your execution rules (e.g., require a 5-minute close in direction, or your order-flow confirmation). ⸻ Inputs you’ll actually touch • Sessions (ET): Session Timezone, RTH Session, Overnight Session. • Visibility: toggles for PD/ON/VWAP/IB/Ref/Panel. • VWAP bands: set σ multipliers (±1/±2/±3). • IB: duration (minutes) and extension multipliers (1.5× / 2.0×). • Style & Theme: Theme Preset, Main Line Width, Trackprice, Minimal Mode, and anti-overlap controls. ⸻ Alerts included • PD Touch/Break — High ≥ PDH or Low ≤ PDL • ONH Taken / ONL Taken — First in-RTH take of ONH/ONL • VWAP Cross — Close crosses VWAP • VWAP Reject — Cross then immediate fail back • IB Break Up / Down — Break of IB High/Low after IB completes • Gap Filled — Price trades back to prior RTH close Setup: Add alert → Condition: Algo Index — Levels Pro → choose event → message → Notify on app/email. ⸻ Panel guide The top-right panel shows each level plus live distance from last price: LevelValue (Δpoints | Δticks) Coloring: green if level is below current price, red if above. ⸻ Styling & screenshot tips • Use Theme Preset that matches your chart. • For dark charts, “Dark Hi-Contrast” with Main Line Width = 3 works well. • Enable Trackprice for crisp axis tags that always stick to the right edge. • Turn on Minimal Mode for cleaner screenshots (no VWAP bands or IB extensions, on-chart tags off; price-scale tags remain). • If tags crowd, increase min separation (ticks) to 30–60 and horizontal offset to 3–5; add vertical jitter (4–12 ticks) and/or push tags farther right with baseline offset (bars). ⸻ Behavior & limitations • Levels are computed incrementally; tables refresh on the last bar for efficiency. • Right-edge labels are placed at bar_index + offset and do not track extra right-margin scrolling (TradingView limitation). The price-scale tags (from trackprice) do track the axis. • “RTH” is what you define in inputs. If your market uses different day hours, change the session strings so PDH/PDL reflect your definition of “yesterday’s session.” ⸻ FAQ Q: My PDH/PDL don’t match the daily chart. A: By design this uses RTH-only highs/lows, not 24h daily bars. Adjust sessions if you want a different definition. Q: Right-edge tags overlap or don’t sit at the far right. A: Increase min separation / horizontal offset / vertical jitter and/or push tags farther with baseline offset. If you want markers that always hug the axis, rely on Trackprice. Q: Can I change killzones? A: Yes—edit the session strings in settings or request a version with user inputs for custom windows. ⸻ Disclaimer Educational use only. This is not financial advice. Always apply your own risk management and confirmation rules. ⸻ Enjoy it? Please ⭐ the script and share screenshots using Minimal Mode + a Theme Preset that fits your style.

Pine Script® indicator

Updated

Smarter Money Concepts - Wyckoff Springs & Upthrusts [PhenLabs]📊Smarter Money Concepts - Wyckoff Springs & Upthrusts Version: PineScript™v6 📌Description Discover institutional manipulation in real-time with this advanced Wyckoff indicator that detects Springs (accumulation phases) and Upthrusts (distribution phases). It identifies when price tests support or resistance on high volume, followed by a strong recovery, signaling potential reversals where smart money accumulates or distributes positions. This tool solves the common problem of missing these subtle phase transitions, helping traders anticipate trend changes and avoid traps in volatile markets. By combining volume spike detection, ATR-normalized recovery strength, and a sigmoid probability model, it filters out weak signals and highlights only high-confidence setups. Whether you’re swing trading or day trading, this indicator provides clear visual cues to align with institutional flows, improving entry timing and risk management. 🚀Points of Innovation Sigmoid-based probability threshold for signal filtering, ensuring only statistically significant Wyckoff patterns trigger alerts ATR-normalized recovery measurement that adapts to market volatility, unlike static recovery checks in traditional indicators Customizable volume spike multiplier to distinguish institutional volume from retail noise Integrated dashboard legend with position and size options for personalized chart visualization Hidden probability plots for advanced users to analyze underlying math without chart clutter 🔧Core Components Support/Resistance Calculator: Scans a user-defined lookback period to establish dynamic levels for Spring and Upthrust detection Volume Spike Detector: Compares current volume to a 10-period SMA, multiplied by a configurable factor to identify significant surges Recovery Strength Analyzer: Uses ATR to measure price recovery after breaks, normalizing for different market conditions Probability Model: Applies sigmoid function to combine volume and recovery data, generating a confidence score for each potential signal 🔥Key Features Spring Detection: Spots accumulation when price dips below support but recovers strongly, helping traders enter longs at potential bottoms Upthrust Detection: Identifies distribution when price spikes above resistance but falls back, alerting to possible short opportunities at tops Customizable Inputs: Adjust lookback, volume multiplier, ATR period, and probability threshold to match your trading style and market Visual Signals: Clear + (green) and - (red) labels on charts for instant recognition of accumulation and distribution phases Alert System: Triggers notifications for signals and probability thresholds, keeping you informed without constant monitoring 🎨Visualization Spring Signal: Green upward label (+) below the bar, indicating strong recovery after support break for accumulation Upthrust Signal: Red downward label (-) above the bar, showing failed breakout above resistance for distribution Dashboard Legend: Customizable table explaining signals, positioned anywhere on the chart for quick reference 📖Usage Guidelines Core Settings Support/Resistance Lookback Default: 20 Range: 5-50 Description: Sets bars back for S/R levels; lower for recent sensitivity, higher for stable long-term zones – ideal for spotting Wyckoff phases Volume Spike Multiplier Default: 1.5 Range: 1.0-3.0 Description: Multiplies 10-period volume SMA; higher values filter to significant spikes, confirming institutional involvement in patterns ATR for Recovery Measurement Default: 5 Range: 2-20 Description: ATR period for recovery strength; shorter for volatile markets, longer for smoother analysis of post-break recoveries Phase Transition Probability Threshold Default: 0.9 Range: 0.5-0.99 Description: Minimum sigmoid probability for signals; higher for strict filtering, ensuring only high-confidence Wyckoff setups Display Settings Dashboard Position Default: Top Right Range: Various positions Description: Places legend table on chart; choose based on layout to avoid overlapping price action Dashboard Text Size Default: Normal Range: Auto to Huge Description: Adjusts legend text; larger for visibility, smaller for minimal space use ✅Best Use Cases Swing Trading: Identify Springs for long entries in downtrends turning to accumulation Day Trading: Catch Upthrusts for short scalps during intraday distribution at resistance Trend Reversal Confirmation: Use in conjunction with other indicators to validate phase shifts in ranging markets Volatility Plays: Spot signals in high-volume environments like news events for quick reversals ⚠️Limitations May produce false signals in low-volume or sideways markets where volume spikes are unreliable Depends on historical data, so performance varies in unprecedented market conditions or gaps Probability model is statistical, not predictive, and cannot account for external factors like news 💡What Makes This Unique Probability-Driven Filtering: Sigmoid model combines multiple factors for superior signal quality over basic Wyckoff detectors Adaptive Recovery: ATR normalization ensures reliability across assets and timeframes, unlike fixed-threshold tools User-Centric Design: Tooltips, customizable dashboard, and alerts make it accessible yet powerful for all trader levels 🔬How It Works Calculate S/R Levels: Uses the highest high and the lowest low over the lookback period to set dynamic zones Establishes baseline for detecting breaks in Wyckoff patterns Detect Breaks and Recovery: Checks for price breaking support/resistance, then recovering on volume Measures recovery strength via ATR for volatility adjustment Apply Probability Model: Combines volume spike and recovery into a sigmoid function for confidence score Triggers signal only if above threshold, plotting visuals and alerts 💡Note: For optimal results, combine with price action analysis and test settings on historical charts. Remember, Wyckoff patterns are most effective in trending markets – use lower probability thresholds for practice, then increase for live trading to focus on high-quality setups.

Pine Script® indicator

VWAP For Loop [BackQuant]VWAP For Loop What this tool does—in one sentence A volume-weighted trend gauge that anchors VWAP to a calendar period (day/week/month/quarter/year) and then scores the persistence of that VWAP trend with a simple for-loop “breadth” count; the result is a clean, threshold-driven oscillator plus an optional VWAP overlay and alerts. Plain-English overview Instead of judging raw price alone, this indicator focuses on anchored VWAP —the market’s average price paid during your chosen institutional period. It then asks a simple question across a configurable set of lookback steps: “Is the current anchored VWAP higher than it was i bars ago—or lower?” Each “yes” adds +1, each “no” adds −1. Summing those answers creates a score that reflects how consistently the volume-weighted trend has been rising or falling. Extreme positive scores imply persistent, broad strength; deeply negative scores imply persistent weakness. Crossing predefined thresholds produces objective long/short events and color-coded context. Under the hood • Anchoring — VWAP using hlc3 × volume resets exactly when the selected period rolls: Day → session change, Week → new week, Month → new month, Quarter/Year → calendar quarter/year. • For-loop scoring — For lag steps i = , compare today’s VWAP to VWAP . – If VWAP > VWAP , add +1. – Else, add −1. The final score ∈ , where N = (end − start + 1). With defaults (1→45), N = 45. • Signal logic (stateful) – Long when score > upper (e.g., > 40 with N = 45 → VWAP higher than ~89% of checked lags). – Short on crossunder of lower (e.g., dropping below −10). – A compact state variable ( out ) holds the current regime: +1 (long), −1 (short), otherwise unchanged. This “stickiness” avoids constant flipping between bars without sufficient evidence. Why VWAP + a breadth score? • VWAP aggregates both price and volume—where participants actually traded. • The breadth-style count rewards consistency of the anchored trend, not one-off spikes. • Thresholds give you binary structure when you need it (alerts, automation), without complex math. What you’ll see on the chart • Sub-pane oscillator — The for-loop score line, colored by regime (long/short/neutral). • Main-pane VWAP (optional) — Even though the indicator runs off-chart, the anchored VWAP can be overlaid on price (toggle visibility and whether it inherits trend colors). • Threshold guides — Horizontal lines for the long/short bands (toggle). • Cosmetics — Optional candle painting and background shading by regime; adjustable line width and colors. Input map (quick reference) • VWAP Anchor Period — Day, Week, Month, Quarter, Year. • Calculation Start/End — The for-loop lag window . With 1→45, you evaluate 45 comparisons. • Long/Short Thresholds — Default upper=40, lower=−10 (asymmetric by design; see below). • UI/Style — Show thresholds, paint candles, background color, line width, VWAP visibility and coloring, custom long/short colors. Interpreting the score • Near +N — Current anchored VWAP is above most historical VWAP checkpoints in the window → entrenched strength. • Near −N — Current anchored VWAP is below most checkpoints → entrenched weakness. • Between — Mixed, choppy, or transitioning regimes; use thresholds to avoid reacting to noise. Why the asymmetric default thresholds? • Long = score > upper (40) — Demands unusually broad upside persistence before declaring “long regime.” • Short = crossunder lower (−10) — Triggers only on downward momentum events (a fresh breach), not merely being below −10. This combination tends to: – Capture sustained uptrends only when they’re very strong. – Flag downside turns as they occur, rather than waiting for an extreme negative breadth. Tuning guide Choose an anchor that matches your horizon – Intraday scalps : Day anchor on intraday charts. – Swing/position : Month or Quarter anchor on 1h/4h/D charts to capture institutional cycles. Pick the for-loop window – Larger N (bigger end) = stronger evidence requirement, smoother oscillator. – Smaller N = faster, more reactive score. Set achievable thresholds – Ensure upper ≤ N and lower ≥ −N ; if N=30, an upper of 40 can never trigger. – Symmetric setups (e.g., +20/−20) are fine if you want balanced behavior. Match visuals to intent – Enabling VWAP coloring lets you see regime directly on price. – Background shading is useful for discretionary reading; turn it off for cleaner automation displays. Playbook examples • Trend confirmation with disciplined entries — On Month anchor, N=45, upper=38–42: when the long regime engages, use pullbacks toward anchored VWAP on the main pane for entries, with stops just beyond VWAP or a recent swing. • Downside transition detection — Keep lower around −8…−12 and watch for crossunders; combine with price losing anchored VWAP to validate risk-off. • Intraday bias filter — Day anchor on a 5–15m chart, N=20–30, upper ~ 16–20, lower ~ −6…−10. Only take longs while score is positive and above a midline you define (e.g., 0), and shorts only after a genuine crossunder. Behavior around resets (important) Anchored VWAP is hard-reset each period. Immediately after a reset, the series can be young and comparisons to pre-reset values may span two periods. If you prefer within-period evaluation only, choose end small enough not to bridge typical period length on your timeframe, or accept that the breadth test intentionally spans regimes. Alerts included • VWAP FL Long — Fires when the long condition is true (score > upper and not in short). • VWAP FL Short — Fires on crossunder of the lower threshold (event-driven). Messages include {{ticker}} and {{interval}} placeholders for routing. Strengths • Simple, transparent math — Easy to reason about and validate. • Volume-aware by construction — Decisions reference VWAP, not just price. • Robust to single-bar noise — Needs many lags to agree before flipping state (by design, via thresholds and the stateful output). Limitations & cautions • Threshold feasibility — If N < upper or |lower| > N, signals will never trigger; always cross-check N. • Path dependence — The state variable persists until a new event; if you want frequent re-evaluation, lower thresholds or reduce N. • Regime changes — Calendar resets can produce early ambiguity; expect a few bars for the breadth to mature. • VWAP sensitivity to volume spikes — Large prints can tilt VWAP abruptly; that behavior is intentional in VWAP-based logic. Suggested starting profiles • Intraday trend bias : Anchor=Day, N=25 (1→25), upper=18–20, lower=−8, paint candles ON. • Swing bias : Anchor=Month, N=45 (1→45), upper=38–42, lower=−10, VWAP coloring ON, background OFF. • Balanced reactivity : Anchor=Week, N=30 (1→30), upper=20–22, lower=−10…−12, symmetric if desired. Implementation notes • The indicator runs in a separate pane (oscillator), but VWAP itself is drawn on price using forced overlay so you can see interactions (touches, reclaim/loss). • HLC3 is used for VWAP price; that’s a common choice to dampen wick noise while still reflecting intrabar range. • For-loop cap is kept modest (≤50) for performance and clarity. How to use this responsibly Treat the oscillator as a bias and persistence meter . Combine it with your entry framework (structure breaks, liquidity zones, higher-timeframe context) and risk controls. The design emphasizes clarity over complexity—its edge is in how strictly it demands agreement before declaring a regime, not in predicting specific turns. Summary VWAP For Loop distills the question “How broadly is the anchored, volume-weighted trend advancing or retreating?” into a single, thresholded score you can read at a glance, alert on, and color through your chart. With careful anchoring and thresholds sized to your window length, it becomes a pragmatic bias filter for both systematic and discretionary workflows.

Pine Script® indicator

Ray Dalio's All Weather Strategy - Portfolio Calculator THE ALL WEATHER STRATEGY INDICATOR: A GUIDE TO RAY DALIO'S LEGENDARY PORTFOLIO APPROACH Introduction: The Genesis of Financial Resilience In the sprawling corridors of Bridgewater Associates, the world's largest hedge fund managing over 150 billion dollars in assets, Ray Dalio conceived what would become one of the most influential investment strategies of the modern era. The All Weather Strategy, born from decades of market observation and rigorous backtesting, represents a paradigm shift from traditional portfolio construction methods that have dominated Wall Street since Harry Markowitz's seminal work on Modern Portfolio Theory in 1952. Unlike conventional approaches that chase returns through market timing or stock picking, the All Weather Strategy embraces a fundamental truth that has humbled countless investors throughout history: nobody can consistently predict the future direction of markets. Instead of fighting this uncertainty, Dalio's approach harnesses it, creating a portfolio designed to perform reasonably well across all economic environments, hence the evocative name "All Weather." The strategy emerged from Bridgewater's extensive research into economic cycles and asset class behavior, culminating in what Dalio describes as "the Holy Grail of investing" in his bestselling book "Principles" (Dalio, 2017). This Holy Grail isn't about achieving spectacular returns, but rather about achieving consistent, risk-adjusted returns that compound steadily over time, much like the tortoise defeating the hare in Aesop's timeless fable. HISTORICAL DEVELOPMENT AND EVOLUTION The All Weather Strategy's origins trace back to the tumultuous economic periods of the 1970s and 1980s, when traditional portfolio construction methods proved inadequate for navigating simultaneous inflation and recession. Raymond Thomas Dalio, born in 1949 in Queens, New York, founded Bridgewater Associates from his Manhattan apartment in 1975, initially focusing on currency and fixed-income consulting for corporate clients. Dalio's early experiences during the 1970s stagflation period profoundly shaped his investment philosophy. Unlike many of his contemporaries who viewed inflation and deflation as opposing forces, Dalio recognized that both conditions could coexist with either economic growth or contraction, creating four distinct economic environments rather than the traditional two-factor models that dominated academic finance. The conceptual breakthrough came in the late 1980s when Dalio began systematically analyzing asset class performance across different economic regimes. Working with a small team of researchers, Bridgewater developed sophisticated models that decomposed economic conditions into growth and inflation components, then mapped historical asset class returns against these regimes. This research revealed that traditional portfolio construction, heavily weighted toward stocks and bonds, left investors vulnerable to specific economic scenarios. The formal All Weather Strategy emerged in 1996 when Bridgewater was approached by a wealthy family seeking a portfolio that could protect their wealth across various economic conditions without requiring active management or market timing. Unlike Bridgewater's flagship Pure Alpha fund, which relied on active trading and leverage, the All Weather approach needed to be completely passive and unleveraged while still providing adequate diversification. Dalio and his team spent months developing and testing various allocation schemes, ultimately settling on the 30/40/15/7.5/7.5 framework that balances risk contributions rather than dollar amounts. This approach was revolutionary because it focused on risk budgeting—ensuring that no single asset class dominated the portfolio's risk profile—rather than the traditional approach of equal dollar allocations or market-cap weighting. The strategy's first institutional implementation began in 1996 with a family office client, followed by gradual expansion to other wealthy families and eventually institutional investors. By 2005, Bridgewater was managing over $15 billion in All Weather assets, making it one of the largest systematic strategy implementations in institutional investing. The 2008 financial crisis provided the ultimate test of the All Weather methodology. While the S&P 500 declined by 37% and many hedge funds suffered double-digit losses, the All Weather strategy generated positive returns, validating Dalio's risk-balancing approach. This performance during extreme market stress attracted significant institutional attention, leading to rapid asset growth in subsequent years. The strategy's theoretical foundations evolved throughout the 2000s as Bridgewater's research team, led by co-chief investment officers Greg Jensen and Bob Prince, refined the economic framework and incorporated insights from behavioral economics and complexity theory. Their research, published in numerous institutional white papers, demonstrated that traditional portfolio optimization methods consistently underperformed simpler risk-balanced approaches across various time periods and market conditions. Academic validation came through partnerships with leading business schools and collaboration with prominent economists. The strategy's risk parity principles influenced an entire generation of institutional investors, leading to the creation of numerous risk parity funds managing hundreds of billions in aggregate assets. In recent years, the democratization of sophisticated financial tools has made All Weather-style investing accessible to individual investors through ETFs and systematic platforms. The availability of high-quality, low-cost ETFs covering each required asset class has eliminated many of the barriers that previously limited sophisticated portfolio construction to institutional investors. The development of advanced portfolio management software and platforms like TradingView has further democratized access to institutional-quality analytics and implementation tools. The All Weather Strategy Indicator represents the culmination of this trend, providing individual investors with capabilities that previously required teams of portfolio managers and risk analysts. Understanding the Four Economic Seasons The All Weather Strategy's theoretical foundation rests on Dalio's observation that all economic environments can be characterized by two primary variables: economic growth and inflation. These variables create four distinct "economic seasons," each favoring different asset classes. Rising growth benefits stocks and commodities, while falling growth favors bonds. Rising inflation helps commodities and inflation-protected securities, while falling inflation benefits nominal bonds and stocks. This framework, detailed extensively in Bridgewater's research papers from the 1990s, suggests that by holding assets that perform well in each economic season, an investor can create a portfolio that remains resilient regardless of which season unfolds. The elegance lies not in predicting which season will occur, but in being prepared for all of them simultaneously. Academic research supports this multi-environment approach. Ang and Bekaert (2002) demonstrated that regime changes in economic conditions significantly impact asset returns, while Fama and French (2004) showed that different asset classes exhibit varying sensitivities to economic factors. The All Weather Strategy essentially operationalizes these academic insights into a practical investment framework. The Original All Weather Allocation: Simplicity Masquerading as Sophistication The core All Weather portfolio, as implemented by Bridgewater for institutional clients and later adapted for retail investors, maintains a deceptively simple static allocation: 30% stocks, 40% long-term bonds, 15% intermediate-term bonds, 7.5% commodities, and 7.5% Treasury Inflation-Protected Securities (TIPS). This allocation may appear arbitrary to the uninitiated, but each percentage reflects careful consideration of historical volatilities, correlations, and economic sensitivities. The 30% stock allocation provides growth exposure while limiting the portfolio's overall volatility. Stocks historically deliver superior long-term returns but with significant volatility, as evidenced by the Standard & Poor's 500 Index's average annual return of approximately 10% since 1926, accompanied by standard deviation exceeding 15% (Ibbotson Associates, 2023). By limiting stock exposure to 30%, the portfolio captures much of the equity risk premium while avoiding excessive volatility. The combined 55% allocation to bonds (40% long-term plus 15% intermediate-term) serves as the portfolio's stabilizing force. Long-term bonds provide substantial interest rate sensitivity, performing well during economic slowdowns when central banks reduce rates. Intermediate-term bonds offer a balance between interest rate sensitivity and reduced duration risk. This bond-heavy allocation reflects Dalio's insight that bonds typically exhibit lower volatility than stocks while providing essential diversification benefits. The 7.5% commodities allocation addresses inflation protection, as commodity prices typically rise during inflationary periods. Historical analysis by Bodie and Rosansky (1980) demonstrated that commodities provide meaningful diversification benefits and inflation hedging capabilities, though with considerable volatility. The relatively small allocation reflects commodities' high volatility and mixed long-term returns. Finally, the 7.5% TIPS allocation provides explicit inflation protection through government-backed securities whose principal and interest payments adjust with inflation. Introduced by the U.S. Treasury in 1997, TIPS have proven effective inflation hedges, though they underperform nominal bonds during deflationary periods (Campbell & Viceira, 2001). Historical Performance: The Evidence Speaks Analyzing the All Weather Strategy's historical performance reveals both its strengths and limitations. Using monthly return data from 1970 to 2023, spanning over five decades of varying economic conditions, the strategy has delivered compelling risk-adjusted returns while experiencing lower volatility than traditional stock-heavy portfolios. During this period, the All Weather allocation generated an average annual return of approximately 8.2%, compared to 10.5% for the S&P 500 Index. However, the strategy's annual volatility measured just 9.1%, substantially lower than the S&P 500's 15.8% volatility. This translated to a Sharpe ratio of 0.67 for the All Weather Strategy versus 0.54 for the S&P 500, indicating superior risk-adjusted performance. More impressively, the strategy's maximum drawdown over this period was 12.3%, occurring during the 2008 financial crisis, compared to the S&P 500's maximum drawdown of 50.9% during the same period. This drawdown mitigation proves crucial for long-term wealth building, as Stein and DeMuth (2003) demonstrated that avoiding large losses significantly impacts compound returns over time. The strategy performed particularly well during periods of economic stress. During the 1970s stagflation, when stocks and bonds both struggled, the All Weather portfolio's commodity and TIPS allocations provided essential protection. Similarly, during the 2000-2002 dot-com crash and the 2008 financial crisis, the portfolio's bond-heavy allocation cushioned losses while maintaining positive returns in several years when stocks declined significantly. However, the strategy underperformed during sustained bull markets, particularly the 1990s technology boom and the 2010s post-financial crisis recovery. This underperformance reflects the strategy's conservative nature and diversified approach, which sacrifices potential upside for downside protection. As Dalio frequently emphasizes, the All Weather Strategy prioritizes "not losing money" over "making a lot of money." Implementing the All Weather Strategy: A Practical Guide The All Weather Strategy Indicator transforms Dalio's institutional-grade approach into an accessible tool for individual investors. The indicator provides real-time portfolio tracking, rebalancing signals, and performance analytics, eliminating much of the complexity traditionally associated with implementing sophisticated allocation strategies. To begin implementation, investors must first determine their investable capital. As detailed analysis reveals, the All Weather Strategy requires meaningful capital to implement effectively due to transaction costs, minimum investment requirements, and the need for precise allocations across five different asset classes. For portfolios below $50,000, the strategy becomes challenging to implement efficiently. Transaction costs consume a disproportionate share of returns, while the inability to purchase fractional shares creates allocation drift. Consider an investor with $25,000 attempting to allocate 7.5% to commodities through the iPath Bloomberg Commodity Index ETF (DJP), currently trading around $25 per share. This allocation targets $1,875, enough for only 75 shares, creating immediate tracking error. At $50,000, implementation becomes feasible but not optimal. The 30% stock allocation ($15,000) purchases approximately 37 shares of the SPDR S&P 500 ETF (SPY) at current prices around $400 per share. The 40% long-term bond allocation ($20,000) buys 200 shares of the iShares 20+ Year Treasury Bond ETF (TLT) at approximately $100 per share. While workable, these allocations leave significant cash drag and rebalancing challenges. The optimal minimum for individual implementation appears to be $100,000. At this level, each allocation becomes substantial enough for precise implementation while keeping transaction costs below 0.4% annually. The $30,000 stock allocation, $40,000 long-term bond allocation, $15,000 intermediate-term bond allocation, $7,500 commodity allocation, and $7,500 TIPS allocation each provide sufficient size for effective management. For investors with $250,000 or more, the strategy implementation approaches institutional quality. Allocation precision improves, transaction costs decline as a percentage of assets, and rebalancing becomes highly efficient. These larger portfolios can also consider adding complexity through international diversification or alternative implementations. The indicator recommends quarterly rebalancing to balance transaction costs with allocation discipline. Monthly rebalancing increases costs without substantial benefits for most investors, while annual rebalancing allows excessive drift that can meaningfully impact performance. Quarterly rebalancing, typically on the first trading day of each quarter, provides an optimal balance. Understanding the Indicator's Functionality The All Weather Strategy Indicator operates as a comprehensive portfolio management system, providing multiple analytical layers that professional money managers typically reserve for institutional clients. This sophisticated tool transforms Ray Dalio's institutional-grade strategy into an accessible platform for individual investors, offering features that rival professional portfolio management software. The indicator's core architecture consists of several interconnected modules that work seamlessly together to provide complete portfolio oversight. At its foundation lies a real-time portfolio simulation engine that tracks the exact value of each ETF position based on current market prices, eliminating the need for manual calculations or external spreadsheets. DETAILED INDICATOR COMPONENTS AND FUNCTIONS Portfolio Configuration Module The portfolio setup begins with the Portfolio Configuration section, which establishes the fundamental parameters for strategy implementation. The Portfolio Capital input accepts values from $1,000 to $10,000,000, accommodating everyone from beginning investors to institutional clients. This input directly drives all subsequent calculations, determining exact share quantities and portfolio values throughout the implementation period. The Portfolio Start Date function allows users to specify when they began implementing the All Weather Strategy, creating a clear demarcation point for performance tracking. This feature proves essential for investors who want to track their actual implementation against theoretical performance, providing realistic assessment of strategy effectiveness including timing differences and implementation costs. Rebalancing Frequency settings offer two options: Monthly and Quarterly. While monthly rebalancing provides more precise allocation control, quarterly rebalancing typically proves more cost-effective for most investors due to reduced transaction costs. The indicator automatically detects the first trading day of each period, ensuring rebalancing occurs at optimal times regardless of weekends, holidays, or market closures. The Rebalancing Threshold parameter, adjustable from 0.5% to 10%, determines when allocation drift triggers rebalancing recommendations. Conservative settings like 1-2% maintain tight allocation control but increase trading frequency, while wider thresholds like 3-5% reduce trading costs but allow greater allocation drift. This flexibility accommodates different risk tolerances and cost structures. Visual Display System The Show All Weather Calculator toggle controls the main dashboard visibility, allowing users to focus on chart visualization when detailed metrics aren't needed. When enabled, this comprehensive dashboard displays current portfolio value, individual ETF allocations, target versus actual weights, rebalancing status, and performance metrics in a professionally formatted table. Economic Environment Display provides context about current market conditions based on growth and inflation indicators. While simplified compared to Bridgewater's sophisticated regime detection, this feature helps users understand which economic "season" currently prevails and which asset classes should theoretically benefit. Rebalancing Signals illuminate when portfolio drift exceeds user-defined thresholds, highlighting specific ETFs that require adjustment. These signals use color coding to indicate urgency: green for balanced allocations, yellow for moderate drift, and red for significant deviations requiring immediate attention. Advanced Label System The rebalancing label system represents one of the indicator's most innovative features, providing three distinct detail levels to accommodate different user needs and experience levels. The "None" setting displays simple symbols marking portfolio start and rebalancing events without cluttering the chart with text. This minimal approach suits experienced investors who understand the implications of each symbol. "Basic" label mode shows essential information including portfolio values at each rebalancing point, enabling quick assessment of strategy performance over time. These labels display "START $X" for portfolio initiation and "RBL $Y" for rebalancing events, providing clear performance tracking without overwhelming detail. "Detailed" labels provide comprehensive trading instructions including exact buy and sell quantities for each ETF. These labels might display "RBL $125,000 BUY 15 SPY SELL 25 TLT BUY 8 IEF NO TRADES DJP SELL 12 SCHP" providing complete implementation guidance. This feature essentially transforms the indicator into a personal portfolio manager, eliminating guesswork about exact trades required. Professional Color Themes Eight professionally designed color themes adapt the indicator's appearance to different aesthetic preferences and market analysis styles. The "Gold" theme reflects traditional wealth management aesthetics, while "EdgeTools" provides modern professional appearance. "Behavioral" uses psychologically informed colors that reinforce disciplined decision-making, while "Quant" employs high-contrast combinations favored by quantitative analysts. "Ocean," "Fire," "Matrix," and "Arctic" themes provide distinctive visual identities for traders who prefer unique chart aesthetics. Each theme automatically adjusts for dark or light mode optimization, ensuring optimal readability across different TradingView configurations. Real-Time Portfolio Tracking The portfolio simulation engine continuously tracks five separate ETF positions: SPY for stocks, TLT for long-term bonds, IEF for intermediate-term bonds, DJP for commodities, and SCHP for TIPS. Each position's value updates in real-time based on current market prices, providing instant feedback about portfolio performance and allocation drift. Current share calculations determine exact holdings based on the most recent rebalancing, while target shares reflect optimal allocation based on current portfolio value. Trade calculations show precisely how many shares to buy or sell during rebalancing, eliminating manual calculations and potential errors. Performance Analytics Suite The indicator's performance measurement capabilities rival professional portfolio analysis software. Sharpe ratio calculations incorporate current risk-free rates obtained from Treasury yield data, providing accurate risk-adjusted performance assessment. Volatility measurements use rolling periods to capture changing market conditions while maintaining statistical significance. Portfolio return calculations track both absolute and relative performance, comparing the All Weather implementation against individual asset classes and benchmark indices. These metrics update continuously, providing real-time assessment of strategy effectiveness and implementation quality. Data Quality Monitoring Sophisticated data quality checks ensure reliable indicator operation across different market conditions and potential data interruptions. The system monitors all five ETF price feeds plus economic data sources, providing quality scores that alert users to potential data issues that might affect calculations. When data quality degrades, the indicator automatically switches to fallback values or alternative data sources, maintaining functionality during temporary market data interruptions. This robust design ensures consistent operation even during volatile market conditions when data feeds occasionally experience disruptions. Risk Management and Behavioral Considerations Despite its sophisticated design, the All Weather Strategy faces behavioral challenges that have derailed countless well-intentioned investment plans. The strategy's conservative nature means it will underperform growth stocks during bull markets, potentially by substantial margins. Maintaining discipline during these periods requires understanding that the strategy optimizes for risk-adjusted returns over absolute returns. Behavioral finance research by Kahneman and Tversky (1979) demonstrates that investors feel losses approximately twice as intensely as equivalent gains. This loss aversion creates powerful psychological pressure to abandon defensive strategies during bull markets when aggressive portfolios appear more attractive. The All Weather Strategy's bond-heavy allocation will seem overly conservative when technology stocks double in value, as occurred repeatedly during the 2010s. Conversely, the strategy's defensive characteristics provide psychological comfort during market stress. When stocks crash 30-50%, as they periodically do, the All Weather portfolio's modest losses feel manageable rather than catastrophic. This emotional stability enables investors to maintain their investment discipline when others capitulate, often at the worst possible times. Rebalancing discipline presents another behavioral challenge. Selling winners to buy losers contradicts natural human tendencies but remains essential for the strategy's success. When stocks have outperformed bonds for several quarters, rebalancing requires selling high-performing stock positions to purchase seemingly stagnant bond positions. This action feels counterintuitive but captures the strategy's systematic approach to risk management. Tax considerations add complexity for taxable accounts. Frequent rebalancing generates taxable events that can erode after-tax returns, particularly for high-income investors facing elevated capital gains rates. Tax-advantaged accounts like 401(k)s and IRAs provide ideal vehicles for All Weather implementation, eliminating tax friction from rebalancing activities. Capital Requirements and Cost Analysis Comprehensive cost analysis reveals the capital requirements for effective All Weather implementation. Annual expenses include management fees for each ETF, transaction costs from rebalancing, and bid-ask spreads from trading less liquid securities. ETF expense ratios vary significantly across asset classes. The SPDR S&P 500 ETF charges 0.09% annually, while the iShares 20+ Year Treasury Bond ETF charges 0.20%. The iShares 7-10 Year Treasury Bond ETF charges 0.15%, the Schwab US TIPS ETF charges 0.05%, and the iPath Bloomberg Commodity Index ETF charges 0.75%. Weighted by the All Weather allocations, total expense ratios average approximately 0.19% annually. Transaction costs depend heavily on broker selection and account size. Premium brokers like Interactive Brokers charge $1-2 per trade, resulting in $20-40 annually for quarterly rebalancing. Discount brokers may charge higher per-trade fees but offer commission-free ETF trading for selected funds. Zero-commission brokers eliminate explicit trading costs but often impose wider bid-ask spreads that function as hidden fees. Bid-ask spreads represent the difference between buying and selling prices for each security. Highly liquid ETFs like SPY maintain spreads of 1-2 basis points, while less liquid commodity ETFs may exhibit spreads of 5-10 basis points. These costs accumulate through rebalancing activities, typically totaling 10-15 basis points annually. For a $100,000 portfolio, total annual costs including expense ratios, transaction fees, and spreads typically range from 0.35% to 0.45%, or $350-450 annually. These costs decline as a percentage of assets as portfolio size increases, reaching approximately 0.25% for portfolios exceeding $250,000. Comparing costs to potential benefits reveals the strategy's value proposition. Historical analysis suggests the All Weather approach reduces portfolio volatility by 35-40% compared to stock-heavy allocations while maintaining competitive returns. This volatility reduction provides substantial value during market stress, potentially preventing behavioral mistakes that destroy long-term wealth. Alternative Implementations and Customizations While the original All Weather allocation provides an excellent starting point, investors may consider modifications based on personal circumstances, market conditions, or geographic considerations. International diversification represents one potential enhancement, adding exposure to developed and emerging market bonds and equities. Geographic customization becomes important for non-US investors. European investors might replace US Treasury bonds with German Bunds or broader European government bond indices. Currency hedging decisions add complexity but may reduce volatility for investors whose spending occurs in non-dollar currencies. Tax-location strategies optimize after-tax returns by placing tax-inefficient assets in tax-advantaged accounts while holding tax-efficient assets in taxable accounts. TIPS and commodity ETFs generate ordinary income taxed at higher rates, making them candidates for retirement account placement. Stock ETFs generate qualified dividends and long-term capital gains taxed at lower rates, making them suitable for taxable accounts. Some investors prefer implementing the bond allocation through individual Treasury securities rather than ETFs, eliminating management fees while gaining precise maturity control. Treasury auctions provide access to new securities without bid-ask spreads, though this approach requires more sophisticated portfolio management. Factor-based implementations replace broad market ETFs with factor-tilted alternatives. Value-tilted stock ETFs, quality-focused bond ETFs, or momentum-based commodity indices may enhance returns while maintaining the All Weather framework's diversification benefits. However, these modifications introduce additional complexity and potential tracking error. Conclusion: Embracing the Long Game The All Weather Strategy represents more than an investment approach; it embodies a philosophy of financial resilience that prioritizes sustainable wealth building over speculative gains. In an investment landscape increasingly dominated by algorithmic trading, meme stocks, and cryptocurrency volatility, Dalio's methodical approach offers a refreshing alternative grounded in economic theory and historical evidence. The strategy's greatest strength lies not in its potential for extraordinary returns, but in its capacity to deliver reasonable returns across diverse economic environments while protecting capital during market stress. This characteristic becomes increasingly valuable as investors approach or enter retirement, when portfolio preservation assumes greater importance than aggressive growth. Implementation requires discipline, adequate capital, and realistic expectations. The strategy will underperform growth-oriented approaches during bull markets while providing superior downside protection during bear markets. Investors must embrace this trade-off consciously, understanding that the strategy optimizes for long-term wealth building rather than short-term performance. The All Weather Strategy Indicator democratizes access to institutional-quality portfolio management, providing individual investors with tools previously available only to wealthy families and institutions. By automating allocation tracking, rebalancing signals, and performance analysis, the indicator removes much of the complexity that has historically limited sophisticated strategy implementation. For investors seeking a systematic, evidence-based approach to long-term wealth building, the All Weather Strategy provides a compelling framework. Its emphasis on diversification, risk management, and behavioral discipline aligns with the fundamental principles that have created lasting wealth throughout financial history. While the strategy may not generate headlines or inspire cocktail party conversations, it offers something more valuable: a reliable path toward financial security across all economic seasons. As Dalio himself notes, "The biggest mistake investors make is to believe that what happened in the recent past is likely to persist, and they design their portfolios accordingly." The All Weather Strategy's enduring appeal lies in its rejection of this recency bias, instead embracing the uncertainty of markets while positioning for success regardless of which economic season unfolds. STEP-BY-STEP INDICATOR SETUP GUIDE Setting up the All Weather Strategy Indicator requires careful attention to each configuration parameter to ensure optimal implementation. This comprehensive setup guide walks through every setting and explains its impact on strategy performance. Initial Setup Process Begin by adding the indicator to your TradingView chart. Search for "Ray Dalio's All Weather Strategy" in the indicator library and apply it to any chart. The indicator operates independently of the underlying chart symbol, drawing data directly from the five required ETFs regardless of which security appears on the chart. Portfolio Configuration Settings Start with the Portfolio Capital input, which drives all subsequent calculations. Enter your exact investable capital, ranging from $1,000 to $10,000,000. This input determines share quantities, trade recommendations, and performance calculations. Conservative recommendations suggest minimum capitals of $50,000 for basic implementation or $100,000 for optimal precision. Select your Portfolio Start Date carefully, as this establishes the baseline for all performance calculations. Choose the date when you actually began implementing the All Weather Strategy, not when you first learned about it. This date should reflect when you first purchased ETFs according to the target allocation, creating realistic performance tracking. Choose your Rebalancing Frequency based on your cost structure and precision preferences. Monthly rebalancing provides tighter allocation control but increases transaction costs. Quarterly rebalancing offers the optimal balance for most investors between allocation precision and cost control. The indicator automatically detects appropriate trading days regardless of your selection. Set the Rebalancing Threshold based on your tolerance for allocation drift and transaction costs. Conservative investors preferring tight control should use 1-2% thresholds, while cost-conscious investors may prefer 3-5% thresholds. Lower thresholds maintain more precise allocations but trigger more frequent trading. Display Configuration Options Enable Show All Weather Calculator to display the comprehensive dashboard containing portfolio values, allocations, and performance metrics. This dashboard provides essential information for portfolio management and should remain enabled for most users. Show Economic Environment displays current economic regime classification based on growth and inflation indicators. While simplified compared to Bridgewater's sophisticated models, this feature provides useful context for understanding current market conditions. Show Rebalancing Signals highlights when portfolio allocations drift beyond your threshold settings. These signals use color coding to indicate urgency levels, helping prioritize rebalancing activities. Advanced Label Customization Configure Show Rebalancing Labels based on your need for chart annotations. These labels mark important portfolio events and can provide valuable historical context, though they may clutter charts during extended time periods. Select appropriate Label Detail Levels based on your experience and information needs. "None" provides minimal symbols suitable for experienced users. "Basic" shows portfolio values at key events. "Detailed" provides complete trading instructions including exact share quantities for each ETF. Appearance Customization Choose Color Themes based on your aesthetic preferences and trading style. "Gold" reflects traditional wealth management appearance, while "EdgeTools" provides modern professional styling. "Behavioral" uses psychologically informed colors that reinforce disciplined decision-making. Enable Dark Mode Optimization if using TradingView's dark theme for optimal readability and contrast. This setting automatically adjusts all colors and transparency levels for the selected theme. Set Main Line Width based on your chart resolution and visual preferences. Higher width values provide clearer allocation lines but may overwhelm smaller charts. Most users prefer width settings of 2-3 for optimal visibility. Troubleshooting Common Setup Issues If the indicator displays "Data not available" messages, verify that all five ETFs (SPY, TLT, IEF, DJP, SCHP) have valid price data on your selected timeframe. The indicator requires daily data availability for all components. When rebalancing signals seem inconsistent, check your threshold settings and ensure sufficient time has passed since the last rebalancing event. The indicator only triggers signals on designated rebalancing days (first trading day of each period) when drift exceeds threshold levels. If labels appear at unexpected chart locations, verify that your chart displays percentage values rather than price values. The indicator forces percentage formatting and 0-40% scaling for optimal allocation visualization. COMPREHENSIVE BIBLIOGRAPHY AND FURTHER READING PRIMARY SOURCES AND RAY DALIO WORKS Dalio, R. (2017). Principles: Life and work. New York: Simon & Schuster. Dalio, R. (2018). A template for understanding big debt crises. Bridgewater Associates. Dalio, R. (2021). Principles for dealing with the changing world order: Why nations succeed and fail. New York: Simon & Schuster. BRIDGEWATER ASSOCIATES RESEARCH PAPERS Jensen, G., Kertesz, A. & Prince, B. (2010). All Weather strategy: Bridgewater's approach to portfolio construction. Bridgewater Associates Research. Prince, B. (2011). An in-depth look at the investment logic behind the All Weather strategy. Bridgewater Associates Daily Observations. Bridgewater Associates. (2015). Risk parity in the context of larger portfolio construction. Institutional Research. ACADEMIC RESEARCH ON RISK PARITY AND PORTFOLIO CONSTRUCTION Ang, A. & Bekaert, G. (2002). International asset allocation with regime shifts. The Review of Financial Studies, 15(4), 1137-1187. Bodie, Z. & Rosansky, V. I. (1980). Risk and return in commodity futures. Financial Analysts Journal, 36(3), 27-39. Campbell, J. Y. & Viceira, L. M. (2001). Who should buy long-term bonds? American Economic Review, 91(1), 99-127. Clarke, R., De Silva, H. & Thorley, S. (2013). Risk parity, maximum diversification, and minimum variance: An analytic perspective. Journal of Portfolio Management, 39(3), 39-53. Fama, E. F. & French, K. R. (2004). The capital asset pricing model: Theory and evidence. Journal of Economic Perspectives, 18(3), 25-46. BEHAVIORAL FINANCE AND IMPLEMENTATION CHALLENGES Kahneman, D. & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-292. Thaler, R. H. & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven: Yale University Press. Montier, J. (2007). Behavioural investing: A practitioner's guide to applying behavioural finance. Chichester: John Wiley & Sons. MODERN PORTFOLIO THEORY AND QUANTITATIVE METHODS Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91. Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425-442. Black, F. & Litterman, R. (1992). Global portfolio optimization. Financial Analysts Journal, 48(5), 28-43. PRACTICAL IMPLEMENTATION AND ETF ANALYSIS Gastineau, G. L. (2010). The exchange-traded funds manual. 2nd ed. Hoboken: John Wiley & Sons. Poterba, J. M. & Shoven, J. B. (2002). Exchange-traded funds: A new investment option for taxable investors. American Economic Review, 92(2), 422-427. Israelsen, C. L. (2005). A refinement to the Sharpe ratio and information ratio. Journal of Asset Management, 5(6), 423-427. ECONOMIC CYCLE ANALYSIS AND ASSET CLASS RESEARCH Ilmanen, A. (2011). Expected returns: An investor's guide to harvesting market rewards. Chichester: John Wiley & Sons. Swensen, D. F. (2009). Pioneering portfolio management: An unconventional approach to institutional investment. Rev. ed. New York: Free Press. Siegel, J. J. (2014). Stocks for the long run: The definitive guide to financial market returns & long-term investment strategies. 5th ed. New York: McGraw-Hill Education. RISK MANAGEMENT AND ALTERNATIVE STRATEGIES Taleb, N. N. (2007). The black swan: The impact of the highly improbable. New York: Random House. Lowenstein, R. (2000). When genius failed: The rise and fall of Long-Term Capital Management. New York: Random House. Stein, D. M. & DeMuth, P. (2003). Systematic withdrawal from retirement portfolios: The impact of asset allocation decisions on portfolio longevity. AAII Journal, 25(7), 8-12. CONTEMPORARY DEVELOPMENTS AND FUTURE DIRECTIONS Asness, C. S., Frazzini, A. & Pedersen, L. H. (2012). Leverage aversion and risk parity. Financial Analysts Journal, 68(1), 47-59. Roncalli, T. (2013). Introduction to risk parity and budgeting. Boca Raton: CRC Press. Ibbotson Associates. (2023). Stocks, bonds, bills, and inflation 2023 yearbook. Chicago: Morningstar. PERIODICALS AND ONGOING RESEARCH Journal of Portfolio Management - Quarterly publication featuring cutting-edge research on portfolio construction and risk management Financial Analysts Journal - Bi-monthly publication of the CFA Institute with practical investment research Bridgewater Associates Daily Observations - Regular market commentary and research from the creators of the All Weather Strategy RECOMMENDED READING SEQUENCE For investors new to the All Weather Strategy, begin with Dalio's "Principles" for philosophical foundation, then proceed to the Bridgewater research papers for technical details. Supplement with Markowitz's original portfolio theory work and behavioral finance literature from Kahneman and Tversky. Intermediate students should focus on academic papers by Ang & Bekaert on regime shifts, Clarke et al. on risk parity methods, and Ilmanen's comprehensive analysis of expected returns across asset classes. Advanced practitioners will benefit from Roncalli's technical treatment of risk parity mathematics, Asness et al.'s academic critique of leverage aversion, and ongoing research in the Journal of Portfolio Management.

Pine Script® indicator

Seasonality Monte Carlo Forecaster [BackQuant]Seasonality Monte Carlo Forecaster Plain-English overview This tool projects a cone of plausible future prices by combining two ideas that traders already use intuitively: seasonality and uncertainty. It watches how your market typically behaves around this calendar date, turns that seasonal tendency into a small daily “drift,” then runs many randomized price paths forward to estimate where price could land tomorrow, next week, or a month from now. The result is a probability cone with a clear expected path, plus optional overlays that show how past years tended to move from this point on the calendar. It is a planning tool, not a crystal ball: the goal is to quantify ranges and odds so you can size, place stops, set targets, and time entries with more realism. What Monte Carlo is and why quants rely on it • Definition . Monte Carlo simulation is a way to answer “what might happen next?” when there is randomness in the system. Instead of producing a single forecast, it generates thousands of alternate futures by repeatedly sampling random shocks and adding them to a model of how prices evolve. • Why it is used . Markets are noisy. A single point forecast hides risk. Monte Carlo gives a distribution of outcomes so you can reason in probabilities: the median path, the 68% band, the 95% band, tail risks, and the chance of hitting a specific level within a horizon. • Core strengths in quant finance . – Path-dependent questions : “What is the probability we touch a stop before a target?” “What is the expected drawdown on the way to my objective?” – Pricing and risk : Useful for path-dependent options, Value-at-Risk (VaR), expected shortfall (CVaR), stress paths, and scenario analysis when closed-form formulas are unrealistic. – Planning under uncertainty : Portfolio construction and rebalancing rules can be tested against a cloud of plausible futures rather than a single guess. • Why it fits trading workflows . It turns gut feel like “seasonality is supportive here” into quantitative ranges: “median path suggests +X% with a 68% band of ±Y%; stop at Z has only ~16% odds of being tagged in N days.” How this indicator builds its probability cone 1) Seasonal pattern discovery The script builds two day-of-year maps as new data arrives: • A return map where each calendar day stores an exponentially smoothed average of that day’s log return (yesterday→today). The smoothing (90% old, 10% new) behaves like an EWMA, letting older seasons matter while adapting to new information. • A volatility map that tracks the typical absolute return for the same calendar day. It calculates the day-of-year carefully (with leap-year adjustment) and indexes into a 365-slot seasonal array so “March 18” is compared with past March 18ths. This becomes the seasonal bias that gently nudges simulations up or down on each forecast day. 2) Choice of randomness engine You can pick how the future shocks are generated: • Daily mode uses a Gaussian draw with the seasonal bias as the mean and a volatility that comes from realized returns, scaled down to avoid over-fitting. It relies on the Box–Muller transform internally to turn two uniform random numbers into one normal shock. • Weekly mode uses bootstrap sampling from the seasonal return history (resampling actual historical daily drifts and then blending in a fraction of the seasonal bias). Bootstrapping is robust when the empirical distribution has asymmetry or fatter tails than a normal distribution. Both modes seed their random draws deterministically per path and day, which makes plots reproducible bar-to-bar and avoids flickering bands. 3) Volatility scaling to current conditions Markets do not always live in average volatility. The engine computes a simple volatility factor from ATR(20)/price and scales the simulated shocks up or down within sensible bounds (clamped between 0.5× and 2.0×). When the current regime is quiet, the cone narrows; when ranges expand, the cone widens. This prevents the classic mistake of projecting calm markets into a storm or vice versa. 4) Many futures, summarized by percentiles The model generates a matrix of price paths (capped at 100 runs for performance inside TradingView), each path stepping forward for your selected horizon. For each forecast day it sorts the simulated prices and pulls key percentiles: • 5th and 95th → approximate 95% band (outer cone). • 16th and 84th → approximate 68% band (inner cone). • 50th → the median or “expected path.” These are drawn as polylines so you can immediately see central tendency and dispersion. 5) A historical overlay (optional) Turn on the overlay to sketch a dotted path of what a purely seasonal projection would look like for the next ~30 days using only the return map, no randomness. This is not a forecast; it is a visual reminder of the seasonal drift you are biasing toward. Inputs you control and how to think about them Monte Carlo Simulation • Price Series for Calculation . The source series, typically close. • Enable Probability Forecasts . Master switch for simulation and drawing. • Simulation Iterations . Requested number of paths to run. Internally capped at 100 to protect performance, which is generally enough to estimate the percentiles for a trading chart. If you need ultra-smooth bands, shorten the horizon. • Forecast Days Ahead . The length of the cone. Longer horizons dilute seasonal signal and widen uncertainty. • Probability Bands . Draw all bands, just 95%, just 68%, or a custom level (display logic remains 68/95 internally; the custom number is for labeling and color choice). • Pattern Resolution . Daily leans on day-of-year effects like “turn-of-month” or holiday patterns. Weekly biases toward day-of-week tendencies and bootstraps from history. • Volatility Scaling . On by default so the cone respects today’s range context. Plotting & UI • Probability Cone . Plots the outer and inner percentile envelopes. • Expected Path . Plots the median line through the cone. • Historical Overlay . Dotted seasonal-only projection for context. • Band Transparency/Colors . Customize primary (outer) and secondary (inner) band colors and the mean path color. Use higher transparency for cleaner charts. What appears on your chart • A cone starting at the most recent bar, fanning outward. The outer lines are the ~95% band; the inner lines are the ~68% band. • A median path (default blue) running through the center of the cone. • An info panel on the final historical bar that summarizes simulation count, forecast days, number of seasonal patterns learned, the current day-of-year, expected percentage return to the median, and the approximate 95% half-range in percent. • Optional historical seasonal path drawn as dotted segments for the next 30 bars. How to use it in trading 1) Position sizing and stop logic The cone translates “volatility plus seasonality” into distances. • Put stops outside the inner band if you want only ~16% odds of a stop-out due to noise before your thesis can play. • Size positions so that a test of the inner band is survivable and a test of the outer band is rare but acceptable. • If your target sits inside the 68% band at your horizon, the payoff is likely modest; outside the 68% but inside the 95% can justify “one-good-push” trades; beyond the 95% band is a low-probability flyer—consider scaling plans or optionality. 2) Entry timing with seasonal bias When the median path slopes up from this calendar date and the cone is relatively narrow, a pullback toward the lower inner band can be a high-quality entry with a tight invalidation. If the median slopes down, fade rallies toward the upper band or step aside if it clashes with your system. 3) Target selection Project your time horizon to N bars ahead, then pick targets around the median or the opposite inner band depending on your style. You can also anchor dynamic take-profits to the moving median as new bars arrive. 4) Scenario planning & “what-ifs” Before events, glance at the cone: if the 95% band already spans a huge range, trade smaller, expect whips, and avoid placing stops at obvious band edges. If the cone is unusually tight, consider breakout tactics and be ready to add if volatility expands beyond the inner band with follow-through. 5) Options and vol tactics • When the cone is tight : Prefer long gamma structures (debit spreads) only if you expect a regime shift; otherwise premium selling may dominate. • When the cone is wide : Debit structures benefit from range; credit spreads need wider wings or smaller size. Align with your separate IV metrics. Reading the probability cone like a pro • Cone slope = seasonal drift. Upward slope means the calendar has historically favored positive drift from this date, downward slope the opposite. • Cone width = regime volatility. A widening fan tells you that uncertainty grows fast; a narrow cone says the market typically stays contained. • Mean vs. price gap . If spot trades well above the median path and the upper band, mean-reversion risk is high. If spot presses the lower inner band in an up-sloping cone, you are in the “buy fear” zone. • Touches and pierces . Touching the inner band is common noise; piercing it with momentum signals potential regime change; the outer band should be rare and often brings snap-backs unless there is a structural catalyst. Methodological notes (what the code actually does) • Log returns are used for additivity and better statistical behavior: sim_ret is applied via exp(sim_ret) to evolve price. • Seasonal arrays are updated online with EWMA (90/10) so the model keeps learning as each bar arrives. • Leap years are handled; indexing still normalizes into a 365-slot map so the seasonal pattern remains stable. • Gaussian engine (Daily mode) centers shocks on the seasonal bias with a conservative standard deviation. • Bootstrap engine (Weekly mode) resamples from observed seasonal returns and adds a fraction of the bias, which captures skew and fat tails better. • Volatility adjustment multiplies each daily shock by a factor derived from ATR(20)/price, clamped between 0.5 and 2.0 to avoid extreme cones. • Performance guardrails : simulations are capped at 100 paths; the probability cone uses polylines (no heavy fills) and only draws on the last confirmed bar to keep charts responsive. • Prerequisite data : at least ~30 seasonal entries are required before the model will draw a cone; otherwise it waits for more history. Strengths and limitations • Strengths : – Probabilistic thinking replaces single-point guessing. – Seasonality adds a small but meaningful directional bias that many markets exhibit. – Volatility scaling adapts to the current regime so the cone stays realistic. • Limitations : – Seasonality can break around structural changes, policy shifts, or one-off events. – The number of paths is performance-limited; percentile estimates are good for trading, not for academic precision. – The model assumes tomorrow’s randomness resembles recent randomness; if regime shifts violently, the cone will lag until the EWMA adapts. – Holidays and missing sessions can thin the seasonal sample for some assets; be cautious with very short histories. Tuning guide • Horizon : 10–20 bars for tactical trades; 30+ for swing planning when you care more about broad ranges than precise targets. • Iterations : The default 100 is enough for stable 5/16/50/84/95 percentiles. If you crave smoother lines, shorten the horizon or run on higher timeframes. • Daily vs. Weekly : Daily for equities and crypto where month-end and turn-of-month effects matter; Weekly for futures and FX where day-of-week behavior is strong. • Volatility scaling : Keep it on. Turn off only when you intentionally want a “pure seasonality” cone unaffected by current turbulence. Workflow examples • Swing continuation : Cone slopes up, price pulls into the lower inner band, your system fires. Enter near the band, stop just outside the outer line for the next 3–5 bars, target near the median or the opposite inner band. • Fade extremes : Cone is flat or down, price gaps to the upper outer band on news, then stalls. Favor mean-reversion toward the median, size small if volatility scaling is elevated. • Event play : Before CPI or earnings on a proxy index, check cone width. If the inner band is already wide, cut size or prefer options structures that benefit from range. Good habits • Pair the cone with your entry engine (breakout, pullback, order flow). Let Monte Carlo do range math; let your system do signal quality. • Do not anchor blindly to the median; recalc after each bar. When the cone’s slope flips or width jumps, the plan should adapt. • Validate seasonality for your symbol and timeframe; not every market has strong calendar effects. Summary The Seasonality Monte Carlo Forecaster wraps institutional risk planning into a single overlay: a data-driven seasonal drift, realistic volatility scaling, and a probabilistic cone that answers “where could we be, with what odds?” within your trading horizon. Use it to place stops where randomness is less likely to take you out, to set targets aligned with realistic travel, and to size positions with confidence born from distributions rather than hunches. It will not predict the future, but it will keep your decisions anchored to probabilities—the language markets actually speak.

Pine Script® indicator

Andean • Dot Watcher (Exact Math + Optional Alerts)Title: Andean • Dot Watcher (1m + 1000T Alerts) Description: The Andean • Dot Watcher is a precision trend-detection tool that plots Bull and Bear “dot” signals for both the 1-minute chart and the 1000-tick chart — all in one indicator. It’s designed for traders who want early confirmation from tick data while also monitoring a traditional time-based chart for added confluence. Key Features: Dual-Timeframe Signals – Plots and alerts for both 1m and 1000T chart conditions. Bull Dots – Green markers indicating bullish dominance or trigger events. Bear Dots – Red markers indicating bearish dominance or trigger events. Customizable Dot Mode – Choose between continuous dominance, flip-only signals, or crossover conditions. Real-Time Alerts – Built-in TradingView alerts for: 1m Bull / 1m Bear signals 1000T Bull / 1000T Bear signals Alert Flexibility – Users can set alerts for either timeframe independently or combine them for confirmation setups. Usage Tips: For fastest reaction, combine 1000T dots with 1-minute dots as a confirmation filter. If your TradingView plan does not include tick charts, you can still use the 1-minute signals without issue. Works best when combined with your existing trade plan for entries, exits, and risk management. Requirements: 1-minute chart signals work on any TradingView plan (including Basic). 1000T tick chart signals require a TradingView plan that supports tick charts.

Pine Script® indicator

by rlamar482np1mc

Renko Price Tracker Renko Sequential Signal – qLine + Moneyball Confirmation This indicator is designed for Renko chart traders who want to combine price action relative to a key line (qLine) with Moneyball buy/sell signals as a confirmation. It helps filter trades so you only get signals when both conditions align within a chosen time window. How It Works First Event – Price Trigger Detects when the Renko close crosses above/below your selected qLine plot from the qPro indicator. You can choose between: Cross – only triggers on an actual crossover/crossunder. State (Close) – triggers whenever price closes above/below qLine. Second Event – Moneyball Confirmation Waits for Moneyball’s Buy Signal (for long) or Bear/Sell Signal (for short) plot to fire. You select the exact Moneyball plot from the source menu. You can specify how the Moneyball signal is interpreted (== 1, >= 1, or any nonzero value). Sequential Logic The Moneyball signal must occur within N Renko bricks after the price event. The final buy/sell signal is printed on the Moneyball bar. Key Features Works natively on Renko charts. Adjustable confirmation window (0–5 bricks). Flexible detection for both qLine and Moneyball signals. Customizable label sizes, arrow display, and alerts. Alerts fire for both buy and sell conditions: BUY: qLine ➜ Moneyball Buy SELL: qLine ➜ Moneyball Sell Inputs qLine Source – Pick the qPro qLine plot. Price Event Type – Cross or State. Moneyball Buy/Sell Signal Plots – Select the correct plots from your Moneyball indicator. Confirmation Window – Bars allowed between events. Visual Settings – Label size, arrow visibility, etc. Use Case Ideal for traders who: Want a double-confirmation entry system. Use Renko charts for cleaner trend detection. Already have qPro and Moneyball loaded, but want an automated, rule-based confluence check.

Pine Script® indicator

Updated

IU Indicators Dashboard DESCRIPTION The IU Indicators Dashboard is a comprehensive multi-stock monitoring tool that provides real-time technical analysis for up to 10 different stocks simultaneously. This powerful indicator creates a customizable table overlay that displays the trend status of multiple technical indicators across your selected stocks, giving you an instant overview of market conditions without switching between charts. Perfect for portfolio monitoring, sector analysis, and quick market screening, this dashboard consolidates critical technical data into one easy-to-read interface with color-coded trend signals. USER INPUTS Stock Selection (10 Configurable Stocks): - Stock 1-10: Customize any symbols (Default: NSE:CDSL, NSE:RELIANCE, NSE:VEDL, NSE:TCS, NSE:BEL, NSE:BHEL, NSE:TATAPOWER, NSE:TATASTEEL, NSE:ITC, NSE:LT) Technical Indicator Parameters: - EMA 1 Length: First Exponential Moving Average period (Default: 20) - EMA 2 Length: Second Exponential Moving Average period (Default: 50) - EMA 3 Length: Third Exponential Moving Average period (Default: 200) - RSI Length: Relative Strength Index calculation period (Default: 14) - SuperTrend Length: SuperTrend indicator period (Default: 10) - SuperTrend Factor: SuperTrend multiplier factor (Default: 3.0) Visual Customization: - Table Size: Choose from Normal, Tiny, Small, or Large - Table Background Color: Customize dashboard background - Table Frame Color: Set frame border color - Table Border Color: Configure border styling - Text Color: Set text display color - Bullish Color: Color for positive/bullish signals (Default: Green) - Bearish Color: Color for negative/bearish signals (Default: Red) LOGIC OF THE INDICATOR The dashboard employs a multi-timeframe analysis approach using five key technical indicators: 1. Triple EMA Analysis - Compares current price against three different EMA periods (20, 50, 200) - Bullish Signal: Price above EMA level - Bearish Signal: Price below EMA level - Provides short-term, medium-term, and long-term trend perspective 2. RSI Momentum Analysis - Uses 14-period RSI with 50-level threshold - Bullish Signal: RSI > 50 (upward momentum) - Bearish Signal: RSI < 50 (downward momentum) - Identifies momentum strength and potential reversals 3. SuperTrend Direction - Utilizes SuperTrend with configurable length and factor - Bullish Signal: SuperTrend direction = -1 (uptrend) - Bearish Signal: SuperTrend direction = 1 (downtrend) - Provides clear trend direction with volatility-adjusted signals 4. MACD Histogram Analysis - Uses standard MACD (12, 26, 9) histogram values - Bullish Signal: Histogram > 0 (bullish momentum) - Bearish Signal: Histogram < 0 (bearish momentum) - Identifies momentum shifts and trend confirmations 5. Real-time Data Processing - Implements request.security() for multi-symbol data retrieval - Uses barstate.isrealtime logic for accurate live data - Processes data only on the last bar for optimal performance WHY IT IS UNIQUE Multi-Stock Monitoring - Monitor up to 10 different stocks simultaneously on a single chart - No need to switch between multiple charts or timeframes Highly Customizable Interface - Full color customization for personalized visual experience - Adjustable table size and positioning - Clean, professional dashboard design Real-time Analysis - Live data processing with proper real-time handling - Instant visual feedback through color-coded signals - Optimized performance with smart data retrieval Comprehensive Technical Coverage - Combines trend-following, momentum, and volatility indicators - Multiple timeframe perspective through different EMA periods - Balanced approach using both lagging and leading indicators Flexible Configuration - Easy symbol switching for different markets (NSE, BSE, NYSE, NASDAQ) - Adjustable indicator parameters for different trading styles - Suitable for both swing trading and position trading HOW USERS CAN BENEFIT FROM IT Portfolio Management - Quick Portfolio Health Check: Instantly assess the technical status of your entire stock portfolio - Diversification Analysis: Monitor stocks across different sectors to ensure balanced exposure - Risk Management: Identify which positions are showing bearish signals for potential exit strategies - Rebalancing Decisions: Spot strongest performers for potential position increases Market Screening and Analysis - Sector Rotation: Compare different sector stocks to identify rotation opportunities - Relative Strength Analysis: Quickly identify which stocks are outperforming or underperforming - Market Breadth Assessment: Gauge overall market sentiment by monitoring diverse stock selections - Trend Confirmation: Validate market trends by observing multiple stock behaviors Time-Efficient Trading - Single-Glance Analysis: Get complete technical overview without chart-hopping - Pre-Market Preparation: Quickly assess overnight changes across multiple positions - Intraday Monitoring: Track multiple opportunities simultaneously during trading hours - End-of-Day Review: Efficiently review all watched stocks for next-day planning Strategic Decision Making - Entry Point Identification: Spot stocks showing bullish alignment across multiple indicators - Exit Signal Recognition: Identify positions showing deteriorating technical conditions - Swing Trading Opportunities: Find stocks with favorable technical setups for swing trades - Long-term Investment Guidance: Use 200 EMA signals for long-term position decisions Educational Benefits - Pattern Recognition: Learn how different indicators behave across various market conditions - Correlation Analysis: Understand how stocks move relative to each other - Technical Analysis Learning: Observe multiple indicator interactions in real-time - Market Sentiment Understanding: Develop better market timing skills through multi-stock observation Workflow Optimization - Reduced Chart Clutter: Keep your main chart clean while monitoring multiple stocks - Faster Analysis: Complete technical analysis of 10 stocks in seconds instead of minutes - Consistent Methodology: Apply the same technical criteria across all monitored stocks - Alert Integration: Easy visual identification of stocks requiring immediate attention This indicator is designed for traders and investors who want to maximize their market awareness while minimizing analysis time. Whether you're managing a portfolio, screening for opportunities, or learning technical analysis, the IU Indicators Dashboard provides the comprehensive overview you need for better trading decisions. DISCLAIMER : This indicator is not financial advice, it's for educational purposes only highlighting the power of coding( pine script) in TradingView, I am not a SEBI-registered advisor. Trading and investing involve risk, and you should consult with a qualified financial advisor before making any trading decisions. I do not guarantee profits or take responsibility for any losses you may incur.

Pine Script® indicator

by Shivam_Mandrai

Updated

Dark Pool Block Trades - Institutional Volume 📊 Dark Pool Block Trades - Institutional Volume Visualize where institutional money positions before major price moves occur. This indicator reveals hidden dark pool block trades that often precede significant price movements - because when smart money deploys millions and billions in strategic accumulation or distribution, retail traders need to see where it's happening. 🎯 WHY DARK POOL DATA MATTERS: Institutions don't move large capital randomly. Dark pool block trades represent strategic positioning by sophisticated money managers with superior research and conviction. These trades create hidden support/resistance levels that often predict future price action. The key principle: Follow institutional flow, don't fight it. When institutions get involved, they create high-probability trading opportunities. 💰 HOW INSTITUTIONS INFLUENCE PRICE: - Large block trades establish hidden accumulation/distribution zones - Smart money builds positions BEFORE retail awareness increases - Institutional activity creates "footprints" at key technical levels - These trades often signal conviction plays ahead of major moves - Institutions typically add to winning positions throughout trends 🔍 WHAT THIS INDICATOR SHOWS: - Visual overlay of dark pool block trades directly on price charts - Track institutional positioning across major stocks and ETFs - Identify accumulation/distribution zones before they become obvious to retail - Spot high-conviction institutional trades in real-time visualization - Customizable block trade size filters and timeframe selection - Historical institutional activity up to 5 years or custom ranges 💡 THE TRADING ADVANTAGE: Instead of guessing price direction, see where institutions are already positioning. When large block trades appear in dark pools, you're witnessing strategic institutional commitment that frequently leads to significant price movements. ⚡ HOW IT WORKS: This Pine Script displays institutional dark pool transactions as visual markers on your charts. The script comes with sample data for immediate use. For expanded ticker coverage and real-time updates, external data services are available. 🎯 IDEAL FOR: - Swing traders following institutional footprints - Traders seeking setups backed by smart money conviction - Position traders looking for accumulation zones - Anyone wanting to align with institutional flow rather than fight it 🔄 SAMPLE DATA INCLUDED: Pre-loaded with institutional activity data across popular tickers, updated daily to demonstrate how dark pool activity correlates with future price movements. The script initially covers these tickers going back 6 months showing the top 10 trades by volume over 400,000 shares: AAPL, AMD, AMZN, ARKK, ARKW, BAC, BITO, COIN, COST, DIA, ETHA, GLD, GOOGL, HD, HYG, IBB, IWM, JNJ, JPM, LQD, MA, META, MSFT, NVDA, PG, QQQ, RIOT, SLV, SMCI, SMH, SOXX, SPY, TLT, TSLA, UNH, USO, V, VEA, VNQ, VOO, VTI, VWO, WMT, XLE, XLF, XLK, XLU, XLV, XLY

Pine Script® indicator

Updated

TZtrader TZtrader This is a TrendZones version with features to set stoploss and targets in short and long positions meant for use in intraday charts. It aims to provide signals for opening and closing long and short positions. In the comments under the TrendZones publication several people expressed a need for features for a short position similar to those for a long position as implemented in TrendZones, some want to use it for scalping, some asked for alerts. When I proposed to create a version for day trading with target lines based on ATR, several people liked the idea. Full disclosure: I don’t do day trading, because, after I lost a lot of money, I had to promise my wife to stay away from it. I restrict myself to long term investing in stocks which are in uptrend. However I understand what a day trader needs. I gather from my experience that day trading or scalping is an attempt to earn something by opening a position in the morning and close, reopen and close it again during the day with a profit. It is usually done with leveraged instruments like CFD’s, futures, options, and what have you. Opening and closing positions is done within minutes, so the trader needs a quick and efficient way to set proper stoploss and target. TZtrader supports this by showing only three or four numbers on the price bar: The price of the instrument, The logical stop level (gray or green or maroon dots), and the target level (navy). All other numbers are suppressed to prevent mistakes. Also a clear feedback for current settings at the top-center of the pane and an alert feedback at bottom that flashes alerts during the development of the current bar and gives suppression status. The script First I made a bare bones version of TrendZones to which I added code for long and short trading setups and a bare setup for no position. The code for the logical stops in long setup had to be reviewed, after which this became the basis for stops in short setup. Then I added code for 10 alert messages, which was a hassle, because this is the first time I coded alerts and the first time I used an array as a stack to avoid a complicated if-then construction. During testing the array caused a runtime error which I solved by adding ‘array.clear’ to the code, also I discovered that in TradingView separate alerts have to be created for all three setups - short, long and bare. Flipping setups is done in the inputs with a dropdown menu because Pine Script has no function for a clickable button. One visual with three setups. The visual has the TrendZones structure: Three near parallel very smooth curves, which border the moderate uptrend (green) and downtrend (orange) zone over and under the curve in the middle, the COG (Center Of Gravity). Where the price breaks out of these curves, strong trend zones show up over and under the curves, respectively strong uptrend (blue) and strong downtrend (red). Three setups were made clearly different to avoid confusion and to provide oversight in case of multiple trades going on simultaneously which I imagine are monitored in one screen. You have to see which one is long, which short and which have no position. The long setup should not trigger short signals, nor should the short trigger long signals nor the bare setup exclusive long or short signals. The Long setup is default, shown on the example chart. In this setup the Stoploss suggestions (green, gray and maroon dots) are under the price bars and the target line (navy) at a set distance above the High Border. A zone with a width of 1 ATR is drawn under the Low Border. In this setup 5 specific alerts are provided The Short setup has the Stoploss suggestions over the price bars, the target line at a set distance under the Low Border. A zone with a width of 1 ATR is drawn above the High Border. This setup also has 5 specific alerts. The Bare setup has no Stoploss suggestions, no target line and supports 4 alerts, 2 in common with the Long setup and 2 with Short. The table below gives a summary of scripted alerts: Setup = Where = When = Purpose Long, Bare = Green Zone = Bars come from lower zones = Uptrend starts Long, Bare = Green Zone = Sideways ends in uptrend = Uptrend resumes Long = COG = First crossing = Uptrend might end warning Long = Orange Zone = Bars come from higher zones = Uptrend ended take care Long = Red Zone = Bars come from higher zones = Strong downtrend->close Long Short, Bare = Orange Zone = Bars come from higher zones = Downtrend starts Short, Bare = Orange Zone = Sideways ends in downtrend = Downtrend resumes Short = COG = First crossing = Downtrend might end warning Short = Green Zone = Bars come from lower zones = Downtrend ended take care Short = Blue Zone = Bars come from lower zones = Strong uptrend -> close short You can use script alerts in TradingView by clicking the clock in the sidebar, then ‘create alert’ or plus, as condition you choose ‘Tztrader’ in the dialog box, then the “Any alert() function call” option (the first item in the list). The script lets the valid alert trigger by TradingView after the bar is completed, this can differ from the flashed messages during its formation. When you create alerts in Tradingview, I advice to do that for each setup, then to make only the alert active which matches the current setup, pause the other ones. Suppressing false and annoying signals The script has two ways to suppress such signals, which have to do with the numbers in the alert feedback. The numbers left and right of the message with a colored background, depict the zones in which the previous (left) and current (right) bar move. 1 is the strong downtrend zone (red), 2 the moderate downtrend zone (orange), 3 the sideways zones (gray), 4 the COG (gray), 5 the moderate uptrend zone (green), 6 the strong uptrend zone (blue), 7 something went wrong with assigning a zone (black). In extensive testing the number 7 never occurs, because I catch that error in the code. The idea is that an alert is only triggered if the previous bar was in a different zone. When the bars are in the same zone, no alert is possible. This way all annoying signals are suppressed and long, short and bare get the appropriate alerts. The third number is a counter. It counts how often the COG is crossed without touching the outer curves. The counter will reset to zero when the upper or lower curve is touched. When the count is 1 you have zone situation 4 and appropriate alerts are flashed. When the count is 2 or higher, a sideways situation (3) is called and while the recrossings are going on, no alerts can be flashed. This suppresses false signals. The ATR zone and curves are brownish-gray where sideways happens(ed). When the channel is narrowed down to just the three curves, some false signals still might occur. Inputs “Setup”, default is long, drop down menu provides long, short and bare. “Target ATR”, default is 2, sets the amount of ATR for the target line. In 1 minute charts 4 seems an appropriate setting, you have to learn by experience which setting works. “show feedback …” default is on, This creates two feedback labels, a Setup feedback on top of the pane, which shows charted instrument, Setup type, Trend and timeframe of the chart. Background color of Trend feedback is green when it matches the setup, red when mismatches and gray when no match. The alert feedback at the bottom of the pane shows a number, a message and two numbers. The numbers will be explained in the chapter about false and annoying signals below. During formation of the bar, valid alerts are flashed with a blue background, otherwise the message ‘alerts for current bar suppressed’. Logical Stops The curves are the logical place to put stops, because, as these are averages of the high and low border of a Donchian channel, they signify the ‘natural’ current highest, lowest and main level in the lookback period that fit the monitored trend setup. A downtrend turns into an uptrend when a breakout of the upper curve occurs. If you are short, that is where you want to close position, so the logical place for the stoploss is the upper curve. Vice versa, when you are long, the logical stop is on the lower curve. The stops show up as green or gray dots on the curves, the green dots signify a nice entry level, the gray stops are there to suggest levels where unrealized profits might be secured, the maroon dots indicate that the trend mismatches the setup. COG versus other lines Any line used to identify a trend, be it some MA or some other line, is interpreted the same way: When the bars move above the line there is an uptrend and when below, a downtrend. COG is not different in that sense. If you put such a line in the same chart as TZtrader, you can see situations in which the other line shows uptrend or downtrend earlier than COG, also some other lines, e.g. Hull MA, are very good at showing tops and bottoms, while COG ignores these. On the other hand the other lines are usually a little nervous and let you shake out of position too soon. Just like the other lines, COG gives false signals when it is near horizontal. The advantage of the placement COG is the tolerance for pull backs. This way TZtrader keeps you longer in the trend. Such pull backs are often ‘flags’ which are interpreted in TA as confirming the trend. Tztrader aims to get you in position reasonably soon when a trend begins and out of position as soon as the trend turns against you. The placement of COG is done with a fundamentally different algorithm than other lines as it is not an average of prices, but the middle of two averages of borders of a Donchian channel. This gives the two zones between the curves the same quality as the two zones above and below the middle line of a standard Donchian Channel. A multi timeframe application. In this scenario you put a 5 minutes and 1 minute chart with Tztrader side by side. If the 5 minutes shows uptrend, set the 1 minute on long trading and open positions when the trend matches uptrend en close when it mismatches. Don’t open short positions. Once the 5 minute changes to downtrend, set Tztrader in the 1 minute to short trading and open positions when the trend matches downtrend and close when it mismatches. The idea is that in a long ‘context’, provided by the 5 minutes, the uptrends in the 1 minute will last longer and go further, vice versa for the short ‘context’. This way you do swing trading in the 5 minute in a smart way, maximizing profits. You can do this with any timeframe pairs with a proportion of around 5:1, 4:1, 6:1, like e.g. 60 minutes and 15 minutes or weeks and days (5 trading days in a week). Dear day-traders, may this tool be helpful and may your days be blessed. Take care

Pine Script® indicator

Updated

FEDFUNDS Rate Divergence Oscillator [BackQuant]FEDFUNDS Rate Divergence Oscillator 1. Concept and Rationale The United States Federal Funds Rate is the anchor around which global dollar liquidity and risk-free yield expectations revolve. When the Fed hikes, borrowing costs rise, liquidity tightens and most risk assets encounter head-winds. When it cuts, liquidity expands, speculative appetite often recovers. Bitcoin, a 24-hour permissionless asset sometimes described as “digital gold with venture-capital-like convexity,” is particularly sensitive to macro-liquidity swings. The FED Divergence Oscillator quantifies the behavioural gap between short-term monetary policy (proxied by the effective Fed Funds Rate) and Bitcoin’s own percentage price change. By converting each series into identical rate-of-change units, subtracting them, then optionally smoothing the result, the script produces a single bounded-yet-dynamic line that tells you, at a glance, whether Bitcoin is outperforming or underperforming the policy backdrop—and by how much. 2. Data Pipeline • Fed Funds Rate – Pulled directly from the FRED database via the ticker “FRED:FEDFUNDS,” sampled at daily frequency to synchronise with crypto closes. • Bitcoin Price – By default the script forces a daily timeframe so that both series share time alignment, although you can disable that and plot the oscillator on intraday charts if you prefer. • User Source Flexibility – The BTC series is not hard-wired; you can select any exchange-specific symbol or even swap BTC for another crypto or risk asset whose interaction with the Fed rate you wish to study. 3. Math under the Hood (1) Rate of Change (ROC) – Both the Fed rate and BTC close are converted to percent return over a user-chosen lookback (default 30 bars). This means a cut from 5.25 percent to 5.00 percent feeds in as –4.76 percent, while a climb from 25 000 to 30 000 USD in BTC over the same window converts to +20 percent. (2) Divergence Construction – The script subtracts the Fed ROC from the BTC ROC. Positive values show BTC appreciating faster than policy is tightening (or falling slower than the rate is cutting); negative values show the opposite. (3) Optional Smoothing – Macro series are noisy. Toggle “Apply Smoothing” to calm the line with your preferred moving-average flavour: SMA, EMA, DEMA, TEMA, RMA, WMA or Hull. The default EMA-25 removes day-to-day whips while keeping turning points alive. (4) Dynamic Colour Mapping – Rather than using a single hue, the oscillator line employs a gradient where deep greens represent strong bullish divergence and dark reds flag sharp bearish divergence. This heat-map approach lets you gauge intensity without squinting at numbers. (5) Threshold Grid – Five horizontal guides create a structured regime map: • Lower Extreme (–50 pct) and Upper Extreme (+50 pct) identify panic capitulations and euphoria blow-offs. • Oversold (–20 pct) and Overbought (+20 pct) act as early warning alarms. • Zero Line demarcates neutral alignment. 4. Chart Furniture and User Interface • Oscillator fill with a secondary DEMA-30 “shader” offers depth perception: fat ribbons often precede high-volatility macro shifts. • Optional bar-colouring paints candles green when the oscillator is above zero and red below, handy for visual correlation. • Background tints when the line breaches extreme zones, making macro inflection weeks pop out in the replay bar. • Everything—line width, thresholds, colours—can be customised so the indicator blends into any template. 5. Interpretation Guide Macro Liquidity Pulse • When the oscillator spends weeks above +20 while the Fed is still raising rates, Bitcoin is signalling liquidity tolerance or an anticipatory pivot view. That condition often marks the embryonic phase of major bull cycles (e.g., March 2020 rebound). • Sustained prints below –20 while the Fed is already dovish indicate risk aversion or idiosyncratic crypto stress—think exchange scandals or broad flight to safety. Regime Transition Signals • Bullish cross through zero after a long sub-zero stint shows Bitcoin regaining upward escape velocity versus policy. • Bearish cross under zero during a hiking cycle tells you monetary tightening has finally started to bite. Momentum Exhaustion and Mean-Reversion • Touches of +50 (or –50) come rarely; they are statistically stretched events. Fade strategies either taking profits or hedging have historically enjoyed positive expectancy. • Inside-bar candlestick patterns or lower-timeframe bearish engulfings simultaneously with an extreme overbought print make high-probability short scalp setups, especially near weekly resistance. The same logic mirrors for oversold. Pair Trading / Relative Value • Combine the oscillator with spreads like BTC versus Nasdaq 100. When both the FED Divergence oscillator and the BTC–NDQ relative-strength line roll south together, the cross-asset confirmation amplifies conviction in a mean-reversion short. • Swap BTC for miners, altcoins or high-beta equities to test who is the divergence leader. Event-Driven Tactics • FOMC days: plot the oscillator on an hourly chart (disable ‘Force Daily TF’). Watch for micro-structural spikes that resolve in the first hour after the statement; rapid flips across zero can front-run post-FOMC swings. • CPI and NFP prints: extremes reached into the release often mean positioning is one-sided. A reversion toward neutral in the first 24 hours is common. 6. Alerts Suite Pre-bundled conditions let you automate workflows: • Bullish / Bearish zero crosses – queue spot or futures entries. • Standard OB / OS – notify for first contact with actionable zones. • Extreme OB / OS – prime time to review hedges, take profits or build contrarian swing positions. 7. Parameter Playground • Shorten ROC Lookback to 14 for tactical traders; lengthen to 90 for macro investors. • Raise extreme thresholds (for example ±80) when plotting on altcoins that exhibit higher volatility than BTC. • Try HMA smoothing for responsive yet smooth curves on intraday charts. • Colour-blind users can easily swap bull and bear palette selections for preferred contrasts. 8. Limitations and Best Practices • The Fed Funds series is step-wise; it only changes on meeting days. Rapid BTC oscillations in between may dominate the calculation. Keep that perspective when interpreting very high-frequency signals. • Divergence does not equal causation. Crypto-native catalysts (ETF approvals, hack headlines) can overwhelm macro links temporarily. • Use in conjunction with classical confirmation tools—order-flow footprints, market-profile ledges, or simple price action to avoid “pure-indicator” traps. 9. Final Thoughts The FEDFUNDS Rate Divergence Oscillator distills an entire macro narrative monetary policy versus risk sentiment into a single colourful heartbeat. It will not magically predict every pivot, yet it excels at framing market context, spotting stretches and timing regime changes. Treat it as a strategic compass rather than a tactical sniper scope, combine it with sound risk management and multi-factor confirmation, and you will possess a robust edge anchored in the world’s most influential interest-rate benchmark. Trade consciously, stay adaptive, and let the policy-price tension guide your roadmap.

Pine Script® indicator

Fibonacci Sequence Moving Average [BackQuant]Fibonacci Sequence Moving Average with Adaptive Oscillator 1. Overview The Fibonacci Sequence Moving Average indicator is a two‑part trading framework that combines a custom moving average built from the famous Fibonacci number set with a fully featured oscillator, normalisation engine and divergence suite. The moving average half delivers an adaptive trend line that respects natural market rhythms, while the oscillator half translates that trend information into a bounded momentum stream that is easy to read, easy to compare across assets and rich in confluence signals. Everything from weighting logic to colour palettes can be customised, so the tool comfortably fits scalpers zooming into one‑minute candles as well as position traders running multi‑month trend following campaigns. 2. Core Calculation Fibonacci periods – The default length array is 5, 8, 13, 21, 34. A single multiplier input lets you scale the whole family up or down without breaking the golden‑ratio spacing. For example a multiplier of 3 yields 15, 24, 39, 63, 102. Component averages – Each period is passed through Simple Moving Average logic to produce five baseline curves (ma1 through ma5). Weighting methods – You decide how those five values are blended: • Equal weighting treats every curve the same. • Linear weighting applies factors 1‑to‑5 so the slowest curve counts five times as much as the fastest. • Exponential weighting doubles each step for a fast‑reacting yet still smooth line. • Fibonacci weighting multiplies each curve by its own period value, honouring the spirit of ratio mathematics. Smoothing engine – The blended average is then smoothed a second time with your choice of SMA, EMA, DEMA, TEMA, RMA, WMA or HMA. A short smoothing length keeps the result lively, while longer lengths create institution‑grade glide paths that act like dynamic support and resistance. 3. Oscillator Construction Once the smoothed Fib MA is in place, the script generates a raw oscillator value in one of three flavours: • Distance – Percentage distance between price and the average. Great for mean‑reversion. • Momentum – Percentage change of the average itself. Ideal for trend acceleration studies. • Relative – Distance divided by Average True Range for volatility‑aware scaling. That raw series is pushed through a look‑back normaliser that rescales every reading into a fixed −100 to +100 window. The normalisation window defaults to 100 bars but can be tightened for fast markets or expanded to capture long regimes. 4. Visual Layer The oscillator line is gradient‑coloured from deep red through sky blue into bright green, so you can spot subtle momentum shifts with peripheral vision alone. There are four horizontal guide lines: Extreme Bear at −50, Bear Threshold at −20, Bull Threshold at +20 and Extreme Bull at +50. Soft fills above and below the thresholds reinforce the zones without cluttering the chart. The smoothed Fib MA can be plotted directly on price for immediate trend context, and each of the five component averages can be revealed for educational or research purposes. Optional bar‑painting mirrors oscillator polarity, tinting candles green when momentum is bullish and red when momentum is bearish. 5. Divergence Detection The script automatically looks for four classes of divergences between price pivots and oscillator pivots: Regular Bullish, signalling a possible bottom when price prints a lower low but the oscillator prints a higher low. Hidden Bullish, often a trend‑continuation cue when price makes a higher low while the oscillator slips to a lower low. Regular Bearish, marking potential tops when price carves a higher high yet the oscillator steps down. Hidden Bearish, hinting at ongoing downside when price posts a lower high while the oscillator pushes to a higher high. Each event is tagged with an ℝ or ℍ label at the oscillator pivot, colour‑coded for clarity. Look‑back distances for left and right pivots are fully adjustable so you can fine‑tune sensitivity. 6. Alerts Five ready‑to‑use alert conditions are included: • Bullish when the oscillator crosses above +20. • Bearish when it crosses below −20. • Extreme Bullish when it pops above +50. • Extreme Bearish when it dives below −50. • Zero Cross for momentum inflection. Attach any of these to TradingView notifications and stay updated without staring at charts. 7. Practical Applications Swing trading trend filter – Plot the smoothed Fib MA on daily candles and only trade in its direction. Enter on oscillator retracements to the 0 line. Intraday reversal scouting – On short‑term charts let Distance mode highlight overshoots beyond ±40, then fade those moves back to mean. Volatility breakout timing – Use Relative mode during earnings season or crypto news cycles to spot momentum surges that adjust for changing ATR. Divergence confirmation – Layer the oscillator beneath price structure to validate double bottoms, double tops and head‑and‑shoulders patterns. 8. Input Summary • Source, Fibonacci multiplier, weighting method, smoothing length and type • Oscillator calculation mode and normalisation look‑back • Divergence look‑back settings and signal length • Show or hide options for every visual element • Full colour and line width customisation 9. Best Practices Avoid using tiny multipliers on illiquid assets where the shortest Fibonacci window may drop under three bars. In strong trends reduce divergence sensitivity or you may see false counter‑trend flags. For portfolio scanning set oscillator to Momentum mode, hide thresholds and colour bars only, which turns the indicator into a heat‑map that quickly highlights leaders and laggards. 10. Final Notes The Fibonacci Sequence Moving Average indicator seeks to fuse the mathematical elegance of the golden ratio with modern signal‑processing techniques. It is not a standalone trading system, rather a multi‑purpose information layer that shines when combined with market structure, volume analysis and disciplined risk management. Always test parameters on historical data, be mindful of slippage and remember that past performance is never a guarantee of future results. Trade wisely and enjoy the harmony of Fibonacci mathematics in your technical toolkit.

Pine Script® indicator

Overheat Oscillator with Divergence Indicator Description The Overheat Oscillator with Divergence is an advanced technical indicator designed for the TradingView platform, assisting traders in identifying potential market reversal points by analyzing price momentum and volume, as well as detecting divergences. The indicator combines trend strength assessment with signal smoothing to provide clear indications of market overheat or oversold conditions. An optional divergence detection feature allows for the identification of discrepancies between price movement and the oscillator's value, which may signal upcoming trend changes. The indicator is displayed in a separate panel below the price chart and offers visual cues through a color gradient, horizontal reference lines, and a dynamic market sentiment table. Users can customize numerous parameters, such as calculation periods, sentiment thresholds, line colors, and visualization styles, making the indicator a versatile tool for various trading strategies. How the Indicator Works The indicator is based on the following key components: Oscillator Calculations The indicator analyzes price candles, assigning a score based on their nature. A bullish candle (when the closing price is higher than the opening price) receives a score of +1.0, while a bearish candle (when the closing price is lower than the opening price) receives a score of -1.0. This scoring reflects the strength of price movement over a given period. The score is modified by a volume multiplier (default: 2.0) if the candle's volume exceeds the volume's simple moving average (SMA, default: calculated over 20 candles). This ensures that candles with higher volume have a greater impact on the oscillator's value, better capturing significant market movements driven by increased trading activity. For example, a bullish candle with high volume may receive a score of +2.0 instead of +1.0, amplifying the bullish signal. The scores are summed over a specified number of candles (default: 20), normalized to a 0–100 range, and then smoothed using a simple moving average (SMA, default: 5 periods) to reduce noise and improve signal clarity. Color Gradient The oscillator's values are visualized using a color gradient that changes based on the oscillator's level: Green: Market cooldown (values below the Gradient Min threshold). Yellow: Neutral sentiment (values between Gradient Min and Gradient Yellow). Orange: Elevated activity (values between Gradient Yellow and Gradient Orange). Red: Market overheat (values above Gradient Orange). The color gradient is applied as the background in the oscillator panel, facilitating quick assessment of market sentiment. Reference Levels The indicator displays customizable horizontal lines for key thresholds (e.g., Overheat Threshold, Oversold Threshold, Gradient Min, Yellow, Orange, Max). These lines are visible only at the height of the last few oscillator candles, preventing chart clutter and helping users focus on current values. Users can also define three custom horizontal lines with selectable styles (solid, dotted, dashed) and colors. These lines serve as auxiliary tools, e.g., for marking personal support/resistance levels, but do not affect the oscillator's signals or background colors. Market Sentiment The indicator displays sentiment labels in a table located in the top-right corner of the panel, dynamically updating based on the oscillator's value: Cooled: Values below Gradient Yellow (default: 35). Neutral: Values between Gradient Yellow and Gradient Orange (default: 60). Excited: Values between Gradient Orange and Overheat Threshold (default: 70). Overheated: Values above Overheat Threshold (default: 70). The Overheat Threshold and Oversold Threshold are critical for displaying the "Overheated" and "Cooled" labels in the sentiment table, enabling users to quickly identify extreme market conditions. The labels update when key thresholds are crossed, and their colors match the oscillator's gradient. Divergence Detection The indicator offers optional detection of regular bullish and bearish divergences: Bullish Divergence: Occurs when the price forms a lower low, but the oscillator forms a higher low, suggesting a weakening downtrend. Bearish Divergence: Occurs when the price forms a higher high, but the oscillator forms a lower high, suggesting a weakening uptrend. Divergences are marked on the chart with labels ("Bull" for bullish, "Bear" for bearish) and lines indicating pivot points. They are calculated with a delay equal to the Lookback Right setting (default: 5 candles), meaning signals appear after pivot confirmation in the specified lookback period. The indicator also generates alerts for users when a divergence is detected. Indicator Settings Main Settings (SETTINGS) Period Length: Specifies the number of candles used for oscillator calculations (default: 20). Volume SMA Period: The period for the volume's simple moving average (default: 20). Volume Multiplier: Multiplier applied to candle scores when volume exceeds the average (default: 2.0). SMA Length: The period for smoothing the oscillator with a simple moving average (default: 5). Thresholds (THRESHOLDS) Overheat Threshold: Level indicating market overheat (default: 70). This value determines when the sentiment table displays the "Overheated" label, signaling a potential peak in an uptrend. Oversold Threshold: Level indicating market cooldown (default: 30). This value determines when the sentiment table displays the "Cooled" label, signaling a potential bottom in a downtrend. Gradient Min (Green): Lower threshold for the green gradient (default: 20). Gradient Yellow Threshold: Threshold for the yellow gradient (default: 35). Gradient Orange Threshold: Threshold for the orange gradient (default: 60). Gradient Max (Red): Upper threshold for the red gradient (default: 70). Visualization (VISUALIZATION) Signal Line Color: Color of the oscillator line (default: dark red, RGB(5, 0, 0)). Show Reference Lines: Enables/disables the display of threshold lines (default: enabled). Divergence Settings (DIVERGENCE SETTINGS) Calculate Divergence: Enables/disables divergence detection (default: disabled). Lookback Right: Number of candles back for pivot analysis (default: 5). Lookback Left: Number of candles to the left for pivot analysis (default: 5). Line Style (STYLE) Custom Line 1, 2, 3 Value: Levels for custom horizontal lines (default: 70, 50, 30). Custom Line 1, 2, 3 Color: Colors for custom lines (default: black, RGB(0, 0, 0)). Custom Line 1, 2, 3 Style: Line styles (solid, dotted, dashed; default: dashed, dotted, dashed). How to Use the Indicator Adding to the Chart Add the indicator to your TradingView chart by searching for "Overheat Oscillator with Divergence." Configure the settings according to your trading strategy. Signal Interpretation Overheated: Values above the Overheat Threshold (default: 70) in the sentiment table may indicate a potential uptrend peak. Cooled: Values below the Oversold Threshold (default: 30) in the sentiment table may suggest a potential downtrend bottom. Divergences: Bullish: Look for "Bull" labels on the chart, indicating potential upward reversals (calculated with a Lookback Right delay). Bearish: Look for "Bear" labels, indicating potential downward reversals (calculated with a Lookback Right delay). Customization Experiment with settings such as period length, volume multiplier, or gradient thresholds to tailor the indicator to your trading style (e.g., scalping, medium-term trading). Usage Examples Scalping: Set a shorter period (e.g., Period Length = 10, SMA Length = 3) and monitor rapid sentiment changes and divergences on lower timeframes (e.g., 5-minute charts). Medium-Term Trading: Use default settings or increase Period Length (e.g., 30) and SMA Length (e.g., 7) for more stable signals on hourly or daily charts. Reversal Detection: Enable divergence detection and observe "Bull" or "Bear" labels in conjunction with overheat/cooled levels in the sentiment table. Notes The indicator performs best when used in conjunction with other technical analysis tools, such as support/resistance lines, moving averages, or Fibonacci levels. Divergences may serve as early signals but do not always guarantee immediate trend reversals—confirmation with other indicators is recommended. Test different settings on historical data to find the optimal configuration for your chosen market and timeframe.

Pine Script® indicator

by Uncle_the_shooter

CandelaCharts - HTF Sweeps 📝 Overview This indicator lets you overlay a higher timeframe (HTF) onto your current chart, giving you a clearer view of broader market movements without switching timeframes. This indicator also detects liquidity sweeps and plots them on both the higher timeframe (HTF) and the current lower timeframe (LTF), helping traders clearly spot potential reversal points. It adds LTF dividers for better structure clarity, making it easier to align with HTF shifts and refine entry timing with greater precision. 📦 Features This indicator identifies price sweeps and their invalidations, helping traders spot potential liquidity grabs and failed breakout attempts. Overlay a configurable higher timeframe (HTF) on the current chart Detects and plots liquidity sweeps on both HTF and LTF Adds lower timeframe (LTF) dividers for improved structure clarity Ideal for ICT-style top-down analysis and precision entries without switching charts ⚙️ Settings Customize the indicator to suit your strategy. Alert options are also available, so you can stay informed when key market events are triggered. Timeframes: Select the higher timeframe (HTF) to overlay on your current chart. HTF Coloring: Customize the color scheme for HTF candles. HTF Offset: Space of HTF Candles and current chart. HTF Size: Adjust the size of HTF candles. HTF Labels: Toggle labels for HTF. LTF H/L Line: Show or hide high/low lines from the lower timeframe. LTF O/C Line: Display open/close lines from the lower timeframe. Sweep: Enable detection and plotting of liquidity sweeps. I-sweep: Toggle invalidated sweep detection. Alerts: Enable Sweep Formation or Invalidation alerts ⚡️ Showcase See the indicator applied in live market scenarios, illustrating how sweep detections and invalidations unfold on various charts. HTF Candles HTF Sweeps LTF Sweeps Invalidated Sweeps 🚨 Alerts This indicator includes built-in alert functionality to keep you informed of key market events in real time. It supports the following customizable alerts on TradingView: Sweep Detection: Notifies you when a price sweep is detected—either a liquidity sweep above recent highs or below recent lows. This can be a strong signal of potential reversals or liquidity grabs by larger market participants. Sweep Invalidation: Alerts you when a previously detected sweep becomes invalidated due to price action moving beyond a defined threshold. This helps traders stay adaptive and avoid acting on outdated signals. These alerts are fully integrated with TradingView’s native alert system, so you can receive notifications via app, email, or pop-up—ensuring you're always up to date, even when you're away from the chart. ⚠️ Disclaimer Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.

Pine Script® indicator

by CandelaCharts

Updated

TZanalyser TZanalyser (Trend Zone Monitor With Trend Strength, Volume Focus And -Events Markers) Before I used TrendZones to manage my portfolio I used Fibonacci Zone Oscillator as my favorite in the sub panel, accompanied with another subpanel indicator which I never published called IncliValue and also REVE Cohorts. TZanalyser inherits Ideas and code from all three of them: The visual and the idea of using a channel as the basis for an oscillator depicted as a histogram, is taken from the FibZone Oscillator. The idea of providing a number to evaluate the trend is taken from IncliValue. The idea to create a horizontal line which indicates high and low volume focus completed with markers for volume events, is taken from REVE-cohorts. These ideas are combined in one sleek visual called TZanalyser. TZ stand for TrendZones, because the histogram is based on it. The histogram. Depicted is the distance of the price from COG as percent. The distance between Upper Curve and Lower Curve is used as 100%. The values may reach between 300 and -300. The colors indicate in which zone the candle lives, blue in the blue zone, green in the green zone etc. Despite the absence of a gray zone, there are gray bars. These depict candles that wrap around COG. Because hl2 is used as price, some gray bars point up and others down. The orange and red bars point down because the orange and red downtrend zones are below COG. Use of the histogram. Sometimes I need to create a list of stocks which are in uptrend in monthly, weekly and daily charts from the stocks I follow in my universe. This job is done fast and easy by looking at the last bar of the histogram. The histogram also gives a quick evaluation of how the stock fared in the past. The number. Suppose I need to allocate some money to another stock, selected a few, looked into news and gurus and they look equally good. Then it is nice to be able to find out which has the best charts. Which one has the strongest uptrend. For this purpose this number can be consulted, because it indicates somehow the strength of the trend. It is an integer between 20 and -20, the closer to 20 the stronger the uptrend, closer to -20 indicates a stronger downtrend. The color of the background is the same as the last column of the histogram. Volume focus and events The horizontal lines depict volume focus, the line below the focus that comes with the uptrend columns pointing up, the one above the focus for the downtrend columns pointing down. Thes line have tree colors: maroon for high volume focus, green for normal volume and gray for low volume situations. Between the lines and the histogram triangles appear at volume events, a green triangle when the candle comes with high volume, i.e. 120-200 percent of normal, maroon when extreme volume, i.e. more than 200 percent of normal. The direction of these triangles is that of the histogram, i.e. when the price is higher, direction is up and vice versa. Take care and have fun.

Pine Script® indicator

Updated

Liquidity Break Probability [PhenLabs]📊 Liquidity Break Probability Version: PineScript™ v6 The Liquidity Break Probability indicator revolutionizes how traders approach liquidity levels by providing real-time probability calculations for level breaks. This advanced indicator combines sophisticated market analysis with machine learning inspired probability models to predict the likelihood of high/low breaks before they happen. Unlike traditional liquidity indicators that simply draw lines, LBP analyzes market structure, volume profiles, momentum, volatility, and sentiment to generate dynamic break probabilities ranging from 5% to 95%. This gives traders unprecedented insight into which levels are most likely to hold or break, enabling more confident trading decisions. 🚀 Points of Innovation Advanced 6-factor probability model weighing market structure, volatility, volume, momentum, patterns, and sentiment Real-time probability updates that adjust as market conditions change Intelligent trading style presets (Scalping, Day Trading, Swing Trading) with optimized parameters Dynamic color-coded probability labels showing break likelihood percentages Professional tiered input system - from quick setup to expert-level customization Smart volume filtering that only highlights levels with significant institutional interest 🔧 Core Components Market Structure Analysis: Evaluates trend alignment, level strength, and momentum buildup using EMA crossovers and price action Volatility Engine: Incorporates ATR expansion, Bollinger Band positioning, and price distance calculations Volume Profile System: Analyzes current volume strength, smart money proxies, and level creation volume ratios Momentum Calculator: Combines RSI positioning, MACD strength, and momentum divergence detection Pattern Recognition: Identifies reversal patterns (doji, hammer, engulfing) near key levels Sentiment Analysis: Processes fear/greed indicators and market breadth measurements 🔥 Key Features Dynamic Probability Labels: Real-time percentage displays showing break probability with color coding (red >70%, orange >50%, white <50%) Trading Style Optimization: One-click presets automatically configure sensitivity and parameters for your trading timeframe Professional Dashboard: Live market state monitoring with nearest level tracking and active level counts Smart Alert System: Customizable proximity alerts and high-probability break notifications Advanced Level Management: Intelligent line cleanup and historical analysis options Volume-Validated Levels: Only displays levels backed by significant volume for institutional-grade analysis 🎨 Visualization Recent Low Lines: Red lines marking validated support levels with probability percentages Recent High Lines: Blue lines showing resistance zones with break likelihood indicators Probability Labels: Color-coded percentage labels that update in real-time Professional Dashboard: Customizable panel showing market state, active levels, and current price Clean Display Modes: Toggle between active-only view for clean charts or historical view for analysis 📖 Usage Guidelines Quick Setup Trading Style Preset Default: Day Trading Options: Scalping, Day Trading, Swing Trading, Custom Description: Automatically optimizes all parameters for your preferred trading timeframe and style Show Break Probability % Default: True Description: Displays percentage labels next to each level showing break probability Line Display Default: Active Only Options: Active Only, All Levels Description: Choose between clean active-only view or comprehensive historical analysis Level Detection Settings Level Sensitivity Default: 5 Range: 1-20 Description: Lower values show more levels (sensitive), higher values show fewer levels (selective) Volume Filter Strength Default: 2.0 Range: 0.5-5.0 Description: Controls minimum volume threshold for level validation Advanced Probability Model Market Trend Influence Default: 25% Range: 0-50% Description: Weight given to overall market trend in probability calculations Volume Influence Default: 20% Range: 0-50% Description: Impact of volume analysis on break probability ✅ Best Use Cases Identifying high-probability breakout setups before they occur Determining optimal entry and exit points near key levels Risk management through probability-based position sizing Confluence trading when multiple high-probability levels align Scalping opportunities at levels with low break probability Swing trading setups using high-probability level breaks ⚠️ Limitations Probability calculations are estimations based on historical patterns and current market conditions High-probability setups do not guarantee successful trades - risk management is essential Performance may vary significantly across different market conditions and asset classes Requires understanding of support/resistance concepts and probability-based trading Best used in conjunction with other analysis methods and proper risk management 💡 What Makes This Unique Probability-Based Approach: First indicator to provide quantitative break probabilities rather than simple S/R lines Multi-Factor Analysis: Combines 6 different market factors into a comprehensive probability model Adaptive Intelligence: Probabilities update in real-time as market conditions change Professional Interface: Tiered input system from beginner-friendly to expert-level customization Institutional-Grade Filtering: Volume validation ensures only significant levels are displayed 🔬 How It Works 1. Level Detection: Identifies pivot highs and lows using configurable sensitivity settings Validates levels with volume analysis to ensure institutional significance 2. Probability Calculation: Analyzes 6 key market factors: structure, volatility, volume, momentum, patterns, sentiment Applies weighted scoring system based on user-defined factor importance Generates probability score from 5% to 95% for each level 3. Real-Time Updates: Continuously monitors price action and market conditions Updates probability calculations as new data becomes available Adjusts for level touches and changing market dynamics 💡 Note: This indicator works best on timeframes from 1-minute to 4-hour charts. For optimal results, combine with proper risk management and consider multiple timeframe analysis. The probability calculations are most accurate in trending markets with normal to high volatility conditions.

Pine Script® indicator

Logarithmic Moving Average (LMA) [QuantAlgo]🟢 Overview The Logarithmic Moving Average (LMA) uses advanced logarithmic weighting to create a dynamic trend-following indicator that prioritizes recent price action while maintaining statistical significance. Unlike traditional moving averages that use linear or exponential weights, this indicator employs logarithmic decay functions to create a more sophisticated price averaging system that adapts to market volatility and momentum conditions. The indicator displays a smoothed signal line that oscillates around zero, with positive values indicating bullish momentum and negative values indicating bearish momentum. The signal incorporates trend quality assessment, momentum confirmation, and multiple filtering mechanisms to help traders and investors identify trend continuation and reversal opportunities across different timeframes and asset classes. 🟢 How It Works The indicator's core innovation lies in its logarithmic weighting system, where weights are calculated using the formula: w = 1.0 / math.pow(math.log(i + steepness), 2) The steepness parameter controls how aggressively recent data is prioritized over historical data, creating a dynamic weight decay that can be fine-tuned for different trading styles. This logarithmic approach provides more nuanced weight distribution compared to exponential moving averages, offering better responsiveness while maintaining stability. The LMA calculation combines multiple sophisticated components. First, it calculates the logarithmic weighted average of closing prices. Then it measures the slope of this average over a 10-period lookback: lmaSlope = (lma - lma ) / lma * 100 The system also incorporates trend quality assessment using R-squared correlation analysis of log-transformed prices, measuring how well the price data fits a linear trend model over the specified period. The final signal generation uses the formula: signal = lmaSlope * (0.5 + rSquared * 0.5) which combines the LMA slope with trend quality weighting. When momentum confirmation is enabled, the indicator calculates annualized log-return momentum and applies a multiplier when the momentum direction aligns with the signal direction, strengthening confirmed signals while filtering out weak or counter-trend movements. 🟢 How to Use 1. Signal Interpretation and Threshold Zones Positive Values (Above Zero): LMA slope indicating bullish momentum with upward price trajectory relative to logarithmic baseline Negative Values (Below Zero): LMA slope indicating bearish momentum with downward price trajectory relative to logarithmic baseline Zero Line Crosses: Signal transitions between bullish and bearish regimes, indicating potential trend changes Long Entry Threshold Zone: Area above positive threshold (default 0.5) indicating confirmed bullish signals suitable for long positions Short Entry Threshold Zone: Area below negative threshold (default -0.5) indicating confirmed bearish signals suitable for short positions Extreme Values: Signals exceeding ±1.0 represent strong momentum conditions with higher probability of continuation 2. Momentum Confirmation and Visual Analysis Signal Color Intensity: Gradient coloring shows signal strength, with brighter colors indicating stronger momentum Bar Coloring: Optional price bar coloring matches signal direction for quick visual trend identification Position Labels: Real-time position classification (Bullish/Bearish/Neutral) displayed on the latest bar Momentum Weight Factor: When short-term log-return momentum aligns with LMA signal direction, the signal receives additional weight confirmation Trend Quality Component: R-squared values weight the signal strength, with higher correlation indicating more reliable trend conditions 3. Examples: Preconfigured Settings Default: Universally applicable configuration balanced for medium-term investing and general trading across multiple timeframes and asset classes. Scalping: Highly responsive setup with shorter period and higher steepness for ultra-short-term trades on 1-15 minute charts, optimized for quick momentum shifts. Swing Trading: Extended period with moderate steepness and increased smoothing for multi-day positions, designed to filter noise while capturing larger price swings on 1-4 hour and daily charts. Trend Following: Maximum smoothing with lower steepness for established trend identification, generating fewer but more reliable signals optimal for daily and weekly timeframes. Mean Reversion: Shorter period with high steepness for counter-trend strategies, more sensitive to extreme moves and reversal opportunities in ranging market conditions.

Pine Script® indicator

Intraday & Annual CAPM Alpha Intraday & Annual CAPM Alpha This TradingView™ Pine v6 indicator computes and plots a stock’s CAPM α (alpha) on both intraday and daily/annualized timeframes, allowing you to monitor relative performance against a chosen benchmark (e.g. SPX, NDX). ⸻ Key Outputs 1. Intraday α per Bar (blue line) • Calculates α from a rolling-window linear regression of the last N bars’ returns (default 60). • Expressed as “extra return per bar” vs. the benchmark. 2. Intraday α Daily-Equivalent (stepped blue line) • Scales the per-bar α to a full trading day (390 minutes), showing “if this pace held all day, outperformance (%)”. 3. Annualized α (yellow line) • Performs the same CAPM regression on daily returns over a D-day lookback (default 252), then annualizes α by multiplying by 252. • Indicates longer-term relative strength/weakness vs. the benchmark. ⸻ Inputs • Benchmark Symbol: Choose any index or ETF (e.g. “SPX”, “NDX”). • Intraday Lookback Bars: Number of bars for intraday α regression (default 60). • Daily Lookback Days: Number of trading days for daily CAPM regression (default 252). • Use Log Returns?: Toggle between arithmetic vs. log returns. ⸻ How to Use • Short-Term Signals: • Watch the blue α/bar line on 1–15 min charts. A cross from negative to positive suggests intraday outperformance; a reversal warns of weakening momentum. • The blue daily-equivalent α gives a smoother view—e.g. > +1% signals strong intraday bias, < –1% signals underperformance. • Long-Term Trends: • On daily charts, focus on the yellow annualized α. A sustained positive α implies this stock has historically beaten the benchmark; sustained negative α implies the opposite. • Combining Timeframes: • Use intraday α for timing entries/exits within the session, and annualized α to confirm whether you want a bullish or bearish bias over days to weeks. ⸻ Install & Configure 1. Copy the Pine v6 script into the TradingView Pine Editor. 2. Set your favorite benchmark, lookback periods, and returns type. 3. Add to your chart to start visualizing real-time CAPM α signals! Feel free to adjust the lookback windows and threshold levels to suit your trading style.

Pine Script® indicator

Rolling Z-Score Trend [QuantAlgo]🟢 Overview The Rolling Z-Score Trend measures how far the current price deviates from its rolling mean in terms of standard deviations. It transforms price data into standardized scores to identify overbought and oversold conditions while tracking momentum shifts. The indicator displays a Z-Score line showing price deviation from statistical norms, with background momentum columns showing the rate of change in these deviations. This helps traders and investors identify mean reversion opportunities and momentum shifts across different asset classes and timeframes. 🟢 How It Works The indicator uses the Z-Score formula: Z = (X - μ) / σ, where X is the current closing price, μ is the rolling mean, and σ is the rolling standard deviation over a user-defined lookback period. This creates a dynamic baseline that adapts to changing market conditions and standardizes price movements for interpretation across different assets and volatility conditions. The raw Z-Score undergoes 3-period EMA smoothing to reduce noise while maintaining responsiveness to market signals. Beyond the basic Z-Score calculation, the indicator measures the rate of change in Z-Score values between successive bars, displayed as background momentum columns. This momentum component shows acceleration and deceleration of statistical deviations. All calculations are processed through confirmation filters, displaying signals only on confirmed bars to reduce premature signals based on incomplete price action. 🟢 How to Use 1. Z-Score Interpretation and Threshold Zones Positive Values (Above Zero) : Price trading above statistical mean, suggesting bullish momentum or potential overbought conditions Negative Values (Below Zero) : Price trading below statistical mean, suggesting bearish momentum or potential oversold conditions Zero Line Crosses : Signal transitions between statistical regimes and potential trend changes Upper Threshold Zone : Area above entry threshold (default 1.5) indicating potential overbought conditions Lower Threshold Zone : Area below negative entry threshold (default -1.5) indicating potential oversold conditions Extreme Values (±2.0 or higher) : Statistically significant deviations that may indicate reversal opportunities 2. Momentum Background Analysis and Info Table Green Columns : Accelerating positive momentum in Z-Score values Red Columns : Accelerating negative momentum in Z-Score values Column Height : Magnitude of momentum change between bars Momentum Divergence : When columns contradict primary Z-Score direction, often signals impending reversals Info Table : Displays real-time numerical values for both Z-Score and momentum, including trend direction indicators and bar-to-bar change calculations for position management 3. Preconfigured Settings Default : Balanced performance across multiple timeframes and asset classes for general trading and medium-term position management. Scalping : Responsive setup for ultra-short-term trading on 1-15 minute charts with frequent signals and increased sensitivity to quick price movements. Swing Trading : Optimized for multi-day positions with noise filtering, focusing on larger price swings. Most effective on 1-4 hour and daily timeframes. Trend Following : Maximum smoothing that prioritizes established trends over short-term volatility. Generates fewer signals for daily and weekly charts.

Pine Script® indicator

Multi TF Oscillators Screener [TradingFinder] RSI / ATR / Stoch 🔵 Introduction The oscillator screener is designed to simplify multi-timeframe analysis by allowing traders and analysts to monitor one or multiple symbols across their preferred timeframes—all at the same time. Users can track a single symbol through various timeframes simultaneously or follow multiple symbols in selected intervals. This flexibility makes the tool highly effective for analyzing diverse markets concurrently. At the core of this screener lie two essential oscillators: RSI (Relative Strength Index) and the Stochastic Oscillator. The RSI measures the speed and magnitude of recent price movements and helps identify overbought or oversold conditions. It's one of the most reliable indicators for spotting potential reversals. The Stochastic Oscillator, on the other hand, compares the current price to recent highs and lows to detect momentum strength and potential trend shifts. It’s especially effective in identifying divergences and short-term reversal signals. In addition to these two primary indicators, the screener also displays helpful supplementary data such as the dominant candlestick type (Bullish, Bearish, or Doji), market volatility indicators like ATR and TR, and the four key OHLC prices (Open, High, Low, Close) for each symbol and timeframe. This combination of data gives users a comprehensive technical view and allows for quick, side-by-side comparison of symbols and timeframes. 🔵 How to Use This tool is built for users who want to view the behavior of a single symbol across several timeframes simultaneously. Instead of jumping between charts, users can quickly grasp the state of a symbol like gold or Bitcoin across the 15-minute, 1-hour, and daily timeframes at a glance. This is particularly useful for traders who rely on multi-timeframe confirmation to strengthen their analysis and decision-making. The tool also supports simultaneous monitoring of multiple symbols. Users can select and track various assets based on the timeframes that matter most to them. For example, if you’re looking for entry opportunities, the screener allows you to compare setups across several markets side by side—making it easier to choose the most favorable trade. Whether you’re a scalper focused on low timeframes or a swing trader using higher ones, the tool adapts to your workflow. The screener utilizes the widely-used RSI indicator, which ranges from 0 to 100 and highlights market exhaustion levels. Readings above 70 typically indicate potential pullbacks, while values below 30 may suggest bullish reversals. Viewing RSI across timeframes can reveal meaningful divergences or alignments that improve signal quality. Another key indicator in the screener is the Stochastic Oscillator, which analyzes the closing price relative to its recent high-low range. When the %K and %D lines converge and cross within the overbought or oversold zones, it often signals a momentum reversal. This oscillator is especially responsive in lower timeframes, making it ideal for spotting quick entries or exits. Beyond these oscillators, the table includes other valuable data such as candlestick type (bullish, bearish, or doji), volatility measures like ATR and TR, and complete OHLC pricing. This layered approach helps users understand both market momentum and structure at a glance. Ultimately, this screener allows analysts and traders to gain a full market overview with just one look—empowering faster, more informed, and lower-risk decision-making. It not only saves time but also enhances the precision and clarity of technical analysis. 🔵 Settings 🟣 Display Settings Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge. Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments. 🟣 Symbol Settings Each of the 10 symbol slots comes with a full set of customizable parameters : Enable Symbol : A checkbox to activate or hide each symbol from the table. Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.). Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D). RSI Length : Defines the period used in RSI calculation (default is 14). Stochastic Length : Sets the period for the Stochastic Oscillator. ATR Length : Sets the length used to calculate the Average True Range, a key volatility metric. 🔵 Conclusion By combining powerful oscillators like RSI and Stochastic with full customization over symbols and timeframes, this tool provides a fast, flexible solution for technical analysts. Users can instantly monitor one or several assets across multiple timeframes without opening separate charts. Individual configuration for each symbol, along with the inclusion of key metrics like candlestick type, ATR/TR, and OHLC prices, makes the tool suitable for a wide range of trading styles—from scalping to swing and position trading. In summary, this screener enables traders to gain a clear, high-level view of various markets in seconds and make quicker, smarter, and lower-risk decisions. It saves time, streamlines analysis, and boosts overall efficiency and confidence in trading strategies.

Pine Script® indicator

Yearly Performance Table with CAGR Overview This Pine Script indicator provides a clear table displaying the annual performance of an asset, along with two different average metrics: the arithmetic mean and the geometric mean (CAGR). Core Features Annual Performance Calculation: Automatically detects the first trading day of each calendar year. Calculates the percentage return for each full calendar year. Based on closing prices from the first to the last trading day of the respective year. Flexible Display: Adjustable Period: Displays data for 1-50 years (default: 10 years). Daily Timeframe Only: Functions exclusively on daily charts. Automatic Update: Always shows the latest available years. Two Average Metrics: AVG (Arithmetic Mean) A simple average of all annual returns. (Formula: (R₁ + R₂ + ... + Rₙ) ÷ n) Important: Can be misleading in the presence of volatile returns. GEO (Geometric Mean / CAGR) Compound Annual Growth Rate. (Formula: ^(1/n) - 1) Represents the true average annual growth rate. Fully accounts for the compounding effect. Limitations Daily Charts Only: Does not work on intraday or weekly/monthly timeframes. Calendar Year Basis: Calculations are based on calendar years, not rolling 12-month periods. Historical Data: Dependent on the availability of historical data from the broker/data provider. Interpretation of Results CAGR as Benchmark: The geometric mean is more suitable for performance comparisons. Annual Patterns: Individual year figures can reveal seasonal or cyclical trends.

Pine Script® indicator

HA Reversal Strategy Certainly! Here's a detailed **description (elaboration)** for the **"HA Candle Test"** (i.e., the Heikin Ashi strategy script I just gave you): --- ### 📌 **Script Name**: HA Candle Test ### 📖 **Description**: This script visualizes **Heikin Ashi candles** and identifies **trend reversal signals** using classic momentum candle behavior — particularly the appearance of **no-wick candles**, which are known to reflect strong directional pressure in Heikin Ashi charts. It aims to **capture high-probability trend reversals** with minimal noise, relying on the natural smoothing behavior of Heikin Ashi candles. --- ### ✅ **Buy Signal Conditions**: * At least **two consecutive red Heikin Ashi candles** (indicating a short-term downtrend). * Followed by a **green Heikin Ashi candle** that has **no lower wick** (i.e., open == low). * This suggests that **buyers have taken full control**, with no push from sellers — a potential start of an uptrend. 📍 **Interpreted as**: “Market was selling off, but now buyers stepped in strongly — time to consider buying.” --- ### ✅ **Sell Signal Conditions**: * At least **two consecutive green Heikin Ashi candles** (short-term uptrend). * Followed by a **red Heikin Ashi candle** that has **no upper wick** (i.e., open == high). * This implies **sellers are dominating**, with no attempt from buyers to push higher — possible start of a downtrend. 📍 **Interpreted as**: “Market was rallying, but sellers just took over decisively — time to consider selling.” --- ### 📊 **Visual Aids Included**: * Plots **Heikin Ashi candles** on your main chart for clarity. * Uses **Buy** and **Sell** label markers (green & red) at signal points. * Compatible with any timeframe — higher timeframes typically yield stronger signals. --- ### 💡 **Suggested Use**: * Combine with **support/resistance**, **volume**, or **trend filters** for more robust setups. * Works well on **1H, 4H, and Daily charts** in trending markets. * Can be used manually or turned into an automated strategy for backtesting or alerts. --- Would you like this script packaged as a **strategy()** for backtesting, or would you like me to add **alerts** so you can get notified in real-time when signals appear?

Pine Script® indicator

by HermioneGranger96

SBC Protfo SBC Portfo PNL Indicator Description The SBC Portfo PNL Indicator is a user-friendly tool designed for Hebrew-speaking traders to track the Profit and Loss (PNL) of their stock portfolios on TradingView charts. It supports up to 5 distinct portfolios, each capable of holding an unlimited number of stocks with unlimited buy commands, allowing real-time monitoring of portfolio performance. Key Features - Multi-Portfolio Support: Track up to 5 separate portfolios for different trading strategies or accounts. - Unlimited Stock Entries: Add unlimited stocks and buy commands per portfolio. - Detailed Buy Commands: Input for each stock: - Stock Ticker (e.g., AAPL, TSLA). - Buy Price (e.g., 150.25). - Buy Amount (e.g., 10). - Hebrew-Friendly Interface: Intuitive settings dialog with clear instructions in Hebrew. - Customizable PNL Tracking: Visualize PNL on charts with real-time updates based on market data. How to Use 1. Add the Indicator: - Go to the Indicators menu in TradingView and add the "SBC Portfo" PNL Indicator. 2. Configure Portfolios: - Open the indicator’s settings dialog. - For each portfolio (up to 5), enter data in the provided input fields using this format: PortfolioName:StockTicker:BuyPricexBuyAmount;StockTicker:BuyPricexBuyAmount Example: Portfolio1:AAPL:150.25x10;TSLA:266.72x5 - This represents a portfolio named "Portfolio1" with: - 10 shares of AAPL bought at $150.25. - 5 shares of TSLA bought at $266.72. - Repeat for additional portfolios (e.g., Portfolio2, Portfolio3). - Add multiple buy commands for the same stock if needed (e.g., AAPL:160.50x20). 3. Apply Settings: - Save settings to display PNL based on current market prices. 4. Monitor PNL: - View PNL for each portfolio on the chart via tables, labels, or graphical overlays (based on settings). Input Format Enter portfolio data manually in the settings dialog, one input field per portfolio: PortfolioName:StockTicker:BuyPricexBuyAmount;StockTicker:BuyPricexBuyAmount - PortfolioName: Unique name (e.g., Portfolio1, Growth). - StockTicker: Stock symbol (e.g., AAPL). - BuyPrice: Purchase price per share (e.g., 150.25). - BuyAmount: Number of shares (e.g., 10). - Use : to separate portfolio name, ticker, and buy data x to separate price and amount ; for multiple stocks in the portfolio Example: - Portfolio 1: GrowthPortfolio:AAPL:150.25x10;TSLA:266.72x5 - Portfolio 2: DividendPortfolio:KO:55.20x50;PG:145.30x30 Notes - Hebrew Support: Settings and labels are optimized for Hebrew users. - Manual Input: Enter portfolio data manually in the settings dialog using the correct format. - Compatibility: Works with any stock ticker supported by TradingView. תיאור אינדיקטור SBC Portfo PNL הוא כלי ידידותי למשתמש שתוכנן במיוחד עבור סוחרים דוברי עברית למעקב אחר רווח והפסד (PNL) של תיקי המניות שלהם ישירות בגרפים של TradingView. הוא תומך בעד 5 תיקים נפרדים, כאשר כל תיק יכול להכיל מספר בלתי מוגבל של מניות עם פקודות קנייה בלתי מוגבלות, ומאפשר מעקב בזמן אמת אחר ביצועי התיק. תכונות עיקריות - תמיכה בריבוי תיקים: מעקב אחר עד 5 תיקים נפרדים עבור אסטרטגיות מסחר או חשבונות שונים. - רישום מניות ללא הגבלה: הוספת מספר בלתי מוגבל של מניות ופקודות קנייה לכל תיק. - פקודות קנייה מפורטות: הזנת נתונים עבור כל מניה: - סימול המניה (למשל, AAPL, TSLA). - מחיר קנייה (למשל, 150.25). - כמות קנייה (למשל, 10). - ממשק ידידותי לעברית: חלונית הגדרות אינטואיטיבית עם הוראות ברורות בעברית. - מעקב PNL הניתן להתאמה: הצגת רווח והפסד בגרפים עם עדכונים בזמן אמת בהתבסס על נתוני השוק. כיצד להשתמש 1. הוספת האינדיקטור: - נווט לתפריט האינדיקטורים ב-TradingView והוסף את "SBC Portfo PNL Indicator". 2. הגדרת תיקים: - פתח את חלונית ההגדרות של האינדיקטור. - עבור כל תיק (עד 5), הזן נתונים בשדות המסופקים בפורמט הבא: PortfolioName:StockTicker:BuyPricexBuyAmount;StockTicker:BuyPricexBuyAmount לדוגמה: Portfolio1:AAPL:150.25x10;TSLA:266.72x5 שורה זו מייצגת תיק בשם "Portfolio1" עם: - 10 מניות של AAPL שנקנו ב-$150.25. - 5 מניות של TSLA שנקנו ב-$266.72. - חזור על התהליך עבור תיקים נוספים (למשל, Portfolio2, Portfolio3). - ניתן להוסיף פקודות קנייה מרובות לאותה מניה לפי הצורך (למשל, AAPL:160.50x20). 3. החלת ההגדרות: - שמור את ההגדרות להצגת ה-PNL בהתבסס על מחירי השוק הנוכחיים. 4. מעקב אחר PNL: - צפה ב-PNL עבור כל תיק בגרף באמצעות טבלאות, תוויות או שכבות גרפיות (בהתאם להגדרות). פורמט קלט הזן נתוני תיק ידנית בחלונית ההגדרות, שדה קלט אחד לכל תיק: PortfolioName:StockTicker:BuyPricexBuyAmount;StockTicker:BuyPricexBuyAmount PortfolioName: שם ייחודי (למשל, Portfolio1, Growth). StockTicker: סימול המניה (למשל, AAPL). BuyPrice: מחיר רכישה למניה (למשל, 150.25). BuyAmount: מספר המניות (למשל, 10). השתמש ב- : להפרדה בין שם התיק, סימול ונתוני קנייה x להפרדה בין מחיר וכמות ; להפרדה בין מניות מרובות דוגמה: - תיק 1: GrowthPortfolio:AAPL:150.25x10;TSLA:266.72x5 - תיק 2: DividendPortfolio:KO:55.20x50;PG:145.30x30 Release Notes Version 1.1 includes: - Calculations for extended hours (Pre-Market & After-Hours). - Option to display portfolio summary data for stocks not in the portfolio (enable via settings checkbox). - Table background for better visibility; click to bring table to the front. - Updated text strings (names, titles, tooltips). הערות תמיכה בעברית: ההגדרות והתוויות מותאמות למשתמשים דוברי עברית. הזנה ידנית: הזן נתוני תיק ידנית בחלונית ההגדרות תוך שימוש בפורמט הנכון. תאימות: עובד עם כל סימול מניה הנתמך על ידי TradingView. גרסה 1.1 מכילה: 1. חישובים כוללים שעות מסחר מורחבות (Pre-Market ו-After-Hours). 2. אפשרות להציג נתוני תיק כוללים עבור מניות שאינן בתיק (הפעל באמצעות תיבת סימון בהגדרות). 3. צבע רקע לטבלה לשיפור הנראות; לחיצה על הטבלה מביאה אותה לחזית. 4. תיקון נוסחים (שמות, כותרות, וטולטיפים).

Pine Script® indicator

by shay_private

Updated

11 22 33 44 55 66 77 88 99 1010 1111 1212 1313 1414 1515 1616 1717 1818 1919 2020 2121 2222 2323 2424 2525 2626 2727 2828 2929 3030 3131 3232 3333 3434 3535 3636 3737 3838 3939 4040 4141 4242

Select market data provided by ICE Data Services. Select reference data provided by FactSet. Copyright © 2026 FactSet Research Systems Inc.Copyright © 2026, American Bankers Association. CUSIP Database provided by FactSet Research Systems Inc. All rights reserved. SEC fillings and other documents provided by Quartr.© 2026 TradingView, Inc.

More than a product

Supercharts

Screeners

Stocks
ETFs
Bonds
Crypto coins
CEX pairs
DEX pairs
Pine

Heatmaps

Stocks
ETFs
Crypto

Calendars

Economic
Earnings
Dividends

More products

Yield Curves
Options
News Flow
Pine Script®

Apps

Mobile
Desktop

Community

Social network
Wall of Love
Refer a friend
House Rules
Moderators

Ideas

Trading
Education
Editors' picks

Pine Script

Indicators & strategies
Wizards
Freelancers

Tools & subscriptions

Features
Pricing
Market data
Gift plans

Trading

Overview
Brokers

Special offers

CME Group futures
Eurex futures
US stocks bundle

About company

Who we are
Space mission
Blog
Careers
Media kit

Merch

TradingView store
Tarot cards for traders
The C63 TradeTime

Policies & security

Terms of Use
Disclaimer
Privacy Policy
Cookies Policy
Accessibility Statement
Security tips
Bug Bounty program
Status page

Business solutions

Widgets
Charting libraries
Lightweight Charts™
Advanced Charts
Trading Platform

Growth opportunities

Advertising
Brokerage integration
Partner program
Education program

Community

Social network
Wall of Love
Refer a friend
House Rules
Moderators

Ideas

Trading
Education
Editors' picks

Pine Script

Indicators & strategies
Wizards
Freelancers

Business solutions

Widgets
Charting libraries
Lightweight Charts™
Advanced Charts
Trading Platform

Growth opportunities

Advertising
Brokerage integration
Partner program
Education program