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Top 40 Best Performing Nasdaq Stocks with Advanced Stats ScreenWelcome to the CustomQuantLabs Advanced Stats Screener. This dashboard is designed for traders who need more than just price action—it provides a comprehensive, institutional-grade view of the "Top 40" performing assets in the Nasdaq (or any watchlist of your choice) at a single glance. Instead of flipping through 40 different charts, this screener aggregates Performance Metrics and Advanced Statistical Risk Models into one clean, heatmap-style dashboard. It helps you instantly identify outliers, trend leaders, and potential mean-reversion setups. Key Features 1. Multi-Timeframe Performance Heatmap Instantly spot momentum. The dashboard tracks returns across 5 key timeframes, color-coded with a dynamic heatmap (Bright Green for leaders, Bright Red for laggards): Week% (Short-term momentum) Month% & Quarter% (Medium-term trend) 6M% & 12M% (Long-term secular trend) 2. Institutional Risk Metrics (Advanced Stats) We go beyond simple percentage changes. This screener calculates complex statistical formulas for every single ticker in real-time: Kelly Criterion (%): A money management formula used to determine optimal position size based on win probability and return ratio. A higher Kelly % suggests a statistically stronger "edge" based on recent history. Sharpe Ratio: Measures risk-adjusted return. How much return are you getting for every unit of risk? (Values > 1.0 are generally considered good). Sortino Ratio: Similar to Sharpe, but only penalizes downside volatility. This is crucial for distinguishing between "good volatility" (upside pumps) and "bad volatility" (crashes). Z-Score: A mean-reversion metric. It measures how many standard deviations the current price is from its 20-day mean. High Positive Z-Score (>2): Price may be overextended to the upside. Low Negative Z-Score (<-2): Price may be oversold. Volatility (%): A dynamic measure of the asset's daily range, helping you gauge the "personality" of the stock before entering. Customization & Settings Fully Customizable Watchlist: While pre-loaded with top Nasdaq performers (like NVDA, AMD, PLTR, MU), you can easily edit the "Symbols" input in the settings to track Crypto, Forex, or your own custom stock portfolio. Smart Theme Detection: Includes a toggle for Dark Mode (ProjectSyndicate style) and Light Mode (Clean white style). Compact Mode: You can toggle specific columns on or off to fit the table on smaller screens. How to Use Add the script to your chart. Open Settings (Gear Icon). Paste your list of 40 tickers into the "Ticker List" text area (separated by commas). Use the Z-Score to find overbought/oversold setups and the Relative Strength (Week/Month) to find breakout candidates. Disclaimer: This tool is for informational purposes only. The "Top 40" list requires manual updating if the market leaders change. All statistical metrics (Kelly, Sharpe, etc.) are based on historical data and do not guarantee future performance. Built by CustomQuantLabs.
אינדיקטור Pine Script®
מאת ‎CustomQuantLabs‎
Distance from SMA DisplayThis indicator shows the percentage distance of the price from a selected SMA (e.g., SMA 20) and uses a red or green emoji to indicate whether the price is above or below that SMA. This makes it easier to spot stocks that are far below the SMA for potential long setups, or far above it for potential short setups. In other words, it provides a quick visual way to identify overextended or underextended price conditions relative to the chosen moving average. In addition, the indicator can display the percentage distance from the daily SMA 150, which is commonly used to determine the broader trend direction. The main purpose of this is to quickly see whether the higher-timeframe trend is bullish (price above the daily SMA 150) or bearish (price below it), helping traders align short-term opportunities with the overall market trend.
אינדיקטור Pine Script®
מאת ‎ItamarE7237‎
Daily & Weekly Levels (Sticky + Individual Alerts)🚀 Sticky Levels: PDH/PDL & Weekly High/Low 💡 Overview This lightweight Pine Script v6 utility is designed for high-frequency traders and scalpers who require key Daily and Weekly levels without cluttering their price action. Optimized for speed and clarity, it ensures your most important S/R zones are always exactly where you need them. 🌟 Key Features 📌 Sticky Right Alignment – Labels are anchored to the right price scale using a customizable offset. They stay perfectly visible on mobile devices (Android/iOS) regardless of zoom level or scrolling. ⚡ Performance Optimized – Specifically built for low timeframes (15s, 1m, 5m). By using barstate.islast and tuple-based request.security calls, it ensures zero lag and minimal resource usage. 📅 Daily Levels – Instantly plot Previous Day High (PDH) and Previous Day Low (PDL). 🗓️ Weekly Levels – Monitor Previous Week High (PWH), Previous Week Low (PWL), and Current Weekly Open (WO). 🔔 Individual Alert Management – Granular control over notifications. You can manually enable/disable alerts for each specific level to avoid "alert fatigue." 💎 Clean Visuals – Uses elegant dashed lines and non-intrusive labels with an optional price display for pinpoint accuracy. 🛠️ How to Customize Your Setup 1. Visibility & Visuals Toggle Levels: Turn each level on or off independently in the settings. Label Offset: Adjust the "3cm" margin by changing the bar offset to fit your screen perfectly. Price Toggle: Show or hide exact price values next to the labels. 2. Individual Alert Toggles In the settings menu, you will find a 🔔 icon next to each level. You can manually choose which specific levels should trigger a notification: Enable PDH alerts for breakout trades. Keep Weekly Open alerts off if you only use it as a visual bias. Focus only on what matters for your strategy! ❓ Why use this script? Standard horizontal lines often disappear when you scroll back in time or clutter the immediate price action on lower timeframes. This script solves that by keeping labels fixed at the right margin, providing a professional trading interface similar to high-end institutional platforms. Whether you are at your desk or trading on the go, your key levels remain clear and "sticky." 🚦 Quick Setup Guide Add to Chart: Save the script and add it to your favorite symbols. Configure: Open settings and check the "Alert" box for your desired levels. Create Alert: Press Alt+A, set Condition to this indicator, and select "Any alert() function call". Trade: Receive precise, non-spammy notifications directly to your phone or desktop.
אינדיקטור Pine Script®
מאת ‎Notemptyone‎
cephxs / New X Opening Gaps [Pro +]NWOG & NDOG - OPENING GAPS Smart Gap Detection with Intelligent Filtering Visualizes New Week Opening Gaps (NWOGs) and New Day Opening Gaps (NDOGs) with built-in intelligence to show you only what matters. No more cluttered charts with gaps from 3 months ago that price will never revisit. THE PROBLEM WITH GAP INDICATORS Most gap indicators dump every single gap on your chart and call it a day. You end up with 50 boxes cluttering your screen, half of which are miles away from current price and the other half are so tiny they're basically noise. This one's different and I explain why below. SMART FILTERING (THE GOOD STUFF) Two filters work together to keep your chart clean: Size Filter: Uses ATR-based detection to filter out insignificant gaps, dynamic with less volatile time periods - Filter None: Show everything (if you really want chaos) - Filter Insignificant: Hide the micro-gaps that don't matter - Juicy Gaps Only: Only show gaps worth paying attention to Distance Filter: Only displays gaps within range of current price - Really Close: 0.5 ATR - tight focus on immediate levels - Balanced: 1 ATR - sweet spot for most traders - Slightly Far: 3 ATR - wider view for swing traders Cleanup Interval: Controls how quickly out-of-range gaps disappear - Immediately: Gaps hide/show every bar as price moves - 5 / 15 / 30 Minutes: Gaps only update visibility at interval boundaries - reduces visual noise during choppy price action The magic: gaps appear and disappear as price moves toward or away from them. Old gaps that price has left behind fade out, and gaps that become relevant fade back in. Use delayed cleanup intervals if you want gaps to "stick around" a bit longer before disappearing. GAP TYPES EXPLAINED New Week Opening Gaps (NWOGs): The gap between Friday's close and Monday's open. These form over the weekend when markets are closed and often act as significant support/resistance. Two classifications: Void Gaps: Gap direction aligns with Friday's candle direction (continuation) Overlap Gaps: Gap direction conflicts with Friday's candle (potential reversal) New Day Opening Gaps (NDOGs): The gap between one day's close and the next day's open. Smaller but frequent - useful for intraday traders looking for fill targets. FEATURES Automatic Week/Day Detection: Handles forex (17:00 ET open) and futures (18:00 ET open) correctly DST-Aware: Uses New York timezone with automatic daylight saving adjustments 50% Equilibrium Line: Marks the midpoint of each gap - key level for entries Days Ago Labels: Shows how old each gap is at a glance Extension Modes: Choose between live-extending boxes or fixed-width boxes Separate Color Schemes: Different colors for void vs overlap NWOGs, bullish vs bearish NDOGs INPUTS NWOG Display Show NWOGs: Master toggle Extension Mode: "Extend Live" or "Extend to Week Close" Maximum NWOGs: Limit displayed gaps (1-50) Show Void/Overlap Gaps: Toggle each type independently Show NWOG Labels: Toggle gap labels NDOG Display Show NDOGs: Master toggle Extension Mode: "Extend Live" or "Extend to Day Close" Maximum NDOGs: Limit displayed gaps (1-50) Show NDOG Labels: Toggle gap labels Filter Settings Size Filter: Filter None / Filter Insignificant / Juicy Gaps Only Only Show Near Price: Enable/disable distance filtering Distance Filter: Really Close / Balanced / Slightly Far Cleanup Interval: Immediately / 5 Minutes / 15 Minutes / 30 Minutes - controls how often gaps update visibility ATR Period: Period for ATR calculation (default: 14) Right Edge Offset: How many bars ahead boxes extend Styling Box Transparency: Fill and border opacity Midline Style: Solid / Dotted / Dashed Label Style: Simple ("NWOG, 5d ago") or Descriptive ("NWOG (Void Bull), 5d ago") Label Size: Tiny / Small / Normal / Large RECOMMENDED SETTINGS For intraday (1m-15m): Size Filter: Filter Insignificant Distance Filter: Really Close or Balanced Show NDOGs: On Maximum NDOGs: 5-10 For swing trading (1H-4H): Size Filter: Juicy Gaps Only Distance Filter: Balanced or Slightly Far Show NWOGs: On Maximum NWOGs: 10-20 TIMEFRAME NOTES Works on daily timeframe and below. Above daily, the indicator disables itself since NWOG/NDOG gap detection requires daily open/close data. ASSET SUPPORT Automatically handles different market open times: Forex: Week opens Sunday 17:00 ET, closes Friday 17:00 ET Futures: Week opens Sunday 18:00 ET, closes Friday 16:15 ET Stocks/Other: Uses session-based detection FAQ Why do gaps appear and disappear? That's the distance filter working. As price moves, gaps that were far away become relevant and appear. Gaps that price leaves behind disappear. This keeps your chart focused on actionable levels. What's the difference between void and overlap gaps? Void gaps continue Friday's direction (trend continuation). Overlap gaps conflict with Friday's direction (potential reversal setup). Different traders prefer different types. Why can't I see any gaps? Check your filter settings. "Juicy Gaps Only" with "Really Close" distance filter is very selective. Try "Filter Insignificant" with "Balanced" for more gaps. DISCLAIMER This indicator is for educational purposes only. Opening gaps are one tool among many - they don't guarantee fills or reversals. Always use proper risk management and never trade based on a single indicator. Past gap fills don't guarantee future performance. Do your own analysis. CHANGELOG Pro +: Added smart size/distance filtering, void/overlap classification, NDOG support, DST-aware timezone handling Base: Initial NWOG visualization Made with ❤️ by fstarlabs
אינדיקטור Pine Script®
מאת ‎fstarcapital‎
1
multiple SMAs (up to 5)This indicator lets you display up to five separate Simple Moving Averages (SMAs) in a single script. Each SMA can be independently enabled, disabled, resized, and recolored, allowing full control over how your chart looks—without needing multiple indicators. Benefits Saves screen space: Instead of loading 5 different SMA indicators, everything is organized into one tool. Ideal for free TradingView users: Lets you use multiple SMAs without consuming several indicator slots, which is helpful if you’re limited to only a few indicators at once. Quick visual analysis: Multiple SMAs make it easier to spot trend strength, crossovers, and dynamic support/resistance levels. Customization Turn each SMA on or off Adjust length (period) Change color Change line size Apply to any source (close, open, etc.)
אינדיקטור Pine Script®
מאת ‎ItamarE7237‎
FCF Yield - cristianhkrThis indicator is a fundamental valuation tool that calculates Free Cash Flow Yield in real-time. Unlike standard indicators, this script solves the data gap for European companies reporting semi-annually and allows for short-term projections. What is FCF Yield? It is the real "interest rate" a company generates relative to its current market price. Formula: FCF Yield = (Free Cash Flow / Market Cap) * 100 Key Features: Timeframe Flexibility: Switch between TTM (Trailing Twelve Months), FY (Fiscal Year), and FQ (Fiscal Quarter). Smart Fallback System: Essential for European stocks. If you select "Quarter" for a company that only reports semi-annually (like many European ones: Adidas, LVMH, Pluxee), the script automatically detects and uses the Semi-Annual (FH) data instead of showing an error. Projection/Annualization: Option to annualize short-term data (multiplies Quarters x4 or Semi-Annuals x2) to estimate annual yield based on the last report. Intuitive Visualization: Green area for positive cash generation and red for cash burn. Interpretation Guide (Fundamental): 5%: Generally indicates an attractive valuation (the company generates significant cash relative to its price). < 2%: The company might be overvalued or is a high-growth company reinvesting everything. Negative: The company is burning cash (liquidity risk or early expansion phase).
אינדיקטור Pine Script®
מאת ‎cristianhkr‎
Target Ladder Elite - Median + ATR Active TargetsTarget Ladder Elite — Median + ATR Active Targets is a lightweight price-target framework that uses a median moving average as a central anchor and ATR volatility bands to define realistic upper and lower target zones. Instead of predicting direction, this tool is designed to provide structured, volatility-aware reference levels that traders can use for planning, risk framing, and journaling. The script displays: A central “median” line (EMA by default) Optional upper/lower ATR bands A single “Active Target” label that updates on the last bar “HIT” markers when price reaches the selected target band under simple context conditions What it does Median Anchor (Trend/Centerline) A short moving average is used as the median reference line. This can help traders see whether price is trading above or below its current median. ATR Target Bands (Volatility Range) ATR (Average True Range) is used to measure volatility, and the script plots: Upper Band = Median + (ATR × Multiplier) Lower Band = Median − (ATR × Multiplier) These bands represent a volatility-based “reach” range rather than a guaranteed destination. Active Target (Last Bar Only) The script highlights one band as the “Active Target”: Auto mode: If price is above the median → upper band becomes active If price is below the median → lower band becomes active Or the user can force Upper or Lower. HIT Detection (Touch Confirmation) A “HIT” label prints when price reaches the band under a simple context filter: Upper HIT: price touches/exceeds the upper band while closing above the median Lower HIT: price touches/exceeds the lower band while closing below the median This is meant as a visual confirmation that a volatility target was reached, not a trading signal by itself. How it works (calculation detail) Median = EMA(Source, Median Length) ATR = ATR(ATR Length) Upper = Median + ATR × Multiplier Lower = Median − ATR × Multiplier The “Active Target” is selected based on your Active Target Side setting, then displayed as a label on the most recent bar. How to use it Common use cases: Planning target zones: Use upper/lower bands as potential volatility reach levels for the current market regime. Risk framing: Combine the median and bands with your preferred stop/structure rules to evaluate whether a move is extended or compressed. Trend context: In Auto mode, the active band is chosen based on where price is trading relative to the median. Journaling: HIT labels can help record when price reaches a volatility-defined objective. Suggested starting settings: Median Length: 4 ATR Length: 4 ATR Multiplier: .05–2.0 (adjust based on timeframe and asset volatility) Notes & limitations The bands are volatility references, not predictions. The “Active Target” selection in Auto mode is a simple median-based context rule. HIT markers indicate a band was reached under the defined conditions; they are not buy/sell commands. Best used alongside structure and risk management. This script is for educational and informational purposes only and does not constitute financial advice. Markets carry risk; always use appropriate confirmation and risk management.
אינדיקטור Pine Script®
מאת ‎Dinjin‎
Asset Drift ModelThis Asset Drift Model is a statistical tool designed to detect whether an asset exhibits a systematic directional tendency in its historical returns. Unlike traditional momentum indicators that react to price movements, this indicator performs a formal hypothesis test to determine if the observed drift is statistically significant, economically meaningful, and structurally stable across time. The result is a classification that helps traders understand whether historical evidence supports a directional bias in the asset. The core question the indicator answers is simple: Has this asset shown a reliable tendency to move in one direction over the past three years, and is that tendency strong enough to matter? What is drift and why does it matter In financial economics, drift refers to the expected rate of return of an asset over time. The concept originates from the geometric Brownian motion model, which describes asset prices as following a random walk with an added drift component (Black and Scholes, 1973). If drift is zero, price movements are purely random. If drift is positive, the asset tends to appreciate over time. If negative, it tends to depreciate. The existence of drift has profound implications for trading strategy. Eugene Fama's Efficient Market Hypothesis (Fama, 1970) suggests that in efficient markets, risk-adjusted drift should be minimal because prices already reflect all available information. However, decades of empirical research have documented persistent anomalies. Jegadeesh and Titman (1993) demonstrated that stocks with positive past returns continue to outperform, a phenomenon known as momentum. DeBondt and Thaler (1985) found evidence of long-term mean reversion. These findings suggest that drift is not constant and can vary across assets and time periods. For practitioners, understanding drift is fundamental. A positive drift implies that long positions have a statistical edge over time. A negative drift suggests short positions may be advantageous. No detectable drift means the asset behaves more like a random walk, where directional strategies have no inherent advantage. How professionals use drift analysis Institutional investors and hedge funds have long incorporated drift analysis into their systematic strategies. Quantitative funds typically estimate drift as part of their alpha generation process, using it to tilt portfolios toward assets with favorable expected returns (Grinold and Kahn, 2000). The challenge lies not in calculating drift but in determining whether observed drift is genuine or merely statistical noise. A naive approach might conclude that any positive average return indicates positive drift. However, financial returns are noisy, and short samples can produce misleading estimates. This is why professional quants rely on formal statistical inference. The standard approach involves testing the null hypothesis that expected returns equal zero against the alternative that they differ from zero. The test statistic is typically a t-ratio: the sample mean divided by its standard error. However, financial returns often exhibit serial correlation and heteroskedasticity, which invalidate simple standard errors. To address this, practitioners use heteroskedasticity and autocorrelation consistent standard errors, commonly known as HAC or Newey-West standard errors (Newey and West, 1987). Beyond statistical significance, professional investors also consider economic significance. A statistically significant drift of 0.5 percent annually may not justify trading costs. Conversely, a large drift that fails to reach statistical significance due to high volatility may still inform portfolio construction. The most robust conclusions require both statistical and economic thresholds to be met. Methodology The Asset Drift Model implements a rigorous inference framework designed to minimize false positives while detecting genuine drift. Return calculation The indicator uses logarithmic returns over non-overlapping 60-day periods. Non-overlapping returns are essential because overlapping returns introduce artificial autocorrelation that biases variance estimates (Richardson and Stock, 1989). Using 60-day horizons rather than daily returns reduces noise and captures medium-term drift relevant for position traders. The sample window spans 756 trading days, approximately three years of data. This provides 12 independent observations for the full sample and 6 observations per half-sample for structural stability testing. Statistical inference The indicator calculates the t-statistic for the null hypothesis that mean returns equal zero. To account for potential residual autocorrelation, it applies a simplified HAC correction with one lag, appropriate for non-overlapping returns where autocorrelation is minimal by construction. Statistical significance requires the absolute t-statistic to exceed 2.0, corresponding to approximately 95 percent confidence. This threshold follows conventional practice in financial econometrics (Campbell, Lo, and MacKinlay, 1997). Power analysis A critical but often overlooked aspect of hypothesis testing is statistical power: the probability of detecting drift when it exists. With small samples, even substantial drift may fail to reach significance due to high standard errors. The indicator calculates the minimum detectable effect at 95 percent confidence and requires observed drift to exceed this threshold. This prevents classifying assets as having no drift when the test simply lacks power to detect it. Robustness checks The indicator applies multiple robustness checks before classifying drift as genuine. First, the sign test examines whether the proportion of positive returns differs significantly from 50 percent. This non-parametric test is robust to distributional assumptions and verifies that the mean is not driven by outliers. Second, mean-median agreement ensures that the mean and median returns share the same sign. Divergence indicates skewness that could distort inference. Third, structural stability splits the sample into two halves and requires consistent signs of both means and t-statistics across sub-periods. This addresses the concern that drift may be an artifact of a specific regime rather than a persistent characteristic (Andrews, 1993). Fourth, the variance ratio test detects mean-reverting behavior. Lo and MacKinlay (1988) showed that if returns follow a random walk, the variance of multi-period returns should scale linearly with the horizon. A variance ratio significantly below one indicates mean reversion, which contradicts persistent drift. The indicator blocks drift classification when significant mean reversion is detected. Classification system Based on these tests, the indicator classifies assets into three categories. Strong evidence indicates that all criteria are met: statistical significance, economic significance (at least 3 percent annualized drift), adequate power, and all robustness checks pass. This classification suggests the asset has exhibited reliable directional tendency that is both statistically robust and economically meaningful. Weak evidence indicates statistical significance without economic significance. The drift is detectable but small, typically below 3 percent annually. Such assets may still have directional tendency but the magnitude may not justify concentrated positioning. No evidence indicates insufficient statistical support for drift. This does not prove the asset is driftless; it means the available data cannot distinguish drift from random variation. The indicator provides the specific reason for rejection, such as failed power analysis, inconsistent sub-samples, or detected mean reversion. Dashboard explanation The dashboard displays all relevant statistics for transparency. Classification shows the current drift assessment: Positive Drift, Negative Drift, Positive (weak), Negative (weak), or No Drift. Evidence indicates the strength of evidence: Strong, Weak, or None, with the specific reason for rejection if applicable. Inference shows whether the sample is sufficient for analysis. Blocked indicates fewer than 10 observations. Heuristic indicates 10 to 19 observations, where asymptotic approximations are less reliable. Allowed indicates 20 or more observations with reliable inference. The t-statistics for full sample and both half-samples show the test statistics and sample sizes. Double asterisks denote significance at the 5 percent level. Power displays OK if observed drift exceeds the minimum detectable effect, or shows the MDE threshold if power is insufficient. Sign Test shows the z-statistic for the proportion test. An asterisk indicates significance at 10 percent. Mean equals Median indicates agreement between central tendency measures. Struct(m) shows structural stability of means across half-samples, including the standardized level deviation. Struct(t) shows whether t-statistics have consistent signs across half-samples. VR Test shows the variance ratio and its z-statistic. An asterisk indicates the ratio differs significantly from one. Econ. Sig. indicates whether drift exceeds the 3 percent annual threshold. Drift (ann.) shows the annualized drift estimate. Regime indicates whether the asset exhibits mean-reverting behavior based on the variance ratio test. Practical applications for traders For discretionary traders, the indicator provides a quantitative foundation for directional bias decisions. Rather than relying on intuition or simple price trends, traders can assess whether historical evidence supports their directional thesis. For systematic traders, the indicator can serve as a regime filter. Trend-following strategies may perform better on assets with detectable positive drift, while mean-reversion strategies may suit assets where drift is absent or the variance ratio indicates mean reversion. For portfolio construction, drift analysis helps identify assets where long-only exposure has historical justification versus assets requiring more balanced or tactical positioning. Limitations This indicator performs retrospective analysis and does not predict future returns. Past drift does not guarantee future drift. Markets evolve, regimes change, and historical patterns may not persist. The three-year sample window captures medium-term tendencies but may miss shorter regime changes or longer structural shifts. The 60-day return horizon suits position traders but may not reflect intraday or weekly dynamics. Small samples yield heuristic rather than statistically robust results. The indicator flags such cases but users should interpret them with appropriate caution. References Andrews, D.W.K. (1993) Tests for parameter instability and structural change with unknown change point. Econometrica, 61(4). Black, F. and Scholes, M. (1973) The pricing of options and corporate liabilities. Journal of Political Economy, 81(3). Campbell, J.Y., Lo, A.W. and MacKinlay, A.C. (1997) The econometrics of financial markets. Princeton: Princeton University Press. DeBondt, W.F.M. and Thaler, R. (1985) Does the stock market overreact? Journal of Finance, 40(3). Fama, E.F. (1970) Efficient capital markets: a review of theory and empirical work. Journal of Finance, 25(2). Grinold, R.C. and Kahn, R.N. (2000) Active portfolio management. 2nd ed. New York: McGraw-Hill. Jegadeesh, N. and Titman, S. (1993) Returns to buying winners and selling losers. Journal of Finance, 48(1). Lo, A.W. and MacKinlay, A.C. (1988) Stock market prices do not follow random walks. Review of Financial Studies, 1(1). Newey, W.K. and West, K.D. (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3). Richardson, M. and Stock, J.H. (1989) Drawing inferences from statistics based on multiyear asset returns. Journal of Financial Economics, 25(2).
אינדיקטור Pine Script®
מאת ‎EdgeTools‎
1
ANTS MVP Indicator David Ryan's Institutional Accumulation🚀 ANTS MVP Indicator – David Ryan's Legendary Accumulation Signal Discover stocks under heavy **institutional buying** before they explode — just like 3-time U.S. Investing Champion David Ryan used to crush the markets! This is a faithful, open-source recreation of the famous **ANTS (Momentum-Volume-Price)** pattern popularized by David Ryan (protégé of William O'Neil / IBD / CAN SLIM fame). It scans for the classic 15-day "MVP" setup that often appears in early stages of massive winners. Key Features: • Colored "Ants" diamonds show signal strength: - Gray: Momentum only (12+ up days in 15) - Yellow: Momentum + Volume surge (≥20% avg volume increase) - Blue: Momentum + Price gain (≥20% rise) - Green: FULL MVP (all three!) – the strongest institutional demand signal! • Toggle to show ONLY green ants for cleaner charts • Position ants above or below bars • Built-in alert for NEW green ants (copy the alert condition or use alert() triggers) • Optional background highlight + label on the last bar for quick spotting Why ANTS Works: - Flags consistent up-days + volume explosion + solid price advance - Often clusters before major breakouts (cup-with-handle, flat bases, etc.) - Used by pros to find leaders early (think NVDA, TSLA, CELH runs) - Great for daily charts + combining with RS Rating, earnings growth, and market uptrends How to Use: 1. Add to daily stock charts 2. Watch for GREEN ants (full MVP) in bases or near pivots 3. Wait for volume breakout above resistance for entry 4. Set alerts for "GREEN ANTS MVP detected!" to catch them live Fully open code – feel free to tweak thresholds (lookback, % gains, etc.)! Inspired by public descriptions from IBD, Deepvue, and Ryan's teachings. If this helps you spot winners, drop a ❤️ like, comment your biggest ANTS catch, and follow for more CAN SLIM-style tools! Questions? Want screener tweaks or strategy version? Comment below! #ANTS #DavidRyan #MVPPattern #InstitutionalAccumulation #CANSLIM #TradingView #MomentumTrading #StockScanner The time it takes for a stock to rise significantly after a green ANTS (full MVP) signal appears varies widely — there is no fixed or guaranteed timeframe. The ANTS indicator (developed by David Ryan) flags strong institutional accumulation over a rolling ~3-week (15-day) period, but the actual price breakout or major advance often comes later, after further consolidation or a proper setup. Typical Timings from Real-World Usage and Examples Short-term (days to weeks): Sometimes the green ants appear during or right at the start of a breakout — price can rise 10–30%+ in the following 1–4 weeks if momentum continues and volume supports it (e.g., Rocket Lab (RKLB) showed ANTS strength ahead of a powerful breakout in examples from IBD). Medium-term (weeks to months): More commonly, green ants signal early accumulation while the stock is still building or tightening in a base (e.g., cup-with-handle, flat base, high tight flag, or pullback to 10/21 EMA). The big move (often 50–200%+) happens after the stock forms a proper buy point (pivot breakout on high volume), which can take 2–12 weeks after the first green ants. Longer-term leaders: In historical CAN SLIM winners, ANTS often appeared during the stealth accumulation phase (before the stock became obvious), with the major multi-month/year run starting 1–6 months later once the market confirmed an uptrend and the stock broke out. Key points from David Ryan/IBD sources: ANTS is a demand confirmation tool, not a precise timing signal. Many stocks with green ants are extended when the signal fires — wait for a pullback/consolidation before expecting the next leg up. In strong bull markets, clusters of green ants over several bars increase the odds of an imminent or near-term move. If no breakout follows within ~1–3 months (and market weakens), the signal may fizzle — cut losses or move on. Bottom line: Expect 0–3 months for meaningful upside in good setups, but always wait for a classic buy point (breakout above resistance on volume) rather than buying the ants alone. Backtest examples (e.g., via TradingView replay on past leaders like NVDA, TSLA, or CELH during their runs) to see the lag in action.
אינדיקטור Pine Script®
מאת ‎TrendRiderPro‎
Mission Control Dashboard (AI, Crypto, Liquidity) FASTCONCEPT Price is a lagging indicator. Liquidity is a leading indicator. "Mission Control Dashboard (AI, Crypto, Liquidity) FAST" is a sophisticated macroeconomic dashboard designed to audit the "plumbing" of the financial system in real-time. Unlike standard indicators that rely solely on price action, this tool pulls data from the Federal Reserve (FRED), Treasury Statements, Corporate Financials (10-K/10-Q), and On-Chain Stablecoin metrics to visualize the structural flows driving the market. THE "UNIFIED FIELD" SOLVER One of the hardest challenges in cross-asset scripting is "Time Dilation"—synchronizing 24/7 Crypto markets (Bitcoin) with Mon-Fri Traditional markets (Stocks/Bonds). Standard scripts fail on weekends, showing mismatched data. This engine uses a Weekly Anchor system. It calculates all momentum and liquidity metrics based on "Week-to-Date" or "Month-Ago" anchors. This ensures that a "Liquidity Drain" looks identical whether you are viewing a Bitcoin chart on Saturday or an Apple chart on Monday. THE CHRONOS LOGIC The dashboard is sorted by Time Sensitivity (Speed of impact), from fast-twitch tactical signals to slow-moving structural fundamentals. 1. TACTICAL (Reacts in 24–48h) Stablecoin Flight: Measures the immediate flow of capital from Volatile Assets to Stablecoins (USDT/USDC). A spike (>0.5%) indicates fear/sidelining. Liquidity Alpha: Calculates the efficiency of capital. It subtracts "Friction" (Dollar Strength + Yields) from "Flow" (Liquidity Beta). High Alpha means money is flowing easily into risk assets. Alt Euphoria: Tracks the overheating of the Altcoin market (TOTAL3). Green indicates sustainable growth; Red (>45%) warns of a "blow-off top." Retail FOMO: A sentiment gauge comparing Coinbase Stock ( NASDAQ:COIN ) performance vs. Bitcoin ( CRYPTOCAP:BTC ). When Retail outperforms the Asset, local tops often follow. 2. LIQUIDITY & MACRO (Reacts in 1–4 Weeks) Debt Wall (10Y): The Rate-of-Change of the US 10-Year Treasury Yield. Spiking yields act as gravity on risk assets. Liquidity Beta: The raw "Quantity of Money." Tracks the 4-week change in Net Liquidity (Fed Balance Sheet - TGA + Stablecoins). TGA Balance: The Critical Monitor. Tracks the Treasury General Account. When the TGA rises (Red), the government is draining liquidity from the banking system. When it falls (Green), it releases cash. Note: This script includes an auto-scaler to handle TGA data in both Billions and Millions. 3. STRUCTURAL (Reacts in 3–12 Months) AI Capex (YoY & QoQ): The "Floor" of the 2025/2026 cycle. Tracks the Capital Expenditure of the Hyperscalers (MSFT, GOOGL, AMZN, META). As long as this remains high (>30%), the infrastructure boom supports the tech narrative. PMI Manufacturing: Tracks the ISM Manufacturing cycle. Contraction (<50) often forces Fed intervention. Micron Inventory: A lead indicator for the hardware cycle. HOW TO USE Status Colors: The traffic light system helps you assess risk at a glance. 🟢 GREEN (Healthy): Flow is positive, friction is low, fundamentals are strong. 🔴 RED (Danger): Liquidity is draining (TGA spike), yields are shock-rising, or FOMO is excessive. Zero Configuration: The script auto-detects asset classes and scales units (Billions/Trillions) automatically. DATA SOURCES Federal Reserve Economic Data (FRED) Daily Treasury Statement (DTS) CryptoCap (TradingView) Nasdaq/Corporate Financials Disclaimer: This tool is for informational purposes only and does not constitute financial advice. Macro data feeds are subject to reporting delays.
אינדיקטור Pine Script®
מאת ‎SebK85‎