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インジケーターとストラテジー

Price Channel Breakout Strategy — Long & ShortThis strategy is a dual-direction Price Channel breakout system designed for high-volatility indices such as US30, NAS100, and XAUUSD. It enters long when price breaks above the highest high of the past N bars, and enters short when price breaks below the lowest low. A key feature is the use of fixed dollar-based take-profit and stop-loss, making the strategy adaptive across symbols with different tick values. Core Logic Long entry when price breaks the N-bar high Short entry when price breaks the N-bar low Dollar-based TP and SL (converted to ticks automatically) Suitable for trending and breakout-friendly markets Backtest Notes (US30 Example) Sharpe Ratio: 2.7 Profit Factor: 2.111 Total Return (12-month backtest): +46.89% Max Drawdown: 0.26% Trades: 3,666 This strategy performs well in sustained volatility environments and is particularly effective for intraday momentum bursts on US30.
Pine Script® ストラテジー
michelathayde808の投稿
1
MACDiver — рабочая версия (fixed loops)MACDiver Indicator A Pine Script indicator that identifies bullish and bearish divergences between price action and the MACD oscillator. It uses pivot highs/lows in both price and MACD series to detect potential reversal signals. When price makes higher highs (or lower lows) while MACD makes lower highs (or higher lows), the indicator marks these divergences with lines and labels on the chart, providing potential trading signals.
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axisbhpの投稿
WSMR v3.9 — WhaleSplash → Mean Reversal # WSMR v3.9 — WhaleSplash → Mean Reversal *A Non-Repainting Impulse‑Reversal Engine for Systematic Futures Trading* ## Overview WSMR v3.9 is a complete impulse → exhaustion → mean‑reversion framework designed for systematic intraday trading. It identifies high‑energy displacement events (“WhaleSplashes”), measures volatility structure, tracks VWAP deviation, and confirms reversals using RSI divergence, Z‑Score resets, SMA20 reclaim, and pivot-based structure. All signals are non‑repainting and alerts fire on bar close. --- ## Core Components ### 1. WhaleSplash (Short Impulse Event) Triggered when a candle meets displacement conditions: - Large bar range vs ATR - Minimum % move - Volume expansion - VWAP deviation (tick-based) - Z‑Score oversold / RSI exhaustion - Volatility-gated ### 2. Mean Reversal Long (MR) Requires: - RSI bullish divergence - Z‑Score reset - SMA20 reclaim - Higher-low confirmation ### 3. First-Candle Confirmation (Optional) - MR Confirm → first green after MR - WS Confirm → first red after WS - TTL window configurable ### 4. Asia Session Filter Optional restriction to: **23:00 → 09:00 UTC** ### 5. Volatility Monitor Detects: - Normal - Wicky - Spiky - Extreme ### 6. WS Frequency Analytics Rolling frequency calculation across: - Bars / Days / Weeks / Months --- ## Status Panel (Top-Right) Shows: - Mode (Global / Asia-only) - Timeframe + TTL - WS frequency - Volatility state --- ## Alerts - WhaleSplash SHORT - WhaleSplash LONG (MR) - MR Confirm LONG - WS Confirm SHORT - Volatility Warning --- ## Notes - Fully non‑repainting - Stable bar-close logic - Optimised for 1m–5m - Works on futures, indices, metals, FX
Pine Script® インジケーター
JohnFrancisNolanの投稿
Minor Break of Structure (Minor BoS)This indicator extracts and isolates the Minor Break of Structure (BoS) logic from a full SMC framework and presents it as a clean, lightweight tool for structure-based price action traders. Unlike traditional BOS indicators that rely on swing calculations with heavy filtering, this script uses original SMC-style minor structure logic to detect meaningful shifts in internal order flow. A Minor BoS appears when price breaks above a minor swing high (bullish) or below a minor swing low (bearish), confirming a short-term continuation in trend direction. Features: Bullish Minor BoS detection Bearish Minor BoS detection Automatic line plotting with extend-right Clear “Minor BoS” label with tiny footprint Customizable line styles and colors Lightweight & optimized for fast execution Zero repainting on BoS confirmations This tool is ideal for traders who want a simple, clean, and reliable structure-based signal without the noise of major structure, order blocks, liquidity sweeps, or external SMC modules.
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SMC_Casperの投稿
Research-Backed Intraday MTF MAsResearch-Backed Intraday Multi-Timeframe Moving Averages A precision-tuned intraday trading indicator that displays four key moving averages across two critical timeframes: 📊 What It Shows: - 1-Hour MAs: 75-period SMA & EMA (institutional flow patterns) - 10-Minute MAs: 200-period SMA & EMA (intraday trend structure) 🎯 Designed For: - Day traders seeking multi-timeframe confluence - Identifying strong trending vs. choppy market conditions - Support/resistance level identification - Momentum and trend alignment signals ✨ Key Features: - Optimized periods based on market structure analysis - Fully customizable colors, transparency, and line widths - Toggle each MA on/off independently - Clean, non-cluttered chart display - Efficient tuple-based data requests 💡 Trading Signals: - Price above all 4 MAs = Strong bullish alignment - Price below all 4 MAs = Strong bearish alignment - Mixed signals = Range-bound conditions, reduce risk Perfect for scalpers, day traders, and swing traders who want institutional-grade moving averages without the noise.
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igaudetteの投稿
50 EMA Rejection Strategy V4 (Correct Signal Logic)//@version=6 indicator("50 EMA Rejection Strategy V4 (Correct Signal Logic)", overlay=true, max_labels_count=500) //================ INPUTS ================// group50 = "EMA 50 Trio" ema50HighLen = input.int(50,"EMA50 High",group=group50) ema50CloseLen = input.int(50,"EMA50 Close",group=group50) ema50LowLen = input.int(50,"EMA50 Low",group=group50) groupBase = "Additional EMAs" ema10Len = input.int(10,"EMA10") ema200Len = input.int(200,"EMA200") ema600Len = input.int(600,"EMA600") ema2400Len = input.int(2400,"EMA2400") useTrendFilter = input.bool(false,"Use Higher Time EMA Filter") groupRR = "Risk Reward Settings" RR1 = input.float(1.0,"TP1 RR",step=0.5) RR2 = input.float(2.0,"TP2 RR",step=0.5) //================ CALCULATIONS ================//
Pine Script® インジケーター
hasyal2022の投稿
Composite Market Momentum Indicator//@version=5 indicator("Composite Market Momentum Indicator", shorttitle="CMMI", overlay=false) // Define Inputs lenRSI = input.int(14, title="RSI Length") lenMom = input.int(9, title="Momentum Length") lenShortRSI = input.int(3, title="Short RSI Length") lenShortRSISma = input.int(3, title="Short RSI SMA Length") lenSMA1 = input.int(9, title="Composite SMA 1 Length") lenSMA2 = input.int(34, title="Composite SMA 2 Length") // Step 1: Create a 9-period momentum indicator of the 14-period RSI rsiValue = ta.rsi(close, lenRSI) momRSI = ta.mom(rsiValue, lenMom) // Step 2: Create a 3-period RSI and a 3-period SMA of that RSI shortRSI = ta.rsi(close, lenShortRSI) shortRSISmoothed = ta.sma(shortRSI, lenShortRSISma) // Step 3: Add Step 1 and Step 2 together to create the Composite Index compositeIndex = momRSI + shortRSISmoothed // Step 4: Create two simple moving averages of the Composite Index sma1 = ta.sma(compositeIndex, lenSMA1) sma2 = ta.sma(compositeIndex, lenSMA2) // Step 5: Plot the composite index and its two simple moving averages plot(compositeIndex, title="Composite Index", color=color.new(#f7cf05, 0), linewidth=2) plot(sma1, title="SMA 13", color=color.new(#f32121, 0), linewidth=1, style=plot.style_line) plot(sma2, title="SMA 33", color=color.new(#105eef, 0), linewidth=1, style=plot.style_line) // Add horizontal lines for reference hline(0, "Zero Line", color.new(color.gray, 50))
Pine Script® インジケーター
Alcides0265の投稿
3
Displacement Pulse Markers - sudoThis indicator is designed to highlight sudden and meaningful bursts of price movement. These bursts are called displacement pulses. A pulse appears when price expands with force, closes near the extreme of its own bar, and breaks through a recent structural level. The indicator places small circles above or below the candle to signal these moments so that traders can quickly spot abnormal movement and potential shifts in market intent. How it works The indicator evaluates each bar for three conditions: Range expansion relative to volatility The bar must be larger than normal. It compares the bar range to ATR and requires that range to exceed a multiple of ATR. When this condition is met, the bar is considered a large or forceful bar. Close location within the bar The bar has to close near its own high or low. A close near the top suggests strong buying force. A close near the bottom suggests strong selling force. The user can adjust what percentage qualifies as near the top or bottom. Break of recent structure The bar must break a recent pivot level. For bullish pulses, the high of the bar must exceed the highest high of the past N bars. For bearish pulses, the low must break the lowest low of the past N bars. This confirms that the move did not merely expand but actually displaced prior structure. When all conditions align A bullish displacement pulse is marked with a small aqua circle below the bar. A bearish displacement pulse is marked with a fuchsia circle above the bar. The result is a clean on chart visualization of where price produced meaningful displacement. How traders can use this Spot abnormal momentum Pulses can highlight areas where price behaves with more force than usual. These events often appear around news, liquidity sweeps, or algorithmic shifts. Identify possible regime changes A pulse that breaks structure while closing near the extreme may signal a transition from a ranging environment to a trending one. It does not predict direction but flags where displacement actually occurred. Support narrative building When combined with levels, zones, or other frameworks, pulses can confirm whether the market had enough strength to break through an area with conviction. Filter trades or refine entries Some traders may choose to trade in the direction of recent pulses during trending conditions. Others may only enter a trade after a pulse confirms that the market has shifted away from compression. Track where the market is imbalanced A pulse visually marks whether buyers or sellers were able to generate strong initiative movement. These points often become useful reference zones for continuation or rejection analysis. Why this indicator is useful It reduces complex logic into simple visual markers. Instead of scanning bar by bar for structural breaks, volatility expansions, and close strength, the indicator does this automatically and highlights only the bars that meet all criteria. This keeps the chart clean while still providing precision about where displacement actually occurred.
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hondacivic2002の投稿
VWAP with StdDev + 0,25 channelsThis indicator displays the Volume Weighted Average Price (VWAP) together with standard deviation bands and additional ±0.25 offset bands. VWAP serves as the central reference line, while the deviation bands show how far price typically moves away from VWAP. 1 standard deviation (±1σ) covers roughly 68% of all price movements around VWAP. 2 standard deviations (±2σ) cover about 95% of price movements. 3 standard deviations (±3σ) cover approximately 99.7% of price movements. Around VWAP and the first deviation level, extra ±0.25 offset bands are added to highlight tighter ranges. These shaded zones help traders identify areas of expected price concentration, potential support and resistance, and volatility boundaries. Purpose: The tool provides a statistical framework for intraday trading. VWAP shows the average traded price weighted by volume, while the deviation bands indicate probability zones where price is most likely to remain.
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BaumFlohの投稿
Algoticks.in: MA Crossover Strategy (Sample)MA Crossover Strategy - User Guide Overview This is a Moving Average Crossover strategy that generates trading signals when a fast MA crosses a slow MA. It integrates with Algoticks.in API for automated trading on Delta Exchange. Strategy Logic Long Signal: When Fast MA crosses above Slow MA Short Signal: When Fast MA crosses below Slow MA Automatically closes opposite positions before entering new ones Quick Setup 1. Add to TradingView Open TradingView and go to the chart Click "Pine Editor" at the bottom Paste the script code Click "Add to Chart" 2. Configure Strategy Parameters Strategy Settings Fast MA Length (default: 9): Shorter moving average period Slow MA Length (default: 21): Longer moving average period MA Type : Choose SMA (Simple) or EMA (Exponential) General API Settings Paper Trading : Enable for testing without real money Signal Type : Choose "Trading Signal" (default) for tracking Exchange : DELTA (Delta Exchange) Segment : futures - Perpetual contracts options - Call/Put options spot - Spot trading Order Settings: Basic Quantity : Number of contracts (e.g., 1, 0.5, 2) Validity : GTC - Good Till Cancelled IOC - Immediate or Cancel FOK - Fill or Kill DAY - Day order Product : cross_margin or isolated_margin Order Settings: Entry Type Choose how orders are executed: Market Order : Immediate fill at best price Limit Order : Fill at specified price or better Stop Market : Triggers at stop price, then market order Stop Limit : Triggers at stop price, then limit order Entry Prices (for Limit/Stop orders) Limit Price: Price : The value to use Type : Last Price / Mark Price / Index Price Mode : Absolute - Exact price (e.g., 65000) Relative - Offset from entry price % Checkbox : If checked, relative uses percentage; if unchecked, uses points Example: Absolute: 65000 → Order at exactly 65000 Relative 1% (checked): Entry ± 1% of entry price Relative 100 (unchecked): Entry ± 100 points Trigger Price: Same logic as Limit Price, used for Stop orders Exit / Bracket Prices (SL/TP) Stop Loss (SL): Type : Price type to monitor (Mark Price recommended) Mode : Absolute or Relative % : Percentage or points SL : Stop loss value (e.g., 2 for 2%) Trig : Optional trigger price (creates Stop-Limit SL) Take Profit (TP): Same structure as SL Example: Long entry at 65000, SL = 2% → Exit at 63700 (65000 - 2%) Short entry at 65000, TP = 3% → Exit at 63050 (65000 - 3%) 3. Options Trading Setup (Only if Segment = Options) Strike Selection Method User Defined Mode: Manually specify exact strike and option type Best for: Trading specific levels Required fields: Strike Price : e.g., "65000" Option Type : Call or Put Dynamic Mode: System calculates strike based on ATM price Best for: Automated strategies Required fields: Algo Type : Options Buying or Selling Strike Offset : 0 (ATM), +1 (above ATM), -1 (below ATM) Strike Interval : Gap between strikes (e.g., BTC: 500, ETH: 50) Expiry Date Formats: T+0 - Today T+1 - Tomorrow current week - This Friday next week - Next Friday current month - Last Friday of month 131125 - Specific date (13 Nov 2025) 4. Create Alert for Automation Right-click on chart → "Add Alert" Condition : Select your strategy name Alert Actions : Webhook URL Webhook URL : Your Algoticks.in API endpoint Message : Leave as {{strategy.order.alert_message}} (contains JSON) Click "Create" The alert will automatically send JSON payloads to your API when signals occur. Example Configurations Simple Futures Trading Strategy: Fast MA = 9, Slow MA = 21, SMA Segment: futures Order Type: market_order Quantity: 1 SL: 2% (Relative) TP: 4% (Relative) Options Buying (Dynamic) Segment: options Strike Selection: Dynamic Algo Type: Options Buying Algo Strike Offset: 0 (ATM) Strike Interval: 500 (for BTC) Expiry: current week Order Type: market_order Conservative Spot Trading Segment: spot Order Type: limit_order Limit Price: 0.5% (Relative) Quantity: 0.1 No SL/TP (manual management) Important Notes Paper Trading First : Always test with paper trading enabled before live trading Order Tags : Automatically generated for tracking (max 18 chars) Position Management : Strategy closes opposite positions automatically Signal Confirmation : Uses barstate.isconfirmed to prevent repainting JSON Payload : All settings are converted to JSON and sent via webhook Troubleshooting No signals : Check if MAs are crossing on your timeframe Orders not executing : Verify webhook URL and API credentials Wrong strikes : Double-check Strike Interval for your asset SL/TP not working : Ensure values are non-zero and mode is correct Support For API setup and connector configuration, see CONNECTOR_SETUP_GUIDE.md or visit Algoticks.in documentation.
Pine Script® ストラテジー
Algoticks_Indiaの投稿
Per Bak Self-Organized CriticalityTL;DR: This indicator measures market fragility. It measures the system's vulnerability to cascade failures and phase transitions. I've added four independent stress vectors: tail risk, volatility regime, credit stress, and positioning extremes. This allows us to quantify how susceptible markets are to disproportionate moves from small shocks, similar to how a steep sandpile is primed for avalanches. Avalanches, forest fires, earthquakes, pandemic outbreaks, and market crashes. What do they all have in common? They are not random. These events follow power laws - stable systems that naturally evolve toward critical states where small triggers can unleash catastrophic cascades. For example, if you are building a sandpile, there will be a point with a little bit additional sand will cause a landslide. Markets build fragility grain by grain, like a sandpile approaching avalanche. The Per Bak Self-Organized Criticality (SOC) indicator detects when the markets are a few grains away from collapse. This indicator is highly inspired by the work of Per Bak related to the science of self-organized criticality . As Bak said: "The earthquake does not 'know how large it will become'. Thus, any precursor state of a large event is essentially identical to a precursor state of a small event." For markets, this means: We cannot predict individual crash size from initial conditions We can predict statistical distribution of crashes We can identify periods of increased systemic risk (proximity to critical state) BTW, this is a forwarding looking indicator and doesn't reprint. :) The Story of Per Bak In 1987, Danish physicist Per Bak and his colleagues discovered an important pattern in nature: self-organized criticality. Their sandpile experiment revealed something: drop grains of sand one by one onto a pile, and the system naturally evolves toward a critical state. Most grains cause nothing. Some trigger small slides. But occasionally a single grain triggers a massive avalanche. The key insight is that we cannot predict which grain will trigger the avalanche, but you can measure when the pile has reached a critical state. Why Markets Are the Ultimate SOC System? Financial markets exhibit all the hallmarks of self-organized criticality: Interconnected agents (traders, institutions, algorithms) with feedback loops Non-linear interactions where small events can cascade through the system Power-law distributions of returns (fat tails, not normal distributions) Natural evolution toward fragility as leverage builds, correlations tighten, and positioning crowds Phase transitions where calm markets suddenly shift to crisis regimes Mathematical Foundation Power Law Distributions Traditional finance assumes returns follow a normal distribution. "Markets return 10% on average." But I disagree. Markets follow power laws: P(x) ∝ x^(-α) Where P(x) is the probability of an event of size x, and α is the power law exponent (typically 3-4 for financial markets). What this means: Small moves happen constantly. Medium moves are less frequent. Catastrophic moves are rare but follow predictable probability distributions. The "fat tails" are features of critical systems. Critical Slowing Down As systems approach phase transitions, they exhibit critical slowing down—reduced ability to absorb shocks. Mathematically, this appears as: τ ∝ |T - T_c|^(-ν) Where τ is the relaxation time, T is the current state, T_c is the critical threshold, and ν is the critical exponent. Translation: Near criticality, markets take longer to recover from perturbations. Fragility compounds. Component Aggregation & Non-Linear Emergence The Per Bak SOC our index aggregates four normalized components (each scaled 0-100) with tunable weights: SOC = w₁·C_tail + w₂·C_vol + w₃·C_credit + w₄·C_position Default weights (you can change this): w₁ = 0.34 (Tail Risk via SKEW) w₂ = 0.26 (Volatility Regime via VIX term structure) w₃ = 0.18 (Credit Stress via HYG/LQD + TED spread) w₄ = 0.22 (Positioning Extremes via Put/Call ratio) Each component uses percentile ranking over a 252-day lookback combined with absolute thresholds to capture both relative regime shifts and extreme absolute levels. The Four Pillars Explained 1. Tail Risk (SKEW Index) Measures options market pricing of fat-tail events. High SKEW indicates elevated outlier probability. C_tail = 0.7·percentrank(SKEW, 252) + 0.3·((SKEW - 115)/0.5) 2. Volatility Regime (VIX Term Structure) Combines VIX level with term structure slope. Backwardation signals acute stress. C_vol = 0.4·VIX_level + 0.35·VIX_slope + 0.25·VIX_ratio 3. Credit Stress (HYG/LQD + TED Spread) Tracks high-yield deterioration versus investment-grade and interbank lending stress. C_credit = 0.65·percentrank(LQD/HYG, 252) + 0.35·(TED/0.75)·100 4. Positioning Extremes (Put/Call Ratio) Detects extreme hedging demand through percentile ranking and z-score analysis. C_position = 0.6·percentrank(P/C, 252) + 0.4·zscore_normalized What the Indicator Really Measures? Not Volatility but Fragility Markets Going Down ≠ Fragility Building (actually when markets go down, risk and fragility are released) The 0-100 Scale & Regime Thresholds The indicator outputs a 0-100 fragility score with four regimes: 🟢 Safe (0-39): System resilient, can absorb normal shocks 🟡 Building (40-54): Early fragility signs, watch for deterioration 🟠 Elevated (55-69): System vulnerable 🔴 Critical (70-100): Highly susceptible to cascade failures Further Reading for Nerds Bak, P., Tang, C., & Wiesenfeld, K. (1987). "Self-organized criticality: An explanation of 1/f noise." Physical Review Letters. Bak, P. & Chen, K. (1991). "Self-organized criticality." Scientific American. Bak, P. (1996). How Nature Works: The Science of Self-Organized Criticality. Copernicus. Feedback is appreciated :)
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HenriqueCentieiroの投稿
2
Ultimate Squeeze & BreakoutTitle: Ultimate Squeeze & Breakout Description: This professional volatility indicator utilizes the power of Bollinger Bands and Keltner Channels to identify high-probability consolidation zones and explosive breakouts. It is designed to help traders spot "The Squeeze"—a critical period of low volatility where the market builds potential energy before a significant directional move. How It Works: 1. The Energy (The Squeeze): Using the classic TTM Squeeze logic, the indicator monitors the relationship between price volatility (Bollinger Bands) and average range (Keltner Channels). Red Cloud: Volatility is compressed. The Bollinger Bands have contracted inside the Keltner Channels. The market is coiling like a spring. This is the Setup Phase. 2. The Breakout (The Release): When price expands and closes outside the bands, the energy is released. Momentum Filter: A unique filter checks the slope of the 20-period Basis Line (SMA). Breakout colors only trigger if the momentum slope agrees with the breakout direction, helping to filter out weak "fakeouts." Visual Guide: ☁️ Cloud Colors (Volatility State): 🟥 Red: Squeeze ON (Consolidation/No Trade). 🟣 Fuchsia: Bullish Momentum Breakout. 🔵 Blue: Bearish Momentum Breakout. ⬜ Gray/Green: Normal Trending (Neutral). Features: Smart Filters: Breakouts are validated by the underlying momentum slope. Trend Coloring: Option to switch the neutral trending cloud between Gray and Green. Precision Tuning: Decimal inputs allow for fine-tuning of Standard Deviation and ATR multipliers. Alerts: Full alert support for Squeeze Start, Bullish Breakouts, and Bearish Breakouts. Credits: This script is built upon the foundational TTM Squeeze concept popularized by John Carter, enhanced with dynamic coloring and momentum filtering.
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tonngnh3の投稿
RS Rating Multi-TimeframeRS Rating Multi-Timeframe (IBD-Style Relative Strength) Short Description: IBD-style Relative Strength Rating (1-99) comparing any stock's performance vs the S&P 500 across multiple timeframes. Full Description: Overview This indicator calculates an IBD-style Relative Strength (RS) Rating that measures a stock's price performance relative to the S&P 500 over the past 12 months. The rating scale ranges from 1 (weakest) to 99 (strongest), telling you how a stock ranks against all other stocks in terms of relative performance. How It Works The RS Rating uses a weighted formula based on quarterly performance: Last 63 days (1 quarter): 40% weight Last 126 days (2 quarters): 20% weight Last 189 days (3 quarters): 20% weight Last 252 days (4 quarters): 20% weight This weighting emphasizes recent performance while still accounting for longer-term strength. Rating Interpretation 90-99 (Elite): Top 10% of all stocks - exceptional relative strength 80-89 (Excellent): Top 20% - strong leadership candidates 50-79 (Average): Middle of the pack 30-49 (Below Average): Underperforming the market 1-29 (Weak): Bottom 30% - avoid or consider shorting Features Multi-Timeframe: Works on any timeframe from 1-hour to weekly (always uses daily data for calculation) Moving Average: Optional EMA or SMA of the RS Rating to smooth signals Visual Zones: Color-coded zones for quick identification of strength/weakness Signal Markers: Triangles appear when RS crosses key levels (80 and 30) Info Table: Displays current RS Rating, change, MA value, and raw score Alerts: Built-in alerts for key crossover events Settings Show Moving Average: Toggle MA line on/off MA Length: Period for the moving average (default: 10) MA Type: Choose between EMA or SMA Benchmark Index: Change the comparison index (default: SP:SPX) Show Rating Table: Toggle the info table on/off How To Use Buy candidates: Look for stocks with RS Rating above 80, ideally rising Avoid: Stocks with RS Rating below 30 or falling rapidly Confirmation: Use RS above its moving average as additional confirmation Divergence: Watch for RS making new highs before price (bullish) or new lows before price (bearish) Credits RS Rating calculation methodology inspired by Investor's Business Daily (IBD) and adapted from Fred6724's RS Rating script. Percentile calibration based on analysis of ~6,600 US stocks. Tags: relative strength, RS rating, IBD, momentum, CAN SLIM, benchmark, SPX, market leaders, stock ranking Category: Relative Strength
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rwalk1979の投稿
Markov ProjectionThe idea here is to provide mobile S/R through Markov chaining. Definitely not a reversion to the mean trading system, or a trading system of any sort. More like an error bounded future price envelope that dramatically overshoots projected price in the direction it's moving in while just barely failing price bounding in the opposite direction. So in an uptrend, it'll overshoot the top while the bottom pokes out a bit and vice versa. Looks rather pretty. You'll have to adjust transparency settings. Happy hunting.
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ChronicMasturTraderの投稿
ZScore SemiConductoresZ-Score of Semiconductor Sector Volume This custom Pine Script indicator applies a Z-Score calculation to the aggregated trading volume of leading semiconductor companies. The goal is to highlight statistical extremes in sector activity that may signal unusual market behavior. 🔧 How it works - Fixed ticker list: NVDA, AVGO, TSM, AMD, ASML, MU, ARM, ON, TXN, QCOM, INTC. - Aggregate volume: The script sums the trading volume of all tickers in the list for the selected timeframe. - Z-Score calculation: - Moving average and standard deviation are computed over a configurable window (default = 50 bars). - Formula: Z= (Current Volume - Mean) / Standard Deviation Visualization: - Z-Score plotted in green. - Reference lines at 0, ±1σ, ±2σ. - Labels (triangles) mark critical signals when Z > +2 or Z < -2. 📈 Why it matters - Detects abnormal surges or drops in sector-wide volume. - Highlights potential euphoria (+2σ) or panic (-2σ) moments. - Useful as a filter for trading strategies or as a sector-level alert system. ⚠️ Disclaimer: This script is for educational purposes only and not financial advice
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JuanDeNogoyaの投稿