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Simplified Market ForecastSimplified Market Forecast Indicator This indicator pairs nicely with the Contrarian 100 MA and can be located here: Overview The "Simplified Market Forecast" (SMF) indicator is a streamlined technical analysis tool designed for traders to identify potential buy and sell opportunities based on a momentum-based oscillator. By analyzing price movements relative to a defined lookback period, SMF generates clear buy and sell signals when the oscillator crosses customizable threshold levels. This indicator is versatile, suitable for various markets (e.g., forex, stocks, cryptocurrencies), and optimized for daily timeframes, though it can be adapted to other timeframes with proper testing. Its intuitive design and visual cues make it accessible for both novice and experienced traders. How It Works The SMF indicator calculates a momentum oscillator based on the price’s position within a specified range over a user-defined lookback period. It then smooths this value to reduce noise and plots the result as a line in a separate lower pane. Buy and sell signals are generated when the smoothed oscillator crosses above a user-defined buy level or below a user-defined sell level, respectively. These signals are visualized as triangles either on the main chart or in the lower pane, with a table displaying the current ticker and oscillator value for quick reference. Key Components Momentum Oscillator: The indicator measures the price’s position relative to the highest high and lowest low over a specified period, normalized to a 0–100 scale. Signal Generation: Buy signals occur when the oscillator crosses above the buy level (default: 15), indicating potential oversold conditions. Sell signals occur when the oscillator crosses below the sell level (default: 85), suggesting potential overbought conditions. Visual Aids: The indicator includes customizable horizontal lines for buy and sell levels, shaded zones for clarity, and a table showing the ticker and current oscillator value. Mathematical Concepts Oscillator Calculation: The indicator uses the following formula to compute the raw oscillator value: c1I = close - lowest(low, medLen) c2I = highest(high, medLen) - lowest(low, medLen) fastK_I = (c1I / c2I) * 100 The result is smoothed using a 5-period Simple Moving Average (SMA) to produce the final oscillator value (inter). Signal Logic: A buy signal is triggered when the smoothed oscillator crosses above the buy level (ta.crossover(inter, buyLevel)). A sell signal is triggered when the smoothed oscillator crosses below the sell level (ta.crossunder(inter, sellLevel)). Entry and Exit Rules Buy Signal (Blue Triangle): Triggered when the oscillator crosses above the buy level (default: 15), indicating a potential oversold condition and a buying opportunity. The signal appears as a blue triangle either below the price bar (if plotted on the main chart) or at the bottom of the lower pane. Sell Signal (White Triangle): Triggered when the oscillator crosses below the sell level (default: 85), indicating a potential overbought condition and a selling opportunity. The signal appears as a white triangle either above the price bar (if plotted on the main chart) or at the top of the lower pane. Exit Rules: Traders can exit positions when an opposite signal occurs (e.g., exit a buy on a sell signal) or based on additional technical analysis tools (e.g., support/resistance, trendlines). Always apply proper risk management. Recommended Usage The SMF indicator is optimized for the daily timeframe but can be adapted to other timeframes (e.g., 1H, 4H) with careful testing. It performs best in markets with clear momentum shifts, such as trending or range-bound conditions. Traders should: Backtest the indicator on their chosen asset and timeframe to validate signal reliability. Combine with other indicators (e.g., moving averages, support/resistance) or price action for confirmation. Adjust the lookback period and buy/sell levels to suit market volatility and trading style. Customization Options Intermediate Length: Adjust the lookback period for the oscillator calculation (default: 31 bars). Buy/Sell Levels: Customize the threshold levels for buy (default: 15) and sell (default: 85) signals. Colors: Modify the colors of the oscillator line, buy/sell signals, and threshold lines. Signal Display: Toggle whether signals appear on the main chart or in the lower pane. Visual Aids: The indicator includes dotted horizontal lines at the buy (green) and sell (red) levels, with shaded zones between 0–buy level (green) and sell level–100 (red) for clarity. Ticker Table: A table in the top-right corner displays the current ticker and oscillator value (in percentage), with customizable colors. Why Use This Indicator? The "Simplified Market Forecast" indicator provides a straightforward, momentum-based approach to identifying potential reversals in overbought or oversold markets. Its clear signals, customizable settings, and visual aids make it easy to integrate into various trading strategies. Whether you’re a swing trader or a day trader, SMF offers a reliable tool to enhance decision-making and improve market timing. Tips for Users Test the indicator thoroughly on your chosen asset and timeframe to optimize settings. Use in conjunction with other technical tools for stronger trade confirmation. Adjust the buy and sell levels based on market conditions (e.g., lower levels for less volatile markets). Monitor the ticker table for real-time oscillator values to gauge market momentum. Happy trading with the Simplified Market Forecast indicator!
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chuckaschultz tarafından
ECG Sanbot IndicatorNot my best but my first strategy to pass prop firms. Strength based signals. Change the length and repainting settings before setting alerts up. First strategy to pass my prop firm. Change the tf and length to see reliable signals. Option to remove repainting if you want to set alerts. Not the best compared to my other scripts but will always get you in the green. Core Logic Calculates a double-smoothed EMA source on a higher timeframe (tf input). Builds two RSI streams: Repainting RSI (lookahead on) → reacts quickly to market changes. Non-repainting RSI (lookahead off) → provides stable, confirmed values. Computes the ECG difference between the two RSI streams. Generates a buy signal when the ECG difference crosses above the upper threshold. Generates a sell signal when the ECG difference crosses below the lower threshold. Risk Management Each trade uses a fixed trade size (trade_size). Built-in stop-loss and take-profit controls: Stop Loss: default 0.1% from entry price. Take Profit: default 0.2% from entry price. Both long and short entries are supported (direction selectable). Customization Options Adjustable timeframe (tf) for RSI source. Fully configurable thresholds, lengths, and EMA smoothing. Toggle between repainting vs. non-repainting behavior. Backtest period controls (start and end date). Visualization Plots the ECG difference line in red. Displays horizontal threshold lines for signal reference.
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TANTECHTRADES tarafından
Fisher Volume Transform | AlphaNattFisher Volume Transform | AlphaNatt A powerful oscillator that applies the Fisher Transform - converting price into a Gaussian normal distribution - while incorporating volume weighting to identify high-probability reversal points with institutional participation. "The Fisher Transform reveals what statistics professors have known for decades: when you transform market data into a normal distribution, turning points become crystal clear." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎲 THE MATHEMATICS Fisher Transform Formula: The Fisher Transform converts any bounded dataset into a Gaussian distribution: y = 0.5 × ln((1 + x) / (1 - x)) Where x is normalized price (-1 to 1 range) Why This Matters: Market extremes become statistically identifiable Turning points are amplified and clarified Removes the skew from price distributions Creates nearly instantaneous signals at reversals Volume Integration: Unlike standard Fisher Transform, this version weights price by relative volume: High volume moves get more weight Low volume moves get filtered out Identifies institutional participation Reduces false signals from retail chop ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 KEY ADVANTAGES Statistical Edge: Transforms price into normal distribution where extremes are mathematically defined Volume Confirmation: Only signals with volume support Early Reversal Detection: Fisher Transform amplifies turning points Clean Signals: Gaussian distribution reduces noise No Lag: Mathematical transformation, not averaging ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ SETTINGS OPTIMIZATION Fisher Period (5-30): 5-9: Very sensitive, many signals 10: Default - balanced sensitivity 15-20: Moderate smoothing 25-30: Major reversals only Volume Weight (0.1-1.0): 0.1-0.3: Minimal volume influence 0.5-0.7: Balanced price/volume 0.7: Default - strong volume weight 0.8-1.0: Volume dominant ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING SIGNALS Primary Signals: Zero Cross Up: Bullish momentum shift Zero Cross Down: Bearish momentum shift Signal Line Cross: Early reversal warning Extreme Readings (±75): Potential reversal zones Visual Interpretation: Cyan zones: Bullish momentum Magenta zones: Bearish momentum Gradient intensity: Strength of move Histogram: Raw momentum power ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 OPTIMAL USAGE Best Market Conditions: Range-bound markets (reversals clear) High volume periods Major support/resistance levels Divergence hunting Trading Strategies: 1. Extreme Reversal: Enter when oscillator exceeds ±75 and reverses 2. Zero Line Momentum: Trade crosses of zero line with volume confirmation 3. Signal Line Strategy: Early entry on signal line crosses 4. Divergence Trading: Price makes new high/low but Fisher doesn't ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt | Quantitative Trading Systems Version: 1.0 Classification: Statistical Transform Oscillator Not financial advice. Always DYOR.
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AlphaNatt tarafından
Vector Sniper Pro What it is Vector Sniper (Simplified) is a single, original algorithm that flags impulsive “vector” moves only when volatility, volume, and structure align. It is not a mashup of other indicators; everything below is computed from raw OHLCV with a small, transparent ruleset. ⸻ Core idea (signal = force × participation × context) 1. Force (Volatility): • We z-score true range: trZ = (ATR(1) - SMA(ATR(1), N)) / StDev(ATR(1), N). • A move must exceed a user-set Volatility Z-Score. 2. Participation (Volume): • We z-score raw volume: volZ = (Vol - SMA(Vol, N)) / StDev(Vol, N). • Volume must also exceed a Volume Z-Score. 3. Context (Structure, Body, Imbalance, Traps): • Body% filter: real body / range ≥ Min Body %. • Delta-volume proxy: (bullVol − bearVol) / volume, where bullVol = volume*(close−low)/range and bearVol = volume*(high−close)/range. We require positive imbalance for bulls, negative for bears. • Structure break (optional): price must take out the prior N-bar high/low. • Trap detection (optional): spring/upthrust patterns defined by lower-low/upper-high followed by a close back inside. If the above align, you get a Bull Vector (green) or Bear Vector (red). “Extreme” vectors require the same conditions at a higher multiple (Ext Mult). ⸻ Noise control (pre-signal gate) Before a vector is allowed, a pre-signal score (0–7) must pass: • Checks include spring/upthrust, no-supply/no-demand, imbalance, volume > average, VWAP side alignment, EMA trend alignment, proximity to structure break, and candle direction. • You choose a minimum score, persistence (must occur ≥N times inside last M bars), cooldown after a pass, and hysteresis vs the opposite side. This prevents one-off blips and keeps signals directional. ⸻ Optional confluence • VWAP alignment: require price on the correct side and VWAP slope with it. • EMA filter: require EMA trend agreement. • HTF bias (optional): compare HTF close vs HTF EMA on a selected timeframe. • Implemented with request.security and no look-ahead; bias updates when the higher timeframe bar closes. ⸻ Visuals & alerts • Candle colors (5 total): • Green = Bull Vector, Red = Bear Vector. • Blue = Pre-Bull, Orange = Pre-Bear. • Gray = Neutral. • Markers (optional): diamonds = “Extreme” vectors; small triangles = pre-signals. • Built-in alerts: Bull Vector, Bear Vector, Extreme Bull/Bear, Pre-Bull, Pre-Bear. • Add from: Alerts → Condition → this script → choose event. ⸻ How to use (practical) 1. Start with defaults. Turn on VWAP and EMA filters; add HTF bias if you want fewer but cleaner signals. 2. Hunt for alignment: Pre-signal (blue/orange) → Vector (green/red) in the same direction. 3. Use your own risk model for entries/exits; the script does not place orders or compute stops/targets. ⸻ Inputs (plain English) • ATR/Volume Periods & Z-Scores: sensitivity to volatility/participation. • Extreme Multiplier: threshold for “Extreme” vectors. • Structure Break (bars) & Traps: contextual confirms. • Pre-signal gate: Min Score, Persistence (N in last M), Cooldown, Opposite-side lockout. • Confluence: VWAP side, EMA trend, optional HTF bias (timeframe + EMA length). • Visuals: candle painting and markers. ⸻ Design notes / limitations • Signals evaluate on bar close. Intrabar they can form and cancel; for consistency, trade on closed bars. • HTF bias is derived from closed HTF bars; no future data is used. • This is an indicator, not financial advice. Backtest forward and manage risk. ⸻ Why this isn’t a “mashup”: All components are purposeful and documented: z-score volatility + z-score volume (force & participation), body% and delta-volume (quality), structure & traps (context), and a scored, persistent pre-filter with VWAP/EMA/HTF alignment (noise control).
Pine Script® göstergesi
RickyTSpanish tarafından
2
RSI + Sell/Buy RatesEnglish follow Sell/Buy Rates = des barres vert/rouge qui mesurent la pression acheteurs vs vendeurs (calculé à partir des bougies et du volume), centrées sur 50. > 50 (vert) : acheteurs dominent. < 50 (rouge) : vendeurs dominent. Plus loin de 50 ⇒ plus fort. Avec le RSI : on ne fait que confirmer — RSI > 50 et barres > 50 → acheteurs ; RSI < 50 et barres < 50 → vendeurs ; sinon on s’abstient. Sell/Buy Rates = green/red bars that measure buyer vs. seller pressure (calculated from candles and volume), centered at 50. > 50 (green): buyers dominate. < 50 (red): sellers dominate. Farther from 50 ⇒ stronger. With RSI: it’s just a confirmation — RSI > 50 and bars > 50 → buyers; RSI < 50 and bars < 50 → sellers; otherwise, stand aside.
Pine Script® göstergesi
PhilArsouille tarafından
Supertrend [TradingConToto]Supertrend — ADX/DI + EMA Gap + Breakout (with Mobile UI) What makes it original Supertrend combines trend strength (ADX/DI), multi-timeframe bias (EMA63 and EMA 200D equivalent), a structural filter based on the distance between EMA2400 and EMA4800 expressed in ATR units, and a momentum confirmation through a previous high breakout. This is not a random mashup — it’s a sequence of filters designed to reduce trades in ranging markets and prioritize mature trends: Direction: +DI > -DI (trend led by buyers). Strength: ADX > mean(ADX) (avoids weak, choppy phases). Short-term bias: Close > EMA63. Long-term bias: Close > EMA4800 ≈ EMA200 daily on H1. Momentum: Close > High (immediate breakout). Structure: (EMA2400 − EMA4800) > k·ATR (ensures separation in ATR units, filters out flat phases). Entries & exits Entry: when all six conditions are met and no open position exists. Exit: if +DI < -DI or Close < EMA63. Visuals: EMA63 is painted green while in position and red otherwise, with a supertrend-style band; “BUY” labels appear below the green band and “SELL” labels above the red band. UI: includes a compact table (mobile-friendly) showing the state of each condition. Default parameters used in this publication Initial capital: 10,000 Position size: 10% of equity (≤10% per trade is considered sustainable). Commission: 0.01% per side (adjust to your broker/market). Slippage: 1 tick Pyramiding: 0 (only one position at a time) Adjust commission/slippage to match your market. For US equities, commissions are often per share; for spot crypto, 0.10–0.20% total is common. I publish with 0.01% per side as a conservative example to avoid overestimating results. Recommended backtest dataset Timeframe: H1 Multi-cycle window (e.g. 2015–today) Symbols with high liquidity (e.g. NASDAQ-100 large caps, or BTC/ETH spot) to generate 100+ trades. Avoid cherry-picked short windows. Why each filter matters +DI > -DI + ADX > mean: reduce counter-trend trades and weak signals. Close > EMA63 + Close > EMA4800: enforce trend alignment in short and long horizons. Breakout High : requires immediate momentum, avoids early entries. EMA gap in ATR units: blocks flat or compressed structures where EMA200D aligns with price. Limitations The breakout filter may skip healthy pullbacks; the design prioritizes continuation over perfect entry price. No fixed trailing stop/TP; exits depend on trend degradation via DI/EMA63. Results vary with real costs (commissions, slippage, funding). Adjust defaults to your broker. How to use Apply it on a clean chart (no other indicators when publishing). Keep in mind the default parameters above; if you change them, mention it in your notes and use the same values in the Strategy Tester. Ensure your dataset produces 100+ trades for statistical validity.
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toto_scalper_23 tarafından
1
Decision Matrix [Cnagda] — Adaptive Multi-Signal Trading SystemDecision Matrix is ​​a cutting-edge trading ecosystem that leverages the synergy of price action, volume dynamics, and key momentum indicators to create a powerful, real-time signal engine for traders. Key Features: Multi-Source Signal Fusion: Buy/Sell Power score, TWAP patterns, EMA/RSI crossovers, Volume zones — 7 layers of confirmation per candle. Adaptive Intelligence: Dynamic lookback window, label-size, and threshold are auto-adjusted based on market volatility. Volume Secrets Decoded: Adaptive ‘Low Volume’ (LV) candle detection reveals reversal and hidden accumulation patterns. Order Block Auto-Zoning: Detect Demand & Supply zones to highlight boxes on the chart — market structure is instantly clear. Heikin-Ashi Inspired Trend Mapping: Candle coloring based on trend intensity — clear visual feedback on every phase of a security. Intelligent Pattern Recognition: 4-candle TWAP & Volume structures help to quickly spot rare reversals and momentum shifts. Live Dashboard: Live Buy/Sell power on the chart, long/short trigger levels, multiple timeframes support — decision making lightning fast! Use Cases: Quick Reversal Detection Momentum Entry/Exit Confirmation False Breakout Filtering Volume-Driven Structural Insights Trailing Stop Placement based on True Demand/Supply Zones What difference will it make? Decision Matrix analyzes every uncertain market move from a multi-angle perspective to show where the market bias is right now, where is the best entry, when is the exit alert — and what is the real volume game behind every trend or even the most subtle reversal move — in just one glance! Every curated visual & signal will give you pure information clarity and high-confidence trading advantage.
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cnagda3 tarafından
Momentum Concepts [A1TradeHub]ℹ️ General Information — TSI + Stochastic Z-Score (Momentum Duo) Purpose: A two-oscillator stack that blends trend strength (TSI) with extreme-move normalization (Stochastic Z-Score) to time entries with confirmation instead of guessing tops/bottoms. Components Stochastic Z-Score (SZ): Converts price stretch into a bounded curve. Red zone ≈ overbought supply, Green zone ≈ oversold demand. The hook out of a band often marks turning points. True Strength Index (TSI): Measures momentum quality and direction. Signal/line cross = timing, Zero-line = trend filter, slope = acceleration. Core Read Alignment = edge: SZ leaves a band and TSI agrees (cross/slope). Divergences: Higher-low on SZ/TSI vs lower-low in price (bullish). Lower-high on SZ/TSI vs higher-high in price (bearish). Best when near bands. Mid-range = chop: Avoid trades when SZ is centered and TSI is flat. Best Practices Use structure (PDH/PDL, EMAs 13/48/200, trendlines) as context. Scale profits into opposing SZ band or on TSI flatten/cross-back. Place stops beyond the last swing or key EMA; skip high-volatility news. Timeframes Works on intraday (e.g., 5–15m) and swings (1h/4h). Use higher TF for bias, lower TF for entries. This combo is designed to keep you on the right side of momentum, act at band hooks with TSI confirmation, and stand down when conditions are indecisive. I. 🔴🟢 TSI Oscillator — Quick Guide What you’re seeing Lines: Fast TSI + slow Signal (both EMA-smoothed momentum). Zones: 🟢 Green = oversold, 🔴 Red = overbought, 0-line = trend regime. Long: 🟢 hook up → fast crosses above slow → ideally reclaim 0. Short: 🔴 roll down → fast crosses below slow → ideally lose 0. Exits: Trim into the opposite zone or on a cross back. Divergence: TSI ↑ vs price ↓ = bullish; TSI ↓ vs price ↑ = bearish. Avoid: Both lines chopping around 0. II. Stochastic Z-Score — Quick Guide Zones: 🔴 Red = overbought/supply, 🟢 Green = oversold/demand. Curve: Watch the hook out of a zone for the turn. Signals 🟢 Green Arrow (from Green zone): Momentum turns up → call/long bias. Enter on first pullback; stop under last swing/13-EMA. 🔻 Red/Bearish Arrow (from Red zone): Momentum rolls down → put/short bias. Enter on first lower-high; stop above last swing/13-EMA. ⚪ Ball = Momentum Shift: Early heads-up (slope change). Use as confirmation/add-on, not a standalone entry.
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A1TradingHub tarafından
Script_Algo - Double Smoothed CCI Strategy📉 The uniqueness of this non-trending oscillator strategy lies in the combination of two smoothed CCI lines: one signals entry into a position from overbought/oversold zones, and the other serves as a trend filter for entries. The smoothing of the fast and slow CCI lines significantly reduces market noise, allowing the filtering of false signals often generated by the standard CCI. 📚 For those unfamiliar with CCI: The Commodity Channel Index (CCI) is a momentum-based oscillator used to identify overbought and oversold conditions. It helps traders spot potential trend reversals or confirm trend strength by comparing the current price to its average over a period of time. 1️⃣ General Principle of Operation ⚡ Fast CCI: Generates main signals when exiting oversold and overbought zones. 📈 Slow CCI: Acts as a trend filter. For long positions, the slow CCI must be above zero (confirmation of an uptrend), and for short positions, it must be below zero (confirmation of a downtrend). This prevents the strategy from opening trades against the dominant trend. 🛡️ Dynamic ATR Stop-Loss: Unlike fixed-percentage stop-losses, a stop tied to the Average True Range (ATR) considers market volatility. During calm periods, the stop will be narrower, allowing for more profit capture. In highly volatile periods, the stop becomes wider, protecting against premature closures caused by noise. 📊 Comprehensive Risk Management: The strategy uses not only a take-profit based on signals (exit into the opposite zone) but also a protective ATR stop-loss and a mechanism to close trades upon receiving an opposite signal (e.g., closing a long when a short signal appears). 💡 Usefulness of the Strategy: 👨‍💻 For traders: Provides clear, mathematically justified entry and exit signals with built-in loss protection. 📉 For analysts: Visualizes the behavior of the double CCI on a separate panel, allowing study of the interaction of the fast and slow lines and their reaction to levels without mandatory trades. 📚 For learning: An excellent example of combining multiple indicators and capital management tools into a single trading system. 2️⃣ Detailed Algorithm Logic 📥 Long Entry Signals: The fast smoothed CCI was below the oversold level (oversold_level, e.g., -100) and crossed this level upward (fast_exits_oversold). The slow CCI at this moment is above zero (confirming an uptrend). If both conditions are met, a long position is opened. 📤 Long Exit: Happens under one of these conditions: The fast CCI crosses the overbought level (overbought_level) downward (exit_long). The price reaches a stop-loss level calculated as entry price - (ATR * multiplier). An opposite short signal appears (enter_short). 📥 Short Entry Signals: The fast CCI was above the overbought level (overbought_level, e.g., 100) and crossed this level downward (fast_exits_overbought). The slow CCI at this moment is below zero (confirming a downtrend). If both conditions are met, a short position is opened. 📤 Short Exit: Happens under one of these conditions: The fast CCI crosses the oversold level (oversold_level) upward (exit_short). The price reaches a stop-loss level calculated as entry price + (ATR * multiplier). An opposite long signal appears (enter_long). 3️⃣ Default Settings Description ⚙️ General Strategy Settings (strategy): overlay=false: The indicator is displayed in a separate panel below the chart, not overlaid on it. default_qty_type=strategy.cash, default_qty_value=1000, initial_capital=100000: The strategy manages a virtual capital of 100,000 USD, using 1,000 USD per trade. commission_value=0.1, slippage=1: Commission (0.1%) and slippage (1 tick) are considered for more realistic testing. ⚡ Fast CCI (Signal Generator): Length: 8 (short enough for quick price reactions). Source: hlc3 (average of High, Low, Close). Smoothing: WMA (Weighted Moving Average) for smoother results than SMA. Smoothing Length: 5 (removes part of the noise). 📈 Slow CCI (Trend Filter): Length: 20 (standard mid-term trend period). Source: close. Smoothing: WMA. Smoothing Length: 21 (even stronger smoothing for a clean trend line). 📊 Levels: Overbought Level: 100 (classic CCI level). Oversold Level: -100 (classic CCI level). 🛡️ Stop-Loss (ATR): ATR Length: 6 (short period for quick adaptation). ATR Multiplier: 10.0 (very wide stop, designed for long-term trade holding and noise filtering). 💰 As seen in backtests, this strategy shows a steadily growing equity curve with minor drawdowns. On the highly liquid crypto pair XRPUSDT, the algorithm demonstrated a fairly high win rate and relatively high profit factor on a 4-hour timeframe over 4 years, though the overall profit is moderate. ⚠️ Important Notes Always remember: Strategy results may not repeat in the future. The market constantly changes, so: ✅ Monitor the situation ✅ Backtest regularly ✅ Adjust settings for each asset Also remember about possible bugs in any algorithmic trading strategy. Even if a script is well-tested, no one knows what unpredictable events the market may bring tomorrow. ⚠️ Risk Management: Do not risk more than 1% of your deposit per trade, otherwise you may lose your account balance, since this strategy works without stop losses. ⚠️ Disclaimer The author of the strategy does not encourage anyone to use this algorithm and bears no responsibility for any possible financial losses resulting from its application! Any decision to use this strategy is made personally by the owners of TradingView accounts and cryptocurrency exchange accounts. 📝 Final Notes This is not the final version. I already have ideas on how to improve it further, so follow me to not miss updates. 🐞 Bug Reports If you notice any bugs or inconsistencies in my algorithm, please let me know — I will try to fix them as quickly as possible. 💬 Feedback & Suggestions If you have any ideas on how this or any of my other strategies can be improved, feel free to write to me. I will try to implement your suggestions in the script. Wishing everyone good luck and stable profits! 🚀💰
Pine Script® stratejisi
Script_Algo tarafından
Signal PainterSignal Painter is a trend-focused technical indicator that paints buy/sell signals only when a strong directional move is confirmed. It combines a momentum oscillator with a volatility filter to ensure signals occur during robust trends. In practice, the algorithm waits for price movement and momentum to exceed certain thresholds (for example, requiring both a surge in momentum and price range expansion) before marking a potential up-trend entry or down-trend entry on the chart. This means the system performs best in well-defined trending markets where such conditions are met consistently. In sideways or range-bound conditions, however, these strict requirements can be triggered by random fluctuations, reducing the indicator’s effectiveness (it may generate false or choppy signals when the market lacks clear direction). To adapt to a choppier market, traders can apply Signal Painter on a lower timeframe to make it more reactive to smaller price swings. This increases the frequency and quickness of signals (capturing short-term moves sooner) but at the cost of signal strength and reliability – lower-timeframe signals carry more noise and are less robust compared to signals on higher timeframes. In summary, Signal Painter is designed to highlight significant trend breakouts with visual cues on the chart, excelling during trending phases and cautioning users that its performance will degrade during sideways market conditions.
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CR-JE tarafından
1
RockstarrFX — Stochastic OB/OS Cross SignalsThe RockstarrFX Stochastic Cross Strategy (5/3/3) is a clean, professional-grade tool that plots %K and %D lines and generates buy/sell signals only in high-probability zones. 🔑 How it works: Buy (B): %K crosses above %D in/near oversold (≤22) Sell (S): %K crosses below %D in/near overbought (≥78) ⚙️ Features: Built on the classic Stochastic 5/3/3 oscillator Signals filtered to appear only in OB/OS regions (reducing false triggers) Default label size = Tiny (with options for Small/Normal) Optional OB/OS shading for quick context Mono-inspired muted colors for a clean charting experience 🔥 Designed for traders who rely on momentum shifts, reversals, and confluence setups. Works across all timeframes — forex, crypto, indices, and stocks. 🔍 Keywords (SEO): stochastic oscillator, stochastic cross strategy, overbought oversold signals, stochastic indicator, momentum trading, stochastic trading system, buy sell signals. ⚡ Part of the RockstarrFX 3-Step Setup Toolkit. ⚠️ Disclaimer: This script is published for educational purposes only. It is not financial advice and does not constitute a recommendation to buy or sell any financial instrument. Past performance is not indicative of future results. Always test on demo before using in live markets and trade responsibly.
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RockStarrFX tarafından
1
Savitzky-Golay Hampel Filter | AlphaNattSavitzky-Golay Hampel Filter | AlphaNatt A revolutionary indicator combining NASA's satellite data processing algorithms with robust statistical outlier detection to create the most scientifically advanced trend filter available on TradingView. "This is the same mathematics that processes signals from the Hubble Space Telescope and analyzes data from the Large Hadron Collider - now applied to financial markets." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 SCIENTIFIC PEDIGREE Savitzky-Golay Filter Applications: NASA: Satellite telemetry and space probe data processing CERN: Particle physics data analysis at the LHC Pharmaceutical: Chromatography and spectroscopy analysis Astronomy: Processing signals from radio telescopes Medical: ECG and EEG signal processing Hampel Filter Usage: Aerospace: Cleaning sensor data from aircraft and spacecraft Manufacturing: Quality control in precision engineering Seismology: Earthquake detection and analysis Robotics: Sensor fusion and noise reduction ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🧬 THE MATHEMATICS 1. Savitzky-Golay Filter The SG filter performs local polynomial regression on data points: Fits a polynomial of degree n to a sliding window of data Evaluates the polynomial at the center point Preserves higher moments (peaks, valleys) unlike moving averages Maintains derivative information for true momentum analysis Originally published in Analytical Chemistry (1964) Mathematical Properties: Optimal smoothing in the least-squares sense Preserves statistical moments up to polynomial order Exact derivative calculation without additional lag Superior frequency response vs traditional filters 2. Hampel Filter A robust outlier detector based on Median Absolute Deviation (MAD): Identifies outliers using robust statistics Replaces spurious values with polynomial-fitted estimates Resistant to up to 50% contaminated data MAD is 1.4826 times more robust than standard deviation Outlier Detection Formula: |x - median| > k × 1.4826 × MAD Where k is the threshold parameter (typically 3 for 99.7% confidence) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 WHY THIS IS SUPERIOR vs Moving Averages: Preserves peaks and valleys (critical for catching tops/bottoms) No lag penalty for smoothness Maintains derivative information Polynomial fitting > simple averaging vs Other Filters: Outlier immunity (Hampel component) Scientifically optimal smoothing Preserves higher-order features Used in billion-dollar research projects Unique Advantages: Feature Preservation: Maintains market structure while smoothing Spike Immunity: Ignores false breakouts and stop hunts Derivative Accuracy: True momentum without additional indicators Scientific Validation: 60+ years of academic research ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ PARAMETER OPTIMIZATION 1. Polynomial Order (2-5) 2 (Quadratic): Maximum smoothing, gentle curves 3 (Cubic): Balanced smoothing and responsiveness (recommended) 4-5 (Higher): More responsive, preserves more features 2. Window Size (7-51) Must be odd number Larger = smoother but more lag Formula: 2×(desired smoothing period) + 1 Default 21 = analyzes 10 bars each side 3. Hampel Threshold (1.0-5.0) 1.0: Aggressive outlier removal (68% confidence) 2.0: Moderate outlier removal (95% confidence) 3.0: Conservative outlier removal (99.7% confidence) (default) 4.0+: Only extreme outliers removed 4. Final Smoothing (1-7) Additional WMA smoothing after filtering 1 = No additional smoothing 3-5 = Recommended for most timeframes 7 = Ultra-smooth for position trading ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING STRATEGIES Signal Recognition: Cyan Line: Bullish trend with positive derivative Pink Line: Bearish trend with negative derivative Color Change: Trend reversal with polynomial confirmation 1. Trend Following Strategy Enter when price crosses above cyan filter Exit when filter turns pink Use filter as dynamic stop loss Best in trending markets 2. Mean Reversion Strategy Enter long when price touches filter from below in uptrend Enter short when price touches filter from above in downtrend Exit at opposite band or filter color change Excellent for range-bound markets 3. Derivative Strategy (Advanced) The SG filter preserves derivative information Acceleration = second derivative > 0 Enter on positive first derivative + positive acceleration Exit on negative second derivative (momentum slowing) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 PERFORMANCE CHARACTERISTICS Strengths: Outlier Immunity: Ignores stop hunts and flash crashes Feature Preservation: Catches tops/bottoms better than MAs Smooth Output: Reduces whipsaws significantly Scientific Basis: Not curve-fitted or optimized to markets Considerations: Slight lag in extreme volatility (all filters have this) Requires odd window sizes (mathematical requirement) More complex than simple moving averages Best with liquid instruments ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔬 SCIENTIFIC BACKGROUND Savitzky-Golay Publication: "Smoothing and Differentiation of Data by Simplified Least Squares Procedures" - Abraham Savitzky & Marcel Golay - Analytical Chemistry, Vol. 36, No. 8, 1964 Hampel Filter Origin: "Robust Statistics: The Approach Based on Influence Functions" - Frank Hampel et al., 1986 - Princeton University Press These techniques have been validated in thousands of scientific papers and are standard tools in: NASA's Jet Propulsion Laboratory European Space Agency CERN (Large Hadron Collider) MIT Lincoln Laboratory Max Planck Institutes ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 ADVANCED TIPS News Trading: Lower Hampel threshold before major events to catch spikes Scalping: Use Order=2 for maximum smoothness, Window=11 for responsiveness Position Trading: Increase Window to 31+ for long-term trends Combine with Volume: Strong trends need volume confirmation Multiple Timeframes: Use daily for trend, hourly for entry Watch the Derivative: Filter color changes when first derivative changes sign ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT NOTICES Not financial advice - educational purposes only Past performance does not guarantee future results Always use proper risk management Test settings on your specific instrument and timeframe No indicator is perfect - part of complete trading system ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏆 CONCLUSION The Savitzky-Golay Hampel Filter represents the pinnacle of scientific signal processing applied to financial markets. By combining polynomial regression with robust outlier detection, traders gain access to the same mathematical tools that: Guide spacecraft to other planets Detect gravitational waves from black holes Analyze particle collisions at near light-speed Process signals from deep space This isn't just another indicator - it's rocket science for trading . "When NASA needs to separate signal from noise in billion-dollar missions, they use these exact algorithms. Now you can too." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt Version: 1.0 Release: 2025 Pine Script: v6 "Where Space Technology Meets Market Analysis" Not financial advice. Always DYOR
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AlphaNatt tarafından
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TWAP OscillatorTWAP Oscillator (TOSC) A powerful mean reversion oscillator that measures price deviation from Time-Weighted Average Price (TWAP) in standard deviations, automatically adapting to your chart timeframe. How It Works: The TWAP Oscillator calculates the distance between current price and TWAP, expressed in standard deviations. Unlike VWAP which weights by volume, TWAP gives equal weight to each time period, making it ideal for: • Mean Reversion Trading - Identifies when price is statistically overextended from its time-weighted average • Trend Strength Analysis - Shows how far price has deviated from the TWAP baseline • Entry/Exit Timing - Provides objective levels for trade entries and exits Automatic Timeframe Adaptation: The indicator intelligently selects the appropriate TWAP period based on your chart timeframe: 1m Charts → 1D TWAP (intraday mean reversion) 3m-5m Charts → 7D TWAP (weekly perspective) 15m-1h Charts → 30D TWAP (monthly context) 4h-8h Charts → 90D TWAP (quarterly view) Daily Charts → 365D TWAP (yearly reference) Trading Days vs Calendar Days: Toggle between trading days (5D, 22D, 66D, 252D) or calendar days (7D, 30D, 90D, 365D) to match your analysis style. Divergence Analysis - High Probability Reversals: The most powerful signals occur when price and oscillator diverge at extreme levels: Bullish Divergence (Oversold): • Price makes lower lows • Oscillator makes higher lows • Both at oversold levels (-2 or lower) • Strong buy signal - price weakness not confirmed by TWAP Bearish Divergence (Overbought): • Price makes higher highs • Oscillator makes lower highs • Both at overbought levels (+2 or higher) • Strong sell signal - price strength not confirmed by TWAP Hidden Bullish Divergence: • Price makes higher lows • Oscillator makes lower lows • At oversold levels • Trend continuation signal - pullback in uptrend Hidden Bearish Divergence: • Price makes lower highs • Oscillator makes higher highs • At overbought levels • Trend continuation signal - rally in downtrend Divergence Confluence Zones: Maximum Confluence Setup: • Divergence at extreme levels (±2+ std dev) • Multiple timeframe confirmation • Key support/resistance levels • Volume confirmation • Highest probability reversal Divergence Trading Rules: • Wait for clear divergence formation • Confirm at extreme oscillator levels • Enter on divergence confirmation • Stop loss beyond recent swing • Target return to zero line or opposite extreme Key Features: • Zero Line - Neutral position where price equals TWAP • Overbought/Oversold Levels - Default ±2 standard deviations (customizable) • Smoothing - SMA filter to reduce noise • Info Table - Shows current values and timeframe mapping • Alerts - Zero line crosses and overbought/oversold conditions Trading Applications: Mean Reversion Strategy: • Enter long when oscillator crosses above oversold level (-2) • Enter short when oscillator crosses below overbought level (+2) • Exit when returning to zero line Trend Following: • Stay long while oscillator remains above zero • Stay short while oscillator remains below zero • Use extreme readings as potential reversal signals Risk Management: • Use overbought/oversold levels as stop-loss references • Scale position size based on oscillator magnitude • Combine with other indicators for confirmation Mathematical Foundation: Oscillator = (Current Price - TWAP) / Standard Deviation Where: • TWAP = Time-weighted average price over selected period • Standard Deviation = Statistical measure of price dispersion • Result = Number of standard deviations from mean Best Practices: • Use on higher timeframes for trend analysis • Use on lower timeframes for entry timing • Combine with volume analysis for confirmation • Adjust overbought/oversold levels based on market volatility • Consider market structure and support/resistance levels Perfect For: • Scalping - 1m charts with 1D TWAP • Day Trading - 5m-15m charts with 7D TWAP • Swing Trading - 1h-4h charts with 30D TWAP • Position Trading - Daily charts with 365D TWAP
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Swing Oracle Stock// (\_/) // ( •.•) // (")_(") 📌 Swing Oracle Stock – Professional Cycle & Trend Detection Indicator The Swing Oracle Stock is an advanced market analysis tool designed to highlight price cycles, trend shifts, and key trading zones with precision. It combines trendline dynamics, normalized oscillators, and multi-timeframe confirmation into a single comprehensive indicator. 🔑 Key Features NDOS (Normalized Dynamic Oscillator System): Measures price strength relative to recent highs and lows to detect overbought, neutral, and oversold zones. Dynamic Trendline (EMA8 or SMA231): Flexible source selection for adapting to different trading styles (scalping vs. swing). Multi-Timeframe H1 Confirmation: Adds higher-timeframe validation to improve signal reliability. Automated Buy & Sell Signals: Triggered only on significant crossovers above/below defined levels. Weekly Cycles (7-day M5 projection): Tracks recurring time-based market cycles to anticipate reversal points. Intuitive Visualization: Colored zones (high, low, neutral) for quick market context. Optional background and candlestick coloring for better clarity. Multi-Timeframe Cross Table: Automatically compares SMA50 vs. EMA200 across multiple timeframes (1m → 4h), showing clear status: ⭐️⬆️ UP = bullish trend confirmation 💀⬇️ Drop = bearish trend confirmation 📊 Built-in Statistical Tools Normalized difference between short and long EMA. Projected normalized mean levels plotted directly on the main chart. Dynamic analysis of price distance from SMA50 to capture market “waves.” 🎯 Use Cases Spot trend reversals with multi-timeframe confirmation. Identify powerful breakout and breakdown zones. Time entries and exits based on trend + cycle confluence. Enhance market timing for swing trades, scalps, or long-term positions. ⚡ Swing Oracle Stock brings together cycle detection, oscillator normalization, and multi-timeframe confirmation into one streamlined indicator for traders who want a professional edge.
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Momentum Index [BigBeluga]The Momentum Index is an innovative indicator designed to measure the momentum of price action by analyzing the distribution of positive and negative momentum values over a defined period. By incorporating delta-based calculations and smoothing techniques, it provides traders with a clear and actionable representation of market momentum dynamics. 🔵 Key Features: Delta-Based Momentum Analysis: Calculates the momentum of price by comparing its current state to its value from a defined number of bars back. Inside a loop, it evaluates whether momentum values are above or below zero, producing a delta value that reflects the net momentum direction and intensity. Double EMA Smoothing: Smooths the raw delta-based momentum values with a double EMA filter, reducing noise and providing a clearer trend signal. tmi(len) => sum = 0.0 sum1 = 0.0 above = 0.0 below = 0.0 src_ = src - src for i = 0 to len sum := sum + (src_ > nz(src_ ) ? 1 : -1) sum1 := sum1 + (sum > 0 ? 1 : -1) sum1 := emaEma(sum1, 10) for i = 1 to len above := above + (sum1 > 0 ? 1 : 0) below := below + (sum1 > 0 ? 0 : 1) Directional Momentum Signals: Generates momentum shift signals and displays them on both the oscillator and the main chart: - △ Aqua Triangles: Represent upward momentum shifts. - ▽ Red Triangles: Represent downward momentum shifts. Dynamic Gradient Display: Highlights momentum zones with gradient fills: - Aqua shades for positive momentum (above zero). - Red shades for negative momentum (below zero). Dashboard Display: A dashboard summarizing the count of momentum values above and below zero for the defined period (Sentiment Length e.g. 100), helping traders assess market sentiment at a glance. 🔵 How It Works: The indicator takes price momentum as its source and evaluates the number of momentum values above and below zero within a defined period. The delta calculation aggregates this information, providing a net representation of the prevailing market momentum. A double EMA filter is applied to the delta values, smoothing the momentum line and enhancing signal clarity. Momentum shifts are highlighted with visual signals on the oscillator and price chart, while the gradient display provides a visual representation of intensity. 🔵 Use Cases: Momentum Tracking: Identify whether market momentum is predominantly bullish or bearish. Signal Confirmation: Use chart-based signals to confirm potential trend reversals or continuation. Analyze Market Strength: Leverage the dashboard to quickly assess the distribution of momentum over the chosen period. Overbought/Oversold Conditions: Utilize gradient zones to detect areas of momentum extremes and possible price exhaustion. Momentum Index offers a refined approach to analyzing momentum dynamics, combining delta-based calculations with smoothing techniques and intuitive visuals, making it an essential tool for traders looking to anticipate market movements effectively.
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BigBeluga tarafından
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Artharjan ADXArtharjan ADX (AADX) by Rrahul Desai @Artharjan 📌 Overview The Artharjan ADX (AADX) is an advanced implementation of the Average Directional Index (ADX) with customizable moving averages, momentum thresholds, and visually intuitive grading of bullish and bearish strength. Unlike the standard ADX indicator that only shows trend strength, AADX adds graded bullish/bearish conditions, alerts, smoothed DI signals, histogram visualizations, and background color fills to help traders quickly interpret market conditions. It is designed for traders who want early detection of trend strength, clean visual cues, and automated alert triggers for both bullish and bearish momentum setups. ⚙️ Key Features 🔹 Customizable Calculations DI Length (default 13) – controls sensitivity of directional indicators. +/- DI Smoothing – smooths DI signals with user-selected MA. Multiple Moving Average Types – SMA, EMA, WMA, RMA, VWMA, ALMA, Hull, SWMA, SMMA, TMA. ADX Smoothing – define how smooth/fast the ADX reacts. 🔹 Flexible Display Toggle between line plots or histogram view. Adjustable plot thickness. Option to plot averages of ADX, +DI, -DI for confirmation. Configurable background fills: ADX above/below momentum threshold. ADX rising/falling color shading. Trend-grade based color intensity. 🔹 Momentum & Thresholds Momentum Level (default 25) → defines “strong trend” zone. Crossover Threshold (default 15) → helps detect early DI crossovers. Color-coded histogram bars for +DI vs -DI difference: Above/below zero. Rising/falling momentum. 🔹 Bullish & Bearish Grading System The indicator assigns grades from 1 to 5 for both bullish and bearish setups, based on DI and ADX conditions: Bullish Grades Grade 1 → Very Weak Bullish Grade 2 → Weak Bullish Grade 3 → Moderate Bullish Grade 4 → Strong Bullish Grade 5 → Very Strong Bullish Bearish Grades Grade 1 → Very Weak Bearish Grade 2 → Weak Bearish Grade 3 → Moderate Bearish Grade 4 → Strong Bearish Grade 5 → Very Strong Bearish Labels are automatically plotted above bars to indicate the active grade. 🔹 Alerts Bullish Alert → when +DI crosses above its average below the threshold OR bullish conditions are met. Bearish Alert → when -DI crosses above its average below the threshold OR bearish conditions are met. These alerts make it possible to automate trading signals for scalping, intraday, and swing trading. 📊 Use Cases Trend Strength Measurement Spot when markets shift from range-bound to trending. Confirm the reliability of breakouts with strong ADX readings. Bullish vs Bearish Control Compare +DI vs -DI strength to gauge trend direction. Identify trend reversals early with DI slope changes. Momentum Confirmation Use ADX rising + DI grades to validate trade entries. Filter false breakouts with weak ADX. Trade Grading System Enter aggressively on Grade 4–5 signals. Stay cautious on Grade 1–2 signals. Automated Alerts & Screening Combine AADX alerts with strategy rules. Build scanners to highlight strong ADX setups across multiple stocks. 🎯 Trader’s Advantage More powerful than standard ADX → Adds slope, grading, alerts, and visualization. Adaptable to any style → Works for intraday scalping, swing trading, and positional analysis. Visual clarity → Color fills, histograms, and labels simplify decision-making. Customizable smoothing → Adjusts to fast or slow markets. ✅ Closing Note The Artharjan ADX (AADX) transforms the traditional ADX into a complete trend and momentum analyzer. It helps traders detect, confirm, and act on directional strength with clarity and confidence. With Thanks, Rrahul Desai @Artharjan
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