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SPY EMA + VWAP Day Trading Strategy (Market Hours Only)//@version=5 indicator("SPY EMA + VWAP Day Trading Strategy (Market Hours Only)", overlay=true) // === Market Hours Filter (EST / New York Time) === nySession = input.session("0930-1600", "Market Session (NY Time)") inSession = time(timeframe.period, "America/New_York") >= time(nySession, "America/New_York") // EMAs ema9 = ta.ema(close, 9) ema21 = ta.ema(close, 21) // VWAP vwap = ta.vwap(close) // Plot EMAs & VWAP plot(ema9, "EMA 9", color=color.green, linewidth=2) plot(ema21, "EMA 21", color=color.orange, linewidth=2) plot(vwap, "VWAP", color=color.blue, linewidth=2) // ----------- Signals ----------- long_raw = close > ema9 and ema9 > ema21 and close > vwap and ta.crossover(ema9, ema21) short_raw = close < ema9 and ema9 < ema21 and close < vwap and ta.crossunder(ema9, ema21) // Apply Market Hours Filter long_signal = long_raw and inSession short_signal = short_raw and inSession // Plot Signals plotshape(long_signal, title="BUY", style=shape.labelup, location=location.belowbar, color=color.green, size=size.small, text="BUY") plotshape(short_signal, title="SELL", style=shape.labeldown, location=location.abovebar, color=color.red, size=size.small, text="SELL") // Alerts alertcondition(long_signal, title="BUY Alert", message="BUY Signal (Market Hours Only)") alertcondition(short_signal, title="SELL Alert", message="SELL Signal (Market Hours Only)")
Chỉ báo Pine Script®
của hungryPiex3L
ES-VIX Daily Price Bands - Inner bands (80% and 50%)ES-VIX Daily Price Bands This indicator plots dynamic intraday price bands for ES futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets. Formulas: Upper Band = Daily Low + (ES Price × VIX ÷ √252 ÷ 100) Lower Band = Daily High - (ES Price × VIX ÷ √252 ÷ 100) The calculation uses the square root of 252 (trading days per year) to convert annualized VIX volatility into an expected daily move, then scales it as a percentage adjustment from the current day's extremes. Features: Real-time band calculation that updates throughout the trading session Upper band (green) extends from the current day's low Lower band (red) contracts from the current day's high Inner upper band (green) at 50% of expected move Inner lower band (red) at 50% of expected move Middle Inner upper band (green) at 80% of expected move Middle Inner lower band (red) at 80% of expected move Shaded zone between bands for visual clarity Information table displaying: Current ES price and VIX level Running daily high and low Current upper and lower band values
Chỉ báo Pine Script®
của alanjeremiebarbe
ES-VIX Daily Price BandsES-VIX Daily Price Bands This indicator plots dynamic intraday price bands for ES futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets. Formulas: Upper Band = Daily Low + (ES Price × VIX ÷ √252 ÷ 100) Lower Band = Daily High - (ES Price × VIX ÷ √252 ÷ 100) The calculation uses the square root of 252 (trading days per year) to convert annualized VIX volatility into an expected daily move, then scales it as a percentage adjustment from the current day's extremes. Features: Real-time band calculation that updates throughout the trading session Upper band (green) extends from the current day's low Lower band (red) contracts from the current day's high Shaded zone between bands for visual clarity Information table displaying: Current ES price and VIX level Running daily high and low Current upper and lower band values
Chỉ báo Pine Script®
của alanjeremiebarbe
SymFlex Band - MAD, RSI, ATRThe SymFlex Band is an adaptive volatility and momentum framework that merges three independent band models into a unified analytical tool. • The MAD Band measures deviation from the moving average using Median Absolute Deviation, providing a stable view of range-based volatility. • The RSI Momentum Band adjusts its upper and lower boundaries asymmetrically, expanding in the direction of momentum and contracting against it. • The ATR Band captures classical volatility expansion for breakout and trend-continuation conditions. Rather than placing the three indicators separately on a chart, the script synchronizes their center-line logic, compares their band distances, identifies the nearest active band, and displays real-time correlation between their dynamic ranges. This structure helps traders understand whether price behavior is dominated by range compression, momentum imbalance, or volatility expansion. The table summarizes: • active band ranges • breakout status • distance from each band • cross-band correlation This indicator is designed purely for analysis. It does not generate trade entries.
Chỉ báo Pine Script®
của surirang
ES-VIX Daily Price Bands - Inner bandsES-VIX Daily Price Bands This indicator plots dynamic intraday price bands for ES futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets. Formulas: Upper Band = Daily Low + (ES Price × VIX ÷ √252 ÷ 100) Lower Band = Daily High - (ES Price × VIX ÷ √252 ÷ 100) The calculation uses the square root of 252 (trading days per year) to convert annualized VIX volatility into an expected daily move, then scales it as a percentage adjustment from the current day's extremes. Features: Real-time band calculation that updates throughout the trading session Upper band (green) extends from the current day's low Lower band (red) contracts from the current day's high Inner upper band (green) at 50% of expected move Inner lower band (red) at 50% of expected move Shaded zone between bands for visual clarity Information table displaying: Current ES price and VIX level Running daily high and low Current upper and lower band values
Chỉ báo Pine Script®
của alanjeremiebarbe
Session Markers - JDK AnalysisSession Markers is a tool designed to study how markets behave during specific, recurring time windows. Many traders know that price behaves differently depending on the day of the week, the time of the day, or particular market sessions such as the weekly open, the London session, or the New York open. This indicator makes those recurring windows visible on the chart and then analyzes what price typically does inside them. The result is a clear statistical understanding of how a chosen session behaves, both in direction and in strength. The script works by allowing the trader to define any time window using a start day and time and an end day and time. Every time this window occurs on the chart, the indicator highlights it with a full-height vertical band. These visual markers reveal patterns that are otherwise difficult to detect manually, such as whether certain sessions tend to trend, reverse, consolidate, or create large imbalances. They also help the trader quickly scan through historical price action to see how the market has behaved under similar conditions. For every completed session window, the indicator measures how much price changed from the moment the window began to the moment it ended. Instead of using raw price differences, it converts these changes into percentage moves. This makes the measurement consistent across different price ranges and market regimes. A one-percent move always has the same meaning, whether the asset is trading at 100 or 50,000. These percentage moves are collected for a user-selected number of past sessions, creating a dataset of how the market has behaved in the chosen time window. Based on this dataset, the indicator generates several statistics. It counts how many past sessions closed higher and how many closed lower, producing a directional tendency. It also computes the probability of an upward session by dividing the number of positive sessions by the total. More importantly, it calculates the average percentage movement for all sessions in the lookback period. This average move reflects not just the direction but also the magnitude of price changes. A session with frequent small upward moves but occasional large downward moves will show a negative average movement, even if more sessions ended positive. This creates a more realistic representation of true market behavior. Using this average movement, the script determines a “Bias” for the session. If the average percentage move is positive, the bias is considered bullish. If it is negative, the bias is bearish. If the values are very close to zero, the bias is neutral. This way, the indicator takes both frequency and impact into account, producing a magnitude-aware assessment instead of one that only counts wins and losses. A sequence such as +5%, –1% results in a bullish bias because the overall impact is strongly positive. On the other hand, a series of small gains followed by a large drop produces a bearish bias even if more sessions ended positive, because the large move dominates the average. This provides a far more truthful picture of what the market tends to do during the chosen window. All relevant statistics are displayed neatly in a small panel in the top-right corner of the chart. The panel updates in real time as new sessions complete and older ones fall out of the lookback range. It shows how many sessions were analyzed, how many ended up or down, the probability of an upward move, the average percentage change, and the final bias. The background color of the panel instantly reflects that bias, making it easy to interpret at a glance. To use the tool effectively, the trader simply needs to define a time window of interest. This could be something like the weekly opening window from Sunday to Monday, the London open each day, or even a unique custom window. After selecting how many past sessions to analyze, the indicator takes care of the rest. The vertical session markers reveal the structure visually. The statistics summarize the historical behavior objectively. The magnitude-weighted bias provides a realistic indication of whether the window tends to produce upward or downward movement on average. Session Markers is helpful because it translates repeated market timing behavior into measurable data. It exposes hidden tendencies that are easy to feel intuitively but hard to quantify manually. By analyzing both direction and magnitude, it prevents misleading interpretations that can arise from looking only at win rates. It helps traders understand whether a session typically produces meaningful moves or just small noise, whether it tends to trend or reverse, and whether its behavior has recently changed. Whether used for bias building, session filtering, or deeper market research, it offers a structured framework for understanding the market through time-based patterns.
Chỉ báo Pine Script®
của JDK-Analysis
CIHAN SCALP PRO v3 ELITEI’m sharing a testable scalping strategy: When you see a Long or Short signal, you can open a position without waiting for the candle to close and take quick profits with a short TP. But the real game-changer is coming soon! The Professional Scalping System I’ve been working on, with 85%+ accuracy, is almost ready. This system is fully mechanical — no analysis needed, it instantly catches momentum and trend shifts. It will be available soon with a small monthly subscription fee. Stay tuned!
Chỉ báo Pine Script®
của cihank12378
1
Grok/Claude Turtle Soup Alert SystemReplaces previous Turtle Soup Strategy/Indicator as Tradingview will not let me update it. # 🥣 Turtle Soup Strategy (Enhanced) ## A Mean-Reversion Strategy Based on Failed Breakouts --- ## Historical Origins ### The Original Turtle Traders (1983-1988) The Turtle Trading system is one of the most famous experiments in trading history. In 1983, legendary commodities trader **Richard Dennis** made a bet with his partner **William Eckhardt** about whether great traders were born or made. Dennis believed trading could be taught; Eckhardt believed it was innate. To settle the debate, Dennis recruited 23 ordinary people through newspaper ads—including a professional blackjack player, a fantasy game designer, and an accountant—and taught them his trading system in just two weeks. He called them "Turtles" after turtle farms he had visited in Singapore, saying *"We are going to grow traders just like they grow turtles in Singapore."* The results were extraordinary. Over the next five years, the Turtles reportedly earned over **$175 million in profits**. The experiment proved Dennis right: trading could indeed be taught. #### The Original Turtle Rules: - **Entry:** Buy when price breaks above the 20-day high (System 1) or 55-day high (System 2) - **Exit:** Sell when price breaks below the 10-day low (System 1) or 20-day low (System 2) - **Stop Loss:** 2x ATR (Average True Range) from entry - **Position Sizing:** Based on volatility (ATR) - **Philosophy:** Pure trend-following—catch big moves by riding breakouts The Turtle system was a **trend-following** strategy that assumed breakouts would lead to sustained trends. It worked brilliantly in trending markets but suffered during choppy, range-bound conditions. --- ### The Turtle Soup Strategy (1990s) In the 1990s, renowned trader **Linda Bradford Raschke** (along with Larry Connors) observed something interesting: many of the breakouts that the Turtle system traded actually *failed*. Price would spike above the 20-day high, trigger Turtle buy orders, then immediately reverse—trapping the breakout traders. Raschke realized these failed breakouts were predictable and tradeable. She developed the **Turtle Soup** strategy, which does the *exact opposite* of the original Turtle system: > *"Instead of buying the breakout, we wait for it to fail—then fade it."* The name "Turtle Soup" is a clever play on words: the strategy essentially "eats" the Turtles by trading against them when their breakouts fail. #### Original Turtle Soup Rules: - **Setup:** Price makes a new 20-day high (or low) - **Qualifier:** The previous 20-day high must be at least 3-4 days old (not a fresh breakout) - **Entry Trigger:** Price reverses back inside the channel (failed breakout) - **Entry:** Go SHORT (against the failed breakout above), or LONG (against the failed breakdown below) - **Philosophy:** Mean-reversion—fade false breakouts and profit from trapped traders #### Turtle Soup Plus One Variant: Raschke also developed a more conservative variant called "Turtle Soup Plus One" which waits for the *next bar* after the breakout to confirm the failure before entering. This reduces false signals but may miss some opportunities. --- ## Our Enhanced Turtle Soup Strategy We have taken the classic Turtle Soup concept and enhanced it with modern technical indicators and filters to improve signal quality and adapt to today's markets. ### Core Logic Preserved The fundamental strategy remains true to Raschke's original concept: | Turtle (Original) | Turtle Soup (Our Strategy) | |-------------------|---------------------------| | BUY breakout above 20-day high | SHORT when that breakout FAILS | | SELL breakout below 20-day low | LONG when that breakdown FAILS | | Trend-following | Mean-reversion | | "The trend is your friend" | "Failed breakouts trap traders" | --- ### Enhancements & Improvements #### 1. RSI Exhaustion Filter **Addition:** RSI must confirm exhaustion before entry - **For SHORT entries:** RSI > 60 (buyers exhausted) - **For LONG entries:** RSI < 40 (sellers exhausted) **Why:** The original Turtle Soup had no momentum filter. Adding RSI ensures we only fade breakouts when the market is showing signs of exhaustion, significantly reducing false signals. This enhancement was inspired by later traders who found RSI extremes (originally 90/10, softened to 60/40) dramatically improved win rates. #### 2. ADX Trending Filter **Addition:** ADX must be > 20 for trades to execute **Why:** While the original Turtle Soup was designed for ranging markets, we found that requiring *some* trend strength (ADX > 20) actually improves results. This ensures we're trading in markets with enough directional movement to create meaningful failed breakouts, rather than random noise in dead markets. #### 3. Heikin Ashi Smoothing **Addition:** Optional Heikin Ashi calculations for breakout detection **Why:** Heikin Ashi candles smooth out price noise and make trend reversals more visible. When enabled, the strategy uses HA values to detect breakouts and failures, reducing whipsaws from erratic price spikes. #### 4. Dynamic Donchian Channels with Regime Detection **Addition:** Color-coded channels based on market regime - 🟢 **Green:** Bullish regime (uptrend + DI+ > DI- + OBV bullish) - 🔴 **Red:** Bearish regime (downtrend + DI- > DI+ + OBV bearish) - 🟡 **Yellow:** Neutral regime **Why:** Visual regime detection helps traders understand the broader market context. The original Turtle Soup had no regime awareness—our enhancement lets traders see at a glance whether conditions favor the strategy. #### 5. Volume Spike Detection (Optional) **Addition:** Optional filter requiring volume surge on the breakout bar **Why:** Failed breakouts are more significant when they occur on high volume. A volume spike on the breakout bar (default 1.2x average) indicates more traders got trapped, creating stronger reversal potential. #### 6. ATR-Based Stops and Targets **Addition:** Configurable ATR-based stop losses and profit targets - **Stop Loss:** 1.5x ATR (default) - **Profit Target:** 2.0x ATR (default) **Why:** The original Turtle Soup used fixed stop placement. ATR-based stops adapt to current volatility, providing tighter stops in calm markets and wider stops in volatile conditions. #### 7. Signal Cooldown **Addition:** Minimum bars between trades (default 5) **Why:** Prevents overtrading during choppy conditions where multiple failed breakouts might occur in quick succession. #### 8. Real-Time Info Panel **Addition:** Comprehensive dashboard showing: - Current regime (Bullish/Bearish/Neutral) - RSI value and zone - ADX value and trending status - Breakout status - Bars since last high/low - Current setup status - Position status **Why:** Gives traders instant visibility into all strategy conditions without needing to check multiple indicators. --- ## Entry Rules Summary ### SHORT Entry (Fading Failed Breakout Above) 1. ✅ Price breaks ABOVE the 20-period Donchian high 2. ✅ Previous 20-period high was at least 1 bar ago 3. ✅ Price closes back BELOW the Donchian high (failed breakout) 4. ✅ RSI > 60 (exhausted buyers) 5. ✅ ADX > 20 (trending market) 6. ✅ Cooldown period met → **Enter SHORT**, betting the breakout will fail ### LONG Entry (Fading Failed Breakdown Below) 1. ✅ Price breaks BELOW the 20-period Donchian low 2. ✅ Previous 20-period low was at least 1 bar ago 3. ✅ Price closes back ABOVE the Donchian low (failed breakdown) 4. ✅ RSI < 40 (exhausted sellers) 5. ✅ ADX > 20 (trending market) 6. ✅ Cooldown period met → **Enter LONG**, betting the breakdown will fail --- ## Exit Rules 1. **ATR Stop Loss:** Position closed if price moves 1.5x ATR against entry 2. **ATR Profit Target:** Position closed if price moves 2.0x ATR in favor 3. **Channel Exit:** Position closed if price breaks the exit channel in the opposite direction 4. **Mid-Channel Exit:** Position closed if price returns to channel midpoint --- ## Best Market Conditions The Turtle Soup strategy performs best when: - ✅ Markets are prone to false breakouts - ✅ Volatility is moderate (not too low, not extreme) - ✅ Price is oscillating within a broader range - ✅ There are clear support/resistance levels The strategy may struggle when: - ❌ Strong trends persist (breakouts follow through) - ❌ Volatility is extremely low (no meaningful breakouts) - ❌ Markets are in news-driven directional moves --- ## Default Settings | Parameter | Default | Description | |-----------|---------|-------------| | Lookback Period | 20 | Donchian channel period | | Min Bars Since Extreme | 1 | Bars since last high/low | | RSI Length | 14 | RSI calculation period | | RSI Short Level | 60 | RSI must be above this for shorts | | RSI Long Level | 40 | RSI must be below this for longs | | ADX Length | 14 | ADX calculation period | | ADX Threshold | 20 | Minimum ADX for trades | | ATR Period | 20 | ATR calculation period | | ATR Stop Multiplier | 1.5 | Stop loss distance in ATR | | ATR Target Multiplier | 2.0 | Profit target distance in ATR | | Cooldown Period | 5 | Minimum bars between trades | | Volume Multiplier | 1.2 | Volume spike threshold | --- ## Philosophy > *"The Turtle system made millions by following breakouts. The Turtle Soup strategy makes money when those breakouts fail. In trading, there's always someone on the other side of the trade—this strategy profits by being the smart money that fades the trapped breakout traders."* The beauty of the Turtle Soup strategy is its elegant simplicity: it exploits a known, repeatable pattern (failed breakouts) while using modern filters (RSI, ADX) to improve timing and reduce false signals. --- ## Credits - **Original Turtle System:** Richard Dennis & William Eckhardt (1983) - **Turtle Soup Strategy:** Linda Bradford Raschke & Larry Connors (1990s) - **RSI Enhancement:** Various traders who discovered RSI extremes improve reversal detection - **This Implementation:** Enhanced with Heikin Ashi smoothing, regime detection, ADX filtering, and comprehensive visualization --- *"We're not following the turtles—we're making soup out of them."* 🥣
Chỉ báo Pine Script®
của ralis24
NQ-VIX Expected Move LTF LevelsNQ -VIX LTF Price Bands This indicator plots dynamic intraday price bands for NQ futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets. Formulas: Upper Band = (Input TF Open) + (NQ Price × VIX x √(Input TF ÷ (23h in min) ) ÷ 100 Lower Band = Daily Open - (NQ Price × VIX x √(Input TF ÷ (23h in min) ) ÷ 100 The calculation uses the square root of Input TF ÷ (23h in min) to convert annualized VIX volatility into an expected TF move, then scales it as a percentage adjustment from the current TF input's open. Features: Real-time band calculation that updates throughout the trading session Upper band (green) extends from the current TF's open Lower band (red) contracts from the current TF's open Inner upper band (green) at 50% of expected move Inner lower band (red) at 50% of expected move Middle Inner upper band (green) at 80% of expected move Middle Inner lower band (red) at 80% of expected move Information table displaying: Current input TF Current NQ price and VIX level Current input TF Open Expected move
Chỉ báo Pine Script®
của alanjeremiebarbe
ES-VIX Expected Move LTF LevelsES-VIX LTF Price Bands This indicator plots dynamic intraday price bands for ES futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets. Formulas: Upper Band = (Input TF Open) + (ES Price × VIX x √(Input TF ÷ (23h in min) ) ÷ 100 Lower Band = Daily Open - (ES Price × VIX x √(Input TF ÷ (23h in min) ) ÷ 100 The calculation uses the square root of Input TF ÷ (23h in min) to convert annualized VIX volatility into an expected TF move, then scales it as a percentage adjustment from the current TF input's open. Features: Real-time band calculation that updates throughout the trading session Upper band (green) extends from the current TF's open Lower band (red) contracts from the current TF's open Inner upper band (green) at 50% of expected move Inner lower band (red) at 50% of expected move Middle Inner upper band (green) at 80% of expected move Middle Inner lower band (red) at 80% of expected move Information table displaying: Current input TF Current ES price and VIX level Current input TF Open Expected move
Chỉ báo Pine Script®
của alanjeremiebarbe
ES-VIX Expected Move - Open basedES-VIX Daily Price Bands This indicator plots dynamic intraday price bands for ES futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets. Formulas: Upper Band = Daily Open + (ES Price × VIX ÷ √252 ÷ 100) Lower Band = Daily Open - (ES Price × VIX ÷ √252 ÷ 100) The calculation uses the square root of 252 (trading days per year) to convert annualized VIX volatility into an expected daily move, then scales it as a percentage adjustment from the current day's open. Features: Real-time band calculation that updates throughout the trading session Upper band (green) extends from the current day's open Lower band (red) contracts from the current day's open Inner upper band (green) at 50% of expected move Inner lower band (red) at 50% of expected move Middle Inner upper band (green) at 80% of expected move Middle Inner lower band (red) at 80% of expected move Information table displaying: Current ES price and VIX level Daily Open Expected move
Chỉ báo Pine Script®
của alanjeremiebarbe