MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal.
Purpose of the Indicator
MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior.
Why a Trader Should Use It
Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky.
Why These Components Were Chosen
Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise.
Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1.
Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale.
Market Mode (Regime) : Based on those ranks, MERV classifies the market:
Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity.
Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market.
Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy.
The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral.
Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions.
What Makes MERV Stand Out
Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique.
Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers.
Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds.
Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals.
Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other.
Recommended Timeframes
MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice:
Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends.
Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles.
Scalpers might find MERV too “slow” unless input lengths are set very low.
In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas.
How the Scoring/Logic Works (Step-by-Step)
Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy.
Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are.
Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on .
Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line.
Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action.
Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value.
Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only.
Oscillator Plot – How to Read It
The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element:
Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed.
Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength.
Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close.
Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero.
Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable.
Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime.
Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star).
Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance.
Dashboard (Fixed Corner Panel)
MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows:
Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high).
Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line.
Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle.
Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly.
Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color.
Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low.
Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe.
In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state.
Real-Life Example
Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case.
Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve.
Example: How It Looks in Action
Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m)
What it means:
The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume.
Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h)
What it means:
This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success.
Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m)
What it means:
The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping.
Settings and Inputs
The script is fully open-source; here are key inputs the user can adjust:
Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity.
Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect.
Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action.
Show Heatmap : Toggles the entropy background coloring on/off.
Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red).
Show Mode Bar : Turn the bottom mode bar on/off.
Show Dashboard : Turn the fixed table panel on/off.
Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired.
Oscillator Interpretation (Recap)
Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile).
Fill : Orange tinted area between them (for visual emphasis).
Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom).
Star Line : White star = ideal conditions, Gold = good but not ideal.
Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric.
Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly.
Disclaimer
This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly.
-BullByte
Analisis Trend
RRG RS-Ratio & Momentum – XLF, XLV, XLI vs SPY – Ion JaureguiRRG RS-Ratio & Momentum – XLF, XLV, XLI vs SPY – Ion Jauregui
📘 What does this script do?
This indicator simulates a Relative Rotation Graph (RRG), analyzing the sector rotation of three major U.S. market ETFs:
🟥 XLF – Financial Sector
🟦 XLV – Health Care Sector
🟩 XLI – Industrial Sector
Each is compared against SPY (S&P 500 ETF) as the benchmark.
⚙️ How does it work?
The script calculates two key RRG components:
RS-Ratio (Relative Strength Ratio):
Measures the strength of each sector relative to SPY.
Values above 100 = outperforming SPY
Values below 100 = underperforming SPY
Momentum of RS-Ratio:
Measures the change in RS-Ratio, helping to visualize rotation speed and direction.
These are computed using smoothed relative strength ratios and standard deviation over a user-defined period.
📈 What does it plot?
Colored lines representing the RS-Ratio of each sector versus SPY:
🔴 XLF (Financials)
🔵 XLV (Health Care)
🟢 XLI (Industrials)
Optionally, you can display Momentum as bar charts in a separate panel.
🧩 How to interpret the chart?
This tool helps visualize where each sector is in its relative strength cycle:
📈 Rising RS-Ratio + Positive Momentum → Sector is leading
📉 Falling RS-Ratio + Negative Momentum → Sector is weakening
Momentum shifts often signal early rotations before RS-Ratio reversals
🛠 Technical details:
Compatible with any timeframe (daily or weekly recommended)
🖊 Author:
Ion Jauregui – Analyst at ActivTrades
Designed to provide a visual and accessible approach to sector rotation versus SPY.
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The information provided does not constitute investment research. The material has not been prepared in accordance with the legal requirements designed to promote the independence of investment research and such should be considered a marketing communication.
All information has been prepared by ActivTrades ("AT"). The information does not contain a record of AT's prices, or an offer of or solicitation for a transaction in any financial instrument. No representation or warranty is given as to the accuracy or completeness of this information.
Any material provided does not have regard to the specific investment objective and financial situation of any person who may receive it. Past performance and forecasting are not a synonym of a reliable indicator of future performance. AT provides an execution-only service. Consequently, any person acting on the information provided does so at their own risk. Political risk is unpredictable. Central bank actions can vary. Platform tools do not guarantee success.
INDICATORS RISK ADVICE: The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by ActivTrades. This script intends to help follow the trend and filter out market noise. This script is meant for the use of international users. This script is not meant for the use of Spain users.
Altcoin Season Index [by ADI]A version of the Altcoin Season Index script, based on the methodology from BlockchainCenter (Top 40 altcoins, 90-day window, 75% rule), using CoinMarketCap + 7CryptoRisen + 7Datawallet sources. The script compares the return of each selected altcoin against BTC and plots a percentage-based indicator.
List of supported altcoins
BINANCE:ETHUSDC
BINANCE:BNBUSDC
BINANCE:SOLUSDC
BINANCE:XRPUSDC
BINANCE:ADAUSDC
BINANCE:DOGEUSDC
BINANCE:AVAXUSDC
BINANCE:DOTUSDC
BINANCE:LINKUSDC
BINANCE:LTCUSDC
BINANCE:XLMUSDC
BINANCE:SUIUSDC
BINANCE:BCHUSDC
BINANCE:VETUSDC
BINANCE:BONKUSDC
BINANCE:TONUSDC
BINANCE:SHIBUSDC
BINANCE:PEPEUSDC
BINANCE:GALAUSDC
BINANCE:BOMEUSDC
BINANCE:WIFUSDC
BINANCE:AAVEUSDC
BINANCE:FLOKIUSDC
BINANCE:FETUSDC
BINANCE:NEARUSDC
BINANCE:ETCUSDC
BINANCE:MANTAUSDC
BINANCE:WLDUSDC
BINANCE:ONDOUSDC
BINANCE:JUPUSDC
BINANCE:APTUSDC
BINANCE:PENGUUSDC
BINANCE:ARBUSDC
BINANCE:BONKUSDC
BINANCE:ATOMUSDC
BINANCE:TRUMPUSDC
BINANCE:TIAUSDC
BINANCE:FILUSDC
BINANCE:RENDERUSDC
BINANCE:ATOMUSDC
Detailed Monthly Seasonality Table By TheNextronThe "Detailed Monthly Seasonality Table" script is a Pine Script v6 TradingView indicator designed to visually analyze monthly performance trends for any security. It computes and displays how price behaves month-by-month over a user-defined number of years, offering a clean, data-rich dashboard for evaluating seasonal trading patterns.
📊 Purpose:
To help traders identify which months tend to be bullish or bearish, and how consistently the price reacts during those months, based on historical closing prices.
🧩 Key Features:
✅ User Inputs
Years to Analyze: How many past years to include in the analysis (e.g., 5–20 years).
Result Display Options:
% Change or Point Change
Toggle to show absolute performance or color-coded gain/loss
📅 Monthly Analysis Logic
For each month (Jan to Dec), the script:
Gathers historical data year by year
Calculates monthly return based on selected price type
📋 Dashboard Output
A custom table on the chart showing:
Each month's average % return
Win rate
Number of times the month was positive (green) or negative (red)
BUY in HASH RibbonsHash Ribbons Indicator (BUY Signal)
A TradingView Pine Script v6 implementation for identifying Bitcoin miner capitulation (“Springs”) and recovery phases based on hash rate data. It marks potential low-risk buying opportunities by tracking short- and long-term moving averages of the network hash rate.
⸻
Key Features
• Hash Rate SMAs
• Short-term SMA (default: 30 days)
• Long-term SMA (default: 60 days)
• Phase Markers
• Gray circle: Short SMA crosses below long SMA (start of capitulation)
• White circles: Ongoing capitulation, with brighter white when the short SMA turns upward
• Yellow circle: Short SMA crosses back above long SMA (end of capitulation)
• Orange circle: Buy signal once hash rate recovery aligns with bullish price momentum (10-day price SMA crosses above 20-day price SMA)
• Display Modes
• Ribbons: Plots the two SMAs as colored bands—red for capitulation, green for recovery
• Oscillator: Shows the percentage difference between SMAs as a histogram (red for negative, blue for positive)
• Optional Overlays
• Bitcoin halving dates (2012, 2016, 2020, 2024) with dashed lines and labels
• Raw hash rate data in EH/s
• Alerts
• Configurable alerts for capitulation start, recovery, and buy signals
⸻
How It Works
1. Data Source: Fetches daily hash rate values from a selected provider (e.g., IntoTheBlock, Quandl).
2. Capitulation Detection: When the 30-day SMA falls below the 60-day SMA, miners are likely capitulating.
3. Recovery Identification: A rising 30-day SMA during capitulation signals miner recovery.
4. Buy Signal: Confirmed when the hash rate recovery coincides with a bullish shift in price momentum (10-day price SMA > 20-day price SMA).
⸻
Inputs
Hash Rate Short SMA: 30 days
Hash Rate Long SMA: 60 days
Plot Signals: On
Plot Halvings: Off
Plot Raw Hash Rate: Off
⸻
Considerations
• Timeframe: Best applied on daily charts to capture meaningful miner behavior.
• Data Reliability: Ensure the chosen hash rate source provides consistent, gap-free data.
• Risk Management: Use alongside other technical indicators (e.g., RSI, MACD) and fundamental analysis.
• Backtesting: Evaluate performance over different market cycles before live deployment.
TrendSurfer VF 3.4Questo è il mio Trend Surfer.
I triangoli indicano candele direzionali con vari livelli di volume all'interno da 1 a 10.
Per comodità vengono mostrati solo i livelli da 6 a 10.
Se la candela si trova nei pressi del VWAP ancorato il colore del numero sarà verde, ad indicare un'alta probabilità.
I cerchi invece si basano sull'oscillatore CCI (Commodity Channel Index).
L’indicatore CCI ci permette di osservare se il livello attuale del prezzo è particolarmente al di sopra o al di sotto di una certa media mobile, avente un numero di periodi scelto da noi.
Più la deviazione dal prezzo medio nel breve termine è forte, e maggiormente l’indicatore si allontanerà dallo 0: verso l’alto in caso di uptrend, o verso il basso in caso di downtrend.
Il segnale viene dato quando il valore del CCI supera la linea dello zero.
Il tutto è filtrato con un altro indicatore, il MACD, acronimo di "Moving Average Convergence Divergence", usato per identificare cambiamenti nel momentum del prezzo.
This is my Trend Surfer.
The triangles indicate directional candles with varying volume levels from 1 to 10.
For convenience, only levels 6 to 10 are shown.
If the candle is near the anchored VWAP, the color of the number will be green, indicating a high probability.
The circles, on the other hand, are based on the CCI (Commodity Channel Index) oscillator.
The CCI indicator allows us to observe whether the current price level is significantly above or below a certain moving average, with a number of periods chosen by us.
The greater the deviation from the short-term average price, the further the indicator will deviate from 0: upwards in the case of an uptrend, or downwards in the case of a downtrend.
The signal is given when the CCI value crosses the zero line.
This is all filtered through another indicator, the MACD, which stands for "Moving Average Convergence Divergence," used to identify changes in price momentum.
Alpha Trading AnalysisAlpha Trading Dashboard Analysis
- Candle Analysis
- Pivot Point and Fibonacci
- Bollinger band
STOCK SCHOOL | SWING TRACKER Swing Tracker is a powerful tool that automatically identifies Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL) directly on the chart, helping traders clearly understand market structure and trend direction. Designed for price action traders, it works seamlessly across all timeframes and instruments, offering clean visual labels for swing points to spot trend continuations or potential reversals. Whether you're following the trend or looking for structure shifts, Swing Tracker keeps you aligned with price action for smarter, more confident trading decisions.
Williams Alligator with Background ColoringThe Benefits of the Williams Alligator – Without the “Spaghetti” on Your Chart
If you're one of those traders who prefer a clean, well-structured chart but don't want to miss out on the advantages of the Williams Alligator, this script is the perfect solution.
It includes all the features of the original TradingView script plus a background color feature based on your custom parameters:
Green when all candles are above the Alligator lines
Red when all candles are below all lines
Gray for everything in between
Feel free to customize the colors and transparency to your liking.
Happy Trading!
Initial BalanceFirst hour Initial Balance is calculated automatically with IB range, type, status and target
Koala Trend HackWhat this indicator is
A minimal, “ tweet‑faithful ” trend read with just two visuals:
1. H4 EMA200 (white): the macro/regime line pulled onto any timeframe.
2. Trend Line (colored): the average of EMA‑8 and EMA‑21; its color shows the current state.
How it works (state → color)
Priority is macro first, then short‑term momentum—so it’s simple but still reactive above H4:
Below H4 200 → Red (Be Bearish).
Above H4 200 with wick into it → Yellow (Be Bullish & Pray / Watch the retest).
Above H4 200 and above both 8 & 21 → Green (Be Bullish).
Above H4 200 but below both 8 & 21 → Orange (Be Cautious).
If none of the above applies, it falls back to the 8/21 cluster (above both = green, below both = orange) or stays Yellow (Neutral/Watch).
How it aligns with the tweet’s 5 rules
1. Reclaim EMAs = Long → close > 8 & 21 → Green.
2. Close below EMAs = Be cautious* → close < 8 & 21 → Orange.
3. Retest of H4 EMA200 = Be bullish and pray → close > H4 and low ≤ H4 → Yellow.
4. Lose H4 EMA200 = Be bearish* → close < H4 → Red.
5. Reclaim H4 EMA200 = Be bullish again* → back above H4 (and ideally > 8/21) → Green.
How to use
Green favors longs; Orange means lighten up or wait; Yellow says “watch the level” after a retest; Red warns against longs until H4 200 is reclaimed.
Notes:
The H4 EMA200 is a higher‑timeframe value fetched with request.security; on sub‑H4 charts it updates during the current 4‑hour candle (responsive but can shift slightly until that candle closes).
EMAs 8 & 21 are used internally to color the line; they’re not plotted, keeping the chart clean.
What would make this better? Modify it and show me what you built!
kiwi 지표 통합 v6 MAX많이 사용하는 지표들을 하나의 지표로 만들었습니다.
주로 이동평균선을 기준으로 매매에 유용한 지표를 모았고
볼랜저밴드, 일목군형표를 하나의 지표로 만들었습니다.
특히, 캔들색이 한국 스타일을 원하는 사람에게 적합니다.
(빨간색 = 상승, 파란색 = 하락)
We made the most used indicators one indicator.
We collected indicators that are useful for trading mainly based on the moving average
The bolanger band and the Ilmok group table were made one indicator.
In particular, the candle color is written for those who want the Korean style.
(Red = Up, Blue = Down)
kiwi 지표 통합 v6 MAX많이 사용하는 지료들을 하나의 지표로 만들었습니다.
주로 이동평균선을 기준으로 매매에 유용한 지표를 모았고
볼랜저밴드, 일목군형표를 하나의 지표로 만들었습니다.
특히, 캔들색이 한국 스타일을 원하는 사람에게 적합니다.
(빨간색 = 상승, 파란색 = 하락)
I made a lot of used materials as an indicator.
We collected indicators that are useful for trading mainly based on the moving average
The bolanger band and the Ilmok group table were made one indicator.
In particular, the candle color is written for those who want the Korean style.
(Red = Up, Blue = Down)
21EMA Cross Alert When 21EMA >50EMABullish Signal when 21EMA is higher than 50EMA and gives alert when candle crosses above 21EMA
Key Session LevelsKey Session Levels - Indicator Guide
Created by: MecarderoAurum
Why This Indicator Exists: An Overview
The "Key Session Levels" indicator is a comprehensive tool for day traders that automatically plots the most critical price levels from the current premarket and the previous two full trading days. These levels are watched by countless traders and often act as significant areas of support and resistance.
This indicator provides a clear, objective map of these key zones, helping traders anticipate potential turning points, identify areas of confluence, and make more informed trading decisions without having to manually draw and manage these lines every day.
Features & How to Use Them
This indicator plots several types of important historical levels on your chart. Each one is fully customizable.
1. Premarket Levels (PMH / PML)
What they are: The highest (PMH) and lowest (PML) prices reached during the current day's premarket session (04:00 - 09:30 ET).
Why they matter: The premarket high and low are the first significant levels established for the trading day. They often act as initial support or resistance once the market opens.
How to use them: In the settings under "Premarket Levels," you can toggle the visibility of the PMH and PML, and customize their color, line style, and width.
2. Prior Day Levels (PDH / PDL / PDM / PDP)
What they are: The key price points from the previous full trading day.
PDH: Prior Day High
PDL: Prior Day Low
PDM: Prior Day Midpoint (the exact middle of the PDH and PDL)
PDP: Prior Day Pivot (a classic pivot point calculation)
Why they matter: These are often the most important levels for the current trading day. The market frequently tests the previous day's high and low.
How to use them: Under the "Prior Day" settings, you can enable or disable each of these four levels and customize their appearance.
3. 2-Day Prior Levels (PDH2 / PDL2 / etc.)
What they are: The same set of key levels (High, Low, Mid, Pivot) from two trading days ago.
Why they matter: These levels can still be highly relevant, especially if the market is trading within a multi-day range or returning to test a significant prior level.
How to use them: Under the "2-Day Prior" settings, you can customize the visibility and style of these levels. They are styled with more transparency by default to distinguish them from the more recent prior day's levels.
4. General Settings
Days of History: This setting allows you to control how many past days of historical lines are kept on your chart. This is excellent for back-testing strategies and seeing how price has reacted to these levels in the past.
Label Settings: You can customize the color and size of the on-chart labels (e.g., "PDH," "PML") for better visibility.
Sample Strategy: The Key Level Rejection
This strategy focuses on using the indicator's levels to identify potential reversals at key areas of support or resistance.
Identify a Key Level: Watch as the price approaches a significant level plotted by the indicator, such as the Prior Day High (PDH) or the Premarket Low (PML).
Look for Rejection: Do not trade simply because the price touches the level. Wait for a price action signal that confirms the level is holding. This could be a bearish engulfing candle or a shooting star pattern at a resistance level like PDH, or a bullish hammer or morning star pattern at a support level like PML.
Entry: Once you see a clear rejection candle, enter a trade in the direction of the rejection. For a bearish rejection at the PDH, you would enter a short position.
Stop-Loss: A logical place for a stop-loss is just above the high of the rejection candle (for a short trade) or just below the low of the rejection candle (for a long trade). This defines your risk clearly.
Profit Target: Your first profit target could be the next key level plotted by the indicator. For example, if you shorted a rejection at the PDH, your first target might be the Premarket High (PMH) or the day's opening price.
Hurst Criticality EngineThe Hurst Criticality Engine (HCE) is an advanced trading indicator designed to detect potential breakout (BUY) and exhaustion (SELL) conditions by combining multi‑scale Hurst exponent analysis with tactical confirmations such as VWAP, RSI, volume spikes, Fibonacci log‑periodic patterns and price channels.
It is optimized for traders seeking structured confluence in volatile or trending markets, and can be applied across different timeframes, from intraday scalping (1m–15m) to swing trading (1h–4h).
What It Does
HCE identifies potential turning points and momentum shifts by evaluating market persistence and volatility across several dimensions. It generates three main types of labels:
CRITICAL Signals: Triggered when multiple Hurst scales align and tactical validations confirm the setup. These can indicate breakout (BUY) or exhaustion (SELL) conditions.
CPC (Critical Pivot Confirmation): Appears at structural highs or lows validated by Hurst exponent alignment and VWAP context.
PIVOT Labels: Marks confirmed structural highs (▼) and lows (▲) that can be used to anticipate reversals or continuation setups.
A dynamic Tactical Panel shows real‑time information on signal strength, VWAP zones, last confirmed signals and the current alignment of the Hurst scales.
How It Works
The indicator integrates several analytical components, each designed to filter noise and add context:
Hurst Exponent Analysis:
Evaluates price persistence across up to five customizable time scales (default: 10, 20, 40, 80, 160 bars).
A signal is considered when at least a minimum number of scales (default: 3) align as bullish (>0.6) or bearish (<0.4).
Rolling VWAP with Standard Deviation Bands:
Plots a rolling VWAP and three customizable bands (±1σ, ±2σ, ±3σ).
Signals are validated if price is correctly positioned relative to VWAP (above for BUY, below for SELL) or if it breaks the outermost band, suggesting volatility extremes.
RSI and Volume Confirmation:
Uses RSI (default: 14‑period) to confirm momentum alignment (e.g., oversold for BUY, overbought for SELL).
Incorporates volume spikes (default: 1.5× average) as an additional confirmation of institutional participation.
Fibonacci Log‑Periodic Patterns:
Validates critical signals by checking whether price oscillations align with harmonic Fibonacci ratios (default: 0.618).
Channel Detection:
Runs a 50‑bar regression channel to identify structural boundaries.
Signals are reinforced when price interacts significantly with channel extremes or breaks out from them.
Dynamic Scoring System:
Every signal receives a score from 0 to 8 based on the confluence of all the above factors.
Scores ≥6 indicate strong alignment, 4–5 medium, 2–3 weak and ≤1 neutral.
Why This Combination?
Each component provides different insights: the Hurst exponent captures market persistence, VWAP defines value areas, RSI and volume confirm momentum and participation, while Fibonacci and channels provide structural references. This synergy allows HCE to filter noise and focus on conditions where multiple factors align, increasing the reliability of the setups.
How to Use It
Add the Indicator to the Chart:
Works on any instrument and timeframe (e.g., 1m, 5m, 15m for scalping; 1h, 4h for swing trading).
Configure Settings:
General Parameters: Set the minimum number of Hurst scales, cooldown between signals and spacing mode (manual or adaptive).
Tactical Validations: Enable or disable RSI, volume, Fibonacci or channel filters.
VWAP Settings: Adjust length (default: 50 bars) and deviation bands.
Hurst Scales: Enable up to five scales and customize their lengths.
Tactical Panel and Labels: Choose compact or detailed view and toggle the display of CRITICAL, CPC, PIVOT or Observation labels.
Interpret Signals:
CRITICAL (B/S): Labels appear above/below price with tooltips showing the signal score, VWAP status and momentum context.
CPC (⚡CPC↑ / ⚡CPC↓): Indicates critical pivots confirmed at structural highs or lows.
PIVOT (▲ / ▼): Marks confirmed highs/lows for additional context.
Observation Labels (⚠️): Highlight potential setups not meeting full CRITICAL criteria.
Monitor the Tactical Panel:
Displays the VWAP zone, number of aligned Hurst scales, signal score and last confirmed signals.
Recommendations
Use HCE as a confluence filter, not as a standalone entry tool.
Focus on signals with Medium (4–5) or Strong (≥6) scores.
Combine CPC and PIVOT labels with broader context for swing or reversal trades.
Apply on clean charts (without overlapping indicators) for optimal visualization.
Always use proper risk management, as no indicator can predict outcomes with certainty.
Chart Setup and Alerts
The script includes customizable alerts for CRITICAL, CPC, PIVOT and VWAP breakouts.
For clear visualization, use it on charts without clutter.
Works best on liquid markets (e.g., forex, crypto, stocks) and in volatile or trending conditions
tdx_MACD指标采用中国用户常用的股票期货类macd，符合中国用户常用的macd,另外这套macd匹配本ID的缠论指标使用，默认参数12 26 9，使用收盘价，可以自己修改参数
Adopting the stock and futures-oriented MACD commonly used by Chinese users, this MACD aligns with the commonly used MACD among Chinese users. Additionally, this set of MACD matches the Chuan Theory indicators of this ID. The default parameters are 12, 26, and 9, using closing prices. You can modify the parameters yourself
Phantom RSI TableMulti-Timeframe RSI Dashboard
This indicator provides traders with a comprehensive view of RSI (Relative Strength Index) conditions across multiple timeframes simultaneously, eliminating the need to manually switch between different chart intervals to analyze market momentum.
What It Does:
The dashboard displays RSI values, market status (Overbought/Oversold/Neutral), and volume trends for four key timeframes (1-hour, 4-hour, daily, and weekly) in a clean, easy-to-read table overlay on your chart. This multi-timeframe approach gives you both short-term and long-term market perspective at a glance.
Why It's Useful for All Traders:
Day Traders can spot when shorter timeframes align with longer-term trends, providing higher-probability entry and exit points.
Swing Traders benefit from seeing confluence between daily and weekly RSI levels, helping identify optimal position timing.
Position Traders can monitor long-term momentum while staying aware of shorter-term fluctuations that might affect their holdings.
Risk Management is enhanced by seeing divergences between timeframes - when short-term RSI shows overbought conditions while longer timeframes remain neutral, it may signal caution.
Alert System:
The indicator automatically monitors all timeframes and sends instant notifications when RSI crosses into overbought (≥70) or oversold (≤30) territory on any timeframe. You'll receive alerts that include:
Which specific timeframe triggered the alert
The exact RSI value
Current volume condition
A comprehensive summary when multiple timeframes trigger simultaneously
This means you never miss important RSI signals across any timeframe, allowing you to react quickly to changing market conditions even when you're away from your charts. The alerts help you catch potential reversal points and momentum shifts before they become obvious to other market participants.
✅ VMA Avg ATR + Days to Targets 🎯1) The trend filter: LazyBear VMA
You implement the well‑known “LazyBear” Variable Moving Average (VMA) from price directional movement (pdm/mdm).
Internally you:
Smooth positive/negative one‑bar moves (pdmS, mdmS),
Turn them into relative strengths (pdiS, mdiS),
Measure their difference/total (iS), and
Normalize that over a rolling window to get a scaling factor vI.
The VMA itself is then an adaptive EMA:
vma := (1 - k*vI) * vma + (k*vI) * close, where k = 1/vmaLen.
When vI is larger, VMA hugs price more; when smaller, it smooths more.
Coloring:
Green when vma > vma (rising),
Red when vma < vma (falling),
White when flat.
Candles are recolored to match.
Why this matters: The VMA color is your trend regime; everything else in the script keys off changes in this color.
2) What counts as a “valid” new trend?
A new trend is valid only when the previous bar was white and the current bar turns green or red:
validTrendStart := vmaColor != color.white and vmaColor == color.white.
When that happens, you start a trend segment:
Save entry price (startPrice = close) and baseline ATR (startATR = ATR(atrLen)).
Reset “extreme” trackers: extremeHigh = high, extremeLow = low.
Timestamp the start (trendStartTime = time).
Effect: You only study / trade transitions out of a flat VMA into a slope. This helps avoid chop and reduces false starts.
3) While the trend is active
On each new bar without a color change:
If green trend: update extremeHigh = max(extremeHigh, high).
If red trend: update extremeLow = min(extremeLow, low).
This tracks the best excursion from the entry during that single trend leg.
4) When the VMA color changes (trend ends)
When vmaColor flips (green→red or red→green), you close the prior segment only if it was a valid trend (started after white). Then you:
Compute how far price traveled in ATR units from the start:
Uptrend ended: (extremeHigh - startPrice) / startATR
Downtrend ended: (startPrice - extremeLow) / startATR
Add that result to a running sum and count for the direction:
totalUp / countUp, totalDown / countDown.
Target checks for the ended trend (no look‑ahead):
T1 uses the previous average ATR move before the just‑ended trend (prevAvgUp/prevAvgDown).
Up: t1Up = startPrice + prevAvgUp * startATR
Down: t1Down = startPrice - prevAvgDown * startATR
T2 is a fixed 6× ATR move from the start (up or down).
You increment hit counters and also accumulate time‑to‑hit (ms from trendStartTime) for any target that got reached during that ended leg.
If T1 wasn’t reached, it counts as a miss.
Immediately initialize the next potential trend segment with the current bar’s startPrice/startATR/extremes and set validTrendStart according to the “white → color” rule.
Important detail: Using prevAvgUp/Down to evaluate T1 for the just‑completed trend avoids look‑ahead bias. The current trend’s performance isn’t used to set its own T1.
5) Running statistics & targets (for the current live trend)
After closing/adding to totals:
avgUp = totalUp / countUp and avgDown = totalDown / countDown are the historical average ATR move per valid trend for each direction.
Current plotted targets (only visible while a valid trend is active and in that direction):
T1 Up: startPrice + avgUp * startATR
T2 Up: startPrice + 6 * startATR
T1 Down: startPrice - avgDown * startATR
T2 Down: startPrice - 6 * startATR
The entry line is also plotted at startPrice when a valid trend is live.
If there’s no history yet (e.g., first trend), avgUp/avgDown are na, so T1 is na until at least one valid trend has closed. T2 still shows (6× ATR).
6) Win rate & time metrics
Win % (per direction):
winUp = hitUpT1 / (hitUpT1 + missUp) and similarly for down.
(This is strictly based on T1 hits vs misses; T2 hits don’t affect Win% directly.)
Average days to hit T1/T2:
The script stores milliseconds from trend start to each target hit, then reports the average in days separately for Up/Down and for T1/T2.
7) The dashboard table (bottom‑right)
It shows, side‑by‑side for Up/Down:
Avg ATR: historical average ATR move per completed valid trend.
🎯 Target 1 / Target 2: the current trend’s price levels (T1 = avgATR×ATR; T2 = 6×ATR).
✅ Win %: T1 hit rate so far.
⏱ Days to T1/T2: average days (from valid trend start) for the targets that were reached.
8) Alerts
“New Trend Detected” when a valid trend starts (white → green/red).
Target hits for the active trend:
Uptrend: separate alerts for T1 and T2 (high >= target).
Downtrend: separate alerts for T1 and T2 (low <= target).
9) Inputs & defaults
vmaLen = 17: governs how adaptive/smooth the VMA is (larger = smoother, fewer trend flips).
atrLen = 14: ATR baseline for sizing targets and normalizing moves.
10) Practical read of the plots
When you see white → green: that bar is your valid entry (trend start).
An Entry Line appears at the start price.
Target lines appear only for the active direction. T1 scales with your historical average ATR move; T2 is a fixed stretch (6× ATR).
The table updates as more trends complete, refining:
The average ATR reach (which resets your T1 sizing),
The win rate to T1, and
The average days it typically takes to hit T1/T2.
Subtle points / edge cases
No look‑ahead: T1 for a finished trend is checked against the prior average (not including the trend itself).
First trends: Until at least one valid trend completes, T1 is na (no history). T2 still shows.
Only “valid” trends are counted: Segments must start after a white bar; flips that happen color→color without a white in between don’t start a new valid trend.
Time math: Uses bar timestamps in ms, converted to days; results reflect the chart’s timeframe/market session.
TL;DR
The VMA color defines the regime; entries only trigger when a flat (white) VMA turns green/red.
Each trend’s max excursion from entry is recorded in ATR units.
T1 for current trends = (historical average ATR move) × current ATR from entry; T2 = 6× ATR.
The table shows your evolving edge (avg ATR reach, T1 win%, and days to targets), and alerts fire on new trends and target hits.
If you want, I can add optional features like: per‑ticker persistence of stats, excluding very short trends, or making T2 a user input instead of a fixed 6× ATR.
Qabas HPC ProQabas HPC Pro - Ultimate (Turbo)
Advanced Market Compression & Breakout Detection
The Qabas HPC Pro - Ultimate (Turbo) indicator is a powerful market analysis tool designed to identify High-Precision Compression (HPC) zones, true breakout candles, and volume-based warning signals. Built with performance and adaptability in mind, this indicator helps traders detect key price levels where momentum builds up before explosive moves.
🔍 Key Features:
• HPC Zone Detection: Automatically identifies compressed price ranges with low volatility and balanced volume—ideal zones for potential breakouts.
• Smart Breakout Alerts: Highlights real breakout candles with strong price action and high volume, filtering out noise and false signals.
• Warning Candles: Semi-strong candles are marked as early signs of volatility shifts.
• Adaptive Settings: Automatically adjusts sensitivity based on chart timeframe for optimal signal quality.
• Dynamic Coloring: Candles are color-coded for easy visual recognition:
• 🟧 True Explosion – High volume + breakout movement (Orange)
• 🟣 Warning Candle – Medium strength signals (Purple)
• 🔵 HPC Candles – Optional coloring for standard compression zones (Blue)
• 🔴 Breakouts – Marked level lines turn red upon confirmation
• Smart Line Management: Efficient line handling ensures clean visuals and fast performance, even on lower timeframes.
• Customizable: Fine-tune levels, colors, and intensity to fit your trading strategy.
✅ Best For:
• Scalpers and day traders on lower timeframes
• Swing traders identifying breakout zones
• Volume and volatility-based trading strategies
Developed with a smart adaptive algorithm, Qabas HPC Pro offers an edge for traders looking to time entries around periods of market compression and breakout.
London Session & Market StructureFusion of session indicator with market structure ZigZag line. not my own creation just a fusion of 2 indicators which are publicly available on TV
Advanced ICT Theory - A-ICT📊 Advanced ICT Theory (A-ICT): The Institutional Manipulation Detector
Are you tired of being the liquidity? Stop chasing shadows and start tracking the architects of price movement.
This is not another lagging indicator. This is a complete framework for viewing the market through the lens of institutional traders. Advanced ICT Theory (A-ICT) is an all-in-one, military-grade analysis engine designed to decode the complex language of "Smart Money." It automates the core tenets of Inner Circle Trader (ICT) methodology, moving beyond simple patterns to build a dynamic, real-time narrative of market manipulation, liquidity engineering, and institutional order flow.
AIT provides a living blueprint of the market, identifying high-probability zones, tracking structural shifts, and scoring the quality of setups with a sophisticated, multi-factor algorithm. This is your X-ray into the market's true intentions.
🔬 THE CORE ENGINE: DECODING THE THEORY & FORMULAS
A-ICT is built upon a sophisticated, multi-layered logic system that interprets price action as a story of cause and effect. It does not guess; it confirms. Here is the foundational theory that drives the engine:
1. Market Structure: The Blueprint of Trend
The script first establishes a deep understanding of the market's skeleton through multi-level pivot analysis. It uses ta.pivothigh and ta.pivotlow to identify significant swing points.
Internal Structure (iBOS): Minor swings that show the short-term order flow. A break of internal structure is the first whisper of a potential shift.
External Structure (eBOS): Major swing points that define the primary trend. A confirmed break of external structure is a powerful statement of trend continuation. AIT validates this with optional Volume Confirmation (volume > volumeSMA * 1.2) and Candle Confirmation to ensure the break is driven by institutional force, not just a random spike.
Change of Character (CHoCH): This is the earthquake. A CHoCH occurs when a confirmed eBOS happens against the prevailing trend (e.g., a bearish eBOS in a clear uptrend). A-ICT flags this immediately, as it is the strongest signal that the primary trend is under threat of reversal.
2. Liquidity Engineering: The Fuel of the Market
Institutions don't buy into strength; they buy into weakness. They need liquidity. A-ICT maps these liquidity pools with forensic precision:
Buyside & Sellside Liquidity (BSL/SSL): Using ta.highest and ta.lowest, AIT identifies recent highs and lows where clusters of stop-loss orders (liquidity) are resting. These are institutional targets.
Liquidity Sweeps: This is the "manipulation" part of the detector. AIT has a specific formula to detect a sweep: high > bsl and close < bsl . This signifies that institutions pushed price just high enough to trigger buy-stops before aggressively selling—a classic "stop hunt." This event dramatically increases the quality score of subsequent patterns.
3. The Element Lifecycle: From Potential to Power
This is the revolutionary heart of A-ICT. Zones are not static; they have a lifecycle. AIT tracks this with its dynamic classification engine.
Phase 1: PENDING (Yellow): The script identifies a potential zone of interest based on a specific candle formation (a "displacement"). It is marked as "Pending" because its true nature is unknown. It is a question.
Phase 2: CLASSIFICATION: After the zone is created, AIT watches what happens next. The zone's identity is defined by its actions:
ORDER BLOCK (Blue): The highest-grade element. A zone is classified as an Order Block if it directly causes a Break of Structure (BOS) . This is the footprint of institutions entering the market with enough force to validate the new trend direction.
TRAP ZONE (Orange): A zone is classified as a Trap Zone if it is directly involved in a Liquidity Sweep . This indicates the zone was used to engineer liquidity, setting a "trap" for retail traders before a reversal.
REVERSAL / S&R ZONE (Green): If a zone is not powerful enough to cause a BOS or a major sweep, but still serves as a pivot point, it's classified as a general support/resistance or reversal zone.
4. Market Inefficiencies: Gaps in the Matrix
Fair Value Gaps (FVG): AIT detects FVGs—a 3-bar pattern indicating an imbalance—with a strict formula: low > high (for a bullish FVG) and gapSize > atr14 * 0.5. This ensures only significant, volatile gaps are shown. An FVG co-located with an Order Block is a high-confluence setup.
5. Premium & Discount: The Law of Value
Institutions buy at wholesale (Discount) and sell at retail (Premium). AIT uses a pdLookback to define the current dealing range and divides it into three zones: Premium (sell zone), Discount (buy zone), and Equilibrium. An element's quality score is massively boosted if it aligns with this principle (e.g., a bullish Order Block in a Discount zone).
⚙️ THE CONTROL PANEL: A COMPLETE GUIDE TO THE INPUTS MENU
Every setting is a lever, allowing you to tune the AIT engine to your exact specifications. Master these to unlock the script's full potential.
🎯 A-ICT Detection Engine
Min Displacement Candles: Controls the sensitivity of element detection. How it works: It defines the number of subsequent candles that must be "inside" a large parent candle. Best practice: Use 2-3 for a balanced view on most timeframes. A higher number (4-5) will find only major, more significant zones, ideal for swing trading. A lower number (1) is highly sensitive, suitable for scalping.
Mitigation Method: Defines when a zone is considered "used up" or mitigated. How it works: Cross triggers as soon as price touches the zone's boundary. Close requires a candle to fully close beyond it. Best practice: Cross is more responsive for fast-moving markets. Close is more conservative and helps filter out fake-outs caused by wicks, making it safer for confirmations.
Min Element Size (ATR): A crucial noise filter. How it works: It requires a detected zone to be at least this multiple of the Average True Range (ATR). Best practice: Keep this around 0.5. If you see too many tiny, irrelevant zones, increase this value to 0.8 or 1.0. If you feel the script is missing smaller but valid zones, decrease it to 0.3.
Age Threshold & Pending Timeout: These manage visual clutter. How they work: Age Threshold removes old, mitigated elements after a set number of bars. Pending Timeout removes a "Pending" element if it isn't classified within a certain window. Best practice: The default settings are optimized. If your chart feels cluttered, reduce the Age Threshold. If pending zones disappear too quickly, increase the Pending Timeout.
Min Quality Threshold: Your primary visual filter. How it works: It hides all elements (boxes, lines, labels) that do not meet this minimum quality score (0-100). Best practice: Start with the default 30. To see only A- or B-grade setups, increase this to 60 or 70 for an exceptionally clean, high-probability view.
🏗️ Market Structure
Lookbacks (Internal, External, Major): These define the sensitivity of the trend analysis. How they work: They set the number of bars to the left and right for pivot detection. Best practice: Use smaller values for Internal (e.g., 3) to see minor structure and larger values for External (e.g., 10-15) to map the main trend. For a macro, long-term view, increase the Major Swing Lookback.
Require Volume/Candle Confirmation: Toggles for quality control on BOS/CHoCH signals. Best practice: It is highly recommended to keep these enabled. Disabling them will result in more structure signals, but many will be false alarms. They are your filter against market noise.
... (Continue this detailed breakdown for every single input group: Display Configuration, Zones Style, Levels Appearance, Colors, Dashboards, MTF, Liquidity, Premium/Discount, Sessions, and IPDA).
📊 THE INTELLIGENCE DASHBOARDS: YOUR COMMAND CENTER
The dashboards synthesize all the complex analysis into a simple, actionable intelligence briefing.
Main Dashboard (Bottom Right)
ICT Metrics & Breakdown: This is your statistical overview. Total Elements shows how much structure the script is tracking. High Quality instantly tells you if there are any A/B grade setups nearby. Unmitigated vs. Mitigated shows the balance of fresh opportunities versus resolved price action. The breakdown by Order Blocks, Trap Zones, etc., gives you a quick read on the market's recent character.
Structure & Market Context: This is your core bias. Order Flow tells you the current script-determined trend. Last BOS shows you the most recent structural event. CHoCH Active is a critical warning. HTF Bias shows if you are aligned with the higher timeframe—the checkmark (✓) for alignment is one of the most important confluence factors.
Smart Money Flow: A volume-based sentiment gauge. Net Flow shows the raw buying vs. selling pressure, while the Bias provides an interpretation (e.g., "STRONG BULLISH FLOW").
Key Guide (Large Dashboard only): A built-in legend so you never have to guess. It defines every pattern, structure type, and special level visually.
📖 Narrative Dashboard (Bottom Left)
This is the "story" of the market, updated in real-time. It's designed to build your trading thesis.
Recent Elements Table: A live list of the most recent, high-quality setups. It displays the Type , its Narrative Role (e.g., "Bullish OB caused BOS"), its raw Quality percentage, and its final Trade Score grade. This is your at-a-glance opportunity scanner.
Market Narrative Section: This is the soul of A-ICT. It combines all data points into a human-readable story:
📍 Current Phase: Tells you if you are in a high-volatility Killzone or a consolidation phase like the Asian Range.
🎯 Bias & Alignment: Your primary direction, with a clear indicator of HTF alignment or conflict.
🔗 Events: A causal sequence of recent events, like "💧 Sell-side liquidity swept →
📊 Bullish BOS → 🎯 Active Order Block".
🎯 Next Expectation: The script's logical conclusion. It provides a specific, forward-looking hypothesis, such as "📉 Pullback expected to bullish OB at 1.2345 before continuation up."
🎨 READING THE BATTLEFIELD: A VISUAL INTERPRETATION GUIDE
Every color and line is a piece of information. Learn to read them together to see the full picture.
The Core Zones (Boxes):
Blue Box (Order Block): Highest probability zone for trend continuation. Look for entries here.
Orange Box (Trap Zone): A manipulation footprint. Expect a potential reversal after price interacts with this zone.
Green Box (Reversal/S&R): A standard pivot area. A good reference point but requires more confluence.
Purple Box (FVG): A market imbalance. Acts as a magnet for price. An FVG inside an Order Block is an A+ confluence.
The Structural Lines:
Green/Red Line (eBOS): Confirms the trend direction. A break above the green line is bullish; a break below the red line is bearish.
Thick Orange Line (CHoCH): WARNING. The previous trend is now in question. The market character has changed.
Blue/Red Lines (BSL/SSL): Liquidity targets. Expect price to gravitate towards these lines. A dotted line with a checkmark (✓) means the liquidity has been "swept" or "purged."
How to Synthesize: The magic is in the confluence. A perfect setup might look like this: Price sweeps below a red SSL line , enters a green Discount Zone during the NY Killzone , and forms a blue Order Block which then causes a green eBOS . This sequence, visible at a glance, is the story of a high-probability long setup.
🔧 THE ARCHITECT'S VISION: THE DEVELOPMENT JOURNEY
A-ICT was forged from the frustration of using lagging indicators in a market that is forward-looking. Traditional tools are reactive; they tell you what happened. The vision for A-ICT was to create a proactive engine that could anticipate institutional behavior by understanding their objectives: liquidity and efficiency. The development process was centered on creating a "lifecycle" for price patterns—the idea that a zone's true meaning is only revealed by its consequence. This led to the post-breakout classification system and the narrative-building engine. It's designed not just to show you patterns, but to tell you their story.
⚠️ RISK DISCLAIMER & BEST PRACTICES
Advanced ICT Theory (A-ICT) is a professional-grade analytical tool and does not provide financial advice or direct buy/sell signals. Its analysis is based on historical price action and probabilities. All forms of trading involve substantial risk. Past performance is not indicative of future results. Always use this tool as part of a comprehensive trading plan that includes your own analysis and a robust risk management strategy. Do not trade based on this indicator alone.
観の目つよく、見の目よわく
"Kan no me tsuyoku, ken no me yowaku"
— Miyamoto Musashi, The Book of Five Rings
English: "Perceive that which cannot be seen with the eye."
— Dskyz, Trade with insight. Trade with anticipation.
Golden Sweep - ZTFGolden Sweep - ZTF: Multi-Confluence Reversal Detection System
Purpose & Methodology:
The Golden Sweep combines six distinct market structure analysis methods into a unified confluence system designed to identify high-probability reversal points at inverse Fair Value Gaps (iFVGs). Rather than relying on single-indicator signals, this system requires simultaneous confirmation across multiple independent market dimensions to filter out noise and reduce false signals.
Core Logic & Technical Approach:
1. Fair Value Gap Analysis Foundation
The system begins by detecting standard Fair Value Gaps (price inefficiencies where gaps exist between candle wicks) and monitors when price returns to fill these gaps, creating inverse FVGs. This forms the base signal trigger.
2. Liquidity Sweep Confirmation Engine
Uses pivot-based swing detection to identify when price has recently swept through key support/resistance levels, indicating stop-loss hunting activity. The algorithm tracks recent liquidity events within a configurable lookback period and correlates them with iFVG formations.
3. VWAP Statistical Positioning
Calculates real-time Volume Weighted Average Price with standard deviation bands. Signals are only validated when price is positioned at statistically significant VWAP deviations (configurable zones), ensuring alignment with institutional flow patterns.
4. Balanced Price Range (BPR) Structure Analysis
Detects overlapping bullish and bearish Fair Value Gaps that create consolidation zones. The system identifies when new iFVGs form within or near these balanced ranges, indicating potential breakout reversals from established accumulation/distribution areas.
5. Turtle Soup Reversal Pattern Recognition
Implements Larry Connors' turtle soup methodology to detect false breakouts. Identifies when price penetrates recent highs/lows but closes back within the prior range, indicating failed breakout attempts that often precede strong reversals.
6. Exhaustion Signal Detection
Employs dual-timeframe momentum analysis using Williams %R methodology with optimized smoothing parameters. Detects overbought/oversold exhaustion conditions and confirms when momentum shifts from extreme readings back toward equilibrium, indicating potential trend exhaustion reversals.
Confluence Requirement Logic:
A Golden Sweep signal only triggers when ALL enabled filters simultaneously confirm within their respective lookback periods. This six-dimensional approach significantly reduces signal frequency while increasing reliability by ensuring multiple market forces align before generating alerts.
Session & Timing Integration:
Incorporates session-based filtering to account for varying market dynamics across trading sessions (NY Open, London Close, etc.), as different sessions exhibit distinct liquidity and volatility characteristics.
Implementation Notes:
All calculations use confirmed bar data to prevent repainting
Configurable lookback periods allow adaptation to different timeframes and market conditions
Visual overlays are optional and independent of signal generation logic
Built-in risk management through signal rarity and confluence requirements
This systematic approach addresses the common problem of indicator overload by creating a structured framework where multiple analysis methods must agree before signaling, resulting in fewer but higher-quality trade opportunities.
⚠️ Disclaimer: This indicator is for educational purposes only. It does not constitute financial advice or a recommendation to buy or sell any security. Trading involves risk — always do your own research and use proper risk management.
