Blanco V1-(Custom TF + Super Signals)**Blanco V1 Trading System (Multi-Timeframe Confirmation)**
Blanco V1 is a high-probability trading indicator designed to identify strong market opportunities using a combination of Zero Lag EMA, trend strength, momentum, and multi-timeframe confirmation.
At its core, Blanco V1 uses a Zero Lag Exponential Moving Average (ZLEMA) to reduce delay and provide faster, more accurate trend signals compared to traditional moving averages.
The system includes three trading modes:
* **Aggressive Mode**: More signals with faster entries, ideal for lower timeframes and active trading.
* **Balanced Mode**: A mix of accuracy and frequency, recommended for most traders.
* **Conservative Mode**: Fewer but higher-quality signals, focused on strong trends and confirmation.
Blanco V1 provides two types of trade signals:
* **Entry Signals (Arrows)**: Small green and red arrows show potential entries based on pullbacks, momentum (RSI), and strong trend conditions (ADX).
* **Trend Signals (BUY/SELL Labels)**: Larger labels appear when the overall trend shifts, signaling potential swing trades.
A key feature of Blanco V1 is the **Multi-Timeframe Dashboard**, which displays trend direction across:
* 5-minute
* 15-minute
* 30-minute
* 1-hour
* 2-hour
* 4-hour
Each timeframe is color-coded:
* 🟢 Green = Bullish
* 🔴 Red = Bearish
The most powerful feature is the **Super Signal (❗)**:
* A green ❗ appears when all timeframes are bullish and a valid buy setup is present.
* A red ❗ appears when all timeframes are bearish and a valid sell setup is present.
These signals represent the highest-probability trades, combining trend alignment, momentum, and full multi-timeframe confirmation.
Blanco V1 performs best on higher timeframes such as 1H and 4H and in trending markets. For best results, combine with proper risk management and price action confirmation.
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**Quick Guide:**
* 🔺 Arrows = entry timing
* 🟢 BUY / 🔴 SELL = trend shifts
* ❗ = strongest trades (full alignment)
Indicator
Breakout Trend Bar AlertsEvery trend has a starting point. It's rarely a gradual drift — it's one massive, decisive candle that breaks the market out of consolidation and kicks off a sustained move. Breakout Bar Alerts is built to catch that exact moment.
The indicator monitors price action in real time and identifies when a bar forms that dwarfs everything around it — the largest high-to-low range of any candle in the last 250 bars. These are the bars where conviction enters the market, weak hands get flushed, and a new trend begins. When one appears, you get an instant alert so you're never late to the move.
Why these bars matter:
Big range bars represent a sudden surge of momentum and volume-backed commitment from one side of the market. Bulls or bears have taken control decisively. What follows is often the beginning of a trend leg — not a random spike.
Built to filter out the noise:
The opening bar of every session is excluded entirely. That first chaotic candle never skews your data or triggers a false signal.
Only bars within your active session window are counted. Off-hours price action is completely ignored, so your benchmark is always built from real, tradeable market conditions.
Three alert conditions — Bull Breakout Bar, Bear Breakout Bar, or Both — so you only get notified for the setups you actually trade.
Inputs:
Lookback Period — how many bars back to measure the largest range (default: 250)
Enable Time Filter — restricts detection and calculations to your active trading session
Active Session — define your session window in exchange time
Bull / Bear colors — fully customizable
Best used on intraday timeframes (1m – 15m) on futures, forex, or high-volume equities. When this fires, pay attention — the trend may already be starting. Indicator
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Sentiment SquareThe Sentiment Square is a multi-timeframe (MTF) and multi-length volume analysis tool designed for PulseWire. It provides a top-down visualization of market conviction by calculating the ratio of bullish volume to total volume across 16 different data points simultaneously.
1.Core Logic: How it Works
The indicator calculates a Bullish Volume Ratio (BVR) for every square in the grid.
BVR = sum ( Volume of Up Candles)/ sum(Total Volume) X 100
Up Candle: Any candle where Close > Open .
Total Volume: The sum of all volume within the lookback window.
Each percentage represents the "Share of Power" held by buyers. For example, a value of 70% means bulls provided 70% of the volume, while bears provided the remaining 30%.
2. Visual Interface
The indicator uses a Transposed Matrix layout to match standard top-down trading analysis:
X-Axis: Timeframes : Moves from your lowest selected timeframe (Left) to your highest (Right).
Y-Axis: Lookback Windows: Moves from short-term momentum (Top) to long-term structure (Bottom).
Color Definitions
Green (Bullish): The percentage is above your Neutral Max (default 55%). Brighter green indicates extreme conviction (>70%).
Red (Bearish): The percentage is below your Neutral Min (default 45%). Brighter red indicates extreme selling (<30%).
Gray (Neutral): The percentage falls between 45% and 55%. This indicates a "tug-of-war" or sideways consolidation where neither side has a decisive majority.
Input Settings
Timeframes Window: Select four different intervals (e.g., 15m, 1h, 4h, 1D).
Speed Window: Set four different lookback lengths (e.g., 20, 50, 100, 200 bars).
Neutral Zone: Adjust the sensitivity of the Gray boxes. A wider range (e.g., 40%–60%) filter out more noise but responds slower to new trends.
How to Interpret the Data
Vertical Alignment (Columns): If a whole column is Green, that specific timeframe is bullish across all horizons (from fast momentum to slow structure).
Horizontal Alignment (Rows): If a whole row is Green, it means that specific "window length" is showing buying pressure across all timeframes.
The "Waiting Time" Signal: When a box is Gray, the volume is balanced. Traders typically wait for the percentage to move out of the 45%–55% range before confirming an entry.
Trend Resilience: If the 15M (tactical) squares turn Red while the 1D (structural) squares remain Green, the market is likely undergoing a healthy pullback rather than a total reversal.
Technical Limitations
Data Lag: Higher timeframe squares (like 1D or 4H) only update when their respective candles close.
Volume Requirement: This indicator requires volume data. It is most effective on Centralized Exchanges (Stocks, Crypto, Futures). On Forex, it uses "Tick Volume," which serves as a proxy for activity.
Common Trade Setup Examples
By observing the transition of colors and percentages across the matrix, you can identify high-probability market conditions.
1.The Trend Continuation (The "Dip-Buy")
Condition: The right-most columns (4H and 1D) and the bottom rows (100 and 200) are solid Green.
Setup: The top-left squares (15M / 20 Window) flip to Red or Gray.
Trigger: Wait for the 15M / 20 square to flip back to Green (above 55%).
Logic: The macro structure is bullish; the red squares indicate a temporary pullback that has now found buyers.
2. The Volatility Squeeze (The "Wait for Breakout")
Condition: A cluster of Gray squares (45%–55%) appears in the middle of the matrix.
Logic: Volume is perfectly balanced between buyers and sellers. This often precedes a massive "expansion" move.
Strategy: Avoid entering while the cluster is Gray. Wait for the majority of the cluster to flip to either solid Green or solid Red.
3. The Top/Bottom Exhaustion
Condition: All 16 squares are Vibrant Green (above 70%) or Vibrant Red (below 30%).
Logic: The market is "over-extended." While the trend is strong, the probability of a reversal increases because there are few buyers/sellers left to push the price further.
Strategy: Tighten stop-losses or look for "Divergence" where the price makes a new high but the percentages in the 20-window start dropping toward 60%.
Summary of the "Wait Time" Metric
The closer a number is to 50%, the more "waiting time" is required. As the numbers move toward 0% or 100%, the market conviction is increasing, and the "actionable" window is opening.
Additional Information:
1. Core Logic
The Sentiment Square calculates the Bullish Volume Ratio (BVR) across 16 data points. It measures "Share of Power" by dividing the volume of "Up Candles" (where Close > Open) by the total volume within a lookback window.
2. Visual Grid Layout
X-Axis (Timeframes): Displays user-selected intervals from lowest (Left) to highest (Right).
Y-Axis (Lookback Windows): Displays "Speeds" from short-term momentum (Top) to long-term structural sentiment (Bottom).
3. Color Definitions
Green (>55%): Bullish conviction. Bright green (>70%) signals extreme strength.
Red (<45%): Bearish conviction. Bright red (<30%) signals extreme selling.
Gray (45%–55%): Neutral "Waiting Time." Indicates volume balance or consolidation.
4. Common Trade Setups
The Dip-Buy: Occurs when macro columns (Right) are Green but tactical squares (Top-Left) temporarily turn Red/Gray. Entry is triggered when tactical squares flip back to Green.
Volatility Squeeze: Identified by a cluster of Gray squares. Traders wait for a majority of the cluster to flip to a solid color before entering.
Exhaustion: When all 16 squares reach extreme vibrant colors, the market is over-extended, increasing the probability of a reversal.
Indicator
Volatility Regime Switch [Metrify]VRS is a regime classifier that tries to separate two things most indicators mix together: direction and tradability. It doesn’t just ask "is price above/below a line?". it estimates whether the market is currently behaving more like a trend regime or a noise/chop regime, then adapts its switching logic and trailing structure accordingly. The output is a state machine (bull/bear) with a volatility-normalized corridor, plus explicit markers for switch accepted vs switch rejected.
Core idea: switching should depend on regime
Most trend flip tools fail in choppy markets because they apply the same confirmation rules everywhere. VRS tries to avoid that by measuring a continuous regime score:
trreg ≈ how “trend-like” conditions are
nsreg ≈ how “noise-like” conditions are
That regime estimate is then used to:
shape the trailing band distance (wider in chop, tighter in trend),
change the required confirmation for a switch (more strict in noise), and
demand follow-through after a candidate switch (acceptance check).
Regime estimation: how it decides “trend-like” vs “noise-like”
The regime score is built from three normalized features, then blended using inverse-variance weighting again:
Efficiency ratio (ER): Measures directional efficiency: net displacement over a horizon vs total movement. Trends have higher efficiency; chop has lower.
ADX-like trend strength: A custom ADX calculation is normalized (adxn), giving a bounded “trend strength” component.
Volatility ratio (fast/slow): Compares fast ATR to slow ATR and normalizes it. This helps distinguish active expansion vs quieter conditions.
These three components are combined into trreg (0..1). Noise regime is nsreg = 1 - trreg.
The important part is it can behave differently when the market is structurally trending versus when it is structurally noisy.
The anchor + adaptive bands: how the corridor is built
VRS uses two EMAs:
a fast EMA (emaf)
a slower EMA (emas)
It then creates an anchor that interpolates between them based on regime:
when trend regime is strong (trreg high), the anchor leans toward the fast EMA (more responsive)
when noise regime is strong (nsreg high), it leans toward the slow EMA (more stable)
Band distance is bdist = volc * bmult, and bmult is also regime-dependent:
in noise, bmult becomes larger → bands widen → fewer false flips
in trend, bmult tightens → better trailing sensitivity
Finally, the trailing bands (fup, flo) use a classic "non-decreasing band" logic similar to trailing-stop structures: the band only moves in the favorable direction unless price invalidates it, preventing constant band oscillation.
Bias and conviction layer
A switch is not triggered merely by close above/below a band. VRS computes conviction, which mixes:
Intra-bar price action bias
Two normalized elements are used: CLV (close location value) inside the candle range and body direction/strength relative to candle range. Both are Z-scored and squashed (atan-based) to avoid extreme outliers dominating.
Trend bias
Difference between fast and slow EMA, normalized by volatility, then Z-scored and squashed.
Displacement breakout quality
If price breaks above fup or below flo, it computes a breakout 'distance' normalized by volatility, then converts it into a Z-score relative to recent breakout behavior (dbullz, dbearz)
These get blended into a conviction signal that is smoothed, and then compared against a dynamic trigger threshold built from the average + stdev of conviction magnitude. A flip should happen when price action + trend bias + breakout quality jointly exceed what is normal for this market recently.
Practical reading notes
VRS generally behaves best when read as "current regime context + boundary + switch events" rather than as a constant entry/exit engine. In trending conditions, the trail will tend to hug price more tightly and switches will be less frequent. In noisy conditions, the corridor widens and the script becomes more conservative, often producing rejected switch attempts rather than rapid flips.
The rejected-switch markers (yellow X) are explicit evidence that the script detected an attempted regime change but did not see enough acceptance. For discretionary use, those rejection points can be useful as information about failed break attempts or lack of follow-through.
This script is designed to be adaptive, but it still has structural constraints. It uses volatility normalization and regime weighting to reduce parameter brittleness, yet extreme regime changes (sudden volatility spikes, news-driven moves, illiquid gaps) can still cause behavior that looks late or 'overly strict', because acceptance and confirmation are intentionally conservative in high-noise conditions. Conversely, on very smooth trend legs, the trail can appear tight and switches may look clean, but that depends on how the chosen lengths match the instrument’s tempo.
Also, because this is a state machine with acceptance logic, you should expect situations where price briefly breaks a boundary and then returns—those are exactly the environments that produce rejected switches. The indicator surfaces that behavior explicitly instead of hiding it. Indicator
Adaptive Spectral Forecast [WillyAlgoTrader]📡 Adaptive Spectral Forecast is an overlay indicator that applies Goertzel spectral analysis to decompose price into its dominant cyclical components, reconstructs them as a harmonic sum, and then extrapolates the resulting waveform forward in time to generate a visual forecast with confidence bands. Signals fire when the forecast direction changes with sufficient signal-to-noise ratio and trend alignment — projecting where price is likely to oscillate next based on the cycles detected in recent history.
This is a fundamentally different approach from trend-following or momentum-based indicators. Instead of asking "where is price going based on its direction and speed?", spectral analysis asks "what recurring cycles exist in this price data, and where do they project to next?" The Goertzel algorithm is a targeted frequency detector — it scans a range of cycle periods, measures the power (amplitude²) at each frequency, identifies the dominant peaks, computes their exact phase and amplitude via DFT projection, and recombines them into a multi-harmonic forecast that decays toward the adaptive trend as it extends into the future.
🧩 WHY THESE COMPONENTS WORK TOGETHER
Raw price is a mix of trend, cycles, and noise. Attempting to forecast raw price directly fails because trend and cycles require different extrapolation methods: trend continues linearly, cycles repeat sinusoidally, and noise should not be extrapolated at all.
This indicator solves the problem through decomposition and reassembly:
EMA trend extraction → Hann-windowed detrending → Goertzel spectral scan → SNR peak detection → DFT coefficient extraction → Harmonic recombination with decay → Trend re-addition → Confidence bands
Each stage addresses a specific challenge:
— Trend extraction separates the slow directional component so it can be extrapolated linearly (via slope), not sinusoidally
— Hann windowing reduces spectral leakage — without it, the finite data window creates false frequency peaks that contaminate the analysis
— Goertzel scanning efficiently measures power at each candidate frequency without computing a full FFT — enabling targeted, adaptive-resolution frequency detection
— SNR filtering ensures only cycles with meaningful signal strength are included — weak noise-level frequencies are discarded
— DFT coefficient extraction computes the exact amplitude and phase of each selected cycle on un-windowed data (the Hann window is only for spectral scanning, not for coefficient calculation — this preserves correct amplitudes)
— Harmonic decay causes the cyclic component to gradually fade toward the trend as the forecast extends forward — reflecting the reality that detected cycles have limited persistence
— Confidence bands widen with √(bars ahead) × ATR, showing that forecast uncertainty grows with distance
Removing any component breaks the pipeline: without detrending, the Goertzel scan detects the trend as a low-frequency "cycle". Without Hann windowing, spectral leakage creates phantom peaks. Without SNR filtering, the forecast includes noise-level harmonics that produce random oscillations. Without decay, the harmonic projection repeats forever at full amplitude (unrealistic). The full pipeline is required.
🔍 WHAT MAKES IT ORIGINAL
1️⃣ Goertzel spectral analysis for cycle detection.
The Goertzel algorithm is a single-frequency DFT that computes the power at one specific period using a recursive formula:
s0 = data + 2×cos(2π/period) × s1 − s2
After iterating through all N data points, the power is: (s1 − s2×cos(ω))² + (s2×sin(ω))², normalized by N² for cross-period comparability.
The indicator scans every integer period from Min Cycle Period (default 8) up to N/2, with an adaptive step size: every period for fast cycles (≤30 bars), step of 2 for longer cycles (reducing computation without losing resolution where it matters most). For each period, the Goertzel power is computed, producing a power spectrum — a map of which cycle lengths carry the most energy in the current price data.
This is fundamentally more targeted than an FFT. An FFT computes power at all frequencies simultaneously but at fixed resolution (determined by window size). The Goertzel approach allows scanning exactly the frequency range of interest with customizable resolution.
2️⃣ SNR-based peak detection with fallback.
From the power spectrum, the indicator identifies local peaks (frequencies where power is higher than both neighbors) and computes the Signal-to-Noise Ratio for each: SNR = peak_power / mean_power_across_all_frequencies. Only peaks with SNR ≥ Min Cycle SNR (default 2.0) are accepted as genuine cycles — the rest are considered noise-level fluctuations.
If no peaks pass the SNR filter (possible in highly random or trend-dominated price action), the algorithm falls back to the single strongest frequency. In this case, the dashboard displays "Weak*" strength and buy/sell signals are suppressed — the forecast is shown for visual reference only, but the indicator acknowledges that no reliable cyclical structure was found.
The top N peaks (sorted by power, N = Harmonics Count, default 5) are selected as the dominant cycles.
3️⃣ DFT coefficient extraction on un-windowed data.
For each selected cycle period, the indicator computes exact sine and cosine coefficients using standard DFT projection:
a = (2/N) × Σ data × sin(2π × i / period)
b = (2/N) × Σ data × cos(2π × i / period)
Critically, this computation uses the raw detrended data (without Hann windowing). The Hann window was only applied for the spectral scan (to identify which frequencies are dominant). Using windowed data for coefficient extraction would distort the amplitude of the harmonics. This two-pass approach — windowed scan for detection, raw data for coefficients — is a key design choice that preserves forecast accuracy.
4️⃣ Harmonic extrapolation with configurable decay.
The forecast is constructed by evaluating the harmonic sum at each future bar:
forecast = trend_projection + Σ (a_k × sin(ω_k × t) + b_k × cos(ω_k × t)) × decay^(t − t_base)
Where trend_projection = trend_last + trend_slope × bars_ahead (linear extrapolation of the EMA trend). The decay factor (default 0.97) causes harmonic amplitude to reduce by 3% per bar, so the cyclic component gradually fades and the forecast converges toward the trend line.
At decay = 1.0, harmonics repeat at full amplitude forever (pure cycle projection). At decay = 0.95, they fade rapidly (forecast becomes trend-only within ~20 bars). Default 0.97 provides meaningful oscillation for the first 20–30 bars before fading. The forecast line is colored by segment: green segments where the forecast is rising, red where falling. Reversal dots mark predicted peaks and troughs.
5️⃣ ATR-based confidence bands with √t scaling.
Uncertainty in the forecast grows with distance. The confidence band width is calculated as:
band_width = ATR(14) × confidence_multiplier × √(bars_ahead)
The √t scaling follows the mathematical principle that forecast variance grows linearly with time horizon (standard deviation grows with square root). The ATR provides the natural volatility scale of the instrument. At bar +1, the band is approximately ATR × multiplier. At bar +25, it's 5× wider. This gives a realistic visual envelope of where price might actually be, not just the central harmonic forecast.
6️⃣ 3-bar consensus forecast direction.
Instead of using a simple "is the next bar higher or lower?" check (which is noisy), the forecast direction is determined by majority vote over 3 bars:
The indicator evaluates the forecast at t+0, t+1, t+2, t+3 and counts upward moves: upVotes = (y1>y0 ? 1:0) + (y2>y1 ? 1:0) + (y3>y2 ? 1:0). If ≥2 of 3 transitions are upward → forecast direction is bullish. If ≤1 → bearish. This consensus approach prevents a single-bar oscillation from flipping the forecast direction.
7️⃣ Trend alignment filter for signal quality.
When enabled (default on), buy signals require the EMA trend slope to be positive, and sell signals require negative slope. This prevents the indicator from generating counter-trend signals when a cycle oscillation temporarily points against the broader trend — which is the most common source of false signals in cycle-based systems.
If the trend filter blocks a direction change, the forecast visualization still updates (you can see the cycle projection) but no signal label is emitted. Additionally, signals are suppressed when the SNR is below the minimum threshold or when the spectral scan fell back to a single non-significant frequency.
8️⃣ Adaptive trend extraction with linear extrapolation.
The trend component is extracted using an EMA with configurable smoothing (default 30 bars), applied forward using the buildTrendArray function. The trend's slope is computed via weighted linear regression over the last 5 points of the trend array — providing a stable slope estimate that isn't dominated by a single bar.
The trend is extrapolated linearly into the forecast: trend_forecast = trend_last + slope × i. This linear projection is appropriate for the short-term forecast horizon (15–55 bars) where trend curvature is typically negligible.
9️⃣ Historical fit visualization.
The reconstructed harmonic sum + trend is plotted over historical data as a polyline, showing how well the detected cycles explain the actual price movement. This serves as an immediate visual validation: if the fit tracks price well, the detected cycles are meaningful. If the fit diverges significantly, the current market regime may not have strong cyclical structure (reflected in low SNR scores in the dashboard).
The fit line is colored by trend direction (green for bullish slope, red for bearish) and decimated for performance (every 1–3 bars depending on lookback length).
🔟 Four presets with coordinated parameter scaling.
— Conservative : lookback ≥ 150, harmonics ≤ 3, forecast ≥ 40 bars — stable, long-term cycles, less overfitting risk
— Default : user settings unchanged
— Aggressive : lookback ≤ 80, harmonics +1, forecast ≤ 25 — faster adaptation, more cycles included
— Scalping : lookback ≤ 50, harmonics +2, forecast ≤ 15 — shortest window, most harmonics, very short projection
Each preset adjusts lookback (spectral window), harmonics count (complexity), and forecast length (projection horizon) as a coordinated unit. Longer lookback needs fewer harmonics (the cycles are more stable). Shorter lookback needs more harmonics (to capture the faster fluctuations within the compressed window).
⚙️ HOW IT WORKS — CALCULATION FLOW
Step 1 — Data collection: The last N bars (Analysis Lookback, default 144) of the selected price source are collected into an array, oldest first.
Step 2 — Trend extraction: An EMA with the Trend Smoothing period (default 30) is applied across the array using a forward-pass recursive formula: trend = α × price + (1−α) × trend . This produces a smooth trend array.
Step 3 — Detrending + Hann window: Each bar's trend value is subtracted from its price. The residual is multiplied by a Hann window: w = 0.5 × (1 − cos(2π×i/(N−1))). This isolates the cyclical component while minimizing spectral leakage at the data boundaries.
Step 4 — Goertzel spectral scan: For each candidate period from minPeriod to N/2 (adaptive step: 1 for periods ≤30, 2 for longer), the Goertzel algorithm computes power. The result is a power spectrum across all scanned frequencies.
Step 5 — Peak detection: Local maxima in the power spectrum are identified (power > both neighbors). Each peak's SNR is computed against the mean power. Peaks with SNR ≥ threshold are accepted. If none pass, the strongest single frequency is used as fallback (with "Weak*" marking).
Step 6 — Coefficient extraction: For the top N peaks (by power), sine and cosine coefficients are computed via DFT projection on raw (un-windowed) detrended data. This gives exact amplitude and phase for each cycle.
Step 7 — Forecast generation: The trend is extrapolated linearly using its 5-bar regression slope. Each harmonic is evaluated at future time steps with decay applied. The sum of trend + decayed harmonics produces the central forecast line. Confidence bands = ATR × multiplier × √(bars_ahead).
Step 8 — Direction and signals: 3-bar consensus determines forecast direction. Trend filter and SNR check gate signal emission. Buy/sell labels appear on bar-close confirmation.
📖 HOW TO USE
🎯 Quick start:
1. Add the indicator — the historical fit and forecast line appear on the last bar
2. The colored dotted line extending right is the forecast (green = rising, red = falling)
3. Colored dots (●) on the forecast mark predicted peaks and troughs
4. Dotted lines above and below = confidence bands (forecast uncertainty zone)
5. ▲/▼ labels = buy/sell signals when the forecast direction changes
👁️ Reading the chart:
— 🟢 Green solid line on history = harmonic fit (uptrend slope)
— 🔴 Red solid line on history = harmonic fit (downtrend slope)
— 🟢🔴 Dotted line extending right = forecast (colored by direction: green rising, red falling)
— 🔵 Upper/lower dotted lines = confidence bands (uncertainty grows with distance)
— 🟢 ● dots = predicted troughs (potential support)
— 🔴 ● dots = predicted peaks (potential resistance)
— 🟢 ▲ below bar = buy signal (forecast changed to bullish)
— 🔴 ▼ above bar = sell signal (forecast changed to bearish)
📊 Dashboard fields:
— Trend: current EMA trend direction (Bullish / Bearish / Neutral)
— Forecast: predicted direction (▲ Up / ▼ Down / — Flat)
— Signal: current state (BUY / SELL / Bullish Bias / Bearish Bias / Wait)
— Strength: cycle quality based on average SNR (Strong > 5.0 / Medium > 2.5 / Weak / Weak* = fallback)
— Dom. Cycle: dominant cycle period in bars (e.g., "34 bars")
— Cycles: how many cycles passed SNR filter vs. requested (e.g., "3 / 5")
— Timeframe, preset, version
🔧 Tuning guide:
— Forecast too noisy: reduce Harmonics Count (3), increase Min SNR (3.0+), increase Trend Smoothing
— Forecast too smooth: increase Harmonics Count (5–7), decrease Min SNR (1.5), decrease Trend Smoothing
— Cycles don't match price: increase Analysis Lookback (200+) for more stable cycle detection, or decrease for faster adaptation
— Forecast fades too fast: increase Decay Rate toward 0.99–1.0
— Forecast unrealistic long-term: decrease Decay Rate toward 0.95, reduce Forecast Bars
— Too many false signals: enable Trend Alignment Filter, increase Min SNR
— Scalping 1–5M: use Scalping preset (lookback ≤50, 7 harmonics, 15-bar forecast)
— Swing 4H–1D: use Conservative preset (lookback ≥150, 3 harmonics, 40-bar forecast)
⚙️ KEY SETTINGS REFERENCE
⚙️ Main:
— Analysis Lookback (default 144): spectral analysis window — the last N bars analyzed
— Harmonics Count (default 5): how many dominant cycles to include in the forecast
— Min Cycle Period (default 8): shortest cycle to scan for (bars)
— Preset (default Default): Conservative / Default / Aggressive / Scalping
— Trend Alignment Filter (default On): require trend-forecast agreement for signals
🔮 Forecast:
— Forecast Bars (default 55): projection length into the future
— Confidence Band Width (default 1.5× ATR): band multiplier
— Trend Smoothing (default 30): EMA period for trend component
— Harmonic Decay Rate (default 0.97): amplitude reduction per bar (1.0 = no decay)
— Min Cycle SNR (default 2.0): signal-to-noise threshold for cycle acceptance
🎨 Visual:
— Historical fit, trend line, reversal dots, confidence bands (all toggleable)
— Auto / Dark / Light theme
🔔 Alerts
— 🟢 BUY — ticker, price, timeframe, time
— 🔴 SELL — same fields
Both support plain text and JSON webhook format. Signals are bar-close confirmed, direction-locked, trend-filtered, and SNR-gated.
⚠️ IMPORTANT NOTES
— 📐 This is spectral analysis, not trend following. The indicator detects and projects recurring cycles. In markets with strong cyclical structure (commodities, forex majors, crypto with regular oscillations), it performs well. In news-driven or momentum-dominated markets with no cyclical structure, the SNR will be low and the forecast unreliable — the dashboard reflects this via the Strength reading.
— 🚫 No repainting of signals. The spectral analysis runs on barstate.islast (updating the forecast in real time on the current forming bar). Signals only fire on the next barstate.isconfirmed bar, after the forecast direction has been set. This means the forecast line itself updates in real time (by design — it's a live projection), but buy/sell signals are confirmed and do not change retroactively.
— 📊 The forecast is a projection, not a prediction. It shows where price would go if the detected cycles continue with their current amplitude and phase. Real markets introduce new information that disrupts cycles. The confidence bands reflect this growing uncertainty. Treat the forecast as a probabilistic zone, not a target.
— 🔄 "Weak*" strength means no cycles passed the SNR filter and the indicator fell back to the single strongest frequency. In this state, signals are suppressed. The forecast is still shown for visual reference but should not be trusted for trading decisions.
— ⚖️ The Hann window is applied only for spectral scanning , not for coefficient extraction. This is deliberate: the window prevents spectral leakage during frequency detection, but the un-windowed data preserves correct harmonic amplitudes for the forecast.
— 📏 The forecast extends a fixed number of bars into the future. Accuracy degrades with distance — the first 10–15 bars are typically the most reliable. The confidence bands quantify this degradation visually.
— 🛠️ This is a spectral analysis and forecasting tool , not an automated trading bot. It detects cycles, projects them forward, and generates directional signals — trade decisions remain yours.
— 🌐 Works on all markets and timeframes. Cycle periods adapt automatically to whatever timeframe you apply it on. Indicator
AMT Multi-Ticker Imbalance Dashboard [AMT] + Strength/Age ScoreAMT Multi-Ticker Imbalance Dashboard + Strength/Age Score
The AMT Multi-Ticker Imbalance Dashboard is a multi-asset volume imbalance scanner designed to detect, rank, and compare stacked buying or selling pressure across up to six symbols — all from a single chart.
This tool does not rely on simple candle direction or trend signals. Instead, it builds a structured micro-profile of price and volume distribution over a rolling lookback window, then identifies stacked volume dominance inside price bins. The result is a real-time dashboard that highlights where aggressive participation is building — and how strong and fresh that imbalance is.
What This Script Does
This script:
• Scans up to 6 user-defined tickers simultaneously
• Builds a rolling price-volume profile over a configurable lookback
• Detects stacked buy or sell imbalances inside price bins
• Measures imbalance strength (stack size)
• Tracks imbalance age (how recent it triggered)
• Calculates a weighted strength score
• Displays everything in a color-graded dashboard
It functions as a cross-market orderflow pressure monitor, helping traders identify where initiative activity is expanding across correlated or leading assets.
The Core Concept: Stacked Volume Imbalances
Instead of evaluating the whole bar as bullish or bearish, the script:
Takes the last Profile Lookback bars.
Finds the highest high and lowest low.
Divides that range into Profile Resolution bins (price slices).
Inside each bin, it calculates:
Total buy volume (close > open)
Total sell volume (open > close)
It then measures dominance:
Buy imbalance = Buy volume ≥ threshold % of total volume
Sell imbalance = Sell volume ≥ threshold % of total volume
If multiple consecutive bins meet that dominance threshold, they form a stack.
Stack size represents how many adjacent price zones show aggressive one-sided participation.
Why Stacked Imbalances Matter
Single imbalances can be noise.
Stacked imbalances suggest:
• Aggressive initiative activity
• Strong directional conviction
• Potential continuation pressure
• Possible structural repricing
The script only signals when the stack size meets or exceeds the Stack Size Trigger, filtering weak participation.
Dashboard Columns Explained
1️⃣ Ticker
The symbol being scanned.
2️⃣ Stack
Displays:
“X BUY” → number of consecutive buy imbalance bins
“X SELL” → number of consecutive sell imbalance bins
“—” → no qualifying imbalance
3️⃣ Bias
Directional interpretation:
Bullish Imbalance
Bearish Imbalance
Neutral
4️⃣ Score (Strength + Recency Weighted)
The score combines:
Stack Size × Age Weight
Age weighting logic:
New signal (age = 0 bars): 1.5x multiplier
1–3 bars old: 1.0x multiplier
Older than 3 bars: 0.5x multiplier
This means:
• Fresh imbalances rank higher
• Older signals decay in importance
• Strong and new stacks visually dominate
Color Logic
Color intensity reflects both direction and weighted strength:
Bullish
Bright Green → Strong + Fresh
Medium Green → Moderate
Dim Green → Weak or Aging
Bearish
Bright Red → Strong + Fresh
Medium Red → Moderate
Dim Red → Weak or Aging
Neutral = Gray
This allows instant visual ranking across assets.
Inputs Explained
Profile Lookback
Number of bars used to build the rolling profile.
Smaller values:
• Faster responsiveness
• More reactive
Larger values:
• Smoother structure
• More institutional footprint detection
Profile Resolution
Number of bins dividing the price range.
Higher resolution:
• More granular imbalance detection
• More sensitive stacking
Lower resolution:
• Broader structural imbalance zones
Bin Imbalance Threshold
Minimum % dominance required to qualify.
Default: 0.75 (75%)
Higher:
• Stronger conviction required
• Fewer but more aggressive signals
Lower:
• More frequent but softer signals
Stack Size Trigger
Minimum consecutive imbalance bins required.
This filters weak activity and prevents single-bin noise.
Dashboard Position
Choose where the table appears.
How This Script Is Original
This is not:
• A delta oscillator
• A cumulative volume line
• A simple up/down volume ratio
• A standard volume profile
It uniquely combines:
Rolling dynamic profile construction
Per-bin dominance calculation
Consecutive imbalance stacking
Multi-ticker cross-asset scanning
Age-weighted strength scoring
Visual ranking dashboard
Most imbalance tools operate on a single chart and focus on visual zones.
This script transforms imbalance logic into a comparative, cross-market decision tool.
How Traders Can Use It:
Market Leadership Detection
Identify which asset is currently driving momentum.
Example:
If IWM shows a fresh 5 BUY stack while SPX shows neutral → small caps may be leading risk appetite.
Confirmation Tool
Use imbalance confirmation before entering:
• Breakouts
• Acceptance above value
• Fair value gap continuation
• Sequence continuation setups
Rotation Monitoring
Watch for:
• Bullish stacks turning neutral
• Bearish stacks emerging in correlated assets
• Leadership shifting across sectors
Timing Advantage
Fresh stacks (bright colors + high score) highlight where initiative flow is most recent — often before broader price expansion.
Important Notes
• Signals are calculated on the chart’s current timeframe.
• Higher timeframes detect structural imbalance.
• Lower timeframes detect short-term aggression.
• This is a participation pressure scanner — not a standalone entry trigger.
• Always confirm with structure, liquidity, and context.
Summary
The AMT Multi-Ticker Imbalance Dashboard transforms raw volume into structured imbalance intelligence.
It tells you:
• Who is dominant (buyers or sellers)
• How strong that dominance is
• How fresh it is
• Which asset is leading
I
nstead of watching one chart, you monitor relative aggressive participation across six markets — in real time — with objective scoring and visual ranking.
This allows traders to align with the strongest active pressure, avoid fading initiative flow, and improve timing precision through imbalance awareness. Indicator
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BASCOOL_LibBASCOOL Library v1
Range–Body Structure Analysis Toolkit for Intraday Trading
The BASCOOL Library provides high-quality, reusable Pine Script components for structural conviction analysis based purely on price action. It is designed for intraday traders who rely on volatility-adjusted range expansion and candle-body efficiency to identify strong, weak, or choppy market conditions.
Included Functions
rbm_from_ohlc() – Range–Body Measure (RBM)
A volatility-normalized structure indicator that evaluates:
Range Expansion:
Smooth EMA of (High–Low), normalized by ATR
→ captures strength of movement relative to volatility
Body Efficiency:
Body-to-Range ratio smoothed with EMA
→ measures how much of the candle’s range is “directional”
The RBM output is a smooth structural strength score typically between 0 and 1, where:
High RBM → strong structure, clean movement, trend-friendly conditions
Low RBM → compressed ranges, weak bodies, low-quality structure
Flat RBM → choppy environment, avoid directional trades Library
SuperTrend AI AdaptiveSuperTrend AI detects market regime shifts and adapts the band width automatically, then scores every trend flip with a 5-factor quality engine so you know which signals to trust.
◈ How It Works
Standard SuperTrend has one fixed multiplier. It works great in trending markets but gets chopped apart in ranging conditions. This version solves that by detecting the current market regime and adapting in real time.
The indicator classifies every bar into one of three regimes:
TRENDING: ADX above threshold + normal ATR. Multiplier stays at base. SuperTrend works as intended.
RANGING: ADX below threshold + compressed ATR. Multiplier tightens slightly for faster response. Band draws as a dotted line to warn you.
VOLATILE: ATR expanding well above its historical average. Multiplier widens to absorb the noise and prevent false flips.
The regime is determined by two factors: the ATR ratio (current ATR vs its moving average over the lookback period) and the ADX reading. This gives you a structural view of market conditions, not just price direction.
◈ Adaptive Multiplier
When adaptation is enabled, the multiplier adjusts dynamically:
In volatile regimes, the multiplier increases proportionally to how expanded the ATR is. This widens the band and filters out noise-driven flips.
In ranging regimes, the multiplier drops to 85% of base. Tighter bands let you catch the transition when a real trend starts.
In trending regimes, the multiplier stays at base. No adjustment needed when conditions are ideal.
The multiplier is capped between 0.5x and 2x of your base setting so it never goes extreme. You can see the current adaptive multiplier in the dashboard at all times.
◈ AI Signal Scoring
Every SuperTrend flip gets a quality score from 0 to 100 based on 5 factors:
Volume Surge (0-20 pts): Volume on the flip bar vs 20-period average. Higher volume = more conviction behind the move.
Displacement (0-25 pts): How far price closed beyond the band on the flip. Bigger displacement = stronger breakout.
Trend Alignment (0-20 pts): Does the flip direction match the EMA trend? Aligned signals score higher.
Regime Quality (0-15 pts): Signals in trending regimes score highest. Ranging regime signals get penalized.
Band Distance (0-20 pts): How far price traveled to reach the band before flipping. Wider gap = more conviction.
Bright signals (★) score above 70 and represent high-quality flips with multiple factors confirming. Dim signals (○) score 40-69 and are worth watching but carry more risk. By default only bright signals display.
◈ Visual System
The band uses a neon glow effect (three layered plots) that makes it easy to track on any chart. The band color itself tells you the current regime at a glance:
Green/red glow = trending regime, normal SuperTrend behavior.
Amber glow = volatile regime, multiplier has widened to absorb noise.
Gray dotted line = ranging regime, multiplier tightened, use caution.
A subtle background tint appears during volatile (amber) and ranging (gray) periods so you can see regime context without looking at the dashboard. Both the glow and background tint can be toggled off in settings.
The gradient fill between price and band is available but off by default. Enable it in settings if you prefer that style.
◈ How to Read the Dashboard
ST AI ◈: header
Trend: current SuperTrend direction (▲ BULLISH / ▼ BEARISH) with bias label
Regime: current market classification (TRENDING / VOLATILE / RANGING) with ATR ratio
EMA: whether the trend EMA agrees with SuperTrend direction (✓ ALIGNED / ✗ COUNTER)
Multiplier: current adaptive value vs your base setting
ADX: trend strength reading with visual bar
Signal: last signal state with score in points
◈ Recommended Settings
Forex (EUR/USD, GBP/JPY) 1H to 4H: ATR 10, Multiplier 3.0, Regime Lookback 40, ADX 14
Crypto (BTC, ETH) 1H to 4H: ATR 10, Multiplier 3.0, Regime Lookback 50, ADX 14
Scalping 5min to 15min: ATR 7, Multiplier 2.0, Regime Lookback 30, ADX 10
Swing trading Daily: ATR 14, Multiplier 3.5, Regime Lookback 50, ADX 14
Indices (NAS100, SPX500) 15min to 1H: ATR 10, Multiplier 2.5, Regime Lookback 40, ADX 14
For fewer signals: Raise Min Signal Score to 60+, increase cooldown
For more signals: Lower Min Signal Score to 30, enable dim signals, reduce cooldown
◈ Key Features
✓ Non-repainting: all signals on confirmed bar close
✓ Regime-adaptive: multiplier adjusts to trending, ranging, and volatile conditions automatically
✓ AI signal scoring: 5-factor quality engine, 0-100 per flip
✓ Neon glow band: color shifts with regime state, visible at a glance
✓ Regime background: subtle tint shows volatile and ranging periods on the chart
✓ ADX integration: trend strength directly influences regime detection and scoring
✓ 7 alert conditions: bull/bear signals, AI-confirmed signals, trend flips, regime changes
✓ Clean dashboard: trend, regime, multiplier, ADX, and signal score in one panel
✓ 100% original code: not derived from any existing script
◈ What Makes This Different
Standard SuperTrend uses a fixed multiplier. It works until the market changes character, then gives false flips until you manually adjust. This version detects the change and adjusts for you.
The scoring tells you not just that a flip happened, but whether it is likely to be meaningful. A flip during a trending regime with high volume and strong displacement scores 85+. The same flip during a ranging regime with weak volume might score 45. Both are flips, but only one is worth trading.
◈ Disclaimer
No indicator predicts the future. Regime detection is probabilistic, not certain. Use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
Happy trading. Indicator
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Trend Harmony🚀 Trend Harmony: Multi-Timeframe Momentum & Trend Dashboard
Trend Harmony is a sophisticated multi-timeframe (MTF) analysis tool designed to help traders identify high-probability setups by spotting "Market Harmony." Instead of flipping through charts, this indicator synthesizes RSI momentum and EMA trend structures from four different time horizons into a single, intuitive dashboard.
🔍 How It Works
The core philosophy of this indicator is that the most powerful moves happen when short-term momentum aligns with long-term trend structure. The script tracks four user-defined timeframes simultaneously.
1. The Trend Scoring Engine
The indicator evaluates the relationship between a Fast EMA (default 20) and a Slow EMA (default 50) across all active timeframes.
Bullish Alignment: Fast EMA > Slow EMA.
Bearish Alignment: Fast EMA < Slow EMA.
2. The Harmony Summary
At the bottom of the dashboard, the "Summary" status calculates the total "Harmony" of the market:
🚀 FULL BULL HARMONY: All selected timeframes are in a bullish trend.
📉 FULL BEAR HARMONY: All selected timeframes are in a bearish trend.
⚠️ CAUTION (Overbought/Oversold): Triggered when the market is in "Full Harmony" but RSI levels suggest the price is overextended (>70 or <30). This warns you not to "chase" the trade.
Neutral/Mixed: Timeframes are in conflict (e.g., 15m is bullish but Daily is bearish).
🛠 Key Features
Unified RSI Pane: View four RSI lines on one chart to spot divergences or "clusters" where all timeframes bottom out at once.
Dynamic Table: Real-time tracking of:
Price vs EMA: Instant visual (▲/▼) showing if price is above/below your key averages.
Smart RSI Coloring: RSI values turn Green during "Power Zones" (0–30 or 50–70) and Red otherwise.
Full Customization: Change timeframes (1m, 5m, 1H, D, etc.), EMA lengths, and RSI parameters to fit your strategy.
📈 Trading Strategy Tips
Wait for the Sync: The "Full Harmony" status is your signal that the "tide" is moving in one direction. Look for long entries when the status is Green and short entries when it is Red.
The Pullback Entry: When the summary says "Caution (Overbought)," wait for the RSI lines to cool down toward the 50 level before entering the trend again.
RSI Clustering: When all four RSI lines converge at extreme levels (30 or 70), a massive volatility expansion is usually imminent. Indicator
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Trend Break Targets [MarkitTick]Trend Break Targets
Trend Break Targets is a technical analysis tool designed to assist traders in identifying trendline breakouts and projecting potential price targets based on market geometry. Unlike fully automated indicators that guess trendlines, this tool provides you with precise control by allowing you to manually Pivot Point the trendline to specific points in time, while automating the complex math of target projection and structure mapping.
Theoretical Basis & Concepts
This indicator is grounded in classic technical analysis principles found in foundational trading literature. It automates the following methodology:
Drawing a trend line between two key points to represent dynamic support or resistance.
Identifying a breakout when the price closes above or below this line, potentially signaling a change in trend.
Calculating a price target by measuring the vertical distance between the breakout line and the last high/low (pivot), then projecting that same distance in the direction of the breakout.
This concept is based on methods and "Measured Move" theories explained in classic books such as "Technical Analysis of Stock Trends" by Edwards & Magee, "Technical Analysis of the Financial Markets" by John Murphy, and in Thomas Bulkowski's Price Pattern Studies.
How It Works
Pivot Pointed Trendline Construction The script draws a trendline between two user-defined points in time (Start Date and End Date). It calculates the slope between these points and extends the line infinitely to the right, allowing you to define the exact structure (e.g., a resistance trendline on a wedge).
Breakout Detection The script monitors the "Price Source" (High, Low, or Close) relative to the extended trendline.
A Bullish Breakout (BC) occurs when the Close crosses above a bearish trendline.
A Bearish Breakout (BC) occurs when the Close crosses below a bullish trendline.
Dynamic Target Projection (The Math) Upon a confirmed breakout, the script automatically calculates three distinct targets by identifying the most significant "Swing Point" (Pivot) prior to the breakout.
Distance (D): The vertical distance between the Trendline and the Pivot Price at the specific bar where the pivot occurred.
Target 1 (T1): The Breakout Price +/- (Distance × 1.0). This represents a classic 1:1 measured move.
Target 2 (T2): The Breakout Price +/- (Distance × 1.618). Based on the Golden Ratio extension.
Target 3 (T3): The Breakout Price +/- (Distance × 2.618).
Market Structure (CHOCH) The script includes an optional Change of Character (CHOCH) module. This runs independently of the trendline logic, identifying local Swing Highs and Swing Lows based on the "Swing Detection Length." It plots dashed lines and labels to visualize immediate shifts in market structure.
How to Use This Tool
This is an interactive tool that requires user input to define the setup.
Identify a Setup: Locate a clear trend, wedge, or flag pattern on your chart.
Set Pivot Points: Go to the Indicator Settings. Input the exact Start Date and End Date corresponding to the two main touches of your trendline.
Monitor for Breakout: The script will extend the line. Wait for a "BC" label to appear.
Trade Management: Once "BC" prints, the T1, T2, and T3 lines will instantly render. These can be used as potential take-profit zones or areas to tighten stop-losses.
Settings & Configuration
Indicator Settings
Start/End Date: The timestamp Pivot Points for your trendline.
Price Source: Determines what price (High or Low) Pivot Points the line and triggers the breakout.
Pivot Left/Right: Adjusts the sensitivity for finding the "Pivot Before Break" used for target calculations.
Extend Target Line: How far forward the target lines are drawn.
Visual Style
Colors: Fully customizable colors for the Trendline, Breakout Labels, and each Target level (T1, T2, T3).
Gold Bullish Reversal
This analysis dissects a confirmed bullish reversal on Gold using a custom Trend Break system. The setup identifies a transition from a bearish corrective phase to bullish momentum, validated by a structural break and a geometric target projection.
Trend Identification (The Pivot Points) The descending white trendline serves as the primary dynamic resistance, defining the bearish correction.
Pivot Points: The line is drawn connecting two significant swing highs, marked by Label 1 and Label 2.
Logic: These points represent the "lower highs" characteristic of the previous downtrend. As long as price remained below this trajectory, the bearish bias was intact.
The Trigger: Breakout & Confirmation The transition occurs at the candle marked BC (Breakout Candle).
Breakout Criteria: The indicator logic dictates that a signal is only valid when the bar closes above the trendline. This filters out intraday wicks and ensures genuine buyer commitment.
CHOCH Confluence: Immediately following the breakout, a CHOCH (Change of Character) label appears. This signals a shift in market structure, indicating that the internal lower-high/lower-low sequence has been violated, adding probability to the reversal.
Target Projection: The Measured Move The vertical green lines (T1, T2) represent profit objectives derived from the depth of the prior move. The logic calculates the distance between the breakout line and the lowest pivot prior to the break.
T1 (Standard Target): This is a 1:1 projection of the pre-breakout volatility. We see price action initially stalling near this level, confirming it as a zone of interest.
T2 (Golden Ratio Extension): The second target is calculated as the initial distance multiplied by 1.618 (Fibonacci Golden Ratio). The chart shows the price rallying aggressively through T1 to tap the T2 zone, often considered an exhaustion or major take-profit level in harmonic extensions.
Conclusion Gold has successfully invalidated the 4-hour bearish trendline. The confluence of a confirmed close above resistance (BC) and a structural shift (CHOCH) provided a high-probability long setup. The price has now fulfilled the T2 (1.618) extension, suggesting traders should watch for consolidation or a reaction at this key Fibonacci resistance level.
Bearish Trendline Breakdown
The image displays a Bearish Trendline Breakdown on the Gold (XAUUSD) 4-hour chart. The indicator is actually functioning in "Low" mode here (connecting swing lows to form support), which triggers the bearish logic found in the code. Here is the step-by-step breakdown:
The Setup: Pivot Points & Trendline
Visual: The Blue Labels "1" and "2" connected by a white diagonal line.
Code Logic: These are the user-defined start and end points.
Pivot Point 1 (startDate): The starting pivot of the trendline.
Pivot Point 2 (endDate): The ending pivot.
Trendline: The code draws a line between these two points and extends it to the right (extend.right). In this specific image, the line acts as a Support Trendline.
The Trigger: Break Candle (BC)
Visual: The Red Label "BC" appearing just below the white trendline.
Code Logic: This is the execution signal. The code detects a "Down Break" (dnBreak) because the Price Source was likely set to "Low" and the candle's Close was lower than the Trendline Price at that specific bar (close < currLinePrice). This confirms the support level has been breached.
The Projection: Targets (T1 & T2)
Visual: The Green Labels "T1" and "T2" with dotted horizontal lines projected downward.
Code Logic: These are profit targets based on a "Measured Move."
Pivot Calculation: The script looks back for a recent "Pivot High" (the peak before the crash) to calculate the volatility/distance (dist) between that peak and the trendline.
T1 (Conservative): The price is projected downward by 1x that distance (currLinePrice - dist).
T2 (Extended): The price is projected downward by 1.618x that distance (Golden Ratio extension).
Market Context: CHOCH
Visual: The small Red/Orange "CHOCH" labels appearing above the price action.
Code Logic: This is a secondary confirmation system running independently of the trendline. It detects a Change of Character (structural shift). The red labels indicate a "Bearish CHOCH," meaning the price broke below a significant prior swing low (last_swing_low). This supports the bearish bias of the trendline break.
Disclaimer This tool is for educational and technical analysis purposes only. Breakouts can fail (fake-outs), and past geometric patterns do not guarantee future price action. Always manage risk and use this tool in conjunction with other forms of analysis. Indicator
Trend detection zero lag Trend Detection Zero-Lag (v6)
Trend Detection Zero-Lag is a high-performance trend identification indicator designed for intraday traders, scalpers, and swing traders who require fast trend recognition with minimal lag. It combines a zero-lag Hull Moving Average, slope analysis, swing structure logic, and adaptive volatility sensitivity to deliver early yet stable trend signals.
This indicator is optimized for real-time decision-making, particularly in fast markets where traditional moving averages react too slowly.
Core Features
🔹 Zero-Lag Trend Engine
Uses a Zero-Lag Hull Moving Average (HMA) to reduce lag by approximately 40–60% versus standard moving averages.
Provides earlier trend shifts while maintaining smoothness.
🔹 Multi-Factor Trend Detection
Trend direction is determined using a hybrid engine:
HMA slope (momentum direction)
Rising / falling confirmation
Swing structure detection (HH/HL vs LH/LL)
ATR-adjusted dynamic sensitivity
This approach allows fast flips when conditions change, without excessive noise.
Adaptive Volatility Sensitivity
Sensitivity dynamically adjusts based on ATR relative to price
In high volatility: faster reaction
In low volatility: smoother, more stable trend state
This ensures the indicator adapts across:
Trend days
Range days
Volatility expansion or contraction
Trend Duration Intelligence
The indicator tracks historical trend durations and maintains a rolling memory of recent bullish and bearish phases.
From this, it calculates:
Current trend duration
Average historical duration for the active trend direction
This helps traders gauge:
Whether a trend is early, mature, or extended
Probability of continuation vs exhaustion
Strength Scoring
A normalized Trend Strength Score (0–100) is calculated using:
Zero-lag slope magnitude
ATR normalization
This provides a quick read on:
Weak / choppy trends
Healthy trend continuation
Overextended momentum
Visual Design
Color-coded Zero-Lag HMA
Bullish trend → user-defined bullish color
Bearish trend → user-defined bearish color
Designed for dark mode / neon-style charts
Clean overlay with no clutter
Trend Detection Zero-Lag is built for traders who need:
Faster trend recognition
Adaptive behavior across market regimes
Structural confirmation beyond simple moving averages
Clear, actionable visual signals Indicator
The Abramelin Protocol [MPL]"Any sufficiently advanced technology is indistinguishable from magic." — Arthur C. Clarke
🌑 SYSTEM OVERVIEW
The Abramelin Protocol is not a standard technical indicator; it is a "Technomantic" trading algorithm engineered to bridge the gap between 15th-century esoteric mathematics and modern high-frequency markets.
This script is the flagship implementation of the MPL (Magic Programming Language) project—an open-source experimental framework designed to compile metaphysical intent into executable Python and Pine Script algorithms.
Unlike traditional indicators that rely on arbitrary constants (like the 14-period RSI or 200 SMA), this protocol calculates its parameters using "Dynamic Entity Gematria." We utilize a custom Python backend to analyze the ASCII vibrational frequencies of specific metaphysical archetypes, reducing them via Tesla's 3-6-9 harmonic principles to derive market-responsive periods.
🧬 WHAT IS ?
MPL (Magic Programming Language) is a domain-specific language and research initiative created to explore Technomancy—the art of treating code as a spellbook and the market as a chaotic entity to be tamed.
By integrating the logic of ancient Grimoires (such as The Book of Abramelin) with modern Data Science, MPL aims to discover hidden correlations in price action that standard tools overlook.
🔗 CONNECT WITH THE PROJECT:
If you are a developer, a trader, or a seeker of hidden knowledge, examine the source code and join the order:
• 📂 Official Project Site: hakanovski.github.io
• 🐍 MPL Source Code (GitHub): github.com
• 👨💻 Developer Profile (LinkedIn): www.linkedin.com
🔢 THE ALGORITHM: 452 - 204 - 50
The inputs for this script are mathematically derived signatures of the intelligence governing the system:
1. THE PAIMON TREND (Gravity)
• Origin: Derived from the ASCII summation of the archetype PAIMON (King of Secret Knowledge).
• Function: This 452-period Baseline acts as the market's "Event Horizon." It represents the deep, structural direction of the asset.
• Price > Line: Bullish Domain.
• Price < Line: Bearish Void.
2. THE ASTAROTH SIGNAL (Trigger)
• Origin: Derived from the ASCII summation of ASTAROTH (Knower of Past & Future), reduced by Tesla’s 3rd Harmonic.
• Function: This is the active trigger line. It replaces standard moving averages with a precise, gematria-aligned trajectory.
3. THE VOLATILITY MATRIX (Scalp)
• Origin: Based on the 9th Harmonic reduction.
• Function: Creates a "Cloud" around the signal line to visualize market noise.
🛡️ THE MILON GATE (Matrix Filter)
Unique to this script is the "MILON Gate" toggle found in the settings.
• ☑️ Active (Default): The algorithm applies the logic of the MILON Magic Square. Signals are ONLY generated if Volume and Volatility align with the geometric structure of the move. This filters out ~80% of false signals (noise).
• ⬜ Inactive: The algorithm operates in "Raw Mode," showing every mathematical crossover without the volume filter.
⚠️ OPERATIONAL USAGE
• Timeframe: Optimized for 4H (The Builder) and Daily (The Architect) charts.
• Strategy: Use the Black/Grey Line (452) as your directional bias. Take entries only when the "EXECUTE" (Long) or "PURGE" (Short) sigils appear.
Use this tool wisely. Risk responsibly. Let the harmonics guide your entries.
— Hakan Yorganci
Technomancer & Full Stack Developer Indicator
Trend Vector Pro v2.0Trend Vector Pro v2.0
👨💻 Developed by: Mohammed Bedaiwi
💡 Strategy Overview & Coherence
Trend Vector Pro (TVPro) is a momentum-based trend & reversal strategy that uses a custom smoothed oscillator, an optional ADX filter, and classic Pivot Points to create a single, coherent trading framework.
Instead of stacking random indicators, TVPro is built around these integrated components:
A custom momentum engine (signal generation)
An optional ADX filter (trend quality control)
Daily Pivot Points (context, targets & S/R)
Swing-based “Golden Bar” trailing stops (trade management)
Optional extended bar detection (overextension alerts)
All parts are designed to work together and are documented below to address originality & usefulness requirements.
🔍 Core Components & Justification
1. Custom Momentum Engine (Main Signal Source)
TVPro’s engine is a custom oscillator derived from the bar midpoint ( hl2 ), similar in spirit to the Awesome Oscillator but adapted and fully integrated into the strategy. It measures velocity and acceleration of price, letting the script distinguish between strong impulses, weakening trends, and pure noise.
2. ADX Filter (Trend Strength Validation – Optional)
Uses Average Directional Index (ADX) as a gatekeeper.
Why this matters: This prevents the strategy from firing signals in choppy, non-trending environments (when ADX is below the threshold) and keeps trades focused on periods of clear directional strength.
3. Classic Pivot Points (Context & Targets)
Calculates Daily Pivot Points ( PP, R1-R3, S1-S3 ) via request.security() using prior session data.
Why this matters: Momentum gives the signal, ADX validates the environment, and Pivots add external structure for risk and target planning. This is a designed interaction, not a random mashup.
🧭 Trend State Logic (5-State Bar Coloring)
The strategy uses the momentum's value + slope to define five states, turning the chart into a visual momentum map:
🟢 STRONG BULL (Bright Green): Momentum accelerating UP. → Strong upside impulse.
🌲 WEAK BULL (Dark Green): Momentum decelerating DOWN (while positive). → Pullback/pause zone.
🔴 STRONG BEAR (Bright Red): Momentum accelerating DOWN. → Strong downside impulse.
🍷 WEAK BEAR (Dark Red): Momentum decelerating UP (while negative). → Rally/short-covering zone.
🔵 NEUTRAL / CHOP (Cyan): Momentum is near zero (based on noise threshold). → Consolidation / low volatility.
🎯 Signal Logic Modes
TVPro provides two selectable entry styles, controlled by input:
Reversals Only (Cleaner Mode – Default): Targets trend flips. Entry triggers when the current state is Bullish (or Bearish) and the previous state was not. This reduces noise and over-trading.
All Strong Pulses (Aggressive Mode): Targets acceleration phases. Entry triggers when the bar turns to STRONG BULL or STRONG BEAR after any other state. This mode produces more trades.
📌 Risk Management Tools
🟡 Golden Bars – Trailing Stops: Yellow “Trail” Arrows mark confirmed Swing Highs/Lows. These are used as logical trailing stop levels based on market structure.
Extended Bars: Detects when price closes outside a 2-standard-deviation channel, flagging overextension where a pullback is more likely.
Pivot Points: Used as external targets for Take Profit and structural stop placement.
⚙️ Strategy Defaults (Crucial for Publication Compliance)
To keep backtest results realistic and in line with House Rules, TVPro is published with the following fixed default settings:
Order Size: 5% of equity per trade ( default_qty_value = 5 )
Commission: 0.04% per order ( commission_value = 0.04 )
Slippage: 2 ticks ( slippage = 2 )
Initial Capital: 10,000
📘 How to Trade with Trend Vector Pro
Entry: Take Long when a Long signal appears and confirm the bar is Green (Bull state). Short for Red (Bear state).
Stop Loss: Place the initial SL near the latest swing High/Low, or near a relevant Pivot level.
Trade Management: Follow Golden (Trail) Arrows to trail your stop behind structure.
Exits: Exit when: the trailing stop is hit, Price reaches a major Pivot level, or an opposite signal prints.
🛑 Disclaimer
This script is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always forward-test and use proper risk management before applying any strategy to live trading.
Strategy
