[Pandora] Laguerre Ultimate Explorations MulticatorIt's time to begin demonstrations differentiating the difference between known and actual feasibility beyond imagination... Welcome to my algorithmic twilight zone .
INTRODUCTION:
Hot off my press, I present this Laguerre multicator employing PSv6.0, originally formulated by John Ehlers for TASC - July 2025 Traders Tips. Basically I transcended Ehlers' notions of transversal filtration with an overhaul of his Laguerre design with my "what if" Pandora notions included. Striving beyond John Ehlers' original intended design. This action packed indicator is a radically revamped version of his original filter using novel techniques. My aim was to explore whether providing even more enhanced responsiveness and lesser lag is possible and how. Presented here is my mind warping results to witness.
EHLERS' LAGUERRE EXPLAINED:
First and foremost, the concept of Ehlers' Laguerre-izing method deserves a comprehensive deep dive. Ehlers' Laguerre filter design, as it functions originally, begins with his Ultimate Smoother (US) followed by a gang of four LERP (jargon for Linear intERPolation) filters. Following a myriad of cascading LERPs is a window-like FIR filter tapped into the LERP delay values to provide extra smoothness via the output.
On a side note, damping factor controlled LERP filters resemble EMAs indeed, but aren't exactly "periodic" filters that would have a period/length parameter and their subsequent calculations. I won't go into fine-grained relationship details, but EMA and LERP are indeed related in approach, being cousins of similar pedigree.
EXAMINING LAGUERRE:
I focused firstly on US initialization obstacles at Pine's bar_index==0 with nz() in abundance. The next primary notion of intrigue I mostly wondered about was, why are there four LERP elements instead of fewer or more. Why not three or why not two LERPs, etc... 1-4-6-4-1, I remember seeing those coefficients before in high pass filters.
Gathering my thoughts from that highpass knowledge base, I devised other tapped configuration modes to inspect their behavior out of curiosity. Eureka! There is actually more to Laguerre than Ehlers' mind provided, now that I had formulated additional modes. Each mode exhibits it's own lag/smoothness characteristics better than the quad LERPed version. I narrowed it down to a total of 5 modes for exploration. Mode 0 is just the raw US by itself.
ANALYZING FILTER BEHAVIORS:
Which option might be possibly superior, and how may I determine that? Fortunately, I have a custom-built analyzer allowing me to thoroughly examine transient responses across multiple periodicities simultaneously, providing remarkable visual insights.
While Ehlers has meagerly touched upon presenting general frequency responses in his books, I have excelled far beyond that. This robust filter analysis capability enables me to observe finer aspects hidden to others, ultimately leading to the deprecation of numerous existing filters. Not only this, but inventing entirely new species of filtration whether lowpass, highpass, or bandpass is already possible with a thorough comprehensive evaluation.
Revealing what's quirky with each filter and having the ability to discover what filters may be lacking in performance, is one of it's implications. I'm just going to explain this: For example US has a little too much overshoot to my liking, along with nonconformant cutoff frequency compliance with the period parameter. Perhaps Ehlers should inspect US coefficients a bit closer... I hope stating this is not received in an ill manner, as it's not my intention here.
What this technically eludes to is that UltimateSmoother can be further improved, analogous to my Laguerre alterations described above. I will also state Laguerre can indeed be reformulated to an even greater extent concerning group delay, from what I have already discussed. Another exciting time though... More investigative research is warranted.
LAGUERRE CONCLUSIONS:
After analyzing Laguerre's frequency compliance, transient responses, amplitudes, lag, symmetry across periodicities, noise rejection, and smoothness... I favor mode 3 for a multitude of reasons over the mode 4 configuration, but mostly superb smoothing with less lag, AND I also appreciated mode 1 & 2 for it's lower lag performance options.
Each mode and lag (phase shift) damping value has it's own unique characteristics at extremes, yet they demonstrate additional finesse in it's new hybrid form without adding too much more complexity. This multicator has a bunch of Laguerre filters in the overlay chart over many periodicities so you can easily witness it's differing periodic symmetries on an input signal while adjusting lag and mode.
LAGUERRE OSCILLATOR:
The oscillator is integrated into the laguerreMulti() function for the intention of posterity only. I performed no evaluation on it, only providing the code in Pine. That wasn't part of my intended exploration adventure, as I'm more TREND oriented for the time being, focusing my efforts there.
Market analysis has two primary aspects in my observations, one cyclic while the other is trending dynamics... There's endless oscillators, but my expectations for trend analysis seems a little lesser explored in my opinion, hence my laborious trend endeavors. Ehlers provided both indicator facets this time around, and I hope you find the filtration aspect more intriguing after absorption of this reading.
FUNCTION MODULES EXPLAINED:
The Ultimate Smoother is an advanced IIR lowpass smoothing filter intended to minimize noise in time series data with minimal group delay, similar to a traditional biquad filter. This calculation helps to create a smoother version of the original signal without the distortions of short-term fluctuations and with minimal lag, adjustable by period.
The Modified Laguerre Lowpass Filter (MLLF) enhances the functionality of US by introducing a Laguerre mode parameter along side the lag parameter to refine control over the amount of additional smoothing/lag applied to the signal. By tethering US with this LERPed lag mechanism, MLLF achieves an effective balance between responsiveness and smoothness, allowing for customizable lag adjustments via multiple inputs. This filter ends with selecting from a choice of weighted averages derived from a gang of up to four cascading LERP calculations, resulting with smoother representations of the data.
The Laguerre Oscillator is a momentum-like indicator derived from the output of US and a singular LERPed lowpass filter. It calculates the difference between the US data and Laguerre filter data, normalizing it by the root mean square (RMS). This quasi-normalization technique helps to assess the intensity of the momentum on any timeframe within an expected bound range centered around 0.0. When the Laguerre Oscillator is positive, it suggests that the smoothed data is trending upward, while a negative value indicates a downward trend. Adjustability is controlled with period, lag, Laguerre mode, and RMS period.
指標和策略
Price action + MA + MTF RSI + S/R Zones by GunjanPanditDescription:
This script combines multiple powerful trading tools into a unified indicator designed for trend-following and confirmation-based entries. It is built to assist traders in identifying actionable signals based on price structure, volatility, and momentum across multiple timeframes.
🔧 How It Works
✅ UT Bot Core Logic
The script uses a variation of the UT Bot (Ultimate Trend Bot) method to generate buy/sell signals.
Signals are based on ATR-filtered trailing stop levels to reduce noise and detect real trend changes.
A Buy is triggered when the price closes above the UT trailing stop.
A Sell is triggered when the price closes below it.
✅ Multi-Timeframe RSI Confirmation
RSI is calculated on a user-defined higher timeframe (default: 1 hour).
A buy signal is confirmed only if RSI is below the oversold level, and vice versa for sell signals.
This confirmation layer adds an extra filter to improve signal reliability and reduce whipsaws.
✅ Support & Resistance Zones (MTF)
The script automatically plots dynamic support and resistance zones using highs/lows from the selected higher timeframe.
These zones are visualized as shaded bands, helping users recognize key levels where price may reverse or consolidate.
✅ Visual Aids & Alerts
Buy and Sell signals are clearly labeled on the chart.
Optional RSI plot in a separate pane for visual monitoring.
Real-time alert conditions included for both Buy and Sell entries.
📈 Use Case & Recommendations
This script is best suited for:
Swing trading or intraday strategies in trending markets.
Traders who want confirmation across timeframes to filter noise.
Spotting key entry zones aligned with momentum and volatility.
Recommended to use in combination with:
Volume or trend structure analysis.
Stop-loss and take-profit risk management based on ATR or S/R zones.
inal Thoughts
This indicator is ideal for traders who value:
Multi-timeframe analysis
Visual clarity
Signal confirmation
And clean, customizable overlays for actionable trading insights.
Pre-Market High and LowThis indicator automatically tracks and plots the daily pre-market high and low levels on your chart for U.S. stocks. It monitors the pre-market session from 4:30 AM to 9:30 AM Eastern Time (New York) and captures the highest and lowest prices during this period.
At exactly 9:30 AM ET, when the regular market opens, the indicator draws dashed horizontal lines representing the pre-market high and pre-market low, extending them forward for better visibility throughout the trading day.
MVRV Altcoins📌 Technical Description of Indicator: MVRV Altcoins
This advanced script calculates the Market Value to Realized Value (MVRV) ratio across multiple cryptocurrencies simultaneously. It offers two analytical modes: Normal and Z-Score, optimized for visual comparison and real-time monitoring of up to 13 predefined assets. If a user applies the indicator to a symbol that is not among the 13 programmed assets, the default behavior displays the Bitcoin chart as a fallback reference.
🔍 What Is MVRV and Why Is It Important?
MVRV is an on-chain metric designed to assess whether a cryptocurrency is overvalued or undervalued by comparing its market capitalization to its realized capitalization.
- Market Cap: The total circulating supply multiplied by the current market price.
- Realized Cap: The sum value of all coins based on the price at the time they last moved on-chain, offering a time-weighted valuation.
Normal Calculation:
MVRV_Normal = Market Cap / Realized Cap
This version reflects investor profitability and identifies potential accumulation or distribution zones.
📊 Z-Score Calculation:
MVRV_ZScore = (Market Cap − Realized Cap) / Standard Deviation of Market Cap
This formula evaluates how extreme the current market conditions are compared to historical norms. It normalizes the difference using statistical dispersion, turning it into a volatility-aware metric that better reflects valuation extremes.
🔎 How Market Cap Is Computed
Unlike conventional indicators relying on consolidated feeds, this script uses modular components from CoinMetrics to construct the active capitalization more accurately, especially for altcoins. Here's the breakdown:
Active Capitalization = MARKETCAPFF + MARKETCAPACTSPLY
Realized Capitalization = MARKETCAPREAL
Component Definitions:
- MARKETCAPFF: Market Cap Free Float — total valuation based only on truly circulating coins.
- MARKETCAPACTSPLY: Capitalization from actively circulating supply — filters dormant or locked coins.
- MARKETCAPREAL: Realized Cap — historical valuation weighted by the last on-chain movement of each coin.
This method offers enhanced precision and compatibility across assets that may lack comprehensive data from centralized providers.
⚙️ User-Configurable Parameters
- MVRV Mode: Choose between Normal and Z-Score.
- Percentage Scale View: If enabled, visual output is scaled using predefined divisors (100 / 3.5 or 100 / 6).
- Thresholds for Analysis:
- Normal mode: Define overbought and oversold levels (default 1.0 and 3.5).
- Z-Score mode: Configure statistical boundaries (default 0.0 and 6.0).
- Table Controls:
- Adjustable position on screen (9 options).
- Font size customization: tiny, small, normal, large.
- Color scheme personalization:
- Header: text and background
- Body: text and background
- Central column separator color
📊 Multicrypto Table Architecture
The indicator renders a high-performance visual table displaying data from up to 13 assets simultaneously. Each asset is represented as a vertical column featuring eigth historical data points plus the most recent value.
- Assets are displayed in two blocks separated by a decorative column.
- Each value is rounded to one decimal place for clarity.
- Cells are styled dynamically based on user settings.
🎨 Decorative Column Separator
Since the entire table is built as a unified structure, a color-configurable empty column is inserted mid-table to act as a visual divider. This approach improves readability and aesthetic balance without duplicating code or splitting table logic.
🔁 Default Behavior on Unsupported Assets
If the active chart is not one of the 13 predefined assets, the indicator will automatically display Bitcoin’s data. This ensures the chart remains functional and informative even outside the target asset group.
🎯 Color Interpretation by Condition
The MVRV value for each asset is highlighted using a traffic light system:
- Green: Undervalued (below oversold threshold)
- Red: Overvalued (above overbought threshold)
- Yellow: Neutral zone
This coding simplifies decision-making and visual scanning across assets.
Final Notes
This indicator is modular and fully adaptable, with well-commented sections designed for efficient customization. Its multiactive architecture makes it a valuable tool for crypto analysts tracking diversified portfolios beyond Bitcoin and Ethereum.
It supports visual storytelling across assets, comparative historical evaluation, and identification of strategic zones — whether for accumulation, distribution, or monitoring on-chain sentiment.
📊 TickerTrendz - TradeScopeWhat This Indicator Does — In Plain English
This indicator helps you understand how much the market might move today and tomorrow, so you can trade smarter.
Here’s how it works:
Today’s Expected Range (Intraday ATR Projection):
It measures how much the market typically moves in a day (called ATR).
Starting from when the overnight Globex session opens at 5 PM CST, it draws lines showing 20%, 60%, and 100% of that typical daily movement above and below today’s session open price.
It also tells you, in real time, how far price has moved relative to that typical range, shown as a percentage. For example, “You’re 60% through today’s expected move.”
This helps you see if the market is calm, just starting to move, or already reaching typical daily highs or lows.
Tomorrow’s Volatility Forecast:
Using yesterday’s price moves, yesterday’s daily volatility, and average market volatility, it predicts how volatile the market might be tomorrow.
It colors the forecast to show if tomorrow is likely to be a normal day (green), a high volatility day (orange), or an extreme volatility day (red).
This gives you a heads-up if you should expect big moves or more calm trading the next day.
All Info in One Place:
Instead of cluttering your chart with many labels, all this info is neatly shown in a box on the top-right corner of your chart.
You get a quick snapshot of both today’s progress and tomorrow’s volatility forecast without distraction.
Why It Helps You
Manage your trades better: Knowing how much the market tends to move helps you place smarter stops and targets.
Prepare for volatility spikes: You’ll get a warning before big moves so you can adjust your trading style or risk.
Stay aware intraday: See if the market is already “done moving” for the day or if there’s still room for big swings.
MACD 衰减信号For Max's MACD Decay Signal
A non-repainting signal based on MACD histogram momentum decay combined with price structure divergence. This script helps traders identify potential trend reversal points using multi-wave analysis.
📈 Bullish Signal
Triggered when:
MACD histogram prints three weakening red waves (histogram bars are rising toward zero)
Price makes lower lows, while MACD histogram rises (bullish divergence)
Histogram just turns green
🟢 Label: "MACD多头" appears below the candle
📢 Alert: "MACD 多头信号"
📉 Bearish Signal
Triggered when:
MACD histogram prints three weakening green waves (histogram bars falling toward zero)
Price makes higher highs, while MACD histogram falls (bearish divergence)
Histogram just turns red
🔴 Label: "MACD空头" appears above the candle
📢 Alert: "MACD 空头信号"
⚙️ Features
Adjustable MACD parameters: Fast, Slow, Signal lengths
Uses arrays to track momentum and price shift patterns
Built to avoid repainting, works on all timeframes
Comes with alert conditions for automation or manual notifications
✅ Best For
Catching early trend reversal opportunities
Combining with price action or support/resistance levels
Traders who value momentum + structure-based signals
Confirmed Entry Grid Pro//@version=5
indicator("Confirmed Entry Grid Pro", overlay=true,
max_lines_count=500, max_labels_count=500,
title="Confirmed Entry Grid Pro")
// === إعدادات المستخدم ===
showImpulse = input.bool(true, "Show Impulse Wave")
showShrinkWarning = input.bool(true, "Shrink Warning")
minConfirmations = input.int(5, "Minimum Confirmations", minval=3, maxval=10)
// === المتوسطات ===
ma9 = ta.sma(close, 9)
ma21 = ta.sma(close, 21)
ma200 = ta.sma(close, 200)
// === الاتجاه ===
trendBull = close > ma200
trendBear = close < ma200
// === الزخم ===
rsi = ta.rsi(close, 14)
rsiBull = rsi > 50
rsiBear = rsi < 50
// === الحجم ===
volMA = ta.sma(volume, 20)
volHigh = volume > volMA
// === شموع ابتلاعية ===
bullEngulf = close > open and open < close and close > open
bearEngulf = close < open and open > close and close < open
// === بولنجر باند ===
basis = ta.sma(close, 20)
dev = ta.stdev(close, 20)
upper = basis + 2 * dev
lower = basis - 2 * dev
bbBreakUp = close > upper
bbBreakDown = close < lower
// === دعم / مقاومة ديناميكية ===
support = ta.lowest(low, 20)
resistance = ta.highest(high, 20)
nearSupport = math.abs(close - support) / close < 0.015
nearResistance = math.abs(close - resistance) / close < 0.015
// === تقاطع المتوسطات ===
crossUp = ta.crossover(ma9, ma21)
crossDown = ta.crossunder(ma9, ma21)
// === ATR ===
atr = ta.atr(14)
atrActive = atr > ta.sma(atr, 14)
// === SMC: BOS + CHOCH + Impulsive Wave ===
bosUp = high > high and low > low
bosDown = low < low and high < high
chochUp = close > high and close < high
chochDown = close < low and close > low
smcBuy = bosUp and chochUp
smcSell = bosDown and chochDown
// === الموجة الدافعة (مؤشر اختياري لإشارة دخول قوية)
impulseWaveSell = close <= close and close <= close and close <= close and close < open
impulseWave = close >= close and close >= close and close >= close and close > open
// === مناطق السيولة ===
liqHigh = ta.highest(high, 30)
liqLow = ta.lowest(low, 30)
liquidityBuyZone = close < liqLow
liquiditySellZone = close > liqHigh
// === حساب النقاط لكل صفقة ===
buyScore = (trendBull ? 1 : 0) + (rsiBull ? 1 : 0) + (volHigh ? 1 : 0) + (bullEngulf ? 1 : 0) + (smcBuy ? 1 : 0) + (bbBreakUp ? 1 : 0) + (nearSupport ? 1 : 0) + (crossUp ? 1 : 0) + (atrActive ? 1 : 0) + (liquidityBuyZone ? 1 : 0)
sellScore = (trendBear ? 1 : 0) + (rsiBear ? 1 : 0) + (volHigh ? 1 : 0) + (bearEngulf ? 1 : 0) + (smcSell ? 1 : 0) + (bbBreakDown ? 1 : 0) + (nearResistance ? 1 : 0) + (crossDown ? 1 : 0) + (atrActive ? 1 : 0) + (liquiditySellZone ? 1 : 0)
// === شروط الإشارات مع منع التكرار خلال آخر 5 شموع ===
var int lastBuyBar = na
var int lastSellBar = na
canBuy = buyScore >= 5 and impulseWave and (na(lastBuyBar) or bar_index - lastBuyBar > 3)
canSell = sellScore >= 5 and impulseWaveSell and (na(lastSellBar) or bar_index - lastSellBar > 3)
if canBuy
lastBuyBar := bar_index
if canSell
lastSellBar := bar_index
showBuy = canBuy and buyScore >= minConfirmations
showSell = canSell and sellScore >= minConfirmations
// === طول الخطوط ===
var int lineLen = 5
// === رسم الإشارات ===
plotshape(showBuy, title="BUY", location=location.belowbar, style=shape.triangleup, size=size.small, color=color.green)
plotshape(showImpulse and impulseWave, title="Impulsive Buy", location=location.belowbar, style=shape.labelup, size=size.tiny, color=color.lime, text="IB")
plotshape(showSell, title="SELL", location=location.abovebar, style=shape.triangledown, size=size.small, color=color.red)
plotshape(showImpulse and impulseWaveSell, title="Impulsive Sell", location=location.abovebar, style=shape.labeldown, size=size.tiny, color=color.maroon, text="IS")
// === خطوط الصفقة ===
var line buyLines = array.new_line(0)
var line sellLines = array.new_line(0)
if (showBuy)
entry = close
label.new(bar_index, entry, "Entry " + str.tostring(entry, format.mintick), style=label.style_label_left, textcolor=color.white, size=size.normal)
tpLevels = array.from(0.618, 1.0, 1.272, 1.618, 2.0)
for i = 0 to array.size(tpLevels) - 1
fib = array.get(tpLevels, i)
tp = entry + fib * atr
fibLabel = "TP" + str.tostring(i + 1) + " - Fib " + str.tostring(fib)
line = line.new(bar_index, tp, bar_index + lineLen, tp, color=color.green)
label.new(bar_index + lineLen, tp, fibLabel + " " + str.tostring(tp, format.mintick), style=label.style_label_right, textcolor=color.lime, size=size.normal)
array.push(buyLines, line)
sl = entry - 0.618 * atr
slLine = line.new(bar_index, sl, bar_index + lineLen, sl, color=color.red)
label.new(bar_index + lineLen, sl, "SL " + str.tostring(sl, format.mintick), style=label.style_label_right, textcolor=color.red, size=size.normal)
array.push(buyLines, slLine)
if (showSell)
entry = close
label.new(bar_index, entry, "Entry " + str.tostring(entry, format.mintick), style=label.style_label_left, textcolor=color.white, size=size.normal)
tpLevels = array.from(-0.618, -1.0, -1.272, -1.618, -2.0)
for i = 0 to array.size(tpLevels) - 1
fib = array.get(tpLevels, i)
tp = entry + fib * atr
fibLabel = "TP" + str.tostring(i + 1) + " - Fib " + str.tostring(math.abs(fib))
line = line.new(bar_index, tp, bar_index + lineLen, tp, color=color.green)
label.new(bar_index + lineLen, tp, fibLabel + " " + str.tostring(tp, format.mintick), style=label.style_label_right, textcolor=color.green, size=size.normal)
array.push(sellLines, line)
sl = entry + 0.618 * atr
slLine = line.new(bar_index, sl, bar_index + lineLen, sl, color=color.red)
label.new(bar_index + lineLen, sl, "SL " + str.tostring(sl, format.mintick), style=label.style_label_right, textcolor=color.red, size=size.normal)
array.push(sellLines, slLine)
400 EMA 1min and 5min Collision Alert//@version=5
indicator("400 EMA 1min and 5min Collision Alert", overlay=true)
// === Inputs ===
len = input.int(400, title="EMA Length")
threshold = input.float(0.1, title="Collision Threshold", tooltip="Max difference between EMAs to trigger alert")
// === EMAs ===
// 400 EMA on 1-minute timeframe
ema_1min = request.security(syminfo.tickerid, "1", ta.ema(close, len))
// 400 EMA on 5-minute timeframe
ema_5min = request.security(syminfo.tickerid, "5", ta.ema(close, len))
// === Plot EMAs ===
plot(ema_1min, title="400 EMA (1min)", color=color.orange, linewidth=2)
plot(ema_5min, title="400 EMA (5min)", color=color.blue, linewidth=2)
// === Collision Detection ===
collide = math.abs(ema_1min - ema_5min) <= threshold
plotshape(collide, title="Collision!", location=location.abovebar, color=color.red, style=shape.triangleup, size=size.small)
// === Alerts ===
alertcondition(collide, title="EMAs Collide", message="400 EMA (1min) and 400 EMA (5min) have collided.")
Days Since ±1% Move on CloseInterpretation & Use‑Case
The “Days Since ±1% Move” indicator simply tells you how many trading days have passed since the last daily close that moved at least 1% in either direction. Here’s how to put it to work:
Complacency Gauge
A long stretch without a ≥1% move often signals that realized volatility has collapsed and market participants may be under‑positioned for a sudden swing.
Positioning Insight
When institutional hedges and systematic strategies see low recent volatility, they tend to scale back protection (fewer options hedges, tighter risk limits), which can amplify the impact of any eventual volatility pickup.
Mean‑Reversion Signal
After an extended streak (e.g. 20–30 days), a fresh ≥1% move is more likely—and often more violent—because pent‑up positioning flows rush to adjust.
Trend Confirmation
Conversely, a reset in the count (i.e., a new ≥1% move) that coincides with strong volume and follow‑through suggests genuine directional conviction rather than just a volatility “blip.”
MR.Z Strategy Reversal Signal Nadaraya SMA)Nadaraya-Watson Envelope (NW Envelope):
A smoothed, non-linear dynamic envelope that adapts to price structure. It visually identifies price extremes using kernel regression. The upper and lower bands move with the chart and provide reliable dynamic support and resistance.
EMA Levels:
Includes three key exponential moving averages:
EMA 50 (short-term trend)
EMA 100 (medium-term)
EMA 200 (long-term, institutional level)
Fully Scrollable and Responsive:
All lines and envelopes are plotted using plot() so they move with the chart and respond to zoom and pan actions naturally.
🧠 Ideal Use:
Identify reversal zones, dynamic support/resistance, and trend momentum exhaustion.
Combine WTB and NW Envelope for confluence-based entries.
Use EMA structure for trend confirmation or breakout anticipation.
Let me know if you'd like to add:
Divergence detection
Buy/Sell signals
Alerts or signal filtering options
I’ll be happy to extend the description or the script accordingly!
PRO Investing - Apex EnginePRO Investing - Apex Engine
1. Core Concept: Why Does This Indicator Exist?
Traditional momentum oscillators like RSI or Stochastic use a fixed "lookback period" (e.g., 14). This creates a fundamental problem: a 14-period setting that works well in a fast, trending market will generate constant false signals in a slow, choppy market, and vice-versa. The market's character is dynamic, but most tools are static.
The Apex Engine was built to solve this problem. Its primary innovation is a self-optimizing core that continuously adapts to changing market conditions. Instead of relying on one fixed setting, it actively tests three different momentum profiles (Fast, Mid, and Slow) in real-time and selects the one that is most synchronized with the current price action.
This is not just a random combination of indicators; it's a deliberate synthesis designed to create a more robust momentum tool. It combines:
Volatility analysis (ATR) to generate adaptive lookback periods.
Momentum measurement (ROC) to gauge the speed of price changes.
Statistical analysis (Correlation) to validate which momentum measurement is most effective right now.
Classic trend filters (Moving Average, ADX) to ensure signals are only taken in favorable market conditions.
The result is an oscillator that aims to be more responsive in volatile trends and more stable in quiet periods, providing a more intelligent and adaptive signal.
2. How It Works: The Engine's Three-Stage Process
To be transparent, it's important to understand the step-by-step logic the indicator follows on every bar. It's a process of Adapt -> Validate -> Signal.
Stage 1: Adapt (Dynamic Length Calculation)
The engine first measures market volatility using the Average True Range (ATR) relative to its own long-term average. This creates a volatility_factor. In high-volatility environments, this factor causes the base calculation lengths to shorten. In low-volatility, they lengthen. This produces three potential Rate of Change (ROC) lengths: dynamic_fast_len, dynamic_mid_len, and dynamic_slow_len.
Stage 2: Validate (Self-Optimizing Mode Selection)
This is the core of the engine. It calculates the ROC for all three dynamic lengths. To determine which is best, it uses the ta.correlation() function to measure how well each ROC's movement has correlated with the actual bar-to-bar price changes over the "Optimization Lookback" period. The ROC length with the highest correlation score is chosen as the most effective profile for the current moment. This "active" mode is reflected in the oscillator's color and the dashboard.
Stage 3: Signal (Normalized Velocity Oscillator)
The winning ROC series is then normalized into a consistent oscillator (the Velocity line) that ranges from -100 (extreme oversold) to +100 (extreme overbought). This ensures signals are comparable across any asset or timeframe. Signals are only generated when this Velocity line crosses its signal line and the trend filters (explained below) give a green light.
3. How to Use the Indicator: A Practical Guide
Reading the Visuals:
Velocity Line (Blue/Yellow/Pink): The main oscillator line. Its color indicates which mode is active (Fast, Mid, or Slow).
Signal Line (White): A moving average of the Velocity line. Crossovers generate potential signals.
Buy/Sell Triangles (▲ / ▼): These are your primary entry signals. They are intentionally strict and only appear when momentum, trend, and price action align.
Background Color (Green/Red/Gray): This is your trend context.
Green: Bullish trend confirmed (e.g., price above a rising 200 EMA and ADX > 20). Only Buy signals (▲) can appear.
Red: Bearish trend confirmed. Only Sell signals (▼) can appear.
Gray: No clear trend. The market is likely choppy or consolidating. No signals will appear; it is best to stay out.
Trading Strategy Example:
Wait for a colored background. A green or red background indicates the market is in a tradable trend.
Look for a signal. For a green background, wait for a lime Buy triangle (▲) to appear.
Confirm the trade. Before entering, confirm the signal aligns with your own analysis (e.g., support/resistance levels, chart patterns).
Manage the trade. Set a stop-loss according to your risk management rules. An exit can be considered on a fixed target, a trailing stop, or when an opposing signal appears.
4. Settings and Customization
This script is open-source, and its settings are transparent. You are encouraged to understand them.
Synaptic Engine Group:
Volatility Period: The master control for the adaptive engine. Higher values are slower and more stable.
Optimization Lookback: How many bars to use for the correlation check.
Switch Sensitivity: A buffer to prevent frantic switching between modes.
Advanced Configuration & Filters Group:
Price Source: The data source for momentum calculation (default close).
Trend Filter MA Type & Length: Define your long-term trend.
Filter by MA Slope: A key feature. If ON, allows for "buy the dip" entries below a rising MA. If OFF, it's stricter, requiring price to be above the MA.
ADX Length & Threshold: Filters out non-trending, choppy markets. Signals will not fire if the ADX is below this threshold.
5. Important Disclaimer
This indicator is a decision-support tool for discretionary traders, not an automated trading system or financial advice. Past performance is not indicative of future results. All trading involves substantial risk. You should always use proper risk management, including setting stop-losses, and never risk more than you are prepared to lose. The signals generated by this script should be used as one component of a broader trading plan.
signBTC Day&Session BoxesThis indicator visually segments the trading week on your chart, drawing each day from 17:00 to 17:00 New York time (corresponding to the typical forex daily rollover). For enhanced session structure, every day is further divided into three major trading sessions:
Asian Session
London Session
New York Session
Additionally, the indicator automatically marks the opening time of each new day at 17:00 (New York time) directly on the chart, helping traders quickly identify daily cycles and session transitions.
Customization Features
Adjustable Session Times: Users can modify the start and end times for each session (Asian, London, New York) to match personal or institutional trading hours.
Flexible Day Boundaries: The time marking the start and end of each day (default: 17:00 NY) can also be adjusted according to preference or asset specifics.
Opening Time Marker: The feature for drawing the daily opening time can be enabled or disabled in the settings.
This tool is ideal for traders needing clear visual cues for session boundaries and daily market resets, especially those operating across multiple time zones or managing strategies dependent on session-specific behavior. All settings are conveniently accessible and fully customizable within the indicator’s parameter panel.
QT Separator by BailaSimple and Clean QT indicator.
Helps to spot SSMT
Based on: Daye Quarterly Theory by toodegrees
These Quarters represent:
A - Accumulation (required for a cycle to occur)
M - Manipulation
D - Distribution
X - Reversal/Continuation
Vasyl Ivanov | Volatility by Extremums"Volatility by Extremums" is an original technical indicator designed to measure market volatility based on the analysis of price extreme points. Unlike traditional volatility indicators that use standard statistical methods, this indicator calculates volatility as a percentage price change between local maximums and minimums, providing a more accurate understanding of actual price fluctuations in the market.
Unique Methodology
The indicator uses an innovative approach to volatility calculation:
Extremum Detection: The algorithm automatically identifies local maximums and minimums based on configurable parameters, including lookback period and minimum distance between extremums, measured in ATR (Average True Range) units.
Relative Volatility Calculation: For each pair of adjacent extremums, volatility is calculated using the formula: (|Max - Min| / Max) × 100%, where volatility is expressed as a percentage of the maximum value in the pair.
Result Aggregation: The indicator computes two key metrics:
Average volatility - arithmetic mean of all calculated volatility values
Maximum volatility - highest volatility value between extremums during the analyzed period
Technical Parameters
Main Settings:
Lookback (1000): Number of bars for historical analysis
Extremums Bars Lookback (10): Period for extremum search
Extremums Minimal Distance (2 ATR): Minimum distance between extremums for noise filtering
ATR Period (30): Average True Range calculation period
ATR Average Period (20): ATR averaging period
Visualization:
Color-coded extremums: Bullish extremums marked in green, bearish in red
Information table: Displays current average and maximum volatility values in the top-right corner of the chart
Dynamic markers: Automatic placement of ▼ and ▲ symbols on corresponding extremums
Practical Applications
Market Condition Analysis
The indicator helps traders identify:
High volatility periods: When average volatility exceeds historical norms, indicating potential for large price movements
Consolidation phases: Low volatility values signal periods of energy accumulation before potential breakouts
Extreme movements: Maximum volatility shows the largest price swings, which may indicate important market events
Risk Management
Volatility data enables:
Position size adaptation based on current market volatility
Dynamic stop-loss setting corresponding to market activity levels
Optimal entry point selection during periods of reduced volatility
Trading Strategies
The indicator is effective for:
Breakout strategies: Low volatility often precedes strong directional movements
Counter-trend trading: Extremely high volatility values may signal potential reversals
Scalping: Understanding current volatility level helps choose appropriate instruments and timeframes
Advantages Over Traditional Indicators
Unlike standard volatility measures such as standard deviation or ATR, this indicator:
Focuses on actual extremums: Analyzes real price reversal points rather than abstract statistical indicators
Adapts to market conditions: Uses ATR to determine significant extremums, filtering market noise
Provides contextual information: Shows not only current volatility but also historical maximum, helping assess the relative significance of current movements
Usage Recommendations
Parameter Optimization:
For intraday trading: Reduce Lookback period to 200-500 bars
For position trading: Increase minimum distance between extremums to 3-4 ATR
For high-volatility assets: Set ATR period to shorter periods (14-21)
Combining with Other Indicators:
Best results are achieved when used together with:
Trend indicators to determine overall market direction
Oscillators for precise entry and exit timing
Volume indicators to confirm movement strength
Technical Limitations
Users should consider:
The indicator is based on historical data and does not guarantee future results
Requires sufficient historical data for correct operation (minimum 100 bars)
Most effective on liquid markets with clearly defined extremums
"Volatility by Extremums" represents an innovative approach to market volatility analysis, providing traders with a unique tool for understanding price dynamics and making informed trading decisions based on actual market extremums.
Liquidity Factor Spectrum [Modified by Markking77]Liquidity Spectrum Visualizer — Modified Version
This script “Liquidity Spectrum Visualizer ” is an open-source tool originally created by BigBeluga under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Modified & Refactored by: Markking77
This version has been factorized and slightly modified to ensure unique functionality and better performance while respecting the original license terms.
Key Features:
Liquidity levels with adaptive calculation.
Volume Profile histogram for easy demand/supply zones.
Smart Volume Bubbles for quick visual insight.
Clear color coding for uptrend/downtrend zones.
Factorized code for improved readability.
License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Original Author: BigBeluga
Modified & Published By: Markking77
This script is provided for educational purposes only and can be freely reused or modified under the same license, with proper credit to the original author and modifier.
Combined Entry Signal - SMI + MACD + EMA + Volume//@version=5
indicator("Combined Entry Signal - SMI + MACD + EMA + Volume", overlay=true)
// ==== INPUTS ====
smiK = input.int(5, "SMI K", minval=1)
smiD = input.int(3, "SMI D", minval=1)
macdFast = input.int(12, "MACD Fast")
macdSlow = input.int(26, "MACD Slow")
macdSignal = input.int(9, "MACD Signal")
emaShort = input.int(20, "EMA Short")
emaMid = input.int(50, "EMA Mid")
emaLong = input.int(100, "EMA Long")
volMult = input.float(1.2, "Volume Multiplier for Confirm")
// ==== SMI ====
smiSource = close
smi = ta.stoch(close, high, low, smiK)
smiSignal = ta.sma(smi, smiD)
// ==== MACD ====
= ta.macd(close, macdFast, macdSlow, macdSignal)
macdCrossUp = ta.crossover(macdLine, signalLine)
macdCrossDown = ta.crossunder(macdLine, signalLine)
// ==== EMA Trend ====
emaS = ta.ema(close, emaShort)
emaM = ta.ema(close, emaMid)
emaL = ta.ema(close, emaLong)
trendUp = close > emaS and emaS > emaM and emaM > emaL
trendDown = close < emaS and emaS < emaM and emaM < emaL
// ==== Volume confirmation ====
avgVol = ta.sma(volume, 20)
volConfirm = volume > avgVol * volMult
// ==== BUY/SELL CONDITIONS ====
smiBuy = smi > smiSignal and smi < 20
smiSell = smi < smiSignal and smi > 80
buySignal = smiBuy and macdCrossUp and trendUp and volConfirm
sellSignal = smiSell and macdCrossDown and trendDown and volConfirm
// ==== PLOTS ====
plotshape(buySignal, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(sellSignal, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
plot(emaS, title="EMA 20", color=color.orange)
plot(emaM, title="EMA 50", color=color.green)
plot(emaL, title="EMA 100", color=color.blue)
Highs and Lows🔍 Highs and Lows – Liquidity Zone Tracker
This script automatically detects and highlights key swing highs and lows on your chart using a pivot-based algorithm. These zones are dynamically plotted as visual rectangles that help identify unmitigated liquidity pools commonly used in Smart Money and institutional trading models.
Each level is marked as “fresh” when first plotted, meaning it hasn't been interacted with by price. When price touches a zone (via wick or full body), the script automatically de-emphasizes that zone to help you focus on actionable, untested levels.
📌 Key Features:
Pivot-Based Detection: Highs and lows are derived from confirmed swing points using a user-defined lookback period (default: 25 bars).
Freshness Logic:
Fresh zones are visually emphasized.
Touched zones fade automatically once price interacts, reducing chart clutter and drawing focus to relevant liquidity.
Customizable Visuals:
Individual styling for high and low zones (border color, fill color, style, width).
Adjustable max number of zones shown (default: 4 per side).
Touch & Break Detection:
Uses both wick interaction and full-body candle cross to determine freshness.
Real-Time Alerts:
Optional alerts for when price touches fresh high or low levels, ideal for breakout, mitigation, or reaction-based strategies.
📈 Practical Use Cases:
Identify untapped liquidity pools for entries/exits.
Visualize institutional interest areas in line with ICT/Smart Money models.
Use as entry confirmation zones in confluence with FVGs, BOS/CHOCH, and displacement tools.
Highlight stop-hunt or inducement zones before market expansion.
⚙️ How It Works:
High/low levels are detected using ta.pivothigh and ta.pivotlow.
Detected zones are boxed from the swing candle’s high/low to its close.
Price interaction logic:
Wick touch sets a box to "unfresh".
Full-body cross can reset a box as “fresh”.
Arrays are used to manage both box objects and their freshness states.
Max zone limits keep the chart clean and focused.
🛑 This script is closed-source to protect unique zone-tracking and visual management logic, but all key functionality and use cases are fully described above.
Gabriel's Dynamic Sentiment RSI📊 Dynamic Sentiment RSI with Velocity, Acceleration & Divergence Detection
Created by GabrielAmadeusLau
This advanced Pine Script indicator fuses multiple layers of market insight into a unified momentum and sentiment tool. It is designed to extract nuanced sentiment signals from price action using a hybridized RSI model enhanced with stochastic dynamics, volatility weighting, and divergence tracking. It adapts to a wide range of asset classes including equities, crypto, gold, and forex.
🔍 Core Components
✅ 1. Dynamic Sentiment RSI
A normalized, stochastic-based RSI that adjusts its sensitivity using the Sentiment Factor.
Smoothed using a Jurik Moving Average for precision noise filtering.
Weighted using volume, volatility (VIX-like), HL extremes, and trend-based adaptive weighting, giving it a powerful multi-dimensional response.
✅ 2. Hann-Window RSI Calculation
Leverages a Hann Window and Levy Flight transformation to amplify cyclical behavior in RSI inputs.
Applies power-based weighting to directional movement, ideal for assets with cyclic or fractal-like structure.
✅ 3. Velocity & Acceleration Engine
Measures the rate of RSI change over a customizable period, and then the rate of that rate (acceleration).
Both are plotted with adaptive coloring to visually represent momentum shifts.
This dynamic structure aids in anticipating breakout strength or exhaustion.
✅ 4. Sentiment Heat Background
Background shading reflects bullish (teal) or bearish (silver) sentiment using smoothed stochastic RSI outputs.
Creates an intuitive market "mood" indicator for quick-glance visual analysis.
🔁 Smoothing & Weighting Customizations
You can toggle between different weighting modes:
Volume Weighted: Uses volume or ATR if unavailable.
VIX Weighted: Incorporates a volatility-based weight via a WVF-like formula.
HL Weighted: High-Low range smoothed.
Linear Weighted: Applies linear regression to the signal.
Trend Adaptive: Squares rolling maximums/minimums for dynamic strength adaptation.
🔎 Divergence Detection System
Supports Regular & Hidden Divergence using any of the following pivots:
Raw RSI
Smoothed K% RSI
Sentiment RSI
Velocity
Acceleration
Allows divergence tracking on custom timeframes and Heikin Ashi data.
Custom line styles, colors, and optional “last signal only” visibility.
Alerts are provided for all four divergence types.
📌 Built-in Alerts
✅ Bullish/Bearish Regular Divergence
✅ Bullish/Bearish Hidden Divergence
✅ General Divergence Summary Alerts
⚙️ Highly Configurable Settings
Sentiment Factor scaling (default ~2.2)
Levy exponent (ideal between 0.4 to 3.2 depending on asset class)
Velocity & Acceleration scaling inputs
Pivot lookback controls
Toggle smoothing methods and weighting logic
🧠 Ideal Use Cases
Swing and Trend Trading: The dynamic structure identifies both trend continuations and reversals with precision.
Divergence Confirmation: Confirm entries or exits using regular/hidden divergence alongside acceleration/velocity overlays.
Adaptive Strategy Building: Integrate this tool as a sentiment engine for algorithmic trading strategies.
🔬 Recommended Settings by Asset Class
Asset Type Levy Sentiment Factor
Crypto 0.6–1.2 2.0–2.5
Gold 0.4–1.0 2.0–2.2
Stocks 0.9–1.2 2.2–2.5
Forex 2.5–3.2 1.8–2.3
*A sentiment Factor of 9.5 can tell the larger trend apart on Daily and up.*
🧩 Technical Notes
Uses Jurik MA (Power 2, Phase 50) for minimal lag smoothing.
Employs Chebyshev filters (pre-Stochastic) for advanced sentiment smoothing.
Weighted RSI is normalized from -100 to 100, with color-coded velocity and acceleration histograms.
The Visualized Trader (Fractal Timeframe)The **The Visualized Trader (Fractal Timeframe)** indicator for TradingView is a tool designed to help traders identify strong bullish or bearish trends by analyzing multiple technical indicators across two timeframes: the current chart timeframe and a user-selected higher timeframe. It visually displays trend alignment through arrows on the chart and a condition table in the top-right corner, making it easy to see when conditions align for potential trade opportunities.
### Key Features
1. **Multi-Indicator Analysis**: Combines five technical conditions to confirm trend direction:
- **Trend**: Based on the slope of the 50-period Simple Moving Average (SMA). Upward slope indicates bullish, downward indicates bearish.
- **Stochastic (Stoch)**: Uses Stochastic Oscillator (5, 3, 2) to measure momentum. Rising values suggest bullish momentum, falling values suggest bearish.
- **Momentum (Mom)**: Derived from the MACD fast line (5, 20, 30). Rising MACD line indicates bullish momentum, falling indicates bearish.
- **Dad**: Uses the MACD signal line. Rising signal line is bullish, falling is bearish.
- **Price Change (PC)**: Compares the current close to the previous close. Higher close is bullish, lower is bearish.
2. **Dual Timeframe Comparison**:
- Calculates the same five conditions on both the current timeframe and a user-selected higher timeframe (e.g., daily).
- Helps traders see if the trend on the higher timeframe aligns with the current chart, providing context for stronger trade decisions.
3. **Visual Signals**:
- **Arrows on Chart**:
- **Current Timeframe**: Blue upward arrows below bars for bullish alignment, red downward arrows above bars for bearish alignment.
- **Higher Timeframe**: Green upward triangles below bars for bullish alignment, orange downward triangles above bars for bearish alignment.
- Arrows appear only when all five conditions align (all bullish or all bearish), indicating strong trend potential.
4. **Condition Table**:
- Displays a table in the top-right corner with two rows:
- **Top Row**: Current timeframe conditions (Trend, Stoch, Mom, Dad, PC).
- **Bottom Row**: Higher timeframe conditions (labeled with "HTF").
- Each cell is color-coded: green for bullish, red for bearish.
- The table can be toggled on/off via input settings.
5. **User Input**:
- **Show Condition Boxes**: Toggle the table display (default: on).
- **Comparison Timeframe**: Choose the higher timeframe (e.g., "D" for daily, default setting).
### How It Works
- The indicator evaluates the five conditions on both timeframes.
- When all conditions are bullish (or bearish) on a given timeframe, it plots an arrow/triangle to signal a strong trend.
- The condition table provides a quick visual summary, allowing traders to compare the current and higher timeframe trends at a glance.
### Use Case
- **Purpose**: Helps traders confirm strong trend entries by ensuring multiple indicators align across two timeframes.
- **Example**: If you're trading on a 1-hour chart and see blue arrows with all green cells in the current timeframe row, plus green cells in the higher timeframe (e.g., daily) row, it suggests a strong bullish trend supported by both timeframes.
- **Benefit**: Reduces noise by focusing on aligned signals, helping traders avoid weak or conflicting setups.
### Settings
- Access the indicator settings in TradingView to:
- Enable/disable the condition table.
- Select a higher timeframe (e.g., 4H, D, W) for comparison.
### Notes
- Best used in trending markets; may produce fewer signals in choppy conditions.
- Combine with other analysis (e.g., support/resistance) for better decision-making.
- The higher timeframe signals (triangles) provide context, so prioritize trades where both timeframes align.
This indicator simplifies complex trend analysis into clear visual cues, making it ideal for traders seeking confirmation of strong momentum moves.
Elliott Wave Probability SystemAdvanced Elliott Wave analysis system with AI-powered probability calculations for price targets. Combines multiple technical indicators to generate high-probability trading signals with specific price objectives.
🎯 KEY FEATURES:
- Automatic Elliott Wave pattern detection
- Dynamic Fibonacci retracement & extension levels
- Probability-weighted price targets (up to 10 levels)
- Multi-indicator confluence scoring system
- Real-time probability calculations
- Visual wave projections with success rates
- Comprehensive status dashboard
📊 TECHNICAL INDICATORS INTEGRATED:
- Elliott Wave pattern recognition
- Fibonacci levels (0-261.8%)
- RSI momentum analysis
- MACD trend confirmation
- Stochastic oscillator
- Volume spike detection
- Weighted scoring algorithm
💡 PROBABILITY ENGINE:
- Calculates target probabilities based on:
- Current wave position
- Technical indicator alignment
- Volume confirmation
- Market structure
- Updates in real-time
- Adjusts for market conditions
🎨 VISUAL ELEMENTS:
- Wave connection lines
- Fibonacci grid with prices
- Probability table with 5-10 targets
- Color-coded signal strength
- Status dashboard
- Target projection lines
🔧 CUSTOMIZATION:
- Adjustable wave detection period
- Number of price targets (3-10)
- Toggle visual elements
- Custom color schemes
- Flexible indicator parameters
📈 TRADING METHODOLOGY:
- Entry: High probability targets + confluence
- Exit: Target completion or signal reversal
- Risk: Use Fibonacci levels for stops
- Position sizing: Based on probability %
Perfect for traders seeking objective, probability-based price targets using Elliott Wave theory combined with technical confirmation.
⚡ ALERTS INCLUDED:
- Strong buy/sell signals
- Target approach notifications
- Wave completion alerts
Correlating AI Agent coded by ITECS .
