RSI + Fibonacci HH LL Support Resistance I have integrated my past scripts and brushed them up further.
This tool allows for support/resistance, stop loss, take profit, and trend analysis using RSI and Fibonacci ratios.
For example, the Fibonacci ratio is used as follows
l1 = m - dist * 0.618
l2 = m - dist * 1.618
l3 = m - dist * 2.618
l4 = m - dist * 4.235
l5 = m - dist * 6.857
l6 = m - dist * 11.089
When the Fibonacci ratio reaches 2.618 or higher and the RSI smoothed by the 5-day EMA is oversold/overbought, the bar color is changed by a gradation.
We have tried to make the design as beautiful and good-looking as possible. You can also hide the lines to suit your own preference.
Example usages are here:
BTCUSDT 1Hour Chart
Using Fibonacci numbers
BTCUSDT 15min Chart, for Scalping
Here, to set the highest and lowest prices one hour ago, "4" is substituted as the calculation: 15 minutes x 4 = 60
BTCUSDT 15min Chart, for Scalping
To set the highest and lowest prices 4 hours ago , "4" is substituted as the calculation: 15 minutes x 16 = 240
BTCUSDT 15min Chart, for Scalping
To draw yesterday's high and low as support/resistance lines, I substituted the number "96" as 1440/15=96.
BTCUSDT 1min Chart, for Scalping
Substituted "60" to trail the highest and lowest prices over a 60-minute period on a 1-minute chart, and removed lines to beautify
BTCUSDT 1day Chart, for Long-Term Investers
This is an example of using "90" because it is a 1-day chart and assumes that 3 months = 90 days in order to trail the highest and lowest prices over a 3-month period and no lines.
My past scripts are here:
RSI + FIB HH LL StopLoss Finder／Contrarian Trades
Fibonacci HH LL TRAMA Band
In den Scripts nach "scalping" suchen
ROC_PA_Strategy (A3Sh)Hi there,
An experiment with rate of price change in combination with price averaging. The strategy is inspired by Price Change Scalping Strategy developed by Prosum Solutions and Scalping Dips On Trend Strategy developed by Coinrule. Both strategies look at the percentage of price change to open orders.
When the price drops beyond a specified percentage, a order entry threshold (yellow line) is setup. The order entry threshold is only active for a specified number of bars and will de-activate when not crossed within the specified number of bars. When the price drops further and crosses the entry threshold with a minimum of a specified percentage, a long position is entered. The same reverse logic (white line) used to close the long position.
I first ran the strategy without stop loss and take profit and that worked very well in a bullish market. I later added stop loss and take profit and that seems to work better in a side ways or bearisch market. There are a lot of tweaking possibilities in the settings.
In the settings you can specify the percentage of portfolio to use for each trade to spread the risk and for each order a trading fee of 0.075% is calculated.
EMA SCALPEUR SHORTI'm trying to find the best EMA's for scalpingm you are able to choose 2 differents EMAs for your enter and 2 differents EMAs for you exit.
It's putting entry and exit on the graph
Capns Bollinger Bands MTF This Simple Script display higher time frame Bollinger Band on current resolution . Etc : On 1 Minutes chart BB Band is 5 Minutes Band. I use this code on my pc for scalping...Hope You like the idea
Goldilocks Regime FilterGoldilocks Regime Filter is a lightweight market condition confirmation indicator engineered specifically for 1-minute Gold scalping.
Rather than generating trade signals, this tool focuses on identifying the current market regime—helping traders quickly determine whether price action is behaving in a directional (trending) or rotational (ranging) manner. This allows traders to align their existing entry strategies with appropriate market conditions and avoid applying momentum tactics in unfavorable environments.
The indicator synthesizes multiple aspects of market behavior—trend strength, volatility behavior, and price efficiency—into a simple, intuitive top-right table with a clear regime label and confidence reading. This makes it easy to assess market state at a glance without adding clutter to the chart.
Key Features
Designed specifically for 1-minute Gold charts
Clear Trending / Ranging / Neutral regime classification
Confidence score to gauge strength of the current condition
Non-repainting, confirmation-only logic
Minimalist table display that stays out of the way
Works alongside any strategy or discretionary approach
Intended Use
This indicator is designed to be used as a confirmation filter, not a standalone trading system. It is best applied to:
Confirm momentum-based setups during directional conditions
Avoid overtrading during low-efficiency, rotational markets
Improve discipline and context during fast intraday sessions
Goldilocks Regime Filter does not provide buy or sell signals and should be used in conjunction with proper risk management and a defined trading plan.
BALANCED Strategy: Intraday Pro + Smart DashboardWelcome to the BALANCED Strategy: Intraday Pro.
This all-in-one indicator is designed for Intraday traders looking to capture trend movements while effectively filtering out sideways market noise. It combines the power of Supertrend for direction, EMA 100 for the baseline trend, and rigorous validation via RSI and ADX.
The script also integrates a complete Risk Management system with targets based on the Golden Ratio (Fibonacci) and a real-time Dashboard.
⏳ Recommended Timeframes
This algorithm is optimized for Intraday volatility:
M5 (5 Minutes) ⭐️: Ideal for quick Scalping. The ADX filter is crucial here to avoid false signals.
M15 (15 Minutes) 🏆: The "Sweet Spot." It offers the best balance between signal frequency and trend reliability.
M30 / H1: For a "Swing Intraday" approach—calmer, fewer signals, but higher precision.
Not recommended for M1 (1 Minute) with default settings (too much noise).
🚀 How It Works
The algorithm follows a strict 3-step logic to generate high-quality signals:
1. Trend Identification (The Engine)
Supertrend: Determines the immediate direction.
EMA 100: Acts as a background trend filter. We only buy above and sell below the EMA.
2. Noise Filtering (Safety)
ADX (Average Directional Index): The signal is only validated if there is sufficient volatility (Configurable threshold, default 12) to avoid "chop markets" (flat markets).
RSI (Relative Strength Index): Strict momentum filter. Buy only if RSI > 50, Sell if RSI < 50.
3. Entry Confirmation (The Trigger)
The script doesn't just rely on a crossover. It waits for "Price Action" confirmation: the candle must close higher than the previous one (for Long) or lower (for Short) to validate the entry.
🛡️ Risk Management (Money Management)
This is the core strength of this tool. Upon signal validation, the script automatically calculates and plots:
Stop Loss (SL): Based on volatility (ATR). It places the stop at the recent Low/High with a safety padding.
Take Profit (TP): Two modes available:
Fibonacci Mode (Default): Targets the 1.618 extension (Golden Ratio) of the risk taken.
Fixed Ratio Mode: Targets a manual Risk/Reward ratio (e.g., 2.0).
📊 The Dashboard
Located at the bottom right, the smart dashboard provides vital info at a glance:
Signal Time: To check if the alert is fresh.
Type (LONG/SHORT): Color-coded (Green/Pink).
Tech Data: RSI and ADX values at the moment of the signal.
Exact Prices: Entry Level, Target (TP), and Stop Loss (SL).
⚙️ Configurable Settings
Sensitivity: Adjust the Supertrend factor (Default 2.0).
Filters: Toggle the RSI filter ON/OFF or adjust the ADX threshold.
Execution: Choose between Fibonacci Target (1.618) or a Manual Ratio.
⚠️ Disclaimer: This tool is a technical decision aid and does not constitute financial investment advice. Always use prudent risk management and backtest the indicator on your preferred assets before live use.
Hyper Insight MA Strategy [Universal]Hyper Insight MA Strategy ** is a comprehensive trend-following engine designed for traders who require precision and flexibility. Unlike standard indicators that lock you into a single calculation method, this strategy serves as a "Universal Adapter," allowing you to **Mix & Match 13 different Moving Average types** for both the Fast and Slow trend lines independently.
Whether you need the smoothness of T3, the responsiveness of HMA, or the classic reliability of SMA, this script enables you to backtest thousands of combinations to find the perfect edge for your specific asset class.
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🔬 Deep Dive: Calculation Logic of Included MAs
This strategy includes 13 distinct calculation methods. Understanding the math behind them will help you choose the right tool for your specific market conditions.
#### 1. Standard Averages
* **SMA (Simple Moving Average):** The unweighted mean of the previous $n$ data points.
* *Logic:* Treats every price point in the period with equal importance. Good for identifying long-term macro trends but reacts slowly to recent volatility.
* **WMA (Weighted Moving Average):** A linear weighted average.
* *Logic:* Assigns heavier weight to current data linearly (e.g., $1, 2, 3... n$). It reacts faster than SMA but is still relatively smooth.
* **SWMA (Symmetrically Weighted Moving Average):**
* *Logic:* Uses a fixed-length window (usually 4 bars) with symmetrical weights $ $. It prioritizes the center of the recent data window.
#### 2. Exponential & Lag-Reducing Averages
* **EMA (Exponential Moving Average):**
* *Logic:* Applies an exponential decay weighting factor. Recent prices have significantly more impact on the average than older prices, reducing lag compared to SMA.
* **RMA (Running Moving Average):** Also known as Wilder's Smoothing (used in RSI).
* *Logic:* It is essentially an EMA but with a slower alpha weight of $1/length$. It provides a very smooth, stable line that filters out noise effectively.
* **DEMA (Double Exponential Moving Average):**
* *Logic:* Calculated as $2 \times EMA - EMA(EMA)$. By subtracting the "lag" (the smoothed EMA) from the original EMA, DEMA provides a much faster reaction to price changes with less noise than a standard EMA.
* **TEMA (Triple Exponential Moving Average):**
* *Logic:* Calculated as $3 \times EMA - 3 \times EMA(EMA) + EMA(EMA(EMA))$. This effectively eliminates the lag inherent in single and double EMAs, making it an extremely fast-tracking indicator for scalping.
#### 3. Advanced & Adaptive Averages
* **HMA (Hull Moving Average):**
* *Logic:* A composite formula involving Weighted Moving Averages: ASX:WMA (2 \times Integer(n/2)) - WMA(n)$. The result is then smoothed by a $\sqrt{n}$ WMA.
* *Effect:* It eliminates lag almost entirely while managing to improve curve smoothness, solving the traditional trade-off between speed and noise.
* **ZLEMA (Zero Lag Exponential Moving Average):**
* *Logic:* This calculation attempts to remove lag by modifying the data source before smoothing. It calculates a "lag" value $(length-1)/2$ and applies an EMA to the data: $Source + (Source - Source )$. This creates a projection effect that tracks price tightly.
* **T3 (Tillson T3 Moving Average):**
* *Logic:* A complex smoothing technique that runs an EMA through a filter multiple times using a "Volume Factor" (set to 0.7 in this script).
* *Effect:* It produces a curve that is incredibly smooth and free of "overshoot," making it excellent for filtering out market chop.
* **ALMA (Arnaud Legoux Moving Average):**
* *Logic:* Uses a Gaussian distribution (bell curve) to assign weights. It allows the user to offset the moving average (moving the peak of the weight) to align it perfectly with the price, balancing smoothness and responsiveness.
* **LSMA (Least Squares Moving Average):**
* *Logic:* Calculates the endpoint of a Linear Regression line for the lookback period. It essentially guesses where the price "should" be based on the best-fit line of the recent trend.
* **VWMA (Volume Weighted Moving Average):**
* *Logic:* Weights the closing price by the volume of that bar.
* *Effect:* Prices on high volume days pull the MA harder than prices on low volume days. This is excellent for validating true trend strength (i.e., a breakout on high volume will move the VWMA significantly).
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### 🛠 Features & Settings
* **Universal Switching:** Change the `Fast MA` and `Slow MA` types instantly via the settings menu.
* **Trend Cloud:** A dynamic background fill (Green/Red) highlights the crossover zone for immediate visual trend identification.
* **Strategy Mode:** Built-in Backtesting logic triggers `LONG` entries when Fast MA crosses over Slow MA, and `EXIT` when Fast MA crosses under.
### ⚠️ Disclaimer
This script is intended for educational and research purposes. The wide variety of MA combinations can produce vastly different results. Past performance is not indicative of future results. Please use proper risk management.
Bayesian Liquidity Pain & Gain [Instit. Vol Weighted]Bayesian Liquidity Pain & Gain Indicator
Stop guessing where support and resistance are.
The Bayesian Liquidity Pain & Gain indicator moves beyond arbitrary lines and raw price action. It quantifies Institutional Intent by calculating the exact price levels where large volume has been accumulated and visualizes the "Pain" (stress) those participants feel when the market moves against them.
The Logic: Quantified Institutional Stress
Institutions don't trade single candles; they accumulate positions over time. This indicator tracks their Volume-Weighted Average Cost Basis to answer two critical questions:
Where did they enter? (The Cost Basis Lines)
Are they underwater? (The Pain Clouds)
By normalizing price distance using volatility (ATR) and statistical deviation (Z-Score), we filter out noise and only highlight zones where "Smart Money" is statistically forced to defend their positions or capitulate.
How to Read the Chart
1. The Cost Basis Lines (Anchors)
• 🟢 Green Line (Buyer Cost Basis): The average price where institutions accumulated long positions. This acts as dynamic Support.
• 🔴 Red Line (Seller Cost Basis): The average price where institutions accumulated short positions. This acts as dynamic Resistance.
2. The Pain Clouds (Signals)
When price moves significantly away from the cost basis (Z-Score > 2.0), "Clouds" appear to visualize the PnL status of the participants:
• 🔴 Red Cloud (Buyer Pain): Price is below the buyer's entry. Buyers are losing money (in the red). This creates a "Discount" zone where they may defend support.
• 🟢 Green Cloud (Seller Pain): Price is above the seller's entry. Sellers are losing money (shorts are squeezed). This indicates strong bullish momentum.
3. The Multi-Timeframe Dashboard
A real-time HUD showing the Z-Score status across 4 timeframes (1m, 5m, 15m, 1h):
• 🟢 Green: Profitable/Neutral (Trend Continuation)
• 🟠 Orange: Warning (Pressure Building)
• 🔴 Red: Critical Pain (High Probability Reversal)
Trading Strategies
Setup 1: The Defensive Bounce (Long)
• Context: Price drops into a 🔴 Red Cloud (Buyer Pain).
• Trigger: Price touches the 🟢 Green Line (Buyer Cost Basis) and shows a rejection wick.
• Logic: Institutional buyers defend their cost basis to avoid realizing losses.
Setup 2: The Short Squeeze (Momentum)
• Context: Price rallies into a 🟢 Green Cloud (Seller Pain).
• Trigger: Price holds above the 🔴 Red Line (Seller Cost Basis).
• Logic: Short sellers are trapped and forced to buy back (cover), fueling the rally.
Fractal Alignment:
For high-conviction trades, wait for the Dashboard to show "Pain" signals on both the 1h (Anchor) and 5m (Trigger) timeframes simultaneously.
Settings
• Memory Length (Default 144): The lookback period for the institutional cost basis. Increase for swing trading, decrease for scalping.
• Sigma Threshold (Default 2.0): The statistical confidence level for "Pain". Higher values = fewer, stronger signals.
• Volume Amp: When enabled, high volume amplifies the pain signal, giving more weight to institutional footprints.
Range Lattice## RangeLattice
RangeLattice constructs a higher-timeframe scaffolding on any intraday chart, locking in structural highs/lows, mid/quarter grids, VWAP confluence, and live acceptance/break analytics. It provides a non-repainting overlay that turns range management into a disciplined process.
HOW IT WORKS
Structure Harvesting – Using request.security() , the script samples highs/lows from a user-selected timeframe (default 240 minutes) over a configurable lookback to establish the dominant range.
Grid Construction – Midpoint and quarter levels are derived mathematically, mirroring how institutional traders map distribution/accumulation zones.
Acceptance Detection – Consecutive closes inside the range flip an acceptance flag and darken the cloud, signaling balanced auction conditions.
Break Confirmation – Multi-bar closes outside the structure raise break labels and alerts, filtering the countless fake-outs that plague breakout traders.
VWAP Fan Overlay – Session VWAP plus ATR-based bands provide a live measure of flow centering relative to the lattice.
HOW TO USE IT
Range Plays : Fade taps of the outer rails only when acceptance is active and VWAP sits inside the grid—this is where mean-reversion works best.
Breakout Plays : Wait for confirmed break labels before entering expansion trades; the dashboard's Width/ATR metric tells you if the expansion has enough fuel.
Market Prep : Carry the same lattice from pre-market into regular trading hours by keeping the structure timeframe fixed; alerts keep you notified even when managing multiple tickers.
VISUAL FEATURES
Range Tap and Mid Pivot markers provide a tape-reading breadcrumb trail for journaling.
Cloud fill opacity tightens when acceptance persists, visually signaling balance compressions ready to break.
Dashboard displays absolute width, ATR-normalized width, and current state (Balanced vs Transitional) so you can glance across charts quickly.
Acceptance Flag toggle: Keep the repeated acceptance squares hidden until you need to audit balance.
PARAMETERS
Structure Timeframe (default: 240): Choose the timeframe whose ranges matter most (4H for indices, Daily for stocks).
Structure Lookback (default: 60): Bars sampled on the structure timeframe.
Acceptance Bars (default: 8): How many consecutive bars inside the range confirm balance.
Break Confirmation Bars (default: 3): Bars required outside the range to validate a breakout.
ATR Reference (default: 14): ATR period for width normalization.
Show Midpoint Grid (default: enabled): Display the midpoint and quarter levels.
Show Adaptive VWAP Fan (default: enabled): Toggle the VWAP channel for assets where volume distribution matters most.
Show Acceptance Flags (default: disabled): Turn the acceptance markers on/off for maximum visual control.
Show Range Dashboard (default: enabled): Disable if screen space is limited, re-enable during prep sessions.
ALERTS
The indicator includes five alert conditions:
Range High Tap: Price interacted with the RangeLattice high
Range Low Tap: Price interacted with the RangeLattice low
Range Mid Tap: Price interacted with the RangeLattice mid
Range Break Up: Confirmed upside breakout
Range Break Down: Confirmed downside breakout
Where it works best
This indicator works best on liquid instruments with clear structural levels. On very low timeframes (1-minute and below), the structure may update too frequently to be useful. The acceptance/break confirmation system requires patience—faster traders may find the multi-bar confirmation too slow for scalping. The VWAP fan is session-based and resets daily, which may not suit all trading styles.
FluxPulse Beacon## FluxPulse Beacon
FluxPulse Beacon applies a microstructure lens to every bar, combining directional thrust, realized volatility, and multi-timeframe liquidity checks to decide whether the tape is being pushed by real sponsorship or just noise. The oscillator's color-coded columns and adaptive burst thresholds transform complex flow dynamics into a single actionable flux score for futures and equities traders.
HOW IT WORKS
Momentum Extraction – Price differentials over a configurable pulse distance are smoothed using exponential moving averages to isolate directional thrust without reacting to single prints.
Volatility + Liquidity Normalization – The momentum stream is divided by realized volatility and multiplied by both local and higher-timeframe EMA volume ratios, ensuring pulses only appear when volatility and liquidity align.
Adaptive Thresholding – A volatility-derived standard deviation of flux is blended with the base threshold so bursts scale automatically between low-volatility and high-volatility market conditions.
Divergence Engine – Linear regression slopes compare price vs. flux to tag bullish/bearish divergences, highlighting stealth accumulation or distribution zones.
HOW TO USE IT
Continuation Entries : Go with the trend when histogram bars stay above the adaptive threshold, the signal line confirms, and trend bias agrees—this is where liquidity-backed follow-through lives.
Fade Plays : Watch for divergence alerts and shrinking compression values; when flux prints below zero yet price grinds higher, hidden selling pressure often precedes rollovers.
Session Filter : Compression percentage in the diagnostics table instantly tells you whether to trade thin overnight sessions—low compression means stand down.
VISUAL FEATURES
Dynamic background heat maps flux magnitude, while threshold lines provide a quick read on whether a pulse is statistically significant.
Diagnostics table displays live flux, signal, adaptive threshold, and compression for quick reference.
Alert-first workflow: The surface is intentionally clean—bursts and divergences are delivered via alerts instead of on-chart clutter.
PARAMETERS
Trend EMA Length (default: 34): Defines the macro bias anchor; increase for higher-timeframe confirmation.
Pulse Distance (default: 8): Controls how sensitive momentum extraction becomes.
Volatility Window (default: 21): Sample window for realized volatility normalization.
Liquidity Window (default: 55): Volume smoothing window that proxies liquidity expansion.
Liquidity Reference TF (default: 60): Select a higher timeframe to cross-check whether current volume matches institutional flows.
Adaptive Threshold (default: enabled): Disable for fixed thresholds on slower markets; enable for high-volatility assets.
Base Burst Threshold (default: 1.25): Minimum flux magnitude that qualifies as an actionable pulse.
ALERTS
The indicator includes four alert conditions:
Bull Burst: Detects upside liquidity pulses
Bear Burst: Detects downside liquidity pulses
Bull Divergence: Flags bullish delta divergence
Bear Divergence: Flags bearish delta divergence
LIMITATIONS
This indicator is designed for liquid futures and equity markets. Performance may degrade in low-volume or highly illiquid instruments. The adaptive threshold system works best on timeframes where sufficient volatility history exists (typically 15-minute charts and above). Divergence signals are probabilistic and should be confirmed with price action.
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## RangeLattice Mapper
RangeLattice Mapper constructs a higher-timeframe scaffolding on any intraday chart, locking in structural highs/lows, mid/quarter grids, VWAP confluence, and live acceptance/break analytics. It provides a non-repainting overlay that turns range management into a disciplined process.
HOW IT WORKS
Structure Harvesting – Using request.security() , the script samples highs/lows from a user-selected timeframe (default 240 minutes) over a configurable lookback to establish the dominant range.
Grid Construction – Midpoint and quarter levels are derived mathematically, mirroring how institutional traders map distribution/accumulation zones.
Acceptance Detection – Consecutive closes inside the range flip an acceptance flag and darken the cloud, signaling balanced auction conditions.
Break Confirmation – Multi-bar closes outside the structure raise break labels and alerts, filtering the countless fake-outs that plague breakout traders.
VWAP Fan Overlay – Session VWAP plus ATR-based bands provide a live measure of flow centering relative to the lattice.
HOW TO USE IT
Range Plays : Fade taps of the outer rails only when acceptance is active and VWAP sits inside the grid—this is where mean-reversion works best.
Breakout Plays : Wait for confirmed break labels before entering expansion trades; the dashboard's Width/ATR metric tells you if the expansion has enough fuel.
Market Prep : Carry the same lattice from pre-market into regular trading hours by keeping the structure timeframe fixed; alerts keep you notified even when managing multiple tickers.
VISUAL FEATURES
Range Tap and Mid Pivot markers provide a tape-reading breadcrumb trail for journaling.
Cloud fill opacity tightens when acceptance persists, visually signaling balance compressions ready to break.
Dashboard displays absolute width, ATR-normalized width, and current state (Balanced vs Transitional) so you can glance across charts quickly.
Acceptance Flag toggle: Keep the repeated acceptance squares hidden until you need to audit balance.
PARAMETERS
Structure Timeframe (default: 240): Choose the timeframe whose ranges matter most (4H for indices, Daily for stocks).
Structure Lookback (default: 60): Bars sampled on the structure timeframe.
Acceptance Bars (default: 8): How many consecutive bars inside the range confirm balance.
Break Confirmation Bars (default: 3): Bars required outside the range to validate a breakout.
ATR Reference (default: 14): ATR period for width normalization.
Show Midpoint Grid (default: enabled): Display the midpoint and quarter levels.
Show Adaptive VWAP Fan (default: enabled): Toggle the VWAP channel for assets where volume distribution matters most.
Show Acceptance Flags (default: disabled): Turn the acceptance markers on/off for maximum visual control.
Show Range Dashboard (default: enabled): Disable if screen space is limited, re-enable during prep sessions.
ALERTS
The indicator includes five alert conditions:
Range High Tap: Price interacted with the RangeLattice high
Range Low Tap: Price interacted with the RangeLattice low
Range Mid Tap: Price interacted with the RangeLattice mid
Range Break Up: Confirmed upside breakout
Range Break Down: Confirmed downside breakout
LIMITATIONS
This indicator works best on liquid instruments with clear structural levels. On very low timeframes (1-minute and below), the structure may update too frequently to be useful. The acceptance/break confirmation system requires patience—faster traders may find the multi-bar confirmation too slow for scalping. The VWAP fan is session-based and resets daily, which may not suit all trading styles.
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Moving VWAP-KAMA CloudMoving VWAP-KAMA Cloud
Overview
The Moving VWAP-KAMA Cloud is a high-conviction trend filter designed to solve a major problem with standard indicators: Noise. By combining a smoothed Volume Weighted Average Price (MVWAP) with Kaufman’s Adaptive Moving Average (KAMA), this indicator creates a "Value Zone" that identifies the true structural trend while ignoring choppy price action.
Unlike brittle lines that break constantly, this cloud is "slow" by design—making it exceptionally powerful for spotting genuine trend reversals and filtering out fakeouts.
How It Works
This script uses a unique "Double Smoothing" architecture:
The Anchor (MVWAP): We take the standard VWAP and smooth it with a 30-period EMA. This represents the "Fair Value" baseline where volume has supported price over time.
The Filter (KAMA): We apply Kaufman's Adaptive Moving Average to the already smoothed MVWAP. KAMA is unique because it flattens out during low-volatility (choppy) periods and speeds up during high-momentum trends.
The Cloud:
Green/Teal Cloud: Bullish Structure (MVWAP > KAMA)
Purple Cloud: Bearish Structure (MVWAP < KAMA)
🔥 The "Reversal Slingshot" Strategy
Backtests reveal a powerful behavior during major trend changes, particularly after long bear markets:
The Resistance Phase: During a long-term downtrend, price will repeatedly rally into the Purple Cloud and get rejected. The flattened KAMA line acts as a "concrete ceiling," keeping the bearish trend intact.
The Breakout & Flip: When price finally breaks above the cloud with conviction, and the cloud flips Green, it signals a structural regime change.
The "Slingshot" Retest: Often, immediately after this flip, price will drop back into the top of the cloud. This is the "Slingshot" moment. The old resistance becomes new, hardened support.
The Rally: From this support bounce, stocks often launch into a sustained, multi-month bull run. This setup has been observed repeatedly at the bottom of major corrections.
How to Use This Indicator
1. Dynamic Support & Resistance
The KAMA Wall: When price retraces into the cloud, the KAMA line often flattens out, acting as a hard "floor" or "wall." A break of this wall usually signals a genuine trend change, not just a stop hunt.
2. Trend Confirmation (Regime Filter)
Bullish Regime: If price is holding above the cloud, only look for Long setups.
Bearish Regime: If price is holding below the cloud, only look for Short setups.
No-Trade Zone: If price is stuck inside the cloud, the market is traversing fair value. Stand aside until a clear winner emerges.
3. Multi-Timeframe Versatility
While designed for trend confirmation on higher timeframes (4H, Daily), this indicator adapts beautifully to lower timeframes (5m, 15m) for intraday scalping.
On Lower Timeframes: The cloud reacts much faster, acting as a dynamic "VWAP Band" that helps intraday traders stay on the right side of momentum during the session.
Settings
Moving VWAP Period (30): The lookback period for the base VWAP smoothing.
KAMA Settings (10, 10, 30): Controls the sensitivity of the adaptive filter.
Cloud Transparency: Adjust to keep your chart clean.
Alerts Included
Price Cross Over/Under MVWAP
Price Cross Over/Under KAMA
Cloud Flip (Bullish/Bearish Trend Change)
Tip for Traders
This is not a signal entry indicator. It is a Trend Conviction tool. Use it to filter your entries from faster indicators (like RSI or MACD). If your fast indicator signals "Buy" but the cloud is Purple, the probability is low. Wait for the Cloud Flip
Simple Line📌 Understanding the Basic Concept
The trend reverses only when the price moves up or down by a fixed filter size.
It ignores normal volatility and noise, recognizing a trend change only when price moves beyond a specified threshold.
Trend direction is visually intuitive through line colors (green: uptrend, red: downtrend).
⚙️ Explanation of Settings
Auto Brick Size: Automatically determines the brick/filter size.
Fixed Brick Size: Manually set the size (e.g., 15, 30, 50, 100, etc.).
Volatility Length: The lookback period used for calculations (default: 14).
📈 Example of Identifying Buy Timing
When the line changes from gray or red to green, it signals the start of an uptrend.
This indicates that the price has moved upward by more than the required threshold.
📉 Example of Identifying Sell Timing
When the line changes from green to red, it suggests a possible downtrend reversal.
At this point, consider closing long positions or evaluating short entries.
🧪 Recommended Use Cases
Use as a trend filter to enhance the accuracy of existing strategies.
Can be used alone as a clean directional indicator without complex oscillators.
Works synergistically with trend-following strategies, breakout strategies, and more.
🔒 Notes & Cautions
More suitable for medium- to long-term trend trading than for fast scalping.
If the brick size is too small, the indicator may react to noise.
Sensitivity varies greatly depending on the selected brick size, so backtesting is essential to determine optimal values.
❗ The Trend Simple Line focuses solely on direction—remove the noise and focus purely on the trend.
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MTF Scalper - alemicihanMulti-Timeframe Scalper Strategy: Aligning the Big Picture for Quick Gains
This article presents a robust futures trading strategy designed for high-frequency scalping in the crypto market. It’s built on the principle of minimizing risk by ensuring that short-term entries are always aligned with the dominant, higher-timeframe trend.
The Core Concept: Alignment is Key
A Balanced Trend Follower approach, now refined for rapid scalping, uses a Multi-Timeframe (MTF) confirmation system to filter out market noise and increase the probability of a successful trade.
The strategy operates on a Low Timeframe (LTF) chart (e.g., 3m, 5m, or 15m) but only executes trades if the direction is validated by three Higher Timeframes (HTF).
ComponentPurposeFunctionHTF (D, 4h, 1h) EMA => Trend Confirmation =>Checks if the current price is above/below all three Exponential Moving Averages (EMA 20). This provides a strong directional bias.
LTF (5m) Stochastic RSI => Momentum Entry => Generates the actual buy/sell signal by spotting a swift crossover, indicating fresh momentum in the direction of the confirmed HTF trend.
How The Signal Is Generated
Trend Alignment: The system first confirms the trend. If the price is trading above the Daily, 4-Hour, and 1-Hour EMAs, the market is deemed to be in a Strong LONG Trend. Only LONG signals are permitted.
Momentum Trigger: Once the trend is confirmed, a Long Signal is generated only when the Stochastic K-Line crosses above the D-Line, indicating a momentum shift (a pullback ending) towards the main trend direction.
Short Signal: The inverse logic applies to the Short Trend confirmation and entry signal.
Mandatory Risk Management: ATR-Based Exit
Given the high leverage nature of futures and scalping, static Stop-Loss (SL) and Take-Profit (TP) levels are inefficient. This strategy uses the Average True Range (ATR) indicator to dynamically set profit and loss targets based on current market volatility.
Stop Loss (SL): Set dynamically at 1.5 x ATR below (for long) or above (for short) the entry price. This gives the trade enough room to breathe without risking excessive capital.
Take Profit (TP): Set dynamically at 3.0 x ATR, establishing a robust Risk-to-Reward Ratio of 1:2.
Final Thoughts on Testing
This sophisticated approach combines the reliability of MTF analysis with the speed of momentum indicators. However, data analysis is key. Backtesting these parameters (EMA, ATR Multipliers, RSI/Stochastic lengths) on your chosen asset (like BTC/USDT or ETH/USDT) and timeframe is crucial to achieving optimal performance.
Systemic Net Liquidity (Macro Fuel for Crypto & Stocks)This indicator tracks Systemic Net Liquidity, the single most important macro factor for determining the long-term trend of risk assets like Bitcoin (BTC) and major indices (S&P 500). It measures the amount of actual cash available in the financial system to chase speculative assets, distinguishing between money that is circulating and money that is locked up at the Federal Reserve.
Mechanism (What It Measures)
The script uses direct data from the FRED (Federal Reserve Economic Data) to calculate the true state of market funding:
\text{Net Liquidity} = \text{Fed Assets (WALCL)} - \text{Treasury General Account (TGA)} - \text{Reverse Repo (RRP)}
1. Fed Assets (WALCL): The total balance sheet of the Fed (The overall supply of money).
2. Treasury General Account (TGA): Funds the US Treasury collects via bond issuance. When the TGA rises, liquidity is actively drained from the banking system (A major bearish pressure).
3. Overnight Reverse Repo (RRP): Cash parked by banks and money market funds at the Fed, effectively frozen and not contributing to market activity.
How to Interpret Signals
Treat the Net Liquidity line as the market's "Fuel Gauge":
📈 BULLISH SIGNAL (Liquidity Injection): When the Net Liquidity line is rising, money is flowing back into the system, signalling a tailwind for risk assets.
📉 BEARISH SIGNAL (Liquidity Drain): When the line is falling (often due to high TGA balances), cash is being removed. This signals major friction and pressure on price action.
⚠️ DIVERGENCE WARNING: A strong signal is generated when Price (e.g., BTC) rises, but Net Liquidity falls. This macro divergence strongly suggests a major trend reversal or correction is imminent.
Important Notes
Data Source: Data is directly sourced from FRED and updates daily/weekly. This tool is best used for macro analysis and identifying high-level cycles, not short-term scalping.
Disclaimer: Use this indicator as a confirmation tool within your broader strategy. It is not a standalone trading signal.
Systemic Net Liquidity (Macro Fuel for Crypto & Stocks)This indicator tracks Systemic Net Liquidity, the single most important macro factor for determining the long-term trend of risk assets like Bitcoin (BTC) and major indices (S&P 500). It measures the amount of actual cash available in the financial system to chase speculative assets, distinguishing between money that is circulating and money that is locked up at the Federal Reserve.
Mechanism (What It Measures)
The script uses direct data from the FRED (Federal Reserve Economic Data) to calculate the true state of market funding:
\text{Net Liquidity} = \text{Fed Assets (WALCL)} - \text{Treasury General Account (TGA)} - \text{Reverse Repo (RRP)}
1. Fed Assets (WALCL): The total balance sheet of the Fed (The overall supply of money).
2. Treasury General Account (TGA): Funds the US Treasury collects via bond issuance. When the TGA rises, liquidity is actively drained from the banking system (A major bearish pressure).
3. Overnight Reverse Repo (RRP): Cash parked by banks and money market funds at the Fed, effectively frozen and not contributing to market activity.
How to Interpret Signals
Treat the Net Liquidity line as the market's "Fuel Gauge":
📈 BULLISH SIGNAL (Liquidity Injection): When the Net Liquidity line is rising, money is flowing back into the system, signalling a tailwind for risk assets.
📉 BEARISH SIGNAL (Liquidity Drain): When the line is falling (often due to high TGA balances), cash is being removed. This signals major friction and pressure on price action.
⚠️ DIVERGENCE WARNING: A strong signal is generated when Price (e.g., BTC) rises, but Net Liquidity falls. This macro divergence strongly suggests a major trend reversal or correction is imminent.
Important Notes
Data Source: Data is directly sourced from FRED and updates daily/weekly. This tool is best used for macro analysis and identifying high-level cycles, not short-term scalping.
Disclaimer: Use this indicator as a confirmation tool within your broader strategy. It is not a standalone trading signal.
Mars Signals - Ultimate Institutional Suite v3.0(Joker)Comprehensive Trading Manual
Mars Signals – Ultimate Institutional Suite v3.0 (Joker)
## Chapter 1 – Philosophy & System Architecture
This script is not a simple “buy/sell” indicator.
Mars Signals – UIS v3.0 (Joker) is designed as an institutional-style analytical assistant that layers several methodologies into a single, coherent framework.
The system is built on four core pillars:
1. Smart Money Concepts (SMC)
- Detection of Order Blocks (professional demand/supply zones).
- Detection of Fair Value Gaps (FVGs) (price imbalances).
2. Smart DCA Strategy
- Combination of RSI and Bollinger Bands
- Identifies statistically discounted zones for scaling into spot positions or exiting shorts.
3. Volume Profile (Visible Range Simulation)
- Distribution of volume by price, not by time.
- Identification of POC (Point of Control) and high-/low-volume areas.
4. Wyckoff Helper – Spring
- Detection of bear traps, liquidity grabs, and sharp bullish reversals.
All four pillars feed into a Confluence Engine (Scoring System).
The final output is presented in the Dashboard, with a clear, human-readable signal:
- STRONG LONG 🚀
- WEAK LONG ↗
- NEUTRAL / WAIT
- WEAK SHORT ↘
- STRONG SHORT 🩸
This allows the trader to see *how many* and *which* layers of the system support a bullish or bearish bias at any given time.
## Chapter 2 – Settings Overview
### 2.1 General & Dashboard Group
- Show Dashboard Panel (`show_dash`)
Turns the dashboard table in the corner of the chart ON/OFF.
- Show Signal Recommendation (`show_rec`)
- If enabled, the textual signal (STRONG LONG, WEAK SHORT, etc.) is displayed.
- If disabled, you only see feature status (ON/OFF) and the current price.
- Dashboard Position (`dash_pos`)
Determines where the dashboard appears on the chart:
- `Top Right`
- `Bottom Right`
- `Top Left`
### 2.2 Smart Money (SMC) Group
- Enable SMC Strategy (`show_smc`)
Globally enables or disables the Order Block and FVG logic.
- Order Block Pivot Lookback (`ob_period`)
Main parameter for detecting key pivot highs/lows (swing points).
- Default value: 5
- Concept:
A bar is considered a pivot low if its low is lower than the lows of the previous 5 and the next 5 bars.
Similarly, a pivot high has a high higher than the previous 5 and the next 5 bars.
These pivots are used as anchors for Order Blocks.
- Increasing `ob_period`:
- Fewer levels.
- But levels tend to be more significant and reliable.
- In highly volatile markets (major news, war events, FOMC, etc.),
using values 7–10 is recommended to filter out weak levels.
- Show Fair Value Gaps (`show_fvg`)
Enables/disables the drawing of FVG zones (imbalances).
- Bullish OB Color (`c_ob_bull`)
- Color of Bullish Order Blocks (Demand Zones).
- Default: semi-transparent green (transparency ≈ 80).
- Bearish OB Color (`c_ob_bear`)
- Color of Bearish Order Blocks (Supply Zones).
- Default: semi-transparent red.
- Bullish FVG Color (`c_fvg_bull`)
- Color of Bullish FVG (upward imbalance), typically yellow.
- Bearish FVG Color (`c_fvg_bear`)
- Color of Bearish FVG (downward imbalance), typically purple.
### 2.3 Smart DCA Strategy Group
- Enable DCA Zones (`show_dca`)
Enables the Smart DCA logic and visual labels.
- RSI Length (`rsi_len`)
Lookback period for RSI (default: 14).
- Shorter → more sensitive, more noise.
- Longer → fewer signals, higher reliability.
- Bollinger Bands Length (`bb_len`)
Moving average period for Bollinger Bands (default: 20).
- BB Multiplier (`bb_mult`)
Standard deviation multiplier for Bollinger Bands (default: 2.0).
- For extremely volatile markets, values like 2.5–3.0 can be used so that only extreme deviations trigger a DCA signal.
### 2.4 Volume Profile (Visible Range Sim) Group
- Show Volume Profile (`show_vp`)
Enables the simulated Volume Profile bars on the right side of the chart.
- Volume Lookback Bars (`vp_lookback`)
Number of bars used to compute the Volume Profile (default: 150).
- Higher values → broader historical context, heavier computation.
- Row Count (`vp_rows`)
Number of vertical price segments (rows) to divide the total price range into (default: 30).
- Width (%) (`vp_width`)
Relative width of each volume bar as a percentage.
In the code, bar widths are scaled relative to the row with the maximum volume.
> Technical note: Volume Profile calculations are executed only on the last bar (`barstate.islast`) to keep the script performant even on higher timeframes.
### 2.5 Wyckoff Helper Group
- Show Wyckoff Events (`show_wyc`)
Enables detection and plotting of Wyckoff Spring events.
- Volume MA Length (`vol_ma_len`)
Length of the moving average on volume.
A bar is considered to have Ultra Volume if its volume is more than 2× the volume MA.
## Chapter 3 – Smart Money Strategy (Order Blocks & FVG)
### 3.1 What Is an Order Block?
An Order Block (OB) represents the footprint of large institutional orders:
- Bullish Order Block (Demand Zone)
The last selling region (bearish candle/cluster) before a strong upward move.
- Bearish Order Block (Supply Zone)
The last buying region (bullish candle/cluster) before a strong downward move.
Institutions and large players place heavy orders in these regions. Typical price behavior:
- Price moves away from the zone.
- Later returns to the same zone to fill unfilled orders.
- Then continues the larger trend.
In the script:
- If `pl` (pivot low) forms → a Bullish OB is created.
- If `ph` (pivot high) forms → a Bearish OB is created.
The box is drawn:
- From `bar_index ` to `bar_index`.
- Between `low ` and `high `.
- `extend=extend.right` extends the OB into the future, so it acts as a dynamic support/resistance zone.
- Only the last 4 OB boxes are kept to avoid clutter.
### 3.2 Order Block Color Guide
- Semi-transparent Green (`c_ob_bull`)
- Represents a Bullish Order Block (Demand Zone).
- Interpretation: a price region with a high probability of bullish reaction.
- Semi-transparent Red (`c_ob_bear`)
- Represents a Bearish Order Block (Supply Zone).
- Interpretation: a price region with a high probability of bearish reaction.
Overlap (Multiple OBs in the Same Area)
When two or more Order Blocks overlap:
- The shared area appears visually denser/stronger.
- This suggests higher order density.
- Such zones can be treated as high-priority levels for entries, exits, and stop-loss placement.
### 3.3 Demand/Supply Logic in the Scoring Engine
is_in_demand = low <= ta.lowest(low, 20)
is_in_supply = high >= ta.highest(high, 20)
- If current price is near the lowest lows of the last 20 bars, it is considered in a Demand Zone → positive impact on score.
- If current price is near the highest highs of the last 20 bars, it is considered in a Supply Zone → negative impact on score.
This logic complements Order Blocks and helps the Dashboard distinguish whether:
- Market is currently in a statistically cheap (long-friendly) area, or
- In a statistically expensive (short-friendly) area.
### 3.4 Fair Value Gaps (FVG)
#### Concept
When the market moves aggressively:
- Some price levels are skipped and never traded.
- A gap between wicks/shadows of consecutive candles appears.
- These regions are called Fair Value Gaps (FVGs) or Imbalances.
The market generally “dislikes” imbalance and often:
- Returns to these zones in the future.
- Fills the gap (rebalance).
- Then resumes its dominant direction.
#### Implementation in the Code
Bullish FVG (Yellow)
fvg_bull_cond = show_smc and show_fvg and low > high and close > high
if fvg_bull_cond
box.new(bar_index , high , bar_index, low, ...)
Core condition:
`low > high ` → the current low is above the high of two bars ago; the space between them is an untraded gap.
Bearish FVG (Purple)
fvg_bear_cond = show_smc and show_fvg and high < low and close < low
if fvg_bear_cond
box.new(bar_index , low , bar_index, high, ...)
Core condition:
`high < low ` → the current high is below the low of two bars ago; again a price gap exists.
#### FVG Color Guide
- Transparent Yellow (`c_fvg_bull`) – Bullish FVG
Often acts like a magnet for price:
- Price tends to retrace into this zone,
- Fill the imbalance,
- And then continue higher.
- Transparent Purple (`c_fvg_bear`) – Bearish FVG
Price tends to:
- Retrace upward into the purple area,
- Fill the imbalance,
- And then resume downward movement.
#### Trading with FVGs
- FVGs are *not* standalone entry signals.
They are best used as:
- Targets (take-profit zones), or
- Reaction areas where you expect a pause or reversal.
Examples:
- If you are long, a bearish FVG above is often an excellent take-profit zone.
- If you are short, a bullish FVG below is often a good cover/exit zone.
### 3.5 Core SMC Trading Templates
#### Reversal Long
1. Price trades down into a green Order Block (Demand Zone).
2. A bullish confirmation candle (Close > Open) forms inside or just above the OB.
3. If this zone is close to or aligned with a bullish FVG (yellow), the signal is reinforced.
4. Entry:
- At the close of the confirmation candle, or
- Using a limit order near the upper boundary of the OB.
5. Stop-loss:
- Slightly below the OB.
- If the OB is broken decisively and price consolidates below it, the zone loses validity.
6. Targets:
- The next FVG,
- Or the next red Order Block (Supply Zone) above.
#### Reversal Short
The mirror scenario:
- Price rallies into a red Order Block (Supply).
- A bearish confirmation candle forms (Close < Open).
- FVG/premium structure above can act as a confluence.
- Stop-loss goes above the OB.
- Targets: lower FVGs or subsequent green OBs below.
## Chapter 4 – Smart DCA Strategy (RSI + Bollinger Bands)
### 4.1 Smart DCA Concept
- Classic DCA = buying at fixed time intervals regardless of price.
- Smart DCA = scaling in only when:
- Price is statistically cheaper than usual, and
- The market is in a clear oversold condition.
Code logic:
rsi_val = ta.rsi(close, rsi_len)
= ta.bb(close, bb_len, bb_mult)
dca_buy = show_dca and rsi_val < 30 and close < bb_lower
dca_sell = show_dca and rsi_val > 70 and close > bb_upper
Conditions:
- DCA Buy – Smart Scale-In Zone
- RSI < 30 → oversold.
- Close < lower Bollinger Band → price has broken below its typical volatility envelope.
- DCA Sell – Overbought/Distribution Zone
- RSI > 70 → overbought.
- Close > upper Bollinger Band → price is extended far above the mean.
### 4.2 Visual Representation on the Chart
- Green “DCA” Label Below Candle
- Shape: `labelup`.
- Color: lime background, white text.
- Meaning: statistically attractive level for laddered spot entries or short exits.
- Red “SELL” Label Above Candle
- Warning that the market is in an extended, overbought condition.
- Suitable for profit-taking on longs or considering short entries (with proper confluence and risk management).
- Light Green Background (`bgcolor`)
- When `dca_buy` is true, the candle background turns very light green (high transparency).
- This helps visually identify DCA Zones across the chart at a glance.
### 4.3 Practical Use in Trading
#### Spot Trading
Used to build a better average entry price:
- Every time a DCA label appears, allocate a fixed portion of capital (e.g., 2–5%).
- Combining DCA signals with:
- Green OBs (Demand Zones), and/or
- The Volume Profile POC
makes the zone structurally more important.
#### Futures Trading
- Longs
- Use DCA Buy signals as low-risk zones for opening or adding to longs when:
- Price is inside a green OB, or
- The Dashboard already leans LONG.
- Shorts
- Use DCA Sell signals as:
- Exit zones for longs, or
- Areas to initiate shorts with stops above structural highs.
## Chapter 5 – Volume Profile (Visible Range Simulation)
### 5.1 Concept
Traditional volume (histogram under the chart) shows volume over time.
Volume Profile shows volume by price level:
- At which prices has the highest trading activity occurred?
- Where did buyers and sellers agree the most (High Volume Nodes – HVNs)?
- Where did price move quickly due to low participation (Low Volume Nodes – LVNs)?
### 5.2 Implementation in the Script
Executed only when `show_vp` is enabled and on the last bar:
1. The last `vp_lookback` bars (default 150) are processed.
2. The minimum low and maximum high over this window define the price range.
3. This price range is divided into `vp_rows` segments (e.g., 30 rows).
4. For each row:
- All bars are scanned.
- If the mid-price `(high + low ) / 2` falls inside a row, that bar’s volume is added to the row total.
5. The row with the greatest volume is stored as `max_vol_idx` (the POC row).
6. For each row, a volume box is drawn on the right side of the chart.
### 5.3 Color Scheme
- Semi-transparent Orange
- The row with the maximum volume – the Point of Control (POC).
- Represents the strongest support/resistance level from a volume perspective.
- Semi-transparent Blue
- Other volume rows.
- The taller the bar → the higher the volume → the stronger the interest at that price band.
### 5.4 Trading Applications
- If price is above POC and retraces back into it:
→ POC often acts as support, suitable for long setups.
- If price is below POC and rallies into it:
→ POC often acts as resistance, suitable for short setups or profit-taking.
HVNs (Tall Blue Bars)
- Represent areas of equilibrium where the market has spent time and traded heavily.
- Price tends to consolidate here before choosing a direction.
LVNs (Short or Nearly Empty Bars)
- Represent low participation zones.
- Price often moves quickly through these areas – useful for targeting fast moves.
## Chapter 6 – Wyckoff Helper – Spring
### 6.1 Spring Concept
In the Wyckoff framework:
- A Spring is a false break of support.
- The market briefly trades below a well-defined support level, triggers stop losses,
then sharply reverses upward as institutional buyers absorb liquidity.
This movement:
- Clears out weak hands (retail sellers).
- Provides large players with liquidity to enter long positions.
- Often initiates a new uptrend.
### 6.2 Code Logic
Conditions for a Spring:
1. The current low is lower than the lowest low of the previous 50 bars
→ apparent break of a long-standing support.
2. The bar closes bullish (Close > Open)
→ the breakdown was rejected.
3. Volume is significantly elevated:
→ `volume > 2 × volume_MA` (Ultra Volume).
When all conditions are met and `show_wyc` is enabled:
- A pink diamond is plotted below the bar,
- With the label “Spring” – one of the strongest long signals in this system.
### 6.3 Trading Use
- After a valid Spring, markets frequently enter a meaningful bullish phase.
- The highest quality setups occur when:
- The Spring forms inside a green Order Block, and
- Near or on the Volume Profile POC.
Entries:
- At the close of the Spring bar, or
- On the first pullback into the mid-range of the Spring candle.
Stop-loss:
- Slightly below the Spring’s lowest point (wick low plus a small buffer).
## Chapter 7 – Confluence Engine & Dashboard
### 7.1 Scoring Logic
For each bar, the script:
1. Resets `score` to 0.
2. Adjusts the score based on different signals.
SMC Contribution
if show_smc
if is_in_demand
score += 1
if is_in_supply
score -= 1
- Being in Demand → `+1`
- Being in Supply → `-1`
DCA Contribution
if show_dca
if dca_buy
score += 2
if dca_sell
score -= 2
- DCA Buy → `+2` (strong, statistically driven long signal)
- DCA Sell → `-2`
Wyckoff Spring Contribution
if show_wyc
if wyc_spring
score += 2
- Spring → `+2` (entry of strong money)
### 7.2 Mapping Score to Dashboard Signal
- score ≥ 2 → STRONG LONG 🚀
Multiple bullish conditions aligned.
- score = 1 → WEAK LONG ↗
Some bullish bias, but only one layer clearly positive.
- score = 0 → NEUTRAL / WAIT
Rough balance between buying and selling forces; staying flat is usually preferable.
- score = -1 → WEAK SHORT ↘
Mild bearish bias, suited for cautious or short-term plays.
- score ≤ -2 → STRONG SHORT 🩸
Convergence of several bearish signals.
### 7.3 Dashboard Structure
The dashboard is a two-column table:
- Row 0
- Column 0: `"Mars Signals"` – black background, white text.
- Column 1: `"UIS v3.0"` – black background, yellow text.
- Row 1
- Column 0: `"Price:"` (light grey background).
- Column 1: current closing price (`close`) with a semi-transparent blue background.
- Row 2
- Column 0: `"SMC:"`
- Column 1:
- `"ON"` (green) if `show_smc = true`
- `"OFF"` (grey) otherwise.
- Row 3
- Column 0: `"DCA:"`
- Column 1:
- `"ON"` (green) if `show_dca = true`
- `"OFF"` (grey) otherwise.
- Row 4
- Column 0: `"Signal:"`
- Column 1: signal text (`status_txt`) with background color `status_col`
(green, red, teal, maroon, etc.)
- If `show_rec = false`, these cells are cleared.
## Chapter 8 – Visual Legend (Colors, Shapes & Actions)
For quick reading inside TradingView, the visual elements are described line by line instead of a table.
Chart Element: Green Box
Color / Shape: Transparent green rectangle
Core Meaning: Bullish Order Block (Demand Zone)
Suggested Trader Response: Look for longs, Smart DCA adds, closing or reducing shorts.
Chart Element: Red Box
Color / Shape: Transparent red rectangle
Core Meaning: Bearish Order Block (Supply Zone)
Suggested Trader Response: Look for shorts, or take profit on existing longs.
Chart Element: Yellow Area
Color / Shape: Transparent yellow zone
Core Meaning: Bullish FVG / upside imbalance
Suggested Trader Response: Short take-profit zone or expected rebalance area.
Chart Element: Purple Area
Color / Shape: Transparent purple zone
Core Meaning: Bearish FVG / downside imbalance
Suggested Trader Response: Long take-profit zone or temporary supply region.
Chart Element: Green "DCA" Label
Color / Shape: Green label with white text, plotted below the candle
Core Meaning: Smart ladder-in buy zone, DCA buy opportunity
Suggested Trader Response: Spot DCA entry, partial short exit.
Chart Element: Red "SELL" Label
Color / Shape: Red label with white text, plotted above the candle
Core Meaning: Overbought / distribution zone
Suggested Trader Response: Take profit on longs, consider initiating shorts.
Chart Element: Light Green Background (bgcolor)
Color / Shape: Very transparent light-green background behind bars
Core Meaning: Active DCA Buy zone
Suggested Trader Response: Treat as a discount zone on the chart.
Chart Element: Orange Bar on Right
Color / Shape: Transparent orange horizontal bar in the volume profile
Core Meaning: POC – price with highest traded volume
Suggested Trader Response: Strong support or resistance; key reference level.
Chart Element: Blue Bars on Right
Color / Shape: Transparent blue horizontal bars in the volume profile
Core Meaning: Other volume levels, showing high-volume and low-volume nodes
Suggested Trader Response: Use to identify balance zones (HVN) and fast-move corridors (LVN).
Chart Element: Pink "Spring" Diamond
Color / Shape: Pink diamond with white text below the candle
Core Meaning: Wyckoff Spring – liquidity grab and potential major bullish reversal
Suggested Trader Response: One of the strongest long signals in the suite; look for high-quality long setups with tight risk.
Chart Element: STRONG LONG in Dashboard
Color / Shape: Green background, white text in the Signal row
Core Meaning: Multiple bullish layers in confluence
Suggested Trader Response: Consider initiating or increasing longs with strict risk management.
Chart Element: STRONG SHORT in Dashboard
Color / Shape: Red background, white text in the Signal row
Core Meaning: Multiple bearish layers in confluence
Suggested Trader Response: Consider initiating or increasing shorts with a logical, well-placed stop.
## Chapter 9 – Timeframe-Based Trading Playbook
### 9.1 Timeframe Selection
- Scalping
- Timeframes: 1M, 5M, 15M
- Objective: fast intraday moves (minutes to a few hours).
- Recommendation: focus on SMC + Wyckoff.
Smart DCA on very low timeframes may introduce excessive noise.
- Day Trading
- Timeframes: 15M, 1H, 4H
- Provides a good balance between signal quality and frequency.
- Recommendation: use the full stack – SMC + DCA + Volume Profile + Wyckoff + Dashboard.
- Swing Trading & Position Investing
- Timeframes: Daily, Weekly
- Emphasis on Smart DCA + Volume Profile.
- SMC and Wyckoff are used mainly to fine-tune swing entries within larger trends.
### 9.2 Scenario A – Scalping Long
Example: 5-Minute Chart
1. Price is declining into a green OB (Bullish Demand).
2. A candle with a long lower wick and bullish close (Pin Bar / Rejection) forms inside the OB.
3. A Spring diamond appears below the same candle → very strong confluence.
4. The Dashboard shows at least WEAK LONG ↗, ideally STRONG LONG 🚀.
5. Entry:
- On the close of the confirmation candle, or
- On the first pullback into the mid-range of that candle.
6. Stop-loss:
- Slightly below the OB.
7. Targets:
- Nearby bearish FVG above, and/or
- The next red OB.
### 9.3 Scenario B – Day-Trading Short
Recommended Timeframes: 1H or 4H
1. The market completes a strong impulsive move upward.
2. Price enters a red Order Block (Supply).
3. In the same zone, a purple FVG appears or remains unfilled.
4. On a lower timeframe (e.g., 15M), RSI enters overbought territory and a DCA Sell signal appears.
5. The main timeframe Dashboard (1H) shows WEAK SHORT ↘ or STRONG SHORT 🩸.
Trade Plan
- Open a short near the upper boundary of the red OB.
- Place the stop above the OB or above the last swing high.
- Targets:
- A yellow FVG lower on the chart, and/or
- The next green OB (Demand) below.
### 9.4 Scenario C – Swing / Investment with Smart DCA
Timeframes: Daily / Weekly
1. On the daily or weekly chart, each time a green “DCA” label appears:
- Allocate a fixed fraction of your capital (e.g., 3–5%) to that asset.
2. Check whether this DCA zone aligns with the orange POC of the Volume Profile:
- If yes → the quality of the entry zone is significantly higher.
3. If the DCA signal sits inside a daily green OB, the probability of a medium-term bottom increases.
4. Always build the position laddered, never all-in at a single price.
Exits for investors:
- Near weekly red OBs or large purple FVG zones.
- Ideally via partial profit-taking rather than closing 100% at once.
### 9.5 Case Study 1 – BTCUSDT (15-Minute)
- Context: Price has sold off down towards 65,000 USD.
- A green OB had previously formed at that level.
- Near the lower boundary of this OB, a partially filled yellow FVG is present.
- As price returns to this region, a Spring appears.
- The Dashboard shifts from NEUTRAL / WAIT to WEAK LONG ↗.
Plan
- Enter a long near the OB low.
- Place stop below the Spring low.
- First target: a purple FVG around 66,200.
- Second (optional) target: the first red OB above that level.
### 9.6 Case Study 2 – Meme Coin (PEPE – 4H)
- After a strong pump, price enters a corrective phase.
- On the 4H chart, RSI drops below 30; price breaks below the lower Bollinger Band → a DCA label prints.
- The Volume Profile shows the POC at approximately the same level.
- The Dashboard displays STRONG LONG 🚀.
Plan
- Execute laddered buys in the combined DCA + POC zone.
- Place a protective stop below the last significant swing low.
- Target: an expected 20–30% upside move towards the next red OB or purple FVG.
## Chapter 10 – Risk Management, Psychology & Advanced Tuning
### 10.1 Risk Management
No signal, regardless of its strength, replaces risk control.
Recommendations:
- In futures, do not expose more than 1–3% of account equity to risk per trade.
- Adjust leverage to the volatility of the instrument (lower leverage for highly volatile altcoins).
- Place stop-losses in zones where the idea is clearly invalidated:
- Below/above the relevant Order Block or Spring, not randomly in the middle of the structure.
### 10.2 Market-Specific Parameter Tuning
- Calmer Markets (e.g., major FX pairs)
- `ob_period`: 3–5.
- `bb_mult`: 2.0 is usually sufficient.
- Highly Volatile Markets (Crypto, news-driven assets)
- `ob_period`: 7–10 to highlight only the most robust OBs.
- `bb_mult`: 2.5–3.0 so that only extreme deviations trigger DCA.
- `vol_ma_len`: increase (e.g., to ~30) so that Spring triggers only on truly exceptional
volume spikes.
### 10.3 Trading Psychology
- STRONG LONG 🚀 does not mean “risk-free”.
It means the probability of a successful long, given the model’s logic, is higher than average.
- Treat Mars Signals as a confirmation and context system, not a full replacement for your own decision-making.
- Example of disciplined thinking:
- The Dashboard prints STRONG LONG,
- But price is simultaneously testing a multi-month macro resistance or a major negative news event is imminent,
- In such cases, trade smaller, widen stops appropriately, or skip the trade.
## Chapter 11 – Technical Notes & FAQ
### 11.1 Does the Script Repaint?
- Order Blocks and Springs are based on completed pivot structures and confirmed candles.
- Until a pivot is confirmed, an OB does not exist; after confirmation, behavior is stable under classic SMC assumptions.
- The script is designed to be structurally consistent rather than repainting signals arbitrarily.
### 11.2 Computational Load of Volume Profile
- On the last bar, the script processes up to `vp_lookback` bars × `vp_rows` rows.
- On very low timeframes with heavy zooming, this can become demanding.
- If you experience performance issues:
- Reduce `vp_lookback` or `vp_rows`, or
- Temporarily disable Volume Profile (`show_vp = false`).
### 11.3 Multi-Timeframe Behavior
- This version of the script is not internally multi-timeframe.
All logic (OB, DCA, Spring, Volume Profile) is computed on the active timeframe only.
- Practical workflow:
- Analyze overall structure and key zones on higher timeframes (4H / Daily).
- Use lower timeframes (15M / 1H) with the same tool for timing entries and exits.
## Conclusion
Mars Signals – Ultimate Institutional Suite v3.0 (Joker) is a multi-layer trading framework that unifies:
- Price structure (Order Blocks & FVG),
- Statistical behavior (Smart DCA via RSI + Bollinger),
- Volume distribution by price (Volume Profile with POC, HVN, LVN),
- Liquidity events (Wyckoff Spring),
into a single, coherent system driven by a transparent Confluence Scoring Engine.
The final output is presented in clear, actionable language:
> STRONG LONG / WEAK LONG / NEUTRAL / WEAK SHORT / STRONG SHORT
The system is designed to support professional decision-making, not to replace it.
Used together with strict risk management and disciplined execution,
Mars Signals – UIS v3.0 (Joker) can serve as a central reference manual and operational guide
for your trading workflow, from scalping to swing and investment positioning.
Advanced Triple Strategy ScalperHere are the three scalping strategies presented in the video "3 Scalping Strategies That Work Every Day (Backtested & Proven)" by Asia Forex Mentor – Ezekiel Chew:
### Scalper’s Trend Filter (Triple EMA)
This strategy uses three EMAs (25, 50, 100) on the 5-minute chart to filter high-probability trades aligned with momentum .
- Only trade when all three EMAs are angled in the same direction and clearly separated (no crossing or tangling) .
- Enter when price pulls back toward the 25 or 50 EMA and then bounces back toward the 25 EMA, but do not enter if price closes below the 100 EMA .
- Set stop-loss just below the 50 EMA or swing low and aim for a risk-to-reward ratio of 1:1.5 .
### Flip Zone Trap (Reversal Catching)
This method identifies precise reversal moments where market structure shifts from weakness to strength .
- Use the 15-min chart to locate key support or resistance zones where price previously reacted .
- Wait for price to stop making lower lows and begin making higher highs (or vice versa for shorts); confirm with a trendline break AND follow-through (higher lows & highs within 5-7 candles) .
- Use confirmation candles (bullish engulfing, pin bar rejection) at the zone before entry .
### Liquidity Shift Trigger (Smart Money Trap)
This system leverages institutional stop hunts and liquidity sweeps at key zones for sniper entries .
- Start with a 15-min chart to identify structure breaks and points of interest (order blocks, flip zones, demand zones) .
- Drop to 1-min chart and wait for price to enter the refined zone and sweep liquidity (sharp wick/spike below/above key level) .
- Once liquidity is swept, wait for a clean structure shift (break of most recent internal high or low) within 5–6 candles—if confirmed, refine entry to the candle that caused the break and enter when price returns to that candle with a strong reaction .
***
### Practical Application
- These strategies are systematic, rule-based, and designed to cut out fake moves, avoid early stop-outs, and align entries with momentum and institutional activity .
- Perfect for short timeframes and volatile pairs like XAUUSD, especially if paired with additional confirmation from other technical analysis tools .
All three strategies emphasize filtering noise, waiting for momentum/trend confirmation, and avoiding impulsive entries—key principles for consistent scalping success
Multi EMA + Indicators + Mini-Dashboard + Reversals v6📘 Multi EMA + Indicators + Mini-Dashboard + Reversals v6
🧩 Overview
This indicator is a multi-EMA setup that combines trend, momentum, and reversal analysis in a single visual framework.
It integrates four exponential moving averages (EMAs), key oscillators (RSI, MACD, Stochastic, CCI), volatility filtering (ATR), and a dynamic mini-dashboard that summarizes all signals in real time.
Its purpose is to help traders visually confirm trend alignment, filter valid entries, and identify possible trend continuation or reversal points.
It can display buy/sell arrows, detect reversal candles, and issue alerts when trading conditions are met.
⚙️ Core Components
1. Moving Averages (EMA Setup)
EMA1 (fast) and EMA2 (medium) define the short-term trend and trigger bias.
When the price is above both EMAs → bullish bias.
When below → bearish bias.
EMA3 and EMA4 act as trend filters. Their slopes (up or down) confirm overall momentum and help validate signals.
Each EMA has customizable lengths, sources, and colors for up/down trends.
This “EMA stack” is the foundation of the setup — a structured trend-following framework that adapts to market speed and volatility.
2. Momentum and Confirmation Filters
Each indicator can be individually enabled or disabled for flexibility.
RSI: confirms direction (above/below 50).
MACD: detects momentum crossover (MACD > Signal for bullish confirmation).
Stochastic: identifies trend continuation (K > D for longs, K < D for shorts).
CCI: adds trend bias above/below a threshold.
ATR Filter: filters out small, low-volatility candles to reduce noise.
You can activate only the filters that fit your trading plan — for instance, trend traders often use RSI and MACD, while scalpers may rely on Stochastic and ATR.
3. Reversal Detection
The indicator includes an optional Reversal Section that independently detects potential turning points.
It combines multiple configurable criteria:
Candlestick patterns (Bullish Hammer, Shooting Star).
Large Candle filter — detects unusually large bars (relative to close).
Price-to-EMA distance — identifies overextended moves that might revert.
RSI Divergence — detects potential momentum shifts.
RSI Overbought/Oversold zones (70/30 by default).
Doji Candles — sign of indecision.
A bullish or bearish reversal signal appears when enough selected criteria are met.
All sub-modules can be toggled on/off individually, giving you full control over sensitivity.
4. Signal Logic
Buy and sell signals are triggered when EMA alignment and the chosen confirmations agree:
Buy Signal
→ Price above EMA1 & EMA2
→ Confirmations (RSI/MACD/Stoch/CCI/ATR) pass
→ Trend filters (EMA3/EMA4) point upward
Sell Signal
→ Price below EMA1 & EMA2
→ Confirmations align bearishly
→ Trend filters (EMA3/EMA4) slope downward
Reversal signals can appear independently, even against the current EMA trend, depending on your settings.
5. Visual Dashboard
A mini-dashboard appears near the chart showing:
Current trade bias (LONG / SHORT / NEUTRAL)
EMA3 and EMA4 trend directions (↑ / ↓)
Quick visual bars (🟩 / 🟥) for each filter: RSI, MACD, Stoch, ATR, CCI, EMA filters
Reversal criteria status (Doji, RSI divergence, candle size, etc.)
This panel gives you a compact overview of all indicator states at a glance.
The color of the panel changes dynamically — green for bullish, red for bearish, gray for neutral.
6. Alerts
Built-in alerts allow automation or notifications:
Buy Alert
Sell Alert
Reversal Buy
Reversal Sell
You can connect these alerts to TradingView notifications or external bots for semi-automated execution.
💡 How to Use
✅ Trend-Following Setup
Focus on trades in the direction of EMA1 & EMA2.
Confirm with EMA3 & EMA4 trending in the same direction.
Use RSI/MACD/Stoch filters to ensure momentum supports the trade.
Avoid entries when ATR filter indicates low volatility.
🔄 Reversal Setup
Enable the Reversal section for potential tops/bottoms.
Look for reversal buy signals near support zones or after strong downtrends.
Use RSI divergence or Doji + Hammer signals as confirmation.
Combine with key chart areas (supply/demand or previous swing levels).
⚖️ Combination Approach
Trade continuation signals when all EMAs are aligned and filters are green.
Trade reversals only when at a key area (support/resistance) and confirmed by reversal conditions.
Always check higher-timeframe bias before entering a trade.
🧭 Practical Tips
Use different EMA sets for different timeframes:
9/21/50/100 for swing or trend trades.
5/13/34/89 for intraday scalping.
Turn off filters you don’t use to reduce lag.
Always validate signals with price structure, not just indicator alignment.
Practice in replay mode before live trading.
🗺️ Key Chart Confluence (Highly Recommended)
Although the indicator provides structured signals, its best use is in confluence with:
Support and resistance levels
Supply/demand zones
Trendlines and channels
Liquidity pools
Volume clusters
Signals aligned with strong key areas on the chart tend to have greater reliability than isolated indicator triggers.
I use EMA 1 - 20 Open ; EMA 2 - 20 Close ; EMA 3 - 50 ; EMA 4 - 200 or 100 , but that's me...
⚠️ Important Disclaimer
This indicator is a technical tool, not a guarantee of results.
Trading involves risk, and no signal is ever 100% accurate.
Every trader should develop a personal strategy, use proper risk management, and adapt settings to their instrument and timeframe.
Always combine indicator signals with key chart areas, higher-timeframe context, and your own analysis before taking a trade.
RSI MTF Table - 12 Pairs (1,5,15)
The relative strength index measures the speed and magnitude of an asset's recent price changes. Therefore, it is considered a momentum indicator in technical analysis. Essentially, the RSI is the ratio of the days an asset's value increases to decreases over a given period.
Generally speaking, if the RSI is around 50, we do not expect strong movements. RSI above 65 or below 35 are areas we expect. In this context, this chart and the general momentum in 1-5-15 minutes allow us to quickly determine the parity we will trade. It is useful for intraday trading and scalping.
ADX Color Change by BehemothI find this tool to be the most valuable and accurate entry point indicator along with moving averages and the VWAP.
ADX Color Indicator - Controls & Intraday Trading Benefits
Indicator Controls:
1. ADX Length (default: 14)
- Controls the calculation period for ADX
- Lower values (7-10) = more sensitive, faster signals (better for scalping)
- Higher values (14-20) = smoother, fewer false signals (better for swing trades)
- *Intraday tip:* Try 10-14 for most intraday timeframes
2. Show Threshold Levels (default: On)
- Displays the 20 and 25 horizontal lines
- Helps you quickly identify when ADX crosses key strength levels
3. Use Custom Timeframe (default: Off)
- Allows viewing higher timeframe ADX on lower timeframe charts
- *Example:* Trade on 5-min chart but see 15-min or 1-hour ADX
4. Custom Timeframe
- Select any timeframe: 1m, 5m, 15m, 30m, 1H, 4H, D, etc.
- *Intraday tip:* Use 15m or 1H ADX on 5m charts for better trend context
5. Show +DI and -DI (default: Off)
- Shows directional movement indicators
- Green line (+DI) > Red line (-DI) = bullish trend
- Red line (-DI) > Green line (+DI) = bearish trend
6. Show Background Zon es (default: Off)
- Visual background colors for quick trend strength identification
- Green = strong trend (ADX > 25)
- Yellow = moderate trend (ADX 20-25)
Intraday Trading Benefits:
1. Avoid Choppy Markets
- When ADX < 20 (no background color), market is ranging
- Reduces false breakout trades and whipsaws
- Save time and capital by stepping aside during low-quality setups
2. Identify High-Probability Trend Trades
- **Green line + Green zone** = strong trend building, look for pullback entries
- Yellow line crossing above 20 = early trend formation signal
- Catch trends early when ADX starts rising from below 20
3. Multi-Timeframe Analysis
- Use custom timeframe to align with higher timeframe trends
- *Example:* If 1H ADX shows green (strong trend), take breakout trades on 5m chart in same direction
- Increases win rate by trading with the bigger picture
4. Exit Signals
- When ADX turns red (falling), trend is weakening
- Consider tightening stops or taking profits
- Avoid entering new positions when ADX is declining
5. Quick Visual Confirmation
- Color coding eliminates need to analyze numbers
- Instant recognition: Green = go, Yellow = caution, Red = trend dying
- Faster decision-making during fast market moves
6. Scalping Strategy
- Set ADX length to 7-10 for sensitive signals
- Only scalp when ADX is rising (blue, yellow, or green)
- Exit when ADX turns red
7. Breakout Confirmation
- Wait for ADX to rise above 20 after a breakout
- Filters false breakouts in ranging markets
- Yellow or green color confirms momentum behind the move
Optimal Intraday Settings:
- Day Trading (5-15 min charts):** ADX Length = 10-14
- Scalping (1-5 min charts):** ADX Length = 7-10, watch custom 15m timeframe
- Swing Intraday (30min-1H charts):** ADX Length = 14-20
Simple Trading Rules:
✅ Trade: ADX rising + above 20 (yellow or green)
⚠️ Caution: ADX flat or just crossed 20
❌ Avoid:*ADX falling (red) or below 20
The key advantage is staying out of low-quality, choppy price action which is where most intraday traders lose money!
Kalman VWAP Filter [BackQuant]Kalman VWAP Filter
A precision-engineered price estimator that fuses Kalman filtering with the Volume-Weighted Average Price (VWAP) to create a smooth, adaptive representation of fair value. This hybrid model intelligently balances responsiveness and stability, tracking trend shifts with minimal noise while maintaining a statistically grounded link to volume distribution.
If you would like to see my original Kalman Filter, please find it here:
Concept overview
The Kalman VWAP Filter is built on two core ideas from quantitative finance and control theory:
Kalman filtering — a recursive Bayesian estimator used to infer the true underlying state of a noisy system (in this case, fair price).
VWAP anchoring — a dynamic reference that weights price by traded volume, representing where the majority of transactions have occurred.
By merging these concepts, the filter produces a line that behaves like a "smart moving average": smooth when noise is high, fast when markets trend, and self-adjusting based on both market structure and user-defined noise parameters.
How it works
Measurement blend : Combines the chosen Price Source (e.g., close or hlc3) with either a Session VWAP or a Rolling VWAP baseline. The VWAP Weight input controls how much the filter trusts traded volume versus price movement.
Kalman recursion : Each bar updates an internal "state estimate" using the Kalman gain, which determines how much to trust new observations vs. the prior state.
Noise parameters :
Process Noise controls agility — higher values make the filter more responsive but also more volatile.
Measurement Noise controls smoothness — higher values make it steadier but slower to adapt.
Filter order (N) : Defines how many parallel state estimates are used. Larger orders yield smoother output by layering multiple one-dimensional Kalman passes.
Final output : A refined price trajectory that captures VWAP-adjusted fair value while dynamically adjusting to real-time volatility and order flow.
Why this matters
Most smoothing techniques (EMA, SMA, Hull) trade off lag for smoothness. Kalman filtering, however, adaptively rebalances that tradeoff each bar using probabilistic weighting, allowing it to follow market state changes more efficiently. Anchoring it to VWAP integrates microstructure context — capturing where liquidity truly lies rather than only where price moves.
Use cases
Trend tracking : Color-coded candle painting highlights shifts in slope direction, revealing early trend transitions.
Fair value mapping : The line represents a continuously updated equilibrium price between raw price action and VWAP flow.
Adaptive moving average replacement : Outperforms static MAs in variable volatility regimes by self-adjusting smoothness.
Execution & reversion logic : When price diverges from the Kalman VWAP, it may indicate short-term imbalance or overextension relative to volume-adjusted fair value.
Cross-signal framework : Use with standard VWAP or other filters to identify convergence or divergence between liquidity-weighted and state-estimated prices.
Parameter guidance
Process Noise : 0.01–0.05 for swing traders, 0.1–0.2 for intraday scalping.
Measurement Noise : 2–5 for normal use, 8+ for very smooth tracking.
VWAP Weight : 0.2–0.4 balances both price and VWAP influence; 1.0 locks output directly to VWAP dynamics.
Filter Order (N) : 3–5 for reactive short-term filters; 8–10 for smoother institutional-style baselines.
Interpretation
When price > Kalman VWAP and slope is positive → bullish pressure; buyers dominate above fair value.
When price < Kalman VWAP and slope is negative → bearish pressure; sellers dominate below fair value.
Convergence of price and Kalman VWAP often signals equilibrium; strong divergence suggests imbalance.
Crosses between Kalman VWAP and the base VWAP can hint at shifts in short-term vs. long-term liquidity control.
Summary
The Kalman VWAP Filter blends statistical estimation with market microstructure awareness, offering a refined alternative to static smoothing indicators. It adapts in real time to volatility and order flow, helping traders visualize balance, transition, and momentum through a lens of probabilistic fair value rather than simple price averaging.
Ehlers Autocorrelation Periodogram (EACP)# EACP: Ehlers Autocorrelation Periodogram
## Overview and Purpose
Developed by John F. Ehlers (Technical Analysis of Stocks & Commodities, Sep 2016), the Ehlers Autocorrelation Periodogram (EACP) estimates the dominant market cycle by projecting normalized autocorrelation coefficients onto Fourier basis functions. The indicator blends a roofing filter (high-pass + Super Smoother) with a compact periodogram, yielding low-latency dominant cycle detection suitable for adaptive trading systems. Compared with Hilbert-based methods, the autocorrelation approach resists aliasing and maintains stability in noisy price data.
EACP answers a central question in cycle analysis: “What period currently dominates the market?” It prioritizes spectral power concentration, enabling downstream tools (adaptive moving averages, oscillators) to adjust responsively without the lag present in sliding-window techniques.
## Core Concepts
* **Roofing Filter:** High-pass plus Super Smoother combination removes low-frequency drift while limiting aliasing.
* **Pearson Autocorrelation:** Computes normalized lag correlation to remove amplitude bias.
* **Fourier Projection:** Sums cosine and sine terms of autocorrelation to approximate spectral energy.
* **Gain Normalization:** Automatic gain control prevents stale peaks from dominating power estimates.
* **Warmup Compensation:** Exponential correction guarantees valid output from the very first bar.
## Implementation Notes
**This is not a strict implementation of the TASC September 2016 specification.** It is a more advanced evolution combining the core 2016 concept with techniques Ehlers introduced later. The fundamental Wiener-Khinchin theorem (power spectral density = Fourier transform of autocorrelation) is correctly implemented, but key implementation details differ:
### Differences from Original 2016 TASC Article
1. **Dominant Cycle Calculation:**
- **2016 TASC:** Uses peak-finding to identify the period with maximum power
- **This Implementation:** Uses Center of Gravity (COG) weighted average over bins where power ≥ 0.5
- **Rationale:** COG provides smoother transitions and reduces susceptibility to noise spikes
2. **Roofing Filter:**
- **2016 TASC:** Simple first-order high-pass filter
- **This Implementation:** Canonical 2-pole high-pass with √2 factor followed by Super Smoother bandpass
- **Formula:** `hp := (1-α/2)²·(p-2p +p ) + 2(1-α)·hp - (1-α)²·hp `
- **Rationale:** Evolved filtering provides better attenuation and phase characteristics
3. **Normalized Power Reporting:**
- **2016 TASC:** Reports peak power across all periods
- **This Implementation:** Reports power specifically at the dominant period
- **Rationale:** Provides more meaningful correlation between dominant cycle strength and normalized power
4. **Automatic Gain Control (AGC):**
- Uses decay factor `K = 10^(-0.15/diff)` where `diff = maxPeriod - minPeriod`
- Ensures K < 1 for proper exponential decay of historical peaks
- Prevents stale peaks from dominating current power estimates
### Performance Characteristics
- **Complexity:** O(N²) where N = (maxPeriod - minPeriod)
- **Implementation:** Uses `var` arrays with native PineScript historical operator ` `
- **Warmup:** Exponential compensation (§2 pattern) ensures valid output from bar 1
### Related Implementations
This refined approach aligns with:
- TradingView TASC 2025.02 implementation by blackcat1402
- Modern Ehlers cycle analysis techniques post-2016
- Evolved filtering methods from *Cycle Analytics for Traders*
The code is mathematically sound and production-ready, representing a refined version of the autocorrelation periodogram concept rather than a literal translation of the 2016 article.
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Min Period | 8 | Lower bound of candidate cycles | Increase to ignore microstructure noise; decrease for scalping. |
| Max Period | 48 | Upper bound of candidate cycles | Increase for swing analysis; decrease for intraday focus. |
| Autocorrelation Length | 3 | Averaging window for Pearson correlation | Set to 0 to match lag, or enlarge for smoother spectra. |
| Enhance Resolution | true | Cubic emphasis to highlight peaks | Disable when a flatter spectrum is desired for diagnostics. |
**Pro Tip:** Keep `(maxPeriod - minPeriod)` ≤ 64 to control $O(n^2)$ inner loops and maintain responsiveness on lower timeframes.
## Calculation and Mathematical Foundation
**Explanation:**
1. Apply roofing filter to `source` using coefficients $\alpha_1$, $a_1$, $b_1$, $c_1$, $c_2$, $c_3$.
2. For each lag $L$ compute Pearson correlation $r_L$ over window $M$ (default $L$).
3. For each period $p$, project onto Fourier basis:
$C_p=\sum_{n=2}^{N} r_n \cos\left(\frac{2\pi n}{p}\right)$ and $S_p=\sum_{n=2}^{N} r_n \sin\left(\frac{2\pi n}{p}\right)$.
4. Power $P_p=C_p^2+S_p^2$, smoothed then normalized via adaptive peak tracking.
5. Dominant cycle $D=\frac{\sum p\,\tilde P_p}{\sum \tilde P_p}$ over bins where $\tilde P_p≥0.5$, warmup-compensated.
**Technical formula:**
```
Step 1: hp_t = ((1-α₁)/2)(src_t - src_{t-1}) + α₁ hp_{t-1}
Step 2: filt_t = c₁(hp_t + hp_{t-1})/2 + c₂ filt_{t-1} + c₃ filt_{t-2}
Step 3: r_L = (M Σxy - Σx Σy) / √
Step 4: P_p = (Σ_{n=2}^{N} r_n cos(2πn/p))² + (Σ_{n=2}^{N} r_n sin(2πn/p))²
Step 5: D = Σ_{p∈Ω} p · ĤP_p / Σ_{p∈Ω} ĤP_p with warmup compensation
```
> 🔍 **Technical Note:** Warmup uses $c = 1 / (1 - (1 - \alpha)^{k})$ to scale early-cycle estimates, preventing low values during initial bars.
## Interpretation Details
- **Primary Dominant Cycle:**
- High $D$ (e.g., > 30) implies slow regime; adaptive MAs should lengthen.
- Low $D$ (e.g., < 15) signals rapid oscillations; shorten lookback windows.
- **Normalized Power:**
- Values > 0.8 indicate strong cycle confidence; consider cyclical strategies.
- Values < 0.3 warn of flat spectra; favor trend or volatility approaches.
- **Regime Shifts:**
- Rapid drop in $D$ alongside rising power often precedes volatility expansion.
- Divergence between $D$ and price swings may highlight upcoming breakouts.
## Limitations and Considerations
- **Spectral Leakage:** Limited lag range can smear peaks during abrupt volatility shifts.
- **O(n²) Segment:** Although constrained (≤ 60 loops), wide period spans increase computation.
- **Stationarity Assumption:** Autocorrelation presumes quasi-stationary cycles; regime changes reduce accuracy.
- **Latency in Noise:** Even with roofing, extremely noisy assets may require higher `avgLength`.
- **Downtrend Bias:** Negative trends may clip high-pass output; ensure preprocessing retains signal.
## References
* Ehlers, J. F. (2016). “Past Market Cycles.” *Technical Analysis of Stocks & Commodities*, 34(9), 52-55.
* Thinkorswim Learning Center. “Ehlers Autocorrelation Periodogram.”
* Fab MacCallini. “autocorrPeriodogram.R.” GitHub repository.
* QuantStrat TradeR Blog. “Autocorrelation Periodogram for Adaptive Lookbacks.”
* TradingView Script by blackcat1402. “Ehlers Autocorrelation Periodogram (Updated).”
