Trend Tracer [AlgoAlpha]🟠 OVERVIEW
This tool builds a two-stage trend model that reacts to structure shifts while also showing how strong or weak the move is. It uses a mid-price band (from the highest high and lowest low over a lookback) and applies two Supertrend passes on top of it. The first pass smoothens the basis. The second pass refines that direction and produces the final trail used for signals. A gradient fill between the two trails uses RSI of price-to-trail distance to show when price is stretched or cooling off. The aim is to give traders a simple way to read trend alignment, pressure, and early turns without guessing.
🟠 CONCEPTS
The script starts with a mid-range basis. This is the average of the rolling highest high and lowest low. It acts as a stable structure reference instead of raw close or typical price. From there, two Supertrend layers are applied:
• The first Supertrend uses a shorter ATR period and lower factor. It reacts faster and sets the main regime.
• The second Supertrend uses a slightly longer ATR and higher factor. It filters noise, waits for confirmed continuation, and generates the signal line.
The interaction between these trails matters. The outer Supertrend provides context by defining the broader regime. The inner Supertrend provides timing by flipping earlier and marking possible shifts. The gradient fill uses RSI of (close − supertrend value) to display when price stretches away from the trail. This shows strength, exhaustion, or compression within the trend.
🟠 FEATURES
Bullish and bearish flip markers placed at recent highs/lows
Rejection signals off the trend tracer line
Alerts for bullish and bearish trend changes
🟠 USAGE
Setup : Add the script to your chart. Timeframe is flexible; lower timeframes show more flips while higher ones give cleaner swings. Adjust Length to change how wide the basis range is. Use the two ATR settings and factors to match the volatility of the market you trade.
Read the chart : When the refined trail (stv_) sits above price the regime is bearish; when below, it is bullish. The wide trail (stv) confirms the larger move. Watch the gradient fill: darker colors appear when price is stretched from the trail and lighter colors appear when the move is weakening. Flip markers ▲ or ▼ highlight the first clean shift of the refined trail.
Settings that matter : Increasing the Main Factor slows main-trend flips and filters chop. Increasing the Signal Factor delays the timing trail but reduces noise. Shortening Length makes the basis more reactive. ATR periods change how sensitive each Supertrend pass is to volatility.
Algoalpha
Change in State of Delivery CISD [AlgoAlpha]🟠 OVERVIEW
This script tracks how price “changes delivery” after failed attempts to push in one direction. It builds swing levels from pivots, watches for those levels to be wicked, and then checks if price delivers cleanly in the opposite direction. When the pattern meets the script’s tolerance rules, it marks a Change in State of Delivery (CISD). These CISD levels are drawn as origin lines and are used to spot shifts in intent, failed pushes, and continuation attempts. A CISD becomes stronger when it forms after opposing liquidity is swept within a defined lookback.
🟠 CONCEPTS
The script first defines structure using swing highs/lows. These levels act as potential liquidity points. When price wicks through a swing, the script registers a mitigation event. After this, it looks for a reversal-style candle sequence: a failed push, followed by a counter-move strong enough to pass a tolerance ratio. This ratio compares how far price expanded away from the failed attempt versus the counter-move that followed. If the ratio is high enough, this becomes a CISD. The idea is simple: liquidity interaction sets context , and the tolerance logic identifies actual intent . CISD levels and sweep markers combine these two ideas into a clean map of where delivery flipped.
🟠 FEATURES
Liquidity tracking: marks swing highs/lows and updates them until expiry
Liquidity sweep confirmation when CISD aligns with recent mitigations
Alert conditions for all key events: mitigations, CISDs, and strong CISDs
🟠 USAGE
Setup : Add the script to your chart. Use it on any timeframe where swing behavior matters. Set the Swing Period for how wide a pivot must be. Set Noise Filter to control how strict the CISD detection is. Liquidity Lookback defines how recent a wick must be to confirm a sweep.
Read the chart : Origin lines mark where the CISD began. A green line signals bullish intent; a red line signals bearish intent. ▲ and ▼ shapes show CISDs that form after liquidity is swept, these mark strong signals for potential entry. Swing dots show recent swing highs/lows. Candle colors follow the latest CISD trend.
Settings that matter : Increasing Swing Period produces fewer but stronger swings. Raising Noise Filter requires cleaner counter-moves and reduces false CISDs. Liquidity Lookback controls how strict the sweep confirmation is. Expiry Bars decides how long swing levels remain active.
Screener (SSA) [AlgoAlpha]🟠 OVERVIEW
This script is a multi-symbol screener that serves as a dashboard companion to the "Smart Signals Assistant (SSA)" indicator. Its purpose is to monitor the entire suite of SSA components—from the core signals to all confluence tools—across a customizable watchlist of up to 18 assets. By displaying the real-time status of each indicator in a single table, it allows traders to get a bird's-eye view of the market, quickly identify assets with strong trend confluence, and filter for high-probability setups without needing to switch charts.
The screener is designed to mirror the modularity of the main SSA indicator, allowing you to enable or disable components in the table to match your preferred trading dashboard.
🟠 CONCEPTS
The screener is built directly on the analytical framework of the Smart Signals Assistant, applying its complex, proprietary algorithms to each symbol in your watchlist and summarizing the results. The combination of these different analytical concepts is what gives the screener its utility, as it helps traders find opportunities where multiple, distinct strategies align.
Each column in the table represents a core trading concept:
Smart Signals: This is the primary signal engine, designed to identify potential entry points. It operates in different modes to capture both long-term swings and faster scalping opportunities.
Fair Value Trail (FVT): This component provides a dynamic, volatility-adjusted baseline for the trend. It acts as a form of dynamic support or resistance, helping to confirm the validity of a trend shown by the Smart Signals.
Trend Spine: This tool is designed to identify the underlying "backbone" of the market's trend. It filters out short-term price noise to provide a more stable, clear indication of the dominant market direction.
Trend Bias: This measures the strength and conviction behind a trend. It helps distinguish between a strong, accelerating move and a weak, decelerating one, adding a layer of momentum analysis.
Firmament Clouds: These are volatility-based bands that create dynamic overbought and oversold zones. They help identify when price is potentially overextended and due for a pullback or consolidation.
Trend-Range Classifier (TRC): A machine-learning model that analyzes market characteristics to classify the current environment as either "Trending" or "Ranging." This is crucial for helping traders apply the right strategy for the current conditions.
🟠 FEATURES
This screener organizes the complex data from the SSA indicator into a simple, color-coded table. Here is a breakdown of each column and its possible values:
Asset: Displays the ticker symbol for the asset being analyzed.
Smart Signals: Shows the latest signal from the core engine.
▲: A standard bullish signal has been detected.
▼: A standard bearish signal has been detected.
▲+: A strong bullish signal with higher conviction has been detected.
▼+: A strong bearish signal with higher conviction has been detected.
Fair Value Trail: Indicates the trend direction based on the volatility trail.
▲: The FVT is in a bullish trend (acting as dynamic support).
▼: The FVT is in a bearish trend (acting as dynamic resistance).
Trend Spine: Shows the direction of the core underlying trend.
▲: The underlying trend backbone is bullish.
▼: The underlying trend backbone is bearish.
Trend Bias: Measures the current momentum strength.
Strong▲: Strong and accelerating bullish momentum.
Weak▲: Bullish momentum exists but is weakening.
Strong▼: Strong and accelerating bearish momentum.
Weak▼: Bearish momentum exists but is weakening.
Firmament Clouds: Identifies overbought/oversold conditions relative to volatility.
Very Overbought / Overbought: Price is significantly extended above its recent range.
Very Oversold / Oversold: Price is significantly extended below its recent range.
Neutral: Price is trading within its normal volatility range.
Trend-Range Classifier: Displays the market state as determined by the ML model.
Trend: The market is in a trending environment, suitable for trend-following strategies.
Range: The market is in a ranging or consolidating environment, suitable for mean-reversion strategies.
Exit Signal Count: Tracks the number of take-profit signals that have occurred since the last primary Smart Signal.
0, 1, 2, 3...: A numerical count of exit signals. A higher number suggests a trend may be maturing or exhausting.
🟠 USAGE
The main purpose of the screener is to quickly identify assets where multiple components of the SSA system are in alignment, indicating a high-confluence trading opportunity.
1. Setup and Configuration:
Add the screener to your chart.
Go into the settings and populate the "Watchlist" group with the symbols you wish to monitor.
Ensure the settings for the components (Time Horizon, Signal Mode, etc.) are synchronized with the settings on your main SSA indicator for consistency.
2. Interpreting the Columns for Trading Decisions:
Start with the Big Picture (TRC): First, look at the "Trend-Range Classifier" column. If it shows "Trend," you should be looking for trend-following setups. If it shows "Range," you might avoid taking strong trend signals.
Establish Directional Bias (Spine & Bias): For trend-following, look for assets where the "Trend Spine" and "Trend Bias" agree. A "▲" in the Spine column combined with a "Strong▲" in the Bias column indicates a healthy and robust uptrend.
Time Your Entry (Smart Signals): Once you have an asset with a clear bias, watch the "Smart Signals" column for a fresh signal that aligns with that bias. A "▲+" signal appearing in an asset with a strong bullish bias across other columns is a high-confluence entry point.
Add Context (FVT & Clouds): Use the "Fair Value Trail" and "Firmament Clouds" to refine your entry. A buy signal is generally stronger if the FVT is also bullish ("▲") and the price is not in a "Very Overbought" state according to the clouds.
Manage the Trade (Exit Count): After entering a trade, keep an eye on the "Exit Signal Count." As the number increases, it serves as a warning that the trend is becoming extended and it might be time to take partial profits or tighten your stop-loss.
Paid script
Screener (ILPAC) [AlgoAlpha]🟠 OVERVIEW
This script is a powerful multi-symbol scanner designed to work as a companion to the "Institutional Liquidity & PA Concepts" (ILPAC) indicator. It allows you to monitor the key price action and liquidity signals from the ILPAC suite across a watchlist of up to 18 assets, all from a single dashboard. The primary goal of this tool is to provide a high-level market overview, enabling you to efficiently spot assets that are showing strong structural trends, interacting with key liquidity zones, or exhibiting signs of FOMO-driven volatility.
Instead of switching between dozens of charts, you can use this screener to quickly filter for assets that meet your specific trading criteria based on the advanced concepts of market structure, liquidity analysis, trend lines, and market sentiment.
🟠 CONCEPTS
The screener is built upon the core analytical engine of the "Institutional Liquidity & PA Concepts" indicator. It applies the proprietary algorithms of the ILPAC indicator to each symbol in your watchlist and presents the results in an easy-to-digest table. The concepts are combined to create a holistic view of the market.
Each column in the table is a window into a specific trading concept:
Market Structure: This is the foundation of price action analysis. The screener identifies the current market trend (bullish or bearish) by tracking swing highs and lows. It also flags critical events like a Break of Structure (BOS), which signals trend continuation, and a Change of Character (CHoCH), which suggests a potential trend reversal.
Liquidity Analysis: The screener analyzes order flow to determine where significant liquidity is resting. The "Liquidity Bias" column shows the net direction of this pressure, while the "Liquidity Event" column alerts you when price interacts with these key zones, either by forming a new one or mitigating an old one.
Trend Lines: This concept automates the classic technical analysis technique of drawing trend lines. The screener identifies significant swing points to form trend lines and then monitors them, alerting you to potential trend continuations or breakouts.
FOMO Bubbles: This concept measures crowd psychology by identifying sudden spikes in volume and price movement that are characteristic of "Fear of Missing Out." These signals can help identify potential trend exhaustion points or the start of a speculative rally.
By presenting these distinct but interconnected concepts together, the screener provides a multi-faceted view that allows traders to build a strong, confluence-based trading thesis.
🟠 FEATURES
This screener organizes a vast amount of data into a simple, color-coded table. Here is a breakdown of each column and the values you can expect to see:
Asset: Displays the ticker symbol for the asset being analyzed.
Market Structure: Shows the dominant trend based on swing highs and lows.
Bull: The asset is in a structural uptrend (making higher highs and higher lows).
Bear: The asset is in a structural downtrend (making lower highs and lower lows).
Detecting: The trend is neutral or a clear structure has not yet been established.
Structure Event: Flags the most recent significant market structure event.
Bull CHoCH: A bullish Change of Character, signaling a potential shift from a downtrend to an uptrend.
Bear CHoCH: A bearish Change of Character, signaling a potential shift from an uptrend to a downtrend.
Bull BOS: A bullish Break of Structure, confirming the continuation of an uptrend.
Bear BOS: A bearish Break of Structure, confirming the continuation of a downtrend.
–: No significant event has occurred recently.
Latest Swing Label: Identifies the most recently confirmed swing point.
HH: Higher High.
HL: Higher Low.
LH: Lower High.
LL: Lower Low.
–: No new swing point has been confirmed.
Liquidity Bias: Measures the net direction of liquidity and its relative strength.
▲ : A bullish liquidity bias, where the number indicates the strength.
▼ : A bearish liquidity bias, where the number indicates the strength.
Balanced: Liquidity is relatively balanced between buyers and sellers.
Liquidity Event: Indicates recent interactions with key liquidity zones.
New▲: A new bullish liquidity zone has just formed.
New▼: A new bearish liquidity zone has just formed.
Mit▲: Price has just tested (mitigated) a key bullish liquidity zone.
Mit▼: Price has just tested (mitigated) a key bearish liquidity zone.
–: No recent interaction.
Trend Line: Displays the status of automatically drawn trend lines.
Break▲: Price has broken above a key bearish trend line.
Break▼: Price has broken below a key bullish trend line.
Bull TL: Price is respecting an active bullish trend line.
Bear TL: Price is respecting an active bearish trend line.
–: No significant trend line is currently active.
FOMO: Detects sentiment-driven price moves of varying intensity.
Big▲/Med▲/Small▲: A bullish FOMO bubble has been detected (large, medium, or small).
Big▼/Med▼/Small▼: A bearish FOMO bubble has been detected (large, medium, or small).
–: No FOMO activity detected.
🟠 USAGE
The primary way to use this screener is to quickly scan your watchlist for assets that exhibit a confluence of bullish or bearish signals, which can significantly improve the probability of a trade.
1. Setup and Configuration:
Add the screener to your chart.
Open the settings and populate the "Watchlist" section with the symbols you want to track.
Fine-tune the input settings for each component (Market Structure, Liquidity, etc.) to match your preferred trading style. These settings will apply to all symbols in the table.
2. Interpreting the Columns for Trading Decisions:
Market Structure Columns: Use the first three structure columns to define your trading bias. For a high-probability long setup, you would look for an asset with a "Bull" structure, a recent "Bull BOS" event, and a "HL" as the latest swing point. This confirms the uptrend is healthy and ongoing.
Liquidity Columns: These are crucial for identifying key price levels. A strong "Liquidity Bias" can confirm your directional bias. A "Mit▲" (mitigation) event at a support level can be a powerful entry trigger, as it shows that institutional buy orders are defending that zone.
Trend Line Column: This is ideal for breakout traders. A "Break▲" signal can serve as an excellent entry confirmation, especially if the overall "Market Structure" is already "Bull".
FOMO Column: This column is best used for identifying potential exhaustion points. For instance, if you are in a long trade and a "Big▲" FOMO signal appears after a strong rally, it could be a sign that the move is overextended and it's a good time to consider taking profits.
Paid script
Screener (MC) [AlgoAlpha]🟠 OVERVIEW
This script is a multi-symbol scanner that works as a companion to the "Momentum Concepts" indicator. It provides a comprehensive dashboard view, allowing traders to monitor the momentum signals of up to 18 different assets in real-time from a single chart. The main purpose is to offer a bird's-eye view of the market, helping you quickly identify assets with strong momentum confluence or potential reversal opportunities without having to switch between different charts.
The screener displays the status of all key components from the Momentum Concepts indicator, including the Fast Oscillator, Scalper's Momentum, Momentum Impulse Oscillator, and Hidden Liquidity Flow, organizing them into a clear and easy-to-read table.
🟠 CONCEPTS
The core of this screener is built upon the analytical framework of the "Momentum Concepts" indicator, which evaluates market momentum across multiple layers: short-term, medium-term, and long-term. This screener applies those complex, proprietary calculations to each symbol in your watchlist and visualizes the current state of each component.
Each column in the table represents a specific aspect of momentum analysis:
Fast Oscillator Columns: These columns reflect the short-term momentum. They show the immediate trend direction, whether the asset is in an overbought or oversold condition, and flag high-probability events like divergences, reversals, or diminishing momentum.
Scalper's Momentum Column: This column gives insight into medium-term momentum. It distinguishes between strong, sustained moves and weakening, corrective moves, which is useful for gauging the health of a trend.
Momentum Impulse Column: This column represents the dominant, long-term trend bias. It helps you understand the underlying market regime (bullish, bearish, or consolidating) to align your trades with the bigger picture.
Hidden Liquidity Flow Column: This column provides a unique view into the market's underlying liquidity dynamics. It signals whether there is net buying or selling pressure and uses special coloring to highlight periods of unusually high liquidity activity, which often precedes volatile price movements.
By combining these perspectives, the screener justifies its utility by enabling traders to make more informed decisions based on multi-layered signal confluence.
🟠 FEATURES
This screener organizes momentum data into several key columns. Here is a breakdown of each column and its possible values:
Asset: Displays the symbol for the asset being analyzed in that row.
Fast Oscillator Trend: Shows the immediate, short-term momentum direction.
▲: Indicates a bullish short-term trend.
▼: Indicates a bearish short-term trend.
–: Indicates a neutral or transitional state.
Fast Oscillator Valuation: Measures whether the asset is in a short-term overbought or oversold state.
OB: Signals an "Overbought" condition, often associated with bullish exhaustion.
OS: Signals an "Oversold" condition, often associated with bearish exhaustion.
Neutral: The asset is trading in a neutral zone, neither overbought nor oversold.
Scalper's Momentum: Assesses the strength and direction of medium-term momentum.
Strong▲: Strong bullish momentum.
Weak▲: Bullish momentum exists but is weakening or corrective.
Strong▼: Strong bearish momentum.
Weak▼: Bearish momentum exists but is weakening or corrective.
–: Neutral or no clear medium-term momentum.
Momentum Impulse: Identifies the dominant, long-term trend bias. A colored background indicates that the momentum is in a strong "impulse" phase.
▲: Indicates a bullish long-term bias.
▼: Indicates a bearish long-term bias.
0: Indicates a neutral or ranging market condition.
Hidden Liquidity Flow: Tracks underlying buying and selling pressure. The background color highlights periods of unusual liquidity activity.
▲: Positive liquidity flow, suggesting net buying pressure.
▼: Negative liquidity flow, suggesting net selling pressure.
–: Neutral liquidity flow.
Dim. Momentum: Provides an early warning that short-term momentum is beginning to fade.
● (Bullish Color): Bullish momentum is weakening.
● (Bearish Color): Bearish momentum is weakening.
–: No diminishing momentum detected.
Divergence: Flags classic or hidden divergences between price and the Fast Oscillator.
Div▲: A bullish divergence has been detected.
Div▼: A bearish divergence has been detected.
–: No active divergence signal.
Reversal: Signals a potential reversal when the Fast Oscillator crosses its trend line from an overbought or oversold zone.
Rev▲: A bullish reversal signal has occurred.
Rev▼: A bearish reversal signal has occurred.
–: No active reversal signal.
🟠 USAGE
The primary function of this screener is to quickly identify trading opportunities and filter setups based on momentum confluence across your watchlist.
1. Setup and Configuration:
Add the indicator to your chart.
Go into the script settings and populate the "Watchlist" group with the symbols you wish to monitor.
Adjust the settings for the various momentum components (Fast Oscillator, Scalper's Momentum, etc.) to align with your trading strategy. These settings will be universally applied to all symbols in the screener.
2. Interpreting the Columns for Trading Decisions:
Momentum Impulse & Hidden Liquidity Flow: Use these columns to establish a directional bias. A bullish "▲" in both columns on an asset suggests a strong underlying uptrend with supportive buying pressure, making it a good candidate for long positions.
Scalper's Momentum: Use this for entry timing and trend health. A "Strong▲" reading can confirm the strength of an uptrend, while a shift to "Weak▲" might suggest it's time to tighten stops or look for an exit.
Fast Oscillator Trend & Valuation: These are best for precise entry triggers. For a "buy the dip" strategy in an uptrend, you could wait for the Fast Oscillator to show "OS" (Oversold) and then enter when the "Trend" column flips back to "▲".
Dim. Momentum: This is an excellent take-profit signal. If you are in a long position and a bullish-colored "●" appears, it's a warning that the upward move is losing steam, and you might consider closing your trade.
Divergence & Reversal: These columns are for identifying potential turning points. A "Div▲" or "Rev▲" signal is a strong alert that a downtrend might be ending, making the asset a prime candidate to watch for a long entry.
3. Finding High-Probability Setups:
Trend Confluence: Look for assets where multiple components show alignment. For example, an ideal long setup might show a bullish "Momentum Impulse" (▲), a "Strong▲" reading in "Scalper's Momentum," and a bullish trend in the "Fast Oscillator." This indicates that the long-term, medium-term, and short-term momentums are all in agreement.
Reversal and Exhaustion: Use the "Divergence" and "Reversal" columns to spot potential turning points. A "Div▲" signal appearing in an asset that is in an oversold "Fast Oscillator Valuation" zone can be a strong indication of an upcoming bounce.
Paid script
Liquidation Reversal Signals [AlgoAlpha]🟠 OVERVIEW
This tool detects potential liquidation-driven reversals by combining z-score analysis of up/down volume with the classic Supertrend. It watches for abnormal surges in directional volume (on a lower timeframe) and links them to trend flips on the main chart. When both align within a short window, it flags a probable reversal caused by forced liquidations. The goal is to help traders identify exhaustion points where aggressive liquidation moves may mark the end of a trend leg.
🟠 CONCEPTS
The logic revolves around Z-score normalization of up and down volume to locate statistical extremes. When up-volume z-scores exceed a threshold during a bearish Supertrend, it implies trapped shorts being squeezed; the opposite applies for long liquidations. The script tracks these liquidation spikes and monitors whether a Supertrend regime change follows soon after. If confirmed within the allowed timeout, a colored signal marks the event.
In essence:
Z-score outliers = potential forced liquidations.
Supertrend = structural regime context.
Combined = statistically confirmed reversal signals, not random flips.
This pairing reduces false positives by ensuring that both volatility structure and order-flow extremes agree before flagging a reversal.
🟠 FEATURES
Z-score detection for liquidation spikes with adjustable lookback and threshold.
Confirmation logic linking liquidations to Supertrend flips.
Alerts for liquidation spikes and confirmed reversal starts.
On-chart “No Volume” warning to avoid misreads on illiquid assets.
🟠 USAGE
Setup : Add the script to your main chart. Choose a lower timeframe (default 15m) to capture more granular liquidation flows. Adjust Z-Score Length to control how far back the script measures normal behavior and Threshold to decide what counts as extreme. Keep Timeout Bars low (e.g. 20–50) for faster reversals, or higher for slower markets.
Read the chart :
• Circles appear below bars when long liquidations occur; above bars for short liquidations.
• A Supertrend flip with a recent liquidation spike will display an arrow and color shift.
• Fills between candles and trend lines show which side dominates: green for bullish reversal, red for bearish.
• Candle color fades based on the magnitude of liquidation pressure.
Settings that matter :
• Z-Score Length : Longer smooths noise but delays signal; shorter reacts faster.
• Z-Score Threshold : Higher means only extreme liquidations trigger; lower finds smaller squeezes.
• Timeout Bars : Defines how long after a liquidation the Supertrend flip remains valid.
• Lower Timeframe : Determines the precision of volume readings; too low may increase noise.
Volume Sentiment Breakout Channels [AlgoAlpha]🟠 OVERVIEW
This tool visualizes breakout zones based on volume sentiment within dynamic price channels . It identifies high-impact consolidation areas, quantifies buy/sell dominance inside those zones, and then displays real-time shifts in sentiment strength. When the market breaks above or below these sentiment-weighted channels, traders can interpret the event as a change in conviction, not just a technical breakout.
🟠 CONCEPTS
The script builds on two layers of logic:
Channel Detection : A volatility-based algorithm locates price compression areas using normalized highs and lows over a defined lookback. These “boxes” mark accumulation or distribution ranges.
Volume Sentiment Profiling : Each channel is internally divided into small bins, where volume is aggregated and signed by candle direction. This produces a granular sentiment map showing which levels are dominated by buyers or sellers.
When a breakout occurs, the script clears the previous box and forms a new one, letting traders visually track transitions between phases of control. The colored gradients and text updates continuously reflect the internal bias—green for net-buying, red for net-selling—so you can see conviction strength at a glance.
🟠 FEATURES
Volume-weighted sentiment map inside each box, with gradient color intensity proportional to participation.
Dynamic text display of current and overall sentiment within each channel.
Real-time trail lines to show active bullish/bearish trend extensions after breakout.
🟠 USAGE
Setup : Add the script to your chart and enable Strong Closes Only if you prefer cleaner breakouts. Use shorter normalization length (e.g., 50–80) for fast markets; longer (100–200) for smoother transitions.
Read Signals : Transparent boxes mark active sentiment channels. Green gradients show buy-side dominance, red shows sell-side. The middle dashed line is the equilibrium of the channel. “▲” appears when price breaks upward, “▼” when it breaks downward.
Understanding Sentiment : The sentiment profile can be used to show the probability of the price moving up or down at respective price levels.
Smart Money Volume Activity [AlgoAlpha]🟠 OVERVIEW
This tool visualizes how Smart Money and Retail participants behave through lower-timeframe volume analysis. It detects volume spikes far beyond normal activity, classifies them as institutional or retail, and projects those zones as reactive levels. The script updates dynamically with each bar, showing when large players enter while tracking whether those events remain profitable. Each event is drawn as a horizontal line with bubble markers and summarized in a live P/L table comparing Smart Money versus Retail.
🟠 CONCEPTS
The core logic uses Z-score normalization on lower-timeframe volumes (like 5m inside a 1h chart). This lets the script detect statistically extreme bursts of buying or selling activity. It classifies each detected event as:
Smart Money — volume inside the candle body (suggesting hidden accumulation or distribution)
Retail — volume closing at bar extremes (suggesting chase entries or panic exits)
When new events appear, the script plots them as horizontal levels that persist until price interacts again. Each level acts as a potential reaction zone or liquidity footprint. The integrated P/L table then measures which class (Retail or Smart Money) is currently “winning” — comparing cumulative profitable versus losing volume.
🟠 FEATURES
Classifies flows into Smart Money or Retail based on candle-body context.
Displays live P/L comparison table for Smart vs Retail performance.
Alerts for each detected Smart or Retail buy/sell event.
🟠 USAGE
Setup : Add the script to any chart. Set Lower Timeframe Value (e.g., “5” for 5m) smaller than your main chart timeframe. The Period input controls how many bars are analyzed for the Z-score baseline. The Threshold (|Z|) decides how extreme a volume must be to plot a level.
Read the chart : Horizontal lines mark where heavy Smart or Retail volume occurred. Bright bubbles show the strongest events — their size reflects Z-score intensity. The on-chart table updates live: green cells show profitable flows, red cells show losing flows. A dominant green Smart Money row suggests institutions are currently controlling price.
See what others are doing :
Settings that matter : Raising Threshold (|Z|) filters noise, showing only large players. Increasing Period smooths results but reacts slower to new bursts. Use Show = “Both” for full comparison or isolate “Smart Money” / “Retail” to focus on one class.
Inversion Fair Value Gap Signals [AlgoAlpha]🟠 OVERVIEW
This script is a custom signal tool called Inversion Fair Value Gap Signals (IFVG) , designed to detect, track, and visualize fair value gaps (FVGs) and their inversions directly on price charts. It identifies bullish and bearish imbalances, monitors when these zones are mitigated or rejected, and extends them until resolution or expiration. What makes this script original is the inclusion of inversion logic—when a gap is filled, the area flips into an opposite "inversion fair value gap," creating potential reversal or continuation zones that give traders additional context beyond classic FVG analysis.
🟠 CONCEPTS
The script builds on the Smart Money Concepts (SMC) principle of fair value gaps, where inefficiencies form when price moves too quickly in one direction. Detection requires a three-bar sequence: a strong up or down move that leaves untraded price between bar highs and lows. To refine reliability, the script adds an ATR-based size filter and prevents overlap between zones. Once created, gaps are tracked in arrays until mitigation (price closing back into the gap), expiration, or transformation into an inversion zone. Inversions act as polarity flips, where bullish gaps become bearish resistance and bearish gaps become bullish support. Lower-timeframe volume data is also displayed inside zones to highlight whether buying or selling pressure dominated during gap creation.
🟠 FEATURES
Automatic detection of bullish and bearish FVGs with ATR-based thresholding.
Inversion logic: mitigated gaps flip into opposite-colored IFVG zones.
Volume text overlay inside each zone showing up vs down volume.
Visual markers (△/▽ for FVG, ▲/▼ for IFVG) when price exits a zone without mitigation.
🟠 USAGE
Apply the indicator to any chart and enable/disable bullish or bearish FVG detection depending on your focus. Use the colored gap zones as areas of interest: bullish gaps suggest possible continuation to the upside until mitigated, while bearish gaps suggest continuation down. When a gap flips into an inversion zone, treat it as potential support/resistance—bullish IFVGs below price may act as demand, while bearish IFVGs above price may act as supply. Watch the embedded up/down volume data to gauge the strength of participants during gap formation. Use the △/▽ and ▲/▼ markers to spot when price rejects gaps or inversions without filling them, which can indicate strong trending momentum. For practical use, combine alerts with your trade plan to track when new gaps form, when old ones are resolved, or when key zones flip into inversions, helping you align entries, targets, or reversals with institutional order flow logic.
High Probability Order Blocks [AlgoAlpha]🟠 OVERVIEW
This script detects and visualizes high-probability order blocks by combining a volatility-based z-score trigger with a statistical survival model inspired by Kaplan-Meier estimation. It builds and manages bullish and bearish order blocks dynamically on the chart, displays live survival probabilities per block, and plots optional rejection signals. What makes this tool unique is its use of historical mitigation behavior to estimate and plot how likely each zone is to persist, offering traders a probabilistic perspective on order block strength—something rarely seen in retail indicators.
🟠 CONCEPTS
Order blocks are regions of strong institutional interest, often marked by large imbalances between buying and selling. This script identifies those areas using z-score thresholds on directional distance (up or down candles), detecting statistically significant moves that signal potential smart money footprints. A bullish block is drawn when a strong up-move (zUp > 4) follows a down candle, and vice versa for bearish blocks. Over time, each block is evaluated: if price “mitigates” it (i.e., closes cleanly past the opposite side and confirmed with a 1 bar delay), it’s considered resolved and logged. These resolved blocks then inform a Kaplan-Meier-like survival curve, estimating the likelihood that future blocks of a given age will remain unbroken. The indicator then draws a probability curve for each side (bull/bear), updating it in real time.
🟠 FEATURES
Live label inside each block showing survival probability or “N.E.D.” if insufficient data.
Kaplan-Meier survival curves drawn directly on the chart to show estimated strength decay.
Rejection markers (▲ ▼) if price bounces cleanly off an active order block.
Alerts for zone creation and rejection signals, supporting rule-based trading workflows.
🟠 USAGE
Read the label inside each block for Age | Survival% (or N.E.D. if there aren’t enough samples yet); higher survival % suggests blocks of that age have historically lasted longer.
Use the right-side survival curves to gauge how probability decays with age for bull vs bear blocks, and align entries with the side showing stronger survival at current age.
Treat ▲ (bullish rejection) and ▼ (bearish rejection) as optional confluence when price tests a boundary and fails to break.
Turn on alerts for “Bullish Zone Created,” “Bearish Zone Created,” and rejection signals so you don’t need to watch constantly.
If your chart gets crowded, enable Prevent Overlap ; tune Max Box Age to your timeframe; and adjust KM Training Window / Minimum Samples to trade off responsiveness vs stability.
Reverse RSI Signals [AlgoAlpha]🟠 OVERVIEW
This script introduces the Reverse RSI Signals system, an original approach that inverts traditional RSI values back into price levels and then overlays them directly on the chart as dynamic bands. Instead of showing RSI in a subwindow, the script calculates the exact price thresholds that correspond to common RSI levels (30/70/50) and displays them as upper, lower, and midline bands. These are further enhanced with an adaptive Supertrend filter and divergence detection, allowing traders to see overbought/oversold zones translated into actionable price ranges and trend signals. The script combines concepts of RSI inversion, volatility envelopes, and divergence tracking to provide a context-driven tool for spotting reversals and regime shifts.
🟠 CONCEPTS
The script relies on inverting RSI math: by solving for the price that would yield a given RSI level, it generates real chart levels tied to oscillator conditions. These RSI-derived price bands act like support/resistance, adapting each bar as RSI changes. On top of this, a Supertrend built around the RSI midline introduces directional bias, switching regimes when the midline is breached. Regular bullish and bearish divergences are detected by comparing RSI pivots against price pivots, highlighting early reversal conditions. This layered approach means the indicator is not just RSI on price but a hybrid of oscillator translation, volatility-tracking midline envelopes, and divergence analysis.
🟠 FEATURES
Inverted RSI bands: upper (70), lower (30), and midline (50), smoothed with EMA for noise reduction.
Supertrend overlay on the RSI midline to confirm regime direction (bullish or bearish).
Gradient-filled zones between outer and inner RSI bands to visualize proximity and exhaustion.
Non-repainting bullish and bearish divergence markers plotted directly on chart highs/lows.
🟠 USAGE
Apply the indicator to any chart and use the plotted RSI price bands as adaptive support/resistance. The midline defines equilibrium, while upper and lower bands represent classic RSI thresholds translated into real price action. In bullish regimes (green candles), long trades are stronger when price approaches or bounces from the lower band; in bearish regimes (red candles), shorts are favored near the upper band. Divergence markers (▲ for bullish, ▼ for bearish) flag potential reversal points early. Traders can combine the band proximity, divergence alerts, and Supertrend context to time entries, exits, or to refine ongoing trend trades. Adjust smoothing and Supertrend ATR settings to match the volatility of the instrument being analyzed.
Backtest - Strategy Builder [AlgoAlpha]🟠 OVERVIEW
This script by AlgoAlpha is a modular Strategy Builder designed to let traders test custom trade entry and exit logic on TradingView without writing their own Pine code. It acts as a framework where users can connect multiple external signals, chain them in sequences, and run backtests with built-in leverage, margin, and risk controls. Its main strength is flexibility—you can define up to five sequential steps for entry and exit conditions on both long and short sides, with logic connectors (AND/OR) controlling how conditions combine. This lets you test complex multi-step confirmation workflows in a controlled, visual backtesting environment.
🟠 CONCEPTS
The system works by linking external signals —these can be values from other indicators, and/or custom sources—to conditional checks like “greater than,” “less than,” or “crossover.” You can stack these checks into steps , where all conditions in a step must pass before the sequence moves to the next. This creates a chain of logic that must be completed before a trade triggers. On execution, the strategy sizes positions according to your chosen leverage mode ( Cross or Isolated ) and allocation method ( Percent of equity or absolute USD value]). Liquidation prices are simulated for both modes, allowing realistic margin behaviour in testing. The script also tracks performance metrics like Sharpe, Sortino, profit factor, drawdown, and win rate in real time.
🟠 FEATURES
Up to 5 sequential steps for both long and short entries, each with multiple conditions linked by AND/OR logic.
Two leverage modes ( Cross and Isolated ) with independent long/short leverage multipliers.
Separate multi-step exit triggers for longs and shorts, with optional TP/SL levels or opposite-side triggers for flipping positions.
Position sizing by equity percent or fixed USD amount, applied before leverage.
Realistic liquidation price simulation for margin testing.
Built-in trade gating and validation—prevents trades if configuration rules aren’t met (e.g., no exit defined for an active side).
Full performance dashboard table showing live strategy status, warnings, and metrics.
Configurable bar coloring based on position side and TP/SL level drawing on chart.
Integration with TradingView's strategy backtester, allowing users to view more detailed metrics and test the strategy over custom time horizons.
🟠 USAGE
Add the strategy to your chart. In the settings, under Master Settings , enable longs/shorts, select leverage mode, set leverage multipliers, and define position sizing. Then, configure your Long Trigger and Short Trigger groups: turn on conditions, pick which external signal they reference, choose the comparison type, and assign them to a sequence step. For exits, use the corresponding Exit Long Trigger and Exit Short Trigger groups, with the option to link exits to opposite-side entries for auto-flips. You can also enable TP and/or SL exits with custom sources for the TP/SL levels. Once set, the strategy will simulate trades, show performance stats in the on-chart table, and highlight any configuration issues before execution. This makes it suitable for testing both simple single-signal systems and complex, multi-filtered strategies under realistic leverage and margin constraints.
🟠 EXAMPLE
The backtester on its own does not contain any indicator calculation; it requires input from external indicators to function. In this example, we'll be using AlgoAlpha's Smart Signals Assistant indicator to demonstrate how to build a strategy using this script.
We first define the conditions beforehand:
Entry :
Longs – SSA Bullish signal (strong OR weak)
Shorts – SSA Bearish signal (strong OR weak)
Exit
Longs/Shorts: (TP/SL hit OR opposing signal fires)
Other Parameters (⚠️Example only, tune this based on proper risk management and settings)
Long Leverage: default (3x)
Short Leverage: default (3x)
Position Size: default (10% of equity)
Steps
Load up the required indicators (in this example, the Smart Signals Assistant).
Ensure the required plots are being output by the indicator properly (signals and TP/SL levels are being plotted).
Open the Strategy Builder settings and scroll down to "CONDITION SETUP"; input the signals from the external indicator.
Configure the exit conditions, add in the TP/SL levels from the external indicator, and add an additional exit condition → {{Opposite Direction}} Entry Trigger.
After configuring the entry and exit conditions, the strategy should now be running. You can view information on the strategy in TradingView's backtesting report and also in the Strategy Builder's information table (default top right corner).
It is important to note that the strategy provided above is just an example, and the complexity of possible strategies stretches beyond what was shown in this short demonstration. Always incorporate proper risk management and ensure thorough testing before trading with live capital.
Paid script
Zero Lag Liquidity [AlgoAlpha]🟠 OVERVIEW
This script plots liquidity zones with zero lag using lower-timeframe wick profiles and high-volume wicks to mark key price reactions. It’s called Zero Lag Liquidity because it captures significant liquidity imbalances in real time by processing lower-TF price-volume distributions directly inside the wick of abnormal candles. The tool builds a volume histogram inside long upper/lower wicks, then calculates a local Point of Control (POC) to mark the price where most volume occurred. These levels act as visual liquidity zones, which can trigger labels, break signals, and trend detection depending on price interaction.
🟠 CONCEPTS
The core concept relies on identifying high-volume candles with unusually long wicks—often a sign of opposing liquidity. When a large upper or lower wick appears with a strong volume spike, the script builds a histogram of lower-timeframe closes and volumes inside that wick. It bins the wick into segments, sums volume per bin, and finds the POC. This POC becomes the liquidity level. The script then dynamically tracks whether price breaks above or rejects off these levels, adjusts the active trend regime accordingly, and highlights bars to help users spot continuation or reversal behavior. The logic avoids repainting or subjective interpretation by using fixed thresholds and lower-TF price action.
🟠 FEATURES
Dynamic liquidity levels rendered at POC of significant wicks, colored by bullish/bearish direction.
Break detection that removes levels once price decisively crosses them twice in the same direction.
Rejection detection that plots ▲/▼ markers when price bounces off levels intrabar.
Volume labels for each level, shown either as raw volume or percentage of total level volume.
Candle coloring based on trend direction (break-dominant).
🟠 USAGE
Use this indicator to track where liquidity has most likely entered the market via abnormal wick events. When a long wick forms with high volume, the script looks inside it (using your chosen lower timeframe) and marks the most traded price within it. These levels can serve as expected reversal or breakout zones. Rejections are marked with small arrows, while breaks trigger trend shifts and remove the level. You can toggle trend coloring to see directional bias after a breakout. Use the wick multiplier to control how selective the detector is (higher = stricter). Alerts and label modes help customize the signal for different asset types and chart styles.
Smart Money Breakout Channels [AlgoAlpha]🟠 OVERVIEW
This script draws breakout detection zones called “Smart Money Breakout Channels” based on volatility-normalized price movement and visualizes them as dynamic boxes with volume overlays. It identifies temporary accumulation or distribution ranges using a custom normalized volatility metric and tracks when price breaks out of those zones—either upward or downward. Each channel represents a structured range where smart money may be active, helping traders anticipate key breakouts with added context from volume delta, up/down volume, and a visual gradient gauge for momentum bias.
🟠 CONCEPTS
The script calculates normalized price volatility by measuring the standard deviation of price mapped to a scale using the highest and lowest prices over a set lookback period. When normalized volatility reaches a local low and flips upward, a boxed channel is drawn between the highest and lowest prices in that zone. These boxes persist until price breaks out, either with a strong candle close (configurable) or by touching the boundary. Volume analysis enhances interpretation by rendering delta bars inside the box, showing volume distribution during the channel. Additionally, a real-time visual “gauge” shows where volume delta sits within the channel range, helping users spot pressure imbalances.
🟠 FEATURES
Automatic detection and drawing of breakout channels based on volatility-normalized price pivots.
Optional nested channels to allow multiple simultaneous zones or a clean single-zone view.
Gradient-filled volume gauge with dynamic pointer to show current delta pressure within the box.
Three volume visualization modes: raw volume, comparative up/down volume, and delta.
Alerts for new channel creation and confirmed bullish or bearish breakouts.
🟠 USAGE
Apply the indicator to any chart. Wait for a new breakout box to form—this occurs when volatility behavior shifts and a stable range emerges. Once a box appears, monitor price relative to its boundaries. A breakout above suggests bullish continuation, below suggests bearish continuation; signals are stronger when “Strong Closes Only” is enabled.
Watch the internal volume candles to understand where buy/sell pressure is concentrated during the box. Use the gauge on the right to interpret whether net pressure is building upward or downward before breakout to anticipate the direction.
Use alerts to catch breakout events without needing to monitor the chart constantly 🚨.
Stochastic Z-Score [AlgoAlpha]🟠 OVERVIEW
This indicator is a custom-built oscillator called the Stochastic Z-Score , which blends a volatility-normalized Z-Score with stochastic principles and smooths it using a Hull Moving Average (HMA). It transforms raw price deviations into a normalized momentum structure, then processes that through a stochastic function to better identify extreme moves. A secondary long-term momentum component is also included using an ALMA smoother. The result is a responsive oscillator that reacts to sharp imbalances while remaining stable in sideways conditions. Colored histograms, dynamic oscillator bands, and reversal labels help users visually assess shifts in momentum and identify potential turning points.
🟠 CONCEPTS
The Z-Score is calculated by comparing price to its mean and dividing by its standard deviation—this normalizes movement and highlights how far current price has stretched from typical values. This Z-Score is then passed through a stochastic function, which further refines the signal into a bounded range for easier interpretation. To reduce noise, a Hull Moving Average is applied. A separate long-term trend filter based on the ALMA of the Z-Score helps determine broader context, filtering out short-term traps. Zones are mapped with thresholds at ±2 and ±2.5 to distinguish regular momentum from extreme exhaustion. The tool is built to adapt across timeframes and assets.
🟠 FEATURES
Z-Score histogram with gradient color to visualize deviation intensity (optional toggle).
Primary oscillator line (smoothed stochastic Z-Score) with adaptive coloring based on momentum direction.
Dynamic bands at ±2 and ±2.5 to represent regular vs extreme momentum zones.
Long-term momentum line (ALMA) with contextual coloring to separate trend phases.
Automatic reversal markers when short-term crosses occur at extremes with supporting long-term momentum.
Built-in alerts for oscillator direction changes, zero-line crosses, overbought/oversold entries, and trend confirmation.
🟠 USAGE
Use this script to track momentum shifts and identify potential reversal areas. When the oscillator is rising and crosses above the previous value—especially from deeply negative zones (below -2)—and the ALMA is also above zero, this suggests bullish reversal conditions. The opposite holds for bearish setups. Reversal labels ("▲" and "▼") appear only when both short- and long-term conditions align. The ±2 and ±2.5 thresholds act as momentum warning zones; values inside are typical trends, while those beyond suggest exhaustion or extremes. Adjust the length input to match the asset’s volatility. Enable the histogram to explore underlying raw Z-Score movements. Alerts can be configured to notify key changes in momentum or zone entries.
Fair Value Gap Profiles [AlgoAlpha]🟠 OVERVIEW
This script draws and manages Fair Value Gap (FVG) zones by detecting unfilled gaps in price action and then augmenting them with intra-gap volume profiles from a lower timeframe. It is designed to help traders find potential areas where price may return to fill liquidity voids, and to provide extra detail about volume distribution inside each gap to assess strength and likely mitigation. The script automatically tracks each gap, updates its state over time, and can show which gaps are still unfilled or have been mitigated.
🟠 CONCEPTS
A Fair Value Gap is a zone between candles where no trades occurred, often seen as an inefficiency that price later revisits. The script checks each bar to see if a bullish (low above 2-bars-ago high) or bearish (high below 2-bars-ago low) gap has formed, and measures whether the gap’s size exceeds a threshold defined by a volatility-adjusted multiplier of past gap widths (to only detect significantly large gaps). Once a qualified gap is found, it gets recorded and visualized with a box that can stretch forward in time until filled. To add more context, a mini volume profile is built from a lower timeframe’s price and volume data, showing how volume is distributed inside the gap. The lowest-volume subzone is also highlighted using a sliding window scan method to visualise the true gap (area with least trading activity)
🟠 FEATURES
Visual gap boxes that appear automatically when bullish or bearish fair value gaps are detected on the chart.
Color-coded zones showing bullish gaps in one color and bearish gaps in another so you can easily see which side the gap favors.
Volume profile histograms plotted inside each gap using data from a lower timeframe, helping you see where volume concentrated inside the gap area.
Highlight of the lowest-volume subzone within each gap so you can spot areas price may target when filling the gap.
Dynamic extension of the gap boxes across the chart until price comes back and fills them, marking them as mitigated.
Customizable colors and transparency settings for gap boxes, profiles, and low-volume highlights to match your chart style.
Alerts that notify you when a new gap is created or when price fills an existing gap.
🟠 USAGE
This indicator helps you find and track unfilled price gaps that often act as magnets for price to revisit. You can use it to spot areas where liquidity may rest and plan entries or exits around these zones.
The colored gap boxes show you exactly where a fair value gap starts and ends, so you can anticipate potential pullbacks or continuations when price approaches them.
The intra-gap volume profile lets you gauge whether the gap was created on strong or thin participation, which can help judge how likely it is to be filled. The highlighted lowest-volume subzone shows where price might accelerate once inside the gap.
Traders often look for entries when price returns to a gap, aiming for a reaction or reversal in that area. You can also combine the mitigation alerts with your trade management to track when gaps have been closed and adjust your bias accordingly. Overall, the tool gives a clear visual reference for imbalance zones that can help structure trades around supply and demand dynamics.
Machine Learning Key Levels [AlgoAlpha]🟠 OVERVIEW
This script plots Machine Learning Key Levels on your chart by detecting historical pivot points and grouping them using agglomerative clustering to highlight price levels with the most past reactions. It combines a pivot detection, hierarchical clustering logic, and an optional silhouette method to automatically select the optimal number of key levels, giving you an adaptive way to visualize price zones where activity concentrated over time.
🟠 CONCEPTS
Agglomerative clustering is a bottom-up method that starts by treating each pivot as its own cluster, then repeatedly merges the two closest clusters based on the average distance between their members until only the desired number of clusters remain. This process creates a hierarchy of groupings that can flexibly describe patterns in how price reacts around certain levels. This offers an advantage over K-means clustering, since the number of clusters does not need to be predefined. In this script, it uses an average linkage approach, where distance between clusters is computed as the average pairwise distance of all contained points.
The script finds pivot highs and lows over a set lookback period and saves them in a buffer controlled by the Pivot Memory setting. When there are at least two pivots, it groups them using agglomerative clustering: it starts with each pivot as its own group and keeps merging the closest pairs based on their average distance until the desired number of clusters is left. This number can be fixed or chosen automatically with the silhouette method, which checks how well each point fits in its cluster compared to others (higher scores mean cleaner separation). Once clustering finishes, the script takes the average price of each cluster to create key levels, sorts them, and draws horizontal lines with labels and colors showing their strength. A metrics table can also display details about the clusters to help you understand how the levels were calculated.
🟠 FEATURES
Agglomerative clustering engine with average linkage to merge pivots into level groups.
Dynamic lines showing each cluster’s price level for clarity.
Labels indicating level strength either as percent of all pivots or raw counts.
A metrics table displaying pivot count, cluster count, silhouette score, and cluster size data.
Optional silhouette-based auto-selection of cluster count to adaptively find the best fit.
🟠 USAGE
Add the indicator to any chart. Choose how far back to detect pivots using Pivot Length and set Pivot Memory to control how many are kept for clustering (more pivots give smoother levels but can slow performance). If you want the script to pick the number of levels automatically, enable Auto No. Levels ; otherwise, set Number of Levels . The colored horizontal lines represent the calculated key levels, and circles show where pivots occurred colored by which cluster they belong to. The labels beside each level indicate its strength, so you can see which levels are supported by more pivots. If Show Metrics Table is enabled, you will see statistics about the clustering in the corner you selected. Use this tool to spot areas where price often reacts and to plan entries or exits around levels that have been significant over time. Adjust settings to better match volatility and history depth of your instrument.
Momentum Trail Oscillator [AlgoAlpha]🟠 OVERVIEW
This script builds a Momentum Trail Oscillator designed to measure directional momentum strength and dynamically track shifts in trend bias using a combination of smoothed price change calculations and adaptive trailing bands. The oscillator aims to help traders visualize when momentum is expanding or contracting and to identify transitions between bullish and bearish conditions.
🟠 CONCEPTS
The core idea combines two methods. First, the script calculates a normalized momentum measure by smoothing price changes relative to their absolute values, which creates a bounded oscillator that highlights whether moves are directional or choppy. Second, it uses a trailing band mechanism inspired by volatility stops, where bands adapt to the oscillator’s volatility, adjusting the thresholds that define a shift in directional bias. This dual approach seeks to address both the magnitude and persistence of momentum, reducing false signals in ranging markets.
🟠 FEATURES
The momentum calculation applies Hull Moving Averages and double EMA smoothing to price changes, producing a smooth, responsive oscillator.
The trailing bands are derived by offsetting a weighted moving average of the oscillator by a multiple of recent momentum volatility. A directional state variable tracks whether the oscillator is above or below the bands, updating when the momentum crosses these dynamic thresholds.
Overbought and oversold zones are visually marked between fixed levels (+30/+40 and -30/-40), with color fills to highlight when momentum is in extreme areas. The script plots signals on both the oscillator pane and optionally overlays markers on the main price chart for clarity.
🟠 USAGE
To use the indicator, apply it to any symbol and timeframe. The “Oscillator Length” controls how sensitive the momentum line is to recent price changes—lower values react faster, higher values smooth out noise. The “Trail Multiplier” sets how far the adaptive bands sit from the oscillator mid-line, which affects how often trend state changes occur. When the momentum line rises into the upper filled area and then crosses back below +40, it signals potential overbought exhaustion. The opposite applies for the oversold zone below -40. The plotted trailing bands switch visibility depending on the current directional state: when momentum is trending up, the lower band acts as the active trailing stop, and when trending down, the upper band becomes active. Trend changes are marked with circular symbols when the direction variable flips, and optional overlay arrows appear on the price chart to highlight overbought or oversold reversals. Traders can combine these signals with their own price action or volume analysis to confirm entries or exits.
Trend Flow Trail [AlgoAlpha]OVERVIEW
This script overlays a custom hybrid indicator called the Money Flow Trail which combines a volatility-based trend-following trail with a volume-weighted momentum oscillator. It’s built around two core components: the AlphaTrail—a dynamic band system influenced by Hull MA and volatility—and a smoothed Money Flow Index (MFI) that provides insights into buying or selling pressure. Together, these tools are used to color bars, generate potential reversal markers, and assist traders in identifying trend continuation or exhaustion phases in any market or timeframe.
CONCEPTS
The AlphaTrail calculates a volatility-adjusted channel around price using the Hull Moving Average as the base and an EMA of range as the spread. It adaptively shifts based on price interaction to capture trend reversals while avoiding whipsaws. The direction (bullish or bearish) determines both the band being tracked and how the trail locks in. The Money Flow Index (MFI) is derived from hlc3 and volume, measuring buying vs selling pressure, and is further smoothed with a short Hull MA to reduce noise while preserving structure. These two systems work in tandem: AlphaTrail governs directional context, while MFI refines the timing.
FEATURES
Dynamic AlphaTrail line with regime switching logic that controls directional bias and bar coloring.
Smoothed MFI with gradient coloring to visually communicate pressure and exhaustion levels.
Overbought/oversold thresholds (80/20), mid-level (50), and custom extreme zones (90/10) for deeper signal granularity.
Built-in take-profit signal logic: crossover of MFI into overbought with bullish AlphaTrail, or into oversold with bearish AlphaTrail.
Visual fills between price and AlphaTrail for clearer confirmation during trend phases.
Alerts for regime shifts, MFI crossovers, trail interactions, and bar color regime changes.
USAGE
Add the indicator to any chart. Use the AlphaTrail plot to define trend context: bullish (trailing below price) or bearish (trailing above). MFI values give supporting confirmation—favor long setups when MFI is rising and above 50 in a bullish regime, and shorts when MFI is falling and below 50 in a bearish regime. The colored fills help visually track strength; sharp changes in MFI crossing 80/20 or 90/10 zones often precede pullbacks or reversals. Use the plotted circles as optional take-profit signals when MFI and trend are extended. Adjust AlphaTrail length/multiplier and MFI smoothing to better match the asset’s volatility profile.
Fibonacci Entry Bands [AlgoAlpha]OVERVIEW
This script plots Fibonacci Entry Bands, a trend-following and mean-reversion hybrid system built around dynamic volatility-adjusted bands scaled using key Fibonacci levels. It calculates a smoothed basis line and overlays multiple bands at fixed Fibonacci multipliers of either ATR or standard deviation. Depending on the trend direction, specific upper or lower bands become active, offering a clear framework for entry timing, trend identification, and profit-taking zones.
CONCEPTS
The core idea is to use Fibonacci levels—0.618, 1.0, 1.618, and 2.618—as multipliers on a volatility measure to form layered price bands around a trend-following moving average. Trends are defined by whether the basis is rising or falling. The trend determines which side of the bands is emphasized: upper bands for downtrends, lower bands for uptrends. This approach captures both directional bias and extreme price extensions. Take-profit logic is built in via crossovers relative to the outermost bands, scaled by user-selected aggressiveness.
FEATURES
Basis Line – A double EMA smoothing of the source defines trend direction and acts as the central mean.
Volatility Bands – Four levels per side (based on selected ATR or stdev) mark the Fibonacci bands. These become visible only when trend direction matches the side (e.g., only lower bands plot in an uptrend).
Bar Coloring – Bars are shaded with adjustable transparency depending on distance from the basis, with color intensity helping gauge overextension.
Entry Arrows – A trend shift triggers either a long or short signal, with a marker at the outermost band with ▲/▼ signs.
Take-Profit Crosses – If price rejects near the outer band (based on aggressiveness setting), a cross appears marking potential profit-taking.
Bounce Signals – Minor pullbacks that respect the basis line are marked with triangle arrows, hinting at continuation setups.
Customization – Users can toggle bar coloring, signal markers, and select between ATR/stdev as well as take-profit aggressiveness.
Alerts – All major signals, including entries, take-profits, and bounces, are available as alert conditions.
USAGE
To use this tool, load it on your chart, adjust the inputs for volatility method and aggressiveness, and wait for entries to form on trend changes. Use TP crosses and bounce arrows as potential exit or scale-in signals.
Adaptive MACD Deluxe [AlgoAlpha]OVERVIEW
This script is an advanced rework of the classic MACD indicator, designed to be more adaptive, visually informative, and customizable. It enhances the original MACD formula using a dynamic feedback loop and a correlation-based weighting system that adjusts in real-time based on how deterministic recent price action is. The signal line is flexible, offering several smoothing types including Heiken Ashi, while the histogram is color-coded with gradients to help users visually identify momentum shifts. It also includes optional normalization by volatility, allowing MACD values to be interpreted as relative percentage moves, making the indicator more consistent across different assets and timeframes.
CONCEPTS
This version of MACD introduces a deterministic weight based on R-squared correlation with time, which modulates how fast or slow the MACD adapts to price changes. Higher correlation means smoother, slower MACD responses, and low correlation leads to quicker reaction. The momentum calculation blends traditional EMA math with feedback and damping components to create a smoother, less noisy series. Heiken Ashi is optionally used for signal smoothing to better visualize short-term trend bias. When normalization is enabled, the MACD is scaled by an EMA of the high-low range, converting it into a bounded, volatility-relative indicator. This makes extreme readings more meaningful across markets.
FEATURES
The script offers six distinct options for signal line smoothing: EMA, SMA, SMMA (RMA), WMA, VWMA, and a custom Heiken Ashi mode based on the MACD series. Each option provides a different response speed and smoothing behavior, allowing traders to match the indicator’s behavior to their strategy—whether it's faster reaction or reduced noise.
Normalization is another key feature. When enabled, MACD values are scaled by a volatility proxy, converting the indicator into a relative percentage. This helps standardize the MACD across different assets and timeframes, making overbought and oversold readings more consistent and easier to interpret.
Threshold zones can be customized using upper and lower boundaries, with inner zones for early warnings. These zones are highlighted on the chart with subtle background fills and directional arrows when MACD enters or exits key levels. This makes it easier to spot strong or weak reversals at a glance.
Lastly, the script includes multiple built-in alerts. Users can set alerts for MACD crossovers, histogram flips above or below zero, and MACD entries into strong or weak reversal zones. This allows for hands-free monitoring and quick decision-making without staring at the chart.
USAGE
To use this script, choose your preferred signal smoothing type, enable normalization if you want MACD values relative to volatility, and adjust the threshold zones to fit your asset or timeframe. Use the colored histogram to detect changes in momentum strength—brighter colors indicate rising strength, while faded colors imply weakening. Heiken Ashi mode smooths out noise and provides clearer signals, especially useful in choppy conditions. Use alert conditions for crossover and reversal detection, or monitor the arrow markers for entries into potential exhaustion zones. This setup works well for trend following, momentum trading, and reversal spotting across all market types.
SuperTrend Confluence Signals [AlgoAlpha]OVERVIEW
This script enhances the classic SuperTrend indicator by integrating volume dynamics, retracement detection, and a multi-asset trend matrix—alongside an automatic mitigation-level drawing system. It's designed for traders who want to see not just trend direction, but the confluence of trend strength, volatility-adjusted retracements, and capital flow through volume pressure. It visually maps key transitions in market structure while offering a clean, color-coded overview of multiple symbols and timeframes in a single chart.
CONCEPTS
At the core is the traditional SuperTrend , which determines directional bias using Average True Range (ATR) with a volatility multiplier. This script overlays that with a dynamic volume histogram that scales relative to recent volume standard deviation, coloring volume bursts within the trend. Retracement signals are triggered when price pulls back toward the SuperTrend level but respects it—quantified through normalized distance sensitivity. On top of that, the indicator automatically draws and manages horizontal support/resistance zones that appear at key trend shifts. These levels persist and are cleared based on configurable rules such as wick/body sweeps or consecutive candle closes. A multi-asset, multi-timeframe table then gives an instant snapshot of trend status across five user-defined symbols and timeframes.
FEATURES
SuperTrend : Configurable ATR length and multiplier for flexible trend sensitivity.
Volumetric Histogram : Gradient-filled candles anchored to SuperTrend bands, scaled by relative volume to indicate activity intensity during trends.
Retracement Arrows : Signals printed when price nears the SuperTrend level without breaking it, allowing identification of high-probability continuation zones.
Volume TP Markers : Diamond markers flag high-volume events, contextualizing price moves with liquidity bursts.
Automatic Structure Levels : Draws clean horizontal lines at significant trend transitions, with optional volatility-based band fills. These levels self-update and clear based on price interaction logic.
Trend Table : Displays trend direction (▲/▼) across five assets and five timeframes. Each cell is colored according to trend bias, providing a compact overview for multi-market confluence.
USAGE
Start by loading the indicator on your main chart and adjusting the ATR Length and Multiplier to match your strategy timeframe. Use lower values for scalping and higher values for swing trading. The histogram bars will appear as colored candles above or below the SuperTrend level, indicating how strong volume is within that trend. Arrow signals suggest minor pullbacks within the trend, which can act as entry opportunities. The level system will automatically plot key price zones during trend flips; if "Body" is selected for mitigation, price must close through the level to invalidate it. If "Wick" is chosen, a single wick breach is enough. Adjust expiry and rejection settings to fine-tune how long levels stay on chart. Finally, enable the Multi-Asset Table to view live trend signals across popular symbols like AAPL or NVDA in different timeframes, helping spot macro-to-micro alignment for higher-confidence trades.
Equal High/Low (EQH/EQL) [AlgoAlpha]OVERVIEW
This script detects and visualizes Equal High (EQH) and Equal Low (EQL) zones—key liquidity areas where price has previously stalled or reversed. These levels often attract institutional interest due to the liquidity buildup around them. The indicator is built to highlight such zones using dynamic thresholding, overbought/oversold RSI filtering, and adaptive mitigation logic to manage zone relevance over time.
CONCEPTS
Equal Highs/Lows are price points where the market has repeatedly failed to break past a certain high or low, hinting at areas where stop orders and pending interest may be concentrated. These areas are often prime targets for liquidity grabs or reversals. By combining this with RSI filtering, the script avoids false signals during neutral conditions and instead focuses on zones where market pressure is more directional.
FEATURES
Detection Logic: The script identifies EQH and EQL zones by comparing the similarity between recent highs or lows with a dynamic volatility threshold. The `tolerance` input allows users to control how strict this comparison is.
RSI Filtering: If enabled, it only creates zones when RSI is significantly overbought or oversold (based on the `state_thresh` input). This helps ensure zones form only in meaningful market conditions.
Zone Display: Bullish (EQL) zones are shown in grey, while bearish (EQH) zones are in blue. Two horizontal lines mark the zone using wick and body extremes, and a filled area visualizes the zone between them.
Zone Management: Zones automatically extend with price until they’re invalidated. You can choose whether a zone is removed based on wick or body sweeps and whether it requires one or two candle confirmations. Zones also expire after a customizable number of bars.
Alerts: Four alert conditions are built in—when a new EQH/EQL is formed and when one is mitigated—making it easy to integrate into alert-based workflows.
USAGE
Equal highs/lows can be used as liquidity markers, either as entry points or as take-profit targets.
This tool is ideal for liquidity-based strategies and helps traders map out possible reversal or sweep zones that often precede aggressive moves.
