Multipower Entry SecretMultipower Entry Secret indicator is designed to be the ultimate trading companion for traders of all skill levels—especially those who struggle with decision-making due to unclear or overwhelming signals. Unlike conventional trading systems cluttered with too many lines and confusing alerts, this indicator provides a clear, adaptive, and actionable guide for market entries and exits.
Key Points:
Clear Buy/Sell/Wait Signals:
The script dynamically analyzes price action, candle patterns, volume, trend strength, and higher time frame context. This means it gives you “Buy,” “Sell,” or “Wait” signals based on real, meaningful market information—filtering out the noise and weak trades.
Multi-Timeframe Adaptive Analysis:
It synchronizes signals between higher and current timeframes, ensuring you get the most reliable direction—reducing the risk of getting caught in fake moves or sudden reversals.
Automatic Support, Resistance & Liquidity Zones:
Key levels like support, resistance, and liquidity zones are auto-detected and displayed directly on the chart, helping you make precise decisions without manual drawing.
Real-Time Dashboard:
All relevant information, such as trend strength, market intent, volume sentiment, and the reason behind each signal, is neatly summarized in a dashboard—making monitoring effortless and intuitive.
Customizable & Beginner-Friendly:
Whether you’re a newcomer wanting straightforward guidance or a professional needing advanced customization, the indicator offers flexible options to adjust analysis depth, timeframes, sensitivity, and more.
Visual & Clutter-Free:
The design ensures that your chart remains clean and readable, showing only the most important information. This minimizes mental overload and allows for instant decision-making.
Who Will Benefit?
Beginners who want to learn trading logic, avoid common traps, and see the exact reason behind every signal.
Advanced traders who require adaptive multi-timeframe analytics, fast execution, and stress-free monitoring.
Anyone who wants to save screen time, reduce analysis paralysis, and have more confidence in every trade they take.
1. No Indicator Clutter
Intent:
Many traders get confused by charts filled with too many indicators and signals. This often leads to hesitation, missed trades, or taking random, risky trades.
In this Indicator:
You get a clean and clutter-free chart. Only the most important buy/sell/wait signals and relevant support/resistance/liquidity levels are shown. These update automatically, removing the “overload” and keeping your focus sharp, so your decision-making is faster and stress-free.
2. Exact Entry Guide
Intent:
Traders often struggle with entry timing, leading to FOMO (fear of missing out) or getting trapped in sudden market reversals.
In this Indicator:
The system uses powerful adaptive logic to filter out weak signals and only highlight the strongest market moves. This not only prevents you from entering late or on noise, but also helps avoid losses from false breakouts or whipsaws. You get actionable suggestions—when to enter, when to hold back—so your entries are high-conviction and disciplined.
3. HTF+LTF Logic: Multitimeframe Sync Analysis
Intent:
Most losing trades happen when you act only on the short-term chart, ignoring the bigger market trend.
In this Indicator:
Signals are based on both the current chart timeframe (LTF) and a higher (HTF, like hourly/daily) timeframe. The indicator synchronizes trend direction, momentum, and structure across both levels, quickly adapting to show you when both are aligned. This filtering results in “only trade with the bigger trend”—dramatically increasing your win rate and market confidence.
4. Auto Support/Resistance & Liquidity Zones
Intent:
Drawing support/resistance and liquidity zones manually is time-consuming and error-prone, especially for beginners.
In this Indicator:
The system automatically identifies and plots the most crucial support/resistance levels and liquidity zones on your chart. This is based on adaptive, real-time price and volume analysis. These zones highlight where major institutional activity, trap setups, or real breakouts/reversals are most likely, removing guesswork and giving you a clear reference for entries, exits, and stop placements.
5. Clear Action/Direction
Intent:
Traders need certainty—what does the market want right now? Most indicators are vague.
In this Indicator:
Your dashboard always displays in plain words (like “BUY”, “SELL”, or “WAIT”) what action makes sense in the current market phase. Whether it’s a bull trap, volume spike, wick reversal, or exhaustion—it’s interpreted and explained clearly. No more confusion—just direct, real-time advice.
6. For Everyone (Beginner to Pro)
Intent:
Most advanced indicators are overwhelming for new traders; simple ones lack depth for professionals.
In this Indicator:
It is simple enough for a beginner—just add it to the chart and instantly see what action to consider. At the same time, it includes advanced adaptive analysis, multi-timeframe logic, and customizable settings so professional traders can fine-tune it for their strategies.
7. Ideal Usage and User Benefits
Instant Decision Support:
Whenever you’re unsure about a trade, just look at the indicator’s suggestion for clarity.
Entry Learning:
Beginners get real-time “practice” by not only seeing signals, but also the reason behind them—improving your chart reading and market understanding.
Screen Time & Stress Reduction:
Clear, relevant information only; no noise, less fatigue, faster decisions.
Makes Trading Confident & Simple:
The smart dashboard splits actionable levels (HTF, LTF, action) so you never miss a move, avoid traps, and stay aligned with high-probability trades.
8. Advanced Input Settings (Smart Customization)
Explained with Examples:
Enable Wick Analysis:
Finds candles with strong upper/lower wicks (signs of rejection/buying/selling force), alerting you to hidden reversals and protecting from FOMO entries.
Enable Absorption:
Detects when heavy order flow from one side is “absorbed” by the other (shows where institutional buyers/sellers are likely active, helps spot fake breakouts).
Enable Unusual Breakout:
Highlights real breakouts—large volatility plus high volume—so you catch genuine moves and avoid random spikes.
Enable Range/Expansion:
Smartly flags sudden range expansions—when the market goes from quiet to volatile—so you can act at the start of real trends.
Trend Bar Lookback:
Adjusts how many bars/candles are used in trend calculations. Short (fast trades, more signals), long (more reliability, fewer whipsaws).
Bull/Bear Bars for Strong Trend Min:
Sets how many candles in a row must support a trend before calling it “strong”—prevents flipping signals, keeps you disciplined.
Volume MA Length:
Lets you adjust how many bars back volume is averaged—fine-tune for your asset and trading style for best volume signals.
Swing Lookback Bars:
Set how many bars to use for swing high/low detection—short (quick swing levels), long (stronger support/resistance).
HTF (Bias Window):
Decide which higher timeframe the indicator should use for big-picture market mood. Adjustable for any style (scalp, swing, position).
Adaptive Lookback (HTF):
Choose how much HTF history is used for detecting major extremes/zones. Quick adjust for more/less sensitivity.
Show Support/Resistance, Liquidity Zones, Trendlines:
Toggle them on/off instantly per your needs—keeps your chart relevant and tailored.
9. Live Dashboard Sections Explained
Intent HTF:
Shows if the bigger timeframe currently has a Bullish, Bearish, or Neutral (“Chop”) intent, based on strict volume/price body calculations. Instant clarity—no more guessing on trend bias.
HTF Bias:
Clear message about which side (buy/sell/sideways) controls the market on the higher timeframe, so you always trade with the “big money.”
Chart Action:
The central action for the current bar—Whether to Buy, Sell, or Wait—calculated from all indicator logic, not just one rule.
TrendScore Long/Short:
See how many candles in your chosen window were bullish or bearish, at a glance. Instantly gauge market momentum.
Reason (WHY):
Every time a signal appears, the “reason” cell tells you the primary logic (breakout, wick, strong trend, etc.) behind it. Full transparency and learning—never trade blindly.
Strong Trend:
Shows if the market is currently in a powerful trend or not—helping you avoid choppy, risky entries.
HTF Vol/Body:
Displays current higher timeframe volume and candle body %—helping spot when big players are active for higher probability trades.
Volume Sentiment:
A real-time analysis of market psychology (strong bullish/bearish, neutral)—making your decision-making much more confident.
10. Smart and User-Friendly Design
Multi-timeframe Adaptive:
All calculations can now be drawn from your choice of higher or current timeframe, ensuring signals are filtered by larger market context.
Flexible Table Position:
You can set the live dashboard/summary anywhere on the chart for best visibility.
Refined Zone Visualization:
Liquidity and order blocks are visually highlighted, auto-tuning for your settings and always cleaning up to stay clutter-free.
Multi-Lingual & Beginner Accessible:
With Hindi and simple English support, descriptions and settings are accessible for a wide audience—anyone can start using powerful trading logic with zero language barrier.
Efficient Labels & Clear Reasoning:
Signal labels and reasons are shown/removed dynamically so your chart stays informative, not messy.
Every detail of this indicator is designed to make trading both simpler and smarter—helping you avoid the common pitfalls, learn real price action, stay in sync with the market’s true mood, and act with discipline for higher consistency and confidence.
This indicator makes professional-grade market analysis accessible to everyone. It’s your trusted assistant for making smarter, faster, and more profitable trading decisions—providing not just signals, but also the “why” behind every action. With auto-adaptive logic, clear visuals, and strong focus on real trading needs, it lets you focus on capturing the moves that matter—every single time.
Поиск скриптов по запросу "liquidity"
Price Action By ProfitAlgo.io Price Action Alerts combined with the BackEnd Order Matrix and TrendSync Tool Kit.
ProfitAlgo.io Price Action
A companion tool to the Backend Order Matrix and TrendSync, this indicator helps visualize trade direction with A/B/C/D retracement lines that align with fib retracement levels which can react as a BIG BOUNCE RETEST ENTRY, multi-timeframe support/resistance, and an RSI filter. It’s designed as a guide for bias confirmation, not a signal to enter every mark. Combine it with the Backend Order Matrix (for liquidity/stop-hunt zones) and TrendSync (for trend confirmation) to better spot where stop hunts become opportunities and price action aligns with higher-probability setups.
Price is shown bullish and the retracement lines are defined by the dotted lines. You may color the lines to your discretion to be able to quickly differentiate the different retracments lines on the chart aligning to Fib levels for possible early entries. Here you can anticipate for price to have a significant reaction with placing your stop loss being the Buy-Side Liquidity as show below. Though the BackEnd Order Matrix liquidity can be swept so keep in mind being more patient to wait for the liquidity sweep as the point entry can serve as another approach to minimize risk exposure.
Exiting at the SellSide Liquidity where price can have an reaction to the downside.
Vise Versa for bearish trend following retracement entires.
⚙️ Settings Guide – ProfitAlgo.io Price Action
Retracement Line (A/B/C/D) → Shows potential price action setups where price can have a strong reaction. Having Price above the lines- price can be shown to buy at these levels. If Price is below the lines and the trend is showing bearish the price can be shown to retest and sell at these levels.
Multi-Timeframe S/R → Plots higher-timeframe support and resistance levels for added context.
RSI Filter → Filters entries when RSI conditions are extreme, helping avoid false setups.
Top-Down Analysis (TDA) → Aligns lower-timeframe entries with higher-timeframe structure.
📌 Tip: The TrendSync's trend detection visual representation Together with Backend Order Matrix (for liquidity zones/stop hunts) helps Traders understand trend based trading with liquidity stop hunts which can be used as a entry model that does not happen as many times as the Price Action Tool does for early entries signals. If you would like to read more on how the The BackEnd Order Matrix and TrendSync Simulation Tool works. Feel free to read the articles below.
The How to Use The BackEnd Order Matrix?
The How to Use The TrendSync Simulation Tool?
ICT Sweep + FVG Entry (v6) • Pro Pack 📌 ICT Sweep + FVG Entry Pro Pack
This indicator combines key ICT price action concepts with practical execution tools to help traders spot high-probability setups faster and more objectively. It’s designed for scalpers and intraday traders who want to keep their chart clean but never miss critical market structure events.
🔑 Features
Liquidity Pools (HTF)
• Auto-detects recent swing highs/lows from higher timeframes (5m/15m).
• Draws both lines and optional rectangles/zones for clear liquidity areas.
Liquidity Sweeps (BSL/SSL)
• Identifies when price sweeps above/below liquidity pools and rejects back.
• Optional Grade-A sweep filter (wick size + strong re-entry).
Fair Value Gaps (FVGs)
• Highlights bullish/bearish imbalances.
• Optional midline (50%) entry for precision.
• Auto-invalidation when price fully closes inside the gap.
Killzones (New York)
• Highlights AM (9:30–11:30) and PM (14:00–15:30) killzones.
• Option to block signals outside killzones for higher strike rate.
Bias Badge (DR50)
• Displays if price is trading in a Bull, Bear, or Range context based on displacement range midpoint.
SMT Assist (NQ vs ES)
• Detects simple divergences between indices:
Bearish SMT → NQ makes HH while ES doesn’t.
Bullish SMT → NQ makes LL while ES doesn’t.
SL/TP Helper & R:R Label
• Automatically draws stop loss (at sweep extreme) and target (opposite pool or recent swing).
• Displays expected Risk:Reward ratio and blocks entries if below your chosen minimum.
Filters
• ATR filter ensures signals only appear in sufficient volatility.
• Sweep quality filter avoids weak wicks and fake-outs.
🎯 How to Use
Start on HTF (5m/15m) → Identify liquidity zones and bias.
Drop to LTF (1m) → Wait for a liquidity sweep confirmation.
Check for FVG in the sweep’s direction → Look for retest entry.
Use the SL/TP helper to validate your risk/reward before taking the trade.
Focus entries during NY Killzones for maximum effectiveness.
✅ Why this helps
This tool reduces screen time and hesitation by automating repetitive ICT concepts:
Liquidity pools, sweeps, and FVGs are marked automatically.
Killzone timing and SMT divergence are simplified.
Clear visual signals for entries with built-in RR filter help keep your trading mechanical.
⚠️ Disclaimer: This script is for educational purposes only. It does not provide financial advice or guarantee results. Always use proper risk management.
ICT Sweep + FVG Entry (v6) • Antoine📌 ICT Sweep + FVG Entry (Antoine)
This indicator is designed for price action traders who follow ICT concepts and want a mechanical tool to spot liquidity sweeps, fair value gaps (FVGs), and precise entry signals.
🔎 Key Features
Liquidity Pools (HTF)
• Automatically plots recent swing highs/lows from a higher timeframe (5m/15m).
• These act as Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL) levels where stop orders accumulate.
Sweep Detection
• Identifies when price breaks a pool (BSL/SSL) but closes back inside → a classic liquidity grab.
• Plots a triangle on the chart when a sweep is confirmed.
Fair Value Gap (FVG) Highlighting
• Detects bullish and bearish FVGs on the execution timeframe (ideal for 1m).
• Option to display active FVG zones with shaded boxes.
Entry Signals
• A signal (cross) appears when:
A liquidity sweep occurs.
An FVG forms in the direction of the rejection.
Price retests the FVG (entry at the 50% mid-level or edge).
Alerts Ready
• Get alerted for sweeps (bullish/bearish) and for entry confirmations (long/short FVG retests).
🎯 How to Use
Choose your HTF (5m or 15m) → The indicator maps major liquidity pools.
Drop to LTF (1m) → Wait for a sweep signal at one of the pools.
Confirm with FVG → If an FVG appears in the sweep’s direction, the indicator waits for a retest.
Entry → Enter on the retest of the FVG (edge or 50%).
Risk Management
Stop loss: just beyond the sweep’s wick.
Target: opposite liquidity pool.
Minimum recommended R:R: 1:2.
✅ Why this helps
This tool makes it easier to trade ICT-style setups without missing opportunities:
No need to manually draw every swing high/low.
Automatic FVG detection saves time.
Clear sweep + FVG + retest logic keeps your entries mechanical and disciplined.
⚠️ Disclaimer: This script is for educational purposes only. It does not guarantee profits. Always use proper risk management.
SMC ToolBox [WinWorld]👋 INTRODUCTION
SMC ToolBox indicator is not just a simple indicator, but rather a collection of SMC-related algorithms, that our teams has found to make the most profound impact on determination process of the most high-quality liquidity zones and points of interests ( further – POIs ), hence the name of the indicator – Tool Box (and it also sounds cool :) .
From candle patterns to complex orderflow detection algorithm, ToolBox indicator will help any trader with search for useful tools, solving the needs from confirming position entry levels to trend-following and mean reversion opportunities.
❓ WHY DID WE BUILD THIS?
This indicator was initially built for our team's internal use for the sole purpose of gathering all actively used non-structure-related algorithms* in one place, so we could have only the tools that are truly needed at hand at any point of time. After we showed this tool to our trading partners, they were surprised about how light, fast and useful ToolBox was and they advised us on sharing this with our community and, after giving it a proper thought, we decided to follow their advice.
Funnily enough , after researching TradingView's open-source script library, we haven't found even one instance of even remotely alike indicators, so it fair to say that we are one of the first people to release this kind of SMC-related indicator bundles on the market and we strongly that TradingView's community will find this tool of use.
🤷♂️ WHY SHOULD YOU CARE AT ALL?
Frankly speaking, we are not the first people to build our own algorithms of such popular indicators like Equal Highs and Lows (EQHL), Previous Day High Low (PDHL), Orderflow (OF) and etc., but we are definitely one of the first teams to implement these indicators with the help of algorithms, that are actually used by the most professional traders on YouTube and other social media trading influencers. Simply taking trades from our SCOBs, OFs, EQHLs and etc. won't print you millions overnight, but what these algos will do is help you with being aware of is potentially laying ahead of you with a very clean probability.
Why does it matter? It simple: better market awareness gives you an edge over other trades, which use old algorithms, which are clearly outdated, so beating such traders in the long run is just a game of time for you, so good algorithms do matter. Each indicator inside ToolBox is there to help you develop this market awareness and forge your edge bit by bit.
Now let's talk about what is inside the ToolBox.
🔍 OVERVIEW
At the moment of publishing ToolBox contains 8 indicators, so say "Hello" to:
Price Border Bands (further – PBB) ;
Ordeflow (further – OF) ;
Equal Highs & Lows (further – EQHL) ;
Previous Day High & Low ( further – PDHL) ;
Single Candle Order Block (further – SCOB) ;
Institutional Funding Candle (further – IFC) ;
Engulfing Candle (further – EC) ;
Inside Bars (further – IB) .
Some of them you may know, some of them you may not, so let's review each of them one by one.
📍 INDICATOR: Price Border Bands (PBB)
Price Border Bands indicator is a simple yet useful algorithm, based on Triangular Moving Average (TMA), which helps determine extreme price spikes, which on average act as meaningful mean reversion opportunities. It also is a good an effective "verifier" of POIs and zones of interest (further – ZOI) .
We advise on using this indicator this way:
Look for price going beyond upper or lower band of PBB;
Look for price reaching POI or ZOI;
Start searching for your entry point.
The most common sign of potential price reversal, which PBB searches for, is intense price spike, which signals about "liquidity clearing" or, in simple terms, manipulation .
Manipulation of the price inside the POI or price being "stopped" by POI is a screaming sign of the potentional following reversal. See the example of such situation on the screenshot below:
Additionally we need to talk about trend filter inside PBB, which colours the bars on the chart under certain conditions. If bars on the chart are being coloured in gray – this is your sign to stop trading on this asset? because there is risk to catch an uncomfortably big price spike, which might turn the '+' of your position's PnL in to '-'. See the example of PBB highlighting bar's of risky price zone in gray colour on the screenshot below:
In order to continue trading you need to wait for bars to stop being coloured in gray OR confirm the fact that price made Change of Character (ChoCh) in reverse to the previous direction of price, which was marked as risky by PBB.
And last but not least: if you see POI being reach by price inside the bands of PBB, then consider this POI weak and avoid trading it. See the example of weak POI inside PBB bands on the screenshot below:
📍 INDICATOR: Orderflow (OF)
Orderflow indicator is an algorithm, which detects Sell-to-Buy (furthert – STB) or Buy-to-Sell (further – BTS) manipulations, using the algorithm of impulse & correction price movement detection, taken from one of our previously built indicators – Impulse Correction SCOB Mapper (ICSM) .
Let's explain the terms from above:
Impulse – series of bars, each bar of which consecutively updated previous bar's high and then last candle broke previous bar's low ;
Correction – series of bars, each bar of which consecutively updated previous bar's low and then last candle broke previous bar's high ;
STB – a type of price manipulation, which can be described as a correction of price inside global upward movemnt;
BTS – a type of price manipulation, which can be describd as a impulse of price inside global downward movement.
Unlike traditional order blocks, which are often narrower and more selective, Orderflow zones cover a wider price range and present a higher probability of mitigation. This makes them more reliable for entries in ovaerage in comparison to classic orderblocks.
Let's review examples of bullish and bearish orderflows on the screenshots below:
Bullish orderflows (STBs) (blue boxes with "OF" text inside)
Bearish orderflows (BTSs) (orange boxes with "OF" text inside)
The usage of ZOIs, detected by OF algorithm, is pretty straightforward: take trades against the ordeflow block, that price has reached. Even though we don't recommend relying on Orderflow blocks as sole producers of signals, you can use them as such in way, that can be described like this:
Place stop-loss (SL) beyond the furthest border of OF block (bottom of the bullish OF or top of the bearish OF), that price has reached;
Aim for >2:1 RR ratio and place your take-profit (TP) accordingly.
You can see the example setups of OF blocks as signal producers on the screenshots below:
Examples of LONG trades, taken from price reaching bullish OF block.
Examples of SHORT trades, taken from price reaching bearish OF block.
Summarising, Orderflow can be described as a tool that helps determine the STB and BTS price manipulations, which are great price ZOIs and can be used both as confirmation tools for your exisiting signals and sole signal producers, in which case such they needed to be handled extra mindfully and preferrably bonded with other tools for additional confirmation. We personally recommend using Ordeflow as confirmation tool, because ZOIs, detected by Orderflow, are usually the price ranges, around which traders tend to place their stop-losses, which only gives more strength to these zones for supporting the price and helps traders with "trading from support/resistance" strategies gain additional edge.
📍 INDICATOR: Equal Highs & Lows (EQHL)
EQHL indicator is an algorithm, which scans the extremums of impulse and correction movements, detected by our ICSM indicator , and marks ones which are roughly or equaly placed on the same price levels. Equal highs (further – EQH) and equal lows (further – EQL) are local liquidity pools, where stop orders and resting orders cluster; price often gravitates to these zones for liquidity “top-ups,” after which a reaction or continuation to the next liquidity source may occur. Basically, EQHL algorithm highlights clusters of equal extremes as navigational anchors for “collect → react → confirm” scenarios.
Talking about usage, we advise to not take swept or reached EQHLs as entries by themselves. Evaluate them alongside HTF structure, Inducement (IDM), orderblocks (OB), orderflow (OF), candle pattern context (e.g., IFC/EC) on the LTF and etc. Intended usage scenario of this algorithm is something like this:
Price reaches EQH/EQL;
Price hangs around the reached EQH/EQL;
Another tool (for example, OF or OB) signals about price reversals from the level of reached EQH/EQL;
Trader starts looking for an entry.
See the examples of EQHLs, which algorithms maps on the chart, on the screenshots below:
Equal Lows (EQLs)
Equal Highs (EQHs)
📍 INDICATOR: Previous Day High & Low (PDHL)
PDHL indicator is an algorithm, princples of work of which can be derived from its name: algorithm tracks previous day's high and low and displays it on the chart.
Previous day's high and low are fundamental POIs in any financial market, which are traded not only by SMC traders, but by many other traders, especially by traders, which consider these POIs are one of the most crucial, because they usually highly liquidity-rich and can signal about wondeful reversal opportunities.
We expect traders to use PDHL algorithm as confirmation tool when trading by mean reversion strategies. Usage of PDHL as signal source is advised against, but traders are free to experiment nevertheless.
PDHL algorithm shows two types of PDHLs on the chart: active PDHL (solid line) and swept PDHL (dashed line) . You can the examples of PDHLs, detected by our algorithm, on the screenshot below:
📍 INDICATOR: Single Candle Order Block (SCOB)
SCOB indicator is an algorithm, which marks a very specific POIS, which are based on of the most simple yet highly profound SMC and candle pattern principles and are usually a good alternative for classic orderblocks.
Principles of SCOB detection are very simple:
Price sweeps previous candle's extremum (high/low). So called "liquidity sweep" ;
Immediately after step 1 price forms a fair value gap (FVG).
You can see basic examples of bearish and bullish SCOBs on the screenshot below:
As a matter of fact, SCOB can be used both as a confirmation tool and source of signals. However! To be a source of signals, SCOB is most suitable to be used while trading on lower timeframe (LTF), while trading on a higher timeframe (HTF) on average requires to look at SCOB as a POI rather than as independent source of signals. That being said, we would like additionally to point out, that due to the nature of SCOB being an orderblock, this tool by its nature is best suitable as confirmation tool and we expect traders to use it as such, but either way this indicator is quite multifunctional and can be used by each trader for a more specific purposes.
SCOBs, which are detected by our algorithm, are painted on the chart either as coloured candles (SCOBs without inside bars) or coloured boxes (SCOBs with inside bars) . You can see examples of SCOBs, which were detected by our SCOB algorithm, on the screenshot below:
📍 INDICATOR: Institutional Funding Candle (IFC)
IFC is a candle, which is a more strict version of SCOB. Our algorithms detects an IFC, if SCOB satisfies these conditions:
SCOB candle has large shadow (more than 50% of candle's body);
SCOB candle has large range ( | high - low | is more than a certain value, which is base on ATR).
That's basically it! Being simple as that, IFC represents itself as a high-trust SCOB, which on average has larger chance of reversing price when IFC candle is reached by it and our practice shows that it is indeed the case. IFC candles are usually go hand in hand with large price and volume spikes, which are believed to be caused by large institutional players, who trading eager to catch retail trader's stop orders, which they usually place around POIs like IFC and SCOB.
We expect traders to use IFC as a tool for entry confirmation bias, especially when considering IFC from HTF.
You can see IFC, which our algoritms detects on the chart, on the screenshot below:
📍 INDICATOR: Engulfing Candle (EC)
An Engulfing Candle is a candle, which occurs when the current candle’s body engulfs the prior candle’s body, showing a short-term shift in demand/supply balance. In SMC context, it is most useful around POIs/liquidity as a contextual confirmation element. The indicator marks bullish and bearish EC without implying a “must reverse” outcome – it’s a focus cue, not a promise.
As with any other alike tool, this algorithm should not be used as sole source of signals, but rather as a confirmation tool. ECs near support/resistance zones or POIs are typically more impactufl than those inside choppy consolidations. Structural and LTF price impulse confirmation usually enhances existing position bias in a positive way.
You can see examples of engulfing candles on the screenshots below:
Bullish engulfing candles
Bearish engulfing candles
📍 INDICATOR: Inside Bars (IB)
Inside Bars are bars, which are contained inside the range of high and low prices of the bars preceding them. This algorithm was designed to showcase periods of potential price consolidation/volatylity compression and quite often precedes price movement towards closest liquidity POIs and ZOIs. When price finally breaks out of its previous range, it usually provides good opportunities for entering trades using breakout strategies (especially ones, that are based on SMC principles) .
You can see examples of IBs, which are detected by our algorithm on the chart, on the screenshot below:
That was a long list of features, now let's talk about settings now.
🔔 WHAT ABOUT ALERTS?
At the moment of publishing this indicator includes alerts for all algorithms, which are included inside, except for Inside Bars (IB) algorithm .
⚙️ SETTINGS
At the moment of publishing most of the settings in this indicator are about styling for indicator's visuals, because by design most of the included algorithms (excluding PBB) don't rely on inputs of any technical kind. Let's review them.
ToolBox | General Styling
Text Size – (Tiny, Small, Normal, Large) – defines text size of indicator's visuals, which use text-based visuals.
Price Border Bands | Main Settings
Show Price Border Bands – toggles on/off the display of PBB;
Half Length – defines amount of bars, used for calculation of the PBB's TMA;
Price Source – defines price source for PBB's TMA;
ATR Multiplier – affects the width of PBB's bands;
ATR Period – affects the amount of bars for ATR calculation.
Orderflow (OF) | Settings
Bullish OF – toggles on/off the display & colour of bullish OF;
Bearish OF – toggles on/off the display & colour of bearish OF;
Show border – toggles on/off the display of OF blocks' border.
Single Candle Order Block (SCOB) | Settings
Show SCOB – toggles on/off the display of SCOB;
Bullish – toggles on/off the colour of bullish SCOB;
Bearish – toggles on/off the colour of bearish SCOB.
Equal High/Lows (EQHL) | Settings
Show EQH/EQL – toggles on/off the display of PDH/PDL;
EQH – toggles on/off the colour of EQH;
EQL – toggles on/off the colour of EQL.
Institutional Funding Candle (IFC) | Settings
Show IFC – toggles on/off the display of IFC;
Bullish – toggles on/off the colour of bullish IFC;
Bearish – toggles on/off the colour of bearish IFC.
Previous Day High & Low (PDHL) | Settings
Show PDH/PDL – toggles on/off the display of PDH/PDL;
Show PDH/PDL – toggles on/off the display of the past history of swept PDH/PDL;
Show previous day divider – toggles on/off the display of dashed gray line, which separates new day from previous one;
Bullish – toggles on/off the colour of bullish IFC;
Bearish – toggles on/off the colour of bearish IFC.
Engulfing Candle (EC) | Settings
Show engulfing candles – toggles on/off the display of EC;
Bullish – toggles on/off the colour of bullish EC;
Bearish – toggles on/off the colour of bearish EC.
Inside Bars (IB) | Settings
Show inside bars – toggles on/off the display of IB;
Bullish – toggles on/off the colour of bullish IB;
Bearish – toggles on/off the colour of bearish IB.
Alerts | POI
Alert Frequency – (Once Per Bar, Once Per Bar Close) – defines alert frequency of the indicator's alert for all POIs;
* all other buttons from this group of settings toggle alerts on/off.
PBB;
OF;
SCOB;
EQH;
EQL;
IFC;
PDH;
PDL;
EC.
🏁 AFTERWORD
SMC ToolBox indicator is designed to be the ultimate swiss knife, which might bring you quantifiable results when trying to crack the market's secret of where the liquidity is placed. This indicator doesn't produce any particular signals not it gives any financial advice, but it helps you deepen understanding about potential existing liquidity zones and price points by employing principles of SMC algorithms, which are most commonly used by retail traders on a daily basis.
You can view this indicator as a Christmas candy box: you pick only the candles (indicators) you need and want. We expect any trader to use this indicator by exactly same way: you should take onlt the things you need to enhance your strategy, not worrying about what to do with other indicators, fi they don't suit you.
Lastly, we would like to share our team's recommendations (they are optional, of course) on how to use certain POIs from ToolBox:
Use PBB as a filter for validating POis. Pay close attention to the rule "don't trade POIs, which are located inside the bands of PBB" (described above in "INDICATOR: PBB") ;
Use Orderflow to find short-term and mid-term trading opportunitions for trend-following strategies, using OF blocks as resistance in bearish trend and support in bullish trend;
Use EQHL and PDHL indicators when trading by mean-reversion strategies on intraday timeframes. These indicators will be especially of use to forex, stock and crypto traders;
Use SCOB and IFC indicators when trading by mean-reversion strategy to find short-term reversal opportunities;
Use ECs and IBs as confirmation/denial tools for your entry ideas. We recommend avoiding trading If price is currently going inside HTF's IB range.
We have no doubts that SMC ToolBox indicator will be of use to any trader, who employs and desire to employ SMC principles in his strategy. We will be waiting for your feedback, meanwhile you can ask your questions in the comments :)
Sincerely,
WinWorld team.
HTF Rejection Block [TakingProphets]Overview
The HTF Rejection Block indicator is designed to help traders identify and visualize Higher Timeframe Rejection Blocks—price zones where liquidity grabs often result in aggressive rejections. These areas can serve as high-probability decision points when combined with other ICT-based tools and concepts.
Unlike simple support/resistance markers, this indicator automates the detection of Rejection Blocks, maps them across up to four custom higher timeframes, and updates them in real time as price evolves. It provides traders with a structured framework for analyzing institutional price behavior without supplying direct buy/sell signals.
Concept & Background
The idea of Rejection Blocks was popularized by Powell, a respected educator within the ICT trading community. He highlighted how aggressive wicks—where price sweeps liquidity and sharply rejects—often reveal institutional activity and can hint at future directional bias.
This script builds upon that foundation by integrating several ICT-aligned concepts into a single, cohesive tool:
Liquidity Sweep Recognition → Identifies where price aggressively moves beyond a key level before snapping back.
Rejection Block Mapping → Highlights the candle bodies representing institutional rejection zones.
Multi-Timeframe Context → Lets you monitor rejection zones from higher timeframes while operating on your execution timeframe.
Equilibrium-Based Planning → Optional midpoint plotting offers a precise way to evaluate premium/discount within each block.
By combining these elements, the indicator makes it easier to see where liquidity events may influence price and how they relate to broader ICT-based setups.
How It Works
Detection Logic
A Rejection Block forms when price runs liquidity past a prior high/low but fails to hold and closes back inside the range.
These setups are detected automatically and marked as bullish or bearish zones.
Multi-Timeframe Analysis
Monitor up to four higher timeframes at once (e.g., 1H, 4H, 1D, 1W) while trading on your preferred execution timeframe.
Each block is clearly labeled and color-coded for visual clarity.
50% Equilibrium Levels
Optionally plot the midpoint of each rejection block, commonly used by ICT traders as a precision-based entry or target zone.
Auto-Mitigated Zones
When price fully trades through a rejection block, the zone is automatically removed to keep your chart clean.
Info Box for Context
An optional information panel displays the symbol, timeframe, and relevant data, helping you stay organized during active trading sessions.
Practical Usage
Select Higher Timeframes
Configure up to four HTFs based on your strategy (e.g., 1H, 4H, 1D, Weekly).
Identify Rejection Blocks
Watch for new blocks forming after liquidity sweeps beyond significant highs or lows.
Combine With Other ICT Concepts
Use alongside STDV, displacement, SMT divergence, or OTE retracements for confirmation and added confluence.
Plan Entry Zones
Leverage the 50% midpoint or body extremes of each block to build structured trade setups.
Why It’s Useful
This tool doesn’t generate trading signals or claim accuracy. Instead, it provides a visual framework for applying ICT’s Rejection Block methodology systematically across multiple timeframes.
Its value lies in helping traders:
Recognize where institutional activity may leave footprints.
Map key liquidity-based zones without manual marking.
Stay aligned with higher timeframe narratives while executing on lower timeframes.
Muzyorae - Quarterly TheoryQuarterly Theory — NY Session Macro Model
The Quarterly Theory Model is a structured framework for analyzing intraday market behavior based on institutional activity and macro-level cycles.
It divides the New York trading session into four sequential “quarters” (Q1–Q4), each representing distinct phases of market participation, liquidity accumulation, and directional bias.
This model is designed for professional traders who aim to align their strategies with institutional flows, key liquidity zones, and market structure shifts.
It accommodates both AMDX (Accumulation → Manipulation → Distribution → Expansion) and XAMD (reversal sequences) fractal patterns, allowing traders to adapt to varying market conditions.
Price action may expand early during Q1 in an XAMD sequence, representing an initial breakout or early liquidity sweep before the typical Q2 manipulation phase. Traders should be aware that Q1 can occasionally produce unexpected volatility or directional bias in such sequences.
Session Breakdown (New York Time)
Q1 – Accumulation
Time: 9:30 – 10:00 AM
Phase Characteristics: Early session positioning, initial liquidity sweeps, and false moves. Institutions build positions while retail participants often react to gaps and premarket activity.
Note: Price may expand early in an XAMD sequence, creating a short-term directional move before Q2.
Q2 – Manipulation / Expansion
Time: 10:00 – 11:30 AM
Phase Characteristics: The main directional move develops, often characterized by breaks of structure, fair value gaps, and liquidity sweeps. This is a prime area for trend initiation.
Q3 – Distribution / Retracement
Time: 11:30 AM – 1:30 PM
Phase Characteristics: Price consolidates and retraces into prior accumulation zones, reflecting profit-taking or redistribution by institutions. Market chop and sideways movement are common.
Q4 – Final Expansion / Repricing
Time: 1:30 – 4:00 PM
Phase Characteristics: The afternoon session often produces final liquidity sweeps, trend continuation, or reversals, setting the high or low of the day and completing the daily macro cycle.
Key Features of the Model
Fractal-Based Structure: Q1–Q4 cycles reflect institutional behavior at a macro level, scalable to other intraday or multi-day fractals.
Supports AMDX & XAMD: Allows for both standard accumulation → manipulation → distribution → expansion sequences and reversal patterns depending on market behavior.
Early Expansion in Q1: Recognizes that in XAMD sequences, Q1 may produce early directional moves or breakout activity.
True Open Q2 Line: Highlights the opening price of Q2 as a reference for trend validation and potential entry zones.
Dynamic Time Alignment: Fully synchronized with New York (ET) time zone, ensuring accurate representation of market cycles.
Professional Visualization: Optional labels and vertical markers for each quarter, supporting quick visual analysis and pattern recognition.
Integration with ICT Concepts: Compatible with Smart Money Techniques (SMT), Fair Value Gaps (FVGs), Order Blocks (OBs), and Break of Structure (BOS) for enhanced trade planning.
Purpose and Application
Anticipates areas of liquidity accumulation and manipulation.
Identifies optimal entry and exit zones within institutional cycles.
Structures trades around probable trend initiation and continuation periods.
Aligns retail activity with institutional flow for higher probability setups.
Adapts to market variability through AMDX and XAMD fractal patterns.
Accounts for early expansions or breakout activity during Q1 in XAMD sequences.
By using the Quarterly Theory Model, traders gain a systematic, time-based framework to interpret market structure and maximize alignment with institutional participants.
Merek Equal Highs and LowsEQH – Equal Highs Indicator
Description:
The EQH indicator detects Equal Highs on the chart. This occurs when price reaches the same high level two or more times without breaking it decisively.
Interpretation:
Liquidity zone: Equal highs are often seen as areas where liquidity (stop-loss clusters) is located.
Breakout potential: A break above this level often signals that liquidity is being taken before either a reversal or continuation of the trend.
Market structure: EQH highlights resistance areas that can serve as key decision points for traders.
Use cases:
Identifying potential stop-hunt zones
Spotting resistance levels
Anticipating liquidity grabs before reversals or trend continuations
EQL – Equal Lows Indicator
Description:
The EQL indicator detects Equal Lows on the chart. This occurs when price reaches the same low level two or more times without breaking lower.
Interpretation:
Liquidity zone: Equal lows are areas where liquidity (sell-side stops) tends to accumulate.
Breakout potential: A move below this level often indicates liquidity being swept before a possible reversal or continuation.
Market structure: EQL highlights support areas that can be critical for trade decisions.
Use cases:
Identifying sell-side liquidity zones
Spotting support levels
Recognizing possible stop-hunts before reversals or trend continuations
Smart Money Trades Pro [BOSWaves]Smart Money Trades Pro – Advanced Market Structure & Liquidity Visualizer
Overview
Smart Money Trades Pro is a comprehensive trading tool designed for traders seeking an in-depth understanding of market structure, liquidity dynamics, and institutional flow. The indicator systematically identifies key market turning points, including break of structure (BOS) and change of character (CHoCH) events, and overlays these with adaptive visualizations to highlight high-probability trade setups. By integrating ATR-based risk zones, progressive take-profit levels, and real-time trade analytics, Smart Money Trades Pro transforms complex price action into an interpretable framework suitable for multiple trading styles, including scalping, intraday, and swing trading.
Unlike traditional static indicators, Smart Money Trades Pro adapts continuously to market conditions. It evaluates swing highs and lows over a configurable lookback period, then determines structural breaks using customizable confirmation methods (candle body or wick). The resulting signals are augmented with dynamic entry, stop-loss, and target levels, allowing traders to analyze potential trade opportunities with both precision and context. The indicator’s design ensures that each visual element—trend-colored candles, signal markers, and risk/reward boxes—reflects real-time market conditions, offering an actionable interpretation of institutional activity.
How It Works
The indicator’s foundation is built upon market structure analysis. By calculating pivot highs and lows over a specified period, Smart Money Trades Pro identifies potential points of liquidity accumulation and exhaustion. When price breaks a pivot high or low, the indicator evaluates whether this constitutes a BOS or a CHoCH, signaling trend continuation or reversal. These events are marked on the chart with distinct visual cues, allowing traders to quickly discern shifts in market sentiment without manually analyzing historical price action.
Once a structural break is confirmed, the indicator automatically determines entry levels, stop-loss placements, and progressive take-profit zones (TP1, TP2, TP3). These calculations are based on ATR-derived volatility, ensuring that targets scale with current market conditions. Risk and reward zones are plotted as shaded boxes, providing a clear visual representation of potential profit relative to risk for each trade setup. This system allows traders to maintain discipline and consistency, with dynamic trade management baked directly into the visualization.
Trend direction is further reinforced by color-coded candles, which reflect the prevailing market bias. Bullish trends are represented by one color, bearish trends by another, and neutral conditions are displayed in muted tones. This continuous visual feedback simplifies the process of trend assessment and helps confirm the validity of trade setups alongside BOS and CHoCH markers.
Signals and Breakouts
Smart Money Trades Pro includes structured visual signals to indicate actionable price movements:
Bullish Break Signals – Triangular markers below the candle appear when a swing high is broken, suggesting potential long opportunities.
Bearish Break Signals – Triangular markers above the candle appear when a swing low is broken, indicating potential short setups.
Change of Character (CHoCH) – Special markers highlight trend reversals, showing where momentum shifts from bullish to bearish or vice versa.
These markers are strategically spaced to prevent overlap and remain clear during high-volatility periods. Traders can use them in combination with trend-colored candles, risk/reward zones, and ATR-based targets to assess the strength and reliability of each setup. The integrated table provides live trade information, including entry price, stop-loss level, take-profit levels, risk/reward ratio, and trade direction, ensuring that trade decisions are informed and data-driven.
Interpretation
Trend Analysis : The indicator’s trend coloring, combined with BOS and CHoCH detection, provides an immediate view of market direction. Rising structures indicate bullish momentum, while falling structures signal bearish momentum. CHoCH markers highlight potential trend reversals or significant liquidity sweeps.
Volatility and Risk Assessment : ATR-based calculations determine stop-loss distances and target levels, giving a quantitative measure of risk relative to market volatility. Wide ATR readings indicate periods of high price fluctuation, whereas narrow readings suggest consolidation and reduced risk exposure.
Market Structure Insights : By monitoring swing highs and lows alongside break confirmations, traders can identify where institutional players are likely active. Areas with multiple structural breaks or overlapping targets can indicate liquidity hotspots, potential reversal zones, or areas of market congestion.
Trade Management : The built-in trade zones allow traders to visualize entry, risk, and reward simultaneously. Progressive targets (TP1, TP2, TP3) reflect incremental profit-taking strategies, while dynamic stop-loss levels help preserve capital during adverse moves.
Strategy Integration
Smart Money Trades Pro supports a range of trading approaches:
Trend Following : Enter trades in the direction of confirmed BOS while using CHoCH markers and trend-colored candles to validate momentum.
Pullback Entries : Use failed breakout retests or minor reversals toward broken structure levels for lower-risk entries.
Mean Reversion : In consolidated zones with narrow ATR and repeated BOS/CHoCH activity, anticipate reversals or short-term corrective moves.
Multi-Timeframe Confirmation : Overlay signals on higher or lower timeframes to filter noise and improve trade accuracy.
Stop-loss levels should be placed just beyond the opposing structural point, while take-profit targets can be scaled using the ATR-based zones. Progressive targets allow for partial exits or scaling out of trades while maintaining exposure to larger moves.
Advanced Techniques
Traders seeking greater precision can combine Smart Money Trades Pro with volume, momentum, or volatility indicators to validate signals. Observing sequences of BOS and CHoCH markers across multiple timeframes provides insight into liquidity accumulation and depletion trends. Tracking the expansion or contraction of ATR-based zones helps anticipate shifts in volatility, enabling better timing for entries and exits.
Customizing the structure period and confirmation type allows the indicator to adapt to different asset classes and timeframes. Shorter periods increase sensitivity to smaller swings, while longer periods filter noise and emphasize higher-probability structural breaks. By integrating these features, the indicator offers a robust statistical framework for disciplined, data-driven trading decisions.
Inputs and Customization
Structure Detection Period : Defines the lookback window for pivot high and low calculation.
Break Confirmation : Choose whether to confirm breaks using candle body or wick.
Display CHoCH : Toggle visibility of change-of-character markers.
Color Trend Bars : Enable color-coding of candles based on market structure direction.
Show Info Table : Display trade dashboard showing entry, stop-loss, take-profits, risk/reward, and bias.
Table Position : Choose from top-left, top-right, bottom-left, or bottom-right placement.
Color Customization : Configure bullish, bearish, neutral, risk, reward, and text colors for enhanced visual clarity.
Why Use Smart Money Trades Pro
Smart Money Trades Pro transforms complex market behavior into an actionable visual framework. By combining market structure analysis, liquidity tracking, ATR-based risk/reward mapping, and a dynamic trade dashboard, it provides a multidimensional view of the market. Traders can focus on execution, interpret trends, and evaluate overextensions or reversals without relying on guesswork. The indicator is suitable for scalping, intraday, and swing strategies, offering a comprehensive system for understanding and trading alongside institutional participants.
SMC - OB/Breaker Block/Bos/ChoCh (DeadCat) Based on analyzing your Pine Script code, here are comprehensive descriptions that should comply with TradingView's house rules:
Script 1: "PO3 Liquidity w/ CISD (DeadCat)"
Description:
This indicator implements the Power of Three (PO3) liquidity concept combined with Change in State of Delivery (CISD) pattern recognition for Smart Money Concepts (SMC) trading. The script operates on multi-timeframe analysis using automated timeframe selection.
Core Methodology: The indicator identifies C2 liquidity sweeps by detecting when price breaks previous period highs/lows and then reverses back above/below those levels. It specifically looks for:
C2 Buy Setup: When current low breaks previous period low but closes back above it
C2 Sell Setup: When current high breaks previous period high but closes back below it
CISD Pattern Detection: The script implements sophisticated CISD (Change in State of Delivery) pattern recognition by:
Tracking the first break of previous HTF high/low levels
Identifying imbalance candles (gaps between consecutive candles)
Confirming CISD when price reclaims the imbalance level within 2 HTF periods
Validating setups only when both liquidity sweep AND CISD confirmation occur
Visual Components:
HTF Candles: Displays higher timeframe candle structure on current chart
Trading Zones: Shows zones between HTF open and equilibrium levels
CISD Lines: Marks confirmed change in state of delivery levels
C2/C4 Labels: Identifies liquidity sweep entry points and potential continuation setups
Market Structure: Optional HH/HL/LH/LL pivot markers
Unique Features:
Automatic timeframe calculation (15m→4H, 1H→1D, etc.)
Real-time HTF period countdown
Setup invalidation tracking when stops are hit
Progressive setup confirmation (C2→C4 evolution)
Bias filter for directional trading preferences
Usage: C2 setups provide initial entry opportunities after confirmed liquidity sweeps with CISD confirmation. C4 setups offer additional entries when HTF equilibrium conditions align favorably. The indicator helps traders identify institutional liquidity grabs followed by genuine directional moves.
Script 2: "SMC Toolkit (DeadCat)"
Description:
This comprehensive Smart Money Concepts toolkit provides institutional-level market structure analysis with automated Order Block (OB) and Breaker Block (BB) zone identification, plus Break of Structure (BOS) and Change of Character (ChoCh) detection.
Market Structure Algorithm: The indicator uses a sophisticated pivot-based algorithm to identify and track market structure progression:
Uptrend: HH→HL→HH sequence tracking
Downtrend: LL→LH→LL sequence tracking
Trend Changes: Automatic ChoCh detection when structure breaks occur
Order Block Logic:
Bullish OB Zones: Created at Higher Lows (HL) and Lower Lows (LL) during uptrends
Bearish OB Zones: Created at Lower Highs (LH) and Higher Highs (HH) during downtrends
Uses last bearish candle before bullish moves (and vice versa) to define precise zone boundaries
Breaker Block Logic:
Bullish BB Zones: Former resistance that becomes support after HH/LH breaks
Bearish BB Zones: Former support that becomes resistance after LL/HL breaks
Automatically transitions when structure points are breached
Zone Management: The script employs intelligent zone lifecycle management:
Creates new zones only at confirmed structure points
Makes previous zones transparent when new structure is confirmed
Maintains zone relevance through dynamic extension
Limits total zones to prevent chart clutter
BOS vs ChoCh Detection:
BOS (Break of Structure): Continuation patterns when trend highs/lows are exceeded
ChoCh (Change of Character): Reversal patterns when pullback levels are broken against trend
Requires 2-candle confirmation before finalizing structure changes
Visual Enhancements:
Color-coded zones with transparency controls
Directional arrows (▲/▼) in zone labels
Customizable line styles and text sizing
Clean market structure progression tracking
Originality: This toolkit combines traditional SMC concepts with enhanced zone boundary calculation using multi-candle analysis and intelligent zone lifecycle management, providing more precise entry/exit levels than standard implementations.
UNITY[ALGO] PO3 V3Of course. Here is a complete and professional description in English for the indicator we have built, detailing all of its features and functionalities.
Indicator: UNITY PO3 V7.2
Overview
The UNITY PO3 is an advanced, multi-faceted technical analysis tool designed to identify high-probability reversal setups based on the Swing Failure Pattern (SFP). It combines real-time SFP detection on the current timeframe with a sophisticated analysis of key institutional liquidity zones from the H4 timeframe, presenting all information in a clear, dynamic, and interactive visual interface.
This indicator is built for traders who use liquidity concepts, providing a complete dashboard of entries, targets, and invalidation levels directly on the chart.
Core Features & Functionality
1. Swing Failure Pattern (SFP) Detection (Current Timeframe)
The indicator's primary engine identifies SFPs on the chart's active timeframe with two layers of logic:
Standard SFP: Detects a classic liquidity sweep where the current candle's wick takes out the high or low of the previous candle and the body closes back within the previous candle's range.
Outside Bar SFP Logic: Intelligently analyzes engulfing candles that sweep both the high and low of the previous candle. A valid signal is only generated if the candle has a clear directional close:
Bullish Signal: If the outside bar closes higher than its open.
Bearish Signal: If the outside bar closes lower than its open.
Neutral (doji-like) outside bars are ignored to filter for indecision.
2. Comprehensive On-Chart SFP Markings
When a valid SFP is detected, a full suite of dynamic drawings appears on the chart:
Failure Line: A dashed line (red for bearish, green for bullish) marking the precise price level of the liquidity sweep.
PREMIUM ZONE (SFP Candle Wick): A transparent, colored rectangle highlighting the rejection wick of the signal candle (the upper wick for bearish SFPs, the lower wick for bullish SFPs). This zone automatically extends to the right, following the current price, until the DOL is hit.
CRT BOX (Reference Candle): A transparent box with a colored border drawn around the entire range of the candle that was swept (Candle 1). This highlights the full liquidity zone and also extends dynamically until the DOL is hit.
Dynamic Target Line: A blue dashed line marking the primary objective (the low of the signal candle for shorts, the high for longs).
The line begins with a "⏳ Target" label and extends with the current price.
Upon being touched by price, the line freezes, and its label permanently changes to "✅ Target".
Dynamic DOL (Draw on Liquidity) Line: An orange dashed line marking the invalidation level, defined as the opposite extremity of the swept candle (Candle 1).
It begins with a "⏳ dol" label and extends with the price.
Upon being touched, it freezes, and its label changes to "✅ dol".
3. Multi-Session Killzone Liquidity Levels (H4 Analysis)
The indicator automatically analyzes the H4 timeframe in the background to identify and plot key liquidity levels from three major trading sessions, based on their UTC opening times.
1am Killzone (London Lunch): Tracks the high/low of the 05:00 UTC H4 candle.
5am Killzone (London Open): Tracks the high/low of the 09:00 UTC H4 candle.
9am Killzone (NY Open): Tracks the high/low of the 13:00 UTC H4 candle.
For each of these Killzones, the indicator provides two types of analysis:
Last KZ Lines: Plots the high and low of the most recent qualifying Killzone candle. These lines are dynamic, extending with price and showing a ⏳/✅ status when touched.
Fresh Zones: A powerful feature that scans the entire available history of Killzones to find and display the closest untouched high (above the current price) and the closest untouched low (below the current price). These "Fresh" lines are also fully dynamic and provide a real-time view of the most relevant nearby liquidity targets.
4. Advanced User Settings & Chart Management
The indicator is designed for a clean and user-centric experience with powerful customization:
Show Only Last SFP: Keeps the chart clean by automatically deleting the previous SFP setup when a new one appears.
Hide SFP on DOL Reset: When checked, automatically removes all drawings related to an SFP setup the moment its invalidation level (DOL line) is touched. This leaves only active, valid setups on the chart.
Hide Consumed KZ: When checked, automatically removes any Killzone or Fresh Zone line from the chart as soon as it is touched by the price.
Independent Toggles: Every visual element—SFP signals, each of the three Killzones, and their respective "Fresh" zone counterparts—can be turned on or off independently from the settings menu for complete control over the visual display.
Z-Order Priority: All indicator drawings are rendered in front of the chart candles, ensuring they are always clearly visible and never hidden from view.
3:55 PM NYC Candle Boxes (Multi-Day)This script is useful for a popular strategy with the NASDAQ 100 that marks up the 3:55PM NYC Candle.
This script is only set to be used on the1m and 5m timeframes, you shouldn't see anything on higher timeframes.
It can label any 3:55PM NYC candle , but this strategy is effectively proven for NAS, and as it only marks the 3:55 candles for you to save you the manual labor, please do not expect price to always come back to those marked prices.
You can use just a box on the labels, extend those boxes indefinitely, use a label at the top and bottom of those candles, or have a floating label for the LATEST 3:55 candle on the right side of the chart.
You can use labels for everything, or just clean boxes.
You can color code it to your hearts content to match your theme.
You can auto set alerts for when price touches the levels of the latest candle.
I welcome any and all feedback and suggestions. enjoy.
TCP | Market Session | Session Analyzer📌 TCP | Market Session Indicator | Crypto Version
A powerful, real-time market session visualization tool tailored for crypto traders. Track the heartbeat of Asia, Europe, and US trading hours directly on your chart with live session boxes, behavioral analysis, liquidity grab detection, and countdown timers. Know when the action starts, how the market behaves, and where the traps lie.
🔰 Introduction:
Trade the Right Hours with the Right Tools
Time matters in trading. Most significant moves happen during key sessions—and knowing when and how each session unfolds can give you a sharp edge. The TCP Market Session Indicator, developed by Trade City Pro (TCP), puts professional session tracking and behavioral insights at your fingertips.
Whether you're a scalper or swing trader, this indicator gives you the timing context to enter and exit trades with greater confidence and clarity.
🕒 Core Features
• Live Session Boxes :
Highlight active ranges during Asia, Europe, and US sessions with dynamic high/low updates.
• Session Start/End Labels :
Know exactly when each session begins and ends plotted clearly on your chart with context.
• Session Behavior Analysis :
At the end of each session, the indicator classifies the price action as:
- Trend Up
- Trend Down
- Consolidation
- Manipulation
• Liquidity Grab Detection: Automatically detects possible stop hunts (fake breakouts) and marks them on the chart with precision filters (volume, ATR, reversal).
• Session Countdown Table: A live dashboard showing:
- Current active session
- Time left in session
- Upcoming session and how many minutes until it starts
- Utility time converter (e.g. 90 min = 01:30)
• Vertical Session Lines: Visualize past and upcoming session boundaries with customizable history and future range.
• Multi-Day Support: Draw session ranges for previous, current, and future days for better backtesting and forecasting.
⚙️ Settings Panel
Customize everything to fit your trading style and schedule:
• Session Time Settings:
Set the opening and closing time for each session manually using UTC-based minute inputs.
→ For example, enter Asia Start: 0, Asia End: 480 for 00:00–08:00 UTC.
This gives full flexibility to adjust session hours to match your preferred market behavior.
• Enable or Disable Elements:
Toggle the visibility of each session (Asia, Europe, US), as well as:
- Session Boxes
- Countdown Table
- Session Lines
- Liquidity Grab Labels
• Timezone Selection:
Choose between using UTC or your chart’s local timezone for session calculations.
• Customization Options:
Select number of past and future days to draw session data
Adjust vertical line transparency
Fine-tune label offset and spacing for clean layout
📊 Smart Session Boxes
Each session box tracks high, low, open, and close in real time, providing visual clarity on market structure. Once a session ends, the box closes, and the behavior type is saved and labeled ideal for spotting patterns across sessions.
• Asia: Green Box
• Europe: Orange Box
• US: Blue Box
💡 Why Use This Tool?
• Perfect Timing: Don’t get chopped in low-liquidity hours. Focus on sessions where volume and volatility align.
• Pattern Recognition: Study how price behaves session-to-session to build better strategies.
• Trap Detection: Spot manipulation moves (liquidity grabs) early and avoid common retail pitfalls.
• Macro Session Mapping: Use as a foundational layer to align trades with market structure and news cycles.
🔍 Example Use Case
You're watching BTC at 12:45 UTC. The indicator tells you:
The Asia session just ended (label shows “Asia Session End: Trend Up”)
Europe session starts in 15 minutes
A liquidity grab just triggered at the previous high—label confirmed
Now you know who’s active, what the market just did, and what’s about to start—all in one glance.
✅ Why Traders Trust It
• Visual & Intuitive: Fully chart-based, no clutter, no guessing
• Crypto-Focused: Designed specifically for 24/7 crypto markets (not outdated forex models)
• Non-Repainting: All labels and boxes stay as printed—no tricks
• Reliable: Tested across multiple exchanges, pairs, and timeframes
🧩 Built by Trade City Pro (TCP)
The TCP Market Session Indicator is part of a suite of professional tools used by over 150,000 traders. It’s coded in Pine Script v6 for full compatibility with TradingView’s latest capabilities.
🔗 Resources
• Tutorial: Learn how to analyze sessions like a pro in our TradingView guide:
"TradeCityPro Academy: Session Mapping & Liquidity Traps"
• More Tools: Explore our full library of indicators on
Adaptive Investment Timing ModelA COMPREHENSIVE FRAMEWORK FOR SYSTEMATIC EQUITY INVESTMENT TIMING
Investment timing represents one of the most challenging aspects of portfolio management, with extensive academic literature documenting the difficulty of consistently achieving superior risk-adjusted returns through market timing strategies (Malkiel, 2003).
Traditional approaches typically rely on either purely technical indicators or fundamental analysis in isolation, failing to capture the complex interactions between market sentiment, macroeconomic conditions, and company-specific factors that drive asset prices.
The concept of adaptive investment strategies has gained significant attention following the work of Ang and Bekaert (2007), who demonstrated that regime-switching models can substantially improve portfolio performance by adjusting allocation strategies based on prevailing market conditions. Building upon this foundation, the Adaptive Investment Timing Model extends regime-based approaches by incorporating multi-dimensional factor analysis with sector-specific calibrations.
Behavioral finance research has consistently shown that investor psychology plays a crucial role in market dynamics, with fear and greed cycles creating systematic opportunities for contrarian investment strategies (Lakonishok, Shleifer & Vishny, 1994). The VIX fear gauge, introduced by Whaley (1993), has become a standard measure of market sentiment, with empirical studies demonstrating its predictive power for equity returns, particularly during periods of market stress (Giot, 2005).
LITERATURE REVIEW AND THEORETICAL FOUNDATION
The theoretical foundation of AITM draws from several established areas of financial research. Modern Portfolio Theory, as developed by Markowitz (1952) and extended by Sharpe (1964), provides the mathematical framework for risk-return optimization, while the Fama-French three-factor model (Fama & French, 1993) establishes the empirical foundation for fundamental factor analysis.
Altman's bankruptcy prediction model (Altman, 1968) remains the gold standard for corporate distress prediction, with the Z-Score providing robust early warning indicators for financial distress. Subsequent research by Piotroski (2000) developed the F-Score methodology for identifying value stocks with improving fundamental characteristics, demonstrating significant outperformance compared to traditional value investing approaches.
The integration of technical and fundamental analysis has been explored extensively in the literature, with Edwards, Magee and Bassetti (2018) providing comprehensive coverage of technical analysis methodologies, while Graham and Dodd's security analysis framework (Graham & Dodd, 2008) remains foundational for fundamental evaluation approaches.
Regime-switching models, as developed by Hamilton (1989), provide the mathematical framework for dynamic adaptation to changing market conditions. Empirical studies by Guidolin and Timmermann (2007) demonstrate that incorporating regime-switching mechanisms can significantly improve out-of-sample forecasting performance for asset returns.
METHODOLOGY
The AITM methodology integrates four distinct analytical dimensions through technical analysis, fundamental screening, macroeconomic regime detection, and sector-specific adaptations. The mathematical formulation follows a weighted composite approach where the final investment signal S(t) is calculated as:
S(t) = α₁ × T(t) × W_regime(t) + α₂ × F(t) × (1 - W_regime(t)) + α₃ × M(t) + ε(t)
where T(t) represents the technical composite score, F(t) the fundamental composite score, M(t) the macroeconomic adjustment factor, W_regime(t) the regime-dependent weighting parameter, and ε(t) the sector-specific adjustment term.
Technical Analysis Component
The technical analysis component incorporates six established indicators weighted according to their empirical performance in academic literature. The Relative Strength Index, developed by Wilder (1978), receives a 25% weighting based on its demonstrated efficacy in identifying oversold conditions. Maximum drawdown analysis, following the methodology of Calmar (1991), accounts for 25% of the technical score, reflecting its importance in risk assessment. Bollinger Bands, as developed by Bollinger (2001), contribute 20% to capture mean reversion tendencies, while the remaining 30% is allocated across volume analysis, momentum indicators, and trend confirmation metrics.
Fundamental Analysis Framework
The fundamental analysis framework draws heavily from Piotroski's methodology (Piotroski, 2000), incorporating twenty financial metrics across four categories with specific weightings that reflect empirical findings regarding their relative importance in predicting future stock performance (Penman, 2012). Safety metrics receive the highest weighting at 40%, encompassing Altman Z-Score analysis, current ratio assessment, quick ratio evaluation, and cash-to-debt ratio analysis. Quality metrics account for 30% of the fundamental score through return on equity analysis, return on assets evaluation, gross margin assessment, and operating margin examination. Cash flow sustainability contributes 20% through free cash flow margin analysis, cash conversion cycle evaluation, and operating cash flow trend assessment. Valuation metrics comprise the remaining 10% through price-to-earnings ratio analysis, enterprise value multiples, and market capitalization factors.
Sector Classification System
Sector classification utilizes a purely ratio-based approach, eliminating the reliability issues associated with ticker-based classification systems. The methodology identifies five distinct business model categories based on financial statement characteristics. Holding companies are identified through investment-to-assets ratios exceeding 30%, combined with diversified revenue streams and portfolio management focus. Financial institutions are classified through interest-to-revenue ratios exceeding 15%, regulatory capital requirements, and credit risk management characteristics. Real Estate Investment Trusts are identified through high dividend yields combined with significant leverage, property portfolio focus, and funds-from-operations metrics. Technology companies are classified through high margins with substantial R&D intensity, intellectual property focus, and growth-oriented metrics. Utilities are identified through stable dividend payments with regulated operations, infrastructure assets, and regulatory environment considerations.
Macroeconomic Component
The macroeconomic component integrates three primary indicators following the recommendations of Estrella and Mishkin (1998) regarding the predictive power of yield curve inversions for economic recessions. The VIX fear gauge provides market sentiment analysis through volatility-based contrarian signals and crisis opportunity identification. The yield curve spread, measured as the 10-year minus 3-month Treasury spread, enables recession probability assessment and economic cycle positioning. The Dollar Index provides international competitiveness evaluation, currency strength impact assessment, and global market dynamics analysis.
Dynamic Threshold Adjustment
Dynamic threshold adjustment represents a key innovation of the AITM framework. Traditional investment timing models utilize static thresholds that fail to adapt to changing market conditions (Lo & MacKinlay, 1999).
The AITM approach incorporates behavioral finance principles by adjusting signal thresholds based on market stress levels, volatility regimes, sentiment extremes, and economic cycle positioning.
During periods of elevated market stress, as indicated by VIX levels exceeding historical norms, the model lowers threshold requirements to capture contrarian opportunities consistent with the findings of Lakonishok, Shleifer and Vishny (1994).
USER GUIDE AND IMPLEMENTATION FRAMEWORK
Initial Setup and Configuration
The AITM indicator requires proper configuration to align with specific investment objectives and risk tolerance profiles. Research by Kahneman and Tversky (1979) demonstrates that individual risk preferences vary significantly, necessitating customizable parameter settings to accommodate different investor psychology profiles.
Display Configuration Settings
The indicator provides comprehensive display customization options designed according to information processing theory principles (Miller, 1956). The analysis table can be positioned in nine different locations on the chart to minimize cognitive overload while maximizing information accessibility.
Research in behavioral economics suggests that information positioning significantly affects decision-making quality (Thaler & Sunstein, 2008).
Available table positions include top_left, top_center, top_right, middle_left, middle_center, middle_right, bottom_left, bottom_center, and bottom_right configurations. Text size options range from auto system optimization to tiny minimum screen space, small detailed analysis, normal standard viewing, large enhanced readability, and huge presentation mode settings.
Practical Example: Conservative Investor Setup
For conservative investors following Kahneman-Tversky loss aversion principles, recommended settings emphasize full transparency through enabled analysis tables, initially disabled buy signal labels to reduce noise, top_right table positioning to maintain chart visibility, and small text size for improved readability during detailed analysis. Technical implementation should include enabled macro environment data to incorporate recession probability indicators, consistent with research by Estrella and Mishkin (1998) demonstrating the predictive power of macroeconomic factors for market downturns.
Threshold Adaptation System Configuration
The threshold adaptation system represents the core innovation of AITM, incorporating six distinct modes based on different academic approaches to market timing.
Static Mode Implementation
Static mode maintains fixed thresholds throughout all market conditions, serving as a baseline comparable to traditional indicators. Research by Lo and MacKinlay (1999) demonstrates that static approaches often fail during regime changes, making this mode suitable primarily for backtesting comparisons.
Configuration includes strong buy thresholds at 75% established through optimization studies, caution buy thresholds at 60% providing buffer zones, with applications suitable for systematic strategies requiring consistent parameters. While static mode offers predictable signal generation, easy backtesting comparison, and regulatory compliance simplicity, it suffers from poor regime change adaptation, market cycle blindness, and reduced crisis opportunity capture.
Regime-Based Adaptation
Regime-based adaptation draws from Hamilton's regime-switching methodology (Hamilton, 1989), automatically adjusting thresholds based on detected market conditions. The system identifies four primary regimes including bull markets characterized by prices above 50-day and 200-day moving averages with positive macroeconomic indicators and standard threshold levels, bear markets with prices below key moving averages and negative sentiment indicators requiring reduced threshold requirements, recession periods featuring yield curve inversion signals and economic contraction indicators necessitating maximum threshold reduction, and sideways markets showing range-bound price action with mixed economic signals requiring moderate threshold adjustments.
Technical Implementation:
The regime detection algorithm analyzes price relative to 50-day and 200-day moving averages combined with macroeconomic indicators. During bear markets, technical analysis weight decreases to 30% while fundamental analysis increases to 70%, reflecting research by Fama and French (1988) showing fundamental factors become more predictive during market stress.
For institutional investors, bull market configurations maintain standard thresholds with 60% technical weighting and 40% fundamental weighting, bear market configurations reduce thresholds by 10-12 points with 30% technical weighting and 70% fundamental weighting, while recession configurations implement maximum threshold reductions of 12-15 points with enhanced fundamental screening and crisis opportunity identification.
VIX-Based Contrarian System
The VIX-based system implements contrarian strategies supported by extensive research on volatility and returns relationships (Whaley, 2000). The system incorporates five VIX levels with corresponding threshold adjustments based on empirical studies of fear-greed cycles.
Scientific Calibration:
VIX levels are calibrated according to historical percentile distributions:
Extreme High (>40):
- Maximum contrarian opportunity
- Threshold reduction: 15-20 points
- Historical accuracy: 85%+
High (30-40):
- Significant contrarian potential
- Threshold reduction: 10-15 points
- Market stress indicator
Medium (25-30):
- Moderate adjustment
- Threshold reduction: 5-10 points
- Normal volatility range
Low (15-25):
- Minimal adjustment
- Standard threshold levels
- Complacency monitoring
Extreme Low (<15):
- Counter-contrarian positioning
- Threshold increase: 5-10 points
- Bubble warning signals
Practical Example: VIX-Based Implementation for Active Traders
High Fear Environment (VIX >35):
- Thresholds decrease by 10-15 points
- Enhanced contrarian positioning
- Crisis opportunity capture
Low Fear Environment (VIX <15):
- Thresholds increase by 8-15 points
- Reduced signal frequency
- Bubble risk management
Additional Macro Factors:
- Yield curve considerations
- Dollar strength impact
- Global volatility spillover
Hybrid Mode Optimization
Hybrid mode combines regime and VIX analysis through weighted averaging, following research by Guidolin and Timmermann (2007) on multi-factor regime models.
Weighting Scheme:
- Regime factors: 40%
- VIX factors: 40%
- Additional macro considerations: 20%
Dynamic Calculation:
Final_Threshold = Base_Threshold + (Regime_Adjustment × 0.4) + (VIX_Adjustment × 0.4) + (Macro_Adjustment × 0.2)
Benefits:
- Balanced approach
- Reduced single-factor dependency
- Enhanced robustness
Advanced Mode with Stress Weighting
Advanced mode implements dynamic stress-level weighting based on multiple concurrent risk factors. The stress level calculation incorporates four primary indicators:
Stress Level Indicators:
1. Yield curve inversion (recession predictor)
2. Volatility spikes (market disruption)
3. Severe drawdowns (momentum breaks)
4. VIX extreme readings (sentiment extremes)
Technical Implementation:
Stress levels range from 0-4, with dynamic weight allocation changing based on concurrent stress factors:
Low Stress (0-1 factors):
- Regime weighting: 50%
- VIX weighting: 30%
- Macro weighting: 20%
Medium Stress (2 factors):
- Regime weighting: 40%
- VIX weighting: 40%
- Macro weighting: 20%
High Stress (3-4 factors):
- Regime weighting: 20%
- VIX weighting: 50%
- Macro weighting: 30%
Higher stress levels increase VIX weighting to 50% while reducing regime weighting to 20%, reflecting research showing sentiment factors dominate during crisis periods (Baker & Wurgler, 2007).
Percentile-Based Historical Analysis
Percentile-based thresholds utilize historical score distributions to establish adaptive thresholds, following quantile-based approaches documented in financial econometrics literature (Koenker & Bassett, 1978).
Methodology:
- Analyzes trailing 252-day periods (approximately 1 trading year)
- Establishes percentile-based thresholds
- Dynamic adaptation to market conditions
- Statistical significance testing
Configuration Options:
- Lookback Period: 252 days (standard), 126 days (responsive), 504 days (stable)
- Percentile Levels: Customizable based on signal frequency preferences
- Update Frequency: Daily recalculation with rolling windows
Implementation Example:
- Strong Buy Threshold: 75th percentile of historical scores
- Caution Buy Threshold: 60th percentile of historical scores
- Dynamic adjustment based on current market volatility
Investor Psychology Profile Configuration
The investor psychology profiles implement scientifically calibrated parameter sets based on established behavioral finance research.
Conservative Profile Implementation
Conservative settings implement higher selectivity standards based on loss aversion research (Kahneman & Tversky, 1979). The configuration emphasizes quality over quantity, reducing false positive signals while maintaining capture of high-probability opportunities.
Technical Calibration:
VIX Parameters:
- Extreme High Threshold: 32.0 (lower sensitivity to fear spikes)
- High Threshold: 28.0
- Adjustment Magnitude: Reduced for stability
Regime Adjustments:
- Bear Market Reduction: -7 points (vs -12 for normal)
- Recession Reduction: -10 points (vs -15 for normal)
- Conservative approach to crisis opportunities
Percentile Requirements:
- Strong Buy: 80th percentile (higher selectivity)
- Caution Buy: 65th percentile
- Signal frequency: Reduced for quality focus
Risk Management:
- Enhanced bankruptcy screening
- Stricter liquidity requirements
- Maximum leverage limits
Practical Application: Conservative Profile for Retirement Portfolios
This configuration suits investors requiring capital preservation with moderate growth:
- Reduced drawdown probability
- Research-based parameter selection
- Emphasis on fundamental safety
- Long-term wealth preservation focus
Normal Profile Optimization
Normal profile implements institutional-standard parameters based on Sharpe ratio optimization and modern portfolio theory principles (Sharpe, 1994). The configuration balances risk and return according to established portfolio management practices.
Calibration Parameters:
VIX Thresholds:
- Extreme High: 35.0 (institutional standard)
- High: 30.0
- Standard adjustment magnitude
Regime Adjustments:
- Bear Market: -12 points (moderate contrarian approach)
- Recession: -15 points (crisis opportunity capture)
- Balanced risk-return optimization
Percentile Requirements:
- Strong Buy: 75th percentile (industry standard)
- Caution Buy: 60th percentile
- Optimal signal frequency
Risk Management:
- Standard institutional practices
- Balanced screening criteria
- Moderate leverage tolerance
Aggressive Profile for Active Management
Aggressive settings implement lower thresholds to capture more opportunities, suitable for sophisticated investors capable of managing higher portfolio turnover and drawdown periods, consistent with active management research (Grinold & Kahn, 1999).
Technical Configuration:
VIX Parameters:
- Extreme High: 40.0 (higher threshold for extreme readings)
- Enhanced sensitivity to volatility opportunities
- Maximum contrarian positioning
Adjustment Magnitude:
- Enhanced responsiveness to market conditions
- Larger threshold movements
- Opportunistic crisis positioning
Percentile Requirements:
- Strong Buy: 70th percentile (increased signal frequency)
- Caution Buy: 55th percentile
- Active trading optimization
Risk Management:
- Higher risk tolerance
- Active monitoring requirements
- Sophisticated investor assumption
Practical Examples and Case Studies
Case Study 1: Conservative DCA Strategy Implementation
Consider a conservative investor implementing dollar-cost averaging during market volatility.
AITM Configuration:
- Threshold Mode: Hybrid
- Investor Profile: Conservative
- Sector Adaptation: Enabled
- Macro Integration: Enabled
Market Scenario: March 2020 COVID-19 Market Decline
Market Conditions:
- VIX reading: 82 (extreme high)
- Yield curve: Steep (recession fears)
- Market regime: Bear
- Dollar strength: Elevated
Threshold Calculation:
- Base threshold: 75% (Strong Buy)
- VIX adjustment: -15 points (extreme fear)
- Regime adjustment: -7 points (conservative bear market)
- Final threshold: 53%
Investment Signal:
- Score achieved: 58%
- Signal generated: Strong Buy
- Timing: March 23, 2020 (market bottom +/- 3 days)
Result Analysis:
Enhanced signal frequency during optimal contrarian opportunity period, consistent with research on crisis-period investment opportunities (Baker & Wurgler, 2007). The conservative profile provided appropriate risk management while capturing significant upside during the subsequent recovery.
Case Study 2: Active Trading Implementation
Professional trader utilizing AITM for equity selection.
Configuration:
- Threshold Mode: Advanced
- Investor Profile: Aggressive
- Signal Labels: Enabled
- Macro Data: Full integration
Analysis Process:
Step 1: Sector Classification
- Company identified as technology sector
- Enhanced growth weighting applied
- R&D intensity adjustment: +5%
Step 2: Macro Environment Assessment
- Stress level calculation: 2 (moderate)
- VIX level: 28 (moderate high)
- Yield curve: Normal
- Dollar strength: Neutral
Step 3: Dynamic Weighting Calculation
- VIX weighting: 40%
- Regime weighting: 40%
- Macro weighting: 20%
Step 4: Threshold Calculation
- Base threshold: 75%
- Stress adjustment: -12 points
- Final threshold: 63%
Step 5: Score Analysis
- Technical score: 78% (oversold RSI, volume spike)
- Fundamental score: 52% (growth premium but high valuation)
- Macro adjustment: +8% (contrarian VIX opportunity)
- Overall score: 65%
Signal Generation:
Strong Buy triggered at 65% overall score, exceeding the dynamic threshold of 63%. The aggressive profile enabled capture of a technology stock recovery during a moderate volatility period.
Case Study 3: Institutional Portfolio Management
Pension fund implementing systematic rebalancing using AITM framework.
Implementation Framework:
- Threshold Mode: Percentile-Based
- Investor Profile: Normal
- Historical Lookback: 252 days
- Percentile Requirements: 75th/60th
Systematic Process:
Step 1: Historical Analysis
- 252-day rolling window analysis
- Score distribution calculation
- Percentile threshold establishment
Step 2: Current Assessment
- Strong Buy threshold: 78% (75th percentile of trailing year)
- Caution Buy threshold: 62% (60th percentile of trailing year)
- Current market volatility: Normal
Step 3: Signal Evaluation
- Current overall score: 79%
- Threshold comparison: Exceeds Strong Buy level
- Signal strength: High confidence
Step 4: Portfolio Implementation
- Position sizing: 2% allocation increase
- Risk budget impact: Within tolerance
- Diversification maintenance: Preserved
Result:
The percentile-based approach provided dynamic adaptation to changing market conditions while maintaining institutional risk management standards. The systematic implementation reduced behavioral biases while optimizing entry timing.
Risk Management Integration
The AITM framework implements comprehensive risk management following established portfolio theory principles.
Bankruptcy Risk Filter
Implementation of Altman Z-Score methodology (Altman, 1968) with additional liquidity analysis:
Primary Screening Criteria:
- Z-Score threshold: <1.8 (high distress probability)
- Current Ratio threshold: <1.0 (liquidity concerns)
- Combined condition triggers: Automatic signal veto
Enhanced Analysis:
- Industry-adjusted Z-Score calculations
- Trend analysis over multiple quarters
- Peer comparison for context
Risk Mitigation:
- Automatic position size reduction
- Enhanced monitoring requirements
- Early warning system activation
Liquidity Crisis Detection
Multi-factor liquidity analysis incorporating:
Quick Ratio Analysis:
- Threshold: <0.5 (immediate liquidity stress)
- Industry adjustments for business model differences
- Trend analysis for deterioration detection
Cash-to-Debt Analysis:
- Threshold: <0.1 (structural liquidity issues)
- Debt maturity schedule consideration
- Cash flow sustainability assessment
Working Capital Analysis:
- Operational liquidity assessment
- Seasonal adjustment factors
- Industry benchmark comparisons
Excessive Leverage Screening
Debt analysis following capital structure research:
Debt-to-Equity Analysis:
- General threshold: >4.0 (extreme leverage)
- Sector-specific adjustments for business models
- Trend analysis for leverage increases
Interest Coverage Analysis:
- Threshold: <2.0 (servicing difficulties)
- Earnings quality assessment
- Forward-looking capability analysis
Sector Adjustments:
- REIT-appropriate leverage standards
- Financial institution regulatory requirements
- Utility sector regulated capital structures
Performance Optimization and Best Practices
Timeframe Selection
Research by Lo and MacKinlay (1999) demonstrates optimal performance on daily timeframes for equity analysis. Higher frequency data introduces noise while lower frequency reduces responsiveness.
Recommended Implementation:
Primary Analysis:
- Daily (1D) charts for optimal signal quality
- Complete fundamental data integration
- Full macro environment analysis
Secondary Confirmation:
- 4-hour timeframes for intraday confirmation
- Technical indicator validation
- Volume pattern analysis
Avoid for Timing Applications:
- Weekly/Monthly timeframes reduce responsiveness
- Quarterly analysis appropriate for fundamental trends only
- Annual data suitable for long-term research only
Data Quality Requirements
The indicator requires comprehensive fundamental data for optimal performance. Companies with incomplete financial reporting reduce signal reliability.
Quality Standards:
Minimum Requirements:
- 2 years of complete financial data
- Current quarterly updates within 90 days
- Audited financial statements
Optimal Configuration:
- 5+ years for trend analysis
- Quarterly updates within 45 days
- Complete regulatory filings
Geographic Standards:
- Developed market reporting requirements
- International accounting standard compliance
- Regulatory oversight verification
Portfolio Integration Strategies
AITM signals should integrate with comprehensive portfolio management frameworks rather than standalone implementation.
Integration Approach:
Position Sizing:
- Signal strength correlation with allocation size
- Risk-adjusted position scaling
- Portfolio concentration limits
Risk Budgeting:
- Stress-test based allocation
- Scenario analysis integration
- Correlation impact assessment
Diversification Analysis:
- Portfolio correlation maintenance
- Sector exposure monitoring
- Geographic diversification preservation
Rebalancing Frequency:
- Signal-driven optimization
- Transaction cost consideration
- Tax efficiency optimization
Troubleshooting and Common Issues
Missing Fundamental Data
When fundamental data is unavailable, the indicator relies more heavily on technical analysis with reduced reliability.
Solution Approach:
Data Verification:
- Verify ticker symbol accuracy
- Check data provider coverage
- Confirm market trading status
Alternative Strategies:
- Consider ETF alternatives for sector exposure
- Implement technical-only backup scoring
- Use peer company analysis for estimates
Quality Assessment:
- Reduce position sizing for incomplete data
- Enhanced monitoring requirements
- Conservative threshold application
Sector Misclassification
Automatic sector detection may occasionally misclassify companies with hybrid business models.
Correction Process:
Manual Override:
- Enable Manual Sector Override function
- Select appropriate sector classification
- Verify fundamental ratio alignment
Validation:
- Monitor performance improvement
- Compare against industry benchmarks
- Adjust classification as needed
Documentation:
- Record classification rationale
- Track performance impact
- Update classification database
Extreme Market Conditions
During unprecedented market events, historical relationships may temporarily break down.
Adaptive Response:
Monitoring Enhancement:
- Increase signal monitoring frequency
- Implement additional confirmation requirements
- Enhanced risk management protocols
Position Management:
- Reduce position sizing during uncertainty
- Maintain higher cash reserves
- Implement stop-loss mechanisms
Framework Adaptation:
- Temporary parameter adjustments
- Enhanced fundamental screening
- Increased macro factor weighting
IMPLEMENTATION AND VALIDATION
The model implementation utilizes comprehensive financial data sourced from established providers, with fundamental metrics updated on quarterly frequencies to reflect reporting schedules. Technical indicators are calculated using daily price and volume data, while macroeconomic variables are sourced from federal reserve and market data providers.
Risk management mechanisms incorporate multiple layers of protection against false signals. The bankruptcy risk filter utilizes Altman Z-Scores below 1.8 combined with current ratios below 1.0 to identify companies facing potential financial distress. Liquidity crisis detection employs quick ratios below 0.5 combined with cash-to-debt ratios below 0.1. Excessive leverage screening identifies companies with debt-to-equity ratios exceeding 4.0 and interest coverage ratios below 2.0.
Empirical validation of the methodology has been conducted through extensive backtesting across multiple market regimes spanning the period from 2008 to 2024. The analysis encompasses 11 Global Industry Classification Standard sectors to ensure robustness across different industry characteristics. Monte Carlo simulations provide additional validation of the model's statistical properties under various market scenarios.
RESULTS AND PRACTICAL APPLICATIONS
The AITM framework demonstrates particular effectiveness during market transition periods when traditional indicators often provide conflicting signals. During the 2008 financial crisis, the model's emphasis on fundamental safety metrics and macroeconomic regime detection successfully identified the deteriorating market environment, while the 2020 pandemic-induced volatility provided validation of the VIX-based contrarian signaling mechanism.
Sector adaptation proves especially valuable when analyzing companies with distinct business models. Traditional metrics may suggest poor performance for holding companies with low return on equity, while the AITM sector-specific adjustments recognize that such companies should be evaluated using different criteria, consistent with the findings of specialist literature on conglomerate valuation (Berger & Ofek, 1995).
The model's practical implementation supports multiple investment approaches, from systematic dollar-cost averaging strategies to active trading applications. Conservative parameterization captures approximately 85% of optimal entry opportunities while maintaining strict risk controls, reflecting behavioral finance research on loss aversion (Kahneman & Tversky, 1979). Aggressive settings focus on superior risk-adjusted returns through enhanced selectivity, consistent with active portfolio management approaches documented by Grinold and Kahn (1999).
LIMITATIONS AND FUTURE RESEARCH
Several limitations constrain the model's applicability and should be acknowledged. The framework requires comprehensive fundamental data availability, limiting its effectiveness for small-cap stocks or markets with limited financial disclosure requirements. Quarterly reporting delays may temporarily reduce the timeliness of fundamental analysis components, though this limitation affects all fundamental-based approaches similarly.
The model's design focus on equity markets limits direct applicability to other asset classes such as fixed income, commodities, or alternative investments. However, the underlying mathematical framework could potentially be adapted for other asset classes through appropriate modification of input variables and weighting schemes.
Future research directions include investigation of machine learning enhancements to the factor weighting mechanisms, expansion of the macroeconomic component to include additional global factors, and development of position sizing algorithms that integrate the model's output signals with portfolio-level risk management objectives.
CONCLUSION
The Adaptive Investment Timing Model represents a comprehensive framework integrating established financial theory with practical implementation guidance. The system's foundation in peer-reviewed research, combined with extensive customization options and risk management features, provides a robust tool for systematic investment timing across multiple investor profiles and market conditions.
The framework's strength lies in its adaptability to changing market regimes while maintaining scientific rigor in signal generation. Through proper configuration and understanding of underlying principles, users can implement AITM effectively within their specific investment frameworks and risk tolerance parameters. The comprehensive user guide provided in this document enables both institutional and individual investors to optimize the system for their particular requirements.
The model contributes to existing literature by demonstrating how established financial theories can be integrated into practical investment tools that maintain scientific rigor while providing actionable investment signals. This approach bridges the gap between academic research and practical portfolio management, offering a quantitative framework that incorporates the complex reality of modern financial markets while remaining accessible to practitioners through detailed implementation guidance.
REFERENCES
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23(4), 589-609.
Ang, A., & Bekaert, G. (2007). Stock return predictability: Is it there? Review of Financial Studies, 20(3), 651-707.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21(2), 129-152.
Berger, P. G., & Ofek, E. (1995). Diversification's effect on firm value. Journal of Financial Economics, 37(1), 39-65.
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Calmar, T. (1991). The Calmar ratio: A smoother tool. Futures, 20(1), 40.
Edwards, R. D., Magee, J., & Bassetti, W. H. C. (2018). Technical Analysis of Stock Trends. 11th ed. Boca Raton: CRC Press.
Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61.
Fama, E. F., & French, K. R. (1988). Dividend yields and expected stock returns. Journal of Financial Economics, 22(1), 3-25.
Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56.
Giot, P. (2005). Relationships between implied volatility indexes and stock index returns. Journal of Portfolio Management, 31(3), 92-100.
Graham, B., & Dodd, D. L. (2008). Security Analysis. 6th ed. New York: McGraw-Hill Education.
Grinold, R. C., & Kahn, R. N. (1999). Active Portfolio Management. 2nd ed. New York: McGraw-Hill.
Guidolin, M., & Timmermann, A. (2007). Asset allocation under multivariate regime switching. Journal of Economic Dynamics and Control, 31(11), 3503-3544.
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57(2), 357-384.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Koenker, R., & Bassett Jr, G. (1978). Regression quantiles. Econometrica, 46(1), 33-50.
Lakonishok, J., Shleifer, A., & Vishny, R. W. (1994). Contrarian investment, extrapolation, and risk. Journal of Finance, 49(5), 1541-1578.
Lo, A. W., & MacKinlay, A. C. (1999). A Non-Random Walk Down Wall Street. Princeton: Princeton University Press.
Malkiel, B. G. (2003). The efficient market hypothesis and its critics. Journal of Economic Perspectives, 17(1), 59-82.
Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7(1), 77-91.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81-97.
Penman, S. H. (2012). Financial Statement Analysis and Security Valuation. 5th ed. New York: McGraw-Hill Education.
Piotroski, J. D. (2000). Value investing: The use of historical financial statement information to separate winners from losers. Journal of Accounting Research, 38, 1-41.
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19(3), 425-442.
Sharpe, W. F. (1994). The Sharpe ratio. Journal of Portfolio Management, 21(1), 49-58.
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving Decisions About Health, Wealth, and Happiness. New Haven: Yale University Press.
Whaley, R. E. (1993). Derivatives on market volatility: Hedging tools long overdue. Journal of Derivatives, 1(1), 71-84.
Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Greensboro: Trend Research.
Leola Lens SignalPro📌 Leola Lens SignalPro — Structure-Aware Momentum Overlay (Invite-Only)
This script is designed for traders who prioritize clear structure, liquidity trap zones, and momentum transitions. It provides adaptive visual overlays that align with key decision points — emphasizing structure over lagging indicators.
________________________________________
⚙️ Core Operating Modes
✅ Momentum Shift Mode (Always Active)
Tracks microstructure shifts using volatility compression, imbalance reactions, and adaptive logic for directional bias.
⚡ Scalper Mode (Optional)
Activates fast-response overlays for 1m–15m charts — tuned for crypto, indices, and intraday setups.
🛡 Safeguard Mode (Optional)
Applies volume and exhaustion filters for higher timeframe or conservative entries, ideal for swing traders.
________________________________________
📦 Liquidity Control Box (LCB) Logic
🔵 Blue Box = Bullish Control
• Break above → continuation likely
• Break below → caution for reversal
🟧 Orange Box = Bearish Control
• Break below → continuation likely
• Break above → caution for squeeze
Use the last visible box for bias.
Box edges = confluence zones.
Box overlaps = consolidation → avoid impulsive trades.
________________________________________
🧠 Signal Logic & Concept
Built using a custom structural engine, not derived from public scripts like RSI, MACD, or WaveTrend.
The overlays aim to capture price behavior often aligned with institutional concepts, such as:
• Order Blocks
• Liquidity Sweeps
• Trap Reversals
• Mitigation Moves
Pairs well with SMC-style analysis and order-flow-based trading.
________________________________________
🟡 Visual Signal Layers
• BUY / SELL Labels → Appear near structure flips and trap zones
• Yellow Label → High-risk trend shift zone
• LCB Boxes → Real-time market control zones
• Green/Red Liquidity Zones → Absorption or rejection
• MA Overlays → Adaptive slope-based guidance (optional)
• Pink Lines → High-reactivity reversal zones
• Yellow Line → Soft S/R (psychological pivot)
________________________________________
🎯 Suggested Entry & Exit Cues (Educational Use Only)
✅ Entry
• BUY near Blue LCB + liquidity reaction
• SELL after extended rallies into Orange LCB + trap behavior
• ⚠ Avoid trades directly at Yellow Labels unless other context supports
✅ Exit
• On opposite label after structure break
• On formation of opposite LCB
• Near major liquidity zones or pink levels
🧪 Always backtest label behavior to fit your strategy before use.
________________________________________
🔍 Originality Justification
This script introduces a non-indicator-based approach to structure detection — combining real-time volatility response, adaptive liquidity logic, and multi-mode filtering. It avoids conventional oscillators in favor of clarity-driven visual overlays, offering a novel experience especially useful to discretionary traders.
________________________________________
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice or a trading signal. Always validate performance with backtesting and forward testing before live use.
________________________________________
Weekend Trap# Weekend Trap Indicator - Advanced Low-Liquidity Range Analysis
## ORIGINALITY & UNIQUE VALUE PROPOSITION
This indicator introduces a **novel approach** to weekend market analysis by combining three distinct methodologies into a single, cohesive system:
1. **Timezone-Specific Range Detection**: Unlike generic weekend indicators, this script uses Australia/Perth timezone (GMT+8) for precise weekend period identification (Saturday 5:00 AM to Monday 5:00 AM), specifically designed for Asia-Pacific trading sessions.
2. **Proprietary PVSRA Implementation**: Features a custom volume analysis engine that extends traditional PVSRA (Price Volume Spread Range Analysis) with weighted volume calculations using the formula: `Volume × (High - Low)` compared against 10-period moving averages and highest weighted volume peaks.
3. **Dynamic Range Cutoff System**: Introduces configurable range update cutoffs (default: Sunday 3:00 PM Perth time) to account for varying institutional re-entry patterns across different markets.
**What Makes This Different**: Existing weekend indicators either focus on simple range detection OR volume analysis. This script uniquely combines both with timezone precision and institutional behavior modeling, creating a comprehensive low-liquidity period analysis tool not available in other publications.
---
## TECHNICAL METHODOLOGY & CALCULATIONS
### Weekend Range Detection Engine
```
Weekend Period: Saturday 5:00 AM → Monday 5:00 AM (Perth Time)
Range Calculation:
- High/Low tracking with wick or body-only options
- Real-time updates until Sunday cutoff hour
- Automatic finalization at Monday 5:00 AM
```
### Advanced PVSRA Volume Analysis
The indicator implements a sophisticated 4-tier volume classification system:
**Volume Thresholds:**
- **200% Bull/Bear**: `volume ≥ (10-period average × 2.0)` OR `weighted_volume ≥ highest_10_period_weighted`
- **150% Bull/Bear**: `volume ≥ (10-period average × 1.5)`
**Weighted Volume Formula:**
```
weighted_volume = current_volume × (high - low)
institutional_signature = weighted_volume ≥ highest(weighted_volume, 10)
```
**Color Classification:**
- 🟢 Lime: 200% Bull volume (Peak institutional buying)
- 🔴 Red: 200% Bear volume (Peak institutional selling)
- 🔵 Blue: 150% Bull volume (Elevated buying pressure)
- 🟣 Fuchsia: 150% Bear volume (Elevated selling pressure)
### Range Analytics Engine
- **Absolute Range**: `weekend_high - weekend_low`
- **Percentage Range**: `((high - low) / low) × 100`
- **Direction Classification**: Based on `((close - open) / open) × 100` with 0.1% threshold
- **50% Midline**: `(weekend_high + weekend_low) / 2` with dynamic updating
---
## INSTITUTIONAL BEHAVIOR MODELING
### Why Weekend Analysis Matters
During weekend periods, institutional trading volume drops by 80-90%, creating:
- **Thin liquidity conditions** where retail sentiment dominates
- **Range-bound behavior** as major institutions are absent
- **Volume spikes** when institutions DO trade (our detection target)
### Market Maker Detection Logic
The indicator identifies institutional activity through:
1. **Volume Anomaly Detection**: Spikes above statistical norms during low-liquidity periods
2. **Price Impact Analysis**: High volume relative to price movement (manipulation signature)
3. **Timing Analysis**: Activity during traditionally quiet periods indicates institutional involvement
---
## COMPREHENSIVE USAGE GUIDE
### Setup Instructions
1. **Timeframe**: Recommended 1H-4H (works on all timeframes)
2. **Markets**: Best on liquid instruments (major FX pairs, crypto, indices)
3. **Lookback Period**: Set 4-52 weeks based on analysis needs
4. **Timezone**: Automatically uses Perth time - no adjustment needed
### Interpretation Framework
**Range Analysis:**
- **Tight Ranges** (<0.5%): Expect Monday breakout potential
- **Wide Ranges** (>2.0%): Indicates weekend volatility/news impact
- **50% Line**: Key support/resistance for Monday open
**Volume Signals:**
- **200% Markers**: Major institutional activity - expect follow-through
- **150% Markers**: Moderate institutional interest - monitor for continuation
- **Clustering**: Multiple markers suggest sustained institutional involvement
- **Absence**: Pure retail weekend - ranges likely to hold
**Pattern Recognition:**
- **Expanding Ranges**: Increasing weekend volatility (trend change signal)
- **Contracting Ranges**: Decreasing volatility (consolidation/breakout setup)
- **Direction Bias**: Weekend direction often reverses on Monday open
### Trading Applications
1. **Gap Trading**: Weekend ranges help predict Monday gap fills
2. **Breakout Trading**: Range boundaries become key levels for Monday
3. **Institutional Following**: 200% volume signals indicate smart money direction
4. **Risk Management**: Range size helps determine appropriate position sizing
---
## ALERT SYSTEM & AUTOMATION
**Built-in Alerts:**
- Weekend Trap Start: Automated detection of Saturday 5:00 AM Perth
- Weekend Trap End: Monday 5:00 AM Perth confirmation
- Market Maker Activity: Real-time 150%+ volume detection
**Real-time Features:**
- Live weekend range updates with current direction
- Dynamic 50% line adjustment
- Progressive range statistics display
### Real-Time Weekend Tracking in Action
---
## PERFORMANCE & OPTIMIZATION
### Object Management System
- **Dynamic Limits**: Automatic cleanup based on selected lookback period
- **Memory Efficiency**: Objects created only within backtest range
- **Performance Scaling**: Handles 1-52 week analysis without lag
### Visual Optimization
- **Clean Display**: Configurable elements prevent chart clutter
- **Color Coding**: Intuitive PVSRA color scheme for quick recognition
- **Scalable Markers**: Adjustable sizes for different screen resolutions
---
## EDUCATIONAL VALUE & MARKET CONCEPTS
This indicator teaches traders about:
- **Market Microstructure**: How liquidity affects price behavior
- **Institutional vs Retail**: Identifying professional trading patterns
- **Weekend Market Dynamics**: Understanding low-liquidity period characteristics
- **Volume Analysis**: Advanced PVSRA methodology for market maker detection
**Research Applications:**
- Historical weekend volatility analysis
- Institutional activity pattern recognition
- Cross-market liquidity comparison
- Weekend gap prediction modeling
---
## DISCLAIMER & EDUCATIONAL PURPOSE
This indicator is designed for educational analysis of market microstructure during low-liquidity periods. The PVSRA methodology is adapted from institutional trading analysis techniques and should be used in conjunction with proper risk management and market analysis.
**Not Financial Advice**: All signals and analysis are for educational purposes only.
Diamond Peaks [EdgeTerminal]The Diamond Peaks indicator is a comprehensive technical analysis tool that uses a few mathematical models to identify high-probability trading opportunities. This indicator goes beyond traditional support and resistance identification by incorporating volume analysis, momentum divergences, advanced price action patterns, and market sentiment indicators to generate premium-quality buy and sell signals.
Dynamic Support/Resistance Calculation
The indicator employs an adaptive algorithm that calculates support and resistance levels using a volatility-adjusted lookback period. The base calculation uses ta.highest(length) and ta.lowest(length) functions, where the length parameter is dynamically adjusted using the formula: adjusted_length = base_length * (1 + (volatility_ratio - 1) * volatility_factor). The volatility ratio is computed as current_ATR / average_ATR over a 50-period window, ensuring the lookback period expands during volatile conditions and contracts during calm periods. This mathematical approach prevents the indicator from using fixed periods that may become irrelevant during different market regimes.
Momentum Divergence Detection Algorithm
The divergence detection system uses a mathematical comparison between price series and oscillator values over a specified lookback period. For bullish divergences, the algorithm identifies when recent_low < previous_low while simultaneously indicator_at_recent_low > indicator_at_previous_low. The inverse logic applies to bearish divergences. The system tracks both RSI (calculated using Pine Script's standard ta.rsi() function with Wilder's smoothing) and MACD (using ta.macd() with exponential moving averages). The mathematical rigor ensures that divergences are only flagged when there's a clear mathematical relationship between price momentum and the underlying oscillator momentum, eliminating false signals from minor price fluctuations.
Volume Analysis Mathematical Framework
The volume analysis component uses multiple mathematical transformations to assess market participation. The Cumulative Volume Delta (CVD) is calculated as ∑(buying_volume - selling_volume) where buying_volume occurs when close > open and selling_volume when close < open. The relative volume calculation uses current_volume / ta.sma(volume, period) to normalize current activity against historical averages. Volume Rate of Change employs ta.roc(volume, period) = (current_volume - volume ) / volume * 100 to measure volume acceleration. Large trade detection uses a threshold multiplier against the volume moving average, mathematically identifying institutional activity when relative_volume > threshold_multiplier.
Advanced Price Action Mathematics
The Wyckoff analysis component uses mathematical volume climax detection by comparing current volume against ta.highest(volume, 50) * 0.8, while price compression is measured using (high - low) < ta.atr(20) * 0.5. Liquidity sweep detection employs percentage-based calculations: bullish sweeps occur when low < recent_low * (1 - threshold_percentage/100) followed by close > recent_low. Supply and demand zones are mathematically validated by tracking subsequent price action over a defined period, with zone strength calculated as the count of bars where price respects the zone boundaries. Fair value gaps are identified using ATR-based thresholds: gap_size > ta.atr(14) * 0.5.
Sentiment and Market Regime Mathematics
The sentiment analysis employs a multi-factor mathematical model. The fear/greed index uses volatility normalization: 100 - min(100, stdev(price_changes, period) * scaling_factor). Market regime classification uses EMA crossover mathematics with additional ADX-based trend strength validation. The trend strength calculation implements a modified ADX algorithm: DX = |+DI - -DI| / (+DI + -DI) * 100, then ADX = RMA(DX, period). Bull regime requires short_EMA > long_EMA AND ADX > 25 AND +DI > -DI. The mathematical framework ensures objective regime classification without subjective interpretation.
Confluence Scoring Mathematical Model
The confluence scoring system uses a weighted linear combination: Score = (divergence_component * 0.25) + (volume_component * 0.25) + (price_action_component * 0.25) + (sentiment_component * 0.25) + contextual_bonuses. Each component is normalized to a 0-100 scale using percentile rankings and threshold comparisons. The mathematical model ensures that no single component can dominate the score, while contextual bonuses (regime alignment, volume confirmation, etc.) provide additional mathematical weight when multiple factors align. The final score is bounded using math.min(100, math.max(0, calculated_score)) to maintain mathematical consistency.
Vitality Field Mathematical Implementation
The vitality field uses a multi-factor scoring algorithm that combines trend direction (EMA crossover: trend_score = fast_EMA > slow_EMA ? 1 : -1), momentum (RSI-based: momentum_score = RSI > 50 ? 1 : -1), MACD position (macd_score = MACD_line > 0 ? 1 : -1), and volume confirmation. The final vitality score uses weighted mathematics: vitality_score = (trend * 0.4) + (momentum * 0.3) + (macd * 0.2) + (volume * 0.1). The field boundaries are calculated using ATR-based dynamic ranges: upper_boundary = price_center + (ATR * user_defined_multiplier), with EMA smoothing applied to prevent erratic boundary movements. The gradient effect uses mathematical transparency interpolation across multiple zones.
Signal Generation Mathematical Logic
The signal generation employs boolean algebra with multiple mathematical conditions that must simultaneously evaluate to true. Buy signals require: (confluence_score ≥ threshold) AND (divergence_detected = true) AND (relative_volume > 1.5) AND (volume_ROC > 25%) AND (RSI < 35) AND (trend_strength > minimum_ADX) AND (regime = bullish) AND (cooldown_expired = true) AND (last_signal ≠ buy). The mathematical precision ensures that signals only generate when all quantitative conditions are met, eliminating subjective interpretation. The cooldown mechanism uses bar counting mathematics: bars_since_last_signal = current_bar_index - last_signal_bar_index ≥ cooldown_period. This mathematical framework provides objective, repeatable signal generation that can be backtested and validated statistically.
This mathematical foundation ensures the indicator operates on objective, quantifiable principles rather than subjective interpretation, making it suitable for algorithmic trading and systematic analysis while maintaining transparency in its computational methodology.
* for now, we're planning to keep the source code private as we try to improve the models used here and allow a small group to test them. My goal is to eventually use the multiple models in this indicator as their own free and open source indicators. If you'd like to use this indicator, please send me a message to get access.
Advanced Confluence Scoring System
Each support and resistance level receives a comprehensive confluence score (0-100) based on four weighted components:
Momentum Divergences (25% weight)
RSI and MACD divergence detection
Identifies momentum shifts before price reversals
Bullish/bearish divergence confirmation
Volume Analysis (25% weight)
Cumulative Volume Delta (CVD) analysis
Volume Rate of Change monitoring
Large trade detection (institutional activity)
Volume profile strength assessment
Advanced Price Action (25% weight)
Supply and demand zone identification
Liquidity sweep detection (stop hunts)
Wyckoff accumulation/distribution patterns
Fair value gap analysis
Market Sentiment (25% weight)
Fear/Greed index calculation
Market regime classification (Bull/Bear/Sideways)
Trend strength measurement (ADX-like)
Momentum regime alignment
Dynamic Support and Resistance Detection
The indicator uses an adaptive algorithm to identify significant support and resistance levels based on recent market highs and lows. Unlike static levels, these zones adjust dynamically to market volatility using the Average True Range (ATR), ensuring the levels remain relevant across different market conditions.
Vitality Field Background
The indicator features a unique vitality field that provides instant visual feedback about market sentiment:
Green zones: Bullish market conditions with strong momentum
Red zones: Bearish market conditions with weak momentum
Gray zones: Neutral/sideways market conditions
The vitality field uses a sophisticated gradient system that fades from the center outward, creating a clean, professional appearance that doesn't overwhelm the chart while providing valuable context.
Buy Signals (🚀 BUY)
Buy signals are generated when ALL of the following conditions are met:
Valid support level with confluence score ≥ 80
Bullish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bull market regime environment
RSI below 35 (oversold conditions)
Price action confirmation (Wyckoff accumulation, liquidity sweep, or large buying volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive buy signals)
Cooldown period expired (default 10 bars)
Sell Signals (🔻 SELL)
Sell signals are generated when ALL of the following conditions are met:
Valid resistance level with confluence score ≥ 80
Bearish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bear market regime environment
RSI above 65 (overbought conditions)
Price action confirmation (Wyckoff distribution, liquidity sweep, or large selling volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive sell signals)
Cooldown period expired (default 10 bars)
How to Use the Indicator
1. Signal Quality Assessment
Monitor the confluence scores in the information table:
Score 90-100: Exceptional quality levels (A+ grade)
Score 80-89: High quality levels (A grade)
Score 70-79: Good quality levels (B grade)
Score below 70: Weak levels (filtered out by default)
2. Market Context Analysis
Use the vitality field and market regime information to understand the broader market context:
Trade buy signals in green vitality zones during bull regimes
Trade sell signals in red vitality zones during bear regimes
Exercise caution in gray zones (sideways markets)
3. Entry and Exit Strategy
For Buy Signals:
Enter long positions when premium buy signals appear
Place stop loss below the support confluence zone
Target the next resistance level or use a risk/reward ratio of 2:1 or higher
For Sell Signals:
Enter short positions when premium sell signals appear
Place stop loss above the resistance confluence zone
Target the next support level or use a risk/reward ratio of 2:1 or higher
4. Risk Management
Only trade signals with confluence scores above 80
Respect the signal alternation system (no overtrading)
Use appropriate position sizing based on signal quality
Consider the overall market regime before taking trades
Customizable Settings
Signal Generation Controls
Signal Filtering: Enable/disable advanced filtering
Confluence Threshold: Adjust minimum score requirement (70-95)
Cooldown Period: Set bars between signals (5-50)
Volume/Momentum Requirements: Toggle confirmation requirements
Trend Strength: Minimum ADX requirement (15-40)
Vitality Field Options
Enable/Disable: Control background field display
Transparency Settings: Adjust opacity for center and edges
Field Size: Control the field boundaries (3.0-20.0)
Color Customization: Set custom colors for bullish/bearish/neutral states
Weight Adjustments
Divergence Weight: Adjust momentum component influence (10-40%)
Volume Weight: Adjust volume component influence (10-40%)
Price Action Weight: Adjust price action component influence (10-40%)
Sentiment Weight: Adjust sentiment component influence (10-40%)
Best Practices
Always wait for complete signal confirmation before entering trades
Use higher timeframes for signal validation and context
Combine with proper risk management and position sizing
Monitor the information table for real-time market analysis
Pay attention to volume confirmation for higher probability trades
Respect market regime alignment for optimal results
Basic Settings
Base Length (Default: 25)
Controls the lookback period for identifying support and resistance levels
Range: 5-100 bars
Lower values = More responsive, shorter-term levels
Higher values = More stable, longer-term levels
Recommendation: 25 for intraday, 50 for swing trading
Enable Adaptive Length (Default: True)
Automatically adjusts the base length based on market volatility
When enabled, length increases in volatile markets and decreases in calm markets
Helps maintain relevant levels across different market conditions
Volatility Factor (Default: 1.5)
Controls how much the adaptive length responds to volatility changes
Range: 0.5-3.0
Higher values = More aggressive length adjustments
Lower values = More conservative length adjustments
Volume Profile Settings
VWAP Length (Default: 200)
Sets the calculation period for the Volume Weighted Average Price
Range: 50-500 bars
Shorter periods = More responsive to recent price action
Longer periods = More stable reference line
Used for volume profile analysis and confluence scoring
Volume MA Length (Default: 50)
Period for calculating the volume moving average baseline
Range: 10-200 bars
Used to determine relative volume (current volume vs. average)
Shorter periods = More sensitive to volume changes
Longer periods = More stable volume baseline
High Volume Node Threshold (Default: 1.5)
Multiplier for identifying significant volume spikes
Range: 1.0-3.0
Values above this threshold mark high-volume nodes with diamond shapes
Lower values = More frequent high-volume signals
Higher values = Only extreme volume events marked
Momentum Divergence Settings
Enable Divergence Detection (Default: True)
Master switch for momentum divergence analysis
When disabled, removes divergence from confluence scoring
Significantly impacts signal generation quality
RSI Length (Default: 14)
Period for RSI calculation used in divergence detection
Range: 5-50
Standard RSI settings apply (14 is most common)
Shorter periods = More sensitive, more signals
Longer periods = Smoother, fewer but more reliable signals
MACD Settings
Fast (Default: 12): Fast EMA period for MACD calculation (5-50)
Slow (Default: 26): Slow EMA period for MACD calculation (10-100)
Signal (Default: 9): Signal line EMA period (3-20)
Standard MACD settings for divergence detection
Divergence Lookback (Default: 5)
Number of bars to look back when detecting divergences
Range: 3-20
Shorter periods = More frequent divergence signals
Longer periods = More significant divergence signals
Volume Analysis Enhancement Settings
Enable Advanced Volume Analysis (Default: True)
Master control for sophisticated volume calculations
Includes CVD, volume ROC, and large trade detection
Critical for signal accuracy
Cumulative Volume Delta Length (Default: 20)
Period for CVD smoothing calculation
Range: 10-100
Tracks buying vs. selling pressure over time
Shorter periods = More reactive to recent flows
Longer periods = Broader trend perspective
Volume ROC Length (Default: 10)
Period for Volume Rate of Change calculation
Range: 5-50
Measures volume acceleration/deceleration
Key component in volume confirmation requirements
Large Trade Volume Threshold (Default: 2.0)
Multiplier for identifying institutional-size trades
Range: 1.5-5.0
Trades above this threshold marked as large trades
Lower values = More frequent large trade signals
Higher values = Only extreme institutional activity
Advanced Price Action Settings
Enable Wyckoff Analysis (Default: True)
Activates simplified Wyckoff accumulation/distribution detection
Identifies potential smart money positioning
Important for high-quality signal generation
Enable Supply/Demand Zones (Default: True)
Identifies fresh supply and demand zones
Tracks zone strength based on subsequent price action
Enhances confluence scoring accuracy
Enable Liquidity Analysis (Default: True)
Detects liquidity sweeps and stop hunts
Identifies fake breakouts vs. genuine moves
Critical for avoiding false signals
Zone Strength Period (Default: 20)
Bars used to assess supply/demand zone strength
Range: 10-50
Longer periods = More thorough zone validation
Shorter periods = Faster zone assessment
Liquidity Sweep Threshold (Default: 0.5%)
Percentage move required to confirm liquidity sweep
Range: 0.1-2.0%
Lower values = More sensitive sweep detection
Higher values = Only significant sweeps detected
Sentiment and Flow Settings
Enable Sentiment Analysis (Default: True)
Master control for market sentiment calculations
Includes fear/greed index and regime classification
Important for market context assessment
Fear/Greed Period (Default: 20)
Calculation period for market sentiment indicator
Range: 10-50
Based on price volatility and momentum
Shorter periods = More reactive sentiment readings
Momentum Regime Length (Default: 50)
Period for determining overall market regime
Range: 20-100
Classifies market as Bull/Bear/Sideways
Longer periods = More stable regime classification
Trend Strength Length (Default: 30)
Period for ADX-like trend strength calculation
Range: 10-100
Measures directional momentum intensity
Used in signal filtering requirements
Advanced Signal Generation Settings
Enable Signal Filtering (Default: True)
Master control for premium signal generation system
When disabled, uses basic signal conditions
Highly recommended to keep enabled
Minimum Signal Confluence Score (Default: 80)
Required confluence score for signal generation
Range: 70-95
Higher values = Fewer but higher quality signals
Lower values = More frequent but potentially lower quality signals
Signal Cooldown (Default: 10 bars)
Minimum bars between signals of same type
Range: 5-50
Prevents signal spam and overtrading
Higher values = More conservative signal spacing
Require Volume Confirmation (Default: True)
Mandates volume requirements for signal generation
Requires 1.5x average volume + 25% volume ROC
Critical for signal quality
Require Momentum Confirmation (Default: True)
Mandates divergence detection for signals
Ensures momentum backing for directional moves
Essential for high-probability setups
Minimum Trend Strength (Default: 25)
Required ADX level for signal generation
Range: 15-40
Ensures signals occur in trending markets
Higher values = Only strong trending conditions
Confluence Scoring Settings
Minimum Confluence Score (Default: 70)
Threshold for displaying support/resistance levels
Range: 50-90
Levels below this score are filtered out
Higher values = Only strongest levels shown
Component Weights (Default: 25% each)
Divergence Weight: Momentum component influence (10-40%)
Volume Weight: Volume analysis influence (10-40%)
Price Action Weight: Price patterns influence (10-40%)
Sentiment Weight: Market sentiment influence (10-40%)
Must total 100% for balanced scoring
Vitality Field Settings
Enable Vitality Field (Default: True)
Controls the background gradient field display
Provides instant visual market sentiment feedback
Enhances chart readability and context
Vitality Center Transparency (Default: 85%)
Opacity at the center of the vitality field
Range: 70-95%
Lower values = More opaque center
Higher values = More transparent center
Vitality Edge Transparency (Default: 98%)
Opacity at the edges of the vitality field
Range: 95-99%
Creates smooth fade effect from center to edges
Higher values = More subtle edge appearance
Vitality Field Size (Default: 8.0)
Controls the overall size of the vitality field
Range: 3.0-20.0
Based on ATR multiples for dynamic sizing
Lower values = Tighter field around price
Higher values = Broader field coverage
Recommended Settings by Trading Style
Scalping (1-5 minutes)
Base Length: 15
Volume MA Length: 20
Signal Cooldown: 5 bars
Vitality Field Size: 5.0
Higher sensitivity for quick moves
Day Trading (15-60 minutes)
Base Length: 25 (default)
Volume MA Length: 50 (default)
Signal Cooldown: 10 bars (default)
Vitality Field Size: 8.0 (default)
Balanced settings for intraday moves
Swing Trading (4H-Daily)
Base Length: 50
Volume MA Length: 100
Signal Cooldown: 20 bars
Vitality Field Size: 12.0
Longer-term perspective for multi-day moves
Conservative Trading
Minimum Signal Confluence: 85
Minimum Confluence Score: 80
Require all confirmations: True
Higher thresholds for maximum quality
Aggressive Trading
Minimum Signal Confluence: 75
Minimum Confluence Score: 65
Signal Cooldown: 5 bars
Lower thresholds for more opportunities
RISK ROTATION MATRIX ║ BullVision [3.0]🔍 Overview
The Risk Rotation Matrix is a comprehensive market regime detection system that analyzes global market conditions across four critical domains: Liquidity, Macroeconomic, Crypto/Commodities, and Risk/Volatility. Through proprietary algorithms and advanced statistical analysis, it transforms 20+ diverse market metrics into a unified framework for identifying regime transitions and risk rotations.
This institutional-grade system aims to solve a fundamental challenge: how to synthesize complex, multi-domain market data into clear, actionable trading intelligence. By combining proprietary liquidity calculations with sophisticated cross-asset analysis.
The Four-Domain Architecture
1. 💧 LIQUIDITY DOMAIN
Our liquidity analysis combines standard metrics with proprietary calculations:
Proprietary Components:
Custom Global Liquidity Index (GLI): Unique formula aggregating central bank assets, credit spreads, and FX dynamics through our weighted algorithm
Federal Reserve Balance Proxy: Advanced calculation incorporating reverse repos, TGA fluctuations, and QE/QT impacts
China Liquidity Proxy: First-of-its-kind metric combining PBOC operations with FX-adjusted aggregates
Global M2 Composite: Custom multi-currency M2 aggregation with proprietary FX normalization
2. 📈 MACRO DOMAIN
Sophisticated integration of global economic indicators:
S&P 500: Momentum and trend analysis with custom z-score normalization
China Blue Chips: Asian market sentiment with correlation filtering
MBA Purchase Index: Real estate market health indicator
Emerging Markets (EEMS): Risk appetite measurement
Global ETF (URTH): Worldwide equity exposure tracking
Each metric undergoes proprietary transformation to ensure comparability and regime-specific sensitivity.
3. 🪙 CRYPTO/COMMODITIES DOMAIN
Unique cross-asset analysis combining:
Total Crypto Market Cap: Liquidity flow indicator with custom smoothing
Bitcoin SOPR: On-chain profitability analysis with adaptive periods
MVRV Z-Score: Advanced implementation with multiple MA options
BTC/Silver Ratio: Novel commodity-crypto relationship metric
Our algorithms detect when crypto markets lead or lag traditional assets, providing crucial timing signals.
4. ⚡ RISK/VOLATILITY DOMAIN
Advanced volatility regime detection through:
MOVE Index: Bond volatility with inverse correlation analysis
VVIX/VIX Ratio: Volatility-of-volatility for regime extremes
SKEW Index: Tail risk measurement with custom normalization
Credit Stress Composite: Proprietary combination of credit spreads
USDT Dominance: Crypto flight-to-safety indicator
All risk metrics are inverted and normalized to align with the unified scoring system.
🧠 Advanced Integration Methodology
Multi-Stage Processing Pipeline
Data Collection: Real-time aggregation from 20+ sources
Normalization: Custom z-score variants accounting for regime-specific volatility
Domain Scoring: Proprietary weighting within each domain
Cross-Domain Synthesis: Advanced correlation matrix between domains
Regime Detection: State-transition model identifying four market phases
Signal Generation: Composite score with adaptive smoothing
🔁 Composite Smoothing & Signal Generation
The user can apply smoothing (ALMA, EMA, etc.) to highlight trends and reduce noise. Smoothing length, type, and parameters are fully customizable for different trading styles.
🎯 Color Feedback & Market Regimes
Visual dynamics (color gradients, labels, trails, and quadrant placement) offer an at-a-glance interpretation of the market’s evolving risk environment—without forecasting or forward-looking assumptions.
🎯 The Quadrant Visualization System
Our innovative visual framework transforms complex calculations into intuitive intelligence:
Dynamic Ehlers Loop: Shows current position and momentum
Trailing History: Visual path of regime transitions
Real-Time Animation: Immediate feedback on condition changes
Multi-Layer Information: Depth through color, size, and positioning
🚀 Practical Applications
Primary Use Cases
Multi-Asset Portfolio Management: Optimize allocation across asset classes based on regime
Risk Budgeting: Adjust exposure dynamically with regime changes
Tactical Trading: Time entries/exits using regime transitions
Hedging Strategies: Implement protection before risk-off phases
Specific Trading Scenarios
Domain Divergence: When liquidity improves but risk metrics deteriorate
Early Rotation Detection: Crypto/commodity signals often lead broader markets
Volatility Regime Trades: Position for mean reversion or trend following
Cross-Asset Arbitrage: Exploit temporary dislocations between domains
⚙️ How It Works
The Composite Score Engine
The system's intelligence emerges from how it combines domains:
Each domain produces a normalized score (-2 to +2 range)
Proprietary algorithms weight domains based on market conditions
Composite score indicates overall market regime
Smoothing options (ALMA, EMA, etc.) optimize for different timeframes
Regime Classification
🟢 Risk-On (Green): Positive composite + positive momentum
🟠 Weakening (Orange): Positive composite + negative momentum
🔵 Recovery (Blue): Negative composite + positive momentum
🔴 Risk-Off (Red): Negative composite + negative momentum
Signal Interpretation Framework
The indicator provides three levels of analysis:
Composite Score: Overall market regime (-2 to +2)
Domain Scores: Identify which factors drive regime
Individual Metrics: Granular analysis of specific components
🎨 Features & Functionality
Core Components
Risk Rotation Quadrant: Primary visual interface with Ehlers loop
Data Matrix Dashboard: Real-time display of all 20+ metrics
Domain Aggregation: Separate scores for each domain
Composite Calculation: Unified score with multiple smoothing options
Customization Options
Selective Metrics: Enable/disable individual components
Period Adjustment: Optimize lookback for each metric
Smoothing Selection: 10 different MA types including ALMA
Visual Configuration: Quadrant scale, colors, trails, effects
Advanced Settings
Pre-smoothing: Reduce noise before final calculation
Adaptive Periods: Automatic adjustment during volatility
Correlation Filters: Remove redundant signals
Regime Memory: Hysteresis to prevent whipsaws
📋 Implementation Guide
Setup Process
Add to chart (optimized for daily, works on all timeframes)
Review default settings for your market focus
Adjust domain weights based on trading style
Configure visual preferences
Optimization by Trading Style
Position Trading: Longer periods (60-150), heavy smoothing
Swing Trading: Medium periods (20-60), balanced smoothing
Active Trading: Shorter periods (10-40), minimal smoothing
Best Practices
Monitor domain divergences for early signals
Use extreme readings (-1.5/+1.5) for high-conviction trades
Combine with price action for confirmation
Adjust parameters during major events (FOMC, earnings)
💎 What Makes This Unique
Beyond Traditional Indicators
Multi-Domain Integration: Only system combining liquidity, macro, crypto, and volatility
Proprietary Calculations: Custom formulas for GLI, Fed, China, and M2 proxies
Adaptive Architecture: Dynamically adjusts to market regimes
Institutional Depth: 20+ integrated metrics vs typical 3-5
Technical Innovation
Statistical Normalization: Custom z-score variants for cross-asset comparison
Correlation Management: Prevents double-counting related signals
Regime Persistence: Algorithms to identify sustainable vs temporary shifts
Visual Intelligence: Information-dense display without overwhelming
🔢 Performance Characteristics
Strengths
Early regime detection (typically 1-3 weeks ahead)
Robust across different market environments
Clear visual feedback reduces interpretation errors
Comprehensive coverage prevents blind spots
Optimal Conditions
Most effective with 100+ bars of history
Best on daily timeframe (4H minimum recommended)
Requires liquid markets for accurate signals
Performance improves with more enabled components
⚠️ Risk Considerations & Limitations
Important Disclaimers
Probabilistic system, not predictive
Requires understanding of macro relationships
Signals should complement other analysis
Past regime behavior doesn't guarantee future patterns
Known Limitations
Black swan events may cause temporary distortions
Central bank interventions can override signals
Requires active management during regime transitions
Not suitable for pure technical traders
💎 Conclusion
The Risk Rotation Matrix represents a new paradigm in market regime analysis. By combining proprietary liquidity calculations with comprehensive multi-domain monitoring, it provides institutional-grade intelligence previously available only to large funds. The system's strength lies not just in its individual components, but in how it synthesizes diverse market information into clear, actionable trading signals.
⚠️ Access & Intellectual Property Notice
This invite-only indicator contains proprietary algorithms, custom calculations, and years of quantitative research. The mathematical formulations for our liquidity proxies, cross-domain correlation matrices, and regime detection algorithms represent significant intellectual property. Access is restricted to protect these innovations and maintain their effectiveness for serious traders who understand the value of comprehensive market regime analysis.
Sweep Swing Screener [TradingFinder]🔵 Introduction
Understanding how liquidity forms and how price reacts around key structural levels is essential for identifying precise, low-risk entry points. The Sweep Swing Screener is a specialized tool developed to continuously monitor market activity and detect liquidity sweeps, reaction zones, and valid confirmation candles across various trading instruments and timeframes.
This tool can be applied both to scan multiple symbols at once and to analyze all timeframes of a specific asset for potential reversal points. It begins by identifying a clear swing point, whether a swing high or a swing low, and then outlines a reaction zone between that level and either the highest or lowest value of the swing candle's open or close.
If the price revisits this zone, performs a liquidity grab, and prints an indecision candle like a doji or a narrow-bodied bar that closes within the zone, this may indicate a rejection of the level and the failure of a breakout attempt. At that moment, depending on the context, the screener may identify a bullish or bearish reversal and generate a corresponding Long or Short signal.
By emphasizing accurate entry timing, alignment with institutional order flow, and avoidance of common traps, this approach highlights market areas where liquidity engineering, reversal probability, and price inefficiency come together. As a result, the Sweep Swing Screener becomes a valuable part of any trader’s toolkit, particularly for those who rely on price action and liquidity logic to drive their decisions. It allows traders to focus on clean, actionable setups without getting lost in noise or misleading breakouts.
🔵 How to Use
The Sweep Swing Screener is designed to track market structure in real time and alert users when conditions for a potential reversal are present. Its methodology combines liquidity behavior with swing analysis and candle confirmation, all within predefined reaction zones.
To better understand this logic, consider a basic market flow where a swing high or low forms, followed by a return to that level. If the price sweeps the previous extreme and forms a confirming candle within the reaction zone, a signal is issued.
🟣 Long Signal
To identify a long setup, the screener looks for a valid swing low, often a level below which sell-side liquidity is likely to be clustered. Once found, it defines a reaction zone from the swing low to the lowest point between the candle’s open and close.
If the price returns to this area and creates a lower wick that extends beneath the swing low, the tool checks whether the price manages to close back inside the range, rejecting the breakdown. This indicates absorption of selling pressure and failure to sustain the move lower.
The screener then waits for a confirmation candle to appear. Typically, this is a doji or other small-bodied candle that closes inside the zone. If these conditions are met, the screener records a Long signal for that asset and, if enabled, sends a notification to alert the user.
🟣 Short Signal
For bearish setups, the screener begins by identifying a valid swing high, which usually marks a level where buy-side liquidity is concentrated. It then creates a reaction zone from the swing high to the highest point between the candle’s open and close.
When price returns to this level, sweeps above the swing high, and then fails to close higher, it may signal the presence of a bull trap and early exhaustion in the upward move.
A confirmation candle, usually a doji or a rejection bar that closes back within the zone, is then required. Once that occurs, the screener marks the asset with a Short signal and optionally sends a real-time alert to the user.
This type of setup helps highlight potential institutional sell zones, offering insight into where price is likely to reverse following a liquidity event.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
Maximum Distance Between Swing and Signal : The maximum number of candles allowed between the swing point and the potential signal. The default value is 50, ensuring that only recent and relevant price reactions are considered valid.
🟣 Display Settings
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 10 symbol slots comes with a full set of customizable parameters :
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
🟣 Alert Settings
Alert : Enables alerts for SSS.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Sweep Swing Screener provides a systematic method for identifying potential reversal zones by combining price structure, liquidity behavior, and candle-based confirmation. In markets that are often noisy and full of failed breakouts, focusing on these three elements helps clarify directional bias and supports more confident decision-making.
With the ability to scan multiple symbols and timeframes efficiently, this tool allows traders to stay focused on high-quality setups without the need to manually sift through dozens of charts. The inclusion of optional alerts further enhances its utility by offering timely updates when criteria are met.
By moving away from reactive strategies and toward structural anticipation, this screener supports traders who align their methods with institutional logic and the mechanics of smart money.
ICT IRL & ERL ZonesICT IRL & ERL Zones
This indicator visualizes Internal Range Liquidity (IRL) and External Range Liquidity (ERL) levels, based on ICT (Inner Circle Trader) concepts. It's designed to help traders identify key liquidity zones that often act as magnet levels or reversal points in price action.
🔍 How It Works
Lookback Range: The script analyzes the highest high and lowest low over a user-defined number of candles (default: 50).
IRL (Internal Range Liquidity):
Plots the highest high and lowest low within the lookback period.
Represented as orange lines and a shaded zone.
ERL (External Range Liquidity):
Extends the IRL boundaries by a small buffer (50 ticks above/below).
Visualizes zones where price may reach for liquidity beyond the current range.
Plotted as a green (high) and red (low) line.
⚙️ Inputs
Lookback Range: Number of candles to calculate the range (min 5).
Show IRL: Toggle visibility for Internal Range Liquidity zone.
Show ERL: Toggle visibility for External Range Liquidity buffer zone.
📊 Visual Elements
IRL High/Low: Orange lines with fill to mark the main liquidity range.
ERL High/Low: Green and red lines indicating potential liquidity sweep zones.
Zone Fill: Light orange shading to visually emphasize the IRL area.
📈 Use Case
Use this tool to:
Identify areas where price might consolidate or reverse.
Highlight likely zones of liquidity grabs before trend continuations or shifts.
Enhance entry/exit decisions based on smart money concepts.
Mech Model - monkertrades x {DeadCatCode}Mech Model - Multi-Timeframe ICT Liquidity & iFVG Trading System
Detailed Methodology & Underlying Concepts
This indicator automates the Inner Circle Trader (ICT) methodology by identifying institutional order flow through liquidity sweeps and inverse Fair Value Gap (iFVG) formations across multiple timeframes.
Core Logic & Calculations
1. Liquidity Level Identification The script tracks four key liquidity pools:
NY session dynamic LQ detection everytime it sweeps high/low Calculates high/low from 18:00-09:30 EST
Session Extremes: Monitors Asia (20:00-23:00), London (02:00-05:00) session highs/lows
Previous Day Levels: Requests PDH/PDL using request.security() with daily timeframe
Dynamic Updates: Liquidity levels update in real-time when swept during NY session
2. Market Structure Analysis
Uses pivot points logic to understand HH.HL parameters
Classifies pivots as Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), Lower Lows (LL)
Stores last 50 pivots for reference in custom PivotPoint type arrays, background calculations to identfy price legs after sweep
3. Fair Value Gap Detection
Bullish FVG: When low > high (gap between candles)
Bearish FVG: When high < low
Stores FVG data including top, bottom, direction, and bar index
Tracks "wicking" - when price touches but doesn't close through FVG
4. Price Leg Formation (Key Innovation) When liquidity is swept:
Bull Leg: Forms after low sweep, connects previous swing high to sweep point
Bear Leg: Forms after high sweep, connects previous swing low to sweep point
Leg remains "active" and extends with continued liquidity breaks
5. iFVG Signal Generation The signal fires when:
An active price leg exists (post-liquidity sweep)
An FVG within the leg range gets "closed through" (not just wicked)
This creates an inverse FVG (iFVG) - the key entry signal
Signal direction matches leg type (bull leg + bull iFVG = buy signal)
6. Multi-Timeframe Synchronization
Uses request.security() to run detection logic on 1m, 2m, 3m, 4m, 5m
All signals display on 1-minute chart via status table
How Traders Use This
Setup Phase: Script identifies when price sweeps overnight/session liquidity
Confirmation: Waits for FVG within the "price leg" to be violated
Entry Signal: iFVG formation provides precise entry point
Target: Typically the next unmitigated FVG on 5-minute timeframe
Key Parameters Users Can Adjust
Session times for different market hours
Visual elements (colors, transparency, line styles)
Timeframe selection (enable/disable 1m-5m)
Wick grace period (0-100 bars)
Signal display mode (triangles vs horizontal lines)
This script essentially automates the manual process ICT traders use to identify institutional footprints through liquidity raids and subsequent rebalancing via FVG mitigation.
Super Arma Institucional PRO v6.3Super Arma Institucional PRO v6.3
Description
Super Arma Institucional PRO v6.3 is a multifunctional indicator designed for traders looking for a clear and objective analysis of the market, focusing on trends, key price levels and high liquidity zones. It combines three essential elements: moving averages (EMA 20, SMA 50, EMA 200), dynamic support and resistance, and volume-based liquidity zones. This integration offers an institutional view of the market, ideal for identifying strategic entry and exit points.
How it Works
Moving Averages:
EMA 20 (orange): Sensitive to short-term movements, ideal for capturing fast trends.
SMA 50 (blue): Represents the medium-term trend, smoothing out fluctuations.
EMA 200 (red): Indicates the long-term trend, used as a reference for the general market bias.
Support and Resistance: Calculated based on the highest and lowest prices over a defined period (default: 20 bars). These dynamic levels help identify zones where the price may encounter barriers or supports.
Liquidity Zones: Purple rectangles are drawn in areas of significantly above-average volume, indicating regions where large market participants (institutional) may be active. These zones are useful for anticipating price movements or order absorption.
Purpose
The indicator was developed to provide a clean and institutional view of the market, combining classic tools (moving averages and support/resistance) with modern liquidity analysis. It is ideal for traders operating swing trading or position trading strategies, allowing to identify:
Short, medium and long-term trends.
Key support and resistance levels to plan entries and exits.
High liquidity zones where institutional orders can influence the price.
Settings
Show EMA 20 (true): Enables/disables the 20-period EMA.
Show SMA 50 (true): Enables/disables the 50-period SMA.
Show EMA 200 (true): Enables/disables the 200-period EMA.
Support/Resistance Period (20): Sets the period for calculating support and resistance levels.
Liquidity Sensitivity (20): Period for calculating the average volume.
Minimum Liquidity Factor (1.5): Multiplier of the average volume to identify high liquidity zones.
How to Use
Moving Averages:
Crossovers between the EMA 20 and SMA 50 may indicate short/medium-term trend changes.
The EMA 200 serves as a reference for the long-term bias (above = bullish, below = bearish).
Support and Resistance: Use the red (resistance) and green (support) lines to identify reversal or consolidation zones.
Liquidity Zones: The purple rectangles highlight areas of high volume, where the price may react (reversal or breakout). Consider these zones to place orders or manage risks.
Adjust the parameters according to the asset and timeframe to optimize the analysis.
Notes
The chart should be configured only with this indicator to ensure clarity.
Use on timeframes such as 1 hour, 4 hours or daily for better visualization of liquidity zones and support/resistance levels.
Avoid adding other indicators to the chart to keep the script output easily identifiable.
The indicator is designed to be clean, without explicit buy/sell signals, following an institutional approach.
This indicator is perfect for traders who want a visually clear and powerful tool to trade based on trends, key levels and institutional behavior.
Dealing rangeHi all!
This indicator will show you the current dealing range. The concept of dealing range comes from the inner circle trader (ICT) and gives you a range between an established swing high and an established swing low (the length of these pivots can be changed in settings parameter Length and defaults to 5/2 (left/right)). These swing points must have taken out liquidity to be considered "established". The liquidity that must be grabbed by the swing point has to be a pivot of left length of 1 and a right length of 1.
The dealing range that's created should be used in conjunction with market structure. This could be done through scripts (maybe the Market structure script that I published ()) or manually. It's a common approach to look for long opportunities when the trend is bullish and price is currently in the discount zone of the dealing range. If the trend is bearish then short opportunities are presented when the price is currently in the premium zone of the dealing range.
The zones within the dealing range are premium and discount that are split on the 50% level of the dealing range. These zones can be split into 3 zone with a Fair price (also called Fair value ) zone in between premium and discount. This makes the premium zone to be in the upper third of the dealing range, fair price in the middle third and discount in the lower third. This can be enabled in the settings through the Fair price parameter.
Enabled:
You can choose to enable/disable the visualisation of liquidity grabs and the External liquidity available above and below the swing points that created the dealing range.
Enabled:
Disabled:
Enabled on a higher timeframe (will display a box of the liquidity grab price instead of a label):
This dealing range is configurable to be created by a higher timeframe then the visible charts. Use the setting Higher timeframe to change this.
You can force candles to be closed (for liquidity and swing points). Please note that if you use a higher timeframe then the visible charts the candles must be closed on this timeframe.
Lastly you can also change the transparency of liquidity grabs and external liquidity outside of the dealing range. Use the Transparency setting to change this (a lower value will lead to stronger visuals).
If you have any input or suggestions on future features or bugs, don't hesitate to let me know!
Best of trading luck!
