Indicator
Rotating Messages [YM]Trading is 80% psychology and 20% strategy. How many times have you broken your trading plan or made a bad decision simply because you got carried away by the emotion of the moment?
I created the Rotating Messages indicator to act as your personal psychological assistant. This script displays your trading rules, reminders, or motivational quotes directly on your chart, rotating them automatically so you never lose focus while trading.
✨ Main Features:
🔄 Smart Time Rotation: Unlike other indicators that stay frozen until the candle closes, this script uses the internal clock (when the market is open and the price moves) to rotate your messages every "X" seconds of your choosing. Ideal for higher timeframe charts where candles take a long time to close. (Note: In backtesting or weekends, it will automatically switch to bar counting).
⚠️ Dynamic Visual Alerts: Do you have a rule that you absolutely cannot break? Simply add the ! symbol at the beginning of your sentence in the settings (e.g., !Avoid trading on Friday afternoons). The indicator will hide the symbol and highlight that phrase with a striking yellow background to grab your attention immediately.
🛠️ Perfect Positioning: Don't let the text block the price action. You can choose the screen corner and fine-tune the panel using the "Offsets" (Vertical and Horizontal) to place it exactly where it won't bother you.
🎨 Total Customization: Change the text color, adjust the background opacity to see the candles through the panel, and choose between three text sizes.
⌨️ Simplicity of Use: Forget about complex coding. Type your rules in the text box and simply press "ENTER" to separate one phrase from the next.
📝 What's included by default?
The indicator comes pre-loaded with a list of golden risk management rules and trading psychology quotes ready to use, but you can delete everything and put your own personal trading plan.
💡 A disciplined trader is a profitable trader. Keep your mind focused, respect your Stop Loss, and let this indicator remind you of your flight plan every day.
If you find it useful to maintain discipline, don't forget to hit "Like" and add it to your favorites! Let me know in the comments which trading rule is the hardest for you to follow. 👇 Indicator
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Indicator
SMC Setup: Sweep + CHoCH + FVG v21.1SMC Setup: Sweep + CHoCH + FVG v21.1 (Multi-Timeframe Execution Engine)
Introducing a complete, institutional-grade Smart Money Concepts (SMC) execution algorithm. This is not just a standard sweep indicator; it is a "3D" Top-Down Analysis Engine designed to flawlessly mimic how professional human traders track order flow across multiple timeframes, natively executing on your lower-timeframe charts.
Built to solve the common pitfalls of algorithmic SMC (such as repainting, MTF blindness, and zero-width visual crashes), this indicator tracks Major (External) and Minor (Internal) liquidity simultaneously and automates your entire entry and trade management visualization.
🔥 Core Features
Multi-Timeframe (MTF) "Time-Warp" Engine: Track 15-minute and 5-minute structural liquidity sweeps natively on the 1-minute execution chart. The script uses internal mathematical multipliers and a massive 5000-bar deep memory buffer to track HTF structure without relying on laggy or repainting request.security() calls.
Dual-Fractal Liquidity Tracking: * Solid Blue Lines: Tracks Major/External Higher Timeframe liquidity peaks.
Dotted Blue Lines: Tracks Minor/Internal Lower Timeframe pullbacks for aggressive continuation order flow.
Two Selectable Entry Models:
BOS Breakout: For aggressive momentum traders. Executes the exact millisecond the micro-structure BOS (Break of Structure/CHoCH) line is cracked.
FVG Pullback: For conservative traders. Waits for a Break of Structure, verifies a Fair Value Gap has formed, and sets a limit entry exactly at the FVG boundary.
Dynamic Visual Trade Management: The script automatically generates a physical Risk Zone Box (mimicking the native PulseWire Short/Long Position tools) and projects dynamic, trailing lines for your Entry, Stop Loss, TP1, TP2, and Full Target based on customizable Risk:Reward settings.
Webhook-Ready Alerts: Generates highly detailed, once-per-bar-close alerts containing dynamic strings for Entry Price, Stop Loss, and all Take Profit targets, making it perfect for automated execution via 3Commas, PineConnector, etc.
⚙️ How It Works (The Logic Flow)
The Hunt: The algorithm maps higher timeframe peaks (e.g., 15m/5m) and local micro-peaks simultaneously.
The Sweep: When price sweeps a mapped liquidity line, the algorithm "arms" the setup and locks the Stop Loss to the highest point of the sweep.
The CHoCH/BOS: It tracks the immediate local pullback prior to the sweep. If price breaks this micro-structure support, the setup is confirmed.
The Execution: Depending on your selected model, it either triggers instantly on the BOS breakout or waits for a bearish FVG pullback.
The Management: Target lines trail alongside price action and automatically lock into place the moment the trade hits the Full Target or the Stop Loss.
💡 Best Practices
Optimal Use: Load this indicator on the 1-minute chart. Set the Major HTF Multiplier to 15 and the Minor HTF Multiplier to 5. This allows the script to see 15m and 5m market structure while leveraging the 1-minute candles for surgical entries.
Asset Classes: Highly effective on high-volume assets like Indices (NAS100, US30, SPX) and Forex (EURUSD, XAUUSD) during the London or New York sessions. Indicator
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Indicator
ALN Sessions [NQ Stats x CantoLab]A statistical tool for NQ intraday traders built around research from NQ Stats (NQStats on twitter / nqstats.com ). Credit to NQ Stats for the original concept and data — published here as an open source indicator with permission.
Introduction
This indicator visualizes Asia and London session ranges on NQ (NASDAQ futures), then overlays statistically-derived probability levels showing how likely price is to sweep each session's high or low — based on historical pattern data compiled by NQ Stats.
How to Read the Probability Numbers
When London session closes, two horizontal lines appear — one above (London High) and one below (London Low) — each labeled with a percentage like 81.1% or 74.9%.
These numbers answer: "Historically, how often does price return to sweep this level after London closes?"
For example, if you see 81.1% on the high line, it means: in roughly 8 out of 10 historical sessions matching this pattern, price eventually traded back up to or through the London High
What happens when a level is hit?
The label updates to show in blue — confirming that level was reached
The other line's probability updates to a new conditional probability, e.g. 46% , shown in brackets
This delta tells you how the odds of sweeping the second level changed now that the first was reached
The Four Patterns (Asia vs London relationship)
The probabilities change depending on how London's range relates to Asia's range that day. The indicator detects four patterns automatically:
London Engulfs Asia — London trades both above AND below Asia's range. The most expansive session structure.
Asia Engulfs London — Asia's range fully contains London's range. London consolidates inside the prior overnight range.
London High Break — London breaks only above Asia's high, leaving Asia's low intact.
London Low Break — London breaks only below Asia's low, leaving Asia's high intact.
Each pattern has its own set of historical probabilities, so the percentages you see are always contextual to that day's Asia/London relationship — not a fixed number.
Settings
Asia Session — color, session time window, and label text
London Session — color, session time window, and label text
Label Size — Tiny / Small / Normal / Large
Border — toggle, style (Solid/Dashed/Dotted), and width for session boxes
Probability Lines — toggle, Auto color or manual color pick, style (Solid/Dashed/Dotted), and width
Daily Dividers — toggle, color, style (Solid/Dashed/Dotted), and width
Notes
Built for NQ Futures. Behaviour on other instruments is untested
All times are New York time
Probability data is derived from 10 years of NQ historical data by nqstats.com
This indicator does not provide financial advice or a complete strategy. You are responsible for how you build around and execute on this data
⚠️ Important
This is a statistical study indicator. It does not guarantee that the London high or low will be hit. Over a large sample, this is the expected behaviour based on 10 years of NQ data. It is best combined with other confluences to confirm direction — this indicator alone is not a strategy.
Indicator
Market Entropy IndexMarket Entropy Index (MEI)
Most risk indicators react to price. They measure what has already happened. The Market Entropy Index takes a different approach: it measures the structural organization of the market itself, identifying fragility before it becomes visible in price. When sector participation narrows, when sectors stop agreeing on direction, and when credit markets become complacent, the MEI detects these precursor conditions. It applies information theoretic entropy to three independent dimensions of market structure, producing a single composite that distinguishes broad, healthy markets from concentrated, fragile ones. This makes it a leading indicator of structural risk, not a coincident crash detector.
What entropy means in financial markets
Entropy, as formalized by Shannon (1948), quantifies uncertainty in a probability distribution. In information theory, a distribution where all outcomes are equally likely has maximum entropy. A distribution concentrated on a single outcome has minimum entropy. Applied to financial markets, this framework has been used in two distinct ways that should not be confused.
The first is temporal return entropy: measuring how the distribution of an index's daily returns changes over time. Risso (2008) showed that Shannon entropy of stock market return distributions drops before financial crashes, as returns become more extreme and less uniformly distributed. Zunino et al. (2009) found that permutation entropy of return series tracks market efficiency and deteriorates during stress. Gu (2017) extended this to multiple time scales. These studies all measure the statistical properties of a single return series over time.
The second is cross-sectional entropy, which is what the MEI uses. Instead of asking "how are returns distributed over time?", it asks "how is market activity distributed across sectors right now?" When all nine S&P 500 GICS sectors contribute equally to market movement, the entropy of their return distribution reaches its theoretical maximum: roughly log2(9) = 3.17 bits. This corresponds to broad, healthy participation. When movement concentrates in two or three sectors while the rest are flat, entropy drops. The market relies on a narrow base.
These two types of entropy can move in opposite directions. During an acute crash, temporal return entropy drops (Risso's finding: returns become extreme and non-normal). But cross-sectional breadth entropy often rises, because all sectors sell off together, producing a more uniform distribution across the cross-section. The MEI does not measure temporal return entropy. It measures cross-sectional breadth entropy and two related structural conditions. This distinction matters for interpretation (see the section on what the MEI does not do).
How the MEI is constructed
The indicator combines three dimensions, each measuring a distinct aspect of market fragility. All three were validated through statistical screening with Bonferroni correction across seven different parameter configurations to guard against data-mining bias.
Sector Breadth Concentration (weight: 0.40)
This is the primary dimension. It computes the Shannon entropy of the distribution of smoothed absolute returns across nine GICS sector ETFs (XLB, XLE, XLF, XLI, XLK, XLP, XLU, XLV, XLY) over a 21-day rolling window. The entropy value is normalized to the theoretical maximum so it ranges from 0 (all activity in one sector) to 1 (perfectly uniform distribution).
The critical finding from backtesting: low sector entropy (concentrated breadth) is the danger condition, not high entropy. When market movement narrows to a few sectors, the rally or sell-off lacks structural support. This is consistent with the well-documented market breadth divergence effect: narrow rallies tend to precede corrections. In our testing, the low-entropy tercile showed significantly worse forward returns than the high-entropy tercile across a 21-day horizon (spread = +1.18%, t = 5.81, p = 7.3e-09, Bonferroni-significant in all seven parameter configurations).
Sector Directional Discord (weight: 0.30)
This dimension measures the fraction of sectors that agree on daily direction (all up or all down), averaged over 21 days. When eight of nine sectors move in the same direction, concordance is high, indicating a coherent market. When sectors split nearly evenly between positive and negative days, concordance drops, signaling confusion, rotation, or conflicting macro forces.
Low concordance (high discord) is the danger condition. Sectors disagreeing on direction means the market lacks conviction and is vulnerable to dislocations. This dimension was Bonferroni-significant in five of seven parameter configurations (21d: spread = +0.97%, t = 5.20, p = 2.2e-07).
Credit Complacency (weight: 0.30)
The third dimension measures the rolling standard deviation of the daily return spread between iShares High Yield Corporate Bond ETF (HYG) and iShares Investment Grade Corporate Bond ETF (LQD), normalized by its 252-day average. This ratio captures how volatile credit spreads are relative to their recent history.
Low credit spread volatility is the danger condition. When credit markets are calm and spreads barely move, it often reflects complacent risk pricing. The empirical parallel is well-supported: Gilchrist and Zakrajsek (2012) showed that credit spread dynamics, specifically the excess bond premium, predict economic downturns and equity returns. In our testing, this dimension produced the strongest individual t-statistic (63d: spread = +1.89%, t = 6.73, p = 2.2e-11, Bonferroni-significant in three of seven configurations).
Signal processing
Each dimension is z-scored over a 252-day lookback and clipped at three standard deviations. The z-scores are sign-inverted so that high values consistently indicate danger across all three dimensions. After weighting, the composite is re-standardized over 252 days to restore the variance lost through averaging weakly correlated signals. The result is scaled to a 0-10 range (5.0 + z * 2.0) and smoothed with a Kaufman Adaptive Moving Average (Kaufman, 2013). The KAMA adjusts its smoothing speed based on the efficiency ratio of the composite: during clear regime transitions, it responds quickly; during choppy sideways periods, it filters noise. A minimum smoothing constant floor prevents the filter from becoming excessively sluggish.
How to read the MEI
0 to 3: Low Risk. All three dimensions read safe. Sectors participate broadly, agree on direction, and credit markets are actively pricing risk. These conditions are historically associated with favorable forward equity returns.
3 to 7: Normal. No structural signal in either direction. The market is in equilibrium. This is the expected reading roughly two-thirds of the time.
7 to 10: Elevated Risk. One or more dimensions show stress. Sector participation is narrowing, directional agreement is breaking down, or credit markets have become complacent. The higher the reading, the more dimensions agree on risk.
The dashboard shows each dimension individually, so you can diagnose what is driving the composite. The historical percentile tells you where the current reading sits relative to the past 252 days. The trend direction (with arrow symbols) shows whether risk is rising or falling.
What the MEI detects and what it does not
The MEI is a leading indicator of structural fragility, not a coincident crash detector. It measures conditions that build up before market stress: narrowing sector participation, loss of directional agreement, and complacent credit pricing. These are precursor conditions. They describe a market that has become structurally fragile, not one that is already falling apart.
During an acute sell off, the MEI typically drops toward the green zone. This is not a malfunction. When all sectors sell off together, breadth entropy actually increases (uniform distribution across sectors), concordance rises (all sectors agree on the down direction), and credit spread volatility spikes (the opposite of complacency). All three dimensions read "safe" precisely because the structural fragility has already resolved through the sell-off itself.
The practical implication: the MEI is most useful in the quiet periods before stress, when markets look calm but the underlying structure is deteriorating. If the MEI reads 8 while the SPX is making new highs, that is a warning worth paying attention to. If the MEI reads 2 during a violent correction, that means the correction is broad-based and structural participation is actually healthy, which is historically a better setup for recovery than a narrow, concentrated decline.
How to use it in practice
The MEI is a regime monitor, not a timing signal. It answers the question "what kind of market are we in?" rather than "should I buy or sell today?" The most productive way to use it:
As a confluence filter: combine the MEI with your existing trend-following or mean-reversion strategy. When the MEI reads above 7, tighten stops, reduce position sizes, or require stronger entry signals. When it reads below 3, conditions favor taking positions.
As an allocation tool: for portfolio managers running multi-asset or tactical allocation, the MEI provides a daily structural risk reading that can scale equity exposure. Reduce equity allocation when the composite is elevated, increase when it is low.
As a diagnostic tool: enable the individual components (Breadth Concentration, Directional Discord, Credit Complacency) to understand what is driving the composite. If only one dimension is elevated while the others are normal, the risk may be localized. If all three converge, the structural case is stronger.
For monitoring credit conditions: the Credit Complacency dimension alone serves as a real-time gauge of credit market risk pricing. Low readings (complacency) have historically preceded episodes of spread widening.
Quant fund applications
For systematic portfolio managers and quantitative research teams, the MEI framework offers several practical applications.
As a regime classifier for conditional strategies: most equity strategies behave differently in ordered versus disordered markets. Momentum strategies, for example, tend to work well when breadth entropy is high (broad participation) and poorly when it is low (concentrated leadership). The MEI provides a daily regime classification that can condition strategy selection or parameter adjustment. In our backtesting, the composite showed a spread of +2.86% (21-day forward returns, t = 5.91) in high-volatility regimes, offering a quantitatively meaningful signal for regime-conditional allocation.
As a risk budget input: the three z-scored danger signals can feed directly into a risk budgeting framework. When breadth_danger or credit_danger exceeds one standard deviation, the risk model can automatically reduce gross exposure or hedge tail risk. The low cross-correlation between dimensions (breadth-credit: rho = -0.07, breadth-discord: rho = 0.20) means each dimension adds genuine incremental information to the risk estimate.
As an alpha decay monitor: sector concentration (low breadth entropy) is one mechanism through which crowded trades develop. When the breadth dimension rises, it may indicate that a previously broad factor exposure has narrowed to a few names or sectors, which is a warning sign for factor crowding and potential alpha decay.
As a multi-asset overlay: the framework extends naturally beyond equities. The same entropy-based approach can be applied to any cross-section of assets (currencies, commodities, fixed income sectors) to detect concentration and complacency.
Limitations
This indicator has clear boundaries that users should understand.
It detects fragility, not crashes. The MEI measures structural precursors (concentration, complacency, discord) that build up before stress events. During acute sell-offs, the indicator typically drops because the conditions it measures dissolve once panic selling is broad-based. Do not expect the MEI to read red during a crash. Expect it to read red before one.
The signal is regime-dependent. In high-volatility and bear markets, the composite works as designed: high readings correspond to worse forward returns, low readings to better. In calm, trending bull markets, the relationship weakens and can reverse. This is because the "danger" conditions (concentrated breadth, credit complacency) can persist for extended periods during healthy trends without leading to corrections. Weight MEI readings more heavily when realized volatility is already elevated.
It is designed for the S&P 500. The sector ETFs and credit instruments are U.S.-specific. Applying the indicator to other indices or asset classes without modifying the data sources would not be methodologically sound.
It requires a daily timeframe. The cross-sector entropy and credit spread calculations require daily closing prices. Intraday data introduces noise that degrades the signal quality.
It needs historical depth. The z-score normalization uses a 252-day lookback. Results during the first year of data should be treated with caution.
It is not a standalone system. No single indicator captures all relevant market dynamics. The MEI measures structural conditions. It does not measure momentum, valuation, sentiment, or liquidity directly. Use it alongside other analytical tools.
References
Gilchrist, S. and Zakrajsek, E. (2012) 'Credit Spreads and Business Cycle Fluctuations', American Economic Review, 102(4), pp. 1692-1720.
Gu, R. (2017) 'Multiscale Shannon entropy and its application in the stock market', Physica A, 484, pp. 215-224.
Kaufman, P.J. (2013) Trading Systems and Methods. 5th edn. Hoboken: Wiley.
Risso, W.A. (2008) 'The informational efficiency and the financial crashes', Research in International Business and Finance, 22(3), pp. 396-408.
Shannon, C.E. (1948) 'A Mathematical Theory of Communication', Bell System Technical Journal, 27(3), pp. 379-423.
Zunino, L., Zanin, M., Tabak, B.M., Perez, D.G. and Rosso, O.A. (2009) 'Forbidden patterns, permutation entropy and stock market inefficiency', Physica A, 388(14), pp. 2854-2864.
Indicator
Initial Balance Breaks [NQ stats x CantoLab]An open source indicator built around the Initial Balance break statistics from NQ Stats (nqstats.com). Credit to NQ Stats for the original research — published here with permission.
⚠️ Important
This is a statistical study indicator. It does not guarantee that the IB high or low will be hit. Over a large sample, this is the expected behaviour based on 10 years of NQ data. It is best combined with other confluences to confirm direction — this indicator alone is not a strategy.
What is the Initial Balance?
The Initial Balance (IB) is the price range established during the first hour of the New York equity session — 09:30 to 10:30 ET. The high and low set within this window become key levels for the rest of the trading day.
Based on 10 years of NQ data, IB breaks 83% of the time before noon and 96% of the time before 4:00 PM. The stat alone doesn't give you direction — but combined with where the IB closes relative to its own midpoint, you get a directional edge:
IB closes in the upper half → high breaks 82% of the time
IB closes in the lower half → low breaks 76% of the time
What it does
Once the IB window closes at 10:30, the indicator plots the IB High, Low and Mid as levels on the chart and automatically determines the directional bias based on where price closed within the IB range.
The expected break side is labelled with its probability and a tracking line extends forward tracking whether that level gets hit. When the level is breached the label updates to show Success or Failed in real time.
IB High — upper boundary of the initial balance range
IB Low — lower boundary of the initial balance range
IB Mid — equilibrium of the range, plotted in orange.
When price closes above mid, high break is expected.
When price close below mid, low break is expected.
Probability line — extends from IB close forward on the expected side, updates to Success or Failed when hit
Settings
IB Time — configurable session window, default 09:30–10:30 NY time
Label Size — Tiny / Small / Normal / Large / Huge
Per-level line style and width — IB High, Low, Mid and vertical markers
Auto color — IB High and Low auto-adapt to chart theme, or set manually
Notes
Built for NQ Futures. Behaviour on other instruments is untested
All times are New York time
Current version tracks directional bias from IB close relative to midpoint. The 83% before noon and 96% before 4PM time-based breach tracking and IB formation order confluence are not yet implemented
Probability data derived from 10 years of NQ historical data by NQ Stats.
This indicator does not provide financial advice or a complete strategy. You are responsible for how you build around and execute on this data
Indicator
Hour Stats [NQ Stats x CantoLab]A statistical tool for NQ intraday traders built around research from NQ Stats (NQStats on twitter / nqstats.com). Credit to NQ Stats for the original concept and data — published here as an open source indicator with permission.
What it does?
For each New York session hour (08:00 – 16:00 NY time), the indicator tracks a specific setup:
1)Price opens strictly inside the prior hour's range
2)Price breaches the prior hour high or low by at least 1 tick (0.25 pts)
3)Whether price reverts back to the current hour open before the hour closes
Only the first breach per hour is counted. Reversion is confirmed when any bar's wick touches or crosses the hour open after the breach occurs.
What gets plotted
When the setup triggers, the indicator draws the following levels for that hour:
Hour Open — the high probability reversion target. In Simple mode labelled as "High Prob. Retrace", in Advanced mode shows the statistical probability based on which 20-minute segment the breach occurred in
PHH / PHL Swept — marks the breached prior hour high or low
PHH / PHL Target — the opposite side of the prior hour range, the secondary target if reversion extends further
PHM (Prior Hour Mid) — the equilibrium of the prior hour range, visible in Advanced mode only
Sweep Mark — a small shape plotted on the candle where the breach is first detected (x, +, or diamond, configurable)
Vertical dividers — split each hour into its three 20-minute segments
Simple vs Advanced mode
Simple — shows Hour Open, swept level, and opposite target. Clean and uncluttered for execution focus.
Advanced — adds the Prior Hour Mid level and overlays per-segment reversion probabilities directly on the prior hour high and low, showing the statistical likelihood of reversion depending on when in the hour the breach occurs.
Advanced Mode - The 20-minute breakdown
Each hour is divided into three 20-minute windows (00–20, 20–40, 40–60). The timing of the breach within these windows significantly affects reversion probability.
As a general rule, first segment breaches carry the highest probability of reversion — the 09:00 hour first segment sits at 87.4% historically. Probabilities are pulled from 10 years of NQ data.
Settings
Mode — Simple or Advanced
Show History — keep or clear previous setups as new ones form
Time Filter — toggle NY session filter on/off, adjustable session window
Show Optimal Timeframe Message — on-chart warning if you are above 5min timeframe
Per-level toggles — color, style (Solid/Dotted/Dashed) and width for each plotted level
Sweep Mark — toggle, color, and shape
Notes
Built for NQ Futures. Behaviour on other instruments is untested
Best used on 1m – 5min timeframes. Warning displays above 5min, error displays at 60min and above
All times are New York time
Probability data is derived from 10 years of NQ historical data by @NQStats
This indicator does not provide financial advice or a complete strategy. You are responsible for how you build around and execute on this data
Indicator
Indicator
ORB Readiness PlusORB Readiness Plus is an Opening Range Breakout decision-support indicator that tracks ORB breaks, retests, reclaims, midline reactions, and trade-quality context.
Unlike a basic ORB tool that only plots the high and low of the opening range, this script also evaluates whether the price is continuing a breakout, failing a breakout, reclaiming the ORB, or reacting from the ORB midline.
Features include ORB high/low/midline plotting, bullish and bearish close-break detection, edge retest tracking, reclaim warning and confirmation logic, midline reaction logic, VWAP alignment, HTF EMA bias, EMA slope, volume confirmation, ORB/ATR range quality, measured-move target guide, dashboard scoring, alerts, and clean triangle markers.
The goal is to help traders quickly answer:
• Has the ORB been set?
• Did price break the range with a close?
• Is the move continuing or reclaiming?
• Did price retest the ORB edge or react from the midline?
• Is the setup aligned with VWAP, trend, volume, and range quality?
Signal guide:
▲Green triangle = Long entry condition
▼ Red triangle = Short entry condition
▲ Orange triangle = Best setup condition
▲ / ▼ Small yellow triangle = Optional reclaim warning/context signal
▲ / ▼ Small gray triangle = Optional ORB midline reaction signal
This script is best used on intraday charts such as 1-minute, 3-minute, or 5-minute timeframes. It is intended for discretionary ORB traders who want a cleaner structure and context, not automatic buy or sell calls.
This indicator is for education and decision support only. It does not guarantee results. Always use proper risk management and test before using in live trading. Indicator
Bull Flow Scanner Empowerment AssetsBull Flow Scanner — Empowerment Assets
What It Is
A real-time momentum and volume scanner built in Pine Script v5 that mimics how unusual options flow analysts identify institutional buying pressure — using price action, volume surges, and multi-indicator confluence instead of actual options data.
How It Scores (0–10 Bull Points)
Point Condition
1 Price is above the Fast EMA (9)
1 Fast EMA is above Slow EMA (21)
1 Slow EMA is above Trend EMA (50)
1 Price is above VWAP (if filter enabled)
1 Volume surge detected (2x average)
1 RSI above 50
1 RSI above 60 (added momentum)
1 MACD line above Signal line
1 MACD histogram expanding upward
1 Price breaking above 20-bar high
Signal Tiers
Strong Bull (default 7–10) — Green bar highlight + "BULL" label. All major conditions aligned with volume surge. High-conviction entry zone.
Moderate Flow (default 4–6) — Blue bar highlight + "Flow" label. Partial confluence. Watch for continuation.
No Signal — No highlight. Market is not in a qualifying setup.
Visual Output
3 EMAs (fast/slow/trend) + VWAP plotted on chart
Bar highlighting — green for strong, blue for moderate
Labels at signal bars showing tier and score
Live dashboard table showing all 7 metrics updated in real time
Inputs You Can Adjust
Setting Purpose
Avg Volume Length Period for baseline volume average
Surge Multiplier How many times above average volume must be
Fast / Slow / Trend EMA Customize your MA ribbon
VWAP Filter Toggle VWAP as a required condition
Strong / Medium Threshold Raise or lower bar for each signal tier
Display toggles Turn off table, labels, or bar highlight
Table Position Move dashboard to any corner
Best Used On
Stocks, ETFs, crypto on the 5m, 15m, 1H, or daily timeframe
Works well alongside The Strat setups and options flow confirmation
Pair with price action context — the score tells you how much is aligned, not a guaranteed entry Indicator
Daye Quarterly Theory (Open Source) [CantoLab]An open source implementation of Daye's Quarterly Theory, based on the work of traderdaye. Visualises the 4 quarterly cycles — Accumulation, Manipulation, Distribution and Reversal/Continuation — across Weekly, Daily and 90 Minute timeframes in a dedicated pane below the chart.
Introduction
The underlying idea of Daye's Quarterly Theory is that time divides into repeating quarters for correct interpretation of market cycles. These quarters represent the same 4 phases regardless of which timeframe you are looking at:
A — Accumulation
M — Manipulation
D — Distribution
X — Reversal / Continuation
The sequence always follows A → M → D → X, however the cycle can begin at X depending on the analyst's discretion. This indicator focuses on the 3 most practical timeframes for day to day trading - Weekly, Daily and 90 Minute quarters.
Quarterly Cycles
Weekly Quarters
Daye determined the trading week is composed of 4 relevant days:
Q1 — Monday (Accumulation)
Q2 — Tuesday (Manipulation / True Open)
Q3 — Wednesday (Distribution)
Q4 — Thursday (Reversal / Continuation)
Daily Quarters
The trading day breaks into four 6-hour blocks, which roughly align with the major trading sessions:
Q1 — 18:00 – 00:00 (Asian Session)
Q2 — 00:00 – 06:00 (London Session / True Open)
Q3 — 06:00 – 12:00 (New York Session)
Q4 — 12:00 – 18:00 (PM Session)
Times based on New York time. Will vary by instrument, adjust according to preference.
90 Minute Quarters
Each 6-hour Daily block divides further into four 90-minute segments. The indicator automatically updates to display the active 6-hour block's quarters in real time. Using the Asian Session as an example:
Q1 — 18:00 – 19:30
Q2 — 19:30 – 21:00 (
Q3 — 21:00 – 22:30
Q4 — 22:30 – 00:00
The 90 Minute row is the most granular level included and is where most intraday traders will find their entry and exit timing.
Settings
Show History — keep or clear previous cycles as new ones form
Weekly / Daily / 90 Minute Quarters — toggle each row independently
Labels — toggle A/M/D/X labels on or off, with size control
Colors — customise each phase color individually
Border — auto-detects chart theme (light/dark) or set manually
Notes
Displays in a separate pane, does not overlay on price
Times are based on Futures trading in New York Time — adjust expectations for Forex, Metals, Crypto, Commodities and Equities
best on timeframes of 15 minutes or lower to avoid visual clutter.
Theory originally developed by traderdaye — study his material directly for full context on how to apply these cycles.
Indicator
Better Sessions [CantoLab]This session indicator plots Asia, London and New York sessions, with 3 extra fully customisable sessions. Includes sweep detection to automatically track if price has swept session highs/lows, and a visual dashboard to identify overlapping sessions.
Features :
Sessions
Up to 6 sessions can be configured with custom times, colors and labels. By default the indicator comes set to Asia, London and NY stock exchange timings. The 3 additional sessions can be set to anything.
A common use case is replicating ICT killzones by adjusting the session times in settings to London , NY-AM , NY-PM , Asia
The overlapping window between London and New York is highlighted automatically in the dashboard, signifying the period of potential high volume and volatility traders watch closely.
Sweep Detection
On session close, lines are drawn automatically from the session high and low. They extend forward bar by bar and mark as swept the moment price crosses them. No manual drawing or monitoring needed.
Daily Dividers
Vertical lines at each day boundary to separate trading days.
Settings:
Sessions — toggle, time, color and label per session
Sweep Detection — toggle in settings (off by default)
CE Line — session equilibrium/midpoint, toggle in settings
Daily Dividers — toggle, color, style and width
Session Table — 24hr overlap dashboard, 9 position options
Label Size — Tiny / Small / Normal / Large
Notes:
Best used on timeframes at or below 1 hour
Sweep lines reset at the start of each new day
UTC offset applies globally — adjust manually for DST
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Strategy
CHoCH VWAP Smart Money| julzALGO📊 CHoCH VWAP Smart Money| julzALGO
🔷 1. Overview
CHoCH VWAP Smart Money is a structure-anchored smart money repricing framework that combines internal Change of Character (CHoCH), structural pivot detection, anchored VWAP, premium/discount band mapping, and integrated risk-to-reward execution into one unified overlay.
The script is designed to help traders evaluate not only when market structure shifts, but where price may reprice, retest, defend, or reject after that shift.
By combining internal structural flips with pivot-anchored VWAP recalculation, this framework can be used for:
• Initial structural reversal detection
• Smart money demand / supply repricing
• Pullback and retest planning
• Premium / discount zone analysis
• Institutional cost-basis visualization
• Risk-to-reward execution planning
🔷 2. Core Concept
Traditional VWAP often resets from fixed sessions, daily opens, or arbitrary anchors.
CHoCH Anchored VWAP expands this by integrating:
• Internal CHoCH structural flips
• Swing high / swing low pivots
• Structural break confirmation
• Pivot-based anchor reset
• CHoCH-anchored VWAP recalculation
• Premium / discount deviation bands
• Historical structural path preservation
• Dynamic RR projection
The core idea is simple:
Each confirmed internal CHoCH establishes a structural repricing event.
From that event:
• Previous market structure is considered disrupted
• A new structural anchor pivot is selected
• VWAP resets from that anchor
• Institutional average price is recalculated from the structural origin
• Premium / discount bands evolve dynamically until the next opposite CHoCH occurs
Where VWAP and participation calculation starts:
VWAP, Standard Deviation / Percentage Bands, and RR zones begin calculating from the CHoCH anchor pivot marker and continue accumulating through each new bar until the next confirmed opposite structural CHoCH occurs.
Simple rule:
CHoCH Anchor Pivot → Present Active Bar
Bullish CHoCH:
When bullish CHoCH is confirmed, VWAP tracking begins from the prior structural swing low.
Bearish CHoCH:
When bearish CHoCH is confirmed, VWAP tracking begins from the prior structural swing high.
Reset rule:
When a new opposite CHoCH occurs:
• Previous VWAP path stops
• Previous path becomes historical dashed structure
• New anchor is selected
• New VWAP and bands reset
• New RR planning begins
Important:
VWAP and Bands are not session-based.
They represent cumulative structural repricing from the CHoCH origin to the current active bar.
This helps traders evaluate whether the active structure remains institutionally supported, discounted, or overextended—even during pullbacks, retests, or liquidity rebalances.
🔷 3. How It Works
The Internal CHoCH Engine continuously tracks rolling pivot highs and lows using the selected internal pivot length.
This identifies:
• Bullish CHoCH
• Bearish CHoCH
• Internal structure breaks
• Structural anchor pivots
• Demand / supply shift zones
Break confirmation can be based on:
• Candle close
• Wick break
Once a valid CHoCH is confirmed:
The VWAP Engine resets and recalculates a new anchored VWAP path from the structural pivot.
Instead of anchoring to arbitrary time, this model anchors to structural intent.
This transforms VWAP into a dynamic smart money cost-basis path.
The Band Engine projects:
• Band #1 = Primary premium / discount zone
• Band #2 = Extended premium / discount zone
• Band #3 = Exhaustion / expansion zone
Band modes:
• Standard Deviation = Statistical structural expansion
• Percentage = Fixed repricing percentage
The RR system can project:
• Entry
• Stop Loss
• Take Profit
This allows traders to combine structure, institutional repricing, and visual execution planning in one workflow.
Visual interpretation:
• Blue VWAP Path = Bullish structural demand repricing
• Purple VWAP Path = Bearish structural supply repricing
• Blue Diamond = Bullish CHoCH anchor where tracking begins
• Purple Diamond = Bearish CHoCH anchor where tracking begins
• Bands = Premium / Discount deviation zones
• Dashed Historical VWAP = Previous structural cycle
• Entry = Structural execution trigger
• SL = Volatility or pivot invalidation
• TP = RR objective
🔷 4. Smart Money Interpretation
This framework is especially useful for:
For Bullish
For Bearish
Demand Reclaim:
Bullish CHoCH → Pullback into VWAP / Lower Band → Demand hold → Continuation bias
Supply Rejection:
Bearish CHoCH → Pullback into VWAP / Upper Band → Supply reject → Continuation bias
Premium / Discount:
• Below bullish VWAP = Potential discount accumulation
• Above bearish VWAP = Potential premium distribution
Retest Logic:
CHoCH identifies WHEN structure changes
VWAP identifies WHERE smart money may defend that change
This makes the indicator useful for:
• Retests
• Pullbacks
• Demand / Supply zones
• Institutional repricing
• Liquidity rebalance
🔷 5. Settings
Internal Pivot Length
Controls structural sensitivity.
Suggested reference:
• 5–15 = Faster / scalping
• 20–40 = Balanced / intraday
• 50+ = Higher timeframe / smoother
Break Confirmation
Close: More conservative structural confirmation.
Wick: More aggressive / earlier detection.
Band Calculation Mode
Standard Deviation: Adaptive volatility-based premium / discount.
Percentage:Fixed expansion bands.
Stop Loss Type
ATR: Adaptive volatility stop.
Pivot: Structure invalidation stop.
ATR Multiplier
Suggested reference:
• 1.5 = Tight
• 2.0 = Balanced
• 3.0+ = Wider
Risk:Reward
Suggested reference:
• 1.5 = Conservative
• 2.0 = Balanced
• 3.0 = Extended
General preset:
• Internal Pivot Length: 10–20
• Confirmation: Close
• Band Mode: Standard Deviation
• Stop Loss Type: Pivot or ATR
• ATR Multiplier: 2.0–3.0
• RR: 2.0
🔷 IMPORTANT NOTES
• This indicator does not guarantee profits and should not be used in isolation
• Internal CHoCH may be more sensitive than external structure
• VWAP anchoring is structure-based, not session-based
• Premium / discount does not automatically imply reversal
• Market conditions vary; always apply proper risk management
🔷 DISCLAIMER
This script is for educational and informational purposes only.
It does not constitute financial advice. Always perform your own analysis before making trading decisions Indicator
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