SigmoidCycle Oscillator [LuminoAlgo]Purpose:
The SineCycle Oscillator measures price momentum using sigmoid function mathematics (S-curve transformation) borrowed from neural network theory. It generates an oscillator that fluctuates around 1.0, identifying momentum shifts and potential reversal points.
Mathematical Foundation:
This indicator applies the sigmoid logistic function concept: y = 1/(1+e^-x) , which creates an S-shaped curve. In financial markets context, this transformation:
- Maps price changes to a bounded range (-1 to +1)
- Provides non-linear sensitivity (high near zero, low at extremes)
- Naturally filters outliers without lag penalty
Calculation Process:
1. Statistical Normalization: Price deviations are measured from a moving average baseline and scaled by recent volatility (standard deviation over N periods)
2. Sigmoid Transformation: Normalized values undergo S-curve transformation, which weights small movements linearly but compresses large movements logarithmically
3. Dual Timeframe Analysis:
• Short window: User-defined period (N)
• Long window: Double period (2N)
• Ratio calculation: Short sigmoid average ÷ Long sigmoid average
4. Volatility-Weighted Smoothing: Final values use exponential smoothing where the smoothing factor adjusts based on the coefficient of variation (volatility/mean ratio)
What Makes This Different:
Unlike linear momentum oscillators (RSI, Stochastic) that use fixed mathematical relationships, the sigmoid transformation creates variable sensitivity zones. This mimics how professional traders mentally weight price movements.
Trading Application:
Signal Types:
- Momentum: Green (>1.0) = bullish, Red (<1.0) = bearish
- Reversals: 1.0 line crosses with volume confirmation
- Divergence: Price makes new high/low, oscillator doesn't
- Exhaustion: Extended readings (>1.2 or <0.8) suggest overextension
Optimal Conditions:
- Works best: Trending markets with clear swings
- Avoid: Low volume, ranging markets under 1% daily movement
- Timeframes: 4H and above for reliability
Parameter Guidelines:
- Length 8-10: Day trading (expect more whipsaws)
- Length 14-20: Swing trading (balanced signals)
- Length 25-30: Position trading (fewer, stronger signals)
Limitations:
- Lag increases with higher length settings
- Can give false signals during news-driven spikes
- Requires additional confirmation in choppy markets
Trading Framework:
Based on momentum persistence theory - assumes trends continue until sigmoid curve flattens (indicating momentum exhaustion). The mathematical model captures both mean reversion (extreme readings) and trend following (mid-range readings) characteristics.
Analisi trend
Kio IQ [TradingIQ]Introducing: “Kio IQ ”
Kio IQ is an all-in-one trading indicator that brings momentum, trend strength, multi-timeframe analysis, trend divergences, pullbacks, early trend shift signals, and trend exhaustion signals together in one clear view.
🔶 The Philosophy of Kio IQ
Markets move in trends—and capturing them reliably is the key to consistency in trading. Without a tool to see the bigger picture, it’s easy to mistake a pullback for a breakout, a fakeout for the real deal, or random market noise as a meaningful price move.
Kio IQ cuts through that random market noise—scanning multiple timeframes, analyzing short, medium, and long-term momentum, and telling you on the spot whether a move is strong, weak, a trap, or simply a small move within a larger trend.
With Kio IQ, price action reveals its next move.
You’ll instantly see:
Which way it’s pushing — up, down, or stuck in the middle.
How hard it’s pushing — from fading weakness to full-blown strength.
When the gears are shifting — early warnings, explosive moves, smart pullbacks, or signs it’s running out of steam.
🔶 Why This Matters
Markets move in phases—sometimes they’re powering in one direction, sometimes they’re slowing down, and sometimes they’re reversing.
Knowing which phase you’re in can help you:
Avoid chasing a move that’s about to run out of steam.
Jump on a move when it’s just getting started.
Spot pullbacks inside a bigger trend (good for entries).
See when different timeframes are all pointing the same way.
🔶 What Kio IQ Shows You
Simple color-coded phases: “Strong Up,” “Up,” “Weak Up,” “Weak Down,” “Down,” “Strong Down.”
Clear visual signals
Full Shift: Strong momentum in one direction.
Half Shift: Momentum is building but not full power yet.
Pullback Shift: A small move against the trend that may be ending.
Early Scout / Lookout: First hints of a possible shift.
Exhaustion: Momentum is very stretched and may slow down.
Divergences: When price moves one way but momentum moves the opposite way—often a warning of a change.
Multi-Timeframe Table: See the trend strength for multiple timeframes (5m, current, 30m, 4h, 1D, and optional 1W/1M) all in one place.
Trend Strength %: A single number that tells you how strong the trend is across all timeframes.
Optional meters: A “momentum bar” and “trend strength gauge” for quick checks.
🔶 How It Works Behind the Scenes
Kio IQ measures price movement in different “speeds”:
Slow view: Big picture trend.
Medium view: The main engine for detecting the current phase.
Fast view: Catches recent changes in momentum.
Super-fast view: Finds tiny pullbacks inside the bigger move.
It compares these views to decide whether the market is strong up, weak up, weak down, strong down, or in between. Then it blends data from multiple timeframes so you see the whole picture, not just the current chart.
🔶 What You’ll See on the Chart
🔷 Full Shift Oscillator (FSO)
The image above highlights the Full Shift Oscillator (FSO).
The FSO is the cornerstone of Kio IQ, delivering mid-term momentum analysis. Using a proprietary formula, it captures momentum on a smooth, balanced scale — responsive enough to avoid lag, yet stable enough to prevent excessive noise or false signals.
The Key Upside Level for the FSO is +20, while the Key Downside Level is -20.
The image above shows the FSO above +20 and below -20, and the corresponding price movement.
FSML above +20 confirms sustained upside momentum — the market is being driven by consistent, broad-based buying pressure, not just a price spike.
FSML below -20 confirms sustained downside momentum — sellers are firmly in control across the market.
We do not chase the first sudden price move. Entries are only considered when the market demonstrates persistence, not impulse.
🔷 Half Shift Oscillator (HSO)
The image above highlights the Half Shift Oscillator (HSO).
The HSO is the FSO’s wingman — faster, more reactive, and designed to catch the earliest signs of strength, weakness, or momentum shifts.
While HSO reacts first, it is not a standalone confirmation of a major momentum change or trade-worthy strength.
Using the same proprietary formula as the FSO but scaled down, the HSO delivers smooth, balanced short-term momentum analysis. It is more responsive than the FSO, serving as the scout that spots potential setups before the main signal confirms.
The Key Upside Level for the FSO is +4, while the Key Downside Level is -4.
🔷 PlayBook Strategy: Shift Sync
Shift Sync is a momentum alignment play that triggers when short-term and mid-term momentum lock into the same direction, signaling strong directional control.
🔹 UpShift Sync – Bullish Alignment
HSO > +4 – Short-term momentum is firmly bullish.
FSO > +20 – Mid-term momentum confirms the bullish bias.
When both thresholds are met, buyers are in control and price is primed for continuation higher.
🔹 DownShift Sync – Bearish Alignment
HSO < -4 – Short-term momentum is firmly bearish.
FSO < -20 – Mid-term momentum confirms the bearish bias.
When both thresholds are met, sellers dominate and price is primed for continuation lower.
Execution:
Look for an entry opportunity in the direction of the alignment when conditions are met.
Avoid choppy conditions where alignment is frequently lost.
Why It Works
Think of the market as a tug-of-war between traders on different timeframes. Short-term traders (captured by the HSO) are quick movers — scalpers, intraday players, and algos hunting immediate edge. Mid-term traders (captured by the FSO) are swing traders, funds, and institutions who move slower but carry more weight.
Most of the time, these groups pull in opposite directions, creating chop and fakeouts. But when they suddenly lean the same way, the rope gets yanked hard in one direction. That’s when momentum has the highest chance to drive price further with minimal resistance.
Shift Sync works because it isolates those rare moments when multiple market “tribes” agree on direction — and when they do, price doesn’t just move, it flies.
Best Market Conditions
Shift Sync works best when the higher timeframe trend (daily, weekly, or monthly) is moving in the same direction as the alignment. This higher timeframe confluence increases follow-through potential and reduces the likelihood of false moves.
The image above shows an example of an UpShift Sync signal where the momentum table shows that the 1D momentum is bullish.
The image above shows bonus confluence, where the 1M and 1W momentum are also bullish.
The image above shows an example of a DownShift Sync signal where the momentum table shows that the 1D momentum is bearish. Bonus confluence also exists, where the 1W and 1M chart are also bearish.
Common Mistakes
Chasing late signals – Avoid entering if the Shift Sync trigger has been active for a long time. Instead, wait for a Shift Sync Pullback to look for opportunities to join in the direction of the trend.
Ignoring higher timeframe bias – Taking Shift Sync setups against the daily, weekly, or monthly trend reduces follow-through potential and increases the risk of a failed move.
🔷 Micro Shift Oscillator (MSO)
The image above highlights the Micro Shift Oscillator (MSO)
The MSO is the finishing touch to the FSO and HSO — the fastest and most reactive of the three. It’s built to spot pullback opportunities when the FSO and HSO are aligned, helping traders join strong price moves at the right time.
The MSO may reveal the earliest signs of a momentum shift, but that’s not its primary role. Its purpose is to identify retracement and pullback opportunities within the overarching trend, allowing traders to join the move while momentum remains intact.
🔷 Playbook Strategy: Shift Sync Pullback
Key Levels:
MSO Upside Trigger: +3
MSO Downside Trigger: -3
🔹 UpShift Pullback
Momentum Confirmation:
FSO > +20 – Mid-term momentum is strongly bullish.
HSO > +4 – Short-term momentum confirms alignment with the FSO.
Pullback Trigger:
MSO ≤ -3 – Signals a short-term retracement within the ongoing bullish trend and marks the earliest re-entry opportunity.
Entry Zone:
The blue arrow on the top chart shows where momentum remains intact while price pulls back into a zone primed for a move higher.
Setup Validity: Both FSO and HSO must remain above their bullish thresholds during the pullback.
Invalid Example:
If either the FSO or HSO drop below their bullish thresholds, momentum alignment breaks. No trade is taken.
🔹 DownShift Pullback
Momentum Confirmation:
FSO < -20 – Mid-term momentum is strongly bearish.
HSO < -4 – Short-term momentum aligns with the FSO, confirming seller dominance.
Pullback Trigger:
MSO ≥ +3 – Indicates a short-term retracement against the bearish trend, pointing to possible short-entry opportunities.
Entry Zone:
The purple arrow on the top chart marks valid pullback conditions — all three oscillators meet their bearish thresholds, and price is positioned to continue lower.
Setup Validity: Both FSO and HSO must remain below their bearish thresholds during the pullback.
Invalid Example:
If either oscillator rises above the bearish threshold, momentum alignment is lost and the MSO signal is ignored.
Why It Works
Even in strong trends, price rarely moves in a straight line. Supply and demand dynamics naturally create retracements as traders take profits, bet on reversals, or hedge positions.
While many momentum traders fear these pullbacks, they’re often the fuel for the next leg of the move — offering a “second chance” to join the trend at a more favorable price.
The Shift Sync Pullback pinpoints moments when both short-term (HSO) and mid-term (FSO) momentum remain firmly aligned, even as price moves temporarily against the trend. This alignment suggests the retracement is a pause, not a reversal.
By entering during a controlled pullback, traders often secure better entries, tighter stops, and stronger follow-through potential when the trend resumes.
Best Market Conditions:
Works best when the higher timeframe (daily, weekly, or monthly) is trending in the same direction as the pullback setup.
Consistent momentum is ideal — avoid erratic, news-driven chop.
Following a recent breakout (Gate Breaker setup) when momentum is still fresh.
Common Mistakes
Ignoring threshold breaks – Entering when either HSO or FSO dips through their momentum threshold often leads to taking trades in weakening trends.
Trading against higher timeframe bias – A pullback against the daily or weekly trend is more likely to fail; use higher timeframe confluence as a filter.
🔷 Macro Shift Oscillator (MaSO)
The chart above shows the MaSO in isolation.
While the MaSO is not part of any active Kio IQ playbook strategies, it delivers the clearest view of the prevailing macro trend.
MaSO > 0 – Macro trend is bullish. Readings above +4 signal extreme bullish conditions.
MaSO < 0 – Macro trend is bearish. Readings below -4 signal extreme bearish conditions.
Use the MaSO for context, not entries — it frames the environment in which all other signals occur
🔷 Shift Gates – Kio IQ Momentum Barriers
The image above shows UpShift Gates.
UpShift Gates mark the highest price reached during periods when the FSO is above +20 — moments when mid-term momentum is firmly bullish and buyers are in control.
UpShift Gates are upside breakout levels — key swing highs formed before a pullback during periods of strong bullish momentum. When price reclaims an UpShift Gate with momentum confirmation, it signals a potential continuation of the uptrend.
The image above shows DownShift Gates.
DownShift Gates Mark The Lowest Price Reached During Periods When The FSO Is Below -20 — Moments When Mid-Term Momentum Is Firmly Bearish And Sellers Are In Control.
DownShift Gates are downside breakout levels — key swing lows formed before an upside pullback during periods of strong bearish momentum. When price reclaims a DownShift Gate with momentum confirmation, it signals a potential continuation of the downtrend.
🔷 Playbook Strategy: Gate Breakers
Core Rule:
Long signal when price decisively closes beyond an UpGate (for longs) or DownGate (for shorts). The breakout must show commitment — no wick-only tests.
🔹 UpGate Breaker (UpGate)
Trigger: Price closes above the UpShift Gate level.
Bonus Confluence: MaSO > 0 at the moment of the break — confirms that the macro trend bias is in favor of the breakout.
Invalidation: Avoid taking the signal if the gate level forms part of a DownShift Rift (bearish divergence) — this signals underlying weakness despite the break.
The chart above shows valid UpGate Breakers.
The chart above shows an invalidated UpGate Breaker setup.
🔹 DownGate Breaker (DownGate)
Trigger: Price closes below the DownShift Gate level.
Bonus Confluence: MaSO < 0 at the moment of the break — confirms that the macro trend bias is in favor of the breakdown.
Invalidation: Avoid taking the trade if the gate level forms part of an UpShift Rift (bullish divergence) — this signals underlying strength despite the break.
The chart above shows a valid DownGate Breaker.
Why It Works
Key swing levels like Shift Gates attract a high concentration of resting orders — stop losses from traders caught on the wrong side and breakout orders from momentum traders waiting for confirmation.
When price decisively clears a gate with a strong close, these orders trigger in quick succession, creating a burst of directional momentum.
Adding the MaSO filter ensures you’re breaking gates with the prevailing macro bias, improving the odds that the move will continue rather than stall.
The divergence-based invalidation rule (Rift filter) prevents entries when underlying momentum is moving in the opposite direction, helping avoid “fake breakouts” that trap traders.
Best Market Conditions:
Works best in markets with clear trend structure and visible Shift Gates (not during chop).
Strongest when higher timeframe (1D, 1W, 1M) momentum aligns with the breakout direction.
MaSO > 0 for bullish breakouts, MaSO < 0 for bearish breakouts
Most reliable after a period of consolidation near the gate, where pressure builds before the break.
Common Mistakes
Trading wick-only tests – A breakout without a decisive candle close beyond the gate often fails.
Ignoring MaSO bias – Taking a break in the opposite macro direction greatly reduces follow-through odds.
Skipping the Rift filter – Entering when the gate forms part of a divergence setup exposes you to higher reversal risk.
Chasing extended moves – If price is already far beyond the gate by the time you see it, risk/reward is poor; wait for the next setup or a retest.
🔷 Shift Rifts - Kio IQ Divergences
This chart shows an UpShift Rift — a bullish divergence where price action and momentum part ways, signaling a potential trend reversal or acceleration.
Setup:
Price Action: Price is marking lower lows, indicating short-term weakness.
FSO Reading: The Full Shift Oscillator (FSO) is marking higher lows over the same period, showing underlying momentum strengthening despite falling prices.
The rift between price and the FSO suggests selling pressure is losing force while buyers quietly regain control.
When confirmed by broader trend alignment in Kio IQ’s multi-timeframe momentum table, the UpShift Rift becomes a setup for a bullish move.
This chart shows a DownShift Rift — a bearish divergence where price action and momentum split, signaling a potential downside reversal.
Setup:
Price Action: Price is marking higher highs, suggesting continued strength on the surface.
FSO Reading: The Full Shift Oscillator (FSO) is marking lower highs over the same period, revealing weakening momentum beneath the price advance.
The rift between price and momentum signals that buying pressure is fading, even as price makes new highs. This disconnect often precedes a momentum shift in favor of sellers.
When aligned with multi-timeframe bearish signals in Kio IQ’s momentum table, the DownShift Rift becomes a strong setup for downside continuation or reversal.
🔷 Playbook Strategy: Rift Reversal
The Rift Reversal is a divergence-based reversal play that signals when momentum is fading and an trend reversal is likely. It’s designed to catch early turning points before the broader market catches on.
Trader’s Note:
This strategy is not intended for beginners — it requires confidence in reading divergence and trusting momentum shifts even when price action still appears weak. Best suited for traders experienced in managing reversals, as entries often occur before the broader market confirms the move.
🔹 UpRift Reversal
Core Setup:
Price Action – Forms a lower low.
Momentum Rift – The FSO forms a higher low, signaling bullish divergence and weakening selling pressure.
Trigger:
A confirmed UpRift Reversal signal is printed when:
Bullish Divergence is detected — price makes a new low, but the oscillator fails to confirm.
Momentum begins turning up from the divergence low (marked on chart as ⇝)
The image above shows a valid UpRift Reversal play.
🔹 DownRift Reversal
Core Setup:
Price Action – Forms a higher high.
Momentum Rift – The FSO forms a lower high, signaling bearish divergence and weakening buying pressure.
Trigger
A confirmed DownRift Reversal signal is printed when:
Bearish Divergence is detected — price makes a new high, but the oscillator fails to confirm.
Momentum begins turning down from the divergence high (marked on chart as ⇝).
Why It Works
Shift Rifts work because momentum often fades before a price reverses.
Price is the final scoreboard — it reflects what has already happened. Momentum, on the other hand, is a leading indicator of pressure. When the FSO begins to move in the opposite direction of price, it signals that the dominant side in the market is losing steam, even if the scoreboard hasn’t flipped yet.
In an UpShift Rift, sellers keep pushing price lower, but each push has less force — buyers are quietly building pressure under the surface.
In a DownShift Rift, buyers keep marking new highs, but they’re spending more effort for less result — sellers are starting to take control.
These disconnects happen because large participants often scale into or out of positions gradually, creating momentum shifts before price reflects it. Shift Rifts capture those turning points early.
Best Market Conditions:
Best in markets that have been trending strongly but are starting to show signs of exhaustion.
Works well after a prolonged move into key support/resistance, where large players may take profits or reverse positions.
Higher win potential when the Rift aligns with higher timeframe momentum bias in Kio IQ’s multi-timeframe table.
Common Mistakes
Forcing Rifts in choppy markets – In sideways chop, small oscillations can look like divergences but lack conviction.
Ignoring multi-timeframe bias – Trading an UpShift Rift when higher timeframes are strongly bearish (or vice versa) reduces follow-through odds.
Entering too early – Divergences can extend before reversing; wait for momentum to confirm a turn (⇝) before making a trading decision.
Confusing normal pullbacks with Rifts – Not every dip in momentum is a divergence; the Rift requires a clear and opposing trend between price and FSO.
🔷 Shift Count – Momentum Stage Tracker
Purpose:
Shift Count measures how far a bullish or bearish push has progressed, from its first spark to potential exhaustion.
It tracks momentum in defined steps so traders can instantly gauge whether a move is just starting, picking up steam, fully extended, or at risk of reversing.
How It Works
Bullish Momentum:
Start (1–2) → New momentum emerging, early entry window.
Acceleration (3–4) → Momentum in full swing, best for holding or adding to a position.
Extreme Bullish Momentum / Final Stages (5) → Watch for signs of reversal or take partial profits.
Exhaust – Can only occur after 5 is reached, signaling that the rally may be losing steam.
Bearish Momentum:
Start (-1 to -2) → New selling pressure emerging.
Acceleration (-3 to -4) → Bear trend accelerating.
Extreme Bearish Momentum / Final Stages (-5) → Watch for reversal or scale out.
Exhaust – Can only occur after -5 is reached, signaling that the sell-off may be running out of force.
The chart above shows a full 5-UpShift count.
The chart above shows a full 5-DownShift count.
Why It’s Useful
Markets often move in momentum “steps” before reversing or taking a breather.
Shift Count makes these steps visible, helping traders:
Spot the early stages of a potential move.
Identify when a move is picking up steam.
Identify when a move is mature and vulnerable to reversal.
Combine with other Kio IQ strategies for better-timed entries and exits.
Why This Works
It’s visually obvious where you are in the momentum cycle without overthinking.
You can build rules like:
Only enter in Start phase when higher timeframe agrees.
Manage positions aggressively once in Acceleration phase.
Be ready to exit or fade in Exhaust phase.
Best Market Conditions
Trending markets where pullbacks are shallow.
Works best when combined with Shift Sync Pullback or Gate Breaker triggers to confirm timing.
Higher timeframe direction confluence.
Common Mistakes
Treating Exhaust as always a reversal — sometimes strong markets push past 5/-5 multiple times.
Ignoring higher timeframe bias — a “Start” on a 1-minute chart against a strong daily trend is much riskier.
🔷 Playbook Strategy: Exhaust Flip
Core idea: When Shift Count reaches 5 (or -5) and then prints Exhaust, momentum has likely climaxed, whether temporarily or leading to a full reversal. We take the first qualified signal against the prior move.
Trader’s Note:
This strategy is not intended for beginners — it requires confidence in trusting momentum shifts even when price action still appears strong. Best suited for traders experienced in managing reversals, as entries often occur before the broader market confirms the move.
🔹 UpExhaust Flip (fade a bullish run)
Setup:
Shift Count hits 5, then an Exhaust print occurs.
Invalidation
The local high is broken to the upside.
The chart above explains the UpExhaust Flip strategy in greater detail.
🔹 DownExhaust Flip (fade a bearish run)
Setup:
Shift Count hits -5, then an Exhaust print occurs.
Invalidation
The local low is broken to the downside.
The chart above explains the DownExhaust Flip strategy in greater detail.
Bonus Confluence (optional, not required)
Rift assist: An UpShift Rift (for longs) or DownShift Rift (for shorts) near Exhaust strengthens the flip.
MaSO context: Neutral or opposite-leaning MaSO helps. Avoid flips straight against a strong MaSO bias unless you have a structure break.
Why It Works
Exhaust marks climax behavior: the prior side has pushed hard, then failed to extend after meeting significant pushback. Liquidity gets thin at the edges; aggressive profit-taking meets early contrarians. A small confirmation (micro structure break or HSO turn) is often enough to flip the tape for a snapback.
Best Market Conditions
After extended, one-sided runs (multiple Shift Count steps without meaningful pullbacks).
Near Shift Gates or obvious swing extremes where trapped orders cluster.
When higher-timeframe momentum is neutral or softening (you’re fading the last thrust of a decisive move, not a fresh trend).
Common Mistakes
Fading too early: Taking the trade at 5 without waiting for the Exhaust.
Fading freight trains: Fighting a fresh Shift Sync in the same direction right after Exhaust (often just a pause).
No structure reference: Entering without a clear micro swing to anchor risk.
🔷 MTF Shift Table
The MTF Shift Table table provides a compact, multi-timeframe view of market momentum shifts. Each cell represents the current shift count within a given timeframe, while the classification label indicates whether momentum is strong, weak, or normal.
The chart above further outlines the MTF Shift Table.
Why It Works
Markets rarely move in a perfectly linear fashion — momentum develops, stalls, and transitions at different speeds across different timeframes. This table allows you to:
See momentum alignment at a glance – If multiple higher and lower timeframes show a sustained shift count in the same direction, the move has greater structural support.
Spot divergences early – A shorter timeframe reversing against a longer-term sustained count can warn of potential pullbacks or trend exhaustion before price confirms.
Identify “momentum stacking” opportunities – When shift counts escalate across timeframes in sequence, it often signals a stronger and more durable move.
Avoid false enthusiasm – A single timeframe spike without agreement from other periods may be noise rather than genuine momentum.
The Trend Score provides a concise, at-a-glance evaluation of an asset’s directional strength across multiple timeframes. It distills complex momentum and Shift data into a single, easy-to-read metric, allowing traders to quickly determine whether the prevailing conditions favor bullish or bearish continuation. The Trend Scale scales from -100 to 100.
How to Use It in Practice
Trend Confirmation – Confirm that your intended trade direction is backed by multiple timeframes maintaining consistent momentum.
Risk Timing – Reduce position size or take partial profits when lower timeframes begin shifting against the dominant momentum classification.
Multi-timeframe Confluence – Combine with other system signals (e.g., FSO, HSO) for higher-probability entries.
This table effectively turns a complex multi-timeframe read into a single, glanceable heatmap of momentum structure, enabling quicker and more confident decision-making.
The MTF Shift Table is the confluence backbone of every playbook strategy for Kio IQ.
🔷 Momentum Meter
The Momentum Meter is a composite gauge built from three of Kio IQ’s core momentum engines:
HSO – Short-term momentum scout
FSO – Mid-term momentum backbone
MaSO – Macro trend context
By combining these three readings, the meter provides the most strict and lagging momentum classification in Kio IQ.
It only flips direction when a composite score of all three oscillators reach defined thresholds, filtering out short-lived counter-moves and false starts.
Why It Works
Many momentum tools flip too quickly — reacting to short-lived spikes that don’t represent real directional commitment. The Momentum Meter avoids this by requiring alignment across short, mid, and macro momentum engines before it shifts bias.
This triple-confirmation rule filters out noise, catching only those moments when traders of all speeds — scalpers, swing traders, and long-term participants — are leaning in the same direction. When that happens, price movement tends to be more sustained and less prone to immediate reversal.
In other words, the Momentum Meter doesn’t just tell you “momentum looks good” — it tells you momentum looks good to everyone who matters, across all horizons.
How It Works
Blue = All three engines align bullish.
Pink = All three engines align bearish.
The meter ignores smaller pullbacks or temporary oscillations that might flip the faster indicators — it waits for total alignment before changing state.
Because of this strict confirmation requirement, the Momentum Meter reacts slower but delivers higher-conviction shifts.
How to Interpret Readings
Blue (Bullish Alignment):
Sustained buying pressure across short, mid, and macro views. Often marks the “full confirmation” stage of a move.
Pink (Bearish Alignment):
Sustained selling pressure across all views. Confirms sellers are in control.
Practical Uses
Trend Followers – Use as a “stay-in” confirmation once a position is already open.
Swing Traders – Great for filtering out low-conviction setups; if the Momentum Meter disagrees with your intended direction, conditions aren’t fully aligned.
Confluence and Direction Filter – The Momentum Meter can be used as a form of confluence i.e. blue = longs only, pink = shorts only.
Limitations
Will always turn after the faster oscillators (HSO/MSO). This is intentional.
Works best in trending markets — in choppy conditions it may lag shifts significantly.
Should be used as a bias filter, not a standalone entry signal.
🔷 Trend Strength Meter
The Trend Strength Meter is a compact visual gauge that scores the current trend’s strength on a scale from -5 to +5:
+5 = Extremely strong bullish trend
0 = Neutral, no clear trend
-5 = Extremely strong bearish trend
This is an optional tool in Kio IQ — designed for quick reference rather than as a primary trading trigger.
Why it works
Single-indicator trend reads can be misleading — they might look strong on one metric while quietly weakening on another. The Trend Strength Meter solves this by blending multiple inputs (momentum alignment, structure persistence, and multi-timeframe data) into one composite score.
This matters because trend health isn’t just about direction — it’s about persistence. A +5 or -5 score means the market is not only trending but holding that trend with structural support across multiple timeframes.
By tracking both direction and staying power, the Trend Strength Meter flags when a move is at risk of fading before price action fully confirms it — giving you a head start on adjusting your position or taking profits.
How It Works
The Trend Strength Meter evaluates multiple market inputs — including momentum alignment, price structure, and persistence — to assign a numeric value representing how firmly the current move is holding.
The scoring logic:
Positive values indicate bullish conditions.
Negative values indicate bearish conditions.
Higher magnitude (closer to ±5) = stronger conviction in that direction.
Values near zero suggest the market is in a transition or range.
How to Interpret Readings
+4 to +5 (Strong Up) – Trend is well-established, often with multi-timeframe agreement.
+1 to +3 (Up) – Bullish bias present, but not at maximum conviction.
0 (Neutral) – No dominant trend; could be consolidation or pre-shift phase.
-1 to -3 (Down) – Bearish bias present but moderate.
-4 to -5 (Strong Down) – Trend is firmly bearish, with consistent downside momentum.
Why It Works
A single timeframe or momentum reading can give a false sense of trend health.
The Trend Strength Meter aggregates multiple layers of market data into one simplified score, making it easy to see whether a move has the underlying support to continue — or whether it’s more likely to stall.
Because the score considers both direction and persistence, it can flag when a move is losing strength even before price structure fully shifts.
🔷 Kio IQ – Supplemental Playbook Strategies
These phases are part of the Kio IQ Playbook—situational tools that can help you anticipate potential momentum changes.
While they can be useful for planning and tactical adjustments, they are not primary trade triggers and should be treated as early, lower-conviction cues.
🔹 1. Scouting Phase (Light Early Cue)
Purpose: Provide the earliest possible hint that momentum may be shifting.
Upshift Trigger: FSO crosses above the 0 line.
Downshift Trigger: FSO crosses below the 0 line.
Why It Works
The 0 line in the Full Shift Oscillator (FSO) acts as a neutral momentum boundary.
When the FSO moves above 0, it suggests that medium-term momentum has shifted to bullish territory.
When it moves below 0, it suggests that medium-term momentum has shifted to bearish territory.
This crossover is often the first measurable sign of a momentum reversal or acceleration, well before slower indicators confirm it.
Think of it as "momentum poking its head above water"—you’re spotting the change before it becomes obvious on price alone.
Best Use
Works best when confirmed later by Lookout Phase or other primary Kio IQ signals.
Ideal for scouting in anticipation of potential opportunities.
Helpful when monitoring multiple assets and you want a quick filter for shifts worth watching.
Can act as a trade trigger when the MTF Shift Table shows confluence (i.e., UpShift Scouting Signal + Bullish MTF Table + High Trend Strength Score).
Common Mistakes
Acting on Scouting Phase signals against the MTF Shift Table as a stand-alone trade trigger. Without higher timeframe alignment or additional confirmation, many Scouting Phase crossovers can fade quickly or reverse, leading to premature entries.
Ignoring market context
A bullish Scouting Phase in a strong downtrend can easily fail.
Always check higher timeframe trend alignment.
Overreacting to noise: On lower timeframes, small fluctuations can create false scouting signals.
Best Practices
Filter with trend: Only act on Scouting Phases that align with the dominant higher timeframe trend.
Watch volatility: In low-volatility conditions, false scouting triggers are more likely.
🔹 2. Lookout Phase (Early Momentum Alert)
Purpose:
The Lookout Phase signals an early alert that momentum is potentially strengthening in a given direction. It’s more meaningful than the Scouting Phase, but still considered a preliminary cue.
Triggers:
Upshift: FSO crosses above the HSO.
Downshift: FSO crosses below the HSO.
Why It Works:
The Lookout Phase is designed to identify moments when mid-term momentum (FSO) overtakes short-term momentum (HSO). Since the FSO is smoother and reacts more gradually, its crossover of the faster-reacting HSO can indicate a shift from short-lived fluctuations to a more sustained directional move.
This makes it a valuable early read on momentum transitions—especially when supported by higher-timeframe context.
Best Practices:
Always check the MTF Shift Table for higher-timeframe alignment before acting on a Lookout Phase signal.
Look for confluence with the Momentum Meter
Treat Lookout Phase entries as probing positions—small, exploratory trades that can be scaled into if follow-through develops.
Common Mistakes:
Treating Lookout Phase signals as a definitive trade trigger without context
Entering solely on a Lookout Phase crossover, without considering the MTF Shift Table or broader market structure, can result in chasing short-lived momentum bursts that fail to follow through.
Ignoring prevailing higher-timeframe momentum
Trading a Lookout Phase signal that is counter to the dominant trend or higher-timeframe bias increases the risk of whipsaws and false moves.
🔶 Summary
Kio IQ is an all-in-one trading indicator that combines momentum, trend strength, multi-timeframe analysis, divergences, pullbacks, and exhaustion alerts into a clear, structured view. It helps traders cut through market noise by showing whether a move is strong, weak, a trap, or simply part of a larger trend. With tools like the Full Shift Oscillator, Multi-Timeframe Shift Table, Shift Gates, and Rift Divergences, Kio IQ simplifies complex market behavior into easy-to-read signals. It’s designed to help traders spot early shifts, align with momentum, and recognize when trends are building or losing steam—all in one place.
Smarter Money Concepts - Wyckoff Springs & Upthrusts [PhenLabs]📊Smarter Money Concepts - Wyckoff Springs & Upthrusts
Version: PineScript™v6
📌Description
Discover institutional manipulation in real-time with this advanced Wyckoff indicator that detects Springs (accumulation phases) and Upthrusts (distribution phases). It identifies when price tests support or resistance on high volume, followed by a strong recovery, signaling potential reversals where smart money accumulates or distributes positions. This tool solves the common problem of missing these subtle phase transitions, helping traders anticipate trend changes and avoid traps in volatile markets.
By combining volume spike detection, ATR-normalized recovery strength, and a sigmoid probability model, it filters out weak signals and highlights only high-confidence setups. Whether you’re swing trading or day trading, this indicator provides clear visual cues to align with institutional flows, improving entry timing and risk management.
🚀Points of Innovation
Sigmoid-based probability threshold for signal filtering, ensuring only statistically significant Wyckoff patterns trigger alerts
ATR-normalized recovery measurement that adapts to market volatility, unlike static recovery checks in traditional indicators
Customizable volume spike multiplier to distinguish institutional volume from retail noise
Integrated dashboard legend with position and size options for personalized chart visualization
Hidden probability plots for advanced users to analyze underlying math without chart clutter
🔧Core Components
Support/Resistance Calculator: Scans a user-defined lookback period to establish dynamic levels for Spring and Upthrust detection
Volume Spike Detector: Compares current volume to a 10-period SMA, multiplied by a configurable factor to identify significant surges
Recovery Strength Analyzer: Uses ATR to measure price recovery after breaks, normalizing for different market conditions
Probability Model: Applies sigmoid function to combine volume and recovery data, generating a confidence score for each potential signal
🔥Key Features
Spring Detection: Spots accumulation when price dips below support but recovers strongly, helping traders enter longs at potential bottoms
Upthrust Detection: Identifies distribution when price spikes above resistance but falls back, alerting to possible short opportunities at tops
Customizable Inputs: Adjust lookback, volume multiplier, ATR period, and probability threshold to match your trading style and market
Visual Signals: Clear + (green) and - (red) labels on charts for instant recognition of accumulation and distribution phases
Alert System: Triggers notifications for signals and probability thresholds, keeping you informed without constant monitoring
🎨Visualization
Spring Signal: Green upward label (+) below the bar, indicating strong recovery after support break for accumulation
Upthrust Signal: Red downward label (-) above the bar, showing failed breakout above resistance for distribution
Dashboard Legend: Customizable table explaining signals, positioned anywhere on the chart for quick reference
📖Usage Guidelines
Core Settings
Support/Resistance Lookback
Default: 20
Range: 5-50
Description: Sets bars back for S/R levels; lower for recent sensitivity, higher for stable long-term zones – ideal for spotting Wyckoff phases
Volume Spike Multiplier
Default: 1.5
Range: 1.0-3.0
Description: Multiplies 10-period volume SMA; higher values filter to significant spikes, confirming institutional involvement in patterns
ATR for Recovery Measurement
Default: 5
Range: 2-20
Description: ATR period for recovery strength; shorter for volatile markets, longer for smoother analysis of post-break recoveries
Phase Transition Probability Threshold
Default: 0.9
Range: 0.5-0.99
Description: Minimum sigmoid probability for signals; higher for strict filtering, ensuring only high-confidence Wyckoff setups
Display Settings
Dashboard Position
Default: Top Right
Range: Various positions
Description: Places legend table on chart; choose based on layout to avoid overlapping price action
Dashboard Text Size
Default: Normal
Range: Auto to Huge
Description: Adjusts legend text; larger for visibility, smaller for minimal space use
✅Best Use Cases
Swing Trading: Identify Springs for long entries in downtrends turning to accumulation
Day Trading: Catch Upthrusts for short scalps during intraday distribution at resistance
Trend Reversal Confirmation: Use in conjunction with other indicators to validate phase shifts in ranging markets
Volatility Plays: Spot signals in high-volume environments like news events for quick reversals
⚠️Limitations
May produce false signals in low-volume or sideways markets where volume spikes are unreliable
Depends on historical data, so performance varies in unprecedented market conditions or gaps
Probability model is statistical, not predictive, and cannot account for external factors like news
💡What Makes This Unique
Probability-Driven Filtering: Sigmoid model combines multiple factors for superior signal quality over basic Wyckoff detectors
Adaptive Recovery: ATR normalization ensures reliability across assets and timeframes, unlike fixed-threshold tools
User-Centric Design: Tooltips, customizable dashboard, and alerts make it accessible yet powerful for all trader levels
🔬How It Works
Calculate S/R Levels:
Uses the highest high and the lowest low over the lookback period to set dynamic zones
Establishes baseline for detecting breaks in Wyckoff patterns
Detect Breaks and Recovery:
Checks for price breaking support/resistance, then recovering on volume
Measures recovery strength via ATR for volatility adjustment
Apply Probability Model:
Combines volume spike and recovery into a sigmoid function for confidence score
Triggers signal only if above threshold, plotting visuals and alerts
💡Note:
For optimal results, combine with price action analysis and test settings on historical charts. Remember, Wyckoff patterns are most effective in trending markets – use lower probability thresholds for practice, then increase for live trading to focus on high-quality setups.
Live Trading Metrics DashboardReal-Time Trading Data Table for Chart Analysis
This clean and professional dashboard displays essential trading metrics directly on your chart in an easy-to-read table format. Perfect for traders who need quick access to key volatility and momentum data without cluttering their chart with multiple indicators.
Key Metrics Displayed:
IBD Relative Strength (RS):
Professional Formula: Uses Investor's Business Daily methodology
Multi-Timeframe Analysis: Weighted calculation across 3, 6, 9, and 12-month periods
Performance Indicator: Shows how the instrument performs relative to its historical price action
Real-Time Updates: Values update with each bar for current market conditions
1.5 ATR (Average True Range):
Volatility Measurement: 14-period ATR multiplied by 1.5 for extended range analysis
Stop-Loss Placement: Ideal for setting dynamic stop-loss levels
Risk Management: Helps determine appropriate position sizing based on volatility
Breakout Targets: Useful for setting profit targets on breakout trades
1.5 ATR Percentage:
Relative Volatility: Shows 1.5 ATR as a percentage of current price
Cross-Asset Comparison: Enables volatility comparison across different instruments
Position Sizing: Helps calculate risk per trade as percentage of price
Market Context: Understand volatility relative to instrument value
How to Interpret:
Positive IBD RS: Instrument showing strength relative to historical performance
Negative IBD RS: Instrument showing weakness relative to historical performance
Higher ATR Values: Increased volatility, wider stops needed
Higher ATR %: Greater relative volatility for the instrument's price level
Perfect For:
Day traders needing quick volatility reference
Swing traders using IBD methodology
Position traders managing risk with ATR-based stops
Any trader wanting clean, organized data display
Average True Ranges with IBD RSAdvanced ATR Analysis with IBD Relative Strength
This comprehensive indicator combines Average True Range (ATR) analysis with IBD (Investor's Business Daily) Relative Strength calculation, providing both volatility measurement and momentum analysis in one powerful tool.
Key Features:
ATR Analysis:
Standard ATR: Customizable period (default 14) with multiple smoothing options
1.5x ATR: Extended range for wider stop-loss and target calculations
Smoothing Options: Choose between RMA, SMA, EMA, or WMA for ATR calculation
Customizable Colors: Distinct colors for easy visual identification
IBD Relative Strength:
Professional RS Formula: Uses the same calculation method as Investor's Business Daily
Multi-Timeframe Analysis: Compares current price to 3, 6, 9, and 12-month performance
Weighted Calculation: 40% weight on 3-month, 20% each on 6, 9, and 12-month performance
Zero-Based Scale: Values above 0 indicate outperformance, below 0 indicate underperformance
Trading Applications:
Volatility-Based Stops: Use ATR and 1.5x ATR for dynamic stop-loss placement
Position Sizing: ATR helps determine appropriate position size based on volatility
Relative Strength Analysis: IBD RS identifies stocks with superior momentum
Market Timing: High RS values often precede strong price moves
Risk Management: Combine volatility (ATR) with momentum (RS) for comprehensive analysis
Technical Details:
ATR Calculation: True Range smoothed over selected period with chosen method
IBD RS Formula: (40% × 3M) + (20% × 6M) + (20% × 9M) + (20% × 12M) - 100
Display: Separate pane indicator with customizable colors for each component
How to Interpret:
High ATR: Increased volatility, wider stops needed
Low ATR: Reduced volatility, tighter stops possible
Positive IBD RS: Stock outperforming market over measured periods
Negative IBD RS: Stock underperforming market over measured periods
Customizable Parameters:
ATR calculation length
Smoothing method for ATR
Individual colors for ATR, 1.5x ATR, and IBD RS lines
Perfect for swing traders and position traders who want to combine volatility analysis with relative strength momentum in their decision-making process. Particularly useful for stock selection and risk management.
Market Structure: HH/HL/LH/LL (v6, simple)What it does
Labels swing High/Low and classifies structure as HH / HL / LH / LL after confirmation.
Uses confirmed fractals (pivothigh/pivotlow) → no repaint after confirmation (there is a right-bar confirmation delay).
Optional swing connectors (lines), optional plain H/L when structure label is not applicable.
Plots last confirmed High/Low levels as reference.
Alerts when a new HH/HL/LH/LL is formed.
How it works
Swings are detected with ta.pivothigh() / ta.pivotlow() using user-defined left and right.
A pivot is confirmed only after right bars on the right—this is the only delay. Once confirmed, the label does not repaint.
Inputs
Left bars & Right bars – fractal sensitivity.
Connect swings with lines – draw lines between consecutive swings.
Show bullish (HH/HL) / Show bearish (LH/LL) – filter what to display.
Show plain H/L – draw H/L when classification is not HH/HL/LH/LL yet.
Recommended settings
1H–4H: left=2, right=2 (responsive).
1D+: left=3, right=3 (cleaner swing map).
Alerts provided
HH formed – new Higher High confirmed.
HL formed – new Higher Low confirmed.
LH formed – new Lower High confirmed.
LL formed – new Lower Low confirmed.
Use them to automate structure tracking or feed your strategy rules.
Tips
Trend up: a sequence of HH + HL; Trend down: LH + LL.
Combine with VWAP/EMA, liquidity zones, or volume/CVD to avoid chasing late signals.
The script is intentionally simple and lightweight; BOS/CHoCH can be added in a future update.
Limitations / Notes
Because the tool relies on confirmed pivots, signals are delayed by right bars.
This is not financial advice and not a buy/sell system on its own.
Changelog
v1.0 – Initial public release (Pine v6). Structure labels, swing connectors, last levels, and alert set.
Keywords
market structure, hh hl lh ll, swing, fractal, pivothigh, pivotlow, trend, structure labels, price action
Auto-Fit Growth Trendline# **Theoretical Algorithmic Principles of the Auto-Fit Growth Trendline (AFGT)**
## **🎯 What Does This Algorithm Do?**
The Auto-Fit Growth Trendline is an advanced technical analysis system that **automates the identification of long-term growth trends** and **projects future price levels** based on historical cyclical patterns.
### **Primary Functionality:**
- **Automatically detects** the most significant lows in regular periods (monthly, quarterly, semi-annually, annually)
- **Constructs a dynamic trendline** that connects these historical lows
- **Projects the trend into the future** with high mathematical precision
- **Generates Fibonacci bands** that act as dynamic support and resistance levels
- **Automatically adapts** to different timeframes and market conditions
### **Strategic Purpose:**
The algorithm is designed to identify **fundamental value zones** where price has historically found support, enabling traders to:
- Identify optimal entry points for long positions
- Establish realistic price targets based on mathematical projections
- Recognize dynamic support and resistance levels
- Anticipate long-term price movements
---
## **🧮 Core Mathematical Foundations**
### **Adaptive Temporal Segmentation Theory**
The algorithm is based on **dynamic temporal partition theory**, where time is divided into mathematically coherent uniform intervals. It uses modular transformations to create bijective mappings between continuous timestamps and discrete periods, ensuring each temporal point belongs uniquely to a specific period.
**What does this achieve?** It allows the algorithm to automatically identify natural market cycles (annual, quarterly, etc.) without manual intervention, adapting to the inherent periodicity of each asset.
The temporal mapping function implements a **discrete affine transformation** that normalizes different frequencies (monthly, quarterly, semi-annual, annual) to a space of unique identifiers, enabling consistent cross-temporal comparative analysis.
---
## **📊 Local Extrema Detection Theory**
### **Multi-Point Retrospective Validation Principle**
Local minima detection is founded on **relative extrema theory with sliding window**. Instead of using a simple minimum finder, it implements a cross-validation system that examines the persistence of the extremum across multiple historical periods.
**What problem does this solve?** It eliminates false minima caused by temporal volatility, identifying only those points that represent true historical support levels with statistical significance.
This approach is based on the **statistical confirmation principle**, where a minimum is only considered valid if it maintains its extremum condition during a defined observation period, significantly reducing false positives caused by transitory volatility.
---
## **🔬 Robust Interpolation Theory with Outlier Control**
### **Contextual Adaptive Interpolation Model**
The mathematical core uses **piecewise linear interpolation with adaptive outlier correction**. The key innovation lies in implementing a **contextual anomaly detector** that identifies not only absolute extreme values, but relative deviations to the local context.
**Why is this important?** Financial markets contain extreme events (crashes, bubbles) that can distort projections. This system identifies and appropriately weights them without completely eliminating them, preserving directional information while attenuating distortions.
### **Implicit Bayesian Smoothing Algorithm**
When an outlier is detected (deviation >300% of local average), the system applies a **simplified Kalman filter** that combines the current observation with a local trend estimation, using a weight factor that preserves directional information while attenuating extreme fluctuations.
---
## **📈 Stabilized Extrapolation Theory**
### **Exponential Growth Model with Dampening**
Extrapolation is based on a **modified exponential growth model with progressive dampening**. It uses multiple historical points to calculate local growth ratios, implements statistical filtering to eliminate outliers, and applies a dampening factor that increases with extrapolation distance.
**What advantage does this offer?** Long-term projections in finance tend to be exponentially unrealistic. This system maintains short-to-medium term accuracy while converging toward realistic long-term projections, avoiding the typical "exponential explosions" of other methods.
### **Asymptotic Convergence Principle**
For long-term projections, the algorithm implements **controlled asymptotic convergence**, where growth ratios gradually converge toward pre-established limits, avoiding unrealistic exponential projections while preserving short-to-medium term accuracy.
---
## **🌟 Dynamic Fibonacci Projection Theory**
### **Continuous Proportional Scaling Model**
Fibonacci bands are constructed through **uniform proportional scaling** of the base curve, where each level represents a linear transformation of the main curve by a constant factor derived from the Fibonacci sequence.
**What is its practical utility?** It provides dynamic resistance and support levels that move with the trend, offering price targets and profit-taking points that automatically adapt to market evolution.
### **Topological Preservation Principle**
The system maintains the **topological properties** of the base curve in all Fibonacci projections, ensuring that spatial and temporal relationships are consistently preserved across all resistance/support levels.
---
## **⚡ Adaptive Computational Optimization**
### **Multi-Scale Resolution Theory**
It implements **automatic multi-resolution analysis** where data granularity is dynamically adjusted according to the analysis timeframe. It uses the **adaptive Nyquist principle** to optimize the signal-to-noise ratio according to the temporal observation scale.
**Why is this necessary?** Different timeframes require different levels of detail. A 1-minute chart needs more granularity than a monthly one. This system automatically optimizes resolution for each case.
### **Adaptive Density Algorithm**
Calculation point density is optimized through **adaptive sampling theory**, where calculation frequency is adjusted according to local trend curvature and analysis timeframe, balancing visual precision with computational efficiency.
---
## **🛡️ Robustness and Fault Tolerance**
### **Graceful Degradation Theory**
The system implements **multi-level graceful degradation**, where under error conditions or insufficient data, the algorithm progressively falls back to simpler but reliable methods, maintaining basic functionality under any condition.
**What does this guarantee?** That the indicator functions consistently even with incomplete data, new symbols with limited history, or extreme market conditions.
### **State Consistency Principle**
It uses **mathematical invariants** to guarantee that the algorithm's internal state remains consistent between executions, implementing consistency checks that validate data structure integrity in each iteration.
---
## **🔍 Key Theoretical Innovations**
### **A. Contextual vs. Absolute Outlier Detection**
It revolutionizes traditional outlier detection by considering not only the absolute magnitude of deviations, but their relative significance within the local context of the time series.
**Practical impact:** It distinguishes between legitimate market movements and technical anomalies, preserving important events like breakouts while filtering noise.
### **B. Extrapolation with Weighted Historical Memory**
It implements a memory system that weights different historical periods according to their relevance for current prediction, creating projections more adaptable to market regime changes.
**Competitive advantage:** It automatically adapts to fundamental changes in asset dynamics without requiring manual recalibration.
### **C. Automatic Multi-Timeframe Adaptation**
It develops an automatic temporal resolution selection system that optimizes signal extraction according to the intrinsic characteristics of the analysis timeframe.
**Result:** A single indicator that functions optimally from 1-minute to monthly charts without manual adjustments.
### **D. Intelligent Asymptotic Convergence**
It introduces the concept of controlled asymptotic convergence in financial extrapolations, where long-term projections converge toward realistic limits based on historical fundamentals.
**Added value:** Mathematically sound long-term projections that avoid the unrealistic extremes typical of other extrapolation methods.
---
## **📊 Complexity and Scalability Theory**
### **Optimized Linear Complexity Model**
The algorithm maintains **linear computational complexity** O(n) in the number of historical data points, guaranteeing scalability for extensive time series analysis without performance degradation.
### **Temporal Locality Principle**
It implements **temporal locality**, where the most expensive operations are concentrated in the most relevant temporal regions (recent periods and near projections), optimizing computational resource usage.
---
## **🎯 Convergence and Stability**
### **Probabilistic Convergence Theory**
The system guarantees **probabilistic convergence** toward the real underlying trend, where projection accuracy increases with the amount of available historical data, following **law of large numbers** principles.
**Practical implication:** The more history an asset has, the more accurate the algorithm's projections will be.
### **Guaranteed Numerical Stability**
It implements **intrinsic numerical stability** through the use of robust floating-point arithmetic and validations that prevent overflow, underflow, and numerical error propagation.
**Result:** Reliable operation even with extreme-priced assets (from satoshis to thousand-dollar stocks).
---
## **💼 Comprehensive Practical Application**
**The algorithm functions as a "financial GPS"** that:
1. **Identifies where we've been** (significant historical lows)
2. **Determines where we are** (current position relative to the trend)
3. **Projects where we're going** (future trend with specific price levels)
4. **Provides alternative routes** (Fibonacci bands as alternative targets)
This theoretical framework represents an innovative synthesis of time series analysis, approximation theory, and computational optimization, specifically designed for long-term financial trend analysis with robust and mathematically grounded projections.
Market Outlook Score (MOS)Overview
The "Market Outlook Score (MOS)" is a custom technical indicator designed for TradingView, written in Pine Script version 6. It provides a quantitative assessment of market conditions by aggregating multiple factors, including trend strength across different timeframes, directional movement (via ADX), momentum (via RSI changes), volume dynamics, and volatility stability (via ATR). The MOS is calculated as a weighted score that ranges typically between -1 and +1 (though it can exceed these bounds in extreme conditions), where positive values suggest bullish (long) opportunities, negative values indicate bearish (short) setups, and values near zero imply neutral or indecisive markets.
This indicator is particularly useful for traders seeking a holistic "outlook" score to gauge potential entry points or market bias. It overlays on a separate pane (non-overlay mode) and visualizes the score through horizontal threshold lines and dynamic labels showing the numeric MOS value along with a simple trading decision ("Long", "Short", or "Neutral"). The script avoids using the plot function for compatibility reasons (e.g., potential TradingView bugs) and instead relies on hline for static lines and label.new for per-bar annotations.
Key features:
Multi-Timeframe Analysis: Incorporates slope data from 5-minute, 15-minute, and 30-minute charts to capture short-term trends.
Trend and Strength Integration: Uses ADX to weight trend bias, ensuring stronger signals in trending markets.
Momentum and Volume: Includes RSI momentum impulses and volume deviations for added confirmation.
Volatility Adjustment: Factors in ATR changes to assess market stability.
Customizable Inputs: Allows users to tweak periods for lookback, ADX, and ATR.
Decision Labels: Automatically classifies the MOS into actionable categories with visual labels.
This indicator is best suited for intraday or swing trading on volatile assets like stocks, forex, or cryptocurrencies. It does not generate buy/sell signals directly but can be combined with other tools (e.g., moving averages or oscillators) for comprehensive strategies.
Inputs
The script provides three user-configurable inputs via TradingView's input panel:
Lookback Period (lookback):
Type: Integer
Default: 20
Range: Minimum 10, Maximum 50
Purpose: Defines the number of bars used in slope calculations for trend analysis. A shorter lookback makes the indicator more sensitive to recent price action, while a longer one smooths out noise for longer-term trends.
ADX Period (adxPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Sets the smoothing period for the Average Directional Index (ADX) and its components (DI+ and DI-). Standard value is 14, but shorter periods increase responsiveness, and longer ones reduce false signals.
ATR Period (atrPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Determines the period for the Average True Range (ATR) calculation, which measures volatility. Adjust this to match your trading timeframe—shorter for scalping, longer for positional trading.
These inputs allow customization without editing the code, making the indicator adaptable to different market conditions or user preferences.
Core Calculations
The MOS is computed through a series of steps, blending trend, momentum, volume, and volatility metrics. Here's a breakdown:
Multi-Timeframe Slopes:
The script fetches data from higher timeframes (5m, 15m, 30m) using request.security.
Slope calculation: For each timeframe, it computes the linear regression slope of price over the lookback period using the formula:
textslope = correlation(close, bar_index, lookback) * stdev(close, lookback) / stdev(bar_index, lookback)
This measures the rate of price change, where positive slopes indicate uptrends and negative slopes indicate downtrends.
Variables: slope5m, slope15m, slope30m.
ATR (Average True Range):
Calculated using ta.atr(atrPeriod).
Represents average volatility over the specified period. Used later to derive volatility stability.
ADX (Average Directional Index):
A detailed, manual implementation (not using built-in ta.adx for customization):
Computes upward movement (upMove = high - high ) and downward movement (downMove = low - low).
Derives +DM (Plus Directional Movement) and -DM (Minus Directional Movement) by filtering non-relevant moves.
Smooths true range (trur = ta.rma(ta.tr(true), adxPeriod)).
Calculates +DI and -DI: plusDI = 100 * ta.rma(plusDM, adxPeriod) / trur, similarly for minusDI.
DX: dx = 100 * abs(plusDI - minusDI) / max(plusDI + minusDI, 0.0001).
ADX: adx = ta.rma(dx, adxPeriod).
ADX values above 25 typically indicate strong trends; here, it's normalized (divided by 50) to influence the trend bias.
Volume Delta (5m Timeframe):
Fetches 5m volume: volume_5m = request.security(syminfo.tickerid, "5", volume, lookahead=barmerge.lookahead_on).
Computes a 12-period SMA of volume: avgVolume = ta.sma(volume_5m, 12).
Delta: (volume_5m - avgVolume) / avgVolume (or 0 if avgVolume is zero).
This measures relative volume spikes, where positive deltas suggest increased interest (bullish) and negative suggest waning activity (bearish).
MOS Components and Final Calculation:
Trend Bias: Average of the three slopes, normalized by close price and scaled by 100, then weighted by ADX influence: (slope5m + slope15m + slope30m) / 3 / close * 100 * (adx / 50).
Emphasizes trends in strong ADX conditions.
Momentum Impulse: Change in 5m RSI(14) over 1 bar, divided by 50: ta.change(request.security(syminfo.tickerid, "5", ta.rsi(close, 14), lookahead=barmerge.lookahead_on), 1) / 50.
Captures short-term momentum shifts.
Volatility Clarity: 1 - ta.change(atr, 1) / max(atr, 0.0001).
Measures ATR stability; values near 1 indicate low volatility changes (clearer trends), while lower values suggest erratic markets.
MOS Formula: Weighted average:
textmos = (0.35 * trendBias + 0.25 * momentumImpulse + 0.2 * volumeDelta + 0.2 * volatilityClarity)
Weights prioritize trend (35%) and momentum (25%), with volume and volatility at 20% each. These can be adjusted in code for experimentation.
Trading Decision:
A variable mosDecision starts as "Neutral".
If mos > 0.15, set to "Long".
If mos < -0.15, set to "Short".
Thresholds (0.15 and -0.15) are hardcoded but can be modified.
Visualization and Outputs
Threshold Lines (using hline):
Long Threshold: Horizontal dashed green line at +0.15.
Short Threshold: Horizontal dashed red line at -0.15.
Neutral Line: Horizontal dashed gray line at 0.
These provide visual reference points for MOS interpretation.
Dynamic Labels (using label.new):
Placed at each bar's index and MOS value.
Text: Formatted MOS value (e.g., "0.2345") followed by a newline and the decision (e.g., "Long").
Style: Downward-pointing label with gray background and white text for readability.
This replaces a traditional plot line, showing exact values and decisions per bar without cluttering the chart.
The indicator appears in a separate pane below the main price chart, making it easy to monitor alongside price action.
Usage Instructions
Adding to TradingView:
Copy the script into TradingView's Pine Script editor.
Save and add to your chart via the "Indicators" menu.
Select a symbol and timeframe (e.g., 1-minute for intraday).
Interpretation:
Long Signal: MOS > 0.15 – Consider bullish positions if supported by other indicators.
Short Signal: MOS < -0.15 – Potential bearish setups.
Neutral: Between -0.15 and 0.15 – Avoid trades or wait for confirmation.
Watch for MOS crossings of thresholds for momentum shifts.
Combine with price patterns, support/resistance, or volume for better accuracy.
Limitations and Considerations:
Lookahead Bias: Uses barmerge.lookahead_on for multi-timeframe data, which may introduce minor forward-looking bias in backtesting (use with caution).
No Alerts Built-In: Add custom alerts via TradingView's alert system based on MOS conditions.
Performance: Tested for compatibility; may require adjustments for illiquid assets or extreme volatility.
Backtesting: Use TradingView's strategy tester to evaluate historical performance, but remember past results don't guarantee future outcomes.
Customization: Edit weights in the MOS formula or thresholds to fit your strategy.
This indicator distills complex market data into a single score, aiding decision-making while encouraging users to verify signals with additional analysis. If you need modifications, such as restoring plot functionality or adding features, provide details for further refinement.
VWAP For Loop [BackQuant]VWAP For Loop
What this tool does—in one sentence
A volume-weighted trend gauge that anchors VWAP to a calendar period (day/week/month/quarter/year) and then scores the persistence of that VWAP trend with a simple for-loop “breadth” count; the result is a clean, threshold-driven oscillator plus an optional VWAP overlay and alerts.
Plain-English overview
Instead of judging raw price alone, this indicator focuses on anchored VWAP —the market’s average price paid during your chosen institutional period. It then asks a simple question across a configurable set of lookback steps: “Is the current anchored VWAP higher than it was i bars ago—or lower?” Each “yes” adds +1, each “no” adds −1. Summing those answers creates a score that reflects how consistently the volume-weighted trend has been rising or falling. Extreme positive scores imply persistent, broad strength; deeply negative scores imply persistent weakness. Crossing predefined thresholds produces objective long/short events and color-coded context.
Under the hood
• Anchoring — VWAP using hlc3 × volume resets exactly when the selected period rolls:
Day → session change, Week → new week, Month → new month, Quarter/Year → calendar quarter/year.
• For-loop scoring — For lag steps i = , compare today’s VWAP to VWAP .
– If VWAP > VWAP , add +1.
– Else, add −1.
The final score ∈ , where N = (end − start + 1). With defaults (1→45), N = 45.
• Signal logic (stateful)
– Long when score > upper (e.g., > 40 with N = 45 → VWAP higher than ~89% of checked lags).
– Short on crossunder of lower (e.g., dropping below −10).
– A compact state variable ( out ) holds the current regime: +1 (long), −1 (short), otherwise unchanged. This “stickiness” avoids constant flipping between bars without sufficient evidence.
Why VWAP + a breadth score?
• VWAP aggregates both price and volume—where participants actually traded.
• The breadth-style count rewards consistency of the anchored trend, not one-off spikes.
• Thresholds give you binary structure when you need it (alerts, automation), without complex math.
What you’ll see on the chart
• Sub-pane oscillator — The for-loop score line, colored by regime (long/short/neutral).
• Main-pane VWAP (optional) — Even though the indicator runs off-chart, the anchored VWAP can be overlaid on price (toggle visibility and whether it inherits trend colors).
• Threshold guides — Horizontal lines for the long/short bands (toggle).
• Cosmetics — Optional candle painting and background shading by regime; adjustable line width and colors.
Input map (quick reference)
• VWAP Anchor Period — Day, Week, Month, Quarter, Year.
• Calculation Start/End — The for-loop lag window . With 1→45, you evaluate 45 comparisons.
• Long/Short Thresholds — Default upper=40, lower=−10 (asymmetric by design; see below).
• UI/Style — Show thresholds, paint candles, background color, line width, VWAP visibility and coloring, custom long/short colors.
Interpreting the score
• Near +N — Current anchored VWAP is above most historical VWAP checkpoints in the window → entrenched strength.
• Near −N — Current anchored VWAP is below most checkpoints → entrenched weakness.
• Between — Mixed, choppy, or transitioning regimes; use thresholds to avoid reacting to noise.
Why the asymmetric default thresholds?
• Long = score > upper (40) — Demands unusually broad upside persistence before declaring “long regime.”
• Short = crossunder lower (−10) — Triggers only on downward momentum events (a fresh breach), not merely being below −10. This combination tends to:
– Capture sustained uptrends only when they’re very strong.
– Flag downside turns as they occur, rather than waiting for an extreme negative breadth.
Tuning guide
Choose an anchor that matches your horizon
– Intraday scalps : Day anchor on intraday charts.
– Swing/position : Month or Quarter anchor on 1h/4h/D charts to capture institutional cycles.
Pick the for-loop window
– Larger N (bigger end) = stronger evidence requirement, smoother oscillator.
– Smaller N = faster, more reactive score.
Set achievable thresholds
– Ensure upper ≤ N and lower ≥ −N ; if N=30, an upper of 40 can never trigger.
– Symmetric setups (e.g., +20/−20) are fine if you want balanced behavior.
Match visuals to intent
– Enabling VWAP coloring lets you see regime directly on price.
– Background shading is useful for discretionary reading; turn it off for cleaner automation displays.
Playbook examples
• Trend confirmation with disciplined entries — On Month anchor, N=45, upper=38–42: when the long regime engages, use pullbacks toward anchored VWAP on the main pane for entries, with stops just beyond VWAP or a recent swing.
• Downside transition detection — Keep lower around −8…−12 and watch for crossunders; combine with price losing anchored VWAP to validate risk-off.
• Intraday bias filter — Day anchor on a 5–15m chart, N=20–30, upper ~ 16–20, lower ~ −6…−10. Only take longs while score is positive and above a midline you define (e.g., 0), and shorts only after a genuine crossunder.
Behavior around resets (important)
Anchored VWAP is hard-reset each period. Immediately after a reset, the series can be young and comparisons to pre-reset values may span two periods. If you prefer within-period evaluation only, choose end small enough not to bridge typical period length on your timeframe, or accept that the breadth test intentionally spans regimes.
Alerts included
• VWAP FL Long — Fires when the long condition is true (score > upper and not in short).
• VWAP FL Short — Fires on crossunder of the lower threshold (event-driven).
Messages include {{ticker}} and {{interval}} placeholders for routing.
Strengths
• Simple, transparent math — Easy to reason about and validate.
• Volume-aware by construction — Decisions reference VWAP, not just price.
• Robust to single-bar noise — Needs many lags to agree before flipping state (by design, via thresholds and the stateful output).
Limitations & cautions
• Threshold feasibility — If N < upper or |lower| > N, signals will never trigger; always cross-check N.
• Path dependence — The state variable persists until a new event; if you want frequent re-evaluation, lower thresholds or reduce N.
• Regime changes — Calendar resets can produce early ambiguity; expect a few bars for the breadth to mature.
• VWAP sensitivity to volume spikes — Large prints can tilt VWAP abruptly; that behavior is intentional in VWAP-based logic.
Suggested starting profiles
• Intraday trend bias : Anchor=Day, N=25 (1→25), upper=18–20, lower=−8, paint candles ON.
• Swing bias : Anchor=Month, N=45 (1→45), upper=38–42, lower=−10, VWAP coloring ON, background OFF.
• Balanced reactivity : Anchor=Week, N=30 (1→30), upper=20–22, lower=−10…−12, symmetric if desired.
Implementation notes
• The indicator runs in a separate pane (oscillator), but VWAP itself is drawn on price using forced overlay so you can see interactions (touches, reclaim/loss).
• HLC3 is used for VWAP price; that’s a common choice to dampen wick noise while still reflecting intrabar range.
• For-loop cap is kept modest (≤50) for performance and clarity.
How to use this responsibly
Treat the oscillator as a bias and persistence meter . Combine it with your entry framework (structure breaks, liquidity zones, higher-timeframe context) and risk controls. The design emphasizes clarity over complexity—its edge is in how strictly it demands agreement before declaring a regime, not in predicting specific turns.
Summary
VWAP For Loop distills the question “How broadly is the anchored, volume-weighted trend advancing or retreating?” into a single, thresholded score you can read at a glance, alert on, and color through your chart. With careful anchoring and thresholds sized to your window length, it becomes a pragmatic bias filter for both systematic and discretionary workflows.
Range Percent Histogram📌 Range Percent Histogram – Indicator Description
The Range Percent Histogram is a custom indicator that behaves like a traditional volume histogram, but instead of showing traded volume it displays the percentage range of each candle.
In other words, the height of each bar represents how much the price moved (in percentage terms) within that candle, from its low to its high.
🔧 What it shows
The indicator has two main components:
Component Description
Histogram Bars Columns plotted in red or green depending on the candle direction (green = bullish candle, red = bearish). The height of each bar = (high - low) / low * 100. That means a candle that moved, for example, 1 % from its lowest point to its highest point will show a bar with 1 % height.
Moving Average (optional) A 20-period Simple Moving Average applied directly to the bar values. It can be turned ON/OFF via a checkbox and helps you detect whether current range activity is above or below the average range of the past candles.
⚙️ How it works
Every time a new candle closes, the indicator calculates its range and converts it into a percentage.
This value is drawn as a column under the chart.
If the closing price is above the opening price → the bar is green (bullish range).
If the closing price is below the opening price → the bar is red (bearish range).
When the Show Moving Average option is enabled, a smooth line is plotted on top of the histogram representing the average percentage range of the last 20 candles.
📈 How to use it
This indicator is very helpful for detecting moments of range expansion or contraction.
One powerful way to use it is similar to a volume exhaustion / low-volume pattern:
Situation Interpretation
Consecutive bars with very low height Price is in a period of low volatility → possible accumulation or "pause" phase.
A sudden large bar after a series of small ones Indicates a strong pickup in volatility → often marks the start of a new impulse in the direction of the breakout.
Trading Macro Windows by BW v2
Trading Macros by BW: Integrating ICT Concepts for Session Analysis
This indicator combines two key Inner Circle Trader (ICT) concepts—Change in State of Delivery (CISD) or Inverted Fair Value Gap (IFVG) signals with Macro Time Windows—to provide a unified tool for analyzing intraday price action, particularly during Pacific Time (PT) sessions. Rather than simply merging existing scripts, this integration creates a cohesive visual framework that highlights how macro consolidation periods interact with potential reversal or continuation signals like CISD or IFVG. By overlaying macro candle styling and borders on the chart alongside selectable signal lines, traders can better contextualize setups within ICT's macro narrative, where price often manipulates liquidity during these windows before displacing toward higher-timeframe objectives.
Core Components and How They Work Together:
Macro Time Windows (Inspired by ICT's Macro Periods):
ICT emphasizes "macro" as 30-minute windows (e.g., 06:45–07:15 PT, 07:45–08:15 PT, up to 11:45–12:15 PT) where price tends to consolidate, sweep liquidity, or form key structures like Fair Value Gaps (FVGs). These periods set the stage for the session's directional bias.
The indicator styles candles within these windows using a user-defined color for wicks, borders, and bodies (translucent for visibility). This visual emphasis helps traders focus on activity inside macros, where reversals or continuations often originate.
Borders are drawn as vertical lines at the start and end of each window (with a +5 minute buffer to capture related activity), using a dotted style by default. This creates a "study zone" that encapsulates macro events, allowing traders to assess if price is respecting or violating these zones in alignment with broader ICT models like the Power of 3 (AMD cycle).
Toggle: "Macro Candles Enabled" (default: true) – Turn off to disable styling and borders if focusing solely on signals.
CISD or IFVG Signals (Selectable Mode):
Mode Selection: Choose between "Change in the State of Delivery" (CISD) or "IFVG" (default: IFVG). Both detect shifts in market delivery during specific 30-minute slices (15–45 or 17–45 minutes past the hour in PT sessions).
CISD Mode: Based on ICT's definition of a sudden directional shift, this identifies aggressive displacements after sweeping recent highs/lows. It uses a rolling reference high/low over 6 bars, checks for sweeps (penetrating by at least 2 ticks in the last 2-3 bars), reclamation (closing beyond the reference with at least 50% body), and displacement (50% of prior range or an immediate FVG of 6+ ticks). Signals plot a horizontal line from the close, extending 24 bars right, labeled "CISD."
IFVG Mode: Focuses on Inverted Fair Value Gaps, where a bullish FVG (low > high by 13+ ticks) forms but is inverted (closed below) in the same slice, signaling bearish intent (or vice versa). This targets violations against opposing liquidity, often leading to raids on external ranges. Signals plot similarly, labeled "IFVG."
Shared Logic: Both modes enforce a 55-bar cooldown to prevent clustering, operate only during PT sessions (06:30–13:00), and use tick-based thresholds for precision across instruments. The integration with macros allows traders to see if signals occur within or at the edges of macro windows, enhancing confirmation—for example, a CISD inside a macro might indicate a manipulated reversal toward the session's true objective.
Toggle: "Signals Enabled" (default: true) – Turn off to hide all signal lines and labels, isolating the macro visualization.
How Components Interact:
Macro windows provide the "narrative context" (consolidation/manipulation), while CISD/IFVG signals detect the "delivery shift" (displacement). Together, they form a mashup that justifies publication: isolated signals can be noisy, but when filtered by macro periods, they align with ICT's session model. For instance, an IFVG inversion during a macro might confirm a liquidity sweep before targeting PD arrays or order blocks.
No external dependencies; all calculations are self-contained using Pine's built-in functions like ta.highest/lowest for references and time-based sessions for windows.
Usage Guidelines:
Apply to intraday charts (e.g., 1-5 min) or stocks during PT hours.
Look for confluence: A bull IFVG signal post-macro low sweep might target the next macro high or daily bias.
Customize colors/styles for signals (solid/dashed/dotted lines) and macros to suit your chart.
Backtest in replay mode to observe how macros frame signals—e.g., price often respects macro borders as S/R.
Limitations: Timezone-fixed to PT (America/Los_Angeles); signals are directional hints, not trade entries. Combine with ICT tools like order blocks or liquidity pools for full setups.
This script draws from community ICT implementations but refines them into a single, purpose-built tool for macro-driven trading, reducing chart clutter while emphasizing interconnected concepts. Feedback welcome!
Bills Advanced Market Sessions V5Bill007 Advanced Enhanced Market Sessions & Table V5 is a TradingView Pine Script indicator that
visualizes major stock market sessions and data for (Tokyo, London, New York, Sydney, Frankfurt) on charts.
**Purpose and Logic:**
- Visual Displays include session boxes, open/close/average lines, labels for session
names/metrics (ticks, avg price, volume), and trend labels (UP/Down/Neutral with % change)
and a Debug table.
- Uses custom types (SessionDisplay, SessionInfo) and methods to create/update sessions
dynamically, handling multi-part sessions (e.g., Tokyo breaks).
- Batch updates sessions for efficiency, checks timezones, weekdays, and daily changes to avoid
duplicates.
- Includes tables for session times/status/countdowns and debug metrics (tick range, average
price, volume, trend %, open, close).
- Supports 25 timezones for accurate global session timing.
- All labels have dynamaic tooltips that provide extra outputs which saves chart clutter
- Realtime lastbar session updates for current session
**Settings:**
- Select Market Sessions to suit
- Toggles for lines, ranges, averages, volumes, labels, boxes, weekends.
- Customizable colors, timezones, session times, thresholds for neutral trends, label offsets to
move labels around for clearer visuals.
- Table position/timezone, debug options.
- Timezone select to update Session times open close according to what time zone you're in
**Benefits:**
- Enhanced session data at a glance
- Enhances multi-market awareness, highlights session overlaps, trends, and key metrics.
- Aids timing entries/exits, volume analysis, reduces clutter with toggles.
- Supports global trading strategies with accurate timezone handling and visuals.
Daily Seasonality Strength + Prediction TableDaily Seasonality Strength + Prediction Table
Return Estimates:
This indicator uses historical price data to calculate average returns for each day (of the week or month) and uses these to predict the next day’s return.
Seasonality Strength:
It measures seasonality strength by comparing predicted returns with actual returns, using the inverse of MSE (higher values mean stronger seasonality).
supports up to 10 assets
This script is for informational and educational purposes only. It does not constitute financial, investment, or trading advice. I am not a financial advisor. Any decisions you make based on this indicator are your own responsibility. Always do your own research and consult with a qualified financial professional before making any investment decisions.
Past performance is no guarantee of future results. The value of the instruments may fluctuate and is not guaranteed
Z Distance from VWAP Enhanced (ZVWAP)The "Z Distance from VWAP Enhanced" (ZVWAP) indicator is a comprehensive oscillator that provides deep insights into market dynamics. It calculates a Z-score, which tells you how many standard deviations the current price is away from the VWAP. This normalization makes it a consistent and reliable tool for identifying market extremes.
The indicator comes packed with features, including:
Customizable Overbought & Oversold Zones
Built-in Bullish & Bearish Divergence Detection
Automatic Trendline Plotting
A Moving Exponential Average (MEA) for crossover signals
Fully customizable alerts for every key event.
How to Use It - The BTC Dominance Strategy for Altcoins
As shown in the screenshot, this indicator is an exceptional tool for trading altcoins by analyzing the BTC Dominance (BTC.D) chart. The relationship is typically inverse:
When ZVWAP on BTC.D is RISING (or Overbought) ➔ It's BEARISH for Altcoins.
This means Bitcoin is gaining dominance, and capital is flowing out of altcoins and into Bitcoin. This is a time to be cautious with or short altcoins.
When ZVWAP on BTC.D is FALLING (or Oversold) ➔ It's BULLISH for Altcoins.
This means Bitcoin is losing dominance, and capital is flowing into altcoins, often starting an "altcoin season." This is a great time to look for long entries on your favorite altcoins.
Key Signals on the BTC.D Chart:
Zone Entries: When ZVWAP enters the red (Overbought) zone, prepare for altcoins to weaken. When it enters the blue (Oversold) zone, look for altcoin strength.
MEA Crossover: A crossover of the yellow ZVWAP line below the cyan MEA line is a strong confirmation that dominance is falling and the trend is becoming bullish for altcoins.
Divergences: A bearish divergence on the BTC.D chart can be an early warning that dominance is about to fall, signaling a potential bullish move for altcoins.
Key Features Explained
Overbought / Oversold Zones: The red and blue shaded areas clearly define when an asset is statistically over-extended. These are prime areas to look for mean reversion or trend exhaustion.
Divergence Detection: The script automatically detects and plots divergences between price and the ZVWAP.
• Bullish Divergence: Price makes a lower low, but ZVWAP makes a higher low. (Potential buy signal).
• Bearish Divergence: Price makes a higher high, but ZVWAP makes a lower high. (Potential sell signal).
The Reference Lines (+1 / -1): These gray lines represent one standard deviation from the VWAP. They act as an early warning system. When the ZVWAP crosses these lines, it shows that momentum is building, and the price is starting to deviate significantly from its average.
Automatic Trendlines: The indicator can automatically draw and manage trendlines based on recent pivots in the ZVWAP, helping you visualize the current momentum and potential breakout points. This feature can be turned off if you prefer a cleaner chart.
Customization and Alerts
The indicator is fully customizable. You can adjust the lengths, zone levels, and visual settings to fit your trading style. Most importantly, it includes a comprehensive set of alerts:
Enter Overbought Zone
Enter Oversold Zone
Bullish Divergence Detected
Bearish Divergence Detected
Enter Any Zone (OB/OS) - a single alert for either condition.
Any Divergence (Bull/Bear) - a single alert for any divergence.
This allows you to stay informed of every important signal without having to watch the charts all day.
i.imgur.com
Possible Deviations | Session Fibs📌 Session Fibs with Confluence Detection
This script automatically plots custom Fibonacci extensions from key market sessions and candles, giving you a structured view of intraday levels that matter:
Asia Session (20:00–00:00 NY time)
→ Marks the session high/low, draws fib projections, and shades the range.
London 4:00 AM (1H) Candle
→ Captures the 1-hour “last leg” move into London and projects fib levels.
New York Open Key Candles
→ 8:30 AM and 9:30 AM (5-minute) candles with fib projections.
⚡ Features
Custom fib set (0, 0.5, ±0.618, ±2.0, ±2.25, ±2.5, ±3.0, ±3.25, ±3.5, ±4.0, ±4.25, ±4.5, 4.618).
Adjustable line extension mode (none, right N bars, infinite right).
Toggleable labels & text color, with placement options (on line / left of line).
Asia session box highlight for visual clarity.
Confluence detection: automatically checks for overlapping fib levels between
Asia ↔ London (same day)
Today ↔ Previous day (optional)
→ Highlights overlaps with dashed lines + labels (e.g., LON -3.25 ≈ ASIA -2.25).
🎯 Use Case
Designed for traders who track session ranges and liquidity sweeps, this tool makes it easy to spot:
Intraday fib alignment between Asia and London.
Key NYO candles in relation to overnight ranges.
High-probability confluence zones for entries/exits.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
Fractal Circles#### FRACTAL CIRCLES ####
I combined 2 of my best indicators Fractal Waves (Simplified) and Circles.
Combining the Fractal and Gann levels makes for a very simple trading strategy.
Core Functionality
Gann Circle Levels: This indicator plots mathematical support and resistance levels based on Gann theory, including 360/2, 360/3, and doubly strong levels. The system automatically adjusts to any price range using an intelligent multiplier system, making it suitable for forex, stocks, crypto, or any market.
Fractal Wave Analysis: Integrates real-time trend analysis from both current and higher timeframes. Shows the current price range boundaries (high/low) and trend direction through dynamic lines and background fills, helping traders understand market structure.
Key Trading Benefits
Active Level Detection: The closest Gann level to current price is automatically highlighted in green with increased line thickness. This eliminates guesswork about which level is most likely to act as immediate support or resistance.
Real-Time Price Tracking: A customizable line follows current price with an offset to the right, projecting where price sits relative to upcoming levels. A gradient-filled box visualizes the exact distance between current price and the active Gann level.
Multi-Timeframe Context: View fractal waves from higher timeframes while maintaining current timeframe precision. This helps identify whether short-term moves align with or contradict longer-term structure.
Smart Alert System: Comprehensive alerts trigger when price crosses any Gann level, with options to monitor all levels or focus only on the active level. Reduces the need for constant chart monitoring while ensuring you never miss significant level breaks.
Practical Trading Applications
Entry Timing: Use active level highlighting to identify the most probable support/resistance for entries. The real-time distance box helps gauge risk/reward before entering positions.
Risk Management: Set stops based on Gann level breaks, particularly doubly strong levels which tend to be more significant. The gradient visualization makes it easy to see how much room price has before hitting key levels.
Trend Confirmation: Fractal waves provide immediate context about whether current price action aligns with broader market structure. Bullish/bearish background fills offer quick visual confirmation of trend direction.
Multi-Asset Analysis: The auto-scaling multiplier system works across all markets and timeframes, making it valuable for traders who monitor multiple instruments with vastly different price ranges.
Confluence Trading: Combine Gann levels with fractal wave boundaries to identify high-probability setups where multiple technical factors align.
This tool is particularly valuable for traders who appreciate mathematical precision in their technical analysis while maintaining the flexibility to adapt to real-time market conditions.
Multi-Band Trend LineThis Pine Script creates a versatile technical indicator called "Multi-Band Trend Line" that builds upon the concept of the popular "Follow Line Indicator" by Dreadblitz. While the original Follow Line Indicator uses simple trend detection to place a line at High or Low levels, this enhanced version combines multiple band-based trading strategies with dynamic trend line generation. The indicator supports five different band types and provides more sophisticated buy/sell signals based on price breakouts from various technical analysis bands.
Key Features
Multi-Band Support
The indicator supports five different band types:
- Bollinger Bands: Uses standard deviation to create bands around a moving average
- Keltner Channels: Uses ATR (Average True Range) to create bands around a moving average
- Donchian Channels: Uses the highest high and lowest low over a specified period
- Moving Average Envelopes: Creates bands as a percentage above and below a moving average
- ATR Bands: Uses ATR multiplier to create bands around a moving average
Dynamic Trend Line Generation (Enhanced Follow Line Concept)
- Similar to the Follow Line Indicator, the trend line is placed at High or Low levels based on trend direction
- Key Enhancement: Instead of simple trend detection, this version uses band breakouts to trigger trend changes
- When price breaks above the upper band (bullish signal), the trend line is set to the low (optionally adjusted with ATR) - similar to Follow Line's low placement
- When price breaks below the lower band (bearish signal), the trend line is set to the high (optionally adjusted with ATR) - similar to Follow Line's high placement
- The trend line acts as dynamic support/resistance, following the price action more precisely than the original Follow Line
ATR Filter (Follow Line Enhancement)
- Like the original Follow Line Indicator, an ATR filter can be selected to place the line at a more distance level than the normal mode settled at candles Highs/Lows
- When enabled, it adds/subtracts ATR value to provide more conservative trend line placement
- Helps reduce false signals in volatile markets
- This feature maintains the core philosophy of the Follow Line while adding more precision through band-based triggers
Signal Generation
- Buy Signal: Generated when trend changes from bearish to bullish (trend line starts rising)
- Sell Signal: Generated when trend changes from bullish to bearish (trend line starts falling)
- Signals are displayed as labels on the chart
Visual Elements
- Upper and lower bands are plotted in gray
- Trend line changes color based on direction (green for bullish, red for bearish)
- Background color changes based on trend direction
- Buy/sell signals are marked with labeled shapes
How It Works
Band Calculation: Based on the selected band type, upper and lower boundaries are calculated
Signal Detection: When price closes above the upper band or below the lower band, a breakout signal is generated
Trend Line Update: The trend line is updated based on the breakout direction and previous trend line value
Trend Direction: Determined by comparing current trend line with the previous value
Alert Generation: Buy/sell conditions trigger alerts and visual signals
Use Cases
Enhanced trend following strategies: More precise than basic Follow Line due to band-based triggers
Breakout trading: Multiple band types provide various breakout opportunities
Dynamic support/resistance identification: Combines Follow Line concept with band analysis
Multi-timeframe analysis with different band types: Choose the most suitable band for your timeframe
Reduced false signals: Band confirmation provides better entry/exit points compared to simple trend following
CHoCH Reversal Hunter🔥 CHoCH Reversal Hunter — Detect Bearish CHoCH Patterns & Fibonacci Golden Zone For Precision Reversal Setups
📈 Overview
CHoCH Reversal Hunter is a Pine Script™ indicator for structured bearish market analysis.
It combines major/minor pivot detection, Change of Character (CHoCH) filtering, and logarithmic Fibonacci retracements into one framework.
The goal: identify Small LL → CHoCH → Golden Zone setups with higher precision.
🧠 Core Logic
1. 📊 Market Structure Backbone
Tracks the 4 most recent major highs (H0–H3) and 3 major lows.
These pivots form the basis for trend evaluation.
2. 🔻 Bearish Background Conditions
A bearish market context is confirmed when:
// Bearish Background Condition
isBearish = (High 3 < High 2) and (
(High 2 > High 1 and High 2 < High 0) or
(High 2 <= High 1)
)
// Reset to neutral if High 2 < High 3
This ensures that only a true lower-high structure activates the bearish framework.
3. 🎯 Hunt for Small Lower Low (LL)
Monitors minor pivot lows with a smaller lookback period.
A valid Small LL must break below the third major low (Low 2).
This Small LL becomes the 0% Fibonacci anchor.
4. 🔄 Change of Character (CHoCH) Selection
The indicator scans recent bars for three possible CHoCH patterns:
// CHoCH Type Definitions in CHoCH Hunter
// Inside → current bar inside previous bar
isInsideBar = high < high and low > low
// Smarty → short-term reversal clue
isSmartyBar = low > low and low < low
// Pivot → minor swing high (small swing detection)
isSmallPivotHigh = ta.pivothigh(high, small_swing_period, small_swing_period)
Filter rules for validity:
CHoCH must occur before the Small LL bar.
Its high must be greater than the Small LL bar’s high (dominance criterion).
5. ⚡ Confirmation & Fibonacci Activation
Once price crosses above the selected CHoCH → setup confirmed.
Fibonacci retracements (logarithmic scale) are calculated:
100% → current high (dynamic, updates before breach).
65% → Golden Zone upper boundary.
50% → Golden Zone lower boundary.
0% → Small LL anchor.
6. 📈 Dynamic Management & Reset Rules
Before 50% breach → Fibo High auto-updates with new highs.
After breach → Levels freeze.
Setup resets if:
Price drops below Small LL.
Price breaks beyond frozen levels.
New Small LL formation detected.
✨ Key Features
📍 Automatic detection of major & minor pivots.
🔍 Clear definitions for Inside, Smarty, Pivot CHoCHs.
📐 Logarithmic Fibonacci retracements for exponential markets.
🎯 Golden Zone highlighting (50%–65%).
🔄 Built-in reset logic to invalidate weak setups.
🎨 Visualization
Pivot markers for Major (📕) & Minor (📘) swings.
Labels for CHoCH points with type (“Inside”, “Smarty”, “Pivot”).
Golden Zone highlighted between 50%–65%.
Optional structure labels for clarity.
⚙️ Inputs & Customization
Major Structure Period (default: 4) — sensitivity for big swings.
Minor Structure Period (default: 2) — sensitivity for small swings.
Toggle display of pivots, structure labels, and Golden Zone.
📚 Educational Value
CHoCH Reversal Hunter is designed to help traders learn:
How bearish structures are objectively defined.
Different CHoCH types and how to filter them.
Applying Fibonacci retracements in structured setups.
⚠️ Risk Disclaimer
🚨 This indicator is for educational purposes only and does not constitute financial advice.
Trading involves significant risk — always backtest and apply sound risk management.
🆕 Release Notes v1.0
Bearish structure detection logic added.
CHoCH type classification (Inside, Smarty, Pivot).
Logarithmic Fibonacci retracement with Golden Zone.
Automatic reset & invalidation rules.
💡 Pro Tip: Watch for the sequence Bearish Background → Small LL → CHoCH → Golden Zone — this is the core hunting pattern of CHoCH Reversal Hunter.
Session Volume Profile (DeadCat)Volume Profile is a charting study that displays trading activity over specific time periods at various price levels. It appears as a horizontal histogram on the chart, revealing where traders have shown the most interest based on volume concentration.
This Volume Profile automatically anchors to user-selected timeframes, creating fresh volume analysis for each new period while maintaining clean, systematic visualization of price-volume relationships.
Core Components :
Point of Control (POC): The price level with the highest volume activity during the selected period, marked with a yellow line and left-side label.
Value Area High/Low (VAH/VAL): Price boundaries that contain a specified percentage of the total volume (default 40%), helping identify the main trading range where most activity occurred.
Volume Histogram: Left-aligned bars showing volume distribution across price levels, with value area highlighting for enhanced visual clarity.
Key Features :
- Automatic Period Detection: Supports hourly, daily, weekly, and monthly timeframe anchoring
- Customizable Granularity: Adjustable rows (10-500) for different price resolution needs
- Labels: Clear POC, VAH, and VAL identification positioned at profile start
- Toggle Controls**: Optional display for volume rows, key levels, and background fills
- Clean Visualization: Profiles reset automatically at each new period for current market focus
Display Options :
- Profile Rows: Show/hide the volume histogram bars
- Key Level Lines: Individual controls for POC, VAH, and VAL display
- Value Area Background: Optional shading between VAH and VAL levels
- Color Customization: Separate color controls for all visual elements
The indicator provides systematic volume analysis by creating fresh profiles at regular intervals, helping traders identify significant price levels and volume patterns within their preferred timeframe structure.
Disclaimer : This indicator is for educational and informational purposes only. Trading decisions should be based on comprehensive analysis and proper risk management. Past performance does not guarantee future results.
TrendMaster Pro with Dynamic ATROverview
TrendMaster Pro with Dynamic ATR is a comprehensive trend-following indicator designed for traders seeking to identify entry and exit points in trending markets while incorporating volatility-based risk management. Built on a multi-timeframe Exponential Moving Average (EMA) system, it combines short-term momentum signals with long-term trend filters, enhanced by a Volatility-Adjusted Moving Average (VMA) for confirmation and Average True Range (ATR) for adaptive stop-loss and take-profit levels.
This indicator overlays directly on your chart, providing visual cues for buy/sell signals, dynamic stops/targets, and optional EMA lines. It's ideal for swing trading, day trading, or scalping across various assets like stocks, forex, cryptocurrencies, and commodities. The system emphasizes trend alignment to reduce false signals, with customizable options for trailing mechanisms and filters to suit different market conditions.
Key benefits:
Multi-Timeframe Analysis: Incorporates higher timeframe EMAs for robust trend detection without needing to switch charts.
Volatility Adaptation: Uses ATR for dynamic positioning of stops and targets, helping manage risk in volatile environments.
Flexible Customization: Toggles for displaying EMAs, using trailing stops/targets, and applying VMA filters for entries/exits.
Alert Integration: Built-in alerts for entries, exits, stop breaches, and target hits to automate notifications.
Core Components
The indicator revolves around four EMAs, a VMA, and ATR calculations:
Exponential Moving Averages (EMAs):
Fast EMA (Default: 12 periods): Captures short-term momentum and quick price changes.
Slow EMA (Default: 27 periods): Identifies medium-term trends, providing a smoother view than the Fast EMA.
Stop EMA (Default: 48 periods on 15-minute timeframe): Acts as dynamic support/resistance for risk management and exit signals.
Trend EMA (Default: 288 periods on 5-minute timeframe): Serves as a long-term trend filter to ensure trades align with the overall market direction.
Volatility-Adjusted Moving Average (VMA):
A dynamic moving average that adjusts its sensitivity based on market volatility (using a Directional Movement Index-inspired calculation).
Length: Default 6 periods.
Colored green (uptrend), red (downtrend), or blue (neutral/sideways).
Optionally filters entries and exits to confirm trend direction.
Average True Range (ATR):
Measures volatility over a specified period (Default: 14).
Used to set adaptive stop-loss and take-profit levels.
Multipliers allow customization: Stop (Default: 1.5x ATR), Fixed Target (Default: 3.0x ATR), Trailing Target (Default: 2.0x ATR).
Supports trailing options for stops (based on highest/lowest since entry) and targets (ratcheting with price movement).
Signal Generation
Entry Signals
Buy (Long) Signal: Triggered when the price is above the Trend EMA (bullish alignment) and one of the following occurs:
Price crosses above the Trend EMA.
Price crosses above the Fast EMA, with Fast EMA > Slow EMA > Trend EMA.
Price crosses above the Slow EMA, with Fast EMA > Slow EMA > Trend EMA.
Filtered optionally by VMA being green (uptrend confirmation).
Visual: Green "BUY" label below the bar.
Sell (Short) Signal: Triggered when the price is below the Trend EMA (bearish alignment) and one of the following occurs:
Price crosses below the Trend EMA.
Price crosses below the Fast EMA, with Fast EMA < Slow EMA < Trend EMA.
Price crosses below the Slow EMA, with Fast EMA < Slow EMA < Trend EMA.
Filtered optionally by VMA being red (downtrend confirmation).
Visual: Red "SELL" label above the bar.
Exit Signals
Exit Long: Occurs when the position is active and:
Price crosses below the Stop EMA, or
Price hits the ATR stop-loss (fixed or trailing), or
Price reaches the ATR take-profit (fixed or trailing).
Filtered optionally by VMA > Stop EMA and VMA red (downtrend shift).
Visual: Green "E" label (exit) or "TP" label (if target hit).
Exit Short: Occurs when the position is active and:
Price crosses above the Stop EMA, or
Price hits the ATR stop-loss (fixed or trailing), or
Price reaches the ATR take-profit (fixed or trailing).
Filtered optionally by VMA < Stop EMA and VMA green (uptrend shift).
Visual: Red "E" label (exit) or "TP" label (if target hit).
The indicator tracks only one active position at a time (long or short), resetting on exit. Trailing stops update based on the highest high (long) or lowest low (short) since entry.
Visual Elements
How to Use ?
Setup: Add to your chart and adjust inputs based on your timeframe (e.g., shorter lengths for intraday, longer for swings).
Trading Strategy:
Enter on "BUY" or "SELL" labels when aligned with your broader analysis.
Monitor ATR lines for risk/reward: Aim for targets at least 2x stop distance.
Use trailing options in trending markets to lock in profits; fixed in ranging ones.
Combine with volume or other indicators for confirmation.
Risk Management: Always respect ATR stops to limit losses. Position size based on stop distance (e.g., 1-2% account risk).
Backtesting: Test on historical data to optimize parameters for your asset.
Alerts: Set up notifications for signals via TradingView's alert system. Examples:
"BUY signal triggered"
"EXIT long trade"
"Long ATR target reached on close"
Notes and Limitations
This is not financial advice; use at your own risk and combine with personal analysis.
Performance varies by market conditions—best in trending environments; may whipsaw in sideways markets.
Multi-timeframe requests may cause slight repainting on live charts due to higher TF data.
No repainting on closed bars, but ensure your chart timeframe is compatible with input TFs.
Licensed under Mozilla Public License 2.0. For questions or feedback, contact @MudraMiner.
This indicator empowers traders with a balanced, adaptive system—happy trading! 🚀
AI Fib Strategy (Full Trade Plan)This indicator automatically plots Fibonacci retracements and a Golden Zone box (61.8%–65% retracement) based on the 4H candle body high/low.
Features:
Auto-detects session breaks or daily breaks (configurable).
Draws standard Fib retracement levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%).
Highlights the Golden Zone for high-probability trade entries.
Optional Take Profit extensions (TP1, TP2, TP3).
Fully compatible with Pine Script v6.
Usage:
Best applied on intraday charts (15m, 30m, 1H).
Use the Golden Zone for entry confirmations.
Combine with candlestick patterns, order blocks, or volume for stronger signals.
Price Action Key Level Break & Retest — Instant ReversalThis script identifies high-confidence support and resistance levels using pivot points and multi-step retest confirmation. It helps traders detect reliable breakout and reversal zones using price action.
How It Works:
1. The script scans for pivot highs and lows on the chart to identify potential key levels.
2. Each level is monitored for multiple retests (configurable by the user). The more a level is tested and holds, the stronger it becomes.
3. When price interacts with a key level:
o A Support signal occurs if the level acts as support after multiple retests.
o A Resistance signal occurs if the level acts as resistance after multiple retests.
o If a signal fails (price breaks the level), an opposite signal is automatically placed at the breach point.
4. Optional volume filter validates the strength of moves, reducing false signals.
5. Horizontal Line Visualization: Support and Resistance signals are represented by drawing manually horizontal lines, which remain on the chart regardless of scrolling, zooming, or candle compression and helps traders to identify the breakout of key levels
Example:
• Suppose a stock forms a pivot low at ₹1,000.
• Price retraces and touches ₹1,000 two to three times, holding each time — the level is confirmed as strong support.
• The script places a buy line at ₹1,000.
• If price breaks below ₹1,000 after holding it for multiple retests, the script automatically generates a Resistance Signal at the breach point, signaling a potential trend reversal.
• That Resistance Signal act as Resistance level throughout. if such Resistance level breaks out above, it act as Support level and vice versa
• This allows traders to react adaptively, entering trades based on confirmed support or resistance while managing risk.
Why It’s Useful:
• Focuses on multi-retest confirmation rather than single touch points, reducing false signals.
• To draw horizontal lines on key levels, providing clear visualization of key levels without clutter.
• Integrates adaptive breach signals, so traders can respond when levels fail.
• Suitable for swing, intraday, and trend-following strategies.
How to Use:
1. Apply the script to any timeframe.
2. Configure pivot detection length and maximum retests to match trading style.
3. Enable the optional volume filter for stronger signal validation.
4. Monitor the horizontal lines for Support/Resistance signals and opposite signals at breaches.
5. Combine with other technical analysis if desired.
Concepts Behind the Script:
• Pivot-based support and resistance
• Multi-retest validation for stronger levels
• Adaptive opposite signals for failed levels
• Volume-based confirmation for reliability
• Horizontal line visualization for easy tracking
Key Features:
Horizontal Lines visualization: Support and Resistance levels remain on the chart permanently, providing constant visual reference.
Multi-Timeframe Compatible: Can be applied on any timeframe; lines and breach logic adjust automatically.
Optional Noise Filters: Volume and retest filters improve signal reliability.
Why It’s Worth Paying:
• Uses multi-retest confirmation to reduce false signals compared to standard support/resistance scripts.
• Provides adaptive opposite signals for failed levels — giving traders an actionable edge.
• Visualizes key levels as fixed horizontal lines, helping traders track trends clearly.
• Works across multiple timeframes — suitable for intraday, swing, or trend-following strategies.
How to Request Access:
This script is invite-only on TradingView. To get access:
1. DM me on TradingView with your username.
2. Access is granted individually to ensure proper use and avoid unauthorized sharing.
3. Once approved, you can apply the script to your charts immediately and benefit from high-confidence level detection.
Disclaimer:
Trading involves risk. Signals are based on historical price action and should be used alongside other technical analysis and risk management strategies.
Past performance does not guarantee future results. This is an analytical tool; it does not provide investment advice.
