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.
Statistics
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
USDT ETH Printer Days [AlexKo]This indicator highlights the days when USDT was minted or redeemed on Ethereum network (based on TronScan API data).
Vertical dotted lines show printer events.
Labels display the amount (Mint in teal, Redeem in red).
You can filter by minimum size, type (mint/redeem), and adjust label position.
Optional EMA line at the bottom shows cumulative “printer pressure”.
Alerts can be set when an event occurs.
Simple NASDAQ TrackerNasdaq Tracker, is an indicator to use while trading nasdaq stocks.
It uses the chart as a market tracker too know what the overall blue chip market is doing, if it trades above the moving average, it indicates the the overall market is going upp or down.
ICT Midnight PDH PDLPara marcar rango Midnight to Midnight (NYMO).
También para marcar rangos horarios que tu quieras.
5EMA Touch/Break EMA Touch/Break Monitor (5 Lines) — Overview
Purpose: Track downside touches and breakdowns against key EMAs (default 20/60/100/200/300) to judge pullbacks and risk control.
Direction considered: From above to below only. Upside touches/breakouts are not counted.
Signals:
Downside Touch (T): Previous bar at/above EMA, current low ≤ EMA → draw an upward triangle below the bar in the EMA’s color.
Downside Break (B): Previous bar at/above EMA, current low ≤ EMA × (1 − threshold) (default 2%) → draw a gold downward triangle above the bar.
Priority: If both occur on the same bar, Break overrides Touch.
First-only: Within a continuous run, only the first bar is marked; condition must clear before re-marking.
Scope: Signals are produced only for EMAs with length ≥ 60 (adjustable).
Display: The status line shows EMA prices only; a top-right table shows EMA name / price / color.
Inputs: Adjustable EMA lengths; break threshold (default 2%); optional date filter (default 2024-02-14 → 2025-12-30).
Alerts: Global first-only alerts for downside touch/break, plus per-EMA alerts.
用途:跟踪价格对关键 EMA(默认 20/60/100/200/300)的下行触及与下破,便于回踩/风控判断。
仅计算方向:从上向下。向上的触及/突破不计。
信号含义:
下触及(T):上一根在 EMA 上方,本根 低点 ≤ EMA → K线下方画与该 EMA 同色向上三角形。
下破位(B):上一根在 EMA 上方,本根 低点 ≤ EMA × (1 − 阈值)(默认 2%) → K线上方画金色向下三角形。
优先级:同根同时满足时,破位优先于触及。
首次原则:连续区间内只标第一根;需先离开条件,才会再次标记。
范围限制:仅对 长度 ≥60 的 EMA 标记信号(阈值可改)。
显示:状态行只显示 5 条 EMA 的价格;右上角表格展示每条 EMA 的名称/价格/颜色。
参数:EMA 长度可改;破位阈值默认 2%;可启用日期过滤(默认 2024-02-14 → 2025-12-30)。
提醒:提供“向下触及/向下破位(首次)”总提醒与每条 EMA 独立提醒。
NQ Stats Mean ReversionBased off of Multi-timeframe support by keypoems, modified to be anchored on a HTF and added a dynamic label to give current SD level with chance of reversion
Chaos Theory : public release
What is Chaos Theory?
Chaos theory is the study of complex systems that appear random but actually follow deterministic mathematical laws. Discovered by meteorologist Edward Lorenz in the 1960s, it revealed that seemingly chaotic behavior often hides precise mathematical patterns.
Key Concepts:
The Butterfly Effect
The famous principle that tiny changes in initial conditions can lead to vastly different outcomes. In markets, this means a small price movement at a critical juncture can cascade into major trend changes. Named after Lorenz's discovery that a butterfly flapping its wings in Brazil could theoretically cause a tornado in Texas.
Sensitive Dependence on Initial Conditions
Chaotic systems are extremely sensitive to their starting state. While we cannot predict exact long-term outcomes, we can identify probability zones where the system is likely to evolve. This is why weather forecasts work for days, not months - and why our indicator predicts price destinations, not timing.
Strange Attractors
In chaos theory, systems tend to evolve toward certain states called attractors. Price doesn't move randomly - it's drawn toward these mathematical attractors that we identify as probability zones.
Fractals and Self-Similarity
Chaotic systems display similar patterns at different scales. This is why price charts look similar whether viewing 1-minute or daily timeframes - the same mathematical forces operate across all time scales.
Deterministic Chaos
The paradox at the heart of chaos theory: systems that are completely deterministic (following precise mathematical rules) can produce behavior that appears random. Markets aren't random - they're chaotic, which means they're predictable within probability bounds.
Why This Matters for Trading
Traditional technical analysis assumes markets are either random (efficient market hypothesis) or follow simple patterns (support/resistance). Chaos theory reveals a third truth: markets are complex dynamical systems that follow mathematical laws we can model and predict - not with certainty, but with probability.
This is the foundation of our indicator: applying the same mathematics that predicts weather patterns and planetary orbits to identify where price is mathematically likely to travel next.
🌟 Welcome to the World of Chaos Theory
We hope to provide our clients with a program that will define future points to which we believe price will expand to, based on a given probability % of one event occurring rather than another. In this case, the other event = price not expanding to our predicted area and reaching an invalidation state. This entire theory and the work done assumes that price behaves like a complex dynamical system that is highly sensitive to initial conditions.
🔮 Predictive vs. Reactive Systems
Pay special attention to the language used. Our belief is that we can provide you a tool that is predictive, not reactive - the latter of which falls into the class of descriptive systems. Although the term of price action study is referred to as time-series forecasting, most if not all of the works done under this umbrella do not forecast anything. They only describe the current or recent past state of affairs using averages, volume, volatility, and other concepts.
📊 Understanding Probability-Based Prediction
A predictive system conjured from the world of chaos theory is not a final solution to the mystery of price. In reality, we only can give you probabilities of where price may end up - this would be a point in space, not time, which we believe would be more likely than another, depending on the analysis of the initial conditions.
To make the point of the last paragraph crystal clear: while we can tell you, with respect to the probabilities, where price will end up in terms of a price point, we don't know WHEN. That is another part of the mystery that perhaps only clairvoyance can hope to uncover.
📈 Performance Statistics
For the question of what the probabilities are, meaning the success of the follow through of price, the answer is given in a stats panel, which measures the success of promises made by the indicator - that price would reach a certain point before being invalidated by moving too far in the opposing direction. It's not helpful to advertise or make false claims, therefore one should take advantage that we offer a free version, and using a pre-defined lookback window, confirm the probability calculations and determine the follow through rate with respect to the specific symbol and timeframe that the user decides to use.
⚠️ What This Is Not
What this is not → Descriptive. We have zero interest in describing what price is doing. In fact, the entire industry of price forecasting is dedicated to this task, therefore you can rest assured that any coincidence with an RSI or any type of moving average etc. is simply that - coincidence. We do not use any known pre-made indicators or formulas.
It has been our belief that price has an underlying mathematical pattern that can be predicted within probability bounds. If you read that carefully, we are predicting the pattern, not looking to find and describe some sort of underlying structure.
🧩 Understanding Market Complexity
It should be understood that price is a complex system, even if our initial assessment of the conditions are correct. We have to remember that price is a fractal structure - there are always different initial conditions clashing, as well as forming. This is without taking into account the manipulation of the system, as well as external intervention in the natural progression of the system by news or other significant events.
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📋 To Summarize:
🔬 1. Chaos Theory Application to Markets
- Novel Concept: Treating price as a chaotic particle rather than random movement
- What This Means: Chaotic systems have underlying mathematical patterns that can be predicted within probability bounds
- Your Benefit: Access to predictive mathematics previously used only in physics and meteorology
🧮 2. Complex Systems Mathematics
- Novel Concept: Applying non-linear dynamical systems theory to financial markets
- What This Means: Markets behave like complex adaptive systems with emergent properties
- Your Benefit: Understanding market behavior at a fundamental mathematical level
🎯 3. Probability Field Mapping
- Novel Concept: Creating mathematical probability fields for future price locations
- What This Means: Each zone represents a calculated probability destination, not arbitrary support/resistance
- Your Benefit: Trade toward mathematically-derived targets instead of guessing
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💡 Why This is Fundamentally Different from All Other Indicators
📉 Traditional Indicators:
- Use historical price data to create lagging signals
- Based on statistical averages and linear mathematics
- Assume markets are random or follow simple patterns
- React to what already happened
🚀 This Chaos Theory Approach:
- Uses mathematical modeling to predict future probability zones
- Based on non-linear complex systems mathematics
- Treats markets as chaotic but predictable systems
- Proactively identifies where price is likely to go
No Curve Fitting: Unlike indicators optimized for specific timeframes or instruments, chaos theory principles are universal mathematical laws that apply consistently across all markets.
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🎁 Concrete Benefits You Receive
💫 1. Predictive Intelligence
- Know probable price destinations before they're reached
- Eliminate guesswork in setting profit targets
- Make informed decisions about trade direction
🎯 2. Mathematical Precision
- Every zone placement has mathematical justification
- No subjective interpretation required
- Consistent application across all market conditions
🌍 3. Universal Market Application
- Works identically on forex, stocks, crypto, commodities
- No need to adjust parameters for different instruments
- Mathematical principles transcend market types
🏆 4. Professional-Grade Analysis
- Access to institutional-level mathematical modeling
- Same complexity as quantitative hedge fund systems
- Simplified visual output for practical trading
✅ 5. Real-Time Performance Validation
- Built-in statistics track actual prediction accuracy
- Transparent performance measurement
- Data-driven confidence in signal quality
🛡️ 6. Risk Management Precision
- Mathematically-defined probable targets of desired and undesired price locations
- Systematic approach eliminates emotional decisions
⏱️ 7. Multi-Timeframe Consistency
- Zones maintain mathematical validity across timeframes
- Higher timeframe bias with lower timeframe precision
- Coherent analysis from scalping to position trading
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🌟 Novel Trading Advantages
Probability-Based Targeting: Instead of hoping price reaches your target, you're trading toward mathematically-calculated probability zones.
Chaos Pattern Recognition: Probability-based predictions of the underlying chaotic patterns that govern price movement gives you an edge other traders don't possess.
Dynamic Adaptation: Unlike static indicators, this system continuously recalculates based on evolving market mathematics.
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🔄 Why This Represents a Trading Evolution
From Reactive to Predictive: Traditional analysis tells you what happened. Chaos theory mathematics tells you what's likely to happen.
From Subjective to Objective: No more debating support and resistance levels. Mathematics determines probable price destinations.
From Curve-Fitted to Universal: Based on fundamental mathematical principles that work consistently across all markets and timeframes.
From Emotional to Systematic: Clear mathematical signals eliminate the psychological challenges that destroy most traders.
This indicator doesn't just give you another way to analyze markets - it gives you access to an entirely different mathematical framework for understanding price behavior. You're not getting a variation of existing concepts; you're getting a completely novel approach based on advanced mathematical principles that treat markets as the complex systems they actually are.
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📚 How to Use the Indicator
🎨 Zone Mechanics
• Orange Zones: Target areas for price expansion
• Activation Trigger: Price must close outside any zone (full candle body, not just wicks)
• Primary Rule: Price travels to the next zone before closing back behind the originating zone border
🔴 Understanding the Red Dots
• Red dots on chart: Represent areas where we had valid zone sets available for trading
• Empty spaces indicate: Areas where price closed past the highest/lowest zone or where zone invalidation occurred
• Important note: We cannot always identify zones. Simply wait or switch timeframe/symbol
Session Volatility MonitorOverview
Session Volatility Monitor is a versatile volatility indicator tailored for intraday and session-based trading. It computes the average maximum price deviation (either up or down) from the session's opening price over a user-specified number of prior days, providing insights into expected "room to move" in the current session. This helps traders gauge potential exhaustion points, set realistic targets or stops, and identify when a directional move has reached historical norms (flagged as "REACHED" with the exact price level).
Displayed via a customisable table and optional horizontal target lines, it's ideal for markets like forex, crypto, futures, or stocks where session volatility matters. The indicator supports custom sessions with timezone adjustments, making it adaptable to global trading hours (e.g., London, NY, or Asia kill zones). For assets with small tick sizes (e.g., forex pairs at 0.0001), a multiplier scales values for readability (e.g., showing pips as 67.0 instead of 0.00670).
Key Features
Session-Based Calculations:
Defines sessions via presets (e.g., "NY Kill Zone: 07:00-10:00") or custom HHMM-HHMM inputs. (please note that preset sessions are mainly for futures e.g. "Full Day18:01-17:00", but also can be useful for forex and crypto)
Adjustable UTC offset (e.g., -5 for ET) to align with your asset's timezone—ensures accurate detection regardless of TradingView's UTC internal clock.
Tracks the max one-sided move (high - open or open - low) per session, averaging over 1–N previous days (default: 14).
Table Display:
Avg Max Move: Historical average deviation, labeled with days averaged and session time.
Current Move: Real-time displacement from session open (positive for up, negative for down).
Room to Go Up/Down: Remaining distance to reach the average, updating live; appends "REACHED (price)" if hit during the session.
Customisable: Text color, font size (tiny to huge), position (e.g., bottom_left), and value scaling via multiplier/decimal places.
Target Lines:
Optional horizontal lines at "Up Target" (open + avg move) and "Down Target" (open - avg move).
Lines start at the session open bar and extend only through the session duration (e.g., stops at 12:00 for a 07:00-12:00 session)—no further projection post-session.
Fully customisable: Toggle on/off, color, style (solid/dotted/dashed), width, label text/background.
Display Adjustments for Forex/Crypto:
Multiplier: Scales raw values (e.g., set to 10000 for EURUSD to show pips like 45.0 instead of 0.0045).
Decimals: Controls precision (0–5 places) for table values.
How to Use
Add to Chart: Search for "Session Volatility Monitor" in TradingView's indicators and apply to your symbol (e.g., EURUSD for forex, NQ1! for futures, BTCUSD for crypto).
Configure Settings:
Select a session preset or custom range; adjust UTC offset if needed (e.g., +0 for UTC symbols like crypto).
Set "Number of Previous Days to Average" (e.g., 14 for a two-week look back).
For small-tick assets, set Multiplier (e.g., 100 for crypto points, 10000 for forex pips) and Decimals (e.g., 0 for whole numbers).
Customise table position/size/color and target lines for visibility.
Interpret Outputs:
Monitor the table for "room to go"—if Room Up is low/negative, upside might be limited; "REACHED" signals a potential reversal or exhaustion.
Use target lines as visual S/R levels; they auto-start at session open and halt at close.
Combine with price action, volume, or other indicators for entries (e.g., buy near down target if bullish bias).
Example Scenario:
Forex (GBPUSD, 1-min): Set session to "London Kill Zone: 02:00-05:00" (UTC+0), multiplier=10000. Table shows pips; lines mark expected highs/lows.
Limitations and Tips
Historical Data Limits: Averages are capped by TradingView's bar history (e.g., ~14 days on 1-min for free plans). Upgrade for deeper look backs or use higher timeframes.
Session Accuracy: Ensure UTC offset matches your chart—test with the "In Session" plot (enable in Style tab, zoom y-axis if columns are tiny).
No Alerts/Signals: Purely informational; add custom alerts via TradingView for "REACHED" conditions.
Performance: On very low timeframes with long sessions, lines might consume line limits (max ~50)—toggle off if needed.
Tips: For crypto/forex, experiment with multiplier to match your preferred units (e.g., points vs. decimals). Hide debug plot in Style tab for clean charts. If "REACHED" doesn't trigger, verify on historical data where moves exceed averages.
This tool draws from concepts like Average Daily Range but focuses on directional, session-specific volatility for precise intraday decision-making. Feedback welcome!
Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Always consult a professional before trading.
Cheat CodeWhy Monday & Friday
Monday evening (NY): frequently seeds the weekly expansion. Its DR/IDR often acts as a weekly “starter envelope,” useful for breakout continuation or fade back into the box plays as liquidity builds.
Friday evening (NY): often exposes end-of-week traps (run on stops into the close) and sets expectation boundaries into the following week. Carry these levels forward to catch Monday’s reaction to Friday’s closing structure.
Typical use-cases
Breakout & retest:
Price closes outside the Monday DR/IDR → look for retests of the band edge for continuation.
Liquidity sweep (“trap”) recognition:
Friday session wicks briefly beyond Friday DR/IDR then closes back inside → watch for mean reversion early next week.
Bias filter:
Above both Monday DR midline and Friday DR midline → bias long until proven otherwise; the inverse for shorts.
Session open confluence:
Reactions at the open line frequently mark decision points for momentum vs. fade setups.
(This is a levels framework, not a signals engine. Combine with your execution model: orderflow, S/R, session timing, or higher-TF bias.)
Inputs & styling (quick reference)
Display toggles (per day):
Show DR / IDR / Middle DR / Middle IDR
Show Opening Line
Show DR/IDR Box (choose DR or IDR as box source)
Show Price Labels
Style controls (per day):
Line width (1–4), style (Solid/Dashed/Dotted)
Independent colors for DR, IDR, midlines, open line
Box background opacity
Timezone:
Default America/New_York (changeable).
Optional on-chart warning if your chart TZ differs.
Practical notes
Works on intraday charts; levels are anchored using weekly timestamps for accuracy on any symbol.
Live updating: During the Mon/Fri calc windows, DR/IDR highs/lows and midlines keep updating until the session ends.
Clean drawings: Lines, box, and labels are created once per session and then extended/updated—efficient on resources even with long display windows.
Max elements: Script reserves ample line/box/label capacity for stability across weeks.
Pips Promedio - PersonalizableMuestra el promedio de pips de los ultimos 50 dias los ultimos 20 dias y lo que se ha movido en el dia en curso, es personalizable segun tu necesidad.
It shows the average pips for the last 50 days, the last 20 days, and the movement of the current day. It is customizable according to your needs.
Session Highs and LowsThis indicator plots the following:
- Previous day high and low (based on previous daily candle) - purple lines
- Asian high and low (1800-0200) - red lines
- London high and low (0300-0930) - blue lines
During NY session, once one of these point of interest has been hit or passed, the line thickness reduces so you can tell at a glance which points have been taken, but they still remain on the chart for reference.
Correlation Heatmap Matrix [TradingFinder] 20 Assets Variable🔵 Introduction
Correlation is one of the most important statistical and analytical metrics in financial markets, data mining, and data science. It measures the strength and direction of the relationship between two variables.
The correlation coefficient always ranges between +1 and -1 : a perfect positive correlation (+1) means that two assets or currency pairs move together in the same direction and at a constant ratio, a correlation of zero (0) indicates no clear linear relationship, and a perfect negative correlation (-1) means they move in exactly opposite directions.
While the Pearson Correlation Coefficient is the most common method for calculation, other statistical methods like Spearman and Kendall are also used depending on the context.
In financial market analysis, correlation is a key tool for Forex, the Stock Market, and the Cryptocurrency Market because it allows traders to assess the price relationship between currency pairs, stocks, or coins. For example, in Forex, EUR/USD and GBP/USD often have a high positive correlation; in stocks, companies from the same sector such as Apple and Microsoft tend to move similarly; and in crypto, most altcoins show a strong positive correlation with Bitcoin.
Using a Correlation Heatmap in these markets visually displays the strength and direction of these relationships, helping traders make more accurate decisions for risk management and strategy optimization.
🟣 Correlation in Financial Markets
In finance, correlation refers to measuring how closely two assets move together over time. These assets can be stocks, currency pairs, commodities, indices, or cryptocurrencies. The main goal of correlation analysis in trading is to understand these movement patterns and use them for risk management, trend forecasting, and developing trading strategies.
🟣 Correlation Heatmap
A correlation heatmap is a visual tool that presents the correlation between multiple assets in a color-coded table. Each cell shows the correlation coefficient between two assets, with colors indicating its strength and direction. Warm colors (such as red or orange) represent strong negative correlation, cool colors (such as blue or cyan) represent strong positive correlation, and mid-range tones (such as yellow or green) indicate correlations that are close to neutral.
🟣 Practical Applications in Markets
Forex : Identify currency pairs that move together or in opposite directions, avoid overexposure to similar trades, and spot unusual divergences.
Crypto : Examine the dependency of altcoins on Bitcoin and find independent movers for portfolio diversification.
Stocks : Detect relationships between stocks in the same industry or find outliers that move differently from their sector.
🟣 Key Uses of Correlation in Trading
Risk management and diversification: Select assets with low or negative correlation to reduce portfolio volatility.
Avoiding overexposure: Prevent opening multiple positions on highly correlated assets.
Pairs trading: Exploit temporary deviations between historically correlated assets for arbitrage opportunities.
Intermarket analysis: Study the relationships between different markets like stocks, currencies, commodities, and bonds.
Divergence detection: Spot when two typically correlated assets move apart as a possible trend change signal.
Market forecasting: Use correlated asset movements to anticipate others’ behavior.
Event reaction analysis: Evaluate how groups of assets respond to economic or political events.
❗ Important Note
It’s important to note that correlation does not imply causation — it only reflects co-movement between assets. Correlation is also dynamic and can change over time, which is why analyzing it across multiple timeframes provides a more accurate picture. Combining correlation heatmaps with other analytical tools can significantly improve the precision of trading decisions.
🔵 How to Use
The Correlation Heatmap Matrix indicator is designed to analyze and manage the relationships between multiple assets at once. After adding the tool to your chart, start by selecting the assets you want to compare (up to 20).
Then, choose the Correlation Period that fits your trading strategy. Shorter periods (e.g., 20 bars) are more sensitive to recent price movements, making them suitable for short-term trading, while longer periods (e.g., 100 or 200 bars) provide a broader view of correlation trends over time.
The indicator outputs a color-coded matrix where each cell represents the correlation between two assets. Warm colors like red and orange signal strong negative correlation, while cool colors like blue and cyan indicate strong positive correlation. Mid-range tones such as yellow or green suggest correlations that are close to neutral. This visual representation makes it easy to spot market patterns at a glance.
One of the most valuable uses of this tool is in portfolio risk management. Portfolios with highly correlated assets are more vulnerable to market swings. By using the heatmap, traders can find assets with low or negative correlation to reduce overall risk.
Another key benefit is preventing overexposure. For example, if EUR/USD and GBP/USD have a high positive correlation, opening trades on both is almost like doubling the position size on one asset, increasing risk unnecessarily. The heatmap makes such relationships clear, helping you avoid them.
The indicator is also useful for pairs trading, where a trader identifies assets that are usually correlated but have temporarily diverged — a potential arbitrage or mean-reversion opportunity.
Additionally, the tool supports intermarket analysis, allowing traders to see how movements in one market (e.g., crude oil) may impact others (e.g., the Canadian dollar). Divergence detection is another advantage: if two typically aligned assets suddenly move in opposite directions, it could signal a major trend shift or a news-driven move.
Overall, the Correlation Heatmap Matrix is not just an analytical indicator but also a fast, visual alert system for monitoring multiple markets at once. This is particularly valuable for traders in fast-moving environments like Forex and crypto.
🔵 Settings
🟣 Logic
Correlation Period : Number of bars used to calculate correlation between assets.
🟣 Display
Table on Chart : Enable/disable displaying the heatmap directly on the chart.
Table Size : Choose the table size (from very small to very large).
Table Position : Set the table location on the chart (top, middle, or bottom in various alignments).
🟣 Symbol Custom
Select Market : Choose the market type (Forex, Stocks, Crypto, or Custom).
Symbol 1 to Symbol 20: In custom mode, you can define up to 20 assets for correlation calculation.
🔵 Conclusion
The Correlation Heatmap Matrix is a powerful tool for analyzing correlations across multiple assets in Forex, crypto, and stock markets. By displaying a color-coded table, it visually conveys both the strength and direction of correlations — warm colors for strong negative correlation, cool colors for strong positive correlation, and mid-range tones such as yellow or green for near-zero or neutral correlation.
This helps traders select assets with low or negative correlation for diversification, avoid overexposure to similar trades, identify arbitrage and pairs trading opportunities, and detect unusual divergences between typically aligned assets. With support for custom mode and up to 20 symbols, it offers high flexibility for different trading strategies, making it a valuable complement to technical analysis and risk management.
Seasonality Monte Carlo Forecaster [BackQuant]Seasonality Monte Carlo Forecaster
Plain-English overview
This tool projects a cone of plausible future prices by combining two ideas that traders already use intuitively: seasonality and uncertainty. It watches how your market typically behaves around this calendar date, turns that seasonal tendency into a small daily “drift,” then runs many randomized price paths forward to estimate where price could land tomorrow, next week, or a month from now. The result is a probability cone with a clear expected path, plus optional overlays that show how past years tended to move from this point on the calendar. It is a planning tool, not a crystal ball: the goal is to quantify ranges and odds so you can size, place stops, set targets, and time entries with more realism.
What Monte Carlo is and why quants rely on it
• Definition . Monte Carlo simulation is a way to answer “what might happen next?” when there is randomness in the system. Instead of producing a single forecast, it generates thousands of alternate futures by repeatedly sampling random shocks and adding them to a model of how prices evolve.
• Why it is used . Markets are noisy. A single point forecast hides risk. Monte Carlo gives a distribution of outcomes so you can reason in probabilities: the median path, the 68% band, the 95% band, tail risks, and the chance of hitting a specific level within a horizon.
• Core strengths in quant finance .
– Path-dependent questions : “What is the probability we touch a stop before a target?” “What is the expected drawdown on the way to my objective?”
– Pricing and risk : Useful for path-dependent options, Value-at-Risk (VaR), expected shortfall (CVaR), stress paths, and scenario analysis when closed-form formulas are unrealistic.
– Planning under uncertainty : Portfolio construction and rebalancing rules can be tested against a cloud of plausible futures rather than a single guess.
• Why it fits trading workflows . It turns gut feel like “seasonality is supportive here” into quantitative ranges: “median path suggests +X% with a 68% band of ±Y%; stop at Z has only ~16% odds of being tagged in N days.”
How this indicator builds its probability cone
1) Seasonal pattern discovery
The script builds two day-of-year maps as new data arrives:
• A return map where each calendar day stores an exponentially smoothed average of that day’s log return (yesterday→today). The smoothing (90% old, 10% new) behaves like an EWMA, letting older seasons matter while adapting to new information.
• A volatility map that tracks the typical absolute return for the same calendar day.
It calculates the day-of-year carefully (with leap-year adjustment) and indexes into a 365-slot seasonal array so “March 18” is compared with past March 18ths. This becomes the seasonal bias that gently nudges simulations up or down on each forecast day.
2) Choice of randomness engine
You can pick how the future shocks are generated:
• Daily mode uses a Gaussian draw with the seasonal bias as the mean and a volatility that comes from realized returns, scaled down to avoid over-fitting. It relies on the Box–Muller transform internally to turn two uniform random numbers into one normal shock.
• Weekly mode uses bootstrap sampling from the seasonal return history (resampling actual historical daily drifts and then blending in a fraction of the seasonal bias). Bootstrapping is robust when the empirical distribution has asymmetry or fatter tails than a normal distribution.
Both modes seed their random draws deterministically per path and day, which makes plots reproducible bar-to-bar and avoids flickering bands.
3) Volatility scaling to current conditions
Markets do not always live in average volatility. The engine computes a simple volatility factor from ATR(20)/price and scales the simulated shocks up or down within sensible bounds (clamped between 0.5× and 2.0×). When the current regime is quiet, the cone narrows; when ranges expand, the cone widens. This prevents the classic mistake of projecting calm markets into a storm or vice versa.
4) Many futures, summarized by percentiles
The model generates a matrix of price paths (capped at 100 runs for performance inside TradingView), each path stepping forward for your selected horizon. For each forecast day it sorts the simulated prices and pulls key percentiles:
• 5th and 95th → approximate 95% band (outer cone).
• 16th and 84th → approximate 68% band (inner cone).
• 50th → the median or “expected path.”
These are drawn as polylines so you can immediately see central tendency and dispersion.
5) A historical overlay (optional)
Turn on the overlay to sketch a dotted path of what a purely seasonal projection would look like for the next ~30 days using only the return map, no randomness. This is not a forecast; it is a visual reminder of the seasonal drift you are biasing toward.
Inputs you control and how to think about them
Monte Carlo Simulation
• Price Series for Calculation . The source series, typically close.
• Enable Probability Forecasts . Master switch for simulation and drawing.
• Simulation Iterations . Requested number of paths to run. Internally capped at 100 to protect performance, which is generally enough to estimate the percentiles for a trading chart. If you need ultra-smooth bands, shorten the horizon.
• Forecast Days Ahead . The length of the cone. Longer horizons dilute seasonal signal and widen uncertainty.
• Probability Bands . Draw all bands, just 95%, just 68%, or a custom level (display logic remains 68/95 internally; the custom number is for labeling and color choice).
• Pattern Resolution . Daily leans on day-of-year effects like “turn-of-month” or holiday patterns. Weekly biases toward day-of-week tendencies and bootstraps from history.
• Volatility Scaling . On by default so the cone respects today’s range context.
Plotting & UI
• Probability Cone . Plots the outer and inner percentile envelopes.
• Expected Path . Plots the median line through the cone.
• Historical Overlay . Dotted seasonal-only projection for context.
• Band Transparency/Colors . Customize primary (outer) and secondary (inner) band colors and the mean path color. Use higher transparency for cleaner charts.
What appears on your chart
• A cone starting at the most recent bar, fanning outward. The outer lines are the ~95% band; the inner lines are the ~68% band.
• A median path (default blue) running through the center of the cone.
• An info panel on the final historical bar that summarizes simulation count, forecast days, number of seasonal patterns learned, the current day-of-year, expected percentage return to the median, and the approximate 95% half-range in percent.
• Optional historical seasonal path drawn as dotted segments for the next 30 bars.
How to use it in trading
1) Position sizing and stop logic
The cone translates “volatility plus seasonality” into distances.
• Put stops outside the inner band if you want only ~16% odds of a stop-out due to noise before your thesis can play.
• Size positions so that a test of the inner band is survivable and a test of the outer band is rare but acceptable.
• If your target sits inside the 68% band at your horizon, the payoff is likely modest; outside the 68% but inside the 95% can justify “one-good-push” trades; beyond the 95% band is a low-probability flyer—consider scaling plans or optionality.
2) Entry timing with seasonal bias
When the median path slopes up from this calendar date and the cone is relatively narrow, a pullback toward the lower inner band can be a high-quality entry with a tight invalidation. If the median slopes down, fade rallies toward the upper band or step aside if it clashes with your system.
3) Target selection
Project your time horizon to N bars ahead, then pick targets around the median or the opposite inner band depending on your style. You can also anchor dynamic take-profits to the moving median as new bars arrive.
4) Scenario planning & “what-ifs”
Before events, glance at the cone: if the 95% band already spans a huge range, trade smaller, expect whips, and avoid placing stops at obvious band edges. If the cone is unusually tight, consider breakout tactics and be ready to add if volatility expands beyond the inner band with follow-through.
5) Options and vol tactics
• When the cone is tight : Prefer long gamma structures (debit spreads) only if you expect a regime shift; otherwise premium selling may dominate.
• When the cone is wide : Debit structures benefit from range; credit spreads need wider wings or smaller size. Align with your separate IV metrics.
Reading the probability cone like a pro
• Cone slope = seasonal drift. Upward slope means the calendar has historically favored positive drift from this date, downward slope the opposite.
• Cone width = regime volatility. A widening fan tells you that uncertainty grows fast; a narrow cone says the market typically stays contained.
• Mean vs. price gap . If spot trades well above the median path and the upper band, mean-reversion risk is high. If spot presses the lower inner band in an up-sloping cone, you are in the “buy fear” zone.
• Touches and pierces . Touching the inner band is common noise; piercing it with momentum signals potential regime change; the outer band should be rare and often brings snap-backs unless there is a structural catalyst.
Methodological notes (what the code actually does)
• Log returns are used for additivity and better statistical behavior: sim_ret is applied via exp(sim_ret) to evolve price.
• Seasonal arrays are updated online with EWMA (90/10) so the model keeps learning as each bar arrives.
• Leap years are handled; indexing still normalizes into a 365-slot map so the seasonal pattern remains stable.
• Gaussian engine (Daily mode) centers shocks on the seasonal bias with a conservative standard deviation.
• Bootstrap engine (Weekly mode) resamples from observed seasonal returns and adds a fraction of the bias, which captures skew and fat tails better.
• Volatility adjustment multiplies each daily shock by a factor derived from ATR(20)/price, clamped between 0.5 and 2.0 to avoid extreme cones.
• Performance guardrails : simulations are capped at 100 paths; the probability cone uses polylines (no heavy fills) and only draws on the last confirmed bar to keep charts responsive.
• Prerequisite data : at least ~30 seasonal entries are required before the model will draw a cone; otherwise it waits for more history.
Strengths and limitations
• Strengths :
– Probabilistic thinking replaces single-point guessing.
– Seasonality adds a small but meaningful directional bias that many markets exhibit.
– Volatility scaling adapts to the current regime so the cone stays realistic.
• Limitations :
– Seasonality can break around structural changes, policy shifts, or one-off events.
– The number of paths is performance-limited; percentile estimates are good for trading, not for academic precision.
– The model assumes tomorrow’s randomness resembles recent randomness; if regime shifts violently, the cone will lag until the EWMA adapts.
– Holidays and missing sessions can thin the seasonal sample for some assets; be cautious with very short histories.
Tuning guide
• Horizon : 10–20 bars for tactical trades; 30+ for swing planning when you care more about broad ranges than precise targets.
• Iterations : The default 100 is enough for stable 5/16/50/84/95 percentiles. If you crave smoother lines, shorten the horizon or run on higher timeframes.
• Daily vs. Weekly : Daily for equities and crypto where month-end and turn-of-month effects matter; Weekly for futures and FX where day-of-week behavior is strong.
• Volatility scaling : Keep it on. Turn off only when you intentionally want a “pure seasonality” cone unaffected by current turbulence.
Workflow examples
• Swing continuation : Cone slopes up, price pulls into the lower inner band, your system fires. Enter near the band, stop just outside the outer line for the next 3–5 bars, target near the median or the opposite inner band.
• Fade extremes : Cone is flat or down, price gaps to the upper outer band on news, then stalls. Favor mean-reversion toward the median, size small if volatility scaling is elevated.
• Event play : Before CPI or earnings on a proxy index, check cone width. If the inner band is already wide, cut size or prefer options structures that benefit from range.
Good habits
• Pair the cone with your entry engine (breakout, pullback, order flow). Let Monte Carlo do range math; let your system do signal quality.
• Do not anchor blindly to the median; recalc after each bar. When the cone’s slope flips or width jumps, the plan should adapt.
• Validate seasonality for your symbol and timeframe; not every market has strong calendar effects.
Summary
The Seasonality Monte Carlo Forecaster wraps institutional risk planning into a single overlay: a data-driven seasonal drift, realistic volatility scaling, and a probabilistic cone that answers “where could we be, with what odds?” within your trading horizon. Use it to place stops where randomness is less likely to take you out, to set targets aligned with realistic travel, and to size positions with confidence born from distributions rather than hunches. It will not predict the future, but it will keep your decisions anchored to probabilities—the language markets actually speak.
Weekly High/Low Weekday Stats by [M1rage]Патч: условная статистика по дню недельного экстремума
Добавлена новая функция, позволяющая строить условное распределение по дням недели.
Что нового.
Два новых параметра в настройках:
Condition: Weekly High on — зафиксировать день недели, в который сформировался недельный High.
Condition: Weekly Low on — зафиксировать день недели, в который сформировался недельный Low.
Таблица автоматически перестраивается:
Левая колонка показывает — вероятности минимума недели при выбранном дне максимума.
Правая колонка показывает — вероятности максимума недели при выбранном дне минимума.
В заголовках колонок появляется подпись формата:
Weekly Low | High=Tue
Weekly High | Low=Thu
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Patch: Conditional Statistics by Day of the Weekly Extremum
A new feature has been added that builds a conditional distribution by weekdays.
What’s new
Two new settings:
Condition: Weekly High on — fix the weekday on which the weekly High formed.
Condition: Weekly Low on — fix the weekday on which the weekly Low formed.
The table updates automatically:
Left column — probabilities of the weekly Low given the selected day of the High.
Right column — probabilities of the weekly High given the selected day of the Low.
Column headers now display labels in the format:
Weekly Low | High=Tue
Weekly High | Low=Thu
Weekly High/Low Weekday Stats by [M1rage]Weekly High/Low Weekday Stats by
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Индикатор показывает, в какие дни недели чаще всего формируются недельные High и Low инструмента. Поддерживает режимы 24/5 (FX) и 24/7 (крипто). Работает на Daily (D) таймфрейме.
Что делает:
Скользит по дневным барам, собирает недельные экстремумы.
Для каждой завершённой недели фиксирует день недели недельного High и Low.
Строит таблицу-частот Mon..Fri (24/5) или Mon..Sun (24/7) с процентами/счётчиками.
Опционально помечает на графике лейблами бары, где сформировались недельные High/Low (для быстрой визуальной проверки).
Параметры:
Lookback (years) — глубина истории (примерно 52 недели × годы).
Show percentages — показывать проценты.
Show raw counts — показывать «сырые» счётчики.
Show debug labels (weekly H/L) — лейблы H/L на графике для завершённых недель.
Debug: keep last N weeks — сколько последних недель держать на графике лейблами (старые удаляются).
Market mode — режим рынка: 24/5 (Mon..Fri) или 24/7 (Mon..Sun).
Table theme — цветовая тема таблицы: Dark Theme / Light Theme
(меняет цвет текста, шапки, внешней рамки и внутренних границ).
Очень короткие праздничные недели фильтруются, чтобы не искажать статистику.
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The indicator shows on which weekdays a symbol most often sets its weekly High and Low. It supports 24/5 (FX) and 24/7 (crypto) modes. Works on the Daily (D) timeframe.
What it does:
Scans daily bars to build weekly extremes.
For each completed week, records the weekday of the weekly High and Low.
Builds a frequency table Mon–Fri (24/5) or Mon–Sun (24/7) with percentages/counts.
Optionally labels on the chart the bars where the weekly High/Low formed (for quick visual verification).
Inputs:
Lookback (years) — history depth (≈ 52 weeks × years).
Show percentages — display percentages.
Show raw counts — display raw counts.
Show debug labels (weekly H/L) — H/L labels on the chart for completed weeks.
Debug: keep last N weeks — how many recent weeks to keep as labels on the chart (older labels are deleted).
Market mode — market schedule: 24/5 (Mon–Fri) or 24/7 (Mon–Sun).
Table theme — table color theme: Dark Theme / Light Theme (changes text color, header, outer frame, and inner grid).
Very short holiday weeks are filtered out to avoid skewing the statistics.
Line color best indices grouped by Artificial Intelligence
The script uses the best buy indicators, such as moving average crossovers, RSI, and others selected by AI. The idea is to determine whether the stock is classified as a strong buy (yellow line), a buy (green line), or a red (sell)
Strong Indicator for ISM PMI EURUSD (mtbr)Overview:
This indicator is designed for EURUSD traders who want to analyse the market's reaction to the ISM Services PMI economic event. It automatically detects the event candle, calculates the “surprise” between Actual and Forecast, and generates a full trading plan with entry, take profit, and stop loss levels.
How it works:
Set the event time (or a custom date/time) and input Forecast, Previous, and Actual values.
The indicator calculates the surprise: Actual − Forecast.
Based on the surprise magnitude, it classifies the strength as Weak, Moderate, or Strong, and as Bullish or Bearish.
Direction is set automatically but can be inverted via the “Invert Signal Logic” option.
Entry, TP1, TP2, TP3, and SL are calculated based on your percentage settings.
Levels are plotted on the chart, with labels and a vertical dashed line marking the event candle.
A table displays key event data: name, forecast, actual, surprise, and strength classification.
How to use:
Select your trading asset (EURUSD by default).
Choose between automatic event time logic or a custom date/time.
Input the Forecast, Previous, and Actual values from the economic calendar.
Adjust percentage settings for entry, take profits, and stop loss.
Use the plotted lines as a reference for trade planning.
Optionally enable pullback confirmation before entry.
Disclaimer:
This tool is for educational and analytical purposes only. It is not financial advice. Always use proper risk management and perform independent analysis before trading.
RS Power Scanner by MashrabThis script implements a custom IBD-style Relative Strength (RS) rating and RS line breakout scanner for any symbol versus SPY. It is designed to help traders quickly identify stocks with market-leading performance.
How It Works:
RS Rating (0–100 scale)
Calculates 252-bar Rate of Change (ROC) for the stock and SPY.
Compares stock ROC to SPY’s ROC.
Uses ta.percentrank() to convert the result into a percentile ranking (0–100).
A high RS rating means the stock has outperformed SPY over the past 252 bars.
RS Line New Highs
Plots the RS line = (Stock Close ÷ SPY Close).
Checks for a 50-bar highest value — a classic sign of market leadership.
Signal Logic
Plots a green ▲ label below bars when:
RS Rating ≥ 85 (strong relative performance)
RS line makes a 50-bar high (confirming strength)
Table Display
Shows live RS Rating and RS new high status for quick decision-making.
Use Case:
This tool is designed for traders using momentum, CAN SLIM, or relative strength strategies to spot potential leaders early. It is not a standalone buy/sell system; rather, it helps filter stocks for further analysis.
How to Use:
Apply to your watchlist charts.
Look for ▲ signals during market uptrends.
Combine with fundamental or volume analysis for best results.
Franco Varacalli binary options |ENGLISH|
What if you could know, with mathematical precision, when your trades have the highest probability of success?
Franco V. ~ Stats is not just an indicator: it’s a real-time performance tracking and analysis system that transforms price action into clear, actionable metrics.
🔍 What it does
It analyzes candle sequences and detects changes in price dynamics, filtering opportunities according to your settings (buy only, sell only, or both). From there, it records each entry, counts wins and losses, and calculates success probabilities for different scenarios.
🛠 How it works (core concepts)
-Evaluates proportional relationships between open, close, high, and low prices.
-Detects shifts in the balance of buying/selling pressure.
-Classifies trades by the number of prior consecutive losses.
-Calculates success probabilities based on accumulated historical data.
📈 What you get
-On-chart table showing entries, wins, losses, and win percentage.
-Dynamic colors to instantly spot the best-performing scenarios.
-Optional arrows marking moments when conditions are met.
-Filters and thresholds to adapt the analysis to your trading style.
💡 How to use it
-Set your preferred signal type and consecutive loss threshold.
-Monitor the table to see which sequences show higher probability.
-Use the signals as a reference and confirm with your own technical analysis.
⚠ Disclaimer: This tool is designed for market analysis and performance tracking. It should be used in combination with your own research, risk management, and decision-making process.
Franco Varacalli
XAUUSD Strength Dashboard with VolumeXAUUSD Strength Dashboard with Volume Analysis
📌 Description
This advanced Pine Script indicator provides a multi-timeframe dashboard for XAUUSD (Gold vs. USD), combining price action analysis with volume confirmation to generate high-probability trading signals. It detects:
✅ Break of Structure (BOS)
✅ Fair Value Gaps (FVG)
✅ Change of Character (CHOCH)
✅ Trendline Breaks (9/21 SMA Crossover)
✅ Volume Spikes (Confirmation of Strength)
The dashboard displays strength scores (0-100%) and action recommendations (Strong Buy/Buy/Neutral/Sell/Strong Sell) across multiple timeframes, helping traders identify confluences for better trade decisions.
🎯 How It Works
1. Multi-Timeframe Analysis
Fetches data from 1m, 5m, 15m, 30m, 1h, 4h, Daily, and Weekly timeframes.
Compares trend direction, BOS, FVG, CHOCH, and volume spikes across all timeframes.
2. Volume-Confirmed Strength Score
The Strength Score (0-100%) is calculated using:
Trend Direction (25 points) → 9 SMA vs. 21 SMA
Break of Structure (20 points) → New highs/lows with momentum
Fair Value Gaps (10 points) → Imbalance zones
Change of Character (10 points) → Shift in market structure
Trendline Break (20 points) → SMA crossover confirmation
Volume Spike (15 points) → High volume confirms moves
Score Interpretation:
≥75% → Strong Buy (High confidence bullish move)
60-74% → Buy (Bullish but weaker confirmation)
40-59% → Neutral (No strong bias)
25-39% → Sell (Bearish but weaker confirmation)
≤25% → Strong Sell (High confidence bearish move)
3. Dashboard & Chart Markers
Dashboard Table: Shows Trend, BOS, Volume, CHOCH, TL Break, Strength %, Key Level, and Action for each timeframe.
Chart Markers:
🟢 Green Triangles → Bullish BOS
🔴 Red Triangles → Bearish BOS
🟢 Green Circles → Bullish CHOCH
🔴 Red Circles → Bearish CHOCH
📈 Green Arrows → Bullish Trendline Break
📉 Red Arrows → Bearish Trendline Break
"Vol↑" (Lime) → Bullish Volume Spike
"Vol↓" (Maroon) → Bearish Volume Spike
🚀 How to Use
1. Dashboard Interpretation
Higher Timeframes (D/W) → Show the dominant trend.
Lower Timeframes (1m-4h) → Help with entry timing.
Strength Score ≥75% or ≤25% → Look for high-confidence trades.
Volume Spikes → Confirm breakouts/reversals.
2. Trading Strategy
📈 Long (Buy) Setup:
Higher TFs (D/W/4h) show bullish trend (↑).
Current TF has BOS & Volume Spike.
Strength Score ≥60%.
Key Level (Low) holds as support.
📉 Short (Sell) Setup:
Higher TFs (D/W/4h) show bearish trend (↓).
Current TF has BOS & Volume Spike.
Strength Score ≤40%.
Key Level (High) holds as resistance.
3. Customization
Adjust Volume Spike Multiplier (Default: 1.5x) → Controls sensitivity to volume spikes.
Toggle Timeframes → Enable/disable higher/lower timeframes.
🔑 Key Benefits
✔ Multi-Timeframe Confluence → Avoids false signals.
✔ Volume Confirmation → Filters low-quality breakouts.
✔ Clear Strength Scoring → Removes emotional bias.
✔ Visual Chart Markers → Easy to spot key signals.
This indicator is ideal for gold traders who follow institutional order flow, market structure, and volume analysis to improve their trading decisions.
🎯 Best Used With:
Support/Resistance Levels
Fibonacci Retracements
Price Action Confirmation
🚀 Happy Trading! 🚀