Options Symphony Adaptive CE/PE for Indian IndicesDescription:
This invite-only Pine Script indicator is built for Indian market options traders. It plots the Call and Put charts for a selected strike simultaneously, including adaptive moving averages on both.
Single-Chart Options View: Visualize both CE and PE charts on a single pane.
User-Friendly: Enter one strike (Put), and the indicator handles the dual-chart display.
Adaptive MA: Features adaptive moving averages for smarter trend analysis in both trending and ranging markets.
Invite-Only: Access is granted by the author and requires permission.
To get started: Request access from the author to be added to the invite list.
インジケーターとストラテジー
SSMT [TakingProphets]SSMT (Sequential SMT) — multi-cycle intermarket divergence with quarter-based timing
Purpose
Informational overlay that detects intermarket SMT divergences between the chart symbol and a user-selected correlated symbol. It does not generate buy/sell signals and is not financial advice. Use it to structure analysis and alerts, not to automate trades.
What it does
Scans for SMT on five coordinated cycles: Micro, 90-Minute, Daily (Q1–Q4), Weekly, Monthly.
Draws anchored lines and labels where divergences occur and keeps them after the period ends so you can use historical SMTs as context.
Offers per-cycle alerts (high-side/bearish, low-side/bullish).
Optional session/quarter boxes for timing context.
Time base uses America/New_York to align with common session conventions (with a 17:00–18:00 ET pause guard for CME instruments).
Why these modules belong together (more than a mashup)
All cycles share a single time-partitioning framework (quarters/sessions → day → week → month). That common clock means:
Comparability: divergences on Micro/90m/D/W/M are directly comparable because they’re computed with the same boundaries for both instruments.
Sequencing: higher-cycle context can gate lower-cycle events (e.g., a Daily Q3 divergence framing how you treat a Micro divergence).
Persistence: drawings retain the cycle identity (e.g., , ) so prior signals remain interpretable as the market progresses.
This is a coherent engine—not separate indicators pasted together—because detection, labeling, alerts, and persistence are all driven by the same quarter/period state machine.
How it works (high-level mechanics)
Time partitioning
Daily quarters (ET):
Q1: 18:00–00:00
Q2: 00:00–06:00
Q3: 06:00–12:00
Q4: 12:00–18:00
90-Minute cycle: four 90-minute blocks inside the active session.
Micro cycle: finer 20–22 minute blocks inside the session for granular timing.
Weekly/Monthly: tracked by calendar periods (Mon–Fri, and calendar month).
Pause guard: 17:00–18:00 ET to avoid false transitions during CME’s daily maintenance window.
State tracking (per cycle)
Tracks previous vs. current highs/lows for the chart symbol and the correlated symbol (fetched at the same timeframe).
Maintains cycle IDs (e.g., year*100 + weekofyear for weekly) so drawings remain tied to the originating period.
Divergence condition (SMT)
High-side (bearish): one instrument makes a higher high vs. its previous period while the other does not.
Low-side (bullish): one instrument makes a lower low vs. its previous period while the other does not.
When detected, the script plots a labeled span/line (e.g., SSMT w/ES) and records it for persistence.
Alerts
Two per cycle: High-side (bearish) and Low-side (bullish).
Fire on the bar where the condition first becomes true.
Inputs & customization
Correlated symbol (default can be an index future).
Cycle toggles: Micro, 90m, Daily (Q1–Q4), Weekly, Monthly.
Styling: line color/width, label text/size.
Session/quarter boxes: on/off.
Alerts: per-cycle SMT events on/off.
How to use
Add the indicator to your chart (e.g., NQ, ES) and select a correlated symbol.
Turn on the cycles you want to monitor; optionally enable quarter/session boxes.
Interpret SMTs by side:
High-side (bearish): chart makes HH, correlated does not.
Low-side (bullish): chart makes LL, correlated does not.
Set alerts for the cycles that matter to your workflow.
Combine with your higher-timeframe narrative and risk rules.
Repainting, timing, and limitations
Uses higher-timeframe data without look-ahead; values can update intrabar until the period closes.
SMTs may form and resolve within a period; conservative users may wait for period close.
Assumes America/New_York timing; very thin markets may yield fewer or noisier signals.
SMT quality depends on the benchmark you select; correlations vary across regimes.
Educational tool only. No performance claims; not a signal generator.
Originality & scope (for protected/invite-only publications)
A multi-cycle SMT engine built on a shared quarter/period state machine (Micro → 90m → Daily Q1–Q4 → Weekly → Monthly).
Quarter-aware persistence keeps divergence drawings tied to their source cycle for durable context.
CME pause handling and stable calendar IDs make detections consistent across sessions and rollovers.
Implements SMT through extremum sequencing and cross-instrument comparison rather than wrapping generic divergence indicators.
CRT [TakingProphets]CRT (Candle Range Theory) — HTF context overlay with alerts
Purpose
Informational overlay to structure higher-timeframe (HTF) context. It does not generate buy/sell signals and is not financial advice. Use it to organize analysis and alerts—not to automate trades.
What it does
Projects HTF candles (1m → 1M) on any lower timeframe so the big picture stays on the chart.
Detects CRT transitions on the HTF (bullish/bearish “failed continuation” pattern).
Evaluates SMT divergence vs. a user-selected correlated instrument on the same HTF (historical & real-time).
Extends live HTF Open/High/Low/Close as developing reference levels.
Concepts (what it looks for)
Candle Range Theory (CRT) — a 3-bar HTF pattern where candle 2 fails to continue candle 1’s move:
Bearish CRT: candle 2 trades above candle 1’s high but closes back inside candle 1’s range and does not break its low.
Bullish CRT: candle 2 trades below candle 1’s low but closes back inside candle 1’s range and does not break its high.
SMT divergence (intermarket) — compares HTF swing extremes between the chart symbol and a correlated symbol:
Bearish SMT: one makes a higher high while the other does not.
Bullish SMT: one makes a lower low while the other does not.
Checked in two modes: historical (between the two last closed HTF bars) and real-time (last closed vs. current forming HTF bar).
How the elements work together (integration, not a mashup)
All modules share one HTF time base, so annotations describe the same segment of price action. The overlay produces an explicit context state by sequencing the modules in this order:
HTF Projection → Structural Frame
The last three HTF candles are drawn (bodies+wicks). This creates the “canvas” the rest of the logic references (ranges, highs/lows, and time boundaries).
CRT Test → Directional Bias Candidate
The script evaluates the 3-bar CRT conditions on those exact HTF candles (not lower-TF approximations).
If conditions are forming on the current HTF bar, status is CRT Forming.
If they complete on the close, status becomes CRT Confirmed (Bullish/Bearish).
SMT Check → Confirmation/Stress-Test on the Same HTF
Using the same HTF window, the tool compares swing progress with the correlated symbol.
Historical SMT comments on whether the prior HTF segment’s push had intermarket agreement.
Real-time SMT comments on the current forming push.
This lets you confirm a CRT bias (e.g., Bearish CRT + Bearish SMT) or challenge it (e.g., Bullish CRT but Bearish SMT).
Live HTF OHLC → Actionable Reference Levels
The current HTF Open/High/Low/Close are extended as levels. These are the decision rails you’ll typically use to judge follow-through, failure, mitigation, or targets in the same CRT/SMT context.
Resulting context states (what you’ll see in alerts/labels):
Neutral (no CRT; SMT may still inform context).
CRT Forming (monitor): HTF push is underway; watch real-time SMT into HTF High/Low/Close projections.
CRT Confirmed (bias): HTF failure pattern locked; use projections as reference for continuation/invalidations.
CRT + SMT Aligned (confluence): CRT direction agrees with SMT; strongest context.
CRT vs. SMT Mixed (caution): bias exists but intermarket is disagreeing; treat levels as potential fade zones.
Why this is not a mashup
Every module is computed and plotted in the same HTF coordinate system, so signals are about one thing: the current HTF segment.
CRT provides the bias hypothesis, SMT provides a cross-market test of that hypothesis in the same window, and live OHLC projections supply the exact levels used to act on or fade that hypothesis.
Alerts are tied to state transitions (e.g., CRT forming → confirmed; SMT flip), not to unrelated features.
Mechanics (high-level)
HTF Projection: pulls HTF OHLC/time for the last three HTF bars and renders body boxes + wicks; optional time labels adapt to intraday vs D/W/M.
CRT Labels: when the three-bar conditions are met, prints BULLISH CRT or BEARISH CRT on the HTF stack.
SMT Lines: draws labeled diagonals across the relevant HTF pair for historical and real-time checks using your correlated symbol.
Live Levels: extends the current HTF Open/High/Low/Close horizontally; anchors are deterministic (Open = first bar, High/Low = first occurrence, Close = current bar).
Inputs & customization
HTF timeframe: 1m–1M.
Display: candle width/opacity, borders/wicks, time labels (12h/24h).
SMT: enable/disable, correlated symbol, line style/width, optional labels.
Projections: enable/disable, left extension (bars), per-level styling and price labels.
Alerts: switches for CRT, SMT-historical, SMT-real-time.
Alerts (workflow prompts)
Bullish/Bearish CRT detected on the selected HTF.
Bullish/Bearish SMT (historical) between the two last closed HTF bars.
Bullish/Bearish SMT (real-time) between the last closed and current forming HTF bar.
Suggested text includes the HTF and current context state so you know if CRT and SMT are aligned or mixed.
Example use
Bearish scenario: A Bearish CRT confirms on the 4H; soon after, real-time SMT (bearish) appears while price probes the projected 4H High. Context = CRT + SMT Aligned → treat the projected Open/Close as near-term objectives.
Mixed scenario: A Bullish CRT forms on 1H, but historical SMT (bearish) printed in the prior segment. Context = Mixed → continue to monitor real-time SMT and projected Low for possible invalidation.
Notes & limitations
HTF values are provisional until the HTF bar closes; labels/lines can update while forming.
SMT depends on the correlated symbol you select; relationships vary by market/regime.
Session gaps/illiquid hours can distort extremes and time labels.
Educational tool: no performance claims, no entry/exit signals.
Originality & scope (for protected/invite-only publications)
A unified HTF projection → CRT test → SMT check → live level pipeline that yields explicit context states instead of separate, unrelated overlays.
Formal CRT detection performed on actual HTF bars (not lower-TF approximations).
Dual-mode SMT tied to the same HTF windows (historical + real-time), plotted as labeled span lines.
Deterministic OHLC projection (first-occurrence anchoring) to align decisions with the identified context.
Attribution: CRT/SMT concepts inspired by ICT. Design, implementation, and alert framework by TakingProphets.
Metals vs DXY CorrelationThere's a growing interest in Gold and Metals in general - due to safe have demand - a lot of traders get blindsided by sudden consolidation and reversals while trading Gold or Silver. The key is to know that GC is closely related to DXY because large institutions and central banks hedge the two instruments. They are inversely correlated for the most part.
This indicator looks at price action applies Pearson correlation to find the strength in their "entanglement" and tells you if its is strongly, weakly or positively correlated.
It has helped me stay away from the markets when there's a strong inverse correlation because the price action can be very unpredictable.
Hopefully you find this useful.
Prophet Model [TakingProphets]The Prophet Model — context pipeline (HTF PDA → Sweep → CISD → EPE) with dynamic risk
Purpose
Informational overlay for organizing institutional context in real time. It does not issue buy/sell signals and is not financial advice. Use it to structure analysis and checklist-driven execution—not to automate decisions.
What it does (modules at a glance)
Projects HTF PD Arrays (FVGs) onto your current chart and maintains only the nearest active array.
Validates directional bias using Candle Range Theory (CRT) on the same HTF.
Tracks Liquidity Sweeps (BSL/SSL) on HTF-aware pivots.
Confirms Change in State of Delivery (CISD) via displacement after a sweep.
Optionally refines entries with EPE when a local (internal) imbalance forms right after CISD.
Derives dynamic TP/BE/SL from measured displacement and recent extremes (not fixed distances).
Keeps a rules checklist (PDA tap → CRT → Sweep → CISD) and a relationships table (common HTF↔LTF pairings) to enforce process.
How it works (integration, not a mashup)
The modules are sequenced on one HTF time base so each step gates the next:
HTF PD Arrays (context zone). The model identifies valid HTF FVGs, filters tiny/weekend gaps, removes arrays that are invalidated by clean trades-through, and persists only the nearest PDA. This focuses attention on the institutional zone most likely to matter now.
CRT (directional gating). CRT on the same HTF establishes a provisional bias. No entries are implied; CRT simply permits or forbids the following steps. If CRT disagrees with the PDA context, the checklist remains incomplete.
Liquidity Sweep (event). The model tracks HTF-aware BSL/SSL pivots. A sweep only “counts” if it occurs in relation to the active PDA (tap/engagement). This prevents generic swing-high/low tags from triggering downstream logic.
CISD (confirmation). After a qualified sweep, the tool looks for displacement through the sequence open (the open of the impulsive leg beginning at or immediately after the sweep). Crossing that threshold confirms CISD, which marks a structural delivery shift consistent with the CRT bias.
EPE (refinement, optional). Immediately following CISD, the model scans for a fresh internal imbalance. If found quickly, it promotes that price area as the Easiest Point of Entry (EPE) and relabels the reference. If not, the CISD level remains primary.
Dynamic risk levels. TP/BE/SL are derived from the measured displacement around the CISD leg (e.g., BE ≈ 1× leg, TP ≈ 2.25× stretch; SL aligned to nearby structural extremes rather than a fixed pip offset). Levels update with structure and can display prices.
By chaining PDA → CRT → Sweep → CISD → (EPE) → Risk on a single HTF backbone, the tool creates a coherent workflow where later signals simply do not appear without earlier context. That’s why this is not a bundle of independent features: each module’s output is another module’s input.
Concepts & operational rules (high level)
HTF PD Arrays (FVGs)
Uses a standard three-candle gap definition on the chosen HTF, with filters for weekend/tiny gaps.
Inverse mitigation: if price trades cleanly through an array, the box is removed and internal state resets.
Nearest-PDA persistence: when multiple arrays exist, only the closest remains visible to reduce clutter.
Optional right-extension draws lingering influence X bars forward.
Candle Range Theory (CRT)
Bullish CRT: candle 2 wicks below candle 1’s low but closes back inside candle 1’s range, without taking its high.
Bearish CRT: candle 2 wicks above candle 1’s high but closes back inside candle 1’s range, without taking its low.
Role: bias validation paired to CISD when alignments match the active PDA.
Liquidity Sweeps (BSL/SSL)
Tracks candidate HTF pivots as buy-/sell-side liquidity.
A sweep registers when price takes a tracked pivot in the vicinity of the active PDA.
CISD (Change in State of Delivery)
Finds the sequence open for the impulsive leg that begins at/after the sweep.
Bearish path (after BSL sweep): CISD when close < sequence-open.
Bullish path (after SSL sweep): CISD when close > sequence-open.
On confirmation, the model plots a CISD line, checks the box in the Strategy Checklist, and triggers risk calc.
EPE (Easiest Point of Entry)
Within a short window after CISD, scans for a local imbalance; if present, promotes that level as EPE.
If no imbalance forms, CISD remains the operative reference.
Dynamic TP / BE / SL
Built from the measured leg around CISD (not fixed pip steps).
Approximate geometry: BE ≈ 1× leg, TP ≈ 2.25× leg; SL respects nearby structural extremes.
Labels and price markers are optional.
Architecture notes
Maps the current chart to a higher timeframe (e.g., 15s→M5, M1→M15, M5→H1, M15→H4, H1→D, H4→W, D→M).
Retrieves HTF OHLC/time with no lookahead so structures update intrabar until the HTF bar closes.
Periodic cleanup clears obsolete lines/labels/boxes to keep charts responsive.
Inputs (summary)
FVGs/PD Arrays: show/hide, colors, borders, label size, right-extension, nearest-only toggle.
CRT: enable/disable, label style.
Sweeps/CISD/EPE: enable/disable, line/label styles, EPE window.
Risk Levels (TP/BE/SL): enable each, price labels on/off, colors.
Tables/Checklist: strategy checklist on/off; relationships table (common HTF↔LTF pairings); text sizes and header colors.
Alerts (optional)
You may add alertconditions aligned with these events in your own workspace:
HTF PDA tap (bullish/bearish box)
CRT detected (bullish/bearish)
CISD confirmed (bullish/bearish)
EPE set/updated
Example messages:
“Prophet: CISD confirmed on {{ticker}} / {{interval}}”
“Prophet: EPE refined at {{close}} ({{time}})”
Notes & limitations
HTF values are provisional until the HTF bar closes; labels/levels can update while forming.
CISD/EPE are live conditions; they can form and later invalidate within the same HTF bar.
Liquidity relationships vary by market/regime; thin sessions and large gaps can affect clarity.
Educational tool only. No performance claims; no trade signals.
Originality & scope (for protected/invite-only publications)
A single HTF-synchronized engine sequences PDA → CRT → Sweep → CISD → (EPE) and withholds later steps unless prerequisites are met.
Nearest-PDA persistence and inverse-mitigation enforce focus on the most relevant institutional zone.
Displacement-based risk math ties TP/BE/SL to structure instead of static offsets.
Checklist + relationships table promote consistent, rules-first behavior and reduce discretionary drift.
Attribution: Concepts inspired by ICT (PD arrays/FVGs, CRT, sweeps, displacement, refined entries). Design, integration logic, and risk framework by TakingProphets.
HTF Candles [TakingProphets]HTF Candles — higher-timeframe structure, SMT divergence, and live OHLC projections
Purpose
Informational overlay to keep higher-timeframe (HTF) context visible on a lower-timeframe chart. It does not generate buy/sell signals and is not financial advice. Use it to structure analysis and alerts, not to automate trading.
What it does
HTF candle visualization (up to 10 candles, optional right-side offset) with bodies, wicks, and time labels.
SMT divergence checks on the chosen HTF—both historical (last two completed HTF bars) and real-time (last closed vs. current forming bar) vs. a user-selected correlated symbol (default can be an index future).
Live HTF OHLC projections: forward-extending Open / High / Low / Close from the current HTF bar with optional price labels and styling.
HTF close timer (optional) to show when the active HTF candle ends.
Why these modules belong together (more than a mashup)
This overlay uses one HTF time base to align three lenses of the same context:
Candle projection provides the structural frame (ranges and bodies of true HTF bars).
SMT divergence provides intermarket confirmation/invalidations on that same HTF, so the divergence you see is directly comparable to the projected candles.
Live OHLC projections turn the current HTF bar’s evolving state into concrete reference levels for intraday decisions.
Because all three share the same HTF clock and data source, alerts and drawings change together when the HTF state actually changes. The intent is a coherent workflow tool where each module gates the others (structure → confirmation → actionable references), rather than separate indicators merely co-plotted.
How it works (high-level)
Timeframe mapping & data
You choose an HTF (1m–1M). The script retrieves HTF OHLC/time without look-ahead. Objects update intrabar until the HTF bar closes.
Candle rendering
Up to 10 recent HTF candles are drawn as body boxes with wicks.
A horizontal offset/spacing option places the stack right of the current price for clarity.
Visuals (colors, transparency, borders, wick width, label size/format 12h/24h) are configurable.
SMT divergence (historical & real-time)
Compares HTF highs/lows of your chart vs. a correlated symbol using the same HTF.
Bearish SMT (high-side): one makes a higher high while the other does not.
Bullish SMT (low-side): one makes a lower low while the other does not.
Historical mode compares HTF → HTF ; real-time mode compares HTF → HTF as the current HTF bar forms.
Optional lines/labels mark where the divergence is detected.
Live OHLC projections
Extends the current HTF Open / High / Low / Close forward as horizontal lines.
Anchors: Open = first bar of the HTF period; High/Low = first occurrence of each extreme inside the period; Close = current bar.
Each level has independent toggles for price labels, style, and width.
Alerts (workflow prompts)
Bullish SMT, Bearish SMT, Bullish Real-time SMT, Bearish Real-time SMT.
Fire on the bar where the condition first becomes true.
Inputs & customization
Timeframe: select HTF (1m–1M).
Display: number of candles (1–10), right-offset, candle width, transparency, time labels on/off (12h/24h), label size, HTF close timer on/off.
Visuals: bullish/bearish body colors, border color, wick color.
SMT: enable/disable, correlated symbol, line style/width, labels on/off, alerts on/off.
Projections: enable/disable, per-level toggles (Open/High/Low/Close), color/style/width, optional price labels.
Notes & limitations
HTF values are provisional until the HTF bar closes; lines/labels can update during formation.
SMT usefulness depends on the correlated symbol you select; relationships vary by market/regime.
Session gaps/low liquidity can affect extremes and time labels.
Educational tool only. No performance claims and no trade signals.
Originality & scope (for protected/invite-only publications)
A single HTF-synchronized engine: candle projection, dual-mode SMT, and live OHLC projections all computed from the same HTF series to ensure consistent timing and interpretation.
Real-time SMT explicitly ties the developing HTF bar to the prior closed bar, reducing ambiguity vs. generic divergence checks.
Projection anchoring (first-occurrence rules for H/L, period start for Open, current bar for Close) provides deterministic, reproducible reference levels.
Bull-Bear EfficiencyBull-Bear Efficiency
This indicator measures the directional efficiency of price movement across many historical entry points to estimate overall market bias. It is designed as a trend gauge rather than a timing signal.
Concept
For each historical bar (tau) and a chosen lookahead horizon (h), the script evaluates how efficiently price has traveled from that starting point to the endpoint. Efficiency is defined as the net price change divided by the total absolute movement that occurred along the path.
Formula:
E(tau,h) = ( Price - Price ) / ( Sum from i = tau+1 to tau+h of | Price - Price | )
This measures how "straight" the path was from the entry to the current bar:
If price moved steadily upward, the numerator and denominator are nearly equal, and E approaches +1 (efficient bullish trend).
If price moved steadily downward, E approaches -1 (efficient bearish trend).
If price chopped back and forth, the denominator grows faster than the numerator, and E approaches 0 (inefficient movement).
The algorithm computes this efficiency for many past starting points and multiple horizons, optionally normalizing by ATR to account for volatility. The efficiencies are then weighted by recency to emphasize more recent behavior.
From this, the script derives:
Bull = weighted average of positive efficiencies
Bear = weighted average of negative efficiencies (absolute value)
Net = Bull - Bear (net directional efficiency)
Interpretation
Bull, Bear, and Net quantify how coherently the market has been trending.
Bull near 1.0, Bear near 0.0, Net > 0 -> clean upward trends; long positions have been more efficient.
Bear near 1.0, Bull near 0.0, Net < 0 -> clean downward trends; short positions have been more efficient.
Bull and Bear both small or similar -> low-efficiency, range-bound environment.
Net therefore acts as a "trend coherence index" that measures whether price action is directionally organized or noisy.
Practical Use
Trend filter:
Apply trend-following systems only when Net is strongly positive or negative.
Avoid them when Net is near zero.
Regime change detection:
Crossings through zero often correspond to transitions between trending and ranging regimes.
Momentum loss detection:
If price makes new highs but Net or Bull weakens, it suggests trend exhaustion.
Settings Overview
Lookback: Number of historical bars considered as entry points (tau values).
Horizons: List of forward projection lengths (in bars) for measuring efficiency.
Recency Decay (lambda): Exponential weighting that emphasizes recent data.
Normalize by ATR: Adjusts "effort" to account for volatility changes.
Display Options: Toggle Bull, Bear, Net, or Signed Average (S). Customize line colors.
Notes
This indicator does not produce entry or exit signals.
It is a statistical tool that measures how efficiently price has trended over time.
High Net values indicate smooth, coherent trends.
Low or neutral Net values indicate noisy, directionless conditions.
ParallaxMind™️ MACD-V: Volatility Normalized Momentum Candles🚀 Award-Winning Momentum Indicator that Outperforms the Standard MACD in All Market Conditions
📈 ParallaxMind™️ MACD-V: Volatility Normalized Momentum Colored Bars with Alerts
The MACD-V (Volatility Normalized MACD) was first developed by trader Alex Spiroglou in 2015, published in a 2022 research paper, and awarded the Charles H. Dow Award for outstanding research in technical analysis.
Unlike the standard MACD, which often suffers from noisy false signals and inconsistent readings, the MACD-V introduces volatility normalization. This innovation creates a hybrid momentum tool that solves the five core limitations of the classic MACD — making signals stable across time, universally comparable across markets, and structured within a clear momentum framework.
🔑 Key Features & Benefits
Time-Stable & Cross-Market Comparable: A reading of +100 or -100 has the same meaning across decades and across assets — stocks, forex, commodities, and crypto.
Objective Momentum Framework: Levels at +150, +50, -50, and -150 create universal benchmarks to identify rallying, declining, ranging, and extreme conditions.
Alerting Capability: Built-in alerts notify you the moment momentum shifts — including crossovers, zero-line breaks, and entries into overbought/oversold zones. This ensures you never miss critical setups without constantly watching charts.
Momentum Stage Labels: Clear, automatic labels appear on your chart to define the current state of the market — Rallying, Retracing, Ranging, Declining, Rebounding, or Risk Zones. These labels cut through noise and provide instant clarity about market conditions.
With these features, the MACD-V transforms momentum analysis from subjective art into objective science, delivering cleaner entries, smarter exits, and greater confidence in any market.
ParallaxMind™️ MACD-V: Volatility Normalized Momentum w/Alerts🚀 Award-Winning Momentum Indicator that Outperforms the Standard MACD in All Market Conditions
📈 ParallaxMind™️ MACD-V: Volatility Normalized Momentum with Alerts
The MACD-V (Volatility Normalized MACD) was first developed by trader Alex Spiroglou in 2015, published in a 2022 research paper, and awarded the Charles H. Dow Award for outstanding research in technical analysis.
Unlike the standard MACD, which often suffers from noisy false signals and inconsistent readings, the MACD-V introduces volatility normalization. This innovation creates a hybrid momentum tool that solves the five core limitations of the classic MACD — making signals stable across time, universally comparable across markets, and structured within a clear momentum framework.
🔑 Key Features & Benefits
Time-Stable & Cross-Market Comparable: A reading of +100 or -100 has the same meaning across decades and across assets — stocks, forex, commodities, and crypto.
Objective Momentum Framework: Levels at +150, +50, -50, and -150 create universal benchmarks to identify rallying, declining, ranging, and extreme conditions.
Alerting Capability: Built-in alerts notify you the moment momentum shifts — including crossovers, zero-line breaks, and entries into overbought/oversold zones. This ensures you never miss critical setups without constantly watching charts.
Momentum Stage Labels: Clear, automatic labels appear on your chart to define the current state of the market — Rallying, Retracing, Ranging, Declining, Rebounding, or Risk Zones. These labels cut through noise and provide instant clarity about market conditions.
With these features, the MACD-V transforms momentum analysis from subjective art into objective science, delivering cleaner entries, smarter exits, and greater confidence in any market.
SEIZ - Statistical External & Internal Zones [Pro]Overview
SEIZ (Statistical External & Internal Zones) visualizes how far price typically travels beyond a prior candle’s range (external to previous candles high/low) or within it (internal to previous candles high/low).
It displays percentile thresholds that highlight when movement is statistically common vs. stretched relative to recent structure.
Key Features
• External zones: mark areas where price historically tends to extend beyond the previous range.
Example: a 50th external high percentile is a historically common extension above the prior candle range’s high; a 50th external low percentile is a historically common extension below the prior candle range’s low.
• Internal zones: mark areas where price historically tends to retrace while remaining inside the previous range.
Example: a 50th internal high percentile represents a historically common move that remained within the prior candle range on the high side; similarly for internal low.
• Auto-switching: When "enabled" the indicator will automatically switch to the correct internal or external zones. For example if the indicator is on the daily timeframe it will automatically show external high zones and levels if it has gone above the previous days high. It will then hide/filter out the internal high zones because price is no longer within the previous daily range.
• Multi-time-frame table: summarizes the most significant percentile reached on each enabled timeframe (e.g., 15m → 12h, 1D) with an interval-progress readout. For example if indicator is set to "Daily" it will show the highest level reached within the day under the "High" column, and the lowest level reached in the day under the "Low" column. The "Progress" column shows how much of the timeframe of that row has completed its candle/interval.
• Highly customizable settings:
- "Show Historic": When on will show current interval zones and as many previous intervals as possible
- "Show Intervals 2 Only": When on will show only the current and previous interval zones and levels.
- Choose between drawing lines for levels or zones or both. Customize colors and transparency of zones.
Methodology (transparency)
• SEIZ uses pre-computed, timeframe-specific percentile datasets that quantify typical extensions and retracements observed in historical data.
• The datasets are embedded in the script for deterministic plotting across timeframes; no external connections are used.
• Percentile values reflect empirical frequencies (not assumptions of a normal distribution).
• These levels do not have any prediction power over future price. They are a visual to compare historically where highs and lows most commonly formed for a time period with current price.
How to use
Choose the Timeframe to reference for zones.
Leave Auto external/internal zones filtering ON for regime-aware plotting.
Optional: enable percentile lines (25 / 50 / 75 / 85 / 95) and/or filled zones; adjust opacity and labels to taste.
Set alerts on percentile crosses to be notified when price reaches statistically rare areas.
Treat SEIZ as context; it does not generate entries or exits.
Notes
• Descriptive tool — no prediction or performance claims.
• Percentiles summarize historical behavior and can vary with market conditions.
• Source is protected to safeguard the proprietary construction of percentile datasets.
• Non-standard chart types (e.g., Heikin Ashi, Renko) are for display only.
Credits
Developed by LevelLogic Indicators to help interpret market structure through empirical percentile context.
Bollinger Band ToolkitBollinger Band Toolkit
An advanced, adaptive Bollinger Band system for traders who want more context, precision, and edge.
This indicator expands on the classic Bollinger Bands by combining statistical and volatility-based methods with modern divergence and squeeze detection tools. It helps identify volatility regimes, potential breakouts, and early momentum shifts — all within one clean overlay.
🔹 Core Features
1. Adaptive Bollinger Bands (σ + ATR)
Classic 20-period bands enhanced with an ATR-based volatility adjustment, making them more responsive to true market movement rather than just price variance.
Reduces “overreacting” during chop and avoids bands collapsing too tightly during trends.
2. %B & RSI Divergence Detection
🟢 Green dots: Positive %B divergence — price makes a lower low, but %B doesn’t confirm (bullish).
🔴 Red dots: Negative %B divergence — price makes a higher high, but %B doesn’t confirm (bearish).
✚ Red/green crosses: RSI divergence confirmation — momentum fails to confirm the price’s new extreme.
These signals highlight potential reversal or slowdown zones that are often invisible to the naked eye.
3. Bollinger Band Squeeze (with Volume Filter)
Yellow squares (■) show periods when Bollinger Bands are at their narrowest relative to recent history.
Volume confirmation ensures the squeeze only triggers when both volatility and participation contract.
Often marks the “calm before the storm” — breakout potential zones.
4. Multi-Timeframe Breakout Markers
Optionally displays breakouts from higher or lower timeframes using different colors/symbols.
Lets you see when a higher timeframe band break aligns with your current chart — a strong trend continuation signal.
5. Dual- and Triple-Band Visualization (±1σ, ±2σ, ±3σ)
Optional inner (±1σ) and outer (±3σ) bands provide a layered volatility map:
Price holding between ±1σ → stable range / mean-reverting behavior
Price riding near ±2σ → trending phase, sustained momentum
Price touching or exceeding ±3σ → volatility expansion or exhaustion zone
This triple-band layout visually distinguishes normal movement from statistical extremes, helping you read when the market is balanced, expanding, or approaching its limits.
⚙️ Inputs & Customization
Choose band type (SMA/EMA/SMMA/WMA/VWMA)
Adjust deviation multiplier (σ) and ATR multiplier
Toggle individual features (divergence dots, squeeze markers, inner bands, etc.)
Multi-timeframe and colour controls for advanced users
🧠 How to Use
Watch for squeeze markers followed by a breakout bar beyond ±2σ → volatility expansion signal.
Combine divergence dots with RSI or price structure to anticipate slowdowns or reversals.
Confirm direction using multi-timeframe breakouts and volume expansion.
💬 Why It Works
This toolkit transforms qualitative chart reading (tight bands, hidden divergence) into quantitative, testable conditions — giving you objective insights that can be backtested, coded, or simply trusted in live setups.
Confirmed Breakout Detector v2This indicator automatically:
Detects breakouts above recent resistance (pivot high).
Confirms volume surge (≥ 1.5× average 50-day volume).
Compares RS line vs QQQ to ensure leadership.
Checks candle strength (close in upper half).
Verifies MACD slope ≥ 0 (no bearish divergence).
Plots green triangles under confirmed buys, orange for watch-list breakouts.
Displays an on-chart label (HUD) with real-time confirmation status.
Supports TradingView alerts, so you can set “Confirmed Buy Alert” → Send Email / App Notification.
Institutional AI-Enhanced Market StructureInstitutional AI-Enhanced Market Structure Indicator
COMPREHENSIVE DESCRIPTION
Overview and Purpose
This indicator combines institutional trading concepts (Smart Money Concepts) with a proprietary AI-inspired probability scoring system to identify high-probability trading opportunities. Unlike standard trend-following or support/resistance indicators, this tool integrates multiple institutional order flow concepts and quantifies their confluence through a dynamic scoring algorithm that adapts to market conditions.
The indicator is closed-source because it contains a unique multi-factor probability calculation engine and adaptive parameter optimization system that took extensive development and backtesting to create. The specific weighting, thresholds, and interaction between components represent proprietary intellectual property.
What Makes This Original
1. AI-Inspired Adaptive Probability Scoring System
The core innovation is a dynamic scoring algorithm that evaluates trade setups based on 6 confluence factors:
Market Structure Quality (20 points): Validates Break of Structure (BOS) or Change of Character (CHoCH) using pivot-based swing analysis
Order Flow Strength (15 points): Measures institutional volume participation relative to 20 and 50-period moving averages with standard deviation filtering
Liquidity Engineering (15 points): Detects liquidity sweeps at equal highs/lows (EQL) where retail stop losses cluster
Imbalance Presence (10 points): Identifies unfilled Fair Value Gaps (3-candle imbalances) as institutional entry zones
Market Regime Alignment (10 points): Confirms directional bias through multi-factor regime classification
Volatility Environment (5 points): Penalizes signals during high-volatility "chop" periods
Each factor is weighted based on backtested importance, and the total score (50-100%) must exceed a user-defined threshold before displaying signals. This is NOT a simple indicator mashup—the scoring system dynamically evaluates how these concepts work together in real-time.
2. Dynamic Market Regime Detection
Most indicators use static parameters. This indicator continuously classifies the market into one of four regimes using four calculations:
Trend Strength: EMA(21) vs EMA(50) divergence relative to price
Volatility Ratio: Current price standard deviation vs 50-period average
Volume Regime: Current volume vs 50-period SMA
Average Daily Range: 20-bar high-low range normalized to price
Based on these inputs, the algorithm classifies markets as:
BULL_TREND: Strong upward momentum with above-average volume
BEAR_TREND: Strong downward momentum with above-average volume
RANGING: Low trend strength with contained volatility
VOLATILE: Elevated volatility ratio above 1.5x average
The regime detection then adaptively modifies:
ATR multipliers for stop placement (2.5x in volatile, 1.2x in ranging, 1.8x in trending)
Signal probability requirements (higher in volatile conditions)
Order block decay rates
Fair value gap sensitivity
3. Institutional Order Flow Integration
The indicator detects and tracks institutional footprints through three proprietary methods:
Order Blocks: Unlike simple supply/demand zones, this uses a multi-condition filter:
Volume spike > 2.0 standard deviations above 20-period average
Large candle body > 0.8x ATR
Confirmation of Break of Structure in the same direction
Touch tracking and "tested" status when price revisits
Automatic decay after user-defined bars (prevents chart clutter)
Fair Value Gaps (Imbalances): 3-candle inefficiency detection where:
Bullish FVG: low > high AND close > high (gap between candle 0 and 2)
Bearish FVG: high < low AND close < low
Real-time fill percentage tracking as price revisits the gap
Assumes institutions will defend or fill these imbalances
Liquidity Zones: Detects equal highs/lows where retail stops cluster:
Identifies swing points within user-defined percentage threshold (default 0.3%)
Tracks "sweep" events when price spikes through then reverses (wick through level, close back inside)
Differentiates swept vs unswept liquidity for entry timing
4. Volume-Weighted Dynamic Levels
Instead of simple moving averages or static pivots, support/resistance are calculated using volume-weighted price:
Support = Σ(low × volume ) / Σ(volume ) for i=0 to 19
Resistance = Σ(high × volume ) / Σ(volume ) for i=0 to 19
This gives more weight to price levels with higher institutional participation, creating more reliable stop-loss placement when "Adaptive Stop Loss" is enabled.
5. Multi-Timeframe Confluence
The indicator queries daily timeframe data for higher-timeframe confirmation:
Daily EMA trend direction (21 vs 50)
Daily volume regime (above/below 20-period average)
Daily market regime classification
Signals only trigger when current timeframe setup aligns with daily timeframe bias, filtering out counter-trend noise.
How It Works - Technical Methodology
Market Structure Detection (Smart Money Concepts)
Uses ta.pivothigh() and ta.pivotlow() with user-defined strength (default 5 bars each side)
Stores last 50 swing highs and lows in arrays for historical reference
Break of Structure (BOS): Price closes beyond the most recent swing high (bullish) or swing low (bearish)
Change of Character (CHoCH): Price breaks counter-trend structure (low breaks above previous swing low = potential reversal)
Signal Generation Logic
A valid LONG signal requires ALL of the following:
Setup: Bullish BOS or CHoCH confirmed
Confirmation: Bullish liquidity sweep OR unfilled bullish FVG present
HTF Alignment: Daily timeframe in uptrend with above-average volume
Probability Score: AI scoring system returns ≥65% (user adjustable 50-95%)
Risk:Reward: Calculated stop (ATR-based or adaptive) allows minimum 2:1 R:R (user adjustable)
SHORT signals use inverse logic (bearish structure, bearish sweeps/FVGs, daily downtrend).
Adaptive Risk Management
Stop loss calculation adapts based on:
Current market regime (wider stops in volatile markets)
Volume-weighted support/resistance levels when "Adaptive" enabled
Minimum risk threshold (0.2% of price) to avoid over-tight stops
Take profit targets automatically calculate based on user-defined risk:reward ratio (default 2:1).
How To Use This Indicator
Initial Setup
Market Structure Group:
Start with default Swing Strength (5) for 1H-4H timeframes
Increase to 10-15 for daily timeframes
Decrease to 3 for scalping on 5-15min timeframes
AI Features Group:
Set "Signal Probability Threshold" to 65% for balanced approach
Increase to 75-80% for fewer but higher-quality signals
Lower to 60% in strong trending markets for more entries
Risk Management:
Enable "Adaptive Stop Loss" for dynamic support/resistance-based stops
Set "Minimum Risk:Reward" to 2.0 or higher (institutional standard)
Adjust ATR Length (14) based on timeframe (shorter for intraday)
Reading The Signals
Visual Elements:
Small triangles: Swing highs (red) and lows (green) - market structure pivots
Circles: Break of Structure - lime (bullish) or red (bearish)
Diamonds: Change of Character - cyan (bullish reversal) or orange (bearish reversal)
Boxes: Order blocks (green=bullish, red=bearish, yellow border=tested)
Transparent boxes: Fair Value Gaps (blue=bullish, purple=bearish)
Dashed/solid lines: Liquidity zones (purple=unswept, yellow=swept)
Large arrows: Trade signals with probability % (🔼 LONG / 🔽 SHORT)
Red/Green lines: Stop loss and take profit levels
Statistics Dashboard (top right by default):
Market Regime: Current classification (BULL_TREND, BEAR_TREND, RANGING, VOLATILE)
Volatility Ratio: Current vs average volatility (>1.5 = avoid trading)
Volume Regime: Current vs average volume (>1.2 = strong institutional participation)
Active Order Blocks: Number of untested institutional zones
Unfilled FVGs: Number of imbalances awaiting price return
Liquidity Zones: Unswept equal highs/lows (potential reversal areas)
HTF Alignment: Daily timeframe bias (confirm direction)
Last Signal Prob: Confidence score of most recent signal
Trading Strategy
For LONG Entries:
Wait for bullish BOS or CHoCH marker (circle/diamond below price)
Confirm market regime is BULL_TREND or RANGING (not VOLATILE)
Look for bullish liquidity sweep (yellow line below price) or unfilled bullish FVG (blue box)
When all align, watch for 🔼 LONG signal with probability ≥65%
Enter on signal candle close
Stop loss = red line, Take profit = green line
Monitor FVG fills and order block tests for possible early exit
For SHORT Entries:
Same logic in reverse (bearish structure, BEAR_TREND regime, bearish sweeps/FVGs, 🔽 SHORT signals)
Advanced Usage:
Order Block Confluence: Highest probability entries occur when price retraces to tested order block (yellow border) + FVG overlap
Liquidity Sweep Reversals: Best entries often follow immediate sweep (yellow line) then signal in opposite direction
Regime Filtering: Avoid trading during VOLATILE regime or when volatility ratio >1.5
HTF Confirmation: Only take signals when HTF Alignment matches direction (BULLISH for longs, BEARISH for shorts)
Customization:
Every visual element has individual toggle and color controls in settings:
Hide swing points if chart too cluttered
Disable BOS/CHoCH markers if only using order blocks
Turn off FVGs if focusing on liquidity sweeps
Customize colors to match your chart theme
Reposition dashboard to any corner
Why This Requires Closed-Source Protection
This indicator represents months of development integrating:
Proprietary probability weighting system - The specific point allocation (20/15/15/10/10/5) and interaction logic between factors is based on extensive backtesting across multiple markets and timeframes
Adaptive parameter optimization algorithms - How the indicator modifies ATR multipliers, decay rates, and thresholds based on regime detection uses proprietary mathematical relationships
Volume-weighted level calculations - The specific lookback periods and weighting formulas for dynamic support/resistance are optimized through statistical analysis
Multi-factor regime classification - The exact thresholds for trend strength (0.02), volatility ratio (1.3/1.5), and volume regime (1.0/1.2) are calibrated values
While the underlying concepts (SMC, order blocks, FVGs) are known, the integration methodology, scoring system, and adaptive algorithms are original intellectual property. An open-source version would allow immediate copying of years of development work, defeating the purpose of creating a professional-grade tool.
The detailed description above provides traders with complete transparency on WHAT the indicator does and HOW to use it effectively, without revealing the exact mathematical relationships and thresholds that make it effective.
Disclaimer
This indicator is an analytical tool for identifying potential trading opportunities based on institutional order flow concepts. It does not guarantee profits and should be used alongside proper risk management, fundamental analysis, and personal trading rules. Past performance does not indicate future results. Always use stop losses and never risk more than you can afford to lose.
Previous Day High, Low, and Mid (Extended)This indicator shows the previous sessions high, low, and midpoint with extended lines for the trading session.
CI Volatility UVXY Spike LevelsThis handy script tracks potential spikes for UVXY, VXX, or UVIX, pinpointing exactly where each needs to hit for 20%, 50%, 75%, or 100% gains. Check the handy levels box in the top-right corner for quick reference, plus real-time updates on your current spike progress. Say goodbye to endless manual math.
www.CIVolatility.com
AlphaTrend - Medium Term Trend Probability Indicator on TOTALESWHAT IS ALPHATREND?
AlphaTrend is a consensus-based trend identification system that combines 7 independent trend detection methodologies into a single probability score. Designed for medium-term trading (days to weeks), it aggregates diverse analytical approaches—from volatility-adjusted moving averages to statistical oscillators—to determine directional bias with quantifiable confidence.
Unlike single-indicator systems prone to false signals during consolidation, AlphaTrend requires majority agreement across multiple uncorrelated methods before generating directional signals, significantly reducing whipsaws in choppy markets.
METHODOLOGY - THE 7-INDICATOR VOTING SYSTEM
Each indicator analyzes trend from a mathematically distinct perspective and casts a vote: +1 (bullish), -1 (bearish), or 0 (neutral). The average of all 7 votes creates the final probability score ranging from -1 (strong bearish) to +1 (strong bullish).
1. FLXWRT RMA (VOLATILITY-ADJUSTED BASELINE)
Method: RMA (Running Moving Average) with ATR-based dynamic bands
Calculation:
RMA = Running MA of price over 12 periods
ATR = Average True Range over 20 periods
Long Signal: Price > RMA + ATR
Short Signal: Price < RMA - ATR
Logic: Trend confirmed only when price breaks beyond volatility-adjusted boundaries, not just the moving average itself. This filters noise by requiring momentum sufficient to overcome recent volatility.
Why it works: Standard MA crossovers generate excessive false signals in ranging markets. Adding ATR bands ensures price has genuine directional momentum, not just minor fluctuations.
Settings:
RMA Length (12): Base trend smoothing
ATR Length (20): Volatility measurement period
2. BOOSTED MOVING AVERAGE (MOMENTUM-ENHANCED TREND)
Method: Double EMA with acceleration boost factor
Calculation:
EMA1 = EMA(close, length)
EMA2 = EMA(close, length/2) // Faster EMA
Boosted Value = EMA2 + sensitivity × (EMA2 - EMA1)
Final = EMA smoothing of Boosted Value
Logic: Amplifies the difference between fast and slow EMAs to emphasize trend momentum. The boost factor (1.3) accelerates response to directional moves while subsequent smoothing prevents over-reaction.
Why it works: Traditional MAs lag price action. The boost mechanism projects trend direction forward by amplifying the momentum differential between two EMAs, providing earlier signals without sacrificing reliability.
Settings:
Length (36): Base EMA period
Boost Factor (1.3): Momentum amplification multiplier
Originality: This is a proprietary enhancement to standard double EMA systems. Most indicators simply cross fast/slow EMAs; this one mathematically projects momentum trajectory.
3. HEIKIN ASHI TREND (T3-SMOOTHED CANDLES)
Method: Heikin Ashi candles with T3 exponential smoothing
Calculation:
Heikin Ashi candles = Smoothed OHLC transformation
T3 Smoothing = Triple-exponential smoothing (Tillson T3)
Signal: T3(HA_Open) crosses T3(HA_Close)
Logic: Heikin Ashi candles filter intrabar noise by averaging consecutive bars. T3 smoothing adds additional filtering using Tillson's generalized DEMA algorithm with custom volume factor.
Why it works: Regular candlesticks contain high-frequency noise. Heikin Ashi transformation creates smoother trends, and T3 smoothing eliminates remaining whipsaws while maintaining responsiveness. The T3 algorithm specifically addresses the lag-vs-smoothness tradeoff.
Settings:
T3 Length (13): Smoothing period
T3 Factor (0.3): Volume factor for T3 algorithm
Percent Squeeze (0.2): Sensitivity adjustment
Technical Note: T3 is superior to simple EMA smoothing because it applies the generalized DEMA formula recursively, reducing lag while maintaining smooth output.
4. VIISTOP (ATR-BASED TREND FILTER)
Method: Simple trend detection using price position vs smoothed baseline with ATR confirmation
Calculation:
Baseline = SMA(close, 16)
ATR = ATR(16)
Uptrend: Close > Baseline
Downtrend: Close < Baseline
Logic: The simplest component—pure price position relative to medium-term average. While basic, it provides a "sanity check" against over-optimized indicators.
Why it works: Sometimes the simplest approach is most robust. In strong trends, price consistently stays above/below its moving average. This indicator prevents the system from over-complicating obvious directional moves.
Settings:
Length (16): Baseline period
Multiplier (2.8): ATR scaling (not actively used in vote logic)
Purpose in Ensemble: Provides grounding in basic trend logic. Complex indicators can sometimes generate counterintuitive signals; ViiStop ensures the system stays aligned with fundamental price positioning.
5. NORMALIZED KAMA OSCILLATOR (ADAPTIVE EFFICIENCY-BASED TREND)
Method: Kaufman Adaptive Moving Average normalized to oscillator format
Calculation:
Efficiency Ratio = |Close - Close | / Sum(|Close - Close |, 8)
Smoothing Constant = ER × (Fast SC - Slow SC) + Slow SC
KAMA = Adaptive moving average using dynamic smoothing
Normalized = (KAMA - Lowest) / (Highest - Lowest) - 0.5
Logic: KAMA adjusts its smoothing speed based on market efficiency. In trending markets (high efficiency), it speeds up. In ranging markets (low efficiency), it slows down. Normalization converts absolute values to -0.5/+0.5 oscillator for consistent voting.
Why it works: Fixed-period moving averages perform poorly across varying market conditions. KAMA's adaptive nature makes it effective in both trending and choppy environments by automatically adjusting its responsiveness.
Settings:
Fast Period (9): Maximum responsiveness
Slow Period (21): Minimum responsiveness
ER Period (8): Efficiency calculation window
Normalization Lookback (35): Oscillator scaling period
Mathematical Significance: Kaufman's algorithm is one of the most sophisticated adaptive smoothing methods in technical analysis. The Efficiency Ratio mathematically quantifies trend strength vs noise.
6. LÉVY FLIGHT RSI (HEAVY-TAILED MOMENTUM)
Method: Modified RSI using Lévy distribution weighting for gains/losses
Calculation:
Weighted Gain = (Max(Price Change, 0))^Alpha
Weighted Loss = (-Min(Price Change, 0))^Alpha
RSI = 100 - (100 / (1 + RMA(Gain) / RMA(Loss)))
Centered RSI = RSI - 50
Logic: Standard RSI treats all price changes linearly. Lévy Flight RSI applies power-law weighting (Alpha = 1.5) to emphasize larger moves, modeling heavy-tailed distributions observed in real market data.
Why it works: Market returns exhibit "fat tails"—large moves occur more frequently than normal distribution predicts. Lévy distributions (Alpha between 1-2) better model this behavior. By weighting larger price changes more heavily, this RSI variant becomes more sensitive to genuine momentum shifts while filtering small noise.
Settings:
RSI Length (14): Standard period
Alpha (1.5): Lévy exponent (1=linear, 2=quadratic)
MA Length (12): Final smoothing
Originality: Standard RSI uses unweighted gains/losses. This implementation applies stochastic process theory (Lévy flights) from quantitative finance to create a momentum indicator more aligned with actual market behavior.
Mathematical Background: Lévy flights describe random walks with heavy-tailed step distributions, observed in financial markets, animal foraging patterns, and human mobility. Alpha=1.5 balances between normal distribution (Alpha=2) and Cauchy distribution (Alpha=1).
7. REGULARIZED-MA OSCILLATOR (Z-SCORED TREND DEVIATION)
Method: Moving average converted to z-score oscillator
Calculation:
MA = EMA(close, 19)
Mean = SMA(MA, 30)
Std Dev = Standard Deviation(MA, 30)
Z-Score = (MA - Mean) / Std Dev
Logic: Converts absolute MA values to statistical standard deviations from mean. Positive z-score = MA above its typical range (bullish), negative = below range (bearish).
Why it works: Raw moving averages don't indicate strength—a 50-day MA at $50k vs $60k has no contextual meaning. Z-scoring normalizes this to "how unusual is current MA level?" This makes signals comparable across different price levels and time periods.
Settings:
Length (19): Base MA period
Regularization Length (30): Statistical normalization window
Statistical Significance: Z-scores are standard in quantitative analysis. This indicator asks: "Is the current trend statistically significant or just random noise?"
AGGREGATION METHODOLOGY
Voting System:
Each indicator returns: +1 (bullish), -1 (bearish), or 0 (neutral)
Total Score = Sum of all 7 votes (-7 to +7)
Average Score = Total / 7 (-1.00 to +1.00)
Signal Generation:
Long Signal: Average > 0 (majority bullish)
Short Signal: Average < 0 (majority bearish)
Neutral: Average = 0 (perfect split or all neutral)
Why Equal Weighting:
Each indicator represents a fundamentally different analytical approach:
Volatility-adjusted (RMA, ViiStop)
Momentum-based (Boosted MA, Lévy RSI)
Adaptive smoothing (KAMA)
Statistical (MA Oscillator)
Noise-filtered (Heikin Ashi T3)
Equal weighting ensures no single methodology dominates. This diversification reduces bias and improves robustness across market conditions.
ORIGINALITY - WHY THIS COMBINATION WORKS
Traditional Multi-Indicator Approaches:
Combine similar indicators (multiple MAs, multiple oscillators)
Use arbitrary thresholds for each indicator
Don't normalize signals (hard to compare RSI to MACD)
Often just "if RSI > 70 AND MACD > 0 = buy"
AlphaTrend MTPI Innovations:
Methodological Diversity: Includes volatility-adaptive (RMA), momentum-enhanced (Boosted MA), efficiency-based (KAMA), heavy-tailed statistics (Lévy RSI), and smoothed candles (HA). No redundant indicators.
Binary Voting: Each indicator reduces to simple +1/-1/0 vote, making aggregation transparent and preventing any indicator from overwhelming the consensus.
Medium-Term Optimization: Parameter choices (12-36 period averages) specifically target multi-day to multi-week trends, not scalping or long-term positioning.
Advanced Mathematics: Incorporates Tillson T3, Kaufman Efficiency Ratio, Lévy distributions, and statistical z-scoring—not just basic MAs and RSIs.
No Overfit Risk: With 7 diverse components voting equally, the system can't overfit to any specific market regime. If trending markets favor KAMA, but choppy markets favor Boosted MA, the ensemble stays robust.
Why 7 Indicators, Not 3 or 10:
Fewer than 5: Insufficient diversification, single indicator failures impact results heavily
More than 9: Diminishing returns, redundancy increases, computational load grows
7 provides: Odd number (no ties), sufficient diversity, manageable complexity
VISUAL COMPONENTS
1. Bar Coloring:
Cyan bars: Bullish consensus (average score > 0)
Magenta bars: Bearish consensus (average score < 0)
No color: Neutral (score = 0 or date filter disabled)
2. MTPI Summary Table (Bottom Center):
MTPI Signal: Current directional bias (LONG/SHORT/NEUTRAL)
Average Score: Precise consensus reading (-1.00 to +1.00)
3. Indicator Status Table (Bottom Right):
Shows all 7 individual indicator scores
Score column: +1 (bullish), -1 (bearish), 0 (neutral)
Signal column: Text interpretation of each vote
Color-coded cells: Cyan (long), Magenta (short), Gray (neutral)
HOW TO USE
For Swing Trading (Recommended - Days to Weeks):
Entry Signals:
Strong Long: 5+ indicators bullish (score ≥ 0.71)
Standard Long: 4+ indicators bullish (score ≥ 0.57)
Weak Long: Simple majority (score > 0) — use with caution
Exit Signals:
Hard Stop: Score flips negative (consensus reverses)
Partial Take Profit: Score drops to +0.30 or below (weakening)
Trailing Stop: Use ATR-based stop below entry
Position Sizing:
Strong signals (|score| > 0.7): Full position
Moderate signals (0.4-0.7): 50-75% position
Weak signals (< 0.4): 25-50% or skip
For Trend Confirmation:
Use alongside your primary strategy for confluence
Only take trades when AlphaTrend agrees with your analysis
Avoid counter-trend trades when score is extreme (|score| > 0.7)
Best Timeframes:
4H: Primary timeframe for swing trading
1D: Position trading and major trend identification
1H: Active trading (shorter hold periods)
< 1H: Not recommended (designed for medium-term)
Market Conditions:
Trending markets: System excels (consensus emerges quickly)
Ranging markets: Expect mixed signals (score oscillates near zero)
High volatility: RMA and ViiStop provide stabilization
Low volatility: KAMA and Boosted MA maintain responsiveness
SETTINGS EXPLAINED
General Settings:
Use Date Filter: Enable/disable historical backtesting range
Start Date: When to begin signal generation (default: Jan 1, 2018)
Flxwrt RMA Settings:
RMA Length (12): Base trend smoothing
ATR Length (20): Volatility measurement period
Source: Price input (default: close)
Boosted MA Settings:
Length (36): Base EMA period
Boost Factor (1.3): Momentum amplification
Source: Price input
Heikin Ashi Settings:
Percent Squeeze (0.2): Sensitivity adjustment
T3 Factor (0.3): Tillson volume factor
T3 Length (13): Smoothing period
ViiStop Settings:
Length (16): Baseline period
Multiplier (2.8): ATR scaling
Source: Price input
KAMA Settings:
Fast Period (9): Maximum responsiveness
Slow Period (21): Minimum responsiveness
ER Period (8): Efficiency calculation
Normalization Lookback (35): Oscillator scaling
Levy RSI Settings:
RSI Length (14): Standard period
Alpha (1.5): Lévy exponent (power-law weighting)
MA Length (12): Final smoothing
Source: Price input
MA Oscillator Settings:
Length (19): Base MA period
Regularize Length (30): Z-score normalization window
PERFORMANCE CHARACTERISTICS
Strengths:
✅ Reduced whipsaws vs single indicators
✅ Works across varying market conditions (adaptive components)
✅ Transparent methodology (see every vote)
✅ Customizable to trading style via timeframe selection
✅ No curve-fitting (equal weighting, no optimization)
Limitations:
⚠️ Medium-term focus (not for scalping or very long-term)
⚠️ Lagging by design (consensus requires confirmation)
⚠️ Less effective in violent reversals (momentum carries votes)
⚠️ Requires clean price data (gaps/thin volume can distort)
ALERTS & AUTOMATION
No built-in alerts in current version (visual-only indicator). Users can create custom alerts based on:
Bar color changes (cyan to magenta or vice versa)
Average score crossing above/below thresholds
Specific indicator status changes in the table
BEST PRACTICES
Risk Management:
Never risk more than 1-2% per trade regardless of score
Use stop losses (ATR-based recommended)
Scale positions based on signal strength
Don't average down on losing positions
Combining with Other Analysis:
✅ Support/Resistance levels for entries
✅ Volume confirmation (accumulation/distribution)
✅ Market structure (higher highs/lower lows)
✅ Volatility regimes (adjust position size)
❌ Don't combine with redundant trend indicators (adds no value)
❌ Don't override strong consensus with gut feeling
❌ Don't use on news-driven spikes (wait for stabilization)
Backtesting Notes:
Use "Date Filter" to test specific periods
Forward-test before live deployment
Remember: consensus systems perform best in trending markets, expect reduced edge in ranges
IMPORTANT NOTES
Not a standalone strategy - Use with proper risk management
Requires clean data - Works best on liquid markets with tight spreads
Medium-term by design - Don't expect scalping signals
No magic - No indicator predicts the future; this shows current trend probability
Diversification within - The 7-component ensemble IS the diversification strategy
Not financial advice. This indicator identifies medium-term trend probability based on multi-component consensus. Past performance does not guarantee future results. Always use proper risk management and position sizing.
Previous Day High, Low, and MidThis indicator will draw out levels for the previous sessions highs and lows as well as the middle point between the two. Might not work with indices
SMMA Strategy [SMMA ULTIMATE]SMMA 21/50/200 + RSI — M5/M15 (Rule-marked entries & exits)
Release Notes (EN)
Version: 1.0 (Pine v6 — Indicator)
Date: 14 Oct 2025
Type: Multi-TF overlay indicator with rule-based entry/exit markers and optional runtime alerts
🚀 Summary
A disciplined multi-timeframe scanner for M5 and M15 that highlights rule-driven setups (R1…R4) around SMMA 21/50/200, RSI (buy > 52 / sell < 48), directional VWAP, volume, and ATR activity.
It also simulates ATR-based TP/SL/Break-Even to provide immediate visual feedback and tags each trade idea with the origin rule.
✨ Highlights
• Full MTF stack (M5 & M15) with dedicated series (price, volume, SMMA, ATR, VWAP, RSI) and lookahead_off to avoid repaint.
• 4 modular entry rules (enable/disable independently):
◦ R1: Price crosses the max/min of SMMA(21/50/200) + RSI filter + market OK.
◦ R2: Touch of SMMA21 (pullback) + trend alignment + RSI + market OK.
◦ R3: Three candles impulse + engulfing reversal + RSI + market OK.
◦ R4: SMMA21/SMMA50 cross (structural momentum) + market OK.
• Stackable filters (toggle): Trend (price vs SMMA200), Directional VWAP (price vs VWAP + slope), Volume (Vol > MA×k), ATR activity (ATR > MA(ATR,20)×k).
• RSI thresholds: BUY if RSI > 52, SELL if RSI < 48 (per TF).
• ATR exit simulation: SL = k×ATR, TP = k×ATR, Break-Even armed after ATR gain (return to entry → BE exit).
• Clear rule tags: Entry/exit markers carry R1…R4 for immediate provenance.
• Optional runtime alerts: Human-readable messages on entries and exits, per TF and rule.
🔧 Key Inputs
General
• Price source for display: chart candles / force regular / force Heikin Ashi.
• Lengths: SMMA 21/50/200, RSI (14), ATR (14), Volume MA (20).
• RSI thresholds: Buy > 52, Sell < 48.
Filters (on/off)
• Trend (price vs SMMA200).
• Directional VWAP (price relative to VWAP and VWAP slope).
• ATR activity gate.
• Volume gate (Volume > MA×multiplier).
Rules (on/off)
• Enable R1/R2/R3/R4 individually.
Exit simulation
• Use ATR stops (SL/TP multipliers).
• Break-Even (armed by ATR progress).
Alerts
• Enable runtime alerts to fire alert() at bar close.
🧠 Rule Logic (condensed)
• R1 BUY/SELL: Cross of max/min(SMMA21,50,200) + RSI gate + all selected filters OK.
• R2 BUY/SELL: Touch of SMMA21 + price aligned vs SMMA50/200 + RSI + filters OK.
• R3 BUY/SELL: Three consecutive bars in one direction + engulfing opposite + RSI + filters OK.
• R4 BUY/SELL: SMMA21/SMMA50 crossover + filters OK.
Entry priority per TF: R1 > R4 > R2 > R3.
🔔 Runtime Alerts
When enabled, the script emits close-of-bar alerts with TF and rule tag:
• 🚀 M5/M15 ENTRY LONG (R#)
• 🔻 M5/M15 ENTRY SHORT (R#)
• ✅ M5/M15 EXIT TP (R#)
• ❌ M5/M15 EXIT SL (R#)
• 🟨 M5/M15 EXIT BE (R#)
(You can still build custom UI alerts if you need additional combinations.)
🖼 Visuals
• SMMA 21/50/200 and VWAP (green when price above, red below).
• Plotshape per rule and exit type (TP/SL/BE) with R1…R4 tags on M5 and M15.
• Optional Heikin Ashi for display (core MTF calculations remain consistent).
🔒 Robustness & No-Repaint Notes
• All MTF request.security calls use lookahead_off.
• Pattern logic (three bars, engulfing) is evaluated on bar close.
• ATR/TP/SL/BE are indicator-level simulations using the chart’s H/L/Close (standard intrabar limitations).
⚠️ Limitations & Tips
• This is an indicator, not a strategy: no orders are sent; exits are simulated for visualization.
• Signals are generated on bar close.
• MTF signals synchronize to the chart TF’s close, not intrabar ticks.
ICT AMD Model – Full Engine [Forex.lk] (Phase 1–4)⚙️ ICT AMD Model – Full Engine (Phase 1–4)
By Forex.lk | info@forex.lk
The ICT AMD Model – Full Engine is a
structured market-phase framework developed to help traders recognize the natural rhythm of price delivery.
It maps the evolving cycle of Accumulation → Manipulation → Distribution to highlight when the market is building, faking, or delivering directional intent.
The indicator automatically adapts to your selected timeframes, monitors bias alignment, and presents a clean visual roadmap of market behavior in real time.
With clear on-chart highlights and a compact dashboard, it assists traders in timing entries and exits based on phase context and higher-timeframe direction.
Designed for traders who study market structure, timing, and precision execution within the AMD model.
It’s a practical, research-driven visual aid—simple to interpret, powerful in insight.
Developed by Forex.lk
📩 Contact : info@forex.lk
🌐 www.forex.lk
VWAP + EMA + RSI + MACD Confluence (Options Trader)VWAP
EMAs (9, 21, 50)
RSI
MACD
and clear visual + alert signals for option-style entries (bullish = calls, bearish = puts).
Here’s what it’ll do visually:
✅ Plot EMAs (9, 21, 50)
✅ Plot VWAP
✅ Show background color when confluence aligns for bullish or bearish entries
✅ Add optional alerts (so you can set triggers)
✅ Display RSI + MACD panels for confirmation
Logic:
Bullish (“Call”) signal:
Price > VWAP and > EMA50
EMA9 > EMA21
MACD line > signal line
RSI > 50
Bearish (“Put”) signal:
Price < VWAP and < EMA50
EMA9 < EMA21
MACD line < signal line
RSI < 50
Measured Pattern Move (Bulkowski) [SS]Hey everyone,
This is the Measured Pattern Move using Bulkowski's process for measured move calculation.
What the indicator does:
The indicator has the associated measured move across 20 of the most common and frequent Bulkowski patterns, including:
Double Bottom / Adam Eve Bottom
Double Top / Adam Eve Top
Inverse Head and Shoulders
Bear Flag
Bull Flag
Horn Bottom
Horon Top
Broadening Top
Descending Broadening Wedge
Broadening Bottoms
Broadening Tops
Cup and Handle
Inverted cup and handle
Diamond Bottom
Diamond Top
Falling Wedge
Rising Wedge
Pipe Bottom
Pipe Top
Head and Shoulders
It will calculate the measured move according to the Bulkowski process.
What is the Bulkowski Process?
Each move has an associated continuation percentage, which Bulkowski has studied, analyzed and concluded statistically.
For example, Double tops have a continuation percent of 54%. Bear flags, 47%. These are "constants" that are associated with the pattern.
Bulkowski applies them to the daily, but how I have formulated this, it can be used on all timeframes, and with the constant, it will correctly calculate the measured move of the pattern.
What this indicator DOES NOT DO
This indicator will not identify the pattern for you.
I tried this using Dynamic Time Warping (DTW) using my own pre-trained Bulkowski model in R. I was successfully able to get Pinescript to calculate DTW which was amazing! But applying it to all these patterns actually went over the execution time limit, which is understandable.
As such, you will need to identify the pattern yourself, then use this indicator to hilight the pattern and it will calculate the measured move based on the constant and the pattern range.
Let's look at some examples:
Use examples
Double bottom / adam eve bottom on SPY on the 1-Minute chart
Adam and Eve Double Bottom QQQ 1-Hour Chart
Adam Eve Double Bottom MSFT Daily Chart
Bearish Head and Shoulders Pattern MSFT Daily
You get the point.
How to use the indicator
To use the indicator, identify the pattern of interest to you.
Then, highlight the pattern using the indicator (it will ask you to select start time of the pattern and end time of the pattern). The indicator will then highlight the pattern and calculate the measured move, as seen in the examples above.
Best approaches
To make the most of the indicator, its best to draw out your pattern and wait for an actual break, the point of the break is usually the end of the pattern formation.
From here, you will then apply this indicator to calculate the expected up or down move.
Let me show you an example:
Here we see CME_MINI:ES1! has made an Adam bottom pattern. We know the Eve should be forming soon and it indeed does:
We mark the top of the pattern like so:
Then we use our Measured move indicator to calculate the measured move:
Measured move here for CME_MINI:ES1! is 6,510.
Now let's see....
Voila!
Selecting the Pattern
After you highlight the selected pattern, in the indicator settings, simply select the type of pattern it is, for example "head and shoulders" or "Broadening wedge", etc.
The indicator will then adjust its measurements to the appropriate constant and direction.
Concluding remarks
That is the indicator!
It is helpful for determining the actual projected move of a pattern on breakout.
Remember, it does not find the pattern for you , you are responsible for identifying the pattern. But this will calculate the actual TP of the pattern for you, without you having to do your own calculations.
I hope you find it useful, I actually use this indicator every day, especially on the lower timeframes!
And you will find, the more you use it, the better you get at recognizing significant patterns!
If you are not aware of these patterns, Bulkowski lists all of this information freely accessible on his website. I cannot link it here but you can just Google him and he has graciously made his information public and free!
That's it, I hope you enjoy and safe trades!
Disclaimer
This is not my intellectual property. The pattern calculations come from the work of Thomas Bulkowski and not myself. I simply coded this into an indicator using his publicly accessible information.
You can get more information from Bulkowski's official website about his work and patterns.
MicroX_Trader Psychology Simulatorيحاكي هذا المؤشر مشاعر التفاؤل والخوف لدى المتداول.
It simulates the feelings of optimism and fear in a trader
SP2L Strategy Tool by Rava AcademyRava Academy - SP2L Strategy Tool
This indicator has been designed and developed by Rava Academy to implement the SP2L trading strategy. The primary goal of this tool is to automate the process of identifying potential trade setups based on this specific strategy, helping traders to save valuable time and reduce analytical errors.
Key Features:
Automatic Setup Detection: The indicator automatically scans the chart for conditions that align with the SP2L strategy rules.
Clear Visual Signals: It provides straightforward visual cues on the chart, using arrows to indicate potential setups, which simplifies the decision-making process.
Time-Saving Analysis: This tool is designed to minimize the need for manual and repetitive analysis, allowing traders to focus on other aspects of their trading plan.
Multi-Market Compatibility: It is optimized for use in various financial markets, including Forex and Cryptocurrencies.
How to Use:
Green Arrow (▲): Indicates a potential buy setup according to the strategy's rules. Traders should look for their own confirmation before entering a trade.
Red Arrow (▼): Indicates a potential sell setup according to the strategy's rules. Traders should look for their own confirmation before entering a trade.
IMPORTANT NOTE:
This indicator is a powerful assistive tool, not a standalone "buy/sell" signal generator. For best results, it is essential to combine its signals with your own analysis of market structure, price action, and a robust risk management plan. It should be used to augment, not replace, your trading judgment.
About Rava Academy:
This indicator is a contribution to the trading community from Rava Academy. We specialize in financial market education, building custom trading tools, and converting strategies into intelligent indicators.
For more educational content and trading tools, follow us on Instagram: @RavaFinance
Disclaimer:
Trading in financial markets involves significant risk. This tool is provided for educational and analytical purposes only and should not be considered financial advice. All trading decisions, profits, and losses are the sole responsibility of the user. Past performance is not indicative of future results.
