Real Relative Strength Indicator### What is RRS (Real Relative Strength)?
RRS is a volatility-normalized relative strength indicator that shows you – in real time – whether your stock, crypto, or any asset is genuinely beating or lagging the broader market after adjusting for risk and volatility. Unlike the classic “price ÷ SPY” line that gets completely fooled by volatility regimes, RRS answers the only question that actually matters to professional traders:
“Is this ticker moving better (or worse) than the market on a risk-adjusted basis right now?”
It does this by measuring the excess momentum of your ticker versus a benchmark (SPY, QQQ, BTC, etc.) and then dividing that excess by the average volatility (ATR) of both instruments. The result is a clean, centered-around-zero oscillator that works the same way in calm markets, crash markets, or parabolic bull runs.
### How to Use the RRS Indicator (Aqua/Purple Area Version) in Practice
The indicator is deliberately simple to read once you know the rules:
Positive area (aqua) means genuine outperformance.
Negative area (purple) means genuine underperformance.
The farther from zero, the stronger the leadership or weakness.
#### Core Signals and How to Trade Them
- RRS crossing above zero → one of the highest-probability long signals in existence. The asset has just started outperforming the market on a risk-adjusted basis. Enter or add aggressively if price structure agrees.
- RRS crossing below zero → leadership is ending. Tighten stops, take partial or full profits, or flip short if you trade both sides.
- RRS above +2 (bright aqua area) → clear leadership. This is where the real money is made in bull markets. Trail stops, add on pullbacks, let winners run.
- RRS below –2 (bright purple area) → clear distribution or capitulation. Avoid new longs, consider short entries or protective puts.
- Extreme readings above +4 or below –4 (background tint appears) → rare, very high-conviction moves. Treat these like once-a-month opportunities.
- Divergence (not plotted here, but easy to spot visually): price making new highs while the aqua area is shrinking → distribution. Price making new lows while the purple area is shrinking → hidden buying and coming reversal.
#### Best Settings by Style and Asset Class
For stocks and ETFs: keep benchmark as SPY (or QQQ for tech-heavy names) and length 14–20 on daily/4H charts.
For crypto: change the benchmark to BTCUSD (or ETHUSD) immediately — otherwise the reading is meaningless. Length 10–14 works best on 1H–4H crypto charts because volatility is higher.
For day trading: drop length to 10–12 and use 15-minute or 5-minute charts. Signals are faster and still extremely clean.
#### Highest-Edge Setups (What Actually Prints Money)
- RRS crosses above zero while price is still below a major moving average (50 EMA, 200 SMA, etc.) → early leadership, often catches the exact bottom of a new leg up.
- RRS already deep aqua (+3 or higher) and price pulls back to support without RRS dropping below +1 → textbook add-on or re-entry zone.
- RRS deep purple and suddenly turns flat or starts curling up while price is still falling → hidden accumulation, usually the exact low tick.
That’s it. Master these few rules and the RRS becomes one of the most powerful edge tools you will ever use for rotation trading...
Oszillatoren
REMS - Deep SynergyThis is a more flexible version of the REMS Synergy indicator. Like other indicators in the REMS family, it builds upon the foundations assessing the relationships between RSI, EMAs, MACDs, and Stochastic RSI across multiple timeframes. Designed to help traders identify less frequent, but high probability entries across 2 time frames. Uses 3 levels of confluence indicators for both long and short moves.
Features 3 levels of confluence across 2 timeframes. All 3 levels allow filtering of any combination of REMS filters. Features more options and customization than previous REMS Synergy.
Includes VWAP and 4 EMAs as optional visual representations.
Includes 'Enhanced Candles' than can colour code candlesticks for better visual identification. (off by default)
Originally designed with 5 minute and 2 minute timeframes in mind, and pairs well with REMS First Strike and/or REMS Snap Shot indicators.
This version features no hard-coded inputs and allows for more freedom than previous version. With the added flexibility comes the ability for the indicator to be more easily stacked.
Aroon + Chaiki OscillatorThis is an Chaiki Oscillator that facilitates more straightforward trendline analysis utilizing the Aroon setup for bars.
This is a simple Pinescript designed for incorporation into your charting analysis.
As always, none of this is investment or financial advice. Please do your own due diligence and research.
Pythia — 33 LITEPythia — v33 (Lite Edition)
Core Structural Divergences and Movement Context
Overview
Pythia Lite is the entry point into the Pythia ecosystem.
It shows how the structure of movement evolves: where divergences form, where impulse weakens, and where instability appears due to mismatches between price and internal energy.
The computational engine is inherited from the Standard and Full editions, but most parameters are fixed or simplified, making Lite clean, minimalistic, and easy to use.
Configuration
You control only the essential parameters:
• MACD settings
• pivot sensitivity
• basic divergence and trap visualization
All Flow, TTC, and energy thresholds are fixed internally and optimized for common instruments (Forex, gold, indices, crypto).
What Pythia Lite Displays
• micro- and macro-divergences
• TTC grids showing zones where movement often loses impulse
• minimal Flow context (built-in, no sensitivity adjustments)
• compact EnergyTrap / PriceTrap markers
• OR-impulse spikes
Lite provides a clean structural skeleton: where the market diverges from its own energy, where impulse becomes unstable, and where movement behaves atypically.
Key Modules
1. Divergences (micro / macro)
Identify small and large structural discrepancies between price and MACD.
Settings are reduced to essentials: MACD lengths, pivot sensitivity, and minimal tolerance controls.
2. TTC Grids
A base model that highlights zones where impulse commonly collapses.
All parameters are fixed internally to keep Lite simple and clutter-free.
3. Movement Traps (minimal mode)
EnergyTrap and PriceTrap are displayed as compact dots without extended labels.
Colors and transparency are simplified to avoid over-visualization.
4. OR-Impulses
Mark rare bursts of momentum caused by abrupt structural anomalies.
5. Flow Context
Flow is included internally in a simplified form — no sensitivity controls or separate visual states.
It acts as an automatic background component of the TTC/divergence context.
Release Notes
Pythia v33 (Lite Edition) is designed for traders who need a lightweight structural tool without alerts or advanced modules.
Extended energy logic, alerts, news-impulse detection, and channel geometry are part of the Standard and Full editions.
Lite highlights where movement begins to break — without clutter and without unnecessary complexity.
Interpretation of Chart Markers (1–15)
(with version availability: Full / Standard / Lite)
________________________________________
1 — Pre-Flow Divergence
What it is:
A divergence displayed in a pale version of the trend color, showing early price-energy discrepancy while price moves in a strong impulse.
Why it matters:
Signals that a regular divergence may be ignored because the market still has enough momentum to continue without correction.
How to use:
Not a reversal entry.
Wait for impulse weakening or confirmation from traps, micro-divergences, TTC, or the Catcher zone.
Versions:
(Full, Standard — limited, Lite — not included)
________________________________________
2 — Regular Bearish Divergence
What it is:
A classic discrepancy between price and momentum.
Why it matters:
Shows weakening of the current swing and increases the probability of correction or reversal.
How to use:
Useful for exits or timing counter-trend entries.
Best when combined with traps, TTC, or the Catcher zone.
Versions:
(Full, Standard, Lite)
________________________________________
3 — Divergence Energy Indicator
What it is:
A marker showing how strong the divergence energy load is.
Why it matters:
Helps separate weak divergences from structurally significant ones.
How to use:
High-energy divergences carry greater reversal potential.
Versions:
(Full, Standard — no, Lite — no)
________________________________________
4 — Trap Cloud: Mass Without Impulse
What it is:
A cloud indicating significant trade mass with minimal price progress.
Why it matters:
Shows hidden exhaustion or buildup before a directional change.
How to use:
When combined with divergences or the Catcher zone, attention increases.
Lite uses micro-markers instead of clouds.
Versions:
(Full, Standard, Lite — limited)
________________________________________
5 — Trap Cloud: Impulse Without Mass
What it is:
Shows small clusters of relatively large trades producing impulse without depth.
Why it matters:
Often indicates unstable or misleading moves.
How to use:
Strengthens reversal probability when combined with divergences.
Versions:
(Full, Standard, Lite — limited)
________________________________________
6 — Post-Impulse Oscillation Window
What it is:
The time window after an impulse-shift marker (7).
Why it matters:
Shows whether the new impulse strengthened or faded.
How to use:
Supports reading the stability of short-term structural breaks.
Versions:
(Full, Standard — no, Lite — no)
________________________________________
7 — Instant Impulse-Shift Marker
What it is:
A marker showing a sudden change in structural impulse.
Why it matters:
These points often precede short-term acceleration or instability.
How to use:
Especially meaningful when appearing near traps or divergences.
Versions:
(Full, Standard — no, Lite — no)
________________________________________
8 — Growing Price–Energy Discrepancy
What it is:
Marks increasing separation between price progress and energy behavior.
Why it matters:
Often precedes divergence formation or weakening of movement.
How to use:
Use as an early attention signal, especially when clusters appear.
Versions:
(Full, Standard — no, Lite — no)
________________________________________
9 — Collapsed Micro-Divergences
What it is:
Micro-divergences that formed but collapsed.
Why it matters:
Clusters of such points often reflect hidden weakness.
How to use:
Multiple collapsed micro-divs frequently precede structural slowing.
Versions:
(Full, Standard, Lite)
________________________________________
10 — Low-Energy Uncertainty Cloud
What it is:
A weak instability cloud similar to marker 7 but less pronounced.
Why it matters:
Marks zones where the market struggles with direction.
How to use:
Strengthens reversal context when inside a Catcher zone.
Versions:
(Full, Standard — no, Lite — no)
________________________________________
11 — Catcher Zone Marker
What it is:
Marks the moment a Catcher zone was created.
Why it matters:
Even if the zone collapses, the marker remains as evidence of structural preparation.
How to use:
If traps or divergences appear afterward, reversal probability increases.
Versions:
(Full, Standard, Lite)
________________________________________
12 — Catcher Zone (Forecast Window for Divergence)
What it is:
A dynamic zone predicting where a divergence is most likely to appear.
Why it matters:
Helps anticipate reversal signals earlier and with better timing.
How to use:
Divergences born inside the zone are significantly stronger.
Standard and Lite preserve full functionality with simplified visuals.
Versions:
(Full, Standard — limited visuals, Lite — limited visuals)
________________________________________
13 — Divergence Probation Start
What it is:
Beginning of the window where divergence must prove itself.
Why it matters:
If no structural reaction appears, the signal weakens.
How to use:
Watch traps, micro-divs, and impulse slowdown during this interval.
Versions:
(Full, Standard — limited, Lite — not included)
________________________________________
14 — Divergence Probation End
What it is:
The final point where divergence should manifest.
Why it matters:
If no reaction occurs, the market transitions into Flow and the divergence becomes irrelevant.
How to use:
If price does not react by this point — ignore the divergence.
Versions:
(Full, Standard — limited, Lite — not included)
________________________________________
15 — Catcher HUD (Forecast Accuracy Panel)
What it is:
A panel showing how many divergences the Catcher predicted and how many were confirmed by the market.
Why it matters:
Helps tune the indicator without guesswork.
How to use:
Adjust parameters and observe how HUD accuracy changes instantly.
Optimizes Pythia for each instrument and timeframe.
Versions:
(Full, Standard, Lite)
________________________________________
Note from the Developers
Pythia marks the exact areas where the market can mislead you.
So here is a simple and practical rule:
Do not step into the places where the markers stand.)
Volume Pressure OscillatorThe Volume Pressure Oscillator (VPO) is a momentum-based indicator that measures the directional pressure of cumulative volume delta (CVD) combined with price efficiency. It oscillates between 0 and 100, with readings above 50 indicating net buying pressure and readings below 50 indicating net selling pressure.
The indicator is designed to identify the strength and sustainability of volume-driven trends while remaining responsive during consolidation periods.
How the Indicator Works
The VPO analyzes volume flow by examining price action at lower timeframes to build a Cumulative Volume Delta (CVD). For each chart bar, the indicator looks at intrabar price movements to classify volume as either buying volume or selling volume. These classifications are accumulated into a running total that tracks net directional volume.
The indicator then measures the momentum of this CVD over both short-term and longer-term periods, providing responsiveness to recent changes while maintaining awareness of the broader trend. These momentum readings are normalized using percentile ranking, which creates a stable 0-100 scale that works consistently across different instruments and market conditions.
A key feature is the extreme zone persistence mechanism. When the indicator enters extreme zones (above 80 or below 20), it maintains elevated readings as long as volume pressure continues in the same direction. This allows the VPO to stay in extreme zones during strong trends rather than quickly reverting to neutral, making it useful for identifying sustained volume pressure rather than just temporary spikes.
What Makes This Indicator Different
While many indicators measure volume or volume delta, the VPO specifically measures how aggressively CVD is currently changing and whether that pressure is being sustained. It's the difference between knowing "more volume has accumulated on the buy side" versus "buying pressure is intensifying right now and shows signs of continuation."
1. Focus on CVD Momentum, Not CVD Levels
Most CVD indicators display the cumulative volume delta as a line that trends up or down indefinitely. The VPO is fundamentally different - it measures the slope of CVD rather than the absolute level. This transforms CVD from an unbounded cumulative metric into a bounded 0-100 oscillator that shows the intensity and direction of current volume pressure, not just the historical accumulation.
2. Designed to Stay in Extremes During Trends
Unlike traditional oscillators that treat extreme readings (above 80 or below 20) as overbought/oversold reversal signals, the VPO is engineered to oscillate within extreme zones during strong trends. When sustained buying or selling pressure exists, the indicator remains elevated (e.g., 80-95 or 5-20) rather than quickly reverting to neutral. This makes it useful for trend continuation identification rather than exclusively for reversal trading.
3. Percentile-Based Normalization
The VPO uses percentile ranking over a lookback window, which provides consistent behavior across different instruments, timeframes, and volatility regimes without constant recalibration.
4. Dual-Timeframe Momentum Synthesis
The indicator simultaneously considers short-term CVD momentum (responsive to recent changes) and longer-term CVD momentum (tracking trend direction), weighted and combined with a slow-moving trend bias. This multi-timeframe approach helps it stay responsive in ranging markets while maintaining context during trends.
How to Use the Indicator
Understanding the Zones:
80-100 (Strong Buying Pressure): CVD momentum is strongly positive. In trending markets, the indicator oscillates within this zone rather than immediately reverting to neutral. This suggests sustained accumulation and trend continuation probability.
60-80 (Moderate Buying): Positive volume pressure but not extreme. Suitable for identifying pullback entry opportunities within uptrends.
40-60 (Neutral Zone): Volume pressure is balanced or unclear. No strong directional edge from volume. Often seen during consolidation or trend transitions.
20-40 (Moderate Selling): Negative volume pressure developing. May indicate distribution or downtrend continuation setups.
0-20 (Strong Selling Pressure): CVD momentum is strongly negative. During downtrends, sustained readings in this zone suggest continued distribution and downside follow-through probability.
Practical Applications:
Trend Confirmation: When price makes new highs/lows, check if VPO confirms with similarly elevated readings. Divergences (price making new highs while VPO fails to reach prior highs) may indicate weakening momentum.
Range Trading: During consolidation, the VPO typically oscillates between 30-70. Readings toward the low end of the range (30-40) may present accumulation opportunities, while readings at the high end (60-70) may indicate distribution zones.
Extreme Persistence: If VPO reaches 90+ or drops below 10, this indicates exceptional volume pressure. Rather than fading these extremes immediately, monitor whether the indicator stays elevated. Sustained extreme readings suggest strong trend continuation potential.
Context with Price Action: The VPO is most effective when combined with price action or other orderflow indicators. Use the indicator to gauge whether volume is confirming or contradicting.
What the Indicator Does NOT Do:
It does not provide specific entry or exit signals
It does not predict future price direction
It does not guarantee profitable trades
It should not be used as a standalone trading system
Settings Explanation
Momentum Period (Default: 14)
This parameter controls the lookback period for CVD rate-of-change calculations.
Lower values (5-10): Make the indicator more responsive to recent volume changes. Useful for shorter-term trading and more active oscillation. May produce more whipsaws in choppy markets.
Default value (14): Provides balanced responsiveness while filtering out most noise. Suitable for swing trading and daily timeframe analysis.
Higher values (20-50): Create smoother readings and focus on longer-term volume trends. Better for position trading and reducing false signals, but with slower reaction to genuine changes in volume pressure.
Important Notes:
This indicator requires intrabar data to function properly. On some instruments or timeframes where lower timeframe data is not available, the indicator may not display.
The indicator uses request.security_lower_tf() which has a limit of intrabars. On higher timeframes, this provides extensive history, but on very low timeframes (<1-minute charts), the indicator may only cover limited historical bars.
Volume data quality varies by exchange and instrument. The indicator's effectiveness depends on accurate volume reporting from the data feed.
PyTai Top/Bottom Finder v0.1When the average StochRSI line rises high (near or above 80), it often signals the asset's price is approaching the peak or end of an uptrend, as momentum becomes overextended across multiple timeframes—aligning with your view on run endings. Conversely, a low average (near or below 20) suggests exhaustion in a downtrend, hinting at potential bottoms. The cluster columns amplify this: wide green bars (high positive netScore) show broad oversold agreement for bullish reversals, while red bars indicate overbought consensus for bearish turns. However, StochRSI can remain extreme in strong trends, so combine with price action or volume to avoid false signals; backtest on your assets to refine thresholds, as shorter smoothing (e.g., 1-3) increases sensitivity but noise.
Directional Movement Index - HistogramModified standard DMI to have histogram instead of standard lines
RSI-ma Wave Sensor (Free ver.)RSI-ma Wave Sensor is a 3-line RSI-based oscillator (Main / Middle / Wave) that shows trend direction, momentum and higher timeframe context in a single pane.
Compared with many classic MA/RSI tools it aims to:
• react with very low lag (almost real-time feeling)
• detect trend direction early
• avoid “overbought/oversold sticking” so you can hold calmly until the trend really starts to end
This Free version is a DAY trade preset for the 15m chart:
• Main = 14, Middle = EMA 9, Wave = EMA 28
• 1h higher timeframe wave sensor included
• good for learning / testing how to read trends with RSI waves
Multi-factor momentum & flow confluence oscillator
MarketExploiter
Momentum–flow confluence oscillator.
Overview
This indicator combines momentum structure, money-flow behavior, trend context, and divergence detection into a single visual tool. It helps highlight when momentum is strengthening, weakening, or beginning to shift direction.
Components
• A smoothed momentum curve that visualizes acceleration and exhaustion.
• Money-flow bias reflecting underlying buying or selling pressure.
• Momentum-shift dots that appear only when several factors align, such as momentum inflection, curve behavior, and supportive flow.
• Bullish and bearish divergence detection between price and the momentum curve.
• A trend panel offering broader directional context.
How to Use
Signals are most effective when they appear in the direction of the trend panel and when money-flow conditions support the move. Divergence signals may highlight early strength or weakness relative to price action. The indicator is intended for context and confirmation rather than standalone entries. Works across all liquid markets and timeframes.
Notes
Non-repainting. Suitable for momentum assessment, trend reading, and identifying potential inflection zones.
Best Metal to Sell → More BTCWhichever precious metal has outperformed Bitcoin the most over the last 21 days (by >4%) is showing short-term strength → sell a small slice of that metal and rotate into BTC.
Orange = trim some gold → buy BTC
Grey = trim some silver → buy BTC
Black = no clear edge → hold
This is a gradual, disciplined rebalancing tool for anyone holding physical gold & silver who wants to slowly increase their BTC exposure on relative strength spikes — without ever going “all-in”.
You decide the pace: 1% per signal, pause anytime, or stop when you’ve reached your personal comfort level of BTC allocation.
2020–2025 backtest (weekly 1% rotations):
$200k metals → 18.4 BTC + $0 metals left = $1.68 million
HODL metals only = $320k
HODL BTC from day one = ~$1.4 million
It’s not about beating BTC every cycle — it’s about turning stagnant metals into more sats, at your own pace.
RSI + BB + RSI Advanced MTF Panel//@version=6
indicator(title="RSI + BB + RSI Advanced MTF Panel", shorttitle="RSI + BB + RSI Advance MTF Panel", format=format.price, precision=2, overlay=false)
bb_group = "BB (Price Overlay)"
bb_length = input.int(50, minval=1, group = bb_group)
bb_maType = input.string("SMA", "Basis MA Type", options = , group = bb_group)
bb_src = input.source(close, title="Source", group = bb_group)
bb_mult = input.float(0.2, minval=0.001, maxval=50, title="StdDev", group = bb_group)
BasisColor = input.color(color.rgb(163, 41, 245), "Basis Color", group = bb_group, display = display.none)
UpperColor = input.color(color.rgb(120, 156, 202,100), "Upper Color", group = bb_group, display = display.none)
LowerColor = input.color(color.rgb(120, 156, 202,100), "Lower Color", group = bb_group, display = display.none)
offset = input.int(0, "Offset", minval = -500, maxval = 500, display = display.data_window, group = bb_group)
ma(source, bb_length, _type) =>
switch _type
"SMA" => ta.sma(source, bb_length)
"EMA" => ta.ema(source, bb_length)
"SMMA (RMA)" => ta.rma(source, bb_length)
"WMA" => ta.wma(source, bb_length)
"VWMA" => ta.vwma(source, bb_length)
basis = ma(bb_src, bb_length, bb_maType)
dev = bb_mult * ta.stdev(bb_src, bb_length)
upper = basis + dev
lower = basis - dev
plot(basis, "Basis", color=BasisColor, offset = offset, force_overlay = true)
p1 = plot(upper, "Upper", color=UpperColor, offset = offset, force_overlay = true)
p2 = plot(lower, "Lower", color=LowerColor, offset = offset, force_overlay = true)
fill(p1, p2, title = "Background", color=color.rgb(163, 41, 245, 90))
rsiLengthInput = input.int(30, minval=1, title="RSI Length", group="RSI Settings")
rsiSourceInput = input.source(close, "Source", group="RSI Settings")
calculateDivergence = input.bool(false, title="Calculate Divergence", group="RSI Settings", display = display.data_window, tooltip = "Calculating divergences is needed in order for divergence alerts to fire.")
SignalDot = input.bool(false, title="Signal Dot", group="Smoothing", display = display.data_window, tooltip = "Signal for possible entry")
change = ta.change(rsiSourceInput)
up = ta.rma(math.max(change, 0), rsiLengthInput)
down = ta.rma(-math.min(change, 0), rsiLengthInput)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
rsiPlot = plot(rsi, "RSI", color= rsi >= 51 ? color.rgb(13, 197, 230) : color.red)
rsiUpperBand = hline(70, "RSI Upper Band", color=#787B86)
midline = hline(50, "RSI Middle Band", color=color.new(#787B86, 50))
rsiLowerBand = hline(30, "RSI Lower Band", color=#787B86)
fill(rsiUpperBand, rsiLowerBand, color=color.rgb(126, 87, 194, 90), title="RSI Background Fill")
midLinePlot = plot(50, color = na, editable = false, display = display.none)
fill(rsiPlot, midLinePlot, 100, 70, top_color = color.new(color.green, 0), bottom_color = color.new(color.green, 100), title = "Overbought Gradient Fill")
fill(rsiPlot, midLinePlot, 30, 0, top_color = color.new(color.red, 100), bottom_color = color.new(color.red, 0), title = "Oversold Gradient Fill")
GRP = "Smoothing"
TT_BB = "Only applies when 'SMA + Bollinger Bands' is selected. Determines the distance between the SMA and the bands."
maTypeInput = input.string("SMA", "Type", options = , group = GRP, display = display.data_window)
maLengthInput = input.int(14, "Length", group = GRP, display = display.data_window)
bbMultInput = input.float(2.0, "BB StdDev", minval = 0.001, maxval = 50, step = 0.5, tooltip = TT_BB, group = GRP, display = display.data_window)
var enableMA = maTypeInput != "None"
var isBB = maTypeInput == "SMA + Bollinger Bands"
smoothma(source, length, MAtype) =>
switch MAtype
"SMA" => ta.sma(source, length)
"SMA + Bollinger Bands" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
smoothingMA = enableMA ? smoothma(rsi, maLengthInput, maTypeInput) : na
smoothingStDev = isBB ? ta.stdev(rsi, maLengthInput) * bbMultInput : na
plot(smoothingMA, "RSI-based MA", color=color.yellow, display = enableMA ? display.all : display.none, editable = enableMA)
bbUpperBand = plot(smoothingMA + smoothingStDev, title = "Upper Bollinger Band", color=color.green, display = isBB ? display.all : display.none, editable = isBB)
bbLowerBand = plot(smoothingMA - smoothingStDev, title = "Lower Bollinger Band", color=color.green, display = isBB ? display.all : display.none, editable = isBB)
fill(bbUpperBand, bbLowerBand, color= isBB ? color.new(color.green, 90) : na, title="Bollinger Bands Background Fill", display = isBB ? display.all : display.none, editable = isBB)
lookbackRight = 5
lookbackLeft = 5
rangeUpper = 60
rangeLower = 5
bearColor = color.red
bullColor = color.green
textColor = color.white
noneColor = color.new(color.white, 100)
_calcBarsSince(cond) =>
ta.barssince(cond)
rsiLBR = rsi
// 1. Calculate Pivots Unconditionally
plFound = not na(ta.pivotlow(rsi, lookbackLeft, lookbackRight))
phFound = not na(ta.pivothigh(rsi, lookbackLeft, lookbackRight))
// 2. Calculate History Unconditionally
barsSincePL = _calcBarsSince(plFound )
barsSincePH = _calcBarsSince(phFound )
// 3. Check Ranges Unconditionally
inRangePL = rangeLower <= barsSincePL and barsSincePL <= rangeUpper
inRangePH = rangeLower <= barsSincePH and barsSincePH <= rangeUpper
// 4. Calculate Conditions
var bool bullCond = false
var bool bearCond = false
if calculateDivergence
rsiHL = rsiLBR > ta.valuewhen(plFound, rsiLBR, 1) and inRangePL
lowLBR = low
priceLL = lowLBR < ta.valuewhen(plFound, lowLBR, 1)
bullCond := priceLL and rsiHL and plFound
rsiLH = rsiLBR < ta.valuewhen(phFound, rsiLBR, 1) and inRangePH
highLBR = high
priceHH = highLBR > ta.valuewhen(phFound, highLBR, 1)
bearCond := priceHH and rsiLH and phFound
else
bullCond := false
bearCond := false
plot(plFound ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bullish", linewidth = 2, color = (bullCond ? bullColor : noneColor), display = display.pane, editable = calculateDivergence)
plotshape(bullCond ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bullish Label", text = " Bull ", style = shape.labelup, location = location.absolute, color = bullColor, textcolor = textColor, display = display.pane, editable = calculateDivergence)
plot(phFound ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bearish", linewidth = 2, color = (bearCond ? bearColor : noneColor), display = display.pane, editable = calculateDivergence)
plotshape(bearCond ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bearish Label", text = " Bear ", style = shape.labeldown, location = location.absolute, color = bearColor, textcolor = textColor, display = display.pane, editable = calculateDivergence)
alertcondition(bullCond, title='Regular Bullish Divergence', message="Found a new Regular Bullish Divergence.")
alertcondition(bearCond, title='Regular Bearish Divergence', message='Found a new Regular Bearish Divergence.')
// --- Panel Options (General) ---
g_panel = 'MTF Panel Options'
i_orientation = input.string('Vertical', 'Orientation', options = , group = g_panel)
i_position = input.string('Bottom Right', 'Position', options = , group = g_panel)
i_border_width = input.int(1, 'Border Width', minval = 0, maxval = 10, group = g_panel, inline = 'border')
i_color_border = input.color(#000000, '', group = g_panel, inline = 'border')
i_showHeaders = input.bool(true, 'Show Headers', group = g_panel)
i_color_header_bg = input.color(#5d606b, 'Headers Background', group = g_panel, inline = 'header')
i_color_header_text = input.color(color.white, 'Text', group = g_panel, inline = 'header')
i_color_tf_bg = input.color(#2a2e39, 'Timeframe Background', group = g_panel, inline = 'tf')
i_color_tf_text = input.color(color.white, 'Text', group = g_panel, inline = 'tf')
i_debug = input.bool(false, 'Display colors palette (debug)', group = g_panel)
// --- RSI Colors (Conditional Formatting) ---
g_rsi = 'MTF RSI Colors'
i_threshold_ob = input.int(70, 'Overbought Threshold', minval=51, maxval=100, group = g_rsi)
i_color_ob = input.color(#128416, 'Overbought Background', inline = 'ob', group = g_rsi)
i_tcolor_ob = input.color(color.white, 'Text', inline = 'ob', group = g_rsi)
i_threshold_uptrend = input.int(60, 'Uptrend Threshold', minval=51, maxval=100, group = g_rsi)
i_color_uptrend = input.color(#2d472e, 'Uptrend Background', inline = 'up', group = g_rsi)
i_tcolor_uptrend = input.color(color.white, 'Text', inline = 'up', group = g_rsi)
i_color_mid = input.color(#131722, 'No Trend Background', group = g_rsi, inline = 'mid')
i_tcolor_mid = input.color(#b2b5be, 'Text', group = g_rsi, inline = 'mid')
i_threshold_downtrend = input.int(40, 'Downtrend Threshold', group = g_rsi, minval=0, maxval=49)
i_color_downtrend = input.color(#5b2e2e, 'Downtrend Background', group = g_rsi, inline = 'down')
i_tcolor_downtrend = input.color(color.white, 'Text', group = g_rsi, inline = 'down')
i_threshold_os = input.int(30, 'Oversold Threshold', minval=0, maxval=49, group = g_rsi)
i_color_os = input.color(#db3240, 'Oversold Background', group = g_rsi, inline = 'os')
i_tcolor_os = input.color(color.white, 'Text', group = g_rsi, inline = 'os')
// --- Individual RSI Settings (MTF Sources) ---
g_rsi1 = 'RSI #1'
i_rsi1_enabled = input.bool(true, title = 'Enabled', group = g_rsi1)
i_rsi1_tf = input.timeframe('5', 'Timeframe', group = g_rsi1)
i_rsi1_len = input.int(30, 'Length', minval = 1, group = g_rsi1)
i_rsi1_src = input.source(close, 'Source', group = g_rsi1) * 10000
v_rsi1 = i_rsi1_enabled ? request.security(syminfo.tickerid, i_rsi1_tf, ta.rsi(i_rsi1_src, i_rsi1_len)) : na
g_rsi2 = 'RSI #2'
i_rsi2_enabled = input.bool(true, title = 'Enabled', group = g_rsi2)
i_rsi2_tf = input.timeframe('15', 'Timeframe', group = g_rsi2)
i_rsi2_len = input.int(30, 'Length', minval = 1, group = g_rsi2)
i_rsi2_src = input.source(close, 'Source', group = g_rsi2) * 10000
v_rsi2 = i_rsi2_enabled ? request.security(syminfo.tickerid, i_rsi2_tf, ta.rsi(i_rsi2_src, i_rsi2_len)) : na
g_rsi3 = 'RSI #3'
i_rsi3_enabled = input.bool(true, title = 'Enabled', group = g_rsi3)
i_rsi3_tf = input.timeframe('60', 'Timeframe', group = g_rsi3)
i_rsi3_len = input.int(30, 'Length', minval = 1, group = g_rsi3)
i_rsi3_src = input.source(close, 'Source', group = g_rsi3) * 10000
v_rsi3 = i_rsi3_enabled ? request.security(syminfo.tickerid, i_rsi3_tf, ta.rsi(i_rsi3_src, i_rsi3_len)) : na
g_rsi4 = 'RSI #4'
i_rsi4_enabled = input.bool(true, title = 'Enabled', group = g_rsi4)
i_rsi4_tf = input.timeframe('240', 'Timeframe', group = g_rsi4)
i_rsi4_len = input.int(30, 'Length', minval = 1, group = g_rsi4)
i_rsi4_src = input.source(close, 'Source', group = g_rsi4) * 10000
v_rsi4 = i_rsi4_enabled ? request.security(syminfo.tickerid, i_rsi4_tf, ta.rsi(i_rsi4_src, i_rsi4_len)) : na
g_rsi5 = 'RSI #5'
i_rsi5_enabled = input.bool(true, title = 'Enabled', group = g_rsi5)
i_rsi5_tf = input.timeframe('D', 'Timeframe', group = g_rsi5)
i_rsi5_len = input.int(30, 'Length', minval = 1, group = g_rsi5)
i_rsi5_src = input.source(close, 'Source', group = g_rsi5) * 10000
v_rsi5 = i_rsi5_enabled ? request.security(syminfo.tickerid, i_rsi5_tf, ta.rsi(i_rsi5_src, i_rsi5_len)) : na
g_rsi6 = 'RSI #6'
i_rsi6_enabled = input.bool(true, title = 'Enabled', group = g_rsi6)
i_rsi6_tf = input.timeframe('W', 'Timeframe', group = g_rsi6)
i_rsi6_len = input.int(30, 'Length', minval = 1, group = g_rsi6)
i_rsi6_src = input.source(close, 'Source', group = g_rsi6) * 10000
v_rsi6 = i_rsi6_enabled ? request.security(syminfo.tickerid, i_rsi6_tf, ta.rsi(i_rsi6_src, i_rsi6_len)) : na
g_rsi7 = 'RSI #7'
i_rsi7_enabled = input.bool(false, title = 'Enabled', group = g_rsi7)
i_rsi7_tf = input.timeframe('W', 'Timeframe', group = g_rsi7)
i_rsi7_len = input.int(30, 'Length', minval = 1, group = g_rsi7)
i_rsi7_src = input.source(close, 'Source', group = g_rsi7) * 10000
v_rsi7 = i_rsi7_enabled ? request.security(syminfo.tickerid, i_rsi7_tf, ta.rsi(i_rsi7_src, i_rsi7_len)) : na
g_rsi8 = 'RSI #8'
i_rsi8_enabled = input.bool(false, title = 'Enabled', group = g_rsi8)
i_rsi8_tf = input.timeframe('W', 'Timeframe', group = g_rsi8)
i_rsi8_len = input.int(30, 'Length', minval = 1, group = g_rsi8)
i_rsi8_src = input.source(close, 'Source', group = g_rsi8) * 10000
v_rsi8 = i_rsi8_enabled ? request.security(syminfo.tickerid, i_rsi8_tf, ta.rsi(i_rsi8_src, i_rsi8_len)) : na
g_rsi9 = 'RSI #9'
i_rsi9_enabled = input.bool(false, title = 'Enabled', group = g_rsi9)
i_rsi9_tf = input.timeframe('W', 'Timeframe', group = g_rsi9)
i_rsi9_len = input.int(30, 'Length', minval = 1, group = g_rsi9)
i_rsi9_src = input.source(close, 'Source', group = g_rsi9) * 10000
v_rsi9 = i_rsi9_enabled ? request.security(syminfo.tickerid, i_rsi9_tf, ta.rsi(i_rsi9_src, i_rsi9_len)) : na
g_rsi10 = 'RSI #10'
i_rsi10_enabled = input.bool(false, title = 'Enabled', group = g_rsi10)
i_rsi10_tf = input.timeframe('W', 'Timeframe', group = g_rsi10)
i_rsi10_len = input.int(30, 'Length', minval = 1, group = g_rsi10)
i_rsi10_src = input.source(close, 'Source', group = g_rsi10) * 10000
v_rsi10 = i_rsi10_enabled ? request.security(syminfo.tickerid, i_rsi10_tf, ta.rsi(i_rsi10_src, i_rsi10_len)) : na
// --- Panel Helper Functions ---
// Function 4: String Position to Constant (Indentation cleaned)
f_StrPositionToConst(_p) =>
switch _p
'Top Left' => position.top_left
'Top Right' => position.top_right
'Top Center' => position.top_center
'Middle Left' => position.middle_left
'Middle Right' => position.middle_right
'Middle Center' => position.middle_center
'Bottom Left' => position.bottom_left
'Bottom Right' => position.bottom_right
'Bottom Center' => position.bottom_center
=> position.bottom_right
// Function 5: Timeframe to Human Readable (Indentation cleaned)
f_timeframeToHuman(_tf) =>
seconds = timeframe.in_seconds(_tf)
if seconds < 60
_tf
else if seconds < 3600
str.tostring(seconds / 60) + 'm'
else if seconds < 86400
str.tostring(seconds / 60 / 60) + 'h'
else
switch _tf
"1D" => "D"
"1W" => "W"
"1M" => "M"
=> str.tostring(_tf)
type TPanel
table src = na
bool vertical_orientation = true
int row = 0
int col = 0
// Method 1: Increment Column (Indentation cleaned)
method incCol(TPanel _panel) =>
if _panel.vertical_orientation
_panel.col += 1
else
_panel.row += 1
// Method 2: Increment Row (Indentation cleaned)
method incRow(TPanel _panel) =>
if not _panel.vertical_orientation
_panel.col += 1
_panel.row := 0
else
_panel.row += 1
_panel.col := 0
// Method 3: Add Cell (Indentation cleaned)
method add(TPanel _panel, string _v1, color _bg1, color _ctext1, string _v2, color _bg2, color _ctext2) =>
table.cell(_panel.src, _panel.col, _panel.row, _v1, text_color = _ctext1, bgcolor = _bg1)
_panel.incCol()
table.cell(_panel.src, _panel.col, _panel.row, _v2, text_color = _ctext2, bgcolor = _bg2)
_panel.incRow()
// Function 6: Background Color
f_bg(_rsi) =>
c_line = na(_rsi) ? i_color_mid :
_rsi >= i_threshold_ob ? i_color_ob :
_rsi >= i_threshold_uptrend ? i_color_uptrend :
_rsi <= i_threshold_os ? i_color_os :
_rsi <= i_threshold_downtrend ? i_color_downtrend :
i_color_mid
// Function 7: Text Color
f_rsi_text_color(_rsi) =>
c_line = na(_rsi) ? i_tcolor_mid :
_rsi >= i_threshold_ob ? i_tcolor_ob :
_rsi >= i_threshold_uptrend ? i_tcolor_uptrend :
_rsi <= i_threshold_os ? i_tcolor_os :
_rsi <= i_threshold_downtrend ? i_tcolor_downtrend :
i_tcolor_mid
f_formatRsi(_rsi) => na(_rsi) ? 'N/A' : str.tostring(_rsi, '0.00')
// --- Panel Execution Logic ---
if barstate.islast
v_panel = TPanel.new(vertical_orientation = i_orientation == 'Vertical')
v_max_rows = 20
v_panel.src := table.new(f_StrPositionToConst(i_position), v_max_rows, v_max_rows, border_width = i_border_width, border_color = i_color_border)
if i_showHeaders
v_panel.add('TF', i_color_header_bg, i_color_header_text, 'RSI', i_color_header_bg, i_color_header_text)
if i_rsi1_enabled
v_panel.add(f_timeframeToHuman(i_rsi1_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi1), f_bg(v_rsi1), f_rsi_text_color(v_rsi1))
if i_rsi2_enabled
v_panel.add(f_timeframeToHuman(i_rsi2_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi2), f_bg(v_rsi2), f_rsi_text_color(v_rsi2))
if i_rsi3_enabled
v_panel.add(f_timeframeToHuman(i_rsi3_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi3), f_bg(v_rsi3), f_rsi_text_color(v_rsi3))
if i_rsi4_enabled
v_panel.add(f_timeframeToHuman(i_rsi4_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi4), f_bg(v_rsi4), f_rsi_text_color(v_rsi4))
if i_rsi5_enabled
v_panel.add(f_timeframeToHuman(i_rsi5_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi5), f_bg(v_rsi5), f_rsi_text_color(v_rsi5))
if i_rsi6_enabled
v_panel.add(f_timeframeToHuman(i_rsi6_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi6), f_bg(v_rsi6), f_rsi_text_color(v_rsi6))
if i_rsi7_enabled
v_panel.add(f_timeframeToHuman(i_rsi7_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi7), f_bg(v_rsi7), f_rsi_text_color(v_rsi7))
if i_rsi8_enabled
v_panel.add(f_timeframeToHuman(i_rsi8_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi8), f_bg(v_rsi8), f_rsi_text_color(v_rsi8))
if i_rsi9_enabled
v_panel.add(f_timeframeToHuman(i_rsi9_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi9), f_bg(v_rsi9), f_rsi_text_color(v_rsi9))
if i_rsi10_enabled
v_panel.add(f_timeframeToHuman(i_rsi10_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi10), f_bg(v_rsi10), f_rsi_text_color(v_rsi10))
if i_debug
t = table.new(position.middle_center, 21, 20, border_width = i_border_width, border_color = i_color_border)
v_panel2 = TPanel.new(t, vertical_orientation = i_orientation == 'Vertical')
v_panel2.add('Debug', i_color_header_bg, i_color_header_text, 'Colors', i_color_header_bg, i_color_header_text)
// Using a tuple array for debugging colors demo
// Final Syntax Correction: Use array.new() and array.set() to avoid 'tuple()' function reference error
v_rows = 5 // We know we have 5 elements
demo = array.new(v_rows, '') // Initialize array with 5 string elements, will hold string representation of the tuple
// We will push the elements as a *string* representation of the tuple, as Pine v6 allows
// and then parse them inside the loop if necessary.
// To preserve the structure (string, float) without the tuple() function:
// We must define two separate arrays if the 'tuple' function is truly unavailable.
tf_array = array.new(v_rows)
rsi_array = array.new(v_rows)
// Populate the arrays
array.set(tf_array, 0, 'Overbought')
array.set(rsi_array, 0, float(i_threshold_ob))
array.set(tf_array, 1, 'Uptrend')
array.set(rsi_array, 1, float(i_threshold_uptrend))
array.set(tf_array, 2, 'No Trend')
array.set(rsi_array, 2, 50.0)
array.set(tf_array, 3, 'Downtrend')
array.set(rsi_array, 3, float(i_threshold_downtrend))
array.set(tf_array, 4, 'Oversold')
array.set(rsi_array, 4, float(i_threshold_os))
// Iterate over the arrays using a simple index
for i = 0 to v_rows - 1
tf = array.get(tf_array, i)
rsi = array.get(rsi_array, i)
v_panel2.add(tf, i_color_tf_bg, i_color_tf_text, f_formatRsi(rsi), f_bg(rsi), f_rsi_text_color(rsi))
RSI cyclic smoothed ProCyclic Smoothed Relative Strength Indicator - Pro Version
The cyclic smoothed RSI indicator is an enhancement of the classic RSI, adding
additional smoothing according to the market vibration,
adaptive upper and lower bands according to the cyclic memory and
using the current dominant cycle length as input for the indicator.
The cRSI is used like a standard indicator. The chart highlights trading signals where the signal line crosses above or below the adaptive lower/upper bands. It is much more responsive to market moves than the basic RSI.
The indicator uses the dominant cycle as input to optimize signal, smoothing and cyclic memory. To get more in-depth information on the cyclic-smoothed RSI indicator, please read Chapter 4 "Fine tuning technical indicators" of the book "Decoding the Hidden Market Rhythm, Part 1" available at your favorite book store.
Info: Pro Version
This is the actively maintained and continuously enhanced edition of my free, open-source indicator “RSI Cyclic Smoothed v2” which was recognized with a TradingView Editors’ Pick. The Pro Version will remain fully up to date with the latest Pine Script standards and will receive ongoing refinements and feature improvements, all while preserving the core logic and intent of the original tool. The legacy version will continue to be available for code review and educational purposes, but it will no longer receive updates. The legacy open-source version is here
Pro Features V1:
1) Leveraging multi-timeframe analysis
Indicator can be used on one chart by using different time frames at the same time. Read more on TradingView here .
2) Scoring feature added for scanning and filtering
This indicator now provides four distinct scoring states for both bullish and bearish conditions, making it fully compatible with the TradingView Screener .
Each score reflects a specific market phase based on RSI behavior, slope, and crossover signals.
Bullish States (Positive Scores)
+1 – Bull Exhaustion: Price is above the upper threshold and still rising (upsloping).
+2 – Bull Fatigue: Price is above the upper threshold but losing momentum (downsloping).
+3 – Bull Exit: A fresh downward crossover has occurred.
+4 – Recent Bull Exit: A downward crossover occurred within the recent lookback window.
Bearish States (Negative Scores)
–1 – Bear Exhaustion: Price is below the lower threshold and still declining (downsloping).
–2 – Bear Fatigue: Price is below the lower threshold but starting to turn upward (upsloping).
–3 – Bear Exit: A fresh upward crossover has occurred.
–4 – Recent Bear Exit: An upward crossover occurred within the recent lookback window.
The scoring states are shown in the indicator status panel when plotting the indicator on the chart. For a Screener run, use a generic cycle length setting.
How to determine the current active cycle length?
You can use the following additional tools to fine-tune the current dominant cycle length:
1. The advanced dyanmic Cycle Spectrum Scanner
2. The free Detremded Market Rhythm Oscillator
Bezahltes Script
Volume Trabar Rank PRO🔑 Key Concept
The indicator uses a rank-based system that counts the number of timeframe periods (lengths) where price has exceeded standard deviation thresholds. The higher the absolute rank value, the more extreme the market condition — indicating stronger potential reversal zones.
⚙️ How The Indicator Works
The indicator operates on a unique multi-length Bollinger Band analysis system:
📏 Multiple Length Analysis
📊 Rank Calculation
Counts how many bands the price has broken through to generate a rank value from -18 to +18
🎨 Visual Coding
Color-coded histogram and threshold lines for quick visual interpretation
Ranking System Explained :
Rank Value Signal Strength Typical Action
+8 to +18 Very Strong Consider Selling / Taking Profit
+7 Strong Watch for reversal signals
+4 to +6 Moderate Caution for new longs
+1 to +3 Weak Monitor market conditions
0 Neutral No extreme condition
-1 to -3 Weak Monitor market conditions
-4 to -6 Moderate Look for entry opportunities
-7 Strong Strong buy signal
-8 to -18 Very Strong High probability buy zone
Advanced Features
✅Filter #1: Volume Weighting
✅Filter #2: Outlier Filtering (IQR)
✅Filter #3: Anti-Repaint Logic
⏰ Multi-Timeframe Analysis
The indicator can simultaneously monitor up to 4 different timeframes (default: 1m, 5m, 15m, 30m), allowing traders to:
Identify confluence zones where multiple timeframes show the same signal
Spot divergences between timeframes for better timing
Generate "READY" signals when all MTF conditions align
🎯 MTF Ready Signal
READY BUY: Triggers when MTF #1, #2, and #3 all show oversold ranks ≤ -5
READY SELL: Triggers when MTF #1, #2, and #3 all show overbought ranks ≥ +5
These signals indicate strong multi-timeframe alignment, providing high-probability trading opportunities.
You can see here :
🛠️ How This Indicator Was Created
Accuracy Improvements (v3.0)
Volume Weighting: Replaced SMA with VWMA for better accuracy
Outlier Filtering: Added IQR-based filtering to remove false signals from price spikes
✨ Key Advantages
🚫 No Repainting
Anti-repaint logic ensures signals don't disappear or change after bar closure, providing reliable backtesting and live trading signals.
📊 Multi-Timeframe
Simultaneously monitor up to 4 timeframes, identifying confluence and divergence for better timing and higher probability trades.
🎯 Volume-Weighted
Uses actual volume data to weight calculations, making signals more representative of true market sentiment and participation.
🔬 Outlier Filtered
IQR-based filtering removes false signals from flash crashes, spikes, and other anomalous price action that doesn't represent real conditions.
⚡ Performance Optimized
Carefully tuned to balance accuracy with speed. Default settings optimize for the top 10% extreme conditions without lag.
🎨 Highly Customizable
Over 30 input parameters allow complete customization of lengths, thresholds, colors, and display options to match your trading style.
I just also add :
5M SCALPING OPTIMAL SETTINGS
Alert 🔥 Extreme Signal (Buy/Sell) - Priority HIGH and ⭐ Mid-Term Signal (Buy/Sell) - Priority NORMAL
MTF Blending Options ( 8 Blending Modes )
Rank Occurrences Table.
Bull and Bear divergence
-------
To get access to this script you have to be a member, or DM on TradingView.
Trend-Momentum Matrix [Pro]The Problem: Analysis Paralysis Traders often struggle to align multiple timeframe signals. You might see momentum on the 5-minute chart but fail to notice a major resistance on the 1-hour, or enter a trend just as it loses strength. Juggling multiple indicators (RSI, Moving Averages, ADX, Clouds) on a single chart creates clutter and confusion.
The Solution: Trend-Momentum Matrix The Trend-Momentum Matrix is a professional-grade dashboard that condenses complex market data into a single, high-contrast heatmap. It allows you to monitor the health of a trend across 7 distinct timeframes simultaneously—from scalping charts to long-term views—without cluttering your screen.
This tool is built on a "Strict Compliance" engine. It does not issue signals based on loose guesses; it waits for a high-probability confluence of three market forces: Price Structure, Momentum Velocity, and Trend Strength.
Core Capabilities
1. Dual-Engine Logic The system runs two independent strategies in parallel to catch both sides of the market:
Compounder Engine (Longs) : Identifies high-growth setups where momentum has entered a "Bullish Power Zone," supported by institutional trend strength.
Breakdown Engine (Shorts): Detects structural failures where momentum is accelerating downward and trend support has been breached.
2. The "Squint Test" Visualization Markets move fast. You shouldn't have to read numbers to know the trend. The Matrix utilizes a Heatmap Architecture:
Solid Green Row: Confirmed Bullish Confluence (Safe to Buy).
Solid Red Row: Confirmed Bearish Breakdown (Safe to Short).
Black/Mixed: Noise or Consolidation (Stay Out).
3. Advanced Noise Filtering: Most indicators fail in choppy markets. This tool uses a multi-layered filter:
Trend Strength (ADX) Filter: Signals are ignored if the prevailing trend is too weak or sideways.
Structure Lock: Signals are strictly gated by key moving averages. If the price structure isn't sound, the signal is suppressed.
4. Donchian Breakout Detection The matrix automatically tracks volatility breakouts. It monitors whether the current price action is expanding beyond historical volatility bands (Upper/Lower Donchian channels) to confirm true breakouts versus fake-outs.
Key Features
Multi-Timeframe Matrix: Monitor 7 timeframes (fully customizable with On/Off toggles) in one corner of your screen.
Auto-Adaptive Interface: The table uses a high-contrast Black background that remains clearly visible on both Light and Dark TradingView themes.
Smart Ribbon: Includes an optional, non-intrusive 8-line Moving Average Ribbon to visualize trend flow directly on the chart.
Strict Exit System: The system is designed to protect capital. The moment the specific conditions for Momentum or Structure are lost, the signal immediately converts to an EXIT or COVER command.
Risk Disclaimer: Trading involves substantial risk and is not suitable for every investor. This tool is an analysis aid and does not constitute financial advice. Past performance is not indicative of future results.
Access: This is an Invite-Only premium indicator. Please contact the author to request access.
Trend Composite (Auto 125d + Daily Overlay)Arthur Hill’s Trend Composite is a multi-factor trend indicator designed to quantify the overall trend strength of any market. Instead of relying on a single moving average or MACD signal, the Trend Composite combines five proven long-term trend measures into one clear score.
The indicator outputs a value from –5 to +5, where:
+5 → Strong uptrend
0 → Neutral / transition zone
–5 → Strong downtrend
A higher score means more trend components are aligned bullishly. A lower score means multiple trend components are pointing bearish.
The Trend Composite evaluates:
Price vs 100-day SMA
Price vs 200-day SMA
50-day SMA vs 200-day SMA
Slope of the 200-day SMA
MACD line vs Signal line
Each component votes +1 (bullish) or –1 (bearish), and the sum becomes the Trend Composite score.
Why This Indicator Works
Trend signals by themselves can be noisy or lagging. When you combine multiple uncorrelated trend measures, you remove false positives and get a cleaner picture of market direction. The result is a powerful, balanced trend filter that works across stocks, crypto, forex, indices, and commodities.
How Traders Use It
Trend filter for long trades: Only trade long when the score is ≥ +3
Avoid chop: Stay out when the score is between –2 and +2
Short setups: Look for –3 or lower
Watchlist ranking: Sort symbols by composite score to find the strongest trends
Stage analysis: Helps identify clear Stage 2 uptrends and Stage 4 downtrends
This makes it ideal for systematic traders, swing traders, trend followers, and anyone building rule-based strategies.
Notes
This is not a buy/sell signal on its own — it’s a trend framework. Combine it with volume patterns, relative strength, volatility contraction, or your preferred entry setup for best results.
ZynIQ Premium/Discount Master v2 - (Lite Pack)Overview
ZynIQ Premium-Discount Master v2 (Lite) is a simplified tool designed to highlight premium/discount zones relative to short-term market structure. It helps traders see when price is stretched above or below fair value, using volatility-adjusted logic suitable for intraday and swing trading.
Key Features
• Automated premium/discount classification
• Volatility-aware thresholds for mild and strong stretch conditions
• Clear visual cues for overbought/oversold environments
• Direction-aware structure to complement trend and momentum tools
• Clean labels marking stretch transitions
• Lightweight visuals suitable for fast charting workflows
Use Cases
• Identifying premium and discount zones for entries or exits
• Assessing when price has deviated significantly from equilibrium
• Combining with breakout or VWAP tools for structured confluence
• Improving trade timing with stretch-based context
Notes
This tool provides premium/discount structure and stretch context. It is not a standalone trading system. Use it along with your own confirmation and risk management rules.
Double Relative Strength IndexBase on Regular Relative Streng Index, I am add 1 more RSI on it.
Using method:
When faster RSI cross lower RSI, price direction move at the same direction. It faster to know the direction of price than just using 1 RSI.
Hope it useful for you.
Ehlers Dominant Cycle Stochastic RSIEhlers Enhanced Cycle Stochastic RSI
OVERVIEW
The Ehlers Enhanced Cycle Stochastic RSI is a momentum oscillator that automatically adjusts its lookback periods based on the dominant market cycle. Unlike traditional Stochastic RSI which uses fixed periods, this indicator detects the current cycle length and scales its calculations—making it responsive in fast markets and stable in slow ones.
The indicator combines John Ehlers' digital signal processing research with the classic Stochastic RSI indicator, then adds a confirmation system to ensure cycle measurements are reliable.
THE THEORY
Traditional oscillators use fixed lookback periods (ie, 14-bar RSI). This creates a fundamental problem: markets don't move in fixed cycles. A 14-period RSI might capture the rhythm perfectly during one market phase, then completely miss it when conditions change.
Ehlers' research demonstrated that price data contains measurable cyclical components. If you can detect the dominant cycle length, you can tune your indicators to match it—like tuning a radio to the right frequency.
This indicator takes that concept further by using three independent cycle detection methods and only trusting the measurement when they agree:
Hilbert Transform — A mathematical technique from signal processing that extracts cycle period from the phase relationship between price and its derivative. It is fast but can be noisy.
Autocorrelation Periodogram — Measures how similar the price series is to lagged versions of itself. The lag with highest correlation reveals the dominant cycle. More stable than Hilbert, but slightly slower to adapt.
Goertzel Algorithm (DFT) — A frequency-domain approach that calculates spectral power at each candidate period. Identifies which frequencies contain the most energy.
When all three methods converge on similar period estimates, confidence is high. When they disagree, the market may be in a non-cyclical or in transition.
HOW IT CHANGES THE STOCHASTIC RSI
Standard Stochastic RSI:
1. Calculate RSI with fixed period (14 bars)
2. Apply Stochastic formula over fixed period (14 bars)
3. Smooth with fixed periods
Ehlers Enhanced Cycle Stochastic RSI:
1. Detect dominant cycle using three methods
2. Confirm cycle measurement (methods must agree)
3. Calculate RSI with period scaled to the detected cycle
4. Apply Stochastic formula with cycle-scaled lookback
5. Smooth adaptively
The result: when the market is cycling quickly (say, 15-bar cycles), the indicator uses shorter periods and responds faster. When the market stretches into longer cycles (such as 40-bar cycles), it automatically extends its lookback to avoid whipsaws.
The Period Multipliers let you fine-tune this relationship:
• 1.0 = Use the full detected cycle (smoother, fewer signals)
• 0.5 = Use half the cycle (more responsive, catches turns earlier)
INTERPRETATION
Reading the Oscillator:
• K Line (Blue) — The main signal line. Moves between 0 and 100.
• D Line (Orange) — Smoothed version of K. Use for confirmation.
• Above 80 — Overbought. Momentum stretched to upside.
• Below 20 — Oversold. Momentum stretched to downside.
• Crossovers — K crossing above D suggests bullish momentum shift; K crossing below D suggests bearish.
Spectral Dilation (optional):
When enabled, applies a bandpass filter before cycle detection. This isolates the frequency band of interest and reduces noise. Useful for:
• Very noisy instruments
• Lower timeframes
• When confidence stays persistently low
MTF Trend Avcısı ema ve supertrendi birleştirip h2-h3-h4 uyumlu olduğu zaman al sat sinyali üreten indikatördür
Penny Stock Golden Cross ScannerPenny Stock Golden Cross Scanner
Scan and track potential breakout opportunities in penny stocks with this Golden Cross Scanner. Designed for traders looking at low-priced, high-volume stocks, this indicator identifies bullish setups using 50, 100, and 200-period moving averages.
Key Features:
✅ Monitors up to 10 user-defined tickers.
✅ Filters penny stocks by maximum price and minimum volume.
✅ Detects proximity to 100 MA and 200 MA for potential golden cross or support/resistance signals.
✅ Assigns signal tiers for each stock (Tier 1 🔥, Tier 2 ⚡, Tier 3 📊) based on price action relative to moving averages.
✅ Customizable scanner table with position options on the chart.
✅ Real-time plotting of 50, 100, and 200 moving averages for context.
✅ Option to display only stocks currently generating signals.
CYCLE RESEARCH PRO - FIXEDCYCLE RESEARCH PRO – Fixed & Cleaned (2025 Edition)
The only public T+21 / T+35 / T+147 cycle tracker that actually works.
Features:
• Exact days since the legendary GME sneeze (28 Jan 2021)
• Highlights active T+21, T+35, and T+147 windows (± user-defined tolerance)
• Live countdown to next cycle date for all three
• FTD Proxy detector (extreme volume + true-range spike)
• Clean wide dashboard – no clutter
• Background glows when any cycle window is active
• Built-in alerts including the infamous “T+21 + FTD” combo
• 100 % non-repainting – uses only confirmed bars
• Zero errors, zero warnings, Pine v6 native
Made famous in the meme-stock wars.
Now cleaned, fixed, and ready for the next run.
Works on GME, AMC, BBBY, any stock or crypto.
Use it. Share it. Profit.
Not financial advice. Just math & cycles.
– Published with love for the apes, degens, and cycle chads everywhere
Erva & nur (stoch rsi)This script builds a custom oscillator that combines WaveTrend, RSI and Stochastic RSI to analyze momentum and overbought/oversold zones.
Bli-Rik (Buy and sell based on RSI & SMA)Basis analysis of Stoch RSI + RSI + 34/200 SMA Signals we have identified and generated Buy and sell indication on chart, This will help to guild buy and sell process...
