FFI-Trend Rider ProFFI-Trend Rider Pro is a trend-following strategy designed to help traders make more structured and disciplined entries.
It uses a crossover between the 11 EMA and 21 SMA to detect potential trend shifts, while avoiding premature entries by checking how far the price is from the moving averages. If the price is extended, it waits for a pullback — just like professional traders do.
The indicator also includes:
Auto stoploss based on 21 SMA
Visual background colors based on RSI to help gauge trend strength
A built-in trade info table showing current trade type, entry price, stoploss, and trailing SL
Strategy-enabled functionality for easy backtesting
🔍 Ideal For:
Intraday & Swing Traders
Traders who want fewer, high-quality trades
Anyone looking to reduce emotional decision-making
⚠️ Disclaimer:
This script is for educational purposes only and does not constitute financial advice. Always do your own analysis before making any trading decisions. Past performance is not indicative of future results.
相对强弱指数(RSI)
RSI Zones - Directional Entry Strict RSI Zones – Directional Entry Tool (Modified RSI)
This is a simple modification of the standard RSI indicator. I’ve added two custom horizontal lines at the 60–65 and 35–40 zones to help spot momentum shifts and potential reversal points.
60–65 zone: When RSI returns here from above 65, it often signals weakening bullish momentum — useful for spotting short opportunities.
35–40 zone: When RSI returns here from below 35, it can indicate momentum loss on the downside — good for potential long setups.
This version helps traders filter out weak signals and avoid chasing extreme moves.
It works best when combined with price action, structure, or divergence.
Only 2 lines were added to the default RSI for better zone awareness. Everything else remains unchanged.
RSI Halving Heatmap by GUELFO
📈 **RSI Halving Heatmap Indicator**
This custom RSI indicator colors the RSI line based on the number of months remaining until the next Bitcoin halving. The closer we get to the halving, the warmer the color—ranging from deep blue (far from halving) to bright red (near halving).
✅ Includes:
- Customizable RSI length and source
- 12-color gradient scale for halving proximity
- Optional SMA overlay on RSI for trend smoothing
Ideal for visualizing market momentum in the context of Bitcoin’s halving cycle.
New Rsi For Entry FiltrationThis indicator, which is based on the RSI indicator, is written to prevent you from entering the wrong trade. Its operation is very simple. Enter a long trade when both the main area and the lower ribbon are green. Also, for a short trade, both the main area and the lower ribbon are red. The purple line also shows the stop loss level based on ATR. It is not advisable to enter the trade at the points indicated by R because the candlestick length is long.
RSI WMA VWMA Divergence Indicator// This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © Kenndjk
//@version=6
indicator(title="RSI WMA VWMA Divergence Indicator", shorttitle="Kenndjk", format=format.price, precision=2)
oscType = input.string("RSI", "Oscillator Type", options = , group="General Settings")
// RSI Settings
rsiGroup = "RSI Settings"
rsiLengthInput = input.int(14, minval=1, title="RSI Length", group=rsiGroup)
rsiSourceInput = input.source(close, "Source", group=rsiGroup)
// WMA VWMA
wmaLength = input.int(9, "WMA Length", minval=1, group="WMA Settings")
vwmaLength = input.int(3, "VWMA Length", minval=1, group="WMA Settings")
wma = ta.wma(close, wmaLength)
vwma = ta.vwma(close, vwmaLength)
useVWMA = input.bool(true, "Use VWMA for Divergence (when WMA + VWMA mode)", group="WMA Settings")
// Oscillator selection
rsi = ta.rsi(rsiSourceInput, rsiLengthInput) // Calculate RSI always, but use conditionally
osc = oscType == "RSI" ? rsi : useVWMA ? vwma : wma
// RSI plots (conditional)
isRSI = oscType == "RSI"
rsiPlot = plot(isRSI ? rsi : na, "RSI", color=isRSI ? #7E57C2 : na)
rsiUpperBand = hline(isRSI ? 70 : na, "RSI Upper Band", color=isRSI ? #787B86 : na)
midline = hline(isRSI ? 50 : na, "RSI Middle Band", color=isRSI ? color.new(#787B86, 50) : na)
rsiLowerBand = hline(isRSI ? 30 : na, "RSI Lower Band", color=isRSI ? #787B86 : na)
fill(rsiUpperBand, rsiLowerBand, color=isRSI ? color.rgb(126, 87, 194, 90) : na, title="RSI Background Fill")
midLinePlot = plot(isRSI ? 50 : na, color = na, editable = false, display = display.none)
fill(rsiPlot, midLinePlot, 100, 70, top_color = isRSI ? color.new(color.green, 0) : na, bottom_color = isRSI ? color.new(color.green, 100) : na, title = "Overbought Gradient Fill")
fill(rsiPlot, midLinePlot, 30, 0, top_color = isRSI ? color.new(color.red, 100) : na, bottom_color = isRSI ? color.new(color.red, 0) : na, title = "Oversold Gradient Fill")
// WMA VWMA plots
wmaColor = oscType != "RSI" ? (useVWMA ? color.new(color.blue, 70) : color.blue) : na
wmaWidth = useVWMA ? 1 : 2
vwmaColor = oscType != "RSI" ? (useVWMA ? color.orange : color.new(color.orange, 70)) : na
vwmaWidth = useVWMA ? 2 : 1
plot(oscType != "RSI" ? wma : na, "WMA", color=wmaColor, linewidth=wmaWidth)
plot(oscType != "RSI" ? vwma : na, "VWMA", color=vwmaColor, linewidth=vwmaWidth)
// Smoothing MA inputs (only for RSI)
GRP = "Smoothing (RSI only)"
TT_BB = "Only applies when 'Show Bollinger Bands' is selected. Determines the distance between the SMA and the bands."
maLengthSMA = input.int(14, "SMA Length", minval=1, group=GRP, display=display.data_window)
maLengthEMA = input.int(14, "EMA Length", minval=1, group=GRP, display=display.data_window)
maLengthRMA = input.int(14, "SMMA (RMA) Length", minval=1, group=GRP, display=display.data_window)
maLengthWMA = input.int(14, "WMA Length", minval=1, group=GRP, display=display.data_window)
maLengthVWMA = input.int(14, "VWMA Length", minval=1, 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)
showSMA = input.bool(false, "Show SMA", group=GRP)
showEMA = input.bool(false, "Show EMA", group=GRP)
showRMA = input.bool(false, "Show SMMA (RMA)", group=GRP)
showWMAsmooth = input.bool(false, "Show WMA", group=GRP)
showVWMAsmooth = input.bool(false, "Show VWMA", group=GRP)
showBB = input.bool(false, "Show SMA + Bollinger Bands", group=GRP, tooltip=TT_BB)
// Smoothing MA Calculations
sma_val = (showSMA or showBB) and isRSI ? ta.sma(rsi, maLengthSMA) : na
ema_val = showEMA and isRSI ? ta.ema(rsi, maLengthEMA) : na
rma_val = showRMA and isRSI ? ta.rma(rsi, maLengthRMA) : na
wma_val = showWMAsmooth and isRSI ? ta.wma(rsi, maLengthWMA) : na
vwma_val = showVWMAsmooth and isRSI ? ta.vwma(rsi, maLengthVWMA) : na
smoothingStDev = showBB and isRSI ? ta.stdev(rsi, maLengthSMA) * bbMultInput : na
// Smoothing MA plots
plot(sma_val, "RSI-based SMA", color=(showSMA or showBB) ? color.yellow : na, display=(showSMA or showBB) ? display.all : display.none, editable=(showSMA or showBB))
plot(ema_val, "RSI-based EMA", color=showEMA ? color.purple : na, display=showEMA ? display.all : display.none, editable=showEMA)
plot(rma_val, "RSI-based RMA", color=showRMA ? color.red : na, display=showRMA ? display.all : display.none, editable=showRMA)
plot(wma_val, "RSI-based WMA", color=showWMAsmooth ? color.blue : na, display=showWMAsmooth ? display.all : display.none, editable=showWMAsmooth)
plot(vwma_val, "RSI-based VWMA", color=showVWMAsmooth ? color.orange : na, display=showVWMAsmooth ? display.all : display.none, editable=showVWMAsmooth)
bbUpperBand = plot(showBB ? sma_val + smoothingStDev : na, title="Upper Bollinger Band", color=showBB ? color.green : na, display=showBB ? display.all : display.none, editable=showBB)
bbLowerBand = plot(showBB ? sma_val - smoothingStDev : na, title="Lower Bollinger Band", color=showBB ? color.green : na, display=showBB ? display.all : display.none, editable=showBB)
fill(bbUpperBand, bbLowerBand, color=showBB ? color.new(color.green, 90) : na, title="Bollinger Bands Background Fill", display=showBB ? display.all : display.none, editable=showBB)
// Divergence Settings
divGroup = "Divergence Settings"
calculateDivergence = input.bool(true, title="Calculate Divergence", group=divGroup, tooltip = "Calculating divergences is needed in order for divergence alerts to fire.")
lookbackLeft = input.int(5, "Pivot Lookback Left", minval=1, group=divGroup)
lookbackRight = input.int(5, "Pivot Lookback Right", minval=1, group=divGroup)
rangeLower = input.int(5, "Min Range for Divergence", minval=0, group=divGroup)
rangeUpper = input.int(60, "Max Range for Divergence", minval=1, group=divGroup)
showHidden = input.bool(true, "Show Hidden Divergences", group=divGroup)
bearColor = color.red
bullColor = color.green
textColor = color.white
noneColor = color.new(color.white, 100)
_inRange(cond) =>
bars = ta.barssince(cond)
rangeLower <= bars and bars <= rangeUpper
bool plFound = false
bool phFound = false
bool bullCond = false
bool bearCond = false
bool hiddenBullCond = false
bool hiddenBearCond = false
float oscLBR = na
float lowLBR = na
float highLBR = na
float prevPlOsc = na
float prevPlLow = na
float prevPhOsc = na
float prevPhHigh = na
if calculateDivergence
plFound := not na(ta.pivotlow(osc, lookbackLeft, lookbackRight))
phFound := not na(ta.pivothigh(osc, lookbackLeft, lookbackRight))
oscLBR := osc
lowLBR := low
highLBR := high
prevPlOsc := ta.valuewhen(plFound, oscLBR, 1)
prevPlLow := ta.valuewhen(plFound, lowLBR, 1)
prevPhOsc := ta.valuewhen(phFound, oscLBR, 1)
prevPhHigh := ta.valuewhen(phFound, highLBR, 1)
// Regular Bullish
oscHL = oscLBR > prevPlOsc and _inRange(plFound )
priceLL = lowLBR < prevPlLow
bullCond := priceLL and oscHL and plFound
// Regular Bearish
oscLL = oscLBR < prevPhOsc and _inRange(phFound )
priceHH = highLBR > prevPhHigh
bearCond := priceHH and oscLL and phFound
// Hidden Bullish
oscLL_hidden = oscLBR < prevPlOsc and _inRange(plFound )
priceHL = lowLBR > prevPlLow
hiddenBullCond := priceHL and oscLL_hidden and plFound and showHidden
// Hidden Bearish
oscHH_hidden = oscLBR > prevPhOsc and _inRange(phFound )
priceLH = highLBR < prevPhHigh
hiddenBearCond := priceLH and oscHH_hidden and phFound and showHidden
// Plot divergences (lines and labels on pane)
if bullCond
leftBar = ta.valuewhen(plFound, bar_index , 1)
line.new(leftBar, prevPlOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bullColor, width=2)
label.new(bar_index , oscLBR, "R Bull", style=label.style_label_up, color=noneColor, textcolor=textColor)
if bearCond
leftBar = ta.valuewhen(phFound, bar_index , 1)
line.new(leftBar, prevPhOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bearColor, width=2)
label.new(bar_index , oscLBR, "R Bear", style=label.style_label_down, color=noneColor, textcolor=textColor)
if hiddenBullCond
leftBar = ta.valuewhen(plFound, bar_index , 1)
line.new(leftBar, prevPlOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bullColor, width=2, style=line.style_dashed)
label.new(bar_index , oscLBR, "H Bull", style=label.style_label_up, color=noneColor, textcolor=textColor)
if hiddenBearCond
leftBar = ta.valuewhen(phFound, bar_index , 1)
line.new(leftBar, prevPhOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bearColor, width=2, style=line.style_dashed)
label.new(bar_index , oscLBR, "H Bear", style=label.style_label_down, color=noneColor, textcolor=textColor)
// Alert conditions
alertcondition(bullCond, title="Regular Bullish Divergence", message="Found a new Regular Bullish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
alertcondition(bearCond, title="Regular Bearish Divergence", message="Found a new Regular Bearish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
alertcondition(hiddenBullCond, title="Hidden Bullish Divergence", message="Found a new Hidden Bullish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
alertcondition(hiddenBearCond, title="Hidden Bearish Divergence", message="Found a new Hidden Bearish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
RSI+BOLLINGER (LONG & SHORT)This indicator combines two of the most popular tools in technical analysis, the Relative Strength Index (RSI) and Bollinger Bands (BB), to generate both long (BUY) and short (SELL) trading signals.
Strategy:
Entries (Buy/Short): Entry signals are based on the RSI.
A BUY is suggested when the RSI crosses above an oversold level (default: 29), indicating a possible upward reversal.
A SHORT is suggested when the RSI crosses below an overbought level (default: 71), indicating a possible downward reversal.
Exits (Position Closure): Exit signals are based on Bollinger Bands.
A long position is closed when the price crosses below the upper Bollinger Band.
A short position is closed when the price crosses above the lower Bollinger Band.
Key Features:
Cascade Filter: Includes a smart filter that prevents opening new consecutive trades if the price hasn't moved significantly in favor of a new entry, optimizing signal quality.
Automation Alerts: Generates detailed alerts in JSON format for each event (buy, sell, close), designed for easy integration with trading bots and automated systems via webhooks.
Fully Configurable: All parameters of the RSI, Bollinger Bands, and strategy filters can be adjusted from the indicator’s settings menu.
MIGA Trader DNAMIGA Trader DNA is a composite indicator that integrates:
Trend Identification: Uses three exponential moving averages (fast, mid, slow) to determine market bias based on their order.
Momentum Filter: An adaptive RSI whose period automatically matches the fastest EMA highlights overbought or oversold conditions.
Entry Timing: A Stochastic %K crossover signals precise entry points when momentum aligns with trend direction.
Volatility Envelope: An optional, SuperTrend band adjusts dynamically to changing ATR-based volatility.
Visual Signals: Discrete “Buy” and “Sell” labels mark entry opportunities directly on the price chart when all conditions align.
RSI Long Only with Confirmed CrossbacksThis RSI-based long-only strategy aims to identify and trade potential reversals with confirmation to reduce false signals. It enters a long position only after the Relative Strength Index (RSI) first dips below a specified oversold threshold (default 44) and then crosses back above it, signaling a possible bullish reversal with momentum. The strategy avoids premature entries by requiring this two-step confirmation. Similarly, it exits the long position only after RSI first rises above the overbought threshold (default 70) and then crosses back below it, indicating a potential loss of bullish momentum. By waiting for RSI to travel beyond the thresholds and then revert, the strategy attempts to capture stronger and more reliable directional moves while filtering out temporary spikes.
BoaBias 3RSI(Custom) + Stats3RSI(Custom) + Stats
3RSI(Custom) + Stats is an advanced multi-RSI indicator for professional and active traders. It visualizes overbought/oversold conditions using three independently configured, smoothed RSI lines (defaults: 24, 14, 9), and provides unique statistics on how long your chosen asset stays in these extreme zones.
Key Features
Triple RSI Display: Simultaneously plots three customizable RSI lines, each with its own period and smoothing.
Dynamic Overbought/Oversold Highlights: Background color highlights only when any RSI is above the overbought level or below the oversold level—no clutter, just the key moments.
In-Panel Statistics Table: See current RSI values, and average streak length in overbought and oversold zones for each RSI, calculated over your chosen historical window (default: 360 bars). Table font size can be adjusted in settings for maximum readability.
Configurable Levels: Set your preferred levels for overbought/oversold zones, as well as additional mid-levels for more nuanced analysis.
Alerts: Instantly set up alerts for when any (or each) RSI enters an extreme zone. Never miss a key reversal setup.
How to Use
Use the indicator to objectively spot exhaustion and reversal points on any timeframe and asset.
The average streak statistics help you judge whether the market is behaving “normally” or if an extreme condition is being sustained.
Table with live RSI and stats makes your decision process faster and more data-driven.
Alerts allow you to stay informed even when you’re not watching the chart.
Settings
RSI Periods & Smoothing: Adjust all three lines independently to suit your strategy.
Overbought/Oversold Levels: Customize thresholds to fit your asset or timeframe.
Statistical Window: Define how many bars to use for calculating streak averages.
Font Size: Make the stats table readable on any screen size with adjustable font.
Summary
All-in-one solution for tracking momentum exhaustion with real statistical support.
Visual clarity: only shows what matters, when it matters.
Fully compatible with TradingView alerts for ultimate automation and risk management.
Questions or suggestions? Leave feedback in the comments!
RSI Ichimoku-like (Subchart) tohungmcThe RSI Ichimoku-like (Subchart) indicator offers a novel approach to technical analysis by uniquely combining the Relative Strength Index (RSI) with the principles of the Ichimoku Kinko Hyo system. Unlike traditional Ichimoku, which is applied to price data, this indicator innovatively uses RSI values to construct Ichimoku components (Conversion Line, Base Line, Leading Span 1, Leading Span 2, and Cloud). Displayed on a separate subchart, it provides traders with a powerful tool to analyze momentum and trend dynamics in a single, intuitive view.
Unique Features
Innovative RSI-based Ichimoku System: By applying Ichimoku calculations to RSI instead of price, this indicator creates a momentum-driven trend analysis framework, offering a fresh perspective on market dynamics.
Cloud Visualization: The cloud (formed between Leading Span 1 and 2) highlights bullish (green) or bearish (red) momentum zones, helping traders identify trend strength and potential reversals.
Customizable Parameters: Adjust RSI and Ichimoku periods to suit various trading styles and timeframes.
Subchart Design: Keeps your price chart clean while providing a dedicated space for momentum and trend analysis.
Components
RSI Line: A 14-period RSI (customizable) plotted in blue, with overbought (70) and oversold (30) levels marked for quick reference.
Conversion Line: Average of the highest and lowest RSI over 9 periods, acting as a short-term momentum indicator.
Base Line: Average of the highest and lowest RSI over 26 periods, serving as a medium-term trend guide.
Leading Span 1: Average of Conversion and Base Lines, shifted forward 26 periods.
Leading Span 2: Average of the highest and lowest RSI over 52 periods, shifted forward 26 periods.
Cloud: The area between Leading Span 1 and 2, colored green (bullish) when Span 1 is above Span 2, and red (bearish) when Span 2 is above Span 1.
How to Use
Momentum Analysis:
Monitor the RSI line for overbought (>70) or oversold (<30) conditions to spot potential reversals.
A RSI crossing above 30 or below 70 can indicate shifts in momentum.
Trend Identification:
When the RSI is above the cloud and the cloud is green, it suggests bullish momentum.
When the RSI is below the cloud and the cloud is red, it indicates bearish momentum.
Crossovers:
RSI crossing above the Conversion or Base Line may signal bullish opportunities, especially if aligned with a green cloud.
RSI crossing below these lines may suggest bearish opportunities, particularly with a red cloud.
Cloud Breakouts:
A RSI breaking through the cloud can signal a potential trend change, with the cloud’s color indicating the direction.
Customization:
Adjust the RSI Period (default: 14), Conversion Line Period (default: 9), Base Line Period (default: 26), and Leading Span 2 Period (default: 52) to match your trading timeframe or strategy.
Settings
RSI Period: Default 14. Increase for smoother signals or decrease for higher sensitivity.
Conversion Line Period: Default 9. Adjust for short-term momentum sensitivity.
Base Line Period: Default 26. Modify for medium-term trend analysis.
Leading Span 2 Period: Default 52. Tune for long-term trend context.
Why Closed Source?
The unique methodology of applying Ichimoku calculations to RSI, combined with optimized subchart visualization, represents a proprietary approach to momentum and trend analysis. Protecting the source code ensures the integrity of this innovative concept while allowing traders worldwide to benefit from its functionality.
Notes
This indicator does not generate explicit Buy/Sell signals, giving traders flexibility to interpret signals based on their strategies.
Best used in conjunction with other technical tools (e.g., support/resistance, candlestick patterns) for confirmation.
Suitable for all timeframes, from intraday to long-term trading.
RSI Shift Zone [ChartPrime]OVERVIEW
RSI Shift Zone is a sentiment-shift detection tool that bridges momentum and price action. It plots dynamic channel zones directly on the price chart whenever the RSI crosses above or below critical thresholds (default: 70 for overbought, 30 for oversold). These plotted zones reveal where market sentiment likely flipped, helping traders pinpoint powerful support/resistance clusters and breakout opportunities in real time.
⯁ HOW IT WORKS
When the RSI crosses either the upper or lower level:
A new Shift Zone channel is instantly formed.
The channel’s boundaries anchor to the high and low of the candle at the moment of crossing.
A mid-line (average of high and low) is plotted for easy visual reference.
The channel remains visible on the chart for at least a user-defined minimum number of bars (default: 15) to ensure only meaningful shifts are highlighted.
The channel is color-coded to reflect bullish or bearish sentiment, adapting dynamically based on whether the RSI breached the upper or lower level. Labels with actual RSI values can also be shown inside the zone for added context.
⯁ KEY TECHNICAL DETAILS
Uses a standard RSI calculation (default length: 14).
Detects crossovers above the upper level (trend strength) and crossunders below the lower level (oversold exhaustion).
Applies the channel visually on the main chart , rather than only in the indicator pane — giving traders a precise map of where sentiment shifts have historically triggered price reactions.
Auto-clears the zone when the minimum bar length is satisfied and a new shift is detected.
⯁ USAGE
Traders can use these RSI Shift Zones as powerful tactical levels:
Treat the channel’s high/low boundaries as dynamic breakout lines — watch for candles closing beyond them to confirm fresh trend continuation.
Use the midline as an equilibrium reference for pullbacks within the zone.
Visual RSI value labels offer quick checks on whether the zone formed due to extreme overbought or oversold conditions.
CONCLUSION
RSI Shift Zone transforms a simple RSI threshold crossing into a meaningful structural tool by projecting sentiment flips directly onto the price chart. This empowers traders to see where momentum-based turning points occur and leverage those levels for breakout plays, reversals, or high-confidence support/resistance zones — all in one glance.
RSI Overbought/Oversold MTFRSI Overbought / Oversold MTF — Dashboard & Alerts
What it does
This script scans up to 13 symbols at once and shows their RSI readings on three lower‑time‑frames (1 min, 5 min, 15 min).
If all three RSIs for a symbol are simultaneously above the overbought threshold or below the oversold threshold, the script:
Prints the condition (“Overbought” / “Oversold”) in a color‑coded dashboard table.
Fires a one‑per‑bar alert so you never miss the move.
Key features
Feature Details
Multi‑symbol Default list includes BTC, ETH, SOL, BNB, XRP, ADA, AVAX, AVAAI, DOGE, VIRTUAL, SUI, ALCH, LAYER (all Binance pairs). Replace or reorder in the inputs.
Triple‑time‑frame check RSI is calculated on 1 m, 5 m, 15 m for each symbol.
Customizable thresholds Set your own RSI Period, Overbought and Oversold levels. Defaults: 14 / 70 / 30.
Color‑coded dashboard Top‑right table shows:
• Symbol name
• RSI 1 m / 5 m / 15 m (red = overbought, green = oversold, white = neutral)
• Overall Status column (“Overbought”, “Oversold”, “Mixed”).
Alerts built in Triggers once per bar whenever a symbol is overbought or oversold on all three time‑frames simultaneously.
Typical use cases
Scalp alignment — Enter when all short TFs agree on overbought/oversold extremes.
Mean‑reversion spotting — Identify stretched conditions across multiple coins without switching charts.
Quick sentiment scan — Glance at the dashboard to see where momentum is heating up or cooling down.
How to use
Add to chart (overlay = false; it sits in its own pane).
Adjust symbols & thresholds in the Settings panel.
Create alerts → choose “RSI Overbought/Oversold MTF” → “Any Alert() Function Call” to receive push, email, or webhook notifications.
Note: The script queries many symbols each bar; use on lower time‑frames only if your data limits allow.
For educational purposes only — not financial advice. Always test on paper before trading live.
Quantum Reversal Engine [ApexLegion]Quantum Reversal Engine
STRATEGY OVERVIEW
This strategy is constructed using 5 custom analytical filters that analyze different market dimensions - trend structure, momentum expansion, volume confirmation, price action patterns, and reversal detection - with results processed through a multi-component scoring calculation that determines signal generation and position management decisions.
Why These Custom Filters Were Independently Developed:
This strategy employs five custom-developed analytical filters:
1. Apex Momentum Core (AMC) - Custom oscillator with volatility-scaled deviation calculation
Standard oscillators lag momentum shifts by 2-3 bars. Custom calculation designed for momentum analysis
2. Apex Wick Trap (AWT) - Wick dominance analysis for trap detection
Existing wick analysis tools don't quantify trap conditions. Uses specific ratios for wick dominance detection
3. Apex Volume Pulse (AVP) - Volume surge validation with participation confirmation
Volume indicators typically use simple averages. Uses surge multipliers with participation validation
4. Apex TrendGuard (ATG) - Angle-based trend detection with volatility band integration
EMA slope calculations often produce false signals. Uses angle analysis with volatility bands for confirmation
5. Quantum Composite Filter (QCF) - Multi-component scoring and signal generation system
Composite scoring designed to filter noise by requiring multiple confirmations before signal activation.
Each filter represents mathematical calculations designed to address specific analytical requirements.
Framework Operation: The strategy functions as a scoring framework where each filter contributes weighted points based on market conditions. Entry signals are generated when minimum threshold scores are met. Exit management operates through a three-tier system with continued signal strength evaluation determining position holds versus closures at each TP level.
Integration Challenge: The core difficulty was creating a scoring system where five independent filters could work together without generating conflicting signals. This required backtesting to determine effective weight distributions.
Custom Filter Development:
Each of the five filters represents analytical approaches developed through testing and validation:
Integration Validation: Each filter underwent individual testing before integration. The composite scoring system required validation to verify that filters complement rather than conflict with each other, resulting in a cohesive analytical framework that was tested during the development period.
These filters represent custom-developed components created specifically for this strategy, with each component addressing different analytical requirements through testing and parameter adjustment.
Programming Features:
Multi-timeframe data handling with backup systems
Performance optimization techniques
Error handling for live trading scenarios
Parameter adaptation based on market conditions
Strategy Features:
Uses multi-filter confirmation approach
Adapts position holding based on continued signal strength
Includes analysis tools for trade review and optimization
Ongoing Development: The strategy was developed through testing and validation processes during the creation period.
COMPONENT EXPLANATION
EMA System
Uses 8 exponential moving averages (7, 14, 21, 30, 50, 90, 120, 200 periods) for trend identification. Primary signals come from 8/21 EMA crossovers, while longer EMAs provide structural context. EMA 1-4 determine short-term structure, EMA 5-8 provide long-term trend confirmation.
Apex Momentum Core (AMC)
Built custom oscillator mathematics after testing dozens of momentum calculation methods. Final algorithm uses price deviation from EMA baseline with volatility scaling to reduce lag while maintaining accuracy across different market conditions.
Custom momentum oscillator using price deviation from EMA baseline:
apxCI = 100 * (source - emaBase) / (sensitivity * sqrt(deviation + 1))
fastLine = EMA(apxCI, smoothing)
signalLine = SMA(fastLine, 4)
Signals generate when fastLine crosses signalLine at +50/-50 thresholds.
This identifies momentum expansion before traditional oscillators.
Apex Volume Pulse (AVP)
Created volume surge analysis that goes beyond simple averages. Extensive testing determined 1.3x multiplier with participation validation provides reliable confirmation while filtering false volume spikes.
Compares current volume to 21-period moving average.
Requires 1.3x average volume for signal confirmation. This filters out low-volume moves during quiet periods and confirms breakouts with actual participation.
Apex Wick Trap (AWT)
Developed proprietary wick trap detection through analysis of failed breakout patterns. Tested various ratio combinations before settling on 60% wick dominance + 20% body limit as effective trap identification parameters.
Analyzes candle structure to identify failed breakouts:
candleRange = math.max(high - low, 0.00001)
candleBody = math.abs(close - open)
bodyRatio = candleBody / candleRange
upperWick = high - math.max(open, close)
lowerWick = math.min(open, close) - low
upperWickRatio = upperWick / candleRange
lowerWickRatio = lowerWick / candleRange
trapWickLong = showAWT and lowerWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close > open
trapWickShort = showAWT and upperWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close < open This catches reversals after fake breakouts.
Apex TrendGuard (ATG)
Built angle-based trend detection after standard EMA crossovers proved insufficient. Combined slope analysis with volatility bands through iterative testing to eliminate false trend signals.
EMA slope analysis with volatility bands:
Fast EMA (21) vs Slow EMA (55) for trend direction
Angle calculation: atan(fast - slow) * 180 / π
ATR bands (1.75x multiplier) for breakout confirmation
Minimum 25° angle for strong trend classification
Core Algorithm Framework
1. Composite Signal Generation
calculateCompositeSignals() =>
// Component Conditions
structSignalLong = trapWickLong
structSignalShort = trapWickShort
momentumLong = amcBuySignal
momentumShort = amcSellSignal
volumeSpike = volume > volAvg_AVP * volMult_AVP
priceStrength_Long = close > open and close > close
priceStrength_Short = close < open and close < close
rsiMfiComboValue = (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2
reversalTrigger_Long = ta.crossover(rsiMfiComboValue, 50)
reversalTrigger_Short = ta.crossunder(rsiMfiComboValue, 50)
isEMACrossUp = ta.crossover(emaFast_ATG, emaSlow_ATG)
isEMACrossDown = ta.crossunder(emaFast_ATG, emaSlow_ATG)
// Enhanced Composite Score Calculation
scoreBuy = 0.0
scoreBuy += structSignalLong ? scoreStruct : 0.0
scoreBuy += momentumLong ? scoreMomentum : 0.0
scoreBuy += flashSignal ? weightFlash : 0.0
scoreBuy += blinkSignal ? weightBlink : 0.0
scoreBuy += volumeSpike_AVP ? scoreVolume : 0.0
scoreBuy += priceStrength_Long ? scorePriceAction : 0.0
scoreBuy += reversalTrigger_Long ? scoreReversal : 0.0
scoreBuy += emaAlignment_Bull ? weightTrendAlign : 0.0
scoreBuy += strongUpTrend ? weightTrendAlign : 0.0
scoreBuy += highRisk_Long ? -1.2 : 0.0
scoreBuy += signalGreenDot ? 1.0 : 0.0
scoreBuy += isAMCUp ? 0.8 : 0.0
scoreBuy += isVssBuy ? 1.5 : 0.0
scoreBuy += isEMACrossUp ? 1.0 : 0.0
scoreBuy += signalRedX ? -1.0 : 0.0
scoreSell = 0.0
scoreSell += structSignalShort ? scoreStruct : 0.0
scoreSell += momentumShort ? scoreMomentum : 0.0
scoreSell += flashSignal ? weightFlash : 0.0
scoreSell += blinkSignal ? weightBlink : 0.0
scoreSell += volumeSpike_AVP ? scoreVolume : 0.0
scoreSell += priceStrength_Short ? scorePriceAction : 0.0
scoreSell += reversalTrigger_Short ? scoreReversal : 0.0
scoreSell += emaAlignment_Bear ? weightTrendAlign : 0.0
scoreSell += strongDownTrend ? weightTrendAlign : 0.0
scoreSell += highRisk_Short ? -1.2 : 0.0
scoreSell += signalRedX ? 1.0 : 0.0
scoreSell += isAMCDown ? 0.8 : 0.0
scoreSell += isVssSell ? 1.5 : 0.0
scoreSell += isEMACrossDown ? 1.0 : 0.0
scoreSell += signalGreenDot ? -1.0 : 0.0
compositeBuySignal = enableComposite and scoreBuy >= thresholdCompositeBuy
compositeSellSignal = enableComposite and scoreSell >= thresholdCompositeSell
if compositeBuySignal and compositeSellSignal
compositeBuySignal := false
compositeSellSignal := false
= calculateCompositeSignals()
// Final Entry Signals
entryCompositeBuySignal = compositeBuySignal and ta.rising(emaFast_ATG, 2)
entryCompositeSellSignal = compositeSellSignal and ta.falling(emaFast_ATG, 2)
Calculates weighted scores from independent modules and activates signals only when threshold requirements are met.
2. Smart Exit Hold Evaluation System
evaluateSmartHold() =>
compositeBuyRecentCount = 0
compositeSellRecentCount = 0
for i = 0 to signalLookbackBars - 1
compositeBuyRecentCount += compositeBuySignal ? 1 : 0
compositeSellRecentCount += compositeSellSignal ? 1 : 0
avgVolume = ta.sma(volume, 20)
volumeSpike = volume > avgVolume * volMultiplier
// MTF Bull/Bear conditions
mtf_bull = mtf_emaFast_final > mtf_emaSlow_final
mtf_bear = mtf_emaFast_final < mtf_emaSlow_final
emaBackupDivergence = math.abs(mtf_emaFast_backup - mtf_emaSlow_backup) / mtf_emaSlow_backup
emaBackupStrong = emaBackupDivergence > 0.008
mtfConflict_Long = inLong and mtf_bear and emaBackupStrong
mtfConflict_Short = inShort and mtf_bull and emaBackupStrong
// Layer 1: ATR-Based Dynamic Threshold (Market Volatility Intelligence)
atr_raw = ta.atr(atrLen)
atrValue = na(atr_raw) ? close * 0.02 : atr_raw
atrRatio = atrValue / close
dynamicThreshold = atrRatio > 0.02 ? 1.0 : (atrRatio > 0.01 ? 1.5 : 2.8)
// Layer 2: ROI-Conditional Time Intelligence (Selective Pressure)
timeMultiplier_Long = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure
holdTimer_Long <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base
holdTimer_Long <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter
1.3 // Loss positions 17+ bars: +30% stricter
timeMultiplier_Short = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure
holdTimer_Short <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base
holdTimer_Short <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter
1.3 // Loss positions 17+ bars: +30% stricter
// Dual-Layer Threshold Calculation
baseThreshold_Long = mtfConflict_Long ? dynamicThreshold + 1.0 : dynamicThreshold
baseThreshold_Short = mtfConflict_Short ? dynamicThreshold + 1.0 : dynamicThreshold
timeAdjustedThreshold_Long = baseThreshold_Long * timeMultiplier_Long
timeAdjustedThreshold_Short = baseThreshold_Short * timeMultiplier_Short
// Final Smart Hold Decision with Dual-Layer Intelligence
smartHold_Long = not mtfConflict_Long and smartScoreLong >= timeAdjustedThreshold_Long and compositeBuyRecentCount >= signalMinCount
smartHold_Short = not mtfConflict_Short and smartScoreShort >= timeAdjustedThreshold_Short and compositeSellRecentCount >= signalMinCount
= evaluateSmartHold()
Evaluates whether to hold positions past TP1/TP2/TP3 levels based on continued signal strength, volume confirmation, and multi-timeframe trend alignment
HOW TO USE THE STRATEGY
Step 1: Initial Setup
Apply strategy to your preferred timeframe (backtested on 15M)
Enable "Use Heikin-Ashi Base" for smoother signals in volatile markets
"Show EMA Lines" and "Show Ichimoku Cloud" are enabled for visual context
Set default quantities to match your risk management (5% equity default)
Step 2: Signal Recognition
Visual Signal Guide:
Visual Signal Guide - Complete Reference:
🔶 Red Diamond: Bearish momentum breakdown - short reversal signal
🔷 Blue Diamond: Strong bullish momentum - long reversal signal
🔵 Blue Dot: Volume-confirmed directional move - trend continuation
🟢 Green Dot: Bullish EMA crossover - trend reversal confirmation
🟠 Orange X: Oversold reversal setup - counter-trend opportunity
❌ Red X: Bearish EMA breakdown - trend reversal warning
✡ Star Uprising: Strong bullish convergence
💥 Ultra Entry: Ultra-rapid downward momentum acceleration
▲ VSS Long: Velocity-based bullish momentum confirmation
▼ VSS Short: Velocity-based bearish momentum confirmation
Step 3: Entry Execution
For Long Positions:
1. ✅ EMA1 crossed above EMA2 exactly 3 bars ago [ta.crossover(ema1,ema2) ]
2. ✅ Current EMA structure: EMA1 > EMA2 (maintained)
3. ✅ Composite score ≥ 5.0 points (6.5+ for 5-minute timeframes)
4. ✅ Cooldown period completed (no recent stop losses)
5. ✅ Volume spike confirmation (green dot/blue dot signals)
6. ✅ Bullish candle closes above EMA structure
For Short Positions:
1. ✅ EMA1 crossed below EMA2 exactly 3 bars ago [ta.crossunder(ema1,ema2) ]
2. ✅ Current EMA structure: EMA1 < EMA2 (maintained)
3. ✅ Composite score ≥ 5.4 points (7.0+ for 5-minute timeframes)
4. ✅ Cooldown period completed (no recent stop losses)
5. ✅ Momentum breakdown (red diamond/red X signals)
6. ✅ Bearish candle closes below EMA structure
🎯 Critical Timing Note: The strategy requires EMA crossover to have occurred 3 bars prior to entry, not at the current bar. This attempts to avoid premature entries and may improve signal reliability.
Step 4: Reading Market Context
EMA Ribbon Interpretation:
All EMAs ascending = Strong uptrend context
EMAs 1-3 above EMAs 4-8 = Bullish structure
Tight EMA spacing = Low volatility/consolidation
Wide EMA spacing = High volatility/trending
Ichimoku Cloud Context:
Price above cloud = Bullish environment
Price below cloud = Bearish environment
Cloud color intensity = Momentum strength
Thick cloud = Strong support/resistance
THE SMART EXIT GRID SYSTEM
Smart Exit Grid Approach:
The Smart Exit Grid uses dynamic hold evaluation that continuously analyzes market conditions after position entry. This differs from traditional fixed profit targets by adapting exit timing based on real-time signal strength.
How Smart Exit Grid System Works
The system operates through three evaluation phases:
Smart Score Calculation:
The smart score calculation aggregates 22 signal components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. MTF analysis provides additional confirmation as a separate validation layer.
Signal Stack Management:
The per-tick signal accumulation system monitors 22 active signal types with MTF providing trend validation and conflict detection as a separate confirmation layer.
Take Profit Progression:
Smart Exit Activation:
The QRE system activates Smart Exit Grid immediately upon position entry. When strategy.entry() executes, the system initializes monitoring systems designed to track position progress.
Upon position opening, holdTimer begins counting, establishing the foundation for subsequent decisions. The Smart Exit Grid starts accumulating signals from entry, with all 22 signal components beginning real-time tracking when the trade opens.
The system operates on continuous evaluation where smartScoreLong and smartScoreShort calculate from the first tick after entry. QRE's approach is designed to capture market structure changes, trend deteriorations, or signal pattern shifts that can trigger protective exits even before the first take profit level is reached.
This activation creates a proactive position management framework. The 8-candle sliding window starts from entry, meaning that if market conditions change rapidly after entry - due to news events, liquidity shifts, or technical changes - the system can respond within the configured lookback period.
TP Markers as Reference Points:
The TP1, TP2, and TP3 levels function as reference points rather than mandatory exit triggers. When longTP1Hit or shortTP1Hit conditions activate, they serve as profit confirmation markers that inform the Smart Exit algorithm about achieved reward levels, but don't automatically initiate position closure.
These TP markers enhance the Smart Exit decision matrix by providing profit context to ongoing signal evaluation. The system recognizes when positions have achieved target returns, but the actual exit decision remains governed by continuous smart score evaluation and signal stack analysis.
TP2 Reached: Enhanced Monitoring
TP2 represents significant profit capture with additional monitoring features:
This approach is designed to help avoid premature profit-taking during trending conditions. If TP2 is reached but smartScoreLong remains above the dynamic threshold and the 8-candle sliding window shows persistent signals, the position continues holding. If market structure deteriorates before reaching TP2, the Smart Exit can trigger closure based on signal analysis.
The visual TP circles that appear when levels are reached serve as performance tracking tools, allowing users to see how frequently entries achieve various profit levels while understanding that actual exit timing depends on market structure analysis.
Risk Management Systems:
Operating independently from the Smart Exit Grid are two risk management systems: the Trap Wick Detection Protocol and the Stop Loss Mechanism. These systems maintain override authority over other exit logic.
The Trap Wick System monitors for conditionBearTrapExit during long positions and conditionBullTrapExit during short positions. When detected, these conditions trigger position closure with state reset, bypassing Smart Exit evaluations. This system recognizes that certain candlestick patterns may indicate reversal risk.
Volatility Exit Monitoring: The strategy monitors for isStrongBearCandle combined with conditionBearTrapExit, recognizing when market structure may be shifting.
Volume Validation: Before exiting on volatility, the strategy requires volume confirmation: volume > ta.sma(volume, 20) * 1.8. This is designed to filter exits on weak, low-volume movements.
The Stop Loss Mechanism operates through multiple triggers including traditional price-based stops (longSLHit, shortSLHit) and early exit conditions based on smart score deterioration combined with negative ROI. The early exit logic activates when smartScoreLong < 1.0 or smartScoreShort < 1.0 while realROI < -0.9%.
These risk management systems are designed so that risk scenarios can trigger protective closure with state reset across all 22 signal counters, TP tracking variables, and smart exit states.
This architecture - Smart Exit activation, TP markers as navigation tools, and independent risk management - creates a position management system that adapts to market conditions while maintaining risk discipline through dedicated protection protocols.
TP3 Reached: Enhanced Protection
Once TP3 is hit, the strategy shifts into enhanced monitoring:
EMA Structure Monitoring: isEMAStructureDown becomes a primary exit trigger
MTF Alignment: The higher timeframe receives increased consideration
Wick Trap Priority: conditionBearTrapExit becomes an immediate exit signal
Approach Differences:
Traditional Fixed Exits:
Exit at predetermined levels regardless of market conditions
May exit during trend continuation
May exit before trend completion
Limited adaptation to changing volatility
Smart Exit Grid Approach:
Adaptive timing based on signal conditions
Exits when supporting signals weaken
Multi-timeframe validation for trend confirmation
Volume confirmation requirements for holds
Structural monitoring for trend analysis
Dynamic ATR-Based Smart Score Threshold System
Market Volatility Adaptive Scoring
// Real-time ATR Analysis
atr_raw = ta.atr(atrLen)
atrValue = na(atr_raw) ? close * 0.02 : atr_raw
atrRatio = atrValue / close
// Three-Tier Dynamic Threshold Matrix
dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold
(atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard
2.8) // Low volatility: Higher threshold
The market volatility adaptive scoring calculates real-time ATR with a 2% fallback for new markets. The atrRatio represents the relationship between current volatility and price, creating a foundation for threshold adjustment.
The three-tier dynamic threshold matrix responds to market conditions by adjusting requirements based on volatility levels: lowering thresholds during high volatility periods above 2% ATR ratio to 1.0 points, maintaining standard requirements at 1.5 points for medium volatility between 1-2%, and raising standards to 2.8 points during low volatility periods below 1%.
Profit-Loss Adaptive Management:
The system applies different evaluation criteria based on position performance:
Winning Positions (realROI ≥ 0%):
→ timeMultiplier = 1.0 (No additional pressure)
→ Maintains base threshold requirements
→ Allows natural progression to TP2/TP3 levels
Losing Positions (realROI < 0%):
→ Progressive time pressure activated
→ Increasingly strict requirements over time
→ Faster decision-making on underperforming trades
ROI-Adaptive Smart Hold Decision Process:
The strategy uses a profit-loss adaptive system:
Winning Position Management (ROI ≥ 0%):
✅ Standard threshold requirements maintained
✅ No additional time-based pressure applied
✅ Allows positions to progress toward TP2/TP3 levels
✅ timeMultiplier remains at 1.0 regardless of hold duration
Losing Position Management (ROI < 0%):
⚠️ Time-based threshold adjustments activated
⚠️ Progressive increase in required signal strength over time
⚠️ Earlier exit evaluation on underperforming positions
⚠️ timeMultiplier increases from 1.0 → 1.1 → 1.3 based on hold duration
Real-Time Monitoring:
Monitor Analysis Table → "Smart" filter → "Score" vs "Dynamic Threshold"
Winning positions: Evaluation based on signal strength deterioration only
Losing positions: Evaluation considers both signal strength and progressive time adjustments
Breakeven positions (0% ROI): Treated as winning positions - no time adjustments
This approach differentiates between winning and losing positions in the hold evaluation process, requiring higher signal thresholds for extended holding of losing positions while maintaining standard requirements for winning ones.
ROI-Conditional Decision Matrix Examples:
Scenario 1 - Winning Position in Any Market:
Position ROI: +0.8% → timeMultiplier = 1.0 (regardless of hold time)
ATR Medium (1.2%) → dynamicThreshold = 1.5
Final Threshold = 1.5 × 1.0 = 1.5 points ✅ Position continues
Scenario 2 - Losing Position, Extended Hold:
Position ROI: -0.5% → Time pressure activated
Hold Time: 20 bars → timeMultiplier = 1.3
ATR Low (0.8%) → dynamicThreshold = 2.8
Final Threshold = 2.8 × 1.3 = 3.64 points ⚡ Enhanced requirements
Scenario 3 - Fresh Losing Position:
Position ROI: -0.3% → Time pressure activated
Hold Time: 5 bars → timeMultiplier = 1.0 (still early)
ATR High (2.1%) → dynamicThreshold = 1.0
Final Threshold = 1.0 × 1.0 = 1.0 points 📊 Recovery opportunity
Scenario 4 - Breakeven Position:
Position ROI: 0.0% → timeMultiplier = 1.0 (no pressure)
Hold Time: 15 bars → No time penalty applied
Final Threshold = dynamicThreshold only ⚖️ Neutral treatment
🔄8-Candle Sliding Window Signal Rotation System
Composite Signal Counting Mechanism
// Dynamic Lookback Window (configurable: default 8)
signalLookbackBars = input.int(8, "Composite Lookback Bars", minval=1, maxval=50)
// Rolling Signal Analysis
compositeBuyRecentCount = 0
compositeSellRecentCount = 0
for i = 0 to signalLookbackBars - 1
compositeBuyRecentCount += compositeBuySignal ? 1 : 0
compositeSellRecentCount += compositeSellSignal ? 1 : 0
Candle Flow Example (8-bar window):
→
✓ ✓ ✗ ✓ ✗ ✓ ✗ ✓ 🗑️
New Signal Count = 5/8 signals in window
Threshold Check: 5 ≥ signalMinCount (2) = HOLD CONFIRMED
Signal Decay & Refresh Mechanism
// Signal Persistence Tracking
if compositeBuyRecentCount >= signalMinCount
smartHold_Long = true
else
smartHold_Long = false
The composite signal counting operates through a configurable sliding window. The system maintains rolling counters that scan backward through the specified number of candles.
During each evaluation cycle, the algorithm iterates through historical bars, incrementing counters when composite signals are detected. This creates a dynamic signal persistence measurement where recent signal density determines holding decisions.
The sliding window rotation functions like a moving conveyor belt where new signals enter while the oldest signals drop off. For example, in an 8-bar window, if 5 out of 8 recent candles showed composite buy signals, and the minimum required count is 2, the system confirms the hold condition. As new bars form, the window slides forward, potentially changing the signal count and triggering exit conditions when signal density falls below the threshold.
Signal decay and refresh occur continuously where smartHold_Long remains true only when compositeBuyRecentCount exceeds signalMinCount. When recent signal density drops below the minimum requirement, the system switches to exit mode.
Advanced Signal Stack Management - 22-Signal Real-Time Evaluation
// Long Position Signal Stacking (calc_on_every_tick=true)
if inLong
// Primary Reversal Signals
if signalRedDiamond: signalCountRedDiamond += 1 // -0.5 points
if signalStarUprising: signalCountStarUprising += 1 // +1.5 points
if entryUltraShort: signalCountUltra += 1 // -1.0 points
// Trend Confirmation Signals
if strongUpTrend: trendUpCount_Long += 1 // +1.5 points
if emaAlignment_Bull: bullAlignCount_Long += 1 // +1.0 points
// Risk Assessment Signals
if highRisk_Long: riskCount_Long += 1 // -1.5 points
if topZone: tzoneCount_Long += 1 // -0.5 points
The per-tick signal accumulation system operates with calc_on_every_tick=true for real-time responsiveness. During long positions, the system monitors primary reversal signals where Red Diamond signals subtract 0.5 points as reversal warnings, Star Uprising adds 1.5 points for continuation signals, and Ultra Short signals deduct 1.0 points as counter-trend warnings.
Trend confirmation signals provide weighted scoring where strongUpTrend adds 1.5 points for aligned momentum, emaAlignment_Bull contributes 1.0 point for structural support, and various EMA-based confirmations contribute to the overall score. Risk assessment signals apply negative weighting where highRisk_Long situations subtract 1.5 points, topZone conditions deduct 0.5 points, and other risk factors create defensive scoring adjustments.
The smart score calculation aggregates all 22 components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. This score updates continuously, providing the foundation for hold-or-exit decisions.
MULTI-TIMEFRAME (MTF) SYSTEM
MTF Data Collection
The strategy requests higher timeframe data (default 30-minute) for trend confirmation:
= request.security(syminfo.tickerid, mtfTimeframe, , lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_off)
MTF Watchtower System - Implementation Logic
The system employs a timeframe discrimination protocol where currentTFInMinutes is compared against a 30-minute threshold. This creates different operational behavior between timeframes:
📊 Timeframe Testing Results:
30M+ charts: Full MTF confirmation → Tested with full features
15M charts: Local EMA + adjusted parameters → Standard testing baseline
5M charts: Local EMA only → Requires parameter adjustment
1M charts: High noise → Limited testing conducted
When the chart timeframe is 30 minutes or above, the strategy activates useMTF = true and requests external MTF data through request.security(). For timeframes below 30 minutes, including your 5-minute setup, the system deliberately uses local EMA calculations to avoid MTF lag and data inconsistencies.
The triple-layer data sourcing architecture works as follows: timeframes from 1 minute to 29 minutes rely on chart-based EMA calculations for immediate responsiveness. Timeframes of 30 minutes and above utilize MTF data through the security function, with a backup system that doubles the EMA length (emaLen * 2) if MTF data fails. When MTF data is unavailable or invalid, the system falls back to local EMA as the final safety net.
Data validation occurs through a pipeline where mtf_dataValid checks not only for non-null values but also verifies that EMA values are positive above zero. The system tracks data sources through mtf_dataSource which displays "MTF Data" for successful external requests, "Backup EMA" for failed MTF with backup system active, or "Chart EMA" for local calculations.
🔄 MTF Smart Score Caching & Recheck System
// Cache Update Decision Logic
mtfSmartIntervalSec = input.int(300, "Smart Grid Recheck Interval (sec)") // 5-minute cache
canRecheckSmartScore = na(timenow) ? false :
(na(lastCheckTime) or (timenow - lastCheckTime) > mtfSmartIntervalSec * 1000)
// Cache Management
if canRecheckSmartScore
lastCheckTime := timenow
cachedSmartScoreLong := smartScoreLong // Store current calculation
cachedSmartScoreShort := smartScoreShort
The performance-optimized caching system addresses the computational intensity of continuous MTF analysis through intelligent interval management. The mtfSmartIntervalSec parameter, defaulting to 300 seconds (5 minutes), determines cache refresh frequency. The system evaluates canRecheckSmartScore by comparing current time against lastCheckTime plus the configured interval.
When cache updates trigger, the system stores current calculations in cachedSmartScoreLong and cachedSmartScoreShort, creating stable reference points that reduce excessive MTF requests. This cache management balances computational efficiency with analytical accuracy.
The cache versus real-time hybrid system creates a multi-layered decision matrix where immediate signals update every tick for responsive market reaction, cached MTF scores refresh every 5 minutes for stability filtering, dynamic thresholds recalculate every bar for volatility adaptation, and sliding window analysis updates every bar for trend persistence validation.
This architecture balances real-time signal detection with multi-timeframe strategic validation, creating adaptive trading intelligence that responds immediately to market changes while maintaining strategic stability through cached analysis and volatility-adjusted decision thresholds.
⚡The Execution Section Deep Dive
The execution section represents the culmination of all previous systems – where analysis transforms into action.
🚪 Entry Execution: The Gateway Protocol
Primary Entry Validation:
Entry isn't just about seeing a signal – it's about passing through multiple security checkpoints, each designed to filter out low-quality opportunities.
Stage 1: Signal Confirmation
entryCompositeBuySignal must be TRUE for longs
entryCompositeSellSignal must be TRUE for shorts
Stage 2: Enhanced Entry Validation
The strategy employs an "OR" logic system that recognizes different types of market opportunities:
Path A - Trend Reversal Entry:
When emaTrendReversal_Long triggers, it indicates the market structure is shifting in favor of the trade direction. This isn't just about a single EMA crossing – it represents a change in market momentum that experienced traders recognize as potential high-probability setups.
Path B - Momentum Breakout Entry:
The strongBullMomentum condition is where QRE identifies accelerating market conditions:
Criteria:
EMA1 rising for 3+ candles AND
EMA2 rising for 2+ candles AND
Close > 10-period high
This combination captures those explosive moves where the market doesn't just trend – it accelerates, creating momentum-driven opportunities.
Path C - Recovery Entry:
When previous exit states are clean (no recent stop losses), the strategy permits entry based purely on signal strength. This pathway is designed to help avoid the strategy becoming overly cautious after successful trades.
🛡️ The Priority Exit Matrix: When Rules Collide
Not all exit signals are created equal. QRE uses a strict hierarchy that is designed to avoid conflicting signals from causing hesitation:
Priority Level 1 - Exception Exits (Immediate Action):
Condition: TP3 reached AND Wick Trap detected
Action: Immediate exit regardless of other signals
Rationale: Historical analysis suggests wick traps at TP3 may indicate potential reversals
Priority Level 2 - Structural Breakdown:
Condition: TP3 active AND EMA structure deteriorating AND Smart Score insufficient
Logic: isEMAStructureDown AND NOT smartHold_Long
This represents the strategy recognizing that the underlying market structure that justified the trade is failing. It's like a building inspector identifying structural issues – you don't wait for additional confirmation.
Priority Level 3 - Enhanced Volatility Exits:
Conditions: TP2 active AND Strong counter-candle AND Wick trap AND Volume spike
Logic: Multiple confirmation required to reduce false exits
Priority Level 4 - Standard Smart Score Exits:
Condition: Any TP level active AND smartHold evaluates to FALSE
This is the bread-and-butter exit logic where signal deterioration triggers exit
⚖️ Stop Loss Management: Risk Control Protocol
Dual Stop Loss System:
QRE provides two stop loss modes that users can select based on their preference:
Fixed Mode (Default - useAdaptiveSL = false):
Uses predetermined percentage levels regardless of market volatility:
- Long SL = entryPrice × (1 - fixedRiskP - slipBuffer)
- Short SL = entryPrice × (1 + fixedRiskP + slipBuffer)
- Default: 0.6% risk + 0.3% slippage buffer = 0.9% total stop
- Consistent and predictable stop loss levels
- Recommended for users who prefer stable risk parameters
Adaptive Mode (Optional - useAdaptiveSL = true):
Dynamic system that adjusts stop loss based on market volatility:
- Base Calculation uses ATR (Average True Range)
- Long SL = entryPrice × (1 - (ATR × atrMultSL) / entryPrice - slipBuffer)
- Short SL = entryPrice × (1 + (ATR × atrMultSL) / entryPrice + slipBuffer)
- Automatically widens stops during high volatility periods
- Tightens stops during low volatility periods
- Advanced users can enable for volatility-adaptive risk management
Trend Multiplier Enhancement (Both Modes):
When strongUpTrend is detected for long positions, the stop loss receives 1.5x breathing room. Strong trends often have deeper retracements before continuing. This is designed to help avoid the strategy being shaken out of active trades by normal market noise.
Mode Selection Guidance:
- New Users: Start with Fixed Mode for predictable risk levels
- Experienced Users: Consider Adaptive Mode for volatility-responsive stops
- Volatile Markets: Adaptive Mode may provide better stop placement
- Stable Markets: Fixed Mode often sufficient for consistent risk management
Early Exit Conditions:
Beyond traditional stop losses, QRE implements "smart stops" that trigger before price-based stops:
Early Long Exit: (smartScoreLong < 1.0 OR prev5BearCandles) AND realROI < -0.9%
🔄 State Management: The Memory System
Complete State Reset Protocol:
When a position closes, QRE doesn't just wipe the slate clean – it performs a methodical reset:
TP State Cleanup:
All Boolean flags: tp1/tp2/tp3HitBefore → FALSE
All Reached flags: tp1/tp2/tp3Reached → FALSE
All Active flags: tp1/tp2/tp3HoldActive → FALSE
Signal Counter Reset:
Every one of the 22 signal counters returns to zero.
This is designed to avoid signal "ghosting" where old signals influence new trades.
Memory Preservation:
While operational states reset, certain information is preserved for learning:
killReasonLong/Short: Why did this trade end?
lastExitWasTP1/TP2/TP3: What was the exit quality?
reEntryCount: How many consecutive re-entries have occurred?
🔄 Re-Entry Logic: The Comeback System
Re-Entry Conditions Matrix:
QRE implements a re-entry system that recognizes not all exits are created equal:
TP-Based Re-Entry (Enabled):
Criteria: Previous exit was TP1, TP2, or TP3
Cooldown: Minimal or bypassed entirely
Logic: Target-based exits indicate potentially viable market conditions
EMA-Based Re-Entry (Conditional):
Criteria: Previous exit was EMA-based (structural change)
Requirements: Must wait for EMA confirmation in new direction
Minimum Wait: 5 candles
Advanced Re-Entry Features:
When adjustReEntryTargets is enabled, the strategy becomes more aggressive with re-entries:
Target Adjustment: TP1 multiplied by reEntryTP1Mult (default 2.0)
Stop Adjustment: SL multiplied by reEntrySLMult (default 1.5)
Logic: If we're confident enough to re-enter, we should be confident enough to hold for bigger moves
Performance Tracking: Strategy tracks re-entry win rate, average ROI, and total performance separately from initial entries for optimization analysis.
📊 Exit Reason Analytics: Learning from Every Trade
Kill Reason Tracking:
Every exit is categorized and stored:
"TP3 Exit–Wick Trap": Exit at target level with wick pattern detection
"Smart Exit–EMA Down": Structural breakdown exit
"Smart Exit–Volatility": Volatility-based protection exit
"Exit Post-TP1/TP2/TP3": Standard smart exit progression
"Long SL Exit" / "Short SL Exit": Stop loss exits
Performance Differentiation:
The strategy tracks performance by exit type, allowing for continuous analysis:
TP-based exits: Achieved target levels, analyze for pattern improvement
EMA-based exits: Mixed results, analyze for pattern improvement
SL-based exits: Learning opportunities, adjust entry criteria
Volatility exits: Protective measures, monitor performance
🎛️ Trailing Stop Implementation:
Conditional Trailing Activation:
Activation Criteria: Position profitable beyond trailingStartPct AND
(TP hold active OR re-entry trade)
Dynamic Trailing Logic:
Unlike simple trailing stops, QRE's implementation considers market context:
Trending Markets: Wider trail offsets to avoid whipsaws
Volatile Markets: Tighter offsets to protect gains
Re-Entry Trades: Enhanced trailing to maximize second-chance opportunities
Return-to-Entry Protection:
When deactivateOnReturn is enabled, the strategy will close positions that return to entry level after being profitable. This is designed to help avoid the frustration of watching profitable trades turn into losers.
🧠 How It All Works Together
The beauty of QRE lies not in any single component, but in how everything integrates:
The Entry Decision: Multiple pathways are designed to help identify opportunities while maintaining filtering standards.
The Progression System: Each TP level unlocks new protection features, like achieving ranks in a video game.
The Exit Matrix: Prioritized decision-making aims to reduce analysis paralysis while providing appropriate responses to different market conditions.
The Memory System: Learning from each trade while preventing contamination between separate opportunities.
The Re-Entry Logic: Re-entry system that balances opportunity with risk management.
This creates a trading system where entry conditions filter for quality, progression systems adapt to changing market conditions, exit priorities handle conflicting signals intelligently, memory systems learn from each trade cycle, and re-entry logic maximizes opportunities while managing risk exposure.
📊 ANALYSIS TABLE INTERPRETATION -
⚙️ Enabling Analysis Mode
Navigate to strategy settings → "Testing & Analysis" → Enable "Show Analysis Table". The Analysis Table displays different information based on the selected test filter and provides real-time insight into all strategy components, helping users understand current market conditions, position status, and system decision-making processes.
📋 Filter Mode Interpretations
"All" Mode (Default View):
Composite Section:
Buy Score: Aggregated strength from all 22 bullish signals (threshold 5.0+ triggers entry consideration)
Sell Score: Aggregated strength from all 22 bearish signals (threshold 5.4+ triggers entry consideration)
APEX Filters:
ATG Trend: Shows current trend direction analysis
Indicates whether momentum filters are aligned for directional bias
ReEntry Section:
Most Recent Exit: Displays exit type and timeframe since last position closure
Status: Shows if ReEntry system is Ready/Waiting/Disabled
Count: Current re-entry attempts versus maximum allowed attempts
Position Section (When Active):
Status: Current position state (LONG/SHORT/FLAT)
ROI: Dual calculation showing Custom vs Real ROI percentages
Entry Price: Original position entry level
Current Price: Live market price for comparison
TP Tracking: Progress toward profit targets
"Smart" Filter (Critical for Active Positions):
Smart Exit Section:
Hold Timer: Time elapsed since position opened (bar-based counting)
Status: Whether Smart Exit Grid is Enabled/Disabled
Score: Current smart score calculation from 22-component matrix
Dynamic Threshold: ATR-based minimum score required for holding
Final Threshold: Time and ROI-adjusted threshold actually used for decisions
Score Check: Pass/Fail based on Score vs Final Threshold comparison
Smart Hold: Current hold decision status
Final Hold: Final recommendation based on all factors
🎯 Advanced Smart Exit Debugging - ROI & Time-Based Threshold System
Understanding the Multi-Layer Threshold System:
Layer 1: Dynamic Threshold (ATR-Based)
atrRatio = ATR / close
dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold
(atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard
2.8) // Low volatility: Higher threshold
Layer 2: Time Multiplier (ROI & Duration-Based)
Winning Positions (ROI ≥ 0%):
→ timeMultiplier = 1.0 (No time pressure, regardless of hold duration)
Losing Positions (ROI < 0%):
→ holdTimer ≤ 8 bars: timeMultiplier = 1.0 (Early stage, standard requirements)
→ holdTimer 9-16 bars: timeMultiplier = 1.1 (10% stricter requirements)
→ holdTimer 17+ bars: timeMultiplier = 1.3 (30% stricter requirements)
Layer 3: Final Threshold Calculation
finalThreshold = dynamicThreshold × timeMultiplier
Examples:
- Winning Position: 2.8 × 1.0 = 2.8 (Always standard)
- Losing Position (Early): 2.8 × 1.0 = 2.8 (Same as winning initially)
- Losing Position (Extended): 2.8 × 1.3 = 3.64 (Much stricter)
Real-Time Debugging Display:
Smart Exit Section shows:
Score: 3.5 → Current smartScoreLong/Short value
Dynamic Threshold: 2.8 → Base ATR-calculated threshold
Final Threshold: 3.64 (ATR×1.3) → Actual threshold used for decisions
Score Check: FAIL (3.5 vs 3.64) → Pass/Fail based on final comparison
Final Hold: NO HOLD → Actual system decision
Position Status Indicators:
Winner + Early: ATR×1.0 (No pressure)
Winner + Extended: ATR×1.0 (No pressure - winners can run indefinitely)
Loser + Early: ATR×1.0 (Recovery opportunity)
Loser + Extended: ATR×1.1 or ATR×1.3 (Increasing pressure to exit)
MTF Section:
Data Source: Shows whether using MTF Data/EMA Backup/Local EMA
Timeframe: Configured watchtower timeframe setting
Data Valid: Confirms successful MTF data retrieval status
Trend Signal: Higher timeframe directional bias analysis
Close Price: MTF price data availability confirmation
"Composite" Filter:
Composite Section:
Buy Score: Real-time weighted scoring from multiple indicators
Sell Score: Opposing directional signal strength
Threshold: Minimum scores required for signal activation
Components:
Flash/Blink: Momentum acceleration indicators (F = Flash active, B = Blink active)
Individual filter contributions showing which specific signals are firing
"ReEntry" Filter:
ReEntry System:
System: Shows if re-entry feature is Enabled/Disabled
Eligibility: Conditions for new entries in each direction
Performance: Success metrics of re-entry attempts when enabled
🎯 Key Status Indicators
Status Column Symbols:
✓ = Condition met / System active / Signal valid
✗ = Condition not met / System inactive / No signal
⏳ = Cooldown active (waiting period)
✅ = Ready state / Good condition
🔄 = Processing / Transitioning state
🔍 Critical Reading Guidelines
For Active Positions - Smart Exit Priority Reading:
1. First Check Position Type:
ROI ≥ 0% = Winning Position (Standard requirements)
ROI < 0% = Losing Position (Progressive requirements)
2. Check Hold Duration:
Early Stage (≤8 bars): Standard multiplier regardless of ROI
Extended Stage (9-16 bars): Slight pressure on losing positions
Long Stage (17+ bars): Strong pressure on losing positions
3. Score vs Final Threshold Analysis:
Score ≥ Final Threshold = HOLD (Continue position)
Score < Final Threshold = EXIT (Close position)
Watch for timeMultiplier changes as position duration increases
4. Understanding "Why No Hold?"
Common scenarios when Score Check shows FAIL:
Losing position held too long (timeMultiplier increased to 1.1 or 1.3)
Low volatility period (dynamic threshold raised to 2.8)
Signal deterioration (smart score dropped below required level)
MTF conflict (higher timeframe opposing position direction)
For Entry Signal Analysis:
Composite Score Reading: Signal strength relative to threshold requirements
Component Analysis: Individual filter contributions to overall score
EMA Structure: Confirm 3-bar crossover requirement met
Cooldown Status: Ensure sufficient time passed since last exit
For ReEntry Opportunities (when enabled):
System Status: Availability and eligibility for re-engagement
Exit Type Analysis: TP-based exits enable immediate re-entry, SL-based exits require cooldown
Condition Monitoring: Requirements for potential re-entry signals
Debugging Common Issues:
Issue: "Score is high but no hold?"
→ Check Final Threshold vs Score (not Dynamic Threshold)
→ Losing position may have increased timeMultiplier
→ Extended hold duration applying pressure
Issue: "Why different thresholds for same score?"
→ Position ROI status affects multiplier
→ Time elapsed since entry affects multiplier
→ Market volatility affects base threshold
Issue: "MTF conflicts with local signals?"
→ Higher timeframe trend opposing position
→ System designed to exit on MTF conflicts
→ Check MTF Data Valid status
⚡ Performance Optimization Notes
For Better Performance:
Analysis table updates may impact performance on some devices
Use specific filters rather than "All" mode for focused monitoring
Consider disabling during live trading for optimal chart performance
Enable only when needed for debugging or analysis
Strategic Usage:
Monitor "Smart" filter when positions are active for exit timing decisions
Use "Composite" filter during setup phases for signal strength analysis
Reference "ReEntry" filter after position closures for re-engagement opportunities
Track Final Threshold changes to understand exit pressure evolution
Advanced Debugging Workflow:
Position Entry Analysis:
Check Composite score vs threshold
Verify EMA crossover timing (3 bars prior)
Confirm cooldown completion
Hold Decision Monitoring:
Track Score vs Final Threshold progression
Monitor timeMultiplier changes over time
Watch for MTF conflicts
Exit Timing Analysis:
Identify which threshold layer caused exit
Track performance by exit type
Analyze re-entry eligibility
This analysis system provides transparency into strategy decision-making processes, allowing users to understand how signals are generated and positions are managed according to the programmed logic during various market conditions and position states.
SIGNAL TYPES AND CHARACTERISTICS
🔥 Core Momentum Signals
Flash Signal
Calculation: ta.rma(math.abs(close - close ), 5) > ta.sma(math.abs(close - close ), 7)
Purpose: Detects sudden price acceleration using smoothed momentum comparison
Characteristics: Triggers when recent price movement exceeds historical average movement
Usage: Primary momentum confirmation across multiple composite calculations
Weight: 1.3 points in composite scoring
Blink Signal
Calculation: math.abs(ta.change(close, 1)) > ta.sma(math.abs(ta.change(close, 1)), 5)
Purpose: Identifies immediate price velocity spikes
Characteristics: More sensitive than Flash, captures single-bar momentum bursts
Usage: Secondary momentum confirmation, often paired with Flash
Weight: 1.3 points in composite scoring
⚡ Advanced Composite Signals
Apex Pulse Signal
Calculation: apexAngleValue > 30 or apexAngleValue < -30
Purpose: Detects extreme EMA angle momentum
Characteristics: Identifies when trend angle exceeds ±30 degrees
Usage: Confirms directional momentum strength in trend-following scenarios
Pressure Surge Signal
Calculation: volSpike_AVP and strongTrendUp_ATG
Purpose: Combines volume expansion with trend confirmation
Characteristics: Requires both volume spike and strong uptrend simultaneously
Usage: bullish signal for trend continuation
Shift Wick Signal
Calculation: ta.crossunder(ema1, ema2) and isWickTrapDetected and directionFlip
Purpose: Detects bearish reversal with wick trap confirmation
Characteristics: Combines EMA crossunder with upper wick dominance and directional flip
Usage: Reversal signal for trend change identification
🛡️ Trap Exit Protection Signals
Bear Trap Exit
Calculation: isUpperWickTrap and isBearEngulfNow
Conditions: Previous bullish candle with 80%+ upper wick, followed by current bearish engulfing
Purpose: Emergency exit signal for long positions
Priority: Highest - overrides all other hold conditions
Action: Immediate position closure with full state reset
Bull Trap Exit
Calculation: isLowerWickTrap and isBullEngulfNow
Conditions: Previous bearish candle with 80%+ lower wick, followed by current bullish engulfing
Purpose: Emergency exit signal for short positions
Priority: Highest - overrides all other hold conditions
Action: Immediate position closure with full state reset
📊 Technical Analysis Foundation Signals
RSI-MFI Hybrid System
Base Calculation: (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2
Oversold Threshold: < 35
Overbought Threshold: > 65
Weak Condition: < 35 and declining
Strong Condition: > 65 and rising
Usage: Momentum confirmation and reversal identification
ADX-DMI Trend Classification
Strong Up Trend: (adx > 25 and diplus > diminus and (diplus - diminus) > 5) or (ema1 > ema2 and ema2 > ema3 and ta.rising(ema2, 3))
Strong Down Trend: (adx > 20 and diminus > diplus - 5) or (ema1 < ema2 and ta.falling(ema1, 3))
Trend Weakening: adx < adx and adx < adx
Usage: Primary trend direction confirmation
Bollinger Band Squeeze Detection
Calculation: bbWidth < ta.lowest(bbWidth, 20) * 1.2
Purpose: Identifies low volatility periods before breakouts
Usage: Entry filter - avoids trades during consolidation
🎨 Visual Signal Indicators
Red X Signal
Calculation: isBearCandle and ta.crossunder(ema1, ema2)
Visual: Red X above price
Purpose: Bearish EMA crossunder with confirming candle
Composite Weight: +1.0 for short positions, -1.0 for long positions
Characteristics: Simple but effective trend change indicator
Green Dot Signal
Calculation: isBullCandle and ta.crossover(ema1, ema2)
Visual: Green dot below price
Purpose: Bullish EMA crossover with confirming candle
Composite Weight: +1.0 for long positions, -1.0 for short positions
Characteristics: Entry confirmation for trend-following strategies
Blue Diamond Signal
Trigger Conditions: amcBuySignal and score >= 4
Scoring Components: 11 different technical conditions
Key Requirements: AMC bullish + momentum rise + EMA expansion + volume confirmation
Visual: Blue diamond below price
Purpose: Bullish reversal or continuation signal
Characteristics: Multi-factor confirmation requiring 4+ technical alignments
Red Diamond Signal
Trigger Conditions: amcSellSignal and score >= 5
Scoring Components: 11 different technical conditions (stricter than Blue Diamond)
Key Requirements: AMC bearish + momentum crash + EMA compression + volume decline
Visual: Red diamond above price
Purpose: Potential bearish reversal or continuation signal
Characteristics: Requires higher threshold (5 vs 4) for more selective triggering
🔵 Specialized Detection Signals
Blue Dot Signal
Calculation: volumePulse and isCandleStrong and volIsHigh
Requirements: Volume > 2.0x MA, strong candle body > 35% of range, volume MA > 55
Purpose: Volume-confirmed momentum signal
Visual: Blue dot above price
Characteristics: Volume-centric signal for high-liquidity environments
Orange X Signal
Calculation: Complex multi-factor oversold reversal detection
Requirements: AMC oversold + wick trap + flash/blink + RSI-MFI oversold + bullish flip
Purpose: Oversold bounce signal with multiple confirmations
Visual: Orange X below price
Characteristics: Reversal signal requiring 5+ simultaneous conditions
VSS (Velocity Signal System)
Components: Volume spike + EMA angle + trend direction
Buy Signal: vssTrigger and vssTrendDir == 1
Sell Signal: vssTrigger and vssTrendDir == -1
Visual: Green/Red triangles
Purpose: Velocity-based momentum detection
Characteristics: Fast-response signal for momentum trading
⭐ Elite Composite Signals
Star Uprising Signal
Base Requirements: entryCompositeBuySignal and echoBodyLong and strongUpTrend and isAMCUp
Additional Confirmations: RSI hybrid strong + not high risk
Special Conditions: At bottom zone OR RSI bottom bounce OR strong volume bounce
Visual: Star symbol below price
Purpose: Bullish reversal signal from oversold conditions
Characteristics: Most selective bullish signal requiring multiple confirmations
Ultra Short Signal
Scoring System: 7-component scoring requiring 4+ points
Key Components: EMA trap + volume decline + RSI weakness + composite confirmation
Additional Requirements: Falling EMA structure + volume spike + flash confirmation
Visual: Explosion emoji above price
Purpose: Aggressive short entry for trend reversal or continuation
Characteristics: Complex multi-layered signal for experienced short selling
🎯 Composite Signal Architecture
Enhanced Composite Scoring
Long Composite: 15+ weighted components including structure, momentum, flash/blink, volume, price action, reversal triggers, trend alignment
Short Composite: Mirror structure with bearish bias
Threshold: 5.0 points required for signal activation
Conflict Resolution: If both long and short signals trigger simultaneously, both are disabled
Final Validation: Requires EMA momentum confirmation (ta.rising(emaFast_ATG, 2) for longs, ta.falling(emaFast_ATG, 2) for shorts)
Risk Assessment Integration
High Risk Long: RSI > 70 OR close > upper Bollinger Band 80%
High Risk Short: RSI < 30 OR close < lower Bollinger Band 80%
Zone Analysis: Top zone (95% of 50-bar high) vs Bottom zone (105% of 50-bar low)
Risk Penalty: High risk conditions subtract 1.5 points from composite scores
This signal architecture creates a multi-layered detection system where simple momentum signals provide foundation, technical analysis adds structure, visual indicators offer clarity, specialized detectors capture different market conditions, and composite signals identify potential opportunities while integrated risk assessment is designed to filter risky entries.
VISUAL FEATURES SHOWCASE
Ichimoku Cloud Visualization
Dynamic Color Intensity: Cloud transparency adapts to momentum strength - darker colors indicate stronger directional moves, while lighter transparency shows weakening momentum phases.
Gradient Color Mapping: Bullish momentum renders blue-purple spectrum with increasing opacity, while bearish momentum displays corresponding color gradients with intensity-based transparency.
Real-time Momentum Feedback: Color saturation provides immediate visual feedback on market structure strength, allowing traders to assess levels at a glance without additional indicators.
EMA Ribbon Bands
The 8-level exponential moving average system creates a comprehensive trend structure map with gradient color coding.
Signal Type Visualization
STRATEGY PROPERTIES & BACKTESTING DISCLOSURE
📊 Default Strategy Configuration:
✅ Initial Capital: 100,000 USD (realistic for average traders)
✅ Commission: 0.075% per trade (realistic exchange fees)
✅ Slippage: 3 ticks (market impact consideration)
✅ Position Size: 5% equity per trade (sustainable risk level)
✅ Pyramiding: Disabled (single position management)
✅ Sample Size: 185 trades over 12-month backtesting period
✅ Risk Management: Adaptive stop loss with maximum 1% risk per trade
COMPREHENSIVE BACKTESTING RESULTS
Testing Period & Market Conditions:
Backtesting Period: June 25, 2024 - June 25, 2025 (12 months)
Timeframe: 15-minute charts (MTF system active)
Market: BTCUSDT (Bitcoin/Tether)
Market Conditions: Full market cycle including volatility periods
Deep Backtesting: Enabled for maximum accuracy
📈 Performance Summary:
Total Return: +2.19% (+2,193.59 USDT)
Total Trades Executed: 185 trades
Win Rate: 34.05% (63 winning trades out of 185)
Profit Factor: 1.295 (gross profit ÷ gross loss)
Maximum Drawdown: 0.65% (653.17 USDT)
Risk-Adjusted Returns: Consistent with conservative risk management approach
📊 Detailed Trade Analysis:
Position Distribution:
Long Positions: 109 trades (58.9%) | Win Rate: 36.70%
Short Positions: 76 trades (41.1%) | Win Rate: 30.26%
Average Trade Duration: Optimized for 15-minute timeframe efficiency
Profitability Metrics:
Average Profit per Trade: 11.74 USDT (0.23%)
Average Winning Trade: 151.17 USDT (3.00%)
Average Losing Trade: 60.27 USDT (1.20%)
Win/Loss Ratio: 2.508 (winners are 2.5x larger than losses)
Largest Single Win: 436.02 USDT (8.69%)
Largest Single Loss: 107.41 USDT (controlled risk management)
💰 Financial Performance Breakdown:
Gross Profit: 9,523.93 USDT (9.52% of capital)
Gross Loss: 7,352.48 USDT (7.35% of capital)
Net Profit After Costs: 2,171.44 USDT (2.17%)
Commission Costs: 1,402.47 USDT (realistic trading expenses)
Maximum Equity Run-up: 2,431.66 USDT (2.38%)
⚖️ Risk Management Validation:
Maximum Drawdown: 0.65% showing controlled risk management
Drawdown Recovery: Consistent equity curve progression
Risk per Trade: Successfully maintained below 1.5% per position
Position Sizing: 5% equity allocation proved sustainable throughout testing period
📋 Strategy Performance Characteristics:
✅ Strengths Demonstrated:
Controlled Risk: Maximum drawdown well below industry standards (< 1%)
Positive Expectancy: Win/loss ratio of 2.5+ creates profitable edge
Consistent Performance: Steady equity curve without extreme volatility
Realistic Costs: Includes actual commission and slippage impacts
Sample Size: 185 trades during testing period
⚠️ Performance Considerations:
Win Rate: 34% win rate requires discipline to follow system signals
Market Dependency: Performance may vary significantly in different market conditions
Timeframe Sensitivity: Optimized for 15-minute charts; other timeframes may show different results
Slippage Impact: Real trading conditions may affect actual performance
📊 Benchmark Comparison:
Strategy Return: +2.19% over 12 months
Buy & Hold Bitcoin: +71.12% over same period
Strategy Advantage: Significantly lower drawdown and volatility
Risk-Adjusted Performance: Different risk profile compared to holding cryptocurrency
🎯 Real-World Application Insights:
Expected Trading Frequency:
Average: 15.4 trades per month (185 trades ÷ 12 months)
Weekly Frequency: Approximately 3-4 trades per week
Active Management: Requires regular monitoring during market hours
Capital Requirements:
Minimum Used in Testing: $10,000 for sustainable position sizing
Tested Range: $50,000-$100,000 for comfortable risk management
Commission Impact: 0.075% per trade totaled 1.4% of capital over 12 months
⚠️ IMPORTANT BACKTESTING DISCLAIMERS:
📈 Performance Reality:
Past performance does not guarantee future results. Backtesting results represent hypothetical performance and may not reflect actual trading outcomes due to market changes, execution differences, and emotional factors.
🔄 Market Condition Dependency:
This strategy's performance during the tested period may not be representative of performance in different market conditions, volatility regimes, or trending vs. sideways markets.
💸 Cost Considerations:
Actual trading costs may vary based on broker selection, market conditions, and trade size. Commission rates and slippage assumptions may differ from real-world execution.
🎯 Realistic Expectations:
The 34% win rate requires psychological discipline to continue following signals during losing streaks. Risk management and position sizing are critical for replicating these results.
⚡ Technology Dependencies:
Strategy performance assumes reliable internet connection, platform stability, and timely signal execution. Technical failures may impact actual results.
CONFIGURATION OPTIMIZATION
5-Minute Timeframe Optimization (Advanced Users Only)
⚠️ Important Warning: 5-minute timeframes operate without MTF confirmation, resulting in reduced signal quality and higher false signal rates.
Example 5-Minute Parameters:
Composite Thresholds: Long 6.5, Short 7.0 (vs 15M default 5.0/5.4)
Signal Lookback Bars: 12 (vs 15M default 8)
Volume Multiplier: 2.2 (vs 15M default 1.8)
MTF Timeframe: Disabled (automatic below 30M)
Risk Management Adjustments:
Position Size: Reduce to 3% (vs 5% default)
TP1: 0.8%, TP2: 1.2%, TP3: 2.0% (tighter targets)
SL: 0.8% (tighter stop loss)
Cooldown Minutes: 8 (vs 5 default)
Usage Notes for 5-Minute Trading:
- Wait for higher composite scores before entry
- Require stronger volume confirmation
- Monitor EMA structure more closely
15-Minute Scalping Setup:
TP1: 1.0%, TP2: 1.5%, TP3: 2.5%
Composite Threshold: 5.0 (higher filtering)
TP ATR Multiplier: 7.0
SL ATR Multiplier: 2.5
Volume Multiplier: 1.8 (requires stronger confirmation)
Hold Time: 2 bars minimum
3-Hour Swing Setup:
TP1: 2.0%, TP2: 4.0%, TP3: 8.0%
Composite Threshold: 4.5 (more signals)
TP ATR Multiplier: 8.0
SL ATR Multiplier: 3.2
Volume Multiplier: 1.2
Hold Time: 6 bars minimum
Market-Specific Adjustments
High Volatility Periods:
Increase ATR multipliers (TP: 2.0x, SL: 1.2x)
Raise composite thresholds (+0.5 points)
Reduce position size
Enable cooldown periods
Low Volatility Periods:
Decrease ATR multipliers (TP: 1.2x, SL: 0.8x)
Lower composite thresholds (-0.3 points)
Standard position sizing
Disable extended cooldowns
News Events:
Temporarily disable strategy 30 minutes before major releases
Increase volume requirements (2.0x multiplier)
Reduce position sizes by 50%
Monitor for unusual price action
RISK MANAGEMENT
Dual ROI System: Adaptive vs Fixed Mode
Adaptive RR Mode:
Uses ATR (Average True Range) for automatic adjustment
TP1: 1.0x ATR from entry price
TP2: 1.5x ATR from entry price
TP3: 2.0x ATR from entry price
Stop Loss: 1.0x ATR from entry price
Automatically adjusts to market volatility
Fixed Percentage Mode:
Uses predetermined percentage levels
TP1: 1.0% (default)
TP2: 1.5% (default)
TP3: 2.5% (default)
Stop Loss: 0.9% total (0.6% risk tolerance + 0.3% slippage buffer)(default)
Consistent levels regardless of volatility
Mode Selection: Enable "Use Adaptive RR" for ATR-based targets, disable for fixed percentages. Adaptive mode works better in varying volatility conditions, while fixed mode provides predictable risk/reward ratios.
Stop Loss Management
In Adaptive SL Mode:
Automatically scales with market volatility
Tight stops during low volatility (smaller ATR)
Wider stops during high volatility (larger ATR)
Include 0.3% slippage buffer in both modes
In Fixed Mode:
Consistent percentage-based stops
2% for crypto, 1.5% for forex, 1% for stocks
Manual adjustment needed for different market conditions
Trailing Stop System
Configuration:
Enable Trailing: Activates dynamic stop loss adjustment
Start Trailing %: Profit level to begin trailing (default 1.0%)
Trailing Offset %: Distance from current price (default 0.5%)
Close if Return to Entry: Optional immediate exit if price returns to entry level
Operation: Once position reaches trailing start level, stop loss automatically adjusts upward (longs) or downward (shorts) maintaining the offset distance from favorable price movement.
Timeframe-Specific Risk Considerations
15-Minute and Above (Tested):
✅ Full MTF system active
✅ Standard risk parameters apply
✅ Backtested performance metrics valid
✅ Standard position sizing (5%)
5-Minute Timeframes (Advanced Only):
⚠️ MTF system inactive - local signals only
⚠️ Higher false signal rate expected
⚠️ Reduced position sizing preferred (3%)
⚠️ Tighter stop losses required (0.8% vs 1.2%)
⚠️ Requires parameter optimization
⚠️ Monitor performance closely
1-Minute Timeframes (Limited Testing):
❌ Excessive noise levels
❌ Strategy not optimized for this frequency
Risk Management Practices
Allocate no more than 5% of your total investment portfolio to high-risk trading
Never trade with funds you cannot afford to lose
Thoroughly backtest and validate the strategy with small amounts before full implementation
Always maintain proper risk management and stop-loss settings
IMPORTANT DISCLAIMERS
Performance Disclaimer
Past performance does not guarantee future results. All trading involves substantial risk of loss. This strategy is provided for informational purposes and does not constitute financial advice.
Market Risk
Cryptocurrency and forex markets are highly volatile. Prices can move rapidly against positions, resulting in significant losses. Users should never risk more than they can afford to lose.
Strategy Limitations
This strategy relies on technical analysis and may not perform well during fundamental market shifts, news events, or unprecedented market conditions. No trading strategy can guarantee 100% success or eliminate the risk of loss.
Legal Compliance
You are responsible for compliance with all applicable regulations and laws in your jurisdiction. Consult with licensed financial professionals when necessary.
User Responsibility
Users are responsible for their own trading decisions, risk management, and compliance with applicable regulations in their jurisdiction.
EMA Curl Strength+EMA Curl Strength+
Description:
This indicator provides a statistically normalized view of EMA slope momentum using Z-score transformation. By evaluating the rate of change of an EMA and comparing it against its historical behavior, the script highlights momentum shifts in a dynamic, adaptive way.
⸻
How It Works:
• Calculates the slope (percentage change) of a chosen EMA.
• Normalizes the slope using Z-score over a custom lookback period.
• Smooths the resulting signal and computes two signal lines for comparison.
• Assigns dynamic colors based on user-defined Z-score thresholds for mild, moderate, and strong momentum in both directions.
⸻
Visual Features:
• Gradient fill between the Z Curl Line and Signal 1 to highlight slope acceleration.
• Histogram showing the difference between the Z Curl Line and its signal.
• Optional signal crossover shapes between configurable pairs (e.g., Z Curl vs. Signal).
• Background highlights when the Z Curl Line exceeds ±2, indicating strong trending behavior.
⸻
Customization:
• Adjustable EMA length, smoothing lengths, signal lengths, histogram smoothing, and Z-score lookback.
• Separate color controls for:
• Z-score strength bands (mild/moderate/strong up/down)
• Histogram bars
• Signal lines
• Background highlight zones
• Crossover shapes
⸻
Use Cases:
• Momentum Confirmation: Confirm strength when Z Curl exceeds ±2 with matching background highlights.
• Trend Entry Timing: Look for trades when Z Curl crosses above or below the 0-line.
• Scalping: Capture quick directional moves when momentum accelerates.
• Trend Following: Use strong Z Curl values to confirm trade direction and filter sideways action.
• Divergence Detection: Spot divergences between price and Z Curl movement to anticipate reversals.
RSI with 2-Pole FilterA momentum indicator that tells you if a stock is overbought or oversold.
RSI goes between 0 and 100.
70 = overbought (might fall)
<30 = oversold (might rise)
It often looks jagged or choppy on volatile days.
Think of this filter like a momentum smoother:
It still follows RSI closely,
But it doesn’t react to every little jiggle in price,
Which helps avoid false signals.
it keeps track of:
The current RSI,
The last 2 RSI values (inputs), and
The last 2 outputs (filtered RSIs).
It uses feedback to shape the output based on previous values, making it smoother than a simple moving average.
Degen Screener – ALTs vs. BTCDegen Screener – ALTs vs. BTC
🛠️ What This Script Does:
This multi-asset screener monitors up to 10 cryptocurrencies and compares their RSI strength relative to Bitcoin (BTC) — acting like BTC is the "north star." It's perfect for catching early shifts in momentum across the crypto market.
🎨 Color Logic:
RSI Column:
RSI < 30 → Green (oversold)
RSI > 70 → Red (overbought)
In between → Gray
Relative RSI Column:
0 → Green (stronger than BTC)
< 0 → Red (weaker than BTC)
Trend Column:
🤑 → Bullish shift (green background)
🖕 → Bearish shift (red background)
🔔 Alert Conditions:
Alerts fire when all three of these are true:
RSI is below 30 (oversold)
The asset is stronger than BTC
Momentum is turning bullish (🤑)
Perfect for spotting early reversals in oversold altcoins.
✅ How to Use:
Add the script to any chart (doesn’t matter which asset)
Customize the list of up to 10 symbols
Set your timeframe
Enable the alert condition: Relative RSI Signal
💡 Notes:
Script runs on whatever chart you’re on, but it pulls data from the 10 assets you select on your indicator.
⚠️ Disclaimer:
This tool is for educational and informational purposes only. It is not financial advice. Always do your own research.
RSI Mansfield +RSI Mansfield+ – Adaptive Relative Strength Indicator with Divergences
Overview
RSI Mansfield+ is an advanced relative strength indicator that compares your instrument’s performance against a configurable benchmark index or asset (e.g., Bitcoin Dominance, S&P 500). It combines Mansfield normalization, adaptive smoothing techniques, and automatic detection of bullish and bearish divergences (regular and hidden), delivering a comprehensive tool for assessing relative strength across any market and timeframe.
Originality and Motivation
Unlike traditional relative strength scripts, this indicator introduces several distinctive improvements:
Mansfield Normalization: Scales the ratio between the asset and the benchmark relative to its moving average, transforming it into a normalized oscillator that fluctuates around zero, making it easier to spot outperformance or underperformance.
Adaptive Smoothing: Automatically selects whether to use EMA or SMA based on the market type (crypto or stocks) and timeframe (intraday, daily, weekly, monthly), avoiding manual configuration and providing more robust results under varying volatility conditions.
Divergence Detection: Identifies four types of divergences in the Mansfield oscillator to help anticipate potential reversal points or trend confirmations.
Multi-Market Support: Offers benchmark selection among major crypto and global stock indices from a single input.
These enhancements make RSI Mansfield+ more practical and powerful than conventional relative strength scripts with static benchmarks or without divergence capabilities.
Core Concepts
Relative Strength (RS): Compares price evolution between your asset and the selected benchmark.
Mansfield Normalization: Measures how much the RS deviates from its historical moving average, expressed as a scaled oscillator.
Divergences: Detects regular and hidden bullish or bearish divergences within the Mansfield oscillator.
Timeframe Adaptation: Dynamically adjusts moving average lengths based on timeframe and market type.
How It Works
Benchmark Selection
Choose among over 10 indices or market domains (BTC Dominance, ETH Dominance, S&P 500, European indices, etc.).
Ratio Calculation
Computes the price-to-benchmark ratio and smooths it with the adaptive moving average.
Normalization and Scaling
Transforms deviations into a Mansfield oscillator centered around zero.
Dynamic Coloring
Green indicates relative outperformance, red signals underperformance.
Divergence Detection
Automatically identifies bullish and bearish (regular and hidden) divergences by comparing oscillator pivots against price pivots.
Baseline Reference
A clear zero line helps interpret relative strength trends.
Usage Guidelines
Benchmark Comparison
Ideal for traders analyzing whether an asset is outperforming or lagging its sector or market.
Divergence Analysis
Helps detect potential reversal or continuation signals in relative strength.
Multi-Timeframe Compatibility
Can be applied to intraday, daily, weekly, or monthly charts.
Interpretation
Oscillator >0 and green: outperforming the benchmark.
Oscillator <0 and red: underperforming.
Bullish divergences: potential relative strength reversal to the upside.
Bearish divergences: possible loss of momentum or reversal to the downside.
Credits
The concept of Mansfield Relative Strength is based on Stan Weinstein’s original work on relative performance analysis. This script was built entirely from scratch in TradingView Pine Script v6, incorporating original logic for adaptive smoothing, normalized scaling, and divergence detection, without reusing any external open-source code.
Divergence Strategy [Trendoscope®]🎲 Overview
The Divergence Strategy is a sophisticated TradingView strategy that enhances the Divergence Screener by adding automated trade signal generation, risk management, and trade visualization. It leverages the screener’s robust divergence detection to identify bullish, bearish, regular, and hidden divergences, then executes trades with precise entry, stop-loss, and take-profit levels. Designed for traders seeking automated trading solutions, this strategy offers customizable trade parameters and visual feedback to optimize performance across various markets and timeframes.
For core divergence detection features, including oscillator options, trend detection methods, zigzag pivot analysis, and visualization, refer to the Divergence Screener documentation. This description focuses on the strategy-specific enhancements for automated trading and risk management.
🎲 Strategy Features
🎯Automated Trade Signal Generation
Trade Direction Control : Restrict trades to long-only or short-only to align with market bias or strategy goals, preventing conflicting orders.
Divergence Type Selection : Choose to trade regular divergences (bullish/bearish), hidden divergences, or both, targeting reversals or trend continuations.
Entry Type Options :
Cautious : Enters conservatively at pivot points and exits quickly to minimize risk exposure.
Confident : Enters aggressively at the latest price and holds longer to capture larger moves.
Mixed : Combines conservative entries with delayed exits for a balanced approach.
Market vs. Stop Orders: Opt for market orders for instant execution or stop orders for precise price entry.
🎯 Enhanced Risk Management
Risk/Reward Ratio : Define a risk-reward ratio (default: 2.0) to set profit targets relative to stop-loss levels, ensuring consistent trade sizing.
Bracket Orders : Trades include entry, stop-loss, and take-profit levels calculated from divergence pivot points, tailored to the entry type and risk-reward settings.
Stop-Loss Placement : Stops are strategically set (e.g., at recent pivot or last price point) based on entry type, balancing risk and trade validity.
Order Cancellation : Optionally cancel pending orders when a divergence is broken (e.g., price moves past the pivot in the wrong direction), reducing invalid trades. This feature is toggleable for flexibility.
🎯 Trade Visualization
Target and Stop Boxes : Displays take-profit (lime) and stop-loss (orange) levels as boxes on the price chart, extending 10 bars forward for clear visibility.
Dynamic Trade Updates : Trade visualizations are added, updated, or removed as trades are executed, canceled, or invalidated, ensuring accurate feedback.
Overlay Integration : Trade levels overlay the price chart, complementing the screener’s oscillator-based divergence lines and labels.
🎯 Strategy Default Configuration
Capital and Sizing : Set initial capital (default: $1,000,000) and position size (default: 20% of equity) for realistic backtesting.
Pyramiding : Allows up to 4 concurrent trades, enabling multiple divergence-based entries in trending markets.
Commission and Margin : Accounts for commission (default: 0.01%) and margin (100% for long/short) to reflect trading costs.
Performance Optimization : Processes up to 5,000 bars dynamically, balancing historical analysis and real-time execution.
🎲 Inputs and Configuration
🎯Trade Settings
Direction : Select Long or Short (default: Long).
Divergence : Trade Regular, Hidden, or Both divergence types (default: Both).
Entry/Exit Type : Choose Cautious, Confident, or Mixed (default: Cautious).
Risk/Reward : Set the risk-reward ratio for profit targets (default: 2.0).
Use Market Order : Enable market orders for immediate entry (default: false, uses limit orders).
Cancel On Break : Cancel pending orders when divergence is broken (default: true).
🎯Inherited Settings
The strategy inherits all inputs from the Divergence Screener, including:
Oscillator Settings : Oscillator type (e.g., RSI, CCI), length, and external oscillator option.
Trend Settings : Trend detection method (Zigzag, MA Difference, External), MA type, and length.
Zigzag Settings : Zigzag length (fixed repaint = true).
🎲 Entry/Exit Types for Divergence Scenarios
The Divergence Strategy offers three Entry/Exit Type options—Cautious, Confident, and Mixed—which determine how trades are entered and exited based on divergence pivot points. This section explains how these settings apply to different divergence scenarios, with placeholders for screenshots to illustrate each case.
The divergence pattern forms after 3 pivots. The stop and entry levels are formed on one of these levels based on Entry/Exit types.
🎯Bullish Divergence (Reversal)
A bullish divergence occurs when price forms a lower low, but the oscillator forms a higher low, signaling a potential upward reversal.
💎 Cautious:
Entry : At the pivot high point for a conservative entry.
Exit : Stop-loss at the last pivot point (previous low that is higher than the current pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Entry : At the last pivot low, (previous low which is higher than the current pivot low) for an aggressive entry.
Exit : Stop-loss at recent pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
💎Mixed:
Entry : At the pivot high point (conservative).
Exit : Stop-loss at the recent pivot point that has resulted in lower low (lazy exit). Canceled if price breaks below the pivot.
Behavior : Balances entry caution with extended holding for trend continuation.
🎯Bearish Divergence (Reversal)
A bearish divergence occurs when price forms a higher high, but the oscillator forms a lower high, indicating a potential downward reversal.
💎Cautious:
Entry : At the pivot low point (lower high) for a conservative short entry.
Exit : Stop-loss at the previous pivot high point (previous high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident:
Entry : At the last price point (previous high) for an aggressive short entry.
Exit : Stop-loss at the pivot point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Enters early to maximize trend continuation, holding longer.
💎Mixed:
Entry : At the previous piot high point (conservative).
Exit : Stop-loss at the last price point (delayed exit). Canceled if price breaks above the pivot.
Behavior : Combines conservative entry with extended holding for downtrend gains.
🎯Bullish Hidden Divergence (Continuation)
A bullish hidden divergence occurs when price forms a higher low, but the oscillator forms a lower low, suggesting uptrend continuation. In case of Hidden bullish divergence, b]Entry is always on the previous pivot high (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the recent pivot low point (higher than previous pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Exit : Stop-loss at previous pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
🎯Bearish Hidden Divergence (Continuation)
A bearish hidden divergence occurs when price forms a lower high, but the oscillator forms a higher high, suggesting downtrend continuation. In case of Hidden Bearish divergence, b]Entry is always on the previous pivot low (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the latest pivot high point (which is a lower high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident/Mixed:
Exit : Stop-loss at the previous pivot high point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Uses the late exit point to hold longer.
🎲 Usage Instructions
🎯Add to Chart:
Add the Divergence Strategy to your TradingView chart.
The oscillator and divergence signals appear in a separate pane, with trade levels (target/stop boxes) overlaid on the price chart.
🎯Configure Settings:
Adjust trade settings (direction, divergence type, entry type, risk-reward, market orders, cancel on break).
Modify inherited Divergence Screener settings (oscillator, trend method, zigzag length) as needed.
Enable/disable alerts for divergence notifications.
🎯Interpret Signals:
Long Trades: Triggered on bullish or bullish hidden divergences (if allowed), shown with green/lime lines and labels.
Short Trades: Triggered on bearish or bearish hidden divergences (if allowed), shown with red/orange lines and labels.
Monitor lime (target) and orange (stop) boxes for trade levels.
Review strategy performance metrics (e.g., profit/loss, win rate) in the strategy tester.
🎯Backtest and Optimize:
Use TradingView’s strategy tester to evaluate performance on historical data.
Fine-tune risk-reward, entry type, position sizing, and cancellation settings to suit your market and timeframe.
For questions, suggestions, or support, contact Trendoscope via TradingView or official support channels. Stay tuned for updates and enhancements to the Divergence Strategy!
Crowding model ║ BullVision🔬 Overview
The Crypto Crowding Model Pro is a sophisticated analytical tool designed to visualize and quantify market conditions across multiple cryptocurrencies. By leveraging Relative Strength Index (RSI) and Z-score calculations, this indicator provides traders with an intuitive and detailed snapshot of current crypto market dynamics, highlighting areas of extreme momentum, crowded trades, and potential reversal points.
⚙️ Key Concepts
📊 RSI and Z-Score Analysis
RSI (Relative Strength Index) evaluates the momentum and strength of each cryptocurrency, identifying overbought or oversold conditions.
Z-Score Normalization measures each asset's current price deviation relative to its historical average, identifying statistically significant extremes.
🎯 Crowding Analytics
An integrated analytics panel provides real-time crowding metrics, quantifying market sentiment into four distinct categories:
🔥 FOMO (Fear of Missing Out): High momentum, potential exhaustion.
❄️ Fear: Low momentum, potential reversal or consolidation.
📈 Recovery: Moderate upward momentum after a downward trend.
💪 Strength: Stable bullish conditions with sustained momentum.
🖥️ Visual Scatter Plot
Assets are plotted on a dynamic scatter plot, positioning each cryptocurrency according to its RSI and Z-score.
Color coding, symbol shapes, and sizes help quickly identify main market segments (BTC, ETH, TOTAL, OTHERS) and individual asset conditions.
🧩 Quadrant Classification
Assets are categorized into four quadrants based on their momentum and deviation:
Overbought Extended: High RSI and positive Z-score.
Recovery Phase: Low RSI but positive Z-score.
Oversold Compressed: Low RSI and negative Z-score.
Strong Consolidation: High RSI but negative Z-score.
🔧 User Customization
🎨 Visual Settings
Bar Scale: Adjust the scatter plot visual scale.
Asset Visibility: Optionally display key market benchmarks (TOTAL, BTC, ETH, OTHERS).
Gradient Background: Enhances visual interpretation of asset clusters.
Crowding Analytics Panel: Toggle the analytics panel on/off.
📊 Indicator Parameters
RSI Length: Defines the calculation period for RSI.
Z-score Lookback: Historical lookback period for normalization.
Crowding Alert Threshold: Sets alert sensitivity for crowded market conditions.
🎯 Zone Settings
Quadrant Labels: Displays descriptive labels for each quadrant.
Danger Zones: Highlights extreme RSI levels indicative of heightened market risk.
📈 Visual Output
Dynamic Scatter Plot: Visualizes asset positioning clearly and intuitively.
Gradient and Grid: Professional gridlines and subtle gradient backgrounds assist visual assessment.
Danger Zone Highlights: Visually indicates RSI extremes to warn of potential market turning points.
Crowding Analytics Panel: Real-time summary of market sentiment and asset distribution.
🔍 Use Cases
This indicator is particularly beneficial for traders and analysts looking to:
Identify crowded trades and potential reversal points.
Quickly assess overall market sentiment and individual asset strength.
Integrate a robust momentum analysis into broader technical or fundamental strategies.
Enhance market timing and improve risk management decisions.
⚠️ Important Notes
This indicator does not provide explicit buy or sell signals.
It is intended solely for informational, analytical, and educational purposes.
Past performance and signals are not indicative of future market results.
Always combine with additional tools and analysis as part of comprehensive decision-making.
[Top] VWAP + RSI Divergence IndicatorThe “VWAP RSI Divergence Indicator” combines the Volume Weighted Average Price (VWAP), Relative Strength Index (RSI), divergence detection, and volume confirmation to identify high-probability trading opportunities.
How It Works:
The indicator integrates three powerful methodologies:
1. Volume Weighted Average Price (VWAP):
VWAP calculates an average price weighted by volume, providing critical insights into the fair value of an asset within the trading session.
Includes standard deviation bands (+1/-1 and +2/-2) around the VWAP, offering key levels of support, resistance, and price extremities.
2. Relative Strength Index (RSI):
A momentum oscillator that measures the speed and change of recent price movements.
RSI levels define overbought and oversold conditions, offering traders insight into potential reversal zones.
3. Divergence Detection:
Identifies divergences between price action and RSI, signaling potential reversals or continuations.
Detects both Regular Divergences (signifying potential reversals) and Hidden Divergences (indicating possible continuation of current trends).
Core Features:
Real-Time Divergence Detection: Automatically detects and clearly labels Regular and Hidden Divergences with included tooltips to help you identify trading opportunities.
VWAP and Standard Deviation Bands: Visualizes important dynamic support/resistance levels on the chart.
RSI-Based Heat Map: Offers intuitive heat map coloring between standard deviation bands, colored dynamically according to RSI levels and divergence activity.
Optional Volume-Based Candle Coloring: Enhances visual insight by coloring candles according to volume relative to a moving average.
Customizable Alerts: Provides alerts for divergences and standard deviation band breaches, enabling traders to act swiftly.
What Makes It Unique:
Integrated Divergence and VWAP Analysis: Unlike typical divergence indicators, this tool uniquely combines RSI divergence signals with VWAP analysis, enhancing signal reliability by considering both price momentum and volume-weighted price dynamics.
Dynamic RSI Heat Map and Volume Coloring: Incorporates advanced visual customization through dynamic coloring based on RSI levels and divergences, as well as volume-based bar coloring, designed to allow you to understand detailed information at a glance.
How to Use:
Identify Divergences: Watch for divergence labels indicating potential reversals (Regular Divergence) or continuations (Hidden Divergence).
Monitor VWAP Bands: Use VWAP bands as dynamic support/resistance levels, particularly observing price reactions at +1/-1 and +2/-2 standard deviation extremes.
Volume Confirmation: Combine divergence signals with volume-colored bars to confirm strength or weakness behind potential moves.
Leverage Alerts: Enable customizable alerts to stay promptly informed about key divergences and price extremes, ensuring timely decision-making.
Zero-Lag RSI DivergenceZero-Lag RSI Divergence
Overview
This indicator identifies RSI divergences in real-time without delay, providing immediate signals as price-momentum discrepancies develop. The indicator analyzes price action against RSI momentum across dual configurable periods, enabling traders to detect potential reversal opportunities with zero lag.
Key Features
Instant Divergence Detection : Identifies bullish and bearish divergences immediately upon formation without waiting for candle confirmation or historical validation. This eliminates signal delay but may increase false signals due to higher sensitivity.
Dual Period Analysis : Configure detection across two independent cycles - Short Period (default 15) and Long Period (default 50) - allowing for multi-timeframe divergence analysis and enhanced signal validation across different market conditions.
Visual Divergence Lines : Automatically draws dashed lines connecting divergence points between price highs/lows and corresponding RSI peaks/troughs, clearly illustrating the momentum-price relationship.
Customizable RSI Parameters : Adjustable RSI length (default 14) allows optimization for different market volatility and trading timeframes.
How It Works
The indicator continuously monitors price action patterns and RSI momentum:
- Bullish Divergence : Detected when price makes lower lows while RSI makes higher lows, suggesting potential upward momentum
- Bearish Divergence : Identified when price makes higher highs while RSI makes lower highs, indicating potential downward momentum
The algorithm uses candle color transitions and immediate RSI comparisons to trigger signals without historical repainting , ensuring backtesting accuracy and real-time reliability.
How To Read
Important Notes
Higher Signal Frequency : The zero-lag approach increases signal sensitivity, generating more frequent alerts that may include false signals. Consider using additional confirmation methods for trade entries.
Non-Repainting : All signals are generated and maintained without historical modification, ensuring consistent backtesting and forward-testing results.
Input Parameters
RSI Length: Period for RSI calculation (default: 14)
Short/Long Periods: Lookback periods for divergence detection (default: 15/50)
Line Colors: Customizable colors for short and long period divergence lines
Label Settings: Optional divergence labels with custom text
This indicator is designed for traders seeking immediate divergence identification across multiple timeframes while maintaining signal integrity and backtesting reliability.
RSI PotentialRSI Potential
This indicator does more than just track RSI; it measures the "energy" or "fuel" left in a trend. It answers a critical question: how much further can the price move before momentum is exhausted?
The key insight is that high momentum often means low potential, and vice versa. This inverse relationship is what allows the indicator to provide powerful, forward-looking signals about trend health and potential reversals.
Think of it like a race car:
Momentum is the car's current speed.
Potential is the amount of fuel left in the tank.
A car at top speed (high momentum) is burning fuel rapidly (potential is decreasing). A car just starting (low momentum) has a full tank of fuel (high potential). This indicator helps you see the fuel gauge, not just the speedometer.
This indicator plots three distinct components in a separate pane below your chart:
1. Upside Potential (Green Line)
What it shows: The percentage price increase required to hit the Overbought RSI Level. In other words, how much "fuel" is left for the upward trend.
How to interpret it:
Low Value (Approaching Zero): This is a warning sign. It means the price is already in high gear, and there is very little room left to run before hitting overbought exhaustion. Even if the price is rocketing up (high momentum), low potential signals the rally is likely on its last legs.
High Value: This indicates the market has a full tank of fuel for a rally. Even if the price is moving sideways or slowly (low momentum), the high potential suggests that if a new uptrend starts, it has the energy to be sustainable and significant.
2. Downside Potential (Red Line)
What it shows: The percentage price decrease required to hit the Oversold RSI Level—the "fuel" for a downtrend.
How to interpret it:
Low Value (Approaching Zero): A warning for bears. The price may be dropping fast (high momentum), but it's running out of energy to fall further. This signals seller exhaustion and increases the probability of a bounce or reversal.
High Value: The market has significant room to fall before becoming oversold. This can confirm the health of a new downtrend or suggest that a current downtrend has more to go.
3. Net Potential (Columns / Histogram)
What it shows: The net balance of energy: Upside Potential - Downside Potential. It answers, "Which side has more fuel in the tank?"
52SIGNAL RECIPE RSI Linreg Bands═══ 52SIGNAL RECIPE RSI Linreg Bands ═══
◆ Overview
52SIGNAL RECIPE RSI Linreg Bands is an advanced technical indicator that combines the RSI (Relative Strength Index) with Linear Regression Bands. This indicator visualizes the volatility of the RSI using linear regression bands, helping to clearly identify overbought/oversold areas and more accurately capture potential trend reversal points.
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◆ Key Features
• RSI-Based Overbought/Oversold Analysis: Uses the traditional RSI indicator to identify overbought/oversold conditions in the market
• Integrated Linear Regression Bands: Applies linear regression analysis to the RSI to visually represent the direction and strength of trends
• Dual Overbought/Oversold Levels: Sets overbought/oversold levels for both RSI and Linear Regression Bands to increase the accuracy of signals
• Advanced Visualization: Intuitive chart analysis is possible with color changes according to trend direction and clear band display
• Multiple Alert Settings: Alert functions for various conditions ensure you don't miss important trading moments
─────────────────────────────────────
◆ Technical Foundation
■ RSI (Relative Strength Index)
• Basic Settings: 14-period RSI with 5-period Weighted Moving Average (WMA) applied
• Calculation Method: Measures the relative strength of gains and losses, expressed as a value between 0-100
• Overbought/Oversold Levels: Default values set to 70 (overbought) and 30 (oversold)
■ Linear Regression Bands
• Period: Default value of 100 days
• Deviation: Default value of 2.5 standard deviations
• Center Line: The center line of the linear regression analysis for the RSI values
• Band Width: Displays the range of volatility around the center line based on the calculated standard deviation
• Overbought/Oversold Levels: Default values set to 85 (overbought) and 15 (oversold)
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◆ Practical Applications
■ Identifying Trading Signals
• Buy Signal:
▶ When the RSI falls below the oversold level (30)
▶ When the lower band of the Linear Regression Bands falls below the oversold level (15)
▶ When both conditions are met simultaneously (extreme oversold state) - a strong buy signal
• Sell Signal:
▶ When the RSI rises above the overbought level (70)
▶ When the upper band of the Linear Regression Bands rises above the overbought level (85)
▶ When both conditions are met simultaneously (extreme overbought state) - a strong sell signal
■ Trend Analysis
• Uptrend: When the linear regression center line is rising and the RSI is moving above the midline (50)
• Downtrend: When the linear regression center line is falling and the RSI is moving below the midline (50)
• Trend Strength: The wider the gap between the bands, the greater the volatility; the narrower, the more stable the trend
■ Divergence Confirmation
• Bearish Divergence: Price forms a new high, but the RSI is lower than the previous high (potential bearish signal)
• Bullish Divergence: Price forms a new low, but the RSI is higher than the previous low (potential bullish signal)
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◆ Advanced Setting Options
■ RSI Setting Adjustments
• RSI Source: Selectable options include Close (default), Open, High, Low, HL2, HLC3, OHLC4, etc.
• RSI Length: Adjust to lower values for short-term volatility, higher values for long-term trends
■ Linear Regression Setting Adjustments
• Period: Use lower values (20-50) for short-term analysis, higher values (100-200) for long-term analysis
• Deviation: Higher values create wider bands (more signals), lower values create narrower bands (more accurate signals)
■ Overbought/Oversold Level Adjustments
• RSI Levels: Adjust to more extreme values (80/20) in highly volatile markets
• Linear Regression Band Levels: Adjustable to 90/10 or 80/20 depending on market conditions
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◆ Synergy with Other Indicators
• Bollinger Bands: Use alongside Bollinger Bands on the price chart to compare price volatility with RSI volatility
• MACD: Use with MACD for momentum and trend confirmation
• Fibonacci Retracement: Check RSI Linreg Bands signals with key support/resistance levels
• Moving Averages: Combine moving average crossovers with RSI Linreg Bands signals to improve reliability
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◆ Conclusion
52SIGNAL RECIPE RSI Linreg Bands provides a powerful and accurate technical analysis tool by combining traditional RSI with linear regression analysis. The dual overbought/oversold system increases the accuracy of trading signals and clearly visualizes trend direction and strength to help traders make decisions. You can achieve optimal results by adjusting various settings to match your trading style and market conditions.
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※ Disclaimer: Past performance does not guarantee future results. Always use appropriate risk management strategies.
═══ 52SIGNAL RECIPE RSI 선형회귀 밴드 ═══
◆ 개요
52SIGNAL RECIPE RSI 선형회귀 밴드는 RSI(상대강도지수)와 선형회귀 밴드를 결합한 고급 기술적 지표입니다. 이 지표는 선형회귀 밴드를 사용하여 RSI의 변동성을 시각화하여 과매수/과매도 영역을 명확하게 식별하고 잠재적인 추세 반전 지점을 더 정확하게 포착하는 데 도움을 줍니다.
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◆ 주요 특징
• RSI 기반 과매수/과매도 분석: 전통적인 RSI 지표를 사용하여 시장의 과매수/과매도 상태를 식별
• 통합된 선형회귀 밴드: RSI에 선형회귀 분석을 적용하여 추세의 방향과 강도를 시각적으로 표현
• 이중 과매수/과매도 레벨: RSI와 선형회귀 밴드 모두에 과매수/과매도 레벨을 설정하여 신호의 정확도 향상
• 고급 시각화: 추세 방향에 따른 색상 변화와 명확한 밴드 표시로 직관적인 차트 분석 가능
• 다중 알림 설정: 다양한 조건에 대한 알림 기능으로 중요한 트레이딩 시점을 놓치지 않도록 보장
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◆ 기술적 기반
■ RSI (상대강도지수)
• 기본 설정: 14기간 RSI에 5기간 가중이동평균(WMA) 적용
• 계산 방법: 상승과 하락의 상대적 강도를 측정하여 0-100 사이의 값으로 표현
• 과매수/과매도 레벨: 기본값으로 70(과매수)과 30(과매도) 설정
■ 선형회귀 밴드
• 기간: 기본값 100일
• 편차: 기본값 2.5 표준편차
• 중심선: RSI 값에 대한 선형회귀 분석의 중심선
• 밴드 폭: 계산된 표준편차에 기반하여 중심선 주변의 변동성 범위 표시
• 과매수/과매도 레벨: 기본값으로 85(과매수)와 15(과매도) 설정
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◆ 실용적 응용
■ 트레이딩 신호 식별
• 매수 신호:
▶ RSI가 과매도 레벨(30) 아래로 떨어질 때
▶ 선형회귀 밴드의 하단이 과매도 레벨(15) 아래로 떨어질 때
▶ 두 조건이 동시에 충족될 때(극단적 과매도 상태) - 강한 매수 신호
• 매도 신호:
▶ RSI가 과매수 레벨(70) 위로 상승할 때
▶ 선형회귀 밴드의 상단이 과매수 레벨(85) 위로 상승할 때
▶ 두 조건이 동시에 충족될 때(극단적 과매수 상태) - 강한 매도 신호
■ 추세 분석
• 상승 추세: 선형회귀 중심선이 상승하고 RSI가 중간선(50) 위로 움직일 때
• 하락 추세: 선형회귀 중심선이 하락하고 RSI가 중간선(50) 아래로 움직일 때
• 추세 강도: 밴드 사이의 간격이 넓을수록 변동성이 크고, 좁을수록 추세가 안정적
■ 다이버전스 확인
• 약세 다이버전스: 가격이 신고점을 형성하지만 RSI가 이전 고점보다 낮을 때(잠재적 약세 신호)
• 강세 다이버전스: 가격이 신저점을 형성하지만 RSI가 이전 저점보다 높을 때(잠재적 강세 신호)
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◆ 고급 설정 옵션
■ RSI 설정 조정
• RSI 소스: 선택 가능한 옵션에는 종가(기본값), 시가, 고가, 저가, HL2, HLC3, OHLC4 등이 포함
• RSI 길이: 단기 변동성을 위해 낮은 값으로, 장기 추세를 위해 높은 값으로 조정
■ 선형회귀 설정 조정
• 기간: 단기 분석을 위해 낮은 값(20-50), 장기 분석을 위해 높은 값(100-200) 사용
• 편차: 높은 값은 더 넓은 밴드(더 많은 신호), 낮은 값은 더 좁은 밴드(더 정확한 신호) 생성
■ 과매수/과매도 레벨 조정
• RSI 레벨: 변동성이 큰 시장에서는 더 극단적인 값(80/20)으로 조정
• 선형회귀 밴드 레벨: 시장 상황에 따라 90/10 또는 80/20으로 조정 가능
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◆ 다른 지표와의 시너지
• 볼린저 밴드: 가격 차트의 볼린저 밴드와 함께 사용하여 가격 변동성과 RSI 변동성 비교
• MACD: 모멘텀과 추세 확인을 위해 MACD와 함께 사용
• 피보나치 되돌림: RSI 선형회귀 밴드 신호를 주요 지지/저항 레벨과 함께 확인
• 이동평균선: 이동평균 교차와 RSI 선형회귀 밴드 신호를 결합하여 신뢰성 향상
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◆ 결론
52SIGNAL RECIPE RSI 선형회귀 밴드는 전통적인 RSI와 선형회귀 분석을 결합하여 강력하고 정확한 기술적 분석 도구를 제공합니다. 이중 과매수/과매도 시스템은 트레이딩 신호의 정확도를 높이고 추세 방향과 강도를 명확하게 시각화하여 트레이더의 의사 결정을 돕습니다. 다양한 설정을 트레이딩 스타일과 시장 상황에 맞게 조정하여 최적의 결과를 얻을 수 있습니다.
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※ 면책 조항: 과거 성과가 미래 결과를 보장하지 않습니다. 항상 적절한 리스크 관리 전략을 사용하세요.
