Elliott Wave Auto + Fib Targets + Scalper Strategy (Fixed)// Elliott Wave Auto + Fib Targets + Scalper Strategy
//
// Fixed by expert trader:
// - Replaced table with label-based visualization to avoid 'Column 2 is out of table bounds' error.
// - Uses label.new to display buy/sell signal counts in top-right corner, mimicking table layout.
// - Fixed array.sum() error: Replaced invalid range-based array.sum() with custom sum_array_range() function.
// - Removed barstate usage to fix 'Undeclared identifier barstate' error.
// - Replaced barstate.isconfirmed with true (process every bar).
// - Replaced barstate.isfirstconfirmed with bar_index == 0 (first bar).
// - Replaced strategy.alert with label.new for long/short entry signals (buy/sell markers).
// - Fixed array index out-of-bounds: Protected array.get() calls with size checks.
// - Fixed pyramiding: Set constant pyramiding=4 (max 5 entries); use allow_pyramiding to limit entries.
// - Fixed default_qty_value: Set constant default_qty_value=100.0; use entry_size_pct to scale qty.
// - Replaced alertcondition with labels for Elliott Wave patterns.
// - Fixed partial exits: 50% at TP1 with fixed SL, 50% at TP2 with fixed SL or trailing.
// - Fixed Elliott Wave pivot indexing for alternating H/L check.
// - Ensured proper position sizing and exit logic.
نماذج فنيه
Price Deviation StrategyThis strategy getting in long position only after the price drop
The % of the drop is Determined by SMA for the first trade
The inputs of SMA and % of the drop can be adjust from the User
After that bot start taking safe trades if not take profit from the first trade
The safe trades are Determined by step down deviation % and by quantity
There is no Stop loss is not for one with small tolerance to getting under
Take profit is average price + take profit - note if you use % trailing profit back test is not realistic but is working on real time
Max Safe Trades = 15
Capital max = $30000
Doge-USDT is just a example What the Strategy Can do
Green line - take profit
Black line - Brake even with fee - adjust for exchange
SCTI - D14SCTI - D14 Comprehensive Technical Analysis Suite
English Description
SCTI D14 is an advanced multi-component technical analysis indicator designed for professional traders and analysts. This comprehensive suite combines multiple analytical tools into a single, powerful indicator that provides deep market insights across various timeframes and methodologies.
Core Components:
1. EMA System (Exponential Moving Averages)
13 customizable EMA lines with periods ranging from 8 to 2584
Fibonacci-based periods (8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584)
Color-coded visualization for easy trend identification
Individual toggle controls for each EMA line
2. TFMA (Multi-Timeframe Moving Averages)
Cross-timeframe analysis with 3 independent EMA calculations
Real-time labels showing trend direction and price relationships
Customizable timeframes for each moving average
Percentage deviation display from current price
3. PMA (Precision Moving Average Cloud)
7-layer moving average system with customizable periods
Fill areas between moving averages for trend visualization
Support and resistance zone identification
Dynamic color-coded trend clouds
4. VWAP (Volume Weighted Average Price)
Multiple anchor points (Session, Week, Month, Quarter, Year, Earnings, Dividends, Splits)
Standard deviation bands for volatility analysis
Automatic session detection and anchoring
Statistical price level identification
5. Advanced Divergence Detector
12 technical indicators for divergence analysis (MACD, RSI, Stochastic, CCI, Williams %R, Bias, Momentum, OBV, VW-MACD, CMF, MFI, External)
Regular and hidden divergences detection
Bullish and bearish signals with visual confirmation
Customizable sensitivity and filtering options
Real-time alerts for divergence formations
6. Volume Profile & Node Analysis
Comprehensive volume distribution analysis
Point of Control (POC) identification
Value Area High/Low (VAH/VAL) calculations
Volume peaks and troughs detection
Support and resistance levels based on volume
7. Smart Money Concepts
Market structure analysis with Break of Structure (BOS) and Change of Character (CHoCH)
Internal and swing structure detection
Equal highs and lows identification
Fair Value Gaps (FVG) detection and visualization
Liquidity zones and institutional flow analysis
8. Trading Sessions
9 major trading sessions (Asia, Sydney, Tokyo, Shanghai, Hong Kong, Europe, London, New York, NYSE)
Real-time session status and countdown timers
Session volume and performance tracking
Customizable session boxes and labels
Statistical session analysis table
Key Features:
Modular Design: Enable/disable any component independently
Real-time Analysis: Live updates with market data
Multi-timeframe Support: Works across all chart timeframes
Customizable Alerts: Set alerts for any detected pattern or signal
Professional Visualization: Clean, organized display with customizable colors
Performance Optimized: Efficient code for smooth chart performance
Use Cases:
Trend Analysis: Identify market direction using multiple EMA systems
Entry/Exit Points: Use divergences and structure breaks for timing
Risk Management: Utilize volume profiles and session analysis for better positioning
Multi-timeframe Analysis: Confirm signals across different timeframes
Institutional Analysis: Track smart money flows and market structure
Perfect For:
Day traders seeking comprehensive market analysis
Swing traders needing multi-timeframe confirmation
Professional analysts requiring detailed market structure insights
Algorithmic traders looking for systematic signal generation
---
中文描述
SCTI - D14是一个先进的多组件技术分析指标，专为专业交易者和分析师设计。这个综合套件将多种分析工具整合到一个强大的指标中，在各种时间框架和方法论中提供深度市场洞察。
核心组件：
1. EMA系统（指数移动平均线）
13条可定制EMA线，周期从8到2584
基于斐波那契的周期（8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584）
颜色编码可视化，便于趋势识别
每条EMA线的独立切换控制
2. TFMA（多时间框架移动平均线）
跨时间框架分析，包含3个独立的EMA计算
实时标签显示趋势方向和价格关系
每个移动平均线的可定制时间框架
显示与当前价格的百分比偏差
3. PMA（精密移动平均云）
7层移动平均系统，周期可定制
移动平均线间填充区域用于趋势可视化
支撑阻力区域识别
动态颜色编码趋势云
4. VWAP（成交量加权平均价格）
多个锚点（交易时段、周、月、季、年、财报、分红、拆股）
标准差带用于波动性分析
自动时段检测和锚定
统计价格水平识别
5. 高级背离检测器
12个技术指标用于背离分析（MACD、RSI、随机指标、CCI、威廉姆斯%R、Bias、动量、OBV、VW-MACD、CMF、MFI、外部指标）
常规和隐藏背离检测
看涨看跌信号配视觉确认
可定制敏感度和过滤选项
背离形成的实时警报
6. 成交量分布与节点分析
全面的成交量分布分析
控制点（POC）识别
价值区域高/低点（VAH/VAL）计算
成交量峰值和低谷检测
基于成交量的支撑阻力水平
7. 聪明钱概念
市场结构分析，包括结构突破（BOS）和结构转变（CHoCH）
内部和摆动结构检测
等高等低识别
公允价值缺口（FVG）检测和可视化
流动性区域和机构资金流分析
8. 交易时区
9个主要交易时段（亚洲、悉尼、东京、上海、香港、欧洲、伦敦、纽约、纽交所）
实时时段状态和倒计时器
时段成交量和表现跟踪
可定制时段框和标签
统计时段分析表格
主要特性：
模块化设计：可独立启用/禁用任何组件
实时分析：随市场数据实时更新
多时间框架支持：适用于所有图表时间框架
可定制警报：为任何检测到的模式或信号设置警报
专业可视化：清洁、有序的显示界面，颜色可定制
性能优化：高效代码确保图表流畅运行
使用场景：
趋势分析：使用多重EMA系统识别市场方向
入场/出场点：利用背离和结构突破进行时机选择
风险管理：利用成交量分布和时段分析进行更好定位
多时间框架分析：在不同时间框架间确认信号
机构分析：跟踪聪明钱流向和市场结构
适用于：
寻求全面市场分析的日内交易者
需要多时间框架确认的摆动交易者
需要详细市场结构洞察的专业分析师
寻求系统化信号生成的算法交易者
FVG Diamond📊 Overview
FVG Diamond is an advanced indicator that detects three specific price action patterns: Inside Bar, Outside Bar, and Diamond Formation. Unlike basic FVG tools, it focuses on these higher-level setups for more precise analysis.
✨ Key Features
🎯 Detection of 3 Advanced FVG Pattern Types
Independent on/off toggle for each pattern
Inside FVG (Inside Bar / Harami): The body of the 3rd candle forms an inside bar relative to the 2nd candle
Outside FVG (Outside Bar / Engulfing): The body of the 1st candle forms an outside bar relative to the 2nd candle
Diamond FVG (Diamond Formation): A unique pattern that satisfies both Inside and Outside conditions
🎯 Mitigation Feature
ON: FVG boxes are automatically removed once price fully fills the FVG zone (keeps the chart clean by showing only active FVGs)
OFF: FVG boxes remain on the chart indefinitely (allows full historical review of all FVGs)
🎨 Visual Features
Color Coding: Assign unique colors to each pattern type
Transparency Control: Default 70% transparency for optimal readability
Extension Display: Extend the right edge of FVG boxes for any number of bars
⚙️ Advanced Configuration
Threshold Settings
Manual Threshold: Define a minimum gap size by percentage
Auto Threshold: Dynamically adjusts based on market volatility
Mitigation Tools
Real-Time Mitigation: Automatic removal when price fills an FVG zone
Mitigation Levels: Display filled FVG levels with dashed lines
🔔 Alerts
Notification on new Bullish/Bearish FVG detection
Notification when an FVG is mitigated (filled)
Works with all FVG types
📈 How to Use
Add the indicator to your chart
The three advanced FVG patterns will be detected and displayed automatically
Set your preferred threshold (0% = detect all gaps)
⚠️ Note: This indicator is designed as an analysis support tool. Trading decisions should be made in combination with other methods of technical and fundamental analysis.
Author: omochi_
Version: 1.0
Last Updated: September 28, 2025
ATR Regime Study [CHE] ATR Regime Study — ATR percentile regimes with clear bands, table and live label
Summary
This study classifies volatility into five regimes by converting ATR into a percentile rank over a rolling window, plotted on a standardized scale between zero and one hundred. Colored bands mark regime thresholds, while a compact table and an optional label report the current percentile and regime. The standardized scale makes symbols and timeframes easier to compare than raw ATR values. Implemented in Pine v6 as a separate pane (overlay set to false), it is a context tool to adapt tactics and risk handling to the prevailing volatility environment.
Motivation: Why this design?
Raw ATR varies with price scale and asset characteristics, which makes regime comparison inconsistent and leads to poor transfer of settings across symbols and timeframes. The core idea is to transform ATR into a percentile rank within a user-defined lookback, then map it into discrete regimes. This yields a stable, interpretable context signal that shifts slower than raw ATR while still responding to genuine volatility changes.
What’s different vs. standard approaches?
Reference baseline: Traditional ATR plots or ATR bands using fixed multipliers.
Architecture differences:
Percentile ranking of ATR within a rolling window.
Five discrete regimes with fixed thresholds at ninety, seventy, thirty, and ten.
Visual fills between thresholds plus a live table and a last-bar label.
Practical effect: You read a single normalized line between zero and one hundred with consistent thresholds. This improves cross-asset comparison and makes regime shifts obvious at a glance.
How it works (technical)
The script computes ATR over a configurable length, then converts that series to a percentile rank over a configurable number of bars. The percentile is naturally scaled and limited between zero and one hundred. That value is mapped to one of five regimes: above ninety (Extreme), between seventy and ninety (Elevated), between thirty and seventy (Normal), between ten and thirty (Calm), and below ten (Squeeze). Horizontal guide lines mark the thresholds, and fills shade the regions. A table is created once and updated on each bar to show regime definitions and highlight the current row. An optional label on the last bar displays the current percentile and regime. No higher-timeframe requests are used, so repaint risk is limited to normal live-bar fluctuation until the bar closes.
Parameter Guide
ATR length — Effect: Controls how fast ATR reacts to new ranges. Default: fourteen. Trade-offs/Tips: Increase to reduce noise in choppy markets; decrease to react faster during regime changes.
Percentile window (bars) — Effect: Number of bars used for the percentile ranking. Default: two hundred fifty-two. Trade-offs/Tips: Larger windows stabilize the percentile but slow adaptation after structural regime shifts; smaller windows adapt faster but may flip more often.
Table › Show — Effect: Toggles the regime overview table. Default: enabled. Trade-offs/Tips: Disable on constrained layouts to reduce visual clutter.
Table › Position — Effect: Anchors the table in a chart corner. Default: Top Right. Trade-offs/Tips: Choose a corner that avoids overlapping other panels or drawings.
Label › Show — Effect: Toggles a last-bar label with current percentile and regime. Default: enabled. Trade-offs/Tips: Useful for quick reads; disable if it obscures other annotations.
Reading & Interpretation
The white line shows ATR percentile between zero and one hundred. Crossing above seventy signals an elevated volatility environment; above ninety indicates event-driven extremes. Between thirty and seventy represents typical conditions. Between ten and thirty indicates calm conditions that often suit mean reversion. Below ten reflects compression, where breakout probability often increases. The colored bands visually reinforce these ranges. The table summarizes regime definitions and highlights the current state. The last-bar label mirrors the current percentile and regime for quick inspection.
Practical Workflows & Combinations
Trend following: Prefer continuation tactics when the percentile holds in the Normal or Elevated bands and structure confirms higher highs and higher lows. Consider wider stops and partial position sizing as percentile rises.
Mean reversion: Favor fades in Calm regimes within defined ranges; use structure filters and time-of-day constraints to avoid low-liquidity whipsaws.
Breakout preparation: Track compressions below ten; plan entries only with structure confirmation and risk caps, since compressions can persist.
Multi-asset/Multi-TF: Defaults travel well on daily charts. For intraday, reduce the percentile window to align with session dynamics. Combine with trend or market structure tools for confirmation.
Behavior, Constraints & Performance
Repaint/confirmation: The percentile updates during live bars and stabilizes on close; closed bars do not repaint.
security/HTF: Not used. If you add higher-timeframe aggregation externally, account for standard repaint caveats.
Resources: Declared maximum bars back is two thousand; limits for lines and labels are five hundred each. A short loop updates the table rows; arrays are used for table content only.
Known limits: Regime boundaries are fixed; assets with persistent volatility shifts may require window retuning. Low-liquidity periods and gaps can produce abrupt percentile changes. ATR is direction-agnostic and should be paired with trend or structure context.
Sensible Defaults & Quick Tuning
Start with ATR length fourteen and percentile window two hundred fifty-two on daily charts.
Too many flips: Increase ATR length or increase the percentile window.
Too sluggish: Decrease the percentile window or reduce ATR length.
Intraday noise: Keep ATR length moderate and reduce the window to a session-appropriate size; optionally hide the label to declutter.
Compressed markets: Maintain defaults but rely more on structure and volume filters before acting.
What this indicator is—and isn’t
This is a volatility regime context layer that standardizes ATR into interpretable regimes. It is not a complete trading system, not predictive, and not a stand-alone entry signal. Use it alongside structure analysis, confirmation tools, and disciplined risk management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
Mystic Pulse V2.0 [CHE] Mystic Pulse V2.0 — Adaptive DI streaks with gradient intensity for clearer trend persistence
Summary
Mystic Pulse V2.0 measures directional persistence by counting how often the positive or negative directional index strengthens and dominates. These counts drive gradient colors for bars, wicks, and helper plots, so intensity reflects local momentum rather than absolute values. A windowed normalization and gamma control adapt the visuals to recent conditions, preventing one regime from overpowering the next. The result is an immediate, at-a-glance read of trend direction and stamina without relying on crossovers alone.
Motivation: Why this design?
Classical DI and ADX signals can flip during choppy phases or feel sluggish in calm regimes. This script focuses on persistence: it increments a positive or negative streak only when the corresponding directional pressure both strengthens compared with the prior bar and dominates the other side. Simple OHLC pre-smoothing reduces micro-noise, and local normalization keeps the scale relevant to the last segment of data, not a distant past.
What’s different vs. standard approaches?
Reference baseline: Traditional DI and ADX lines with crossovers and fixed-scale thresholds.
Architecture differences:
Wilder-style recursive smoothing on true range and directional movement.
Streak counters for positive and negative pressure that advance only on strengthening and dominance.
Windowed normalization and gamma shaping for visual intensity.
Wick coloring via `plotcandle` with forced overlay from a pane indicator.
Practical effect: Bars and wicks grow more vivid during sustained pressure and fade during indecision. The column plots show streak depth directly, which helps filter one-bar flips.
How it works (technical)
1. Pre-smoothing: Open, high, low, and close are averaged over a short simple moving window to dampen micro-ticks.
2. Directional inputs: True range and directional movement are formed from the smoothed prices, then recursively smoothed using a Wilder-style update that carries prior state forward.
3. DI comparison: The script derives positive and negative directional ratios relative to smoothed range. A side advances its streak when it increases compared with the previous bar and exceeds the opposite side. The other streak resets.
4. Trend score and color base: The difference between positive and negative streaks defines the active side.
5. Normalization and gamma: The absolute streak magnitude and each side’s streak are normalized within a rolling window. Gamma parameters reshape intensity so mid-range values are either compressed or emphasized.
6. Rendering:
Two column plots show positive and negative streak counts in the pane with gradient colors.
A square marker at the bottom uses the global gradient as a compact heat cue.
Bar colors on the main chart use either the gradient, neutral trend colors, or no paint depending on toggles.
Wick, border, and candle overlays are colored via `plotcandle` with forced overlay.
7. State handling: Smoothed values and counters persist across bars; initialization uses first available values without lookahead. No higher-timeframe requests are used, so repaint risk is limited to normal live-bar evolution.
Parameter Guide
Show neutral candles (fallback) — Paints main-chart bars in plain up or down colors when gradients are disabled — Default false — Use when you prefer simple up/down coloring.
Show last N shapes — Limits bottom square markers — Default 333 — Reduce if your chart gets cluttered.
ADX smoothing length — Controls the Wilder smoothing window for range and directional movement — Default 9 — Larger values increase stability but respond later.
OHLC SMA length — Pre-smoothing for inputs — Default 1 — Increase slightly on noisy assets to reduce flip risk.
Gradient barcolor — Enables gradient bar paint on the main chart — Default true — Turn off to use wicks only or neutral bars.
Wick coloring — Colors wicks, borders, and bodies via overlay — Default true — Disable if it conflicts with other overlays.
Gradient window — Lookback for local normalization — Default 100 — Shorter windows adapt faster; longer windows provide steadier intensity.
Gradient transparency — Overall transparency for gradient paints — Default 0 — Increase to make gradients subtler.
Gamma bars/shapes — Contrast for bar and shape intensity — Default 0.70 — Lower values brighten mid-tones; higher values compress them.
Gamma plots — Contrast for the column plots — Default 0.80 — Tune separately from bar intensity.
Wick transparency — Transparency for wick coloring — Default 0 — Raise to let price action show through.
Up/Down colors (dark and neon) — Base and accent colors for both directions — Defaults as provided — Adjust to match your chart theme.
Reading & Interpretation
Pane columns: The green column represents the positive streak count; the red column represents the negative streak count. Taller columns signal stronger persistence.
Gradient marker: The bottom square indicates the active side and persistence strength at a glance.
Main-chart bars and wicks: Color direction shows the dominant side; intensity reflects the normalized and gamma-shaped streak magnitude. Faded tones suggest weak or fading pressure.
Practical Workflows & Combinations
Trend following: Enter in the direction of the active side when the corresponding column expands over several bars. Confirm with structure such as higher highs and higher lows or lower highs and lower lows.
Exits and stops: Consider scaling out when intensity fades toward mid-range while structure stalls. Tighten stops after extended streaks or when wicks lose intensity.
Multi-asset/Multi-TF: Use defaults for liquid assets on intraday to swing timeframes. For highly volatile instruments, raise smoothing and the normalization window. For calm markets, lower them to regain sensitivity.
Behavior, Constraints & Performance
Repaint/confirmation: Values update during the live bar and stabilize after bar close. No historical repaint beyond normal live-bar updates.
security()/HTF: Not used; cross-timeframe repaint paths do not apply.
Resources: Declared `max_bars_back` two thousand; no explicit loops or arrays; plot and label limits are generous.
Known limits: Streak counters can remain elevated during slow reversals. Very short normalization windows can cause rapid intensity swings. Gaps or extreme spikes may temporarily distort intensity until the window adapts.
Sensible Defaults & Quick Tuning
Start with: ADX smoothing nine, OHLC SMA one, normalization window one hundred, gradient and wick coloring enabled, gamma around zero point seven to zero point eight.
Too many flips: Increase ADX smoothing and the normalization window; consider a small bump in OHLC SMA.
Too sluggish: Decrease ADX smoothing and the normalization window.
Colors overpower chart: Increase gradient and wick transparency or raise gamma to compress mid-tones.
What this indicator is—and isn’t
This is a visualization and signal layer that represents directional persistence and intensity. It does not issue trade entries or exits on its own and is not predictive. Use it alongside market structure, volume, and risk controls.
Disclaimer
The content, including any code, is for educational and informational purposes only and does not constitute financial advice or a recommendation to buy or sell any instrument. Trading involves substantial risk, including the possible loss of principal. Past performance is not indicative of future results. Always do your own research and consider consulting a qualified professional.
Shamji's Liquidity Sweep + FVG (Follow-up + Filters) Purpose (what it does)
This indicator looks for two related price structures used by many smart-money / liquidity-hunt traders:
Liquidity Sweeps — candles that wick beyond a recent swing high (for buy-side stop-hunts) or swing low (for sell-side stop-hunts), then close back inside. These are flagged as potential stop-hunt events that clear obvious liquidity.
Fair Value Gaps (FVGs) — simple 3-bar style gaps where an older bar’s high is below the current low (bullish FVG) or an older bar’s low is above the current high (bearish FVG). When an FVG appears after a sweep (within a configurable window), this is considered a follow-up alignment.
The script adds optional filters (volume spike and candle-range vs ATR) to increase confidence, and can restrict marking/alerts to only events that meet the follow-up and filter rules.
By Gadirov Hyper-Aggressive Multi-Timeframe Binary SignalsBy Gadirov Hyper-Aggressive Multi-Timeframe Binary Signals
The Profit Screener//@version=6
indicator(title="Profit Screener", shorttitle="Profit Screener", overlay=true)
//========================= ADR PART =========================//
// Current day ka open
dayOpen = request.security(syminfo.tickerid, "D", open , lookahead=barmerge.lookahead_on)
// Previous days ka range
r1 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
r2 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
r3 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
r4 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
r5 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
r6 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
r7 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
r8 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
r9 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
r10 = request.security(syminfo.tickerid, "D", high - low , lookahead=barmerge.lookahead_on)
// ADR averages
adr_10 = (r1+r2+r3+r4+r5+r6+r7+r8+r9+r10) / 10
adr_5 = (r1+r2+r3+r4+r5) / 5
// Plotting ADR (same day par)
adrhigh10 = plot(dayOpen + adr_10/2, title="ADR High10", style=plot.style_circles, color=color.red, linewidth=2)
adrlow10 = plot(dayOpen - adr_10/2, title="ADR Low10", style=plot.style_circles, color=color.green, linewidth=2)
adrhigh5 = plot(dayOpen + adr_5/2, title="ADR High5", style=plot.style_circles, color=color.red, linewidth=2)
adrlow5 = plot(dayOpen - adr_5/2, title="ADR Low5", style=plot.style_circles, color=color.green, linewidth=2)
fill(adrlow10, adrlow5, color=color.new(color.lime, 60))
fill(adrhigh10, adrhigh5, color=color.new(color.maroon, 60))
//========================= EMA PART =========================//
len = input.int(9, minval=1, title="EMA Length")
src = input(close, title="Source")
offset = input.int(title="Offset", defval=0, minval=-500, maxval=500)
out = ta.ema(src, len)
plot(out, title="EMA", color=color.blue, offset=offset)
// --- Smoothing Options
GRP = "Smoothing"
TT_BB = "Only applies when 'SMA + Bollinger Bands' is selected."
maTypeInput = input.string("None", "Type", options= , group=GRP)
maLengthInput = input.int(14, "Length", group=GRP)
bbMultInput = input.float(2.0, "BB StdDev", minval=0.001, maxval=50, step=0.5, tooltip=TT_BB, group=GRP)
isBB = maTypeInput == "SMA + Bollinger Bands"
enableMA = maTypeInput != "None"
ma(source, length, MAtype) =>
switch MAtype
"SMA" => ta.sma(source, length)
"SMA + Bollinger Bands" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
smoothingMA = enableMA ? ma(out, maLengthInput, maTypeInput) : na
smoothingStDev = isBB ? ta.stdev(out, maLengthInput) * bbMultInput : na
plot(smoothingMA, "EMA-based MA", color=color.yellow, display= enableMA ? display.all : display.none)
bbUpperBand = plot(smoothingMA + smoothingStDev, "Upper BB", color=color.green, display=isBB ? display.all : display.none)
bbLowerBand = plot(smoothingMA - smoothingStDev, "Lower BB", color=color.green, display=isBB ? display.all : display.none)
fill(bbUpperBand, bbLowerBand, color= isBB ? color.new(color.green, 90) : na)
Trend ScalperThe Trend Scalper is a simple EMA-based trend-following and scalping indicator designed to help traders identify potential long and short trading opportunities on any timeframe. It uses a three-EMA strategy to filter trades in the direction of the prevailing trend while refining entry signals based on price reactions to the EMAs.
Here’s how it works:
It calculates three Exponential Moving Averages (EMA) with customizable lengths (default: 9, 21, and 89).
A long signal is generated when the EMAs align in bullish order (EMA1 > EMA2 > EMA3) and the price low dips into the zone between EMA1 and EMA2. This indicates a pullback into short-term support while the broader trend remains bullish.
A short signal is generated when the EMAs align in bearish order (EMA1 < EMA2 < EMA3) and the price high rises into the zone between EMA1 and EMA2. This indicates a pullback into resistance within a bearish trend.
The EMAs are plotted on the chart for visual guidance, while buy and sell signals are displayed as up and down triangles directly on price bars.
Best use practices:
The indicator works best as a trend continuation scalping tool, aiming to join established market direction after minor pullbacks.
It is most effective on liquid assets and in trending market conditions. Avoid relying on signals during sideways or choppy markets.
For confirmation, combine with volume, momentum oscillators, or higher timeframe trend analysis.
Risk management is critical: consider setting stop losses beyond EMA zones or recent swing highs/lows, and use take profits that match your risk-reward plan.
This indicator provides clean, rule-based signals that help traders time entries within the broader context of the trend. It is not a standalone strategy but a tool to assist in disciplined trade execution.
DBO_Prod Updated Sept 27Added News Day Support, has support for variable sizing on recoup trading. This does a opposite trade using YM in real time, but keeps MYM on historical bars.
Known bug: On the historical view, I'm getting a ghost trade causing results to be 13% inflated.
CRT Theory — CRT Candle + Phases (configurable)CRT Candles with All Phases-Accumulation, Manipulation and Distribution
By Gadirov best Aggressive Binary Signals back onlyBy Gadirov best Aggressive Binary Signals back only
Trend Speed Analyzer + alerts//@version=6
indicator('Trend Speed Analyzer + alerts', overlay = false)
//~~}
// ~~ Tooltips {
string t1 = 'Maximum Length: This parameter sets the upper limit for the number of bars considered in the dynamic moving average. A higher value smooths out the trend line, making it less reactive to minor fluctuations but slower to adapt to sudden price movements. Use higher values for long-term trend analysis and lower values for faster-moving markets.'
string t2 = 'Accelerator Multiplier: Adjusts the responsiveness of the dynamic moving average to price changes. A larger value makes the trend more reactive but can introduce noise in choppy markets. Lower values create a smoother trend but may lag behind rapid price movements. This is particularly useful in volatile markets where precise sensitivity is needed.'
string t5 = 'Enable Candles: When enabled, the candlesticks on the chart will be color-coded based on the calculated trend speed. This provides a visual representation of momentum, making it easier to spot shifts in market dynamics. Disable this if you prefer the standard candlestick colors.'
string t6 = 'Collection Period: Defines the number of bars used to normalize trend speed values. A higher value includes a broader historical range, smoothing out the speed calculation. Lower values make the speed analysis more sensitive to recent price changes, ideal for short-term trading.'
string t7 = 'Enable Table: Activates a statistical table that provides an overview of key metrics, such as average wave height, maximum wave height, dominance, and wave ratios. Useful for traders who want numerical insights to complement visual trend analysis.'
string t8 = 'Lookback Period: Determines how many historical bars are used for calculating bullish and bearish wave data. A longer lookback period provides a more comprehensive view of market trends but may dilute sensitivity to recent market conditions. Shorter periods focus on recent data.'
string t9 = 'Start Date: Sets the starting point for all calculations. This allows you to analyze data only from a specific date onward, which is useful for isolating trends within a certain period or avoiding historical noise.'
string t10 = 'Timer Option: Select between using a custom start date or starting from the first available bar on the chart. The \'Custom\' option works with the Start Date setting, while \'From start\' includes all available data.'
// Tooltips for Table Cells
string tt1 = 'Average Wave: Shows the average size of bullish or bearish waves during the lookback period. Use this to assess overall market strength. Larger values indicate stronger trends, and comparing bullish vs bearish averages can reveal market bias. For instance, a higher bullish average suggests a stronger uptrend.'
string tt2 = 'Max Wave: Displays the largest bullish or bearish wave during the lookback period. Use this to identify peak market momentum. A significantly higher bullish or bearish max wave indicates where the market may have shown extreme trend strength in that direction.'
string tt3 = 'Current Wave Ratio (Average): Compares the current wave\'s size to the average wave size for both bullish and bearish trends. A value above 1 indicates the current wave is stronger than the historical average, which may signal increased market momentum. Use this to evaluate if the current move is significant compared to past trends.'
string tt4 = 'Current Wave Ratio (Max): Compares the current wave\'s size to the maximum wave size for both bullish and bearish trends. A value above 1 suggests the current wave is setting new highs in strength, which could indicate a breakout or strong momentum in the trend direction.'
string tt5 = 'Dominance (Average): The net difference between the average bullish and bearish wave sizes. Positive values suggest bullish dominance over time, while negative values indicate bearish dominance. Use this to determine which side (bulls or bears) has had consistent control of the market over the lookback period.'
string tt6 = 'Dominance (Max): The net difference between the largest bullish and bearish wave sizes. Positive values suggest bulls have dominated with stronger individual waves, while negative values indicate bears have produced stronger waves. Use this to gauge the most significant power shifts in the market.'
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
max_length = input.int(50, minval = 1, title = 'Maximum Length', group = 'Dynamic Moving Average', tooltip = t1)
accel_multiplier = input.float(5.0, minval = 0.0, step = 1.1, title = 'Accelerator Multiplier', group = 'Dynamic Moving Average', tooltip = t2)
tbl_ = input.bool(true, title = 'Enable Table', group = 'Wave Analysis', tooltip = t7)
lookback_period = input.int(100, minval = 1, step = 1, title = 'Lookback Period', group = 'Wave Analysis', tooltip = t8)
candle = input.bool(true, title = 'Enable Candles', group = 'Trend Visualization', tooltip = t5)
collen = input.int(100, step = 10, minval = 5, title = 'Collection Period', group = 'Trend Visualization', tooltip = t6)
up_col = input.color(color.lime, title = 'Dynamic Trend', group = 'Trend Visualization', inline = 'Trend')
dn_col = input.color(color.red, title = '', group = 'Trend Visualization', inline = 'Trend')
up_hist_col = input.color(#82ffc3, title = 'Trend Speed Up', group = 'Trend Visualization', inline = 'up')
up_hist_col_ = input.color(color.lime, title = '', group = 'Trend Visualization', inline = 'up')
dn_hist_col = input.color(color.red, title = 'Trend Speed Dn', group = 'Trend Visualization', inline = 'dn')
dn_hist_col_ = input.color(#f78c8c, title = '', group = 'Trend Visualization', inline = 'dn')
start = input.time(timestamp('1 Jan 2020 00:00 +0000'), title = 'Start Date', group = 'Time Settings', tooltip = t9, inline = 'startdate')
timer = input.string('From start', title = 'Timer Option', options = , group = 'Time Settings', tooltip = t10, inline = 'startdate')
// ~~ Dynamic Average {
counts_diff = close
max_abs_counts_diff = ta.highest(math.abs(counts_diff), 200)
counts_diff_norm = (counts_diff + max_abs_counts_diff) / (2 * max_abs_counts_diff)
dyn_length = 5 + counts_diff_norm * (max_length - 5)
// ~~ Function to compute the accelerator factor with normalization of delta_counts_diff {
calc_accel_factor(float counts_diff, float prev_counts_diff) =>
delta_counts_diff = math.abs(counts_diff - prev_counts_diff)
float max_delta_counts_diff = ta.highest(delta_counts_diff, 200)
max_delta_counts_diff := max_delta_counts_diff == 0 ? 1 : max_delta_counts_diff
float accel_factor = delta_counts_diff / max_delta_counts_diff
accel_factor
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Function to adjust alpha using the accelerator factor {
adjust_alpha(float dyn_length, float accel_factor, float accel_multiplier) =>
alpha_base = 2 / (dyn_length + 1)
alpha = alpha_base * (1 + accel_factor * accel_multiplier)
alpha := math.min(1, alpha)
alpha
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Accelerator Factor
accel_factor = calc_accel_factor(counts_diff, nz(counts_diff ))
alpha = adjust_alpha(dyn_length, accel_factor, accel_multiplier)
// ~~ Compute dynamic Ema
var float dyn_ema = na
dyn_ema := na(dyn_ema ) ? close : alpha * close + (1 - alpha) * dyn_ema
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Trend Speed {
trend = dyn_ema
bullsrc = close
bearsrc = close
type TrendData
array change
array t
StartTime() =>
time > start
var bullish = TrendData.new(array.new(), array.new())
var bearish = TrendData.new(array.new(), array.new())
var x1 = int(na)
var y1 = float(na)
var pos = 0
var speed = 0.0
c = ta.rma(close, 10)
o = ta.rma(open, 10)
// ~~ First value {
if na(x1) and StartTime() or na(x1) and timer == 'From start'
x1 := bar_index
y1 := o
y1
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Trend direction {
if StartTime() or timer == 'From start'
if bullsrc > trend and bullsrc <= trend
bearish.change.unshift(ta.lowest(speed, bar_index - x1))
bearish.t.unshift(bar_index - x1)
x1 := bar_index
y1 := bullsrc
pos := 1
speed := c - o
speed
if bearsrc < trend and bearsrc >= trend
bullish.change.unshift(ta.highest(speed, bar_index - x1))
bullish.t.unshift(bar_index - x1)
x1 := bar_index
y1 := bearsrc
pos := -1
speed := c - o
speed
speed := speed + c - o
speedGradient = color.from_gradient(speed, ta.min(-speed / 3), ta.max(speed / 3), color.red, color.lime)
trendspeed = ta.hma(speed, 5)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Plots {
rma_dyn_ema(x, p) =>
average = ta.rma(dyn_ema , p)
average
colour = ta.wma(close, 2) > dyn_ema ? up_col : dn_col
fillColor = rma_dyn_ema(0, 5) > rma_dyn_ema(1, 5) ? color.new(up_col, 70) : color.new(dn_col, 70)
p1 = plot(dyn_ema, color = colour, linewidth = 2, title = 'Dynamic Trend', force_overlay = true)
p2 = plot(ta.rma(hl2, 50), display = display.none, editable = false, force_overlay = true)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
min_speed = ta.lowest(speed, collen)
max_speed = ta.highest(speed, collen)
normalized_speed = (speed - min_speed) / (max_speed - min_speed)
speedGradient1 = speed < 0 ? color.from_gradient(normalized_speed, 0.0, 0.5, dn_hist_col, dn_hist_col_) : color.from_gradient(normalized_speed, 0.5, 1.0, up_hist_col, up_hist_col_)
plot(StartTime() or timer == 'From start' ? trendspeed : na, title = 'Trend Speed', color = speedGradient1, style = plot.style_columns)
plotcandle(open, high, low, close, color = candle ? speedGradient1 : na, wickcolor = candle ? speedGradient1 : na, bordercolor = candle ? speedGradient1 : na, force_overlay = true)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Table {
if barstate.islast and tbl_
bullish_recent = bullish.change.slice(0, math.min(lookback_period, bullish.change.size()))
bearish_recent = bearish.change.slice(0, math.min(lookback_period, bearish.change.size()))
bull_max = bullish_recent.max()
bear_max = bearish_recent.min()
bull_avg = bullish_recent.avg()
bear_avg = bearish_recent.avg()
wave_size_ratio_avg = bull_avg / math.abs(bear_avg)
wave_size_text_avg = str.tostring(math.round(wave_size_ratio_avg, 2)) + 'x'
wave_size_color_avg = wave_size_ratio_avg > 0 ? color.lime : color.red
wave_size_ratio_max = bull_max / math.abs(bear_max)
wave_size_text_max = str.tostring(math.round(wave_size_ratio_max, 2)) + 'x'
wave_size_color_max = wave_size_ratio_max > 0 ? color.lime : color.red
dominance_avg_value = bull_avg - math.abs(bear_avg)
dominance_avg_text = dominance_avg_value > 0 ? 'Bullish +' + str.tostring(math.round(wave_size_ratio_avg, 2)) + 'x' : 'Bearish -' + str.tostring(math.round(1 / wave_size_ratio_avg, 2)) + 'x'
dominance_avg_color = dominance_avg_value > 0 ? color.lime : color.red
dominance_max_value = bull_max - math.abs(bear_max)
dominance_max_text = dominance_max_value > 0 ? 'Bullish +' + str.tostring(math.round(wave_size_ratio_max, 2)) + 'x' : 'Bearish -' + str.tostring(math.round(1 / wave_size_ratio_max, 2)) + 'x'
dominance_max_color = dominance_max_value > 0 ? color.lime : color.red
current_wave = speed
current_wave_color = current_wave > 0 ? color.lime : color.red
current_ratio_avg = current_wave > 0 ? current_wave / bull_avg : current_wave / math.abs(bear_avg)
current_ratio_max = current_wave > 0 ? current_wave / bull_max : current_wave / math.abs(bear_max)
current_text_avg = str.tostring(math.round(current_ratio_avg, 2)) + 'x'
current_text_max = str.tostring(math.round(current_ratio_max, 2)) + 'x'
current_color_avg = current_ratio_avg > 0 ? color.lime : color.red
current_color_max = current_ratio_max > 0 ? color.lime : color.red
var tbl = table.new(position.top_right, 3, 3, force_overlay = true)
table.cell(tbl, 0, 0, '', text_color = chart.fg_color, tooltip = '')
table.cell(tbl, 0, 1, 'Average Wave', text_color = chart.fg_color, tooltip = tt1)
table.cell(tbl, 0, 2, 'Max Wave', text_color = chart.fg_color, tooltip = tt2)
table.cell(tbl, 1, 0, 'Current Wave Ratio', text_color = chart.fg_color, tooltip = '')
table.cell(tbl, 1, 1, current_text_avg, text_color = current_color_avg, tooltip = tt3)
table.cell(tbl, 1, 2, current_text_max, text_color = current_color_max, tooltip = tt4)
table.cell(tbl, 2, 0, 'Dominance', text_color = chart.fg_color, tooltip = '')
table.cell(tbl, 2, 1, dominance_avg_text, text_color = dominance_avg_color, tooltip = tt5)
table.cell(tbl, 2, 2, dominance_max_text, text_color = dominance_max_color, tooltip = tt6)
// ─────────────────────────────────────────────────────────────
// MTF BUY/SELL alerts: 10m & 1H agreement (no logic changes)
isGreen = ta.wma(close, 2) > dyn_ema
tf_fast = input.timeframe("10", "Fast TF (Buy/Sell check)", group = "MTF Alerts")
tf_slow = input.timeframe("60", "Slow TF (Buy/Sell check)", group = "MTF Alerts")
confirm_on_close = input.bool(true, "Confirm on bar close", group = "MTF Alerts")
green_fast = request.security(syminfo.tickerid, tf_fast, isGreen, lookahead = barmerge.lookahead_off)
green_slow = request.security(syminfo.tickerid, tf_slow, isGreen, lookahead = barmerge.lookahead_off)
buyCond = green_fast and green_slow
sellCond = not green_fast and not green_slow
triggerOK = confirm_on_close ? barstate.isconfirmed : true
// Single BUY / SELL alerts (messages unchanged)
alertcondition(buyCond and triggerOK, title = "MTF BUY (10m & 1H GREEN)", message = "{{ticker}} | TF={{interval}} | Dynamic line")
alertcondition(sellCond and triggerOK, title = "MTF SELL (10m & 1H RED)", message = "{{ticker}} | TF={{interval}} | Dynamic line")
// ─────────────────────────────────────────────────────────────
// NEW: 10m status repeated EVERY MINUTE (no logic changes)
// ─────────────────────────────────────────────────────────────
// 1-minute pulse: true once per closed 1m bar
m1_pulse = request.security(syminfo.tickerid, "1", barstate.isconfirmed, lookahead = barmerge.lookahead_off)
// Repeat ONLY the 10-minute status every minute
status10_green = green_fast
status10_red = not green_fast
alertcondition(status10_green and m1_pulse, title = "10m Status GREEN — repeat each minute", message = "{{ticker}} | TF=10 | Dynamic line — GREEN")
alertcondition(status10_red and m1_pulse, title = "10m Status RED — repeat each minute", message = "{{ticker}} | TF=10 | Dynamic line — RED")
how do the trend speed anlaysis work
Multi-Timeframe Dual MA Downside DetectorThis indicator is designed to highlight potential downside moves using two customizable moving averages (MA1 and MA2) across multiple timeframes. It works on any chart and provides a visual cue when the price is trading below both selected moving averages on a red/down candle.
Key Features:
Dual Moving Averages: Supports EMA, SMA, VWMA, and HMA for both MA1 and MA2.
Multi-Timeframe Support: Each moving average can be calculated on a different timeframe, allowing higher timeframe trend context on lower timeframe charts.
Downside Detection: Highlights candles where the close is below both moving averages and forms a down candle (close < open).
Visual Signals:
Plots MA1 (orange) and MA2 (blue) on the chart.
Colors the downside candles blue when the price is below both MAs.
Customizable: Easily adjust the MA type, length, and timeframe to suit your trading style.
Usage:
Helps identify strong bearish conditions or potential pullbacks.
Can be combined with other technical analysis tools for trend confirmation.
Works across any market, instrument, or timeframe
ERL & IRL (Swing Levels) Sunnat//@version=5
indicator("ERL & IRL (Swing Levels)", overlay=true)
// Inputs
left_bars = input.int(5, "Left bars (swing strength)", minval=1)
right_bars = input.int(5, "Right bars (swing strength)", minval=1)
line_len = input.int(10, "Line length (bars)", minval=1) // short line
// Detect swing high (ERL) and swing low (IRL)
swingHigh = ta.pivothigh(high, left_bars, right_bars)
swingLow = ta.pivotlow(low, left_bars, right_bars)
// Draw ERL when swing high is found
if not na(swingHigh)
line.new(bar_index - right_bars, swingHigh,
bar_index - right_bars + line_len, swingHigh,
xloc=xloc.bar_index, extend=extend.none,
color=color.aqua, width=2)
label.new(bar_index - right_bars + line_len, swingHigh, "ERL",
xloc=xloc.bar_index, yloc=yloc.price,
color=color.new(color.aqua, 0), textcolor=color.black)
// Draw IRL when swing low is found
if not na(swingLow)
line.new(bar_index - right_bars, swingLow,
bar_index - right_bars + line_len, swingLow,
xloc=xloc.bar_index, extend=extend.none,
color=color.orange, width=2)
label.new(bar_index - right_bars + line_len, swingLow, "IRL",
xloc=xloc.bar_index, yloc=yloc.price,
color=color.new(color.orange, 0), textcolor=color.black)
XAUUSD CSI+RSI+Delta (15m)XAUUSD 15m
Candle Stability Index: 0.4
RSI Index: 80
Candle Delta Length: 6
Disable Repeating Signals: Enabled
Jasons Bullish Reversal DetectorThis bullish reversal detector is designed to spot higher-quality turning points instead of shallow bounces. At its core, it looks for candles closing above the 20-period SMA, a MACD bullish crossover, and RSI strength above 50. On top of that, it layers in “depth” filters: price must reclaim and retest a long-term baseline (like the 200-period VWMA), momentum should confirm with RSI and +DI leading, short-term EMAs need to slope upward, and conditions like overheated ATR or strong downside ADX will block false signals. When all of these align, the script flags a depth-confirmed bullish reversal, aiming to highlight spots where structure, momentum, and volatility all support a sustainable shift upward.
Ultra High-Prob MTF BO Signals for binary take returnUltra High-Prob MTF BO Signals for binary take return
SuperScript Filtered (Stable)🔎 What This Indicator Does
The indicator is a trend and momentum filter.
It looks at multiple well-known technical tools (T3 moving averages, RSI, TSI, and EMA trend) and assigns a score to the current market condition.
• If most tools are bullish → score goes up.
• If most tools are bearish → score goes down.
• Only when the score is very strong (above +75 or below -75), it prints a Buy or Sell signal.
This helps traders focus only on high-probability setups instead of reacting to every small wiggle in price.
________________________________________
⚙️ How It Works
1. T3 Trend Check
o Compares a fast and slow T3 moving average.
o If the fast T3 is above the slow T3 → bullish signal.
o If it’s below → bearish signal.
2. RSI Check
o Uses the Relative Strength Index.
o If RSI is above 50 → bullish momentum.
o If RSI is below 50 → bearish momentum.
3. TSI Check
o Uses the True Strength Index.
o If TSI is above its signal line → bullish momentum.
o If TSI is below → bearish momentum.
4. EMA Trend Check
o Looks at two exponential moving averages (fast and slow).
o If price is above both → bullish.
o If price is below both → bearish.
5. Score System
o Each condition contributes +25 (bullish) or -25 (bearish).
o The total score can range from -100 to +100.
o Score ≥ +75 → Strong Buy
o Score ≤ -75 → Strong Sell
6. Signal Filtering
o Only one buy is allowed until a sell appears (and vice versa).
o A minimum bar gap is enforced between signals to avoid clutter.
________________________________________
📊 How It Appears on the Chart
• Green “BUY” label below candles → when multiple signals agree and the market is strongly bullish.
• Red “SELL” label above candles → when multiple signals agree and the market is strongly bearish.
• Background softly shaded green or red → highlights bullish or bearish conditions.
No messy tables, no clutter — just clear trend-based entries.
________________________________________
🎯 How Traders Can Use It
This indicator is designed to help traders by:
1. Filtering Noise
o Instead of reacting to every small crossover or RSI blip, it waits until at least 3–4 conditions agree.
o This avoids entering weak trades.
2. Identifying Strong Trend Shifts
o When a Buy or Sell arrow appears, it usually signals a shift in momentum that can lead to a larger move.
3. Reducing Overtrading
o By limiting signals, traders won’t be tempted to jump in and out unnecessarily.
4. Trade Confirmation
o Traders can use the signals as confirmation for their own setups.
o Example: If your strategy says “go long” and the indicator also shows a strong Buy, that trade has more conviction.
5. Alert Automation
o Built-in alerts mean you don’t have to watch the chart all day.
o You’ll be notified only when a strong signal appears.
________________________________________
⚡ When It Helps the Most
• Works best in trending markets (bullish or bearish).
• Very useful on higher timeframes (1h, 4h, daily) for swing trading.
• Can also work on lower timeframes (5m, 15m) if combined with higher timeframe trend filtering.
________________________________________
👉 In short
This indicator is a signal filter + trend detector. It combines four powerful tools into one scoring system, and only tells you to act when the odds are stacked in your favor.
________________________________________
