RSI +++Customizable RSI indicator with bullish and bearish color coding and pivot dots when RSI crosses its moving average.
Analisis Tren
Beta -> PROFABIGHI_CAPITAL🌟 Overview
The Beta → PROFABIGHI_CAPITAL indicator calculates the systematic risk measurement of any asset relative to a chosen benchmark using statistical correlation analysis and variance decomposition methodology . It combines return calculation, covariance analysis, and variance measurement across (Asset Returns, Benchmark Returns, Correlation Analysis) with rolling window calculations. The indicator features automated beta coefficient calculation , zero-division protection , and benchmark comparison analysis for enhanced systematic risk assessment and market correlation identification.
⚙️ General Settings
– Lookback Period : Number of bars for calculating rolling statistics and correlations (1-500 bars, default: 30).
– Benchmark Symbol : Reference market index for beta calculation (default: CRYPTO:BTCUSD).
– Overlay Setting : False - displays as separate pane oscillator for clear beta visualization.
📊 Beta Calculation Components & Methods
The indicator calculates systematic risk metrics using advanced statistical methods:
- Asset Returns : Rate of change calculation for current asset percentage movements per bar
- Benchmark Returns : Rate of change calculation for benchmark percentage movements per bar
- Mean Asset Returns : Simple moving average of asset returns over lookback period
- Mean Benchmark Returns : Simple moving average of benchmark returns over lookback period
- Covariance Calculation : Manual computation measuring how asset and benchmark move together
- Benchmark Variance : Manual calculation of benchmark return volatility and dispersion
- Beta Coefficient : Systematic risk measure derived from covariance divided by benchmark variance
📈 Advanced Statistical Features
Correlation Analysis Framework:
- Return Decomposition : Separation of asset returns into systematic and unsystematic components
- Market Sensitivity : Measurement of asset responsiveness to benchmark movements
- Risk Attribution : Identification of market-related versus asset-specific risk factors
Rolling Window Analysis:
- Dynamic Lookback : Continuously updated statistics over specified period for current relevance
- Adaptive Calculation : Real-time recalculation with each new bar for evolving correlation analysis
- Statistical Smoothing : Moving average application for return volatility reduction
Mathematical Protection:
- Zero-Division Safety : Built-in protection preventing calculation errors when benchmark variance equals zero
- Error Handling : Returns appropriate values when statistical calculations become undefined
- Robust Framework : Maintains functionality across all market conditions and correlation scenarios
📏 Signal Levels & Interpretation
– Beta = 1 (Gray Dash) : Asset moves in perfect correlation with benchmark (same volatility)
– Beta > 1 (Above Line) : Asset exhibits higher volatility than benchmark (amplified movements)
– Beta < 1 (Below Line) : Asset exhibits lower volatility than benchmark (dampened movements)
– Beta = 0 (Zero Line) : No correlation between asset and benchmark movements
– Negative Beta : Inverse correlation - asset moves opposite to benchmark direction
📋 Beta Interpretation Framework
Systematic Risk Analysis :
- Beta > 1.0 : High Beta Asset - greater systematic risk and volatility than market
- Beta = 1.0 : Market Beta - moves in line with benchmark volatility
- Beta < 1.0 : Low Beta Asset - lower systematic risk and volatility than market
- Beta ≈ 0 : Market Neutral - minimal correlation with benchmark movements
- Negative Beta : Hedge Asset - provides portfolio diversification through inverse correlation
Portfolio Management Applications :
- Risk Assessment : Understanding asset's contribution to portfolio systematic risk
- Diversification Analysis : Identifying correlation patterns for portfolio construction
- Hedging Strategy : Utilizing beta relationships for risk management
- Asset Selection : Choosing assets based on desired beta characteristics
🎨 Visual Features
– Beta Line : Blue line plot with 2-pixel thickness showing beta coefficient evolution
– Reference Line : Horizontal dashed gray line at beta = 1 for market correlation reference
– Separate Pane Display : Independent oscillator visualization for focused beta analysis
– Dynamic Scaling : Automatic y-axis adjustment to accommodate beta value ranges
🔍 Advanced Features
– Multi-Asset Compatibility : Works across all asset classes and market instruments
– Benchmark Flexibility : Any tradable symbol can serve as correlation benchmark
– Real-Time Updates : Continuous beta recalculation with each new price bar
– Statistical Accuracy : Manual covariance and variance calculations ensuring precision
– Rolling Window Methodology : Maintains specified lookback period for all calculations
– Correlation Sensitivity : Responsive to changing market relationships and correlations
🔔 Beta Applications & Signals
– High Beta Identification : Assets with beta > 1.2 indicating high market sensitivity
– Low Beta Recognition : Assets with beta < 0.8 indicating defensive characteristics
– Beta Stability Analysis : Monitoring beta consistency over time for reliability assessment
– Correlation Breakdown : Identifying periods when historical correlations change
– Risk Management : Using beta values for position sizing and portfolio risk control
– Market Regime Detection : Beta changes often signal shifting market conditions
By utilizing precise statistical correlation analysis and systematic risk measurement , the Beta → PROFABIGHI_CAPITAL indicator provides mathematically robust market sensitivity analysis , offering accurate identification of systematic risk exposure through rigorous covariance calculation , variance analysis , and benchmark correlation assessment .
NY Session (PIPNEXUS) Description:
This indicator, created for the PIPNEXUS Community, is designed to make backtesting easier and more efficient. It highlights the New York session, allowing you to clearly see when the market experiences the highest volume and liquidity. By using this tool, PIPNEXUS members can better identify peak trading hours, spot potential high-momentum moves, and optimize their trading strategy. Ideal for traders who want a precise and visual way to track the most active market periods.
RSI Divergence + Smoothed MA + Bollinger Bandadjust same settings as what you see on the pics.
imgur.com
ZoneRadar by Chaitu50cZoneRadar
ZoneRadar is a tool designed to detect and visualize hidden buy or sell pressures in the market. Using a Z-Score based imbalance model, it identifies areas where buyers or sellers step in with strong momentum and highlights them as dynamic supply and demand zones.
How It Works
Z-Score Imbalance : Calculates statistical deviations in order flow (bull vs. bear pressure).
Buy & Sell Triggers: Detects when imbalances cross predefined thresholds.
Smart Zones: Marks potential buy (green) or sell (red) zones directly on your chart.
Auto-Merge & Clean: Overlapping or noisy zones are automatically merged to keep the chart clean.
History Control: Keeps only the most recent and strongest zones for focus.
Key Features
Customizable Z-Score level and lookback period
Cooldown filter to avoid over-signaling
Smart zone merging to prevent clutter
Adjustable price tolerance for merging overlapping zones (ticks)
Extend zones into the future with right extensions
Fully customizable colors and display settings
Alert conditions for Buy Pressure and Sell Pressure
Why ZoneRadar?
Simplifies complex order flow into clear, tradable zones
Helps identify high-probability reversal or continuation levels
Avoids noise by keeping only the cleanest zones
Works across any timeframe or market (stocks, futures, forex, crypto)
Disclaimer
This tool is designed for educational and informational purposes only. It does not provide financial advice. Always test on demo and combine with your own trading strategy.
Strength by EGThis indicator from equitygurukul.in is designed to help traders identify key market trend phases using classic moving averages. It includes:
50, 150, 200-period MAs (user can choose SMA or EMA via dropdown).
A Custom MA (default length 21, user-adjustable).
Buy Signal Arrow when bullish alignment conditions are met.
Weak Label when price crosses below the Custom MA.
Strength Label when price crosses above the Custom MA and is also above the 50 MA.
Fully customizable colors, label display toggles, and arrow size options.
This tool allows traders to quickly visualize momentum shifts, long-term trend alignment, and strength/weakness signals on the chart.
⚠️ Disclaimer
This script is created for educational purposes under the brand equitygurukul.in. It is not financial advice. Trading and investing involve risk, and past performance does not guarantee future results. Please do your own research or consult a financial advisor before making investment decisions.
utt ohlc Pivot Linecheck only on day time frame and mark a line based on line u can plan a trade line above bullish below bearish ,its educational purpose only
Trend Scalping Strategy Overview
This is a short-term trading strategy designed to capitalize on momentum shifts within a broader trend. It combines multiple technical indicators across different timeframes—including Stochastic, RSI, and custom trend logic—to generate entry and exit signals. The strategy incorporates a time filter to operate only during specified high-liquidity hours and includes a mandatory end-of-session close-out to avoid overnight risk. It is suitable for volatile markets like equities, futures, and cryptocurrencies.
Input Parameters
Source
The price data used for calculations. Default is hl2 (the average of high and low prices).
Short Term Trend (x_len_a)
The period for the short-term RSI calculation. Default is 5. Used to capture recent price momentum.
Long Term Trend (x_len_b)
The period for the Stochastic Oscillator calculation. Default is 60. Defines the medium-to-long-term trend context.
Smooth Long Term Trend (x_k_b)
The smoothing period applied to the Stochastic value (K). Default is 13. Reduces noise for a clearer trend signal.
Clear Short Term Pullback Appears Recently (x_changk)
The lookback period to identify a recent significant pullback. Default is 15.
Threshold of Short Term Pullback Clear (x_rsi_ct)
The RSI level indicating an oversold (for longs) or overbought (for shorts) condition. Default is 35.0.
Threshold of Short Term Pullback End (x_rsi_ft)
The RSI level signaling that the short-term pullback has concluded and momentum is reversing. Default is 50.0.
Exit if Reason Over (x_exit_if_reason_over)
A boolean switch. If enabled, the strategy will automatically close a position if the original entry condition is no longer valid.
Time Filter (Start/End Hour & Minute)
Defines the specific intraday window during which the strategy is active (e.g., 7:00 to 15:10). All trades are initiated and managed only within this window.
Strategy Logic
Indicator Calculation:
y_stoch: The raw Stochastic Oscillator value calculated over the x_len_b period.
y_k: A smoothed version of the Stochastic (y_stoch) using a Simple Moving Average with period x_k_b.
y_rsi: The Relative Strength Index calculated on the Source price over the short-term period x_len_a.
Entry & Exit Conditions:
The core logic generates a composite signal (y_upper for long, y_lower for short) based on three components:
The deviation of the smoothed Stochastic (y_k) from its midpoint (50).
The deviation of the RSI (y_rsi) from its pullback-end threshold (x_rsi_ft).
The extremity of the recent RSI move compared to the pullback-clear threshold (x_rsi_ct) over the x_changk period.
Long Entry (LE): Triggered when the composite signal y_upper is greater than 0 AND the current time is within the allowed trading window.
Short Entry (SE): Triggered when the composite signal y_lower is less than 0 AND the current time is within the allowed trading window.
Conditional Exit: If x_exit_if_reason_over is true, long positions are closed if y_upper <= 0, and short positions are closed if y_lower >= 0.
Time-Based Filter:
The strategy only evaluates entries and exits if the current bar's time falls within the user-defined start_time and end_time range.
Mandatory Close-Out:
A critical risk management feature: All open positions are automatically closed at 16:10 (4:10 PM) based on the chart's timezone, ensuring no positions are held overnight or into the late session.
Plotting
The strategy plots three key series in the indicator pane:
Stochastic (y_stoch): Red line.
Smoothed Stochastic (y_k): Blue line.
RSI (y_rsi): Yellow line.
A hline at 50 serves as a visual midpoint reference for both Stochastic and RSI.
Usage Recommendations
This strategy performs best in markets with high volatility and strong trending characteristics.
It is highly recommended to use this script with a brokerage account that supports and enforces stop-loss orders on the strategy's behalf, as the script itself does not calculate stop-loss levels.
Parameters, especially periods and thresholds, should be optimized for the specific asset and timeframe being traded.
Always conduct rigorous backtesting and forward testing before deploying capital. 策略概述
本策略是一个基于多时间框架动能的短线交易策略，通过结合短期与长期趋势指标、RSI超买超卖判断以及时间过滤机制，在趋势明确时入场，并在特定条件或时间点退出交易。策略适用于股票、期货、加密货币等高频波动的市场。
输入参数说明
数据源（Source）
默认使用 hl2（最高最低价的平均值），也可选择其他价格数据。
短期趋势周期（Short Term Trend）
默认值为5，用于计算短期RSI，捕捉近期价格动量的变化。
长期趋势周期（Long Term Trend）
默认值为60，用于计算随机指标（Stochastic）的周期，判断中长期趋势方向。
长期趋势平滑周期（Smooth Long Term Trend）
默认值为13，对长期随机指标进行平滑处理，减少噪音。
近期回调检测周期（Clear Short Term Pullback Appears Recently）
默认值为15，用于检测短期是否出现明显回调。
RSI超卖阈值（Threshold of Short Term Pullback Clear）
默认值为35.0，RSI低于该值视为短期超卖，可能出现反弹。
RSI回调结束阈值（Threshold of Short Term Pullback End）
默认值为50.0，RSI回升至此表示短期回调结束。
条件失效时退出（Exit if Reason Over）
若启用，当入场条件不再成立时自动平仓。
交易时间范围
可设置策略运行的开始与结束时间（以小时和分钟为单位），仅在指定时间段内交易。
策略逻辑
指标计算：
随机指标（Stochastic）：基于长期周期计算，反映价格在近期区间内的位置。
平滑随机值（y_k）：对随机指标进行移动平均平滑处理。
RSI指标：基于短期周期计算，反映近期价格动量的强弱。
多空判断：
多头信号（y_upper）：
当平滑随机值高于50、RSI高于结束阈值，且近期出现明显超卖回调时，触发做多信号。
空头信号（y_lower）：
当平滑随机值低于50、RSI低于结束阈值，且近期出现明显超买回调时，触发做空信号。
时间过滤：
策略仅在用户设定的时间范围内（例如7:00至15:10）运行，避免在波动性较低或非主力交易时段操作。
强制平仓机制：
每天下午16:10（或指定时间区间）强制平仓所有头寸，避免隔夜风险或尾盘波动。
图表显示
策略在副图中绘制以下三条线：
随机指标（红色）
平滑随机值（蓝色）
RSI指标（黄色）
水平线50：作为多空分界线参考。
使用建议
本策略适合在流动性高、波动性强的市场中运行。
建议配合止损机制使用，以控制单笔交易风险。
用户可根据不同品种调整参数周期和阈值，优化入场时机。
Distance Between EMA'sThis indicator measures the distance between any two EMA's you choose. You can change the EMA's by clicking settings and change the inputs to the two that you choose
Rossgram
Script Name: ADMF: Rossgram Aggregated cumulative volume, volatility-dependent-parabolic-length, divergence-inverting EMA admf
Description:
This publication is a major revision by the original author. The script has been significantly improved to provide more accurate and timely signals by enhancing its core adaptive logic.
Key Improvements & Originality:
Enhanced Dynamic Calculation: The core algorithm now features a sophisticated volatility normalization mechanism. Instead of using a simple ATR, it calculates a normalized volatility index (volATR_admf) and dynamically adjusts the EMA length based on its position within a dynamically updated percentile range (2nd to 98th). This allows the indicator to be exceptionally responsive across different market regimes, from extreme volatility to calm conditions.
Advanced Percentile Anchoring: A dedicated initialization and update routine ensures robust calculation of volatility extremes. The script:
Initializes with safe defaults for the first 1000 bars.
After the 1000th bar, it calculates precise percentile levels (ta.percentile_nearest_rank) every 100 bars, ensuring the adaptive mechanism is always anchored to the most relevant recent market data rather than a fixed historical period. This is a unique approach to defining "extremes".
Multi-Exchange Data Aggregation (User-Configurable): The script is designed to aggregate volume data from multiple sources. This provides a more accurate picture of market activity than a single exchange. Users can manually configure a list of tickers for non-BTC assets in the settings, tailoring the data input to their specific trading instrument.
How It Works & How to Use:
The indicator plots a moving average that exponentially adjusts its sensitivity based on real-time market volatility. As volatility approaches historically high levels (98th percentile), the EMA length expands to filter out noise and help identify exhaustion. In low volatility (near the 2nd percentile), it contracts to become more responsive to new trends.
Usage: Add to the chart. For non-BTC assets, configure the tickers in settings.
Signal Interpretation: Look for the adaptive line to change direction, especially after it has been trending near one of the volatility extremes. This often anticipates sharp reversals.
Why Closed-Source? The specific implementation of the dynamic percentile-based anchoring, the volatility normalization formula, and the data aggregation logic are proprietary developments. Protecting the source code is necessary to safeguard the unique intellectual property behind this adaptive calculation method.
M/S Signal v2 - Multi-Zone Signal SystemM/S Signal v2 - Advanced Multi-Zone Breakout System
🔧 TECHNICAL INNOVATION
This indicator introduces a unique combination of adaptive zone confluence detection with multi-timeframe directional filtering that addresses specific limitations found in standard breakout indicators.
🎯 CORE ALGORITHM DIFFERENCES:
1. Adaptive Level Management:
Code
// Unlike static S/R indicators, levels update dynamically
if close > active_high:
active_high := current_high
active_low := current_low
generate_signal("BUY")
Traditional indicators use fixed pivot points. This system continuously adapts support/resistance levels based on actual price action.
2. Zone Confluence Mathematics:
Code
zones_match(level1, level2, tolerance_percent) =>
diff = math.abs(level1 - level2)
avg_price = (level1 + level2) / 2
tolerance = avg_price * tolerance_percent / 100
diff <= tolerance
This mathematical approach to zone alignment is not available in standard zone-based indicators.
3. Multi-Timeframe Signal Validation:
Code
htf_signal = request.security(symbol, htf_tf, get_last_signal_type())
allow_signal = current_tf_signal AND htf_allows_direction
The system tracks the last active signal from higher timeframes, not just current trend direction.
📊 UNIQUE FEATURES:
Triple Zone System:
Zone 1 (100-period): Macro trend identification
Zone 2 (60-period): Impulse movement detection
Zone 3 (20-period): Precise entry triggers
Dual Independent Filters:
Filter 1: Zone confluence with customizable tolerance (0.1% default)
Filter 2: Higher timeframe last signal direction
Each filter operates independently and can be toggled on/off
Dynamic Level Tracking: Unlike indicators that use predetermined levels, this system:
Updates support/resistance after each breakout
Prevents duplicate signals until new level formation
Tracks signal history to avoid repetitive alerts
📈 TECHNICAL SPECIFICATIONS:
Code Architecture:
PineScript v6 with optimized performance
45+ customizable parameters across 8 setting groups
Maximum 500 objects for stable operation
Overlay design with full visual control
Signal Generation Logic:
Monitor current support/resistance levels
Detect price breakouts above/below active levels
Apply zone confluence filter (if enabled)
Validate against higher timeframe direction (if enabled)
Generate final signal only when all conditions align
Visualization Components:
Three colored zone overlays with customizable fills
Active support/resistance level lines
BUY/SELL signal labels with price information
Key breakout candle highlighting
Real-time current price tracking
⚙️ SETTING GROUPS:
Zone Settings - Configure zone periods and colors
Zone Signal Filters - Control confluence detection
Higher Timeframe Filter - Set HTF validation rules
BUY Signal Configuration - Customize buy signal appearance
SELL Signal Configuration - Customize sell signal appearance
Alert System - Configure notification preferences
Visual Display - Control chart appearance elements
Level Management - Active support/resistance display
🎯 PRACTICAL APPLICATIONS:
For Scalping (M1-M5):
Disable HTF filter for faster signals
Use tight zone confluence tolerance (0.05%)
Focus on Zone 3 breakouts for quick entries
For Swing Trading (H1-H4):
Enable HTF filter with Daily timeframe
Use standard confluence tolerance (0.1%)
Combine all three zones for confirmation
For Position Trading (H4-Daily):
Set HTF filter to Weekly timeframe
Wider confluence tolerance (0.2%)
Focus on Zone 1 trend alignment
🔧 HOW TO USE:
Basic Setup: Use default parameters for most markets
Enable Filters: Turn on zone confluence for higher accuracy
Set HTF Filter: Choose appropriate higher timeframe for your strategy
Customize Signals: Adjust BUY/SELL signal appearance preferences
Configure Alerts: Set up notifications for real-time signal delivery
The indicator works by continuously monitoring price action against dynamically updated support and resistance levels, applying sophisticated filtering mechanisms to ensure only high-probability setups generate signals.
均线趋势过滤器 (MA_trend Signal/Noise Filter)双语简介
中文：
这款指标是一个基于“信噪比”思想的终极趋势过滤器。它通过比较快速和慢速EMA均线之间的差值（即信号）与ATR（平均真实波幅，代表噪音）来判断市场趋势。只有当信号的强度超过噪音的指定倍数时，才会确认趋势的有效性。该指标可帮助交易者过滤掉噪音，精确捕捉强势趋势，避免误操作。
English:
This indicator is the Ultimate Trend Filter based on the Signal-to-Noise ratio concept. It compares the difference between the fast and slow EMA (Signal) to the ATR (Noise) to determine market trends. A trend is confirmed only when the signal strength exceeds the noise by a specified multiplier. This indicator helps traders filter out noise and accurately capture strong trends, avoiding false signals.
High For Loop | MisinkoMasterThe High For Loop is a new Trend Following tool designed to give traders smooth and fast signals without being too complex, overfit or repainting.
It works by finding how many bars have a higher high than the current high, how many have a lower high, and scores it based on that. This provides users with easy and accurate signals, allowing for gaining a large edge in the market.
It is pretty simple but you can still play around with it pretty well and improve uppon your strategies.
For any backtests using strategies, I left many comments and tried to make it as easy as possible to backtest.
Enjoy G´s
MA-Median For Loop | MisinkoMasterThe MA-Median For Loop is a new Trend Following tool that gives the user smooth yet responsive trend signals, allowing you to see clear and accurate trends by combining the Moving Average & Median in a For Loop concept.
How does it work?
1. Select user defined inputs
=> Adjust it to your liking, everyone can set it to their liking.
2. Calculate the MA and the Median
=> Simple, but important
3. Calculate the For Loop
=> For every bar back where the median or ma of that bar is higher than the current median or ma subtract 0.5 from the trend score, and for every bar back where the current median/ma is higher than the previous one add 0.5 to the trend score.
This simple yet effective approach enhances speed, decreases noise, and produces accurate signals everyone can utilize to get an edge in the market
Enjoy G´s
HMA super trade by @arkancapMulti-HMA with five customizable moving averages: visual colors, transparency via picker, flexible line styles, and label/alert for HMA50↔HMA100 crossovers. Lightweight, readable, and ready for trading templates.
Мульти-HMA с пятью настраиваемыми скользящими: визуальные цвета, прозрачность через пикер, гибкие стили линий и метка/алерт для пересечений HMA50↔HMA100. Лёгкий, читабельный и готовый к торговым шаблонам.
Five Hull moving averages that show the trend and indicate key crossovers. Customize colors, thickness, and get accurate alerts. Suitable for scalping and multi-timeframes. Support for filling between moving averages to visually highlight areas of strength or weakness.
Пять Hull-скользящих, которые показывают тренд и подсказывают ключевые пересечения. Настраивай цвета, толщину и получай аккуратные алерты. Подходит для скальпа и мульти-таймфрейма. Поддержка заливки между скользящими для наглядного выделения зон силы или слабости.
DAILY WYCKOFF ATMWyckoff Confidence Dashboard
A clean, mobile-optimized Wyckoff phase and alignment dashboard built for serious traders.
This tool dynamically detects Accumulation, Distribution, Markup, and Markdown across multiple timeframes (1H/15M) and scores confidence based on:
• HTF trend direction
• Liquidity sweeps
• Fair Value Gap (FVG) presence
• Volume/OBV confirmation
• Multi-timeframe phase/action alignment
Includes smart alerts and a lightweight dashboard interface — no clutter, just actionable structure-based insight.
Great for SMC, Wyckoff, or price-action traders seeking high-confluence entries.
Statistical Mapping [Version 3]Edit Statistical Mapping (ESM) is a statistical technique used mainly in data validation, error detection, and imputation. It’s often applied in official statistics and large surveys. The method works by:
Defining a set of edits (logical or mathematical rules) that data records must satisfy.
Example: Income ≥ 0, Age ≥ 15 if Employment Status = “Employed”.
Identifying inconsistencies in the data when these edits are violated.
Using statistical mapping to correct or impute missing/inconsistent values based on relationships in the dataset.
Ensuring coherence of microdata so that it aligns with macro-level aggregates.
Supporting survey data cleaning, census editing, and economic statistics preparation.
It’s particularly important for official statistics agencies because data collected from respondents often contains errors, missing entries, or contradictions. ESM ensures that the final dataset is internally consistent, reliable, and ready for analysis.
Smart Money Price Action ProSmart Money Price Action Pro - Smart Money and Price Action Dynamic Toolkit
The Smart Money Price Action Pro is designed to bring together multiple layers of market analysis into a single, cohesive framework, combining trend identification and consolidation detection in an actionable format. While individual indicators can provide useful insights, they often work in isolation. This toolkit integrates market flow detection, range analytics, and adaptive visualization into one system, allowing traders to see the bigger picture without piecing together multiple disconnected tools.
Building on principles from institutional trading behaviors, the toolkit gives traders a clearer picture of where “smart money” may be entering or exiting the market. Its design emphasizes confluence: signals from multiple independent modules overlap to create higher conviction setups, offering a structured edge when planning entries, exits, and risk levels.
At its core, the toolkit addresses the duality of market conditions: trending versus ranging. By offering a combination of trend-following signals and contrarian insights, it helps traders operate with a deeper understanding of market structure. While it provides actionable signals and visual guidance, it is intended as an assistive system, helping traders make more informed decisions rather than serving as a single source of truth.
Key Modules
1. Smart Money Signal Module
The Smart Money Signal Module identifies potential institutional activity by analyzing price swings and momentum shifts. Using configurable swing detection, it highlights potential reversal or continuation zones, expressed as adaptive zones around key market levels.
Signals are augmented with trend-colored candle overlays, offering immediate guidance on market bias. Bullish and bearish zones are clearly marked, while continuation and reversal markers help distinguish between trend shifts and market noise.
At its core, the engine applies swing detection combined with a sensitivity filter to track directional momentum across recent bars. This allows it to pinpoint bullish pivots (where downside momentum fades and strength returns) and bearish pivots (where upside momentum collapses). Once a pivot is confirmed, the system draws flow lines that map the breakout and classify it as either continuation or reversal, depending on broader market bias.
Momentum zones are then plotted to show areas where buyers stepped in with strength or sellers forced price lower. These levels extend forward dynamically, shifting in real time as new data forms. Zones change color the moment they break, visually confirming whether market structure has held or failed. Gradient shading highlights periods of extreme pressure, giving traders a clear visual of when momentum surges into overbought or oversold territory.
Instead of simply showing trend direction, this module also maps accumulation and distribution zones tied to institutional flows. When combined with the Range Module, these zones become more meaningful — for example, when institutional accumulation aligns with a breakout from consolidation.
Practical Use: Traders can use these signals to align trades with institutional flows. For example, entering a long position near a bullish accumulation zone or managing risk when bearish distribution areas form. By combining these insights with higher timeframe analysis, traders can filter out false signals and improve decision-making.
2. Range Detection Module
The Range Detection engine continuously monitors price action to flag when markets transition into consolidation phases. Ranges are defined not just by flat price action, but by a measurable contraction in volatility, repeated touches of boundary levels, and the clustering of traded volume around a central equilibrium point.
Once a valid range is identified, the system assigns a compression strength score (0–100). This score reflects how cleanly defined and structurally sound the consolidation is—higher scores indicate tighter boundaries and stronger evidence of accumulation or distribution.
Breakout tendencies are modeled dynamically. The system updates a forward-looking bias by incorporating:
Boundary time distribution – how often price presses against upper vs. lower edges
Historical breakout patterns – probability benchmarks derived from structurally similar ranges
Volume skew – whether traded volume leans toward buyers or sellers inside the range
Momentum alignment – auxiliary filters such as slope-based oscillators that indicate when energy is building for a directional move
The result is a live breakout forecast that evolves bar by bar as the range matures. Each active range carries a visual strength meter plotted above the consolidation zone, quantifying both compression and breakout potential in real time.
The module also supports range memory, preserving completed consolidations even after a breakout. This allows traders to review the prior structure for post-analysis or to track whether price respects the boundaries of the old range as support or resistance going forward.
Practical Use : Traders can use these ranges to anticipate breakout direction or step aside when conditions are unclear. A tight consolidation near a bullish zone, for instance, often signals a potential long opportunity, while overlapping bearish flows warn of false breakouts.
Integrated Workflow
The strength of the toolkit lies in its synergy. Each module is effective on its own, but the real advantage comes when their signals align.
A typical workflow may include:
Assessing the market trend using the Smart Money Signal Module and its trend-colored overlays
Identifying consolidation and breakout zones with the Range Detection Module
Watching for confluences: institutional accumulation aligning with range compression, or dashboard bias matching local setups
Executing trades with structured confidence, using these layered confirmations rather than relying on a single trigger
This integrated workflow streamlines decision-making and avoids the conflicting signals that can occur when combining unrelated indicators.
Additional Features
Adaptive Visualization : Dynamic zones and trend overlays adjust to volatility, keeping charts clear and focused
Analytics Dashboard : A compact summary panel shows active zones, bullish vs bearish flow counts, and current bias, giving context at a glance
Instead of simply adding more signals, the dashboard provides a meta-layer of analysis — context, bias, and flow strength — helping traders manage risk and stay aligned with broader market conditions.
Use Cases
Trend Confluence : Entering trades in line with prevailing smart money flows while filtering out counter-trend setups
Breakout Trading : Using the Range Detection Module to anticipate breakout zones and confirming direction with institutional flow signals
Contrarian Reversal Trades : Targeting accumulation/distribution zones where both modules indicate potential reversals
Each use case demonstrates how layered confluence creates clarity and conviction, making the toolkit a strong complement to other forms of technical analysis.
Conclusion
The Smart Money Signals Toolkit simplifies complex market analysis into actionable, visually intuitive insights. While standalone indicators provide value, this toolkit goes further by combining smart money flows, range detection, adaptive zones, and dashboard analytics into one cohesive system.
It doesn’t just generate buy/sell markers — it shows why a setup matters, where it is occurring, and how it aligns with broader conditions. This allows traders to operate with greater clarity, structure, and discipline.
Risk Disclaimer : This toolkit and its features are for educational and informational purposes only. Past performance does not guarantee future results. All suggested use cases are theoretical and should be applied with proper risk management.
Double Median ATR Bands | MisinkoMasterThe Double Median ATR Bands is a version of the SuperTrend that is designed to be smoother, more accurate while maintaining a good speed by combining the HMA smoothing technique and the median source.
How does it work?
Very simple!
1. Get user defined inputs:
=> Set them up however you want, for the result you want!
2. Calculate the Median of the source and the ATR
=> Very simple
3. Smooth the median with √length (for example if median length = 9, it would be smoothed over the length of 3 since 3x3 = 9)
4. Add ATR bands like so:
Upper = median + (atr*multiplier)
Lower = median - (atr*multiplier)
Trend Logic:
Source crossing over the upper band = uptrend
Source crossing below the lower band = downtrend
Enjoy G´s!
Cardwell RSI by TQ📌 Cardwell RSI – Enhanced Relative Strength Index
This indicator is based on Andrew Cardwell’s RSI methodology , extending the classic RSI with tools to better identify bullish/bearish ranges and trend dynamics.
In uptrends, RSI tends to hold between 40–80 (Cardwell bullish range).
In downtrends, RSI tends to stay between 20–60 (Cardwell bearish range).
Key Features :
Standard RSI with configurable length & source
Fast (9) & Slow (45) RSI Moving Averages (toggleable)
Cardwell Core Levels (80 / 60 / 40 / 20) – enabled by default
Base Bands (70 / 50 / 30) in dotted style
Optional custom levels (up to 3)
Alerts for MA crosses and level crosses
Data Window metrics: RSI vs Fast/Slow MA differences
How to Use :
Monitor RSI behavior inside Cardwell’s bullish (40–80) and bearish (20–60) ranges
Watch RSI crossovers with Fast (9) and Slow (45) MAs to confirm momentum or trend shifts
Use levels and alerts as confluence with your trading strategy
Default Settings :
RSI Length: 14
MA Type: WMA
Fast MA: 9 (hidden by default)
Slow MA: 45 (hidden by default)
Cardwell Levels (80/60/40/20): ON
Base Bands (70/50/30): ON
