PulsePoint SqueezePulsePoint Squeeze™ is a dynamic momentum compression and divergence detection system built to help traders identify high-pressure zones before breakout moves. Combining RSI-based thresholds, price compression zones, and divergence cues, it offers high-clarity insights with minimal noise — ideal for intraday precision and swing positioning.
Bande e canali
6868//@version=5
indicator(title='6868', shorttitle='ICHI', overlay=true)
// Version 1.1
// Created by NgheTrader
TS_D1 = input.int(9, minval=1, title='Tenkan-sen')
KS_D1 = input.int(17, minval=1, title='Kijun-sen')
TS_D2 = input.int(65, minval=1, title='Tenkan-sen')
KS_D2 = input.int(129, minval=1, title='Kijun-sen')
Chikou_Displacement = input.int(25, minval=1, title='Chikou-span')
SB = input.int(26, minval=1, title='Senko Span B')
donchian(len) =>
math.avg(ta.lowest(len), ta.highest(len))
Tenkan = donchian(TS_D1)
Kijun = donchian(KS_D1)
KumoA = math.avg(Tenkan, Kijun)
KumoB = donchian(SB)
DG65 = donchian(TS_D2)
DG129 = donchian(KS_D2)
plot(Tenkan, color=color.new(#0fc7db, 10), title='Tenkan-sen', linewidth=2)
plot(Kijun, color=color.new(#f00f0f, 10), title='Kijun-sen', linewidth=2)
plot(DG65, color=color.new(#f8e804e6, 10), title='dg65', linewidth=2)
plot(DG129, color=color.new(#f99b04, 10), title='DG129', linewidth=2)
plot(close, offset=-Chikou_Displacement, color=color.new(#9c27b0, 10), title='Chikou-span', linewidth=2)
p1 = plot(KumoA, offset=Chikou_Displacement, color=color.new(#0cb71a, 0), linewidth=1, title='Span A')
p2 = plot(KumoB, offset=Chikou_Displacement, color=color.new(#afaaaac5,0), linewidth=1, title='Span B')
fill(p1, p2, color=KumoA > KumoB ? color.new(#106323,80) : color.new(#e4e1e1,0), title='Kumo Cloud')
// Plot Future Lines
Midpoint_future1(len) =>
math.avg(ta.highest(len - 1), ta.lowest(len - 1))
Midpoint_future2(len) =>
math.avg(ta.highest(len - 2), ta.lowest(len - 2))
Midpoint_future3(len) =>
math.avg(ta.highest(len - 3), ta.lowest(len - 3))
Midpoint_future4(len) =>
math.avg(ta.highest(len - 4), ta.lowest(len - 4))
Midpoint_future5(len) =>
math.avg(ta.highest(len - 5), ta.lowest(len - 5))
Midpoint_future6(len) =>
math.avg(ta.highest(len - 6), ta.lowest(len - 6))
Midpoint_future7(len) =>
math.avg(ta.highest(len - 7), ta.lowest(len - 7))
Midpoint_future8(len) =>
math.avg(ta.highest(len - 8), ta.lowest(len - 8))
Midpoint_future9(len) =>
math.avg(ta.highest(len - 9), ta.lowest(len - 9))
Midpoint_future10(len) =>
math.avg(ta.highest(len - 10), ta.lowest(len - 10))
Midpoint_future11(len) =>
math.avg(ta.highest(len - 11), ta.lowest(len - 11))
Midpoint_future12(len) =>
math.avg(ta.highest(len - 12), ta.lowest(len - 12))
Midpoint_future13(len) =>
math.avg(ta.highest(len - 13), ta.lowest(len - 13))
Midpoint_future14(len) =>
math.avg(ta.highest(len - 14), ta.lowest(len - 14))
// Plot Future Daily Kijun
KJ_Next_1 = Midpoint_future1(KS_D1)
KJ_Next_2 = Midpoint_future2(KS_D1)
KJ_Next_3 = Midpoint_future3(KS_D1)
KJ_Next_4 = Midpoint_future4(KS_D1)
KJ_Next_5 = Midpoint_future5(KS_D1)
KJ_Next_6 = Midpoint_future6(KS_D1)
KJ_Next_7 = Midpoint_future7(KS_D1)
KJ_Next_8 = Midpoint_future8(KS_D1)
KJ_Next_9 = Midpoint_future9(KS_D1)
KJ_Next_10 = Midpoint_future10(KS_D1)
plot(KJ_Next_1, color=color.new(#f00f0f, 10), linewidth=1, offset=1, show_last=1, style=plot.style_circles)
plot(KJ_Next_2, color=color.new(#f00f0f, 10), linewidth=1, offset=2, show_last=1, style=plot.style_circles)
plot(KJ_Next_3, color=color.new(#f00f0f, 10), linewidth=1, offset=3, show_last=1, style=plot.style_circles)
plot(KJ_Next_4, color=color.new(#f00f0f, 10), linewidth=1, offset=4, show_last=1, style=plot.style_circles)
plot(KJ_Next_5, color=color.new(#f00f0f, 10), linewidth=1, offset=5, show_last=1, style=plot.style_circles)
plot(KJ_Next_6, color=color.new(#f00f0f, 10), linewidth=1, offset=6, show_last=1, style=plot.style_circles)
plot(KJ_Next_7, color=color.new(#f00f0f, 10), linewidth=1, offset=7, show_last=1, style=plot.style_circles)
plot(KJ_Next_8, color=color.new(#f00f0f, 10), linewidth=1, offset=8, show_last=1, style=plot.style_circles)
plot(KJ_Next_9, color=color.new(#f00f0f, 10), linewidth=1, offset=9, show_last=1, style=plot.style_circles)
plot(KJ_Next_10,color=color.new(#f00f0f, 10), linewidth=1, offset=10, show_last=1, style=plot.style_circles)
// Plot Future Daily Tenkan
TS_Next_1 = Midpoint_future1(TS_D1)
TS_Next_2 = Midpoint_future2(TS_D1)
TS_Next_3 = Midpoint_future3(TS_D1)
TS_Next_4 = Midpoint_future4(TS_D1)
TS_Next_5 = Midpoint_future5(TS_D1)
TS_Next_6 = Midpoint_future6(TS_D1)
TS_Next_7 = Midpoint_future7(TS_D1)
TS_Next_8 = Midpoint_future8(TS_D1)
plot(TS_Next_1, color=color.new(#0fc7db, 10), linewidth=1, offset=1, show_last=1, style=plot.style_circles)
plot(TS_Next_2, color=color.new(#0fc7db, 10), linewidth=1, offset=2, show_last=1, style=plot.style_circles)
plot(TS_Next_3, color=color.new(#0fc7db, 10), linewidth=1, offset=3, show_last=1, style=plot.style_circles)
plot(TS_Next_4, color=color.new(#0fc7db, 10), linewidth=1, offset=4, show_last=1, style=plot.style_circles)
plot(TS_Next_5, color=color.new(#0fc7db, 10), linewidth=1, offset=5, show_last=1, style=plot.style_circles)
plot(TS_Next_6, color=color.new(#0fc7db, 10), linewidth=1, offset=6, show_last=1, style=plot.style_circles)
plot(TS_Next_7, color=color.new(#0fc7db, 10), linewidth=1, offset=7, show_last=1, style=plot.style_circles)
plot(TS_Next_8, color=color.new(#0fc7db, 10), linewidth=1, offset=8, show_last=1, style=plot.style_circles)
// Plot Future Kumo A
Next_KumoA_1 = Midpoint_future1(TS_D2)
Next_KumoA_2 = Midpoint_future2(TS_D2)
Next_KumoA_3 = Midpoint_future3(TS_D2)
Next_KumoA_4 = Midpoint_future4(TS_D2)
Next_KumoA_5 = Midpoint_future5(TS_D2)
Next_KumoA_6 = Midpoint_future6(TS_D2)
Next_KumoA_7 = Midpoint_future7(TS_D2)
Next_KumoA_8 = Midpoint_future8(TS_D2)
Next_KumoA_9 = Midpoint_future9(TS_D2)
plot(Next_KumoA_1, color=color.new(#f8e804e6, 10), linewidth=1, offset=1, show_last=1, style=plot.style_circles)
plot(Next_KumoA_2, color=color.new(#f8e804e6, 10), linewidth=1, offset=2, show_last=1, style=plot.style_circles)
plot(Next_KumoA_3, color=color.new(#f8e804e6, 10), linewidth=1, offset=3, show_last=1, style=plot.style_circles)
plot(Next_KumoA_4, color=color.new(#f8e804e6, 10), linewidth=1, offset=4, show_last=1, style=plot.style_circles)
plot(Next_KumoA_5, color=color.new(#f8e804e6, 10), linewidth=1, offset=5, show_last=1, style=plot.style_circles)
plot(Next_KumoA_6, color=color.new(#f8e804e6, 10), linewidth=1, offset=6, show_last=1, style=plot.style_circles)
plot(Next_KumoA_7, color=color.new(#f8e804e6, 10), linewidth=1, offset=7, show_last=1, style=plot.style_circles)
plot(Next_KumoA_8, color=color.new(#f8e804e6, 10), linewidth=1, offset=8, show_last=1, style=plot.style_circles)
plot(Next_KumoA_9, color=color.new(#f8e804e6, 10), linewidth=1, offset=9, show_last=1, style=plot.style_circles)
// Plot Future Kumo B
KB_Next_1 = Midpoint_future1(KS_D2)
KB_Next_2 = Midpoint_future2(KS_D2)
KB_Next_3 = Midpoint_future3(KS_D2)
KB_Next_4 = Midpoint_future4(KS_D2)
KB_Next_5 = Midpoint_future5(KS_D2)
KB_Next_6 = Midpoint_future6(KS_D2)
KB_Next_7 = Midpoint_future7(KS_D2)
KB_Next_8 = Midpoint_future8(KS_D2)
KB_Next_9 = Midpoint_future9(KS_D2)
KB_Next_10 = Midpoint_future10(KS_D2)
KB_Next_11 = Midpoint_future11(KS_D2)
KB_Next_12 = Midpoint_future12(KS_D2)
KB_Next_13 = Midpoint_future13(KS_D2)
KB_Next_14 = Midpoint_future14(KS_D2)
plot(KB_Next_1, color=color.rgb(253, 173, 0), linewidth=1, offset=1, show_last=1, style=plot.style_circles)
plot(KB_Next_2, color=color.rgb(253, 173, 0), linewidth=1, offset=2, show_last=1, style=plot.style_circles)
plot(KB_Next_3, color=color.rgb(253, 173, 0), linewidth=1, offset=3, show_last=1, style=plot.style_circles)
plot(KB_Next_4, color=color.rgb(253, 173, 0), linewidth=1, offset=4, show_last=1, style=plot.style_circles)
plot(KB_Next_5, color=color.rgb(253, 173, 0), linewidth=1, offset=5, show_last=1, style=plot.style_circles)
plot(KB_Next_6, color=color.rgb(253, 173, 0), linewidth=1, offset=6, show_last=1, style=plot.style_circles)
plot(KB_Next_7, color=color.rgb(253, 173, 0), linewidth=1, offset=7, show_last=1, style=plot.style_circles)
plot(KB_Next_8, color=color.rgb(253, 173, 0), linewidth=1, offset=8, show_last=1, style=plot.style_circles)
plot(KB_Next_9, color=color.rgb(253, 173, 0), linewidth=1, offset=9, show_last=1, style=plot.style_circles)
plot(KB_Next_10, color=color.rgb(253, 173, 0), linewidth=1, offset=10, show_last=1, style=plot.style_circles)
plot(KB_Next_11, color=color.rgb(253, 173, 0), linewidth=1, offset=11, show_last=1, style=plot.style_circles)
plot(KB_Next_12, color=color.rgb(253, 173, 0), linewidth=1, offset=12, show_last=1, style=plot.style_circles)
plot(KB_Next_13, color=color.rgb(253, 173, 0), linewidth=1, offset=13, show_last=1, style=plot.style_circles)
plot(KB_Next_14, color=color.rgb(253, 173, 0), linewidth=1, offset=14, show_last=1, style=plot.style_circles)
var line greenLine = na
var line redLine = na
xGreen = bar_index - 8
xRed = bar_index - 16
// Dùng khoảng 100 nến gần nhất để lấy phạm vi giá hiện hành
lookback = 100
top = ta.highest(high, lookback)
bottom = ta.lowest(low, lookback)
if bar_index > 17
line.delete(greenLine)
line.delete(redLine)
greenLine := line.new( x1 = xGreen, y1 = top, x2 = xGreen, y2 = bottom, color=color.new(#0fc7db, 85), width = 4)
redLine := line.new( x1 = xRed, y1 = top, x2 = xRed, y2 = bottom,color =color.new(#f00f0f, 85), width = 4 )
Scalping Intraday Hariss 369This indicator is very useful in 1 or 3 min chart for scalping. However, it can be used in higher time frame also.
The main indicator used here is cross over of 9 and 21 EMA. 21 VWMA is working as dynamic buy and sell stop loss. However, PSAR can also be used as SL.
Buy signal is displayed when all criteria are fulfilled. Same is for sell. KAMA is used to analyze the market trend. Avoid taking trade while KAMA is flat. Sell when KAMA is down trend and buy when KAMA is uptrend.
Best works in scalping, especially for NIFTY option trading.
You can add Super trend indicator to enhance trend direction. Super trend has not been considered to take trade. Use Hekin Ashi candles for better visualization.
HuntXHuntX is a comprehensive visual tool designed to support decision-making for intraday and swing traders. Built to simplify complex market data into actionable insights, this tool brings together multiple technical signals in a clean and easy-to-read format.
The core logic uses a combination of market structure, momentum detection, trend-following principles, and price confirmation triggers. Every component is built to reduce clutter and eliminate unnecessary noise found in traditional indicators.
Whats included:
Buy/Sell Signals
Real-time, color-coded signals based on momentum, trend alignment, and confirmation logic.
Dynamic Trend Bands
Visually track price direction and volatility zones using adaptive upper and lower fibonacci bands.
Auto Trendlines
Automatically draws relevant diagonal trendlines based on recent price structure and breakout potential.
Trend Direction System
Built-in engine to detect and filter trades based on macro direction — avoids choppy zones and whipsaws.
Institutional Volume Zones
Highlights areas where large volume may indicate smart money activity.
Wave Overlay System
Visualizes trending vs ranging environments using subtle wave patterns to guide entries/exits.
Support/Resistance Zones
Automatically detects and plots key levels where price has historically reacted.
Multi-Timeframe Awareness
Optional filters based on higher timeframe trends to align with broader market context.
Alerts Ready
Supports custom TradingView alerts for buy, sell, or other internal logic triggers.
Opening Range Breakout (ORB)
It contains a customizable ORB with suggested SL and TP
Clean UI and Customization
Easily toggle components on or off, adjust colors, and tailor the visual look to your chart style.
This script is invite-only and not visible by default. Access is only granted upon request.
Nadaraya,poly100,MA ribbon,volume nến,RSInadaraya
polynomial 100
volume nến
rsi break out 75,25
MA Ribbon
EMA Reclaim Alert - FVG StrategyThis script identifies momentum-based trend reclaims using two Exponential Moving Averages (EMAs), and plots entry, stop-loss, and take-profit levels for trade signals. It also highlights potential fakeouts.
SMA Fecho na Máxima, Mínima e NormalLarry Williams' Strategy - Short Moving Average Channel
✅ Indicators used:
High SMA: 3 periods
Low SMA: 3 periods
30-period Closing SMA: used as a trend filter
XX Swing Trader 202507The "XX Swing Trader 202507" is a sophisticated TradingView indicator that combines multiple technical analysis tools to help traders identify trends, reversals, and optimal entry/exit points.
Here's a comprehensive breakdown of its key components:
Core Components
Reversal Bar X Signals
Identifies potential trend reversals using bar colors
Generates buy signals when price transitions from bearish to bullish
Generates sell signals when price transitions from bullish to bearish
Uses a 50-bar lookback period to confirm significant price levels
Adaptive SuperTrend
Implements a dynamic SuperTrend indicator
Uses K-means clustering to adapt to market volatility
Automatically adjusts to high, medium, and low volatility periods
Provides clear trend direction signals
Includes visual fill colors for trend identification
Long-Term EMA
200-period Exponential Moving Average
Color-coded based on trend direction
Serves as a major trend filter
Hull Moving Averages
Implements two different Hull Moving Average calculations
First HMA (Wavy1) for general trend direction
Second HMA (Wavy2) for more precise entry/exit points
Color-coded based on trend direction
Peak Detection
Identifies significant price peaks and troughs
Uses a customizable lookback period
Helps identify potential support and resistance levels
Visual Features
Color-coded indicators for easy trend identification
Dynamic fill colors for trend visualization
Customizable transparency and line thickness
Optional candle coloring based on trend direction
Trading Applications
Entry Signals: Combined signals from multiple components for higher probability entries
Trend Identification: Multiple timeframe analysis through various moving averages
Risk Management: stop-loss placement
Volatility Adaptation: Automatic adjustment to changing market conditions
Support/Resistance: Multiple methods for identifying key price levels
Ideal For
Swing traders looking to identify potential trend reversals
Traders who want to manage risk through multiple technical levels
Those seeking indicators that adapt to changing market volatility
Traders who prefer combining multiple technical analysis tools
Anyone looking to make informed trading decisions based on multiple confirmations
ORB Norman (2 Sessions, Auto Timezone)ORB Norman (2 Sessions, Auto Timezone)
This script plots Opening Range Breakout (ORB) levels for two configurable sessions. It’s designed for intraday traders—especially in futures markets like Gold (GC), Nasdaq (NQ), and S&P (ES)—who trade based on early session breakouts or range rejections. Unlike standard indicators, this tool auto-adjusts for timezones based on the instrument, ensuring precise session alignment.
Features:
Automatically adjusts for NQ/ES (Chicago time) and GC (New York time) based on the symbol.
Plots high, low, and optional midpoint lines for each session.
Clean, minimal settings with visual separation for better usability.
Ray extension length is fully customizable.
Works on any intraday chart (recommended: 5–15 minute timeframes).
Includes customizable session times, colors, ray length, and an optional midpoint line.
Default Sessions:
Session 1:
‣ 07:00–08:00 EST for GC
‣ 06:00–07:00 CT for NQ/ES
Session 2:
‣ 09:30–09:45 EST for GC
‣ 08:30–08:45 CT for NQ/ES
This tool is ideal for traders who scalp the early morning breakout or look for range rejections based on the opening auction.
This script was developed from scratch based on the author's own intraday trading needs.
BURSA Intraday GANN By ZAM V1.4// BURSA GANN By ZAM V1.4
// Created by Zam – Programmer & Trader
This script is designed specifically for **Bursa Malaysia** market (MYX) and combines GANN-based price levels with volume spike detection, VWAP positioning, and visual entry signal markers to support fast decision-making for scalpers and intraday traders.
✅ Key Features:
- GANN Levels displayed with color-coded zones:
🔴 Red (Major Resistance), 🟡 Yellow (Minor Zone), 🔵 Blue (Strong Support)
- Entry Point (EP) signal based on volume spike, bullish candle, and trend strength
- 9:00 AM market open marker with price label (auto-adjustable for backtest)
- VWAP short line with percentage deviation from current price
- EMA20 (thin orange) and EMA50 (thick blue) trend guides
- Upper Bollinger Band to indicate overextension zones
- GANN Info Box showing:
🎯 Zone Type | Open Price | VWAP & % Deviation
🧪 Backtest-Friendly & Modular:
- Toggle options to display EP and 9AM markers across all historical bars
- Modular controls for EP logic (Basic/Strict), VWAP, and visual elements
🎯 Purpose:
Designed for **intraday traders on Bursa Malaysia (MYX)** who want fast, high-clarity visual signals with structured zone logic for TP planning and entry timing.
This is the stable release V1.4 – fully tested and ready for live trading or strategy building.
“Build a system, not just hope.”
ORBopen range breakout- if the prices move out this band in the morning opening sess then long if no then short
Dow Theory - AnchorTime Linear Regression Channel🧭 Dow Theory – AnchorTime Linear Regression Channel
Not moving. Not smoothing. Just anchored price structure from the point that matters.
Unlike traditional regression channels that constantly shift with every new candle, this indicator allows you to anchor your channel to a fixed historical time, letting you draw a stable trend channel that reflects the real structure of price since that exact point.
🚫 Why It Was Built:
No moving averages
No smoothing techniques
This ensures that you don't distort the structure when the market moves fast, slow, or with inconsistent volatility.
Traditional regression channels recalculate and slide continuously, making it nearly impossible to identify a reliable structure for breakout or long-term channel trading.
🎯 What It Does:
You choose an anchor time (e.g., a major pivot low or breakout).
The channel is drawn from that fixed point to now, using raw price data only.
Automatically adjusts upper/lower boundaries based on actual price deviation – not based on average noise.
🧱 Why It Matters in Dow Theory:
In Dow Theory, identifying major trends requires knowing where they started.
This tool helps you:
Lock in a structural starting point
Track channel integrity over long periods
Prepare for breakouts with full visual context
⚙️ Key Features:
Fully customizable slope calculation method (Close, OHLC, Median, Typical)
Dynamic buffer-based channel deviation
Static anchor = stable channel
Clean labels and clear visual hierarchy
Dow Theory - High Timeframe Linear Regression Channel🧭 Dow Theory – High Timeframe Linear Regression Channel
No moving averages. No smoothing. Just clean structure, drawn directly from price.
This indicator is built for serious price action traders who need to stay aligned with the true structure of the market - especially when volatility shifts or price moves in irregular waves. Unlike indicators that rely on moving averages or smoothed data, this tool is based purely on confirmed high-timeframe raw price movement.
⚙️ How It Works:
Detects highs and lows from your chosen higher timeframe (e.g., H1 or H4).
Draws real-time trendlines and parallel regression channels based on true price action — no smoothing involved.
When price closes beyond the channel, the indicator breaks the trend visually and structurally.
In sideways phases, it automatically draws clean horizontal boundaries to define consolidation zones.
❌ What It Doesn’t Do:
No moving averages
No exponential or weighted filters
No price smoothing
→ Which means no distortion when price moves with inconsistent speed or volatile ranges.
🌟 Key Features:
Trend-aligned trading made visual: Clearly see if structure is trending or ranging.
Auto break detection: Trendlines are removed once structure is invalidated.
100% price-based logic: No repainting, no lag.
Customizable visuals: Adjust timeframe, color, line style, and more.
🧪 Perfect For:
Traders who avoid lagging indicators and want real structure.
Systems that require clean, event-driven signals based on HTF behavior.
Navigating fast or irregular markets without being misled by artificial smoothing.
Dow Theory - Low timeframe Linear Regression Channel🔍 Dow Theory - Minor Trend: Linear Regression Channel for Low Timeframes
Catch Every Move. No Smoothing. No Delay. Pure Price Action.
This indicator redefines how you analyze minor trends on low timeframes by applying Dow Theory principles without relying on traditional smoothing techniques like moving averages. Instead, it maps trends using pure candle high and low points, capturing even the smallest structural shifts with surgical precision.
🧠 What Makes It Special?
Unlike traditional linear regression channels that smooth price across fixed windows (which often fail during high volatility or abrupt moves), this tool is built to react instantly, adapting to the true pulse of the market—the candle’s own highs and lows. The result: no lag, no distortion, and no compromise during fast, slow, wide, or tight market phases.
🧩 Core Functionalities:
Minor Trend Mapping: Automatically identifies and draws channels using candle-by-candle pivot detection (not swing highs/lows).
Adaptive Channel Drawing: Draws real-time parallel channels as soon as a valid trend structure is detected—uptrend, downtrend, or sideway range.
Break Detection Logic: Highlights when price breaks above or below the current channel to anticipate trend shifts.
Sideway Detection: Dynamically tracks contraction phases using overlapping pivot structures.
No Repainting: All lines are fixed and historical; what you see is what really happened.
Fully Customizable:
Change trendline colors for bullish, bearish, or sideway zones.
Adjustable line width and style (solid, dashed, dotted).
Toggle on/off channel lines for clarity.
💡 Why Use This?
If you’re tired of average-based indicators that get whipsawed in volatile markets, this is your surgical tool for clarity. Whether you’re scalping, building entry logic, or looking to automate setups—this indicator gives you the raw market structure in its cleanest, most responsive form.
ENJOY!
gop 3 trong 1"This approach is designed to help traders be proactive. It focuses on identifying the footprints of 'sharks' (Smart Money) to understand institutional activity. It dynamically maps the market structure in real-time, and provides clear, proactive guidance using Fibo OTE (Optimal Trade Entry) zones for high-probability Price Action trading."
Gelismiş Piyasya ve Hizli Trend Analizi (AI Destekli)I Powered Market & Fast Trend Analysis
Dear investors and analysts,
Today, we are excited to present an advanced, AI-powered TradingView indicator designed to empower your market decisions and accelerate your trend analysis. This indicator has been developed to help you make sense of complex market data and make more informed trading decisions.
Key Features and Benefits:
Comprehensive Market Analysis: The indicator comprehensively analyzes four main market dynamics: trend, momentum, volatility, and volume. This provides an in-depth perspective on the overall health of the market.
Multi-Timeframe Integration: By combining data from both the current timeframe (4-hour) and the daily timeframe, it generates more robust and reliable signals. This allows you to balance short-term fluctuations with long-term trends.
AI-Powered Decision Mechanism: Through weights assigned to each market dynamic and dynamic thresholds, the indicator generates a combined AI-powered score and signal. This helps you make objective decisions by reducing subjective interpretations.
Market Context Integration: By analyzing data from important market indicators like BIST indices (XU100, XU030, XBANK), it relates the performance of a single asset to broader market conditions. This helps you "see the forest, not just the trees."
Clear and Understandable Signals: With clear text-based signals such as "Strong Buy," "Potential Sell," "Money Inflow," and "Money Outflow," it allows you to quickly grasp the market situation. These signals, supported by color coding, are also easy to follow visually.
Customizable Settings: Many parameters, such as periods, weights, and thresholds, can be adjusted by the user. This allows you to personalize the indicator according to your own trading strategy and risk tolerance.
Why Should You Use This Indicator?
This indicator simplifies your market analysis process while strengthening the logic behind your decisions. By leveraging the power of artificial intelligence, it helps you identify market opportunities more quickly and accurately. It is a valuable tool for both novice and experienced investors.
Thank you. Get your 1-month free demo of our indicator now!
Unified Signals + BB Expansion Filtercan be universal use for different futures product but yet to fine tune for individual use
Delta Volume Movement TrackerOverview
This Pine Script, titled "Delta Volume Movement Tracker," is a sophisticated volume analysis tool designed to run in a separate pane below the main price chart. Its primary purpose is to dissect market activity by analyzing volume data from a lower timeframe to provide a clearer picture of the real buying and selling pressure behind price movements.
The core concept is to look at the volume delta (up-tick volume minus down-tick volume) from a faster timeframe (e.g., 1-minute) and correlate it with the price action on the current chart. This allows the indicator to distinguish between different market scenarios, such as strong, confirmed buying versus selling pressure that occurs even as the price rises.
Key Components
1. Lower Timeframe Volume Delta
The script's engine is the ta.requestUpAndDownVolume() function. It pulls detailed volume data from a user-specified lower timeframe. This provides a high-resolution view of the order flow. From this, it calculates the delta, which is the net difference between buying and selling volume.
Positive Delta: More volume occurred on up-ticks than down-ticks, suggesting buying pressure.
Negative Delta: More volume occurred on down-ticks than up-ticks, suggesting selling pressure.
2. Categorizing Price and Volume Interaction
The script intelligently categorizes market action by looking at both the direction of the price change and the sign of the volume delta. This creates four distinct conditions:
Strong Buying (upPositiveDelta): Price is moving up, AND the volume delta is positive. This is a confirmation signal, indicating that the upward price move is supported by aggressive buying.
Selling into Strength (upNegativeDelta): Price is moving up, BUT the volume delta is negative. This is a divergence, suggesting that despite the price rise, larger players may be distributing or selling into the rally.
Buying into Weakness (downPositiveDelta): Price is moving down, BUT the volume delta is positive. This is also a divergence, suggesting that buyers are stepping in to absorb the selling pressure, potentially indicating a bottom.
Strong Selling (downNegativeDelta): Price is moving down, AND the volume delta is negative. This is a confirmation signal, indicating that the downward price move is supported by aggressive selling.
3. Price-Weighted Summation
Instead of just counting the occurrences, the script calculates a rolling sum for each category over a lookbackPeriod. Crucially, it weights these values by the close price, effectively measuring the monetary value of the flow in each category. This gives more significance to volume that occurs at higher price levels.
How It Appears on the Chart
The indicator plots the two most powerful confirmation signals as columns to make them easy to interpret:
Green Columns (upBuySum): Represents the cumulative, price-weighted value of "Strong Buying." Taller green bars indicate significant and sustained buying pressure.
Red Columns (downSellSum): Represents the cumulative, price-weighted value of "Strong Selling." Taller red bars indicate significant and sustained selling pressure.
EMA Lines: Smooth exponential moving averages of both the buying and selling plots are overlaid to help identify the prevailing trend in order flow.
Filled Zones: The areas beneath the zero line and the plotted columns are filled with color, making it easy to visually gauge the magnitude of buying or selling pressure at a glance.
In summary, this indicator provides a nuanced view of market dynamics, helping traders see beyond simple price action to understand the strength and conviction of the buyers and sellers driving the trend.
Machine Learning RSI with MatrixThe "Machine Learning RSI with Matrix," is an adaptive version of the traditional Relative Strength Index (RSI). It's designed to dynamically adjust to changing market conditions by learning from past price action. Instead of using a fixed calculation, it employs machine learning concepts to create a more responsive and nuanced momentum oscillator.
Core Concepts
At its heart, the indicator analyzes market characteristics like momentum and volatility over a long lookback period. It uses this information to:
Cluster Market Regimes: It categorizes the market's volatility into different states or "clusters." This allows the indicator to behave differently in calm, normal, or highly volatile environments.
Store Patterns: A unique "matrix" system stores recent RSI patterns corresponding to each volatility cluster. This creates a memory of what has happened before in similar market conditions, helping it anticipate future behavior.
Generate Probabilistic Signals: It runs thousands of Monte Carlo simulations on each bar. These simulations use weighted random probabilities based on current momentum and volatility to generate a forward-looking, probabilistic signal.
Dynamic and Adaptive Features
This isn't a static tool. Its key strength lies in its ability to adapt in real-time:
Self-Adjusting RSI Length: The indicator continuously compares its predicted RSI value to a more traditional RSI calculation. The "error" between these two is then used to dynamically adjust the RSI calculation length, making it shorter for faster response in volatile markets and longer for smoother signals in trending markets.
Adaptive Learning Rate: The speed at which the indicator adapts can be set to automatically adjust based on market volatility, allowing it to learn faster when the market is moving quickly.
Recursive Memory: The final output includes a "memory" component, which is a feedback loop from its own recent values. This helps create a smoother, more stable signal that is less prone to sudden spikes.
Final Output and Visualization
The final plotted value is a sophisticated blend of multiple elements: the adaptive RSI, the true RSI, the cluster average, and the memory average. This combined signal provides a comprehensive view of momentum.
Dynamic Thresholds: The overbought and oversold levels are not fixed at 70 and 30. They move up and down based on a Z-Score of the price, which measures how extreme the current price is relative to its recent history. This helps avoid premature signals in strong trends.
Adaptive Trend & Whale Vol + POCAdaptive Trend & Whale Vol + POC — powerful multi-tool indicator combining adaptive trend, whale volume spikes, RSI divergences, and volume-based POC to enhance trade entries and exits with clear signals and alerts.
