AlphaTrend_TC// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// author © KivancOzbilgic
// developer © KivancOzbilgic
// I'm just playing with it.... Jake Ryan
//@version=5
indicator('AlphaTrend', shorttitle='AT', overlay=true, format=format.price, precision=2, timeframe='')
coeff = input.float(1, 'Multiplier', step=0.1)
AP = input(14, 'Common Period')
ATR = ta.sma(ta.tr, AP)
src = input(close)
showsignalsk = input(title='Show Signals?', defval=true)
novolumedata = input(title='Change calculation (no volume data)?', defval=false)
upT = low - ATR * coeff
downT = high + ATR * coeff
AlphaTrend = 0.0
AlphaTrend := (novolumedata ? ta.rsi(src, AP) >= 50 : ta.mfi(hlc3, AP) >= 50) ? upT < nz(AlphaTrend ) ? nz(AlphaTrend ) : upT : downT > nz(AlphaTrend ) ? nz(AlphaTrend ) : downT
color1 = AlphaTrend > AlphaTrend ? #00E60F : AlphaTrend < AlphaTrend ? #80000B : AlphaTrend > AlphaTrend ? #00E60F : #80000B
k1 = plot(AlphaTrend, color=color.new(#0022FC, 0), linewidth=3)
k2 = plot(AlphaTrend , color=color.new(#FC0400, 0), linewidth=3)
fill(k1, k2, color=color1)
buySignalk = ta.crossover(AlphaTrend, AlphaTrend )
sellSignalk = ta.crossunder(AlphaTrend, AlphaTrend )
// Calculate Bollinger Bands around AlphaTrend
length = input(20, title="Bollinger Bands Length")
mult = input(2.0, title="Bollinger Bands Multiplier")
basis = ta.sma(AlphaTrend, length)
dev = mult * ta.stdev(AlphaTrend, length)
upperBand = basis + dev
lowerBand = basis - dev
// Plot Bollinger Bands
plot(upperBand, color=#2962FF, linewidth=1, title="Upper Bollinger Band")
plot(lowerBand, color=#2962FF, linewidth=1, title="Lower Bollinger Band")
// Rest of the code remains the same for generating signals and plotting arrows
K1 = ta.barssince(buySignalk)
K2 = ta.barssince(sellSignalk)
O1 = ta.barssince(buySignalk )
O2 = ta.barssince(sellSignalk )
plotshape(buySignalk and showsignalsk and O1 > K2 ? AlphaTrend * 0.9999 : na, title='BUY', text='BUY', location=location.absolute, style=shape.labelup, size=size.tiny, color=color.new(#0022FC, 0), textcolor=color.new(color.white, 0))
plotshape(sellSignalk and showsignalsk and O2 > K1 ? AlphaTrend * 1.0001 : na, title='SELL', text='SELL', location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(color.maroon, 0), textcolor=color.new(color.white, 0))
alertcondition(buySignalk and O1 > K2, title='Potential BUY Alarm', message='BUY SIGNAL!')
alertcondition(sellSignalk and O2 > K1, title='Potential SELL Alarm', message='SELL SIGNAL!')
alertcondition(buySignalk and O1 > K2, title='Confirmed BUY Alarm', message='BUY SIGNAL APPROVED!')
alertcondition(sellSignalk and O2 > K1, title='Confirmed SELL Alarm', message='SELL SIGNAL APPROVED!')
alertcondition(ta.cross(close, AlphaTrend), title='Price Cross Alert', message='Price - AlphaTrend Crossing!')
alertcondition(ta.crossover(low, AlphaTrend), title='Candle CrossOver Alarm', message='LAST BAR is ABOVE ALPHATREND')
alertcondition(ta.crossunder(high, AlphaTrend), title='Candle CrossUnder Alarm', message='LAST BAR is BELOW ALPHATREND!')
alertcondition(ta.cross(close , AlphaTrend ), title='Price Cross Alert After Bar Close', message='Price - AlphaTrend Crossing!')
alertcondition(ta.crossover(low , AlphaTrend ), title='Candle CrossOver Alarm After Bar Close', message='LAST BAR is ABOVE ALPHATREND!')
alertcondition(ta.crossunder(high , AlphaTrend ), title='Candle CrossUnder Alarm After Bar Close', message='LAST BAR is BELOW ALPHATREND!')
//from AlphaTrend
Indicators and strategies
Sistema Neutro GOULART HUD Regime Radar ORB VWAPSistema Neutro GOULART is an advanced visual trading indicator that integrates:
• A unified HUD displaying session status, ORB, VWAP, risk and market bias
• A Regime Radar heatmap (GO / WAIT / NO) designed to provide clarity without chart clutter
• ORB with straight daily lines and a clean zone limited to the current session
• Direction filtering using VWAP and VWAP slope
• Condition assessment based on risk and overall market context
• A harmonized visual design focused on objective decision-making
⚠️ This indicator does NOT generate trade signals.
It provides market context, regime classification, and quality assessment to support discretionary trading decisions.
Ideal for:
• Futures markets (ES, NQ, YM)
• Day trading using ORB + VWAP
• Traders who prioritize context, discipline, and structure over signals
For educational purposes only.
BTC - Metcalfes Law (Deviation)Title: BTC – Metcalfe's Law (Deviation) | RM
Overview & Philosophy
The BTC – Metcalfe's Law (Deviation) is a fundamental valuation oscillator that answers one of the most important questions in network economics: "Is the current price justified by the number of active users?" Metcalfe's Law states that the value of a network is proportional to the square of the number of its connected users (Value = Users squared). In the context of Bitcoin, this means that as the number of active addresses grows linearly, the network's fair value should grow exponentially.This script identifies periods where Bitcoin’s market capitalization has become "overextended" or "undervalued" relative to its actual network activity.
Methodology
The indicator performs a rolling log-log regression (Ordinary Least Squares) between Bitcoin's Market Cap and its Active Address count over a 730-day (2-year) window.
1. The Regression: The script calculates the statistical relationship: ln(Market Cap) = alpha + beta * ln(Active Addresses)
2. Pure Metcalfe vs. Generalized Metcalfe:
• Pure Metcalfe (Beta=2): By default, the script enforces a slope of 2.0, adhering to the classic mathematical law.
• Dynamic Fit: Users can disable the "Enforce Metcalfe" setting to let the model find the best historical fit (often resulting in a Beta between 1.5 and 1.8).
3. The Deviation (The Signal):
The resulting line represents the Log-Deviation from Fair Value.
• A value of 0.0 means Bitcoin is priced exactly according to its network utility.
• Positive values indicate a "valuation premium".
• Negative values indicate a "valuation discount".
How to Read the Chart
🔴 The Red Zone (Overvaluation > 1.0)
Meaning: The Market Cap has outpaced the growth of active users. Historically, these peaks represent speculative bubbles or cycle tops where price is driven by hype rather than utility.
🟢 The Green Zone (Undervaluation < -0.25)
Meaning: The network is being utilized, but the price has crashed below its fundamental support. Historically, these "Utility Floors" have marked the most profitable accumulation zones in Bitcoin’s history.
🟠 The Orange Line (Fair Value Transition)
Meaning: The market is in a healthy growth phase, moving in lockstep with user adoption.
Strategy & Interpretation
This tool is a Macro Compass . It is designed to help investors stay objective during periods of extreme market emotion.
• In a Bull Market: Watch for the deviation to hit the Red Zone. This is your signal that the "Network Utility" can no longer support the price, and a major correction is likely imminent.
• In a Bear Market: Look for the "Green Floor." When the price stays below the -0.25 level despite stable user activity, it suggests a massive mismatch between value and price—a classic buy signal.
Settings
• Regression Window (Default: 730 Days): Chosen to capture mid-to-long term cycle trends. Adjust to shorter timeframes for more dynamic behavior or longer timeframes (like 1460 Days) to catch longer cycles.
• Enforce Metcalfe: Toggle between the classic law (Beta=2) and a dynamic fit.
• Smoothing: A 30-day SMA is applied to active addresses to filter out daily "jitter."
Credits
• Robert Metcalfe: For the original law of network utility.
• Willy Woo & Greg Wheatley: For their pioneering work in applying Metcalfe's Law specifically to Bitcoin's valuation.
Important Data Requirement
To function, this indicator requires a data feed for Active Addresses . By default, it is set to GLASSNODE:BTC_ACTIVEADDRESSES . Please Note: On-chain data usually requires a premium vendor subscription on TradingView (e.g., Glassnode, IntoTheBlock, or CryptoQuant). If you do not have a subscription, the indicator will display a "Missing Data" warning.
⚠️ Note: This indicator is optimized for the Daily (1D) Timeframe. Please switch your chart to 1D for accurate signal reading.
Disclaimer
This script is for research and educational purposes only. It relies on third-party on-chain data. Fundamental valuation is only one piece of the puzzle; market dynamics can remain irrational longer than metrics can predict.
Tags
bitcoin, btc, on-chain, metcalfe, adoption, fundamental, valuation, active addresses, cycle, Rob Maths
Multi-Timeframe 5 Moving Averages//@version=5
indicator("Multi-Timeframe 5 Moving Averages", shorttitle="MTF MA x5", overlay=true)
// ============== MOVING AVERAGE 1 ==============
ma1_enabled = input(true, title="Enable MA1", group="Moving Average 1")
ma1_period = input.int(9, title="MA1 Period", minval=1, group="Moving Average 1")
ma1_type = input.string("EMA", title="MA1 Type", options= , group="Moving Average 1")
ma1_color = input(color.new(#FF6B35, 0), title="MA1 Color", group="Moving Average 1")
// ============== MOVING AVERAGE 2 ==============
ma2_enabled = input(true, title="Enable MA2", group="Moving Average 2")
ma2_period = input.int(20, title="MA2 Period", minval=1, group="Moving Average 2")
ma2_type = input.string("EMA", title="MA2 Type", options= , group="Moving Average 2")
ma2_color = input(color.new(#004E89, 0), title="MA2 Color", group="Moving Average 2")
// ============== MOVING AVERAGE 3 ==============
ma3_enabled = input(true, title="Enable MA3", group="Moving Average 3")
ma3_period = input.int(50, title="MA3 Period", minval=1, group="Moving Average 3")
ma3_type = input.string("SMA", title="MA3 Type", options= , group="Moving Average 3")
ma3_color = input(color.new(#F7931E, 0), title="MA3 Color", group="Moving Average 3")
// ============== MOVING AVERAGE 4 ==============
ma4_enabled = input(true, title="Enable MA4", group="Moving Average 4")
ma4_period = input.int(100, title="MA4 Period", minval=1, group="Moving Average 4")
ma4_type = input.string("SMA", title="MA4 Type", options= , group="Moving Average 4")
ma4_color = input(color.new(#1E88E5, 0), title="MA4 Color", group="Moving Average 4")
// ============== MOVING AVERAGE 5 ==============
ma5_enabled = input(true, title="Enable MA5", group="Moving Average 5")
ma5_period = input.int(200, title="MA5 Period", minval=1, group="Moving Average 5")
ma5_type = input.string("EMA", title="MA5 Type", options= , group="Moving Average 5")
ma5_color = input(color.new(#43A047, 0), title="MA5 Color", group="Moving Average 5")
// ============== FUNCTION TO CALCULATE MA ==============
calcMA(period, maType, source) =>
switch maType
"SMA" => ta.sma(source, period)
"EMA" => ta.ema(source, period)
"WMA" => ta.wma(source, period)
=> ta.sma(source, period)
// ============== CALCULATE MOVING AVERAGES (CHART TIMEFRAME ONLY) ==============
ma1_value = calcMA(ma1_period, ma1_type, close)
ma2_value = calcMA(ma2_period, ma2_type, close)
ma3_value = calcMA(ma3_period, ma3_type, close)
ma4_value = calcMA(ma4_period, ma4_type, close)
ma5_value = calcMA(ma5_period, ma5_type, close)
// ============== PLOT MOVING AVERAGES ==============
plot(ma1_enabled ? ma1_value : na, title="MA1", color=ma1_color, linewidth=2)
plot(ma2_enabled ? ma2_value : na, title="MA2", color=ma2_color, linewidth=2)
plot(ma3_enabled ? ma3_value : na, title="MA3", color=ma3_color, linewidth=2)
plot(ma4_enabled ? ma4_value : na, title="MA4", color=ma4_color, linewidth=2)
plot(ma5_enabled ? ma5_value : na, title="MA5", color=ma5_color, linewidth=2)
Custom Reversal Oscillator [wjdtks255]📊 Indicator Overview: Custom Reversal Oscillator
This indicator is a momentum-based oscillator designed to identify potential trend reversals by analyzing price velocity and relative strength. It visualizes market exhaustion and recovery through a dynamic histogram and signal dots, similar to premium institutional tools.
Key Components
Dynamic Histogram (Bottom Bars): Changes color based on momentum strength. Bright Green/Red indicates accelerating momentum, while Darker shades suggest fading strength.
Signal Line: A white line tracing the core momentum, helping to visualize the "wave" of the market.
Buy/Sell Dots: Small circles at the bottom (Mint) or top (Red) that signal high-probability reversal points when the market is overextended.
📈 Trading Strategy (How to Trade)
1. Long Entry (Buy Signal)
Condition 1: The price should ideally be near or above the 200 EMA (for trend following) or showing a Bullish Divergence.
Condition 2: The Histogram bars transition from Dark Red to Bright Green.
Condition 3: A Mint Buy Dot appears at the bottom of the oscillator (near the -25 level).
Entry: Enter on the close of the candle where the Buy Dot is confirmed.
2. Short Entry (Sell Signal)
Condition 1: The price is struggling at resistance or showing a Bearish Divergence.
Condition 2: The Histogram bars transition from Dark Green to Bright Red.
Condition 3: A Red Sell Dot appears at the top of the oscillator (near the +25 level).
Entry: Enter on the close of the candle where the Sell Dot is confirmed.
3. Exit & Take Profit
Take Profit: Close the position when the Signal Line reaches the opposite extreme or when the histogram color starts to fade (loses its brightness).
Stop Loss: Place your stop loss slightly below the recent swing low (for Longs) or above the recent swing high (for Shorts).
💡 Pro Tips for Accuracy
Watch for Divergences: The most powerful signals occur when the price makes a lower low, but the Custom Reversal Oscillator makes a higher low. This indicates "Hidden Strength" and a massive reversal is often imminent.
krishnadeshmukh/NIFTY50 Micro Sentiment Part 1📘 Script Description: NIFTY50 Micro Sentiment — Part 1
This indicator tracks real-time micro sentiment across the top 25 weighted stocks of the NIFTY50 index using a volume-based distribution model.
🔍 How it works:
Scans last N bars (configurable) for each stock.
Divides each stock’s price range into equal bins.
Measures bullish vs bearish volume in each bin based on:
Candle Color (Close > Open) or
Close Near High (Close > Midpoint).
Assigns a sentiment value:
+1 → Bullish dominance
-1 → Bearish dominance
0 → Neutral
📊 Each stock's sentiment is weighted by its contribution to the index.
🧮 Displays:
Weighted Sentiment Score
Bullish / Bearish / Neutral Components
Updated every 5 bars with an easy-to-read table.
Use this to gauge underlying micro shifts in sentiment before broader market moves.
Monthly High/Low - [JTCAPITAL]Monthly High/Low Probability Table - is a modified way to use historical monthly high and low tracking combined with probabilistic analysis for bullish and bearish months to detect potential patterns in monthly price behavior.
The indicator works by calculating in the following steps:
Variable Declaration
Persistent variables ( var ) are used to store monthly highs, lows, open and close prices, and the days on which highs and lows occurred. Separate arrays track bullish and bearish month statistics for highs and lows ( highBull, lowBull, highBear, lowBear ). Counters ( bullCount, bearCount ) store the number of bullish and bearish months recorded.
New Month Detection
The script detects the start of a new month by comparing the current bar’s month to the previous bar’s month. If a new month is detected, the script proceeds to update statistics for the previous month.
Monthly High/Low Recording and Classification
At the start of each new month, the previous month’s high, low, open, and close are evaluated:
If monthClose > monthOpen , the month is classified as bullish.
If monthClose < monthOpen , the month is classified as bearish.
The arrays ( highBull, lowBull, highBear, lowBear ) are updated at the respective high and low days of the month by incrementing counts, which allows the script to keep track of the frequency of monthly highs and lows occurring on specific days.
Monthly High/Low Tracking
During the month, the script continuously updates monthHigh and monthLow if the current bar’s high exceeds monthHigh or the low is below monthLow . The days on which these highs and lows occur are recorded ( highDay and lowDay ). The monthClose variable is continuously updated to the latest closing price.
Probability Calculation
Once monthly data is accumulated, the script calculates probabilities for each day of the month:
bullHighProb and bullLowProb represent the probability (in percentage) that a bullish month’s high or low occurred on a given day.
bearHighProb and bearLowProb represent the probability for bearish months.
These probabilities are calculated by dividing the count of high or low occurrences on each day by the total number of bullish or bearish months, then multiplying by 100. This probabilistic approach allows traders to see recurring patterns for highs and lows across multiple months.
Gradient Coloring Function
The helper function gradientRelative computes a color gradient between lowColor and highColor based on the relative probability value. Higher probabilities are colored closer to highColor , and lower probabilities closer to lowColor . This visual representation allows for quick identification of the most probable days for highs and lows in bullish or bearish months.
Dynamic Updates
As new bars are processed, the table is updated in real-time with new probabilities reflecting the most recent month’s data. This dynamic behavior ensures that the table remains accurate and responsive to the latest market information.
Buy and Sell Conditions:
This indicator does not provide direct buy or sell signals. Instead, it provides probabilistic information about historical patterns for bullish and bearish months. Traders can use the table to:
Identify days in the month where highs or lows are statistically more likely to occur.
Combine with other trend-following or reversal strategies to optimize entry and exit points.
For example, if a trader notices that bullish month highs frequently occur around day 15, they may plan trades around that period when other indicators align.
Features and Parameters:
Dynamic Probability Table : Updates in real-time as new monthly data becomes available.
Historical Pattern Tracking : Maintains arrays for highs and lows in bullish and bearish months.
Gradient Visualization : Uses color interpolation to quickly highlight higher probability days.
Specifications:
Monthly High/Low Tracking
Tracks the highest and lowest prices within each month. This is the foundation of the probability calculations. It allows traders to understand when significant price events historically occur.
Bullish/Bearish Month Classification
Each month is classified based on the relationship between monthClose and monthOpen . This provides context for the high/low occurrences: whether they happened in bullish or bearish months.
High/Low Occurrence Arrays
Four arrays ( highBull, lowBull, highBear, lowBear ) store the count of high and low occurrences for each day of the month. These arrays are the core of the statistical analysis.
Probability Calculation
Divides the count of occurrences for each day by the total number of months in that category (bullish/bearish). Multiplying by 100 converts this to a percentage probability, giving traders a numerical sense of recurrence.
Real-Time Updates
The table and probabilities are recalculated and refreshed with each new bar. This ensures that traders have the most current information available without manual recalculation.
User-Centric Visualization
By showing probabilities for both bullish and bearish months separately, traders gain a deeper understanding of market tendencies and recurring monthly patterns, which can be leveraged for improved timing and strategy alignment.
Important:
There is a misalign in percentages due to not all months having the same amount of days.
Effort-Result Divergence [Interakktive]The Effort-Result Divergence (ERD) measures whether volume effort is producing proportional price result. It quantifies the classic Wyckoff principle: when price moves easily, momentum is real; when price struggles despite heavy volume, absorption is occurring.
Think of ERD as "energy efficiency" for price movement — green means price is gliding, red means price is grinding.
█ WHAT IT DOES
• Measures volume EFFORT relative to average volume
• Measures price RESULT relative to ATR-normalized movement
• Computes ERD = Result minus Effort (each scaled 0-100)
• Flags statistical divergences via Z-score analysis
• Absorption events: high effort, low result (negative ERD)
• Vacuum events: low effort, high result (positive ERD)
█ WHAT IT DOES NOT DO
• NO buy/sell signals
• NO entry/exit recommendations
• NO alerts (v1 is educational only)
• NO performance claims or guarantees
This is a context tool for understanding market participation quality.
█ HOW IT WORKS
The ERD analyzes two dimensions of market activity and compares them.
EFFORT (Volume Intensity)
Compares current volume to a moving average baseline:
Effort Ratio = Volume ÷ SMA(Volume, Length)
Effort Score = clamp(100 × Effort Ratio ÷ Effort Cap)
High effort means above-average volume participation.
Low effort means below-average volume participation.
RESULT (Price Efficiency)
Measures how much price moved relative to expected volatility:
Result Ratio = |Close − Previous Close| ÷ ATR
Result Score = clamp(100 × Result Ratio ÷ Result Cap)
High result means price moved significantly for the volatility regime.
Low result means price barely moved despite market activity.
ERD SCORE
ERD = Result − Effort
• Positive ERD: Result exceeds effort → price moved easily (vacuum/thin liquidity)
• Negative ERD: Effort exceeds result → price struggled (absorption/accumulation)
• Near zero: Balanced effort-to-result relationship
STATISTICAL DIVERGENCE DETECTION
Z-score analysis identifies statistically significant extremes:
Z = (ERD − Mean) ÷ StdDev
• Absorption Event: Z ≤ −threshold (extreme negative ERD)
• Vacuum Event: Z ≥ +threshold (extreme positive ERD)
█ INTERPRETATION
GREEN BARS (Positive ERD)
Price moved with relatively little volume effort. This suggests:
• Thin liquidity / low resistance
• Strong directional interest
• Momentum is "real" — not forced
RED BARS (Negative ERD)
Heavy volume was used but price barely moved. This suggests:
• Absorption / accumulation occurring
• Large players opposing the move
• Inefficiency — someone is working hard for little result
THE KEY INSIGHT
When you see:
• Down moves = high effort (red spikes)
• Up moves = low effort (green bars)
This means: It's easier for price to go up than down.
That is asymmetric strength — classic bullish pressure.
The reverse (red on up moves, green on down moves) signals bearish pressure.
PRACTICAL RULES
Without any other indicators:
• Avoid shorting when ERD is mostly green and red spikes appear only on down candles
• Be cautious buying when ERD turns red on up candles (signals absorption of buying pressure)
• Vacuum events (extreme green) often precede continuation or pause — not violent reversal
• Absorption events (extreme red) often precede reversals or range formation
█ VOLUME DATA NOTE
This indicator uses the volume variable which represents:
• Exchange volume on stocks and futures
• Tick volume on Forex and CFD instruments
Tick volume is a proxy for activity, not actual exchange volume. The indicator remains useful on Forex as relative volume comparisons are still meaningful, but interpretation should account for this limitation.
█ INPUTS
Core Settings
• Volume Average Length: Baseline period for effort calculation (default: 20)
• ATR Length: Volatility normalization period (default: 14)
• Effort Cap: Volume ratio that maps to 100% effort (default: 3.0)
• Result Cap: ATR multiple that maps to 100% result (default: 1.0)
Divergence Detection
• Z-Score Lookback: Statistical analysis window (default: 100)
• Z-Score Threshold: Standard deviations for event flags (default: 2.0)
Visual Settings
• Show ERD Histogram: Toggle main display
• Show Zero Line: Toggle reference line
• Show Divergence Markers: Toggle event circles
• Show Effort/Result Lines: Display component breakdown
█ ORIGINALITY
While Wyckoff's effort-versus-result principle is well-established, existing implementations are typically:
• Purely visual with no quantification
• Pattern-based requiring subjective interpretation
• Not statistically normalized for comparison across instruments
ERD is original because it:
1. Normalizes both effort and result to 0-100 scales for direct comparison
2. Uses ATR for result normalization (adapts to volatility regime)
3. Applies statistical Z-score for objective divergence detection
4. Provides quantified output suitable for systematic analysis
█ DATA WINDOW EXPORTS
When enabled, the following values are exported:
• Effort (0-100)
• Result (0-100)
• ERD Score
• Z-Score
• Absorption Event (1/0)
• Vacuum Event (1/0)
█ SUITABLE MARKETS
Works on: Stocks, Futures, Forex, Crypto
Best on: Instruments with reliable volume data (stocks, futures, crypto)
Timeframes: All timeframes — interpretation adapts accordingly
█ RELATED
• Market Efficiency Ratio — measures price path efficiency
• Wyckoff Volume Spread Analysis — conceptual foundation
█ DISCLAIMER
This indicator is for educational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis before making trading decisions.
CVD & Big Trade Detector By HKOverview The CVD & Big Trade Detector By HK offers a unique perspective on Cumulative Volume Delta (CVD). This indicator utilizes Floating Bars (Candles) to visualize the cumulative buying and selling pressure. This design allows you to clearly see the net delta of each specific candle relative to the cumulative trend.
Additionally, it integrates the "Big Trade" algorithm to highlight statistically significant volume anomalies (Whale activity) directly on the CVD bars.
How it Works Since standard volume data does not always provide buy/sell splitting, this script estimates intrabar pressure using price action logic:
Buying Pressure: Calculated based on the push from the Low to the Close.
Selling Pressure: Calculated based on the push from the High to the Close.
The indicator then calculates the Delta (Buy Vol - Sell Vol) and accumulates it.
Floating Bars: Instead of plotting from the zero-line, each bar opens at the previous CVD value and closes at the new cumulative value.
Teal/Green Bar: Net buying in the current period (CVD increased).
Maroon/Red Bar: Net selling in the current period (CVD decreased).
Key Features
Floating CVD Structure: Prevents the "barcode effect" common in histogram CVDs. It provides a clean, candle-like view of momentum accumulation.
Whale Detection:
The script calculates the moving average and standard deviation (Sigma) of the buying/selling volume.
Green Dots: Appear when buying volume exceeds the statistical threshold (Signifying a "Big Buy").
Red Dots: Appear when selling volume exceeds the statistical threshold (Signifying a "Big Sell").
Precise Positioning: Whale markers are plotted exactly at the closing value of the CVD bar, showing you exactly where the volume spike impacted the delta.
How to Use
Divergences: Look for situations where Price makes a Higher High, but the CVD Bars fail to make a new high (bearish divergence).
Absorption: If you see a Large Whale Dot on a very small CVD bar (doji-like), it indicates massive volume fighting for direction with little net result—often a sign of absorption or a pending reversal.
Trend Confirmation: Strong floating bars in the direction of the trend, accompanied by Whale Dots, confirm smart money participation.
Settings
Lookback Period: Defines the baseline for the statistical volume calculation (default: 50).
Sensitivity (Sigma): Adjusts how strict the "Whale" detection is (default: 3.0). Higher values = fewer, more significant signals.
Colors: Fully customizable colors for Up/Down bars and Buy/Sell markers.
Built with Pine Script™ v6
Global J-1 & W-1 Levels (Fixed Lines / Lignes Fixes)Description
This indicator automatically plots key price levels from the previous day (D-1) and the previous week (W-1). It is designed for Day Traders and Scalpers who need clear visual references without cluttering their chart with past history.
Unlike standard indicators that use plot() and create "step-like" lines, this script uses graphic objects (line.new) to display fixed, infinite horizontal lines, just as if you had drawn them manually.
Key Features:
D-1 Levels (Blue): Previous Day High (DR-1) and Low (DS-1).
W-1 Levels (Red): Previous Week High (WR-1) and Low (WS-1).
Clean Chart: Lines are displayed only for the current session. No historical clutter.
Readability: Dashed lines with level names and exact prices displayed on the right.
How to use it? These levels often act as institutional support and resistance. Watch for price reactions (bounces or breakouts) near these zones to confirm your trade entries.
RSI with 3 Separate Smoothing AveragesRSI has 3 moving averages, to help trade better
RSI period can be adjusted
Moving average has multiple selections (SMA, EMA, HMA)
moving average cross over can be used as signal for trades
Trade at your own risk
Pivot point moving averagesPivot Point Moving Averages builds moving averages from confirmed pivots, not from every bar.
Instead of averaging all highs and lows, this script:
Detects swing pivot highs and pivot lows using a configurable Pivot length (pivotLen).
Converts these sparse pivot prices into continuous series of:
last confirmed pivot low
last confirmed pivot high
Applies a user-selectable moving average (SMA / EMA / RMA / WMA / VWMA) to each of those pivot series.
Plots the two resulting lines and shades the area between them as a pivot value cloud.
Because the lines only move when a new pivot is confirmed, they represent structural acceptance rather than raw volatility. Short “noise” moves and stop hunts between pivots have much less impact on these averages.
You can also enable an optional second pivot MA cloud:
Uses the same Pivot length for structural detection.
Has its own MA length and type.
Can run on a different timeframe (e.g. D, 240, W).
Is projected back onto the current chart so you see local pivot value and higher-timeframe pivot value together.
Why it’s useful
Traditional MAs:
React to every bar.
Move on noise, wicks, and stop runs.
Don’t distinguish between “meaningful” structure and random fluctuation.
This tool uses confirmed pivots, so it is better suited to market structure and phase analysis:
Pivot MA low reflects how demand is stepping up (or down) as new swing lows form.
Pivot MA high reflects how supply is pressing down (or easing) as new swing highs form.
The cloud between them acts as a dynamic, structure-based value area.
Typical interpretations:
Price inside the pivot cloud → balance / fair value area.
Price above the pivot cloud → bullish value expansion.
Price below the pivot cloud → bearish value expansion.
Cloud compressing → possible energy build-up, transition between phases.
Cloud expanding → stronger directional conviction.
With the second cloud enabled on a higher timeframe, you can:
See whether lower-timeframe structure is building with or against the higher-timeframe pivot value.
Use the HTF cloud as a background bias and the LTF cloud for timing and fine-grained context.
Notes
All pivot-based tools have inherent delay: a pivot is only confirmed after pivotLen bars to the right.
On very low timeframes, long pivotLen + long MA lengths will make the lines slower to react.
This is intended as a context and structure tool, not a standalone entry signal.
My OB detector 18 DicProfessional Order Block indicator optimized for M3 timeframe. It features automatic 50% entry detection, a strict 1:1 risk-to-reward ratio, and a 10-pip minimum profit filter. Strictly follows the Madrid session hours for Euro and US sessions.
Composite Index [Auto Signals]Composite Index
Description (描述正文):
Overview This is an enhanced version of the famous Composite Index (CI) developed by Connie Brown. While the traditional RSI is confined between 0 and 100, often masking true momentum in strong trends, the Composite Index is uncapped and incorporates a momentum component to reveal the market's true structural strength.
I have engineered this script to include Automated Signal Markers based on the crossover of the Composite Index and its Slow Moving Average. This helps traders instantly identify momentum shifts and "Timing" entries/exits without manual guesswork.
Key Features
Uncapped Momentum: Unlike RSI, the CI can go anywhere, preventing the "flattening" effect seen in strong trending markets (e.g., TSLA, NVDA).
Automated Signals:
▲ Green Triangle (Launch): Triggers when the Gray CI line crosses ABOVE the Red Slow MA. This indicates bearish momentum is exhausted and bulls are regaining control.
▼ Red Triangle (Warning): Triggers when the Gray CI line crosses BELOW the Red Slow MA. This indicates bullish momentum is failing, serving as an early warning for exits or tightening stops.
Classic Formula: Uses the standard Connie Brown parameters (14, 9, 3) + SMA smoothing for reliable divergence detection.
How to Use This Indicator This script is best used as a companion to trend indicators like TTM Squeeze or Moving Average Ribbons.
For Entries (The "Dip Buy"): In an uptrend, wait for a pullback. When the Green Triangle (▲) appears, it confirms that the pullback is over and momentum has turned back up.
For Exits (The "Top"): Look for Divergence. If Price makes a Higher High but the Composite Index makes a Lower High—followed by a Red Triangle (▼)—this is a high-probability sell signal.
The "Slow MA" Filter: The signals are generated only when the CI crosses the Slow MA (Red Line). This filters out the noise of minor fluctuations (crossing the Green line) and focuses on significant momentum changes.
Settings
RSI Period: 14 (Default)
Momentum Period: 9 (Default)
Signal Logic: Crossover/Crossunder of the Slow MA (33 Period).
Disclaimer This tool is for educational purposes only. Always combine momentum signals with price action and structure analysis.
Power Law of Diminishing Returns for BTC:USDTThis is a script to see if the Law of Diminshining Returns is applicable to BTC/USD
Multi-Timeframe High Low Marking LinesThis indicator automatically draws clean horizontal lines at the high and low of the previous 10 periods (adjustable) for four different timeframes simultaneously: Daily, Weekly, Monthly, and Quarterly.
Perfect for marking key support/resistance levels across multiple timeframes on any chart.
Key features:
• Shows previous 10 highs and lows per timeframe (change to 5, 15, 20 etc. in settings)
• Lines extend 20 bars to the right so they remain visible (adjustable)
• Individual on/off switch for each timeframe
• Clean blue lines, max 500 lines limit respected
• Works perfectly on any chart timeframe (1-minute to monthly)
• No repainting – lines only appear after the period has closed
Use cases:
Spot major daily/weekly/monthly support & resistance at a glance
Trade breakouts and reversals with higher-timeframe confirmation
Combine with your existing strategy (ICT, SMC, price action)
Ideal for stocks, forex, crypto and futures
Settings explained:
Timeframe 1–4 → Choose any timeframe (D, W, M, 3M already preset)
Show/Hide → Turn any timeframe on or off instantly
Periods to show → How many previous highs/lows you want visible
Extend lines → How far right each line continues (default 20 bars)
Completely free to use.
If you like it, please add to favorites and leave a comment – it helps other traders find it!
Enjoy cleaner charts and stronger confluence.
Happy trading!
Seasonality Table: % Move by Day x Month (Open vs Prev Close)Short description
A compact seasonality heatmap that shows the average daily open vs previous session close move for each calendar day (1–31) across months (Jan–Dec).
What it does
This indicator builds a Day × Month table where each cell displays the historical average of:
(Open/Close-1) -1 x 100
In other words: how the market typically “opened” relative to the prior day’s close, grouped by day of month and month.
How to read it
Rows = Day of month (1–31)
Columns = Months (Jan–Dec)
Cell value = average percentage move (signed format like +0.23% or -0.33%)
Heatmap = stronger color intensity indicates larger absolute average moves
Today highlight = the current calendar day cell is visually highlighted for fast context
Key settings
Reference timeframe (Daily): uses daily session data as the source of truth
Decimals / Signed formatting: control numeric display
Theme controls: fully customizable colors for positive/negative/neutral cells, headers, labels, and text
Font sizes: independently adjust header/labels/values
Heatmap scaling: set “max abs (%)” to match the volatility of the instrument
Notes / limitations
The indicator depends on the historical data available on TradingView for the selected
symbol and timeframe.
This is a statistical visualization tool. It does not predict future returns and does not generate trade signals.
Disclaimer
This script is for educational and informational purposes only and is not financial advice. Trading involves risk. Always do your own research and use proper risk management.
ADX&DIThis is an enhanced version of the classic ADX and Directional Movement Index (DMI). It is designed to filter out ranging markets and visually highlight trend strength.
Key Features:
Dual Threshold System:
Level 1 (Default 20): Signals the start of a trend. The background fill appears with high transparency.
Level 2 (Default 25): Signals a strong trend. The background fill becomes more opaque/solid to indicate momentum.
Visual Clarity: The area between DI+ and DI- is only filled when the ADX is above your defined thresholds. This helps you ignore noise in low-volatility environments.
Clean Settings: The logic is optimized so you can easily adjust colors and transparency directly in the "Style" tab without cluttered input menus.
Triple Supertrend + EMA CrossoverCustomized 3 supertrend and EMA crossover which is helpful for identification of the trend.
A program written by a beginner# TXF Choppy Market Detector (Whipsaw Filter)
## Introduction
This project is a technical indicator developed in **Pine Script v5**, specifically optimized for **Taiwan Index Futures (TXF)** intraday trading.
The TXF market is known for its frequent periods of low-volatility consolidation following sharp moves, often resulting in "whipsaws" (double-loss scenarios for trend followers). This script utilizes **volatility analysis** and **trend efficiency metrics** to filter out noise and detect potential "Stop Hunting" or "Liquidity Sweep" setups within range-bound markets.
## Methodology & Algorithms
The strategy operates on the principle of **Mean Reversion**, combining two core components:
### 1. Market Regime Filter: Choppiness Index (CHOP)
We use the Choppiness Index (originally developed by E.W. Dreiss) to determine if the market is trending or consolidating based on **Fractal Dimension** theory.
* **Logic**:
The index ranges from 0 to 100. Higher values indicate low trend efficiency (consolidation), while lower values indicate strong directional trends.
* **Condition**: `CHOP > Threshold` (Default: 50).
* **Application**: When this condition is met, the background turns **gray**, signaling a "No-Trade Zone" for trend strategies and activating the Mean Reversion logic.
### 2. Whipsaw Detection: Bollinger Bands
Bollinger Bands are used to define the dynamic statistical extremities of price action.
* **Logic**:
We identify **Fakeouts** (False Breakouts) that occur specifically during the choppy regime identified above. This is often where institutional traders hunt for liquidity (stops) before reversing the price.
#### Signal Algorithms (Pseudocode)
**A. Bull Trap (Washout High)**
A false upside breakout designed to trap long traders.
```pine
Condition:
1. Is_Choppy == true (Market is sideways)
2. High > Upper_Bollinger_Band (Price pierces the upper band)
3. Close < Upper_Bollinger_Band (Price fails to hold and closes back inside)
