CD_Average Daily Range Zones- highs and lows of the dayUses daily average ranges of 5 and 10 (most used) as buy (support) and highs (resistance) areas - half ranges used in calculations for a more accurate "forecast" of the H and L . Uses open but not close, so it does not repaint - experimental
Cari dalam skrip untuk "low"
Hi-Lo WorldThis script plots the highs/lows from multiple timeframes onto the same chart to help you spot the prevailing long-term, medium-term and short-term trends .
List of timeframes included:
Year
Month
Week
Day
4 Hour
Hour
You can select which timeframes to plot by editing the inputs on the Format Object dialog.
_CM_High_Low_Open_Close_Weekly-IntradayUpdated Indicator - Plots High, Low Open, Close
For Weekly, Daily, 4 Hour, 2 Hour, 1 Hour Current and Previous Sessions Levels.
Updated Adds 4 Hour, 2 Hour, 1 Hour levels for Forex and Intra-Day Traders.
FNGAdataLow“Low prices for FNGA ETF (Dec 2018–May 2025)
The Low prices for FNGA ETF (December 2018 – May 2025) capture the lowest trading price reached during each regular U.S. market session over the entire lifespan of this leveraged exchange-traded note. Initially launched under the ticker FNGU, and later rebranded as FNGA in March 2025 before its eventual redemption, the fund was structured to deliver 3x daily leveraged exposure to the MicroSectors FANG+™ Index. This index concentrated on a small basket of leading technology and tech-enabled growth companies such as Meta (Facebook), Amazon, Apple, Netflix, and Alphabet (Google), along with a few other innovators.
The Low price is particularly important in the study of FNGA because it highlights the intraday downside extremes of a highly volatile, leveraged product. Since FNGA was designed to reset leverage daily, its lows often reflected moments of amplified market stress, when declines in the underlying FANG+™ stocks were multiplied through the 3x leverage structure.
Low volatility Buy w/ TP & SL (Coinrule)The compression of volatility usually leads to expansion. When the breakout comes, it can ignite strong trends. One way to catch a coin trading in an accumulation area is to spot three moving averages with values close to each other. The strategy uses a combination of Moving Averages to spot the best time to buy a coin before its breakout.
Buy Condition
The MA200 is greater than the MA100
The MA50 is greater than the MA100
According to backtesting results, the 1-hour time frame is the best to run this strategy.
Sell Condition
Take Profit: the price increases 8% from the entry price
Stop Loss: the price drops 4% from the entry price
The strategy has a profitability of 40-60% (depending on the market conditions). Having a ratio of two between Take profit and Stop Loss helps keeping the strategy profitable in the long term.
Morning ORB FVG Trigger✅ Overview
Morning ORB FVG Trigger is a complete intraday trading framework built around:
A Morning Opening Range Breakout (ORB)
The first Fair Value Gap (FVG) after that breakout
Strict risk management and position sizing
Optional HTF trend filter (Daily / Weekly / Monthly)
Optional Daily ATR filter to avoid extreme days
The script is designed for futures / indices / FX on intraday charts up to 15 minutes and for traders who want a clean, mechanical entry framework with clear risk.
🧠 Core idea
Define a morning opening range (e.g. 09:30–09:45).
Wait for a clean breakout above/below that range.
After the breakout, wait for the first FVG in breakout direction,
confirmed by the next candle (no immediate full reclaim).
Use a chosen stop logic + R:R factor to build risk/reward boxes.
Calculate position size based on your account risk.
(Optional) Only take trades:
In the direction of the HTF EMA trend (D/W/M).
On days where the morning range is within a band of the Daily ATR.
You can also disable all signals/boxes and use the script just as a visual ORB tool.
⏰ 1. ORB / Morning Range
Inputs (Main section)
Morning Range Session
Time window of the opening range in exchange time
Example: 09:30–09:45 for a 15-minute ORB.
You can type custom ranges (e.g. 09:30–09:35 for a 5-minute ORB).
Risk/Reward (TP factor)
Multiplier for the take-profit distance relative to the stop.
2.0 = TP is 2× the stop distance
1.5 = TP is 1.5× the stop distance
Show ORB range
If enabled, draws:
ORB high/low lines
ORB labels (e.g. 15min ORB high / low)
Optional midline
Extend ORB lines to the right (bars)
How many bars to extend the ORB high/low horizontally beyond the ORB itself.
Trade box width (bars)
Horizontal width (in bars) of:
Red risk box (entry–stop)
Green reward box (entry–TP)
Implementation details
The ORB is always calculated on 1-minute data internally, so it stays precise even on 5m/15m charts.
The script only works on intraday timeframes up to 15 minutes.
📦 2. FVG Block
Group: “FVG”
Threshold %
Minimum size of an FVG in % of price.
0 = every FVG
Higher values = only larger gaps
Auto threshold (from volatility)
If enabled, the minimum FVG size is derived from historical volatility
instead of a fixed percentage.
Allow breakout FVG partly inside ORB
Off (default): the FVG must lie fully outside the ORB.
On: the breakout FVG itself may still overlap the ORB a bit,
as long as it is the first one attached to the breakout move.
Enable FVG entry signals, boxes & alerts
On: full system – FVG detection, entry labels, risk/TP boxes, alerts.
Off: no entries, no risk/TP boxes, no alerts.
You only get the ORB and (optionally) the HTF dashboard, so you can trade your own setups.
Entry mode
Entry mode (Mid / Edge / NextOpen)
Mid – Entry at the midpoint of the FVG.
Edge – Long at the upper FVG edge, short at the lower FVG edge.
NextOpen – No limit order in the gap. Entry is placed at the next bar open after FVG confirmation.
Edge offset (ticks)
Additional offset for Edge entries:
Long:
+ticks = a bit above the FVG (more conservative)
-ticks = deeper into the FVG (more aggressive)
Short:
+ticks = a bit below the FVG
-ticks = deeper into the FVG
FVG detection logic
Uses a LuxAlgo-style 3-candle FVG pattern (gap between candle 1 and 3).
Only one FVG is taken: the first valid FVG after the ORB breakout in breakup direction.
The FVG candle is the middle bar; the script:
Detects the FVG on the previous bar.
Waits for the current bar to confirm it:
Bullish: current low must stay above the lower FVG boundary
Bearish: current high must stay below the upper FVG boundary
Only then an entry signal is generated.
🛑 3. Stop Logic
Group: “Stop Logic”
Stop mode (PrevBar / Pivot / FVG Candle)
PrevBar – Stop at the low/high of the candle before the FVG
(tight/aggressive).
FVG Candle – Stop at the low/high of the FVG candle itself
(medium).
Pivot – Stop at the most recent swing high/low
using pivotLeft / pivotRight pivots (more conservative).
Ticks (stop buffer)
Offset (in ticks) from the selected stop level.
> 0 = further away (more room, more risk)
< 0 = closer (tighter stop)
Pivot left / Pivot right
Number of candles left/right to define a swing high/low
when using Pivot stop mode.
Typical intraday values: 2–3.
The script also sanity-checks the stop:
if the calculated stop would be invalid (e.g. above entry in a long), it moves it by a minimal distance (2 ticks) to keep a valid risk.
📈 4. HTF Trend Filter (Daily / Weekly / Monthly)
Group: “HTF Trend Filter”
Enable HTF trend filter
If enabled, trades are only allowed:
Long when at least 2 of D/W/M closes are above their EMA
Short when at least 2 of D/W/M closes are below their EMA
EMA length (D/W/M)
EMA length for all three higher timeframes (Daily, Weekly, Monthly).
This helps focus entries in the direction of the dominant higher-timeframe trend.
📊 5. ATR Filter (Daily)
Group: “ATR Filter (Daily)”
Use daily ATR filter
If enabled, the height of the ORB (ORB high – ORB low) must be within
a band of the Daily ATR to allow any signals.
Daily ATR length
ATR period on the Daily timeframe.
Min ORB size vs ATR
Lower bound:
Example: 0.3 → ORB must be at least 0.3 × Daily ATR
0.0 = no minimum.
Max ORB size vs ATR
Upper bound:
Example: 1.5 → ORB must be ≤ 1.5 × Daily ATR
0.0 = no maximum.
If the ORB is too small (choppy) or too large (exhausted move), no breakout or FVG signal will be generated on that day.
🧭 6. HTF Dashboard & Signal Labels
Group: “HTF Trend Dashboard”
Show HTF dashboard
Draws a small label at the top of the chart showing:
HTF Trend (EMA X)
D: UP/FLAT/DOWN
W: UP/FLAT/DOWN
M: UP/FLAT/DOWN
Dashboard position
Top Right, Top Center, Top Left – places the dashboard at the top.
Over Risk Info – no top dashboard; instead, the HTF trend info is shown as a label near the risk box when a new signal appears.
Lookback (bars) for top anchor
How many bars to use to determine the top price level for dashboard placement.
Show HTF trend above risk box on signal
Only relevant if Dashboard position = Over Risk Info.
When enabled, a small HTF label appears near the risk box for each new trade.
Signal label vertical offset (ticks)
Vertical spacing between risk info label and HTF label.
Minimum spacing HTF/Risk (ticks)
Ensures a minimum vertical distance so the two labels don’t overlap.
HTF signal label X offset (bars)
Horizontal offset (left/right) relative to the risk info label.
⏳ 7. ORB–FVG Filters (Session & Time Window)
Group: “ORB FVG Filter”
Only same session day
If enabled, FVG entries are only allowed on the same calendar day
as the ORB. When the date changes, all state & drawings are reset.
Limit hours after ORB
Enables a time window after the ORB end.
Trading window after ORB (hours)
Length of that window in hours.
Example: 2.0 → FVG signals only in the first 2 hours after ORB end.
💰 8. Risk Management & Position Sizing
Group: “Risk Management”
Calculate position size
If enabled, the script computes suggested mini and micro contract size for you.
Account size
Your trading account size (in account currency).
Risk mode
Percent – risk is a % of account size (Account risk %).
Fixed amount – risk is a fixed dollar amount (Fixed risk ($)).
Account risk %
Risk per trade as a percentage of account size (e.g. 1.0 for 1%).
Fixed risk ($)
Fixed risk per trade in dollars when using Fixed amount mode.
Micro factor (vs mini)
How much a micro contract is worth relative to a mini.
Example:
0.1 → one micro moves 1/10 of one mini.
Risk Info label
For each new trade, a label is shown above the boxes with:
Stop distance in price and $ risk per mini
Max risk allowed for the trade
Suggested mini and micro size
Text like:
Suggested: 2 mini
Suggested: 5 micro
or Suggested: no trade
This makes the script especially useful for prop-firm rules or strict risk discipline.
🎨 9. Visual Style (Boxes, Labels, ORB Lines)
Group: “Box & Label Style (Trade)”
Label font size (Very small, Small, Normal, Large)
Entry label BG / text color
Stop label BG / text color
TP label BG / text color
Risk info BG / text color
Risk box color (entry–stop zone)
Reward box color (entry–TP zone)
Group: “ORB Style”
ORB high line color
ORB low line color
ORB line width
ORB label font size
ORB label background color
ORB label text color
Show ORB midline
ORB midline color / width / style (Solid / Dashed / Dotted)
⚠️ 10. Alerts
Group: “Alerts”
The script defines three alert conditions:
Long entry FVG breakout
Triggered when a new long signal appears.
Short entry FVG breakout
Triggered when a new short signal appears.
FVG entry (long/short)
Generic alert for any new signal (long or short).
To use them:
Add the indicator to the chart.
Open the Alerts dialog → “Condition”.
Select this script and one of the alert conditions.
Set your preferred expiration and notification settings.
Alerts only fire when Enable FVG entry signals, boxes & alerts is on.
🧩 11. How the trading logic flows (summary)
Build ORB on 1-minute data during the selected session.
Optionally reject the day if ORB is outside the ATR bounds.
Wait for a breakout (close above high or below low), respecting HTF trend filter.
After breakout, look for the first valid FVG in that direction:
Outside the ORB (unless breakout FVG allowed inside)
Confirmed by the next candle (no full reclaim)
Once confirmed:
Compute entry, stop, target.
Draw risk/reward boxes and all labels.
Optionally show HTF signal label over the risk info.
Trigger alerts if enabled.
If you disable FVG signals, only steps 1–3 (plus dashboard) are effectively active.
⚠️ 12. Notes & Disclaimer
Script is intended for intraday trading up to 15-minute timeframes.
All signals are mechanical and do not guarantee profitability.
Always backtest and forward-test on your own data before risking real money.
This script is for educational purposes only and is not financial advice.
🚀 Quick-start guide
Add the script to your chart
Use an intraday timeframe ≤ 15 minutes (1m, 3m, 5m, 15m).
Works best on liquid indices, futures, FX and large-cap stocks.
Set the Morning Range
In “Morning Range Session” choose the exchange’s opening window.
Examples
US index futures (CME): 08:30–08:45 or 08:30–08:35
US stocks (NYSE/Nasdaq): 09:30–09:45 or 09:30–09:35
The ORB is always calculated on 1-minute data internally, so the range stays accurate on higher intraday charts.
Keep the default filters at first
HTF Trend Filter: ON
EMA length = 20
This will only allow trades in the direction of the dominant D/W/M trend.
ATR Filter: OFF (optional; you can enable later once you’re comfortable).
Use the full trade system
In the FVG group leave
“Enable FVG entry signals, boxes & alerts” = ON
Entry mode: Mid
Stop mode: FVG Candle or PrevBar
Risk/Reward: 2.0 as a starting point.
Set your risk
Turn on “Calculate position size”.
Enter your Account size and choose either:
Risk mode = Percent (e.g. 1.0 = 1% per trade), or
Risk mode = Fixed amount (e.g. $250 per trade).
The risk info label will show:
Stop distance in price and $/contract
Max allowed risk
Suggested mini and micro contract size.
Enable alerts (optional)
Open the Alerts dialog → Condition: this script.
Choose one of:
Long entry FVG breakout
Short entry FVG breakout
FVG entry (long/short)
Choose “Once per bar” or “Once per bar close”, and your preferred notification type.
Replay & journal
Use the TradingView bar replay tool to step through past days.
Focus on:
How the ORB defines the structure.
How the first confirmed FVG outside the ORB behaves.
Whether the risk/TP levels fit your own style and product.
🎛 Recommended settings & profiles
These are starting points, not rules. Always adapt to the instrument and your own risk tolerance.
1. Conservative / Trend-following
Timeframe: 5m or 15m
Morning Range Session: 15-minute ORB around the cash or futures open
FVG
Threshold %: 0.05–0.1 (filter out very small gaps)
Auto threshold: OFF (keep it simple)
Allow breakout FVG partly inside ORB: OFF
Enable FVG entry signals/boxes/alerts: ON
Entry mode: Mid
Stop Logic
Stop mode: Pivot
Pivot left/right: 2–3
Stop buffer: +1–2 ticks
HTF Trend Filter
Enabled: ON
EMA length: 20
ATR Filter
Enabled: ON
Daily ATR length: 14
Min ORB vs ATR: 0.3–0.4
Max ORB vs ATR: 1.2–1.5
Risk Management
Risk mode: Percent
Account risk: 0.5–1.0%
Idea: Only trade when the higher-timeframe trend supports the move and the opening range is of a “normal” size for the current volatility.
2. Balanced / Intraday directional
Timeframe: 3m or 5m
FVG
Threshold %: 0.02–0.05
Auto threshold: ON (lets the script adapt to volatility)
Allow breakout FVG partly inside ORB: ON
(first breakout FVG may partly sit inside the ORB)
Entry mode: Edge
Edge offset (ticks): 0 or +1
Stop Logic
Stop mode: FVG Candle
Stop buffer: 0–1 ticks
HTF Trend Filter
Enabled: ON
ATR Filter
Enabled: OFF (optional)
Risk Management
Risk mode: Percent
Account risk: 1.0–1.5% (if this fits your plan)
Idea: Slightly more aggressive entries at the gap edge, still aligned with HTF trend, but with more flexibility on ATR.
3. Aggressive / Scalping around the ORB
Timeframe: 1m or 3m
FVG
Threshold %: 0.0–0.02
Auto threshold: ON
Allow breakout FVG partly inside ORB: ON
Entry mode: NextOpen or Edge with a negative offset (deeper into the gap)
Stop Logic
Stop mode: PrevBar
Stop buffer: 0 or -1 tick
HTF Trend Filter
Enabled: OFF (or ON but treat as soft guidance)
ATR Filter
Enabled: OFF
Risk Management
Risk mode: Percent
Account risk: lower, e.g. 0.25–0.5% per trade
Idea: More trades and tighter stops. Best for experienced traders who understand the limitations of scalping and whipsaw risk.
Final reminder
All of these are templates, not guarantees:
Always check how the system behaves on your market and session.
Start on replay and demo before trading real money.
Adjust filters (HTF, ATR, thresholds) until the signals fit your personal approach.
Minervini VCP Pattern -Indian ContextThis script implements Mark Minervini's Trend Template and VCP (Volatility Contraction Pattern) pattern, specifically adapted for Indian stock markets (NSE). It helps identify stocks that are in strong uptrends and ready to break out.
Core Concepts Explained
1. What is the Minervini Trend Template?
Mark Minervini's method identifies stocks in Stage 2 uptrends - the sweet spot where institutional money is accumulating and stocks show the strongest momentum. Think of it as finding stocks that are "leaders" rather than "laggards."
2. What is VCP (Volatility Contraction Pattern)?
A VCP occurs when:
Stock price consolidates (moves sideways) after an uptrend
Price swings get tighter and tighter (like a coiled spring)
Volume dries up (fewer people trading)
Then it breaks out with force.
You can customize the strategy settings without editing code.
Key Settings:
Minimum Price (₹50): Filters out penny stocks that are too volatile
Min Distance from 52W Low (30%): Stock should be at least 30% above its yearly low
Max Distance from 52W High (25%): Stock should be within 25% of its yearly high (showing strength)
Moving Average Periods: 10, 50, 150, 200 days (industry standard)
Minimum Volume (100,000 shares): Ensures the stock is liquid enough to trade
Indian Market Adaptation: The default values (₹50 minimum, volume thresholds) are adjusted for NSE stocks, which behave differently than US markets.
The script pulls weekly chart data even when you're viewing daily charts.
Why it matters: Weekly trends are more reliable than daily noise. Professional traders use weekly charts to confirm the bigger picture.
What are Moving Averages (MAs)?
Simple averages of closing prices over X days
They smooth out price action to show trends
Think of them as the "average cost" of buyers over different time periods
The 4 Key MAs:
10 MA (Fast): Very short-term trend
50 MA: Short to medium-term trend
150 MA: Medium to long-term trend
200 MA: Long-term trend (the "grandfather" of all MAs)
Why Weekly MAs?
The script also calculates 10 and 50 MAs on weekly data for additional confirmation of the bigger trend.
The script Finds the highest and lowest prices over the past 52 weeks (1 year).
Why it matters:
Stocks near 52-week highs are showing strength (institutions buying)
Stocks far from 52-week lows have "room to run" upward
This is a psychological level that influences trader behaviour.
What is Volume here ?
The number of shares traded each day
High volume = many traders interested (conviction)
Low volume = lack of interest (weakness or consolidation)
Volume in VCP:
During consolidation (sideways movement), volume should dry up - this shows sellers are exhausted and buyers are holding. When volume spikes on a breakout, it confirms the move.
NSE Context: Indian stocks often have different volume patterns than US stocks, so the 50-day average is used as a baseline.
Relative Strength vs Nifty:
Example:
If your stock is up 20% and Nifty is up 10%, your stock has strong RS
If your stock is up 5% and Nifty is up 15%, your stock has weak RS (avoid it!)
Why it matters: The best performing stocks almost always have strong relative strength before major moves.
The 13 Minervini Conditions:-
Condition 1: Price > 50/150/200 MA
Meaning: Current price must be above ALL three major moving averages.
Why: This confirms the stock is in a clear uptrend. If price is below these MAs, the stock is weak or in a downtrend.
Condition 2: MA 50 > 150 > 200
Meaning: The moving averages themselves must be in proper order.
Analogy: Think of this like layers in a cake - short-term on top, long-term at bottom. If they're tangled, the trend is unclear.
Condition 3: 200 MA Rising (1 Month)
Meaning: The 200 MA today must be higher than it was 20 days ago.
Why: This confirms the long-term trend is UP, not flat or down. The means "20 bars ago."
Condition 4: 50 MA Rising
Meaning: The 50 MA today must be higher than 5 days ago.
Why: Confirms short-term momentum is accelerating upward.
Condition 5: Within 25% of 52-Week High
Meaning: Current price should be within 25% of its 1-year high.
Example:
52-week high = ₹1000
Current price must be above ₹750 (within 25%)
Why: Strong stocks stay near their highs. Weak stocks fall far from highs.
Condition 6: 30%+ Above 52-Week Low (OPTIONAL)
Meaning: Stock should be at least 30% above its yearly low.
Note: The script marks this as "SECONDARY - Optional" because the other conditions are more important. However, it's still a good confirmation.
Condition 7: Price > 10 MA
Meaning: Very short-term strength - price above the 10-day moving average.
Why: Ensures the stock hasn't just rolled over in the immediate term.
Condition 8: Price >= ₹50
Meaning: Filters out stocks below ₹50.
Why: In Indian markets, stocks below ₹50 tend to be penny stocks with poor liquidity and higher manipulation risk.
Condition 9: Weekly Uptrend
Meaning: On the weekly chart, price must be above both weekly MAs, and they must be properly aligned.
Why: Confirms the bigger picture trend, not just daily fluctuations.
Condition 10: 150 MA Rising
Meaning: The 150 MA is trending upward over the past 10 days.
Why: Another confirmation of medium-term trend health.
Condition 11: Sufficient Volume
Meaning: Average volume must exceed 100,000 shares (or your custom setting).
Why: Ensures you can actually buy/sell the stock without moving the price too much (liquidity).
Condition 12: RS vs Nifty Strong
Meaning: The stock's relative strength vs Nifty must be improving.
Why: You want stocks that are outperforming the market, not underperforming.
Condition 13: Nifty in Uptrend
Meaning: The Nifty 50 index itself must be above its 50 MA.
Why: "A rising tide lifts all boats." It's easier to make money in individual stocks when the overall market is bullish.
VCP Requirements:
Volatility Contracting: Price swings getting tighter (coiling spring)
Volume Drying Up: Fewer shares trading + trending lower
The Setup: When volatility contracts and volume dries up WHILE all 13 trend conditions are met, you have a VCP setup ready to explode.
What You See on Chart:
Colored Lines: 10 MA (green), 50 MA (blue), 150 MA (orange), 200 MA (red)
Blue Background: Trend template conditions met (watch zone)
Green Background: Full VCP setup detected (buy zone)
↟ Symbol Below Price: New VCP buy signal just triggered
Information Table:
What it does: Creates a checklist table on your chart showing the status of all conditions.
Table Structure:
Column 1: Condition name
Column 2: Status (✓ green = met, ✗ red = not met)
Final Row: Shows "BUY" (green) or "WAIT" (red) based on full VCP setup status.
Dos:
Example:
Account size: ₹5,00,000
Risk per trade: 1% = ₹5,000
Entry: ₹1000
Stop loss: ₹920 (8% below)
Distance to stop: ₹80
Shares to buy: ₹5,000 / ₹80 = 62 shares
Exit Strategy:
Sell 1/3 at +20% profit
Sell another 1/3 at +40% profit
Let the final 1/3 run with a trailing stop
Always exit if price closes below 10 MA on heavy volume
What This Script Does NOT Do:
Guarantee profits - No strategy works 100% of the time
Account for news events - Earnings, regulatory changes, etc.
Consider fundamentals - Company financials, debt, management quality
Adapt to market crashes - Works best in bull markets
Best Market Conditions:
✅ Nifty in uptrend (above 50 MA)
✅ Market breadth positive (more stocks advancing)
✅ Sector rotation happening
❌ Avoid in bear markets or high volatility periods
References:
Trade Like a Stock Market Wizard by Mark Minervini
Think & Trade Like a Champion by Mark Minervini
Chart attached: AU Small Finance Bank as on EoD dated 28/11/25
This script is a powerful tool for educational purpose only, remember: It's a tool, not a crystal ball. Use it to find high-probability setups, then apply proper risk management and patience. Good luck!
Highlight 6-7 PM (IST) candle + mark H/L (Hourly)📌 Highlight 6–7 PM Candle (IST) + High/Low Lines (No Labels)
This indicator automatically detects the 6:00–7:00 PM candle (IST) on the hourly timeframe and visually marks it on the chart.
It highlights the candle and draws horizontal High and Low levels without any labels—making the chart clean and easy to read.
✅ Features
Highlights the 6–7 PM hourly candle (timezone adjustable: IST/UTC/Exchange).
Draws high & low horizontal lines from the target candle.
Option to extend the lines for a selected number of bars.
Optional restriction to only show on 1-hour timeframe.
Clean design — no labels, no clutter.
🛠️ Inputs
Timezone (default: Asia/Kolkata)
Target Hour (default: 18 = 6 PM)
Highlight Color
High/Low Line Colors
Line Extension Length
Enable/Disable Hourly-only Mode
🎯 Use Case
Useful for traders who track post-market candles, volatility behavior, range levels, or want to build intraday strategies based on evening session highs/lows.
2-Close + Bar 5 Reversal (Scan Ready)Bulkowski's Bullish 2-Step Reversal
Bar 1 Any price bar.
Bar 2 Price makes a low below bar 1 with a lower close, too.
Bar 3 Price has a low below bar 2 but a close above bar 1 (which will also be above bar 2's close). Bars 1 to 3 form a 2-close reversal pattern.
Bar 4 Makes a close below bar 3's close.
Bar 5 Has a low below bar 4 but closes above bars 3 and 4.
Breakout Breaks out upward 79% of the time in stocks.
From his page: thepatternsite.com
Grok/Claude Turtle Trend Pro Strategy Turtle Trend Pro Strategy: A Modern Implementation of the Legendary Turtle Trading System
Historical Background: The Original Turtle Experiment
In 1983, legendary commodities trader Richard Dennis made a bet with his partner William Eckhardt: could successful trading be taught, or was it an innate skill? To settle the debate, Dennis recruited and trained a group of novices—whom he called "Turtles" (inspired by turtle farms he'd visited in Singapore)—teaching them a complete mechanical trading system. The results were remarkable: over the next four years, the Turtles reportedly earned over $175 million, proving that systematic, rule-based trading could be taught and replicated.
The strategy you've shared is a faithful modern adaptation of those original Turtle rules, enhanced with contemporary technical filters.
Core Turtle Principles Preserved in This Strategy
1. Donchian Channel Breakouts (The Heart of Turtle Trading)
The original Turtles used Donchian Channels—a simple concept where you track the highest high and lowest low over a specific lookback period. This strategy implements both original Turtle systems:
System 1 (Default): 20-period entry breakout, 15-period exit
System 2 (Optional): 55-period entry breakout, 20-period exit
The logic is elegantly simple:
Go long when price breaks above the highest high of the last 20 (or 55) periods
Go short when price breaks below the lowest low of the last 20 (or 55) periods
This captures the Turtle philosophy of trend-following through momentum breakouts—the idea that markets trending strongly in one direction tend to continue.
2. ATR-Based Position Sizing and Stops
The Turtles were pioneers in using Average True Range (ATR) for risk management. This strategy preserves that approach:
Stop Loss: Set at 2× ATR from entry (the original Turtle rule)
ATR Period : 20 days (matching the original)
The ATR stop adapts to market volatility—wider stops in volatile markets, tighter stops in calm ones—preventing premature exits while still protecting capital.
3. Opposite Channel Exit
Rather than using arbitrary profit targets, the Turtles exited positions when price broke the opposite channel:
Exit longs when price breaks below the 15-period (or 20-period) low
Exit shorts when price breaks above the 15-period (or 20-period) high
This allows winning trades to run while providing a systematic exit that doesn't rely on prediction.
Modern Enhancements Beyond the Original System
While the core mechanics remain true to 1983, this strategy adds sophisticated filters the original Turtles didn't have access to:
Trend Filter (200 EMA)
Only takes long trades when price is above the 200-period moving average (and the MA is sloping up), and vice versa for shorts. This aligns trades with the major trend, reducing whipsaws in choppy markets. Set of off by default and fully adjustable in settings.
ADX Filter (Trend Strength)
The Average Directional Index ensures trades are only taken when the market is actually trending (ADX > 20 threshold). The original Turtles suffered significant drawdowns in ranging markets—this filter addresses that weakness.
Optional RSI Filter
Adds overbought/oversold confirmation to entries, though this is disabled by default to stay closer to the original system.
Volume Confirmation
Optional requirement for volume surges on breakouts, adding conviction to signals.
The Strategy's Risk Management Framework
Parameter Setting Turtle Origin Position Size 10% of equity. Turtles used volatility-adjusted sizing.
Stop Loss2× ATR.
Original Turtle rule Commission 0.075%. Modern crypto exchange rate.
Pyramiding Disabled.
Turtles did pyramid, but simplified here.
Visual Elements and Regime Detection
The strategy includes a "Neural Fusion Pro" styled display that would make the original Turtles jealous:
Color-coded Donchian Channels: Green (bullish), Red (bearish), Yellow (neutral)
Trend Strength Meter: Combines ADX, price vs. MA distance, channel position, and DI spread
Regime Classification : Automatically identifies Bull, Bear, or Neutral market conditions
Information Panel: Real-time display of all key metrics
Why Turtle Trading Still Works
The genius of the Turtle system lies in its mechanical discipline. It removes emotion from trading by providing explicit rules for:
What to trade (anything with sufficient liquidity and volatility)
When to enter (channel breakouts)
How much to trade (volatility-adjusted position sizing)
When to exit (opposite breakout or ATR stop)
This strategy faithfully preserves that mechanical approach while adding modern filters to improve the win rate in today's markets.
PubLibCandleTrendLibrary "PubLibCandleTrend"
candle trend, multi-part candle trend, multi-part green/red candle trend, double candle trend and multi-part double candle trend conditions for indicator and strategy development
chh()
candle higher high condition
Returns: bool
chl()
candle higher low condition
Returns: bool
clh()
candle lower high condition
Returns: bool
cll()
candle lower low condition
Returns: bool
cdt()
candle double top condition
Returns: bool
cdb()
candle double bottom condition
Returns: bool
gc()
green candle condition
Returns: bool
gchh()
green candle higher high condition
Returns: bool
gchl()
green candle higher low condition
Returns: bool
gclh()
green candle lower high condition
Returns: bool
gcll()
green candle lower low condition
Returns: bool
gcdt()
green candle double top condition
Returns: bool
gcdb()
green candle double bottom condition
Returns: bool
rc()
red candle condition
Returns: bool
rchh()
red candle higher high condition
Returns: bool
rchl()
red candle higher low condition
Returns: bool
rclh()
red candle lower high condition
Returns: bool
rcll()
red candle lower low condition
Returns: bool
rcdt()
red candle double top condition
Returns: bool
rcdb()
red candle double bottom condition
Returns: bool
chh_1p()
1-part candle higher high condition
Returns: bool
chh_2p()
2-part candle higher high condition
Returns: bool
chh_3p()
3-part candle higher high condition
Returns: bool
chh_4p()
4-part candle higher high condition
Returns: bool
chh_5p()
5-part candle higher high condition
Returns: bool
chh_6p()
6-part candle higher high condition
Returns: bool
chh_7p()
7-part candle higher high condition
Returns: bool
chh_8p()
8-part candle higher high condition
Returns: bool
chh_9p()
9-part candle higher high condition
Returns: bool
chh_10p()
10-part candle higher high condition
Returns: bool
chh_11p()
11-part candle higher high condition
Returns: bool
chh_12p()
12-part candle higher high condition
Returns: bool
chh_13p()
13-part candle higher high condition
Returns: bool
chh_14p()
14-part candle higher high condition
Returns: bool
chh_15p()
15-part candle higher high condition
Returns: bool
chh_16p()
16-part candle higher high condition
Returns: bool
chh_17p()
17-part candle higher high condition
Returns: bool
chh_18p()
18-part candle higher high condition
Returns: bool
chh_19p()
19-part candle higher high condition
Returns: bool
chh_20p()
20-part candle higher high condition
Returns: bool
chh_21p()
21-part candle higher high condition
Returns: bool
chh_22p()
22-part candle higher high condition
Returns: bool
chh_23p()
23-part candle higher high condition
Returns: bool
chh_24p()
24-part candle higher high condition
Returns: bool
chh_25p()
25-part candle higher high condition
Returns: bool
chh_26p()
26-part candle higher high condition
Returns: bool
chh_27p()
27-part candle higher high condition
Returns: bool
chh_28p()
28-part candle higher high condition
Returns: bool
chh_29p()
29-part candle higher high condition
Returns: bool
chh_30p()
30-part candle higher high condition
Returns: bool
chl_1p()
1-part candle higher low condition
Returns: bool
chl_2p()
2-part candle higher low condition
Returns: bool
chl_3p()
3-part candle higher low condition
Returns: bool
chl_4p()
4-part candle higher low condition
Returns: bool
chl_5p()
5-part candle higher low condition
Returns: bool
chl_6p()
6-part candle higher low condition
Returns: bool
chl_7p()
7-part candle higher low condition
Returns: bool
chl_8p()
8-part candle higher low condition
Returns: bool
chl_9p()
9-part candle higher low condition
Returns: bool
chl_10p()
10-part candle higher low condition
Returns: bool
chl_11p()
11-part candle higher low condition
Returns: bool
chl_12p()
12-part candle higher low condition
Returns: bool
chl_13p()
13-part candle higher low condition
Returns: bool
chl_14p()
14-part candle higher low condition
Returns: bool
chl_15p()
15-part candle higher low condition
Returns: bool
chl_16p()
16-part candle higher low condition
Returns: bool
chl_17p()
17-part candle higher low condition
Returns: bool
chl_18p()
18-part candle higher low condition
Returns: bool
chl_19p()
19-part candle higher low condition
Returns: bool
chl_20p()
20-part candle higher low condition
Returns: bool
chl_21p()
21-part candle higher low condition
Returns: bool
chl_22p()
22-part candle higher low condition
Returns: bool
chl_23p()
23-part candle higher low condition
Returns: bool
chl_24p()
24-part candle higher low condition
Returns: bool
chl_25p()
25-part candle higher low condition
Returns: bool
chl_26p()
26-part candle higher low condition
Returns: bool
chl_27p()
27-part candle higher low condition
Returns: bool
chl_28p()
28-part candle higher low condition
Returns: bool
chl_29p()
29-part candle higher low condition
Returns: bool
chl_30p()
30-part candle higher low condition
Returns: bool
clh_1p()
1-part candle lower high condition
Returns: bool
clh_2p()
2-part candle lower high condition
Returns: bool
clh_3p()
3-part candle lower high condition
Returns: bool
clh_4p()
4-part candle lower high condition
Returns: bool
clh_5p()
5-part candle lower high condition
Returns: bool
clh_6p()
6-part candle lower high condition
Returns: bool
clh_7p()
7-part candle lower high condition
Returns: bool
clh_8p()
8-part candle lower high condition
Returns: bool
clh_9p()
9-part candle lower high condition
Returns: bool
clh_10p()
10-part candle lower high condition
Returns: bool
clh_11p()
11-part candle lower high condition
Returns: bool
clh_12p()
12-part candle lower high condition
Returns: bool
clh_13p()
13-part candle lower high condition
Returns: bool
clh_14p()
14-part candle lower high condition
Returns: bool
clh_15p()
15-part candle lower high condition
Returns: bool
clh_16p()
16-part candle lower high condition
Returns: bool
clh_17p()
17-part candle lower high condition
Returns: bool
clh_18p()
18-part candle lower high condition
Returns: bool
clh_19p()
19-part candle lower high condition
Returns: bool
clh_20p()
20-part candle lower high condition
Returns: bool
clh_21p()
21-part candle lower high condition
Returns: bool
clh_22p()
22-part candle lower high condition
Returns: bool
clh_23p()
23-part candle lower high condition
Returns: bool
clh_24p()
24-part candle lower high condition
Returns: bool
clh_25p()
25-part candle lower high condition
Returns: bool
clh_26p()
26-part candle lower high condition
Returns: bool
clh_27p()
27-part candle lower high condition
Returns: bool
clh_28p()
28-part candle lower high condition
Returns: bool
clh_29p()
29-part candle lower high condition
Returns: bool
clh_30p()
30-part candle lower high condition
Returns: bool
cll_1p()
1-part candle lower low condition
Returns: bool
cll_2p()
2-part candle lower low condition
Returns: bool
cll_3p()
3-part candle lower low condition
Returns: bool
cll_4p()
4-part candle lower low condition
Returns: bool
cll_5p()
5-part candle lower low condition
Returns: bool
cll_6p()
6-part candle lower low condition
Returns: bool
cll_7p()
7-part candle lower low condition
Returns: bool
cll_8p()
8-part candle lower low condition
Returns: bool
cll_9p()
9-part candle lower low condition
Returns: bool
cll_10p()
10-part candle lower low condition
Returns: bool
cll_11p()
11-part candle lower low condition
Returns: bool
cll_12p()
12-part candle lower low condition
Returns: bool
cll_13p()
13-part candle lower low condition
Returns: bool
cll_14p()
14-part candle lower low condition
Returns: bool
cll_15p()
15-part candle lower low condition
Returns: bool
cll_16p()
16-part candle lower low condition
Returns: bool
cll_17p()
17-part candle lower low condition
Returns: bool
cll_18p()
18-part candle lower low condition
Returns: bool
cll_19p()
19-part candle lower low condition
Returns: bool
cll_20p()
20-part candle lower low condition
Returns: bool
cll_21p()
21-part candle lower low condition
Returns: bool
cll_22p()
22-part candle lower low condition
Returns: bool
cll_23p()
23-part candle lower low condition
Returns: bool
cll_24p()
24-part candle lower low condition
Returns: bool
cll_25p()
25-part candle lower low condition
Returns: bool
cll_26p()
26-part candle lower low condition
Returns: bool
cll_27p()
27-part candle lower low condition
Returns: bool
cll_28p()
28-part candle lower low condition
Returns: bool
cll_29p()
29-part candle lower low condition
Returns: bool
cll_30p()
30-part candle lower low condition
Returns: bool
gc_1p()
1-part green candle condition
Returns: bool
gc_2p()
2-part green candle condition
Returns: bool
gc_3p()
3-part green candle condition
Returns: bool
gc_4p()
4-part green candle condition
Returns: bool
gc_5p()
5-part green candle condition
Returns: bool
gc_6p()
6-part green candle condition
Returns: bool
gc_7p()
7-part green candle condition
Returns: bool
gc_8p()
8-part green candle condition
Returns: bool
gc_9p()
9-part green candle condition
Returns: bool
gc_10p()
10-part green candle condition
Returns: bool
gc_11p()
11-part green candle condition
Returns: bool
gc_12p()
12-part green candle condition
Returns: bool
gc_13p()
13-part green candle condition
Returns: bool
gc_14p()
14-part green candle condition
Returns: bool
gc_15p()
15-part green candle condition
Returns: bool
gc_16p()
16-part green candle condition
Returns: bool
gc_17p()
17-part green candle condition
Returns: bool
gc_18p()
18-part green candle condition
Returns: bool
gc_19p()
19-part green candle condition
Returns: bool
gc_20p()
20-part green candle condition
Returns: bool
gc_21p()
21-part green candle condition
Returns: bool
gc_22p()
22-part green candle condition
Returns: bool
gc_23p()
23-part green candle condition
Returns: bool
gc_24p()
24-part green candle condition
Returns: bool
gc_25p()
25-part green candle condition
Returns: bool
gc_26p()
26-part green candle condition
Returns: bool
gc_27p()
27-part green candle condition
Returns: bool
gc_28p()
28-part green candle condition
Returns: bool
gc_29p()
29-part green candle condition
Returns: bool
gc_30p()
30-part green candle condition
Returns: bool
rc_1p()
1-part red candle condition
Returns: bool
rc_2p()
2-part red candle condition
Returns: bool
rc_3p()
3-part red candle condition
Returns: bool
rc_4p()
4-part red candle condition
Returns: bool
rc_5p()
5-part red candle condition
Returns: bool
rc_6p()
6-part red candle condition
Returns: bool
rc_7p()
7-part red candle condition
Returns: bool
rc_8p()
8-part red candle condition
Returns: bool
rc_9p()
9-part red candle condition
Returns: bool
rc_10p()
10-part red candle condition
Returns: bool
rc_11p()
11-part red candle condition
Returns: bool
rc_12p()
12-part red candle condition
Returns: bool
rc_13p()
13-part red candle condition
Returns: bool
rc_14p()
14-part red candle condition
Returns: bool
rc_15p()
15-part red candle condition
Returns: bool
rc_16p()
16-part red candle condition
Returns: bool
rc_17p()
17-part red candle condition
Returns: bool
rc_18p()
18-part red candle condition
Returns: bool
rc_19p()
19-part red candle condition
Returns: bool
rc_20p()
20-part red candle condition
Returns: bool
rc_21p()
21-part red candle condition
Returns: bool
rc_22p()
22-part red candle condition
Returns: bool
rc_23p()
23-part red candle condition
Returns: bool
rc_24p()
24-part red candle condition
Returns: bool
rc_25p()
25-part red candle condition
Returns: bool
rc_26p()
26-part red candle condition
Returns: bool
rc_27p()
27-part red candle condition
Returns: bool
rc_28p()
28-part red candle condition
Returns: bool
rc_29p()
29-part red candle condition
Returns: bool
rc_30p()
30-part red candle condition
Returns: bool
cdut()
candle double uptrend condition
Returns: bool
cddt()
candle double downtrend condition
Returns: bool
cdut_1p()
1-part candle double uptrend condition
Returns: bool
cdut_2p()
2-part candle double uptrend condition
Returns: bool
cdut_3p()
3-part candle double uptrend condition
Returns: bool
cdut_4p()
4-part candle double uptrend condition
Returns: bool
cdut_5p()
5-part candle double uptrend condition
Returns: bool
cdut_6p()
6-part candle double uptrend condition
Returns: bool
cdut_7p()
7-part candle double uptrend condition
Returns: bool
cdut_8p()
8-part candle double uptrend condition
Returns: bool
cdut_9p()
9-part candle double uptrend condition
Returns: bool
cdut_10p()
10-part candle double uptrend condition
Returns: bool
cdut_11p()
11-part candle double uptrend condition
Returns: bool
cdut_12p()
12-part candle double uptrend condition
Returns: bool
cdut_13p()
13-part candle double uptrend condition
Returns: bool
cdut_14p()
14-part candle double uptrend condition
Returns: bool
cdut_15p()
15-part candle double uptrend condition
Returns: bool
cdut_16p()
16-part candle double uptrend condition
Returns: bool
cdut_17p()
17-part candle double uptrend condition
Returns: bool
cdut_18p()
18-part candle double uptrend condition
Returns: bool
cdut_19p()
19-part candle double uptrend condition
Returns: bool
cdut_20p()
20-part candle double uptrend condition
Returns: bool
cdut_21p()
21-part candle double uptrend condition
Returns: bool
cdut_22p()
22-part candle double uptrend condition
Returns: bool
cdut_23p()
23-part candle double uptrend condition
Returns: bool
cdut_24p()
24-part candle double uptrend condition
Returns: bool
cdut_25p()
25-part candle double uptrend condition
Returns: bool
cdut_26p()
26-part candle double uptrend condition
Returns: bool
cdut_27p()
27-part candle double uptrend condition
Returns: bool
cdut_28p()
28-part candle double uptrend condition
Returns: bool
cdut_29p()
29-part candle double uptrend condition
Returns: bool
cdut_30p()
30-part candle double uptrend condition
Returns: bool
cddt_1p()
1-part candle double downtrend condition
Returns: bool
cddt_2p()
2-part candle double downtrend condition
Returns: bool
cddt_3p()
3-part candle double downtrend condition
Returns: bool
cddt_4p()
4-part candle double downtrend condition
Returns: bool
cddt_5p()
5-part candle double downtrend condition
Returns: bool
cddt_6p()
6-part candle double downtrend condition
Returns: bool
cddt_7p()
7-part candle double downtrend condition
Returns: bool
cddt_8p()
8-part candle double downtrend condition
Returns: bool
cddt_9p()
9-part candle double downtrend condition
Returns: bool
cddt_10p()
10-part candle double downtrend condition
Returns: bool
cddt_11p()
11-part candle double downtrend condition
Returns: bool
cddt_12p()
12-part candle double downtrend condition
Returns: bool
cddt_13p()
13-part candle double downtrend condition
Returns: bool
cddt_14p()
14-part candle double downtrend condition
Returns: bool
cddt_15p()
15-part candle double downtrend condition
Returns: bool
cddt_16p()
16-part candle double downtrend condition
Returns: bool
cddt_17p()
17-part candle double downtrend condition
Returns: bool
cddt_18p()
18-part candle double downtrend condition
Returns: bool
cddt_19p()
19-part candle double downtrend condition
Returns: bool
cddt_20p()
20-part candle double downtrend condition
Returns: bool
cddt_21p()
21-part candle double downtrend condition
Returns: bool
cddt_22p()
22-part candle double downtrend condition
Returns: bool
cddt_23p()
23-part candle double downtrend condition
Returns: bool
cddt_24p()
24-part candle double downtrend condition
Returns: bool
cddt_25p()
25-part candle double downtrend condition
Returns: bool
cddt_26p()
26-part candle double downtrend condition
Returns: bool
cddt_27p()
27-part candle double downtrend condition
Returns: bool
cddt_28p()
28-part candle double downtrend condition
Returns: bool
cddt_29p()
29-part candle double downtrend condition
Returns: bool
cddt_30p()
30-part candle double downtrend condition
Returns: bool
Naveen Prabhu with EMA//@version=6
indicator('Naveen Prabhu with EMA', overlay = true, max_labels_count = 500, max_lines_count = 500, max_boxes_count = 500)
a = input(2, title = 'Key Vaule. \'This changes the sensitivity\'')
c = input(5, title = 'ATR Period')
h = input(false, title = 'Signals from Heikin Ashi Candles')
BULLISH_LEG = 1
BEARISH_LEG = 0
BULLISH = +1
BEARISH = -1
GREEN = #089981
RED = #F23645
BLUE = #2157f3
GRAY = #878b94
MONO_BULLISH = #b2b5be
MONO_BEARISH = #5d606b
HISTORICAL = 'Historical'
PRESENT = 'Present'
COLORED = 'Colored'
MONOCHROME = 'Monochrome'
ALL = 'All'
BOS = 'BOS'
CHOCH = 'CHoCH'
TINY = size.tiny
SMALL = size.small
NORMAL = size.normal
ATR = 'Atr'
RANGE = 'Cumulative Mean Range'
CLOSE = 'Close'
HIGHLOW = 'High/Low'
SOLID = '⎯⎯⎯'
DASHED = '----'
DOTTED = '····'
SMART_GROUP = 'Smart Money Concepts'
INTERNAL_GROUP = 'Real Time Internal Structure'
SWING_GROUP = 'Real Time Swing Structure'
BLOCKS_GROUP = 'Order Blocks'
EQUAL_GROUP = 'EQH/EQL'
GAPS_GROUP = 'Fair Value Gaps'
LEVELS_GROUP = 'Highs & Lows MTF'
ZONES_GROUP = 'Premium & Discount Zones'
modeTooltip = 'Allows to display historical Structure or only the recent ones'
styleTooltip = 'Indicator color theme'
showTrendTooltip = 'Display additional candles with a color reflecting the current trend detected by structure'
showInternalsTooltip = 'Display internal market structure'
internalFilterConfluenceTooltip = 'Filter non significant internal structure breakouts'
showStructureTooltip = 'Display swing market Structure'
showSwingsTooltip = 'Display swing point as labels on the chart'
showHighLowSwingsTooltip = 'Highlight most recent strong and weak high/low points on the chart'
showInternalOrderBlocksTooltip = 'Display internal order blocks on the chart\n\nNumber of internal order blocks to display on the chart'
showSwingOrderBlocksTooltip = 'Display swing order blocks on the chart\n\nNumber of internal swing blocks to display on the chart'
orderBlockFilterTooltip = 'Method used to filter out volatile order blocks \n\nIt is recommended to use the cumulative mean range method when a low amount of data is available'
orderBlockMitigationTooltip = 'Select what values to use for order block mitigation'
showEqualHighsLowsTooltip = 'Display equal highs and equal lows on the chart'
equalHighsLowsLengthTooltip = 'Number of bars used to confirm equal highs and equal lows'
equalHighsLowsThresholdTooltip = 'Sensitivity threshold in a range (0, 1) used for the detection of equal highs & lows\n\nLower values will return fewer but more pertinent results'
showFairValueGapsTooltip = 'Display fair values gaps on the chart'
fairValueGapsThresholdTooltip = 'Filter out non significant fair value gaps'
fairValueGapsTimeframeTooltip = 'Fair value gaps timeframe'
fairValueGapsExtendTooltip = 'Determine how many bars to extend the Fair Value Gap boxes on chart'
showPremiumDiscountZonesTooltip = 'Display premium, discount, and equilibrium zones on chart'
modeInput = input.string( HISTORICAL, 'Mode', group = SMART_GROUP, tooltip = modeTooltip, options = )
styleInput = input.string( COLORED, 'Style', group = SMART_GROUP, tooltip = styleTooltip,options = )
showTrendInput = input( false, 'Color Candles', group = SMART_GROUP, tooltip = showTrendTooltip)
showInternalsInput = input( false, 'Show Internal Structure', group = INTERNAL_GROUP, tooltip = showInternalsTooltip)
showInternalBullInput = input.string( ALL, 'Bullish Structure', group = INTERNAL_GROUP, inline = 'ibull', options = )
internalBullColorInput = input( GREEN, '', group = INTERNAL_GROUP, inline = 'ibull')
showInternalBearInput = input.string( ALL, 'Bearish Structure' , group = INTERNAL_GROUP, inline = 'ibear', options = )
internalBearColorInput = input( RED, '', group = INTERNAL_GROUP, inline = 'ibear')
internalFilterConfluenceInput = input( false, 'Confluence Filter', group = INTERNAL_GROUP, tooltip = internalFilterConfluenceTooltip)
internalStructureSize = input.string( TINY, 'Internal Label Size', group = INTERNAL_GROUP, options = )
showStructureInput = input( false, 'Show Swing Structure', group = SWING_GROUP, tooltip = showStructureTooltip)
showSwingBullInput = input.string( ALL, 'Bullish Structure', group = SWING_GROUP, inline = 'bull', options = )
swingBullColorInput = input( GREEN, '', group = SWING_GROUP, inline = 'bull')
showSwingBearInput = input.string( ALL, 'Bearish Structure', group = SWING_GROUP, inline = 'bear', options = )
swingBearColorInput = input( RED, '', group = SWING_GROUP, inline = 'bear')
swingStructureSize = input.string( SMALL, 'Swing Label Size', group = SWING_GROUP, options = )
showSwingsInput = input( false, 'Show Swings Points', group = SWING_GROUP, tooltip = showSwingsTooltip,inline = 'swings')
swingsLengthInput = input.int( 50, '', group = SWING_GROUP, minval = 10, inline = 'swings')
showHighLowSwingsInput = input( false, 'Show Strong/Weak High/Low',group = SWING_GROUP, tooltip = showHighLowSwingsTooltip)
showInternalOrderBlocksInput = input( true, 'Internal Order Blocks' , group = BLOCKS_GROUP, tooltip = showInternalOrderBlocksTooltip, inline = 'iob')
internalOrderBlocksSizeInput = input.int( 5, '', group = BLOCKS_GROUP, minval = 1, maxval = 20, inline = 'iob')
showSwingOrderBlocksInput = input( true, 'Swing Order Blocks', group = BLOCKS_GROUP, tooltip = showSwingOrderBlocksTooltip, inline = 'ob')
swingOrderBlocksSizeInput = input.int( 5, '', group = BLOCKS_GROUP, minval = 1, maxval = 20, inline = 'ob')
orderBlockFilterInput = input.string( 'Atr', 'Order Block Filter', group = BLOCKS_GROUP, tooltip = orderBlockFilterTooltip, options = )
orderBlockMitigationInput = input.string( HIGHLOW, 'Order Block Mitigation', group = BLOCKS_GROUP, tooltip = orderBlockMitigationTooltip, options = )
internalBullishOrderBlockColor = input.color(color.new(GREEN, 80), 'Internal Bullish OB', group = BLOCKS_GROUP)
internalBearishOrderBlockColor = input.color(color.new(#f77c80, 80), 'Internal Bearish OB', group = BLOCKS_GROUP)
swingBullishOrderBlockColor = input.color(color.new(GREEN, 80), 'Bullish OB', group = BLOCKS_GROUP)
swingBearishOrderBlockColor = input.color(color.new(#b22833, 80), 'Bearish OB', group = BLOCKS_GROUP)
showEqualHighsLowsInput = input( false, 'Equal High/Low', group = EQUAL_GROUP, tooltip = showEqualHighsLowsTooltip)
equalHighsLowsLengthInput = input.int( 3, 'Bars Confirmation', group = EQUAL_GROUP, tooltip = equalHighsLowsLengthTooltip, minval = 1)
equalHighsLowsThresholdInput = input.float( 0.1, 'Threshold', group = EQUAL_GROUP, tooltip = equalHighsLowsThresholdTooltip, minval = 0, maxval = 0.5, step = 0.1)
equalHighsLowsSizeInput = input.string( TINY, 'Label Size', group = EQUAL_GROUP, options = )
showFairValueGapsInput = input( false, 'Fair Value Gaps', group = GAPS_GROUP, tooltip = showFairValueGapsTooltip)
fairValueGapsThresholdInput = input( true, 'Auto Threshold', group = GAPS_GROUP, tooltip = fairValueGapsThresholdTooltip)
fairValueGapsTimeframeInput = input.timeframe('', 'Timeframe', group = GAPS_GROUP, tooltip = fairValueGapsTimeframeTooltip)
fairValueGapsBullColorInput = input.color(color.new(#00ff68, 70), 'Bullish FVG' , group = GAPS_GROUP)
fairValueGapsBearColorInput = input.color(color.new(#ff0008, 70), 'Bearish FVG' , group = GAPS_GROUP)
fairValueGapsExtendInput = input.int( 1, 'Extend FVG', group = GAPS_GROUP, tooltip = fairValueGapsExtendTooltip, minval = 0)
showDailyLevelsInput = input( false, 'Daily', group = LEVELS_GROUP, inline = 'daily')
dailyLevelsStyleInput = input.string( SOLID, '', group = LEVELS_GROUP, inline = 'daily', options = )
dailyLevelsColorInput = input( BLUE, '', group = LEVELS_GROUP, inline = 'daily')
showWeeklyLevelsInput = input( false, 'Weekly', group = LEVELS_GROUP, inline = 'weekly')
weeklyLevelsStyleInput = input.string( SOLID, '', group = LEVELS_GROUP, inline = 'weekly', options = )
weeklyLevelsColorInput = input( BLUE, '', group = LEVELS_GROUP, inline = 'weekly')
showMonthlyLevelsInput = input( false, 'Monthly', group = LEVELS_GROUP, inline = 'monthly')
monthlyLevelsStyleInput = input.string( SOLID, '', group = LEVELS_GROUP, inline = 'monthly', options = )
monthlyLevelsColorInput = input( BLUE, '', group = LEVELS_GROUP, inline = 'monthly')
showPremiumDiscountZonesInput = input( false, 'Premium/Discount Zones', group = ZONES_GROUP , tooltip = showPremiumDiscountZonesTooltip)
premiumZoneColorInput = input.color( RED, 'Premium Zone', group = ZONES_GROUP)
equilibriumZoneColorInput = input.color( GRAY, 'Equilibrium Zone', group = ZONES_GROUP)
discountZoneColorInput = input.color( GREEN, 'Discount Zone', group = ZONES_GROUP)
type alerts
bool internalBullishBOS = false
bool internalBearishBOS = false
bool internalBullishCHoCH = false
bool internalBearishCHoCH = false
bool swingBullishBOS = false
bool swingBearishBOS = false
bool swingBullishCHoCH = false
bool swingBearishCHoCH = false
bool internalBullishOrderBlock = false
bool internalBearishOrderBlock = false
bool swingBullishOrderBlock = false
bool swingBearishOrderBlock = false
bool equalHighs = false
bool equalLows = false
bool bullishFairValueGap = false
bool bearishFairValueGap = false
type trailingExtremes
float top
float bottom
int barTime
int barIndex
int lastTopTime
int lastBottomTime
type fairValueGap
float top
float bottom
int bias
box topBox
box bottomBox
type trend
int bias
type equalDisplay
line l_ine = na
label l_abel = na
type pivot
float currentLevel
float lastLevel
bool crossed
int barTime = time
int barIndex = bar_index
type orderBlock
float barHigh
float barLow
int barTime
int bias
// @variable current swing pivot high
var pivot swingHigh = pivot.new(na,na,false)
// @variable current swing pivot low
var pivot swingLow = pivot.new(na,na,false)
// @variable current internal pivot high
var pivot internalHigh = pivot.new(na,na,false)
// @variable current internal pivot low
var pivot internalLow = pivot.new(na,na,false)
// @variable current equal high pivot
var pivot equalHigh = pivot.new(na,na,false)
// @variable current equal low pivot
var pivot equalLow = pivot.new(na,na,false)
// @variable swing trend bias
var trend swingTrend = trend.new(0)
// @variable internal trend bias
var trend internalTrend = trend.new(0)
// @variable equal high display
var equalDisplay equalHighDisplay = equalDisplay.new()
// @variable equal low display
var equalDisplay equalLowDisplay = equalDisplay.new()
// @variable storage for fairValueGap UDTs
var array fairValueGaps = array.new()
// @variable storage for parsed highs
var array parsedHighs = array.new()
// @variable storage for parsed lows
var array parsedLows = array.new()
// @variable storage for raw highs
var array highs = array.new()
// @variable storage for raw lows
var array lows = array.new()
// @variable storage for bar time values
var array times = array.new()
// @variable last trailing swing high and low
var trailingExtremes trailing = trailingExtremes.new()
// @variable storage for orderBlock UDTs (swing order blocks)
var array swingOrderBlocks = array.new()
// @variable storage for orderBlock UDTs (internal order blocks)
var array internalOrderBlocks = array.new()
// @variable storage for swing order blocks boxes
var array swingOrderBlocksBoxes = array.new()
// @variable storage for internal order blocks boxes
var array internalOrderBlocksBoxes = array.new()
// @variable color for swing bullish structures
var swingBullishColor = styleInput == MONOCHROME ? MONO_BULLISH : swingBullColorInput
// @variable color for swing bearish structures
var swingBearishColor = styleInput == MONOCHROME ? MONO_BEARISH : swingBearColorInput
// @variable color for bullish fair value gaps
var fairValueGapBullishColor = styleInput == MONOCHROME ? color.new(MONO_BULLISH,70) : fairValueGapsBullColorInput
// @variable color for bearish fair value gaps
var fairValueGapBearishColor = styleInput == MONOCHROME ? color.new(MONO_BEARISH,70) : fairValueGapsBearColorInput
// @variable color for premium zone
var premiumZoneColor = styleInput == MONOCHROME ? MONO_BEARISH : premiumZoneColorInput
// @variable color for discount zone
var discountZoneColor = styleInput == MONOCHROME ? MONO_BULLISH : discountZoneColorInput
// @variable bar index on current script iteration
varip int currentBarIndex = bar_index
// @variable bar index on last script iteration
varip int lastBarIndex = bar_index
// @variable alerts in current bar
alerts currentAlerts = alerts.new()
// @variable time at start of chart
var initialTime = time
// we create the needed boxes for displaying order blocks at the first execution
if barstate.isfirst
if showSwingOrderBlocksInput
for index = 1 to swingOrderBlocksSizeInput
swingOrderBlocksBoxes.push(box.new(na,na,na,na,xloc = xloc.bar_time,extend = extend.right))
if showInternalOrderBlocksInput
for index = 1 to internalOrderBlocksSizeInput
internalOrderBlocksBoxes.push(box.new(na,na,na,na,xloc = xloc.bar_time,extend = extend.right))
// @variable source to use in bearish order blocks mitigation
bearishOrderBlockMitigationSource = orderBlockMitigationInput == CLOSE ? close : high
// @variable source to use in bullish order blocks mitigation
bullishOrderBlockMitigationSource = orderBlockMitigationInput == CLOSE ? close : low
// @variable default volatility measure
atrMeasure = ta.atr(200)
// @variable parsed volatility measure by user settings
volatilityMeasure = orderBlockFilterInput == ATR ? atrMeasure : ta.cum(ta.tr)/bar_index
// @variable true if current bar is a high volatility bar
highVolatilityBar = (high - low) >= (2 * volatilityMeasure)
// @variable parsed high
parsedHigh = highVolatilityBar ? low : high
// @variable parsed low
parsedLow = highVolatilityBar ? high : low
// we store current values into the arrays at each bar
parsedHighs.push(parsedHigh)
parsedLows.push(parsedLow)
highs.push(high)
lows.push(low)
times.push(time)
leg(int size) =>
var leg = 0
newLegHigh = high > ta.highest( size)
newLegLow = low < ta.lowest( size)
if newLegHigh
leg := BEARISH_LEG
else if newLegLow
leg := BULLISH_LEG
leg
startOfNewLeg(int leg) => ta.change(leg) != 0
startOfBearishLeg(int leg) => ta.change(leg) == -1
startOfBullishLeg(int leg) => ta.change(leg) == +1
drawLabel(int labelTime, float labelPrice, string tag, color labelColor, string labelStyle) =>
var label l_abel = na
if modeInput == PRESENT
l_abel.delete()
l_abel := label.new(chart.point.new(labelTime,na,labelPrice),tag,xloc.bar_time,color=color(na),textcolor=labelColor,style = labelStyle,size = size.small)
drawEqualHighLow(pivot p_ivot, float level, int size, bool equalHigh) =>
equalDisplay e_qualDisplay = equalHigh ? equalHighDisplay : equalLowDisplay
string tag = 'EQL'
color equalColor = swingBullishColor
string labelStyle = label.style_label_up
if equalHigh
tag := 'EQH'
equalColor := swingBearishColor
labelStyle := label.style_label_down
if modeInput == PRESENT
line.delete( e_qualDisplay.l_ine)
label.delete( e_qualDisplay.l_abel)
e_qualDisplay.l_ine := line.new(chart.point.new(p_ivot.barTime,na,p_ivot.currentLevel), chart.point.new(time ,na,level), xloc = xloc.bar_time, color = equalColor, style = line.style_dotted)
labelPosition = math.round(0.5*(p_ivot.barIndex + bar_index - size))
e_qualDisplay.l_abel := label.new(chart.point.new(na,labelPosition,level), tag, xloc.bar_index, color = color(na), textcolor = equalColor, style = labelStyle, size = equalHighsLowsSizeInput)
getCurrentStructure(int size,bool equalHighLow = false, bool internal = false) =>
currentLeg = leg(size)
newPivot = startOfNewLeg(currentLeg)
pivotLow = startOfBullishLeg(currentLeg)
pivotHigh = startOfBearishLeg(currentLeg)
if newPivot
if pivotLow
pivot p_ivot = equalHighLow ? equalLow : internal ? internalLow : swingLow
if equalHighLow and math.abs(p_ivot.currentLevel - low ) < equalHighsLowsThresholdInput * atrMeasure
drawEqualHighLow(p_ivot, low , size, false)
p_ivot.lastLevel := p_ivot.currentLevel
p_ivot.currentLevel := low
p_ivot.crossed := false
p_ivot.barTime := time
p_ivot.barIndex := bar_index
if not equalHighLow and not internal
trailing.bottom := p_ivot.currentLevel
trailing.barTime := p_ivot.barTime
trailing.barIndex := p_ivot.barIndex
trailing.lastBottomTime := p_ivot.barTime
if showSwingsInput and not internal and not equalHighLow
drawLabel(time , p_ivot.currentLevel, p_ivot.currentLevel < p_ivot.lastLevel ? 'LL' : 'HL', swingBullishColor, label.style_label_up)
else
pivot p_ivot = equalHighLow ? equalHigh : internal ? internalHigh : swingHigh
if equalHighLow and math.abs(p_ivot.currentLevel - high ) < equalHighsLowsThresholdInput * atrMeasure
drawEqualHighLow(p_ivot,high ,size,true)
p_ivot.lastLevel := p_ivot.currentLevel
p_ivot.currentLevel := high
p_ivot.crossed := false
p_ivot.barTime := time
p_ivot.barIndex := bar_index
if not equalHighLow and not internal
trailing.top := p_ivot.currentLevel
trailing.barTime := p_ivot.barTime
trailing.barIndex := p_ivot.barIndex
trailing.lastTopTime := p_ivot.barTime
if showSwingsInput and not internal and not equalHighLow
drawLabel(time , p_ivot.currentLevel, p_ivot.currentLevel > p_ivot.lastLevel ? 'HH' : 'LH', swingBearishColor, label.style_label_down)
drawStructure(pivot p_ivot, string tag, color structureColor, string lineStyle, string labelStyle, string labelSize) =>
var line l_ine = line.new(na,na,na,na,xloc = xloc.bar_time)
var label l_abel = label.new(na,na)
if modeInput == PRESENT
l_ine.delete()
l_abel.delete()
l_ine := line.new(chart.point.new(p_ivot.barTime,na,p_ivot.currentLevel), chart.point.new(time,na,p_ivot.currentLevel), xloc.bar_time, color=structureColor, style=lineStyle)
l_abel := label.new(chart.point.new(na,math.round(0.5*(p_ivot.barIndex+bar_index)),p_ivot.currentLevel), tag, xloc.bar_index, color=color(na), textcolor=structureColor, style=labelStyle, size = labelSize)
deleteOrderBlocks(bool internal = false) =>
array orderBlocks = internal ? internalOrderBlocks : swingOrderBlocks
for in orderBlocks
bool crossedOderBlock = false
if bearishOrderBlockMitigationSource > eachOrderBlock.barHigh and eachOrderBlock.bias == BEARISH
crossedOderBlock := true
if internal
currentAlerts.internalBearishOrderBlock := true
else
currentAlerts.swingBearishOrderBlock := true
else if bullishOrderBlockMitigationSource < eachOrderBlock.barLow and eachOrderBlock.bias == BULLISH
crossedOderBlock := true
if internal
currentAlerts.internalBullishOrderBlock := true
else
currentAlerts.swingBullishOrderBlock := true
if crossedOderBlock
orderBlocks.remove(index)
storeOrdeBlock(pivot p_ivot,bool internal = false,int bias) =>
if (not internal and showSwingOrderBlocksInput) or (internal and showInternalOrderBlocksInput)
array a_rray = na
int parsedIndex = na
if bias == BEARISH
a_rray := parsedHighs.slice(p_ivot.barIndex,bar_index)
parsedIndex := p_ivot.barIndex + a_rray.indexof(a_rray.max())
else
a_rray := parsedLows.slice(p_ivot.barIndex,bar_index)
parsedIndex := p_ivot.barIndex + a_rray.indexof(a_rray.min())
orderBlock o_rderBlock = orderBlock.new(parsedHighs.get(parsedIndex), parsedLows.get(parsedIndex), times.get(parsedIndex),bias)
array orderBlocks = internal ? internalOrderBlocks : swingOrderBlocks
if orderBlocks.size() >= 100
orderBlocks.pop()
orderBlocks.unshift(o_rderBlock)
drawOrderBlocks(bool internal = false) =>
array orderBlocks = internal ? internalOrderBlocks : swingOrderBlocks
orderBlocksSize = orderBlocks.size()
if orderBlocksSize > 0
maxOrderBlocks = internal ? internalOrderBlocksSizeInput : swingOrderBlocksSizeInput
array parsedOrdeBlocks = orderBlocks.slice(0, math.min(maxOrderBlocks,orderBlocksSize))
array b_oxes = internal ? internalOrderBlocksBoxes : swingOrderBlocksBoxes
for in parsedOrdeBlocks
orderBlockColor = styleInput == MONOCHROME ? (eachOrderBlock.bias == BEARISH ? color.new(MONO_BEARISH,80) : color.new(MONO_BULLISH,80)) : internal ? (eachOrderBlock.bias == BEARISH ? internalBearishOrderBlockColor : internalBullishOrderBlockColor) : (eachOrderBlock.bias == BEARISH ? swingBearishOrderBlockColor : swingBullishOrderBlockColor)
box b_ox = b_oxes.get(index)
b_ox.set_top_left_point( chart.point.new(eachOrderBlock.barTime,na,eachOrderBlock.barHigh))
b_ox.set_bottom_right_point(chart.point.new(last_bar_time,na,eachOrderBlock.barLow))
b_ox.set_border_color( internal ? na : orderBlockColor)
b_ox.set_bgcolor( orderBlockColor)
displayStructure(bool internal = false) =>
var bullishBar = true
var bearishBar = true
if internalFilterConfluenceInput
bullishBar := high - math.max(close, open) > math.min(close, open - low)
bearishBar := high - math.max(close, open) < math.min(close, open - low)
pivot p_ivot = internal ? internalHigh : swingHigh
trend t_rend = internal ? internalTrend : swingTrend
lineStyle = internal ? line.style_dashed : line.style_solid
labelSize = internal ? internalStructureSize : swingStructureSize
extraCondition = internal ? internalHigh.currentLevel != swingHigh.currentLevel and bullishBar : true
bullishColor = styleInput == MONOCHROME ? MONO_BULLISH : internal ? internalBullColorInput : swingBullColorInput
if ta.crossover(close,p_ivot.currentLevel) and not p_ivot.crossed and extraCondition
string tag = t_rend.bias == BEARISH ? CHOCH : BOS
if internal
currentAlerts.internalBullishCHoCH := tag == CHOCH
currentAlerts.internalBullishBOS := tag == BOS
else
currentAlerts.swingBullishCHoCH := tag == CHOCH
currentAlerts.swingBullishBOS := tag == BOS
p_ivot.crossed := true
t_rend.bias := BULLISH
displayCondition = internal ? showInternalsInput and (showInternalBullInput == ALL or (showInternalBullInput == BOS and tag != CHOCH) or (showInternalBullInput == CHOCH and tag == CHOCH)) : showStructureInput and (showSwingBullInput == ALL or (showSwingBullInput == BOS and tag != CHOCH) or (showSwingBullInput == CHOCH and tag == CHOCH))
if displayCondition
drawStructure(p_ivot,tag,bullishColor,lineStyle,label.style_label_down,labelSize)
if (internal and showInternalOrderBlocksInput) or (not internal and showSwingOrderBlocksInput)
storeOrdeBlock(p_ivot,internal,BULLISH)
p_ivot := internal ? internalLow : swingLow
extraCondition := internal ? internalLow.currentLevel != swingLow.currentLevel and bearishBar : true
bearishColor = styleInput == MONOCHROME ? MONO_BEARISH : internal ? internalBearColorInput : swingBearColorInput
if ta.crossunder(close,p_ivot.currentLevel) and not p_ivot.crossed and extraCondition
string tag = t_rend.bias == BULLISH ? CHOCH : BOS
if internal
currentAlerts.internalBearishCHoCH := tag == CHOCH
currentAlerts.internalBearishBOS := tag == BOS
else
currentAlerts.swingBearishCHoCH := tag == CHOCH
currentAlerts.swingBearishBOS := tag == BOS
p_ivot.crossed := true
t_rend.bias := BEARISH
displayCondition = internal ? showInternalsInput and (showInternalBearInput == ALL or (showInternalBearInput == BOS and tag != CHOCH) or (showInternalBearInput == CHOCH and tag == CHOCH)) : showStructureInput and (showSwingBearInput == ALL or (showSwingBearInput == BOS and tag != CHOCH) or (showSwingBearInput == CHOCH and tag == CHOCH))
if displayCondition
drawStructure(p_ivot,tag,bearishColor,lineStyle,label.style_label_up,labelSize)
if (internal and showInternalOrderBlocksInput) or (not internal and showSwingOrderBlocksInput)
storeOrdeBlock(p_ivot,internal,BEARISH)
fairValueGapBox(leftTime,rightTime,topPrice,bottomPrice,boxColor) => box.new(chart.point.new(leftTime,na,topPrice),chart.point.new(rightTime + fairValueGapsExtendInput * (time-time ),na,bottomPrice), xloc=xloc.bar_time, border_color = boxColor, bgcolor = boxColor)
deleteFairValueGaps() =>
for in fairValueGaps
if (low < eachFairValueGap.bottom and eachFairValueGap.bias == BULLISH) or (high > eachFairValueGap.top and eachFairValueGap.bias == BEARISH)
eachFairValueGap.topBox.delete()
eachFairValueGap.bottomBox.delete()
fairValueGaps.remove(index)
// @function draw fair value gaps
// @returns fairValueGap ID
drawFairValueGaps() =>
= request.security(syminfo.tickerid, fairValueGapsTimeframeInput, [close , open , time , high , low , time , high , low ],lookahead = barmerge.lookahead_on)
barDeltaPercent = (lastClose - lastOpen) / (lastOpen * 100)
newTimeframe = timeframe.change(fairValueGapsTimeframeInput)
threshold = fairValueGapsThresholdInput ? ta.cum(math.abs(newTimeframe ? barDeltaPercent : 0)) / bar_index * 2 : 0
bullishFairValueGap = currentLow > last2High and lastClose > last2High and barDeltaPercent > threshold and newTimeframe
bearishFairValueGap = currentHigh < last2Low and lastClose < last2Low and -barDeltaPercent > threshold and newTimeframe
if bullishFairValueGap
currentAlerts.bullishFairValueGap := true
fairValueGaps.unshift(fairValueGap.new(currentLow,last2High,BULLISH,fairValueGapBox(lastTime,currentTime,currentLow,math.avg(currentLow,last2High),fairValueGapBullishColor),fairValueGapBox(lastTime,currentTime,math.avg(currentLow,last2High),last2High,fairValueGapBullishColor)))
if bearishFairValueGap
currentAlerts.bearishFairValueGap := true
fairValueGaps.unshift(fairValueGap.new(currentHigh,last2Low,BEARISH,fairValueGapBox(lastTime,currentTime,currentHigh,math.avg(currentHigh,last2Low),fairValueGapBearishColor),fairValueGapBox(lastTime,currentTime,math.avg(currentHigh,last2Low),last2Low,fairValueGapBearishColor)))
getStyle(string style) =>
switch style
SOLID => line.style_solid
DASHED => line.style_dashed
DOTTED => line.style_dotted
drawLevels(string timeframe, bool sameTimeframe, string style, color levelColor) =>
= request.security(syminfo.tickerid, timeframe, [high , low , time , time],lookahead = barmerge.lookahead_on)
float parsedTop = sameTimeframe ? high : topLevel
float parsedBottom = sameTimeframe ? low : bottomLevel
int parsedLeftTime = sameTimeframe ? time : leftTime
int parsedRightTime = sameTimeframe ? time : rightTime
int parsedTopTime = time
int parsedBottomTime = time
if not sameTimeframe
int leftIndex = times.binary_search_rightmost(parsedLeftTime)
int rightIndex = times.binary_search_rightmost(parsedRightTime)
array timeArray = times.slice(leftIndex,rightIndex)
array topArray = highs.slice(leftIndex,rightIndex)
array bottomArray = lows.slice(leftIndex,rightIndex)
parsedTopTime := timeArray.size() > 0 ? timeArray.get(topArray.indexof(topArray.max())) : initialTime
parsedBottomTime := timeArray.size() > 0 ? timeArray.get(bottomArray.indexof(bottomArray.min())) : initialTime
var line topLine = line.new(na, na, na, na, xloc = xloc.bar_time, color = levelColor, style = getStyle(style))
var line bottomLine = line.new(na, na, na, na, xloc = xloc.bar_time, color = levelColor, style = getStyle(style))
var label topLabel = label.new(na, na, xloc = xloc.bar_time, text = str.format('P{0}H',timeframe), color=color(na), textcolor = levelColor, size = size.small, style = label.style_label_left)
var label bottomLabel = label.new(na, na, xloc = xloc.bar_time, text = str.format('P{0}L',timeframe), color=color(na), textcolor = levelColor, size = size.small, style = label.style_label_left)
topLine.set_first_point( chart.point.new(parsedTopTime,na,parsedTop))
topLine.set_second_point( chart.point.new(last_bar_time + 20 * (time-time ),na,parsedTop))
topLabel.set_point( chart.point.new(last_bar_time + 20 * (time-time ),na,parsedTop))
bottomLine.set_first_point( chart.point.new(parsedBottomTime,na,parsedBottom))
bottomLine.set_second_point(chart.point.new(last_bar_time + 20 * (time-time ),na,parsedBottom))
bottomLabel.set_point( chart.point.new(last_bar_time + 20 * (time-time ),na,parsedBottom))
higherTimeframe(string timeframe) => timeframe.in_seconds() > timeframe.in_seconds(timeframe)
updateTrailingExtremes() =>
trailing.top := math.max(high,trailing.top)
trailing.lastTopTime := trailing.top == high ? time : trailing.lastTopTime
trailing.bottom := math.min(low,trailing.bottom)
trailing.lastBottomTime := trailing.bottom == low ? time : trailing.lastBottomTime
drawHighLowSwings() =>
var line topLine = line.new(na, na, na, na, color = swingBearishColor, xloc = xloc.bar_time)
var line bottomLine = line.new(na, na, na, na, color = swingBullishColor, xloc = xloc.bar_time)
var label topLabel = label.new(na, na, color=color(na), textcolor = swingBearishColor, xloc = xloc.bar_time, style = label.style_label_down, size = size.tiny)
var label bottomLabel = label.new(na, na, color=color(na), textcolor = swingBullishColor, xloc = xloc.bar_time, style = label.style_label_up, size = size.tiny)
rightTimeBar = last_bar_time + 20 * (time - time )
topLine.set_first_point( chart.point.new(trailing.lastTopTime, na, trailing.top))
topLine.set_second_point( chart.point.new(rightTimeBar, na, trailing.top))
topLabel.set_point( chart.point.new(rightTimeBar, na, trailing.top))
topLabel.set_text( swingTrend.bias == BEARISH ? 'Strong High' : 'Weak High')
bottomLine.set_first_point( chart.point.new(trailing.lastBottomTime, na, trailing.bottom))
bottomLine.set_second_point(chart.point.new(rightTimeBar, na, trailing.bottom))
bottomLabel.set_point( chart.point.new(rightTimeBar, na, trailing.bottom))
bottomLabel.set_text( swingTrend.bias == BULLISH ? 'Strong Low' : 'Weak Low')
drawZone(float labelLevel, int labelIndex, float top, float bottom, string tag, color zoneColor, string style) =>
var label l_abel = label.new(na,na,text = tag, color=color(na),textcolor = zoneColor, style = style, size = size.small)
var box b_ox = box.new(na,na,na,na,bgcolor = color.new(zoneColor,80),border_color = color(na), xloc = xloc.bar_time)
b_ox.set_top_left_point( chart.point.new(trailing.barTime,na,top))
b_ox.set_bottom_right_point(chart.point.new(last_bar_time,na,bottom))
l_abel.set_point( chart.point.new(na,labelIndex,labelLevel))
// @function draw premium/discount zones
// @returns void
drawPremiumDiscountZones() =>
drawZone(trailing.top, math.round(0.5*(trailing.barIndex + last_bar_index)), trailing.top, 0.95*trailing.top + 0.05*trailing.bottom, 'Premium', premiumZoneColor, label.style_label_down)
equilibriumLevel = math.avg(trailing.top, trailing.bottom)
drawZone(equilibriumLevel, last_bar_index, 0.525*trailing.top + 0.475*trailing.bottom, 0.525*trailing.bottom + 0.475*trailing.top, 'Equilibrium', equilibriumZoneColorInput, label.style_label_left)
drawZone(trailing.bottom, math.round(0.5*(trailing.barIndex + last_bar_index)), 0.95*trailing.bottom + 0.05*trailing.top, trailing.bottom, 'Discount', discountZoneColor, label.style_label_up)
parsedOpen = showTrendInput ? open : na
candleColor = internalTrend.bias == BULLISH ? swingBullishColor : swingBearishColor
plotcandle(parsedOpen,high,low,close,color = candleColor, wickcolor = candleColor, bordercolor = candleColor)
if showHighLowSwingsInput or showPremiumDiscountZonesInput
updateTrailingExtremes()
if showHighLowSwingsInput
drawHighLowSwings()
if showPremiumDiscountZonesInput
drawPremiumDiscountZones()
if showFairValueGapsInput
deleteFairValueGaps()
getCurrentStructure(swingsLengthInput,false)
getCurrentStructure(5,false,true)
if showEqualHighsLowsInput
getCurrentStructure(equalHighsLowsLengthInput,true)
if showInternalsInput or showInternalOrderBlocksInput or showTrendInput
displayStructure(true)
if showStructureInput or showSwingOrderBlocksInput or showHighLowSwingsInput
displayStructure()
if showInternalOrderBlocksInput
deleteOrderBlocks(true)
if showSwingOrderBlocksInput
deleteOrderBlocks()
if showFairValueGapsInput
drawFairValueGaps()
if barstate.islastconfirmedhistory or barstate.islast
if showInternalOrderBlocksInput
drawOrderBlocks(true)
if showSwingOrderBlocksInput
drawOrderBlocks()
lastBarIndex := currentBarIndex
currentBarIndex := bar_index
newBar = currentBarIndex != lastBarIndex
if barstate.islastconfirmedhistory or (barstate.isrealtime and newBar)
if showDailyLevelsInput and not higherTimeframe('D')
drawLevels('D',timeframe.isdaily,dailyLevelsStyleInput,dailyLevelsColorInput)
if showWeeklyLevelsInput and not higherTimeframe('W')
drawLevels('W',timeframe.isweekly,weeklyLevelsStyleInput,weeklyLevelsColorInput)
if showMonthlyLevelsInput and not higherTimeframe('M')
drawLevels('M',timeframe.ismonthly,monthlyLevelsStyleInput,monthlyLevelsColorInput)
xATR = ta.atr(c)
nLoss = a * xATR
src = h ? request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, close, lookahead = barmerge.lookahead_off) : close
xATRTrailingStop = 0.0
iff_1 = src > nz(xATRTrailingStop , 0) ? src - nLoss : src + nLoss
iff_2 = src < nz(xATRTrailingStop , 0) and src < nz(xATRTrailingStop , 0) ? math.min(nz(xATRTrailingStop ), src + nLoss) : iff_1
xATRTrailingStop := src > nz(xATRTrailingStop , 0) and src > nz(xATRTrailingStop , 0) ? math.max(nz(xATRTrailingStop ), src - nLoss) : iff_2
pos = 0
iff_3 = src > nz(xATRTrailingStop , 0) and src < nz(xATRTrailingStop , 0) ? -1 : nz(pos , 0)
pos := src < nz(xATRTrailingStop , 0) and src > nz(xATRTrailingStop , 0) ? 1 : iff_3
xcolor = pos == -1 ? color.red : pos == 1 ? color.green : color.blue
ema = ta.ema(src, 1)
above = ta.crossover(ema, xATRTrailingStop)
below = ta.crossover(xATRTrailingStop, ema)
buy = src > xATRTrailingStop and above
sell = src < xATRTrailingStop and below
barbuy = src > xATRTrailingStop
barsell = src < xATRTrailingStop
//---------------------------------------------------------------------------------------------------------------------}
//ALERTS
//---------------------------------------------------------------------------------------------------------------------{
alertcondition(currentAlerts.internalBullishBOS, 'Internal Bullish BOS', 'Internal Bullish BOS formed')
alertcondition(currentAlerts.internalBullishCHoCH, 'Internal Bullish CHoCH', 'Internal Bullish CHoCH formed')
alertcondition(currentAlerts.internalBearishBOS, 'Internal Bearish BOS', 'Internal Bearish BOS formed')
alertcondition(currentAlerts.internalBearishCHoCH, 'Internal Bearish CHoCH', 'Internal Bearish CHoCH formed')
alertcondition(currentAlerts.swingBullishBOS, 'Bullish BOS', 'Internal Bullish BOS formed')
alertcondition(currentAlerts.swingBullishCHoCH, 'Bullish CHoCH', 'Internal Bullish CHoCH formed')
alertcondition(currentAlerts.swingBearishBOS, 'Bearish BOS', 'Bearish BOS formed')
alertcondition(currentAlerts.swingBearishCHoCH, 'Bearish CHoCH', 'Bearish CHoCH formed')
alertcondition(currentAlerts.internalBullishOrderBlock, 'Bullish Internal OB Breakout', 'Price broke bullish internal OB')
alertcondition(currentAlerts.internalBearishOrderBlock, 'Bearish Internal OB Breakout', 'Price broke bearish internal OB')
alertcondition(currentAlerts.swingBullishOrderBlock, 'Bullish Swing OB Breakout', 'Price broke bullish swing OB')
alertcondition(currentAlerts.swingBearishOrderBlock, 'Bearish Swing OB Breakout', 'Price broke bearish swing OB')
alertcondition(currentAlerts.equalHighs, 'Equal Highs', 'Equal highs detected')
alertcondition(currentAlerts.equalLows, 'Equal Lows', 'Equal lows detected')
alertcondition(currentAlerts.bullishFairValueGap, 'Bullish FVG', 'Bullish FVG formed')
alertcondition(currentAlerts.bearishFairValueGap, 'Bearish FVG', 'Bearish FVG formed')
alertcondition(buy, 'UT Long', 'UT Long')
alertcondition(sell, 'UT Short', 'UT Short')
plotshape(buy, title = 'Buy', text = 'Buy', style = shape.labelup, location = location.belowbar, color = color.new(color.green, 0), textcolor = color.new(color.white, 0), size = size.tiny)
plotshape(sell, title = 'Sell', text = 'Sell', style = shape.labeldown, location = location.abovebar, color = color.new(color.red, 0), textcolor = color.new(color.white, 0), size = size.tiny)
//--------------------------------------------------------------------------------------
// EMA ADDITIONS (Editable)
//--------------------------------------------------------------------------------------
ema5Len = input.int(5, "5 EMA Length", minval = 1)
ema9Len = input.int(9, "9 EMA Length", minval = 1)
ema5 = ta.ema(src, ema5Len)
ema9 = ta.ema(src, ema9Len)
plot(ema5, "EMA 5", color = color.red, linewidth = 2)
plot(ema9, "EMA 9", color = color.blue, linewidth = 2)
barcolor(barbuy ? color.green : na)
barcolor(barsell ? color.red : na)
Bifurcation Zone - CAEBifurcation Zone — Cognitive Adversarial Engine (BZ-CAE)
Bifurcation Zone — CAE (BZ-CAE) is a next-generation divergence detection system enhanced by a Cognitive Adversarial Engine that evaluates both sides of every potential trade before presenting signals. Unlike traditional divergence indicators that show every price-oscillator disagreement regardless of context, BZ-CAE applies comprehensive market-state intelligence to identify only the divergences that occur in favorable conditions with genuine probability edges.
The system identifies structural bifurcation points — critical junctures where price and momentum disagree, signaling potential reversals or continuations — then validates these opportunities through five interconnected intelligence layers: Trend Conviction Scoring , Directional Momentum Alignment , Multi-Factor Exhaustion Modeling , Adversarial Validation , and Confidence Scoring . The result is a selective, context-aware signal system that filters noise and highlights high-probability setups.
This is not a "buy the arrow" indicator. It's a decision support framework that teaches you how to read market state, evaluate divergence quality, and make informed trading decisions based on quantified intelligence rather than hope.
What Sets BZ-CAE Apart: Technical Architecture
The Problem With Traditional Divergence Indicators
Most divergence indicators operate on a simple rule: if price makes a higher high and RSI makes a lower high, show a bearish signal. If price makes a lower low and RSI makes a higher low, show a bullish signal. This creates several critical problems:
Context Blindness : They show counter-trend signals in powerful trends that rarely reverse, leading to repeated losses as you fade momentum.
Signal Spam : Every minor price-oscillator disagreement generates an alert, overwhelming you with low-quality setups and creating analysis paralysis.
No Quality Ranking : All signals are treated identically. A marginal divergence in choppy conditions receives the same visual treatment as a high-conviction setup at a major exhaustion point.
Single-Sided Evaluation : They ask "Is this a good long?" without checking if the short case is overwhelmingly stronger, leading you into obvious bad trades.
Static Configuration : You manually choose RSI 14 or Stochastic 14 and hope it works, with no systematic way to validate if that's optimal for your instrument.
BZ-CAE's Solution: Cognitive Adversarial Intelligence
BZ-CAE solves these problems through an integrated five-layer intelligence architecture:
1. Trend Conviction Score (TCS) — 0 to 1 Scale
Most indicators check if ADX is above 25 to determine "trending" conditions. This binary approach misses nuance. TCS is a weighted composite metric:
Formula : 0.35 × normalize(ADX, 10, 35) + 0.35 × structural_strength + 0.30 × htf_alignment
Structural Strength : 10-bar SMA of consecutive directional bars. Captures persistence — are bulls or bears consistently winning?
HTF Alignment : Multi-timeframe EMA stacking (20/50/100/200). When all EMAs align in the same direction, you're in institutional trend territory.
Purpose : Quantifies how "locked in" the trend is. When TCS exceeds your threshold (default 0.80), the system knows to avoid counter-trend trades unless other factors override.
Interpretation :
TCS > 0.85: Very strong trend — counter-trading is extremely high risk
TCS 0.70-0.85: Strong trend — favor continuation, require exhaustion for reversals
TCS 0.50-0.70: Moderate trend — context matters, both directions viable
TCS < 0.50: Weak/choppy — reversals more viable, range-bound conditions
2. Directional Momentum Alignment (DMA) — ATR-Normalized
Formula : (EMA21 - EMA55) / ATR14
This isn't just "price above EMA" — it's a regime-aware momentum gauge. The same $100 price movement reads completely differently in high-volatility crypto versus low-volatility forex. By normalizing with ATR, DMA adapts its interpretation to current market conditions.
Purpose : Quantifies the directional "force" behind current price action. Positive = bullish push, negative = bearish push. Magnitude = strength.
Interpretation :
DMA > 0.7: Strong bullish momentum — bearish divergences risky
DMA 0.3 to 0.7: Moderate bullish bias
DMA -0.3 to 0.3: Balanced/choppy conditions
DMA -0.7 to -0.3: Moderate bearish bias
DMA < -0.7: Strong bearish momentum — bullish divergences risky
3. Multi-Factor Exhaustion Modeling — 0 to 1 Probability
Single-metric exhaustion detection (like "RSI > 80") misses complex market states. BZ-CAE aggregates five independent exhaustion signals:
Volume Spikes : Current volume versus 50-bar average
2.5x average: 0.25 weight
2.0x average: 0.15 weight
1.5x average: 0.10 weight
Divergence Present : The fact that a divergence exists contributes 0.30 weight — structural momentum disagreement is itself an exhaustion signal.
RSI Extremes : Captures oscillator climax zones
RSI > 80 or < 20: 0.25 weight
RSI > 75 or < 25: 0.15 weight
Pin Bar Detection : Identifies rejection candles (2:1 wick-to-body ratio, indicating failed breakout attempts): 0.15 weight
Extended Runs : Consecutive bars above/below EMA20 without pullback
30+ bars: 0.15 weight (market hasn't paused to consolidate)
Total exhaustion score is the sum of all applicable weights, capped at 1.0.
Purpose : Detects when strong trends become vulnerable to reversal. High exhaustion can override trend filters, allowing counter-trend trades at genuine turning points that basic indicators would miss.
Interpretation :
Exhaustion > 0.75: High probability of climax — yellow background shading alerts you visually
Exhaustion 0.50-0.75: Moderate overextension — watch for confirmation
Exhaustion < 0.50: Fresh move — trend can continue, counter-trend trades higher risk
4. Adversarial Validation — Game Theory Applied to Trading
This is BZ-CAE's signature innovation. Before approving any signal, the engine quantifies BOTH sides of the trade simultaneously:
For Bullish Divergences , it calculates:
Bull Case Score (0-1+) :
Distance below EMA20 (pullback quality): up to 0.25
Bullish EMA alignment (close > EMA20 > EMA50): 0.25
Oversold RSI (< 40): 0.25
Volume confirmation (> 1.2x average): 0.25
Bear Case Score (0-1+) :
Price below EMA50 (structural weakness): 0.30
Very oversold RSI (< 30, indicating knife-catching): 0.20
Differential = Bull Case - Bear Case
If differential < -0.10 (default threshold), the bear case is dominating — signal is BLOCKED or ANNOTATED.
For Bearish Divergences , the logic inverts (Bear Case vs Bull Case).
Purpose : Prevents trades where you're fighting obvious strength in the opposite direction. This is institutional-grade risk management — don't just evaluate your trade, evaluate the counter-trade simultaneously.
Why This Matters : You might see a bullish divergence at a local low, but if price is deeply below major support EMAs with strong bearish momentum, you're catching a falling knife. The adversarial check catches this and blocks the signal.
5. Confidence Scoring — 0 to 1 Quality Assessment
Every signal that passes initial filters receives a comprehensive quality score:
Formula :
0.30 × normalize(TCS) // Trend context
+ 0.25 × normalize(|DMA|) // Momentum magnitude
+ 0.20 × pullback_quality // Entry distance from EMA20
+ 0.15 × state_quality // ADX + alignment + structure
+ 0.10 × divergence_strength // Slope separation magnitude
+ adversarial_bonus (0-0.30) // Your side's advantage
Purpose : Ranks setup quality for filtering and position sizing decisions. You can set a minimum confidence threshold (default 0.35) to ensure only quality setups reach your chart.
Interpretation :
Confidence > 0.70: Premium setup — consider increased position size
Confidence 0.50-0.70: Good quality — standard size
Confidence 0.35-0.50: Acceptable — reduced size or skip if conservative
Confidence < 0.35: Marginal — blocked in Filtering mode, annotated in Advisory mode
CAE Operating Modes: Learning vs Enforcement
Off : Disables all CAE logic. Raw divergence pipeline only. Use for baseline comparison.
Advisory : Shows ALL signals regardless of CAE evaluation, but annotates signals that WOULD be blocked with specific warnings (e.g., "Bull: strong downtrend (TCS=0.87)" or "Adversarial bearish"). This is your learning mode — see CAE's decision logic in action without missing educational opportunities.
Filtering : Actively blocks low-quality signals. Only setups that pass all enabled gates (Trend Filter, Adversarial Validation, Confidence Gating) reach your chart. This is your live trading mode — trust the system to enforce discipline.
CAE Filter Gates: Three-Layer Protection
When CAE is enabled, signals must pass through three independent gates (each can be toggled on/off):
Gate 1: Strong Trend Filter
If TCS ≥ tcs_threshold (default 0.80)
And signal is counter-trend (bullish in downtrend or bearish in uptrend)
And exhaustion < exhaustion_required (default 0.50)
Then: BLOCK signal
Logic: Don't fade strong trends unless the move is clearly overextended
Gate 2: Adversarial Validation
Calculate both bull case and bear case scores
If opposing case dominates by more than adv_threshold (default 0.10)
Then: BLOCK signal
Logic: Avoid trades where you're fighting obvious strength in the opposite direction
Gate 3: Confidence Gating
Calculate composite confidence score (0-1)
If confidence < min_confidence (default 0.35)
Then: In Filtering mode, BLOCK signal; in Advisory mode, ANNOTATE with warning
Logic: Only take setups with minimum quality threshold
All three gates work together. A signal must pass ALL enabled gates to fire.
Visual Intelligence System
Bifurcation Zones (Supply/Demand Blocks)
When a divergence signal fires, BZ-CAE draws a semi-transparent box extending 15 bars forward from the signal pivot:
Demand Zones (Bullish) : Theme-colored box (cyan in Cyberpunk, blue in Professional, etc.) labeled "Demand" — marks where smart money likely placed buy orders as price diverged at the low.
Supply Zones (Bearish) : Theme-colored box (magenta in Cyberpunk, orange in Professional) labeled "Supply" — marks where smart money likely placed sell orders as price diverged at the high.
Theory : Divergences represent institutional disagreement with the crowd. The crowd pushed price to an extreme (new high or low), but momentum (oscillator) is waning, indicating smart money is taking the opposite side. These zones mark order placement areas that become future support/resistance.
Use Cases :
Exit targets: Take profit when price returns to opposite-side zone
Re-entry levels: If price returns to your entry zone, consider adding
Stop placement: Place stops just beyond your zone (below demand, above supply)
Auto-Cleanup : System keeps the last 20 zones to prevent chart clutter.
Adversarial Bar Coloring — Real-Time Market Debate Heatmap
Each bar is colored based on the Bull Case vs Bear Case differential:
Strong Bull Advantage (diff > 0.3): Full theme bull color (e.g., cyan)
Moderate Bull Advantage (diff > 0.1): 50% transparency bull
Neutral (diff -0.1 to 0.1): Gray/neutral theme
Moderate Bear Advantage (diff < -0.1): 50% transparency bear
Strong Bear Advantage (diff < -0.3): Full theme bear color (e.g., magenta)
This creates a real-time visual heatmap showing which side is "winning" the market debate. When bars flip from cyan to magenta (or vice versa), you're witnessing a shift in adversarial advantage — a leading indicator of potential momentum changes.
Exhaustion Shading
When exhaustion score exceeds 0.75, the chart background displays a semi-transparent yellow highlight. This immediate visual warning alerts you that the current move is at high risk of reversal, even if trend indicators remain strong.
Visual Themes — Six Aesthetic Options
Cyberpunk : Cyan/Magenta/Yellow — High contrast, neon aesthetic, excellent for dark-themed trading environments
Professional : Blue/Orange/Green — Corporate color palette, suitable for presentations and professional documentation
Ocean : Teal/Red/Cyan — Aquatic palette, calming for extended monitoring sessions
Fire : Orange/Red/Coral — Warm aggressive colors, high energy
Matrix : Green/Red/Lime — Code aesthetic, homage to classic hacker visuals
Monochrome : White/Gray — Minimal distraction, maximum focus on price action
All visual elements (signal markers, zones, bar colors, dashboard) adapt to your selected theme.
Divergence Engine — Core Detection System
What Are Divergences?
Divergences occur when price action and momentum indicators disagree, creating structural tension that often resolves in a change of direction:
Regular Divergence (Reversal Signal) :
Bearish Regular : Price makes higher high, oscillator makes lower high → Potential trend reversal down
Bullish Regular : Price makes lower low, oscillator makes higher low → Potential trend reversal up
Hidden Divergence (Continuation Signal) :
Bearish Hidden : Price makes lower high, oscillator makes higher high → Downtrend continuation
Bullish Hidden : Price makes higher low, oscillator makes lower low → Uptrend continuation
Both types can be enabled/disabled independently in settings.
Pivot Detection Methods
BZ-CAE uses symmetric pivot detection with separate lookback and lookforward periods (default 5/5):
Pivot High : Bar where high > all highs within lookback range AND high > all highs within lookforward range
Pivot Low : Bar where low < all lows within lookback range AND low < all lows within lookforward range
This ensures structural validity — the pivot must be a clear local extreme, not just a minor wiggle.
Divergence Validation Requirements
For a divergence to be confirmed, it must satisfy:
Slope Disagreement : Price slope and oscillator slope must move in opposite directions (for regular divs) or same direction with inverted highs/lows (for hidden divs)
Minimum Slope Change : |osc_slope| > min_slope_change / 100 (default 1.0) — filters weak, marginal divergences
Maximum Lookback Range : Pivots must be within max_lookback bars (default 60) — prevents ancient, irrelevant divergences
ATR-Normalized Strength : Divergence strength = min(|price_slope| × |osc_slope| × 10, 1.0) — quantifies the magnitude of disagreement in volatility context
Regular divergences receive 1.0× weight; hidden divergences receive 0.8× weight (slightly less reliable historically).
Oscillator Options — Five Professional Indicators
RSI (Relative Strength Index) : Classic overbought/oversold momentum indicator. Best for: General purpose divergence detection across all instruments.
Stochastic : Range-bound %K momentum comparing close to high-low range. Best for: Mean reversion strategies and range-bound markets.
CCI (Commodity Channel Index) : Measures deviation from statistical mean, auto-normalized to 0-100 scale. Best for: Cyclical instruments and commodities.
MFI (Money Flow Index) : Volume-weighted RSI incorporating money flow. Best for: Volume-driven markets like stocks and crypto.
Williams %R : Inverse stochastic looking back over period, auto-adjusted to 0-100. Best for: Reversal detection at extremes.
Each oscillator has adjustable length (2-200, default 14) and smoothing (1-20, default 1). You also set overbought (50-100, default 70) and oversold (0-50, default 30) thresholds.
Signal Timing Modes — Understanding Repainting
BZ-CAE offers two timing policies with complete transparency about repainting behavior:
Realtime (1-bar, peak-anchored)
How It Works :
Detects peaks 1 bar ago using pattern: high > high AND high > high
Signal prints on the NEXT bar after peak detection (bar_index)
Visual marker anchors to the actual PEAK bar (bar_index - 1, offset -1)
Signal locks in when bar CONFIRMS (closes)
Repainting Behavior :
On the FORMING bar (before close), the peak condition may change as new prices arrive
Once bar CLOSES (barstate.isconfirmed), signal is locked permanently
This is preview/early warning behavior by design
Best For :
Active monitoring and immediate alerts
Learning the system (seeing signals develop in real-time)
Responsive entry if you're watching the chart live
Confirmed (lookforward)
How It Works :
Uses Pine Script's built-in ta.pivothigh() and ta.pivotlow() functions
Requires full pivot validation period (lookback + lookforward bars)
Signal prints pivot_lookforward bars after the actual peak (default 5-bar delay)
Visual marker anchors to the actual peak bar (offset -pivot_lookforward)
No Repainting Behavior
Best For :
Backtesting and historical analysis
Conservative entries requiring full confirmation
Automated trading systems
Swing trading with larger timeframes
Tradeoff :
Delayed entry by pivot_lookforward bars (typically 5 bars)
On a 5-minute chart, this is a 25-minute delay
On a 4-hour chart, this is a 20-hour delay
Recommendation : Use Confirmed for backtesting to verify system performance honestly. Use Realtime for live monitoring only if you're actively watching the chart and understand pre-confirmation repainting behavior.
Signal Spacing System — Anti-Spam Architecture
Even after CAE filtering, raw divergences can cluster. The spacing system enforces separation:
Three Independent Filters
1. Min Bars Between ANY Signals (default 12):
Prevents rapid-fire clustering across both directions
If last signal (bull or bear) was within N bars, block new signal
Ensures breathing room between all setups
2. Min Bars Between SAME-SIDE Signals (default 24, optional enforcement):
Prevents bull-bull or bear-bear spam
Separate tracking for bullish and bearish signal timelines
Toggle enforcement on/off
3. Min ATR Distance From Last Signal (default 0, optional):
Requires price to move N × ATR from last signal location
Ensures meaningful price movement between setups
0 = disabled, 0.5-2.0 = typical range for enabled
All three filters work independently. A signal must pass ALL enabled filters to proceed.
Practical Guidance :
Scalping (1-5m) : Any 6-10, Same-side 12-20, ATR 0-0.5
Day Trading (15m-1H) : Any 12, Same-side 24, ATR 0-1.0
Swing Trading (4H-D) : Any 20-30, Same-side 40-60, ATR 1.0-2.0
Dashboard — Real-Time Control Center
The dashboard (toggleable, four corner positions, three sizes) provides comprehensive system intelligence:
Oscillator Section
Current oscillator type and value
State: OVERBOUGHT / OVERSOLD / NEUTRAL (color-coded)
Length parameter
Cognitive Engine Section
TCS (Trend Conviction Score) :
Current value with emoji state indicator
🔥 = Strong trend (>0.75)
📊 = Moderate trend (0.50-0.75)
〰️ = Weak/choppy (<0.50)
Color: Red if above threshold (trend filter active), yellow if moderate, green if weak
DMA (Directional Momentum Alignment) :
Current value with emoji direction indicator
🐂 = Bullish momentum (>0.5)
⚖️ = Balanced (-0.5 to 0.5)
🐻 = Bearish momentum (<-0.5)
Color: Green if bullish, red if bearish
Exhaustion :
Current value with emoji warning indicator
⚠️ = High exhaustion (>0.75)
🟡 = Moderate (0.50-0.75)
✓ = Low (<0.50)
Color: Red if high, yellow if moderate, green if low
Pullback :
Quality of current distance from EMA20
Values >0.6 are ideal entry zones (not too close, not too far)
Bull Case / Bear Case (if Adversarial enabled):
Current scores for both sides of the market debate
Differential with emoji indicator:
📈 = Bull advantage (>0.2)
➡️ = Balanced (-0.2 to 0.2)
📉 = Bear advantage (<-0.2)
Last Signal Metrics Section (New Feature)
When a signal fires, this section captures and displays:
Signal type (BULL or BEAR)
Bars elapsed since signal
Confidence % at time of signal
TCS value at signal time
DMA value at signal time
Purpose : Provides a historical reference for learning. You can see what the market state looked like when the last signal fired, helping you correlate outcomes with conditions.
Statistics Section
Total Signals : Lifetime count across session
Blocked Signals : Count and percentage (filter effectiveness metric)
Bull Signals : Total bullish divergences
Bear Signals : Total bearish divergences
Purpose : System health monitoring. If blocked % is very high (>60%), filters may be too strict. If very low (<10%), filters may be too loose.
Advisory Annotations
When CAE Mode = Advisory, this section displays warnings for signals that would be blocked in Filtering mode:
Examples:
"Bull spacing: wait 8 bars"
"Bear: strong uptrend (TCS=0.87)"
"Adversarial bearish"
"Low confidence 32%"
Multiple warnings can stack, separated by " | ". This teaches you CAE's decision logic transparently.
How to Use BZ-CAE — Complete Workflow
Phase 1: Initial Setup (First Session)
Apply BZ-CAE to your chart
Select your preferred Visual Theme (Cyberpunk recommended for visibility)
Set Signal Timing to "Confirmed (lookforward)" for learning
Choose your Oscillator Type (RSI recommended for general use, length 14)
Set Overbought/Oversold to 70/30 (standard)
Enable both Regular Divergence and Hidden Divergence
Set Pivot Lookback/Lookforward to 5/5 (balanced structure)
Enable CAE Intelligence
Set CAE Mode to "Advisory" (learning mode)
Enable all three CAE filters: Strong Trend Filter , Adversarial Validation , Confidence Gating
Enable Show Dashboard , position Top Right, size Normal
Enable Draw Bifurcation Zones and Adversarial Bar Coloring
Phase 2: Learning Period (Weeks 1-2)
Goal : Understand how CAE evaluates market state and filters signals.
Activities :
Watch the dashboard during signals :
Note TCS values when counter-trend signals fail — this teaches you the trend strength threshold for your instrument
Observe exhaustion patterns at actual turning points — learn when overextension truly matters
Study adversarial differential at signal times — see when opposing cases dominate
Review blocked signals (orange X-crosses):
In Advisory mode, you see everything — signals that would pass AND signals that would be blocked
Check the advisory annotations to understand why CAE would block
Track outcomes: Were the blocks correct? Did those signals fail?
Use Last Signal Metrics :
After each signal, check the dashboard capture of confidence, TCS, and DMA
Journal these values alongside trade outcomes
Identify patterns: Do confidence >0.70 signals work better? Does your instrument respect TCS >0.85?
Understand your instrument's "personality" :
Trending instruments (indices, major forex) may need TCS threshold 0.85-0.90
Choppy instruments (low-cap stocks, exotic pairs) may work best with TCS 0.70-0.75
High-volatility instruments (crypto) may need wider spacing
Low-volatility instruments may need tighter spacing
Phase 3: Calibration (Weeks 3-4)
Goal : Optimize settings for your specific instrument, timeframe, and style.
Calibration Checklist :
Min Confidence Threshold :
Review confidence distribution in your signal journal
Identify the confidence level below which signals consistently fail
Set min_confidence slightly above that level
Day trading : 0.35-0.45
Swing trading : 0.40-0.55
Scalping : 0.30-0.40
TCS Threshold :
Find the TCS level where counter-trend signals consistently get stopped out
Set tcs_threshold at or slightly below that level
Trending instruments : 0.85-0.90
Mixed instruments : 0.80-0.85
Choppy instruments : 0.75-0.80
Exhaustion Override Level :
Identify exhaustion readings that marked genuine reversals
Set exhaustion_required just below the average
Typical range : 0.45-0.55
Adversarial Threshold :
Default 0.10 works for most instruments
If you find CAE is too conservative (blocking good trades), raise to 0.15-0.20
If signals are still getting caught in opposing momentum, lower to 0.07-0.09
Spacing Parameters :
Count bars between quality signals in your journal
Set min bars ANY to ~60% of that average
Set min bars SAME-SIDE to ~120% of that average
Scalping : Any 6-10, Same 12-20
Day trading : Any 12, Same 24
Swing : Any 20-30, Same 40-60
Oscillator Selection :
Try different oscillators for 1-2 weeks each
Track win rate and average winner/loser by oscillator type
RSI : Best for general use, clear OB/OS
Stochastic : Best for range-bound, mean reversion
MFI : Best for volume-driven markets
CCI : Best for cyclical instruments
Williams %R : Best for reversal detection
Phase 4: Live Deployment
Goal : Disciplined execution with proven, calibrated system.
Settings Changes :
Switch CAE Mode from Advisory to Filtering
System now actively blocks low-quality signals
Only setups passing all gates reach your chart
Keep Signal Timing on Confirmed for conservative entries
OR switch to Realtime if you're actively monitoring and want faster entries (accept pre-confirmation repaint risk)
Use your calibrated thresholds from Phase 3
Enable high-confidence alerts: "⭐ High Confidence Bullish/Bearish" (>0.70)
Trading Discipline Rules :
Respect Blocked Signals :
If CAE blocks a trade you wanted to take, TRUST THE SYSTEM
Don't manually override — if you consistently disagree, return to Phase 2/3 calibration
The block exists because market state failed intelligence checks
Confidence-Based Position Sizing :
Confidence >0.70: Standard or increased size (e.g., 1.5-2.0% risk)
Confidence 0.50-0.70: Standard size (e.g., 1.0% risk)
Confidence 0.35-0.50: Reduced size (e.g., 0.5% risk) or skip if conservative
TCS-Based Management :
High TCS + counter-trend signal: Use tight stops, quick exits (you're fading momentum)
Low TCS + reversal signal: Use wider stops, trail aggressively (genuine reversal potential)
Exhaustion Awareness :
Exhaustion >0.75 (yellow shading): Market is overextended, reversal risk is elevated — consider early exit or tighter trailing stops even on winning trades
Exhaustion <0.30: Continuation bias — hold for larger move, wide trailing stops
Adversarial Context :
Strong differential against you (e.g., bullish signal with bear diff <-0.2): Use very tight stops, consider skipping
Strong differential with you (e.g., bullish signal with bull diff >0.2): Trail aggressively, this is your tailwind
Practical Settings by Timeframe & Style
Scalping (1-5 Minute Charts)
Objective : High frequency, tight stops, quick reversals in fast-moving markets.
Oscillator :
Type: RSI or Stochastic (fast response to quick moves)
Length: 9-11 (more responsive than standard 14)
Smoothing: 1 (no lag)
OB/OS: 65/35 (looser thresholds ensure frequent crossings in fast conditions)
Divergence :
Pivot Lookback/Lookforward: 3/3 (tight structure, catch small swings)
Max Lookback: 40-50 bars (recent structure only)
Min Slope Change: 0.8-1.0 (don't be overly strict)
CAE :
Mode: Advisory first (learn), then Filtering
Min Confidence: 0.30-0.35 (lower bar for speed, accept more signals)
TCS Threshold: 0.70-0.75 (allow more counter-trend opportunities)
Exhaustion Required: 0.45-0.50 (moderate override)
Strong Trend Filter: ON (still respect major intraday trends)
Adversarial: ON (critical for scalping protection — catches bad entries quickly)
Spacing :
Min Bars ANY: 6-10 (fast pace, many setups)
Min Bars SAME-SIDE: 12-20 (prevent clustering)
Min ATR Distance: 0 or 0.5 (loose)
Timing : Realtime (speed over precision, but understand repaint risk)
Visuals :
Signal Size: Tiny (chart clarity in busy conditions)
Show Zones: Optional (can clutter on low timeframes)
Bar Coloring: ON (helps read momentum shifts quickly)
Dashboard: Small size (corner reference, not main focus)
Key Consideration : Scalping generates noise. Even with CAE, expect lower win rate (45-55%) but aim for favorable R:R (2:1 or better). Size conservatively.
Day Trading (15-Minute to 1-Hour Charts)
Objective : Balance quality and frequency. Standard divergence trading approach.
Oscillator :
Type: RSI or MFI (proven reliability, volume confirmation with MFI)
Length: 14 (industry standard, well-studied)
Smoothing: 1-2
OB/OS: 70/30 (classic levels)
Divergence :
Pivot Lookback/Lookforward: 5/5 (balanced structure)
Max Lookback: 60 bars
Min Slope Change: 1.0 (standard strictness)
CAE :
Mode: Filtering (enforce discipline from the start after brief Advisory learning)
Min Confidence: 0.35-0.45 (quality filter without being too restrictive)
TCS Threshold: 0.80-0.85 (respect strong trends)
Exhaustion Required: 0.50 (balanced override threshold)
Strong Trend Filter: ON
Adversarial: ON
Confidence Gating: ON (all three filters active)
Spacing :
Min Bars ANY: 12 (breathing room between all setups)
Min Bars SAME-SIDE: 24 (prevent bull/bear clusters)
Min ATR Distance: 0-1.0 (optional refinement, typically 0.5-1.0)
Timing : Confirmed (1-bar delay for reliability, no repainting)
Visuals :
Signal Size: Tiny or Small
Show Zones: ON (useful reference for exits/re-entries)
Bar Coloring: ON (context awareness)
Dashboard: Normal size (full visibility)
Key Consideration : This is the "sweet spot" timeframe for BZ-CAE. Market structure is clear, CAE has sufficient data, and signal frequency is manageable. Expect 55-65% win rate with proper execution.
Swing Trading (4-Hour to Daily Charts)
Objective : Quality over quantity. High conviction only. Larger stops and targets.
Oscillator :
Type: RSI or CCI (robust on higher timeframes, smooth longer waves)
Length: 14-21 (capture larger momentum swings)
Smoothing: 1-3
OB/OS: 70/30 or 75/25 (strict extremes)
Divergence :
Pivot Lookback/Lookforward: 5/5 or 7/7 (structural purity, major swings only)
Max Lookback: 80-100 bars (broader historical context)
Min Slope Change: 1.2-1.5 (require strong, undeniable divergence)
CAE :
Mode: Filtering (strict enforcement, premium setups only)
Min Confidence: 0.40-0.55 (high bar for entry)
TCS Threshold: 0.85-0.95 (very strong trend protection — don't fade established HTF trends)
Exhaustion Required: 0.50-0.60 (higher bar for override — only extreme exhaustion justifies counter-trend)
Strong Trend Filter: ON (critical on HTF)
Adversarial: ON (avoid obvious bad trades)
Confidence Gating: ON (quality gate essential)
Spacing :
Min Bars ANY: 20-30 (substantial separation)
Min Bars SAME-SIDE: 40-60 (significant breathing room)
Min ATR Distance: 1.0-2.0 (require meaningful price movement)
Timing : Confirmed (purity over speed, zero repaint for swing accuracy)
Visuals :
Signal Size: Small or Normal (clear markers on zoomed-out view)
Show Zones: ON (important HTF levels)
Bar Coloring: ON (long-term trend awareness)
Dashboard: Normal or Large (comprehensive analysis)
Key Consideration : Swing signals are rare but powerful. Expect 2-5 signals per month per instrument. Win rate should be 60-70%+ due to stringent filtering. Position size can be larger given confidence.
Dashboard Interpretation Reference
TCS (Trend Conviction Score) States
0.00-0.50: Weak/Choppy
Emoji: 〰️
Color: Green/cyan
Meaning: No established trend. Range-bound or consolidating. Both reversal and continuation signals viable.
Action: Reversals (regular divs) are safer. Use wider profit targets (market has room to move). Consider mean reversion strategies.
0.50-0.75: Moderate Trend
Emoji: 📊
Color: Yellow/neutral
Meaning: Developing trend but not locked in. Context matters significantly.
Action: Check DMA and exhaustion. If DMA confirms trend and exhaustion is low, favor continuation (hidden divs). If exhaustion is high, reversals are viable.
0.75-0.85: Strong Trend
Emoji: 🔥
Color: Orange/warning
Meaning: Well-established trend with persistence. Counter-trend is high risk.
Action: Require exhaustion >0.50 for counter-trend entries. Favor continuation signals. Use tight stops on counter-trend attempts.
0.85-1.00: Very Strong Trend
Emoji: 🔥🔥
Color: Red/danger (if counter-trading)
Meaning: Locked-in institutional trend. Extremely high risk to fade.
Action: Avoid counter-trend unless exhaustion >0.75 (yellow shading). Focus exclusively on continuation opportunities. Momentum is king here.
DMA (Directional Momentum Alignment) Zones
-2.0 to -1.0: Strong Bearish Momentum
Emoji: 🐻🐻
Color: Dark red
Meaning: Powerful downside force. Sellers are in control.
Action: Bullish divergences are counter-momentum (high risk). Bearish divergences are with-momentum (lower risk). Size down on longs.
-0.5 to 0.5: Neutral/Balanced
Emoji: ⚖️
Color: Gray/neutral
Meaning: No strong directional bias. Choppy or consolidating.
Action: Both directions have similar probability. Focus on confidence score and adversarial differential for edge.
1.0 to 2.0: Strong Bullish Momentum
Emoji: 🐂🐂
Color: Bright green/cyan
Meaning: Powerful upside force. Buyers are in control.
Action: Bearish divergences are counter-momentum (high risk). Bullish divergences are with-momentum (lower risk). Size down on shorts.
Exhaustion States
0.00-0.50: Fresh Move
Emoji: ✓
Color: Green
Meaning: Trend is healthy, not overextended. Room to run.
Action: Counter-trend trades are premature. Favor continuation. Hold winners for larger moves. Avoid early exits.
0.50-0.75: Mature Move
Emoji: 🟡
Color: Yellow
Meaning: Move is aging. Watch for signs of climax.
Action: Tighten trailing stops on winning trades. Be ready for reversals. Don't add to positions aggressively.
0.75-0.85: High Exhaustion
Emoji: ⚠️
Color: Orange
Background: Yellow shading appears
Meaning: Move is overextended. Reversal risk elevated significantly.
Action: Counter-trend reversals are higher probability. Consider early exits on with-trend positions. Size up on reversal divergences (if CAE allows).
0.85-1.00: Critical Exhaustion
Emoji: ⚠️⚠️
Color: Red
Background: Yellow shading intensifies
Meaning: Climax conditions. Reversal imminent or underway.
Action: Aggressive reversal trades justified. Exit all with-trend positions. This is where major turns occur.
Confidence Score Tiers
0.00-0.30: Low Quality
Color: Red
Status: Blocked in Filtering mode
Action: Skip entirely. Setup lacks fundamental quality across multiple factors.
0.30-0.50: Moderate Quality
Color: Yellow/orange
Status: Marginal — passes in Filtering only if >min_confidence
Action: Reduced position size (0.5-0.75% risk). Tight stops. Conservative profit targets. Skip if you're selective.
0.50-0.70: High Quality
Color: Green/cyan
Status: Good setup across most quality factors
Action: Standard position size (1.0-1.5% risk). Normal stops and targets. This is your bread-and-butter trade.
0.70-1.00: Premium Quality
Color: Bright green/gold
Status: Exceptional setup — all factors aligned
Visual: Double confidence ring appears
Action: Consider increased position size (1.5-2.0% risk, maximum). Wider stops. Larger targets. High probability of success. These are rare — capitalize when they appear.
Adversarial Differential Interpretation
Bull Differential > 0.3 :
Visual: Strong cyan/green bar colors
Meaning: Bull case strongly dominates. Buyers have clear advantage.
Action: Bullish divergences favored (with-advantage). Bearish divergences face headwind (reduce size or skip). Momentum is bullish.
Bull Differential 0.1 to 0.3 :
Visual: Moderate cyan/green transparency
Meaning: Moderate bull advantage. Buyers have edge but not overwhelming.
Action: Both directions viable. Slight bias toward longs.
Differential -0.1 to 0.1 :
Visual: Gray/neutral bars
Meaning: Balanced debate. No clear advantage either side.
Action: Rely on other factors (confidence, TCS, exhaustion) for direction. Adversarial is neutral.
Bear Differential -0.3 to -0.1 :
Visual: Moderate red/magenta transparency
Meaning: Moderate bear advantage. Sellers have edge but not overwhelming.
Action: Both directions viable. Slight bias toward shorts.
Bear Differential < -0.3 :
Visual: Strong red/magenta bar colors
Meaning: Bear case strongly dominates. Sellers have clear advantage.
Action: Bearish divergences favored (with-advantage). Bullish divergences face headwind (reduce size or skip). Momentum is bearish.
Last Signal Metrics — Post-Trade Analysis
After a signal fires, dashboard captures:
Type : BULL or BEAR
Bars Ago : How long since signal (updates every bar)
Confidence : What was the quality score at signal time
TCS : What was trend conviction at signal time
DMA : What was momentum alignment at signal time
Use Case : Post-trade journaling and learning.
Example: "BULL signal 12 bars ago. Confidence: 68%, TCS: 0.42, DMA: -0.85"
Analysis : This was a bullish reversal (regular div) with good confidence, weak trend (TCS), but strong bearish momentum (DMA). The bet was that momentum would reverse — a counter-momentum play requiring exhaustion confirmation. Check if exhaustion was high at that time to justify the entry.
Track patterns:
Do your best trades have confidence >0.65?
Do low-TCS signals (<0.50) work better for you?
Are you more successful with-momentum (DMA aligned with signal) or counter-momentum?
Troubleshooting Guide
Problem: No Signals Appearing
Symptoms : Chart loads, dashboard shows metrics, but no divergence signals fire.
Diagnosis Checklist :
Check dashboard oscillator value : Is it crossing OB/OS levels (70/30)? If oscillator stays in 40-60 range constantly, it can't reach extremes needed for divergence detection.
Are pivots forming? : Look for local swing highs/lows on your chart. If price is in tight consolidation, pivots may not meet lookback/lookforward requirements.
Is spacing too tight? : Check "Last Signal" metrics — how many bars since last signal? If <12 and your min_bars_ANY is 12, spacing filter is blocking.
Is CAE blocking everything? : Check dashboard Statistics section — what's the blocked signal count? High blocks indicate overly strict filters.
Solutions :
Loosen OB/OS Temporarily :
Try 65/35 to verify divergence detection works
If signals appear, the issue was threshold strictness
Gradually tighten back to 67/33, then 70/30 as appropriate
Lower Min Confidence :
Try 0.25-0.30 (diagnostic level)
If signals appear, filter was too strict
Raise gradually to find sweet spot (0.35-0.45 typical)
Disable Strong Trend Filter Temporarily :
Turn off in CAE settings
If signals appear, TCS threshold was blocking everything
Re-enable and lower TCS_threshold to 0.70-0.75
Reduce Min Slope Change :
Try 0.7-0.8 (from default 1.0)
Allows weaker divergences through
Helpful on low-volatility instruments
Widen Spacing :
Set min_bars_ANY to 6-8
Set min_bars_SAME_SIDE to 12-16
Reduces time between allowed signals
Check Timing Mode :
If using Confirmed, remember there's a pivot_lookforward delay (5+ bars)
Switch to Realtime temporarily to verify system is working
Realtime has no delay but repaints
Verify Oscillator Settings :
Length 14 is standard but might not fit all instruments
Try length 9-11 for faster response
Try length 18-21 for slower, smoother response
Problem: Too Many Signals (Signal Spam)
Symptoms : Dashboard shows 50+ signals in Statistics, confidence scores mostly <0.40, signals clustering close together.
Solutions :
Raise Min Confidence :
Try 0.40-0.50 (quality filter)
Blocks bottom-tier setups
Targets top 50-60% of divergences only
Tighten OB/OS :
Use 70/30 or 75/25
Requires more extreme oscillator readings
Reduces false divergences in mid-range
Increase Min Slope Change :
Try 1.2-1.5 (from default 1.0)
Requires stronger, more obvious divergences
Filters marginal slope disagreements
Raise TCS Threshold :
Try 0.85-0.90 (from default 0.80)
Stricter trend filter blocks more counter-trend attempts
Favors only strongest trend alignment
Enable ALL CAE Gates :
Turn on Trend Filter + Adversarial + Confidence
Triple-layer protection
Blocks aggressively — expect 20-40% reduction in signals
Widen Spacing :
min_bars_ANY: 15-20 (from 12)
min_bars_SAME_SIDE: 30-40 (from 24)
Creates substantial breathing room
Switch to Confirmed Timing :
Removes realtime preview noise
Ensures full pivot validation
5-bar delay filters many false starts
Problem: Signals in Strong Trends Get Stopped Out
Symptoms : You take a bullish divergence in a downtrend (or bearish in uptrend), and it immediately fails. Dashboard showed high TCS at the time.
Analysis : This is INTENDED behavior — CAE is protecting you from low-probability counter-trend trades.
Understanding :
Check Last Signal Metrics in dashboard — what was TCS when signal fired?
If TCS was >0.85 and signal was counter-trend, CAE correctly identified it as high risk
Strong trends rarely reverse cleanly without major exhaustion
Your losses here are the system working as designed (blocking bad odds)
If You Want to Override (Not Recommended) :
Lower TCS_threshold to 0.70-0.75 (allows more counter-trend)
Lower exhaustion_required to 0.40 (easier override)
Disable Strong Trend Filter entirely (very risky)
Better Approach :
TRUST THE FILTER — it's preventing costly mistakes
Wait for exhaustion >0.75 (yellow shading) before counter-trending strong TCS
Focus on continuation signals (hidden divs) in high-TCS environments
Use Advisory mode to see what CAE is blocking and learn from outcomes
Problem: Adversarial Blocking Seems Wrong
Symptoms : You see a divergence that "looks good" visually, but CAE blocks with "Adversarial bearish/bullish" warning.
Diagnosis :
Check dashboard Bull Case and Bear Case scores at that moment
Look at Differential value
Check adversarial bar colors — was there strong coloring against your intended direction?
Understanding :
Adversarial catches "obvious" opposing momentum that's easy to miss
Example: Bullish divergence at a local low, BUT price is deeply below EMA50, bearish momentum is strong, and RSI shows knife-catching conditions
Bull Case might be 0.20 while Bear Case is 0.55
Differential = -0.35, far beyond threshold
Block is CORRECT — you'd be fighting overwhelming opposing flow
If You Disagree Consistently
Review blocked signals on chart — scroll back and check outcomes
Did those blocked signals actually work, or did they fail as adversarial predicted?
Raise adv_threshold to 0.15-0.20 (more permissive, allows closer battles)
Disable Adversarial Validation temporarily (diagnostic) to isolate its effect
Use Advisory mode to learn adversarial patterns over 50-100 signals
Remember : Adversarial is conservative BY DESIGN. It prevents "obvious" bad trades where you're fighting strong strength the other way.
Problem: Dashboard Not Showing or Incomplete
Solutions :
Toggle "Show Dashboard" to ON in settings
Try different dashboard sizes (Small/Normal/Large)
Try different positions (Top Left/Right, Bottom Left/Right) — might be off-screen
Some sections require CAE Enable = ON (Cognitive Engine section won't appear if CAE is disabled)
Statistics section requires at least 1 lifetime signal to populate
Check that visual theme is set (dashboard colors adapt to theme)
Problem: Performance Lag, Chart Freezing
Symptoms : Chart loading is slow, indicator calculations cause delays, pinch-to-zoom lags.
Diagnosis : Visual features are computationally expensive, especially adversarial bar coloring (recalculates every bar).
Solutions (In Order of Impact) :
Disable Adversarial Bar Coloring (MOST EXPENSIVE):
Turn OFF "Adversarial Bar Coloring" in settings
This is the single biggest performance drain
Immediate improvement
Reduce Vertical Lines :
Lower "Keep last N vertical lines" to 20-30
Or set to 0 to disable entirely
Moderate improvement
Disable Bifurcation Zones :
Turn OFF "Draw Bifurcation Zones"
Reduces box drawing calculations
Moderate improvement
Set Dashboard Size to Small :
Smaller dashboard = fewer cells = less rendering
Minor improvement
Use Shorter Max Lookback :
Reduce max_lookback to 40-50 (from 60+)
Fewer bars to scan for divergences
Minor improvement
Disable Exhaustion Shading :
Turn OFF "Show Market State"
Removes background coloring calculations
Minor improvement
Extreme Performance Mode :
Disable ALL visual enhancements
Keep only triangle markers
Dashboard Small or OFF
Use Minimal theme if available
Problem: Realtime Signals Repainting
Symptoms : You see a signal appear, but on next bar it disappears or moves.
Explanation :
Realtime mode detects peaks 1 bar ago: high > high AND high > high
On the FORMING bar (before close), this condition can change as new prices arrive
Example: At 10:05, high (10:04 bar) was 100, current high is 99 → peak detected
At 10:05:30, new high of 101 arrives → peak condition breaks → signal disappears
At 10:06 (bar close), final high is 101 → no peak at 10:04 anymore → signal gone permanently
This is expected behavior for realtime responsiveness. You get preview/early warning, but it's not locked until bar confirms.
Solutions :
Use Confirmed Timing :
Switch to "Confirmed (lookforward)" mode
ZERO repainting — pivot must be fully validated
5-bar delay (pivot_lookforward)
What you see in history is exactly what would have appeared live
Accept Realtime Repaint as Tradeoff :
Keep Realtime mode for speed and alerts
Understand that pre-confirmation signals may vanish
Only trade signals that CONFIRM at bar close (check barstate.isconfirmed)
Use for live monitoring, NOT for backtesting
Trade Only After Confirmation :
In Realtime mode, wait 1 full bar after signal appears before entering
If signal survives that bar close, it's locked
This adds 1-bar delay but removes repaint risk
Recommendation : Use Confirmed for backtesting and conservative trading. Use Realtime only for active monitoring with full understanding of preview behavior.
Risk Management Integration
BZ-CAE is a signal generation system, not a complete trading strategy. You must integrate proper risk management:
Position Sizing by Confidence
Confidence 0.70-1.00 (Premium) :
Risk: 1.5-2.0% of account (MAXIMUM)
Reasoning: High-quality setup across all factors
Still cap at 2% — even premium setups can fail
Confidence 0.50-0.70 (High Quality) :
Risk: 1.0-1.5% of account
Reasoning: Standard good setup
Your bread-and-butter risk level
Confidence 0.35-0.50 (Moderate Quality) :
Risk: 0.5-1.0% of account
Reasoning: Marginal setup, passes minimum threshold
Reduce size or skip if you're selective
Confidence <0.35 (Low Quality) :
Risk: 0% (blocked in Filtering mode)
Reasoning: Insufficient quality factors
System protects you by not showing these
Stop Placement Strategies
For Reversal Signals (Regular Divergences) :
Place stop beyond the divergence pivot plus buffer
Bullish : Stop below the divergence low - 1.0-1.5 × ATR
Bearish : Stop above the divergence high + 1.0-1.5 × ATR
Reasoning: If price breaks the pivot, divergence structure is invalidated
For Continuation Signals (Hidden Divergences) :
Place stop beyond recent swing in opposite direction
Bullish continuation : Stop below recent swing low (not the divergence pivot itself)
Bearish continuation : Stop above recent swing high
Reasoning: You're trading with trend, allow more breathing room
ATR-Based Stops :
1.5-2.0 × ATR is standard
Scale by timeframe:
Scalping (1-5m): 1.0-1.5 × ATR (tight)
Day trading (15m-1H): 1.5-2.0 × ATR (balanced)
Swing (4H-D): 2.0-3.0 × ATR (wide)
Never Use Fixed Dollar/Pip Stops :
Markets have different volatility
50-pip stop on EUR/USD ≠ 50-pip stop on GBP/JPY
Always normalize by ATR or pivot structure
Profit Targets and Scaling
Primary Target :
2-3 × ATR from entry (minimum 2:1 reward-risk)
Example : Entry at 100, ATR = 2, stop at 97 (1.5 × ATR) → target at 106 (3 × ATR) = 2:1 R:R
Scaling Out Strategy :
Take 50% off at 1.5 × ATR (secure partial profit)
Move stop to breakeven
Trail remaining 50% with 1.0 × ATR trailing stop
Let winners run if trend persists
Targets by Confidence :
High Confidence (>0.70) : Aggressive targets (3-4 × ATR), trail wider (1.5 × ATR)
Standard Confidence (0.50-0.70) : Normal targets (2-3 × ATR), standard trail (1.0 × ATR)
Low Confidence (0.35-0.50) : Conservative targets (1.5-2 × ATR), tight trail (0.75 × ATR)
Use Bifurcation Zones :
If opposite-side zone is visible on chart (from previous signal), use it as target
Example : Bullish signal at 100, prior supply zone at 110 → use 110 as target
Zones mark institutional resistance/support
Exhaustion-Based Exits :
If you're in a trade and exhaustion >0.75 develops (yellow shading), consider early exit
Market is overextended — reversal risk is high
Take profit even if target not reached
Trade Management by TCS
High TCS + Counter-Trend Trade (Risky) :
Use very tight stops (1.0-1.5 × ATR)
Conservative targets (1.5-2 × ATR)
Quick exit if trade doesn't work immediately
You're fading momentum — respect it
Low TCS + Reversal Trade (Safer) :
Use wider stops (2.0-2.5 × ATR)
Aggressive targets (3-4 × ATR)
Trail with patience
Genuine reversal potential in weak trend
High TCS + Continuation Trade (Safest) :
Standard stops (1.5-2.0 × ATR)
Very aggressive targets (4-5 × ATR)
Trail wide (1.5-2.0 × ATR)
You're with institutional momentum — let it run
Educational Value — Learning Machine Intelligence
BZ-CAE is designed as a learning platform, not just a tool:
Advisory Mode as Teacher
Most indicators are binary: signal or no signal. You don't learn WHY certain setups are better.
BZ-CAE's Advisory mode shows you EVERY potential divergence, then annotates the ones that would be blocked in Filtering mode with specific reasons:
"Bull: strong downtrend (TCS=0.87)" teaches you that TCS >0.85 makes counter-trend very risky
"Adversarial bearish" teaches you that the opposing case was dominating
"Low confidence 32%" teaches you that the setup lacked quality across multiple factors
"Bull spacing: wait 8 bars" teaches you that signals need breathing room
After 50-100 signals in Advisory mode, you internalize the CAE's decision logic. You start seeing these factors yourself BEFORE the indicator does.
Dashboard Transparency
Most "intelligent" indicators are black boxes — you don't know how they make decisions.
BZ-CAE shows you ALL metrics in real-time:
TCS tells you trend strength
DMA tells you momentum alignment
Exhaustion tells you overextension
Adversarial shows both sides of the debate
Confidence shows composite quality
You learn to interpret market state holistically, a skill applicable to ANY trading system beyond this indicator.
Divergence Quality Education
Not all divergences are equal. BZ-CAE teaches you which conditions produce high-probability setups:
Quality divergence : Regular bullish div at a low, TCS <0.50 (weak trend), exhaustion >0.75 (overextended), positive adversarial differential, confidence >0.70
Low-quality divergence : Regular bearish div at a high, TCS >0.85 (strong uptrend), exhaustion <0.30 (not overextended), negative adversarial differential, confidence <0.40
After using the system, you can evaluate divergences manually with similar intelligence.
Risk Management Discipline
Confidence-based position sizing teaches you to adjust risk based on setup quality, not emotions:
Beginners often size all trades identically
Or worse, size UP on marginal setups to "make up" for losses
BZ-CAE forces systematic sizing: premium setups get larger size, marginal setups get smaller size
This creates a probabilistic approach where your edge compounds over time.
What This Indicator Is NOT
Complete transparency about limitations and positioning:
Not a Prediction System
BZ-CAE does not predict future prices. It identifies structural divergences (price-momentum disagreements) and assesses current market state (trend, exhaustion, adversarial conditions). It tells you WHEN conditions favor a potential reversal or continuation, not WHAT WILL HAPPEN.
Markets are probabilistic. Even premium-confidence setups fail ~30-40% of the time. The system improves your probability distribution over many trades — it doesn't eliminate risk.
Not Fully Automated
This is a decision support tool, not a trading robot. You must:
Execute trades manually based on signals
Manage positions (stops, targets, trailing)
Apply discretionary judgment (news events, liquidity, context)
Integrate with your broader strategy and risk rules
The confidence scores guide position sizing, but YOU determine final risk allocation based on your account size, risk tolerance, and portfolio context.
Not Beginner-Friendly
BZ-CAE requires understanding of:
Divergence trading concepts (regular vs hidden, reversal vs continuation)
Market state interpretation (trend vs range, momentum, exhaustion)
Basic technical analysis (pivots, support/resistance, EMAs)
Risk management fundamentals (position sizing, stops, R:R)
This is designed for intermediate to advanced traders willing to invest time learning the system. If you want "buy the arrow" simplicity, this isn't the tool.
Not a Holy Grail
There is no perfect indicator. BZ-CAE filters noise and improves signal quality significantly, but:
Losing trades are inevitable (even at 70% win rate, 30% still fail)
Market conditions change rapidly (yesterday's strong trend becomes today's chop)
Black swan events occur (fundamentals override technicals)
Execution matters (slippage, fees, emotional discipline)
The system provides an EDGE, not a guarantee. Your job is to execute that edge consistently with proper risk management over hundreds of trades.
Not Financial Advice
BZ-CAE is an educational and analytical tool. All trading decisions are your responsibility. Past performance (backtested or live) does not guarantee future results. Only risk capital you can afford to lose. Consult a licensed financial advisor for investment advice specific to your situation.
Ideal Market Conditions
Best Performance Characteristics
Liquid Instruments :
Major forex pairs (EUR/USD, GBP/USD, USD/JPY)
Large-cap stocks and index ETFs (SPY, QQQ, AAPL, MSFT)
High-volume crypto (BTC, ETH)
Major commodities (Gold, Oil, Natural Gas)
Reasoning: Clean price structure, clear pivots, meaningful oscillator behavior
Trending with Consolidations :
Markets that trend for 20-40 bars, then consolidate 10-20 bars, repeat
Creates divergences at consolidation boundaries (reversals) and within trends (continuations)
Both regular and hidden divs find opportunities
5-Minute to Daily Timeframes :
Below 5m: too much noise, false pivots, CAE metrics unstable
Above daily: too few signals, edge diminishes (fundamentals dominate)
Sweet spot: 15m to 4H for most traders
Consistent Volume and Participation :
Regular trading sessions (not holidays or thin markets)
Predictable volatility patterns
Avoid instruments with sudden gaps or circuit breakers
Challenging Conditions
Extremely Low Liquidity :
Penny stocks, exotic forex pairs, low-volume crypto
Erratic pivots, unreliable oscillator readings
CAE metrics can't assess market state properly
Very Low Timeframes (1-Minute or Below) :
Dominated by market microstructure noise
Divergences are everywhere but meaningless
CAE filtering helps but still unreliable
Extended Sideways Consolidation :
100+ bars of tight range with no clear pivots
Oscillator hugs midpoint (45-55 range)
No divergences to detect
Fundamentally-Driven Gap Markets :
Earnings releases, economic data, geopolitical events
Price gaps over stops and targets
Technical structure breaks down
Recommendation: Disable trading around known events
Calculation Methodology — Technical Depth
For users who want to understand the math:
Oscillator Computation
Each oscillator type calculates differently, but all normalize to 0-100:
RSI : ta.rsi(close, length) — Standard Relative Strength Index
Stochastic : ta.stoch(high, low, close, length) — %K calculation
CCI : (ta.cci(hlc3, length) + 100) / 2 — Normalized from -100/+100 to 0-100
MFI : ta.mfi(hlc3, length) — Volume-weighted RSI equivalent
Williams %R : ta.wpr(length) + 100 — Inverted stochastic adjusted to 0-100
Smoothing: If smoothing > 1, apply ta.sma(oscillator, smoothing)
Divergence Detection Algorithm
Identify Pivots :
Price high pivot: ta.pivothigh(high, lookback, lookforward)
Price low pivot: ta.pivotlow(low, lookback, lookforward)
Oscillator high pivot: ta.pivothigh(osc, lookback, lookforward)
Oscillator low pivot: ta.pivotlow(osc, lookback, lookforward)
Store Recent Pivots :
Maintain arrays of last 10 pivots with bar indices
When new pivot confirmed, unshift to array, pop oldest if >10
Scan for Slope Disagreements :
Loop through last 5 pivots
For each pair (current pivot, historical pivot):
Check if within max_lookback bars
Calculate slopes: (current - historical) / bars_between
Regular bearish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold
Regular bullish: price_slope < 0, osc_slope > 0, |osc_slope| > min_threshold
Hidden bearish: price_slope < 0, osc_slope > 0, osc_slope > min_threshold
Hidden bullish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold
Important Disclaimers and Terms
Performance Disclosure
Past performance, whether backtested or live-traded, does not guarantee future results. Markets change. What works today may not work tomorrow. Hypothetical or simulated performance results have inherent limitations and do not represent actual trading.
Risk of Loss
Trading involves substantial risk of loss. Only trade with risk capital you can afford to lose entirely. The high degree of leverage often available in trading can work against you as well as for you. Leveraged trading may result in losses exceeding your initial deposit.
Not Financial Advice
BZ-CAE is an educational and analytical tool for technical analysis. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument. All trading decisions are your sole responsibility. Consult a licensed financial advisor for advice specific to your circumstances.
Technical Indicator Limitations
BZ-CAE is a technical analysis tool based on price and volume data. It does not account for:
Fundamental analysis (earnings, economic data, financial health)
Market sentiment and positioning
Geopolitical events and news
Liquidity conditions and market microstructure changes
Regulatory changes or exchange rules
Integrate with broader analysis and strategy. Do not rely solely on technical indicators for trading decisions.
Repainting Acknowledgment
As disclosed throughout this documentation:
Realtime mode may repaint on forming bars before confirmation (by design for preview functionality)
Confirmed mode has zero repainting (fully validated pivots only)
Choose timing mode appropriate for your use case. Understand the tradeoffs.
Testing Recommendation
ALWAYS test on demo/paper accounts before committing real capital. Validate the indicator's behavior on your specific instruments and timeframes. Learn the system thoroughly in Advisory mode before using Filtering mode.
Learning Resources :
In-indicator tooltips (hover over setting names for detailed explanations)
This comprehensive publishing statement (save for reference)
User guide in script comments (top of code)
Final Word — Philosophy of BZ-CAE
BZ-CAE is not designed to replace your judgment — it's designed to enhance it.
The indicator identifies structural inflection points (bifurcations) where price and momentum disagree. The Cognitive Engine evaluates market state to determine if this disagreement is meaningful or noise. The Adversarial model debates both sides of the trade to catch obvious bad setups. The Confidence system ranks quality so you can choose your risk appetite.
But YOU still execute. YOU still manage risk. YOU still learn from outcomes.
This is intelligence amplification, not intelligence replacement.
Use Advisory mode to learn how expert traders evaluate market state. Use Filtering mode to enforce discipline when emotions run high. Use the dashboard to develop a systematic approach to reading markets. Use confidence scores to size positions probabilistically.
The system provides an edge. Your job is to execute that edge with discipline, patience, and proper risk management over hundreds of trades.
Markets are probabilistic. No system wins every trade. But a systematic edge + disciplined execution + proper risk management compounds over time. That's the path to consistent profitability. BZ-CAE gives you the edge. The discipline and risk management are on you.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Inside SwingsOverview
The Inside Swings indicator identifies and visualizes "inside swing" patterns in price action. These patterns occur when price creates a series of pivots that form overlapping ranges, indicating potential consolidation or reversal zones.
What are Inside Swings?
Inside swings are specific pivot patterns where:
- HLHL Pattern: High-Low-High-Low sequence where the first high is higher than the second high, and the first low is lower than the second low
- LHLH Pattern: Low-High-Low-High sequence where the first low is lower than the second low, and the first high is higher than the second high
Here an Example
These patterns create overlapping price ranges that often act as:
- Support/Resistance zones
- Consolidation areas
- Potential reversal points
- Breakout levels
Levels From the Created Range
Input Parameters
Core Settings
- Pivot Lookback Length (default: 5): Number of bars on each side to confirm a pivot high/low
- Max Boxes (default: 100): Maximum number of patterns to display on chart
Extension Settings
- Extend Lines: Enable/disable line extensions - this extends the Extremes of the Swings to where a new Swing Started or Extended Right for the Latest Inside Swings
- Show High 1 Line: Display first high/low extension line
- Show High 2 Line: Display second high/low extension line
- Show Low 1 Line: Display first low/high extension line
- Show Low 2 Line: Display second low/high extension line
Visual Customization
Box Colors
- HLHL Box Color: Color for HLHL pattern boxes (default: green)
- HLHL Border Color: Border color for HLHL boxes
- LHLH Box Color: Color for LHLH pattern boxes (default: red)
- LHLH Border Color: Border color for LHLH boxes
Line Colors
- HLHL Line Color: Extension line color for HLHL patterns
- LHLH Line Color: Extension line color for LHLH patterns
- Line Width: Thickness of extension lines (1-5)
Pattern Detection Logic
HLHL Pattern (Bullish Inside Swing)
Condition: High1 > High2 AND Low1 < Low2
Sequence: High → Low → High → Low
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form High-Low-High-Low sequence
2. Fourth pivot (first high) > Second pivot (second high)
3. Third pivot (first low) < Last pivot (second low)
LHLH Pattern (Bearish Inside Swing)
Condition: Low1 < Low2 AND High1 > High2
Sequence: Low → High → Low → High
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form Low-High-Low-High sequence
2. Fourth pivot (first low) < Second pivot (second low)
3. Third pivot (first high) > Last pivot (second high)
Visual Elements
Boxes
- Box 1: Spans from first pivot to last pivot (larger range)
- Box 2: Spans from third pivot to last pivot (smaller range)
- Overlap: The intersection of both boxes represents the inside swing zone
Extension Lines
- High 1 Line: Horizontal line at first high/low level
- High 2 Line: Horizontal line at second high/low level
- Low 1 Line: Horizontal line at first low/high level
- Low 2 Line: Horizontal line at second low/high level
Line Extension Behavior
- Historical Patterns: Lines extend until the next pattern starts
- Latest Pattern: Lines extend to the right edge of chart
- Dynamic Updates: All lines are redrawn on each bar for accuracy
Trading Applications
Support/Resistance Levels
Inside swing levels often act as:
- Dynamic support/resistance
- Breakout confirmation levels
- Reversal entry points
Pattern Interpretation
- HLHL Patterns: Potential bullish continuation or reversal
- LHLH Patterns: Potential bearish continuation or reversal
- Overlap Zone: Key area for price interaction
Entry Strategies
1. Breakout Strategy: Enter on break above/below inside swing levels
2. Reversal Strategy: Enter on bounce from inside swing levels
3. Range Trading: Trade between inside swing levels
Technical Implementation
Data Structures
type InsideSwing
int startBar // First pivot bar
int endBar // Last pivot bar
string patternType // "HLHL" or "LHLH"
float high1 // First high/low
float low1 // First low/high
float high2 // Second high/low
float low2 // Second low/high
box box1 // First box
box box2 // Second box
line high1Line // High 1 extension line
line high2Line // High 2 extension line
line low1Line // Low 1 extension line
line low2Line // Low 2 extension line
bool isLatest // Latest pattern flag
Memory Management
- Pattern Storage: Array-based storage with automatic cleanup
- Pivot Tracking: Maintains last 4 pivots for pattern detection
- Resource Cleanup: Automatically removes oldest patterns when limit exceeded
Performance Optimization
- Duplicate Prevention: Checks for existing patterns before creation
- Efficient Redraw: Only redraws lines when necessary
- Memory Limits: Configurable maximum pattern count
Usage Tips
Best Practices
1. Combine with Volume: Use volume confirmation for breakouts
2. Multiple Timeframes: Check higher timeframes for context
3. Risk Management: Set stops beyond inside swing levels
4. Pattern Validation: Wait for confirmation before entering
Common Scenarios
- Consolidation Breakouts: Inside swings often precede significant moves
- Reversal Zones: Failed breakouts at inside swing levels
- Trend Continuation: Inside swings in trending markets
Limitations
- Lagging Indicator: Patterns form after completion
- False Signals: Not all inside swings lead to significant moves
- Market Dependent: Effectiveness varies by market conditions
Customization Options
Visual Adjustments
- Modify colors for different market conditions
- Adjust line widths for visibility
- Enable/disable specific elements
Detection Sensitivity
- Increase pivot length for smoother patterns
- Decrease for more sensitive detection
- Balance between noise and signal
Display Management
- Control maximum pattern count
- Adjust cleanup frequency
- Manage memory usage
Conclusion
The Inside Swings indicator provides a systematic approach to identifying consolidation and potential reversal zones in price action. By visualizing overlapping pivot ranges
The indicator's strength lies in its ability to:
- Identify key price levels automatically
- Provide visual context for market structure
- Offer flexible customization options
- Maintain performance through efficient memory management
[Defaust] Fractals Fractals Indicator
Overview
The Fractals Indicator is a technical analysis tool designed to help traders identify potential reversal points in the market by detecting fractal patterns. This indicator is a fork of the original fractals indicator, with adjustments made to the plotting for enhanced visual clarity and usability.
What Are Fractals?
In trading, a fractal is a pattern consisting of five consecutive bars (candlesticks) that meet specific conditions:
Up Fractal (Potential Sell Signal): Occurs when a high point is surrounded by two lower highs on each side.
Down Fractal (Potential Buy Signal): Occurs when a low point is surrounded by two higher lows on each side.
Fractals help traders identify potential tops and bottoms in the market, signaling possible entry or exit points.
Features of the Indicator
Customizable Periods (n): Allows you to define the number of periods to consider when detecting fractals, offering flexibility to adapt to different trading strategies and timeframes.
Enhanced Plotting Adjustments: This fork introduces adjustments to the plotting of fractal signals for better visual representation on the chart.
Visual Signals: Plots up and down triangles on the chart to signify down fractals (potential bullish signals) and up fractals (potential bearish signals), respectively.
Overlay on Chart: The fractal signals are overlaid directly on the price chart for immediate visualization.
Adjustable Precision: You can set the precision of the plotted values according to your needs.
Pine Script Code Explanation
Below is the Pine Script code for the Fractals Indicator:
//@version=5 indicator(" Fractals", shorttitle=" Fractals", format=format.price, precision=0, overlay=true)
// User input for the number of periods to consider for fractal detection n = input.int(title="Periods", defval=2, minval=2)
// Initialize flags for up fractal detection bool upflagDownFrontier = true bool upflagUpFrontier0 = true bool upflagUpFrontier1 = true bool upflagUpFrontier2 = true bool upflagUpFrontier3 = true bool upflagUpFrontier4 = true
// Loop through previous and future bars to check conditions for up fractals for i = 1 to n // Check if the highs of previous bars are less than the current bar's high upflagDownFrontier := upflagDownFrontier and (high < high ) // Check various conditions for future bars upflagUpFrontier0 := upflagUpFrontier0 and (high < high ) upflagUpFrontier1 := upflagUpFrontier1 and (high <= high and high < high ) upflagUpFrontier2 := upflagUpFrontier2 and (high <= high and high <= high and high < high ) upflagUpFrontier3 := upflagUpFrontier3 and (high <= high and high <= high and high <= high and high < high ) upflagUpFrontier4 := upflagUpFrontier4 and (high <= high and high <= high and high <= high and high <= high and high < high )
// Combine the flags to determine if an up fractal exists flagUpFrontier = upflagUpFrontier0 or upflagUpFrontier1 or upflagUpFrontier2 or upflagUpFrontier3 or upflagUpFrontier4 upFractal = (upflagDownFrontier and flagUpFrontier)
// Initialize flags for down fractal detection bool downflagDownFrontier = true bool downflagUpFrontier0 = true bool downflagUpFrontier1 = true bool downflagUpFrontier2 = true bool downflagUpFrontier3 = true bool downflagUpFrontier4 = true
// Loop through previous and future bars to check conditions for down fractals for i = 1 to n // Check if the lows of previous bars are greater than the current bar's low downflagDownFrontier := downflagDownFrontier and (low > low ) // Check various conditions for future bars downflagUpFrontier0 := downflagUpFrontier0 and (low > low ) downflagUpFrontier1 := downflagUpFrontier1 and (low >= low and low > low ) downflagUpFrontier2 := downflagUpFrontier2 and (low >= low and low >= low and low > low ) downflagUpFrontier3 := downflagUpFrontier3 and (low >= low and low >= low and low >= low and low > low ) downflagUpFrontier4 := downflagUpFrontier4 and (low >= low and low >= low and low >= low and low >= low and low > low )
// Combine the flags to determine if a down fractal exists flagDownFrontier = downflagUpFrontier0 or downflagUpFrontier1 or downflagUpFrontier2 or downflagUpFrontier3 or downflagUpFrontier4 downFractal = (downflagDownFrontier and flagDownFrontier)
// Plot the fractal symbols on the chart with adjusted plotting plotshape(downFractal, style=shape.triangleup, location=location.belowbar, offset=-n, color=color.gray, size=size.auto) plotshape(upFractal, style=shape.triangledown, location=location.abovebar, offset=-n, color=color.gray, size=size.auto)
Explanation:
Input Parameter (n): Sets the number of periods for fractal detection. The default value is 2, and it must be at least 2 to ensure valid fractal patterns.
Flag Initialization: Boolean variables are used to store intermediate conditions during fractal detection.
Loops: Iterate through the specified number of periods to evaluate the conditions for fractal formation.
Conditions:
Up Fractals: Checks if the current high is greater than previous highs and if future highs are lower or equal to the current high.
Down Fractals: Checks if the current low is lower than previous lows and if future lows are higher or equal to the current low.
Flag Combination: Logical and and or operations are used to combine the flags and determine if a fractal exists.
Adjusted Plotting:
The plotting of fractal symbols has been adjusted for better alignment and visual clarity.
The offset parameter is set to -n to align the plotted symbols with the correct bars.
The color and size have been fine-tuned for better visibility.
How to Use the Indicator
Adding the Indicator to Your Chart
Open TradingView:
Go to TradingView.
Access the Chart:
Click on "Chart" to open the main charting interface.
Add the Indicator:
Click on the "Indicators" button at the top.
Search for " Fractals".
Select the indicator from the list to add it to your chart.
Configuring the Indicator
Periods (n):
Default value is 2.
Adjust this parameter based on your preferred timeframe and sensitivity.
A higher value of n considers more bars for fractal detection, potentially reducing the number of signals but increasing their significance.
Interpreting the Signals
– Up Fractal (Downward Triangle): Indicates a potential price reversal to the downside. May be used as a signal to consider exiting long positions or tightening stop-loss orders.
– Down Fractal (Upward Triangle): Indicates a potential price reversal to the upside. May be used as a signal to consider entering long positions or setting stop-loss orders for short positions.
Trading Strategy Suggestions
Up Fractal Detection:
The high of the current bar (n) is higher than the highs of the previous two bars (n - 1, n - 2).
The highs of the next bars meet certain conditions to confirm the fractal pattern.
An up fractal symbol (downward triangle) is plotted above the bar at position n - n (due to the offset).
Down Fractal Detection:
The low of the current bar (n) is lower than the lows of the previous two bars (n - 1, n - 2).
The lows of the next bars meet certain conditions to confirm the fractal pattern.
A down fractal symbol (upward triangle) is plotted below the bar at position n - n.
Benefits of Using the Fractals Indicator
Early Signals: Helps in identifying potential reversal points in price movements.
Customizable Sensitivity: Adjusting the n parameter allows you to fine-tune the indicator based on different market conditions.
Enhanced Visuals: Adjustments to plotting improve the clarity and readability of fractal signals on the chart.
Limitations and Considerations
Lagging Indicator: Fractals require future bars to confirm the pattern, which may introduce a delay in the signals.
False Signals: In volatile or ranging markets, fractals may produce false signals. It's advisable to use them in conjunction with other analysis tools.
Not a Standalone Tool: Fractals should be part of a broader trading strategy that includes other indicators and fundamental analysis.
Best Practices for Using This Indicator
Combine with Other Indicators: Use in combination with trend indicators, oscillators, or volume analysis to confirm signals.
Backtesting: Before applying the indicator in live trading, backtest it on historical data to understand its performance.
Adjust Periods Accordingly: Experiment with different values of n to find the optimal setting for the specific asset and timeframe you are trading.
Disclaimer
The Fractals Indicator is intended for educational and informational purposes only. Trading involves significant risk, and you should be aware of the risks involved before proceeding. Past performance is not indicative of future results. Always conduct your own analysis and consult with a professional financial advisor before making any investment decisions.
Credits
This indicator is a fork of the original fractals indicator, with adjustments made to the plotting for improved visual representation. It is based on standard fractal patterns commonly used in technical analysis and has been developed to provide traders with an effective tool for detecting potential reversal points in the market.
Trading IQ - ICT LibraryLibrary "ICTlibrary"
Used to calculate various ICT related price levels and strategies. An ongoing project.
Hello Coders!
This library is meant for sourcing ICT related concepts. While some functions might generate more output than you require, you can specify "Lite Mode" as "true" in applicable functions to slim down necessary inputs.
isLastBar(userTF)
Identifies the last bar on the chart before a timeframe change
Parameters:
userTF (simple int) : the timeframe you wish to calculate the last bar for, must be converted to integer using 'timeframe.in_seconds()'
Returns: bool true if bar on chart is last bar of higher TF, dalse if bar on chart is not last bar of higher TF
necessaryData(atrTF)
returns necessaryData UDT for historical data access
Parameters:
atrTF (float) : user-selected timeframe ATR value.
Returns: logZ. log return Z score, used for calculating order blocks.
method gradBoxes(gradientBoxes, idColor, timeStart, bottom, top, rightCoordinate)
creates neon like effect for box drawings
Namespace types: array
Parameters:
gradientBoxes (array) : an array.new() to store the gradient boxes
idColor (color)
timeStart (int) : left point of box
bottom (float) : bottom of box price point
top (float) : top of box price point
rightCoordinate (int) : right point of box
Returns: void
checkIfTraded(tradeName)
checks if recent trade is of specific name
Parameters:
tradeName (string)
Returns: bool true if recent trade id matches target name, false otherwise
checkIfClosed(tradeName)
checks if recent closed trade is of specific name
Parameters:
tradeName (string)
Returns: bool true if recent closed trade id matches target name, false otherwise
IQZZ(atrMult, finalTF)
custom ZZ to quickly determine market direction.
Parameters:
atrMult (float) : an atr multiplier used to determine the required price move for a ZZ direction change
finalTF (string) : the timeframe used for the atr calcuation
Returns: dir market direction. Up => 1, down => -1
method drawBos(id, startPoint, getKeyPointTime, getKeyPointPrice, col, showBOS, isUp)
calculates and draws Break Of Structure
Namespace types: array
Parameters:
id (array)
startPoint (chart.point)
getKeyPointTime (int) : the actual time of startPoint, simplystartPoint.time
getKeyPointPrice (float) : the actual time of startPoint, simplystartPoint.price
col (color) : color of the BoS line / label
showBOS (bool) : whether to show label/line. This function still calculates internally for other ICT related concepts even if not drawn.
isUp (bool) : whether BoS happened during price increase or price decrease.
Returns: void
method drawMSS(id, startPoint, getKeyPointTime, getKeyPointPrice, col, showMSS, isUp, upRejections, dnRejections, highArr, lowArr, timeArr, closeArr, openArr, atrTFarr, upRejectionsPrices, dnRejectionsPrices)
calculates and draws Market Structure Shift. This data is also used to calculate Rejection Blocks.
Namespace types: array
Parameters:
id (array)
startPoint (chart.point)
getKeyPointTime (int) : the actual time of startPoint, simplystartPoint.time
getKeyPointPrice (float) : the actual time of startPoint, simplystartPoint.price
col (color) : color of the MSS line / label
showMSS (bool) : whether to show label/line. This function still calculates internally for other ICT related concepts even if not drawn.
isUp (bool) : whether MSS happened during price increase or price decrease.
upRejections (array)
dnRejections (array)
highArr (array) : array containing historical highs, should be taken from the UDT "necessaryData" defined above
lowArr (array) : array containing historical lows, should be taken from the UDT "necessaryData" defined above
timeArr (array) : array containing historical times, should be taken from the UDT "necessaryData" defined above
closeArr (array) : array containing historical closes, should be taken from the UDT "necessaryData" defined above
openArr (array) : array containing historical opens, should be taken from the UDT "necessaryData" defined above
atrTFarr (array) : array containing historical atr values (of user-selected TF), should be taken from the UDT "necessaryData" defined above
upRejectionsPrices (array) : array containing up rejections prices. Is sorted and used to determine selective looping for invalidations.
dnRejectionsPrices (array) : array containing down rejections prices. Is sorted and used to determine selective looping for invalidations.
Returns: void
method getTime(id, compare, timeArr)
gets time of inputted price (compare) in an array of data
this is useful when the user-selected timeframe for ICT concepts is greater than the chart's timeframe
Namespace types: array
Parameters:
id (array) : the array of data to search through, to find which index has the same value as "compare"
compare (float) : the target data point to find in the array
timeArr (array) : array of historical times
Returns: the time that the data point in the array was recorded
method OB(id, highArr, signArr, lowArr, timeArr, sign)
store bullish orderblock data
Namespace types: array
Parameters:
id (array)
highArr (array) : array of historical highs
signArr (array) : array of historical price direction "math.sign(close - open)"
lowArr (array) : array of historical lows
timeArr (array) : array of historical times
sign (int) : orderblock direction, -1 => bullish, 1 => bearish
Returns: void
OTEstrat(OTEstart, future, closeArr, highArr, lowArr, timeArr, longOTEPT, longOTESL, longOTElevel, shortOTEPT, shortOTESL, shortOTElevel, structureDirection, oteLongs, atrTF, oteShorts)
executes the OTE strategy
Parameters:
OTEstart (chart.point)
future (int) : future time point for drawings
closeArr (array) : array of historical closes
highArr (array) : array of historical highs
lowArr (array) : array of historical lows
timeArr (array) : array of historical times
longOTEPT (string) : user-selected long OTE profit target, please create an input.string() for this using the example below
longOTESL (int) : user-selected long OTE stop loss, please create an input.string() for this using the example below
longOTElevel (float) : long entry price of selected retracement ratio for OTE
shortOTEPT (string) : user-selected short OTE profit target, please create an input.string() for this using the example below
shortOTESL (int) : user-selected short OTE stop loss, please create an input.string() for this using the example below
shortOTElevel (float) : short entry price of selected retracement ratio for OTE
structureDirection (string) : current market structure direction, this should be "Up" or "Down". This is used to cancel pending orders if market structure changes
oteLongs (bool) : input.bool() for whether OTE longs can be executed
atrTF (float) : atr of the user-seleceted TF
oteShorts (bool) : input.bool() for whether OTE shorts can be executed
@exampleInputs
oteLongs = input.bool(defval = false, title = "OTE Longs", group = "Optimal Trade Entry")
longOTElevel = input.float(defval = 0.79, title = "Long Entry Retracement Level", options = , group = "Optimal Trade Entry")
longOTEPT = input.string(defval = "-0.5", title = "Long TP", options = , group = "Optimal Trade Entry")
longOTESL = input.int(defval = 0, title = "How Many Ticks Below Swing Low For Stop Loss", group = "Optimal Trade Entry")
oteShorts = input.bool(defval = false, title = "OTE Shorts", group = "Optimal Trade Entry")
shortOTElevel = input.float(defval = 0.79, title = "Short Entry Retracement Level", options = , group = "Optimal Trade Entry")
shortOTEPT = input.string(defval = "-0.5", title = "Short TP", options = , group = "Optimal Trade Entry")
shortOTESL = input.int(defval = 0, title = "How Many Ticks Above Swing Low For Stop Loss", group = "Optimal Trade Entry")
Returns: void (0)
displacement(logZ, atrTFreg, highArr, timeArr, lowArr, upDispShow, dnDispShow, masterCoords, labelLevels, dispUpcol, rightCoordinate, dispDncol, noBorders)
calculates and draws dispacements
Parameters:
logZ (float) : log return of current price, used to determine a "significant price move" for a displacement
atrTFreg (float) : atr of user-seleceted timeframe
highArr (array) : array of historical highs
timeArr (array) : array of historical times
lowArr (array) : array of historical lows
upDispShow (int) : amount of historical upside displacements to show
dnDispShow (int) : amount of historical downside displacements to show
masterCoords (map) : a map to push the most recent displacement prices into, useful for having key levels in one data structure
labelLevels (string) : used to determine label placement for the displacement, can be inside box, outside box, or none, example below
dispUpcol (color) : upside displacement color
rightCoordinate (int) : future time for displacement drawing, best is "last_bar_time"
dispDncol (color) : downside displacement color
noBorders (bool) : input.bool() to remove box borders, example below
@exampleInputs
labelLevels = input.string(defval = "Inside" , title = "Box Label Placement", options = )
noBorders = input.bool(defval = false, title = "No Borders On Levels")
Returns: void
method getStrongLow(id, startIndex, timeArr, lowArr, strongLowPoints)
unshift strong low data to array id
Namespace types: array
Parameters:
id (array)
startIndex (int) : the starting index for the timeArr array of the UDT "necessaryData".
this point should start from at least 1 pivot prior to find the low before an upside BoS
timeArr (array) : array of historical times
lowArr (array) : array of historical lows
strongLowPoints (array) : array of strong low prices. Used to retrieve highest strong low price and see if need for
removal of invalidated strong lows
Returns: void
method getStrongHigh(id, startIndex, timeArr, highArr, strongHighPoints)
unshift strong high data to array id
Namespace types: array
Parameters:
id (array)
startIndex (int) : the starting index for the timeArr array of the UDT "necessaryData".
this point should start from at least 1 pivot prior to find the high before a downside BoS
timeArr (array) : array of historical times
highArr (array) : array of historical highs
strongHighPoints (array)
Returns: void
equalLevels(highArr, lowArr, timeArr, rightCoordinate, equalHighsCol, equalLowsCol, liteMode)
used to calculate recent equal highs or equal lows
Parameters:
highArr (array) : array of historical highs
lowArr (array) : array of historical lows
timeArr (array) : array of historical times
rightCoordinate (int) : a future time (right for boxes, x2 for lines)
equalHighsCol (color) : user-selected color for equal highs drawings
equalLowsCol (color) : user-selected color for equal lows drawings
liteMode (bool) : optional for a lite mode version of an ICT strategy. For more control over drawings leave as "True", "False" will apply neon effects
Returns: void
quickTime(timeString)
used to quickly determine if a user-inputted time range is currently active in NYT time
Parameters:
timeString (string) : a time range
Returns: true if session is active, false if session is inactive
macros(showMacros, noBorders)
used to calculate and draw session macros
Parameters:
showMacros (bool) : an input.bool() or simple bool to determine whether to activate the function
noBorders (bool) : an input.bool() to determine whether the box anchored to the session should have borders
Returns: void
po3(tf, left, right, show)
use to calculate HTF po3 candle
@tip only call this function on "barstate.islast"
Parameters:
tf (simple string)
left (int) : the left point of the candle, calculated as bar_index + left,
right (int) : :the right point of the candle, calculated as bar_index + right,
show (bool) : input.bool() whether to show the po3 candle or not
Returns: void
silverBullet(silverBulletStratLong, silverBulletStratShort, future, userTF, H, L, H2, L2, noBorders, silverBulletLongTP, historicalPoints, historicalData, silverBulletLongSL, silverBulletShortTP, silverBulletShortSL)
used to execute the Silver Bullet Strategy
Parameters:
silverBulletStratLong (simple bool)
silverBulletStratShort (simple bool)
future (int) : a future time, used for drawings, example "last_bar_time"
userTF (simple int)
H (float) : the high price of the user-selected TF
L (float) : the low price of the user-selected TF
H2 (float) : the high price of the user-selected TF
L2 (float) : the low price of the user-selected TF
noBorders (bool) : an input.bool() used to remove the borders from box drawings
silverBulletLongTP (series silverBulletLevels)
historicalPoints (array)
historicalData (necessaryData)
silverBulletLongSL (series silverBulletLevels)
silverBulletShortTP (series silverBulletLevels)
silverBulletShortSL (series silverBulletLevels)
Returns: void
method invalidFVGcheck(FVGarr, upFVGpricesSorted, dnFVGpricesSorted)
check if existing FVGs are still valid
Namespace types: array
Parameters:
FVGarr (array)
upFVGpricesSorted (array) : an array of bullish FVG prices, used to selective search through FVG array to remove invalidated levels
dnFVGpricesSorted (array) : an array of bearish FVG prices, used to selective search through FVG array to remove invalidated levels
Returns: void (0)
method drawFVG(counter, FVGshow, FVGname, FVGcol, data, masterCoords, labelLevels, borderTransp, liteMode, rightCoordinate)
draws FVGs on last bar
Namespace types: map
Parameters:
counter (map) : a counter, as map, keeping count of the number of FVGs drawn, makes sure that there aren't more FVGs drawn
than int FVGshow
FVGshow (int) : the number of FVGs to show. There should be a bullish FVG show and bearish FVG show. This function "drawFVG" is used separately
for bearish FVG and bullish FVG.
FVGname (string) : the name of the FVG, "FVG Up" or "FVG Down"
FVGcol (color) : desired FVG color
data (FVG)
masterCoords (map) : a map containing the names and price points of key levels. Used to define price ranges.
labelLevels (string) : an input.string with options "Inside", "Outside", "Remove". Determines whether FVG labels should be inside box, outside,
or na.
borderTransp (int)
liteMode (bool)
rightCoordinate (int) : the right coordinate of any drawings. Must be a time point.
Returns: void
invalidBlockCheck(bullishOBbox, bearishOBbox, userTF)
check if existing order blocks are still valid
Parameters:
bullishOBbox (array) : an array declared using the UDT orderBlock that contains bullish order block related data
bearishOBbox (array) : an array declared using the UDT orderBlock that contains bearish order block related data
userTF (simple int)
Returns: void (0)
method lastBarRejections(id, rejectionColor, idShow, rejectionString, labelLevels, borderTransp, liteMode, rightCoordinate, masterCoords)
draws rejectionBlocks on last bar
Namespace types: array
Parameters:
id (array) : the array, an array of rejection block data declared using the UDT rejection block
rejectionColor (color) : the desired color of the rejection box
idShow (int)
rejectionString (string) : the desired name of the rejection blocks
labelLevels (string) : an input.string() to determine if labels for the block should be inside the box, outside, or none.
borderTransp (int)
liteMode (bool) : an input.bool(). True = neon effect, false = no neon.
rightCoordinate (int) : atime for the right coordinate of the box
masterCoords (map) : a map that stores the price of key levels and assigns them a name, used to determine price ranges
Returns: void
method OBdraw(id, OBshow, BBshow, OBcol, BBcol, bullishString, bearishString, isBullish, labelLevels, borderTransp, liteMode, rightCoordinate, masterCoords)
draws orderblocks and breaker blocks for data stored in UDT array()
Namespace types: array
Parameters:
id (array) : the array, an array of order block data declared using the UDT orderblock
OBshow (int) : the number of order blocks to show
BBshow (int) : the number of breaker blocks to show
OBcol (color) : color of order blocks
BBcol (color) : color of breaker blocks
bullishString (string) : the title of bullish blocks, which is a regular bullish orderblock or a bearish orderblock that's converted to breakerblock
bearishString (string) : the title of bearish blocks, which is a regular bearish orderblock or a bullish orderblock that's converted to breakerblock
isBullish (bool) : whether the array contains bullish orderblocks or bearish orderblocks. If bullish orderblocks,
the array will naturally contain bearish BB, and if bearish OB, the array will naturally contain bullish BB
labelLevels (string) : an input.string() to determine if labels for the block should be inside the box, outside, or none.
borderTransp (int)
liteMode (bool) : an input.bool(). True = neon effect, false = no neon.
rightCoordinate (int) : atime for the right coordinate of the box
masterCoords (map) : a map that stores the price of key levels and assigns them a name, used to determine price ranges
Returns: void
FVG
UDT for FVG calcualtions
Fields:
H (series float) : high price of user-selected timeframe
L (series float) : low price of user-selected timeframe
direction (series string) : FVG direction => "Up" or "Down"
T (series int) : => time of bar on user-selected timeframe where FVG was created
fvgLabel (series label) : optional label for FVG
fvgLineTop (series line) : optional line for top of FVG
fvgLineBot (series line) : optional line for bottom of FVG
fvgBox (series box) : optional box for FVG
labelLine
quickly pair a line and label together as UDT
Fields:
lin (series line) : Line you wish to pair with label
lab (series label) : Label you wish to pair with line
orderBlock
UDT for order block calculations
Fields:
orderBlockData (array) : array containing order block x and y points
orderBlockBox (series box) : optional order block box
vioCount (series int) : = 0 violation count of the order block. 0 = Order Block, 1 = Breaker Block
traded (series bool)
status (series string) : = "OB" status == "OB" => Level is order block. status == "BB" => Level is breaker block.
orderBlockLab (series label) : options label for the order block / breaker block.
strongPoints
UDT for strong highs and strong lows
Fields:
price (series float) : price of the strong high or strong low
timeAtprice (series int) : time of the strong high or strong low
strongPointLabel (series label) : optional label for strong point
strongPointLine (series line) : optional line for strong point
overlayLine (series line) : optional lines for strong point to enhance visibility
overlayLine2 (series line) : optional lines for strong point to enhance visibility
displacement
UDT for dispacements
Fields:
highPrice (series float) : high price of displacement
lowPrice (series float) : low price of displacement
timeAtPrice (series int) : time of bar where displacement occurred
displacementBox (series box) : optional box to draw displacement
displacementLab (series label) : optional label for displacement
po3data
UDT for po3 calculations
Fields:
dHigh (series float) : higher timeframe high price
dLow (series float) : higher timeframe low price
dOpen (series float) : higher timeframe open price
dClose (series float) : higher timeframe close price
po3box (series box) : box to draw po3 candle body
po3line (array) : line array to draw po3 wicks
po3Labels (array) : label array to label price points of po3 candle
macros
UDT for session macros
Fields:
sessions (array) : Array of sessions, you can populate this array using the "quickTime" function located above "export macros".
prices (matrix) : Matrix of session data -> open, high, low, close, time
sessionTimes (array) : Array of session names. Pairs with array sessions.
sessionLines (matrix) : Optional array for sesion drawings.
OTEtimes
UDT for data storage and drawings associated with OTE strategy
Fields:
upTimes (array) : time of highest point before trade is taken
dnTimes (array) : time of lowest point before trade is taken
tpLineLong (series line) : line to mark tp level long
tpLabelLong (series label) : label to mark tp level long
slLineLong (series line) : line to mark sl level long
slLabelLong (series label) : label to mark sl level long
tpLineShort (series line) : line to mark tp level short
tpLabelShort (series label) : label to mark tp level short
slLineShort (series line) : line to mark sl level short
slLabelShort (series label) : label to mark sl level short
sweeps
UDT for data storage and drawings associated with liquidity sweeps
Fields:
upSweeps (matrix) : matrix containing liquidity sweep price points and time points for up sweeps
dnSweeps (matrix) : matrix containing liquidity sweep price points and time points for down sweeps
upSweepDrawings (array) : optional up sweep box array. Pair the size of this array with the rows or columns,
dnSweepDrawings (array) : optional up sweep box array. Pair the size of this array with the rows or columns,
raidExitDrawings
UDT for drawings associated with the Liquidity Raid Strategy
Fields:
tpLine (series line) : tp line for the liquidity raid entry
tpLabel (series label) : tp label for the liquidity raid entry
slLine (series line) : sl line for the liquidity raid entry
slLabel (series label) : sl label for the liquidity raid entry
m2022
UDT for data storage and drawings associated with the Model 2022 Strategy
Fields:
mTime (series int) : time of the FVG where entry limit order is placed
mIndex (series int) : array index of FVG where entry limit order is placed. This requires an array of FVG data, which is defined above.
mEntryDistance (series float) : the distance of the FVG to the 50% range. M2022 looks for the fvg closest to 50% mark of range.
mEntry (series float) : the entry price for the most eligible fvg
fvgHigh (series float) : the high point of the eligible fvg
fvgLow (series float) : the low point of the eligible fvg
longFVGentryBox (series box) : long FVG box, used to draw the eligible FVG
shortFVGentryBox (series box) : short FVG box, used to draw the eligible FVG
line50P (series line) : line used to mark 50% of the range
line100P (series line) : line used to mark 100% (top) of the range
line0P (series line) : line used to mark 0% (bottom) of the range
label50P (series label) : label used to mark 50% of the range
label100P (series label) : label used to mark 100% (top) of the range
label0P (series label) : label used to mark 0% (bottom) of the range
sweepData (array)
silverBullet
UDT for data storage and drawings associated with the Silver Bullet Strategy
Fields:
session (series bool)
sessionStr (series string) : name of the session for silver bullet
sessionBias (series string)
sessionHigh (series float) : = high high of session // use math.max(silverBullet.sessionHigh, high)
sessionLow (series float) : = low low of session // use math.min(silverBullet.sessionLow, low)
sessionFVG (series float) : if applicable, the FVG created during the session
sessionFVGdraw (series box) : if applicable, draw the FVG created during the session
traded (series bool)
tp (series float) : tp of trade entered at the session FVG
sl (series float) : sl of trade entered at the session FVG
sessionDraw (series box) : optional draw session with box
sessionDrawLabel (series label) : optional label session with label
silverBulletDrawings
UDT for trade exit drawings associated with the Silver Bullet Strategy
Fields:
tpLine (series line) : tp line drawing for strategy
tpLabel (series label) : tp label drawing for strategy
slLine (series line) : sl line drawing for strategy
slLabel (series label) : sl label drawing for strategy
unicornModel
UDT for data storage and drawings associated with the Unicorn Model Strategy
Fields:
hPoint (chart.point)
hPoint2 (chart.point)
hPoint3 (chart.point)
breakerBlock (series box) : used to draw the breaker block required for the Unicorn Model
FVG (series box) : used to draw the FVG required for the Unicorn model
topBlock (series float) : price of top of breaker block, can be used to detail trade entry
botBlock (series float) : price of bottom of breaker block, can be used to detail trade entry
startBlock (series int) : start time of the breaker block, used to set the "left = " param for the box
includes (array) : used to store the time of the breaker block, or FVG, or the chart point sequence that setup the Unicorn Model.
entry (series float) : // eligible entry price, for longs"math.max(topBlock, FVG.get_top())",
tpLine (series line) : optional line to mark PT
tpLabel (series label) : optional label to mark PT
slLine (series line) : optional line to mark SL
slLabel (series label) : optional label to mark SL
rejectionBlocks
UDT for data storage and drawings associated with rejection blocks
Fields:
rejectionPoint (chart.point)
bodyPrice (series float) : candle body price closest to the rejection point, for "Up" rejections => math.max(open, close),
rejectionBox (series box) : optional box drawing of the rejection block
rejectionLabel (series label) : optional label for the rejection block
equalLevelsDraw
UDT for data storage and drawings associated with equal highs / equal lows
Fields:
connector (series line) : single line placed at the first high or low, y = avgerage of distinguished equal highs/lows
connectorLab (series label) : optional label to be placed at the highs or lows
levels (array) : array containing the equal highs or lows prices
times (array) : array containing the equal highs or lows individual times
startTime (series int) : the time of the first high or low that forms a sequence of equal highs or lows
radiate (array) : options label to "radiate" the label in connector lab. Can be used for anything
necessaryData
UDT for data storage of historical price points.
Fields:
highArr (array) : array containing historical high points
lowArr (array) : array containing historical low points
timeArr (array) : array containing historical time points
logArr (array) : array containing historical log returns
signArr (array) : array containing historical price directions
closeArr (array) : array containing historical close points
binaryTimeArr (array) : array containing historical time points, uses "push" instead of "unshift" to allow for binary search
binaryCloseArr (array) : array containing historical close points, uses "push" instead of "unshift" to allow the correct
binaryOpenArr (array) : array containing historical optn points, uses "push" instead of "unshift" to allow the correct
atrTFarr (array) : array containing historical user-selected TF atr points
openArr (array) : array containing historical open points
