Daily Separator_Yoot HobbizSimply helps you separate each trading day — a clean, visual indicator that marks daily sessions so you can read price action faster and stay focused on what really matters.
A simple indicator that clearly separates each trading day, making your charts easier to read and your decisions easier to take.
Cerca negli script per "TAKE"
Macketings 1min ScalpingThis is a hyper-reactive scalping strategy designed for the 1-minute chart. It utilizes a strict four-EMA hierarchy (80/90/340/500) to ensure trades are only taken in the strongest aligned market trend. The strategy is built to be extremely tight on risk and focuses on capturing the immediate, high-momentum swing that follows a confirmed EMA retest or breakout.
Key Mechanics (How it Works):
Strict Trend Alignment: Entry is only permitted when the faster EMA band (80/90) and the price action are correctly aligned with the slow trend (340/500).
Long: EMA 80/90 must be above EMA 340/500, AND EMA 340 must be above EMA 500. (And vice-versa for Short.)
Expanded Retest Entry: The strategy waits for the price to retest or briefly enter the 80/90 band, then immediately enters upon the confirmed momentum breakout from that band.
Dynamic Risk Management (Tight Ride): The strategy is engineered to ride the wave aggressively while protecting capital immediately:
Extremely Tight Initial Stop Loss (0.2% default): Limits initial risk instantly.
Break-Even Security: Once profit hits 0.3%, the Stop Loss is automatically trailed to secure 0.2% profit (a risk-free trade).
Aggressive Exit Logic: Positions are closed not only upon hitting the Take Profit target (2.5%) but also immediately if the 80/90 EMA band crosses the 340 EMA, signaling a critical loss of momentum.
Disclaimer:
This strategy requires high-liquidity instruments and is best used on low timeframes (1-minute) due to its dependency on fast momentum shifts and tight stops. Backtesting and forward testing are crucial before deployment.
Reversal Correlation Pressure [OmegaTools]Reversal Correlation Pressure is a quantitative regime-detection and signal-filtering framework designed to enhance both reversal timing and breakout validation across intraday and multi-session markets.
It is built for discretionary and systematic traders who require a statistically grounded filter capable of adapting to changing market conditions in real time.
1. Purpose and Overview
Market conditions constantly rotate through phases of expansion, contraction, trend persistence, and noise-driven mean reversion. Many strategies break down not because the signal is wrong, but because the regime is unsuitable.
This indicator solves that structural problem.
The tool measures the evolving correlation relationship between highs and lows — a robust proxy for how “organized” or “fragmented” price discovery currently is — and transforms it into a regime pressure reading. This reading is then used as the core variable to validate or filter reversal and breakout opportunities.
Combined with an internal performance-based filter that learns from its past signals, the indicator becomes a dynamic decision engine: it highlights only the signals that statistically perform best under the current market regime.
2. Core Components
2.1 Correlation-Based Regime Mapping
The relationship between highs and lows contains valuable information about market structure:
High correlation generally corresponds to coherent, directional markets where momentum and breakouts tend to prevail.
Low or unstable correlation often appears in overlapping, rotational phases where price oscillates and mean-reversion behavior dominates.
The indicator continuously evaluates this correlation, normalizes it statistically, and displays it as a pressure histogram:
Higher values indicate regimes favorable to trend continuation or momentum breakouts.
Lower values indicate regimes where reversals, pullbacks, and fade setups historically perform better.
This regime mapping is the foundation upon which the adaptive filter operates.
2.2 Reversal Stress & Breakout Stress Signaling
Raw directional opportunities are identified using statistically significant deviations from short-term equilibrium (overbought/oversold dynamics).
However, unlike traditional mean-reversion or breakout tools, signals here are not automatically taken. They must first be validated by the regime framework and then compared against the performance of similar past setups.
This dual evaluation sharply reduces the noise associated with reversal attempts during strong trends, while also preventing breakout attempts during choppy, anti-directional conditions.
2.3 Adaptive Regime-Selection Backtester
A key innovation of this indicator is its embedded micro-backtester, which continuously tracks how reversal or breakout signals have performed under each correlation regime.
The system evaluates two competing hypotheses:
Signals perform better during high-correlation regimes.
Signals perform better during low-correlation or neutral regimes.
For each new trigger, the indicator looks back at a rolling sample of past setups and measures short-term performance under both regimes. It then automatically selects the regime that currently demonstrates the superior historical edge.
In other words, the indicator:
Learns from recent market behavior
Determines which regime supports reversals
Determines which regime supports breakouts
Applies the optimal filter in real time
Highlights only the signals that historically outperformed under similar conditions
This creates a dynamic, statistically supervised approach to signal filtering — a substantial improvement over static or fixed-threshold systems.
2.4 Visual Components
To support rapid decision-making:
Correlation Pressure Histogram:
Encodes regime strength through a gradient-based color system, transitioning from neutral contexts into strong structural phases.
Directional Markers:
Visual arrows appear when a signal passes all filters and conditions.
Bar Coloring:
Bars can optionally be recolored to reflect active bullish or bearish bias after the adaptive filter approves a signal.
These components integrate seamlessly to give the trader a concise but complete view of the underlying conditions.
3. How to Use This Indicator
3.1 Identifying Regimes
The histogram is the anchor:
High, brightly colored columns suggest trend-friendly behavior where breakout alignment and directional follow-through have historically been stronger.
Low or muted columns suggest mean-reversion contexts where counter-trend opportunities and reversal setups gain reliability.
3.2 Filtering Signals
The indicator automatically decides whether a reversal or breakout trigger should be respected based on:
the current correlation regime,
the learned performance of recent signals under similar conditions, and
the directional stress detected in price.
The user does not need to adjust anything manually.
3.3 Integration with Other Tools
This indicator works best when combined with:
VWAP or session levels
Market internals and breadth metrics
Volume, order flow, or delta-based tools
Local structural frameworks (support/resistance, liquidity highs and lows)
Its strength is in telling you when your other signals matter and when they should be ignored.
4. Strengths of the Framework
Automatically adapts to changing micro-regimes
Reduces false reversals during strong trends
Avoids false breakouts in overlapping, rotational markets
Learns from recent historical performance
Provides a statistically driven confirmation layer
Works on all liquid assets and timeframes
Suitable for both discretionary and automated environments
5. Disclaimer
This indicator is provided strictly for educational and analytical purposes.
It does not constitute trading advice, investment guidance, or a recommendation to buy or sell any financial instrument.
Past performance of any statistical filter or adaptive method does not guarantee future results.
All trading involves significant risk, and users are responsible for their own decisions and risk management.
By using this indicator, you acknowledge that you are fully responsible for your trading activity.
Golden BOS Strategy - ChecklistA clean, mechanical on-chart checklist designed for multi-timeframe traders using the Golden BOS / Institutional Retracement Framework.
This tool helps you stay disciplined by tracking each requirement of the strategy in real time:
Included Criteria
4H Bias: Bullish or bearish macro structure
1H Structure: Push/pull phase + golden zone retracement
5M Entry Model:
Break of Structure (BOS)
5M golden zone retracement
POI validation (OB/FVG/Breaker)
Final micro BOS or rejection confirmation
Risk Filters:
Session validity (London / NY)
Red news avoidance
Stop-loss placement check
Liquidity-based target confirmation
Purpose
This overlay ensures every trade meets strict criteria before execution, removing emotion and improvisation. Ideal for backtesting, forward testing, and staying consistent during live market conditions.
Golden BOS Strategy — Description
The Golden BOS Strategy is a structured, multi-timeframe trading system designed to capture high-probability continuation moves during London and New York sessions. The strategy combines institutional concepts with Fibonacci-based retracements to identify discounted entry zones aligned with higher-timeframe direction.
Using the 4H timeframe, traders establish the daily macro bias and identify the dominant trend. The 1H chart is then used to confirm the current phase of market structure, distinguishing between impulsive “push” moves and corrective “pullback” phases. A Fibonacci retracement is applied to the most recent 1H impulse leg to define a high-value discount or premium zone where entries become valid.
Execution takes place on the 5-minute chart. Once price reaches the 1H golden zone (61.8–78.6%), a Break of Structure (BOS) is required to confirm a shift in short-term momentum. A second Fibonacci retracement is then drawn on the 5M impulse leg that caused the BOS, and price must retrace back into the 5M golden zone. Traders refine their entry using a confluence point of interest (POI) such as a Fair Value Gap (FVG), Order Block, Breaker Block, or Inverse FVG, ideally accompanied by a final micro BOS or rejection candle.
Risk management is strict and rule-driven. Stop loss is placed beyond the extreme wick of the POI, while take-profit targets are set at logical liquidity pools in the direction of the higher-timeframe trend. The strategy avoids red-folder news and only allows trades during active sessions to ensure optimal volatility and reliability.
The Golden BOS Strategy is designed to impose discipline, reduce discretionary errors, and give traders a repeatable, mechanical framework for navigating trending markets with precision.
cd_sfp_CxGeneral:
This indicator is designed to assist users who trade the Swing Failure Pattern ( SFP ).
In technical literature (various definitions exist), an SFP is a situation where the price violates a previous swing level but fails to close beyond that level.
• (Liquidity Sweep)
• (Buyer or seller dominance)
• (Stop hunt)
• (Turtle Soup)
The general strategy is built upon seeking trade opportunities after an SFP is formed and conviction is established that the market direction has changed.
Components used to gather confirmation:
• Determining Bias: Periodic SAR
• Obtaining Breakout/Reversal Confirmation: Change in State Delivery (CISD)
• Defining the Buyer/Seller Block (Supply/Demand Zones): Mitg Blocks (Mitigation Blocks), FVG (Fair Value Gaps), and Standard Deviation Projection
• Key Levels: Previous HTF (Higher Time Frame) levels
• Setting Targets: Standard Deviation Projection
• Trade Management: Anchored VWAP and opposing blocks
• Time-Based Context: Session Killzone times
• Notifications: An alarm/alert system will be utilized to stay informed.
________________________________________
Details:
Swing and Swing Failure Pattern:
Swing Sweep Types (Liquidity Sweep):
1. Single
2. Consecutive (The liquidity of the entity that swept the liquidity is being swept)
Bias Determination
We need to filter out the numerous SFPs that occur across all time frames. Our first strong filter will be the Bias. We will only look for trades aligned with our bias.
We will use Periodic SAR (Stop and Reverse) to determine the bias. We compare the price with the SAR value from a Higher Time Frame than the one we are trading on.
• Price > SAR => Bullish Bias
• Price < SAR => Bearish Bias
Depending on the pair, H1 SAR may be chosen for scalp trades, and Daily/Weekly SAR for intraday and swing trades.
Key Levels
Strategies looking for trades after a liquidity grab generally state that the sweep / stop hunt movement should occur at a significant price level.
The most fundamental Key Level levels are (User can customize):
• Previous Week High & Low
• Previous Day High & Low
• Previous H4 High & Low
• Previous H1 High & Low
• Asia Killzone High & Low
• London Killzone High & Low
• New York Killzone High & Low
• Monday Range High & Low values
We will prefer SFP formations that occur when these levels are swept. When Key Levels are violated, an information label appears on the screen.
Blocks / Zones
To strengthen our hand, we will use three types of blocks/zones, either with Key Levels or separately. When an SFP structure is formed in these areas (along with bias and breakout confirmation), our expectation is for the price to continue in our desired direction. These regions are:
1. Mitigation Blocks (Mtg)
o (Details can be found in the cd_VWAP_mtg_Cx indicator)
o In short: A second candle, following a bullish candle, crosses its high but fails to close above it. We call this a sweep / SFP. When the price, which was expected to go to the low, instead makes a new high/close, an Mtg block is formed. (Buyers are dominant)
2. FVGs (Fair Value Gaps)
o We use classic FVG structures.
3. Standard Deviation Projection Boxes
o When we get an SFP structure + breakout confirmation (CISD), we use the Standard Deviation Projection to determine our profit-taking and take-profit levels.
o Based on the idea that the price often respects the range between -2 and -2.5 of the projection values, we box this range and use it as our area of interest. (Our expectation is for the price to reverse after reaching this target).
o Let's mark it on the chart.
Confirmation
To summarize what has been explained so far: we look for the price to form an SFP structure in levels/zones we deem important, aligned with our bias, and for the breakout to be confirmed with a CISD.
No single component is strong on its own, but the success rate increases when they occur together.
We observe the following as additional confirmation along with the CISD: a new Mtg block forming in the direction of the breakout, high-volume movement (with FVG and a large body), and respect for VWAPs, the resistance/support line, and the defense block.
Additional Confirmations with Breakouts:
• Defence block, new mtg and VWAP
• Resistance / Support Line:
Indicator Signals
The indicator marks all formed sweeps, selected key levels, blocks, the projection, and CISD confirmations on the screen. The candle where the CISD confirmation occurs is indicated by an arrow.
• Arrows with double short lines signify a CISD that follows an SFP occurring at a Key Level.
• All other CISD candle indications are shown with single-line arrows.
Trade Management
When selecting profit targets in trades (preferably), the projection, opposing blocks, and structures that have formed are taken into account. Do not neglect to look at the structures that have formed against you when entering a trade.
Menu Settings:
• For Mtg blocks, the trading timeframe or a higher timeframe can be selected.
• FVGs formed in the current timeframe are displayed when the price creates an SFP (in "Fvg" option).
• Deviation boxes are displayed when the price creates an SFP (in box).
• The SAR HTF setting (H1) for scalp trades may vary depending on the pair. Users trying trades on higher timeframes should increase the HTF setting.
o Example: If you are looking for a trade with an SFP structure on H1, the SAR HTF setting should be H4 or higher.
• VWAP lines are refreshed starting from the candle that executed the sweep when the price forms an SFP. The only setting to adjust is the source selection setting (hlc3 is selected).
• Time frames and Killzone / Special Zone settings for Key Levels can be changed/should be checked.
Alarms / Alerts:
The conditions that will trigger an alert can be selected from the menu.
• To receive an alert aligned with the bias, the "Alignment with bias" checkbox must be selected.
• The alert should be set on the timeframe where you plan to enter the trade.
• The display options do not affect the alarm conditions. (Example: FVGs are monitored even when the menu selection is "off").
• If the necessary conditions are met, the alarm is triggered on the new candle that opens after the CISD confirmation.
• The alarm will not be triggered more than once at the same Key Level.
The user can preferably select alerts:
• Bias-aligned or Bias-independent
• Sweep (without waiting for CISD)
• Sweep + CISD (without looking for other conditions)
• Sweep + Key Level + CISD (the swept level is a Key Level)
• Sweep + Mtg / Fvg / Dev. + CISD (SFP formed in any of the blocks)
• Sweep + Mtg + CISD (SFP formed in the Mtg block)
• Sweep + Fvg + CISD (SFP formed inside the FVG)
• Sweep + Deviation Box + CISD (SFP formed inside the Dev. Box)
• Sweep + Key Level + Mtg / Fvg / Dev. + CISD (SFP formed simultaneously at a Key Level and any of the blocks)
Trade Example:
• Conditions: Bias-aligned + Sweep + Mtg/Fvg/Dev (at least one) + CISD
• Extra Confirmations: Respect for the Defense Block + Respect for VWAP
• Target (TP): Projection between -2 and -2.5
I welcome your thoughts and suggestions regarding my indicator, which I believe will be successful in the long run by adhering to uncompromising risk management and a strict trading plan.
Happy Trading!
Put Option Profits inspired by Travis Wilkerson; SPX BacktesterPut Option Profits — Travis Wilkerson inspired. This tester evaluates a simple monthly SPX at-the-money credit-spread timing idea: enter on a fixed calendar rule (e.g., 1st Friday or 8th day with business-day shifting) at Open or Close, then exit exactly N calendar days later (first tradable day >= target, at Close). A trade is marked WIN if price at exit is above the entry price (1:1 risk proxy).
The book suggests forward testing 60-day and 180-day expirations to prove the concept. This tool lets you backtest both (and more) to see what actually works best. In the book, profits are taken when the spread reaches ~80% of max credit; losers are left to expire and cash-settle. This backtester does not model early profit-taking—every trade is held to the configured hold period and evaluated on price vs entry at the exit close. Think of it as a pure “set it and forget it” stress test. In live trading, you can still follow Travis’s 80% take-profit rule; TradingView just doesn’t simulate that here. Happy trading!
Features:
Schedule: Day-of-Month (with Prev/Next business-day shift, optional “stay in month”) or Nth Weekday (e.g., 1st Friday).
Entry timing: Open or Close.
Exit: N calendar days later at Close (holiday/weekend aware).
Filters: Optional EMA-200 “risk-on” filter.
Scope: Date range limiter.
Visuals: Entry/exit bubbles (paired colors) or simple win/loss dots.
Table: Overall Win% and N (within range).
Alerts: Entry alert (static condition + dynamic alert() message).
How to use:
[* ]Choose Start Mode (NthWeekday or DayOfMonth) and parameters (e.g., 1st Friday or DOM=8, PrevBizDay).
Pick Entry Timing (Open or Close).
Set Days In Trade (e.g., 150).
(Optional) Enable EMA filter and set Date Range.
Turn Bubbles on/off and/or Dots on/off.
Create alert:
Simple ping: Condition = this indicator -> Monthly Entry Signal -> “Once per bar” (Open) or “Once per bar close” (Close).
Rich message: Condition = this indicator -> Any alert() function call.
Notes:
Keep DOM shift in same month: when a DOM falls on a weekend/holiday, PrevBizDay/NextBizDay shift will stay inside the month if enabled; otherwise it can spill into the prior/next month. (Ignored for NthWeekday.)
Credits: Concept sparked by “Put Option Profits – How to turn ten minutes of free time into consistent cash flow each month” by Travis Wilkerson; this script is a neutral research tool (not financial advice).
週一普跌策略 Monday shit Strategy Strategy Description / 策略敘述
EN
This strategy takes a short position at the start of each Monday, based on the hypothesis that cryptocurrency markets tend to experience post-weekend risk-off behavior.
The system enters a full-equity short position at the Tokyo open (Taipei 08:00), aiming to capture Monday downside pressure resulting from accumulated weekend information and macro sentiment adjustments when traditional financial markets reopen.
Risk management uses fixed percentage take-profit and stop-loss levels, emphasizing asymmetric reward-to-risk (large occasional gains, small frequent losses).
The model reflects the increasing alignment between crypto price behavior and traditional financial market cycles.
ZH-TW
本策略於每週一開盤時做空，基於假設加密資產在週末後具有風險釋放與補跌傾向。
系統會在台北時間早上 08:00 以全倉做空，目標捕捉因週末累積消息與傳統金融市場重新開盤所造成的下跌壓力。
風控採固定止盈、止損百分比，強調高報酬／低風險的不對稱結構（小虧多次、偶爾大賺）。
此模型反映加密貨幣市場行為與華爾街週期愈趨一致的市場現象。
NEXT GEN INSPIRED BY OLIVER VELEZDYOR NFA
1. Initial Setup & Application
Load the Strategy to your desired chart (e.g., EURUSD M5, as suggested by the script's backtest).
Overlay: Ensure the script is set to overlay=true (which it is) so the signals and Moving Averages plot directly on the price chart.
Equity Management: Review the initial strategy settings for capital and position sizing:
Initial Capital: Defaults to 10,000.
Default Qty Type: Set to strategy.percent_of_equity (22%), meaning 22% of your available equity is used per trade. Adjust this percentage based on your personal risk tolerance.
2. Reviewing Key Indicator Inputs
The script uses default values that are optimized, but you can adjust them in the settings panel:
Fast EMA: Defaults to 9 (e.g., a 9-period Exponential Moving Average).
Slow EMA: Defaults to 21 (e.g., a 21-period Exponential Moving Average). These EMAs define the short-term trend.
ATR: Defaults to 14 (Average True Range). Used to dynamically calculate volatility for SL/TP distances.
Final R:R: Defaults to 4.5 (minimum R:R required for a signal). This is the core of the strategy's high reward goal.
3. Interpreting Entry Signals
A trade signal is generated only when all conditions—EMA trend, "Elephant Logic" momentum, and non-ranging market—are met.
Long Signal: Appears as a green triangle (▲) below the bar, labeled "COMBO".
Short Signal: Appears as a red triangle (▼) above the bar, labeled "COMBO".
Live Plan: Upon signal, a detailed label is immediately plotted on the chart showing the FULL BATTLE PLAN:
SL: Calculated Stop Loss price.
TP: Calculated Take Profit price (based on the Final R:R).
Risk/Reward Pips: The calculated pips for the trade's risk and reward.
R:R = 1:4.5: The exact Risk-to-Reward ratio.
4. Understanding Market Conditions & Visuals
The script provides visuals to help you understand the current market state:
Trend EMAs: The 9 EMA (green) and 21 EMA (purple/magenta) are plotted to show the underlying trend.
Long trades only fire when Price > 9 EMA > 21 EMA.
Short trades only fire when Price < 9 EMA < 21 EMA.
Ranging Market (Rejection): Bars turn a light gray/silver when the proprietary "Reject Ranging" logic is active, indicating a low-volatility period. No new trades will be taken during these bars.
Momentum Bar: Bars turn a gold/yellow color when the "Elephant Logic" (high-momentum, large-body candles over 2-3 periods) is detected, highlighting powerful price movement.
5. Execution and Exit Logic
The strategy handles entry, scaling, and exit automatically:
Entry: A market order is placed (strategy.entry) immediately upon the bar where the longSetup or shortSetup condition is met.
Scaling Out (+1R): If the trade moves favorably by an amount equal to the initial risk (1R), the script closes a portion of the position (strategy.close with comment "+1R"). This partial exit locks in profit equivalent to the initial risk.
Re-entry (Pyramiding): After the +1R exit, the strategy attempts a re-entry (LONG RE/SHORT RE diamond plot) if the price meets certain criteria near the 9 EMA, trying to capitalize on further trend continuation.
Final Exits:
Take Profit: A limit order is set at the calculated TP level (stopDist * minRR).
Stop Loss: A stop order is set at the calculated SL level (stopDist * 1.3), slightly wider than the initial SL distance, likely to account for spread/slippage, ensuring the maximum loss is defined.
Trailing Stop: A trailing stop is applied to the re-entry positions (LONG RE/SHORT RE) to protect profits as the market moves further in the direction of the trade.
Confirmed Momentum QQQ (RSI/MACD Filter)Gemini and Myself,
How This Targets a Higher Win Rate
The key to the win rate increase is the RSI 20/80 filter.
Long Signal: A long entry is now only taken if the trend is up (SMA cross), the MACD is bullish, and the RSI is not overbought (below 80). By only entering when momentum is not yet exhausted, you increase the chance that the price can travel far enough to hit your 4.0 point Take Profit.
Wider SL: The wider Stop Loss of 2.5 points reduces the chance of being stopped out prematurely by routine market movements (whipsaws), which is the number one killer of win rates in high-frequency trading.
After applying these changes, you will need to run the Strategy Tester again to see the new win rate and the new total number of trades.
Would you like me to help you interpret the new Strategy Tester results once you apply these settings?
PSAR with ATR Trailing Stop + SMA Filter📈 Strategy Overview: PSAR + 6×ATR Trailing Stop with SMA Filter
This strategy is built around the principle of “Cut the losers, let the winners run” — a disciplined, trend-following approach that combines the Parabolic SAR indicator with dynamic risk management and a Simple Moving Average (SMA) trend filter.
🔍 Strategy Logic
Trend Filter Trades are only taken in the direction of the prevailing trend, defined by a user-selected SMA (default: 100).
✅ Long trades only when price is above the SMA
✅ Short trades only when price is below the SMA
Entry Signal: A trade is triggered when the Parabolic SAR flips to the opposite side of the price bars, signaling a potential trend reversal.
Stop Loss: The stop loss is dynamically set at 6×ATR from the entry price. This adapts to market volatility and is recalculated every bar — effectively acting as a trailing stop.
Exit Logic: There is no fixed take profit. The trade remains open until the trailing stop is hit — allowing winners to run and losers to be cut quickly.
Risk Management: Each trade risks 0.5% of total equity, ensuring consistent position sizing and capital preservation.
📊 Visual Elements
PSAR dots mark trend direction changes
SMA line shows the broader trend filter
Trailing stop crosses (with 50% opacity) indicate the current stop level without cluttering the chart
⚙️ Customizable Inputs
PSAR parameters: Start, Increment, Maximum
ATR length and multiplier
SMA length
Risk percentage per trade
This strategy is ideal for traders who want to stay aligned with the trend, automate disciplined exits, and avoid emotional decision-making. Clean, simple, and powerful.
Wishing you calm and successful trades!
Enhanced MA Crossover Pro📝 Strategy Summary: Enhanced MA Crossover Pro
This strategy is an advanced, highly configurable moving average (MA) crossover system designed for algorithmic trading. It uses the crossover of two customizable MAs (a "Fast" MA 1 and a "Slow" MA 2) as its core entry signal, but aggressively integrates multiple technical filters, time controls, and dynamic position management to create a robust and comprehensive trading system.
💡 Core Logic
Entry Signal: A bullish crossover (MA1 > MA2) generates a Long signal, and a bearish crossover (MA1 < MA2) generates a Short signal. Users can opt to use MA crossovers from a Higher Timeframe (HTF) for the entry signal.
Confirmation/Filters: The basic MA cross signal is filtered by several optional indicators (see Filters section below) to ensure trades align with a broader trend or momentum context.
Position Management: Trades are managed with a sophisticated system of Stop Loss, Take Profit, Trailing Stops, and Breakeven stops that can be fixed, ATR-based, or dynamically adjusted.
Risk Management: Daily limits are enforced for maximum profit/loss and maximum trades per day.
⚙️ Key Features and Customization
1. Moving Averages
Primary MAs (MA1 & MA2): Highly configurable lengths (default 8 & 20) and types: EMA, WMA, SMA, or SMMA/RMA.
Higher Timeframe (HTF) MAs: Optional MAs calculated on a user-defined resolution (e.g., "60" for 1-hour) for use as an entry signal or as a trend confirmation filter.
2. Multi-Filter System
The entry signal can be filtered by the following optional conditions:
SMA Filter: Price must be above a 200-period SMA for long trades, and below it for short trades.
VWAP Filter: Price must be above VWAP for long trades, and below it for short trades.
RSI Filter: Long trades are blocked if RSI is overbought (default 70); short trades are blocked if RSI is oversold (default 30).
MACD Filter: Requires the MACD Line to be above the Signal Line for long trades (and vice versa for short trades).
HTF Confirmation: Requires the HTF MA1 to be above HTF MA2 for long entries (and vice versa).
3. Dynamic Stop and Target Management (S/L & T/P)
The strategy provides extensive control over exits:
Stop Loss Methods:
Fixed: Fixed tick amount.
ATR: Based on a multiple of the Average True Range (ATR).
Capped ATR: ATR stop limited by a maximum fixed tick amount.
Exit on Close Cross MA: Position is closed if the price crosses back over the chosen MA (MA1 or MA2).
Breakeven Stop: A stop can be moved to the entry price once a trigger distance (fixed ticks or Adaptive Breakeven based on ATR%) is reached.
Trailing Stop: Can be fixed or ATR-based, with an optional feature to auto-tighten the trailing multiplier after the breakeven condition is met.
Profit Target: Can be a fixed tick amount or a dynamic target based on an ATR multiplier.
4. Time and Session Control
Trading Session: Trades are only taken between defined Start/End Hours and Minutes (e.g., 9:30 to 16:00).
Forced Close: All open positions are closed near the end of the session (e.g., 15:45).
Trading Days: Allows specific days of the week to be enabled or disabled for trading.
5. Risk and Position Limits
Daily Profit/Loss Limits: The strategy tracks daily realized and unrealized PnL in ticks and will close all positions and block new entries if the user-defined maximum profit or maximum loss is hit.
Max Trades Per Day: Limits the number of executed trades in a single day.
🎨 Outputs and Alerts
Plots: Plots the MA1, MA2, SMA, VWAP, and HTF MAs (if enabled) on the chart.
Shapes: Plots visual markers (BUY/SELL labels) on the bar where the MA crossover occurs.
Trailing Stop: Plots the dynamic trailing stop level when a position is open.
Alerts: Generates JSON-formatted alerts for entry ({"action":"buy", "price":...}) and exit ({"action":"exit", "position":"long", "price":...}).
Buy And Hold Performance Screener - [JTCAPITAL]Buy And Hold Performance Screener – is a script designed to track and display multi-asset “buy and hold” performance curves and performance statistics over defined timeframes for selected symbols. It doesn’t attempt to time entries or exits; rather, it shows what would happen if one simply bought the asset at the defined start date and held it.
The indicator works by calculating in the following steps:
Start Date Definition
The script begins by reading an input for the start date. This defines the bar from which the equity curves begin.
Symbol Definitions & Close Price Retrieval
The script allows the user to specify up to ten tickers. For each ticker it uses request.security() on the “1D” timeframe to retrieve the daily close price of that symbol.
Plot Enable Inputs
For each ticker there is an input boolean controlling whether the equity curve for that ticker should be plotted.
Asset Name Cleaning
The helper function clean_name(string asset) => … takes the asset string (e.g., “CRYPTO:SOLUSD”) and manipulates it (via string splitting and replacements) to derive a cleaned short name (e.g., “SOL”). This name is used for visuals (labels, table headers).
Equity Curve Calculation (“HODL”)
The helper function f_HODL(closez) defines a variable equity that assumes a starting equity of 1 unit at the start date and then multiplies by the ratio of each bar’s close to the prior bar’s close: i.e. daily compounding of returns.
Performance Metrics Calculation
The helper function f_performance(closez) calculates, for each symbol’s close series, the percentage change of the current close relative to its close 30 days ago, 90 days ago, 180 days ago, 1 year ago (365 days), 2 years ago (730 days) and 3 years ago (1095 days).
Equity Curve Plots
For each ticker, if the corresponding plot input is true, the script assigns a plotted variable equal to the equity curve value. Its then drawing each selected equity curve on the chart, each in a distinct color.
Table Construction
If the plottable input is true, the script constructs a table and populates it with rows and column corresponding to the assigned tickers and the set 6 timeframes used for display.
Buy and Sell Conditions:
Since this is strictly a “buy-and-hold” performance screener, there are no explicit buy or sell signals generated or plotted. The script assumes: buy at the defined start_date, hold continuously to present. There are no filters, no exit logic, no take-profit or stop-loss. The benefit of this approach is to provide a clean benchmark of how selected assets would have performed if one simply adopted a passive “buy & hold” approach from a given start date.
Features and Parameters:
start_date (input.time) : Defines the date from which performance and equity curves begin.
ticker1 … ticker10 (input.symbol) : User-selectable asset symbols to include in the screener.
plot1 … plot10 (input.bool) : Boolean flags to enable/disable plotting of each asset’s equity curve.
plottable (input.bool) : Flag to enable/disable drawing the performance table.
Colored plotting + Labels for identifying each asset curve on the chart.
Specifications:
Here is a detailed breakdown of every calculation/variable/function used in the script and what each part means:
start_date
This is defined via input.time(timestamp("1 Jan 2025"), title = "Start Date"). It allows the user to pick a specific calendar date from which the equity curves and performance calculations will start.
ticker1 … ticker10
These inputs allow the user to select up to ten different assets (symbols) to monitor. The script uses each of these to fetch daily close prices.
plot1 … plot10
Boolean inputs controlling which of the ten asset equity curves are plotted. If plotX is true, the equity curve for ticker X will be visible; otherwise it will be not plotted. This gives the user flexibility to include or exclude specific assets on the chart.
Returns the cleaned asset short name.
This provides friendly text labels like “BTC”, “ETH”, “SOL”, etc., instead of full symbol codes.
The choice of distinct colours for each asset helps differentiate curves visually when multiple assets are overlaid.
Colour definitions
Variables color1…color10 are explicitly defined via color.rgb(r,g,b) to give each asset a unique colour (e.g., red, orange, yellow, green, cyan, blue, purple, pink, etc.).
What are the benefits of combining these calculations?
By computing equity curves for multiple assets from the same start date and overlaying them, you can visualise comparative performance of different assets under a uniform “buy & hold” assumption.
The performance table adds multi-horizon returns (30 D, 90 D, 180 D, 1 Y, 2 Y, 3 Y) which helps the user see both short-term and longer-term performance without having to manually compute returns.
The use of daily close data via request.security(..., "1D") removes dependency on the chart’s timeframe, thereby standardising the comparison across assets.
The equity curve and table together provide both visual (curve) and numerical (table) summaries of performance, making it easier to spot trends, divergences, and cross-asset comparisons at a glance.
Because it uses compounding (equity := equity * (closez / closez )), the curves reflect the real growth of a 1-unit investment held over time, rather than only simple returns.
The labelling of curves and the color-coding make the multi-asset overlay easier to interpret.
Using a clean start date ensures that all curves begin at the same point (1 unit at start_date), making relative performance intuitive.
Because of this, the script is useful as a benchmarking tool: rather than trying to pick entries or exit points, you can simply compare “what if I had held these assets since Jan 1 2025” (or your chosen date), and see which assets out-/under-performed in that period. It helps an investor or trader evaluate the long-term benefits of passive vs. active management, or of allocation decisions.
Please note:
The script assumes continuous daily data and does not account for dividends, fees, slippage, or tax implications.
It does not attempt to optimise timing or provide trading signals.
Returns prior to the start date are ignored (equity only begins once time >= start_date).
For newly listed assets with fewer than 365 or 730 or 1095 days of history, the longer-horizon returns may return na or misleading values.
Because it uses request.security() without specifying lookahead, and on “1D” timeframe, it complies with standard usage but you should verify there is no look-ahead bias in your particular setup.
ENJOY!
Dual Table Dashboard - Correct V3add RSI Data## 📈 Trading Applications
### 1. Trend Following Strategy
```
1. Check TABLE 1 for trend direction (AnEMA29 + PDMDR)
2. If both green → Look for longs
3. If both red → Look for shorts
4. Use TABLE 2 for entry levels
```
### 2. Support/Resistance Strategy
```
@70 levels = Resistance (sell/take profit zones)
@50 levels = Pivot (breakout levels)
@30 levels = Support (buy/accumulation zones)
```
### 3. Multi-Timeframe Alignment
```
W_RSI → Weekly bias (long-term)
D_RSI → Daily bias (medium-term)
Sto50 → Current position (swing)
Sto12 → Immediate position (day trade)
RSI(7) & RSI(3) → Entry timing (scalp)
```
### 4. Color Scanning Method
**Quick visual analysis:**
- Count greens vs reds in each row
- More greens = Bullish position
- More reds = Bearish position
- Mixed colors = Transitioning/choppy
---
## ✅ Verification & Accuracy
### Tested Against AmiBroker:
- ✅ RSI band values match within ±0.01%
- ✅ Stochastic channels match exactly
- ✅ Color logic matches exactly
- ✅ All formulas verified line-by-line
### Known Minor Differences:
Small variations (<1%) may occur due to:
1. **Platform calculation precision** - Different floating-point engines
2. **Historical data feeds** - Slight variations in past prices
3. **Weekly bar boundaries** - TradingView vs AmiBroker week definitions
4. **Initialization period** - First N bars need to "warm up"
**These minor differences don't affect trading signals!**
---
## ⚙️ Settings & Customization
### Input Parameters:
```pine
emaLen = 29 // EMA Length for angle calculation
rangePeriods = 30 // Angle normalization lookback
rangeConst = 25 // Angle normalization constant
dmiLen = 14 // DMI/ADX Length for PDMDR
```
### Available Positions:
Can be changed in the code:
- `position.top_left`
- `position.top_center`
- `position.top_right`
- `position.middle_left` (Table 2 default)
- `position.middle_center`
- `position.middle_right`
- `position.bottom_left` (Table 1 default)
- `position.bottom_center`
- `position.bottom_right`
### Text Sizes:
- `size.tiny`
- `size.small` (current default)
- `size.normal`
- `size.large`
- `size.huge`
---
## 🎯 Best Practices
### DO:
✅ Use multiple confirmations before entering trades
✅ Combine with price action and chart patterns
✅ Pay attention to color changes across timeframes
✅ Use @50 levels as key pivot points
✅ Watch for alignment between W_RSI and D_RSI
### DON'T:
❌ Trade based on color alone without confirmation
❌ Ignore the overall trend (Table 1)
❌ Enter trades against strong trend signals
❌ Overtrade when colors are mixed/choppy
❌ Ignore risk management rules
---
## 📊 Example Reading
### Bullish Setup:
```
TABLE 1:
AnEMA29: Green (15°) across all 3 bars
PDMDR: Green (1.65) and rising
TABLE 2:
W_RSI@50: Green (price above)
D_RSI@50: Green (price above)
Sto50@50: Green (price above midpoint)
Sto12@50: Green (price above midpoint)
Interpretation: Strong bullish trend confirmed across multiple timeframes
Action: Look for long entries on pullbacks to @50 or @30 levels
```
### Bearish Setup:
```
TABLE 1:
AnEMA29: Red (-12°) across all 3 bars
PDMDR: Red (0.45) and falling
TABLE 2:
W_RSI@50: Red (price below)
D_RSI@50: Red (price below)
Sto50@50: Red (price below midpoint)
Interpretation: Strong bearish trend confirmed
Action: Look for short entries on rallies to @50 or @70 levels
```
### Reversal Signal:
```
TABLE 1:
-2D: Red, -1D: Yellow, 0D: Green (momentum shifting)
TABLE 2:
Price just crossed above multiple @50 levels
Colors changing from red to green
Interpretation: Potential trend reversal in progress
Action: Wait for confirmation, consider early long entry with tight stop
```
---
## 🔍 Troubleshooting
### "Values don't match AmiBroker exactly"
- Check you're on the same timeframe
- Verify the symbol is identical
- Compare historical data (last 20 closes)
- Small differences (<1%) are normal
### "Tables are overlapping"
- Adjust positions in code
- Use different combinations (top/middle/bottom with left/center/right)
### "Colors seem wrong"
- Verify current close price
- Check if you're comparing same bar
- Ensure both platforms use same session times
### "Script takes too long"
- Use on Daily or higher timeframes
- The RSI band calculation is computationally intensive
- Don't run on tick-by-tick data
---
## 📝 Version History
**v3.0 (Final)** - Current version
- RSI band calculation verified correct
- Tables positioned bottom-left and middle-left
- All values match AmiBroker
- Production ready ✅
**v2.0**
- Fixed RSI band algorithm order (calculate before updating P/N)
- Improved variable scope handling
**v1.0**
- Initial implementation
- Had incorrect RSI band calculation
---
## 📄 Files in Package
Nifty 50 Weighted Volume IndicatorThis takes the volume of the cash market as per the composite weighted average of the Nifty 50 Components.
You can use this at your discretion to take calls on Index trades.
Multi Timeframe Market Structure ContinuationOverview
This indicator identifies Break of Structure (BOS) and Change of Character (ChoCh) patterns using multi-timeframe (MTF) analysis to filter high-probability trade setups. By aligning lower timeframe signals with higher timeframe bias, it helps traders enter positions in the direction of the dominant trend while avoiding counter-trend traps.
Multi-Timeframe Analysis
The indicator analyzes market structure on two timeframes simultaneously:
Current Timeframe (CTF): Detects immediate BOS and ChoCh signals for entry timing
Higher Timeframe (HTF): Establishes the overall trend direction (default: 1H, customizable)
Signals only appear when the current timeframe structure aligns with the higher timeframe bias, ensuring you're trading with the momentum, not against it.
Break of Structure (BOS)
BOS signals indicate trend continuation - when price breaks a previous high in an uptrend or a previous low in a downtrend. These are reliable entries that confirm the trend is still active and strong.
Change of Character (ChoCh)
ChoCh signals mark early trend reversals - when market structure shifts from bearish to bullish (or vice versa). When captured in alignment with the higher timeframe trend, ChoCh entries can achieve exceptional risk-to-reward ratios as they allow entry near the beginning of a new impulse move.
Exit Signals
Exit signals are plotted when a ChoCh occurs in the opposite direction of the HTF trend. For example, if the HTF is bullish and a bearish ChoCh forms on the current timeframe, an orange "EXIT" signal appears - warning long traders that the lower timeframe structure is shifting against them. This provides an early warning system to protect profits or minimize losses before the HTF trend itself reverses.
Trading Strategy Recommendations
Trending Markets (Recommended)
In strong trending conditions, both BOS and ChoCh signals can be taken when aligned with the HTF bias. ChoCh entries are particularly powerful as they catch early reversals within the larger trend, offering entries with tight stop losses and extended profit targets.
Ranging Markets
During consolidation or choppy conditions, it's best to be selective and take only BOS entries. BOS signals confirm that the trend is continuing beyond the range, reducing false breakouts and whipsaw trades that are common with counter-trend ChoCh signals in sideways markets.
Customization
Pivot Length: Adjust the sensitivity of structure detection (default: 5). Lower values detect structure more frequently with earlier but potentially noisier signals. Higher values provide cleaner, more significant structural breaks but with some delay.
Higher Timeframe: Customize the HTF to suit your trading style. Day traders might use 1H HTF on 5m charts, while swing traders could use 4H or Daily HTF.
Alert System
Six alert conditions available:
Long BOS Entry / Long ChoCh Entry
Short BOS Entry / Short ChoCh Entry
Long Exit / Short Exit
All alerts fire only on confirmed candle closes to eliminate repainting and false signals.
Visual Features
Color-coded background showing HTF bias
Clear BOS/ChoCh labels with horizontal lines at structure levels
Orange "EXIT" signals when structure breaks against your position
Gray lines tracking current swing highs/lows
HTF trend indicator in the top-right corner
Liquidity Sweeps 2nd attemptLiquidity Sweeps 2nd attempt
The Liquidity Sweeps indicator detects the presence of liquidity sweeps on the user's chart, while also providing potential areas of support/resistance or entry when Liquidity levels are taken.
In the event of a Liquidity Sweep a Sweep Area is created which may provide further areas of interest.
Larry Williams Oops StrategyThis strategy is a modern take on Larry Williams’ classic Oops setup. It trades intraday while referencing daily bars to detect opening gaps and align entries with the prior day’s direction. Risk is managed with day-based stops, and—unlike the original—all positions are closed at the end of the session (or at the last bar’s close), not at a fixed profit target or the first profitable open.
Entry Rules
Long setup (bullish reversion): Today opens below yesterday’s low (down gap) and yesterday’s candle was bearish. Place a buy stop at yesterday’s low + Filter (ticks).
Short setup (bearish reversion): Today opens above yesterday’s high (up gap) and yesterday’s candle was bullish. Place a sell stop at yesterday’s high − Filter (ticks).
Longs are only taken on down-gap days; shorts only on up-gap days.
Protective Stop
If long, stop loss trails the current day’s low.
If short, stop loss trails the current day’s high.
Exit Logic
Positions are force-closed at the end of the session (in the last bar), ensuring no overnight exposure. There is no take-profit; only stop loss or end-of-day flat.
Notes
This strategy is designed for intraday charts (minutes/seconds) using daily data for gaps and prior-day direction.
Longs/shorts can be enabled or disabled independently.
Session Gap Fill [LuxAlgo]The Session Gap Fill tool detects and highlights filled and unfilled price gaps between regular sessions. It features a dashboard with key statistics about the detected gaps.
The tool is highly customizable, allowing users to filter by different types of gaps and customize how they are displayed on the chart.
🔶 USAGE
By default, the tool detects all price gaps between sessions. A price gap is defined as a difference between the opening price of one session and the closing price of the previous session. In this case, the tool uses the opening price of the first bar of the session against the closing price of the previous bar.
A bullish gap is detected when the session open price is higher than the last close, and a bearish gap is detected when the session open price is lower than the last close.
Gaps represent a change in market sentiment, a difference in what market participants think between the close of one trading session and the open of the next.
What is useful to traders is not the gap itself, but how the market reacts to it.
Unfilled gaps occur when prices do not return to the previous session's closing price.
Filled gaps occur when prices come back to the previous session's close price.
By analyzing how markets react to gaps, traders can understand market sentiment, whether different prices are accepted or rejected, and take advantage of this information to position themselves in favor of bullish or bearish market sentiment.
Next, we will cover the Gap Type Filter and Statistics Dashboard.
🔹 Gap Type Filter
Traders can choose from three options: display all gaps, display only overlapping gaps, or display only non-overlapping gaps. All gaps are displayed by default.
An overlapping gap is defined when the first bar of the session has any price in common with the previous bar. No overlapping gap is defined when the two bars do not share any price levels.
As we will see in the next section, there are clear differences in market behavior around these types of gaps.
🔹 Statistics Dashboard
The Statistics Dashboard displays key metrics that help traders understand market behavior around each type of gap.
Gaps: The percentage of bullish and bearish gaps.
Filled: The percentage of filled bullish and bearish gaps.
Reversed: The percentage of filled gaps that move in favor of the gap
Bars Avg.: The average number of bars for a gap to be filled.
Now, let's analyze the chart on the left of the image to understand those stats. These are the stats for all gaps, both overlapping and non-overlapping.
Of the total, bullish gaps represent 55%, and bearish ones represent 44%. The gap bias is pretty balanced in this market.
The second statistic, Filled, shows that 63% of gaps are filled, both bullish and bearish. Therefore, there is a higher probability that a gap will be filled than not.
The third statistic is reversed. This is the percentage of filled gaps where prices move in favor of the gap. This applies to filled bullish gaps when the close of the session is above the open, and to filled bearish gaps when the close of the session is below the open. In other words, first there is a gap, then it fills, and finally it reverses. As we can see in the chart, this only happens 35% of the time for bullish gaps and 29% of the time for bearish gaps.
The last statistic is Bars Avg., which is the average number of bars for a gap to be filled. On average, it takes between one and two bars for both bullish and bearish gaps. On average, gaps fill quickly.
As we can see on the chart, selecting different types of gaps yields different statistics and market behavior. For example, overlapping gaps have a greater than 90% chance of being filled, whereas non-overlapping gaps have a less than 40% chance.
🔶 SETTINGS
Gap Type: Select the type of gap to display.
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Position: Select the location of the dashboard.
Size: Select the dashboard size.
🔹 Style
Filled Bullish Gap: Enable or disable this gap and choose the color.
Filled Bearish Gap: Enable or disable this gap and choose the color.
Unfilled Gap: Enable or disable this gap and choose the color.
Max Deviation Level: Enable or disable this level and choose the color.
Open Price Level: Enable or disable this level and choose the color.
First Passage Time - Distribution AnalysisThe First Passage Time (FPT) Distribution Analysis indicator is a sophisticated probabilistic tool that answers one of the most critical questions in trading: "How long will it take for price to reach my target, and what are the odds of getting there first?"
Unlike traditional technical indicators that focus on what might happen, this indicator tells you when it's likely to happen.
Mathematical Foundation: First Passage Time Theory
What is First Passage Time?
First Passage Time (FPT) is a concept in stochastic processes that measures the time it takes for a random process to reach a specific threshold for the first time. Originally developed in physics and mathematics, FPT has applications in:
Quantitative Finance: Option pricing, risk management, and algorithmic trading
Neuroscience: Modeling neural firing patterns
Biology: Population dynamics and disease spread
Engineering: Reliability analysis and failure prediction
The Mathematics Behind It
This indicator uses Geometric Brownian Motion (GBM), the same stochastic model used in the Black-Scholes option pricing formula:
dS = μS dt + σS dW
Where:
S = Asset price
μ = Drift (trend component)
σ = Volatility (uncertainty component)
dW = Wiener process (random walk)
Through Monte Carlo simulation, the indicator runs 1,000+ price path simulations to statistically determine:
When each threshold (+X% or -X%) is likely to be hit
Which threshold is hit first (directional bias)
How often each scenario occurs (probability distribution)
🎯 How This Indicator Works
Core Algorithm Workflow:
Calculate Historical Statistics
Measures recent price volatility (standard deviation of log returns)
Calculates drift (average directional movement)
Annualizes these metrics for meaningful comparison
Run Monte Carlo Simulations
Generates 1,000+ random price paths based on historical behavior
Tracks when each path hits the upside (+X%) or downside (-X%) threshold
Records which threshold was hit first in each simulation
Aggregate Statistical Results
Calculates percentile distributions (10th, 25th, 50th, 75th, 90th)
Computes "first hit" probabilities (upside vs downside)
Determines average and median time-to-target
Visual Representation
Displays thresholds as horizontal lines
Shows gradient risk zones (purple-to-blue)
Provides comprehensive statistics table
📈 Use Cases
1. Options Trading
Selling Options: Determine if your strike price is likely to be hit before expiration
Buying Options: Estimate probability of reaching profit targets within your time window
Time Decay Management: Compare expected time-to-target vs theta decay
Example: You're considering selling a 30-day call option 5% out of the money. The indicator shows there's a 72% chance price hits +5% within 12 days. This tells you the trade has high assignment risk.
2. Swing Trading
Entry Timing: Wait for higher probability setups when directional bias is strong
Target Setting: Use median time-to-target to set realistic profit expectations
Stop Loss Placement: Understand probability of hitting your stop before target
Example: The indicator shows 85% upside probability with median time of 3.2 days. You can confidently enter long positions with appropriate position sizing.
3. Risk Management
Position Sizing: Larger positions when probability heavily favors one direction
Portfolio Allocation: Reduce exposure when probabilities are near 50/50 (high uncertainty)
Hedge Timing: Know when to add protective positions based on downside probability
Example: Indicator shows 55% upside vs 45% downside—nearly neutral. This signals high uncertainty, suggesting reduced position size or wait for better setup.
4. Market Regime Detection
Trending Markets: High directional bias (70%+ one direction)
Range-bound Markets: Balanced probabilities (45-55% both directions)
Volatility Regimes: Compare actual vs theoretical minimum time
Example: Consistent 90%+ bullish bias across multiple timeframes confirms strong uptrend—stay long and avoid counter-trend trades.
First Hit Rate (Most Important!)
Shows which threshold is likely to be hit FIRST:
Upside %: Probability of hitting upside target before downside
Downside %: Probability of hitting downside target before upside
These always sum to 100%
⚠️ Warning: If you see "Low Hit Rate" warning, increase this parameter!
Advanced Parameters
Drift Mode
Allows you to explore different scenarios:
Historical: Uses actual recent trend (default—most realistic)
Zero (Neutral): Assumes no trend, only volatility (symmetric probabilities)
50% Reduced: Dampens trend effect (conservative scenario)
Use Case: Switch to "Zero (Neutral)" to see what happens in a pure volatility environment, useful for range-bound markets.
Distribution Type
Percentile: Shows 10%, 25%, 50%, 75%, 90% levels (recommended for most users)
Sigma: Shows standard deviation levels (1σ, 2σ)—useful for statistical analysis
⚠️ Important Limitations & Best Practices
Limitations
Assumes GBM: Real markets have fat tails, jumps, and regime changes not captured by GBM
Historical Parameters: Uses recent volatility/drift—may not predict regime shifts
No Fundamental Events: Cannot predict earnings, news, or macro shocks
Computational: Runs only on last bar—doesn't give historical signals
Remember: Probabilities are not certainties. Use this indicator as part of a comprehensive trading plan with proper risk management.
Created by: Henrique Centieiro. feedback is more than welcome!
Micro SuiteWhat it is: One Pine v5 indicator that stacks several tools: EMA ribbon + a color-flipping 11/34 EMA trend line, multi-timeframe RSI pressure arrows, and a Bollinger Band re-entry system that marks Top/Bottom triggers (T/B) and later “r” confirmations. It also sprinkles in 3-Line Strike, Leledc exhaustion dots, and a small “Micro Dots” engine (ATR regime + VMA filter). Alerts for all of it.
TradingView
The core signals you’ll actually use:
RSI arrows: Up arrow when current RSI(6) < 30 and selected higher-TF RSIs are also < 30; down arrow when > 70 cluster cools. Idea = stacked OB/OS “pressure.”
TradingView
Bollinger re-entry (T/B + r):
T = first close back inside upper band; B = first close back inside lower band.
r = confirmation within N bars (price takes out the trigger bar’s high/low). These bars tint so they’re easy to see.
TradingView
Trend filter: EMA-11 vs EMA-34 color flip + optional VMA trend line; helps you ignore counter-trend stabs.
TradingView
Quick playbook (how to read it):
Reversal short: See a T near the top band → get the r within your window → bonus if a down RSI arrow or a Leledc high dot shows up.
Reversal long: Mirror that with B → r, plus an up RSI arrow/Leledc low dot.
Continuation: If Micro Dot stays green (or red) and 11>34 EMA holds, ignore isolated T/B traps.
TradingView
Inputs that matter:
confirmBars for the T/B “r” window.
Which higher-TF RSIs must agree for arrows.
Show/hide and lengths for EMAs and BB.
Micro block: show dots, VMA line, and speed (Fast/Med/Slow).
TradingView
Why people like it: You get trend, momentum, and mean-revert cues on one pane with ready-made alerts, so it’s easier to build a ruleset (e.g., “only take B→r longs when 11>34 and there’s an RSI up arrow”).
TradingView
Caveats: It’s still just TA—OB/OS clusters can persist in trends; confirmations can miss V-shaped turns; and stacking signals can be late in fast markets. Pair it with risk rules (fixed R, ATR stops) and a higher-TF bias.
One-liner cheat sheet:
Longs: B → r + RSI up arrow + 11>34 (optional Micro Dot green).
Shorts: T → r + RSI down arrow + 11<34 (optional Micro Dot red).
TradingView
Dynamic Volume Trace Profile [ChartPrime]⯁ OVERVIEW
Dynamic Volume Trace Profile is a reimagined take on volume profile analysis. Instead of plotting a static horizontal histogram on the side of your chart, this indicator projects dynamic volume trace lines directly onto the price action. Each bin is color-graded according to its relative strength, creating a living “volume skeleton” of the market. The orange trace highlights the current Point of Control (POC)—the price level with maximum historical traded volume within the lookback window. On the right side, the tool builds a mini profile, showing absolute volume per bin alongside its percentage share, where the POC always represents 100% strength .
⯁ KEY FEATURES
Dynamic On-Chart Bins:
The range between highest high and lowest low is split into 25 bins. Each bin is drawn as a horizontal trace line across the lookback chart period.
Gradient Color Encoding:
Trace lines fade from transparent to teal depending on relative volume size. The more intense the teal, the stronger the historical traded activity at that level.
Automatic POC Highlight:
The bin with the highest aggregated volume is flagged with an orange line . This POC adapts bar-by-bar as volume distribution shifts.
Right-Side Volume Profile:
At the chart’s right edge, the script prints a box-style profile. Each bin shows:
• Total volume (absolute units).
• Percentage of max volume, in parentheses (POC bin = 100%).
This gives both raw and normalized context at a glance.
Adjustable Lookback Window:
The lookback defines how many bars feed the profile. Increase for stable HTF zones or decrease for responsive intraday distributions.
POC Toggle & Styling:
Optionally toggle POC highlighting on/off, adjust colors, and set line thickness for better integration with your chart theme.
⯁ HOW IT WORKS (UNDER THE HOOD)
Step Sizing:
over last 100 bars is divided by to calculate bin height.
Volume Aggregation:
For each bar in the , the script checks which bin the close falls into, then adds that bar’s volume to the bin’s counter.
Gradient Mapping:
Bin volume is normalized against the max volume across all bins. That value is mapped onto a gradient from transparent → teal.
POC Logic:
The bin with highest volume is colored orange both on the dynamic trace and in the right-side profile.
Right-Hand Profile:
Boxes are drawn for each bin proportional to volume / maxVolume × 50 units, with text labels showing both absolute volume and normalized %.
⯁ USAGE
Use the orange trace as the dominant “magnet” level—price often gravitates to the POC.
Watch for clusters of strong teal traces as areas of high acceptance; thin or faint zones mark low-liquidity gaps prone to fast moves.
On intraday charts, tighten lookback to reveal session-based distributions . For swing or position trading, expand lookback to surface more durable volume shelves.
Compare the right-side profile % to judge how “top-heavy” or “bottom-heavy” the current distribution is.
Use bright, intense color traces as context for confluence with structure, OBs, or liquidity hunts.
⯁ CONCLUSION
Dynamic Volume Trace Profile takes the traditional volume profile and fuses it into the body of price itself. Instead of a fixed sidebar, you see gradient traces layered directly on the chart, giving real-time context of where volume concentrated and where price may be drawn. With built-in POC highlighting, normalized % readouts, and an adaptive right-side profile, it offers both precision levels and market structure awareness in a cleaner, more intuitive form.
Trend TraderThe Trend Trader indicator is a trend-following tool based on a triple EMA (Exponential Moving Average) setup designed to help traders identify market direction and potential reversal zones. It plots three customizable EMAs on the chart to highlight bullish and bearish momentum, then generates trade signals when price shows a strong likelihood of continuing in the direction of the prevailing trend.
EMA Alignment: The indicator checks for bullish stacking (fast EMA above medium, medium above slow) and bearish stacking (fast EMA below medium, medium below slow). This alignment defines the prevailing market trend.
Trend Validation: A user-defined lookback period ensures signals are only taken if the market recently displayed a stacked trend, thus filtering false entries during consolidations.
Signal Generation: Buy signals appear when price dips into the zone between the fast and medium EMAs during a bullish trend. Sell signals appear when price rallies into the zone between the fast and medium EMAs during a bearish trend.
Alerts: Built-in alerts notify traders of new trade opportunities without having to constantly watch the chart.
This indicator is suitable for swing trading and intraday strategies across multiple markets, including forex, stocks, indices, and crypto.
Suggested Strategy for Profitability
This tool is best used as part of a structured trend-trading plan. Below is a suggested framework:
Entry Rules
Long (Buy Trade):
Confirm that EMA alignment is bullish (EMA1 > EMA2 > EMA3).
Wait for a Buy Signal (triangle up below price).
Ensure the higher timeframe (e.g., 4H if trading 1H) trend is also bullish to filter trades.
Short (Sell Trade):
Confirm EMA alignment is bearish (EMA1 < EMA2 < EMA3).
Wait for a Sell Signal (triangle down above price).
Higher timeframe should also be bearish to increase probability.
Stop Loss
For long positions, place the stop loss just below EMA3 or the most recent swing low.
For short positions, place the stop loss just above EMA3 or the most recent swing high.
Take Profit
Conservative: Set TP at 1.5x to 2x the stop loss distance.
Aggressive: Trail stop loss below EMA2 (for longs) or above EMA2 (for shorts) to capture larger trends.
Risk Management
Use no more than 1–2% of account risk per trade.
Trade only when the signal aligns with overall market context (higher timeframe, support/resistance, or volume confirmation).
This indicator is very similar to the indicator "Trend Scalper" by the same developer, the difference is this indicator is used to just find the trade and hold the trade or to find the reversal of a trend instead of triggering alerts every time price enters between EMA1 and EMA2.
Initial Balance Breakout Signals [LuxAlgo]The Initial Balance Breakout Signals help traders identify breakouts of the Initial Balance (IB) range.
The indicator includes automatic detection of IB or can use custom sessions, highlights top and bottom IB extensions, custom Fibonacci levels, and goes further with an IB forecast with two different modes.
🔶 USAGE
The initial balance is the price range made within the first hour of the trading session. It is an intraday concept based on the idea that high volume and volatility enter the market through institutional trading at the start of the session, setting the tone for the rest of the day.
The initial balance is useful for gauging market sentiment, or, in other words, the relationship between buyers and sellers.
Bullish sentiment: Price trades above the IB range.
Mixed sentiment: Price trades within the IB range.
Bearish sentiment: Price trades below the IB range.
The initial balance high and low are important levels that many traders use to gauge sentiment. There are two main ideas behind trading around the IB range.
IB Extreme Breakout: When the price breaks and holds the IB high or low, there is a high probability that the price will continue in that direction.
IB Extreme Rejection: When the price tries to break those levels but fails, there is a high probability that it will reach the opposite IB extreme.
This indicator is a complete Initial Balance toolset with custom sessions, breakout signals, IB extensions, Fibonacci retracements, and an IB forecast. All of these features will be explained in the following sections.
🔹 Custom Sessions and Signals
By default, sessions for Initial Balance and breakout signals are in Auto mode. This means that Initial Balance takes the first hour of the trading session and shows breakout signals for the rest of the session.
With this option, traders can use the tool for open range trading, making it highly versatile. The concept behind open range (OR) is the same as that of initial balance (IB), but in OR, the range is determined by the first minute, three or five minutes, or up to the first 30 minutes of the trading session.
As shown in the image above, the top chart uses the Auto feature for the IB and Breakouts sessions. The bottom chart has the Auto feature disabled to use custom sessions for both parameters. In this case, the first three minutes of the trading session are used, turning the tool into an Open Range trading indicator.
This chart shows another example of using custom sessions to display overnight NASDAQ futures sessions.
The left chart shows a custom session from the Tokyo open to the London open, and the right chart shows a custom session from the London open to the New York open.
The chart shows both the Asian and European sessions, their top and bottom extremes, and the breakout signals from those extremes.
🔹 Initial Balance Extensions
Traders can easily extend both extremes of the Initial Balance to display their preferred targets for breakouts. Enable or disable any of them and set the IB percentage to use for the extension.
As the chart shows, the percentage selected on the settings panel directly affects the displayed levels.
Setting 25 means the tool will use a quarter of the detected initial balance range for extensions beyond the IB extremes. Setting 100 means the full IB range will be used.
Traders can use these extensions as targets for breakout signals.
🔹 Fibonacci Levels
Traders can display default or custom Fibonacci levels on the IB range to trade retracements and assess the strength of market movements. Each level can be enabled or disabled and customized by level, color, and line style.
As we can see on the chart, after the IB was completed, prices were unable to fall below the 0.236 Fibonacci level. This indicates significant bullish pressure, so it is expected that prices will rise.
Traders can use these levels as guidelines to assess the strength of the side trying to penetrate the IB. In this case, the sellers were unable to move the market beyond the first level.
🔹 Initial Balance Forecast
The tool features two different forecasting methods for the current IB. By default, it takes the average of the last ten values and applies a multiplier of one.
IB Against Previous Open: averages the difference between IB extremes and the open of the previous session.
Filter by current day of the week: averages the difference between IB extremes and the open of the current session for the same day of the week.
This feature allows traders to see the difference between the current IB and the average of the last IBs. It makes it very easy to interpret: if the current IB is higher than the average, buyers are in control; if it is lower than the average, sellers are in control.
For example, on the left side of the chart, we can see that the last day was very bullish because the IB was completely above the forecasted value. This is the IB mean of the last ten trading days.
On the right, we can see that on Monday, September 15, the IB traded slightly higher but within the forecasted value of the IB mean of the last ten Mondays. In this case, it is within expectations.
🔶 SETTINGS
Display Last X IBs: Select how many IBs to display.
Initial Balance: Choose a custom session or enable the Auto feature.
Breakouts: Enable or disable breakouts. Choose custom session or enable the Auto feature.
🔹 Extensions
Top Extension: Enable or disable the top extension and choose the percentage of IB to use.
Bottom extension: Enable or disable the bottom extension and choose the percentage of IB to use.
🔹 Fibonacci Levels
Display Fibonacci: Enable or disable Fibonacci levels.
Reverse: Reverse Fibonacci levels.
Levels, Colors & Style
Display Labels: Enable or disable labels and choose text size.
🔹 Forecast
Display Forecast: Select the forecast method.
- IB Against Previous Open: Calculates the average difference between the IB high and low and the previous day's IB open price.
- Filter by Current Day of Week: Calculates the average difference between the IB high and low and the IB open price for the same day of the week.
Forecast Memory: The number of data points used to calculate the average.
Forecast Multiplier: This multiplier will be applied to the average. Bigger numbers will result in wider predicted ranges.
Forecast Colors: Choose from a variety of colors.
Forecast Style: Choose a line style.
🔹 Style
Initial Balance Colors
Extension Transparency: Choose the extension's transparency. 0 is solid, and 100 is fully transparent.
