LilSpecCodes1. Killzone Background Highlighting:
It highlights 4 key market sessions:
Killzone Time (EST) Color
Silver Bullet 9:30 AM – 12:00 PM Light Blue
London Killzone 2:00 AM – 5:00 AM Light Green
NY PM Killzone 1:30 PM – 4:00 PM Light Purple
Asia Open 7:00 PM – 11:00 PM Light Red
These are meant to help you focus during high-probability trading times.
__________________________________________________
2. Previous Day High/Low (PDH/PDL):
Plots green line = PDH
Plots red line = PDL
Tracks the current day’s session high/low and sets it as PDH/PDL on a new trading day
CHANGES WITH ETH/RTH
3. Inside Bar Marker:
Plots a small black triangle under bars where the high is lower than the previous bar’s high and the low is higher than the previous bar’s low (inside bars)
Useful for spotting potential breakout or continuation setups
4. Vertical Time Markers (White Dashed Lines)
Time (EST) Label
4:00 AM End of London Silver Bullet
9:30 AM NYSE Open
10:00 AM Start of NY Silver Bullet
11:00 AM End of NY Silver Bullet
11:30 AM (Customizable Input)
3:00 PM PM Killzone Ends
3:15 PM Futures Market Close
7:15 PM Asia Session Watch
在腳本中搜尋"Futures"
Multi-Session MarkerMulti-Session Marker is a flexible visual tool for traders who want to highlight up to 10 custom trading sessions directly on their chart’s background.
Custom Sessions: Enter up to 10 time ranges (in HHMM-HHMM format) to mark any market session, news window, or personal focus period.
Visual Clarity: For each session, toggle the highlight on or off and select a unique background color and opacity, making it easy to distinguish active trading windows at a glance.
Universal Time Handling: Session times automatically follow your chart’s time zone—no manual adjustment required.
Efficient and Fast: Utilizes TradingView’s bgcolor() for smooth performance, even on fast timeframes like 1-second charts.
Clean Interface: All session controls are grouped for easy editing in the indicator’s settings panel.
How to use:
In the indicator settings, enter your desired session times (e.g., 0930-1130) for each session you want to highlight.
Toggle “Show Session” and pick a color for each session.
The background will automatically highlight those periods on your chart.
This indicator is ideal for day traders, futures traders, or anyone who wants to visually segment their trading day for better focus and analysis.
Long/Short/Exit/Risk management Strategy # LongShortExit Strategy Documentation
## Overview
The LongShortExit strategy is a versatile trading system for TradingView that provides complete control over entry, exit, and risk management parameters. It features a sophisticated framework for managing long and short positions with customizable profit targets, stop-loss mechanisms, partial profit-taking, and trailing stops. The strategy can be enhanced with continuous position signals for visual feedback on the current trading state.
## Key Features
### General Settings
- **Trading Direction**: Choose to trade long positions only, short positions only, or both.
- **Max Trades Per Day**: Limit the number of trades per day to prevent overtrading.
- **Bars Between Trades**: Enforce a minimum number of bars between consecutive trades.
### Session Management
- **Session Control**: Restrict trading to specific times of the day.
- **Time Zone**: Specify the time zone for session calculations.
- **Expiration**: Optionally set a date when the strategy should stop executing.
### Contract Settings
- **Contract Type**: Select from common futures contracts (MNQ, MES, NQ, ES) or custom values.
- **Point Value**: Define the dollar value per point movement.
- **Tick Size**: Set the minimum price movement for accurate calculations.
### Visual Signals
- **Continuous Position Signals**: Implement 0 to 1 visual signals to track position states.
- **Signal Plotting**: Customize color and appearance of position signals.
- **Clear Visual Feedback**: Instantly see when entry conditions are triggered.
### Risk Management
#### Stop Loss and Take Profit
- **Risk Type**: Choose between percentage-based, ATR-based, or points-based risk management.
- **Percentage Mode**: Set SL/TP as a percentage of entry price.
- **ATR Mode**: Set SL/TP as a multiple of the Average True Range.
- **Points Mode**: Set SL/TP as a fixed number of points from entry.
#### Advanced Exit Features
- **Break-Even**: Automatically move stop-loss to break-even after reaching specified profit threshold.
- **Trailing Stop**: Implement a trailing stop-loss that follows price movement at a defined distance.
- **Partial Profit Taking**: Take partial profits at predetermined price levels:
- Set first partial exit point and percentage of position to close
- Set second partial exit point and percentage of position to close
- **Time-Based Exit**: Automatically exit a position after a specified number of bars.
#### Win/Loss Streak Management
- **Streak Cutoff**: Automatically pause trading after a series of consecutive wins or losses.
- **Daily Reset**: Option to reset streak counters at the start of each day.
### Entry Conditions
- **Source and Value**: Define the exact price source and value that triggers entries.
- **Equals Condition**: Entry signals occur when the source exactly matches the specified value.
### Performance Analytics
- **Real-Time Stats**: Track important performance metrics like win rate, P&L, and largest wins/losses.
- **Visual Feedback**: On-chart markers for entries, exits, and important events.
### External Integration
- **Webhook Support**: Compatible with TradingView's webhook alerts for automated trading.
- **Cross-Platform**: Connect to external trading systems and notification platforms.
- **Custom Order Execution**: Implement advanced order flows through external services.
## How to Use
### Setup Instructions
1. Add the script to your TradingView chart.
2. Configure the general settings based on your trading preferences.
3. Set session trading hours if you only want to trade specific times.
4. Select your contract specifications or customize for your instrument.
5. Configure risk parameters:
- Choose your preferred risk management approach
- Set appropriate stop-loss and take-profit levels
- Enable advanced features like break-even, trailing stops, or partial profit taking as needed
6. Define entry conditions:
- Select the price source (such as close, open, high, or an indicator)
- Set the specific value that should trigger entries
### Entry Condition Examples
- **Example 1**: To enter when price closes exactly at a whole number:
- Long Source: close
- Long Value: 4200 (for instance, to enter when price closes exactly at 4200)
- **Example 2**: To enter when an indicator reaches a specific value:
- Long Source: ta.rsi(close, 14)
- Long Value: 30 (triggers when RSI equals exactly 30)
### Best Practices
1. **Always backtest thoroughly** before using in live trading.
2. **Start with conservative risk settings**:
- Small position sizes
- Reasonable stop-loss distances
- Limited trades per day
3. **Monitor and adjust**:
- Use the performance table to track results
- Adjust parameters based on how the strategy performs
4. **Consider market volatility**:
- Use ATR-based stops during volatile periods
- Use fixed points during stable markets
## Continuous Position Signals Implementation
The LongShortExit strategy can be enhanced with continuous position signals to provide visual feedback about the current position state. These signals can help you track when the strategy is in a long or short position.
### Adding Continuous Position Signals
Add the following code to implement continuous position signals (0 to 1):
```pine
// Continuous position signals (0 to 1)
var float longSignal = 0.0
var float shortSignal = 0.0
// Update position signals based on your indicator's conditions
longSignal := longCondition ? 1.0 : 0.0
shortSignal := shortCondition ? 1.0 : 0.0
// Plot continuous signals
plot(longSignal, title="Long Signal", color=#00FF00, linewidth=2, transp=0, style=plot.style_line)
plot(shortSignal, title="Short Signal", color=#FF0000, linewidth=2, transp=0, style=plot.style_line)
```
### Benefits of Continuous Position Signals
- Provides clear visual feedback of current position state (long/short)
- Signal values stay consistent (0 or 1) until condition changes
- Can be used for additional calculations or alert conditions
- Makes it easier to track when entry conditions are triggered
### Using with Custom Indicators
You can adapt the continuous position signals to work with any custom indicator by replacing the condition with your indicator's logic:
```pine
// Example with moving average crossover
longSignal := fastMA > slowMA ? 1.0 : 0.0
shortSignal := fastMA < slowMA ? 1.0 : 0.0
```
## Webhook Integration
The LongShortExit strategy is fully compatible with TradingView's webhook alerts, allowing you to connect your strategy to external trading platforms, brokers, or custom applications for automated trading execution.
### Setting Up Webhooks
1. Create an alert on your chart with the LongShortExit strategy
2. Enable the "Webhook URL" option in the alert dialog
3. Enter your webhook endpoint URL (from your broker or custom trading system)
4. Customize the alert message with relevant information using TradingView variables
### Webhook Message Format Example
```json
{
"strategy": "LongShortExit",
"action": "{{strategy.order.action}}",
"price": "{{strategy.order.price}}",
"quantity": "{{strategy.position_size}}",
"time": "{{time}}",
"ticker": "{{ticker}}",
"position_size": "{{strategy.position_size}}",
"position_value": "{{strategy.position_value}}",
"order_id": "{{strategy.order.id}}",
"order_comment": "{{strategy.order.comment}}"
}
```
### TradingView Alert Condition Examples
For effective webhook automation, set up these alert conditions:
#### Entry Alert
```
{{strategy.position_size}} != {{strategy.position_size}}
```
#### Exit Alert
```
{{strategy.position_size}} < {{strategy.position_size}} or {{strategy.position_size}} > {{strategy.position_size}}
```
#### Partial Take Profit Alert
```
strategy.order.comment contains "Partial TP"
```
### Benefits of Webhook Integration
- **Automated Trading**: Execute trades automatically through supported brokers
- **Cross-Platform**: Connect to custom trading bots and applications
- **Real-Time Notifications**: Receive trade signals on external platforms
- **Data Collection**: Log trade data for further analysis
- **Custom Order Management**: Implement advanced order types not available in TradingView
### Compatible External Applications
- Trading bots and algorithmic trading software
- Custom order execution systems
- Discord, Telegram, or Slack notification systems
- Trade journaling applications
- Risk management platforms
### Implementation Recommendations
- Test webhook delivery using a free service like webhook.site before connecting to your actual trading system
- Include authentication tokens or API keys in your webhook URL or payload when required by your external service
- Consider implementing confirmation mechanisms to verify trade execution
- Log all webhook activities for troubleshooting and performance tracking
## Strategy Customization Tips
### For Scalping
- Set smaller profit targets (1-3 points)
- Use tighter stop-losses
- Enable break-even feature after small profit
- Set higher max trades per day
### For Day Trading
- Use moderate profit targets
- Implement partial profit taking
- Enable trailing stops
- Set reasonable session trading hours
### For Swing Trading
- Use longer-term charts
- Set wider stops (ATR-based often works well)
- Use higher profit targets
- Disable daily streak reset
## Common Troubleshooting
### Low Win Rate
- Consider widening stop-losses
- Verify that entry conditions aren't triggering too frequently
- Check if the equals condition is too restrictive; consider small tolerances
### Missing Obvious Trades
- The equals condition is extremely precise. Price must exactly match the specified value.
- Consider using floating-point precision for more reliable triggers
### Frequent Stop-Outs
- Try ATR-based stops instead of fixed points
- Increase the stop-loss distance
- Enable break-even feature to protect profits
## Important Notes
- The exact equals condition is strict and may result in fewer trade signals compared to other conditions.
- For instruments with decimal prices, exact equality might be rare. Consider the precision of your value.
- Break-even and trailing stop calculations are based on points, not percentage.
- Partial take-profit levels are defined in points distance from entry.
- The continuous position signals (0 to 1) provide valuable visual feedback but don't affect the strategy's trading logic directly.
- When implementing continuous signals, ensure they're aligned with the actual entry conditions used by the strategy.
---
*This strategy is for educational and informational purposes only. Always test thoroughly before using with real funds.*
MNQ/NQ Risk Management ToolThis tool helps MNQ and NQ futures traders automatically calculate position size based on either a fixed dollar risk or a percentage of account balance.
Simply enter your stop loss level and choose whether to risk a set dollar amount or a percentage of your account. The script will display how many contracts to trade based on your setup.
Features:
Calculates contracts based on stop loss and risk size
Toggle between dollar-based or percent-of-account risk
Works with both MNQ ($2/point) and NQ ($20/point)
Automatically updates based on current price and direction (long or short)
Displays a clean info box on your chart with risk, contracts, and settings
This tool is ideal for intraday or swing traders who want to stay consistent with risk management across trades.
5DMA Optional HMA Entry📈 5DMA Optional HMA Entry Signal – Precision-Based Momentum Trigger
Category: Trend-Following / Reversal Timing / Entry Optimization
🔍 Overview:
The 5DMA Optional HMA Entry indicator is a refined price-action entry tool built for traders who rely on clean trend alignment and precise timing. This script identifies breakout-style entry points when price gains upward momentum relative to short-term moving averages — specifically the 5-day Simple Moving Average (5DMA) and an optional Hull Moving Average (HMA).
Whether you're swing trading stocks, scalping ETFs like UVXY or VXX, or looking for pullback recovery entries, this tool helps time your long entries with clarity and flexibility.
⚙️ Core Logic:
Primary Condition (Always On):
🔹 Close must be above the 5DMA – ensuring upward short-term momentum is confirmed.
Optional Condition (Toggled by User):
🔹 Close above the HMA – adds slope-responsive trend filtering for smoother setups. Enable or disable via checkbox.
Bonus Entry Filter (Optional):
🔹 Green Candle Wick Breakout – optional pattern logic that detects bullish momentum when the high pierces above both MAs, with a green body.
Reset Mechanism:
🔁 Signal resets only after price closes back below all active MAs (5DMA and HMA if enabled), reducing noise and avoiding repeated signals during chop.
🧠 Why This Works:
This indicator captures the kind of setups that professional traders look for:
Momentum crossovers without chasing late.
Mean reversion snapbacks that align with fresh bullish moves.
Avoids premature entries by requiring clear structure above moving averages.
Optional HMA filter allows adaptability: turn it off during choppy markets or range conditions, and on during trending environments.
🔔 Features:
✅ Adjustable HMA Length
✅ Enable/Disable HMA Filter
✅ Optional Green Wick Breakout Detection
✅ Visual “Buy” label plotted below qualifying bars
✅ Real-time Alert Conditions for automated trading or manual alerts
🎯 Use Cases:
VIX-based ETFs (e.g., UVXY, VXX): Catch early breakouts aligned with volatility spikes.
Growth Stocks: Time pullback entries during bullish runs.
Futures/Indices: Combine with macro levels for intraday scalps or swing setups.
Overlay on Trend Filters: Combine with RSI, MACD, or VWAP for confirmation.
🛠️ Recommended Settings:
For smooth setups in volatile names, use:
HMA Length: 20
Keep green wick filter ON
For fast momentum trades, disable the HMA filter to act on 5DMA alone.
⭐ Final Thoughts:
This script is built to serve both systematic traders and discretionary scalpers who want actionable signals without noise or lag. The toggleable HMA feature lets you adjust sensitivity depending on market conditions — a key edge in adapting to volatility cycles.
Perfect for those who value clean, non-repainting entries rooted in logical structure.
Trend Blend
Trend blend is my new indicator. I use it to identify my bias when trading and filter out fake setups that are going in the wrong direction.
Trend blend utilises the 9 EMA (Red), 21 EMA (Black), and if you trade futures or Bitcoin, you can also use the VWAP (Blue).
There is also a table at the top right that displays the chart time frame bias
I prefer to use the 1-hour time frame for bias and execute the trades on 5-minute charts, mainly, and sometimes on the 1-minute for a smaller stoploss.
Here's an example of the trade I took during the London session on XAU/USD
1 hour bias was Bearish
Price broke out of the range
I waited for the London session to open, where I ended up taking a short on the 5-minute time frame as we broke out of the pre-London range
Entry was at the Fair Value Gap (5-minute bias was also Bearish as price traded into the FVG)
Stoploss was at the last high
Take Profit was the next major support level
Another set that I like to trade with the Trend blend is when price is trending bullish and price trades inside the 9 and 21 EMA, and there is a bullish candle closer above the 9 EMA with Stoploss below the low of the bullish candle and Take profit between 1-2 Risk to Reward
Same when there's a bearish trend, I wait for price to trade inside the 9 and 21 EMA, and I'll take sells when a bearish candle closes below the 9 EMA.
This setup works best in strong trends, or it can be used to enter a trade on a pullback or to scale into an existing trade.
ORB Breakout Indicator - NQ1!The purpose of this indicator is to assist traders in rapidly identifying high-probability Opening Range Breakout (ORB) setups on the NQ1! 1-minute time frame (Nasdaq Futures)
Key Features:
Opening Range: Automatically plots the high and low of the 1st 15min of the (NYSE session) (09:30–09:45 EST)
Breakout Signals : Illustrates the first candle that breaks upward or downward and:
Green arrow for a bullish breakout
Red arrow for a bearish breakout
Clean Visuals: Dynamic lines show the high and low of the ORB window for easy reference.
(DON'T USE THIS ONLY FOR ENTRY SIGNALS, PAIR THIS WITH OTHER INFLUENCES TO GET HIGH PROBABILITY BREAKOUTS)
Worldwide Sessions and Open Range BreakoutThis script shows when the various normal market hours for each of the major worldwide markets (Asia, New York, and London). It also draws a line on the opening range for each of these market sessions. The opening range defaults to the first 15 minutes of the session, but this can be customized.
This script does automatically handle the session times regardless of your time zone or what time frame you are on. No need to set anything! This probably can't handle non-normal trading days, such as partial days.
This script is made for futures, but would likely work for other markets, like Forex.
Intra_Candle_Welding by Chaitu50cIntra Candle Welding by Chaitu50c
This is a professional price action–based indicator designed to automatically detect and visualize *intra-candle reversal zones* using simple yet powerful logic. It highlights price levels where two consecutive opposite candles meet with a high probability of short-term market reaction.
Concept
The indicator identifies potential intraday support and resistance levels based on the "Intra Candle Welding" concept: when the close of one candle is very close to the open of the next candle, and the two candles have opposite directions (bullish followed by bearish, or bearish followed by bullish). These levels often attract market attention due to order flow imbalance created during such transitions.
How It Works
1. The indicator continuously monitors each new candle and checks if the current open is approximately equal to the previous close, within a configurable buffer.
2. It further ensures that the two candles form an opposite pair (green→red or red→green).
3. When a valid pair is detected, the indicator checks for existing active lines near this level. If no active line exists within the defined tolerance, it draws a new horizontal line at the detected level.
4. Each line is classified as either a potential resistance (from green→red pair) or support (from red→green pair).
5. Lines automatically extend rightward and update with each bar. If price breaks through the line beyond a configurable break buffer, the line stops extending and is visually marked as "broken."
6. The indicator intelligently manages the maximum number of lines on the chart by deleting the oldest ones when the limit is exceeded.
Use Case
Traders can use this tool to identify short-term reaction zones and potential intraday turning points. The highlighted levels act as temporary support and resistance areas where price frequently reacts. It is especially useful in fast-moving or volatile markets such as index futures or liquid stocks.
Features
* Automatically detects intra-candle reversal zones.
* Classifies zones as support (bottom) or resistance (top).
* Automatically updates and breaks lines when invalidated by price action.
* Adjustable parameters for flexibility:
* Equality Buffer
* Max Lines to Keep
* Line Suppression Tolerance
* Initial Extend Bars
* Break Buffer
* Line colors, widths, and styles (active and broken states)
* Efficient memory handling with capped line count.
* Minimalist and clean visual representation, suitable for overlay on any chart.
Recommended Settings
* Works best on intraday timeframes (1 min to 15 min).
* Tune the Equality Buffer and Tolerance parameters based on instrument volatility.
* Use conservative Break Buffer to avoid premature line invalidation.
Disclaimer
This is a tool to support discretionary trading decisions. It is not a standalone buy/sell signal generator. Users are advised to combine it with their own market context and risk management framework.
This indicator is released for the TradingView community for educational and practical trading use.
---
TradeQUO Herrick Payoff RSIHerrick Payoff Index RSI (HPI-RSI) with Signal Line
An advanced oscillator that measures market strength not just by price, but by "smart money flow."
This indicator is not a typical RSI. Instead of applying the Relative Strength Index to price alone, it calculates it on the cumulative Herrick Payoff Index (HPI) . This creates a unique oscillator that reflects the underlying sentiment and capital flow in the market.
What is the Herrick Payoff Index (HPI)?
The HPI is a classic sentiment indicator that combines three crucial elements to determine if money is flowing into or out of an asset:
Price Change: The direction and momentum of the market.
Trading Volume: The conviction behind the price movement.
Open Interest (OI): The total number of open contracts (mainly in futures), which indicates if new capital is entering the market.
By combining these factors, the HPI provides a more comprehensive picture of market strength than indicators based solely on price.
How This Indicator Works
The script follows a logical, multi-step process:
It calculates the raw Herrick Payoff Index for each bar.
It creates a cumulative sum of this index to generate a continuous money flow value.
This cumulative value is smoothed with a short-period EMA to reduce noise.
The RSI is then applied to this smoothed HPI value.
An additional, configurable signal line (moving average) is added to facilitate trading signals.
Interpretation and Application
You can use this indicator much like a standard RSI, but with the added context of money flow:
Overbought/Oversold: Values above 70 suggest an overbought condition, while values below 30 signal an oversold condition.
Signal Line Crossovers: A cross of the HPI-RSI line above the signal line can be seen as a bullish signal. A cross below can be seen as a bearish signal.
Divergences: Look for divergences between the indicator and the price. A bullish divergence (price makes a lower low, indicator makes a higher low) can indicate an upcoming move to the upside. A bearish divergence (price makes a higher high, indicator makes a lower high) can signal a potential move to the downside.
Settings
The indicator has been deliberately kept simple:
HPI Smoothing Length: Smoothing length (1-5) for the cumulative HPI.
RSI Length: The lookback period for the RSI calculation.
Signal Line Settings: Here you can enable/disable the signal line and customize its type and length.
Display Settings: Adjust the colors of the RSI and signal lines to your preference.
This indicator is a tool for analysis and should always be used in combination with other methods and a solid risk management strategy. Happy trading!
Open Interest-RSI + Funding + Fractal DivergencesIndicator — “Open Interest-RSI + Funding + Fractal Divergences”
A multi-factor oscillator that fuses Open-Interest RSI, real-time Funding-Rate data and price/OI fractal divergences.
It paints BUY/SELL arrows in its own pane and directly on the price chart, helping you spot spots where crowd positioning, leverage costs and price action contradict each other.
1 Purpose
OI-RSI – measures conviction behind position changes instead of price momentum.
Funding Rate – shows who pays to hold positions (longs → bull bias, shorts → bear bias).
Fractal Divergences – detects HH/LL in price that are not confirmed by OI-RSI.
Optional Funding filter – hides signals when funding is already extreme.
Together these elements highlight exhaustion points and potential mean-reversion trades.
2 Inputs
RSI / Divergence
RSI length – default 14.
High-OI level / Low-OI level – default 70 / 30.
Fractal period n – default 2 (swing width).
Fractals to compare – how many past swings to scan, default 3.
Max visible arrows – keeps last 50 BUY/SELL arrows for speed.
Funding Rate
mode – choose FR, Avg Premium, Premium Index, Avg Prem + PI or FR-candle.
Visual scale (×) – multiplies raw funding to fit 0-100 oscillator scale (default 10).
specify symbol – enable only if funding symbol differs from chart.
use lower tf – averages 1-min premiums for smoother intraday view.
show table – tiny two-row widget at chart edge.
Signal Filter
Use Funding filter – ON hides long signals when funding > Buy-threshold and short signals when funding < Sell-threshold.
BUY threshold (%) – default 0.00 (raw %).
SELL threshold (%) – default 0.00 (raw %).
(Enter funding thresholds as raw percentages, e.g. 0.01 = +0.01 %).
3 Visual Outputs
Sub-pane
Aqua OI-RSI curve with 70 / 50 / 30 reference lines.
Funding visualised according to selected mode (green above 0, red below 0, or other).
BUY / SELL arrows at oscillator extremes.
Price chart
Identical BUY / SELL arrows plotted with force_overlay = true above/below candles that formed qualifying fractals.
Optional table
Shows current asset ticker and latest funding value of the chosen mode.
4 Signal Logic (Summary)
Load _OI series and compute RSI.
Retrieve Funding-Rate + Premium Index (optionally from lower TF).
Find fractal swings (n bars left & right).
Check divergence:
Bearish – price HH + OI-RSI LH.
Bullish – price LL + OI-RSI HL.
If Funding-filter enabled, require funding < Buy-thr (long) or > Sell-thr (short).
Plot arrows and trigger two built-in alerts (Bearish OI-RSI divergence, Bullish OI-RSI divergence).
Signals are fixed once the fractal bar closes; they do not repaint afterwards.
5 How to Use
Attach to a liquid perpetual-futures chart (BTC, ETH, major Binance contracts).
If _OI or funding series is missing you’ll see an error.
Choose timeframe:
15 m – 4 h for intraday;
1 D+ for swing trades.
Lower TFs → more signals; raise Fractals to compare or use Funding filter to trim noise.
Trade checklist
Funding positive and rising → longs overcrowded.
Price makes higher high; OI-RSI makes lower high; Funding above Sell-threshold → consider short.
Reverse logic for longs.
Combine with trend filter (EMA ribbon, SuperTrend, etc.) so you fade only when price is stretched.
Automation – set TradingView alerts on the two alertconditions and send to webhooks/bots.
Performance tips
Keep Max visible arrows ≤ 50.
Disable lower-TF premium aggregation if script feels heavy.
6 Limitations
Some symbols lack _OI or funding history → script stops with a console message.
Binance Premium Index begins mid-2020; older dates show na.
Divergences confirm only after n bars (no forward repaint).
7 Changelog
v1.0 – 10 Jun 2025
Initial public release.
Added price-chart arrows via force_overlay.
DeltaStrike — Aggressive Candle Detector by Chaitu50cDeltaStrike — Aggressive Candle Detector
by Chaitu50c
DeltaStrike is a simple and effective tool designed to help traders identify the most aggressive candles on the chart in real time. It works purely on price action and internal candle dynamics, with no reliance on lagging indicators.
The indicator combines delta (directional strength), candle range, and volume to compute an overall aggressiveness score for each candle. When this score exceeds a dynamic threshold based on recent market behavior, the candle is marked as an aggressive move.
Aggressive bullish candles are plotted as green diamonds below the candle, while aggressive bearish candles are plotted as red diamonds above the candle. The goal is to help traders visually spot moments of strong directional pressure, where potential trends or reversals may emerge.
The detection logic adapts automatically to changing market volatility and volume, making it suitable for all instruments and timeframes, including index futures, equities, and forex.
An integrated dashboard on the chart displays live readings of the key components contributing to each candle’s aggressiveness score: delta ratio, range ratio, and volume ratio. This helps traders understand the internal structure of each aggressive move.
Features:
Dynamic aggressiveness detection based on delta, range, and volume
Adaptive threshold for consistent behavior across timeframes and instruments
Clean chart output with clear diamond markers only on selected candles
Live dashboard with internal metrics for advanced analysis
Simple, lightweight, and optimized for intraday and swing trading
Works with any instrument: index, equity, forex, commodity
DeltaStrike is intended as an objective visual aid to help traders focus on genuine moments of strong market intent, filtering out ordinary or passive price movement. It can be used standalone or in combination with your existing trading strategy.
P&L Entry Zone Marker (clean)This indicator is a simple visual calculator for futures traders.
It helps you track your long and short entry zones based on position size and average price.
🔹 Green line – recalculated long entry after averaging down.
🔹 Red line – short entry point.
You can manually input your initial entry, volume, averaging volume, and averaging price.
The script calculates your new average entry for long positions and plots both lines as full horizontal levels across the chart.
✳️ Useful for:
Visualizing break-even zones
Planning P&L zones for hedged positions
Quickly aligning your trades with market structure
✅ Clean version — no labels, just lines.
📉 Works on all symbols and timeframes.
VWAP Supply & Demand Zones PRO**Overview:**
This script represents a major evolution of the original "VWAP Supply and Demand Zones" indicator. Initially created to explore price interaction with VWAP, it has now matured into a robust and feature-rich tool for identifying high-probability zones of institutional buying and selling pressure. The update introduces volume and momentum validation, dynamic zone management, alert logic, and a visual dashboard (HUD) — all designed for improved precision and clarity. The structural improvements, anti-repainting logic, and significant added utility warranted releasing this as a new script rather than a minor update.
---
### What It Does:
This indicator dynamically detects **supply and demand zones** using VWAP-based logic combined with **volume** and **momentum confirmation**. When price crosses VWAP with strength, it identifies the potential zone of excess demand (below VWAP) or supply (above VWAP), marking it visually with colored regions on the chart.
Each zone is extended for a user-defined duration, monitored for touch interactions (tests), and tracked for possible breaks. The script helps traders interpret price behavior around these institutional zones as either **reversal** opportunities or **continuation** confirmation depending on context and strategy preference.
---
### How It Works:
* **VWAP Basis**: Zones are anchored at VWAP at the time of a significant cross.
* **Volume & Momentum Filters**: Crosses are only considered valid if backed by above-average volume and notable price momentum.
* **Zone Drawing**: Validated supply and demand zones are drawn as boxes on the chart. Each is extended forward for a customizable number of bars.
* **Touch Counting**: Zones track the number of price touches. Alerts are issued after a user-defined number of tests.
* **Break Detection**: If price closes significantly beyond a zone boundary, the zone is marked as broken and visually dimmed.
* **Visual Dashboard (HUD)**: A compact real-time HUD displays VWAP value, active zone counts, and current market bias.
---
### How to Use It:
**Reversal Trading:**
* Look for price **rejecting** a zone after touching it.
* Use rejection candles or secondary indicators (e.g., RSI divergence) to confirm.
* These setups may offer low-risk entries when price respects the zone.
**Continuation Trading:**
* A **break of a zone** suggests strong directional bias.
* Use confirmed zone breaks to enter in the direction of momentum.
* Ideal in trending environments, especially with high volume and ATR movement.
---
### Key Inputs:
* **VWAP Length**: Moving VWAP period (default: 20)
* **Zone Width %**: Percentage size of zone buffer (default: 0.5%)
* **Min Touches**: How many times price must test a zone before alerts trigger
* **Zone Extension**: How far into the future zones are projected
* **Volume & ATR Filters**: Ensure only strong, valid crossovers create zones
---
### Alerts:
You can enable alerts for:
* **New zone creation**
* **Zone tests (after minimum touch count)**
* **Zone breaks**
* **VWAP crosses**
* **Active presence inside a zone (entry conditions)**
These alerts help automate market monitoring, making it suitable for discretionary or systematic workflows.
---
### Why It's a New Script:
This is not a cosmetic update. The internal logic, signal generation, filtering methodology, visual engine, and UX framework have been entirely rebuilt from the ground up. The result is a highly adaptive, precision-oriented tool — appropriate for intraday scalpers and swing traders alike. It goes far beyond the original in terms of functionality and reliability, justifying a fresh release.
---
### Suitable Markets and Timeframes:
* Works across all liquid markets (crypto, equities, futures, forex)
* Best used on timeframes where volume data is stable (5m and above recommended)
* Recalibrate inputs for optimal detection across instruments
Session Status Table📌 Session Status Table
Session Status Table is an indicator that displays the real-time status of the four major trading sessions:
* 🇯🇵 Asia (Tokyo)
* 🇬🇧 London
* 🇺🇸 New York AM
* 🇺🇸 New York PM
It shows which sessions are currently open, how much time remains until they open or close, and optionally sends alerts in advance.
🧩 Features:
* Real-time session table — shows the status of each session on the chart.
* Color-coded statuses:
* 🟢 Green – Session is open
* 🔴 Red – Session is closed
* ⚪ Gray – Weekend
* Countdown timers until session open or close.
* User alerts — receive a notification a custom number of minutes before a session starts.
⚙️ Customization:
* Table position — fully configurable.
* Session colors — customizable for open, closed, and weekend states.
* Session labels — customizable with icons.
* Notifications:
* Enabled through TradingView's Alerts panel.
* User-defined lead time before session opens.
🕒 Time Zones:
All times are calculated in UTC to ensure consistency across different markets and regions, avoiding discrepancies from time zones and daylight saving time.
🚨 How to enable alerts:
1. Open the "Alerts" panel in TradingView.
2. Click "Create Alert".
3. In the condition dropdown, choose "Session Status Table".
4. Set to any alert() trigger.
5. Save — you'll be notified a set number of minutes before each session begins.
ℹ️ Technical Notes:
* Built with Pine Script version 6.
* Logically divided into clear sections: inputs, session calculations, table rendering, and alerts.
* Optimized for performance and reliability on all timeframes.
Ideal for traders who use session activity in their strategies — especially in Forex, crypto, and futures markets.
Risk-Adjusted Momentum Oscillator# Risk-Adjusted Momentum Oscillator (RAMO): Momentum Analysis with Integrated Risk Assessment
## 1. Introduction
Momentum indicators have been fundamental tools in technical analysis since the pioneering work of Wilder (1978) and continue to play crucial roles in systematic trading strategies (Jegadeesh & Titman, 1993). However, traditional momentum oscillators suffer from a critical limitation: they fail to account for the risk context in which momentum signals occur. This oversight can lead to significant drawdowns during periods of market stress, as documented extensively in the behavioral finance literature (Kahneman & Tversky, 1979; Shefrin & Statman, 1985).
The Risk-Adjusted Momentum Oscillator addresses this gap by incorporating real-time drawdown metrics into momentum calculations, creating a self-regulating system that automatically adjusts signal sensitivity based on current risk conditions. This approach aligns with modern portfolio theory's emphasis on risk-adjusted returns (Markowitz, 1952) and reflects the sophisticated risk management practices employed by institutional investors (Ang, 2014).
## 2. Theoretical Foundation
### 2.1 Momentum Theory and Market Anomalies
The momentum effect, first systematically documented by Jegadeesh & Titman (1993), represents one of the most robust anomalies in financial markets. Subsequent research has confirmed momentum's persistence across various asset classes, time horizons, and geographic markets (Fama & French, 1996; Asness, Moskowitz & Pedersen, 2013). However, momentum strategies are characterized by significant time-varying risk, with particularly severe drawdowns during market reversals (Barroso & Santa-Clara, 2015).
### 2.2 Drawdown Analysis and Risk Management
Maximum drawdown, defined as the peak-to-trough decline in portfolio value, serves as a critical risk metric in professional portfolio management (Calmar, 1991). Research by Chekhlov, Uryasev & Zabarankin (2005) demonstrates that drawdown-based risk measures provide superior downside protection compared to traditional volatility metrics. The integration of drawdown analysis into momentum calculations represents a natural evolution toward more sophisticated risk-aware indicators.
### 2.3 Adaptive Smoothing and Market Regimes
The concept of adaptive smoothing in technical analysis draws from the broader literature on regime-switching models in finance (Hamilton, 1989). Perry Kaufman's Adaptive Moving Average (1995) pioneered the application of efficiency ratios to adjust indicator responsiveness based on market conditions. RAMO extends this concept by incorporating volatility-based adaptive smoothing, allowing the indicator to respond more quickly during high-volatility periods while maintaining stability during quiet markets.
## 3. Methodology
### 3.1 Core Algorithm Design
The RAMO algorithm consists of several interconnected components:
#### 3.1.1 Risk-Adjusted Momentum Calculation
The fundamental innovation of RAMO lies in its risk adjustment mechanism:
Risk_Factor = 1 - (Current_Drawdown / Maximum_Drawdown × Scaling_Factor)
Risk_Adjusted_Momentum = Raw_Momentum × max(Risk_Factor, 0.05)
This formulation ensures that momentum signals are dampened during periods of high drawdown relative to historical maximums, implementing an automatic risk management overlay as advocated by modern portfolio theory (Markowitz, 1952).
#### 3.1.2 Multi-Algorithm Momentum Framework
RAMO supports three distinct momentum calculation methods:
1. Rate of Change: Traditional percentage-based momentum (Pring, 2002)
2. Price Momentum: Absolute price differences
3. Log Returns: Logarithmic returns preferred for volatile assets (Campbell, Lo & MacKinlay, 1997)
This multi-algorithm approach accommodates different asset characteristics and volatility profiles, addressing the heterogeneity documented in cross-sectional momentum studies (Asness et al., 2013).
### 3.2 Leading Indicator Components
#### 3.2.1 Momentum Acceleration Analysis
The momentum acceleration component calculates the second derivative of momentum, providing early signals of trend changes:
Momentum_Acceleration = EMA(Momentum_t - Momentum_{t-n}, n)
This approach draws from the physics concept of acceleration and has been applied successfully in financial time series analysis (Treadway, 1969).
#### 3.2.2 Linear Regression Prediction
RAMO incorporates linear regression-based prediction to project momentum values forward:
Predicted_Momentum = LinReg_Value + (LinReg_Slope × Forward_Offset)
This predictive component aligns with the literature on technical analysis forecasting (Lo, Mamaysky & Wang, 2000) and provides leading signals for trend changes.
#### 3.2.3 Volume-Based Exhaustion Detection
The exhaustion detection algorithm identifies potential reversal points by analyzing the relationship between momentum extremes and volume patterns:
Exhaustion = |Momentum| > Threshold AND Volume < SMA(Volume, 20)
This approach reflects the established principle that sustainable price movements require volume confirmation (Granville, 1963; Arms, 1989).
### 3.3 Statistical Normalization and Robustness
RAMO employs Z-score normalization with outlier protection to ensure statistical robustness:
Z_Score = (Value - Mean) / Standard_Deviation
Normalized_Value = max(-3.5, min(3.5, Z_Score))
This normalization approach follows best practices in quantitative finance for handling extreme observations (Taleb, 2007) and ensures consistent signal interpretation across different market conditions.
### 3.4 Adaptive Threshold Calculation
Dynamic thresholds are calculated using Bollinger Band methodology (Bollinger, 1992):
Upper_Threshold = Mean + (Multiplier × Standard_Deviation)
Lower_Threshold = Mean - (Multiplier × Standard_Deviation)
This adaptive approach ensures that signal thresholds adjust to changing market volatility, addressing the critique of fixed thresholds in technical analysis (Taylor & Allen, 1992).
## 4. Implementation Details
### 4.1 Adaptive Smoothing Algorithm
The adaptive smoothing mechanism adjusts the exponential moving average alpha parameter based on market volatility:
Volatility_Percentile = Percentrank(Volatility, 100)
Adaptive_Alpha = Min_Alpha + ((Max_Alpha - Min_Alpha) × Volatility_Percentile / 100)
This approach ensures faster response during volatile periods while maintaining smoothness during stable conditions, implementing the adaptive efficiency concept pioneered by Kaufman (1995).
### 4.2 Risk Environment Classification
RAMO classifies market conditions into three risk environments:
- Low Risk: Current_DD < 30% × Max_DD
- Medium Risk: 30% × Max_DD ≤ Current_DD < 70% × Max_DD
- High Risk: Current_DD ≥ 70% × Max_DD
This classification system enables conditional signal generation, with long signals filtered during high-risk periods—a approach consistent with institutional risk management practices (Ang, 2014).
## 5. Signal Generation and Interpretation
### 5.1 Entry Signal Logic
RAMO generates enhanced entry signals through multiple confirmation layers:
1. Primary Signal: Crossover between indicator and signal line
2. Risk Filter: Confirmation of favorable risk environment for long positions
3. Leading Component: Early warning signals via acceleration analysis
4. Exhaustion Filter: Volume-based reversal detection
This multi-layered approach addresses the false signal problem common in traditional technical indicators (Brock, Lakonishok & LeBaron, 1992).
### 5.2 Divergence Analysis
RAMO incorporates both traditional and leading divergence detection:
- Traditional Divergence: Price and indicator divergence over 3-5 periods
- Slope Divergence: Momentum slope versus price direction
- Acceleration Divergence: Changes in momentum acceleration
This comprehensive divergence analysis framework draws from Elliott Wave theory (Prechter & Frost, 1978) and momentum divergence literature (Murphy, 1999).
## 6. Empirical Advantages and Applications
### 6.1 Risk-Adjusted Performance
The risk adjustment mechanism addresses the fundamental criticism of momentum strategies: their tendency to experience severe drawdowns during market reversals (Daniel & Moskowitz, 2016). By automatically reducing position sizing during high-drawdown periods, RAMO implements a form of dynamic hedging consistent with portfolio insurance concepts (Leland, 1980).
### 6.2 Regime Awareness
RAMO's adaptive components enable regime-aware signal generation, addressing the regime-switching behavior documented in financial markets (Hamilton, 1989; Guidolin, 2011). The indicator automatically adjusts its parameters based on market volatility and risk conditions, providing more reliable signals across different market environments.
### 6.3 Institutional Applications
The sophisticated risk management overlay makes RAMO particularly suitable for institutional applications where drawdown control is paramount. The indicator's design philosophy aligns with the risk budgeting approaches used by hedge funds and institutional investors (Roncalli, 2013).
## 7. Limitations and Future Research
### 7.1 Parameter Sensitivity
Like all technical indicators, RAMO's performance depends on parameter selection. While default parameters are optimized for broad market applications, asset-specific calibration may enhance performance. Future research should examine optimal parameter selection across different asset classes and market conditions.
### 7.2 Market Microstructure Considerations
RAMO's effectiveness may vary across different market microstructure environments. High-frequency trading and algorithmic market making have fundamentally altered market dynamics (Aldridge, 2013), potentially affecting momentum indicator performance.
### 7.3 Transaction Cost Integration
Future enhancements could incorporate transaction cost analysis to provide net-return-based signals, addressing the implementation shortfall documented in practical momentum strategy applications (Korajczyk & Sadka, 2004).
## References
Aldridge, I. (2013). *High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems*. 2nd ed. Hoboken, NJ: John Wiley & Sons.
Ang, A. (2014). *Asset Management: A Systematic Approach to Factor Investing*. New York: Oxford University Press.
Arms, R. W. (1989). *The Arms Index (TRIN): An Introduction to the Volume Analysis of Stock and Bond Markets*. Homewood, IL: Dow Jones-Irwin.
Asness, C. S., Moskowitz, T. J., & Pedersen, L. H. (2013). Value and momentum everywhere. *Journal of Finance*, 68(3), 929-985.
Barroso, P., & Santa-Clara, P. (2015). Momentum has its moments. *Journal of Financial Economics*, 116(1), 111-120.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. New York: McGraw-Hill.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. *Journal of Finance*, 47(5), 1731-1764.
Calmar, T. (1991). The Calmar ratio: A smoother tool. *Futures*, 20(1), 40.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). *The Econometrics of Financial Markets*. Princeton, NJ: Princeton University Press.
Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). Drawdown measure in portfolio optimization. *International Journal of Theoretical and Applied Finance*, 8(1), 13-58.
Daniel, K., & Moskowitz, T. J. (2016). Momentum crashes. *Journal of Financial Economics*, 122(2), 221-247.
Fama, E. F., & French, K. R. (1996). Multifactor explanations of asset pricing anomalies. *Journal of Finance*, 51(1), 55-84.
Granville, J. E. (1963). *Granville's New Key to Stock Market Profits*. Englewood Cliffs, NJ: Prentice-Hall.
Guidolin, M. (2011). Markov switching models in empirical finance. In D. N. Drukker (Ed.), *Missing Data Methods: Time-Series Methods and Applications* (pp. 1-86). Bingley: Emerald Group Publishing.
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. *Econometrica*, 57(2), 357-384.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. *Journal of Finance*, 48(1), 65-91.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. *Econometrica*, 47(2), 263-291.
Kaufman, P. J. (1995). *Smarter Trading: Improving Performance in Changing Markets*. New York: McGraw-Hill.
Korajczyk, R. A., & Sadka, R. (2004). Are momentum profits robust to trading costs? *Journal of Finance*, 59(3), 1039-1082.
Leland, H. E. (1980). Who should buy portfolio insurance? *Journal of Finance*, 35(2), 581-594.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. *Journal of Finance*, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. *Journal of Finance*, 7(1), 77-91.
Murphy, J. J. (1999). *Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications*. New York: New York Institute of Finance.
Prechter, R. R., & Frost, A. J. (1978). *Elliott Wave Principle: Key to Market Behavior*. Gainesville, GA: New Classics Library.
Pring, M. J. (2002). *Technical Analysis Explained: The Successful Investor's Guide to Spotting Investment Trends and Turning Points*. 4th ed. New York: McGraw-Hill.
Roncalli, T. (2013). *Introduction to Risk Parity and Budgeting*. Boca Raton, FL: CRC Press.
Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. *Journal of Finance*, 40(3), 777-790.
Taleb, N. N. (2007). *The Black Swan: The Impact of the Highly Improbable*. New York: Random House.
Taylor, M. P., & Allen, H. (1992). The use of technical analysis in the foreign exchange market. *Journal of International Money and Finance*, 11(3), 304-314.
Treadway, A. B. (1969). On rational entrepreneurial behavior and the demand for investment. *Review of Economic Studies*, 36(2), 227-239.
Wilder, J. W. (1978). *New Concepts in Technical Trading Systems*. Greensboro, NC: Trend Research.
Demand Index (Hybrid Sibbet) by TradeQUODemand Index (Hybrid Sibbet) by TradeQUO \
\Overview\
The Demand Index (DI) was introduced by James Sibbet in the early 1990s to gauge “real” buying versus selling pressure by combining price‐change information with volume intensity. Unlike pure price‐based oscillators (e.g. RSI or MACD), the DI highlights moves backed by above‐average volume—helping traders distinguish genuine demand/supply from false breakouts or low‐liquidity noise.
\Calculation\
\
\ \Step 1: Weighted Price (P)\
For each bar t, compute a weighted price:
```
Pₜ = Hₜ + Lₜ + 2·Cₜ
```
where Hₜ=High, Lₜ=Low, Cₜ=Close of bar t.
Also compute Pₜ₋₁ for the prior bar.
\ \Step 2: Raw Range (R)\
Calculate the two‐bar range:
```
Rₜ = max(Hₜ, Hₜ₋₁) – min(Lₜ, Lₜ₋₁)
```
This Rₜ is used indirectly in the exponential dampener below.
\ \Step 3: Normalize Volume (VolNorm)\
Compute an EMA of volume over n₁ bars (e.g. n₁=13):
```
EMA_Volₜ = EMA(Volume, n₁)ₜ
```
Then
```
VolNormₜ = Volumeₜ / EMA_Volₜ
```
If EMA\_Volₜ ≈ 0, set VolNormₜ to a small default (e.g. 0.0001) to avoid division‐by‐zero.
\ \Step 4: BuyPower vs. SellPower\
Calculate “raw” BuyPowerₜ and SellPowerₜ depending on whether Pₜ > Pₜ₋₁ (bullish) or Pₜ < Pₜ₋₁ (bearish). Use an exponential dampener factor Dₜ to moderate extreme moves when true range is small. Specifically:
• If Pₜ > Pₜ₋₁,
```
BuyPowerₜ = (VolNormₜ) / exp
```
otherwise
```
BuyPowerₜ = VolNormₜ.
```
• If Pₜ < Pₜ₋₁,
```
SellPowerₜ = (VolNormₜ) / exp
```
otherwise
```
SellPowerₜ = VolNormₜ.
```
Here, H₀ and L₀ are the very first bar’s High/Low—used to calibrate the scale of the dampening. If the denominator of the exponential is near zero, substitute a small epsilon (e.g. 1e-10).
\ \Step 5: Smooth Buy/Sell Power\
Apply a short EMA (n₂ bars, typically n₂=2) to each:
```
EMA_Buyₜ = EMA(BuyPower, n₂)ₜ
EMA_Sellₜ = EMA(SellPower, n₂)ₜ
```
\ \Step 6: Raw Demand Index (DI\_raw)\
```
DI_rawₜ = EMA_Buyₜ – EMA_Sellₜ
```
A positive DI\_raw indicates that buying force (normalized by volume) exceeds selling force; a negative value indicates the opposite.
\ \Step 7: Optional EMA Smoothing on DI (DI)\
To reduce choppiness, compute an EMA over DI\_raw (n₃ bars, e.g. n₃ = 1–5):
```
DIₜ = EMA(DI_raw, n₃)ₜ.
```
If n₃ = 1, DI = DI\_raw (no further smoothing).
\
\Interpretation\
\
\ \Crossing Zero Line\
• DI\_raw (or DI) crossing from below to above zero signals that cumulative buying pressure (over the chosen smoothing window) has overcome selling pressure—potential Long signal.
• Crossing from above to below zero signals dominant selling pressure—potential Short signal.
\ \DI\_raw vs. DI (EMA)\
• When DI\_raw > DI (the EMA of DI\_raw), bullish momentum is accelerating.
• When DI\_raw < DI, bullish momentum is weakening (or bearish acceleration).
\ \Divergences\
• If price makes new highs while DI fails to make higher highs (DI\_raw or DI declining), this hints at weakening buying power (“bearish divergence”), possibly preceding a reversal.
• If price makes new lows while DI fails to make lower lows (“bullish divergence”), this may signal waning selling pressure and a potential bounce.
\ \Volume Confirmation\
• A strong price move without a corresponding rise in DI often indicates low‐volume “fake” moves.
• Conversely, a modest price move with a large DI spike suggests true institutional participation—often a more reliable breakout.
\
\Usage Notes & Warnings\
\
\ \Never Use DI in Isolation\
It is a \filter\ and \confirmation\ tool—combine with price‐action (trendlines, support/resistance, candlestick patterns) and risk management (stop‐losses) before executing trades.
\ \Parameter Selection\
• \Vol EMA length (n₁)\: Commonly 13–20 bars. Shorter → more responsive to volume spikes, but noisier.
• \Buy/Sell EMA length (n₂)\: Typically 2 bars for fast smoothing.
• \DI smoothing (n₃)\: Usually 1 (no smoothing) or 3–5 for moderate smoothing. Long DI\_EMA (e.g. 20–50) gives a slower signal.
\ \Market Adaptation\
Works well in liquid futures, indices, and heavily traded stocks. In thinly traded or highly erratic markets, adjust n₁ upward (e.g., 20–30) to reduce noise.
---
\In Summary\
The Demand Index (James Sibbet) uses a three‐stage smoothing (volume → Buy/Sell Power → DI) to reveal true demand/supply imbalance. By combining normalized volume with price change, Sibbet’s DI helps traders identify momentum backed by real participation—filtering out “empty” moves and spotting early divergences. Always confirm DI signals with price action and sound risk controls before trading.
COT-Index-NocTradingCOT Index Indicator
The COT Index Indicator is a powerful tool designed to visualize the Commitment of Traders (COT) data and offer insights into market sentiment. The COT Index is a measurement of the relative positioning of commercial traders versus non-commercial and retail traders in the futures market. It is widely used to identify potential market reversals by observing the extremes in trader positioning.
Customizable Timeframe: The indicator allows you to choose a custom time interval (in months) to visualize the COT data, making it flexible to fit different trading styles and strategies.
How to Use:
Visualize Market Sentiment: A COT Index near extremes (close to 0 or 100) can indicate potential turning points in the market, as it reflects extreme positioning of different market participant groups.
Adjust the Time Interval: The ability to adjust the time interval (in months) gives traders the flexibility to analyze the market over different periods, which can be useful in detecting longer-term trends or short-term shifts in sentiment.
Combine with Other Indicators: To enhance your analysis, combine the COT Index with your technical analysis.
This tool can serve as an invaluable addition to your trading strategy, providing a deeper understanding of the market dynamics and the positioning of major market participants.
atr stop loss for double SMA v6Strategy Name
atr stop loss for double SMA v6
Credit: This v6 update is based on Daveatt’s “BEST ATR Stop Multiple Strategy.”
Core Logic
Entry: Go long when the 15-period SMA crosses above the 45-period SMA; go short on the inverse cross.
Stop-Loss: On entry, compute ATR(14)×2.0 and set a fixed stop at entry ± that amount. Stop remains static until hit.
Trend Tracking: Uses barssince() to ensure only one active long or short position; stop is only active while that trend persists.
Visualization
Plots fast/slow SMA lines in teal/orange.
On each entry bar, displays a label showing “ATR value” and “ATR×multiple” positioned at the 30-bar low (long) or high (short).
Draws an “×” at the stop-price level in green (long) or red (short) while the position is open.
Execution Settings
Initial Capital: $100 000, Size = 100 shares per trade.
Commission: 0.075% per trade.
Pyramiding: 1.
Calculations: Only on bar close (no intra-bar ticks).
Usage Notes
Static ATR stop adapts to volatility but does not trail.
Ideal for trending, liquid markets (stocks, futures, FX).
Adjust SMA lengths or ATR multiple for faster/slower signals.
NSE/BSE Derivative - Next Expiry Date With HolidaysNSE & BSE Expiry Tracker with Holiday Adjustments
This Pine Script is a TradingView indicator that helps traders monitor upcoming expiry dates for major Indian derivative contracts. It dynamically adjusts these expiry dates based on weekends and holidays, and highlights any expiry that falls on the current day.
⸻
Key Features
1. Tracks Expiry Dates for Major Contracts
The script calculates and displays the next expiry dates for the following instruments:
• NIFTY (weekly expiry every Thursday)
• BANKNIFTY, FINNIFTY, MIDCPNIFTY, NIFTYNXT50 (monthly expiry on the last Thursday of the month)
• SENSEX (weekly expiry every Tuesday)
• BANKEX and SENSEX 50 (monthly expiry on the last Tuesday of the month)
• Stocks in the F&O segment (monthly expiry on the last Thursday)
2. Holiday Awareness
Users can input a list of holiday dates in the format YYYY-MM-DD,YYYY-MM-DD,.... If any calculated expiry falls on one of these holidays or a weekend, the script automatically adjusts the expiry to the previous working day (Monday to Friday).
3. Customization Options
The user can:
• Choose the position of the expiry table on the chart (e.g. top right, bottom left).
• Select the font size for the expiry table.
• Enable or disable the table entirely (if implemented as an input toggle).
4. Visual Expiry Highlighting
If today is an expiry day for any instrument, the script highlights that instrument in the display. This makes it easy to spot significant expiry days, which are often associated with increased volatility and trading volume.
⸻
How It Works
• The script calculates the next expiry for each index using built-in date/time functions.
• For weekly expiries, it finds the next occurrence of the designated weekday.
• For monthly expiries, it finds the last Thursday or Tuesday of the month.
• Each expiry date is passed through a check to adjust for holidays or weekends.
• If today matches the adjusted expiry date, that row is visually emphasized.
⸻
Use Case
This script is ideal for traders who want a quick glance at which instruments are expiring soon — especially those managing options, futures, or expiry-based strategies.
Volume pressure by GSK-VIZAG-AP-INDIA🔍 Volume Pressure by GSK-VIZAG-AP-INDIA
🧠 Overview
“Volume Pressure” is a multi-timeframe, real-time table-based volume analysis tool designed to give traders a clear and immediate view of buying and selling pressure across custom-selected timeframes. By breaking down buy volume, sell volume, total volume, and their percentages, this indicator helps traders identify demand/supply imbalances and volume momentum in the market.
🎯 Purpose / Trading Use Case
This indicator is ideal for intraday and short-term traders who want to:
Spot aggressive buying or selling activity
Track volume dynamics across multiple timeframes *1 min time frame will give best results*
Use volume pressure as a confirming tool alongside price action or trend-based systems
It helps determine when large buying/selling activity is occurring and whether such behavior is consistent across timeframes—a strong signal of institutional interest or volume-driven trend shifts.
🧩 Key Features & Logic
Real-Time Table Display: A clean, dynamic table showing:
Buy Volume
Sell Volume
Total Volume
Buy % of total volume
Sell % of total volume
Multi-Time frame Analysis: Supports 8 user-selectable custom time frames from 1 to 240 minutes, giving flexibility to analyze volume pressure at various granularities.
Color-Coded Volume Bias:
Green for dominant Buy pressure
Red for dominant Sell pressure
Yellow for Neutral
Intensity-based blinking for extreme values (over 70%)
Dynamic Data Calculation:
Uses volume * (close > open) logic to estimate buy vs sell volumes bar-by-bar, then aggregates by timeframe.
⚙️ User Inputs & Settings
Timeframe Selectors (TF1 to TF8): Choose any 8 timeframes you want to monitor volume pressure across.
Text & Color Settings:
Customize text colors for Buy, Sell, Total volumes
Choose Buy/Sell bias colors
Enable/disable blinking for visual emphasis on extremes
Table Appearance:
Set header color, metric background, and text size
Table positioning: top-right, bottom-right, etc.
Blinking Highlight Toggle: Enable this to visually highlight when Buy/Sell % exceeds 70%—a sign of strong pressure.
📊 Visual Elements Explained
The table has 6 rows and 10 columns:
Row 0: Headers for Today and TF1 to TF8
Rows 1–3: Absolute values (Buy Vol, Sell Vol, Total Vol)
Rows 4–5: Relative percentages (Buy %, Sell %), with dynamic background color
First column shows the metric names (e.g., “Buy Vol”)
Cells blink using alternate background colors if volume pressure crosses thresholds
💡 How to Use It Effectively
Use Buy/Sell % rows to confirm potential breakout trades or identify volume exhaustion zones
Look for multi-timeframe confluence: If 5 or more TFs show >70% Buy pressure, buyers are in control
Combine with price action (e.g., breakouts, reversals) to increase conviction
Suitable for equities, indices, futures, crypto, especially on lower timeframes (1m to 15m)
🏆 What Makes It Unique
Table-based MTF Volume Pressure Display: Most indicators only show volume as bars or histograms; this script summarizes and color-codes volume bias across timeframes in a tabular format.
Customization-friendly: Full control over colors, themes, and timeframes
Blinking Alerts: Rare visual feature to capture user attention during extreme pressure
Designed with performance and readability in mind—even for fast-paced scalping environments.
🚨 Alerts / Extras
While this script doesn’t include TradingView alert functions directly, the visual blinking serves as a strong real-time alert mechanism.
Future versions may include built-in alert conditions for buy/sell bias thresholds.
🔬 Technical Concepts Used
Volume Dissection using close > open logic (to estimate buyer vs seller pressure)
Simple aggregation of volume over custom timeframes
Table plotting using Pine Script table.new, table.cell
Dynamic color logic for bias identification
Custom blinking logic using na(bar_index % 2 == 0 ? colorA : colorB)
⚠️ Disclaimer
This indicator is a tool for analysis, not financial advice. Always backtest and validate strategies before using any indicator for live trading. Past performance is not indicative of future results. Use at your own risk and apply proper risk management.
✍️ Author & Signature
Indicator Name: Volume Pressure
Author: GSK-VIZAG-AP-INDIA
TradingView Username: prowelltraders
AMD Setup - Full (Long + Short) ICT ModelICTSNIPERKILLS!
Accumulation, Manipulation, Distribution (AMD) Script!
1. Clarifies Structure: Accumulation, Manipulation, Distribution (AMD)
The script visualizes the AMD framework:
Accumulation → Price ranges inside Initial Balance (IB).
Manipulation → Liquidity sweep above IB High or below IB Low.
Distribution → Market Structure Shift (MSS) confirms a directional move.
This gives you a narrative structure for each session, helping you avoid random trades.
🧠 2. Filters Out Noise with MSS Confirmation
It waits for:
A liquidity sweep (manipulation),
Followed by a market structure shift (MSS),
And then confirms an entry only after a candle closes beyond structure.
This structure:
Reduces false signals,
Improves trade timing,
Helps you align with smart money delivery.
🕘 3. Focuses on the Right Time Window (Initial Balance)
You only engage after the 10:30 AM EST close, once the Initial Balance is formed.This aligns with ICT's focus on:
Killzones (like 9:30–11:00),
Avoiding early overtrading,
Letting the market tip its hand first (through sweeps + MSS).
This timing logic supports discipline and consistency.
🟢🔴 4. Marks Entries with Risk/Reward Guidance
It plots:
AMD SHORT / LONG entries after MSS + candle confirmation,
Basic TP and SL visual markers using a static risk-reward (2:1),
Optional Fair Value Gaps (FVGs) for refinement zones.
While static, these help plan trades visually and frame targets quickly, especially if you're scalping or trading micro futures like MNQ.
📈 5. Alerts You in Real Time
Instead of manually watching:
You'll get alerts when sweeps or MSS setups appear.
You can stay focused during the killzone or walk away and return when signals trigger.
This supports patience and alert-based discipline.
💡
You already:
Use 15M/1M execution,
Wait for ERL or HOD/LOD sweeps,
Look for MSS + CISD,
Trade in killzones only,
Target 50–62–70% Fibs with SMT/FVG confluence.
This script:✅ Automates sweep + MSS detection✅ Plots AMD-based entries visually✅ Simplifies your killzone execution✅ Helps avoid FOMO by filtering setups✅ Keeps your journal entries clean with structure
Delta Volume Color CoderDelta Volume Color Coder - Smart Money Footprint Visualizer
OVERVIEW
The Delta Volume Color Coder is a clean, minimalist indicator that highlights candles with exceptional delta volume, helping you instantly identify where smart money is actively trading. Unlike complex volume indicators that clutter your chart, this tool simply colors candles when institutional-level volume appears, leaving your normal price action untouched.
WHAT IS DELTA VOLUME?
Delta volume represents the difference between buying and selling pressure within each candle. Positive delta indicates more aggressive buying, while negative delta shows stronger selling. When delta reaches extreme levels, it often signals institutional activity or significant market events.
KEY FEATURES
- Clean Chart Design - Only colors candles with significant delta volume
- No Chart Compression - Overlay indicator that doesn't distort price scales
- Smart Detection - Automatically calculates dynamic thresholds based on recent activity
- Customizable Thresholds - Adjust sensitivity to match your trading style
- Multiple Calculation Methods - Classic or Range-Based delta calculations
COLOR CODING (Default)
- White Candles - Extreme positive delta (massive institutional buying)
- Green Candles - High positive delta (strong buying pressure)
- Red Candles - High negative delta (strong selling pressure)
- Violet Candles - Extreme negative delta (massive institutional selling)
- Normal Candles - Unchanged (standard TradingView red/green)
HOW TO USE
1. Add to any chart - Works on all timeframes and instruments
2. Look for colored candles - These mark significant volume events
3. White/Violet candles often mark reversals or breakouts
4. Multiple colored candles in sequence indicate strong trends
5. Colored candles at support/resistance levels are especially significant
SETTINGS EXPLAINED
- Lookback Period (20) - Bars used to calculate average delta
- High Delta Threshold (1.5x) - Triggers green/red coloring
- Extreme Delta Threshold (2.5x) - Triggers white/violet coloring
- Delta Calculation - Classic (open/close) or Range Based (close position)
- Color Wicks - Option to color entire candle or just the body
- All colors fully customizable
TRADING APPLICATIONS
- Reversal Detection - White/violet candles often mark exhaustion points
- Breakout Confirmation - Colored candles on breakouts show conviction
- Support/Resistance - High delta at key levels indicates significance
- Trend Strength - Frequency of colored candles shows trend momentum
- Institutional Tracking - Extreme delta reveals where big players are active
BEST PRACTICES
- Lower timeframes (1-15m) - Use for scalping and day trading entries
- Higher timeframes (1H+) - Identify major accumulation/distribution
- Combine with price action - Most effective at key technical levels
- Watch for clusters - Multiple extreme candles = major event
- Volume confirmation - Extreme delta + high volume = highest significance
TIPS FOR SUCCESS
1. White candles after downtrends often mark bottoms
2. Violet candles after uptrends often mark tops
3. Consecutive colored candles confirm trend direction
4. Lack of colored candles = low volatility, potential breakout ahead
5. Extreme delta at round numbers indicates institutional interest
WHY THIS INDICATOR?
- Simple Yet Powerful - No complex analysis needed
- Instant Visual Feedback - See institutional activity at a glance
- Clean Charts - No overlays, lines, or clutter
- Real-Time Detection - Updates with each new candle
- Universal Application - Works on stocks, forex, crypto, futures
UNIQUE ADVANTAGES
Unlike traditional volume indicators that require separate panes or compress your chart, the Delta Volume Color Coder seamlessly integrates with your existing setup. It answers one simple question: "Where is the smart money trading RIGHT NOW?"
Perfect for traders who want institutional-level insights without the complexity. Just add to your chart and let the colors guide you to where the real action is happening.
