Full Session ATR Range (Live) - with Position ToggleBelow is a publication-ready text for the "Full Session ATR Range (Live) - with Position Toggle" indicator, written in a professional yet accessible style suitable for a trading community (e.g., TradingView or a blog). The text highlights the indicator's features, usage, and benefits, while avoiding overly technical jargon for a broad audience.
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### Introducing the Full Session ATR Range (Live) Indicator with Position Toggle
Enhance your trading strategy with the **Full Session ATR Range (Live) Indicator**, a powerful tool designed to provide real-time insights into market volatility and session dynamics. This customizable indicator, now available with a position toggle feature, compares the current session's range to a 10-day Average True Range (ATR), helping traders gauge market activity and anticipate potential movements.
#### Key Features
- **Live Range Tracking**: Displays the current session's range (high minus low) alongside a 10-day ATR, updated in real-time during market hours.
- **Session Mode Flexibility**: Includes an auto-toggle option to switch between Electronic Trading Hours (ETH) and Regular Trading Hours (RTH), adapting to your preferred trading session. Manually select ETH or RTH, or let the indicator auto-detect based on market hours.
- **Comprehensive Metrics**: Offers a detailed breakdown including:
- Range/Avg %: Percentage of the current range relative to the 10-day ATR.
- Points Left: Remaining points to reach the average range.
- 100% Range Up/Dn: Potential upper and lower targets based on the ATR difference.
- **Position Customization**: Adjust the table's location on your chart with options like top-left, top-right, middle-center, or bottom-right for optimal visibility.
- **Visual Appeal**: Features a customizable background and text color to match your chart theme.
#### How It Works
The indicator calculates the 10-day ATR using daily data and tracks the current session's range, resetting at the start of each day or session change. During market hours (e.g., 6 AM - 8 PM CDT, adjustable), it updates live, providing actionable insights. When the market is closed, it displays historical ATR while marking live metrics as "n/a" to avoid confusion. The ETH/RTH toggle ensures the range reflects either the full extended session or the core trading hours, tailored to your strategy.
#### Why Use It?
Whether you're a day trader monitoring intraday volatility or a swing trader assessing longer-term trends, this indicator helps you:
- Identify overextended or underactive sessions compared to historical norms.
- Plan entries and exits with targets based on the 100% Range Up/Dn levels.
- Stay informed with a clean, adjustable display that fits your workflow.
#### Installation & Customization
1. Add the indicator to your TradingView chart.
2. Adjust the ATR length (default: 10 days) and table position via the input settings.
3. Choose your session mode (Auto, ETH, or RTH) and customize colors to suit your style.
4. Test during market hours for live updates—note that static values may appear outside trading sessions.
#### Feedback & Support
This indicator is designed for flexibility and ease of use. Share your feedback or request enhancements by commenting below or contacting the developer. Happy trading!
在脚本中搜索"Futures"
Futures Key LevelsKey Levels — Sessions, Previous Ranges & Opens (Chicago-aligned sessions)
What it does
This indicator plots commonly used reference levels across multiple timeframes to help you frame the day and find confluence:
Sessions (Chicago TZ): London, New York, and Asia session high/low ranges.
Previous Period Ranges: Previous Day / Week / Month / Quarter / Year High/Low and optional Mid.
Opens: Current Daily / Weekly / Monthly / Quarterly / Yearly opens.
Intraday (4H): Previous 4-Hour High/Low + optional Mid.
Monday Range: Captures Monday’s High/Low (and optional Mid) to use as a weekly reference.
Price-scale markers: Optional markers that track key levels on the price scale without adding extra lines.
How it works (concepts & calculations)
Higher-timeframe values are retrieved using request.security() and update when a new period begins (e.g., previous day’s H/L become fixed at the start of the new day).
Session ranges are built from bar data within session windows using time(session, "America/Chicago"):
London: 02:00–05:00 CT
New York: 08:30–15:00 CT
Asia: 20:00–00:00 CT
“Mid” levels are simple midpoints between each period’s High and Low.
Merge Levels: when different levels land at the same price, their labels are merged to reduce clutter (e.g., “PDH / PWH”).
Why this version is useful / original bits
All-white baseline for clean charts; session colors stand out by design: London = Yellow, New York = Aquatic Blue, Asia = Red.
Right-anchored mode lets you park levels to the right side of the chart with a configurable anchor distance.
Label merging keeps the display minimal when multiple levels coincide.
Price-scale-only markers available when you prefer fewer lines on the chart.
Inputs & customization
Display Style: Standard or Right Anchored (+ distance controls).
Levels toggles: enable/disable each period (Daily/Weekly/Monthly/Quarterly/Yearly), Monday range, 4H range, and session ranges.
Text: optional shorthand labels (e.g., PDH/PDL, PWH/PWL).
Colors: global white theme, with session highlights; you can override in the Inputs.
Price-scale markers: on/off toggle.
How to use it
Use previous High/Low as liquidity pools and areas to watch for sweeps, breaks, or retests.
The Monday range often frames the rest of the week; breaks or rejections around Monday H/L can be informative.
The 4H previous range gives intraday context—great for mean-reversion vs. continuation reads.
Session ranges help you see where the active session expanded price and where liquidity may remain.
Notes & limitations
Sessions are computed in America/Chicago; higher-TF levels use the symbol’s exchange timezone.
This is an indicator, not a strategy; it does not place trades or claim performance.
Always combine levels with your own execution rules (structure, momentum, risk).
Credit: inspired by spacemanBTC; this version adds the all-white styling, Chicago-aligned sessions, right-anchoring, label merging, and price-scale markers.
Also my mentor to tell me about the levels
Disclaimer
This tool is for educational purposes only and is not financial advice. Markets involve risk; do your own research and manage risk appropriately.
Futures Multi-Asset Open Distance Table## Multi-Asset Open Distance Table - Quick Description
This Pine Script indicator displays a **real-time table** that tracks how far **three user-selected assets** are from their key opening price levels.
**What it shows:**
- **Three customizable assets** (default: NQ!, ES!, YM!)
- **Distance from 3 key opens** for each asset:
- **1800 ET Open** (Electronic trading session start)
- **0930 ET Open** (Regular market hours start)
- **Weekly Open** (Beginning of trading week)
**Visual features:**
- **Percentage changes** from each open level
- **Color coding**: Green for gains above opens, red for losses below opens
- **Direction arrows**: ▲ (above), ▼ (below), ■ (unchanged)
- **Customizable table position** and size
**Perfect for:**
- **Intraday traders** monitoring key session levels
- **Multi-timeframe analysis** across different market opens
- **Quick reference** to see which assets are performing relative to major opening levels
- **Session-based trading strategies** using 6PM and 9:30AM opens
The table updates in real-time and provides an at-a-glance view of where your chosen assets stand relative to these critical price reference points throughout the trading day.
Futures Rotation Strategy - Overlay (Tables & Signals)This strategy focuses on the laggards and leaders of the market indices and does some weird stuff and determines which to long or short.
Futures Weekly Open RangeThe weekly opening range ( high to low ) is calculated from the open of the market on Sunday (1800 EST) till the opening of the Bond Market on Monday morning (0800 EST). This is the first and most crucial range for the trading week. As ICT has taught, price is moving through an algorithm and as such is fractal; because price is fractal, the opening range can be calculated and projected to help determine if price is trending or consolidating. As well; this indicator can be used to incorporate his PO3 concept to enter above the weekly opening range for shorts if bearish, or entering below the opening range for longs if bullish.
This indicator takes the high and low of weekly opening range, plots those two levels, plots the opening price for the new week, and calculates the Standard Deviations of the range and plots them both above and below of the weekly opening range. These are all plotted through the week until the start of the new week.
The range is calculated by subtracting the high from the low during the specified time.
The mid-point is half of that range added to the low.
The Standard deviation is multiples of the range (up to 10) added to the high and subtracted
from the low.
At this time the indicator will only plot the Standard deviation lines on the minutes time frame below 1 hour.
Only the range and range lines will be plotted on the hourly chart.
Futures Tick and Point Value TableDisplays a table in the upper right corner of the chart showing the tick and point value in USD.
Really Key Levels█ OVERVIEW
This indicator shows the most useful and universally used key trading levels (and only those) in a visually appealing way. Its originality lies in the fact that it was developed due to being unable to find an indicator that wasn't cluttered with other features or far less relevant levels, or one that would indicate the bar causing the level (i.e., not just using a horizontal line over the whole chart), or one that was well-programmed and didn’t frequently refresh for many seconds for no obvious reason, taking far too long to do so for such a seemingly simple indicator.
█ FEATURES
Shows the most frequently used key levels in a visually appealing way
Indicates the bar that causes the level, with the line starting at that bar
Works correctly and consistently on both RTH and ETH charts
Lines can be optionally extended both left and right, if the user prefers
Works with US/European stocks and US futures (at least)
Configurable futures regular session (default time is for CME futures, e.g., ES/NQ, etc.)
Users can configure line colour, style, and thickness
Adjustable label locations to prevent overlap with other indicator labels
Nice defaults that look good, and a well-contrasting label text colour
Well-documented, high-quality, open-source code for those who are interested
█ CONCEPTS
The indicator shows the following levels by a line starting at the bar that causes them:
Current Day RTH High/Low (visible and updated only during RTH; visible with no further updates in the post-market)
Current Day RTH Open (only after the RTH open)
Pre-Market High/Low (as it develops in the pre-market and fixed after RTH open)
Previous Day RTH Close
Previous Day RTH High/Low
Previous Day Pre-Market High-Low
Two Days Ago RTH Close
Other levels may be added in future versions, if requested and if they are Really Key Levels.
Regarding futures: despite being a 23-hour market (for CME futures, 5 p.m. the previous day to 4 p.m. the current day), most trading activity takes place together with the RTH on stock exchanges in New York, 08:30 to 3 p.m. Central (Chicago) time. Therefore, a user-configurable regular market is defined at those times, with times before this (from 5 p.m. the previous day) being considered pre-market, and times after this (until 4 p.m.) being considered post-market.
Care was taken so that the code uses no hard-coded time zones, exchanges, or session times. For this reason, it can in principle work globally. However, it very much depends on the information provided by the exchange, which is reflected in built-in Pine Script variables (see Limitations below).
█ LIMITATIONS
Pre-market levels are not shown when viewing an RTH chart.
The indicator was developed and tested on US/European stocks and US futures. It may or may not work for stocks and futures in other countries (depending on their pre- and post-market definitions and what information the exchange provides to TradingView via the relevant built-in Pine Script variable). It does not work on other security types, especially those with a 24-hour market that don't have a uniquely defined daily close, implicit H/L time window, or a pre-market.
Cash And Carry Arbitrage BTC Compare Month 6 by SeoNo1Detailed Explanation of the BTC Cash and Carry Arbitrage Script
Script Title: BTC Cash And Carry Arbitrage Month 6 by SeoNo1
Short Title: BTC C&C ABT Month 6
Version: Pine Script v5
Overlay: True (The indicators are plotted directly on the price chart)
Purpose of the Script
This script is designed to help traders analyze and track arbitrage opportunities between the spot market and futures market for Bitcoin (BTC). Specifically, it calculates the spread and Annual Percentage Yield (APY) from a cash-and-carry arbitrage strategy until a specific expiry date (in this case, June 27, 2025).
The strategy helps identify profitable opportunities when the futures price of BTC is higher than the spot price. Traders can then buy BTC in the spot market and short BTC futures contracts to lock in a risk-free profit.
1. Input Settings
Spot Symbol: The real-time BTC spot price from Binance (BTCUSDT).
Futures Symbol: The BTC futures contract that expires in June 2025 (BTCUSDM2025).
Expiry Date: The expiration date of the futures contract, set to June 27, 2025.
These inputs allow users to adjust the symbols or expiry date according to their trading needs.
2. Price Data Retrieval
Spot Price: Fetches the latest closing price of BTC from the spot market.
Futures Price: Fetches the latest closing price of BTC futures.
Spread: The difference between the futures price and the spot price (futures_price - spot_price).
The spread indicates how much higher (or lower) the futures price is compared to the spot market.
3. Time to Maturity (TTM) and Annual Percentage Yield (APY) Calculation
Current Date: Gets the current timestamp.
Time to Maturity (TTM): The number of days left until the futures contract expires.
APY Calculation:
Formula:
APY = ( Spread / Spot Price ) x ( 365 / TTM Days ) x 100
This represents the annualized return from holding a cash-and-carry arbitrage position if the trader buys BTC at the spot price and sells BTC futures.
4. Display Information Table on the Chart
A table is created on the chart's top-right corner showing the following data:
Metric: Labels such as Spread and APY
Value: Displays the calculated spread and APY
The table automatically updates at the latest bar to display the most recent data.
5. Alert Condition
This sets an alert condition that triggers every time the script runs.
In practice, users can modify this alert to trigger based on specific conditions (e.g., APY exceeds a threshold).
6. Plotting the APY and Spread
APY Plot: Displays the annualized yield as a blue line on the chart.
Spread Plot: Visualizes the futures-spot spread as a red line.
This helps traders quickly identify arbitrage opportunities when the spread or APY reaches desirable levels.
How to Use the Script
Monitor Arbitrage Opportunities:
A positive spread indicates a potential cash-and-carry arbitrage opportunity.
The larger the APY, the more profitable the arbitrage opportunity could be.
Timing Trades:
Execute a buy on the BTC spot market and simultaneously sell BTC futures when the APY is attractive.
Close both positions upon futures contract expiry to realize profits.
Risk Management:
Ensure you have sufficient margin to hold both positions until expiry.
Monitor funding rates and volatility, which could affect returns.
Conclusion
This script is an essential tool for traders looking to exploit price discrepancies between the BTC spot market and futures market through a cash-and-carry arbitrage strategy. It provides real-time data on spreads, annualized returns (APY), and visual alerts, helping traders make informed decisions and maximize their profit potential.
Lot Size + Margin InfoThis indicator is designed to give Futures & Options traders instant access to lot size and estimated margin requirements for the instrument they are viewing — directly on their TradingView chart. It combines real-time symbol detection with a built-in, regularly updated margin lookup table (sourced from Kotak Securities’ published margin requirements), while also handling fallback logic for unknown or unsupported symbols.
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### What It Does
* Automatically Detects the Instrument Type
Identifies whether the current chart’s symbol is a futures contract, option, or a cash/spot instrument.
* Shows Accurate Lot Size
For supported F\&O symbols, it fetches the correct lot size directly from exchange data.
For options, it retrieves the lot size from the option’s point value.
For cash/spot symbols with linked futures, it uses the futures lot size.
* Calculates Estimated Margin
* For futures: `Lot Size × Current Price × Margin%` (Margin% sourced from the internal lookup table).
* For options: `Lot Size × Current Price` (simple multiplication, as options margin ≈ premium cost).
* For unsupported or non-FnO symbols: Displays "No FnO".
* Fallback Margin Logic
If a symbol is missing from the margin lookup table, the script applies a user-defined default margin percentage and highlights the data in orange to indicate it’s using fallback values.
* Debug Mode for Transparency
A toggle to display the exact symbol string used for fetching lot size and margin, so traders can verify the data source.
---
### How It Works
1. Symbol Normalization
The script standardizes symbol names to match the margin table format (e.g., converting `"NIFTY1!"` to `"NIFTY"`).
2. Type-Based Handling
* Futures – Uses point value for lot size, applies specific margin % from the table.
* Options – Uses option point value for lot size, margin is simply premium × lot size.
* Cash Symbols with Linked Futures – Attempts to find and use the associated futures contract for lot/margin data.
* Unsupported Symbols – Displays `"No FnO"`.
3. Margin Table Integration
The margin % table is manually updated from a reliable broker’s margin sheet (Kotak Securities) — ensuring alignment with real trading conditions.
4. Customizable Display
* Position (Top Right / Bottom Left / Bottom Right)
* Table background color, text color, font size, border width
* Editable label text for lot size and margin display
* Toggleable lot size and margin sections
---
### How to Use
1. Add the Indicator to Your Chart – Works on any NSE Futures, Options, or Cash symbol with linked F\&O.
2. Configure Display Settings – Choose whether to show lot size, margin, or both, and place the info table where you prefer.
3. Adjust Fallback Margin % – If you trade less common contracts, set your default margin % to reflect your broker’s requirement.
4. Enable Debug Mode (Optional) – To see the exact symbol source the script is using.
---
### Best For
* Intraday & Positional F\&O Traders who need instant clarity on lot size and margin before entering trades.
* Options Sellers & Buyers who want quick cost estimates.
* Traders Switching Symbols Quickly — saves time by removing the need to check the broker’s margin sheet manually.
---
💡 Pro Tip: Since margin requirements can change, keep the script updated whenever your broker revises margin data. This version’s margin table is updated as of 13-08-2025.
Intrabar Volume Delta — RealTime + History (Stocks/Crypto/Forex)Intrabar Volume Delta Grid — RealTime + History (Stocks/Crypto/Forex)
# Short Description
Shows intrabar Up/Down volume, Delta (absolute/relative) and UpShare% in a compact grid for both real-time and historical bars. Includes an MTF (M1…D1) dashboard, contextual coloring, density controls, and alerts on Δ and UpShare%. Smart historical splitting (“History Mode”) for Crypto/Futures/FX.
---
# What it does (Quick)
* **UpVol / DownVol / Δ / UpShare%** — visualizes order-flow inside each candle.
* **Real-time** — accumulates intrabar volume live by tick-direction.
* **History Mode** — splits Up/Down on closed bars via simple or range-aware logic.
* **MTF Dashboard** — one table view across M1, M5, M15, M30, H1, H4, D1 (Vol, Up/Down, Δ%, Share, Trend).
* **Contextual opacity** — stronger signals appear bolder.
* **Label density** — draw every N-th bar and limit to last X bars for performance.
* **Alerts** — thresholds for |Δ|, Δ%, and UpShare%.
---
# How it works (Real-Time vs History)
* **Real-time (open bar):** volume increments into **UpVolRT** or **DownVolRT** depending on last price move (↑ goes to Up, ↓ to Down). This approximates live order-flow even when full tick history isn’t available.
* **History (closed bars):**
* **None** — no split (Up/Down = 0/0). Safest for equities/indices with unreliable tick history.
* **Approx (Close vs Open)** — all volume goes to candle direction (green → Up 100%, red → Down 100%). Fast but yields many 0/100% bars.
* **Price Action Based** — splits by Close position within High-Low range; strength = |Close−mid|/(High−Low). Above mid → more Up; below mid → more Down. Falls back to direction if High==Low.
* **Auto** — **Stocks/Index → None**, **Crypto/Futures/FX → Approx**. If you see too many 0/100 bars, switch to **Price Action Based**.
---
# Rows & Meaning
* **Volume** — total bar volume (no split).
* **UpVol / DownVol** — directional intrabar volume.
* **Delta (Δ)** — UpVol − DownVol.
* **Absolute**: raw units
* **Relative (Δ%)**: Δ / (Up+Down) × 100
* **Both**: shows both formats
* **UpShare%** — UpVol / (Up+Down) × 100. >50% bullish, <50% bearish.
* Helpful icons: ▲ (>65%), ▼ (<35%).
---
# MTF Dashboard (🔧 Enable Dashboard)
A single table with **Vol, Up, Down, Δ%, Share, Trend (🔼/🔽/⏭️)** for selected timeframes (M1…D1). Great for a fast “panorama” read of flow alignment across horizons.
---
# Inputs (Grouped)
## Display
* Toggle rows: **Volume / Up / Down / Delta / UpShare**
* **Delta Display**: Absolute / Relative / Both
## Realtime & History
* **History Mode**: Auto / None / Approx / Price Action Based
* **Compact Numbers**: 1.2k, 1.25M, 3.4B…
## Theme & UI
* **Theme Mode**: Auto / Light / Dark
* **Row Spacing**: vertical spacing between rows
* **Top Row Y**: moves the whole grid vertically
* **Draw Guide Lines**: faint dotted guides
* **Text Size**: Tiny / Small / Normal / Large
## 🔧 Dashboard Settings
* **Enable Dashboard**
* **📏 Table Text Size**: Tiny…Huge
* **🦓 Zebra Rows**
* **🔲 Table Border**
## ⏰ Timeframes (for Dashboard)
* **M1…D1** toggles
## Contextual Coloring
* **Enable Contextual Coloring**: opacity by signal strength
* **Δ% cap / Share offset cap**: saturation caps
* **Min/Max transparency**: solid vs faint extremes
## Label Density & Size
* **Show every N-th bar**: draw labels only every Nth bar
* **Limit to last X bars**: keep labels only in the most recent X bars
## Colors
* Up / Down / Text / Guide
## Alerts
* **Delta Threshold (abs)** — |Δ| in volume units
* **UpShare > / <** — bullish/bearish thresholds
* **Enable Δ% Alert**, **Δ% > +**, **Δ% < −** — relative delta levels
---
# How to use (Quick Start)
1. Add the indicator to your chart (overlay=false → separate pane).
2. **History Mode**:
* Crypto/Futures/FX → keep **Auto** or switch to **Price Action Based** for richer history.
* Stocks/Index → prefer **None** or **Price Action Based** for safer splits.
3. **Label Density**: start with **Limit to last X bars = 30–150** and **Show every N-th bar = 2–4**.
4. **Contextual Coloring**: keep on to emphasize strong Δ% / Share moves.
5. **Dashboard**: enable and pick only the TFs you actually use.
6. **Alerts**: set thresholds (ideas below).
---
# Alerts (in TradingView)
Add alert → pick this indicator → choose any of:
* **Delta exceeds threshold** (|Δ| > X)
* **UpShare above threshold** (UpShare% > X)
* **UpShare below threshold** (UpShare% < X)
* **Relative Delta above +X%**
* **Relative Delta below −X%**
**Starter thresholds (tune per symbol & TF):**
* **Crypto M1/M5**: Δ% > +25…35 (bullish), Δ% < −25…−35 (bearish)
* **FX (tick volume)**: UpShare > 60–65% or < 40–35%
* **Stocks (liquid)**: set **Absolute Δ** by typical volume scale (e.g., 50k / 100k / 500k)
---
# Notes by Market Type
* **Crypto/Futures**: 24/7 and high liquidity — **Price Action Based** often gives nicer history splits than Approx.
* **Forex (FX)**: TradingView volume is typically **tick volume** (not true exchange volume). Treat Δ/Share as tick-based flow, still very useful intraday.
* **Stocks/Index**: historical tick detail can be limited. **None** or **Price Action Based** is a safer default. If you see too many 0/100% shares, switch away from Approx.
---
# “All Timeframes” accuracy
* Works on **any TF** (M1 → D1/W1).
* **Real-time accuracy** is strong for the open bar (live accumulation).
* **Historical accuracy** depends on your **History Mode** (None = safest, Approx = fastest/simplest, Price Action Based = more nuanced).
* The MTF dashboard uses `request.security` and therefore follows the same logic per TF.
---
# Trade Ideas (Use-Cases)
* **Scalping (M1–M5)**: a spike in Δ% + UpShare>65% + rising total Vol → momentum entries.
* **Intraday (M5–M30–H1)**: when multiple TFs show aligned Δ%/Share (e.g., M5 & M15 bullish), join the trend.
* **Swing (H4–D1)**: persistent Δ% > 0 and UpShare > 55–60% → structural accumulation bias.
---
# Advantages
* **True-feeling live flow** on the open bar.
* **Adaptable history** (three modes) to match data quality.
* **Clean visual layout** with guides, compact numbers, contextual opacity.
* **MTF snapshot** for quick bias read.
* **Performance controls** (last X bars, every N-th bar).
---
# Limitations & Care
* **FX uses tick volume** — interpret Δ/Share accordingly.
* **History Mode is an approximation** — confirm with trend/structure/liquidity context.
* **Illiquid symbols** can produce noisy or contradictory signals.
* **Too many labels** can slow charts → raise N, lower X, or disable guides.
---
# Best Practices (Checklist)
* Crypto/Futures: prefer **Price Action Based** for history.
* Stocks: **None** or **Price Action Based**; be cautious with **Approx**.
* FX: pair Δ% & UpShare% with session context (London/NY) and volatility.
* If labels overlap: tweak **Row Spacing** and **Text Size**.
* In the dashboard, keep only the TFs you actually act on.
* Alerts: start around **Δ% 25–35** for “punchy” moves, then refine per asset.
---
# FAQ
**1) Why do some closed bars show 0%/100% UpShare?**
You’re on **Approx** history mode. Switch to **Price Action Based** for smoother splits.
**2) Δ% looks strong but price doesn’t move — why?**
Δ% is an **order-flow** measure. Price also depends on liquidity pockets, sessions, news, higher-timeframe structure. Use confirmations.
**3) Performance slowdown — what to do?**
Lower **Limit to last X bars** (e.g., 30–100), increase **Show every N-th bar** (2–6), or disable **Draw Guide Lines**.
**4) Dashboard values don’t “match” the grid exactly?**
Dashboard is multi-TF via `request.security` and follows the history logic per TF. Differences are normal.
---
# Short “Store” Marketing Blurb
Intrabar Volume Delta Grid reveals the order-flow inside every candle (Up/Down, Δ, UpShare%) — live and on history. With smart history splitting, an MTF dashboard, contextual emphasis, and flexible alerts, it helps you spot momentum and bias across Crypto, Forex (tick volume), and Stocks. Tidy labels and compact numbers keep the panel readable and fast.
Clean Multi-Indicator Alignment System
Overview
A sophisticated multi-indicator alignment system designed for 24/7 trading across all markets, with pure signal-based exits and no time restrictions. Perfect for futures, forex, and crypto markets that operate around the clock.
Key Features
🎯 Multi-Indicator Confluence System
EMA Cross Strategy: Fast EMA (5) and Slow EMA (10) for precise trend direction
VWAP Integration: Institution-level price positioning analysis
RSI Momentum: 7-period RSI for momentum confirmation and reversal detection
MACD Signals: Optimized 8/17/5 configuration for scalping responsiveness
Volume Confirmation: Customizable volume multiplier (default 1.6x) for signal validation
🚀 Advanced Entry Logic
Initial Full Alignment: Requires all 5 indicators + volume confirmation
Smart Continuation Entries: EMA9 pullback entries when trend momentum remains intact
Flexible Time Controls: Optional session filtering or 24/7 operation
🎪 Pure Signal-Based Exits
No Forced Closes: Positions exit only on technical signal reversals
Dual Exit Conditions: EMA9 breakdown + RSI flip OR MACD cross + EMA20 breakdown
Trend Following: Allows profitable trends to run their full course
Perfect for Swing Scalping: Ideal for multi-session position holding
📊 Visual Interface
Real-Time Status Dashboard: Live alignment monitoring for all indicators
Color-Coded Candles: Instant visual confirmation of entry/exit signals
Clean Chart Display: Toggle-able EMAs and VWAP with professional styling
Signal Differentiation: Clear labels for entries, X-crosses for exits
🔔 Alert System
Entry Notifications: Separate alerts for buy/sell signals
Exit Warnings: Technical breakdown alerts for position management
Mobile Ready: Push notifications to TradingView mobile app
Market Applications
Perfect For:
Gold Futures (GC): 24-hour precious metals trading
NASDAQ Futures (NQ): High-volatility index scalping
Forex Markets: Currency pairs with continuous operation
Crypto Trading: 24/7 cryptocurrency momentum plays
Energy Futures: Oil, gas, and commodity swing trades
Optimal Timeframes:
1-5 Minutes: Ultra-fast scalping during high volatility
5-15 Minutes: Balanced approach for most markets
15-30 Minutes: Swing scalping for trend following
🧠 Smart Position Management
Tracks implied position direction
Prevents conflicting signals
Allows trend continuation entries
State-aware exit logic
⚡ Scalping Optimized
Fast-reacting indicators with shorter periods
Volume-based confirmation reduces false signals
Clean entry/exit visualization
Minimal lag for time-sensitive trades
Configuration Options
All parameters fully customizable:
EMA Lengths: Adjustable from 1-30 periods
RSI Period: 1-14 range for different market conditions
MACD Settings: Fast (1-15), Slow (1-30), Signal (1-10)
Volume Confirmation: 0.5-5.0x multiplier range
Visual Preferences: Colors, displays, and table options
Risk Management Features
Clear visual exit signals prevent emotion-based decisions
Volume confirmation reduces false breakouts
Multi-indicator confluence improves signal quality
Optional time filtering for session-specific strategies
Best Use Cases
Futures Scalping: NQ, ES, GC during active sessions
Forex Swing Trading: Major pairs during overlap periods
Crypto Momentum: Bitcoin, Ethereum trend following
24/7 Automated Systems: Algorithmic trading implementation
Multi-Market Scanning: Portfolio-wide signal monitoring
BTC Future Gamma-Weighted Momentum Model (BGMM)The BTC Future Gamma-Weighted Momentum Model (BGMM) is a quantitative trading strategy that utilizes the Gamma-weighted average price (GWAP) in conjunction with a momentum-based approach to predict price movements in the Bitcoin futures market. The model combines the concept of weighted price movements with trend identification, where the Gamma factor amplifies the weight assigned to recent prices. It leverages the idea that historical price trends and weighting mechanisms can be utilized to forecast future price behavior.
Theoretical Background:
1. Momentum in Financial Markets:
Momentum is a well-established concept in financial market theory, referring to the tendency of assets to continue moving in the same direction after initiating a trend. Any observed market return over a given time period is likely to continue in the same direction, a phenomenon known as the “momentum effect.” Deviations from a mean or trend provide potential trading opportunities, particularly in highly volatile assets like Bitcoin.
Numerous empirical studies have demonstrated that momentum strategies, based on price movements, especially those correlating long-term and short-term trends, can yield significant returns (Jegadeesh & Titman, 1993). Given Bitcoin’s volatile nature, it is an ideal candidate for momentum-based strategies.
2. Gamma-Weighted Price Strategies:
Gamma weighting is an advanced method of applying weights to price data, where past price movements are weighted by a Gamma factor. This weighting allows for the reinforcement or reduction of the influence of historical prices based on an exponential function. The Gamma factor (ranging from 0.5 to 1.5) controls how much emphasis is placed on recent data: a value closer to 1 applies an even weighting across periods, while a value closer to 0 diminishes the influence of past prices.
Gamma-based models are used in financial analysis and modeling to enhance a model’s adaptability to changing market dynamics. This weighting mechanism is particularly advantageous in volatile markets such as Bitcoin futures, as it facilitates quick adaptation to changing market conditions (Black-Scholes, 1973).
Strategy Mechanism:
The BTC Future Gamma-Weighted Momentum Model (BGMM) utilizes an adaptive weighting strategy, where the Bitcoin futures prices are weighted according to the Gamma factor to calculate the Gamma-Weighted Average Price (GWAP). The GWAP is derived as a weighted average of prices over a specific number of periods, with more weight assigned to recent periods. The calculated GWAP serves as a reference value, and trading decisions are based on whether the current market price is above or below this level.
1. Long Position Conditions:
A long position is initiated when the Bitcoin price is above the GWAP and a positive price movement is observed over the last three periods. This indicates that an upward trend is in place, and the market is likely to continue in the direction of the momentum.
2. Short Position Conditions:
A short position is initiated when the Bitcoin price is below the GWAP and a negative price movement is observed over the last three periods. This suggests that a downtrend is occurring, and a continuation of the negative price movement is expected.
Backtesting and Application to Bitcoin Futures:
The model has been tested exclusively on the Bitcoin futures market due to Bitcoin’s high volatility and strong trend behavior. These characteristics make the market particularly suitable for momentum strategies, as strong upward or downward movements are often followed by persistent trends that can be captured by a momentum-based approach.
Backtests of the BGMM on the Bitcoin futures market indicate that the model achieves above-average returns during periods of strong momentum, especially when the Gamma factor is optimized to suit the specific dynamics of the Bitcoin market. The high volatility of Bitcoin, combined with adaptive weighting, allows the model to respond quickly to price changes and maximize trading opportunities.
Scientific Citations and Sources:
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91.
• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637–654.
• Fama, E. F., & French, K. R. (1992). The Cross-Section of Expected Stock Returns. The Journal of Finance, 47(2), 427–465.
Market Regime IndexThe Market Regime Index is a top-down macro regime nowcasting tool that offers a consolidated view of the market’s risk appetite. It tracks 32 of the world’s most influential markets across asset classes to determine investor sentiment by applying trend-following signals to each independent asset. It features adjustable parameters and a built-in alert system that notifies investors when conditions transition between Risk-On and Risk-Off regimes. The selected markets are grouped into equities (7), fixed income (9), currencies (7), commodities (5), and derivatives (4):
Equities = S&P 500 E-mini Index Futures, Nasdaq-100 E-mini Index Futures, Russell 2000 E-mini Index Futures, STOXX Europe 600 Index Futures, Nikkei 225 Index Futures, MSCI Emerging Markets Index Futures, and S&P 500 High Beta (SPHB)/Low Beta (SPLV) Ratio.
Fixed Income = US 10Y Treasury Yield, US 2Y Treasury Yield, US 10Y-02Y Yield Spread, German 10Y Bund Yield, UK 10Y Gilt Yield, US 10Y Breakeven Inflation Rate, US 10Y TIPS Yield, US High Yield Option-Adjusted Spread, and US Corporate Option-Adjusted Spread.
Currencies = US Dollar Index (DXY), Australian Dollar/US Dollar, Euro/US Dollar, Chinese Yuan/US Dollar, Pound Sterling/US Dollar, Japanese Yen/US Dollar, and Bitcoin/US Dollar.
Commodities = ICE Brent Crude Oil Futures, COMEX Gold Futures, COMEX Silver Futures, COMEX Copper Futures, and S&P Goldman Sachs Commodity Index (GSCI) Futures.
Derivatives = CBOE S&P 500 Volatility Index (VIX), ICE US Bond Market Volatility Index (MOVE), CBOE 3M Implied Correlation Index, and CBOE VIX Volatility Index (VVIX)/VIX.
All assets are directionally aligned with their historical correlation to the S&P 500. Each asset contributes equally based on its individual bullish or bearish signal. The overall market regime is calculated as the difference between the number of Risk-On and Risk-Off signals divided by the total number of assets, displayed as the percentage of markets confirming each regime. Green indicates Risk-On and occurs when the number of Risk-On signals exceeds Risk-Off signals, while red indicates Risk-Off and occurs when the number of Risk-Off signals exceeds Risk-On signals.
Bullish Signal = (Fast MA – Slow MA) > (ATR × ATR Margin)
Bearish Signal = (Fast MA – Slow MA) < –(ATR × ATR Margin)
Market Regime = (Risk-On signals – Risk-Off signals) ÷ Total assets
This indicator is designed with flexibility in mind, allowing users to include or exclude individual assets that contribute to the market regime and adjust the input parameters used for trend signal detection. These parameters apply to each independent asset, and the overall regime signal is smoothed by the signal length to reduce noise and enhance reliability. Investors can position according to the prevailing market regime by selecting factors that have historically outperformed under each regime environment to minimise downside risk and maximise upside potential:
Risk-On Equity Factors = High Beta > Cyclicals > Low Volatility > Defensives.
Risk-Off Equity Factors = Defensives > Low Volatility > Cyclicals > High Beta.
Risk-On Fixed Income Factors = High Yield > Investment Grade > Treasuries.
Risk-Off Fixed Income Factors = Treasuries > Investment Grade > High Yield.
Risk-On Commodity Factors = Industrial Metals > Energy > Agriculture > Gold.
Risk-Off Commodity Factors = Gold > Agriculture > Energy > Industrial Metals.
Risk-On Currency Factors = Cryptocurrencies > Foreign Currencies > US Dollar.
Risk-Off Currency Factors = US Dollar > Foreign Currencies > Cryptocurrencies.
In summary, the Market Regime Index is a comprehensive macro risk-management tool that identifies the current market regime and helps investors align portfolio risk with the market’s underlying risk appetite. Its intuitive, color-coded design makes it an indispensable resource for investors seeking to navigate shifting market conditions and enhance risk-adjusted performance by selecting factors that have historically outperformed. While it has proven historically valuable, asset-specific characteristics and correlations evolve over time as market dynamics change.
Synthetic Implied APROverview
The Synthetic Implied APR is an artificial implied APR, designed to imitate the implied APR seen when trading cryptocurrency funding rates. It combines real-time funding rates with premium data to calculate an artificial market expectation of the annualized funding rate.
The (actual) implied APR is the market's expectation of the annualized funding rate. This is dependent on bid/ask impacts of the implied APR, something which is currently unavailable to fetch with TradingView. In essence, an implied APR of X% means traders believe that asset's funding fees to average X% when annualized.
What's important to understand, is that the actual value of the synthetic implied APR is not relevant. We only simply use its relative changes when we trade (i.e if it crosses above/below its MA for a given weight). Even for the same asset, the implied APRs will change depending on days to maturity.
How it calculates
The synthetic implied APR is calculated with these steps:
Collects premium data from perpetual futures markets using optimized lower timeframe requests (check my 'Predicted Funding Rates' indicator)
Calculates the funding rate by adding the premium to an interest rate component (clamped within exchange limits)
Derives the underlying APR from the 8-hour funding rate (funding rate × 3 × 365)
Apply a weighed formula that imitates both the direction (underlying APR) with the volatility of prices (from the premium index and funding)
premium_component = (prem_avg / 50 ) * 365
weighedprem = (weight * fr) + ((1 - weight) * apr) + (premium_component * 0.3)
impliedAPR = math.avg(weighedprem, ta.sma(apr, maLength))
How to use it: Generally
Preface: Funding rates are an indication of market sentiment
If funding is positive, generally the market is bullish as longs are willing to pay shorts funding
If funding is negative, generally the market is bearish as shorts are willing to pay longs funding
So, this script can be used like a typical oscillator:
Bullish: If implied APR > MA OR if implied APR MA is green
Bearish: If implied APR < MA OR if implied APR MA is red
The components:
Synthetic Implied APR: The main metric. At current setting of 0.7, it imitates volatility
Weight: The higher the value, the smoother the synthetic implied APR is (and MA too). This value is very important to the imitation. At 0.7, it imitates the actual volatility of the implied APR. At weight = 1, it becomes very smooth. Perfect for trading
Synthetic Implied APR Moving Average: A moving average of the Synthetic implied APR. Can choose from multiple selections, (SMA, EMA, WMA, HMA, VWMA, RMA)
How to use it: Trading Funding
When trading funding there're multiple ways to use it with different settings
Trade funding rates with trend changes
Settings: Weight = 1
Method 1: When the implied APR MA turns green, long funding rates (or short if red)
Method 2: When the implied APR crosses above the MA, long funding rates (or short when crosses below)
Trade funding rates with MA pullbacks
Settings: Weight = 0.7, timeframe 15m
In an uptrend: When implied APR crosses below then above the script, long funding opportunity
In an downtrend: When implied APR crosses above then below the script, shortfunding opportunity
You can determine the trend with the method before, using a weight of 1
To trade funding rates, it's best to have these 3 scripts at these settings:
Predicted Funding Rates: This allows you to see the predicted funding rates and see if they've maxxed out for added confluence too (+/-0.01% usually for Binance BTC futures)
Synthetic implied APR: At weight 1, the MA provides a good trend (whether close above/below or colour change)
Synthetic implied APR: At weight 0.7, it provides a good imitation of volatility
How to use it: Trading Futures
When trading futures:
You can determine roughly what the trend is, if the assumption is made that funding rates can help identify trends if used as a sentiment indicator. It should be supplemented with traditional trend trading methods
To prevent whipsaws, weight should remain high
Long trend: When the implied APR MA turns green OR when it crosses above its MA
Short trend: When the implied APR MA turns red OR when it below above its MA
Why it's original
This indicator introduces a unique synthetic weighting system that combines funding rates, underlying APR, and premium components in a way not found in existing TradingView scripts. Trading funding rates is a niche area, there aren't that many scripts currently available. And to my knowledge, there's no synthetic implied APR scripts available on TradingView either. So I believe this script to be original in that sense.
Notes
Because it depends on my triangular weighting algos, optimal accuracy is found on timeframes that are 4H or less. On higher timeframes, the accuracy drops off. Best timeframes for intraday trading using this are 15m or 1 hour
The higher the timeframe, the lower the MA one should use. At 1 hour, 200 or higher is best. At say, 4h, length of 50 is best
Only works for coins that have a Binance premium index
Inputs
Funding Period - Select between "1 Hour" or "8 Hour" funding cycles. 8 hours is standard for Binance
Table - Toggle the information dashboard on/off to show or hide real-time metrics including funding rate, premium, and APR value
Weight - Controls the balance between funding rate (higher values = smoother) and APR (lower values = more responsive) in the calculation, ranging from 0.0 to 1.0. Default is 0.7, this imitates the volatility
Auto Timeframe Implied Length - Automatically calculates optimal smoothing length based on your chart timeframe for consistent behavior across different time periods
Manual Implied Length - Sets a fixed smoothing length (in bars) when auto mode is disabled, with lower values being more responsive and higher values being smoother
Show Implied APR MA - Displays an additional moving average line of the Synthetic Implied APR to help identify trend direction and crossover signals
MA Type for Implied APR - Selects the calculation method (SMA, EMA, WMA, HMA, VWMA, or RMA) for the moving average, each offering different responsiveness and lag characteristics
MA Length for Implied APR - Sets the lookback period (1-500 bars) for the moving average, with shorter lengths providing more signals and longer lengths filtering noise
Show Underlying APR - Displays the raw APR calculation (without synthetic weighting) as a reference line to compare against the main indicator
Bullish Color - Sets the color for positive values in the table and rising MA line
Bearish Color - Sets the color for negative values in the table and falling MA line
Table Background - Customizes the background color and transparency of the information dashboard
Table Text Color - Sets the color for label text in the left column of the information table
Table Text Size - Controls the font size of table text with options from Tiny to Huge
VWAP Momentum Oscillator How It Works
Core Calculation Method
The oscillator combines four key market measurements into a single, normalized reading:
1. Price-VWAP Deviation: `(Close - VWAP) / VWAP × 100`
2. VWAP-MA Momentum: `(VWAP - MovingAverage) / MovingAverage × 100`
3. Anchored VWAP Strength: Average of high/low anchor deviations from rolling VWAP
4. Range Position: `(Close - PeriodLow) / (PeriodHigh - PeriodLow) × 100 - 50`
Dynamic Signal Line
The signal line uses an EMA that automatically adjusts its length based on your chart timeframe:
- Futures: Always covers 23 hours of trading (1,380 minutes)
- Stocks: Always covers 6.5 hours of trading (390 minutes)
- Examples: 276 periods on 5-min futures chart, 1,380 periods on 1-min futures chart
Trading Signals
🟢 Buy Signals
- Condition: Main oscillator crosses above signal line while below zero
- Logic: Momentum turning bullish from oversold conditions
- Visual: Green "BUY" label below price action
🔴 Sell Signals
- Condition: Main oscillator crosses below signal line while above zero
- Logic: Momentum turning bearish from overbought conditions
- Visual: Red "SELL" label above price action
⚠️ Extreme Warnings
- Extreme Overbought: Red triangle when oscillator crosses above +4.0
- Extreme Oversold: Green triangle when oscillator crosses below -4.0
- Purpose: Risk management alerts, not entry/exit signals
Oscillator Zones
Interpretation Guide
- Above +2.0: Strong bullish momentum zone (green background)
- 0 to +2.0: Mild bullish territory
- 0 to -2.0: Mild bearish territory
- Below -2.0: Strong bearish momentum zone (red background)
- Above +4.0: Extreme overbought (caution advised)
- Below -4.0: Extreme oversold (potential reversal zone)
Customization Options
Moving Average Settings
- EMA/SMA Toggle: Choose between exponential or simple moving average
- Color Customization: Adjust MA line color and width
Visual Controls
- Bullish/Bearish Colors: Customize momentum zone colors
- Signal Line: Toggle visibility and adjust color
- Line Widths: Control thickness of all plot lines
Anchor Modes
- NY Session Only: Anchors reset at NY market open (9:30 AM ET)
- 24H NY Day: Anchors reset at NY calendar day change (midnight ET)
Best Practices
Timeframe Selection
- Scalping: 1-5 minute charts for quick momentum changes
- Day Trading: 5-15 minute charts for clearer trend signals
- Swing Trading: 1-4 hour charts for major momentum shifts
Signal Confirmation
- Wait for crossovers: Don't trade on oscillator position alone
- Respect extreme levels: Exercise caution above +4 or below -4
- Use with price action: Combine with support/resistance levels
Risk Management
- Extreme zones: Reduce position size when oscillator is extended
- Failed signals: Exit quickly if momentum doesn't follow through
- Market context: Consider overall trend direction and market volatility
Technical Specifications
Calculation Components
- Base Length: 1,380 periods (futures) / 390 periods (stocks)
- Signal Line: Dynamic EMA covering one full trading day
- Smoothing: 3-period SMA on raw oscillator (adjustable)
- Update Frequency: Real-time on every price tick
Performance Notes
- Resource Efficient: Optimized calculations minimize CPU usage
- Memory Friendly: Uses incremental VWAP calculations
- Fast Loading: Minimal historical data requirements
Version History & Development
This oscillator evolved from advanced VWAP overlay strategies, transforming complex multi-line analysis into a single, actionable momentum gauge. The indicator maintains the sophistication of institutional VWAP analysis while providing the clarity needed for retail trading decisions.
Core Philosophy
Traditional VWAP indicators show where price is relative to volume-weighted averages, but they don't quantify momentum or provide clear entry/exit signals. This oscillator solves that problem by normalizing all VWAP relationships into a single, bounded indicator that works consistently across all timeframes and asset classes.
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Open Source License: This indicator is provided free for the TradingView community. Feel free to modify and enhance according to your trading needs.
Request█ OVERVIEW
This library is a tool for Pine Script™ programmers that consolidates access to a wide range of lesser-known data feeds available on TradingView, including metrics from the FRED database, FINRA short sale volume, open interest, and COT data. The functions in this library simplify requests for these data feeds, making them easier to retrieve and use in custom scripts.
█ CONCEPTS
Federal Reserve Economic Data (FRED)
FRED (Federal Reserve Economic Data) is a comprehensive online database curated by the Federal Reserve Bank of St. Louis. It provides free access to extensive economic and financial data from U.S. and international sources. FRED includes numerous economic indicators such as GDP, inflation, employment, and interest rates. Additionally, it provides financial market data, regional statistics, and international metrics such as exchange rates and trade balances.
Sourced from reputable organizations, including U.S. government agencies, international institutions, and other public and private entities, FRED enables users to analyze over 825,000 time series, download their data in various formats, and integrate their information into analytical tools and programming workflows.
On TradingView, FRED data is available from ticker identifiers with the "FRED:" prefix. Users can search for FRED symbols in the "Symbol Search" window, and Pine scripts can retrieve data for these symbols via `request.*()` function calls.
FINRA Short Sale Volume
FINRA (the Financial Industry Regulatory Authority) is a non-governmental organization that supervises and regulates U.S. broker-dealers and securities professionals. Its primary aim is to protect investors and ensure integrity and transparency in financial markets.
FINRA's Short Sale Volume data provides detailed information about daily short-selling activity across U.S. equity markets. This data tracks the volume of short sales reported to FINRA's trade reporting facilities (TRFs), including shares sold on FINRA-regulated Alternative Trading Systems (ATSs) and over-the-counter (OTC) markets, offering transparent access to short-selling information not typically available from exchanges. This data helps market participants, researchers, and regulators monitor trends in short-selling and gain insights into bearish sentiment, hedging strategies, and potential market manipulation. Investors often use this data alongside other metrics to assess stock performance, liquidity, and overall trading activity.
It is important to note that FINRA's Short Sale Volume data does not consolidate short sale information from public exchanges and excludes trading activity that is not publicly disseminated.
TradingView provides ticker identifiers for requesting Short Sale Volume data with the format "FINRA:_SHORT_VOLUME", where "" is a supported U.S. equities symbol (e.g., "AAPL").
Open Interest (OI)
Open interest is a cornerstone indicator of market activity and sentiment in derivatives markets such as options or futures. In contrast to volume, which measures the number of contracts opened or closed within a period, OI measures the number of outstanding contracts that are not yet settled. This distinction makes OI a more robust indicator of how money flows through derivatives, offering meaningful insights into liquidity, market interest, and trends. Many traders and investors analyze OI alongside volume and price action to gain an enhanced perspective on market dynamics and reinforce trading decisions.
TradingView offers many ticker identifiers for requesting OI data with the format "_OI", where "" represents a derivative instrument's ticker ID (e.g., "COMEX:GC1!").
Commitment of Traders (COT)
Commitment of Traders data provides an informative weekly breakdown of the aggregate positions held by various market participants, including commercial hedgers, non-commercial speculators, and small traders, in the U.S. derivative markets. Tallied and managed by the Commodity Futures Trading Commission (CFTC) , these reports provide traders and analysts with detailed insight into an asset's open interest and help them assess the actions of various market players. COT data is valuable for gaining a deeper understanding of market dynamics, sentiment, trends, and liquidity, which helps traders develop informed trading strategies.
TradingView has numerous ticker identifiers that provide access to time series containing data for various COT metrics. To learn about COT ticker IDs and how they work, see our LibraryCOT publication.
█ USING THE LIBRARY
Common function characteristics
• This library's functions construct ticker IDs with valid formats based on their specified parameters, then use them as the `symbol` argument in request.security() to retrieve data from the specified context.
• Most of these functions automatically select the timeframe of a data request because the data feeds are not available for all timeframes.
• All the functions have two overloads. The first overload of each function uses values with the "simple" qualifier to define the requested context, meaning the context does not change after the first script execution. The second accepts "series" values, meaning it can request data from different contexts across executions.
• The `gaps` parameter in most of these functions specifies whether the returned data is `na` when a new value is unavailable for request. By default, its value is `false`, meaning the call returns the last retrieved data when no new data is available.
• The `repaint` parameter in applicable functions determines whether the request can fetch the latest unconfirmed values from a higher timeframe on realtime bars, which might repaint after the script restarts. If `false`, the function only returns confirmed higher-timeframe values to avoid repainting. The default value is `true`.
`fred()`
The `fred()` function retrieves the most recent value of a specified series from the Federal Reserve Economic Data (FRED) database. With this function, programmers can easily fetch macroeconomic indicators, such as GDP and unemployment rates, and use them directly in their scripts.
How it works
The function's `fredCode` parameter accepts a "string" representing the unique identifier of a specific FRED series. Examples include "GDP" for the "Gross Domestic Product" series and "UNRATE" for the "Unemployment Rate" series. Over 825,000 codes are available. To access codes for available series, search the FRED website .
The function adds the "FRED:" prefix to the specified `fredCode` to construct a valid FRED ticker ID (e.g., "FRED:GDP"), which it uses in request.security() to retrieve the series data.
Example Usage
This line of code requests the latest value from the Gross Domestic Product series and assigns the returned value to a `gdpValue` variable:
float gdpValue = fred("GDP")
`finraShortSaleVolume()`
The `finraShortSaleVolume()` function retrieves EOD data from a FINRA Short Sale Volume series. Programmers can call this function to retrieve short-selling information for equities listed on supported exchanges, namely NASDAQ, NYSE, and NYSE ARCA.
How it works
The `symbol` parameter determines which symbol's short sale volume information is retrieved by the function. If the value is na , the function requests short sale volume data for the chart's symbol. The argument can be the name of the symbol from a supported exchange (e.g., "AAPL") or a ticker ID with an exchange prefix ("NASDAQ:AAPL"). If the `symbol` contains an exchange prefix, it must be one of the following: "NASDAQ", "NYSE", "AMEX", or "BATS".
The function constructs a ticker ID in the format "FINRA:ticker_SHORT_VOLUME", where "ticker" is the symbol name without the exchange prefix (e.g., "AAPL"). It then uses the ticker ID in request.security() to retrieve the available data.
Example Usage
This line of code retrieves short sale volume for the chart's symbol and assigns the result to a `shortVolume` variable:
float shortVolume = finraShortSaleVolume(syminfo.tickerid)
This example requests short sale volume for the "NASDAQ:AAPL" symbol, irrespective of the current chart:
float shortVolume = finraShortSaleVolume("NASDAQ:AAPL")
`openInterestFutures()` and `openInterestCrypto()`
The `openInterestFutures()` function retrieves EOD open interest (OI) data for futures contracts. The `openInterestCrypto()` function provides more granular OI data for cryptocurrency contracts.
How they work
The `openInterestFutures()` function retrieves EOD closing OI information. Its design is focused primarily on retrieving OI data for futures, as only EOD OI data is available for these instruments. If the chart uses an intraday timeframe, the function requests data from the "1D" timeframe. Otherwise, it uses the chart's timeframe.
The `openInterestCrypto()` function retrieves opening, high, low, and closing OI data for a cryptocurrency contract on a specified timeframe. Unlike `openInterest()`, this function can also retrieve granular data from intraday timeframes.
Both functions contain a `symbol` parameter that determines the symbol for which the calls request OI data. The functions construct a valid OI ticker ID from the chosen symbol by appending "_OI" to the end (e.g., "CME:ES1!_OI").
The `openInterestFutures()` function requests and returns a two-element tuple containing the futures instrument's EOD closing OI and a "bool" condition indicating whether OI is rising.
The `openInterestCrypto()` function requests and returns a five-element tuple containing the cryptocurrency contract's opening, high, low, and closing OI, and a "bool" condition indicating whether OI is rising.
Example usage
This code line calls `openInterest()` to retrieve EOD OI and the OI rising condition for a futures symbol on the chart, assigning the values to two variables in a tuple:
= openInterestFutures(syminfo.tickerid)
This line retrieves the EOD OI data for "CME:ES1!", irrespective of the current chart's symbol:
= openInterestFutures("CME:ES1!")
This example uses `openInterestCrypto()` to retrieve OHLC OI data and the OI rising condition for a cryptocurrency contract on the chart, sampled at the chart's timeframe. It assigns the returned values to five variables in a tuple:
= openInterestCrypto(syminfo.tickerid, timeframe.period)
This call retrieves OI OHLC and rising information for "BINANCE:BTCUSDT.P" on the "1D" timeframe:
= openInterestCrypto("BINANCE:BTCUSDT.P", "1D")
`commitmentOfTraders()`
The `commitmentOfTraders()` function retrieves data from the Commitment of Traders (COT) reports published by the Commodity Futures Trading Commission (CFTC). This function significantly simplifies the COT request process, making it easier for programmers to access and utilize the available data.
How It Works
This function's parameters determine different parts of a valid ticker ID for retrieving COT data, offering a streamlined alternative to constructing complex COT ticker IDs manually. The `metricName`, `metricDirection`, and `includeOptions` parameters are required. They specify the name of the reported metric, the direction, and whether it includes information from options contracts.
The function also includes several optional parameters. The `CFTCCode` parameter allows programmers to request data for a specific report code. If unspecified, the function requests data based on the chart symbol's root prefix, base currency, or quoted currency, depending on the `mode` argument. The call can specify the report type ("Legacy", "Disaggregated", or "Financial") and metric type ("All", "Old", or "Other") with the `typeCOT` and `metricType` parameters.
Explore the CFTC website to find valid report codes for specific assets. To find detailed information about the metrics included in the reports and their meanings, see the CFTC's Explanatory Notes .
View the function's documentation below for detailed explanations of its parameters. For in-depth information about COT ticker IDs and more advanced functionality, refer to our previously published COT library .
Available metrics
Different COT report types provide different metrics . The tables below list all available metrics for each type and their applicable directions:
+------------------------------+------------------------+
| Legacy (COT) Metric Names | Directions |
+------------------------------+------------------------+
| Open Interest | No direction |
| Noncommercial Positions | Long, Short, Spreading |
| Commercial Positions | Long, Short |
| Total Reportable Positions | Long, Short |
| Nonreportable Positions | Long, Short |
| Traders Total | No direction |
| Traders Noncommercial | Long, Short, Spreading |
| Traders Commercial | Long, Short |
| Traders Total Reportable | Long, Short |
| Concentration Gross LT 4 TDR | Long, Short |
| Concentration Gross LT 8 TDR | Long, Short |
| Concentration Net LT 4 TDR | Long, Short |
| Concentration Net LT 8 TDR | Long, Short |
+------------------------------+------------------------+
+-----------------------------------+------------------------+
| Disaggregated (COT2) Metric Names | Directions |
+-----------------------------------+------------------------+
| Open Interest | No Direction |
| Producer Merchant Positions | Long, Short |
| Swap Positions | Long, Short, Spreading |
| Managed Money Positions | Long, Short, Spreading |
| Other Reportable Positions | Long, Short, Spreading |
| Total Reportable Positions | Long, Short |
| Nonreportable Positions | Long, Short |
| Traders Total | No Direction |
| Traders Producer Merchant | Long, Short |
| Traders Swap | Long, Short, Spreading |
| Traders Managed Money | Long, Short, Spreading |
| Traders Other Reportable | Long, Short, Spreading |
| Traders Total Reportable | Long, Short |
| Concentration Gross LE 4 TDR | Long, Short |
| Concentration Gross LE 8 TDR | Long, Short |
| Concentration Net LE 4 TDR | Long, Short |
| Concentration Net LE 8 TDR | Long, Short |
+-----------------------------------+------------------------+
+-------------------------------+------------------------+
| Financial (COT3) Metric Names | Directions |
+-------------------------------+------------------------+
| Open Interest | No Direction |
| Dealer Positions | Long, Short, Spreading |
| Asset Manager Positions | Long, Short, Spreading |
| Leveraged Funds Positions | Long, Short, Spreading |
| Other Reportable Positions | Long, Short, Spreading |
| Total Reportable Positions | Long, Short |
| Nonreportable Positions | Long, Short |
| Traders Total | No Direction |
| Traders Dealer | Long, Short, Spreading |
| Traders Asset Manager | Long, Short, Spreading |
| Traders Leveraged Funds | Long, Short, Spreading |
| Traders Other Reportable | Long, Short, Spreading |
| Traders Total Reportable | Long, Short |
| Concentration Gross LE 4 TDR | Long, Short |
| Concentration Gross LE 8 TDR | Long, Short |
| Concentration Net LE 4 TDR | Long, Short |
| Concentration Net LE 8 TDR | Long, Short |
+-------------------------------+------------------------+
Example usage
This code line retrieves "Noncommercial Positions (Long)" data, without options information, from the "Legacy" report for the chart symbol's root, base currency, or quote currency:
float nonCommercialLong = commitmentOfTraders("Noncommercial Positions", "Long", false)
This example retrieves "Managed Money Positions (Short)" data, with options included, from the "Disaggregated" report:
float disaggregatedData = commitmentOfTraders("Managed Money Positions", "Short", true, "", "Disaggregated")
█ NOTES
• This library uses dynamic requests , allowing dynamic ("series") arguments for the parameters defining the context (ticker ID, timeframe, etc.) of a `request.*()` function call. With this feature, a single `request.*()` call instance can flexibly retrieve data from different feeds across historical executions. Additionally, scripts can use such calls in the local scopes of loops, conditional structures, and even exported library functions, as demonstrated in this script. All scripts coded in Pine Script™ v6 have dynamic requests enabled by default. To learn more about the behaviors and limitations of this feature, see the Dynamic requests section of the Pine Script™ User Manual.
• The library's example code offers a simple demonstration of the exported functions. The script retrieves available data using the function specified by the "Series type" input. The code requests a FRED series or COT (Legacy), FINRA Short Sale Volume, or Open Interest series for the chart's symbol with specific parameters, then plots the retrieved data as a step-line with diamond markers.
Look first. Then leap.
█ EXPORTED FUNCTIONS
This library exports the following functions:
fred(fredCode, gaps)
Requests a value from a specified Federal Reserve Economic Data (FRED) series. FRED is a comprehensive source that hosts numerous U.S. economic datasets. To explore available FRED datasets and codes, search for specific categories or keywords at fred.stlouisfed.org Calls to this function count toward a script's `request.*()` call limit.
Parameters:
fredCode (series string) : The unique identifier of the FRED series. The function uses the value to create a valid ticker ID for retrieving FRED data in the format `"FRED:fredCode"`. For example, `"GDP"` refers to the "Gross Domestic Product" series ("FRED:GDP"), and `"GFDEBTN"` refers to the "Federal Debt: Total Public Debt" series ("FRED:GFDEBTN").
gaps (simple bool) : Optional. If `true`, the function returns a non-na value only when a new value is available from the requested context. If `false`, the function returns the latest retrieved value when new data is unavailable. The default is `false`.
Returns: (float) The value from the requested FRED series.
finraShortSaleVolume(symbol, gaps, repaint)
Requests FINRA daily short sale volume data for a specified symbol from one of the following exchanges: NASDAQ, NYSE, NYSE ARCA. If the chart uses an intraday timeframe, the function requests data from the "1D" timeframe. Otherwise, it uses the chart's timeframe. Calls to this function count toward a script's `request.*()` call limit.
Parameters:
symbol (series string) : The symbol for which to request short sale volume data. If the specified value contains an exchange prefix, it must be one of the following: "NASDAQ", "NYSE", "AMEX", "BATS".
gaps (simple bool) : Optional. If `true`, the function returns a non-na value only when a new value is available from the requested context. If `false`, the function returns the latest retrieved value when new data is unavailable. The default is `false`.
repaint (simple bool) : Optional. If `true` and the chart's timeframe is intraday, the value requested on realtime bars may change its time offset after the script restarts its executions. If `false`, the function returns the last confirmed period's values to avoid repainting. The default is `true`.
Returns: (float) The short sale volume for the specified symbol or the chart's symbol.
openInterestFutures(symbol, gaps, repaint)
Requests EOD open interest (OI) and OI rising information for a valid futures symbol. If the chart uses an intraday timeframe, the function requests data from the "1D" timeframe. Otherwise, it uses the chart's timeframe. Calls to this function count toward a script's `request.*()` call limit.
Parameters:
symbol (series string) : The symbol for which to request open interest data.
gaps (simple bool) : Optional. If `true`, the function returns non-na values only when new values are available from the requested context. If `false`, the function returns the latest retrieved values when new data is unavailable. The default is `false`.
repaint (simple bool) : Optional. If `true` and the chart's timeframe is intraday, the value requested on realtime bars may change its time offset after the script restarts its executions. If `false`, the function returns the last confirmed period's values to avoid repainting. The default is `true`.
Returns: ( ) A tuple containing the following values:
- The closing OI value for the symbol.
- `true` if the closing OI is above the previous period's value, `false` otherwise.
openInterestCrypto(symbol, timeframe, gaps, repaint)
Requests opening, high, low, and closing open interest (OI) data and OI rising information for a valid cryptocurrency contract on a specified timeframe. Calls to this function count toward a script's `request.*()` call limit.
Parameters:
symbol (series string) : The symbol for which to request open interest data.
timeframe (series string) : The timeframe of the data request. If the timeframe is lower than the chart's timeframe, it causes a runtime error.
gaps (simple bool) : Optional. If `true`, the function returns non-na values only when new values are available from the requested context. If `false`, the function returns the latest retrieved values when new data is unavailable. The default is `false`.
repaint (simple bool) : Optional. If `true` and the `timeframe` represents a higher timeframe, the function returns unconfirmed values from the timeframe on realtime bars, which repaint when the script restarts its executions. If `false`, it returns only confirmed higher-timeframe values to avoid repainting. The default is `true`.
Returns: ( ) A tuple containing the following values:
- The opening, high, low, and closing OI values for the symbol, respectively.
- `true` if the closing OI is above the previous period's value, `false` otherwise.
commitmentOfTraders(metricName, metricDirection, includeOptions, CFTCCode, typeCOT, mode, metricType)
Requests Commitment of Traders (COT) data with specified parameters. This function provides a simplified way to access CFTC COT data available on TradingView. Calls to this function count toward a script's `request.*()` call limit. For more advanced tools and detailed information about COT data, see TradingView's LibraryCOT library.
Parameters:
metricName (series string) : One of the valid metric names listed in the library's documentation and source code.
metricDirection (series string) : Metric direction. Possible values are: "Long", "Short", "Spreading", and "No direction". Consult the library's documentation or code to see which direction values apply to the specified metric.
includeOptions (series bool) : If `true`, the COT symbol includes options information. Otherwise, it does not.
CFTCCode (series string) : Optional. The CFTC code for the asset. For example, wheat futures (root "ZW") have the code "001602". If one is not specified, the function will attempt to get a valid code for the chart symbol's root, base currency, or main currency.
typeCOT (series string) : Optional. The type of report to request. Possible values are: "Legacy", "Disaggregated", "Financial". The default is "Legacy".
mode (series string) : Optional. Specifies the information the function extracts from a symbol. Possible modes are:
- "Root": The function extracts the futures symbol's root prefix information (e.g., "ES" for "ESH2020").
- "Base currency": The function extracts the first currency from a currency pair (e.g., "EUR" for "EURUSD").
- "Currency": The function extracts the currency of the symbol's quoted values (e.g., "JPY" for "TSE:9984" or "USDJPY").
- "Auto": The function tries the first three modes (Root -> Base currency -> Currency) until it finds a match.
The default is "Auto". If the specified mode is not available for the symbol, it causes a runtime error.
metricType (series string) : Optional. The metric type. Possible values are: "All", "Old", "Other". The default is "All".
Returns: (float) The specified Commitment of Traders data series. If no data is available, it causes a runtime error.
Commitment of Traders: Legacy Metrics█ OVERVIEW
This indicator displays the Commitment of Traders (COT) legacy data for futures markets.
█ CONCEPTS
Commitment of Traders (COT) data is tallied by the Commodity Futures Trading Commission (CFTC) , a US federal agency that oversees the trading of derivative markets such as futures in the US. It is weekly data that provides traders with information about open interest for an asset. The CFTC oversees derivative markets traded on different exchanges, so COT data is available for assets that can be traded on CBOT, CME, NYMEX, COMEX, and ICEUS.
A detailed description of the COT report can be found on the CFTC's website .
COT data is separated into three notable reports: Legacy, Disaggregated, and Financial. This indicator presents data from the legacy report, which is broken down by exchange. Legacy reports break down the reportable open interest positions into two classifications: non-commercial and commercial traders.
Our other COT indicators are:
• Commitment of Traders: Disaggregated Metrics
• Commitment of Traders: Financial Metrics
• Commitment of Traders: Total
█ HOW TO USE IT
Load the indicator on an active chart (see here if you don't know how).
By default, the indicator uses the chart's symbol to derive the COT data it displays. You can also specify a CFTC code in the "CFTC code" field of the script's inputs to display COT data from a symbol different than the chart's.
The rest of this section documents the script's input fields.
Metric
Each metric represents a different column of the Commitment of Traders report. Details are available in the explanatory notes on the CFTC's website .
Here is a summary of the metrics:
• "Open Interest" is the total of all futures and/or option contracts entered into and not yet offset by a transaction, by delivery, by exercise, etc.
The aggregate of all long open interest is equal to the aggregate of all short open interest.
• "Traders Total" is the number of all unique reportable traders, regardless of the trading direction.
• "Traders Total Reportable/Traders Noncommercial/Traders Commercial" are the quantities of traders reported to hold any position with the specified direction.
All of a trader's reported futures positions in a commodity are classified as commercial if the trader uses futures contracts in that particular commodity for hedging.
To determine the total number of reportable traders in a market, a trader is counted only once, whether or not the trader appears in more than one category.
• "Total Reportable/Noncommercial/Commercial Positions" are all positions held by all reportable/non-commercial/commercial traders.
• "Non-reportable Positions" is derived by subtracting total long and short "Reportable Positions" from the total open interest.
Accordingly, the number of traders involved and the commercial/non-commercial classification of each trader are unknown.
• "Concentration Gross/Net LT 4/8 TDR" is the percentage of open interest held by 4/8 of the largest traders, by gross/net positions,
without regard to whether they are classified as commercial or non-commercial. The Net position ratios are computed after offsetting each trader’s equal long and short positions.
A reportable trader with relatively large, balanced long and short positions in a single market, therefore,
may be among the four and eight largest traders in both the gross long and gross short categories, but will probably not be included among the four and eight largest traders on a net basis.
Direction
Each metric is available for a particular set of directions. Valid directions for each metric are specified with its name in the "Metric" field's dropdown menu.
Type
Possible values are: All, Old, Other. When commodities have a well-defined marketing season or crop year (e.g. Wheat or Lean Hogs futures), this determines how the data is aggregated. Detailed explanation can be found in the "Old and Other Futures" section of the CTFC Explanatory Notes linked above. The "Major Markets for Which the COT Data Is Shown by Crop Year" table in the Explanatory Notes specifies the commodities that this distinction applies to; selecting "Old" for any of the commodities not in that list will return the same data as in "All", while selecting "Other" will return 0.
COT Selection Mode
This field's value determines how the script determines which COT data to return from the chart's symbol:
- "Root" uses the root of a futures symbol ("ES" for "ESH2020").
- "Base currency" uses the base currency in a forex pair ("EUR" for "EURUSD").
- "Currency" uses the quote currency, i.e., the currency the symbol is traded in ("JPY" for "TSE:9984" or "USDJPY").
- "Auto" tries all modes, in turn.
If no COT data can be found, a runtime error is generated.
Note that if the "CTFC Code" input field contains a code, it will override this input.
Futures/Options
Specifies the type of Commitment of Traders data to display: data concerning only Futures, only Options, or both.
CTFC Code
Instead of letting the script generate the CFTC COT code from the chart and the "COT Selection Mode" input when this field is empty, you can specify an unrelated CFTC COT code here, e.g., 001602 for wheat futures.
Look first. Then leap.
Commitment of Traders: Disaggregated Metrics█ OVERVIEW
This indicator displays the Commitment of Traders (COT) Disaggregated data for futures markets.
█ CONCEPTS
Commitment of Traders (COT) data is tallied by the Commodity Futures Trading Commission (CFTC) , a US federal agency that oversees the trading of derivative markets such as futures in the US. It is weekly data that provides traders with information about open interest for an asset. The CFTC oversees derivative markets traded on different exchanges, so COT data is available for assets that can be traded on CBOT, CME, NYMEX, COMEX, and ICEUS.
A detailed description of the COT report can be found on the CFTC's website .
COT data is separated into three notable reports: Legacy, Disaggregated, and Financial. This indicator presents data from the Disaggregated report. The disaggregated reports are broken down by agriculture, petroleum and products, natural gas and products, electricity and metals and other physical contracts. The Disaggregated reports break down the reportable open interest positions into four classifications: Producer/Merchant/Processor/User, Swap Dealers, Managed Money, and Other Reportables.
Our other COT indicators are:
• Commitment of Traders: Legacy Metrics
• Commitment of Traders: Financial Metrics
• Commitment of Traders: Total
█ HOW TO USE IT
Load the indicator on an active chart (see here if you don't know how).
By default, the indicator uses the chart's symbol to derive the COT data it displays. You can also specify a CFTC code in the "CFTC code" field of the script's inputs to display COT data from a symbol different than the chart's.
The rest of this section documents the script's input fields.
Metric
Each metric represents a different column of the Commitment of Traders report. Details are available in the explanatory notes on the CFTC's website .
Here is a summary of the metrics:
• "Open Interest" is the total of all futures and/or option contracts entered into and not yet offset by a transaction, by delivery, by exercise, etc.
The aggregate of all long open interest is equal to the aggregate of all short open interest.
• "Traders Total" is the quantity of all unique reportable traders, regardless of the trading direction.
• "Traders Producer Merchant" is the number of traders classified as a "producer/merchant/processor/user" reported holding any position with the specified direction.
A "producer/merchant/processor/user" is an entity that predominantly engages in the production, processing, packing or handling of a physical commodity and
uses the futures markets to manage or hedge risks associated with those activities.
• "Traders Swap" is the number of traders classified as "swap dealers" reported holding any position with the specified direction.
A "swap dealer" is an entity that deals primarily in swaps for a commodity and uses the futures markets to manage or hedge the risk associated with those swaps transactions.
The swap dealer’s counterparties may be speculative traders, like hedge funds, or traditional commercial clients that are managing risk arising from their dealings in the physical commodity.
• "Traders Managed Money" is the number of traders classified as "money managers" reported holding any position with the specified direction.
A "money manager" is a registered trader that is engaged in managing and conducting organized futures trading on behalf of clients.
• "Traders Other Reportable" is the number of reportable traders that are not placed in any of the three categories specified above.
• "Traders Total Reportable" is the number of traders reported holding any position with the specified direction.
To determine the total number of reportable traders in a market, a trader is counted only once whether or not the trader appears in more than one category.
As a result, the sum of the numbers of traders in each separate category typically exceeds the total number of reportable traders.
• "Producer Merchant/Swap/Managed Money/Total Reportable/Other Reportable Positions" is all positions held by the traders of the specified category.
• "Nonreportable Positions" is the long and short open interest derived by subtracting the total long and short reportable positions from the total open interest.
Accordingly, the number of traders involved and the classification of each trader are unknown.
• "Concentration Gross/Net LE 4/8 TDR" is the percentage of open interest held by 4/8 of the largest traders (entities), by Gross/Net positions, without regard to how they are classified.
The Net position ratios are computed after offsetting each trader’s equal long and short positions.
A reportable trader with relatively large, balanced long and short positions in a single market,
therefore, may be among the four and eight largest traders in both the gross long and gross short categories,
but will probably not be included among the four and eight largest traders on a net basis.
Direction
Each metric is available for a particular set of directions. Valid directions for each metric are specified with its name in the "Metric" field's dropdown menu.
Type
Possible values are: All, Old, Other. When commodities have a well-defined marketing season or crop year (e.g. Wheat or Lean Hogs futures), this determines how the data is aggregated. Detailed explanation can be found in the "Old and Other Futures" section of the CTFC Explanatory Notes linked above. The "Major Markets for Which the COT Data Is Shown by Crop Year" table in the Explanatory Notes specifies the commodities that this distinction applies to; selecting "Old" for any of the commodities not in that list will return the same data as in "All", while selecting "Other" will return 0.
Futures/Options
Specifies the type of Commitment of Traders data to display: data concerning only Futures, only Options, or both.
CTFC Code
Instead of letting the script generate the CFTC COT code from the chart and the "COT Selection Mode" input when this field is empty, you can specify an unrelated CFTC COT code here, e.g., 001602 for wheat futures.
Look first. Then leap.
Commitment of Traders: Financial Metrics█ OVERVIEW
This indicator displays the Commitment of Traders (COT) financial data for futures markets.
█ CONCEPTS
Commitment of Traders (COT) data is tallied by the Commodity Futures Trading Commission (CFTC) , a US federal agency that oversees the trading of derivative markets such as futures in the US. It is weekly data that provides traders with information about open interest for an asset. The CFTC oversees derivative markets traded on different exchanges, so COT data is available for assets that can be traded on CBOT, CME, NYMEX, COMEX, and ICEUS.
A detailed description of the COT report can be found on the CFTC's website .
COT data is separated into three notable reports: Legacy, Disaggregated, and Financial. This indicator presents data from the COT Financial (Traders in Financial Futures) report. The Financial report includes financial contracts, such as currencies, US Treasury securities, Eurodollars, stocks, VIX and Bloomberg commodity index. As such, the TFF data is limited to financial-related tickers. The TFF report breaks down the reportable open interest positions into four classifications: Dealer/Intermediary, Asset Manager/Institutional, Leveraged Funds, and Other Reportables.
Our other COT indicators are:
• Commitment of Traders: Legacy Metrics
• Commitment of Traders: Disaggregated Metrics
• Commitment of Traders: Total
█ HOW TO USE IT
Load the indicator on an active chart (see here if you don't know how).
By default, the indicator uses the chart's symbol to derive the COT data it displays. You can also specify a CFTC code in the "CFTC code" field of the script's inputs to display COT data from a symbol different than the chart's.
The rest of this section documents the script's input fields.
Metric
Each metric represents a different column of the Commitment of Traders report. Details are available in the explanatory notes on the CFTC's website .
Here is a summary of the metrics:
• "Open Interest" is the total of all futures and/or option contracts entered into and not yet offset by a transaction, by delivery, by exercise, etc.
The aggregate of all long open interest is equal to the aggregate of all short open interest.
• "Traders Total" is the number of all unique reportable traders, regardless of the trading direction.
• "Traders Dealer" is the number of traders classified as a "Dealer/Intermediary" reported holding any position with the specified direction.
A "producer/merchant/processor/user" is an entity typically described as the “sell side” of the market.
Though they may not predominately sell futures, they do design and sell various financial assets to clients.
They tend to have matched books or offset their risk across markets and clients.
Futures contracts are part of the pricing and balancing of risk associated with the products they sell and their activities.
• "Traders Asset Manager" is the number of traders classified as "Asset Manager/Institutional" reported holding any position with the specified direction.
These are institutional investors, including pension funds, endowments, insurance companies,
mutual funds and those portfolio/investment managers whose clients are predominantly institutional.
• "Traders Leveraged Funds" is the number of traders classified as "Leveraged Funds" reported holding any position with the specified direction.
These are typically hedge funds and various types of money managers. The traders may be engaged in managing and
conducting proprietary futures trading and trading on behalf of speculative clients.
• "Traders Other Reportable" is the number of reportable traders that are not placed in any of the three categories specified above.
The traders in this category mostly are using markets to hedge business risk, whether that risk is related to foreign exchange, equities or interest rates.
This category includes corporate treasuries, central banks, smaller banks, mortgage originators, credit unions and any other reportable traders not assigned to the other three categories.
• "Traders Total Reportable" is the number of all traders reported holding any position with the specified direction.
To determine the total number of reportable traders in a market, a trader is counted only once whether or not the trader appears in more than one category.
As a result, the sum of the numbers of traders in each separate category typically exceeds the total number of reportable traders.
• "Dealer/Asset Manager/Leveraged Funds/Total Reportable/Other Reportable Positions -- all positions held by the traders of the specified category.
• "Nonreportable Positions" is the long and short open interest derived by subtracting the total long and short reportable positions from the total open interest.
Accordingly, the number of traders involved and the commercial/non-commercial classification of each trader are unknown.
• "Concentration Gross/Net LT 4/8 TDR" is the percentage of open interest held by 4/8 of the largest traders, by gross/net positions,
without regard to whether they are classified as commercial or non-commercial. The Net position ratios are computed after offsetting each trader’s equal long and short positions.
A reportable trader with relatively large, balanced long and short positions in a single market, therefore,
may be among the four and eight largest traders in both the gross long and gross short categories, but will probably not be included among the four and eight largest traders on a net basis.
Direction
Each metric is available for a particular set of directions. Valid directions for each metric are specified with its name in the "Metric" field's dropdown menu.
COT Selection Mode
This field's value determines how the script determines which COT data to return from the chart's symbol:
- "Root" uses the root of a futures symbol ("ES" for "ESH2020").
- "Base currency" uses the base currency in a forex pair ("EUR" for "EURUSD").
- "Currency" uses the quote currency, i.e., the currency the symbol is traded in ("JPY" for "TSE:9984" or "USDJPY").
- "Auto" tries all modes, in turn.
If no COT data can be found, a runtime error is generated.
Note that if the "CTFC Code" input field contains a code, it will override this input.
Futures/Options
Specifies the type of Commitment of Traders data to display: data concerning only Futures, only Options, or both.
CTFC Code
Instead of letting the script generate the CFTC COT code from the chart and the "COT Selection Mode" input when this field is empty, you can specify an unrelated CFTC COT code here, e.g., 001602 for wheat futures.
Look first. Then leap.
Binance TRX & BTTShows TRX with BTT, subtracted or added to. Subtracting makes it in line with BitMEX futures. The option to add is considered for 'true value'. Airdrops, like new coin forks, can split value: a good example being BCHABC and BCHSV.
Getting TRX futures to match TRX on Binance is likely tied to the monthly airdrop rate as defined here: support.binance.com
I'm guessing it has something to do with (spot price * estimated airdrop rate) trading too far from futures. Maybe even too close. Or because futures are trading above spot near a monthly airdrop snapshot. Much complicate. Such guess. Wow.
Binance is chosen as pricing source for its liquidity and earliest open date.
MACD StrategyOverview
The "MACD Strategy" is a straightforward trading strategy tested for BTCUSDT Futures on the 1-minute timeframe, leveraging the Moving Average Convergence Divergence (MACD) indicator to identify momentum-based buy and sell opportunities. Developed with input from expert trading analyst insights, this strategy combines technical precision with risk management, making it suitable for traders of all levels on platforms like TradingView. It focuses on capturing trend reversals and momentum shifts, with clear visual cues and automated alerts for seamless integration with trading bots (e.g., Bitget webhooks).
#### How It Works
This strategy uses the MACD indicator to generate trading signals based on momentum and trend direction:
- **Buy Signal**: Triggered when the MACD line crosses above the signal line, and the MACD histogram turns positive (above zero). This suggests increasing bullish momentum.
- **Sell Signal**: Triggered when the MACD line crosses below the signal line, and the MACD histogram turns negative (below zero), indicating growing bearish momentum.
Once a signal is detected, the strategy opens a position (long for buy, short for sell) with a position size calculated based on your risk tolerance. It includes a stop-loss to limit losses and a take-profit to lock in gains, both dynamically adjusted using the Average True Range (ATR) for adaptability to market volatility.
#### Key Features
- **MACD-Based Signals**: Relies solely on MACD for entry points, plotted in a separate pane for clear momentum analysis.
- **Risk Management**: Automatically calculates position size based on a percentage of your account balance and sets stop-loss and take-profit levels using ATR multipliers and a risk:reward ratio.
- **Visual Feedback**: Plots entry, stop-loss, and take-profit lines on the chart with labeled markers for easy tracking.
- **Alerts**: Includes Bitget webhook-compatible alerts for automated trading, notifying you of buy and sell signals in real-time.
#### Input Parameters
- **Account Balance**: Default 10000 – Set your initial trading capital to determine position sizing.
- **MACD Fast Length**: Default 12 – The short-term EMA period for MACD sensitivity.
- **MACD Slow Length**: Default 26 – The long-term EMA period for MACD calculation.
- **MACD Signal Length**: Default 9 – The smoothing period for the signal line.
- **Risk Per Trade (%)**: Default 3.0 – The percentage of your account balance risked per trade (e.g., 3% of 10000 = 300).
- **Risk:Reward Ratio**: Default 3.0 – The ratio of potential profit to risk (e.g., 3:1 means risking 1 to gain 3).
- **SL Multiplier**: Default 1.0 – Multiplies ATR to set the stop-loss distance (e.g., 1.0 x ATR).
- **TP Multiplier**: Default 3.0 – Multiplies ATR to set the take-profit distance, adjusted by the risk:reward ratio.
- **Line Length (bars)**: Default 25 – Duration in bars for displaying trade lines on the chart.
- **Label Position**: Default 'left' – Position of text labels (left or right) relative to trade lines.
- **ATR Period**: Default 14 – The number of periods for calculating ATR to measure volatility.
#### How to Use
1. **Add to Chart**: Load the "MACD Strategy" as a strategy and the "MACD Indicator" as a separate indicator on your TradingView chart (recommended for BTCUSDT Futures on the 1-minute timeframe).
2. **Customize Settings**: Adjust the input parameters based on your risk tolerance and market conditions. For BTCUSDT Futures, consider reducing `Risk Per Trade (%)` during high volatility (e.g., 1%) or increasing `SL Multiplier` for wider stops.
3. **Visual Analysis**: Watch the main chart for trade entry lines (green for buy, red for sell), stop-loss (red), and take-profit (green) lines with labels. Use the MACD pane below to confirm momentum shifts.
4. **Set Alerts**: Create alerts in TradingView for "Buy Signal" and "Sell Signal" to automate trades via Bitget webhooks.
5. **Backtest and Optimize**: Test the strategy on historical BTCUSDT Futures 1-minute data to fine-tune parameters. The short timeframe requires quick execution, so monitor closely for slippage or latency.
#### Tips for Success
- **Market Conditions**: This strategy performs best in trending markets on the 1-minute timeframe. Avoid choppy conditions where MACD crossovers may produce false signals.
- **Risk Management**: Start with the default 3% risk per trade and adjust downward (e.g., 1%) during volatile periods like BTCUSDT news events. The 3:1 risk:reward ratio targets consistent profitability.
- **Timeframe**: Optimized for 1-minute charts; switch to 5-minute or 15-minute for less noise if needed.
- **Confirmation**: Cross-check MACD signals with price action or support/resistance levels for higher accuracy on BTCUSDT Futures.
#### Limitations
- This strategy relies solely on MACD, so it may lag in fast-moving or sideways markets. Consider adding a secondary filter (e.g., RSI) if needed.
- Stop-loss and take-profit are ATR-based and may need adjustment for BTCUSDT Futures’ high volatility, especially during leverage trading.
#### Conclusion
The "MACD Strategy" offers a simple yet effective way to trade momentum shifts using the MACD indicator, tested for BTCUSDT Futures on the 1-minute timeframe, with robust risk management and visual tools. Whether you’re scalping crypto futures or exploring short-term trends, this strategy provides a solid foundation for automated or manual trading. Share your feedback or customizations in the comments, and happy trading!
