Trade Calculator {Phanchai}Trade Calculator 🧮 {Phanchai} — Documentation
A lightweight sizing helper for TradingView that turns your risk per trade into an estimated maximum nominal position size — using the most recent chart low as your stop reference. Built for speed and clarity right on the chart.
Key Features
Clean on-chart info table with configurable font size and position.
Row toggles: show/hide each line (Price, Last Low, Risk per Trade, Entry − Low, SL to Low %, Max. Nominal Value in USDT).
Configurable low reference: Last N bars or Running since load .
Low label placed exactly at the wick of the lowest bar (no horizontal line).
Custom padding: add extra rows above/below and blank columns left/right (with custom whitespace/text fillers) to fine-tune layout.
Integer display for Risk per Trade (USDT) and Max. Nominal Value (USDT); decimals configurable elsewhere.
Open source script — easy to read and extend.
How to Use
Add the indicator: open TradingView → Indicators → paste the source code → Add to chart.
Pick your low reference in settings:
Last N bars — uses the lowest low within your chosen lookback.
Running since load — tracks the lowest low since the script loaded.
Set your capital and risk:
Total Capital — your account size in USDT.
Max. invest Capital per Trade (%) — your risk per trade as a percent of Total Capital.
Tidy the table:
Use Table Position and Table Size to place it.
Add Extra rows/columns and set left/right fillers (spaces allowed) for padding.
Toggle individual rows (on/off) to show only what you need.
Read the numbers:
Act. Price in USDT — current close.
Last Low in USDT — stop reference price.
Risk per Trade — whole-USDT value of your risk budget for this trade.
Entry − Low — absolute risk per unit.
SL to Low (%) — percentage distance from price to low.
Max. Nominal Value in USDT — estimated max nominal position size given your risk budget and stop at the low.
Scope
This calculator is designed for long trades only (stop below price at the chart low).
Notes & Assumptions
Does not factor fees, funding, slippage, tick size, or broker/venue position limits.
“Running since load” updates as new lows appear; “Last N bars” uses only the selected lookback window.
If price equals the low (zero distance), sizing will be undefined (division by zero guarded as “—”).
Risk Warning
Trading involves substantial risk. Always double-check every value the calculator shows, confirm your stop distance, and verify position sizing with your broker/platform before entering any order. Never risk money you cannot afford to lose.
Open Source & Feedback
The source code is open. If you spot a bug or have an idea to improve the tool, feel free to share suggestions — I’m happy to iterate and make it better.
Cerca negli script per " TABLE"
Weekly pecentage tracker by PRIVATE
Settings Picture below this link: 👇
i.ibb.co
What it is
A lightweight “Weekly % Tracker” overlay that lets you manually enter weekly performance (in percent) for XAUUSD + up to 10 FX pairs, then shows:
a small table panel with each enabled symbol and its % result
one TOTAL row (Sum / Average / Compounded across all enabled symbols)
an optional mini badge showing the % for a single selected symbol
Nothing is auto-calculated from price—you type the % yourself.
Key settings
Panel: show/hide, position, number of decimals, colors (background, text, green/red).
Total mode:
Sum – adds percentages
Average – mean of enabled rows
Compounded –
(
∏
(
1
+
𝑝
/
100
)
−
1
)
×
100
(∏(1+p/100)−1)×100
Symbols:
XAUUSD (toggle + label + % input)
10 FX pairs (each has On/Off, label text, % input). You can rename labels to any symbol text you want.
Mini badge: show/hide, position, and symbol to display.
How it works
Overlay indicator: overlay=true; just draws UI on the chart (no plots).
Arrays (syms, vals, ons) collect the row data in order: XAU first, then FX1…FX10.
Helpers:
posFrom() converts a position string (e.g., “Top Right”) into a position.* constant.
wp_col() picks green/red/neutral based on the sign of the %.
wp_round() rounds values to the selected decimals.
calc_total() computes the TOTAL with the chosen mode over enabled rows only.
Table creation logic:
Counts how many rows are enabled.
If none enabled or panel is off: the panel table is deleted, so no box/background is visible.
If enabled and on: the panel is (re)created at the chosen position.
On each last bar (barstate.islast), it clears the table to transparent (bgcolor=na) and then fills one row per enabled symbol, followed by a single TOTAL row.
Mini badge:
Always (re)created on position change.
Shows selected symbol’s % (or “-” if that symbol isn’t enabled or has no value).
Colors text green/red by sign.
Notes & limits
It’s manual input—the script doesn’t read trades or P/L from price.
You can rename each row’s label to match any symbol name you want.
When no rows are enabled, the panel disappears entirely (no empty background).
Designed to be light: only draws tables; no heavy plotting.
If you want the TOTAL row to be optional, or different color thresholds, or CSV-style export/import of the values, say the word and I’ll add it.
Mikula's Master 360° Square of 12Mikula’s Master 360° Square of 12
An educational W. D. Gann study indicator for price and time. Anchor a compact Square of 12 table to a start point you choose. Begin from a bar’s High or Low (or set a manual start price). From that anchor you can progress or regress the table to study how price steps through cycles in either direction.
What you’re looking at :
Zodiac rail (far left): the twelve signs.
Degree rail: 24 rows in 15° steps from 15° up to 360°/0°.
Transit rail and Natal rail: track one planet per rail. Each planet is placed at its current row (℞ shown when retrograde). As longitude advances, the planet climbs bottom → top, then wraps to the bottom at the next sign; during retrograde it steps downward.
Hover a planet’s cell to see a tooltip with its exact longitude and sign (e.g., 152.4° ♌︎). The linked price cell in the grid moves with the planet’s row so you can follow a planet’s path through the zodiac as a path through price.
Price grid (right): the 12×24 Square of 12. Each column is a cycle; cells are stepped price levels from your start price using your increment.
Bottom rail: shows the current square number and labels the twelve columns in that square.
How the square is read
The square always begins at the bottom left. Read each column bottom → top. At the top, return to the bottom of the next column and read up again. One square contains twelve cycles. Because the anchor can be a High or a Low, you can progress the table upward from the anchor or regress it downward while keeping the same bottom-to-top reading order.
Iterate Square (shifting)
Iterate Square shifts the entire 12×24 grid to the next set of twelve cycles.
Square 1 shows cycles 1–12; Square 2 shows 13–24; Square 3 shows 25–36, etc.
Visibility rules
Pivot cells are table-bound. If you shift the square beyond those prices, their highlights won’t appear in the table.
A/B levels and Transit/Natal planetary lines are chart overlays and can remain visible on the table as you shift the square.
Quick use
Choose an anchor (date/time + High/Low) or enable a manual start price .
Set the increment. If you anchored with a Low and want the table to step downward from there, use a negative value.
Optional: pick Transit and Natal planets (one per rail), toggle their plots, and hover their cells for longitude/sign.
Optional: turn on A/B levels to display repeating bands from the start price.
Optional: enable swing pivots to tint matching cells after the anchor.
Use Iterate Square to shift to later squares of twelve cycles.
Examples
These are exploratory examples to spark ideas:
Overview layout (zodiac & degree rails, Transit/Natal rails, price grid)
A-levels plotted, pivots tinted on the table, real-time price highlighted
Drawing angles from the anchor using price & time read from the table
Using a TradingView Gann box along the A-levels to study reactions
Attribution & originality
This script is an original implementation (no external code copied). Conceptual credit to Patrick Mikula, whose discussion of the Master 360° Square of 12 inspired this study’s presentation.
Further reading (neutral pointers)
Patrick Mikula, Gann’s Scientific Methods Unveiled, Vol. 2, “W. D. Gann’s Use of the Circle Chart.”
W. D. Gann’s Original Commodity Course (as provided by WDGAN.com).
No affiliation implied.
License CC BY-NC-SA 4.0 (non-commercial; please attribute @Javonnii and link the original).
Dependency AstroLib by @BarefootJoey
Disclaimer Educational use only; not financial advice.
BPS Multi-MA 5 — 22/30, SMA/WMA/EMA# Multi-MA 5 — 22/30 base, SMA/WMA/EMA
**What it is**
A lightweight 5-line moving-average ribbon for fast visual bias and trend/mean-reversion reads. You can switch the MA type (SMA/WMA/EMA) and choose between two ways of setting lengths: by monthly “session-based” base (22 or 30) with multipliers, or by entering exact lengths manually. An optional info table shows the effective settings in real time.
---
## How it works
* Calculates five moving averages from the selected price source.
* Lengths are either:
* **Multipliers mode:** `Base × Multiplier` (e.g., base 22 → 22/44/66/88/110), or
* **Manual mode:** any five exact lengths (e.g., 10/22/50/100/200).
* Plots five lines with fixed legend titles (MA1…MA5); the **info table** displays the actual type and lengths.
---
## Inputs
**Length Mode**
* **Multipliers** — choose a **Base** of **22** (≈ trading sessions per month) or **30** (calendar-style, smoother) and set **×1…×5** multipliers.
* **Manual** — enter **Len1…Len5** directly.
**MA Settings**
* **MA Type:** SMA / WMA / EMA
* **Source:** any series (e.g., `close`, `hlc3`, etc.)
* **Use true close (ignore Heikin Ashi):** when enabled, the MA is computed from the underlying instrument’s real `close`, not HA candles.
* **Show info table:** toggles the on-chart table with the current mode, type, base, and lengths.
---
## Quick start
1. Add the indicator to your chart.
2. Pick **MA Type** (e.g., **WMA** for faster response, **SMA** for smoother).
3. Choose **Length Mode**:
* **Multipliers:** set **Base = 22** for session-based monthly lengths (stocks/FX), or **30** for heavier smoothing.
* **Manual:** enter your exact lengths (e.g., 10/22/50/100/200).
4. (Optional) On **Heikin Ashi** charts, enable **Use true close** if you want the lines based on the instrument’s real close.
---
## Tips & notes
* **1 month ≈ 21–22 sessions.** Using 30 as “monthly” yields a smoother, more delayed curve.
* **WMA** reacts faster than **SMA** at the same length; expect earlier signals but more whipsaws in chop.
* **Len = 1** makes the MA track the chosen source (e.g., `close`) almost exactly.
* If changing lengths doesn’t move the lines, ensure you’re editing fields for the **active Length Mode** (Multipliers vs Manual).
* For clean comparisons, use the **same timeframe**. If you later wrap this in MTF logic, keep `lookahead_off` and handle gaps appropriately.
---
## Use cases
* Trend ribbon and dynamic bias zones
* Pullback entries to the mid/slow lines
* Crossovers (fast vs slow) for confirmation
* Volatility filtering by spreading lengths (e.g., 22/44/88/132/176)
---
**Credits:** Built for clarity and speed; designed around session-based “monthly” lengths (22) or smoother calendar-style (30).
[c3s] CWS - M2 Global Liquidity Index & BTC Correlation CWS - M2 Global Liquidity Index with Offset BTC Correlation
This custom indicator visualizes and analyzes the relationship between the global M2 money supply and Bitcoin (BTC) price movements. It calculates the correlation between these two variables to provide insights into how changes in global liquidity may impact Bitcoin’s price over time.
Key Features:
Global M2 Liquidity Index Calculation:
Fetches M2 money supply data from multiple economies (China, US, EU, Japan, UK) and normalizes using currency exchange rates (e.g., CNY/USD, EUR/USD).
Combines all M2 data points and normalizes by dividing by 1 trillion (1e12) for easier visualization.
Offset for M2 Data:
The offset parameter allows users to shift the M2 data by a specified number of days, helping track the influence of past global liquidity on Bitcoin.
BTC Price Correlation:
Computes the correlation between shifted global M2 liquidity and Bitcoin (BTC) price, using a 52-day lookback period by default.
Correlation Quality Display:
Categorizes correlation quality as:
Excellent : Correlation >= 0.8
Good : Correlation >= 0.6 and < 0.8
Weak : Correlation >= 0.4 and < 0.6
Very Weak : Correlation < 0.4
Displays correlation quality as a label on the chart for easy assessment.
Visual Enhancements:
Labels : Displays dynamic labels on the chart with metrics like M2 value and correlation.
Plot Shapes : Uses shapes to indicate data availability for global M2 and correlation.
Data Table : Optionally shows a data table in the top-right corner summarizing:
Global M2 value (in trillions)
The correlation between global M2 and BTC
The correlation quality
Optional Debugging:
Debug plots help identify when data is missing for M2 or correlation, ensuring transparency and accurate functionality.
Inputs:
Offset: Shift the M2 data (in days) to see past liquidity effects on Bitcoin.
Lookback Period: Number of periods (default 52) used to calculate the correlation.
Show Labels: Toggle to show or hide labels for M2 and correlation values.
Show Table: Toggle to show or hide the data table in the top-right corner.
Usage:
Ideal for traders and analysts seeking to understand the relationship between global liquidity and Bitcoin price. The offset and lookback period can be adjusted to explore different timeframes and correlation strengths, aiding more informed trading decisions.
Correlation Heatmap Matrix [TradingFinder] 20 Assets Variable🔵 Introduction
Correlation is one of the most important statistical and analytical metrics in financial markets, data mining, and data science. It measures the strength and direction of the relationship between two variables.
The correlation coefficient always ranges between +1 and -1 : a perfect positive correlation (+1) means that two assets or currency pairs move together in the same direction and at a constant ratio, a correlation of zero (0) indicates no clear linear relationship, and a perfect negative correlation (-1) means they move in exactly opposite directions.
While the Pearson Correlation Coefficient is the most common method for calculation, other statistical methods like Spearman and Kendall are also used depending on the context.
In financial market analysis, correlation is a key tool for Forex, the Stock Market, and the Cryptocurrency Market because it allows traders to assess the price relationship between currency pairs, stocks, or coins. For example, in Forex, EUR/USD and GBP/USD often have a high positive correlation; in stocks, companies from the same sector such as Apple and Microsoft tend to move similarly; and in crypto, most altcoins show a strong positive correlation with Bitcoin.
Using a Correlation Heatmap in these markets visually displays the strength and direction of these relationships, helping traders make more accurate decisions for risk management and strategy optimization.
🟣 Correlation in Financial Markets
In finance, correlation refers to measuring how closely two assets move together over time. These assets can be stocks, currency pairs, commodities, indices, or cryptocurrencies. The main goal of correlation analysis in trading is to understand these movement patterns and use them for risk management, trend forecasting, and developing trading strategies.
🟣 Correlation Heatmap
A correlation heatmap is a visual tool that presents the correlation between multiple assets in a color-coded table. Each cell shows the correlation coefficient between two assets, with colors indicating its strength and direction. Warm colors (such as red or orange) represent strong negative correlation, cool colors (such as blue or cyan) represent strong positive correlation, and mid-range tones (such as yellow or green) indicate correlations that are close to neutral.
🟣 Practical Applications in Markets
Forex : Identify currency pairs that move together or in opposite directions, avoid overexposure to similar trades, and spot unusual divergences.
Crypto : Examine the dependency of altcoins on Bitcoin and find independent movers for portfolio diversification.
Stocks : Detect relationships between stocks in the same industry or find outliers that move differently from their sector.
🟣 Key Uses of Correlation in Trading
Risk management and diversification: Select assets with low or negative correlation to reduce portfolio volatility.
Avoiding overexposure: Prevent opening multiple positions on highly correlated assets.
Pairs trading: Exploit temporary deviations between historically correlated assets for arbitrage opportunities.
Intermarket analysis: Study the relationships between different markets like stocks, currencies, commodities, and bonds.
Divergence detection: Spot when two typically correlated assets move apart as a possible trend change signal.
Market forecasting: Use correlated asset movements to anticipate others’ behavior.
Event reaction analysis: Evaluate how groups of assets respond to economic or political events.
❗ Important Note
It’s important to note that correlation does not imply causation — it only reflects co-movement between assets. Correlation is also dynamic and can change over time, which is why analyzing it across multiple timeframes provides a more accurate picture. Combining correlation heatmaps with other analytical tools can significantly improve the precision of trading decisions.
🔵 How to Use
The Correlation Heatmap Matrix indicator is designed to analyze and manage the relationships between multiple assets at once. After adding the tool to your chart, start by selecting the assets you want to compare (up to 20).
Then, choose the Correlation Period that fits your trading strategy. Shorter periods (e.g., 20 bars) are more sensitive to recent price movements, making them suitable for short-term trading, while longer periods (e.g., 100 or 200 bars) provide a broader view of correlation trends over time.
The indicator outputs a color-coded matrix where each cell represents the correlation between two assets. Warm colors like red and orange signal strong negative correlation, while cool colors like blue and cyan indicate strong positive correlation. Mid-range tones such as yellow or green suggest correlations that are close to neutral. This visual representation makes it easy to spot market patterns at a glance.
One of the most valuable uses of this tool is in portfolio risk management. Portfolios with highly correlated assets are more vulnerable to market swings. By using the heatmap, traders can find assets with low or negative correlation to reduce overall risk.
Another key benefit is preventing overexposure. For example, if EUR/USD and GBP/USD have a high positive correlation, opening trades on both is almost like doubling the position size on one asset, increasing risk unnecessarily. The heatmap makes such relationships clear, helping you avoid them.
The indicator is also useful for pairs trading, where a trader identifies assets that are usually correlated but have temporarily diverged — a potential arbitrage or mean-reversion opportunity.
Additionally, the tool supports intermarket analysis, allowing traders to see how movements in one market (e.g., crude oil) may impact others (e.g., the Canadian dollar). Divergence detection is another advantage: if two typically aligned assets suddenly move in opposite directions, it could signal a major trend shift or a news-driven move.
Overall, the Correlation Heatmap Matrix is not just an analytical indicator but also a fast, visual alert system for monitoring multiple markets at once. This is particularly valuable for traders in fast-moving environments like Forex and crypto.
🔵 Settings
🟣 Logic
Correlation Period : Number of bars used to calculate correlation between assets.
🟣 Display
Table on Chart : Enable/disable displaying the heatmap directly on the chart.
Table Size : Choose the table size (from very small to very large).
Table Position : Set the table location on the chart (top, middle, or bottom in various alignments).
🟣 Symbol Custom
Select Market : Choose the market type (Forex, Stocks, Crypto, or Custom).
Symbol 1 to Symbol 20: In custom mode, you can define up to 20 assets for correlation calculation.
🔵 Conclusion
The Correlation Heatmap Matrix is a powerful tool for analyzing correlations across multiple assets in Forex, crypto, and stock markets. By displaying a color-coded table, it visually conveys both the strength and direction of correlations — warm colors for strong negative correlation, cool colors for strong positive correlation, and mid-range tones such as yellow or green for near-zero or neutral correlation.
This helps traders select assets with low or negative correlation for diversification, avoid overexposure to similar trades, identify arbitrage and pairs trading opportunities, and detect unusual divergences between typically aligned assets. With support for custom mode and up to 20 symbols, it offers high flexibility for different trading strategies, making it a valuable complement to technical analysis and risk management.
Awesome Indicator# Moving Average Ribbon with ADR% - Complete Trading Indicator
## Overview
The **Moving Average Ribbon with ADR%** is a comprehensive technical analysis indicator that combines multiple analytical tools to provide traders with a complete picture of price trends, volatility, relative performance, and position sizing guidance. This multi-faceted indicator is designed for both swing and positional traders looking for data-driven entry and exit signals.
## Key Components
### 1. Moving Average Ribbon System
- **4 Customizable Moving Averages** with default periods: 13, 21, 55, and 189
- **Multiple MA Types**: SMA, EMA, SMMA (RMA), WMA, VWMA
- **Color-coded visualization** for easy trend identification
- **Flexible configuration** allowing users to modify periods, types, and colors
### 2. Average Daily Range Percentage (ADR%)
- Calculates the average daily volatility as a percentage
- Uses a 20-period simple moving average of (High/Low - 1) * 100
- Helps traders understand the stock's typical daily movement range
- Essential for position sizing and stop-loss placement
### 3. Volume Analysis (Up/Down Ratio)
- Analyzes volume distribution over the last 55 periods
- Calculates the ratio of volume on up days vs down days
- Provides insight into buying vs selling pressure
- Values > 1 indicate more buying volume, < 1 indicate more selling volume
### 4. Absolute Relative Strength (ARS)
- **Dual timeframe analysis** with customizable reference points
- **High ARS**: Performance relative to benchmark from a high reference point (default: Sep 27, 2024)
- **Low ARS**: Performance relative to benchmark from a low reference point (default: Apr 7, 2025)
- Uses NSE:NIFTY as default comparison symbol
- Color-coded display: Green for outperformance, Red for underperformance
### 5. Relative Performance Table
- **5 timeframes**: 1 Week, 1 Month, 3 Months, 6 Months, 1 Year
- Shows stock performance **relative to benchmark index**
- Formula: (Stock Return - Index Return) for each period
- **Color coding**:
- Lime: >5% outperformance
- Yellow: -5% to +5% relative performance
- Red: <-5% underperformance
### 6. Dynamic Position Allocation System
- **6-factor scoring system** based on price vs EMAs (21, 55, 189)
- Evaluates:
- Price above/below each EMA
- EMA alignment (21>55, 55>189, 21>189)
- **Allocation recommendations**:
- 100% allocation: Score = 6 (all bullish signals)
- 75% allocation: Score = 4
- 50% allocation: Score = 2
- 25% allocation: Score = 0
- 0% allocation: Score = -2, -4, -6 (bearish signals)
## Display Tables
### Performance Table (Top Right)
Shows relative performance vs benchmark across multiple timeframes with intuitive color coding for quick assessment.
### Metrics Table (Bottom Right)
Displays key statistics:
- **ADR%**: Average Daily Range percentage
- **U/D**: Up/Down volume ratio
- **Allocation%**: Recommended position size
- **High ARS%**: Relative strength from high reference
- **Low ARS%**: Relative strength from low reference
## How to Use This Indicator
### For Trend Analysis
1. **Moving Average Ribbon**: Look for price above ascending MAs for bullish trends
2. **MA Alignment**: Bullish when shorter MAs are above longer MAs
3. **Color coordination**: Use consistent color scheme for quick visual analysis
### For Entry/Exit Timing
1. **Performance Table**: Enter when showing consistent outperformance across timeframes
2. **Volume Analysis**: Confirm entries with U/D ratio > 1.5 for strong buying
3. **ARS Values**: Look for positive ARS readings for relative strength confirmation
### For Position Sizing
1. **Allocation System**: Use the recommended allocation percentage
2. **ADR% Consideration**: Adjust position size based on volatility
3. **Risk Management**: Lower allocation in high ADR% stocks
### For Risk Management
1. **ADR% for Stop Loss**: Set stops at 1-2x ADR% below entry
2. **Relative Performance**: Reduce positions when consistently underperforming
3. **Volume Confirmation**: Be cautious when U/D ratio deteriorates
## Best Practices
### Timeframe Recommendations
- **Intraday**: Use lower MA periods (5, 13, 21, 55)
- **Swing Trading**: Default settings work well (13, 21, 55, 189)
- **Position Trading**: Consider higher periods (21, 50, 100, 200)
### Market Conditions
- **Trending Markets**: Focus on MA alignment and relative performance
- **Sideways Markets**: Rely more on ADR% for range trading
- **Volatile Markets**: Reduce allocation percentage regardless of signals
### Customization Tips
1. Adjust reference dates for ARS calculation based on significant market events
2. Change comparison symbol to sector-specific indices for better relative analysis
3. Modify MA periods based on your trading style and market characteristics
## Technical Specifications
- **Version**: Pine Script v6
- **Overlay**: Yes (plots on price chart)
- **Real-time Updates**: Yes
- **Data Requirements**: Minimum 252 bars for complete calculations
- **Compatible Timeframes**: All standard timeframes
## Limitations
- Performance calculations require sufficient historical data
- ARS calculations depend on selected reference dates
- Volume analysis may be less reliable in low-volume stocks
- Relative performance is only as good as the chosen benchmark
This indicator is designed to provide a comprehensive analysis framework rather than simple buy/sell signals. It's recommended to use this in conjunction with your overall trading strategy and risk management rules.
Key Indicators Dashboard (KID)Key Indicators Dashboard (KID) — Comprehensive Market & Trend Metrics
📌 Overview
The Key Indicators Dashboard (KID) is an advanced multi-metric market analysis tool designed to consolidate essential technical, volatility, and relative performance data into a single on-chart table. Instead of switching between multiple indicators, KID centralizes these key measures, making it easier to assess a stock’s technical health, volatility state, trend status, and relative strength at a glance.
🛠 Key Features
⦿ Average Daily Range (ADR %): Measures average daily price movement over a specified period. It is calculated by averaging the daily price range (high - low) over a set number of days (default 20 days).
⦿ Average True Range (ATR): Measures volatility by calculating the average of a true range over a specific period (default 14). It helps traders gauge the typical extent of price movement, regardless of the direction.
⦿ ATR%: Expresses the Average True Range as a percentage of the price, which allows traders to compare the volatility of stocks with different prices.
⦿ Relative Strength (RS): Compares a stock’s performance to a chosen benchmark index (default NIFTYMIDSML400) over a specific period (default 50 days).
⦿ RS Score (IBD-style): A normalized 1–100 rating inspired by Investor’s Business Daily methodology.
How it works: The RS Score is based on a weighted average of price changes over 3 months (40%), 6 months (20%), 9 months (20%), and 12 months (20%).
The raw value is converted into a percentage return, then normalized over the past 252 trading days so the lowest value maps to 1 and the highest to 100.
This produces a percentile-style score that highlights the strongest stocks in relative terms.
⦿ Relative Volume (RVol): Compares a stock's current volume to its average volume over a specific period (default 50). It is calculated by dividing the current volume by the average historical volume.
⦿ Average ₹ Volume (Turnover): Represents the total monetary value of shares traded for a stock. It's calculated by multiplying a day's closing price by its volume, with the final value converted to crores for clarity. This metric is a key indicator of a stock's liquidity and overall market interest.
⦿ Moving Average Extension: Measures how far a stock's current price has moved from from a selected moving average (EMA or SMA). This deviation is normalized by the stock's volatility (ATR%), with a default threshold of 6 ATR used to indicate that the stock is significantly extended and is marked with a selected shape (default Red Flag).
⦿ 52-Weeks High & Low: Measures a stock's current price in relation to its highest and lowest prices over the past year. It calculates the percentage a stock is below its 52-week high and above its 52-week low.
⦿ Market Capitalization: Market Cap represents the total value of all outstanding.
⦿ Free Float: It is the value of shares readily available for public trading, with the Free Float Percentage showing the proportion of shares available to the public.
⦿ Trend: Uses Supertrend indicator to identify the current trend of a stock's price. A factor (default 3) and an ATR period (default 10) is used to signal whether the trend is up or down.
⦿ Minervini Trend Template (MTT): It is a set of technical criteria designed to identify stocks in strong uptrends.
Price > 50-DMA > 150-DMA > 200-DMA
200-DMA is trending up for at least 1 month
Price is at least 30% above its 52-week low.
Price is within at least 25 percent of its 52-week high
Table highlights when a stock meets all above criteria.
⦿ Sector & Industry: Display stock's sector and industry, provides categorical classification to assist sector-based analysis. The sector is a broad economic classification, while the industry is a more specific group within that sector.
⦿ Moving Averages (MAs): Plot up to four customizable Moving Averages on a chart. You can independently set the type (Simple or Exponential), the source price, and the length for each MA to help visualize a stock's underlying trend.
MA1: Default 10-EMA
MA2: Default 20-EMA
MA3: Default 50-EMA
MA4: Default 200-EMA
⦿ Moving Average (MA) Crossover: It is a trend signal that occurs when a shorter-term moving average crosses a longer-term one. This script identifies these crossover events and plots a marker on the chart to visually signal a potential change in trend direction.
User-configurable MAs (short and long).
A bullish crossover occurs when the short MA crosses above the long MA.
A bearish crossover occurs when the short MA crosses below the long MA.
⦿ Inside Bar (IB): An Inside Bar is a candlestick whose entire price range is contained within the range of the previous bar. This script identifies this pattern, which often signals consolidation, and visually marks bullish and bearish inside bars on the chart with distinct colors and labels.
⦿ Tightness: Identifies periods of low volatility and price consolidation. It compares the price range over a short lookback period (default 3) to the average daily range (ADR). When the lookback range is smaller than the ADR, the indicator plots a marker on the chart to signal consolidation.
⦿ PowerBar (Purple Dot): Identifies candles with a strong price move on high volume. By default, it plots a purple dot when a stock moves up or down by at least 5% and has a minimum volume of 500,000. More dots indicate higher volatility and liquidity.
⦿ Squeezing Range (SQ): Identifies periods of low volatility, which can often precede a significant price move. It checks if the Bollinger Bands have narrowed to a range that is smaller than the Average True Range (ATR) for a set number of consecutive bars (default 3).
(UpperBB - LowerBB) < (ATR × 2)
⦿ Mark 52-Weeks High and Low: Marks and labels a stock's 52-Week High and Low prices directly on the chart. It draws two horizontal lines extending from the candles where the highest and lowest prices occurred over the past year, providing a clear visual reference for long-term price extremes.
⏳PineScreener Filters
The indicator’s alert conditions act as filters for PineScreener.
Price Filter: Minimum and maximum price cutoffs (default ₹25 - ₹10000).
Daily Price Change Filter: Minimum and maximum daily percent change (default -5% and 5%).
🔔 Built-in Alerts
Supports alert creation for:
ADR%, ATR/ATR %, RS, RS Rating, Turnover
Moving Average Crossover (Bullish/Bearish)
Minervini Trend Template
52-Week High/Low
Inside Bars (Bullish/Bearish)
Tightness
Squeezing Range (SQ)
⚙️ Customizable Visualization
Switchable between vertical or horizontal layout.
Works in dark/light mode
User-configurable to toggle any indicator ON or OFF.
User-configurable Moving (EMA/SMA), Period/Lengths and thresholds.
⦿ (Optional) : For horizontal table orientation increase Top Margin to 16% in Chart (Canvas) settings to avoid chart overlapping with table.
⚡ Add this script to your chart and start making smarter trade decisions today! 🚀
ATR+CCI Monetary Risk Tool - TP/SL⚙️ ATR+CCI Monetary Risk Tool — Volatility-aware TP/SL & Position Sizing
Exact prices (no rounding), ATR-percentile dynamic stops, and risk-budget sizing for consistent execution.
🧠 What this indicator is
A risk-first planning tool. It doesn’t generate orders; it gives you clean, objective levels (Entry, SL, TP) and position size derived from your risk budget. It shows only the latest setup to keep charts readable, and a compact on-chart table summarizing the numbers you actually act on.
✨ What makes it different
Dynamic SL by regime (ATR percentile): Instead of a fixed multiple, the SL multiplier adapts to the current volatility percentile (low / medium / high). That helps avoid tight stops in noisy markets and over-wide stops in quiet markets.
Risk budgeting, not guesswork: Size is computed from Account Balance × Max Risk % divided by SL distance × point value. You risk the same dollars across assets/timeframes.
Precision that matches your instrument: Entry, TP, SL, and SL Distance are displayed as exact prices (no rounding), truncated to syminfo.mintick so they align with broker/exchange precision.
Symbol-aware point value: Uses syminfo.pointvalue so you don’t maintain tick tables.
Non-repaint option: Work from closed bars to keep the plan stable.
🔧 How to use (quick start)
Add to chart and pick your timeframe and symbol.
In settings:
Set Account Balance (USD) and Max Risk per Trade (%).
Choose R:R (1:1 … 1:5).
Pick ATR Period and CCI Period (defaults are sensible).
Keep Dynamic ATR ON to adapt SL by regime.
Keep Use closed-bar values ON to avoid repaint when planning.
Read the labels (Entry/TP/SL) and the table (SL Distance, Position Size, Max USD Risk, ATR Percentile, effective SL Mult).
Combine with your entry trigger (price action, levels, momentum, etc.). This indicator handles risk & targets.
📐 How levels are computed
Bias: CCI ≥ 0 ⇒ long, otherwise short.
ATR Percentile: Percent rank of ATR(atrPeriod) over a lookback window.
Effective SL Mult:
If percentile < Low threshold ⇒ use Low SL Mult (tighter).
If between thresholds ⇒ use Base SL Mult.
If percentile > High threshold ⇒ use High SL Mult (wider).
Stop-Loss: SL = Entry ± ATR × SL_Mult (minus for long, plus for short).
Take-Profit: TP = Entry ± (Entry − SL) × R (R from the R:R dropdown).
Position Size:
USD Risk = Balance × Risk%
Contracts = USD Risk ÷ (|Entry − SL| × PointValue)
For futures, quantity is floored to whole contracts.
Exact prices: Entry/TP/SL and SL Distance are not rounded; they’re truncated to mintick so what you see matches valid price increments.
📊 What you’ll see on chart
Latest Entry (blue), TP (green), SL (red) with labels (optional emojis: ➡️ 🎯 🛑).
Info Table with:
Bias, Entry, TP, SL (exact, truncated to mintick)
SL Distance (exact, truncated)
Position Size (contracts/units)
Max USD Risk
Point Value
ATR Percentile and effective SL Mult
🧪 Practical examples
High-volatility session (e.g., XAUUSD, 1H): ATR percentile is high ⇒ wider SL, smaller size. Reduces churn from normal noise during macro events.
Range-bound market (e.g., EURUSD, 4H): ATR percentile low ⇒ tighter SL, better R:R. Helps you avoid carrying unnecessary risk.
Index swing planning (e.g., ES1!, Daily): Non-repaint levels + risk budgeting = consistent sizing across days/weeks, easier to review and journal.
🧭 Why traders should use it
Consistency: Same dollar risk regardless of instrument or volatility regime.
Clarity: One-trade view forces focus; you see the numbers that matter.
Adaptivity: Stops calibrated to the market’s current behavior, not last month’s.
Discipline: A visible checklist (SL distance, size, USD risk) before you hit buy/sell.
🔧 Input guide (practical defaults)
CCI Period: 100 by default; use as a bias filter, not an entry signal.
ATR Period: 14 by default; raise for smoother, lower for more reactive.
ATR Percentile Lookback: 200 by default (stable regime detection).
Percentile thresholds: 33/66 by default; widen the gap to change how often regimes switch.
SL Mults: Start ~1.5 / 2.0 / 2.5 (low/base/high). Tune by asset.
Risk % per trade: Common pro ranges are 0.25–1.0%; adjust to your risk tolerance.
R:R: Start with 1:2 or 1:3 for balanced skew; adapt to strategy edge.
Closed-bar values: Keep ON for planning/live; turn OFF only for exploration.
💡 Best practices
Combine with your entry logic (structure, momentum, liquidity levels).
Review ATR percentile and effective SL Mult across sessions so you understand regime shifts.
For futures, remember size is floored to whole contracts—safer by design.
Journal trades with the table snapshot to improve risk discipline over time.
⚠️ Notes & limitations
This is not a strategy; it does not place orders or alerts.
No slippage/commissions modeled here; build a strategy() version for backtests that mirror your broker/exchange.
Displayed non-price metrics use two decimals; prices and SL Distance are exact (truncated to mintick).
📎 Disclaimer
For educational purposes only. Not financial advice. Markets involve risk. Test thoroughly before trading live.
NightWatch 24/5 [theUltimator5]NightWatch 24/5 is a comprehensive indicator designed to seamlessly display both regular and overnight trading (BOATS exchange) into a single chart. Current TV limitations don't allow both overnight trading and regular exchanges to appear on the same chart due to timeframe visibility settings. We can either select between RTH (Regular Trading Hours) or ETH (Extended Trading Hours). There is no option to show 24 hour charts when looking at a stock. This indicator attempts to solve this issue.
Please read the entire description thoroughly because this indicator takes a little bit of setup to work properly!
---IMPORTANT-- -
This indicator MUST be used over a liquid cryptocurrency chart, like Bitcoin. It requires access to something that trades 24/7 and has volume data for all periods. Bitcoin on Coinbase is the best option. Please select Bitcoin as your main ticker before adding this indicator to the chart.
-------------------
This indicator combines the price of both the regular trading hours and the overnight trading to create a single price line and volume candles. You can select view settings to either overlay the price on the chart, or have it below the chart. Volume can be toggled on or off as well.
Default settings:
Ticker = GME
Overlay Candles on Main Chart = true
Display Data = Both Price and Volume
Show Status Table = true
Here is an explanation for each of these settings:
Ticker - Type in the ticker you want to track overnight and intraday data for
Overlay Candles on Main chart - This will push the price candles onto the main chart area instead of below it. Volume candles will remain in their own separate pane below. This is useful if you want to track both price and volume without adding the indicator twice.
Display Data - This determines what data to show. Volume, price, or both volume and price.
Show Status Table - This toggles on or off the table that shows the ticker name, current session, and the price (change) of the ticker since the most recent daily close.
If you overlay the price onto the chart, the price of the stock you are looking at will likely be a VERY different price than the crypto it is overlaying against. There are a couple workarounds. You can either zoom into the chart around the price of the stock you are looking at (time consuming), or you can go into your object tree and drag the indicator up into the main chart area. This will overlay the price onto the crypto while maintaining it's own unique y-axis.
After you move the indicator up, you can add the indicator back a second time, then change the settings to only show the volume candles. You can then toggle off the table on one of the two so you don't see duplicate tables. This is the setting I am showing in my chart above. The indicator is added twice with the price being pulled up into the same window as Bitcoin, then a second instance below showing just volume.
--LIMITATIONS--
Since the indicator requires the use of a 24 hour market ticker like Bitcoin, it DOES NOT display extended hours data. The price and volume data STOPS at 16:00 EST then resumes back up at 20:00 EST when BOATS opens. At 04:00, the price and volume then stops until 09:30, when the regular trading hours begin. This causes a flat line in the price during those periods. Unfortunately, there is no current workaround to this issue.
If Bitcoin becomes illiquid (or whatever crypto you choose), it will only populate data for the ticker you want if there is data available for that crypto at the same time period. A gap in Bitcoin volume will show a gap in trade activity for your ticker.
The Visualized Trader (Fractal Timeframe)The **The Visualized Trader (Fractal Timeframe)** indicator for TradingView is a tool designed to help traders identify strong bullish or bearish trends by analyzing multiple technical indicators across two timeframes: the current chart timeframe and a user-selected higher timeframe. It visually displays trend alignment through arrows on the chart and a condition table in the top-right corner, making it easy to see when conditions align for potential trade opportunities.
### Key Features
1. **Multi-Indicator Analysis**: Combines five technical conditions to confirm trend direction:
- **Trend**: Based on the slope of the 50-period Simple Moving Average (SMA). Upward slope indicates bullish, downward indicates bearish.
- **Stochastic (Stoch)**: Uses Stochastic Oscillator (5, 3, 2) to measure momentum. Rising values suggest bullish momentum, falling values suggest bearish.
- **Momentum (Mom)**: Derived from the MACD fast line (5, 20, 30). Rising MACD line indicates bullish momentum, falling indicates bearish.
- **Dad**: Uses the MACD signal line. Rising signal line is bullish, falling is bearish.
- **Price Change (PC)**: Compares the current close to the previous close. Higher close is bullish, lower is bearish.
2. **Dual Timeframe Comparison**:
- Calculates the same five conditions on both the current timeframe and a user-selected higher timeframe (e.g., daily).
- Helps traders see if the trend on the higher timeframe aligns with the current chart, providing context for stronger trade decisions.
3. **Visual Signals**:
- **Arrows on Chart**:
- **Current Timeframe**: Blue upward arrows below bars for bullish alignment, red downward arrows above bars for bearish alignment.
- **Higher Timeframe**: Green upward triangles below bars for bullish alignment, orange downward triangles above bars for bearish alignment.
- Arrows appear only when all five conditions align (all bullish or all bearish), indicating strong trend potential.
4. **Condition Table**:
- Displays a table in the top-right corner with two rows:
- **Top Row**: Current timeframe conditions (Trend, Stoch, Mom, Dad, PC).
- **Bottom Row**: Higher timeframe conditions (labeled with "HTF").
- Each cell is color-coded: green for bullish, red for bearish.
- The table can be toggled on/off via input settings.
5. **User Input**:
- **Show Condition Boxes**: Toggle the table display (default: on).
- **Comparison Timeframe**: Choose the higher timeframe (e.g., "D" for daily, default setting).
### How It Works
- The indicator evaluates the five conditions on both timeframes.
- When all conditions are bullish (or bearish) on a given timeframe, it plots an arrow/triangle to signal a strong trend.
- The condition table provides a quick visual summary, allowing traders to compare the current and higher timeframe trends at a glance.
### Use Case
- **Purpose**: Helps traders confirm strong trend entries by ensuring multiple indicators align across two timeframes.
- **Example**: If you're trading on a 1-hour chart and see blue arrows with all green cells in the current timeframe row, plus green cells in the higher timeframe (e.g., daily) row, it suggests a strong bullish trend supported by both timeframes.
- **Benefit**: Reduces noise by focusing on aligned signals, helping traders avoid weak or conflicting setups.
### Settings
- Access the indicator settings in TradingView to:
- Enable/disable the condition table.
- Select a higher timeframe (e.g., 4H, D, W) for comparison.
### Notes
- Best used in trending markets; may produce fewer signals in choppy conditions.
- Combine with other analysis (e.g., support/resistance) for better decision-making.
- The higher timeframe signals (triangles) provide context, so prioritize trades where both timeframes align.
This indicator simplifies complex trend analysis into clear visual cues, making it ideal for traders seeking confirmation of strong momentum moves.
OBR 15min Session Opening Range Breakout + Volume Trend DeltaQuick Overview
This Pine Script plots the opening range for London and New York sessions, highlights breakout levels, draws previous session pivots, and offers a live volume delta table for trend confirmation.
Session Opening Range
- Captures the high/low of the first 15 minutes (configurable) for both London & NY sessions.
- Fills the range area with adjustable semi‑transparent colors.
- Optional alerts fire on breakout above the high or below the low.
Previous Session Levels
- Automatically draws previous day’s High, Low, Open and previous 4‑hour High/Low.
- Helps identify key S/R zones as price approaches ORB breakouts.
Volume Trend Delta
- Uses a CMO‑weighted moving average and ATR bands to detect trend state.
- Accumulates bullish vs. bearish volume during each trend.
- Displays Bull Vol, Bear Vol, and Delta % in a movable table for quick strength checks.
How to Use
1. Let the opening range complete (first 15 min).
2. Look for price closing above/below the ORB—enter long on an upside break, short on a downside break.
3. Check the Volume Delta table: positive delta confirms buying strength; negative delta confirms selling pressure.
4. Use previous day/4h levels as additional support/resistance filters.
Settings & Customization
- ORB Duration & Session Times (London/NY), fill colors, and toggles.
- Enable/disable Previous Day & 4H levels.
- Trend Period, Momentum Window, and Delta table position/size.
- Pre‑built alert conditions for all ORB breakouts.
Developer Notes
- Fully commented for easy adjustments.
- Modular sections: ORB, previous levels, trend delta, and alerts.
- No external libraries—pure Pine Script v6.
Tip
Combine ORB breakouts with Volume Delta and prior session pivots to filter false signals and trade stronger, more reliable moves.
ATR Buy, Target, Stop + OverlayATR Buy, Target, Stop + Overlay
This tool is to assist traders with precise trade planning using the Average True Range (ATR) as a volatility-based reference.
This script plots buy, target, and stop-loss levels on the chart based on a user-defined buy price and ATR-based multipliers, allowing for objective and adaptive trade management.
*NOTE* In order for the indicator to initiate plotted lines and table values a non-zero number must be entered into the settings.
What It Does:
Buy Price Input: Users enter a manual buy price (e.g., an executed or planned trade entry).
ATR-Based Target and Stop: The script calculates:
Target Price = Buy + (ATR × Target Multiplier)
Stop Price = Buy − (ATR × Stop Multiplier)
Customizable Timeframe: Optionally override the ATR timeframe (e.g., use daily ATR on a 1-hour chart).
Visual Overlay: Lines are drawn directly on the price chart for the Buy, Target, and Stop levels.
Interactive Table: A table is displayed with relevant levels and ATR info.
Customization Options:
Line Settings:
Adjust color, style (solid/dashed/dotted), and width for Buy, Target, and Stop lines.
Choose whether to extend lines rightward only or in both directions.
Table Settings:
Choose position (top/bottom, left/right).
Toggle individual rows for Buy, Target, Stop, ATR Timeframe, and ATR Value.
Customize text color and background transparency.
How to Use It for Trading:
Plan Your Trade: Enter your intended buy price when planning a trade.
Assess Risk/Reward: The script immediately visualizes the potential stop-loss and target level, helping assess R:R ratios.
Adapt to Volatility: Use ATR-based levels to scale stop and target dynamically depending on current market volatility.
Higher Timeframe ATR: Select a different timeframe for the ATR calculation to smooth noise on lower timeframe charts.
On-the-Chart Reference: Visually track trade zones directly on the price chart—ideal for live trading or strategy backtesting.
Ideal For:
Swing traders and intraday traders
Risk management and trade planning
Traders using ATR-based exits or scaling
Visualizing asymmetric risk/reward setups
How I Use This:
After entering a trade, adding an entry price will plot desired ATR target and stop level for visualization.
Adjusting ATR multiplier values assists in evaluating and planning trades.
Visualization assists in comparing ATR multiples to recent support and resistance levels.
Rolling VWAP LevelsRolling VWAP Levels Indicator
Overview
Dynamic horizontal lines showing rolling Volume Weighted Average Price (VWAP) levels for multiple timeframes (7D, 30D, 90D, 365D) that update in real-time as new bars form.
Who This Is For
Day traders using VWAP as support/resistance
Swing traders analyzing multi-timeframe price structure
Scalpers looking for mean reversion entries
Options traders needing volatility bands for strike selection
Institutional traders tracking volume-weighted fair value
Risk managers requiring dynamic stop levels
How To Trade With It
Mean Reversion Strategies:
Buy when price is below VWAP and showing bullish divergence
Sell when price is above VWAP and showing bearish signals
Use multiple timeframes - enter on shorter, confirm on longer
Target opposite VWAP level for profit taking
Breakout Trading:
Watch for price breaking above/below key VWAP levels with volume
Use 7D VWAP for intraday breakouts
Use 30D/90D VWAP for swing trade breakouts
Confirm breakout with move beyond first standard deviation band
Support/Resistance Trading:
VWAP levels act as dynamic support in uptrends
VWAP levels act as dynamic resistance in downtrends
Multiple timeframe VWAP confluence creates stronger levels
Use standard deviation bands as additional S/R zones
Risk Management:
Place stops beyond next VWAP level
Use standard deviation bands for position sizing
Exit partial positions at VWAP levels
Monitor distance table for overextended moves
Key Features
Real-time Updates: Lines move and extend as new bars form
Individual Styling: Custom colors, widths, styles for each timeframe
Standard Deviation Bands: Optional volatility bands with custom multipliers
Smart Labels: Positioned above, below, or diagonally relative to lines
Distance Table: Shows percentage distance from each VWAP level
Alert System: Get notified when price crosses VWAP levels
Memory Efficient: Automatically cleans up old drawing objects
Settings Explained
Display Group: Show/hide labels, font size, line transparency, positioning
Individual VWAP Groups: Color, line width (1-5), line style for each timeframe
Standard Deviation Bands: Enable bands with custom multipliers (0.5, 1.0, 1.5, 2.0, etc.)
Labels Group: Position (8 options including diagonal), custom text, price display
Additional Info: Distance table, alert conditions
Technical Implementation
Uses rolling arrays to maintain sliding windows of price*volume data. The core calculation function processes both VWAP and standard deviation efficiently. Lines are created dynamically and updated every bar. Memory management prevents object accumulation through automatic cleanup.
Best Practices
Start with 7D and 30D VWAP for most strategies
Add 90D/365D for longer-term context
Use standard deviation bands when volatility matters
Position labels to avoid chart clutter
Enable distance table during high volatility periods
Set alerts for key VWAP level breaks
Market Applications
Forex: Major pairs during London/NY sessions
Stocks: Large cap names with good volume
Crypto: Bitcoin, Ethereum, major altcoins
Futures: ES, NQ, CL, GC with continuous volume
Options: Use SD bands for strike selection and volatility assessment
Share SizePurpose: The "Share Size" indicator is a powerful risk management tool designed to help traders quickly determine appropriate share/contract sizes based on their predefined risk per trade and the current market's volatility (measured by ATR). It calculates potential dollar differences from recent highs/lows and translates them into a recommended share/contract size, accounting for a user-defined ATR-based offset. This helps you maintain consistent risk exposure across different instruments and market conditions.
How It Works: At its core, the indicator aims to answer the question: "How many shares/contracts can I trade to keep my dollar risk within limits if my stop loss is placed at a recent high or low, plus an ATR-based buffer?"
Price Difference Calculation: It first calculates the dollar difference between the current close price and the high and low of the current bar (Now) and the previous 5 bars (1 to 5).
Tick Size & Value Conversion: These price differences are then converted into dollar values using the instrument's specific tickSize and tickValue. You can select common futures contracts (MNQ, MES, MGC, MCL), a generic "Stock" setting, or define custom values.
ATR Offset: An Average True Range (ATR) based offset is added to these dollar differences. This offset acts as a buffer, simulating a stop loss placed beyond the immediate high/low, accounting for market noise or volatility.
Risk-Based Share Size: Finally, using your Default Risk ($) input, the indicator calculates how many shares/contracts you can take for each of the 6 high/low scenarios (current bar, 5 previous bars) to ensure your dollar risk per trade remains constant.
Dynamic Table: All these calculations are presented in a clear, real-time table at the bottom-left of your chart. The table dynamically adjusts its "Label" to show the selected symbol preset, making it easy to see which instrument's settings are currently being used. The "Shares" rows indicate the maximum shares/contracts you can trade for a given risk and stop placement. The cells corresponding to the largest dollar difference (and thus smallest share size) for both high and low scenarios are highlighted, drawing your attention to the most conservative entry points.
Key Benefits:
Consistent Risk: Helps maintain a consistent dollar risk per trade, regardless of the instrument or its current price/volatility.
Dynamic Sizing: Automatically adjusts share/contract size based on market volatility and your chosen stop placement.
Quick Reference: Provides a real-time, easy-to-read table directly on your chart, eliminating manual calculations.
Informed Decision Making: Assists in quickly assessing trade opportunities and potential position sizes.
Setup Parameters (Inputs)
When you add the "Share Size" indicator to your chart, you'll see a settings dialog with the following parameters:
1. Symbol Preset:
Purpose: This is the primary setting to define the tick size and value for your chosen trading instrument.
Options:
MNQ (Micro Nasdaq 100 Futures)
MES (Micro E-mini S&P 500 Futures)
MGC (Micro Gold Futures)
MCL (Micro Crude Oil Futures)
Stock (Generic stock setting, with tick size/value of 0.01)
Custom (Allows you to manually input tick size and value)
Default: MNQ
Importance: Crucial for accurate dollar calculations. Ensure this matches the instrument you are trading.
2. Tick Size (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the smallest price increment for your instrument.
Type: Float
Default: 0.25
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. You might need to change display=display.none to display=display.inline in the code if you want to see and adjust it directly in the settings for "Custom" mode.
3. Tick Value (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the dollar value of one tickSize increment.
Type: Float
Default: 0.50
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. Similar to Tick Size, you might need to adjust its display property if you want it visible.
4. Default Risk ($):
Purpose: This is your maximum desired dollar risk per trade. All share size calculations will be based on this value.
Type: Float
Default: 50.0
Hidden: This input is hidden (display=display.none). It's a critical setting, so consider making it visible by changing display=display.none to display=display.inline in the code if you want users to easily adjust their risk.
ATR Offset Settings (Group): This group of settings allows you to fine-tune the ATR-based buffer added to your potential stop loss.
5. ATR Offset Length:
Purpose: Defines the lookback period for the Average True Range (ATR) calculation used for the offset.
Type: Integer
Default: 7
Hidden: This input is hidden (display=display.none).
6. ATR Offset Timeframe:
Purpose: Specifies the timeframe on which the ATR for the offset will be calculated. This allows you to use ATR from a higher timeframe for your stop buffer, even if your chart is on a lower timeframe.
Type: Timeframe string (e.g., "1" for 1 minute, "60" for 1 hour, "D" for Daily)
Default: "1" (1 Minute)
Hidden: This input is hidden (display=display.none).
7. ATR Offset Multiplier (x ATR):
Purpose: Multiplies the calculated ATR value to determine the final dollar offset added to your high/low price difference. A value of 1.0 means one full ATR is added. A value of 0.5 means half an ATR is added.
Type: Float
Minimum Value: 0 (no offset)
Default: 1.0
Hidden: This input is hidden (display=display.none).
RSI Multi-TF TabRSI Multi-Timeframe Table 📊
A tool for multi-timeframe RSI analysis with visual overbought/oversold level highlighting.
Description
This indicator calculates the Relative Strength Index (RSI) for the current chart and displays RSI values across five additional timeframes (15m, 1h, 4h, 1d, 1w) in a dynamic table. The color-coded system simplifies identifying overbought (>70), oversold (<30), and neutral zones. Visual signals on the chart enhance analysis for the current timeframe.
Key Features
✅ Multi-Timeframe Analysis :
Track RSI across 15m, 1h, 4h, 1d, and 1w in a compact table.
Color-coded alerts:
🔴 Red — Overbought (potential pullback),
🔵 Blue — Oversold (potential rebound),
🟡 Yellow — Neutral zone.
✅ Visual Signals :
Background shading for oversold/overbought zones on the main chart.
Horizontal lines at 30 and 70 levels for reference.
✅ Customizable Settings :
Adjust RSI length (default: 14), source (close, open, high, etc.), and threshold levels.
How to Use
Table Analysis :
Compare RSI values across timeframes to spot divergences (e.g., overbought on 15m vs. oversold on D).
Use colors for quick decisions.
Chart Signals :
Blue background suggests bullish potential (oversold), red hints at bearish pressure (overbought).
Always confirm with other tools (volume, trends, or candlestick patterns).
Examples :
RSI(1h) > 70 while RSI(4h) < 30 → Possible reversal upward.
Sustained RSI(1d) above 50 may indicate a bullish trend.
Settings
RSI Length : Period for RSI calculation (default: 14).
RSI Source : Data source (close, open, high, low, hl2, hlc3, ohlc4).
Overbought/Oversold Levels : Thresholds for alerts (default: 70/30).
Important Notes
No direct trading signals : Use this as an analytical tool, not a standalone strategy.
Test strategies historically and consider market context before trading.
CCI Divergence Detector
A technical analysis tool that identifies divergences between price action and the Commodity Channel Index (CCI) oscillator. Unlike standard divergence indicators, this system employs advanced gradient visualization, multi-layer wave effects, and comprehensive customization options to provide traders with crystal-clear divergence signals and market momentum insights.
Core Detection Mechanism
CCI-Based Analysis: The indicator utilizes the Commodity Channel Index as its primary oscillator, calculated from user-configurable source data (default: HLC3) with adjustable length parameters. The CCI provides reliable momentum readings that effectively highlight price-momentum divergences.
Dynamic Pivot Detection: The system employs adaptive pivot detection with three sensitivity levels (High/Normal/Low) to identify significant highs and lows in both price and CCI values. This dynamic approach ensures optimal divergence detection across different market conditions and timeframes.
Dual Divergence Analysis:
Regular Bullish Divergences: Detected when price makes lower lows while CCI makes higher lows, indicating potential upward reversal
Regular Bearish Divergences: Identified when price makes higher highs while CCI makes lower highs, signaling potential downward reversal
Strength Classification System: Each detected divergence is automatically classified into three strength categories (Weak/Moderate/Strong) based on:
-Price differential magnitude
-CCI differential magnitude
-Time duration between pivot points
-User-configurable strength multiplier
Advanced Visual System
Multi-Layer Wave Effects: The indicator features a revolutionary wave visualization system that creates depth through multiple gradient layers around the CCI line. The wave width dynamically adjusts based on ATR volatility, providing intuitive visual feedback about market conditions.
Professional Color Gradient System: Nine independent color inputs control every visual aspect:
Bullish Colors (Light/Medium/Dark): Control oversold areas, wave effects, and strong bullish signals
Bearish Colors (Light/Medium/Dark): Manage overbought zones, wave fills, and strong bearish signals
Neutral Colors (Light/Medium/Dark): Handle table elements, zero line, and transitional states
Intelligent Color Mapping: Colors automatically adapt based on CCI values:
Overbought territory (>100): Bearish color gradients with increasing intensity
Neutral positive (0 to 100): Blend from neutral to bearish tones
Oversold territory (<-100): Bullish color gradients with increasing intensity
Neutral negative (-100 to 0): Transition from neutral to bullish tones
Key Features & Components
Advanced Configuration System: Eight organized input groups provide granular control:
General Settings: System enable, pivot length, confidence thresholds
Oscillator Selection: CCI parameters, overbought/oversold levels, normalization options
Detection Parameters: Divergence types, minimum strength requirements
Sensitivity Tuning: Pivot sensitivity, divergence threshold, confirmation bars
Visual System: Line thickness, labels, backgrounds, table display
Wave Effects: Dynamic width, volatility response, layer count, glow effects
Transparency Controls: Independent transparency for all visual elements
Smoothing & Filtering: CCI smoothing types, noise filtering, wave smoothing
Professional Alert System: Comprehensive alert functionality with dynamic messages including:
-Divergence type and strength classification
-Current CCI value and confidence percentage
-Customizable alert frequency and conditions
Enhanced Information Table: Real-time display showing:
-Current CCI length and value
-Market status (Overbought/Normal/Oversold)
-Active sensitivity setting
Configurable table positioning (4 corner options)
Visual Elements Explained
Primary CCI Line: Main oscillator plot with gradient coloring that reflects market momentum and CCI intensity. Line thickness is user-configurable (1-8 pixels).
Wave Effect Layers: Multi-layer gradient fills creating a dynamic wave around the
CCI line:
-Outer layers provide broad market context
-Inner layers highlight immediate momentum
-Core layers show precise CCI movement
-All layers respond to volatility and momentum changes
Divergence Lines & Labels:
-Solid lines connecting divergence pivot points
-Color-coded based on divergence type and strength
-Labels displaying divergence type and strength classification
-Customizable transparency and size options
Reference Lines:
-Zero line with neutral color coding
-Overbought level (default: 100) with bearish coloring
-Oversold level (default: -100) with bullish coloring
Background Gradient: Optional background coloring that reflects CCI intensity and market conditions with user-controlled transparency (80-99%).
Configuration Options
Sensitivity Controls:
Pivot sensitivity: High/Normal/Low detection levels
Divergence threshold: 0.1-2.0 sensitivity range
Confirmation bars: 1-5 bar confirmation requirement
Strength multiplier: 0.1-3.0 calculation adjustment
Visual Customization:
Line transparency: 0-90% for main elements
Wave transparency: 0-95% for fill effects
Background transparency: 80-99% for subtle background
Label transparency: 0-50% for text elements
Glow transparency: 50-95% for glow effects
Advanced Processing:
Five smoothing types: None/SMA/EMA/RMA/WMA
Noise filtering with adjustable threshold (0.1-10.0)
CCI normalization for enhanced gradient scaling
Dynamic wave width with ATR-based volatility response
Interpretation Guidelines
Divergence Signals:
Strong divergences: High-confidence reversal signals requiring immediate attention
Moderate divergences: Reliable signals suitable for most trading strategies
Weak divergences: Early warning signals best combined with additional confirmation
Wave Intensity: Wave width and color intensity provide real-time volatility and momentum feedback. Wider, more intense waves indicate higher market volatility and stronger momentum.
Color Transitions: Smooth color transitions between bullish, neutral, and bearish states help identify market regime changes and momentum shifts.
CCI Levels: Traditional overbought (>100) and oversold (<-100) levels remain relevant, but the gradient system provides more nuanced momentum reading between these extremes.
Technical Specifications
Compatible Timeframes: All timeframes supported
Maximum Labels: 500 (for divergence marking)
Maximum Lines: 500 (for divergence drawing)
Pine Script Version: v5 (latest optimization)
Overlay Mode: False (separate pane indicator)
Usage Recommendations
This indicator works best when:
-Combined with price action analysis and support/resistance levels
-Used across multiple timeframes for confirmation
-Integrated with proper risk management protocols
-Applied in trending markets for divergence-based reversal signals
-Utilized with other technical indicators for comprehensive analysis
Risk Disclaimer: Trading involves substantial risk of loss. This indicator is provided for analytical purposes only and does not constitute financial advice. Divergence signals, while powerful, are not guaranteed to predict future price movements. Past performance is not indicative of future results. Always use proper risk management and never trade with capital you cannot afford to lose.
Adaptive Freedom Machine w/labelsAdaptive Freedom Machine w/ Labels
Overview
The Adaptive Freedom Machine w/ Labels is a versatile Pine Script indicator designed to assist traders in identifying buy and sell opportunities across various market conditions (trending, ranging, or volatile). It combines Exponential Moving Averages (EMAs), Relative Strength Index (RSI), Average True Range (ATR), and customizable time filters to generate actionable signals. The indicator overlays on the price chart, displaying EMAs, a dynamic cloud, scaled RSI levels, buy/sell signals, and market condition labels, making it suitable for swing trading, day trading, or scalping.
What It Does
This indicator generates buy and sell signals based on the interaction of two EMAs, filtered by RSI thresholds, ATR-based volatility, and user-defined time windows. It adapts to the selected market condition by adjusting EMA lengths, RSI thresholds, and trading hours. A dynamic cloud highlights trend direction or neutral zones, and candlestick bodies are colored in neutral conditions for clarity. A table displays real-time trend and volatility status.
How It Works
The indicator uses the following components:
EMAs: Two EMAs (short and long) are calculated on a user-selected timeframe (1, 5, 15, 30, or 60 minutes). Their crossover or crossunder generates potential buy/sell signals, with lengths adjusted based on the market condition (e.g., longer EMAs for trending markets, shorter for ranging).
Dynamic Cloud: The area between the EMAs forms a cloud, colored green for uptrends, red for downtrends, or a user-defined color (default yellow) for neutral zones (when EMAs are close, determined by an ATR-based threshold). Users can widen the cloud for visibility.
RSI Filter: RSI is scaled to price levels and plotted on the chart (optional). Signals are filtered to ensure RSI is within user-defined buy/sell thresholds and not in overbought/oversold zones, with thresholds tailored to the market condition.
ATR Volatility Filter: An optional filter ensures signals occur during sufficient volatility (ATR(14) > SMA(ATR, 20)).
Time Filter: Signals are restricted to a user-defined or market-specific time window (e.g., 10:00–15:00 UTC for volatile markets), with an option for custom hours.
Visual Aids: Buy/sell signals appear as green triangles (buy) or red triangles (sell). Candlesticks in neutral zones are colored (default yellow). A table in the top-right corner shows the current trend (Uptrend, Downtrend, Neutral) and volatility (High or Low).
The indicator ensures compatibility with standard chart types (e.g., candlestick charts) to produce realistic signals, avoiding non-standard types like Heikin Ashi or Renko.
How to Use It
Add to Chart: Apply the indicator to a candlestick or bar chart on TradingView.
Configure Settings:
Timeframe: Choose a timeframe (1, 5, 15, 30, or 60 minutes) to align with your trading style.
Market Condition: Select one market condition (Trending, Ranging, or Volatile). Volatile is the default if none is selected. Only one condition can be active.
Filters:
Enable/disable the ATR volatility filter to trade only in high-volatility periods.
Enable the time filter and choose default hours (specific to the market condition) or set custom UTC hours.
Cloud Settings: Adjust the cloud width, neutral zone threshold, and color. Enable/disable the neutral cloud.
RSI Display: Toggle the scaled RSI and its thresholds on the chart.
Interpret Signals:
Buy Signal: A green triangle below the bar indicates a potential long entry (EMA crossover, RSI above buy threshold, within time window, and passing volatility filter).
Sell Signal: A red triangle above the bar indicates a potential short entry (EMA crossunder, RSI below sell threshold, within time window, and passing volatility filter).
Neutral Zone: Yellow candlesticks and cloud (if enabled) suggest a lack of clear trend; avoid trading or use for range-bound strategies.
Monitor the Table: Check the top-right table for real-time trend (Uptrend, Downtrend, Neutral) and volatility (High or Low) to confirm market context.
Unique Features
Adaptive Parameters: Automatically adjusts EMA lengths, RSI thresholds, and trading hours based on the selected market condition, reducing manual tweaking.
Neutral Zone Detection: Uses an ATR-based threshold to identify low-trend periods, helping traders avoid choppy markets.
Scaled RSI Visualization: Plots RSI and thresholds directly on the price chart, making it easier to assess momentum relative to price action.
Flexible Time Filtering: Supports both default and custom UTC-based trading windows, ideal for day traders targeting specific sessions.
Dynamic Cloud: Enhances trend visualization with customizable width and neutral zone coloring, improving readability.
Notes
Use on standard candlestick or bar charts to ensure realistic signals.
Test the indicator on a demo account to understand its behavior in your chosen market and timeframe.
Adjust settings to match your trading strategy, but avoid over-optimizing for past data.
The indicator is not a standalone system; combine it with other analysis (e.g., support/resistance, news events) for better results.
Limitations
Signals may lag in fast-moving markets due to EMA-based calculations.
Neutral zone detection may vary in extremely volatile or illiquid markets.
Time filters are UTC-based; ensure your platform’s timezone settings align.
This indicator is designed for traders seeking a customizable, trend-following tool that adapts to different market environments while providing clear visual cues and robust filtering.
Hippo Battlefield - Bulls VS Bears 20 bars## Hippo Battlefield – Bulls VS Bears (20 Bars)
**What it is**
A multi-dimensional momentum-and-sentiment oscillator that combines classic Bull/Bear Power with ATR- or peak-normalization, then layers on RSI and MACD-derived metrics into:
1. **A colored bar series** showing net Bull+Bear Power strength over the last 20 bars,
2. **A dynamic table** of each of those 20 BBP values (grouped into four 5-bar “quartals”), with symbols, per-bar change, and rolling averages, and
3. **A composite “Weighted BBP” histogram** blending normalized RSI, MACD, and BBP into a single view.
---
### Key Inputs
- **Length (EMA)** – look-back for the underlying EMA (default 60)
- **Normalization Length** – look-back window for peak-normalization (default 60)
- **Use ATR for Norm.** – toggle ATR-based normalization vs. highest-abs(BBP)
- **Show Tables** – toggle the bottom-right 21×11 grid of raw and average BBP values
---
### What You See
#### 1. Colored Bars (Overlay = false)
- Bars are colored by normalized BBP intensity:
- Extreme Bull (≥+10): deep blue
- Strong Bull (+5 to +10): green/yellow
- Weak Bull (+0 to +5): dark green
- Weak Bear (–0 to –5): dark red
- Strong Bear (–5 to –10): pink/red
- Extreme Bear (<–10): magenta
#### 2. Bottom-Right Table (20 Bars of Data)
- Divided into four columns (0–4, 5–9, 10–14, 15–19 bars ago) and one “average” row.
- Each cell shows:
1. Bar index (1–20),
2. Normalized BBP value (to four decimals),
3. Direction symbol (↑/↓/=),
4. Bar-to-bar change (± value),
5. A separator “|”.
- At the very bottom, each column’s 5-bar average is displayed as “Avg: X.XXXX” with a dot marker.
#### 3. Top-Center Mini-Table
- When ≥20 bars have elapsed, shows the date at 20 bars ago and the average BBP across the full 20-bar window.
#### 4. Normalized RSI Line
- Rescales the classic 14-period RSI into a –20…+20 band to align with BBP.
#### 5. MACD Lines (Hidden) & Composite Histogram
- MACD and signal lines are calculated but not plotted by default.
- A “Weighted BBP” histogram combines:
- 20% normalized RSI,
- 20% average of (MACD + signal + normalized BBP),
- 60% normalized BBP
- Plotted as columns, color-coded by strength using the same palette as the main bars.
#### 6. Middle Reference Line
- A horizontal zero line to anchor over/under-zero readings.
---
### How to Use It
- **Trend confirmation**: Strong blue/green bars alongside a rising histogram suggest bull conviction; strong reds/magentas signal bear dominance.
- **Divergence spotting**: Watch for price making new highs/lows while BBP or the histogram fails to follow.
- **Quartal analysis**: The 5-bar group averages can reveal whether recent momentum is accelerating or waning.
- **Cross-indicator weighting**: Because RSI, MACD, and raw BBP all feed into the final histogram, you get a smoothed, blended view of momentum shifts.
---
**Tip:** Tweak the EMA and normalization length to suit your preferred timeframe (e.g. shorter for intraday scalps, longer for swing trades). Enable/disable the table if you prefer a cleaner pane.
BTC Daily DCA CalculatorThe BTC Daily DCA Calculator is an indicator that calculates how much Bitcoin (BTC) you would own today by investing a fixed dollar amount daily (Dollar-Cost Averaging) over a user-defined period. Simply input your start date, end date, and daily investment amount, and the indicator will display a table on the last candle showing your total BTC, total invested, portfolio value, and unrealized yield (in USD and percentage).
Features
Customizable Inputs: Set the start date, end date, and daily dollar amount to simulate your DCA strategy.
Results Table: Displays on the last candle (top-right of the chart) with:
Total BTC: The accumulated Bitcoin from daily purchases.
Total Invested ($): The total dollars invested.
Portfolio Value ($): The current value of your BTC holdings.
Unrealized Yield ($): Your profit/loss in USD.
Unrealized Yield (%): Your profit/loss as a percentage.
Visual Markers: Green triangles below the chart mark each daily investment.
Overlay on Chart: The table and markers appear directly on the BTCUSD price chart for easy reference.
Daily Timeframe: Designed for Daily (1D) charts to ensure accurate calculations.
How to Use
Add the Indicator: Apply the indicator to a BTCUSD chart (e.g., Coinbase:BTCUSD, Binance:BTCUSDT).
Set Daily Timeframe: Ensure your chart is on the Daily (1D) timeframe, or the script will display an error.
Configure Inputs: Open the indicator’s Settings > Inputs tab and set:
Start Date: When to begin the DCA strategy (e.g., 2024-01-01).
End Date: When to end the strategy (e.g., 2025-04-27 or earlier).
Daily Investment ($): The fixed dollar amount to invest daily (e.g., $100).
View Results: Scroll to the last candle in your date range to see the results table in the top-right corner of the chart. Green triangles below the bars indicate investment days.
Settings
Start Date: Choose the start date for your DCA strategy (default: 2024-01-01).
End Date: Choose the end date (default: 2025-04-27). Must be after the start date and within available chart data.
Daily Investment ($): Set the daily investment amount (default: $100). Minimum is $0.01.
Notes
Timeframe: The indicator requires a Daily (1D) chart. Other timeframes will trigger an error.
Data: Ensure your BTCUSD chart has historical data for the selected date range. Use reliable pairs like Coinbase:BTCUSD or Binance:BTCUSDT.
Limitations: Does not account for trading fees or slippage. Future dates (beyond the current date) will not display results.
Performance: Works best with historical data. Free TradingView accounts may have limited historical data; consider premium for longer ranges.
Uptrick: Z-Score FlowOverview
Uptrick: Z-Score Flow is a technical indicator that integrates trend-sensitive momentum analysi s with mean-reversion logic derived from Z-Score calculations. Its primary objective is to identify market conditions where price has either stretched too far from its mean (overbought or oversold) or sits at a statistically “normal” range, and then cross-reference this observation with trend direction and RSI-based momentum signals. The result is a more contextual approach to trade entry and exit, emphasizing precision, clarity, and adaptability across varying market regimes.
Introduction
Financial instruments frequently transition between trending modes, where price extends strongly in one direction, and ranging modes, where price oscillates around a central value. A simple statistical measure like Z-Score can highlight price extremes by comparing the current price against its historical mean and standard deviation. However, such extremes alone can be misleading if the broader market structure is trending forcefully. Uptrick: Z-Score Flow aims to solve this gap by combining Z-Score with an exponential moving average (EMA) trend filter and a smoothed RSI momentum check, thus filtering out signals that contradict the prevailing market environment.
Purpose
The purpose of this script is to help traders pinpoint both mean-reversion opportunities and trend-based pullbacks in a way that is statistically grounded yet still mindful of overarching price action. By pairing Z-Score thresholds with supportive conditions, the script reduces the likelihood of acting on random price spikes or dips and instead focuses on movements that are significant within both historical and current contextual frameworks.
Originality and Uniquness
Layered Signal Verification: Signals require the fulfillment of multiple layers (Z-Score extreme, EMA trend bias, and RSI momentum posture) rather than merely breaching a statistical threshold.
RSI Zone Lockout: Once RSI enters an overbought/oversold zone and triggers a signal, the script locks out subsequent signals until RSI recovers above or below those zones, limiting back-to-back triggers.
Controlled Cooldown: A dedicated cooldown mechanic ensures that the script waits a specified number of bars before issuing a new signal in the opposite direction.
Gradient-Based Visualization: Distinct gradient fills between price and the Z-Mean line enhance readability, showing at a glance whether price is trading above or below its statistical average.
Comprehensive Metrics Panel: An optional on-chart table summarizes the Z-Score’s key metrics, streamlining the process of verifying current statistical extremes, mean levels, and momentum directions.
Why these indicators were merged
Z-Score measurements excel at identifying when price deviates from its mean, but they do not intrinsically reveal whether the market’s trajectory supports a reversion or if price might continue along its trend. The EMA, commonly used for spotting trend directions, offers valuable insight into whether price is predominantly ascending or descending. However, relying solely on a trend filter overlooks the intensity of price moves. RSI then adds a dedicated measure of momentum, helping confirm if the market’s energy aligns with a potential reversal (for example, price is statistically low but RSI suggests looming upward momentum). By uniting these three lenses—Z-Score for statistical context, EMA for trend direction, and RSI for momentum force—the script offers a more comprehensive and adaptable system, aiming to avoid false positives caused by focusing on just one aspect of price behavior.
Calculations
The core calculation begins with a simple moving average (SMA) of price over zLen bars, referred to as the basis. Next, the script computes the standard deviation of price over the same window. Dividing the difference between the current price and the basis by this standard deviation produces the Z-Score, indicating how many standard deviations the price is from its mean. A positive Z-Score reveals price is above its average; a negative reading indicates the opposite.
To detect overall market direction, the script calculates an exponential moving average (emaTrend) over emaTrendLen bars. If price is above this EMA, the script deems the market bullish; if below, it’s considered bearish. For momentum confirmation, the script computes a standard RSI over rsiLen bars, then applies a smoothing EMA over rsiEmaLen bars. This smoothed RSI (rsiEma) is monitored for both its absolute level (oversold or overbought) and its slope (the difference between the current and previous value). Finally, slopeIndex determines how many bars back the script compares the basis to check whether the Z-Mean line is generally rising, falling, or flat, which then informs the coloring scheme on the chart.
Calculations and Rational
Simple Moving Average for Baseline: An SMA is used for the core mean because it places equal weight on each bar in the lookback period. This helps maintain a straightforward interpretation of overbought or oversold conditions in the context of a uniform historical average.
Standard Deviation for Volatility: Standard deviation measures the variability of the data around the mean. By dividing price’s difference from the mean by this value, the Z-Score can highlight whether price is unusually stretched given typical volatility.
Exponential Moving Average for Trend: Unlike an SMA, an EMA places more emphasis on recent data, reacting quicker to new price developments. This quicker response helps the script promptly identify trend shifts, which can be crucial for filtering out signals that go against a strong directional move.
RSI for Momentum Confirmation: RSI is an oscillator that gauges price movement strength by comparing average gains to average losses over a set period. By further smoothing this RSI with another EMA, short-lived oscillations become less influential, making signals more robust.
SlopeIndex for Slope-Based Coloring: To clarify whether the market’s central tendency is rising or falling, the script compares the basis now to its level slopeIndex bars ago. A higher current reading indicates an upward slope; a lower reading, a downward slope; and similar readings, a flat slope. This is visually represented on the chart, providing an immediate sense of the directionality.
Inputs
zLen (Z-Score Period)
Specifies how many bars to include for computing the SMA and standard deviation that form the basis of the Z-Score calculation. Larger values produce smoother but slower signals; smaller values catch quick changes but may generate noise.
emaTrendLen (EMA Trend Filter)
Sets the length of the EMA used to detect the market’s primary direction. This is pivotal for distinguishing whether signals should be considered (price aligning with an uptrend or downtrend) or filtered out.
rsiLen (RSI Length)
Defines the window for the initial RSI calculation. This RSI, when combined with the subsequent smoothing EMA, forms the foundation for momentum-based signal confirmations.
rsiEmaLen (EMA of RSI Period)
Applies an exponential moving average over the RSI readings for additional smoothing. This step helps mitigate rapid RSI fluctuations that might otherwise produce whipsaw signals.
zBuyLevel (Z-Score Buy Threshold)
Determines how negative the Z-Score must be for the script to consider a potential oversold signal. If the Z-Score dives below this threshold (and other criteria are met), a buy signal is generated.
zSellLevel (Z-Score Sell Threshold)
Determines how positive the Z-Score must be for a potential overbought signal. If the Z-Score surpasses this threshold (and other checks are satisfied), a sell signal is generated.
cooldownBars (Cooldown (Bars))
Enforces a bar-based delay between opposite signals. Once a buy signal has fired, the script must wait the specified number of bars before registering a new sell signal, and vice versa.
slopeIndex (Slope Sensitivity (Bars))
Specifies how many bars back the script compares the current basis for slope coloration. A bigger slopeIndex highlights larger directional trends, while a smaller number emphasizes shorter-term shifts.
showMeanLine (Show Z-Score Mean Line)
Enables or disables the plotting of the Z-Mean and its slope-based coloring. Traders who prefer minimal chart clutter may turn this off while still retaining signals.
Features
Statistical Core (Z-Score Detection):
This feature computes the Z-Score by taking the difference between the current price and the basis (SMA) and dividing by the standard deviation. In effect, it translates price fluctuations into a standardized measure that reveals how significant a move is relative to the typical variation seen over the lookback. When the Z-Score crosses predefined thresholds (zBuyLevel for oversold and zSellLevel for overbought), it signals that price could be at an extreme.
How It Works: On each bar, the script updates the SMA and standard deviation. The Z-Score is then refreshed accordingly. Traders can interpret particularly large negative or positive Z-Score values as scenarios where price is abnormally low or high.
EMA Trend Filter:
An EMA over emaTrendLen bars is used to classify the market as bullish if the price is above it and bearish if the price is below it. This classification is applied to the Z-Score signals, accepting them only when they align with the broader price direction.
How It Works: If the script detects a Z-Score below zBuyLevel, it further checks if price is actually in a downtrend (below EMA) before issuing a buy signal. This might seem counterintuitive, but a “downtrend” environment plus an oversold reading often signals a potential bounce or a mean-reversion play. Conversely, for sell signals, the script checks if the market is in an uptrend first. If it is, an overbought reading aligns with potential profit-taking.
RSI Momentum Confirmation with Oversold/Overbought Lockout:
RSI is calculated over rsiLen, then smoothed by an EMA over rsiEmaLen. If this smoothed RSI dips below a certain threshold (for example, 30) and then begins to slope upward, the indicator treats it as a potential sign of recovering momentum. Similarly, if RSI climbs above a certain threshold (for instance, 70) and starts to slope downward, that suggests dwindling momentum. Additionally, once RSI is in these zones, the indicator locks out repetitive signals until RSI fully exits and re-enters those extreme territories.
How It Works: Each bar, the script measures whether RSI has dropped below the oversold threshold (like 30) and has a positive slope. If it does, the buy side is considered “unlocked.” For sell signals, RSI must exceed an overbought threshold (70) and slope downward. The combination of threshold and slope helps confirm that a reversal is genuinely in progress instead of issuing signals while momentum remains weak or stuck in extremes.
Cooldown Mechanism:
The script features a custom bar-based cooldown that prevents issuing new signals in the opposite direction immediately after one is triggered. This helps avoid whipsaw situations where the market quickly flips from oversold to overbought or vice versa.
How It Works: When a buy signal fires, the indicator notes the bar index. If the Z-Score and RSI conditions later suggest a sell, the script compares the current bar index to the last buy signal’s bar index. If the difference is within cooldownBars, the signal is disallowed. This ensures a predefined “quiet period” before switching signals.
Slope-Based Coloring (Z-Mean Line and Shadow):
The script compares the current basis value to its value slopeIndex bars ago. A higher reading now indicates a generally upward slope, while a lower reading indicates a downward slope. The script then shades the Z-Mean line in a corresponding bullish or bearish color, or remains neutral if little change is detected.
How It Works: This slope calculation is refreshingly straightforward: basis – basis . If the result is positive, the line is colored bullish; if negative, it is colored bearish; if approximately zero, it remains neutral. This provides a quick visual cue of the medium-term directional bias.
Gradient Overlays:
With gradient fills, the script highlights where price stands in relation to the Z-Mean. When price is above the basis, a purple-shaded region is painted, visually indicating a “bearish zone” for potential overbought conditions. When price is below, a teal-like overlay is used, suggesting a “bullish zone” for potential oversold conditions.
How It Works: Each bar, the script checks if price is above or below the basis. It then applies a fill between close and basis, using distinct colors to show whether the market is trading above or below its mean. This creates an immediate sense of how extended the market might be.
Buy and Sell Labels (with Alerts):
When a legitimate buy or sell condition passes every check (Z-Score threshold, EMA trend alignment, RSI gating, and cooldown clearance), the script plots a corresponding label directly on the chart. It also fires an alert (if alerts are set up), making it convenient for traders who want timely notifications.
How It Works: If rawBuy or rawSell conditions are met (refined by RSI, EMA trend, and cooldown constraints), the script calls the respective plot function to paint an arrow label on the chart. Alerts are triggered simultaneously, carrying easily recognizable messages.
Metrics Table:
The optional on-chart table (activated by showMetrics) presents real-time Z-Score data, including the current Z-Score, its rolling mean, the maximum and minimum Z-Score values observed over the last zLen bars, a percentile position, and a short-term directional note (rising, falling, or flat).
Current – The present Z-Score reading
Mean – Average Z-Score over the zLen period
Min/Max – Lowest and highest Z-Score values within zLen
Position – Where the current Z-Score sits between the min and max (as a percentile)
Trend – Whether the Z-Score is increasing, decreasing, or flat
Conclusion
Uptrick: Z-Score Flow offers a versatile solution for traders who need a statistically informed perspective on price extremes combined with practical checks for overall trend and momentum. By leveraging a well-defined combination of Z-Score, EMA trend classification, RSI-based momentum gating, slope-based visualization, and a cooldown mechanic, the script reduces the occurrence of false or premature signals. Its gradient fills and optional metrics table contribute further clarity, ensuring that users can quickly assess market posture and make more confident trading decisions in real time.
Disclaimer
This script is intended solely for informational and educational purposes. Trading in any financial market comes with substantial risk, and there is no guarantee of success or the avoidance of loss. Historical performance does not ensure future results. Always conduct thorough research and consider professional guidance prior to making any investment or trading decisions.
Gradient Trend Filter STRATEGY [ChartPrime/PineIndicators]This strategy is based on the Gradient Trend Filter indicator developed by ChartPrime. Full credit for the concept and indicator goes to ChartPrime.
The Gradient Trend Filter Strategy is designed to execute trades based on the trend analysis and filtering system provided by the Gradient Trend Filter indicator. It integrates a noise-filtered trend detection system with a color-gradient visualization, helping traders identify trend strength, momentum shifts, and potential reversals.
How the Gradient Trend Filter Strategy Works
1. Noise Filtering for Smoother Trends
To reduce false signals caused by market noise, the strategy applies a three-stage smoothing function to the source price. This function ensures that trend shifts are detected more accurately, minimizing unnecessary trade entries and exits.
The filter is based on an Exponential Moving Average (EMA)-style smoothing technique.
It processes price data in three successive passes, refining the trend signal before generating trade entries.
This filtering technique helps eliminate minor fluctuations and highlights the true underlying trend.
2. Multi-Layered Trend Bands & Color-Based Trend Visualization
The Gradient Trend Filter constructs multiple trend bands around the filtered trend line, acting as dynamic support and resistance zones.
The mid-line changes color based on the trend direction:
Green for uptrends
Red for downtrends
A gradient cloud is formed around the trend line, dynamically shifting colors to provide early warning signals of trend reversals.
The outer bands function as potential support and resistance, helping traders determine stop-loss and take-profit zones.
Visualization elements used in this strategy:
Trend Filter Line → Changes color between green (bullish) and red (bearish).
Trend Cloud → Dynamically adjusts color based on trend strength.
Orange Markers → Appear when a trend shift is confirmed.
Trade Entry & Exit Conditions
This strategy automatically enters trades based on confirmed trend shifts detected by the Gradient Trend Filter.
1. Trade Entry Rules
Long Entry:
A bullish trend shift is detected (trend direction changes to green).
The filtered trend value crosses above zero, confirming upward momentum.
The strategy enters a long position.
Short Entry:
A bearish trend shift is detected (trend direction changes to red).
The filtered trend value crosses below zero, confirming downward momentum.
The strategy enters a short position.
2. Trade Exit Rules
Closing a Long Position:
If a bearish trend shift occurs, the strategy closes the long position.
Closing a Short Position:
If a bullish trend shift occurs, the strategy closes the short position.
The trend shift markers (orange diamonds) act as a confirmation signal, reinforcing the validity of trade entries and exits.
Customization Options
This strategy allows traders to adjust key parameters for flexibility in different market conditions:
Trade Direction: Choose between Long Only, Short Only, or Long & Short .
Trend Length: Modify the length of the smoothing function to adapt to different timeframes.
Line Width & Colors: Customize the visual appearance of trend lines and cloud colors.
Performance Table: Enable or disable the equity performance table that tracks historical trade results.
Performance Tracking & Reporting
A built-in performance table is included to monitor monthly and yearly trading performance.
The table calculates monthly percentage returns, displaying them in a structured format.
Color-coded values highlight profitable months (blue) and losing months (red).
Tracks yearly cumulative performance to assess long-term strategy effectiveness.
Traders can use this feature to evaluate historical performance trends and optimize their strategy settings accordingly.
How to Use This Strategy
Identify Trend Strength & Reversals:
Use the trend line and cloud color changes to assess trend strength and detect potential reversals.
Monitor Momentum Shifts:
Pay attention to gradient cloud color shifts, as they often appear before the trend line changes color.
This can indicate early momentum weakening or strengthening.
Act on Trend Shift Markers:
Use orange diamonds as confirmation signals for trend shifts and trade entry/exit points.
Utilize Cloud Bands as Support/Resistance:
The outer bands of the cloud serve as dynamic support and resistance, helping with stop-loss and take-profit placement.
Considerations & Limitations
Trend Lag: Since the strategy applies a smoothing function, entries may be slightly delayed compared to raw price action.
Volatile Market Conditions: In high-volatility markets, trend shifts may occur more frequently, leading to higher trade frequency.
Optimized for Trend Trading: This strategy is best suited for trending markets and may produce false signals in sideways (ranging) conditions.
Conclusion
The Gradient Trend Filter Strategy is a trend-following system based on the Gradient Trend Filter indicator by ChartPrime. It integrates noise filtering, trend visualization, and gradient-based color shifts to help traders identify strong market trends and potential reversals.
By combining trend filtering with a multi-layered cloud system, the strategy provides clear trade signals while minimizing noise. Traders can use this strategy for long-term trend trading, momentum shifts, and support/resistance-based decision-making.
This strategy is a fully automated system that allows traders to execute long, short, or both directions, with customizable settings to adapt to different market conditions.
Credit for the original concept and indicator goes to ChartPrime.
Quarterly Theory ICT 01 [TradingFinder] XAMD + Q1-Q4 Sessions🔵 Introduction
The Quarterly Theory ICT indicator is an advanced analytical system based on the concepts of ICT (Inner Circle Trader) and fractal time. It divides time into quarterly periods and accurately determines entry and exit points for trades by using the True Open as the starting point of each cycle. This system is applicable across various time frames including annual, monthly, weekly, daily, and even 90-minute sessions.
Time is divided into four quarters: in the first quarter (Q1), which is dedicated to the Accumulation phase, the market is in a consolidation state, laying the groundwork for a new trend; in the second quarter (Q2), allocated to the Manipulation phase (also known as Judas Swing), sudden price changes and false moves occur, marking the true starting point of a trend change; the third quarter (Q3) is dedicated to the Distribution phase, during which prices are broadly distributed and price volatility peaks; and the fourth quarter (Q4), corresponding to the Continuation/Reversal phase, either continues or reverses the previous trend.
By leveraging smart algorithms and technical analysis, this system identifies optimal price patterns and trading positions through the precise detection of stop-run and liquidity zones.
With the division of time into Q1 through Q4 and by incorporating key terms such as Quarterly Theory ICT, True Open, Accumulation, Manipulation (Judas Swing), Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, this system enables traders to identify market trends and make informed trading decisions using real data and precise analysis.
♦ Important Note :
This indicator and the "Quarterly Theory ICT" concept have been developed based on material published in primary sources, notably the articles on Daye( traderdaye ) and Joshuuu . All copyright rights are reserved.
🔵 How to Use
The Quarterly Theory ICT strategy is built on dividing time into four distinct periods across various time frames such as annual, monthly, weekly, daily, and even 90-minute sessions. In this approach, time is segmented into four quarters, during which the phases of Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal appear in a systematic and recurring manner.
The first segment (Q1) functions as the Accumulation phase, where the market consolidates and lays the foundation for future movement; the second segment (Q2) represents the Manipulation phase, during which prices experience sudden initial changes, and with the aid of the True Open concept, the real starting point of the market’s movement is determined; in the third segment (Q3), the Distribution phase takes place, where prices are widely dispersed and price volatility reaches its peak; and finally, the fourth segment (Q4) is recognized as the Continuation/Reversal phase, in which the previous trend either continues or reverses.
This strategy, by harnessing the concepts of fractal time and smart algorithms, enables precise analysis of price patterns across multiple time frames and, through the identification of key points such as stop-run and liquidity zones, assists traders in optimizing their trading positions. Utilizing real market data and dividing time into Q1 through Q4 allows for a comprehensive and multi-level technical analysis in which optimal entry and exit points are identified by comparing prices to the True Open.
Thus, by focusing on keywords like Quarterly Theory ICT, True Open, Accumulation, Manipulation, Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, the Quarterly Theory ICT strategy acts as a coherent framework for predicting market trends and developing trading strategies.
🔵b]Settings
Cycle Display Mode: Determines whether the cycle is displayed on the chart or on the indicator panel.
Show Cycle: Enables or disables the display of the ranges corresponding to each quarter within the micro cycles (e.g., Q1/1, Q1/2, Q1/3, Q1/4, etc.).
Show Cycle Label: Toggles the display of textual labels for identifying the micro cycle phases (for example, Q1/1 or Q2/2).
Table Display Mode: Enables or disables the ability to display cycle information in a tabular format.
Show Table: Determines whether the table—which summarizes the phases (Q1 to Q4)—is displayed.
Show More Info: Adds additional details to the table, such as the name of the phase (Accumulation, Manipulation, Distribution, or Continuation/Reversal) or further specifics about each cycle.
🔵 Conclusion
Quarterly Theory ICT provides a fractal and recurring approach to analyzing price behavior by dividing time into four quarters (Q1, Q2, Q3, and Q4) and defining the True Open at the beginning of the second phase.
The Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal phases repeat in each cycle, allowing traders to identify price patterns with greater precision across annual, monthly, weekly, daily, and even micro-level time frames.
Focusing on the True Open as the primary reference point enables faster recognition of potential trend changes and facilitates optimal management of trading positions. In summary, this strategy, based on ICT principles and fractal time concepts, offers a powerful framework for predicting future market movements, identifying optimal entry and exit points, and managing risk in various trading conditions.
