FS Scorpion TailKey Features & Components:
1. Custom Date & Chart-Based Controls
The software allows users to define whether they want signals to start on a specific date (useSpecificDate) or base calculations on the visible chart’s range (useRelativeScreenSumLeft and useRelativeScreenSumRight).
Users can input the number of stocks to buy/sell per signal and decide whether to sell only for profit.
2. Technical Indicators Used
EMA (Exponential Moving Average): Users can define the length of the EMA and specify if buy/sell signals should occur when the EMA is rising or falling.
MACD (Moving Average Convergence Divergence): MACD crossovers, slopes of the MACD line, signal line, and histogram are used for generating buy/sell signals.
ATR (Average True Range): Signals are generated based on rising or falling ATR.
Aroon Indicator: Buy and sell signals are based on the behavior of the Aroon upper and lower lines.
RSI (Relative Strength Index): Tracks whether the RSI and its moving average are rising or falling to generate signals.
Bollinger Bands: Buy/sell signals depend on the basis, upper, and lower band behavior (rising or falling).
3. Signal Detection
The software creates arrays for each indicator to store conditions for buy/sell signals.
The allTrue() function checks whether all conditions for buy/sell signals are true, ensuring that only valid signals are plotted.
Signals are differentiated between buy-only, sell-only, and both buy and sell (dual signal).
4. Visual Indicators
Vertical Lines: When buy, sell, or dual signals are detected, vertical lines are drawn at the corresponding bar with configurable colors (green for buy, red for sell, silver for dual).
Buy/Sell Labels: Visual labels are plotted directly on the chart to denote buy or sell signals, allowing for clear interpretation of the strategy.
5. Cash Flow & Metrics Display
The software maintains an internal ledger of how many stocks are bought/sold, their prices, and whether a profit is being made.
A table is displayed at the bottom right of the chart, showing:
Initial investment
Current stocks owned
Last buy price
Market stake
Net profit
The table background turns green for profit and red for loss.
6. Dynamic Decision Making
Buy Condition: If a valid buy signal is generated, the software decrements the cash balance and adds stocks to the inventory.
Sell Condition: If the sell signal is valid (and meets the profit requirement), stocks are sold, and cash is incremented.
A fallback check ensures the sell logic prevents selling more stocks than are available and adjusts stock holding appropriately (e.g., sell half).
Customization and Usage
Indicator Adjustments: The user can choose which indicators to activate (e.g., EMA, MACD, RSI) via input controls. Each indicator has specific customizable parameters such as lengths, slopes, and conditions.
Signal Flexibility: The user can adjust conditions for buying and selling based on various technical indicators, which adds flexibility in implementing trading strategies. For example, users may require the RSI to be higher than its moving average or trigger sales only when MACD crosses under the signal line.
Profit Sensitivity: The software allows the option to sell only when a profit is assured by checking if the current price is higher than the last buy price.
Summary of Usage:
Indicator Selection: Enable or disable technical indicators like EMA, MACD, RSI, Aroon, ATR, and Bollinger Bands to fit your trading strategy.
Custom Date/Chart Settings: Choose whether to calculate based on specific time ranges or visible portions of the chart.
Dynamic Signal Plotting: Once buy or sell conditions are met, the software will visually plot signals on your chart, giving clear entry and exit points.
Investment Tracking: Real-time tracking of stock quantities, investments, and profit ensures a clear view of your trading performance.
Backtesting: Use this software for backtesting your strategy by analyzing how buy and sell signals would have performed historically based on the chosen indicators.
Conclusion
The FS Scorpion Tail software is a robust and flexible trading tool, allowing traders to develop custom strategies based on multiple well-known technical indicators. Its visual aid, coupled with real-time investment tracking, makes it valuable for systematic traders looking to automate or refine their trading approach.
Chart patterns
Momentum Entry & Trend Strategy M5Momentum Entry & Trend Strategy M5
Description:
The Momentum Entry & Trend Strategy M5 is an indicator script designed to assist traders in determining optimal buy and sell moments based on momentum and trend analysis. This script operates using two different momentum levels—Momentum Length for Entry (5) and Momentum Length for Trend (10)—along with the HMA (Hull Moving Average) indicator for trend confirmation.
Key Features:
Momentum Entry: Calculates momentum using the difference between the current price and the price from previous periods to determine the strength and direction of price movements.
Trend Identification: Utilizes two momentum levels (5 and 10) to identify bullish and bearish trend conditions.
HMA for Trend Confirmation: The HMA indicator is used to provide trend confirmation signals. When HMA indicates bullish, a buy signal is displayed; conversely, a bearish HMA results in a sell signal.
Signal Display: Displays buy (BUY) and sell (SELL) signals on the chart when the conditions for market entry are met, providing clear visualization for traders.
Background Color: Offers a green background for uptrends and a red background for downtrends, allowing traders to easily identify the overall market condition.
ATR (Average True Range): Calculates and plots a smoothed ATR to help traders measure market volatility.
Settings:
Momentum Length for Entry: 5 (to determine entry signals)
Momentum Length for Trend: 10 (to determine trend conditions)
HMA Length: 300 (period length for HMA to confirm trends)
ATR Length: 14 (period length for ATR to measure volatility)
Benefits:
This script is designed to provide visual and data-driven guidance for better trading decision-making. By combining momentum and trend analysis, traders can enhance the accuracy of their signals and reduce the risk of errors when identifying entry and exit points in the market.
Note:
This script is intended for use on the M5 time frame but can be adjusted for other time frames as needed. It is always recommended to conduct thorough testing before applying trading strategies on a live account.
Weekly High/Low Day BreakdownThe "Weekly High/Low Day Breakdown" is a tool designed to help identify patterns in market behaviour by analysing the days of the week when weekly highs and lows occur. This indicator calculates the frequency and percentage of weekly highs and lows for each day from Monday to Sunday within the visible range of your chart.
Features:
Weekly Analysis: Calculates weekly highs and lows based on daily open high and low prices from Monday to Sunday.
Day-Specific Breakdown: Tracks which day of the week each weekly high and low occurred.
Visible Range Focus: Only considers data within the current visible range of your chart for precise analysis.
Interactive Table Display: Presents the results in an easy-to-read table directly on your chart.
How It Works:
Data Collection: Fetches daily high, low, day of the week, and time data regardless of your chart's timeframe. Uses these daily figures to determine the weekly high and low for each week.
Weekly Tracking: Monitors the day of the week when the weekly high and low prices occur. Resets tracking at the end of each week (Sunday).
Visible Range Analysis: Only includes weeks that fall entirely within the visible time range of your chart. Ensures that the analysis is relevant to the period you are focusing on.
Percentage Calculation: Counts the occurrences of weekly highs and lows for each day. Calculates the percentage based on the total number of weeks in the visible range.
Result Display: Generates a table with days of the week as columns and "Weekly High" and "Weekly Low" as rows. Displays the percentage values, indicating how often highs and lows occur on each day.
How to Use:
Add the Indicator: Apply the "Weekly High/Low Day Breakdown" indicator to your TradingView chart.
Adjust Visible Range: Zoom in or out to set the desired visible time range for your analysis.
Interpret the Table:
Columns: Represent days from Monday to Sunday.
"Weekly High" Row: Shows the percentage of times the weekly high occurred on each day. "Weekly Low" Row: Shows the percentage of times the weekly low occurred on each day.
Colors: Blue text indicates high percentages, red text indicates low percentages.
Example Interpretation:
If the table shows a 30% value under "Tuesday" for "Weekly High," it means that in 30% of the weeks within the visible range, the highest price of the week occurred on a Tuesday.
Similarly, a 40% value under "Friday" for "Weekly Low" indicates that 40% of the weekly lows happened on a Friday.
The Ultimate Indicator by ATK
The Ultimate Indicator By ATK
This all-in-one trading indicator integrates multiple advanced tools to provide ICT traders with deep insights into market structure, liquidity zones, Fair Value Gaps (FVG), and AI-powered signals. Whether you’re a scalper or a long-term trader, this indicator offers real-time analysis and helps identify potential trading opportunities in dynamic markets.
🔵 Key Features
🔹 2 options for checking SMT (Separation and Divergence) Detection:
First - Compares highs and lows of a primary symbol (e.g., NQ1!) with a user-defined comparison symbol (e.g., ES1!).
Automatically detects and visualizes discrepancies (red for highs, blue for lows) between the symbols.
Offers customizable comparison settings and alerts for divergence detection.
Second -
Real-time SMT comparison between two tickers - red/green lines.
🔹 Market Structure Change (MSS) & Break of Structure (BOS) Detection:
Identifies market structure shifts and breakouts, crucial for spotting potential reversals.
Customizable sensitivity and length settings to adapt to various market conditions and trading strategies. Use 3 different timeframes on the same chart.
🔹 Buy Side & Sell Side Liquidity Zones:
Highlights liquidity zones on both buy and sell sides, offering a clear view of market pressure points.
Configurable settings for detection length, margin, and alert conditions for liquidity sweeps like the 15-minute Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL).
These lines from Swing Highs & Lows:
Automatically plots horizontal lines at the most recent swing highs and lows.
Lines are removed once the closing price breaches these levels, ensuring real-time updates and clean charting.
🔹 Fair Value Gap (FVG) Detection:
Detects FVG formations on 5-minute and 1-minute charts, making it ideal for scalpers capturing liquidity gaps.
Includes directional arrows and customizable alerts based on higher and lower timeframe FVG analysis, helping traders time their entry and exit points.
🔹IFVG (Inverse fair value gap) - yellow
🔹IFVG + SMT - Light blue
🔹IFVG + SMT + HTF FVG - green/red (1 min only)
🔹IFVG + SMT + BSL/SSL Swept - green/red (1 min only)
for example:
🔹 Capture and plot significant price levels at specific times throughout the trading day:
TDO (True Day Open): The price at which a market opens at 12:00 AM US.
TMSO (True Micro Session Open): The open price of the Q2 of the micro session.
RVT (Revolving True Open): The price recorded at 12:00 PM US.
AO (Asia True Open Price): The price captured at 7:30 PM US, specifically representing the opening price of the Asian session.
LO (London True Open Price): 1:30 AM US
AM (New York Session - Afternoon Market True Open Price): 7:30 AM US
PM (Post Market Open Price): 1:30 PM US.
For example TMSO:
🔹 AI-Powered Entry Detection:
The script helps identify entry points based on specific candle patterns, while also considering the exponential moving averages (EMAs) for trend confirmation.
🔶FFMS Strategy: (First Five Minute Strategy)
Check 5-min time frame if the price is between the high and low of the previous day. then, when NYO if there is retest on the High/Low on the 5-min chart after crossover or crossunder the 5 minute first candle high/low lines.
🔶PSP & PSP + FVG
🔹The Precision Swing Point (PSP). It helps you visually identify price decorrelation (type of SMT) among key futures contracts (NQ/ES or NQ/ES/YM/ZB) and set alerts for these significant market movements.
🔹The PSP HTF 15 Min + FVG LTF 1 Min
In this strategy the script is looking for PSP in HTF (15-Min) and capture the FVG in LTF (1-Min) only if its between High and Low of the PSP.
If there is a retracement in parallel micro session time, for example: Q1 with Q3 or Q2 with Q4, Q3 with Q1, etc…
if the retracement was happened and the price close above/below the high/low of the FVG from the LTF that captured according to the direction for long/short, it plots an arrow.
Update the script that checks the purple arrows and shows all of them each time there is a new PSP in a 15-minute timeframe and then FVG in 1 Min timeframe with the reference to the TDO/TMSO/Open session
for example:
Step 1: PSP 15Min LOW/HIGH Lines look for FVG by the conditions above - purple arrow
Step 2:FVG founded - purple arrow
SMT Fill on 15 min timeframe + IFVG 1 min - Detected option:
When Sym1 closed above/below FVG and Sym2 didn't it is SMT FILL (15 Min timeframe)
White arrows when captured SMT FIll + IFVG:
option to turn on alert on this strategy too.
🔹Detect liquidity swept on 15-min timeframe by $$ - green/red
🔹Detect liquidity to sweep zones on by diamonds - green/red
🔹Alerts for all Events and full scenarios.
Real-time notifications ensure traders can act quickly on potential trade setups.
🔵 Conclusion:
This Ultimate Indicator by ATK brings together critical elements of market analysis in one tool for ICT traders, offering real-time insights, alerts, and visual aids to enhance trading strategies. Whether you’re focused on short-term price action or long-term market trends, this indicator provides the tools necessary for informed decision-making and improved trading performance.
ARMORE Capital: Support–Resistance Levels v2.0 [Enhanced]Enhanced S/R Levels with Signals
The "Enhanced S R Levels with Signals" indicator is designed to help traders and investors identify key Support and Resistance levels on a price chart. It also includes LONG and SHORT signals to help you see potential buy and sell opportunities. Here's a beginner-friendly breakdown of how it works and how to use it:
How it Works
Support and Resistance Levels:
Support Levels (blue lines) are prices where the stock tends to find a "floor" or buying interest, potentially pushing the price up. These levels are calculated based on the lowest prices over a period, with the sensitivity setting helping adjust the distance between each support level.
Resistance Levels (red lines) are prices where the stock often encounters a "ceiling" or selling interest, which could push the price down. These levels are calculated based on the highest prices over a period, with sensitivity adjusting the distance between each resistance level.
The indicator plots up to five support and five resistance lines, giving you a layered view of price levels where the market may react.
LONG and SHORT Signals:
LONG Signal (green arrow pointing up): When the closing price goes above the closest support level, the indicator shows a LONG signal below the bar, suggesting a potential upward trend.
SHORT Signal (red arrow pointing down): When the closing price goes below the closest resistance level, the indicator shows a SHORT signal above the bar, indicating a potential downward trend.
Background Ribbons:
When a LONG condition is met, a faint green background appears on the chart as a visual cue.
When a SHORT condition is met, a faint red background appears to signal potential bearish pressure.
How to Use It
1. Finding Entry and Exit Points: Use the LONG and SHORT signals as a guide, but remember to consider other factors before making trading decisions. A LONG signal suggests that price may rise, while a SHORT signal indicates potential downside.
2. Support & Resistance Levels: Treat these levels as potential points of interest. Prices often react at support or resistance, so you can look for confirmation (e.g., reversal patterns, volume spikes) around these levels.
3. Experiment with Sensitivity: Adjust the "Sensitivity" setting to see how it changes the spacing of support and resistance levels. Higher sensitivity may show more frequent support/resistance levels, which can be helpful for short-term traders.
DISCLAIMER : This is purely experimental and shouldn't be considered a blatant Buy-Sell Indicator. Please feel free to use it to supplement your research, share it with your friends, iterate and improve upon it, and use it to build better, more powerful tools!
Remember, always combine technical indicators with other analysis methods and manage your risk responsibly. Happy Trading!
CRT AMD indicatorThis indicator is based on the Power of three (Accumulation Manipulation Distribution) Cycle, by marking the candle that Sweep the low or high of the previous candle and then closed back inside the range of the previous candle, indicating a possibility of a Manipulation or Reversal.
Combining the indicator with HTF Array and LTF Setup Entry will significantly improve the accuracy.
Exhaustion Candle Indicator (ECI)The Exhaustion Candle Indicator (ECI) is designed to help traders identify significant exhaustion points in price action. These points can indicate potential areas of interest where price may experience a change in momentum, providing insights into both continuation and reversal setups.
Key Features:
Exhaustion Candles: ECI identifies key exhaustion points by analyzing bullish and bearish candle patterns, helping traders spot potential support and resistance areas or moments of market pause.
Customizable Alerts: Built-in alert functionality allows traders to receive notifications when an exhaustion candle forms, providing timely updates for monitoring price action.
Time-Based Filtering: The indicator analyzes price action during peak trading hours (6 AM to 11 AM New York Time), reducing noise and focusing on more impactful market moves.
How It Works:
Bullish Exhaustion: Detects potential market hesitation or demand in a downtrend by spotting bearish-to-bullish candle patterns with long upper wicks.
Bearish Exhaustion: Identifies potential resistance or supply in an uptrend by spotting bullish-to-bearish candle patterns with long lower wicks.
Usage:
This indicator is ideal for traders seeking to understand points of potential market exhaustion, useful in both continuation and reversal setups. It can be used alongside other indicators and technical analysis methods to enhance trading strategies.
Market Structure Overlay🚀 Market Structure Overlay Indicator 🚀
🔍 Overview
The Market Structure Overlay (MSO) is a sophisticated technical analysis tool created to analyze price action and understand market structure in a more precise way. It identifies Break of Structure (BOS), Market Structure Breaks (MSBs), Equal Highs (EQH), and Equal Lows (EQL) with meticulous precision by utilizing both wicks and closing prices for better accuracy. The MSO is suitable for all trading timeframes, providing traders with the flexibility to observe and trade on any scale, from intraday to long-term trends.
⚙️ How It Works
The MSO uses advanced logic to detect critical price levels that highlight structural changes in the market. It calculates swing highs and lows using user-defined settings, allowing for customization in market structure analysis. The indicator further highlights BOS and MSB levels by leveraging supply and demand detection, offering a comprehensive understanding of trend reversals and continuation points.
✨ Key features include:
📈 Bullish and Bearish BOS/MSB Lines: MSO differentiates between bullish and bearish structural events, which helps traders understand the prevailing trend and identify key pivot points.
🎨 Customizable Appearance: Traders can personalize line styles and colors for BOS/MSB, trendlines and EQH/EQL, making the tool integrate seamlessly into any chart setup.
🔄 Swing Length and Demand Memory Settings: MSO allows users to specify the swing length for BOS lookback and how many historical zones should be stored on the chart, enhancing control over how much data is analyzed visually.
📊 Market Structure Elements Explained
Break of Structure (BOS): A BOS occurs when the price breaks through a previous Higher High (HH) or Lower Low (LL), indicating a continuation of the current trend. It helps confirm the prevailing market direction.
Market Structure Break (MSB): occurs when a Higher Low (HL) or Lower High (LH) is broken, signaling a potential shift in the market trend. This typically marks the beginning of a trend reversal.
Equal Highs (EQH) and Equal Lows (EQL): These levels are areas of liquidity where previous highs or lows are tested again by the market, often signifying areas of accumulation or distribution. EQH and EQL are crucial for recognizing potential liquidity traps.
Trendlines: Trendlines are used to connect successive highs or lows, providing a visual representation of the current direction of the market. They help traders understand trend momentum and potential breakouts.
🔥 Key Features and Benefits
✅ Accurate Market Structure Detection
The Market Structure Overlay identifies Break of Structure (BOS) and Market Structure Breaks (MSB) events that indicate potential trend changes or continuations. The indicator also distinguishes between bullish and bearish market structures using color-coded lines and custom labels, which helps in immediately identifying market dynamics.
📊 Supply and Demand Zones for BOS/MSB Detection
The MSO uses Supply and Demand Zones as part of the detection logic for BOS and MSB. Although these zones are not directly plotted, they play a key role in determining when a significant structural break occurs. This unique approach enhances the accuracy of BOS and MSB identification, as it takes into account areas of accumulation or distribution that often serve as precursors to trend shifts.
🔍 Equal Highs and Lows Detection
The MSO features Equal Highs (EQH) and Equal Lows (EQL) detection, which is a significant indicator for liquidity zones where potential orders might be resting. These areas often trigger key price actions as they get tested or broken.
⚙️ Customizable Settings
Users can customize the indicator’s behavior, including choosing whether to use candle wicks or closing prices, setting swing lengths for identifying key levels, and specifying memory for storing past zones. This flexibility allows traders to adjust the indicator to suit their personal trading strategy and preferences.
⏱️ Multi-Timeframe Highs and Lows
The indicator includes multi-timeframe support for significant highs and lows (daily, weekly, monthly, yearly). This helps traders understand where they are in the larger market context, especially when making decisions during intra-session trading.
🔎 Precise Detection Approach
Unlike traditional market structure indicators that rely heavily on simple pivot points, the MSO employs a more advanced and precise detection mechanism for BOS and MSB. Traditional pivot points typically use a lookback function to identify highs and lows over a fixed period, which can lead to false signals due to market noise or temporary price fluctuations. In contrast, the MSO records and checks swing and interim points against stored memory, only signaling structural breaks after a thorough evaluation. This results in a non-repainting and highly accurate depiction of market structure, minimizing false alerts and providing traders with reliable insights based on price action that remains consistent once confirmed.
🎨 Visualization Options
The MSO uses color-coded BOS and MSB lines to easily differentiate between bullish and bearish scenarios. Users also have options to visualize equal highs/lows (EQH/EQL) to recognize potential liquidity points. A detailed breakdown of Supply and Demand Zones helps traders identify high-probability areas for entries and exits. Additionally, the indicator allows traders to toggle visibility of key elements, including trend lines, labels, and multi-timeframe levels.
📝 Summary
The Market Structure Overlay is an essential tool for understanding price behavior and structural shifts in any financial market. Its use of sophisticated logic to detect structural breaks, coupled with customizable visualizations, allows traders to gain a nuanced view of market dynamics. The supply and demand zones, together with the BOS, MSB, EQH, and EQL labels, provide a strong foundation for both trend-following and reversal trading strategies.
MSO is not just a tool for understanding market direction—it's designed to enhance decision-making by delivering reliable and actionable insights into market structure. This indicator provides a seamless blend of market theory with advanced technical features, making it a valuable asset for serious traders.
📊 Key Visual Examples:
📈 Bullish and Bearish BOS/MSB Lines
📸
🌀 Trendlines
📸
⚠️ Note:
This indicator should be used as part of a broader trading strategy. Always confirm your entries and exits with additional tools and analysis methods. 💡
ICT Open Range Gap & 1st FVG (fadi)In his 2024 mentorship program, ICT detailed how price action interacts with Open Range Gaps and the initial 1-minute Fair Value Gap following the market open at 9:30 AM.
What is an Open Range Gap?
An Open Range Gap occurs when the market opens at 9:30 AM at a higher or lower level compared to the previous day's close at 4:14 PM, primarily relevant in futures trading. According to ICT, there is a statistical probability of 70% that the price action will close 50% or more of the Open Range Gap within the first 30 minutes of trading (9:30 AM to 10:00 AM).
What is the First 1-Minute Fair Value Gap?
ICT places significant emphasis on the first 1-minute Fair Value Gap (FVG) that forms after the market opens at 9:30 AM. The FVG must occur at 9:31 AM or later to be considered valid. This gap often presents key opportunities for traders, as it represents a temporary imbalance between supply and demand that the market seeks to correct.
Understanding and leveraging these patterns can enhance trading strategies by offering insights into potential price movements shortly after market open.
ICT Open Range Gap & 1st FVG
This indicator is engineered to identify and highlight the Open Range Gaps and the first 1-minute Fair Value Gap. Furthermore, it functions across multiple timeframes, from seconds to hours, catering to various trading preferences. This flexibility is particularly beneficial for traders who favor higher timeframes or wish to observe these patterns' application at broader intervals.
Settings
The Open Range Gap indicator offers flexible display settings. It identifies the quadrants and provides optional color coding to distinguish them. Additionally, it tracks the "fill" level to visualize how far the price action has progressed into the gap, enhancing traders' ability to monitor and analyze price movements effectively. By default, the Open Range Gap will stop extending at 10:00 AM; however, there is an option to continue extending until the end of the trading day.
The 1st Fair Value Gap (FVG) can be viewed on any timeframe the indicator is active on, offering various styling options to match each trader's preferences. While the 1st FVG is particularly relevant to the day it is created, previous 1st FVGs within the same week may provide additional value. This indicator allows traders to extend Monday's 1st FVG, marking the first FVG of the week, or to extend all 1st FVGs throughout the week.
ShuffleOverview
This TV script is designed to assist traders by visually marking key price levels and identifying potential trading opportunities on their charts. The script highlights the previous day's, week's, and month's highs and lows, as well as hourly fair value gaps. By providing clear visual indicators, traders can make more informed decisions based on significant price movements and gaps in the market.
Features
1. Previous Day Highs and Lows
Highs and Lows: Automatically plots the highest and lowest price points from the previous trading day.
Visual Indicators: Uses distinct colors and lines to differentiate between highs and lows for easy identification.
Alerts: Optional alerts when current price approaches these levels.
2. Weekly Highs and Lows
Weekly Range: Marks the highest and lowest prices of the current week.
Trend Analysis: Helps in identifying the overall trend direction based on weekly extremes.
Support and Resistance: Acts as dynamic support and resistance levels for potential trade setups.
3. Monthly Highs and Lows
Monthly Extremes: Highlights the highest and lowest prices recorded in the current month.
Long-Term Perspective: Provides insights into long-term market sentiment and potential major support/resistance zones.
Investment Decisions: Aids in making strategic investment decisions based on significant monthly price movements.
4. Hourly Fair Value Gaps
Fair Value Gaps (FVG): Identifies gaps between the high of one hour and the low of the next hour where no trading has occurred.
Price Retracement: Marks areas where price is likely to retrace to fill these gaps, offering potential entry points.
Gap Analysis: Assists in understanding market inefficiencies and potential price corrections.
Relative Measured Volatility (RMV) – Spot Tight Entry ZonesTitle: Relative Measured Volatility (RMV) – Spot Tight Entry Zones
Introduction
The Relative Measured Volatility (RMV) indicator is designed to highlight tight price consolidation zones , making it an ideal tool for traders seeking optimal entry points before potential breakouts. By focusing on tightness rather than general volatility, RMV offers traders a practical way to detect consolidation phases that often precede significant market moves.
How RMV Works
The RMV calculates short-term tightness by averaging three ATR (Average True Range) values over different lookback periods and then normalizing them within a specified lookback window. The result is a percentage-based scale from 0 to 100, indicating how tight the current price range is compared to recent history.
Here’s the breakdown:
Three ATR values are computed using user-defined short lookback periods to represent short-term price movements. An average of the ATRs provides a smoothed measure of current tightness. The RMV normalizes this average against the highest and lowest values over the defined lookback period, scaling it from 0 to 100.
This approach helps traders identify consolidation zones that are more likely to lead to breakouts.
Key Features of RMV
Multi-Period ATR Calculation : Uses three ATR values to effectively capture market tightness over the short term. Normalization : Converts the tightness measure to a 0-100 scale for easy interpretation. Dynamic Histogram and Background Colors : The RMV indicator uses a color-coded system for clarity.
How to Use the RMV Indicator
Identify Tight Consolidation Zones:
a - RMV values between 0-10 indicate very tight price ranges, making this the most optimal zone for potential entries before breakouts.
b - RMV values between 11-20 suggest moderate tightness, still favorable for entries.
Monitor Potential Breakout Areas:
As RMV moves from 21-30 , tightness reduces, signaling expanding volatility that may require wider stops or more flexible entry strategies.
Adjust Trading Strategies:
Use RMV values to identify tight zones for entering trades, especially in trending markets or at key support/resistance levels.
Customize the Indicator:
a - Adjust the short-term ATR lookback periods to control sensitivity.
b - Modify the lookback period to match your trading horizon, whether short-term or long-term.
Color-Coding Guide for RMV
ibb.co
How to Add RMV to Your Chart
Open your chart on TradingView.
Go to the “Indicators” section.
Search for "Relative Measured Volatility (RMV)" in the Community Scripts section.
Click on the indicator to add it to your chart.
Customize the input parameters to fit your trading strategy.
Input Parameters
Lookback Period : Defines the period over which tightness is measured and normalized.
Short-term ATR Lookbacks (1, 2, 3) : Control sensitivity to short-term tightness.
Histogram Threshold : Sets the threshold for differentiating between bright (tight) and dim (less tight) histogram colors.
Conclusion
The Relative Measured Volatility (RMV) is a versatile tool designed to help traders identify tight entry zones by focusing on market consolidation. By highlighting narrow price ranges, the RMV guides traders toward potential breakout setups while providing clear visual cues for better decision-making. Add RMV to your trading toolkit today and enhance your ability to identify optimal entry points!
Vishnu's Magics**Vishnu's Magics** is a powerful RSI (Relative Strength Index) indicator designed to enhance trading strategies through effective divergence detection and alerting features. This indicator provides the following key functionalities:
1. **RSI Calculation**: Calculates the RSI over a customizable length, allowing traders to identify overbought and oversold conditions.
2. **Customizable Bands**: Users can set multiple upper and lower bands to define different overbought and oversold levels, facilitating precise trading decisions.
3. **Divergence Detection**: The indicator identifies both bullish and bearish divergences by comparing price action with RSI movements. It highlights these divergences on the chart, helping traders anticipate potential reversals.
4. **Visual Alerts**: When divergences are detected, the indicator visually marks the points on the chart with labeled shapes ("Bull" for bullish divergence and "Bear" for bearish divergence) and changes the background color to indicate the condition.
5. **Alert System**: Users can set alerts for significant events, such as crossing specified bands or detecting divergences, ensuring timely notifications for trading opportunities.
6. **Custom Line Values**: Traders can edit the values for the divergence lines, providing flexibility to tailor the indicator according to their trading strategies.
Overall, **Vishnu's Magics** serves as an intuitive tool for traders looking to leverage RSI analysis and divergence strategies for informed trading decisions.
Quarterly Theory True Day Openings inspired by Daye
The point of this indicator is to catch the big moves that happen in the market.
This is based on Daye Quarterly theory. When applied to the chart you will see different color lines that represent different quarters in the Quarterly theory.
Red line will represent quarter 1 this quarter will be either a accumulation or a continuation from the previous quarter.
Green line will represent quarter 2 this is where the big moves in the market tend to happen. it will start printing the line on the chart where the user will have time to look for entry models to get in a trade. Q2 and Q3 are important levels that are near forms of liquidity such as fair value gaps and old highs and lows.
This app will draw the lines that represent the quarter which will give a visual que to the user of the app to look for fvgs ,old highs and lows. once found they will be able to use an entry model to enter a trade.
entry models could be liquidity sweep . wait for buy/side stops to be taken and enter on fair value gap.
wait for ifvg next to quarter level to be tested and entered.
App Usage:
Max Time Frame is 1 hour and can go down to the min chart
Previous quarters will be left on the chart as they tend to be revisited by price at a later date.
Year > Green line: Year True open
Month > Yellow line: Month true open
Weekly > True open
Q1 == Red line "consolidation/manipulation"
Q2 == Green line "Trade this" >
Q3 == blue Line "Trade this"
Q4 == grey or blue
`TRUE OPEN` = beggining of Q2.
Bullish - buy below `TRUE OPEN`.
Bearish - sell above `TRUE OPEN`.
True Year Open = first Monday of April.
True Month Open = second Monday of the Month.
True Week Open = every Monday at 6:00PM.
True Day Open = 12:00 Midnight.
True New York Session Open = 7:30.
MultiTimeframe Candles for Full Time Frame Continuity AnalysisIn honor of Rob Smith (R.I.P), the creator of TheStrat, I decided to try to figure out how to make an indicator that graphically shows you the price levels and movements on higher timeframes.
The goal is to have full timeframe continuity with TheStrat. Ideally when you are analyzing the lower time, you want it to be in continuity with the higher time frames.
How to Use It:
All you have to do is put on the indicator the number of times you desire.
So if you want the hourly, the daily, the weekly, and the monthly, then you have to just put on the indicator 4 times--once for each timeframe.
Then you go into each one you put on the chart and go to the drop down menu where you choose the timeframe you want displayed.
In the future, I'll do a video to show you exactly how that works, but I think you guys can figure it out.
Magic Base 1.0This indicator draws a box around the candles that were unable to close above or below the previous candles. With the ATR capability, the price range boundaries can be identified within the same timeframe. If the range exceeds the ATR, those price ranges are disregarded."
Ultimate Machine Learning MACD (Deep Learning Edition)This script is a "Deep Learning MACD" indicator that combines traditional MACD calculations with advanced machine learning techniques, including recursive feedback, adaptive learning rates, Monte Carlo simulations, and volatility-based adjustments. Here’s a breakdown of its key components:
Inputs
Lookback: The length of historical data (1000 by default) used for learning and volatility measurement.
Momentum and Volatility Weighting: Adjusts how much momentum and volatility contribute to the learning process (momentum weight: 1.2, volatility weight: 1.5).
MACD Lengths: Defines the range for MACD fast and slow lengths, starting at minimum of 1 and max of 1000.
Learning Rate: Defines how much the model learns from its predictions (very small learning rate by default).
Adaptive Learning: Enables dynamic learning rates based on market volatility.
Memory Factor: A feedback factor that determines how much weight past performance has in the current model.
Simulations: The number of Monte Carlo simulations used for probabilistic modeling.
Price Change: Calculated as the difference between the current and previous close.
Momentum: Measured using a lookback period (1000 bars by default).
Volatility: Standard deviation of closing prices.
ATR: Average true range over 14 periods for measuring market volatility.
Custom EMA Calculation
Implements an exponential moving average (EMA) formula from scratch using a recursive calculation with a smoothing factor.
Dynamic Learning Rate
Adjusts the learning rate based on market volatility. When volatility is high, the learning rate increases, and when volatility is low, it decreases. This makes the model more responsive during volatile markets and more stable during calm periods.
Error Calculation and Adjustment
Error Calculation: Measures the difference between the predicted value (via Monte Carlo simulations) and the true MACD value.
Adjust MACD Length: Uses the error to adjust the fast and slow MACD lengths dynamically, so the system can learn from market conditions.
Probabilistic Monte Carlo Simulation
Runs multiple simulations (200 by default) to generate probabilistic predictions. It uses random values weighted by momentum and volatility to simulate various market scenarios, enhancing
prediction accuracy.
MACD Calculation (Learning-Enhanced)
A custom MACD function that calculates:
Fast EMA and Slow EMA for MACD line.
Signal Line: An EMA of the MACD line.
Histogram: The difference between the MACD and signal lines.
Adaptive MACD Calculation
Adjusts the fast and slow MACD lengths based on the error from the Monte Carlo prediction.
Calculates the adaptive MACD, signal, and histogram using dynamically adjusted lengths.
Recursive Memory Feedback
Stores previous MACD values in an array (macdMemory) and averages them to create a feedback loop. This adds a "memory" to the system, allowing it to learn from past behaviors and refine future predictions.
Volatility-Based Reinforcement
Introduces a volatility reinforcement factor that influences the signal based on market conditions. It adds volatility awareness to the feedback system, making the system more reactive during high volatility periods.
Smoothed MACD
After all the adjustments, the MACD line is further smoothed based on the current market volatility, resulting in a final smoothed MACD.
Key Features
Monte Carlo Simulation: Runs multiple simulations to enhance predictions based on randomness and market behavior.
Adaptive Learning: Dynamic adjustments of learning rates and MACD lengths based on market conditions.
Recursive Feedback: Uses past data as feedback to refine the system’s predictions over time.
Volatility Awareness: Integrates market volatility into the system, making the MACD more responsive to market fluctuations.
This combination of traditional MACD with machine learning creates an adaptive indicator capable of learning from past behaviors and adjusting its sensitivity based on changing market conditions.
Ultimate Machine Learning RSI (Deep Learning Edition)This script represents an advanced implementation of a Machine Learning-based Relative Strength Index (RSI) indicator in Pine Script, incorporating several sophisticated techniques to create a more adaptive, intelligent, and responsive RSI.
Key Components and Features:
Lookback Period: The period over which the indicator "learns" from past data, set to 1000 bars by default.
Momentum and Volatility Weighting: These factors control how much the momentum and volatility of the market influence the learning and signal generation.
RSI Length Range: The minimum and maximum values for the RSI length, allowing the algorithm to adjust the RSI length dynamically.
Learning Rate: Controls how quickly the system adapts to new data. An adaptive learning rate can change based on market volatility.
Memory Factor: Influences how much the system "remembers" previous performance when making adjustments.
Monte Carlo Simulations: Used for probabilistic modeling to create a more robust signal.
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Price Change: Tracks the difference between the current close and the previous close.
Momentum: A measure of the rate of change in the price over the lookback period.
Volatility: Calculated using the standard deviation of the close prices.
ATR (Average True Range): Tracks the volatility of the market over a short period to influence decisions.
Monte Carlo Simulation:
Probabilistic Signal: This uses multiple random simulations (Monte Carlo) to generate potential future signals. These simulations are weighted by the momentum and volatility of the market. A cluster factor further enhances the simulation based on volatility regimes.
Z-Score for Extreme Conditions:
Z-Score: Measures how extreme current price movements are compared to the historical average, providing context for identifying overbought and oversold conditions.
Dynamic Learning Rate:
The learning rate adjusts based on the volatility of the market, becoming more responsive in high-volatility periods and slower in low-volatility markets. This prevents the system from overreacting to noise but ensures responsiveness to significant shifts.
Recursive Learning and Feedback:
Error Calculation: The system calculates the difference between the true RSI and the predicted RSI, creating an error that is fed back into the system to adjust the RSI length and other parameters dynamically.
RSI Length Adjustment: Based on the error, the RSI length is adjusted, ensuring that the system evolves over time to better reflect market conditions.
Adaptive Smoothing:
In periods of high volatility, the indicator applies a Triple Exponential Moving Average (TEMA) for faster adaptation, while in quieter markets, it uses an Exponential Moving Average (EMA) for smoother adjustments.
Recursive Memory Feedback:
The system maintains a memory of past RSI values, which helps refine the output further. The memory factor influences how much weight is given to past performance versus the current adaptive signal.
Volatility-Based Reinforcement: Higher market volatility increases the impact of this memory feedback, making the model more reactive in volatile conditions.
Multi-Factor Dynamic Thresholds:
Dynamic Overbought/Oversold: Instead of fixed RSI levels (70/30), the thresholds adjust dynamically based on the Z-Score, making the system more sensitive to extreme market conditions.
Combined Multi-Factor Signal:
The final output signal is the result of combining the true RSI, adaptive RSI, and the probabilistic signal generated from the Monte Carlo simulations. This creates a robust, multi-factor signal that incorporates various market conditions and machine learning techniques.
Visual Representation:
The final combined signal is plotted in blue on the chart, along with reference lines at 55 (overbought), 10 (oversold), and 35 (neutral).
Alerts are set up to trigger when the combined signal crosses above the dynamic overbought level or below the dynamic oversold level.
Conclusion:
This "Ultimate Machine Learning RSI" script leverages multiple machine learning techniques—probabilistic modeling, adaptive learning, recursive feedback, and dynamic thresholds—to create an advanced, highly responsive RSI indicator. The result is an RSI that continuously learns from market conditions, adjusts itself in real-time, and provides a more nuanced and robust signal compared to traditional fixed-length RSI. This indicator pushes the boundaries of what's possible with Pine Script and introduces cutting-edge techniques for technical analysis.
Ultimate Multi-Physics Financial IndicatorThe Ultimate Multi-Physics Financial Indicator is an advanced Pine Script designed to combine various complex theories from physics, mathematics, and statistical mechanics to create a holistic, multi-dimensional approach to market analysis. Let’s break down the core concepts and how they’re applied in this script:
1. Fractal Geometry: Recursive Pattern Recognition
Purpose: This part of the script uses fractal geometry to recursively analyze price pivots (highs and lows) for detecting patterns.
Fractals: The fractalHigh and fractalLow signals represent key turning points in the market. The script goes deeper by recursively analyzing layers of pivot sequences, adding "depth" to the recognition of patterns.
Recursive Depth: It breaks down each detected pivot into smaller components, giving more nuance to market pattern recognition. This provides a broader context for how prices have behaved historically at various levels of recursion.
2. Quantum Mechanics: Adaptive Probabilistic Monte Carlo with Correlation
Purpose: This component integrates randomness (from Monte Carlo simulations) with current market behavior using correlation.
Randomness Weighted by Correlation: By generating random probabilities and weighting them based on how well the market aligns with recent trends, it creates a probabilistic signal. The random values are scaled by a correlation factor (close prices and their moving average), adding adaptive elements where randomness is adjusted by current market conditions.
3. Thermodynamics: Adaptive Efficiency Ratio (Entropy-Like Decay)
Purpose: This section uses principles from thermodynamics, where efficiency in price movement is dynamically adjusted by recent volatility and changes.
Efficiency Ratio: It calculates how efficiently the market is moving over a certain period. The "entropy decay factor" reflects how stable the market is. Higher entropy (chaos) results in lower efficiency, while stable periods maintain higher efficiency.
4. Chaos Theory: Lorenz-Driven Market Oscillation
Purpose: Instead of using a basic Average True Range (ATR) indicator, this section applies chaos theory (using a Lorenz attractor analogy) to describe complex market oscillations.
Lorenz Attractor: This models market behavior with a chaotic system that depends on the historical price changes at different time intervals. The attractor value quantifies the level of "chaos" or unpredictability in the market.
5. String Theory: Multi-Layered Dimensional Analysis of RSI and MACD
Purpose: Combines traditional indicators like the RSI (Relative Strength Index) and MACD (Moving Average Convergence Divergence) with momentum for multi-dimensional analysis.
Interaction of Layers: Each layer (RSI, MACD, and momentum) is treated as part of a multi-dimensional structure, where they influence one another. The final signal is a blended outcome of these key metrics, weighted and averaged for complexity.
6. Fluid Dynamics: Adaptive OBV (Pressure-Based)
Purpose: This section uses fluid dynamics to understand how price movement and volume create pressure over time, similar to how fluids behave under different forces.
Adaptive OBV: Traditional OBV (On-Balance Volume) is adapted by using statistical smoothing to measure the "pressure" exerted by volume over time. The result is a signal that shows where there might be building momentum or pressure in the market based on volume dynamics.
7. Recursive Synthesis of Signals
Purpose: After calculating all the individual signals (fractal, quantum, thermodynamic, chaos, string, and fluid), the script synthesizes them into one cohesive signal.
Recursive Feedback Loop: Each signal is recursively influenced by others, forming a feedback loop that allows the indicator to continuously learn from new data and self-adjust.
8. Signal Smoothing and Final Output
Purpose: To avoid noise in the output, the final combined signal is smoothed using an Exponential Moving Average (EMA), which helps stabilize the output for easier interpretation.
9. Dynamic Color Coding Based on Signal Extremes
Purpose: Visual clarity is enhanced by using color to highlight different levels of signal strength.
Color Coding: The script dynamically adjusts colors (green, orange, red) based on the strength of the final signal relative to its percentile ranking in historical data, making it easier to spot bullish, neutral, or bearish signals.
The "Ultimate Multi-Physics Financial Indicator" integrates a diverse array of scientific principles — fractal geometry, quantum mechanics, thermodynamics, chaos theory, string theory, and fluid dynamics — to provide a comprehensive market analysis tool. By combining probabilistic simulations, multi-dimensional technical indicators, and recursive feedback loops, this indicator adapts dynamically to evolving market conditions, giving traders a holistic view of market behavior across various dimensions. The result is an adaptive and flexible tool that responds to both short-term and long-term market changes
Al Brooks - SuiteThis indicator is designed to identify some key terms and methodologies inspired by Al Brooks price action. It helps trades to easy recognize for example i/ii/iii patterns or shaved bars defined in his books.
i/ii/iii : Single to triple inside bars. Every bar an inside bar to the previous. This can indiciate a potential contination or reversal pattern. (marked with "i")
o/oo/ooo : Single to triple outside bars. Not defined by Al Brooks, but could be an interesting area to develop a strategy. (marked with "o")
Shaved bar : A bar with little or no tail/wick on one or both sides. It can indicate strong directional movement or momentum. (marked with "s"
The timeframe is not important for the validation of the patterns.
Advanced Physics Financial Indicator Each component represents a scientific theory and is applied to the price data in a way that reflects key principles from that theory.
Detailed Explanation
1. Fractal Geometry - High/Low Signal
Concept: Fractal geometry studies self-similar patterns that repeat at different scales. In markets, fractals can be used to detect recurring patterns or turning points.
Implementation: The script detects pivot highs and lows using ta.pivothigh and ta.pivotlow, representing local turning points in price. The fractalSignal is set to 1 for a pivot high, -1 for a pivot low, and 0 if there is no signal. This logic reflects the cyclical, self-similar nature of price movements.
Practical Use: This signal is useful for identifying local tops and bottoms, allowing traders to spot potential reversals or consolidation points where fractal patterns emerge.
2. Quantum Mechanics - Probabilistic Monte Carlo Simulation
Concept: Quantum mechanics introduces uncertainty and probability into systems, much like how future price movements are inherently uncertain. Monte Carlo simulations are used to model a range of possible outcomes based on random inputs.
Implementation: In this script, we simulate 100 random outcomes by generating a random number between -1 and 1 for each iteration. These random values are stored in an array, and the average of these values is calculated to represent the Quantum Signal.
Practical Use: This probabilistic signal provides a sense of randomness and uncertainty in the market, reflecting the possibility of price movement in either direction. It simulates the market’s chaotic nature by considering multiple possible outcomes and their average.
3. Thermodynamics - Efficiency Ratio Signal
Concept: Thermodynamics deals with energy efficiency and entropy in systems. The efficiency ratio in financial terms can be used to measure how efficiently the price is moving relative to volatility.
Implementation: The Efficiency Ratio is calculated as the absolute price change over n periods divided by the sum of absolute changes for each period within n. This ratio shows how much of the price movement is directional versus random, mimicking the concept of efficiency in thermodynamic systems.
Practical Use: A high efficiency ratio suggests that the market is trending smoothly (high efficiency), while a low ratio indicates choppy, non-directional movement (low efficiency, or high entropy).
4. Chaos Theory - ATR Signal
Concept: Chaos theory studies how complex systems are highly sensitive to initial conditions, leading to unpredictable behavior. In markets, chaotic price movements can often be captured through volatility indicators.
Implementation: The script uses a very long ATR period (1000) to reflect slow-moving chaos over time. The Chaos Signal is computed by measuring the deviation of the current price from its long-term average (SMA), normalized by ATR. This captures price deviations over time, hinting at chaotic market behavior.
Practical Use: The signal measures how far the price deviates from its long-term average, which can signal the degree of chaos or extreme behavior in the market. High deviations indicate chaotic or volatile conditions, while low deviations suggest stability.
5. Network Theory - Correlation with BTC
Concept: Network theory studies how different components within a system are interconnected. In markets, assets are often correlated, meaning that price movements in one asset can influence or be influenced by another.
Implementation: This indicator calculates the correlation between the asset’s price and the price of Bitcoin (BTC) over 30 periods. The Network Signal shows how connected the asset is to BTC, reflecting broader market dynamics.
Practical Use: In a highly correlated market, BTC can act as a leading indicator for other assets. A strong correlation with BTC might suggest that the asset is likely to move in line with Bitcoin, while a weak or negative correlation might indicate that the asset is moving independently.
6. String Theory - RSI & MACD Interaction
Concept: String theory attempts to unify the fundamental forces of nature into a single framework. In trading, we can view the RSI and MACD as interacting forces that provide insights into momentum and trend.
Implementation: The script calculates the RSI and MACD and combines them into a single signal. The formula for String Signal is (RSI - 50) / 100 + (MACD Line - Signal Line) / 100, normalizing both indicators to a scale where their contributions are additive. The RSI represents momentum, and MACD shows trend direction and strength.
Practical Use: This signal helps in detecting moments where momentum (RSI) and trend strength (MACD) align, giving a clearer picture of the asset's direction and overbought/oversold conditions. It unifies these two indicators to create a more holistic view of market behavior.
7. Fluid Dynamics - On-Balance Volume (OBV) Signal
Concept: Fluid dynamics studies how fluids move and flow. In markets, volume can be seen as a "flow" that drives price movement, much like how fluid dynamics describe the flow of liquids.
Implementation: The script uses the OBV (On-Balance Volume) indicator to track the cumulative flow of volume based on price changes. The signal is further normalized by its moving average to smooth out fluctuations and make it more reflective of price pressure over time.
Practical Use: The Fluid Signal shows how the flow of volume is driving price action. If the OBV rises significantly, it suggests that there is strong buying pressure, while a falling OBV indicates selling pressure. It’s analogous to how pressure builds in a fluid system.
8. Final Signal - Combining All Physics-Based Indicators
Implementation: Each of the seven physics-inspired signals is combined into a single Final Signal by averaging their values. This approach blends different market insights from various scientific domains, creating a comprehensive view of the market’s condition.
Practical Use: The final signal gives you a holistic, multi-dimensional view of the market by merging different perspectives (fractal behavior, quantum probability, efficiency, chaos, correlation, momentum/trend, and volume flow). This approach helps traders understand the market's dynamics from multiple angles, offering deeper insights than any single indicator.
9. Color Coding Based on Signal Extremes
Concept: The color of the final signal plot dynamically reflects whether the market is in an extreme state.
Implementation: The signal color is determined using percentiles. If the Final Signal is in the top 55th percentile of its range, the signal is green (bullish). If it is between the 45th and 55th percentiles, it is orange (neutral). If it falls below the 45th percentile, it is red (bearish).
Practical Use: This visual representation helps traders quickly identify the strength of the signal. Bullish conditions (green), neutral conditions (orange), and bearish conditions (red) are clearly distinguished, simplifying decision-making.
Range Tightening Indicator (RTI)The Range Tightening Indicator (RTI) quantifies price volatility relative to recent price action, helping traders identify low-volatility consolidations that often precede breakouts.
Range Tightening is calculated by measuring the range between each bar’s high and low prices over a chosen lookback period.
A 5-bar period is recommended for shorter-term momentum setups and a 15-bar period is recommended for swing trading. An option for a custom period is available to suit specific strategies. The default look back for custom is 50, ideal for longer term traders.
Other Key Features:
Dynamic Color Coding: The RTI line turns green when volatility doubles after a drop to or below 20, flagging significant volatility shifts commonly seen before breakouts.
Low-Volatility Dots: Orange dots appear on the RTI line when two or more consecutive bars show RTI values below 20, visually marking extended low-volatility periods.
Volatility Zones: Shaded zones provide quick context:
Zone 1 (0-5): Extremely tight volatility, shown in red.
Zone 2 (5-10): Low volatility, shown in light green.
Zone 3 (10-15): Moderate low volatility, shown in green.
The RTI indicator is ideal for traders looking to anticipate breakout conditions, with features that highlight consolidation phases, support momentum strategies, and help improve entry timing by focusing on shifts in volatility.
This indicator was inspired after Deepvue's RMV Indicator, but uses a different calculation. Results may vary.
SimpleChart Indicator V1copyThe SimpleChart Indicator V1 is a technical analysis tool designed to facilitate trading decisions by providing clear buy and sell signals based on the relationship between the price and a Simple Moving Average (SMA). This indicator is especially useful for traders who prefer a straightforward, rule-based approach to market analysis.
Key Features:
Simple Moving Average (SMA): The core of the indicator is the SMA, which smooths price data over a specified period (default is 14 periods). This helps to identify the overall trend direction by filtering out short-term fluctuations.
Buy Signal: A buy signal is generated when the price crosses above the SMA. This indicates a potential upward trend, suggesting that it may be a good time to enter a long position.
Sell Signal: Conversely, a sell signal is triggered when the price crosses below the SMA. This suggests a potential downward trend, indicating that it may be time to exit a long position or consider a short position.
Visual Representation: The indicator provides clear visual cues on the chart:
Buy signals are marked with green labels below the bars.
Sell signals are marked with red labels above the bars.
The SMA line is plotted in blue, making it easy to identify the trend.
Benefits of Using SimpleChart Indicator V1:
User-Friendly: The indicator is easy to understand and implement, making it suitable for both novice and experienced traders.
Clarity in Decision Making: By providing distinct signals, the indicator helps traders make quick decisions based on the market's behavior concerning the moving average.
Trend Following: The SimpleChart Indicator V1 is particularly effective in trending markets, allowing traders to capture significant price movements.
Use Cases:
Day Trading: Traders can use the indicator for short-term trades by reacting quickly to buy and sell signals.
Swing Trading: The SMA helps identify trends over a longer period, making it suitable for swing traders looking to capitalize on price movements.
In summary, the SimpleChart Indicator V1 is a valuable tool for traders seeking a straightforward and effective way to analyze market trends and make informed trading decisions.
Weekly OHLC LevelsWeekly OHLC Levels Indicator
This indicator plots the previous week's open, high, low, and close (OHLC) levels on the chart for the entire duration of the current week. These levels can be critical for identifying key support and resistance zones, as they often represent psychological levels that traders watch closely.
Features:
Plots previous week’s High (green), Low (red), Open (blue), and Close (purple).
Levels remain visible throughout the current week, providing consistent reference points.
Helps in visualizing how current price action interacts with last week’s important levels.
How to Use:
Use these levels to gauge potential support and resistance areas.
Monitor price reactions around these levels, especially during the beginning of the week, as they can serve as pivot points.
This indicator is suitable for all markets and timeframes, providing valuable insight into price structure relative to weekly market behavior.
