RSI with Swing Trade by Kelvin_VAlgorithm Description: "RSI with Swing Trade by Kelvin_V"
1. Introduction:
This algorithm uses the RSI (Relative Strength Index) and optional Moving Averages (MA) to detect potential uptrends and downtrends in the market. The key feature of this script is that it visually changes the candle colors based on the market conditions, making it easier for users to identify potential trend swings or wave patterns.
The strategy offers flexibility by allowing users to enable or disable the MA condition. When the MA condition is enabled, the strategy will confirm trends using two moving averages. When disabled, the strategy will only use RSI to detect potential market swings.
2. Key Features of the Algorithm:
RSI (Relative Strength Index):
The RSI is used to identify potential market turning points based on overbought and oversold conditions.
When the RSI exceeds a predefined upper threshold (e.g., 60), it suggests a potential uptrend.
When the RSI drops below a lower threshold (e.g., 40), it suggests a potential downtrend.
Moving Averages (MA) - Optional:
Two Moving Averages (Short MA and Long MA) are used to confirm trends.
If the Short MA crosses above the Long MA, it indicates an uptrend.
If the Short MA crosses below the Long MA, it indicates a downtrend.
Users have the option to enable or disable this MA condition.
Visual Candle Coloring:
Green candles represent a potential uptrend, indicating a bullish move based on RSI (and MA if enabled).
Red candles represent a potential downtrend, indicating a bearish move based on RSI (and MA if enabled).
3. How the Algorithm Works:
RSI Levels:
The user can set RSI upper and lower bands to represent potential overbought and oversold levels. For example:
RSI > 60: Indicates a potential uptrend (bullish move).
RSI < 40: Indicates a potential downtrend (bearish move).
Optional MA Condition:
The algorithm also allows the user to apply the MA condition to further confirm the trend:
Short MA > Long MA: Confirms an uptrend, reinforcing a bullish signal.
Short MA < Long MA: Confirms a downtrend, reinforcing a bearish signal.
This condition can be disabled, allowing the user to focus solely on RSI signals if desired.
Swing Trade Logic:
Uptrend: If the RSI exceeds the upper threshold (e.g., 60) and (optionally) the Short MA is above the Long MA, the candles will turn green to signal a potential uptrend.
Downtrend: If the RSI falls below the lower threshold (e.g., 40) and (optionally) the Short MA is below the Long MA, the candles will turn red to signal a potential downtrend.
Visual Representation:
The candle colors change dynamically based on the RSI values and moving average conditions, making it easier for traders to visually identify potential trend swings or wave patterns without relying on complex chart analysis.
4. User Customization:
The algorithm provides multiple customization options:
RSI Length: Users can adjust the period for RSI calculation (default is 4).
RSI Upper Band (Potential Uptrend): Users can customize the upper RSI level (default is 60) to indicate a potential bullish move.
RSI Lower Band (Potential Downtrend): Users can customize the lower RSI level (default is 40) to indicate a potential bearish move.
MA Type: Users can choose between SMA (Simple Moving Average) and EMA (Exponential Moving Average) for moving average calculations.
Enable/Disable MA Condition: Users can toggle the MA condition on or off, depending on whether they want to add moving averages to the trend confirmation process.
5. Benefits of the Algorithm:
Easy Identification of Trends: By changing candle colors based on RSI and MA conditions, the algorithm makes it easy for users to visually detect potential trend reversals and trend swings.
Flexible Conditions: The user has full control over the RSI and MA settings, allowing them to adapt the strategy to different market conditions and timeframes.
Clear Visualization: With the candle color changes, users can quickly recognize when a potential uptrend or downtrend is forming, enabling faster decision-making in their trading.
6. Example Usage:
Day traders: Can apply this strategy on short timeframes such as 5 minutes or 15 minutes to detect quick trends or reversals.
Swing traders: Can use this strategy on longer timeframes like 1 hour or 4 hours to identify and follow larger market swings.
在脚本中搜索"averages"
Deviation Adjusted MA Overview
The Deviation Adjusted MA is a custom indicator that enhances traditional moving average techniques by introducing a volatility-based adjustment. This adjustment is implemented by incorporating the standard deviation of price data, making the moving average more adaptive to market conditions. The key feature is the combination of a customizable moving average (MA) type and the application of deviation percentage to modify its responsiveness. Additionally, a smoothing layer is applied to reduce noise, improving signal clarity.
Key Components
Customizable Moving Averages
The script allows the user to select from four different types of moving averages:
Simple Moving Average (SMA): A basic average of the closing prices over a specified period.
Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to recent price changes.
Weighted Moving Average (WMA): Weights prices differently, favoring more recent ones but in a linear progression.
Volume-Weighted Moving Average (VWMA): Adjusts the average by trading volume, placing more weight on high-volume periods.
Standard Deviation Calculation
The script calculates the standard deviation of the closing prices over the selected maLength period.
Standard deviation measures the dispersion or volatility of price movements, giving a sense of market volatility.
Deviation Percentage and Adjustment
Deviation Percentage is calculated by dividing the standard deviation by the base moving average and multiplying by 100 to express it as a percentage.
The base moving average is adjusted by this deviation percentage, making the indicator responsive to changes in volatility. The result is a more dynamic moving average that adapts to market conditions.
The parameter devMultiplier is available to scale this adjustment, allowing further fine-tuning of sensitivity.
Smoothing the Adjusted Moving Average
After adjusting the moving average based on deviation, the script applies an additional Exponential Moving Average (EMA) with a length defined by the smoothingLength input.
This EMA serves as a smoothing filter to reduce the noise that could arise from the raw adjustments of the moving average. The smoothing makes trend recognition more consistent and removes short-term fluctuations that could otherwise distort the signal.
Use cases
The Deviation Adjusted MA indicator serves as a dynamic alternative to traditional moving averages by adjusting its sensitivity based on volatility. The script offers extensive customization options through the selection of moving average type and the parameters controlling smoothing and deviation adjustments.
By applying these adjustments and smoothing, the script enables users to better track trends and price movements, while providing a visual cue for changes in market sentiment.
Lsma | viResearchLsma | viResearch
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Conceptual Foundation and Innovation
The "Lsma" (Least Squares Moving Average) indicator, developed by viResearch, offers a refined approach to trend detection by using linear regression to smooth price data. Unlike traditional moving averages, the Lsma reduces lag by fitting a linear regression line through the data points, providing a more responsive and accurate representation of price trends. This dynamic approach enables traders to capture market movements with greater precision, especially in fast-moving markets.
Technical Composition and Calculation
The "Lsma" indicator is based on the least squares method, a statistical analysis technique that minimizes the difference between observed and predicted values. By applying this method to price data, the Lsma indicator calculates a trend line that reduces the impact of random fluctuations.
Linear Regression Calculation:
Length (len_lsma): The Lsma is computed over a user-defined period, allowing traders to adjust the sensitivity of the indicator to market conditions. A longer period provides a smoother trend, while a shorter period makes the indicator more responsive to recent price changes.
Offset (off): The script includes an optional offset parameter, which shifts the trend line forward or backward, providing additional flexibility in visualizing market trends.
Source (src): The input source (default: close price) determines which price data the Lsma is applied to. This can be customized to suit various trading strategies.
Trend Identification:
Lsma Direction: The script compares the current Lsma value to its previous value to detect trend direction. If the Lsma is increasing and the price is above it, this signals an uptrend (L). Conversely, if the Lsma is decreasing and the price is below it, this signals a downtrend (S).
Entry Confirmation (en): The user can select an entry confirmation source to further validate potential trade signals. This ensures that traders are not solely reliant on the Lsma's trend direction but can also confirm signals with additional data points.
Features and User Inputs
The "Lsma" script offers several customizable options, making it adaptable to various trading styles and market conditions:
Lsma Length: Controls the period over which the Lsma is calculated. Traders can increase this value to smooth out short-term fluctuations or reduce it for faster trend detection.
Offset: Allows users to shift the Lsma plot, which can help in analyzing trends or refining entry and exit points.
Source and Entry Confirmation: The indicator can be applied to different data sources, and users can select a secondary confirmation source for more accurate signal generation.
Practical Applications
The "Lsma" indicator is a versatile tool, especially well-suited for traders seeking to capture trends with minimal lag. It is particularly effective in volatile markets where traditional moving averages may lag behind price action, leading to delayed signals.
Key Uses:
Trend Following: The Lsma provides a clear view of the market's direction, allowing traders to align their positions with the prevailing trend.
Signal Confirmation: The entry confirmation feature enhances the reliability of trend signals, reducing the likelihood of false entries in choppy markets.
Trade Timing: The customizable length and offset settings give traders flexibility in determining the optimal timing for entering and exiting trades.
Advantages and Strategic Value
The "Lsma" indicator offers several advantages over traditional moving averages:
Reduced Lag: By applying linear regression, the Lsma minimizes lag, providing more timely trend signals.
Customizability: The adjustable length, offset, and source inputs give traders the ability to fine-tune the indicator to their specific needs.
Trend Clarity: The indicator's design ensures that only significant trends are captured, filtering out short-term noise that can obscure the bigger picture.
Summary and Usage Tips
The "Lsma" indicator is an excellent tool for trend-following traders, offering a powerful blend of precision and adaptability. By using linear regression, it provides a more accurate and responsive measure of price trends, helping traders stay aligned with market direction. For best results, traders should experiment with different Lsma lengths and entry confirmation sources to tailor the indicator to their strategy. Whether used for identifying trend reversals or confirming trend strength, the "Lsma" indicator is a reliable and versatile solution for modern trading.
MTF Candle Multi HubMTF Candle Multi Hub Indicator - Guide 日本語解説は下記
Introduction
The "MTF Candle Multi Hub" indicator is a versatile and comprehensive tool designed to visualize multiple timeframes' candlestick data, Heikin Ashi candles, and moving averages on a single chart. This indicator also includes a Zigzag feature with the ability to draw horizontal lines at significant swing points, making it a powerful tool for technical analysis.
Key Features
Multi-Timeframe Candlestick Display:
The indicator allows you to display candlesticks from different timeframes, including 5-minute, 15-minute, 1-hour, 4-hour, daily, and weekly timeframes.
Each timeframe's candlestick can be toggled on or off using the settings panel.
Candlesticks are color-coded based on whether the close is higher or lower than the open, with customizable colors for bullish and bearish candles.
Heikin Ashi Candlesticks:
Heikin Ashi candlesticks are also available for 5-minute, 15-minute, 1-hour, 4-hour, daily, and weekly timeframes.
Like the standard candlesticks, these can be toggled on or off, and their colors are customizable.
Moving Averages (MA):
The indicator supports up to four different moving averages, which can be either Simple Moving Average (SMA) or Exponential Moving Average (EMA).
The user can toggle each moving average on or off and adjust the period and type from the settings panel.
An additional feature allows the space between two moving averages to be filled with a color, indicating the relative position of the MAs.
Zigzag Indicator with Horizontal Lines:
The Zigzag feature plots lines between significant swing highs and lows, helping identify trends and potential reversal points.
Two Zigzag lines can be configured, each with customizable swing length, line color, style, and width.
The indicator also offers the ability to draw horizontal lines at the start and end of each Zigzag swing. These horizontal lines can be customized in terms of color, style, width, and length.
The number of horizontal lines to be drawn can be set, allowing for focused analysis of the most recent swings.
Label and Comment Display:
The indicator provides the option to display custom labels and comments on the chart.
You can enter up to ten different comments, which will be displayed in a label at the last candlestick of the chart.
The label's position, background color, text color, and text size are fully customizable.
Trading Strategy
Trend Following with Multi-Timeframe Analysis:
Use the multi-timeframe candlestick and Heikin Ashi features to assess the trend across different timeframes. For example, if both the daily and 4-hour Heikin Ashi candles are bullish, it may indicate a strong uptrend.
Entry and Exit Signals:
Use the Zigzag indicator to identify potential entry points by looking for a new swing high or low.
Horizontal lines from the Zigzag can be used as support and resistance levels, helping to determine potential entry and exit points.
Moving Average Crossovers:
Monitor the crossovers of the moving averages. For example, when a shorter-term MA crosses above a longer-term MA, it may signal a potential buy opportunity.
Confluence of Signals:
The best trading opportunities may arise when multiple signals align. For example, a bullish Zigzag swing, supported by bullish Heikin Ashi candles and a moving average crossover, could provide a strong buy signal.
Disclaimer
For Educational Purposes Only: This indicator is provided for educational purposes and should not be used as the sole basis for any trading decisions.
No Guarantees: The indicator is provided "as is" without any guarantees of accuracy or completeness. Market conditions can change rapidly, and this indicator may not always reflect the most accurate market state.
Test Thoroughly: Bugs may exist in the script. It is highly recommended to test this script on a demo account before using it in live trading.
Use with Caution: Always use this indicator in conjunction with other analysis tools. Do not rely solely on this indicator for making trading decisions.
Sudden Changes or Removal: The indicator may be subject to sudden changes or removal without prior notice. The developer is not responsible for any issues this may cause.
By using this indicator, you agree to these terms.
MTF Candle Multi Hub インジケーター - ガイド
はじめに
「MTF Candle Multi Hub」インジケーターは、複数の時間枠のローソク足データ、平均足、移動平均線を1つのチャート上で視覚化するために設計された多用途かつ包括的なツールです。このインジケーターには、水平線を描画する機能を備えたジグザグ機能も含まれており、テクニカル分析において強力なツールとなります。
主な機能
マルチタイムフレームのローソク足表示:
5分足、15分足、1時間足、4時間足、日足、週足のローソク足を表示することができます。
各時間枠のローソク足は設定パネルでオンまたはオフに切り替えることができます。
ローソク足は、終値が始値より高いか低いかに基づいて色分けされており、強気と弱気のローソク足の色をカスタマイズできます。
平均足ローソク足:
5分足、15分足、1時間足、4時間足、日足、週足の平均足ローソク足を表示することができます。
標準のローソク足と同様に、これらをオンまたはオフに切り替え、色をカスタマイズすることが可能です。
移動平均線（MA）:
このインジケーターは、単純移動平均線（SMA）または指数移動平均線（EMA）のいずれかを選択できる4つの移動平均線をサポートしています。
各移動平均線をオンまたはオフに切り替え、期間やタイプを設定パネルから調整できます。
また、2本の移動平均線の間に色を塗ることで、MAの相対的な位置を視覚的に表示する機能もあります。
ジグザグインジケーターと水平線:
ジグザグ機能は、重要なスイングの高値と安値の間に線を引き、トレンドや潜在的な反転ポイントを識別するのに役立ちます。
2本のジグザグラインを設定することができ、それぞれのスイングの長さ、線の色、スタイル、幅をカスタマイズできます。
また、ジグザグのスイングの始点と終点に水平線を描画する機能も提供されています。これらの水平線は、色、スタイル、幅、長さをカスタマイズできます。
描画する水平線の本数を設定でき、最新のスイングに焦点を当てた分析が可能です。
ラベルとコメントの表示:
インジケーターは、チャート上にカスタムラベルとコメントを表示するオプションを提供します。
最大10個の異なるコメントを入力することができ、これらはチャートの最新のローソク足にラベルとして表示されます。
ラベルの位置、背景色、テキストの色、テキストのサイズは完全にカスタマイズ可能です。
トレード戦略
マルチタイムフレーム分析を使用したトレンドフォロー:
マルチタイムフレームのローソク足や平均足の機能を使用して、異なる時間枠でのトレンドを評価します。例えば、日足と4時間足の平均足が共に強気であれば、強い上昇トレンドを示している可能性があります。
エントリーとエグジットシグナル:
ジグザグインジケーターを使用して、新たなスイング高値または安値を確認し、エントリーポイントを見極めます。
ジグザグの水平線をサポートおよびレジスタンスレベルとして使用し、エントリーやエグジットのタイミングを判断します。
移動平均線のクロスオーバー:
移動平均線のクロスオーバーを監視します。例えば、短期の移動平均線が長期の移動平均線を上抜けた場合、買いのシグナルとなる可能性があります。
シグナルのコンフルエンス:
複数のシグナルが一致する場合、最も良いトレード機会が生まれるかもしれません。例えば、強気のジグザグスイング、強気の平均足、移動平均線のクロスオーバーが揃うと、強力な買いシグナルとなる可能性があります。
免責事項
教育目的のみ: このインジケーターは教育目的で提供されており、トレードの決定を行う際の唯一の基準として使用すべきではありません。
保証なし: インジケーターは「現状のまま」提供されており、その正確性や完全性についての保証はありません。市場の状況は急速に変化する可能性があり、このインジケーターが常に最も正確な市場状況を反映するとは限りません。
十分なテストを: このスクリプトにはバグが存在する可能性があります。実際のトレードで使用する前に、デモ口座で十分にテストすることを強くお勧めします。
慎重に使用: このインジケーターを他の分析ツールと併用して使用してください。このインジケーターだけに頼ってトレードの決定を行うべきではありません。
突然の変更や削除の可能性: このインジケーターは予告なく変更や削除が行われる場合があります。そのため、利用者に不利益が生じる可能性がありますが、開発者はその責任を負いません。
このインジケーターを使用することで、これらの条件に同意したものとみなされます。
God's of LiquidityHere’s a detailed description for your script, following the guidelines for clarity and originality:
---
**Title:** God's of Liquidity
**Description:**
The "Gods of Liquidity" script is a comprehensive trading tool designed to help traders identify high-probability buy and sell opportunities based on a combination of liquidity levels, RSI-based sentiment analysis, and session-specific filters.
**Key Features:**
1. **Liquidity Zones Identification:**
- The script dynamically calculates the previous day's high and low levels, which serve as critical liquidity zones. Traders can use these levels to spot potential breakout points and reversals.
2. **RSI-Based Sentiment Analysis:**
- The script incorporates a sophisticated RSI-based sentiment model that differentiates between institutional (Banker) and retail (Hot Money) activity. This dual RSI approach allows traders to gauge market sentiment and anticipate shifts in momentum.
- **Banker RSI:** Measures the sentiment of institutional traders, with customizable sensitivity and period parameters.
- **Hot Money RSI:** Measures retail trader sentiment, with its own adjustable settings to tailor the script to various market conditions.
3. **Session and Day Filters:**
- Traders can restrict signals to specific trading sessions and days of the week, providing greater control and precision in executing trades. This feature is particularly useful for aligning trading activity with market conditions that best suit the strategy.
4. **Breakout and Reversal Signals:**
- The script generates buy signals when the price breaks above the previous day's high, accompanied by bullish RSI sentiment from institutional traders. Conversely, sell signals are generated when the price breaks below the previous day's low, with bearish institutional sentiment.
- These signals are visually marked on the chart, making it easier for traders to identify potential trading opportunities.
5. **Customizable Moving Averages:**
- The script allows users to customize the moving averages used in the RSI calculations, giving traders the flexibility to adapt the tool to their specific trading style and market conditions.
6. **Alert System:**
- Alerts are integrated to notify traders when buy or sell conditions are met, ensuring that traders can react promptly to potential trading opportunities without constantly monitoring the charts.
**How It Works:**
- The script uses the previous day's high and low as key liquidity levels. The price crossing these levels, combined with RSI-based signals, indicates potential buy or sell opportunities.
- The sentiment analysis is derived from the RSI values, with separate calculations for institutional and retail activities. The crossover points of these RSI values against their respective moving averages trigger buy or sell signals.
- The session and day filters allow traders to focus on the most relevant times for trading, enhancing the effectiveness of the strategy.
**Usage:**
- This indicator is designed for Forex traders who want to integrate liquidity zones and sentiment analysis into their trading strategy. It is particularly effective on daily or higher timeframes where liquidity levels and RSI-based sentiment analysis can provide strong indications of market direction.
- The script's flexibility in adjusting session times, days, and RSI parameters makes it suitable for a wide range of trading styles, from day trading to swing trading.
---
**License:**
This source code is subject to the terms of the Mozilla Public License 2.0 at (mozilla.org).
© bankbaguitarcrazy
---
This description should provide sufficient detail to comply with the publication guidelines, offering clear insight into how the script works and its unique features.
Multi Timeframe Bull Market Support BandsMulti Timeframe Bull Market Support Bands (BMSB) Indicator
Concept and Functionality:
The Multi Timeframe Bull Market Support Bands (BMSB) indicator is a powerful tool designed to identify and visualize support levels across multiple timeframes simultaneously. The primary concept behind BMSB is to plot dynamic support bands derived from moving averages (MAs) that adapt to the prevailing bullish conditions across different timeframes. These bands act as support and resistance (S/R) levels, providing traders with critical insights into potential price bounce areas and market direction.
Key Features:
Multi Timeframe Analysis:
- The indicator plots bull market support bands for the following timeframes concurrently: Chart (with price prediction), 5 minutes (5m), 15 minutes (15m), 1 hour (1h or 60), 4 hours (4h or 240), Daily (D), 3 Days (3D), and Weekly (W).
- These bands allow traders to see how the price interacts with different support levels, potentially bouncing between them as it moves across timeframes.
Dynamic Band Visibility:
- Bands from shorter timeframes are only displayed in relevant higher timeframes:
- 5m is shown only in timeframes ≤ 15m.
- 15m is shown only in timeframes ≤ 1h.
- 1h is shown only in timeframes ≤ 4h.
- 4h is shown only in timeframes ≤ D.
- D and 3D are shown only in timeframes ≤ W.
- W is always shown.
Customizable Moving Averages:
- The period of the moving averages used to calculate the support bands can be adjusted. Any changes made will be applied across all bands to maintain consistency.
Future Band Prediction:
- If the current timeframe lacks sufficient bars to calculate a moving average, the indicator shows a blue line on the bar where the band will appear. When a new band appears on the current bar, it is highlighted in purple, allowing traders to notice the first value of the new band.
- These new bands can act as magnets, attracting price action. Knowing when a new band will appear helps traders anticipate whether the price will be drawn to the upcoming band or potentially break through it.
Benefits:
- Enhanced Market Insight: By layering support bands from multiple timeframes, traders gain a comprehensive view of market dynamics and potential bounce areas.
- Improved Decision-Making: The ability to see upcoming support bands and how the price interacts with them aids in making more informed trading decisions.
- Customization and Flexibility: Adjustable moving average periods ensure that the indicator can be tailored to fit various trading strategies and market conditions.
The Multi Timeframe Bull Market Support Bands indicator is a versatile and insightful tool for traders aiming to leverage multi-timeframe analysis to enhance their trading strategies and better understand market behavior.
Bitcoin Macro Trend Map [Ox_kali]
## Introduction
__________________________________________________________________________________
The “Bitcoin Macro Trend Map” script is designed to provide a comprehensive analysis of Bitcoin’s macroeconomic trends. By leveraging a unique combination of Bitcoin-specific macroeconomic indicators, this script helps traders identify potential market peaks and troughs with greater accuracy. It synthesizes data from multiple sources to offer a probabilistic view of market excesses, whether overbought or oversold conditions.
This script offers significant value for the following reasons:
1. Holistic Market Analysis : It integrates a diverse set of indicators that cover various aspects of the Bitcoin market, from investor sentiment and market liquidity to mining profitability and network health. This multi-faceted approach provides a more complete picture of the market than relying on a single indicator.
2. Customization and Flexibility : Users can customize the script to suit their specific trading strategies and preferences. The script offers configurable parameters for each indicator, allowing traders to adjust settings based on their analysis needs.
3. Visual Clarity : The script plots all indicators on a single chart with clear visual cues. This includes color-coded indicators and background changes based on market conditions, making it easy for traders to quickly interpret complex data.
4. Proven Indicators : The script utilizes well-established indicators like the EMA, NUPL, PUELL Multiple, and Hash Ribbons, which are widely recognized in the trading community for their effectiveness in predicting market movements.
5. A New Comprehensive Indicator : By integrating background color changes based on the aggregate signals of various indicators, this script essentially creates a new, comprehensive indicator tailored specifically for Bitcoin. This visual representation provides an immediate overview of market conditions, enhancing the ability to spot potential market reversals.
Optimal for use on timeframes ranging from 1 day to 1 week , the “Bitcoin Macro Trend Map” provides traders with actionable insights, enhancing their ability to make informed decisions in the highly volatile Bitcoin market. By combining these indicators, the script delivers a robust tool for identifying market extremes and potential reversal points.
## Key Indicators
__________________________________________________________________________________
Macroeconomic Data: The script combines several relevant macroeconomic indicators for Bitcoin, such as the 10-month EMA, M2 money supply, CVDD, Pi Cycle, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons (Full description bellow).
Open Source Sources: Most of the scripts used are sourced from open-source projects that I have modified to meet the specific needs of this script.
Recommended Timeframes: For optimal performance, it is recommended to use this script on timeframes ranging from 1 day to 1 week.
Objective: The primary goal is to provide a probabilistic solution to identify market excesses, whether overbought or oversold points.
## Originality and Purpose
__________________________________________________________________________________
This script stands out by integrating multiple macroeconomic indicators into a single comprehensive tool. Each indicator is carefully selected and customized to provide insights into different aspects of the Bitcoin market. By combining these indicators, the script offers a holistic view of market conditions, helping traders identify potential tops and bottoms with greater accuracy. This is the first version of the script, and additional macroeconomic indicators will be added in the future based on user feedback and other inputs.
## How It Works
__________________________________________________________________________________
The script works by plotting each macroeconomic indicator on a single chart, allowing users to visualize and interpret the data easily. Here’s a detailed look at how each indicator contributes to the analysis:
EMA 10 Monthly: Uses an exponential moving average over 10 monthly periods to signal bullish and bearish trends. This indicator helps identify long-term trends in the Bitcoin market by smoothing out price fluctuations to reveal the underlying trend direction.Moving Averages w/ 18 day/week/month.
Credit to @ryanman0
M2 Money Supply: Analyzes the evolution of global money supply, indicating market liquidity conditions. This indicator tracks the changes in the total amount of money available in the economy, which can impact Bitcoin’s value as a hedge against inflation or economic instability.
Credit to @dylanleclair
CVDD (Cumulative Value Days Destroyed): An indicator based on the cumulative value of days destroyed, useful for identifying market turning points. This metric helps assess the Bitcoin market’s health by evaluating the age and value of coins that are moved, indicating potential shifts in market sentiment.
Credit to @Da_Prof
Pi Cycle: Uses simple and exponential moving averages to detect potential sell points. This indicator aims to identify cyclical peaks in Bitcoin’s price, providing signals for potential market tops.
Credit to @NoCreditsLeft
NUPL (Net Unrealized Profit/Loss): Measures investors’ unrealized profit or loss to signal extreme market levels. This indicator shows the net profit or loss of Bitcoin holders as a percentage of the market cap, helping to identify periods of significant market optimism or pessimism.
Credit to @Da_Prof
PUELL Multiple: Assesses mining profitability relative to historical averages to indicate buying or selling opportunities. This indicator compares the daily issuance value of Bitcoin to its yearly average, providing insights into when the market is overbought or oversold based on miner behavior.
Credit to @Da_Prof
MRVR Z-Scores: Compares market value to realized value to identify overbought or oversold conditions. This metric helps gauge the overall market sentiment by comparing Bitcoin’s market value to its realized value, identifying potential reversal points.
Credit to @Pinnacle_Investor
Hash Ribbons: Uses hash rate variations to signal buying opportunities based on miner capitulation and recovery. This indicator tracks the health of the Bitcoin network by analyzing hash rate trends, helping to identify periods of miner capitulation and subsequent recoveries as potential buying opportunities.
Credit to @ROBO_Trading
## Indicator Visualization and Interpretation
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For each horizontal line representing an indicator, a legend is displayed on the right side of the chart. If the conditions are positive for an indicator, it will turn green, indicating the end of a bearish trend. Conversely, if the conditions are negative, the indicator will turn red, signaling the end of a bullish trend.
The background color of the chart changes based on the average of green or red indicators. This parameter is configurable, allowing adjustment of the threshold at which the background color changes, providing a clear visual indication of overall market conditions.
## Script Parameters
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The script includes several configurable parameters to customize the display and behavior of the indicators:
Color Style:
Normal: Default colors.
Modern: Modern color style.
Monochrome: Monochrome style.
User: User-customized colors.
Custom color settings for up trends (Up Trend Color), down trends (Down Trend Color), and NaN (NaN Color)
Background Color Thresholds:
Thresholds: Settings to define the thresholds for background color change.
Low/High Red Threshold: Low and high thresholds for bearish trends.
Low/High Green Threshold: Low and high thresholds for bullish trends.
Indicator Display:
Options to show or hide specific indicators such as EMA 10 Monthly, CVDD, Pi Cycle, M2 Money, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons.
Specific Indicator Settings:
EMA 10 Monthly: Options to customize the period for the exponential moving average calculation.
M2 Money: Aggregation of global money supply data.
CVDD: Adjustments for value normalization.
Pi Cycle: Settings for simple and exponential moving averages.
NUPL: Thresholds for unrealized profit/loss values.
PUELL: Adjustments for mining profitability multiples.
MRVR Z-Scores: Settings for overbought/oversold values.
Hash Ribbons: Options for hash rate moving averages and capitulation/recovery signals.
## Conclusion
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The “Bitcoin Macro Trend Map” by Ox_kali is a tool designed to analyze the Bitcoin market. By combining several macroeconomic indicators, this script helps identify market peaks and troughs. It is recommended to use it on timeframes from 1 day to 1 week for optimal trend analysis. The scripts used are sourced from open-source projects, modified to suit the specific needs of this analysis.
## Notes
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This is the first version of the script and it is still in development. More indicators will likely be added in the future. Feedback and comments are welcome to improve this tool.
## Disclaimer:
__________________________________________________________________________________
Please note that the Open Interest liquidation map is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
GL Gann Swing IndicatorIntroduction
The GL Gann Swing Indicator is a versatile tool designed to help traders identify market trends, support and resistance areas, and potential reversals. This indicator applies the principles of Gann Swing Charts, a technique developed by W.D. Gann, which focuses on market swings to determine the overall direction and turning points of price action. Gann Swing Charts are a time-tested method of technical analysis that simplifies price action by focusing on significant highs and lows, thereby eliminating market noise and providing a clearer view of the trend.
By analyzing price action and determining swing directions and turning points, the indicator filters out market noise using four distinct bar types:
Up Bar: Higher High, Higher Low
Down Bar: Lower High, Lower Low
Inside Bar: Lower High, Higher Low
Outside Bar: Higher High, Lower Low
This approach helps traders to:
Identify the primary trend direction.
Determine key support and resistance levels.
Recognize potential reversal points.
Filter out minor price fluctuations that do not affect the overall trend.
Features
Bar Types: Display bar types by checking the Show Bar Type box in the indicator's settings. Up bars appear as green upward-pointing triangles, down bars as red downward-pointing triangles, inside bars as grey circles, and outside bars as blue diamonds. These visual aids help traders quickly identify the type of bar and its significance.
Break Lines: These lines highlight when the price rises above a previous swing high or falls below a prior swing low. Green lines indicate breaks of swing highs, while red lines indicate breaks of swing lows. Break lines are enabled by default but can be turned off in the indicator's settings. Break lines provide visual confirmation of trend continuation or reversal.
Bar Count: Bar counts help determine if a swing is overextended and if a reversal is likely. This feature is off by default but can be enabled in the indicator's settings. Users can set a minimum bar count to focus on significant swings. Analyzing the number of bars in a swing can help traders gauge the strength and potential exhaustion of a trend.
Swing MA (Moving Averages): This feature plots the average of a user-defined number of previous swing highs and lows. Options are available to add two moving averages, allowing for both fast and slow averages. Swing MAs can be enabled in the indicator's settings. These moving averages smooth out the price data, making it easier to identify the underlying trend direction.
Why This Indicator is Useful
The GL Gann Swing Indicator is particularly useful for several reasons:
Trend Identification: By focusing on significant price swings, the indicator helps traders identify the primary trend direction, making it easier to align trades with the overall market movement.
Noise Reduction: The indicator filters out minor price fluctuations, allowing traders to focus on meaningful market movements and avoid being misled by short-term volatility.
Support and Resistance Levels: By highlighting key swing highs and lows, the indicator helps traders identify crucial support and resistance levels, which are essential for making informed trading decisions.
Potential Reversals: The indicator's ability to identify overextended swings and potential reversal points can help traders anticipate market turning points and adjust their strategies accordingly.
Customizability: With options to display bar types, break lines, bar counts, and swing moving averages, traders can customize the indicator to suit their specific trading style and preferences.
By incorporating Gann Swing principles, the GL Gann Swing Indicator offers traders a powerful tool to enhance their technical analysis, improve their trading decisions, and ultimately achieve better trading outcomes.
Pivot Point Profile [LuxAlgo]The Pivot Point Profile indicator groups and displays data accumulated from previous pivot points, providing a comprehensive method for prioritizing and displaying areas of interest directly given by swing highs and lows.
Users have access to common settings present in other profile-type indicators.
🔶 USAGE
The Pivot Point Profile is particularly helpful in identifying highly active reversal zones that have been visited multiple times by price. Because of this, we could generally expect these areas to serve as future points of interest, often acting as support or resistance when re-visited.
The profile displays data associated with both Pivot Highs and Pivot Lows. Each row consists of pivot high and pivot low counts side-by-side, forming the total width of the row.
By analyzing the row as a whole, we can gain a better understanding of WHERE to look for interactions.
By analyzing the pivot counts independently, we can gain a better understanding of WHAT to expect when returning to these areas.
For example:
If a row in the profile contains entirely Pivot Lows, this could be seen as an indication to look for buyers to hold that level for a continuation upwards. A break of this level could be interpreted as a lack of interest from previous buyers at this level, indicating a further move down.
🔹 Concentrated Areas
Each row in the profile displays the current count of high pivots and low pivots within the selected lookback. The largest count for each pivot direction is identified as a "Concentrated Area (CA)", these CAs are highlighted over the chart with a line displaying the average of all pivots within that CA. The CA Average is the average of all pivot points (in the majority direction) within the given row.
These can hold more importance as potential support/resistance areas.
Note: The CA Threshold can be manually adjusted to highlight all rows based on a user-selected value.
🔶 DETAILS
🔹 Calculation
The idea behind the Pivot Point Profile is a new analysis method for pivot points, taking the idea of a volume profile and adapting it to display pivot points instead of volume. By using this data, in theory, we should be able to better prioritize zones to anticipate reversals, as well as identify key levels to watch for buyer & seller interactions to use as confirmations in direction.
The (vertical) width of each row is the product of the script's "Row Size", this is the number of rows that the profile will consist of. With a max of 250, the profile can be decently granular. That being said, A more granular profile will have fewer overlapping pivot points. By decreasing the row size (Using fewer rows in the profile) you will increase the tolerance for grouping pivot points. Potentially leading to a more comprehensive Profile. Inversely, By reducing the tolerance for grouping, you will better visualize only similar highs and lows but may have noisier data to sift through.
The Profile is calculated based on a "Lookback" parameter, using only the lookback amount of previous high and low pivots to calculate the profile. Configuring this parameter alongside "Pivot Length", will allow for great control over the frame of reference of the profile.
Note: This indicator is capable of utilizing the full chart history of pivot points, this can be done by enabling the "Use Full Chart History" setting, this will cause the script will calculate from everything it has access to on your current chart.
🔹 Display
The Pivot Point Profile display can be customized to fit a various range of chart styles and visual needs. The specific settings to adjust these can be located in the "Profile Display" Section of the User Inputs.
Profile Width: Sets the Left to Right Width of the Profile. This is the maximum width that the profile will occupy and will scale to fit within this width.
Profile Offset: Sets the distance of the Profile's Axis from the current chart candle. This moves the entire profile left and right to enable to user to set the distance between the profile and the current candle.
Direction: Changes the display direction of the profile, allowing for "Left", "Right", or "Center" display styles.
🔶 SETTINGS
🔹 Pivot Point Parameters
Pivot Type: Choose between "Fractal Pivots" or "SMC Structure" to use as the basis for pivots.
Length: Sets the length for the pivot calculations.
🔹 Profile Calculations Parameters
Lookback: Sets the number of pivots to calculate within, in increments of high and low pairs. (Setting this to 1 = 1 Pivot High & 1 Pivot Low)
Use Full Chart History: Disregards the set lookback and instead uses all available chart data to calculate from.
Row Size: Sets the total number of rows to calculate the profile with.
🔹 Profile Display
Profile Width: Sets the max left & right width (in bars) that the profile will occupy.
Profile Offset: Sets the distance of the profile axis from the last chart bar.
Direction: Sets the display direction
🔹 Concentrated Areas
Highlight CAs: Extends the rows left from concentrated areas.
CA Threshold: Manually set the threshold for determining concentrated areas, when disabled, only the largest rows will be displayed.
CA Averages: Toggles the concentrated area averages for each pivot direction.
Note: CA Averages can be displayed independently without CA Highlights being displayed, and vice versa.
CE_ZLSMA_5MIN_CANDLECHART-- Overview
The "CE_ZLSMA_5MIN_CANDLECHART" strategy, developed by DailyPanda, is a comprehensive trading strategy designed for analyzing trading on 5-minute candlestick charts.
It aims to use some indicators calculated from a Hekin Ashi chart, while running it on a normal candlestick chart, making sure that no price distortion affects the strategy results .
It also brings a feature to show, on the candlestick chart, where the entries would take place on the HA chart, to also be able to study the effect that the price distortion would make on your backtest.
-- Credit
The code in this script is based on open-source indicators originally written by veryfid and everget, I've made significant changes and additions to the scripts but all credit for the idea goes to them, I just built on top of it:
-- Key Features
It incorporate already built indicators (ZLSMA) and CandelierExit (CE)
-- Zero Lag Least Squares Moving Average (ZLSMA) - by veryfid
The ZLSMA is used to detect trends with minimal lag, improving the accuracy of entry and exit signals.
It incorporates a double-smoothed linear regression to minimize lag and enhance trend-following capabilities.
Buy signals are generated when the price closes above the ZLSMA together with the CE signal.
It is calculated based on the HA candlestick pattern.
-- Chandelier Exit (CE) - by everget
The Chandelier Exit indicator is used to dynamically manage stop-loss levels based on the Average True Range (ATR).
It ensures that stop-loss levels are adaptive to market volatility, protecting profits and limiting losses.
The ATR period and multiplier can be customized to fit different trading styles and risk tolerances.
It is calculated based on the HA candlestick pattern.
-- Heikin Ashi Candles
The strategy leverages Heikin Ashi candlesticks to be able identify trends more clearly and leverage this to stay on winning trades longer.
Traders can choose to display Heikin Ashi candlesticks and order fills on the chart for better visualization.
-- Risk Management
The strategy includes multiple risk management options to protect traders' capital.
Maximum intraday loss limit based on a percentage of equity.
Maximum stop-loss in points to filter out entries with excessive risk.
Daily profit target to stop trading once the goal is achieved.
Options to use fixed contract sizes or dynamically adjust based on a percentage of equity.
These features help traders manage risk and ensure sustainable trading practices.
Moving Averages
Several moving averages (EMA 9, EMA 20, EMA 50, EMA 72, EMA 200, SMA 200, and SMA 500) are plotted to provide additional context and trend confirmation.
A "Zone of Value" is highlighted between the EMA 200 and SMA 200 to identify potential support and resistance areas.
-- Customizable Inputs
The strategy includes various customizable inputs, allowing traders to tailor it to their specific needs.
Start and stop trading times.
Risk management parameters (e.g., maximum stop-loss, daily drawdown limit, and daily profit target).
Display options for Heikin Ashi candles and moving averages.
ZLSMA length and offset.
-- Usage
-- Setting Up the Strategy
Configure the start year for the strategy and the trading hours using the input fields. The first candle of each day will be filled black for easy identification, while candles that are outside the allowed time range will be filled purple.
Customize the risk management parameters to match your risk tolerance and trading style.
Enable or disable the display of Heikin Ashi candlesticks and moving averages as desired.
-- Interpreting Signals
Buy signals are indicated by a "Buy" label when the Heikin Ashi close price is above the ZLSMA and the Chandelier Exit indicates a long position.
The strategy will automatically enter a long position with a stop-loss level determined the swing low.
Positions are closed when the close price falls below the ZLSMA.
-- Risk Management
The strategy monitors the maximum intraday loss and stops trading if the loss limit is reached.
If enabled, also stops trading once the daily profit target is achieved, helping to lock in gains.
You have the option to filter operations based on a maximum accepted stop-loss level, based on your risk tolerance.
You can also operate with a fixed amount of contracts or dynamically adjust it based on your allowed risk per trade, ensuring optimal protection of capital.
-- Visual Aids
The strategy plots various moving averages to provide additional trend context.
The "Zone of Value" between the EMA 200 and SMA 200 highlights potential support and resistance areas.
Heikin Ashi candlesticks and order fills can be displayed to enhance the difference this strategy would take if you were to backtest it on a Heikin Ashi chart.
-- Table of results
This strategy also breaks down the results on a monthly basis for better understanding of your capital development along the way.
-- Conclusion
The "CE_ZLSMA_5MIN_CANDLECHART" strategy is a tool for intraday traders looking to understand and leaverage the Heikin Ashi chart while still using the normal candle chart. Traders can customize the strategy to fit their specific needs, making it a versatile addition to any trading toolkit.
Pi Cycle Indicator Low and High
The Pi Cycle Indicator is a technical analysis tool used in finance, particularly within cryptocurrency markets, to identify potential market tops or bottoms. It is based on two moving averages: the 111-day moving average and the 350-day moving average of Bitcoin's price. The indicator suggests that when these two moving averages converge or cross each other, it may signal significant market turning points. The name "Pi Cycle" comes from the mathematical relationship between these two moving averages, roughly equivalent to the mathematical constant Pi (3.14). Traders and analysts use this indicator to gauge potential trend reversals and make informed decisions regarding their trading strategies. However, like any technical analysis tool, it should be used in conjunction with other indicators and fundamental analysis for a comprehensive understanding of market conditions.
MTF MA ChaserThis is my own Moving Averages analysis tool, if anyone else will find it useful.
How It Works:
Upon adding the indicator to the chart, it calculates the selected Moving Averages for the defined timeframes. The main chart will display these MAs according to the user's chosen timeframe and type (default is the chart timeframe). Simultaneously, a table is generated on the chart, showcasing the percentage difference of the current price from these MAs across various timeframes. This table is color-coded to indicate different market states, such as proximity to MA/price crossovers.
Key Features:
Multi-Timeframe Analysis: Users can view Moving Average data from different timeframes (5m, 15m, 1H, 4H, 1D, 1W) on their current chart. This allows for quick and efficient analysis without the need to switch between different timeframe charts.
Variety of Moving Averages: The indicator supports different types of MAs, including EMA (Exponential Moving Average), SMA (Simple Moving Average), and others, providing flexibility in analysis.
Realtime Data Option: Users can choose to display real-time data for MAs, enabling them to make timely trading decisions based on the most current market information.
Customizable Display: The indicator features a customizable table that displays the MA values and their differences from the current price in percentages. Users can show or hide this table and adjust its position and text size according to their preference.
Limited Timeframe Support: The indicator is designed to work on equal or higher timeframes relative to the current chart's timeframe. It specifically supports 5-minute (5m), 15-minute (15m), 1-hour (1H), 4-hour (4H), 1-day (1D), and 1-week (1W) timeframes. This means if your current chart is set to a 1-hour timeframe, the indicator will only show MA data for 1-hour and longer timeframes (4H, 1D, 1W), but not for shorter ones like 5m or 15m.
Yet, you can go down to a 1 - 4 minute chart for scalping purposes if necessary.
Temporary imbalances 2.0 This indicator attempts to calculate potential points of imbalance and equilibrium based on VWAPs and modified moving averages. The idea is to determine if there has been a change in volume and perform the calculation from that point It uses the standard deviation to determine the significant imbalance threshold. Candles with bullish imbalances are highlighted in green, while candles with bearish imbalances are highlighted in red.
"It also features a set of VWAPs and modified moving averages that you can enable or disable."
When you activate the 'Show Anchor VWAP' option, it will add five modified VWAPs.
Practical Significance:
The Anchored VWAP is a volume-weighted average price that serves as a dynamic reference to assess the average price during specific moments of market imbalance.
During a bullish imbalance, the anchor_vwap reflects the VWAP at that moment, emphasizing price behavior during that specific period.
Similarly, in a bearish imbalance, the anchor_vwap provides the associated VWAP for that condition, highlighting price movements during the imbalance phase.
How to Use:
The anchor_vwap can be employed to contextualize the volume-weighted average price during critical moments associated with significant changes in market imbalance.
By analyzing price behavior during and after periods of imbalance, the Anchored VWAP can help better understand market dynamics and identify potential areas of support or resistance.
Show VWAP Percent Imbalance"
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The "showDeltaVWAP" is a toggleable setting that you can turn on or off. When activated, it displays special lines on the chart. Let's understand what these lines represent:
Delta Anchor VWAP:
A green line (Delta Anchor VWAP) represents a measure of market volume imbalance.
Delta2 Anchor VWAP:
A red line (Delta2 Anchor VWAP) shows another perspective of volume imbalance.
VWAP Delta Volume:
A light blue line (VWAP Delta Volume) displays a volume-weighted average of price.
VWAP Delta Volume2:
An orange line (VWAP Delta Volume2) shows another view of the volume-weighted average of price.
Delta3 Anchor VWAP:
A light blue line (Delta3 Anchor VWAP) represents a combination of the previous measures.
Delta4 Anchor VWAP:
A purple line (Delta4 Anchor VWAP) is another combination, providing an overall view.
These lines are based on different conditions and calculations related to trading volume. When you activate "showDeltaVWAP," these lines appear on the chart, aiding in better understanding market behavior.
"Show Faster Volatility" is an option that you can enable or disable. When activated (set to true), it displays special lines on the chart called "Faster Volatility VWAP," "Faster Volatility VWAP2," and "Faster Volatility VWAP3." Let's understand what these lines represent:
Faster Volatility VWAP:
A purple line (Faster Volatility VWAP) is a Volume Weighted Average Price (VWAP) that is calculated more quickly based on short-term price reversal patterns.
Faster Volatility VWAP2:
A light gray line (Faster Volatility VWAP2) is another Volume Weighted Average Price (VWAP) that is calculated even more quickly based on even shorter-term price reversal patterns.
Faster Volatility VWAP3:
A purple line (Faster Volatility VWAP3) is another Volume Weighted Average Price (VWAP) calculated rapidly based on even shorter-term price reversal patterns.
These lines are designed to indicate moments of possible exhaustion of volatility in the market, suggesting that there may be a subsequent increase in volatility. When you activate "Show Faster Volatility," these lines are displayed on the chart.
"Show Average VWAPs Imbalance" displays weighted averages of different Volume Weighted Average Prices (VWAPs) in relation to specific market conditions. Here's an explanation of each component:
Standard VWAP:
The blue line represents the standard VWAP, a volume-weighted average of asset prices over a specific period.
VWAP with Added Imbalance (avg_vwap2):
The pink line is a weighted average that adds an imbalance value to the standard VWAP. This component highlights periods of market imbalance.
VWAP with Balance (avg_vwap3):
The lilac line is a weighted average that adds balance based on the imbalance between uptrend and downtrend, reflecting changes in volume. This provides insights into supply and demand dynamics.
Overall Average of VWAPs (avg_vwaptl):
The violet line is a weighted average that incorporates both standard and adjusted VWAPs, offering an overview of market behavior under different considered conditions.
Visual Customization (Show Average VWAPs Imbalance):
Users have the option to show or hide these average lines on the chart, allowing for a clear visualization of market trends.
"Show Min Variation VWAP" is associated with the calculation and display of a smoothed version of the Volume Weighted Average Price (VWAP), taking into account the minimum price variation over a specific period.
"How Imbalance Anchor VWAP Calculated as the smoothed relationship between liquidity difference and maximum VWAP equilibrium" is associated with the calculation and display of a smoothed version of the Imbalance Anchor VWAP. Here is a detailed explanation:
Calculations and Smoothing:
The variable "smoothed_difference" represents the exponential moving average (EMA) of the difference between two variables related to liquidity.
"smoothed_difference2" is the division of "smoothed_difference" by the maximum variation of the VWAP Equilibrium.
"smoothed_difference3" involves additional manipulation of "smoothed_difference" and "vwap_delta3."
"smoothed_difference4" incorporates the previous results, adjusted by the value of the VWAP.
Visual Customization:
The user has the option to enable or disable the display on the chart.
The line is colored in a shade of green.
It provides a smoothed representation of the Imbalance Anchor VWAP.
The line is colored in a shade of blue, and the calculation involves the summation of moving averages (20, 50, 200). Afterward, there is division by 3. Additionally, there is the summation of moving averages (766, 866, 966), divided by 3. The final step is to add these results together and divide by 2. media name is Imbalance Value2
Show VWAP Equilibrium (Max Variation) Calculated as the difference between two VWAPs derived from the highest and lowest price changes
Show Equilibrium VWAP Calculated as the sum of VWAP and (sma200 - sma20)
calculate the difference between the media of 200 to 20
Show Equilibrium VWAP Calculated as the sum of VWAP and (766+866+966)/3 - (sma200 - sma20)
Show Equilibrium VWAP Standard Deviation Calculated as the Exponential Moving Average (EMA) of the Standard Deviation of SMA (sma200 + sma20 + sma8)/3
Show Equilibrium VWAP Delta Calculated as the ratio of the smoothed VWAP Delta Result componentes
Show Standard Deviation Equilibrium VWAP Delta: Calculated as the Standard Deviation between the Average of VWAP Delta Result Components and Their Smoothed Versions
This average attempts to calculate the equilibrium."
vwap_equilibrium:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price (hl2) multiplied by volume, focusing on periods of volume equilibrium.
Calculation: Utilizes the simple moving average weighted (sma) of the product of the volume-weighted average price and volume only when there is no volume imbalance.
Interpretation: This indicator provides a view of the volume-weighted price trend during moments when the market is in equilibrium, meaning there is no noticeable imbalance in volume conditions. The calculation of VWAP is adjusted to reflect market characteristics during periods of stability.
vwap_percent_condition:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The objective of these two VWAPs is to calculate possible equilibrium points between buyers and sellers.
The indicator works for all timeframes This indicator can be adjusted according to the preferences and characteristics of the specific asset or market. It provides clear visual information and can be used as a complementary tool for technical analysis in trading strategies.
Interesting
Interesting
lookback period 7 , 12, 20,70,200, 500,766,866,966
imbalance threshold 2.4, 3.3 ,4.2
The objective of this indicator is to identify and highlight various points of imbalance and equilibrium.
Trend FinderThe "𝙏𝙍𝙀𝙉𝘿 𝙁𝙄𝙉𝘿𝙀𝙍" indicator is a powerful tool designed to detect trends and identify potential reversal points in asset prices. It operates as both a trend-following and mean reversion indicator, offering insights into market movements.
Trend Identification:
Trend Detection:
This indicator primarily identifies trends in asset prices.
When the "𝙏𝙍𝙀𝙉𝘿 𝙁𝙄𝙉𝘿𝙀𝙍" value is above the middle line, it typically indicates an upward trend in the asset's price.
Color Coding: During an upward trend, the bars are colored green, signaling strength in the upward movement. Conversely, during a downtrend, the bars turn red, indicating a potential downward movement in the asset's price.
Calculation Process:
Moving Averages: The calculation involves using multiple Simple Moving Averages (SMAs) based on the open and close prices of the asset.
Incremental SMA Lengths: These SMAs are calculated with increasing lengths, creating a series of comparisons between closing and opening SMAs. If the closing SMA exceeds the opening SMA, a value of 1 is assigned; otherwise, it's assigned as 0.
Aggregation: All these SMA values are compiled into an array and processed to derive an average, emphasizing the trend direction and strength.
Application:
Trend Strength: The indicator's value reflects the overall strength and direction of the trend. Higher values suggest an end or reversing of trend, while lower values what crosses over or under Midline may indicate a trend changing and indicate incrising of trend strength.
Reversal Indication: Besides identifying trends, it can also serve as a mean reversion indicator, potentially pinpointing potential tops and bottoms in the market.
Midline: Additional in settings can be changed a position of midline to up or down to your personal preference.
The "𝙏𝙍𝙀𝙉𝘿 𝙁𝙄𝙉𝘿𝙀𝙍" indicator amalgamates moving averages and trend analysis, offering a comprehensive view of market trends and potential reversal points. Its adaptability through parameter adjustments allows for fine-tuning to suit various market conditions.
Purchasing Managers Index (PMI)The Purchasing Managers Index (PMI) is a widely recognized economic indicator that provides crucial insights into the health and performance of an economy's manufacturing and services sectors. This index is a vital tool for anticipating economic developments and trends, offering an early warning system for changes in these sectors.
The PMI is calculated based on surveys conducted among purchasing managers in various businesses and organizations. These managers are asked about their perceptions of current business conditions and their expectations for future economic activity within their sectors. The responses are then compiled and used to calculate the PMI value.
A PMI value above 50 typically indicates that the manufacturing or services sector is expanding, suggesting a positive economic outlook. Conversely, a PMI value below 50 suggests contraction, which may be an early indication of economic challenges or a potential recession.
In summary, the Purchasing Managers Index (PMI) is an essential economic indicator that assesses the health of manufacturing and services sectors by surveying purchasing managers' opinions. It serves as an early warning system for changes in economic activity and is a valuable tool for forecasting economic trends and potential crises.
This code combines the Purchasing Managers Index (PMI) data with two Simple Moving Averages (SMA) and some visual elements.
Let's break down how this indicator works:
1. Loading PMI Data:
The indicator loads data for the "USBCOI" symbol, which represents the PMI data. It fetches the monthly closing prices of this symbol.
2. Calculating Moving Averages:
Two Simple Moving Averages (SMAs) are calculated based on the PMI data. The first SMA, sma_usbcoi, has a length defined by the input parameter (default: 2). The second SMA, sma2_usbcoi, has a different length defined by the second input parameter (default: 14).
3. Color Coding and Thresholds:
The line color of the PMI plot is determined based on the value of the PMI. If the PMI is above 52, the color is teal; if it's below 48, the color is red; otherwise, it's gray. These threshold values are often used to identify specific conditions in the PMI data.
4. Crossing Indicator:
A key feature of this indicator is to determine if the PMI crosses the first SMA (sma_usbcoi) from top to bottom while also being above the value of 52. This is indicated by the crossedUp variable. This condition suggests a specific situation where the PMI crosses a short-term moving average while indicating strength (above 52).
5. Visual Elements:
A "💀" skull emoji is defined as skullEmoji.
The PMI is plotted on the chart with color coding based on its value, as described earlier.
The two SMAs are also plotted on the chart.
When the crossedUp condition is met (PMI crosses the first SMA from top to bottom while above 52), a skull emoji (indicating potential danger) is plotted at the top of the indicator window.
@tk · fractal emas█ OVERVIEW
This script is an indicator that plots short, medium and long moving averages for multiple fractals. This script was based on sharks EMAs by rlvs indicator, that plots multiple rays for each fractals into the chart. The main feature of this indicator is the customizability. The calculation itself is simple as moving average.
█ MOTIVATION
The trader can customize all aspects of the plotted data. The text size, extended line length, the moving average type — exponential, simple, etc... — the length of fractal rays, line style, line width and visibility. To keep minimalist, this indicator simplifies the logic of line colors based on the purpose of each moving averages. To prevent overnoise the chart with multiple lines with multiple colors for each fractal timefraes, the trader needs to keep in mind that the all lines with the "short" moving average color for example, will represents the short moving averages lines for all fractals. This logic is applied for medium and long moving averages either.
█ CONCEPT
The trading concept to use this indicator is to make entries on uptrend or downtrend pullbacks when the asset price reaches the short, medium or long moving averages price levels. But this strategy don't works alone. It needs to be aligned together with others indicators like RSI, Chart Patterns, Support and Resistance, and so on... Even more confluences that you have, bigger are your chances to increase the probability for a successful trade. So, don't use this indicator alone. Compose a trading strategy and use it to improve your analysis.
█ CUSTOMIZATION
This indicator allows the trader to customize the following settings:
GENERAL
Text size
Changes the font size of the labels to improve accessibility.
Type: string
Options: `tiny`, `small`, `normal`, `large`.
Default: `small`
SHORT
Type
Select the Short Moving Average calculation type.
Type: string
Options: `EMA`, `SMA`, `HMA`, `VWMA`, `WMA`.
Default: `EMA`
Length
Changes the base length for the Short Moving Average calculation.
Type: int
Default: 12
Source
Changes the base source for the Short Moving Average calculation.
Type: float
Default: close
Color
The base color that will represent the Short Moving Average.
Type: color
Default: color.rgb(255, 235, 59) (yellow)
Fractal Style
The fractal ray line style.
Type: string
Options: `dotted`, `dashed`, `solid`.
Default: `dotted`
Fractal Width
The fractal ray line width.
Type: string
Options: `1px`, `2px`, `3px`, `4px`.
Default: `1px`
Fractal Ray Length
The fractal ray line length.
Type: int
Default: 12
MEDIUM
Type
Select the Medium Moving Average calculation type.
Type: string
Options: `EMA`, `SMA`, `HMA`, `VWMA`, `WMA`.
Default: `EMA`
Length
Changes the base length for the Medium Moving Average calculation.
Type: int
Default: 26
Source
Changes the base source for the Medium Moving Average calculation.
Type: float
Default: close
Color
The base color that will represent the Short Moving Average.
Type: color
Default: color.rgb(0, 230, 118) (lime)
Fractal Style
The fractal ray line style.
Type: string
Options: `dotted`, `dashed`, `solid`.
Default: `dotted`
Fractal Width
The fractal ray line width.
Type: string
Options: `1px`, `2px`, `3px`, `4px`.
Default: `1px`
Fractal Ray Length
The fractal ray line length.
Type: int
Default: 12
LONG
Type
Select the Long Moving Average calculation type.
Type: string
Options: `EMA`, `SMA`, `HMA`, `VWMA`, `WMA`.
Default: `EMA`
Length
Changes the base length for the Long Moving Average calculation.
Type: int
Default: 200
Source
Changes the base source for the Long Moving Average calculation.
Type: float
Default: close
Color
The base color that will represent the Short Moving Average.
Type: color
Default: color.rgb(255, 82, 82) (red)
Fractal Style
The fractal ray line style.
Type: string
Options: `dotted`, `dashed`, `solid`.
Default: `dotted`
Fractal Width
The fractal ray line width.
Type: string
Options: `1px`, `2px`, `3px`, `4px`.
Default: `1px`
Fractal Ray Length
The fractal ray line length.
Type: int
Default: 12
VISIBILITY
Show Fractal Rays · (Short)
Shows short moving average fractal rays.
Type: bool
Default: true
Show Fractal Rays · (Medium)
Shows short moving average fractal rays.
Type: bool
Default: true
Show Fractal Rays · (Long)
Shows short moving average fractal rays.
Type: bool
Default: true
█ FUNCTIONS
The script contains the following functions:
`fn_labelizeTimeFrame`
Labelize timeframe period in minutes and hours.
Parameters:
tf: (string) Timeframe period to be labelized.
Returns: (string) Labelized timeframe string.
`fn_builtInLineStyle`
Converts simple string to built-in line style variable value.
Parameters:
lineStyle: (string) The line style simple string.
Returns: (string) Built-in line style string value.
`fn_builtInLineWidth`
Converts simple pixel string to line width number value.
Parameters:
lineWidth: (string) The line width pixel simple string.
Returns: (string) Built-in line width number value.
`fn_requestFractal`
Requests fractal data based on `period` given an expression.
Parameters:
period: (string) The period timeframe of fractal.
expression: (series float) The expression to retrieve data from fractal.
Returns: (mixed) A result determined by `expression`.
`fn_plotRay`
Plots line after chart bars.
Parameters:
y: (float) Y axis line position.
label: (string) Label to be ploted after line.
color: (color) Line and label color.
length: (int) Line length.
show: (bool) Flag to display the line. (default: `true`)
lineStyle: (string) Line style to be applied. (default: `line.style_dotted`)
lineWidth: (int) Line width. (default: `1`)
Returns: void
`fn_plotEmaRay`
Plots moving average line for a specific period.
Parameters:
period: (simple string) Period of fractal to retrieve
expression: (series float) The expression to retrieve data from fractal.
color: (color) Line and label color.
length: (int) Line length. (default: `12`)
show: (bool) Flag to display the line. (default: `true`)
lineStyle: (string) Line style to be applied. (default: `line.style_dotted`)
lineWidth: (string) Line width. (default: `1px`)
Returns: void
`fn_plotExtendedEmaRay`
Draws extended line for current timeframe moving average.
Parameters:
coordY: (float) Extended line Y axis position.
textValue: (simple string) Extended line label text.
textColor: (color) Extended line text color.
length: (int) Extended length. (default: `5`)
Returns: void
RelativeVolatilityIndicator with Trend FilterGuide to the Relative Volatility Indicator with Trend Filter (RVI_TF)
Introduction
The Relative Volatility Indicator with Trend Filter (RVI_TF) aims to provide traders with a comprehensive tool to analyze market volatility and trend direction. This unique indicator combines volatility ratio calculations with a trend filter to help you make more informed trading decisions.
Key Components
Scaled Volatility Ratio: This measures the current market volatility relative to historical volatility and scales the values for better visualization.
Fast and Slow Moving Averages for Volatility: These provide a smoothed representation of the scaled volatility ratio, making it easier to spot trends in market volatility.
Trend Filter: An additional line representing a long-term Simple Moving Average (SMA) to help you identify the prevailing market trend.
User Inputs
Short and Long ATR Period: These allow you to define the length for calculating the Average True Range (ATR), used in the volatility ratio.
Short and Long StdDev Period: Periods for short-term and long-term standard deviation calculations.
Min and Max Volatility Ratio for Scaling: Scale the volatility ratio between these min and max values.
Fast and Slow SMA Period for Volatility Ratio: Periods for the fast and slow Simple Moving Averages of the scaled volatility ratio.
Trend Filter Period: Period for the long-term SMA, used in the trend filter.
Show Trend Filter: Toggle to show/hide the trend filter line.
Trend Filter Opacity: Adjust the opacity of the trend filter line.
Visual Components
Histogram: The scaled volatility ratio is displayed as a histogram. It changes color based on the ratio value.
Fast and Slow Moving Averages: These are plotted over the histogram for additional context.
Trend Filter Line: Shown when the corresponding toggle is enabled, this line gives an indication of the general market trend.
How to Use
Volatility Analysis: Look for divergences between the fast and slow MAs of the scaled volatility ratio. It can signal potential reversals or continuation of trends.
Trend Confirmation: Use the Trend Filter line to confirm the direction of the current trend.
Conclusion
The RVI_TF is a multi-faceted indicator designed for traders who seek to integrate both volatility and trend analysis into their trading strategies. By providing a clearer understanding of market conditions, this indicator can be a valuable asset in a trader's toolkit.
Support & Resistance AI (K means/median) [ThinkLogicAI]█ OVERVIEW
K-means is a clustering algorithm commonly used in machine learning to group data points into distinct clusters based on their similarities. While K-means is not typically used directly for identifying support and resistance levels in financial markets, it can serve as a tool in a broader analysis approach.
Support and resistance levels are price levels in financial markets where the price tends to react or reverse. Support is a level where the price tends to stop falling and might start to rise, while resistance is a level where the price tends to stop rising and might start to fall. Traders and analysts often look for these levels as they can provide insights into potential price movements and trading opportunities.
█ BACKGROUND
The K-means algorithm has been around since the late 1950s, making it more than six decades old. The algorithm was introduced by Stuart Lloyd in his 1957 research paper "Least squares quantization in PCM" for telecommunications applications. However, it wasn't widely known or recognized until James MacQueen's 1967 paper "Some Methods for Classification and Analysis of Multivariate Observations," where he formalized the algorithm and referred to it as the "K-means" clustering method.
So, while K-means has been around for a considerable amount of time, it continues to be a widely used and influential algorithm in the fields of machine learning, data analysis, and pattern recognition due to its simplicity and effectiveness in clustering tasks.
█ COMPARE AND CONTRAST SUPPORT AND RESISTANCE METHODS
1) K-means Approach:
Cluster Formation: After applying the K-means algorithm to historical price change data and visualizing the resulting clusters, traders can identify distinct regions on the price chart where clusters are formed. Each cluster represents a group of similar price change patterns.
Cluster Analysis: Analyze the clusters to identify areas where clusters tend to form. These areas might correspond to regions of price behavior that repeat over time and could be indicative of support and resistance levels.
Potential Support and Resistance Levels: Based on the identified areas of cluster formation, traders can consider these regions as potential support and resistance levels. A cluster forming at a specific price level could suggest that this level has been historically significant, causing similar price behavior in the past.
Cluster Standard Deviation: In addition to looking at the means (centroids) of the clusters, traders can also calculate the standard deviation of price changes within each cluster. Standard deviation is a measure of the dispersion or volatility of data points around the mean. A higher standard deviation indicates greater price volatility within a cluster.
Low Standard Deviation: If a cluster has a low standard deviation, it suggests that prices within that cluster are relatively stable and less likely to exhibit sudden and large price movements. Traders might consider placing tighter stop-loss orders for trades within these clusters.
High Standard Deviation: Conversely, if a cluster has a high standard deviation, it indicates greater price volatility within that cluster. Traders might opt for wider stop-loss orders to allow for potential price fluctuations without getting stopped out prematurely.
Cluster Density: Each data point is assigned to a cluster so a cluster that is more dense will act more like gravity and
2) Traditional Approach:
Trendlines: Draw trendlines connecting significant highs or lows on a price chart to identify potential support and resistance levels.
Chart Patterns: Identify chart patterns like double tops, double bottoms, head and shoulders, and triangles that often indicate potential reversal points.
Moving Averages: Use moving averages to identify levels where the price might find support or resistance based on the average price over a specific period.
Psychological Levels: Identify round numbers or levels that traders often pay attention to, which can act as support and resistance.
Previous Highs and Lows: Identify significant previous price highs and lows that might act as support or resistance.
The key difference lies in the approach and the foundation of these methods. Traditional methods are based on well-established principles of technical analysis and market psychology, while the K-means approach involves clustering price behavior without necessarily incorporating market sentiment or specific price patterns.
It's important to note that while the K-means approach might provide an interesting way to analyze price data, it should be used cautiously and in conjunction with other traditional methods. Financial markets are influenced by a wide range of factors beyond just price behavior, and the effectiveness of any method for identifying support and resistance levels should be thoroughly tested and validated. Additionally, developments in trading strategies and analysis techniques could have occurred since my last update.
█ K MEANS ALGORITHM
The algorithm for K means is as follows:
Initialize cluster centers
assign data to clusters based on minimum distance
calculate cluster center by taking the average or median of the clusters
repeat steps 1-3 until cluster centers stop moving
█ LIMITATIONS OF K MEANS
There are 3 main limitations of this algorithm:
Sensitive to Initializations: K-means is sensitive to the initial placement of centroids. Different initializations can lead to different cluster assignments and final results.
Assumption of Equal Sizes and Variances: K-means assumes that clusters have roughly equal sizes and spherical shapes. This may not hold true for all types of data. It can struggle with identifying clusters with uneven densities, sizes, or shapes.
Impact of Outliers: K-means is sensitive to outliers, as a single outlier can significantly affect the position of cluster centroids. Outliers can lead to the creation of spurious clusters or distortion of the true cluster structure.
█ LIMITATIONS IN APPLICATION OF K MEANS IN TRADING
Trading data often exhibits characteristics that can pose challenges when applying indicators and analysis techniques. Here's how the limitations of outliers, varying scales, and unequal variance can impact the use of indicators in trading:
Outliers are data points that significantly deviate from the rest of the dataset. In trading, outliers can represent extreme price movements caused by rare events, news, or market anomalies. Outliers can have a significant impact on trading indicators and analyses:
Indicator Distortion: Outliers can skew the calculations of indicators, leading to misleading signals. For instance, a single extreme price spike could cause indicators like moving averages or RSI (Relative Strength Index) to give false signals.
Risk Management: Outliers can lead to overly aggressive trading decisions if not properly accounted for. Ignoring outliers might result in unexpected losses or missed opportunities to adjust trading strategies.
Different Scales: Trading data often includes multiple indicators with varying units and scales. For example, prices are typically in dollars, volume in units traded, and oscillators have their own scale. Mixing indicators with different scales can complicate analysis:
Normalization: Indicators on different scales need to be normalized or standardized to ensure they contribute equally to the analysis. Failure to do so can lead to one indicator dominating the analysis due to its larger magnitude.
Comparability: Without normalization, it's challenging to directly compare the significance of indicators. Some indicators might have a larger numerical range and could overshadow others.
Unequal Variance: Unequal variance in trading data refers to the fact that some indicators might exhibit higher volatility than others. This can impact the interpretation of signals and the performance of trading strategies:
Volatility Adjustment: When combining indicators with varying volatility, it's essential to adjust for their relative volatilities. Failure to do so might lead to overemphasizing or underestimating the importance of certain indicators in the trading strategy.
Risk Assessment: Unequal variance can impact risk assessment. Indicators with higher volatility might lead to riskier trading decisions if not properly taken into account.
█ APPLICATION OF THIS INDICATOR
This indicator can be used in 2 ways:
1) Make a directional trade:
If a trader thinks price will go higher or lower and price is within a cluster zone, The trader can take a position and place a stop on the 1 sd band around the cluster. As one can see below, the trader can go long the green arrow and place a stop on the one standard deviation mark for that cluster below it at the red arrow. using this we can calculate a risk to reward ratio.
Calculating risk to reward: targeting a risk reward ratio of 2:1, the trader could clearly make that given that the next resistance area above that in the orange cluster exceeds this risk reward ratio.
2) Take a reversal Trade:
We can use cluster centers (support and resistance levels) to go in the opposite direction that price is currently moving in hopes of price forming a pivot and reversing off this level.
Similar to the directional trade, we can use the standard deviation of the cluster to place a stop just in case we are wrong.
In this example below we can see that shorting on the red arrow and placing a stop at the one standard deviation above this cluster would give us a profitable trade with minimal risk.
Using the cluster density table in the upper right informs the trader just how dense the cluster is. Higher density clusters will give a higher likelihood of a pivot forming at these levels and price being rejected and switching direction with a larger move.
█ FEATURES & SETTINGS
General Settings:
Number of clusters: The user can select from 3 to five clusters. A good rule of thumb is that if you are trading intraday, less is more (Think 3 rather than 5). For daily 4 to 5 clusters is good.
Cluster Method: To get around the outlier limitation of k means clustering, The median was added. This gives the user the ability to choose either k means or k median clustering. K means is the preferred method if the user things there are no large outliers, and if there appears to be large outliers or it is assumed there are then K medians is preferred.
Bars back To train on: This will be the amount of bars to include in the clustering. This number is important so that the user includes bars that are recent but not so far back that they are out of the scope of where price can be. For example the last 2 years we have been in a range on the sp500 so 505 days in this setting would be more relevant than say looking back 5 years ago because price would have to move far to get there.
Show SD Bands: Select this to show the 1 standard deviation bands around the support and resistance level or unselect this to just show the support and resistance level by itself.
Features:
Besides the support and resistance levels and standard deviation bands, this indicator gives a table in the upper right hand corner to show the density of each cluster (support and resistance level) and is color coded to the cluster line on the chart. Higher density clusters mean price has been there previously more than lower density clusters and could mean a higher likelihood of a reversal when price reaches these areas.
█ WORKS CITED
Victor Sim, "Using K-means Clustering to Create Support and Resistance", 2020, towardsdatascience.com
Chris Piech, "K means", stanford.edu
█ ACKNOLWEDGMENTS
@jdehorty- Thanks for the publish template. It made organizing my thoughts and work alot easier.
Moving Average Continuity [QuantVue]"Moving Average Continuity," is designed to compare the position of two Moving Averages (MAs) across multiple timeframes.
The user can select three timeframes and determine the length and type of both a fast and slow moving average.
The indicator will display a small table in a user selected location.
This table helps traders quickly determine if, for their selected timeframes, the faster moving average is trending above or below the slower moving average.
The “Moving Average Continuity” indicator can also send you three types of alerts;
1. All moving averages are aligned bullish
2. All moving averages are aligned bearish
3. Moving averages are mixed
Key Features:
1. Timeframes: The user can select up to three distinct timeframes to compare the moving averages.
2. Moving Average Inputs: For each MA, users can determine:
• Length of the MA
• Type of the MA - Options include EMA (Exponential Moving Average), SMA (Simple Moving Average), HMA (Hull Moving Average), WMA (Weighted Moving Average), and VWMA (Volume Weighted Moving Average).
3. Positioning: Users have the ability to adjust the table's positioning (top, middle, or bottom) and horizontal alignment (right, center, or left) on the chart overlay.
4. Runtime Error Prevention: The indicator will throw an error if the chart's timeframe exceeds the maximum selected timeframe, ensuring that comparisons are done correctly.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers.
6 EMA/SMA/RMA + Forecasting 10 candles 6EMA/SMA/RMA + Forecasting 10 candles
The script allows the user to choose between different types of moving averages (SMA, EMA, RMA) using the soft_func_choice input.
The user can also choose between two types of forecasting: "Repetition" or "Linear Regression" using the type_of_forecast input.
For the linear regression forecast, the user can specify the number of candles to use in the linear regression calculation using the Linreglen input.
First Moving Average (MA) Calculation:
The script calculates the first MA based on the selected type (SMA, EMA, RMA) and plots it on the chart.
The user can customize the length and source of data for this MA.
If the selected forecast type is "Repetition," the script also calculates additional offset values for different repetitions of the MA.
Forecasting and Offset Calculation:
Depending on the chosen forecast type, the script calculates additional offset values for the MA. These offsets are used to forecast the future values of the MA.
The script calculates offsets for up to five repetitions (offset1, offset2, ..., offset5) for each MA.
If the forecast type is "Linear Regression," the script combines the MA's historical values with linear regression predictions to generate the forecasted values.
Plotting Additional Moving Averages:
The script allows the user to plot up to four additional MAs (Second MA, Third MA, Fourth MA, Fifth MA) with similar customizable settings for length and source of data.
Forecast Repetition:
If the forecast type is "Repetition," the script iterates through historical data and accumulates offset values, effectively simulating a repeated forecasting approach.
This repetition is controlled by a loop that adjusts the offset values based on historical price data.
Overall, this script provides a versatile tool for analyzing and forecasting multiple moving averages using various methods, allowing traders and analysts to experiment with different MA types and forecast strategies on their chosen price series.
ICT Implied Fair Value Gap (IFVG) [LuxAlgo]An Implied Fair Value Gap (IFVG) is a three candles imbalance formation conceptualized by ICT that is based on detecting a larger candle body & then measuring the average between the two adjacent candle shadows.
This indicator automatically detects this imbalance formation on your charts and can be extended by a user set number of bars.
The IFVG average can also be extended until a new respective IFVG is detected, serving as a support/resistance line.
Alerts for the detection of bullish/bearish IFVG's are also included in this script.
🔶 SETTINGS
Shadow Threshold %: Threshold percentage used to filter out IFVG's with low adjacent candles shadows.
IFVG Extension: Number of bars used to extend highlighted IFVG's areas.
Extend Averages: Extend IFVG's averages up to a new detected respective IFVG.
🔶 USAGE
Users of this indicator can primarily find it useful for trading imbalances just as they would for trading regular Fair Value Gaps or other imbalances, which aims to highlight a disparity between supply & demand.
For trading a bullish IFVG, users can find this imbalance as an area where price is likely to fill or act as an area of support.
In the same way, a user could trade bearish IFVGs by seeing it as a potential area to be filled or act as resistance within a downtrend.
Users can also extend the IFVG averages and use them as longer-term support/resistances levels. This can highlight the ability of detected IFVG to provide longer term significant support and resistance levels.
🔶 DETAILS
Various methods have been proposed for the detection of regular FVG's, and as such it would not be uncommon to see various methods for the implied version.
We propose the following identification rules for the algorithmic detection of IFVG's:
🔹 Bullish
Central candle body is larger than the body of the adjacent candles.
Current price low is higher than high price two bars ago.
Current candle lower shadow makes up more than p percent of its total candle range.
Candle upper shadow two bars ago makes up more than p percent of its total candle range.
The average of the current candle lower shadow is greater than the average of the candle upper shadow two bars ago.
where p is the user set threshold.
🔹 Bearish
Central candle body is larger than the body of the adjacent candles.
Current price high is higher than low price two bars ago.
Current candle upper shadow makes up more than p percent of its total candle range.
Candle lower shadow two bars ago makes up more than p percent of its total candle range.
The average of the candle lower shadow 2 bars ago is greater than the average of the current candle higher shadow.
where p is the user set threshold.
🔶 SUPPLEMENTARY MATERIAL
You can see our previously posted script that detects various imbalances as well as regular Fair Value Gaps which have very similar usability to Implied Fair Value Gaps here:
VWMA/SMA 3Commas BotThis strategy utilizes two pairs of different Moving Averages, two Volume-Weighted Moving Averages (VWMA) and two Simple Moving Averages (SMA).
There is a FAST and SLOW version of each VWMA and SMA.
The concept behind this strategy is that volume is not taken into account when calculating a Simple Moving Average.
Simple Moving Averages are often used to determine the dominant direction of price movement and to help a trader look past any short-term volatility or 'noise' from price movement, and instead determine the OVERALL direction of price movement so that one can trade in that direction (trend-following) or look for opportunities to trade AGAINST that direction (fading).
By comparing the different movements of a Volume-Weighted Moving Average against a Simple Moving Average of the same length, a trader can get a better picture of what price movements are actually significant, helping to reduce false signals that might occur from only using Simple Moving Averages.
The practical applications of this strategy are identifying dominant directional trends. These can be found when the Volume Weighted Moving Average is moving in the same direction as the Simple Moving Average, and ideally, tracking above it.
This would indicate that there is sufficient volume supporting an uptrend or downtrend, and thus gives traders additional confirmation to potentially look for a trade in that direction.
One can initially look for the Fast VWMA to track above the Fast SMA as your initial sign of bullish confirmation (reversed for downtrending markets). Then, when the Fast VWMA crosses over the Slow SMA, one can determine additional trend strength. Finally, when the Slow VWMA crosses over the Slow SMA, one can determine that the trend is truly strong.
Traders can choose to look for trade entries at either of those triggers, depending on risk tolerance and risk appetite.
Furthermore, this strategy can be used to identify divergence or weakness in trending movements. This is very helpful for identifying potential areas to exit one's trade or even look for counter-trend trades (reversals).
These moments occur when the Volume-Weighted Moving Average, either fast or slow, begins to trade in the opposite direction as their Simple Moving Average counterpart.
For instance, if price has been trending upwards for awhile, and the Fast VWMA begins to trade underneath the Fast SMA, this is an indication that volume is beginning to falter. Uptrends need appropriate volume to continue moving with momentum, so when we see volume begin to falter, it can be a potential sign of an upcoming reversal in trend.
Depending on how quickly one wants to enter into a movement, one could look for crosses of the Fast VWMA under/over the Fast SMA, crosses of the Fast VWMA over/under the Slow SMA, or crosses over/under of the Slow VWMA and the Slow SMA.
This concept was originally published here on TradingView by ProfitProgrammers.
Here is a link to his original indicator script:
I have added onto this concept by:
converting the original indicator into a strategy tester for backtesting
adding the ability to conveniently test long or short strategies, or both
adding the ability to calculate dynamic position sizes
adding the ability to calculate dynamic stop losses and take profit levels using the Average True Range
adding the ability to exit trades based on overbought/oversold crosses of the Stochastic RSI
conveniently switch between different thresholds or speeds of the Moving Average crosses to test different strategies on different asset classes
easily hook this strategy up to 3Commas for automation via their DCA bot feature
Full credit to ProfitProgrammers for the original concept and idea.
Any feedback or suggestions are greatly appreciated.
MTF MA Ribbon and Bands + BB, Gaussian F. and R. VWAP with StDev█ Multi Timeframe Moving Average Ribbon and Bands + Bollinger Bands, Gaussian Filter and Rolling Volume Weighted Average Price with Standard Deviation Bands
Up to 9 moving averages can be independently applied.
The length , type and timeframe of each moving average are configurable .
The lines, colors and background fill are customizable too.
This script can also display:
Moving Average Bands
Bollinger Bands
Gaussian Filter
Rolling VWAP and Standard Deviation Bands
Types of Moving Averages:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Arnaud Legoux Moving Average (ALMA)
█ Moving Average
Moving Averages are price based, lagging (or reactive) indicators that display the average price of a security over a set period of time.
A Moving Average is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
█ Bollinger Bands
Bollinger Bands consist of a band of three lines which are plotted in relation to security prices.
The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader, a 20 day moving average is by far the most popular).
The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price.
█ Gaussian Filter
Gaussian filter can be used for smoothing.
It rejects high frequencies (fast movements) better than an EMA and has lower lag.
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve.
In the case of low-pass filters, only the upper half of the curve describes the filter.
The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
█ Rolling VWAP
The typical VWAP is designed to be used on intraday charts, as it resets at the beginning of the day.
Such VWAPs cannot be used on daily, weekly or monthly charts. Instead, this rolling VWAP uses a time period that automatically adjusts to the chart's timeframe.
You can thus use the rolling VWAP on any chart that includes volume information in its data feed.
Because the rolling VWAP uses a moving window, it does not exhibit the jumpiness of VWAP plots that reset.
Made with the help from scripts of: adam24x, VishvaP, loxx and pmk07.
