Price Ratio Indicator [ChartPrime]The Price Ratio Indicator is a versatile tool designed to analyze the relationship between the price of an asset and its moving average. It helps traders identify overbought and oversold conditions in the market, as well as potential trend reversals.
◈ User Inputs:
MA Length: Specifies the length of the moving average used in the calculation.
MA Type Fast: Allows users to choose from various types of moving averages such as Exponential Moving Average (EMA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Relative Moving Average (RMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Zero-Lag Exponential Moving Average (ZLEMA), and Hull Moving Average (HMA).
Upper Level and Lower Level: Define the threshold levels for identifying overbought and oversold conditions.
Signal Line Length: Determines the length of the signal line used for smoothing the indicator's values.
◈ Indicator Calculation:
The indicator calculates the ratio between the price of the asset and the selected moving average, subtracts 1 from the ratio, and then smooths the result using the chosen signal line length.
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
//@ Moving Average's Function
ma(src, ma_period, ma_type) =>
ma =
ma_type == 'EMA' ? ta.ema(src, ma_period) :
ma_type == 'SMA' ? ta.sma(src, ma_period) :
ma_type == 'WMA' ? ta.wma(src, ma_period) :
ma_type == 'VWMA' ? ta.vwma(src, ma_period) :
ma_type == 'RMA' ? ta.rma(src, ma_period) :
ma_type == 'DEMA' ? ta.ema(ta.ema(src, ma_period), ma_period) :
ma_type == 'TEMA' ? ta.ema(ta.ema(ta.ema(src, ma_period), ma_period), ma_period) :
ma_type == 'ZLEMA' ? ta.ema(src + src - src , ma_period) :
ma_type == 'HMA' ? ta.hma(src, ma_period)
: na
ma
//@ Smooth of Source
src = math.sum(source, 5)/5
//@ Ratio Price / MA's
p_ratio = src / ma(src, ma_period, ma_type) - 1
◈ Visualization:
The main plot displays the price ratio, with color gradients indicating the strength and direction of the ratio.
The bar color changes dynamically based on the ratio, providing a visual representation of market conditions.
Invisible Horizontal lines indicate the upper and lower threshold levels for overbought and oversold conditions.
A signal line, smoothed using the specified length, helps identify trends and potential reversal points.
High and low value regions are filled with color gradients, enhancing visualization of extreme price movements.
MA type HMA gives faster changes of the indicator (Each MA has its own specifics):
MA type TEMA:
◈ Additional Features:
A symbol displayed at the bottom right corner of the chart provides a quick visual reference to the current state of the indicator, with color intensity indicating the strength of the ratio.
Overall, the Price Ratio Indicator offers traders valuable insights into price dynamics and helps them make informed trading decisions based on the relationship between price and moving averages. Adjusting the input parameters allows for customization according to individual trading preferences and market conditions.
Centered Oscillators
WaveTrend Oscillator PlusThe WaveTrend based on “Enhanced WaveTrend” of EliCobra. The WaveTrend Oscillator is a popular technical analysis tool used to identify overbought and oversold conditions in the market and generate trading signals. This indicator introduces additional features for improved analysis and comparison across assets.
WaveTrend:
The original WaveTrend indicator calculates two lines based on exponential moving averages and their relationship to the asset's price. The first line measures the distance between the asset's price and its EMA, while the second line smooths the first line over a specific period. The result is divided by 0.015 multiplied by the smoothed difference ('d' for reference). The indicator aims to identify overbought and oversold conditions by analyzing the relationship between the two lines.
In the original formula, the rudimentary estimation factor 0.015 times 'd' fails to accomodate for approximately a quarter of the data, preventing the indicator from reaching the traditional stationary levels of +-100. This limitation renders the indicator quantitatively biased, as it relies on the user's subjective adjustment of the levels. The enhanced version replaces this factor with the standard deviation of the asset's price, resulting in improved estimation accuracy and provides a more dynamic and robust outcome, we thereafter multiply the result by 100 to achieve a more traditional oscillation.
Enhancements and Features:
Dynamic Estimation: The original indicator uses an arbitrary estimation factor, while the enhanced version replaces it with the standard deviation of the asset's price. This modification provides a more dynamic and accurate estimation, adapting to the specific price characteristics of each asset.
Stationary Support and Resistance Levels: The enhanced version provides stationary key support and resistance levels that range from -150 to 150. These levels are determined based on the analysis of the indicator's data and encompass more than 95% of the indicator's values. These levels offer important reference points for traders to identify potential price reversals or significant price movements.
Comparison Across Assets: The enhanced version allows for better comparison and analysis across different assets. By incorporating the standard deviation of the asset's price, the indicator provides a more consistent and comparable interpretation of the market conditions across multiple assets.
Z-Score Analysis:
The Z-Score is a statistical measurement that quantifies how far a particular data point deviates from the mean in terms of standard deviations. In the enhanced version, the calculation involves determining the basis (mean) and deviation (standard deviation) of the asset's price to calculate its Z-Score, thereafter applying a smoothing technique to generate the final WaveTrend value.
Utility:
The offers traders and investors valuable insights into overbought and oversold conditions in the market. By analyzing the indicator's values and referencing the stationary support and resistance levels, traders can identify potential trend reversals, evaluate market strength, and make better informed analysis.
The following indicators were added:
⎆⎆ Squeeze Momentum Indicator
⎆⎆ Elliott Wave Oscillator
⎆⎆ Expert Trend Locator
Multiple Indicators Screener v2After taking the approval of Mr. QuantNomad
Multiple Indicators Screener by QuantNomad
New lists have been modified and added
Built-in indicators:
RSI (Relative Strength Index): Provides trading opportunities based on overbought or oversold market conditions.
MFI (Cash Flow Index): Measures the flow of cash into or from assets, which helps in identifying buying and selling areas.
Williams Percent Range (WPR): Measures how high or low the price has been in the last time period, giving signals of periods of saturation.
Supertrend: Used to determine market direction and potential entry and exit locations.
Volume Change Percentage: Provides an analysis of the volume change percentage, which helps in identifying demand and supply changes for assets.
How to use:
Users can choose which symbols they want to monitor and analyze using a variety of built-in indicators.
The indicator provides visual signals that help traders identify potential trading opportunities based on the selected settings.
RSI in purple = buy weak liquidity (safe entry).
MFI in yellow = Liquidity
WPR in blue = RSI, MFI and WPR in oversold areas for all.
Allows users to customize the display locations and appearance of the cursor to their personal preferences.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
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فاحص لمؤشرات متعددة مع مخرجات جدول شاملة لتسهيل مراقبة الكثير من العملات تصل الى 99 في وقت واحد
بختصر الشرح
ظهور اللون البنفسجي يعني كمية الشراء ضعف السيولة .
ظهور اللون الازرق جميع المؤشرات وصلة الى مرحلة التشبع البيعي ( دخول آمن )
ظهور اللون الاصفر يعني السيولة ضعفين الشراء ( عكس اتجاه قريب ) == ركزو على هاللون خصوصا مع عملات الخفيفة
Kalman Volume Filter [ChartPrime]The "Kalman Volume Filter" , aims to provide insights into market volume dynamics by filtering out noise and identifying potential overbought or oversold conditions. Let's break down its components and functionality:
Settings:
Users can adjust various parameters to customize the indicator according to their preferences:
Volume Length: Defines the length of the volume period used in calculations.
Stabilization Coefficient (k): Determines the level of noise reduction in the signals.
Signal Line Length: Sets the length of the signal line used for identifying trends.
Overbought & Oversold Zone Level: Specifies the threshold levels for identifying overbought and oversold conditions.
Source: Allows users to select the price source for volume calculations.
Volume Zone Oscillator (VZO):
Calculates a volume-based oscillator indicating the direction and intensity of volume movements.
Utilizes a volume direction measurement over a specified period to compute the oscillator value.
Normalizes the oscillator value to improve comparability across different securities or timeframes.
// VOLUME ZONE OSCILLATOR
VZO(get_src, length) =>
Volume_Direction = get_src > get_src ? volume : -volume
VZO_volume = ta.hma(Volume_Direction, length)
Total_volume = ta.hma(volume, length)
VZO = VZO_volume / (Total_volume)
VZO := (VZO - 0) / ta.stdev(VZO, 200)
VZO
Kalman Filter:
Applies a Kalman filter to smooth out the VZO values and reduce noise.
Utilizes a stabilization coefficient (k) to control the degree of smoothing.
Generates a filtered output representing the underlying volume trend.
// KALMAN FILTER
series float M_n = 0.0 // - the resulting value of the current calculation
series float A_n = VZO // - the initial value of the current measurement
series float M_n_1 = nz(M_n ) // - the resulting value of the previous calculation
float k = input.float(0.06) // - stabilization coefficient
// Kalman Filter Formula
kalm(k)=>
k * A_n + (1 - k) * M_n_1
Volume Visualization:
Displays the volume histogram, with color intensity indicating the strength of volume movements.
Adjusts bar colors based on volume bursts to highlight significant changes in volume.
Overbought and Oversold Zones:
Marks overbought and oversold levels on the chart to assist in identifying potential reversal points.
Plotting:
Plots the Kalman Volume Filter line and a signal line for visual analysis.
Utilizes different colors and fills to distinguish between rising and falling trends.
Highlights specific events such as local buy or sell signals, as well as overbought or oversold conditions.
This indicator provides traders with a comprehensive view of volume dynamics, trend direction, and potential market turning points, aiding in informed decision-making during trading activities.
VWAP DivergenceThe "VWAP Divergence" indicator leverages the VWAP Rolling indicator available in TradingView's library to analyze price and volume dynamics. This custom indicator calculates a rolling VWAP (Volume Weighted Average Price) and compares it with a Simple Moving Average (SMA) over a specified historical period.
Advantages:
1. Accurate VWAP Calculation: The VWAP Rolling indicator computes a VWAP that dynamically adjusts based on recent price and volume data. VWAP is a vital metric used by traders to understand the average price at which a security has traded, factoring in volume.
2. SMA Comparison: By contrasting the rolling VWAP from the VWAP Rolling indicator with an SMA of the same length, the indicator highlights potential divergences. This comparison can reveal shifts in market sentiment.
3. Divergence Identification: The primary purpose of this indicator is to detect divergences between the rolling VWAP from VWAP Rolling and the SMA. Divergence occurs when the rolling VWAP significantly differs from the SMA, indicating potential changes in market dynamics.
Interpretation:
1. Positive Oscillator Values: A positive oscillator (difference between rolling VWAP and SMA) suggests that the rolling VWAP, derived from the VWAP Rolling indicator, is above the SMA. This could indicate strong buying interest or accumulation.
2. Negative Oscillator Values: Conversely, a negative oscillator value indicates that the rolling VWAP is below the SMA. This might signal selling pressure or distribution.
3. Divergence Signals: Significant divergences between the rolling VWAP (from VWAP Rolling) and SMA can indicate shifts in market sentiment. For instance, a rising rolling VWAP diverging upwards from the SMA might suggest increasing bullish sentiment.
4. Confirmation with Price Movements: Traders often use these divergences alongside price action to confirm potential trend reversals or continuations.
Implementation:
1. Length Parameter: Adjust the Length input to modify the lookback period for computing both the rolling VWAP from VWAP Rolling and the SMA. A longer period provides a broader view of market sentiment, while a shorter period is more sensitive to recent price movements.
2. Visualization: The indicator plots the VWAP SMA Oscillator, which visually represents the difference (oscillator) between the rolling VWAP (from VWAP Rolling) and SMA over time.
3. Zero Line: The zero line (gray line) serves as a reference point. Oscillator values crossing above or below this line can be interpreted as bullish or bearish signals, respectively.
4. Contextual Analysis: Interpret signals from this indicator in conjunction with broader market conditions and other technical indicators to make informed trading decisions.
This indicator, utilizing the VWAP Rolling component, is valuable for traders seeking insights into the relationship between volume-weighted price levels and traditional moving averages, aiding in the identification of potential trading opportunities based on market dynamics.
MACD 4C with DivergenceMACD 4C Indicator with Divergence
This indicator, named MACD 4C, enhances the traditional MACD (Moving Average Convergence Divergence) by providing a visually intuitive representation with four distinct colors for the histogram bars. It offers a clear interpretation of market momentum and potential trend reversals.
Key Features:
Customizable Parameters: Users can adjust the fast and slow moving average periods along with the signal smoothing parameter to tailor the indicator to their preferred trading style and market conditions.
Four-color Histogram: The histogram bars are color-coded for easy interpretation. Lime and green bars indicate increasing bullish momentum, while maroon and red bars signify increasing bearish momentum.
Bullish and Bearish Divergence Detection: The indicator identifies bullish and bearish divergences between the MACD histogram and price action. Bullish divergence occurs when the price makes a lower low while the MACD histogram forms a higher low, indicating potential bullish reversal. Conversely, bearish divergence occurs when the price makes a higher high while the MACD histogram forms a lower high, suggesting a potential bearish reversal.
How to Use:
Trend Confirmation: Monitor the color of the histogram bars. A series of green (or lime) bars suggests a strengthening bullish trend, while a series of red (or maroon) bars indicates a strengthening bearish trend.
Divergence Identification: Watch for divergences between the MACD histogram and price action. Bullish divergence may signal a potential bullish reversal, while bearish divergence may indicate a potential bearish reversal. These signals can be used in conjunction with other technical analysis tools to confirm trade entries and exits.
The MACD 4C indicator was developed by user vkno422 You can find the original author and their work on their TradingView profile: www.tradingview.com
RSI and MACD Composite ScoreComponents of the Indicator
RSI Settings:
The RSI is set with a length parameter, which can be adjusted by the user but defaults to 14. This measures the speed and change of price movements.
MACD Settings:
The MACD is composed of two lines: the MACD line and the signal line, which are calculated from exponential moving averages (EMAs) of different lengths (fast and slow). The default settings are 9 for the fast length, 26 for the slow length, and 3 for the signal length.
The MACD histogram, which is the difference between the MACD line and the signal line, is also calculated.
Normalization and Combination
RSI Normalization : The RSI values are normalized around 0 by subtracting 50 from the RSI and then dividing by 50. This scaling adjusts the RSI to fluctuate around 0, where positive values indicate strength and negative values indicate weakness relative to the median RSI value of 50.
MACD Normalization : The MACD histogram is normalized by dividing it by the highest absolute value of the histogram over the slow length period. This adjustment scales the MACD histogram to fall between -1 and 1, making it comparable in magnitude to the normalized RSI.
Composite Score Calculation
The composite score is simply the sum of the normalized RSI and the normalized MACD histogram. This results in a combined score that reflects both momentum (from RSI) and trend (from MACD), providing a multifaceted view of market dynamics.
Visualization
The composite score is plotted as an oscillator, with a horizontal zero line that helps identify when the score shifts from positive to negative or vice versa.
The background color changes based on the trend: green if the composite score is above zero (bullish trend) and red if below zero (bearish trend).
KC-MACD Entry Master @shrilssThe KC-MACD Entry Master is designed to enhance trading strategies by utilizing Keltner Channels and MACD for dynamic market analysis. This indicator excels in visually identifying market conditions with a sophisticated bar coloring system and an informative MACD Traffic Light feature.
Key Features:
- Dynamic Bar Coloring: The core feature of this indicator is its ability to adjust the color of bars based on their positioning relative to the Keltner Channels and the EMA (Exponential Moving Average). It colors bars lime or red when the closing price is within the Keltner Channels but above or below the EMA, respectively. Additionally, it uses a fuchsia color to indicate breakouts when the price extends beyond the Keltner Channels. This visual aid helps traders quickly identify potential buying or selling opportunities based on market volatility and price action.
- MACD Traffic Light: Positioned at the bottom of the chart, this unique feature displays the histogram color of the MACD, set by default to a 3/10/16 configuration—known as the 3-10 Oscillator. This Traffic Light gives traders an at-a-glance view of the underlying momentum and trend shifts, further aiding in decision-making processes.
- MACD-Based Entry Signals: By calculating the fast and slow moving averages specified by the user, the script determines MACD values and their crossover with a smoothed signal line. Entry points are then highlighted with shapes (e.g., "Buy" or "Sell") plotted on the chart when conditions are met, including alignment with the bar colors for enhanced accuracy.
Dynamic Price Oscillator (Zeiierman)█ Overview
The Dynamic Price Oscillator (DPO) by Zeiierman is designed to gauge the momentum and volatility of asset prices in trading markets. By integrating elements of traditional oscillators with volatility adjustments and Bollinger Bands, the DPO offers a unique approach to understanding market dynamics. This indicator is particularly useful for identifying overbought and oversold conditions, capturing price trends, and detecting potential reversal points.
█ How It Works
The DPO operates by calculating the difference between the current closing price and a moving average of the closing price, adjusted for volatility using the True Range method. This difference is then smoothed over a user-defined period to create the oscillator. Additionally, Bollinger Bands are applied to the oscillator itself, providing visual cues for volatility and potential breakout signals.
█ How to Use
⚪ Trend Confirmation
The DPO can serve as a confirmation tool for existing trends. Traders might look for the oscillator to maintain above or below its mean line to confirm bullish or bearish trends, respectively. A consistent direction in the oscillator's movement alongside price trend can provide additional confidence in the strength and sustainability of the trend.
⚪ Overbought/Oversold Conditions
With the application of Bollinger Bands directly on the oscillator, the DPO can highlight overbought or oversold conditions in a unique manner. When the oscillator moves outside the Bollinger Bands, it signifies an extreme condition.
⚪ Volatility Breakouts
The width of the Bollinger Bands on the oscillator reflects market volatility. Sudden expansions in the bands can indicate a breakout from a consolidation phase, which traders can use to enter trades in the direction of the breakout. Conversely, a contraction suggests a quieter market, which might be a signal for traders to wait or to look for range-bound strategies.
⚪ Momentum Trading
Momentum traders can use the DPO to spot moments when the market momentum is picking up. A sharp move of the oscillator towards either direction, especially when crossing the Bollinger Bands, can indicate the start of a strong price movement.
⚪ Mean Reversion
The DPO is also useful for mean reversion strategies, especially considering its volatility adjustment feature. When the oscillator touches or breaches the Bollinger Bands, it indicates a deviation from the normal price range. Traders might look for opportunities to enter trades anticipating a reversion to the mean.
⚪ Divergence Trading
Divergences between the oscillator and price action can be a powerful signal for reversals. For instance, if the price makes a new high but the oscillator fails to make a corresponding high, it may indicate weakening momentum and a potential reversal. Traders can use these divergence signals to initiate counter-trend moves.
█ Settings
Length: Determines the lookback period for the oscillator and Bollinger Bands calculation. Increasing this value smooths the oscillator and widens the Bollinger Bands, leading to fewer, more significant signals. Decreasing this value makes the oscillator more sensitive to recent price changes, offering more frequent signals but with increased noise.
Smoothing Factor: Adjusts the degree of smoothing applied to the oscillator's calculation. A higher smoothing factor reduces noise, offering clearer trend identification at the cost of signal timeliness. Conversely, a lower smoothing factor increases the oscillator's responsiveness to price movements, which may be useful for short-term trading but at the risk of false signals.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Trend Tide Oscillator [UAlgo]🔶 Description:
The "Trend Tide Oscillator " is a technical analysis tool designed to identify potential trend reversals and overbought/oversold conditions in the market. It calculates an oscillator based on the Commodity Channel Index (CCI) and then applies smoothing techniques to provide a clearer view of market momentum.
🔶 Key Features:
Oscillator Calculation : The indicator calculates an oscillator based on the Commodity Channel Index (CCI), which is a momentum-based oscillator used to identify overbought and oversold conditions.
Smoothing : Smoothing techniques are applied to the oscillator to reduce noise and provide a clearer view of market momentum. This helps traders in identifying trends more effectively.
Support and Resistance Zones : The indicator plots support and resistance zones based on the highest and lowest values of the oscillator over a specified lookback (default 50) period. These zones can help traders identify potential areas of price reversal. The indicator considers volatility when plotting the support and resistance zones. This aims to create more adaptable levels that account for fluctuating market conditions.
Visualization : The indicator visually represents overbought and oversold conditions with shapes (⚠️), aiding traders in quickly identifying potential entry or exit points.
Customization : Users can adjust parameters such as oscillator length, smoothing, and overbought/oversold levels, support and resistance lookbacks according to their trading preferences.
🔶 Disclaimer :
This indicator is provided for informational and educational purposes only and should not be considered as financial advice. Trading in the financial markets involves risk, and users should conduct their own research and analysis before making any investment decisions.
UT Bot Stochastic RSIUT Bot Stochastic RSI is a powerful trading tool designed to help traders identify potential buy and sell signals in the market. This indicator combines the Stochastic and RSI (Relative Strength Index) oscillators, two of the most popular and effective technical analysis tools, to provide a comprehensive view of market conditions.
The Stochastic oscillator is a momentum indicator that compares a security's closing price to its price range over a given time period. The RSI, on the other hand, is a momentum oscillator that measures the speed and change of price movements. By combining these two indicators, the UT Bot Stochastic RSI can help traders identify overbought and oversold conditions, as well as potential trend reversals.
The UT Bot Stochastic RSI also includes an ATR (Average True Range) trailing stop, which can be used to set stop-loss levels and manage risk. This feature is particularly useful in volatile markets, where price movements can be large and unpredictable.
In addition to its powerful technical analysis tools, the UT Bot Stochastic RSI also includes a backtesting feature, allowing traders to test their strategies on historical data. This can help traders identify the most effective settings for the indicator and improve their trading performance.
Overall, the UT Bot Stochastic RSI is a versatile and effective tool for traders of all levels, providing valuable insights into market conditions and helping to improve trading decisions
Neutral State MACD {DCAquant}The Neutral State MACD {DCAquant}
The Neutral State MACD {DCAquant} offers a nuanced interpretation of the classic MACD (Moving Average Convergence Divergence) indicator. By focusing on the neutrality of price movements, it serves to identify periods where the market lacks a defined directional bias, often seen as potential phases of accumulation or distribution before a new trend emerges.
Characteristics of the Neutral State MACD {DCAquant}:
Enhanced MACD Formula: Incorporates a neutral zone detection system into the traditional MACD framework to spotlight periods of market equilibrium.
Neutral Zone Threshold: A user-defined parameter that establishes a range within which the MACD and the signal line convergence is considered indicative of a neutral state.
Color-Coded Visualization: Utilizes color variations to illustrate the relationship between the MACD line and the signal line, accentuating the detection of neutral states, bullish crossovers, and bearish crossovers.
Functionality:
MACD and Signal Line Calculation: Employs fast and slow EMA inputs to generate the MACD line, contrasted against a signal line to capture momentum shifts.
Neutral State Detection: Assesses the proximity between the MACD and signal lines relative to the neutral zone threshold, identifying periods where neither bullish nor bearish momentum is dominant.
Background Highlighting: Modifies the chart's background color to reflect the current state of the market—neutral (gray), bullish divergence (teal), or bearish divergence (purple).
Interpretation and Trading Strategy:
Market Phases Identification: Traders can spot periods of equilibrium that may precede significant market moves, aiding in the timing of entry and exit points.
Momentum Analysis: The MACD line's cross above the signal line suggests increasing bullish momentum, whereas a cross below may signal growing bearish momentum.
Trend Confirmation: Acts as a confirmation tool when aligned with trend-following strategies, providing additional validation for trade setups.
Customization and User Guidance:
Adjustable Parameters: Allows for fine-tuning of length settings and the neutral zone threshold to match different trading styles and market conditions.
Complementary Indicator: Can be paired with volume indicators, price action patterns, or other oscillators to form a comprehensive trading system.
Disclaimer:
The Neutral State MACD {DCAquant} is a sophisticated tool meant for educational and strategic development. Traders should integrate it within a broader analytical framework and consider additional market factors. It is not a standalone signal for trades and should be used with caution and proper risk management. Trading decisions should always be made in the context of well-researched strategies and responsible investment practices.
Multi-time Frame Trend DirectionThis is a multi-time frame trend direction indicator. It indicates whether the trend is ascending or descending across multiple time frames: 5M, 15M, 30M, 1H, 4H, and Daily.
The logic is based on the positions of EMA12 and EMA26.
These EMAs are smoothed with an SMA.
Why 12 and 26, and why are they smoothed with 9?
As you might surmise, these parameters are derived from the MACD.
I recommend not altering the parameters, but the choice is yours. Enjoy.
Triple EMA Distance IndicatorTriple EMA Distance Indicator
The Triple EMA Distance indicator comprises two sets of triple exponential moving averages (EMAs). One set uses the same smoothing length for all EMAs, while the other set doubles the length for the last EMA. This indicator provides visual cues based on the relationship between these EMAs and candlestick patterns.
Blue Condition:
Indicates when the fast EMA is above the slow EMA.
The distance between the two EMAs is increasing.
Candlesticks and EMAs are colored light blue.
Orange Condition:
Activates when the fast EMA is below the slow EMA.
The distance between the two EMAs is increasing.
Candlesticks and EMAs are colored orange.
Beige Condition:
Occurs when the fast EMA is below the slow EMA.
The distance between the two EMAs is decreasing.
Candlesticks and EMAs are colored beige.
Light Blue Condition:
Represents when the fast EMA is above the slow EMA.
The distance between the two EMAs is decreasing.
Candlesticks and EMAs are colored light blue.
Multi-Timeframe Momentum Indicator [Ox_kali]The Multi-Timeframe Momentum Indicator is a trend analysis tool designed to examine market momentum across various timeframes on a single chart. Utilizing the Relative Strength Index (RSI) to assess the market’s strength and direction, this indicator offers a multidimensional perspective on current trends, enriching technical analysis with a deeper understanding of price movements. Other oscillators, such as the MACD and StochRSI, will be integrated in future updates.
Regarding the operation with the RSI: when its value is below 50 for a given period, the trend is considered bearish. Conversely, a value above 50 indicates a bullish trend. The indicator goes beyond the isolated analysis of each period by calculating an average of the displayed trends, based on user preferences. This average, ranging from “Strong Down” to “Strong Up,” reflects the percentage of periods indicating a bullish or bearish trend, thus providing a precise overview of the overall market condition.
Key Features:
Multi-Timeframe Analysis : Allows RSI analysis across multiple timeframes, offering an overview of market dynamics.
Advanced Customization : Includes options to adjust the RSI period, the RSI trend threshold, and more.
Color and Transparency Options : Offers color styles for bullish and bearish trends, as well as adjustable transparency levels for personalized visualization.
Average Trend Display : Calculates and displays the average trend based on activated timeframes, providing a quick summary of the current market state.
Flexible Table Positioning : Allows users to choose the indicator’s display location on the chart for seamless integration.
List of Parameters:
RSI Period : Defines the RSI period for calculation.
RSI Up/Down Threshold: Threshold for determining bullish or bearish trends of the RSI.
Table Position: Location of the indicator’s display on the chart.
Color Style : Selection of the color style for the indicator.
Strong Down/Up Color (User) : Customization of colors for strong market movements.
Table TF Transparency : Adjustment of the transparency level for the timeframe table.
Show X Minute/Hour/Day/Week Trend : Activation of the RSI display for specific timeframes.
Show AVG : Option to display or not the calculated average trend.
the Multi-Timeframe Momentum Indicator , stands as a comprehensive tool for market trend analysis across various timeframes, leveraging the RSI for in-depth market insights. With the promise of future updates including the integration of additional oscillators like the MACD and StochRSI, this indicator is set to offer even more robust analysis capabilities.
Please note that the MTF-Momentum 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.
Divergence Detector [TradingFinder] RSI + MACD + AO Oscillator 🔵 Introduction
🟣 Understanding Divergence
As mentioned, divergence occurs in technical analysis when a stock's price behaves contrary to indicators on the price chart. Divergence can signify either a reversal of the stock's trend or a continuation of the previous trend correction.
Divergences can act as reversal patterns or continuation patterns. Moreover, divergences can be utilized to identify potential support and resistance levels.
For instance, when an indicator is trending upwards and positive, but the price is declining and trending downwards, divergence occurs. Divergence in a stock indicates trader indecision in buying and selling and warns traders to reconsider their decisions regarding buying or holding the stock.
Divergence aids analysts in identifying critical price points. In indicator divergences, it serves as a potent signal in the realm of technical analysis.
🟣 Types of Divergence
1.Regular Divergence
o Positive Regular Divergence (RD+)
o Negative Regular Divergence (RD-)
2.Hidden Divergence
o Positive Hidden Divergence (HD+)
o Negative Hidden Divergence (HD-)
3.Time Divergence
Key Note : This indicator is specifically designed to identify "Regular Divergence" only. Therefore, the following explanation pertains to this type of divergence.
🔵 Regular Divergence/Convergence
Regular Divergence(Convergence) occurs due to conflicting behavior between the indicator and the price chart, typically at the end of a trend. Recognizing Regular Divergence suggests an anticipation of a trend reversal or a pattern resembling a reversal.
🟣 Positive Regular Divergence (RD+)
In contrast to negative divergence, positive Regular Divergence occurs at the end of a downtrend and between two price lows. It manifests when the price forms a new low on the price chart, but the indicator fails to recognize it.
Positive Regular Divergence indicates strong buying pressure and weak selling pressure. Following the identification of positive divergence on the chart, one can anticipate a price increase for the examined stock.
🟣 Negative Regular Divergence (RD-)
This type of Regular Divergence emerges between two price highs during an uptrend. A new high is formed on the price chart, but the indicator fails to acknowledge it. This scenario indicates negative Regular Divergence.
The likelihood of a subsequent market downturn is high. Negative divergence signifies strong selling pressure and weak buying pressure, suggesting an unfavorable future for the stock.
🔵 How to use
By utilizing the "Fractal Period" input, you can specify your desired periods for identifying divergences.
Additionally, through the "Divergence Detect Method" feature, you can choose which oscillators (MACD, RSI, or AO) to base divergence identification on.
Divergence in MACD Oscillator :
Divergence in the MACD indicator occurs when the price chart and the MACD line form a noticeable opposing pattern, meaning the price moves contrary to the MACD line. In this scenario, one expects a reversal in price direction.
Divergence in RSI Oscillator :
If divergence occurs during a downtrend on the price chart (two consecutive lows, with the second low being lower) and on the corresponding RSI point (two consecutive lows, with the second low being higher), it signifies positive Regular Divergence and implies a buying signal.
Conversely, if divergence occurs during an uptrend on the price chart (two consecutive highs, with the second high being higher) and on the corresponding RSI point (two consecutive highs, with the second high being lower), it indicates negative Regular Divergence, signaling a selling opportunity.
Divergence in AO Oscillator :
The AO indicator calculates histograms similar to the AO base. It calculates the difference between the simple moving averages of 5 and 34 periods based on the median of each bar. Then, it plots the bars based on the difference.
It then compares the histograms to detect peaks and troughs in the AO histograms and compares the identified peaks and troughs to the price. Whenever divergence is detected, it plots lines and arrows.
🔵 Table
The table contains information on the functional features of this oscillator that you can utilize. Four categories of information are presented in the table: "Exist," "Consecutive," "Divergence Quality," and "Change Phase Indicator."
Exist :
If divergence exists, you'll see "+" in this row.
Consecutive :
Divergences may occur consecutively. If same-type divergences form within short intervals, you can observe the count in this row.
Divergence Quality : Based on the number of consecutive divergences, their quality can be evaluated. If one divergence exists, its quality is considered "Normal." If two divergences exist, the quality is "Good," and if three or more divergences exist, the quality is considered "Strong."
Change Phase Indicator : If a phase change occurs between two oscillation peaks formed based on divergence, this change is identified and displayed in this row.
MACD on RSIThe MACD on RSI indicator combines elements of the Moving Average Convergence Divergence (MACD) and the Relative Strength Index (RSI). It calculates the RSI on a specified source with a customizable length, then applies two exponential moving averages (EMAs) to the RSI values. The difference between these EMAs forms the MACD line, visually representing the momentum of the RSI.
ROC Since MorningThe "ROC Since Morning" indicator is designed for traders who wish to gauge the momentum of an asset from a specific time in the morning, allowing for a customizable analysis of pre-market and intraday movements. This indicator calculates the Rate of Change (ROC) from a user-defined hour, offering insights into how the price has moved since then.
How to Use:
Add the "ROC Since Morning" indicator to your chart.
Adjust the start hour input to your preferred time, considering pre-market hours or the official market opening time.
Analyze the ROC values to understand price movements and momentum since your specified start hour. A positive ROC indicates an upward price movement, while a negative ROC suggests downward movement.
TrendLine Toolkit w/ Breaks (Real-Time)The TrendLine Toolkit script introduces an innovating capability by extending the conventional use of trendlines beyond price action to include oscillators and other technical indicators. This tool allows traders to automatically detect and display trendlines on any TradingView built-in oscillator or community-built script, offering a versatile approach to trend analysis. With breakout detection and real-time alerts, this script enhances the way traders interpret trends in various indicators.
🔲 Methodology
Trendlines are a fundamental tool in technical analysis used to identify and visualize the direction and strength of a price trend. They are drawn by connecting two or more significant points on a price chart, typically the highs or lows of consecutive price movements (pivots).
Drawing Trendlines:
Uptrend Line - Connects a series of higher lows. It signals an upward price trend.
Downtrend Line - Connects a series of lower highs. It indicates a downward price trend.
Support and Resistance:
Support Line - A trendline drawn under rising prices, indicating a level where buying interest is historically strong.
Resistance Line - A trendline drawn above falling prices, showing a level where selling interest historically prevails.
Identification of Trends:
Uptrend - Prices making higher highs and higher lows.
Downtrend - Prices making lower highs and lower lows.
Sideways (or Range-bound) - Prices moving within a horizontal range.
A trendline helps confirm the existence and direction of a trend, providing guidance in aligning with the prevailing market sentiment. Additionally, they are usually paired with breakout analysis, a breakout occurs when the price breaches a trendline. This signals a potential change in trend direction or an acceleration of the existing trend.
The script adapts this methodology to oscillators and other indicators. Instead of relying on price pivots, which can only be detected in retrospect, the script utilizes a trailing stop on the oscillator to identify potential swings in real-time, you may find more info about it here (SuperTrend toolkit) . We detect swings or pivots simply by testing for crosses between the indicator and its trailing stop.
type oscillator
float o = Oscillator Value
float s = Trailing Stop Value
oscillator osc = oscillator.new()
bool l = ta.crossunder(osc.o, osc.s) => Utilized as a formed high
bool h = ta.crossover (osc.o, osc.s) => Utilized as a formed low
This approach enables the algorithm to detect trendlines between consecutive pivot highs or lows on the oscillator itself, providing a dynamic and immediate representation of trend dynamics.
🔲 Breakout Detection
The script goes beyond trendline creation by incorporating breakout detection directly within the oscillator. After identifying a trendline, the algorithm continuously monitors the oscillator for potential breakouts, signaling shifts in market sentiment.
🔲 Setup Guide
A simple example on one of my public scripts, Z-Score Heikin-Ashi Transformed
🔲 Settings
Source - Choose an oscillator source of which to base the Toolkit on.
Zeroing - The Mid-Line value of the oscillator, for example RSI & MFI use 50.
Sensitivity - Calibrates the Sensitivity of which TrendLines are detected, higher values result in more detections.
🔲 Alerts
Bearish TrendLine
Bullish TrendLine
Bearish Breakout
Bullish Breakout
As well as the option to trigger 'any alert' call.
By integrating trendline analysis into oscillators, this Toolkit enhances the capabilities of technical analysis, bringing a dynamic and comprehensive approach to identifying trends, support/resistance levels, and breakout signals across various indicators.
MACD - Calculated with VWMAThe only difference from the classic MACD is that this one is calculated with VWMA instead of sma.
Why do I prefer it?
Classic MACD does not include volume.
But MACD - VWMA includes volume as well.
How to use it?
Whatever you do with MACD, you can do with this.
However, if my other indicators meet the conditions, I check MACD - VWMA and if I see that Macd is above the signal, I open the position to buy etc. even if it is below zero.
Again, if my other indicators meet the conditions, I use this method.
Enjoy it!
Trend AngleThe "Trend Angle" indicator serves as a tool for traders to decipher market trends through a methodical lens. It quantifies the inclination of price movements within a specified timeframe, making it easy to understand current trend dynamics.
Conceptual Foundation:
Angle Measurement: The essence of the "Trend Angle" indicator is its ability to compute the angle between the price trajectory over a defined period and the horizontal axis. This is achieved through the calculation of the arctangent of the percentage price change, offering a straightforward measure of market directionality.
Smoothing Mechanisms: The indicator incorporates options for "Moving Average" and "Linear Regression" as smoothing mechanisms. This adaptability allows for refined trend analysis, catering to diverse market conditions and individual preferences.
Functional Versatility:
Source Adaptability: The indicator affords the flexibility to select the desired price source, enabling users to tailor the angle calculation to their analytical framework and other indicators.
Detrending Capability: With the detrending feature, the indicator allows for the subtraction of the smoothing line from the calculated angle, highlighting deviations from the main trend. This is particularly useful for identifying potential trend reversals or significant market shifts.
Customizable Period: The 'Length' parameter empowers traders to define the observation window for both the trend angle calculation and its smoothing, accommodating various trading horizons.
Visual Intuition: The optional colorization enhances interpretability, with the indicator's color shifting based on its relation to the smoothing line, thereby providing an immediate visual cue regarding the trend's direction.
Interpretative Results:
Market Flatness: An angle proximate to 0 suggests a flat market condition, indicating a lack of significant directional movement. This insight can be pivotal for traders in assessing market stagnation.
Trending Market: Conversely, a relatively high angle denotes a trending market, signifying strong directional momentum. This distinction is crucial for traders aiming to capitalize on trend-driven opportunities.
Analytical Nuance vs. Simplicity:
While the "Trend Angle" indicator is underpinned by mathematical principles, its utility lies in its simplicity and interpretative clarity. However, it is imperative to acknowledge that this tool should be employed as part of a comprehensive trading strategy , complemented by other analytical instruments for a holistic market analysis.
In essence, the "Trend Angle" indicator exemplifies the harmonization of simplicity and analytical rigor. Its design respects the complexity of market behaviors while offering straightforward, actionable insights, making it a valuable component in the arsenal of both seasoned and novice traders alike.
Momentum Ghost Machine [ChartPrime]Momentum Ghost Machine (ChartPrime) is designed to be the next generation in momentum/rate of change analysis. This indicator utilizes the properties of one of our favorite filters to create a more accurate and stable momentum oscillator by using a high quality filtered delayed signal to do the momentum comparison.
Traditional momentum/roc uses the raw price data to compare current price to previous price to generate a directional oscillator. This leaves the oscillator prone to false readings and noisy outputs that leave traders unsure of the real likelihood of a future movement. One way to mitigate this issue would be to use some sort of moving average. Unfortunately, this can only go so far because simple moving average algorithms result in a poor reconstruction of the actual shape of the underlying signal.
The windowed sinc low pass filter is a linear phase filter, meaning that it doesn't change the shape or size of the original signal when applied. This results in a faithful reconstruction of the original signal, but without the "high frequency noise". Just like any filter, the process of applying it requires that we have "future" samples resulting in a time delay for real time applications. Fortunately this is a great thing in the context of a momentum oscillator because we need some representation of past price data to compare the current price data to. By using an ideal low pass filter to generate this delayed signal we can super charge the momentum oscillator and fix the majority of issues its predecessors had.
This indicator has a few extra features that other momentum/roc indicators dont have. One major yet simple improvement is the inclusion of a moving average to help gauge the rate of change of this indicator. Since we included a moving average, we thought it would only be appropriate to add a histogram to help visualize the relationship between the signal and its average. To go further with this we have also included linear extrapolation to further help you predict the momentum and direction of this oscillator. Included with this extrapolation we have also added the histogram in the extrapolation to further enhance its visual interpretation. Finally, the inclusion of a candle coloring feature really drives how the utility of the Momentum Machine .
There are three distinct options when using the candle coloring feature: Direct, MA, and Both. With direct the candles will be colored based on the indicators direction and polarity. When it is above zero and moving up, it displays a green color. When it is above zero and moving down it will display a light green color. Conversely, when the indicator is below zero and moving down it displays a red color, and when it it moving up and below zero it will display a light red color. MA coloring will color the candles just like a MACD. If the signal is above its MA and moving up it will display a green color, and when it is above its MA and moving down it will display a light green color.
When the signal is below its MA and moving down it will display a red color, and when its below its ma and moving up it will display a light red color. Both combines the two into a single color scheme providing you with the best of both worlds. If the indicator is above zero it will display the MA colors with a slight twist. When the indicator is moving down and is below its MA it will display a lighter color than before, and when it is below zero and is above its MA it will display a darker color color.
Length of 50 with a smoothing of 100
Length of 50 with a smoothing of 25
By default, the indicator is set to a momentum length of 50, with a post smoothing of 2. We have chosen the longer period for the momentum length to highlight the performance of this indicator compared to its ancestors. A major point to consider with this indicator is that you can only achieve so much smoothing for a chosen delay. This is because more data is required to produce a smoother signal at a specified length. Once you have selected your desired momentum length you can then select your desired momentum smoothing . This is made possible by the use of the windowed sinc low pass algorithm because it includes a frequency cutoff argument. This means that you can have as little or as much smoothing as you please without impacting the period of the indicator. In the provided examples above this paragraph is a visual representation of what is going on under the hood of this indicator. The blue line is the filtered signal being compared to the current closing price. As you can see, the filtered signal is very smooth and accurately represents the underlying price action without noise.
We hope that users can find the same utility as we did in this indicator and that it levels up your analysis utilizing the momentum oscillator or rate of change.
Enjoy
Historical Correlation [LuxAlgo]The Historical Correlation tool aims to provide the historical correlation coefficients of up to 10 pairs of user-defined tickers starting from a user-defined point in time.
Users can choose to display the historical values as lines or the most recent correlation values as a heat map.
🔶 USAGE
This tool provides historical correlation coefficients, the correlation coefficient between two assets highlight their linear relationship and is always within the range (-1, 1).
It is a simple and easy to use statistical tool, with the following interpretation:
Positive correlation (values close to +1.0): the two assets move in sync, they rise and fall at the same time.
Negative correlation (values close to -1.0): the two assets move in opposite directions: when one goes up, the other goes down and vice versa.
No correlation (values close to 0): the two assets move independently.
The user must confirm the selection of the anchor point in order for the tool to be executed; this can be done directly on the chart by clicking on any bar, or via the date field in the settings panel.
For the parameter Anchor period , the user can choose between the following values NONE, HOURLY, DAILY, WEEKLY, MONTHLY, QUARTERLY and YEARLY. If NONE is selected, there will be no resetting of the calculations, otherwise the calculations will start from the first bar of the new period.
There is a wide range of trading strategies that make use of correlation coefficients between assets, some examples are:
Pair Trading: Traders may wish to take advantage of divergences in the price movements of highly positively correlated assets; even highly positively correlated assets do not always move in the same direction; when assets with a correlation close to +1.0 diverge in their behavior, traders may see this as an opportunity to buy one and sell the other in the expectation that the assets will return to the likely same price behavior.
Sector rotation: Traders may want to favor some sectors that are expected to perform in the next cycle, tracking the correlation between different sectors and between the sector and the overall market.
Diversification: Traders can aim to have a diversified portfolio of uncorrelated assets. From a risk management perspective, it is useful to know the correlation between the assets in your portfolio, if you hold equal positions in positively correlated assets, your risk is tilted in the same direction, so if the assets move against you, your risk is doubled. You can avoid this increased risk by choosing uncorrelated assets so that they move independently.
Hedging: Traders may want to hedge positions with correlated assets, from a hedging perspective, if you are long an asset, you can hedge going long a negative correlated asset or going short a positive correlated asset.
Traders generally need to develop awareness, a key point is to be aware of the relationships between the assets we hold or trade, the historical correlation is an invaluable tool in our arsenal which allows us to make better informed decisions.
On this chart we have an example of historical correlations for several futures markets.
We can clearly see how positively correlated the Nasdaq100 and Dow30 are with the SP500 over the whole period, or how the correlation between the Euro and the SP500 falls from almost +85% to almost -4% since 2021.
As we can see, correlations, like everything else in the market, are not static and vary over time depending on many factors, from macro to technical and everything in between.
🔹 Heatmap
The chart above shows the tool with the default settings and the Drawing Mode set to 'HEATMAP'.
We can see the current correlation between the assets, in this case the FX pairs.
The highest positive correlation is +90% (+0.90) between EURUSD and GBPUSD.
The highest negative correlation is -78% (-0.78) between EURUSD and USDJPY.
The pair with no correlation is AUDUSD and EURCAD with 1% (0.01)
On the above chart we can see the current correlations for the futures markets.
Currently, the assets that are less correlated to the SP500 are NaturalGas and the Euro, the more positive correlations are Nasdaq100 and Dow20, and the more negative correlations are the Yen, Treasury Bonds and 10-Year Notes.
🔶 DETAILS
🔹 Anchor Period
This chart shows the standard FX correlations with the Anchor Period set to `MONTHLY`.
We can clearly see how the calculations restart with the new month, in this case we can clearly see the differences between the correlations from month to month.
Let us look at the correlation coefficient between GBPUSD and USDJPY
In January, their correlation started at close to -100%, rose to close to +50%, only to fall to close to 0% and remain there for the second half of the month.
In February it was -90% in the first few days of the month and is now around -57%.
And between AUDUSD and EURCAD
Last month their correlation was negative for most of the month, reaching -70% and ending around -14%.
This month their correlation has never gone below +21% and at the time of writing is close to +53%.
🔶 SETTINGS
Anchor point: Starting point from which the tool is executed
Anchor period: At the beginning of each new period, the tool will reset the calculations
Pairs from 1 to 10: For each pair of tickers, you can: enable/disable the pair, select the color and specify the two tickers from which you wish to obtain the correlation
🔹 Style
Drawing Mode: Output style, `LINES` will show the historical correlations as lines, `HEATMAP` will show the current correlations with a color gradient from green for correlations near 1 to red for correlations near -1.
