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.
Medie mobili
Uptrick: Trend Analysis 1 Trend Identification:
• The indicator primarily aims to identify trends in the market. It does this by computing two EMAs (fast and slow) and deriving the MACD line, which is the difference between these two EMAs. The MACD line is a momentum indicator that shows the relationship between two moving averages. When the MACD line is above the signal line, it suggests bullish momentum, while below indicates bearish momentum.
2 Entry and Exit Signals:
• The indicator generates potential entry and exit signals based on several conditions:
• Price vs. 20-period EMA: It checks whether the price is above or below the 20-period Exponential Moving Average. This is a common technique used to determine the overall direction of the trend. If the price is above the 20-period EMA, it suggests a bullish trend, and if it's below, it indicates a bearish trend.
• MACD Slope: It calculates the slope of the MACD line over a specified number of bars. A positive slope suggests increasing bullish momentum, while a negative slope indicates increasing bearish momentum.
• Signal Line Crossings: Traders often look for crossovers between the MACD line and the signal line as potential buy or sell signals. When the MACD line crosses above the signal line, it's considered a bullish signal (buy), and when it crosses below, it's seen as a bearish signal (sell).
3 Visual Representation:
• The indicator provides a visual representation of these conditions by plotting the MACD line with different colors depending on the market conditions (bullish, bearish, or neutral). Additionally, it draws vertical lines at the start of negative MACD slopes to highlight potential shifts in momentum.
4 Volume Analysis:
• It incorporates volume analysis by coloring the volume histogram differently based on whether the price is above or below the 20-period EMA. This can provide additional confirmation of trend strength. Higher volumes during price movements above the EMA may confirm bullish trends, while higher volumes during price movements below the EMA may confirm bearish trends.
5 Customization:
• Traders can customize the input parameters such as the fast and slow EMA periods according to their trading strategies and the specific market they're analyzing.
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.
Combined Indicator: Solar EMA and BWMACombined Indicator: Solar EMA and BWMA
This custom indicator combines two popular moving average techniques, the Exponential Moving Average (EMA) and the Barycenter Weighted Moving Average (BWMA), to provide insights into market trends and potential trade opportunities.
Solar EMA (Exponential Moving Average):
The Solar EMA is a dynamic moving average that reacts quickly to price changes while reducing lag.
It is plotted on the chart with customizable lengths, allowing traders to adapt to different market conditions.
Bullish (upward) trends are indicated by a green line, bearish (downward) trends by a red line, and neutral periods by a yellow line.
BWMA (Barycenter Weighted Moving Average):
The BWMA is a weighted moving average that emphasizes recent price action while maintaining smoothness.
It is calculated using a combination of alpha and beta parameters, providing flexibility in tuning to specific market behaviors.
The BWMA line is plotted on the chart, with color indicating trend direction: blue for bullish, red for bearish, and gray for neutral.
Key Features:
Dynamic adaptation to different timeframes, adjusting lengths for both EMA and BWMA based on the selected timeframe.
Detection of potential trend changes and significant market movements using a combination of EMA trend analysis and RSI (Relative Strength Index).
Buy and sell signals generated based on support and resistance levels, providing actionable insights for traders.
Usage:
Traders can use the Solar EMA and BWMA to identify trends, confirm trend reversals, and plan entry and exit points for trades.
Combining both moving averages offers a comprehensive view of market sentiment and enhances decision-making processes.
Disclaimer:
This indicator is intended for educational and informational purposes only and should not be construed as financial advice. Traders are encouraged to conduct their own research and analysis before making any trading decisions.
UM-MA-Directional-Colors
UM-MA-DIRECTION Indicator
Indicator Description
The UM-MA-Direction indicator adds a few more features to a traditional Moving Average indicator. The primary difference is color change upon MA direction. The indicator is green when trending higher and red when trending lower. Additionally, a MA of the MA can be configured. This gives a smoothing effect of the indicator. The indicator also includes a fill between the configured moving average and the moving average of the moving average.
User Configuration
All parameters and colors are user-configurable. While the default is an EMA (Exponential Moving Average), of 8 with a EMA of the EMA set to 5, both can be configured or disabled to the user's liking. The default trending and fill colors are red for trending lower and green for trending higher. The type of MA used is also user configurable with EMA - Exponential Moving Average set as the default.
Alerts
Alerts can be set for Bullish (red to green) color changes or Bearish (green to red) color changes by right-clicking the indicator and selecting "Add Alert."
Recommended Usage
Use this indicator to better determine trend direction over traditional Moving Averages. If you use several MAs, add this indicator to the chart as many times as you like with different settings and configurations.
Author Recommended Settings
I use an 8 period EMA with a 5 period EMA of the EMA on daily and hourly charts. I also use the 233 EMA with no fill and no EMA of EMA on the 3 minute chart. Both 8 and 233 are Fibonacci numbers in case you are wondering. I have also observed there is a fractal nature (recurring pattern within a recurring pattern) to the EMAs. An 8 period EMA color transition on the 1 hour chart is close to a 233 period color transition on the 3 minute chart as far as direction changes. The 233 EMA on the 3 minute chart was borrowed from the "Perfect Storm Trading" book by Wendy and Kim Kirkland which I highly recommend.
UM-Relative Strength Index with Trending EMA and Fill
Description
This is a different take on the traditional RSI - Relative Strength Index. This indicator turns the RSI line green when above 50 and red when below 50 making directional changes highly visual. Additionally, an exponential Moving Average is drawn of the RSI. The EMA is green when trending higher and red when trending lower. The area between the RSI and EMA lines are green when the RSI is above the RSI EMA and red when the RSI is below the EMA.
About
The RSI by itself is a good tool to determine trend with the colors. It can also be used to determined overbought and oversold extremes. The EMA of the RSI is a smoothing technique. The indicator can also be used to determine trend with the directional color changes.
Recommended Usage
I look for crossovers; bullish crossovers when the RSI crosses above the EMA AND the RSI crosses above 50. A bearish crossover is when the RSI crosses down through the EMA AND crosses below 50. It can also be used for trade confirmation; for example if the RSI EMA is green consider staying long. The indicator works on any timeframe and any security. I use it on smaller timeframes, 3 minute, 1 hour, and 3 hour, to better time entries/exits.
Default settings
The defaults are the author's preferred settings:
- RSI period is 10 using the open, high, low, and close for calculation. The additional data points using the OHLC give smoother effect.
- The EMA used by default is 34.
All parameters and colors are user-configurable.
Alerts
Alerts can be set on the indicator itself and/or alert on color changes of the EMA.
Helpful Hints:
Look for positive or negative crossovers.
Look for crosses above or below 50
Look for RSI divergences, for example if a security hits a new high, the RSI does not, this a sign of subtle weakness.
Draw trend lines on the RSI line. A violation of a recent trend line may indicate a change of trend for the security.
Average Directional Index with MACombining the Average Directional Index (ADX) with a 14-period Exponential Moving Average (EMA) can provide traders with a comprehensive approach to identify both the strength of a trend (through ADX) and the trend's direction (using EMA). Let's break down each component and then discuss how they can be combined:
Average Directional Index (ADX):
The ADX is a technical indicator that measures the strength or momentum of a trend, regardless of its direction. The ADX is derived from two other indicators:
Positive Directional Index (+DI): Measures the strength of upward price movement.
Negative Directional Index (-DI): Measures the strength of downward price movement.
14-period Exponential Moving Average (EMA):
The 14-period EMA is a trend-following indicator that gives more weight to recent price data compared to simple moving averages (SMAs). The EMA is calculated by taking the average of the last 14 closing prices, giving more importance to the most recent prices.
Combining ADX and EMA:
When combining ADX with a 14-period EMA:
ADX as a Filter:
Traders might use the ADX to filter out trades when the trend's strength is weak (e.g., ADX below 25) to avoid trading in sideways or choppy markets.
EMA for Trend Direction:
Traders can use the 14-period EMA to determine the trend direction.
A price above the 14-period EMA might indicate an uptrend, while a price below the EMA might suggest a downtrend.
Example Strategy:
Here's a simplified trading strategy combining ADX and EMA:
Trend Identification:
Buy when the price is above the 14-period EMA and the ADX indicates a strong uptrend (e.g., ADX > 25).
Sell or go short when the price is below the 14-period EMA and the ADX indicates a strong downtrend (e.g., ADX > 25).
Avoid Choppy Markets:
Avoid trading when the ADX is below a certain threshold (e.g., ADX < 25) to filter out sideways or range-bound markets.
Combining ADX and a 14-period EMA can provide traders with a balanced approach to identify both the strength and direction of a trend. However, it's essential to remember that no indicator or strategy can guarantee profits, and it's crucial to use risk management techniques and other tools to make informed trading decisions. Consider back testing this strategy on historical data and adjusting the parameters based on their trading style and risk tolerance.
Steinkopff SteigungThe "Steinkopff Slope" indicator is a custom tool for TradingView designed to measure and visually represent the percentage slope of a moving average. This indicator is particularly useful for analyzing the momentum of a financial instrument by highlighting changes in the slope of the moving average.
Initially, the indicator allows the user to define the length of the moving average to be used as the basis for the calculation. This input is set to 220 periods by default but can be adjusted according to the user's preference. The moving average itself is calculated based on the closing prices.
The core functionality of the indicator is to calculate the percentage slope of the moving average. This is achieved by determining the change in the moving average between the current period and the previous period and expressing this change relative to the value of the previous period. The result is then scaled by a factor of 10,000 to derive a percentage slope.
To refine the results and smooth out potential outliers, the indicator additionally performs a smoothing of the calculated slope. The user can adjust the length of this smoothing through another input parameter, which is set to 3 periods by default. The smoothed slope is finally displayed as a histogram in blue, with the line thickness set to 1.
A horizontal line at zero (displayed in gray) serves as a reference point to visually distinguish between positive and negative slopes. This helps traders and analysts identify trends: a slope above the zero line indicates a positive trend, while a slope below the zero line signals a negative trend.
In summary, the "Steinkopff Slope" indicator provides a simple yet effective way to understand the momentum and direction of a trend by analyzing and visualizing changes in the slope of a moving average over a definable period.
Gaussian Price Filter [BackQuant]Gaussian Price Filter
Overview and History of the Gaussian Transformation
The Gaussian transformation, often associated with the Gaussian (normal) distribution, is a mathematical function characteristically prominent in statistics and probability theory. The bell-shaped curve of the Gaussian function, expressing the normal distribution, is ubiquitously employed in various scientific and engineering disciplines, including financial market analysis. This transformation's core utility in trading and economic forecasting is derived from its efficacy in smoothing data series and highlighting underlying trends, which are pivotal for making strategic trading decisions.
The Gaussian filter, specifically, is a type of data-smoothing algorithm that mitigates the random "noise" of market price data, thus enhancing the visibility of crucial trend changes and patterns. Historically, this concept was adapted from fields such as signal processing and image editing, where precise extraction of useful information from noisy environments is critical.
1. What is a Gaussian Transformation?
A Gaussian transformation involves the application of a Gaussian function to a set of data points. The function is applied as a filter in the context of trading algorithms to smooth time series data, which helps in identifying the intrinsic trends obscured by market volatility. The transformation is characterized by its parameter, sigma (σ), representing the standard deviation, which determines the width of the Gaussian bell curve. The breadth of this curve impacts the degree of smoothing: a wider curve (higher sigma value) results in more smoothing, beneficial for longer-term trend analysis.
2. Filtering Price with Gaussian Transformation and its Benefits
In the provided Script, the Gaussian transformation is utilized to filter price data. The filtering process involves convolving the price data with Gaussian weights, which are calculated based on the chosen length (the number of data points considered) and sigma. This convolution process smooths out short-term fluctuations and highlights longer-term movements, facilitating a clearer analysis of market trends.
Benefits:
Reduces noise: It filters out minor price movements and random fluctuations, which are often misleading.
Enhances trend recognition: By smoothing the data, it becomes easier to identify significant trends and reversals.
Improves decision-making: Traders can make more informed decisions by focusing on substantive, smoothed data rather than reacting to random noise.
3. Potential Limitations and Issues
While Gaussian filters are highly effective in smoothing data, they are not without limitations:
Lag introduction: Like all moving averages, the Gaussian filter introduces a lag between the actual price movements and the output signal, which can delay decision-making.
Feature blurring: Over-smoothing might obscure significant price movements, especially if a large sigma is used.
Parameter sensitivity: The choice of length and sigma significantly affects the output, requiring optimization and backtesting to determine the best settings for specific market conditions.
4. Extending Gaussian Filters to Other Indicators
The methodology used to filter price data with a Gaussian filter can similarly be applied to other technical indicators, such as RSI (Relative Strength Index) or MACD (Moving Average Convergence Divergence). By smoothing these indicators, traders can reduce false signals and enhance the reliability of the indicators' outputs, leading to potentially more accurate signals and better timing for entering or exiting trades.
5. Application in Trading
In trading, the Gaussian Price Filter can be strategically used to:
Spot trend reversals: Smoothed price data can more clearly indicate when a trend is starting to change, which is crucial for catching reversals early.
Define entry and exit points: The filtered data points can help in setting more precise entry and exit thresholds, minimizing the risk and maximizing the potential return.
Filter other data streams: Apply the Gaussian filter on volume or open interest data to identify significant changes in market dynamics.
6. Functionality of the Script
The script is designed to:
Calculate Gaussian weights (f_gaussianWeights function): Generates the weights used for the Gaussian kernel based on the provided length and sigma.
Apply the Gaussian filter (f_applyGaussianFilter function): Uses the weights to compute the smoothed price data.
Conditional Trend Detection and Coloring: Determines the trend direction based on the filtered price and colors the price bars on the chart to visually represent the trend.
7. Specific Actions of This Code
The Pine Script provided by BackQuant executes several specific actions:
Input Handling: It allows users to specify the source data (src), kernel length, and sigma directly in the chart settings.
Weight Calculation and Normalization: Computes the Gaussian weights and normalizes them to ensure their sum equals one, which maintains the original data scale.
Filter Application: Applies the normalized Gaussian kernel to the price data to produce a smoothed output.
Trend Identification and Visualization: Identifies whether the market is trending upwards or downwards based on the smoothed data and colors the bars green (up) or red (down) to indicate the trend direction.
Money Flow DashboardThe Money Flow Dashboard is my take on trying to replicate the great and mighty Market Cipher's Money Flow and pack it into a comprehensive dashboard format with access to various timeframes.
If Money Flow is king 👑, then follow the Money 💸
How to Use Money Flow Dashboard:
1. Timeframe Selection: Choose the relevant timeframes based on your trading style and preferences. Enable or disable timeframes in the settings to focus on the most relevant ones for your strategy.
2. Dashboard Interpretation: The Money Flow Dashboard displays green (🟢) and red (🔴) symbols to indicate when the Money Flow is in green or in red zone. You can also leverage the Money Flow values on the dashboard to better interpret sentiment and its changes.
3. Dashboard Placement: To maximize effectiveness, consider placing the Money Flow Dashboard alongside your Market Cipher indicator, allowing for seamless analysis of market dynamics on multiple timeframes at the same time.
4. Confirmation and Strategy: Consider Money Flow Dashboard signals as confirmation for your trading strategy. For instance, in an uptrend, look for long opportunities when the dashboard displays consistent green symbols. Conversely, in a downtrend, focus on short opportunities when red symbols dominate.
5. Risk Management: As with any indicator, use Money Flow Dashboard in conjunction with proper risk management techniques. Avoid trading solely based on indicator signals; instead, integrate them into a comprehensive trading plan.
Coiled Moving AveragesThis indicator detects when 3 moving averages converge and become coiled. This indicates volatility contraction which often leads to volatility expansion, i.e. large price movements.
Moving averages are considered coiled when the percent difference from each moving average to the others is less than the Coil Tolerance % input value.
This indicator is unique in that it detects when moving averages converge within a specified percent range. This is in contrast to other indicators that only detect moving average crossovers, or the distance between price and a moving average.
This indicator includes options such as:
- % difference between the MAs to be considered coiled
- type and length of MAs
- background color to indicate when the MAs are coiled
- arrows to indicate if price is above or below the MAs when they become coiled
While coiling predicts an increased probability for volatility expansion, it does not necessarily predict the direction of expansion. However, the arrows which indicate whether price is above or below the moving average coil may increase the odds of a move in that direction. Bullish alignment of the moving averages (faster MAs above the slower MAs) may also increase the odds of a bullish break, while bearish alignment may increase the odds of a bearish break.
Note that mean reversion back to the MA coil is common after initial volatility expansion. This can present an entry opportunity for traders, as mean reversion may be followed by continuation in the direction of the initial break.
Experiment with different settings and timeframes to see how coiled MAs can help predict the onset of volatility.
BINANCE-BYBIT Cross Chart: Spot-Perpetual CorrelationName: "Binance-Bybit Cross Chart: Spot-Perpetual Correlation"
Category: Scalping, Trend Analysis
Timeframe: 1M, 5M, 30M, 1D (depending on the specific technique)
Technical analysis: This indicator facilitates a comparison between the price movements shown on the Binance spot chart and the Bybit perpetual chart, with the aim of discerning the correlation between the two charts and identifying the dominant market trends. It automatically generates the corresponding chart based on the ticker selected in the primary chart. When a Binance pair is selected in the main chart, the indicator replicates the Bybit perpetual chart for the same pair and timeframe, and vice versa, selecting the Bybit perpetual chart as the primary chart generates the Binance spot chart.
Suggested use: You can utilize this tool to conduct altcoin trading on Binance or Bybit, facilitating the comparison of price actions and real-time monitoring of trigger point sensitivity across both exchanges. We recommend prioritizing the Binance Spot chart in the main panel due to its typically longer historical data availability compared to Bybit.
The primary objective is to efficiently and automatically manage the following three aspects:
- Data history analysis for higher timeframes, leveraging the extensive historical data of the Binance spot market. Variations in indicators such as slow moving averages may arise due to differences in historical data between exchanges.
- Assessment of coin liquidity on both exchanges by observing candlestick consistency on smaller timeframes or the absence of gaps. In the crypto market, clean charts devoid of gaps indicate dominance and offer enhanced reliability.
- Identification of precise trigger point levels, including daily, previous day, or previous week highs and lows, which serve as sensitive areas for breakout or reversal operations.
All-Time High (ATH) and All-Time Low (ATL) levels may vary significantly across exchanges due to disparities in historical data series.
This tool empowers traders to make informed decisions by leveraging historical data, liquidity insights, and precise trigger point identification across Binance Spot and Bybit Perpetual market.
Configuration:
EMA length:
- EMA 1: Default 5, user configurable
- EMA 2: Default 10, user configurable
- EMA 3: Default 60, user configurable
- EMA 4: Default 223, user configurable
- Additional Average: Optional display of an additional average, such as a 20-period average.
Chart Elements:
- Session separator: Indicates the beginning of the current session (in blue)
- Background: Indicates an uptrend (60 > 223) with a green background and a downtrend (60 < 223) with a red background.
Instruments:
- EMA Daily: Shows daily averages on an intraday timeframe.
- EMA levels 1h - 30m: Shows the levels of the 1g-30m EMAs.
- EMA Levels Highest TF: Provides the option to select additional EMA levels from the major timeframes, customizable via the drop-down menu.
- "Hammer Detector: Marks hammers with a green triangle and inverted hammers with a red triangle on the chart
- "Azzeramento" signal on TF > 30m: Indicates a small candlestick on the EMA after a dump.
- "No Fomo" signal on TF < 30m: Indicates a hyperextended movement.
Trigger Points:
- Today's highs and lows: Shows the opening price of the day's candlestick, along with the day's highs and lows (high in purple, low in red, open in green).
- Yesterday's highs and lows: Displays the opening price of the daily candlestick, along with the previous day's highs and lows (high in yellow, low in red).
You can customize the colors in "Settings" > "Style".
It is best used with the Scalping The Bull indicator on the main panel.
Credits:
@tumiza999: for tests and suggestions.
Thanks for your attention, happy to support the TradingView community.
Fibonacci Adaptive Timeframe EMA (FAT EMA)The "Fibonacci Adaptive Timeframe EMA" is a sophisticated trading indicator designed for the TradingView platform, leveraging the power of Exponential Moving Averages (EMAs) determined by Fibonacci sequence lengths to provide traders with dynamic market insights. This indicator overlays directly on the price chart, offering a unique blend of trend analysis, smoothing techniques, and timeframe adaptability, making it an invaluable tool for traders looking to enhance their technical analysis strategy.
Key Features
1. Fibonacci-Based EMA Lengths: Utilizes the Fibonacci sequence to select EMA lengths, incorporating natural mathematical ratios believed to be significant in financial markets. The available lengths range from 1 to 987, allowing for detailed trend analysis over various periods.
2. Multiple Smoothing Methods: Offers the choice between several smoothing techniques, including Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA or RMA), Weighted Moving Average (WMA), and Volume Weighted Moving Average (VWMA). This versatility ensures that users can tailor the indicator to suit their analytical preferences.
3. Timeframe Adaptability: Features the ability to fetch and calculate EMAs from different timeframes, providing a multi-timeframe analysis within a single chart view. This adaptability gives traders a broader perspective on market trends, enabling more informed decision-making.
4. Dynamic Visualization Options: Traders can customize the display to suit their analysis needs, including toggling the visibility of Fibonacci EMA lines, EMA prices, and smoothed EMA lines. Additionally, forecast lines can be projected into the future, offering speculative insights based on current trends.
5. Ema Tail Visualization: An innovative feature allowing for the visualization of the 'tail' or the continuation of EMA lines, which can be particularly useful for identifying trend persistence or reversal points.
6. User-friendly Customization: Through a series of input options, traders can easily adjust the source data, Fibonacci lengths, smoothing method, and visual aspects such as line colors and transparency, ensuring a seamless integration into any trading strategy.
Application and Use Cases
The "Fibonacci Adaptive Timeframe EMA" indicator is designed for traders who appreciate the significance of Fibonacci numbers in market analysis and seek a flexible tool to analyze trends across different timeframes. Whether it's for scalping, day trading, or long-term investing, this indicator can provide valuable insights into price dynamics, trend strengths, and potential reversal points. Its adaptability makes it suitable for various asset classes, including stocks, forex, commodities, and cryptocurrencies.
Trend, Momentum, Volume Delta Ratings Emoji RatingsThis indicator provides a visual summary of three key market conditions - Trend, Momentum, and Volume Delta - to help traders quickly assess the current state of the market. The goal is to offer a concise, at-a-glance view of these important technical factors.
Trend (HMA): The indicator uses a Hull Moving Average (HMA) to assess the overall trend direction. If the current price is above the HMA, the trend is considered "Good" or bullish (represented by a 😀 emoji). If the price is below the HMA, the trend is "Bad" or bearish (🤮). If the price is equal to the HMA, the trend is considered "Neutral" (😐).
Momentum (ROC): The Rate of Change (ROC) is used to measure the momentum of the market. A positive ROC indicates "Good" or bullish momentum (😀), a negative ROC indicates "Bad" or bearish momentum (🤮), and a zero ROC is considered "Neutral" (😐).
Volume Delta: The indicator calculates the difference between the current trading volume and a simple moving average of the volume (Volume Delta). If the Volume Delta is above a user-defined threshold, it is considered "Good" or bullish (😀). If the Volume Delta is below the negative of the threshold, it is "Bad" or bearish (🤮). Values within the threshold are considered "Neutral" (😐).
The indicator displays these three ratings in a compact table format in the top-right corner of the chart. The table uses color-coding to quickly convey the overall market conditions - green for "Good", red for "Bad", and gray for "Neutral".
This indicator can be useful for traders who want a concise, at-a-glance view of the current market trend, momentum, and volume activity. By combining these three technical factors, traders can get a more well-rounded understanding of the market conditions and potentially identify opportunities or areas of concern more easily.
The user can customize the indicator by adjusting the lengths of the HMA, ROC, and Volume moving average, as well as the Volume Delta threshold. The colors used in the table can also be customized to suit the trader's preferences.
On Chart Reverse PMARPIntroducing the On Chart Reverse PMARP
Concept
The PMAR/PMARP is an indicator which calculates :
The ratio between a chosen source price and a user defined moving average ( Price Moving Average Ratio ).
The percentile of the PMAR over an adjustable lookback period ( Price Moving Average Ratio Percentile ).
Here I have 'reverse engineered' the PMAR / PMARP formulas to derive several functions.
These functions calculate the chart price at which the PMARP will cross a particular PMARP level.
I have employed those functions here to give the "crossover" price levels for :
Scale high level
High alert level
High test level
Mid-Line
Low test level
Low alert level
Scale low level
Knowing the price at which these various user defined PMARP levels will be crossed can be useful in setting price levels that trigger components of various strategies.
For example: A trader can use the reverse engineered upper high alert price level, to set a take profit limit order on a long trade, which was entered when PMARP was low.
This 'On Chart' RPMARP indicator displays these 'reverse engineered' price levels as plotted lines on the chart.
This allows the user to see directly on the chart the interplay between the various crossover levels and price action.
This allows for more intuitive Technical Analysis, and allows traders to precisely plan entries, exits and stops for their PMARP based trades.
It optionally plots the user defined moving average from which the PMARP is derived.
It also optionally plots the 'Reverse engineered' midline, test level lines, visual alert level lines, scale max. and min. level lines, and background alert signal bars.
Main Properties :
Price Source :- Choice of price values or external value from another indicator ( default *Close ).
PMAR Length :- User defined time period to be used in calculating the Moving Average for the Price Moving Average Ratio and the PMAR component of the PMARP ( default *21 ).
MA Type :- User defined type of Moving Average which creates the MA for the Price Moving Average Ratio and the PMAR component of the PMARP ( default *EMA ).
Checkbox and color selection box for the optionally plotted Moving Average line.
Price Moving Average Ratio Percentile Properties :
PMARP Length :- The lookback period to be used in calculating the Price Moving Average Ratio Percentile ( default *350 ).
PMARP Level Settings :
Scale High :- Scale high level ( Locked at 100 ).
Hi Alert :- High alert level ( default *99 ).
Hi Test :- High test level ( default *70 ).
Lid Line :- Mid line level ( Locked at 50 ).
Lo Test :- Low test level ( default *30 ).
Lo Alert :- Low alert level ( default *1 ).
Scale Low :- Scale low level ( Locked at 0 ).
Checkboxes and color selection boxes for each of the optionally plotted lines.
PMARP MA Settings :
Checkbox to optionally plot 'reverse engineered' PMARP MA line.
PMARP MA Length :- The time period to be used in calculating the signal Moving Average for the Line Plot ( default *20 ).
PMARP MA Type :- The type of Moving Average which creates the signal Moving Average for the Line Plot ( default *EMA ).
Color Type :- User choice from dropdown between "single" or "dual" line color ( default *dual ).
Single Color :- Color selection box.
Dual Color :- Color selection box. Note: Defines the color of the signal MA when the MA is falling in "dual" line coloring mode.
Signal Bar Settings :
Signal Bars Transparency :- Sets the transparency of the vertical signal bars ( default *70 ).
Checkboxes and color selection boxes for Upper/Lower alert signal bars.
RSI EMA WMA (hieuhn)Indicator: RSI & EMA & WMA (14-9-45)
This indicator, named "RSI & EMA & WMA", is a versatile tool designed to provide insights into market momentum and trend strength by combining multiple technical indicators.
The Relative Strength Index (RSI) is a popular momentum oscillator used to measure the speed and change of price movements. In this indicator, RSI is plotted alongside its Exponential Moving Average (EMA) and Weighted Moving Average (WMA). EMA and WMA are smoothing techniques applied to RSI to help identify trends more clearly.
Key features of this indicator include:
RSI: The main RSI line is plotted on the chart, offering insights into overbought and oversold conditions.
EMA of RSI: The Exponential Moving Average of RSI smooths out short-term fluctuations, aiding in trend identification.
WMA of RSI: The Weighted Moving Average of RSI gives more weight to recent data points, providing a faster response to price changes.
Additionally, this indicator marks specific RSI levels considered as bullish and bearish trends, helping traders identify potential entry or exit points based on market sentiment.
By combining these technical indicators, traders can gain a comprehensive understanding of market dynamics, helping them make more informed trading decisions.
Fibonacci Timeframe Adaptive EMAThe "Fibonacci Timeframe Adaptive EMA" is a sophisticated trading indicator designed for the TradingView platform, leveraging the power of Exponential Moving Averages (EMAs) determined by Fibonacci sequence lengths to provide traders with dynamic market insights. This indicator overlays directly on the price chart, offering a unique blend of trend analysis, smoothing techniques, and timeframe adaptability, making it an invaluable tool for traders looking to enhance their technical analysis strategy.
Key Features
1. Fibonacci-Based EMA Lengths: Utilizes the Fibonacci sequence to select EMA lengths, incorporating natural mathematical ratios believed to be significant in financial markets. The available lengths range from 1 to 987, allowing for detailed trend analysis over various periods.
2. Multiple Smoothing Methods: Offers the choice between several smoothing techniques, including Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA or RMA), Weighted Moving Average (WMA), and Volume Weighted Moving Average (VWMA). This versatility ensures that users can tailor the indicator to suit their analytical preferences.
3. Timeframe Adaptability: Features the ability to fetch and calculate EMAs from different timeframes, providing a multi-timeframe analysis within a single chart view. This adaptability gives traders a broader perspective on market trends, enabling more informed decision-making.
4. Dynamic Visualization Options: Traders can customize the display to suit their analysis needs, including toggling the visibility of Fibonacci EMA lines, EMA prices, and smoothed EMA lines. Additionally, forecast lines can be projected into the future, offering speculative insights based on current trends.
5. Ema Tail Visualization: An innovative feature allowing for the visualization of the 'tail' or the continuation of EMA lines, which can be particularly useful for identifying trend persistence or reversal points.
6. User-friendly Customization: Through a series of input options, traders can easily adjust the source data, Fibonacci lengths, smoothing method, and visual aspects such as line colors and transparency, ensuring a seamless integration into any trading strategy.
Application and Use Cases
The "Fibonacci Timeframe Adaptive EMA" indicator is designed for traders who appreciate the significance of Fibonacci numbers in market analysis and seek a flexible tool to analyze trends across different timeframes. Whether it's for scalping, day trading, or long-term investing, this indicator can provide valuable insights into price dynamics, trend strengths, and potential reversal points. Its adaptability makes it suitable for various asset classes, including stocks, forex, commodities, and cryptocurrencies.
Volatility Adjusted Weighted DEMA [BackQuant]Volatility Adjusted Weighted DEMA
The Volatility Adjusted Weighted Double Exponential Moving Average (VAWDEMA) by BackQuant is a sophisticated technical analysis tool designed for traders seeking to integrate volatility into their moving average calculations. This innovative indicator adjusts the weighting of the Double Exponential Moving Average (DEMA) according to recent volatility levels, offering a more dynamic and responsive measure of market trends.
Primarily, the single Moving average is very noisy, but can be used in the context of strategy development, where as the crossover, is best used in the context of defining a trading zone/ macro uptrend on higher timeframes.
Why Volatility Adjustment is Beneficial
Volatility is a fundamental aspect of financial markets, reflecting the intensity of price changes. A volatility adjustment in moving averages is beneficial because it allows the indicator to adapt more quickly during periods of high volatility, providing signals that are more aligned with the current market conditions. This makes the VAWDEMA a versatile tool for identifying trend strength and potential reversal points in more volatile markets.
Understanding DEMA and Its Advantages
DEMA is an indicator that aims to reduce the lag associated with traditional moving averages by applying a double smoothing process. The primary benefit of DEMA is its sensitivity and quicker response to price changes, making it an excellent tool for trend following and momentum trading. Incorporating DEMA into your analysis can help capture trends earlier than with simple moving averages.
The Power of Combining Volatility Adjustment with DEMA
By adjusting the weight of the DEMA based on volatility, the VAWDEMA becomes a powerful hybrid indicator. This combination leverages the quick responsiveness of DEMA while dynamically adjusting its sensitivity based on current market volatility. This results in a moving average that is both swift and adaptive, capable of providing more relevant signals for entering and exiting trades.
Core Logic Behind VAWDEMA
The core logic of the VAWDEMA involves calculating the DEMA for a specified period and then adjusting its weighting based on a volatility measure, such as the average true range (ATR) or standard deviation of price changes. This results in a weighted DEMA that reflects both the direction and the volatility of the market, offering insights into potential trend continuations or reversals.
Utilizing the Crossover in a Trading System
The VAWDEMA crossover occurs when two VAWDEMAs of different lengths cross, signaling potential bullish or bearish market conditions. In a trading system, a crossover can be used as a trigger for entry or exit points:
Bullish Signal: When a shorter-period VAWDEMA crosses above a longer-period VAWDEMA, it may indicate an uptrend, suggesting a potential entry point for a long position.
Bearish Signal: Conversely, when a shorter-period VAWDEMA crosses below a longer-period VAWDEMA, it might signal a downtrend, indicating a possible exit point or a short entry.
Incorporating VAWDEMA crossovers into a trading strategy can enhance decision-making by providing timely and adaptive signals that account for both trend direction and market volatility. Traders should combine these signals with other forms of analysis and risk management techniques to develop a well-rounded trading strategy.
Alert Conditions For Trading
alertcondition(vwdema>vwdema , title="VWDEMA Long", message="VWDEMA Long - {{ticker}} - {{interval}}")
alertcondition(vwdema<vwdema , title="VWDEMA Short", message="VWDEMA Short - {{ticker}} - {{interval}}")
alertcondition(ta.crossover(crossover, 0), title="VWDEMA Crossover Long", message="VWDEMA Crossover Long - {{ticker}} - {{interval}}")
alertcondition(ta.crossunder(crossover, 0), title="VWDEMA Crossover Short", message="VWDEMA Crossover Short - {{ticker}} - {{interval}}")
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
EMA Cross Dashboard | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Exponential Moving Average (EMA) Cross Dashboard! This dashboard let's you select a source for the calculation of the EMA of it, then let's you enter 2 lengths for up to 5 timeframes, plotting their crosses in the chart.
Features of the new EMA Cross Dashboard :
Shows EMA Crosses Across Up To 5 Different Timeframes.
Select Any Source, Including Other Indicators.
Customizable Dashboard.
📌 HOW DOES IT WORK ?
EMA is a widely used indicator within trading community, it is similar to a Simple Moving Average (SMA) but places more weight on recent prices, making it more reactive to current trends. Crosses of EMA lines can be helpful to determine strong bullish & bearish movements of an asset. This indicator shows finds crosses across 5 different timeframes in a dashboard and plots them in your chart for ease of use.
🚩UNIQUENESS
This dashboard cuts through the hassle of manual EMA cross calculations and plotting. It offers flexibility by allowing various data sources (even custom indicators) and customization through enabling / disabling individual timeframes. The clear visualization lets you see EMA crosses efficiently.
⚙️SETTINGS
1. Timeframes
You can set up to 5 timeframes & 2 lenghts to detect crosses for each timeframe here. You can also enable / disable them.
2. General Configuration
EMA Source -> You can select the source for the calculation of the EMA here. You can select sources from other indicators as well as more general sources like close, high and low price.
SMA Cross Dashboard | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Simple Moving Average (SMA) Cross Dashboard! This dashboard let's you select a source for the calculation of the SMA of it, then let's you enter 2 lengths for up to 5 timeframes, plotting their crosses in the chart.
Features of the new SMA Cross Dashboard :
Shows SMA Crosses Across Up To 5 Different Timeframes.
Select Any Source, Including Other Indicators.
Customizable Dashboard.
📌 HOW DOES IT WORK ?
SMA is a widely used indicator within trading community, it simply works by taking the mathematical average of a source by desired length. Crosses of SMA lines can be helpful to determine strong bullish & bearish movements of an asset. This indicator shows finds crosses across 5 different timeframes in a dashboard and plots them in your chart for ease of use.
🚩UNIQUENESS
This dashboard cuts through the hassle of manual SMA cross calculations and plotting. It offers flexibility by allowing various data sources (even custom indicators) and customization through enabling / disabling individual timeframes. The clear visualization lets you see SMA crosses efficiently.
⚙️SETTINGS
1. Timeframes
You can set up to 5 timeframes & 2 lenghts to detect crosses for each timeframe here. You can also enable / disable them.
2. General Configuration
SMA Source -> You can select the source for the calculation of the SMA here. You can select sources from other indicators as well as more general sources like close, high and low price.
Range Finder [UAlgo]🔶 Description:
The "Range Finder " indicator aims at identifying and visualizing price ranges within a specified number of candles. By utilizing the Average True Range (ATR) indicator and Simple Moving Average (SMA), it detects potential breakout conditions and tracks consecutive candles that remain within the breakout range. This indicator offers flexibility by allowing users to customize settings such as range length, method for determining range breaks (based on either candle close or wick), and visualization options for displaying range breaks on the chart.
🔶 Key Features
Identifying Ranges: The Range Finder automatically adapts to the market by continuously evaluating the Average True Range (ATR) and its Simple Moving Average (SMA). This helps in dynamically adjusting the range based on market volatility.
Range Length: Users can specify the number of candles to be used for constructing the range via the "Range Length" input setting. This allows for customization based on trading strategies and preferences.
Range Break Method: The indicator offers the flexibility to choose between two methods for identifying range breaks. Users can select between "Close" or "Wick" based on their preference for using the closing price or the highs and lows (including wicks) of candles for defining the breakout.
Show Range Breaks: This option enables visual representation of range breaks on the chart. When activated, labels with the letter "B" will appear at the breakout point, colored according to the breakout direction (upward breakouts in the chosen up range color and downward breakouts in the chosen down range color).
Range Color Customization: The indicator provides the ability to personalize the visual appearance of the range by selecting preferred colors for ranges indicating potential upward and downward breakouts.
🔶 Disclaimer
It's important to understand that the Range Finder indicator is intended for informational purposes only and should not be solely relied upon for making trading decisions. Trading financial instruments involves inherent risks, and past performance is not necessarily indicative of future results.
DEMA RSI Overlay [BackQuant]DEMA RSI Overlay
PLEASE Read the following, knowing what an indicator does at its core before adding it into a system is pivotal. The core concepts can allow you to include it in a logical and sound manner.
Anyways,
BackQuant's new trading indicator that blends the Double Exponential Moving Average (DEMA) with the Relative Strength Index (RSI) to create a unique overlay on the trading chart. This combination is not arbitrary; both the DEMA and RSI are revered for their distinct advantages in trading strategy development. Let's delve into the core components of this script, the rationale behind choosing DEMA and RSI, the logic of long and short signals, and its practical trading applications.
Understanding DEMA
DEMA is an enhanced version of the conventional exponential moving average that aims to reduce the lag inherent in traditional averages. It does this by applying more weight to recent prices. The reduction in lag makes DEMA an excellent tool for tracking price trends more closely. In the context of this script, DEMA serves as the foundation for the RSI calculation, offering a smoother and more responsive signal line that can provide clearer trend indications.
Why DEMA?
DEMA is chosen for its responsiveness to price changes. This characteristic is particularly beneficial in fast-moving markets where entering and exiting positions quickly is crucial. By using DEMA as the price source, the script ensures that the signals generated are timely and reflective of the current market conditions, reducing the risk of entering or exiting a trade based on outdated information.
Integrating RSI
The RSI, a momentum oscillator, measures the speed and change of price movements. It oscillates between zero and 100 and is typically used to identify overbought or oversold conditions. In this script, the RSI is calculated based on DEMA, which means it inherits the responsiveness of DEMA, allowing traders to spot potential reversals or continuation signals sooner.
Why RSI?
Incorporating RSI offers a measure of price momentum and market conditions relative to past performance. By setting thresholds for long (buy) and short (sell) signals, the script uses RSI to identify potential turning points in the market, providing traders with strategic entry and exit points.
Calculating Long and Short Signals
Long Signals : These are generated when the RSI of the DEMA crosses above the longThreshold (set at 70 by default) and the closing price is not above the upper volatility band. This suggests that the asset is gaining upward momentum while not being excessively overbought, presenting a potentially favorable buying opportunity.
Short Signals : Generated when the RSI of the DEMA falls below the shortThreshold (set at 55 by default). This indicates that the asset may be losing momentum or entering a downtrend, signaling a possible selling or shorting opportunity.
Logical Soundness
The logic of combining DEMA with RSI for generating trade signals is sound for several reasons:
Timeliness : The use of DEMA ensures that the price source for RSI calculation is up-to-date, making the momentum signals more relevant.
Balance : By setting distinct thresholds for long and short signals, the script balances sensitivity and specificity, aiming to minimize false signals while capturing genuine market movements.
Adaptability : The inclusion of user inputs for periods and thresholds allows traders to customize the indicator to fit various trading styles and timeframes.
Trading Use-Cases
This DEMA RSI Overlay indicator is versatile and can be applied across different markets and timeframes. Its primary use-cases include:
Trend Following: Traders can use it to identify the start of a new trend or the continuation of an existing trend.
Swing Trading: The indicator's sensitivity to price changes makes it ideal for swing traders looking to capitalize on short to medium-term price movements.
Risk Management: By providing clear long and short signals, it helps traders manage their positions more effectively, potentially reducing the risk of significant losses.
Final Note
We have also decided to add in the option of standard deviation bands, calculated on the DEMA, this can be used as a point of confluence rendering trading ranges. Expanding when volatility is high and compressing when it is low.
For example:
This provides the user with a 1, 2, 3 standard deviation band of the DEMA.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Multi-Timeframe SMA Crossover Indicator## Description of the "Multi-Timeframe SMA Crossover Indicator" script
### Introduction:
The "Multi-Timeframe SMA Crossover Indicator" script is a technical indicator created in Pine Script for the TradingView platform. It is a technical indicator that helps traders identify signals of simple moving average (SMA) crossovers on different timeframes.
### Features:
1. **Multi-Timeframe Analysis:** The script covers various timeframes, allowing traders to analyze SMA crossover signals on different time scales.
2. **SMA Crossover Signals:** The script identifies moments when the crossover of 20 and 40 simple moving averages occurs on timeframes ranging from 1 minute to 120 minutes.
3. **Visualization:** It visualizes SMA crossover signals on the chart, making it easy for traders to identify trend reversal points.
### How to Use:
1. **Interpreting Signals:** A positive signal (green) indicates that the SMA crossover suggests a potential uptrend, while a negative signal (red) suggests a potential downtrend.
2. **Multiple Confirmation:** Traders can seek trend confirmation by analyzing signals on different timeframes. Confirming signals on multiple timeframes can increase confidence in the trade.
### Application:
The "Multi-Timeframe SMA Crossover Indicator" script can be used as a supplementary tool in making investment decisions in financial markets, especially when analyzing trends and identifying entry or exit points.
### Notes:
1. The script is based on simple moving averages (SMA), which can be useful for traders using trend analysis strategies.
2. Investors should use other technical analysis indicators and tools in conjunction with this indicator to obtain a more comprehensive market analysis.
### Conclusion:
The "Multi-Timeframe SMA Crossover Indicator" script is a useful tool for traders who want to analyze trend changes on different timeframes. By using this tool, investors can make better-informed investment decisions in financial markets.
