Adaptive EMA with ATR and Standard Deviation [QuantAlgo]Adaptive EMA with ATR and Standard Deviation by QuantAlgo 📈✨
Introducing the Adaptive EMA with ATR and Standard Deviation , a comprehensive trend-following indicator designed to combine the smoothness of an Exponential Moving Average (EMA) with the volatility adjustments of Average True Range (ATR) and Standard Deviation. This synergy allows traders and investors to better identify market trends while accounting for volatility, delivering clearer signals in both trending and volatile market conditions. This indicator is suitable for traders and investors seeking to balance trend detection and volatility management, offering a robust and adaptable approach across various asset classes and timeframes.
💫 Core Concept and Innovation
The Adaptive EMA with ATR and Standard Deviation brings together the trend-smoothing properties of the EMA and the volatility sensitivity of ATR and Standard Deviation. By using the EMA to track price movements over time, the indicator smooths out minor fluctuations while still providing valuable insights into overall market direction. However, market volatility can sometimes distort simple moving averages, so the ATR and Standard Deviation components dynamically adjust the trend signals, offering more nuanced insights into trend strength and reversals. This combination equips traders with a powerful tool to navigate unpredictable markets while minimizing false signals.
📊 Technical Breakdown and Calculations
The Adaptive EMA with ATR and Standard Deviation relies on three key technical components:
1. Exponential Moving Average (EMA): The EMA forms the base of the trend detection. Unlike a Simple Moving Average (SMA), the EMA gives more weight to recent price changes, allowing it to react more quickly to new data. Users can adjust the length of the EMA to make it more or less responsive to price movements.
2. Standard Deviation Bands: These bands are calculated from the standard deviation of the EMA and represent dynamic volatility thresholds. The upper and lower bands expand or contract based on recent price volatility, providing more accurate signals in both calm and volatile markets.
3. ATR-Based Volatility Filter: The Average True Range (ATR) is used to measure market volatility over a user-defined period. It helps refine the trend signals by filtering out false positives caused by minor price swings. The ATR filter ensures that the indicator only signals significant market movements.
⚙️ Step-by-Step Calculation:
1. EMA Calculation: First, the indicator calculates the EMA over a specified period based on the chosen price source (e.g., close, high, low).
2. Standard Deviation Bands: Then, it computes the standard deviation of the EMA and applies a multiplier to create upper and lower bands around the EMA. These bands adjust dynamically with the level of market volatility.
3. ATR Filtering: In addition to the standard deviation bands, the ATR is applied as a secondary filter to help refine the trend signals. This step helps eliminate signals generated by short-term price spikes or corrections, ensuring that the signals are more reliable.
4. Trend Detection: When the price crosses above the upper band, a bullish trend is identified, while a move below the lower band signals a bearish trend. The system accounts for both the standard deviation and ATR bands to generate these signals.
✅ Customizable Inputs and Features
The Adaptive EMA with ATR and Standard Deviation provides a range of customizable options to fit various trading/investing styles:
📈 Trend Settings:
1. Price Source: Choose the price type (e.g., close, high, low) to base the EMA calculation on, influencing how the trend is tracked.
2. EMA Length: Adjust the length to control how quickly the EMA reacts to price changes. A shorter length provides a more responsive EMA, while a longer period smooths out short-term fluctuations.
🌊 Volatility Controls:
1. Standard Deviation Multiplier: This parameter controls the sensitivity of the trend detection by adjusting the distance between the upper and lower bands from the EMA.
2. TR Length and Multiplier: Fine-tune the ATR settings to control how volatility is filtered, adjusting the indicator’s responsiveness during high or low volatility phases.
🎨 Visualization and Alerts:
1. Bar Coloring: Select different colors for uptrends and downtrends, providing a clear visual cue when trends change.
2. Alerts: Set up alerts to notify you when the price crosses the upper or lower bands, signaling a potential long or short trend shift. Alerts can help you stay informed without constant chart monitoring.
📈 Practical Applications
The Adaptive EMA with ATR and Standard Deviation is ideal for traders and investors looking to balance trend-following strategies with volatility management. Key uses include:
Detecting Trend Reversals: The dynamic bands help identify when the market shifts direction, providing clear signals when a trend reversal is likely.
Filtering Market Noise: By applying both Standard Deviation and ATR filtering, the indicator helps reduce false signals during periods of heightened volatility.
Volatility-Based Risk Management: The adaptability of the bands ensures that traders can manage risk more effectively by responding to shifts in volatility while keeping focus on long-term trends.
⭐️ Comprehensive Summary
The Adaptive EMA with ATR and Standard Deviation is a highly customizable indicator that provides traders with clearer signals for trend detection and volatility management. By dynamically adjusting its calculations based on market conditions, it offers a powerful tool for navigating both trending and volatile markets. Whether you're looking to detect early trend reversals or avoid false signals during periods of high volatility, this indicator gives you the flexibility and accuracy to improve your trading and investing strategies.
Note: The Adaptive EMA with ATR and Standard Deviation is designed to enhance your market analysis but should not be relied upon as the sole basis for trading or investing decisions. Always combine it with other analytical tools and practices. No statements or signals from this indicator constitute financial advice. Past performance is not indicative of future results.
Cerca negli script per "Exponential Moving Average"
Trend Fusion: ADX&EMA+Ichimoku (Custom)SAME AS THE ORIGINAL (WITHOUT BOTTOM PART)
Trend Fusion: ADX & EMA+Ichimoku is an innovative indicator designed to provide traders with comprehensive insights into market trends. Combining the power of the Average Directional Index (ADX) with Exponential Moving Averages (EMA) and the Ichimoku Cloud, this indicator offers a sophisticated approach to trend analysis.
This indicator stands out for its unique integration of multiple trend-following indicators, offering traders a holistic view of market dynamics. Unlike traditional trend indicators that focus solely on price movements, Trend Fusion incorporates the ADX, EMA, and Ichimoku Cloud to provide a more nuanced understanding of trend strength and direction. By combining these indicators, traders can make more informed decisions and enhance their trading strategies.
How it works:
Trend Fusion generates buy and sell signals based on the convergence of these indicators. A combination of strong ADX readings, EMA crossovers, and alignment with the Ichimoku Cloud confirms trend direction and provides entry and exit points for traders.
Average Directional Index (ADX): Measures the strength of the prevailing trend by analyzing price movements. A rising ADX indicates a strengthening trend, while a falling ADX suggests weakening momentum.
Exponential Moving Averages (EMA): Detects potential trend reversals through crossover signals. A bullish crossover (fast EMA crossing above slow EMA) suggests an uptrend, while a bearish crossover indicates a downtrend.
Ichimoku Cloud: Provides support and resistance levels along with trend direction. Price movements above the cloud indicate bullish sentiment, while movements below the cloud suggest bearish sentiment.
How to useColour codes:
Green Candles: Represent a strong uptrend, indicating robust buying momentum. The intensity of green color deepens with increasing trend strength.
Red Candles: Indicate a strong downtrend, signaling significant selling pressure in the market. The intensity of red color deepens with increasing trend strength.
Yellow Candles: Suggest a weak trend, characterized by indecision and lack of clear direction. The intensity of yellow color varies based on the strength of the trend, with lighter shades indicating weaker trends and darker shades suggesting slightly stronger trends.
Trend Strength: Monitor the ADX to gauge the strength of the prevailing trend. Higher ADX values indicate stronger trends, while lower values suggest weaker trends.
Trend Direction: Confirm trend direction using EMA crossovers and Ichimoku Cloud signals. Look for bullish crossovers and price movements above the cloud for uptrends, and bearish crossovers and movements below the cloud for downtrends.
Entry and Exit Signals: Enter trades when all components align, signaling a strong trend. Use EMA crossovers and cloud confirmations to identify potential entry points, and consider exiting trades when these signals reverse.
The ADX calculation and signal logic are based on the ADX script by PineCoders, with modifications to integrate it into this indicator.
The EMA crossover logic is adapted from the GDAX EMA Cross script by stefano98.
The Ichimoku Cloud calculation and plotting are adapted from the Ichimoku Cloud script by lonesometheblue.
Trading involves risk, and past performance is not indicative of future results. It is recommended to use this indicator alongside other technical analysis tools and risk management strategies.
Double CCI Confirmed Hull Moving Average Reversal StrategyOverview
The Double CCI Confirmed Hull Moving Average Strategy utilizes hull moving average (HMA) in conjunction with two commodity channel index (CCI) indicators: the slow and fast to increase the probability of entering when the short and mid-term uptrend confirmed. The main idea is to wait until the price breaks the HMA while both CCI are showing that the uptrend has likely been already started. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Double trade setup confirmation: Strategy utilizes two different period CCI indicators to confirm the breakouts of HMA.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Short-term period CCI indicator shall be above 0.
Long-term period CCI indicator shall be above 0.
Price shall cross the HMA and candle close above it with the same candle
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 25, used for calculation short term period CCI
CCI Slow Length (by default = 50, used for calculation long term period CCI)
Hull MA Length (by default = 34, period of HMA, which shall be broken to open trade)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI and HMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator used in trading to measure a security's price relative to its average price over a given period. Developed by Donald Lambert in 1980, the CCI is primarily used to identify cyclical trends in a security, helping traders to spot potential buying or selling opportunities.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Hull Moving Average (HMA) is a type of moving average that was developed by Alan Hull to improve upon the traditional moving averages by reducing lag while maintaining smoothness. The goal of the HMA is to create an indicator that is both quick to respond to price changes and less prone to whipsaws (false signals).
How the Hull Moving Average is Calculated?
The Hull Moving Average is calculated using the following steps:
Weighted Moving Average (WMA): The HMA starts by calculating the Weighted Moving Average (WMA) of the price data over a period square root of n (sqrt(n))
Speed Adjustment: A WMA is then calculated for half of the period n/2, and this is multiplied by 2 to give more weight to recent prices.
Lag Reduction: The WMA of the full period n is subtracted from the doubled n/2 WMA.
Final Smoothing: To smooth the result and reduce noise, a WMA is calculated for the square root of the period n.
The formula can be represented as:
HMA(n) = WMA(WMA(n/2) × 2 − WMA(n), sqrt(n))
The Weighted Moving Average (WMA) is a type of moving average that gives more weight to recent data points, making it more responsive to recent price changes than a Simple Moving Average (SMA). In a WMA, each data point within the selected period is multiplied by a weight, with the most recent data receiving the highest weight. The sum of these weighted values is then divided by the sum of the weights to produce the WMA.
This strategy leverages HMA of user given period as a critical level which shall be broken to say that probability of trend change to the upside increased. HMA reacts faster than EMA or SMA to the price change, that’s why it increases chances to enter new trade earlier. Long-term period CCI helps to have an approximation of mid-term trend. If it’s above 0 the probability of uptrend increases. Short-period CCI allows to have an approximation of short-term trend reversal from down to uptrend. This approach increases chances to have a long trade setup in the direction of mid-term trend when the short-term trend starts to reverse.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses HMA to enter the trade, but for trailing it leverages EMA. It’s used because EMA has no such fast reaction to price move which increases probability not to be stopped out from any significant uptrend move.
Backtest Results
Operating window: Date range of backtests is 2022.07.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 100%
Maximum Single Position Loss: -4.67%
Maximum Single Profit: +19.66%
Net Profit: +14897.94 USDT (+148.98%)
Total Trades: 104 (36.54% win rate)
Profit Factor: 2.312
Maximum Accumulated Loss: 1302.66 USDT (-9.58%)
Average Profit per Trade: 143.25 USDT (+0.96%)
Average Trade Duration: 34 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
GMMA Toolkit [QuantVue]The GMMA Toolkit is designed to leverage the principles of the Guppy Multiple Moving Average (GMMA). This indicator is equipped with multiple features to help traders identify trends, reversals, and periods of market compression.
The Guppy Multiple Moving Average (GMMA) is a technical analysis tool developed by Australian trader and author Daryl Guppy in the late 1990s.
It utilizes two sets of Exponential Moving Averages (EMAs) to capture both short-term and long-term market trends. The short-term EMAs represent the activity of traders, while the long-term EMAs reflect the behavior of investors.
By analyzing the interaction between these two groups of EMAs, traders can identify the strength and direction of trends, as well as potential reversals.
Due to the nature of GMMA, charts can become cluttered with numerous lines, making analysis challenging.
However, this indicator simplifies visualization by using clouds to represent the short-term and long-term EMA groups, determined by filling the area between the maximum and minimum EMAs in each group.
The GMMA Toolkit goes a step further and includes an oscillator that measures the difference between the average short-term and long-term EMAs, providing a clear visual representation of trend strength and direction.
The farther the oscillator is from the 0 level, the stronger the trend. It is plotted on a separate panel with values above zero indicating bullish conditions and values below zero indicating bearish conditions.
The inclusion of the oscillator in the GMMA Toolkit allows traders to identify earlier buy and sell signals based on the GMMA oscillator crossing the zero line compared to traditional crossover methods.
Lastly, the GMMA Toolkit features compression dots that indicate periods of market consolidation.
By measuring the spread between the maximum and minimum EMAs within both short-term and long-term groups, the indicator identifies when these spreads are significantly narrower than average by comparing the current spread to the average spread over a lookback period.
This visual cue helps traders anticipate potential breakout or breakdown scenarios, enhancing their ability to react to imminent trend changes.
By simplifying the visualization of the Guppy Multiple Moving Averages with clouds, providing earlier buy and sell signals through the oscillator, and highlighting periods of market consolidation with compression dots, this toolkit offers traders insightful tools for navigating market trends and potential reversals.
Give this indicator a BOOST and COMMENT your thoughts below!
We hope you enjoy.
Cheers!
[EVI]EMA with Volume LevelsThe " EMA with Volume Levels" script calculates the Exponential Moving Average (EMA) of the closing prices over a specified period and dynamically changes the color of the EMA based on volume levels. This indicator helps traders easily identify the current volume conditions. As the volume increases or decreases, the color of the EMA changes, providing a visual cue that can assist in making better trading decisions.
Features
This script offers the following features:
EMA Calculation: Calculates the Exponential Moving Average of the closing prices over the user-defined period (default is 360).
Volume Threshold Calculation: Computes the Simple Moving Average (SMA) and standard deviation of the volume over the user-defined period (default is 500), classifying the volume levels into extreme, high, medium, and low.
Dynamic EMA Color: Changes the color of the EMA dynamically based on volume levels, displaying it visually on the chart.
Chart Interpretation
EMA Color and Volume:
If the EMA line is red, it indicates very high volume.
If the EMA line is green, it indicates high volume.
If the EMA line is light green, it indicates medium volume.
If the EMA line is gray, it indicates low volume.
If the EMA line is dark gray, it indicates very low volume.
Cross Analysis:
When the EMA line and the candles are about to cross, and the volume is high (causing the EMA line to turn red), the candles are more likely to break through the 360-day EMA line.
Conversely, if the volume is low and the EMA line turns dark, the EMA line will likely act as a resistance or support level, increasing the likelihood of a bounce.
Additional Indicator:
Using the 20-day moving average along with this script can be beneficial. Combining these two moving averages can provide a more comprehensive view of market volatility.
Notes
Clean Chart: Ensure your chart is clean when using this script. Avoid including other scripts or unnecessary elements.
Additional Explanation: If further explanation is needed on how to use or understand the script, you can use drawings or images on the chart to provide additional context.
Enhanced Forex IndicatorDescription of the "Enhanced Forex Indicator"
The "Enhanced Forex Indicator" is designed for traders who want a comprehensive technical analysis tool on the TradingView platform. This script integrates Exponential Moving Averages (EMAs), support and resistance zones, and candlestick pattern recognition to provide actionable trading signals, particularly useful for Forex and other financial markets. The script is suitable for intraday trading and swing trading.
Components of the Indicator
Exponential Moving Averages (EMAs):
Short EMA (Blue Line): Faster responding average, good for identifying recent trend changes.
Long EMA (Red Line): Slower moving average, helps in confirming longer-term trends.
Support and Resistance Zones:
Resistance Zone (Red): Area where potential selling pressure could overcome buying pressure, halting price increases temporarily or reversing them.
Support Zone (Green): Area where potential buying pressure could overcome selling pressure, supporting prices and preventing them from falling further.
Candlestick Patterns:
Bullish Engulfing Pattern (Green Triangle Up 'BE'): Suggests a potential upward reversal or start of a bullish trend.
Bearish Engulfing Pattern (Red Triangle Down 'BE'): Indicates a potential downward reversal or start of a bearish trend.
Buy/Sell Signals:
Buy Signal (Green Label 'BUY'): Triggered when the price is above both EMAs and a bullish engulfing pattern is detected.
Sell Signal (Red Label 'SELL'): Triggered when the price is below both EMAs and a bearish engulfing pattern is detected.
Trading Setup:
Entry: Consider entering a buy position when the 'BUY' signal appears, indicating bullish conditions. Enter a sell position when the 'SELL' signal appears, indicating bearish conditions.
Exit: Look for closing signals opposite your entry or use predefined take profit and stop loss levels. For instance, exit a buy position on a 'SELL' signal or when the price drops below the support zone.
Risk Management:
Set stop losses just below the support zone for buy orders and above the resistance zone for sell orders to protect against significant losses.
Adjust position sizes according to your risk tolerance and account balance.
Considerations:
Use this indicator in conjunction with other analysis tools and fundamental data to confirm signals and strengthen your trading strategy.
Periodically backtest the strategy based on this indicator to ensure its effectiveness in current market conditions.
Optimization:
Adjust the lengths of the EMAs and the buffer size of the support and resistance zones to better fit the asset's volatility and your trading timeframe.
Trend Fusion: ADX&EMA+IchimokuTrend Fusion: ADX & EMA+Ichimoku is an innovative indicator designed to provide traders with comprehensive insights into market trends. Combining the power of the Average Directional Index (ADX) with Exponential Moving Averages (EMA) and the Ichimoku Cloud, this indicator offers a sophisticated approach to trend analysis.
This indicator stands out for its unique integration of multiple trend-following indicators, offering traders a holistic view of market dynamics. Unlike traditional trend indicators that focus solely on price movements, Trend Fusion incorporates the ADX, EMA, and Ichimoku Cloud to provide a more nuanced understanding of trend strength and direction. By combining these indicators, traders can make more informed decisions and enhance their trading strategies.
How it works:
Trend Fusion generates buy and sell signals based on the convergence of these indicators. A combination of strong ADX readings, EMA crossovers, and alignment with the Ichimoku Cloud confirms trend direction and provides entry and exit points for traders.
Average Directional Index (ADX): Measures the strength of the prevailing trend by analyzing price movements. A rising ADX indicates a strengthening trend, while a falling ADX suggests weakening momentum.
Exponential Moving Averages (EMA): Detects potential trend reversals through crossover signals. A bullish crossover (fast EMA crossing above slow EMA) suggests an uptrend, while a bearish crossover indicates a downtrend.
Ichimoku Cloud: Provides support and resistance levels along with trend direction. Price movements above the cloud indicate bullish sentiment, while movements below the cloud suggest bearish sentiment.
How to use
Colour codes:
Green Candles: Represent a strong uptrend, indicating robust buying momentum. The intensity of green color deepens with increasing trend strength.
Red Candles: Indicate a strong downtrend, signaling significant selling pressure in the market. The intensity of red color deepens with increasing trend strength.
Yellow Candles: Suggest a weak trend, characterized by indecision and lack of clear direction. The intensity of yellow color varies based on the strength of the trend, with lighter shades indicating weaker trends and darker shades suggesting slightly stronger trends.
Trend Strength: Monitor the ADX to gauge the strength of the prevailing trend. Higher ADX values indicate stronger trends, while lower values suggest weaker trends.
Trend Direction: Confirm trend direction using EMA crossovers and Ichimoku Cloud signals. Look for bullish crossovers and price movements above the cloud for uptrends, and bearish crossovers and movements below the cloud for downtrends.
Entry and Exit Signals: Enter trades when all components align, signaling a strong trend. Use EMA crossovers and cloud confirmations to identify potential entry points, and consider exiting trades when these signals reverse.
The ADX calculation and signal logic are based on the ADX script by PineCoders, with modifications to integrate it into this indicator.
The EMA crossover logic is adapted from the GDAX EMA Cross script by stefano98.
The Ichimoku Cloud calculation and plotting are adapted from the Ichimoku Cloud script by lonesometheblue.
Trading involves risk, and past performance is not indicative of future results. It is recommended to use this indicator alongside other technical analysis tools and risk management strategies.
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.
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.
Fine-tune Inputs: Fourier Smoothed Volume zone oscillator WFSVZ0Use this Strategy to Fine-tune inputs for the (W&)FSVZ0 Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Wavelet & Fourier Smoothed Volume Zone Oscillator (W&)FSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the Discrete Fourier Transform . Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Wavalet and Fourier aproximation with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
When I ndicator/Strategy returns 0 or natural trend , Strategy Closes All it's positions.
ORIGINALITY & USFULLNESS:
Personal combination of Fourier and Wavalet aproximation of a price which results in less noise Volume Zone Oscillator.
The Wavelet Transform is a powerful mathematical tool for signal analysis, particularly effective in analyzing signals with varying frequency or non-stationary characteristics. It dissects a signal into wavelets, small waves with varying frequency and limited duration, providing a multi-resolution analysis. This approach captures both frequency and location information, making it especially useful for detecting changes or anomalies in complex signals.
The Discrete Fourier Transform (DFT) is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
In the next Image you can see that trend is negative on 4h, negative on 12h and positive on 1D. That means trend is negative.
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Wavelet approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Fourier Transform (FFT) , the innovative Double Discrete Fourier Transform (DTF32) and Wavelet soothed Fourier soothed price series to suit your analytical needs.
Image of Wavelet transform with FAST settings, Double Fourier transform with FAST settings. Improved noice reduction with SLOW settings, and standard FSVZO with SLOW settings:
Fast setting are setting by default:
VZO length = 2
NoiceR max Length = 2
Slow settings are:
VZO length = 5 or 7
NoiceR max Length = 8
As you can see fast setting are more volatile. I suggest averaging fast setting on 4h 12h 1d 2d 3d 4d W and M Timeframe to get a clear view on market trend.
What if I want long only when VZO is rising and above 15 not 0?
You have set Setting VzoDifference to 15. That reduces the number of trend changes.
Example of W&FSVZO with VzoDifference 15 than 0:
VZO crossed 0 line but not 15 line and that's why Indicator returns 0 in one case an 1 in another.
What is Smooth length setting?
A way of calculating Bullish or Bearish (W&)FSVZO .
If smooth length is 2 the trend is rising if:
rising = VZO > ta.ema(VZO, 2)
Meaning that we check if VZO is higher that exponential average of the last 2 elements.
If smooth length is 1 the trend is rising if:
rising = VZO_ > VZO_
Use this Strategy to fine-tune inputs for the (W&)FSVZO Indicator.
(Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data)
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame . When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame . I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
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.
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
Wavelet & Fourier Smoothed Volume zone oscillator (W&)FSVZO Indicator id:
USER;e7a774913c1242c3b1354334a8ea0f3c
(only relevant to those that use API requests)
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Wavelet & Fourier Smoothed Volume Zone Oscillator (W&)FSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the Discrete Fourier Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Wavalet and Fourier aproximation with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in natural trend.
ORIGINALITY & USFULLNESS:
Personal combination of Fourier and Wavalet aproximation of a price which results in less noise Volume Zone Oscillator.
The Wavelet Transform is a powerful mathematical tool for signal analysis, particularly effective in analyzing signals with varying frequency or non-stationary characteristics. It dissects a signal into wavelets, small waves with varying frequency and limited duration, providing a multi-resolution analysis. This approach captures both frequency and location information, making it especially useful for detecting changes or anomalies in complex signals.
The Discrete Fourier Transform (DFT) is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
In the next Image you can see that trend is positive on 4h, neutral on 12h and positive on 1D. That means trend is positive.
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Wavelet approximation of a close price are taken from aprox library.
Key Features:
You can tailor the indicator to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Fourier Transform (FFT), the innovative Double Discrete Fourier Transform (DTF32) and Wavelet soothed Fourier soothed price series to suit your analytical needs.
Image of Wavelet transform with FAST settings, Double Fourier transform with FAST settings. Improved noice reduction with SLOW settings, and standard FSVZO with SLOW settings:
Fast setting are setting by default:
VZO length = 2
NoiceR max Length = 2
Slow settings are:
VZO length = 5 or 7
NoiceR max Length = 8
As you can see fast setting are more volatile. I suggest averaging fast setting on 4h 12h 1d 2d 3d 4d W and M Timeframe to get a clear view on market trend.
What if I want long only when VZO is rising and above 15 not 0?
You have set Setting VzoDifference to 15. That reduces the number of trend changes.
Example of W&FSVZO with VzoDifference 15 than 0:
VZO crossed 0 line but not 15 line and that's why Indicator returns 0 in one case an 1 in another.
What is Smooth length setting?
A way of calculating Bullish or Bearish FSVZO.
If smooth length is 2 the trend is rising if:
rising = VZO > ta.ema(VZO, 2)
Meaning that we check if VZO is higher that exponential average of the last 2 elements.
If smooth length is 1 the trend is rising if:
rising = VZO_ > VZO_
Rising is boolean value, meaning TRUE if rising and FALSE if falling.
Mathematical equations presented in Pinescript:
Fourier of the real (x axis) discrete:
x_0 = array.get(x, 0) + array.get(x, 1) + array.get(x, 2)
x_1 = array.get(x, 0) + array.get(x, 1) * math.cos( -2 * math.pi * _dir / 3 ) - array.get(y, 1) * math.sin( -2 * math.pi * _dir / 3 ) + array.get(x, 2) * math.cos( -4 * math.pi * _dir / 3 ) - array.get(y, 2) * math.sin( -4 * math.pi * _dir / 3 )
x_2 = array.get(x, 0) + array.get(x, 1) * math.cos( -4 * math.pi * _dir / 3 ) - array.get(y, 1) * math.sin( -4 * math.pi * _dir / 3 ) + array.get(x, 2) * math.cos( -8 * math.pi * _dir / 3 ) - array.get(y, 2) * math.sin( -8 * math.pi * _dir / 3 )
Euler's Noice reduction with both close and Discrete Furrier approximated price.
w = (dft1*src - dft1 *src ) / math.sqrt(math.pow(math.abs(src- src ),2) + math.pow(math.abs(dft1 - dft1 ),2))
filt := na(filt ) ? 0 : c1 * (w*dft1 + nz(w *dft1 )) / 2.0 /math.abs(dft1 -dft1 ) + c2 * nz(filt ) - c3 * nz(filt )
Usecase:
First option:
Select the preferred version of DFT and noise reduction settings based on your analysis requirements.
Leverage the script to identify Bullish and Bearish trends, shown with green and red triangle.
Combine Different Timeframes to accurately determine market trend.
Second option:
Pull the data with API sockets to automate your trading journey.
plot(close, title="ClosePrice", display=display.status_line)
plot(open, title="OpenPrice", display=display.status_line)
plot(greencon ? 1 : redcon ? -1 : 0, title="position", display=display.status_line)
Use ClosePrice, OpenPrice and "position" titles to easily read and backtest your strategy utilising more than 1 Time Frame.
Indicator id:
USER;e7a774913c1242c3b1354334a8ea0f3c
(only relevant to those that use API requests)
[blackcat] L1 Fibonacci MA BandThe true charm of the Fibonacci moving average band lies not only in its predictive ability. Its essence is that it combines the beauty of mathematics with the practicality of market analysis, providing traders with a powerful tool to optimize trading strategies. It's not a simple number game, but a wisdom that sees into the deeper structure of the market.
Next, we will delve into the core technical indicators of the Fibonacci moving average band - WHALES, RESOLINE, STICKLINE functions, and TRENDLINE, as well as their clever applications. The WHALES indicator, with its 12-period exponential moving average, captures short-term market trends; the RESOLINE indicator, through the 120-period EMA, reveals mid-term market movements; the STICKLINE function, distinguishes the relationship between WHALES and RESOLINE with colors, providing clear visual aids; while TRENDLINE, combining price slope with EMA, depicts more detailed market changes for traders.
The integrated application of these indicators has built a multi-dimensional market analysis framework for traders. They help traders examine the market from different angles, judge the market status more accurately, and make wiser decisions in the ever-changing market environment. The Fibonacci moving average band indicator is like a lighthouse, emitting guiding light in the ocean of trader's navigation.
1. `xsl(src, len)` function: This function calculates a value called the linear regression slope. Len defines the length of the linear regression. Then, this function normalizes the difference between the current value of the linear regression and the previous value. The formula is `(lrc - lrprev) / timeframe.multiplier`.
2. `whales`, `resoline`, and `trendline` are Exponential Moving Averages (EMA) calculated in different ways. "whales" is the 13-period closing price EMA, "resoline" is the 144-period closing price EMA, and "trendline" is a more complicated EMA. It is the 50-period EMA calculated by the 21-period closing price slope multiplied by 23 plus the closing price.
3. The `plotcandle` function draws two sets of candlestick charts. One set shows in blue when "whales" is greater than "resoline", and the other set shows in green when "whales" is less than "resoline".
4. The `plot` function draws three lines: "whales", "resoline", and "trendline". "whales" is displayed in orange with a line thickness of 2. "resoline" is displayed in yellow with a line thickness of 1. "trendline" is displayed in red with a line thickness of 3.
5. The last line draws a conditional line. When the closing price is less than the "trendline", the green "trendline" is drawn, otherwise, it is not drawn. This is a logical judgment, the drawing operation is only executed when the condition is met.
Multi MAs mit LabelA MA (Moving Average) is useful to identify a trend of an assets. The TradingView builtin indicator "Exponential Moving Average" is useful, but limited in some aspects:
Bound to the active timeframe (e.g. h1)
One MA per indicator instance. Makes it confusing when using multiple
In reality to want to have multiple MAs with different types (EMA, SMA), length and timeframes on your chart to identify trading opportunities. As an example you can use the daily EMA12 and EMA21 to identify the trend and EMA200 on the h4 to enter a trade. That's what this script is used for.
The provided script is an extension to the indicator powered by chipmonk (link to profile below). The original script let you add up to 8 EMAs that can be bound to any timeframe and length. The timeframe and length is displayed on the chart next to EMA.
Unfortunately you can only add EMAs (Exponential Moving Averages) and no SMAs (Simple Moving Averages). That's why the script was extended. You can now choose the type (EMA or SMA) for up to 8 MAs.
Links
Profile of chipmonk
Indicator by chipmonk
[blackcat] L3 Fibonacci Bands With ATRToday, what I'm going to introduce is a technical indicator that I think is quite in line with the indicator displayed by Tang - Fibonacci Bands with ATR. This indicator combines Bollinger Bands and Average True Range (ATR) to provide insights into market volatility and potential price reversals. Sounds complicated, right? Don't worry, I will explain it to you in the simplest way.
First, let's take a look at how Fibonacci Bands are constructed. They are similar to Bollinger Bands and consist of three lines: upper band, middle band (usually a 20-period simple moving average), and lower band. The difference is that Fibonacci Bands use ATR to calculate the distance between the upper and lower bands and the middle band.
Next is a key factor - ATR multiplier. We need to smooth the ATR using Welles Wilder's method. Then, by multiplying the ATR by a Fibonacci multiplier (e.g., 1.618), we get the upper band, called the upper Fibonacci channel. Similarly, multiplying the ATR by another Fibonacci multiplier (e.g., 0.618 or 1.0) gives us the lower band, called the lower Fibonacci channel.
Now, let's see how Fibonacci Bands can help us assess market volatility. When the channel widens, it means that market volatility is high, while a narrow channel indicates low market volatility. This way, we can determine the market's activity level based on the width of the channel.
In addition, when the price touches or crosses the Fibonacci channel, it may indicate a potential price reversal, similar to Bollinger Bands. Therefore, using Fibonacci Bands in trading can help us capture potential buy or sell signals.
In summary, Fibonacci Bands with ATR is an interesting and practical technical indicator that provides information about market volatility and potential price reversals by combining Bollinger Bands and ATR. Remember, make good use of these indicators and apply them flexibly in trading!
This code is a TradingView indicator script used to plot L3 Fibonacci Bands With ATR.
First, the indicator function is used to define the title and short title of the indicator, and whether it should be overlaid on the main chart.
Then, the input function is used to define three input parameters: MA type (maType), MA length (maLength), and data source (src). There are four options for MA type: SMA, EMA, WMA, and HMA. The default values are SMA, 55, and hl2 respectively.
Next, the moving average line is calculated based on the user's selected MA type. If maType is 'SMA', the ta.sma function is called to calculate the simple moving average; if maType is 'EMA', the ta.ema function is called to calculate the exponential moving average; if maType is 'WMA', the ta.wma function is called to calculate the weighted moving average; if maType is 'HMA', the ta.hma function is called to calculate the Hull moving average. The result is then assigned to the variable ma.
Then, the _atr variable is used to calculate the ATR (Average True Range) value using ta.atr, and multiplied by different coefficients to obtain four Fibonacci bias values: fibo_bias4, fibo_bias3, fibo_bias2, and fibo_bias1.
Finally, the prices of the upper and lower four Fibonacci bands are calculated by adding or subtracting the corresponding Fibonacci bias values from the current price, and plotted on the chart using the plot function.
Interactive MA Stop Loss [TANHEF]This indicator is "Interactive." Once added to the chart, you need to click the start point for the moving average stoploss. Dragging it afterward will modify its position.
Why choose this indicator over a traditional Moving Average?
To accurately determine that a wick has crossed a moving average, you must examine the moving average's range on that bar (blue area on this indicator) and ensure the wick fully traverses this area.
When the price moves away from a moving average, the average also shifts towards the price. This can make it look like the wick crossed the average, even if it didn't.
How is the moving average area calculated?
For each bar, the moving average calculation is standard, but when the current bar is involved, its high or low is used instead of the close. For precise results, simply setting the source in a typical moving average calculation to 'Low' or 'High' is not sufficient in calculating the moving average area on a current bar.
Moving Average Options:
Simple Moving Average
Exponential Moving Average
Relative Moving Average
Weighted Moving Average
Indicator Explanation
After adding indicator to chart, you must click on a location to begin an entry.
The moving average type can be set and length modified to adjust the stoploss. An optional profit target may be added.
A symbol is display when the stoploss and profit target are hit. If a position is create that is not valid, "Overlapping MA and Bar" is displayed.
Alerts
'Check' alerts to use within indicator settings (stop hit and/or profit target hit).
Select 'Create Alert'
Set the condition to 'Interactive MA''
Select create.
Alert messages can have additional details using these words in between two Curly (Brace) Brackets:
{{stop}} = MA stop-loss (price)
{{upper}} = Upper MA band (price)
{{lower}} = Lower MA band (price)
{{band}} = Lower or Upper stoploss (word)
{{type}} = Long or Short stop-loss (word)
{{stopdistance}} = Stoploss Distance (%)
{{targetdistance}} = Target Distance (%)
{{starttime}} = Start time of stoploss (day:hour:minute)
{{maLength}} = MA Length (input)
{{maType}} = MA Type (input)
{{target}} = Price target (price)
{{trigger}} = Wick or Close Trigger input (input)
{{ticker}} = Ticker of chart (word)
{{exchange}} = Exchange of chart (word)
{{description}} = Description of ticker (words)
{{close}} = Bar close (price)
{{open}} = Bar open (price)
{{high}} = Bar high (price)
{{low}} = Bar low (price)
{{hl2}} = Bar HL2 (price)
{{volume}} = Bar volume (value)
{{time}} = Current time (day:hour:minute)
{{interval}} = Chart timeframe
{{newline}} = New line for text
I will add further moving averages types in the future. If you suggestions post them below.
Williams %R with EMA'sThe provided Pine Script code presents a comprehensive technical trading strategy on the TradingView platform, incorporating the Williams %R indicator, exponential moving averages (EMAs), and upper bands for enhanced decision-making. This strategy aims to help traders identify potential buy and sell signals based on various technical indicators, thereby facilitating more informed trading decisions.
The key components of this strategy are as follows:
**Williams %R Indicator:** The Williams %R, also known as the "Willy," is a momentum oscillator that measures overbought and oversold conditions. In this code, the Williams %R is calculated with a user-defined period (default 21) and smoothed using an exponential moving average (EMA).
**Exponential Moving Averages (EMAs):** Two EMAs are computed on the Williams %R values. The "Fast" EMA (default 8) responds quickly to price changes, while the "Slow" EMA (default 21) provides a smoother trend-following signal. Crossovers and divergences between these EMAs can indicate potential buy or sell opportunities.
**Candle Color Detection:** The code also tracks the color of candlesticks, distinguishing between green (bullish) and red (bearish) candles. This information is used in conjunction with other indicators to identify specific trading conditions.
**Additional Upper Bands:** The script introduces upper bands at various levels (-5, -10, -20, -25) to create zones for potential buy and sell signals. These bands are visually represented on the chart and can help traders gauge the strength of a trend.
**Alert Conditions:** The code includes several alert conditions that trigger notifications when specific events occur, such as %R crossing certain levels, candle color changes within predefined upper bands, and EMA crossovers.
**Background Highlighting:** The upper bands and the zero line are visually highlighted with different colors, making it easier for traders to identify critical price levels.
This code is valuable for traders seeking a versatile technical strategy that combines multiple indicators to improve trading decisions. By incorporating the Williams %R, EMAs, candlestick analysis, and upper bands, it offers a holistic approach to technical analysis. Traders can customize the parameters to align with their trading preferences and risk tolerance. The use of alerts ensures that traders are promptly notified of potential trade setups, allowing for timely execution and risk management. Overall, this code serves as a valuable tool for traders looking to make more informed decisions in the dynamic world of financial markets.
EMA/SMA Cross with LevelsThe EMA/SMA Cross indicator is a valuable trading tool designed to assist traders in identifying potential trend reversals or entry and exit points in the market. By plotting two moving averages, one based on the Exponential Moving Average (EMA) and the other on the Simple Moving Average (SMA), this indicator highlights the points at which these averages cross, signaling a potential change in the market trend. This straightforward yet powerful indicator follows the core principles of technical analysis, allowing traders to visualize key price levels that may influence future price action.
The underlying concept of this indicator revolves around the calculation and comparison of the short-term EMA and the long-term SMA. The EMA is a type of weighted moving average that gives more importance to recent price data, making it more responsive to new information. In contrast, the SMA assigns equal weight to all data points within a specified period, providing a smoother representation of price trends. By comparing these two averages, traders can gain insights into potential shifts in market sentiment and momentum.
When the short-term EMA crosses above the long-term SMA, it signals a possible bullish trend reversal, indicating that the recent price momentum is gaining strength. Conversely, when the short-term EMA crosses below the long-term SMA, it suggests a bearish trend reversal, implying that the recent price momentum is weakening. Traders can use these crossing points as potential entry or exit signals, depending on their trading strategy and risk tolerance.
A unique feature of this indicator is its ability to plot the crossing levels on the chart. When the short-term EMA crosses the long-term SMA, a dashed line is drawn horizontally at the level of the cross, emphasizing the significance of the price level. This line serves as a reference point for traders, helping them to identify potential support or resistance levels that may influence future price movements.
By plotting the crossing levels, the EMA/SMA Cross indicator offers traders an additional layer of information that can be used in their decision-making process. These levels can act as crucial points for stop-loss or take-profit orders, depending on the trader's strategy and risk tolerance. Additionally, they can serve as a basis for further technical analysis, such as the identification of chart patterns or the application of other technical indicators.
This indicator works best with trading methods that focus on capturing price reversals or breakouts. It is particularly useful for traders who employ trend-following or momentum-based strategies, as it helps them identify the optimal moments to enter or exit a trade. However, it's important to note that the EMA/SMA Cross indicator should be used in conjunction with other technical analysis tools and an understanding of the overall market context to make informed trading decisions.
When using the EMA/SMA Cross indicator on TradingView, users can customize the time frame, source, and length for both the short-term EMA and long-term SMA, as well as the number of recent crossing lines displayed on the chart. This flexibility allows traders to tailor the indicator to their specific trading style and preferences.
In summary, the EMA/SMA Cross indicator is an essential tool for traders looking to identify potential trend reversals or entry and exit points in the market. By comparing the short-term EMA and long-term SMA, this indicator provides valuable insights into shifts in market sentiment and momentum. It is best suited for trend-following and momentum-based trading strategies and should be used in combination with other technical analysis tools for optimal results.
RSI Exponential Smoothing (Expo)█ Background information
The Relative Strength Index (RSI) and the Exponential Moving Average (EMA) are two popular indicators. Traders use these indicators to understand market trends and predict future price changes. However, traders often wonder which indicator is better: RSI or EMA.
What if these indicators give similar results? To find out, we wanted to study the relationship between RSI and EMA. We focused on a hypothesis: when the RSI goes above 50, it might be similar to the price crossing above a certain length of EMA. Similarly, when the RSI goes below 50, it might be similar to the price crossing below a certain length of EMA.
Our goal was simple: to figure out if there is any connection between RSI and EMA.
Conclusion: Yes, it seems that there is a correlation between RSI and EMA, and this indicator clearly displays that relationship. Read more about the study here:
█ Overview of the indicator
The RSI Exponential Smoothing indicator displays RSI levels with clear overbought and oversold zones, shown as easy-to-understand moving averages, and the RSI 50 line as an EMA. Another excellent feature is the added FIB levels. To activate, open the settings and click on "FIB Bands." These levels act as short-term support and resistance levels which can be used for scalping.
█ Benefits of using this indicator instead of regular RSI
The findings about the Relative Strength Index (RSI) and the Exponential Moving Average (EMA) highlight that both indicators are equally accurate (when it comes to crossings), meaning traders can choose either one without compromising accuracy. This empowers traders to pick the indicator that suits their personal preferences and trading style.
█ How it works
Crossings over/under the value of 50
The EMA line in the indicator acts as the corresponding 50 line in the RSI. When the RSI crosses the value 50 equals when Close crosses the EMA line.
Bouncess from the value 50
In this example, we can see that the EMA line on the chart acts as support/resistance equals when RSI rejects the 50 level.
Overbought and Oversold
The indicator comes with overbought and oversold bands equal when RSI becomes overbought or oversold.
█ How to use
This visual representation helps traders to apply RSI strategies directly on the price chart, potentially making RSI trading easier for traders.
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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!
HS,HH,LL,and EMA by: rpalconitHello everyone,
HS,HH,LL, and EMA stands for Hull Suite, Higher High, Lower Low and Exponential Moving Average.
Signal Features:
• Long Position: If the Higher High and Lower Low signals are LL and LH at the SUPPORT LEVEL, plot the Fibonacci Retracement and get retracement from 0.382,0.5 and 0.618 for EP. and your SL should be at 1.1 level of the Fibonacci, target TP should be 1.5 ratio. For confirmations the Hull Suite (HS) should be green color and on or below the Exponential Moving Average (EMA).
• Short Position: If the Higher High and Lower Low signals are HH and HL at the RESISTANCE LEVEL, plot the Fibonacci Retracement and get retracement from 0.382,0.5 and 0.618 for EP. and your SL should be at 1.1 level of the Fibonacci, target TP should be 1.5 ratio. For confirmations the Hull Suite (HS) should be red color and on or above the Exponential Moving Average (EMA).
You can change EMA length in any of your preference. The Default is 50.
Details about the indicator
INPUTS
Time Frame
• Time Frames Chart: You can select your preferred timeframe at the dropdown list. Default is 4H. Aside from Time Fame, I advice not to change anything at input default for better result.
STYLE
• Note: For effective signals results and to minimize noise, you need to uncheck first on the style tab: MHULL, BAR COLOR AND LINES.
Best regards,
ruelpalconit
Democratic Fibonacci McGinley DynamicsWith this indicator, we have taken McGinley Dynamic lines at Fibonacci lengths (3 to 233) as well as the average of these values, labeled the DFMG (Democratic Fib. McGinley). Additionally, these values have been inputted into a table overlay. The cross of the FibMG(233) and the DFMG can be used as a signal for long or short.
The FibMG lengths of 3 and 233 are plotted in white by default, the FibMGs with lengths between 3 and 233 are plotted in blue by default, and the democratic line (DFMG) that averages these lines is plotted in green or red depending on if the value is above or below the 233-length FibMG.
This is the same indicator as our DFMA except using McGinley Dynamic lines as opposed to exponential moving averages.
Parabolic SAR MARSI, Adaptive MACD [Loxx]Parabolic SAR MARSI, Adaptive MACD is a trend following indicator that combines MACD, Parabolic SAR, and RSI into a signal indicator.
What is Parabolic SAR?
The parabolic stop and reverse, more commonly known as the "Parabolic SAR," or "PSAR" is a trend-following indicator developed by J. Welles Wilder. It is displayed as a single parabolic line (or dots) underneath the price bars in an uptrend, and above the price bars in a downtrend.
What is MACD?
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA.
What is RSI?
The relative strength index (RSI) is a momentum indicator used in technical analysis that measures the magnitude of recent price changes to evaluate overbought or oversold conditions in the price of a stock or other asset. The RSI is displayed as an oscillator (a line graph that moves between two extremes) and can have a reading from 0 to 100. The indicator was originally developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, “New Concepts in Technical Trading Systems.”
How to combine PSAR, MACD, and RSI into one:
1. Create a new type of moving average called MARSI. MARSI is like a typical moving average but it flexes to RSI sensitivities
2. Calculate MACD for the MARSI of High/Low values
3. Calculate the midpoint MACD between the High/Low MACDs created in step 2
4. Create a final MACD by calculating the MARSI for the midpoint MACD created in step 3
5. Finally, Inject these values into a customized Parabolic SAR function
Results:
-A unique spin on three different indicators that identifies trends of both RSI, MACD, and price of the underlying asset
-Entry, exit, and reversal points in price, RSI, and MACD
-A MACD that adapts to RSI
What's Included?
-Customization of all variables
-A variety of moving averages to smooth the signal line
-Customizable colors
-Alerts for MACD zero-line and signal crosses, and PSAR trend direction changes
Things to know:
-The histogram in this indicator is NOT the normal histogram found in the classic MACD indicator. The histogram here is a histogram of MACD itself. The classic histogram has questionable utility but the histogram in this indicator is very important and useful
-Parabolic SAR is calculated on the MARSI of High/Low values
Future releases:
-Divergences
-Regular, continuation, and exit signals
Happy trading!
