Timeframe WatermarkA small indicator designed for the minimalist chartist which prints the timeframe on your chart. The color of the text is based on whether the currency is trending (using the 8 and 21 EMAs) in that timeframe. Trending here is simply defined as the direction in which the 8 is above or below the 21. When used in a multi-timeframe layout, this indicator lets you easily scan multiple charts to see if they are trending across multiple timeframes by looking at the color of each chart's timeframe stamp.
This is designed to be used in a multi-timeframe window layout to efficiently and minimally present trending information across multiple timeframes.
Features:
adjustable colors
adjustable text position within the chart (top left/middle/right, bottom left/middle/right)
Moving Averages
Altcoin Total Average Divergence (YavuzAkbay)The "Average Price and Divergence" indicator is a strong tool built exclusively for cryptocurrency traders who understand the significance of comparing altcoins to Bitcoin (BTC). While traditional research frequently focusses on the value of cryptocurrencies against fiat currencies such as the US dollar, this indicator switches the focus to the value of altcoins against Bitcoin itself, allowing you to detect potential market opportunities and divergences.
The indicator allows you to compare the price of an altcoin to Bitcoin (e.g., ETHBTC, SOLBTC), which is critical for determining how well an altcoin performs against the main cryptocurrency. This is especially important for investors who expect Bitcoin's price will continue to rise logarithmically and want to ensure that their altcoin holdings retain or expand in market capitalisation compared to Bitcoin.
The indicator computes the average price of the chosen cryptocurrency relative to Bitcoin over the viewable portion of the chart. This average acts as a benchmark, indicating the normal value around which the altcoin's price moves.
The primary objective of this indicator is to calculate and plot the divergence, which is the difference between the altcoin's current price relative to Bitcoin and its average value. This divergence can reveal probable overbought or oversold conditions, allowing traders to make better decisions about entry and exit points.
The divergence is represented as a histogram, with bars representing the magnitude of the difference between the current and average prices. Positive values indicate that the altcoin is trading above its average value in comparison to Bitcoin, whereas negative values indicate that it is trading below its average.
The indicator automatically adjusts to the chart's visible range, ensuring that the average price and divergence are always calculated using the most relevant data. This makes the indicator extremely sensitive to changes in the chart view and market conditions.
How to Use:
A significant positive divergence may imply that the cryptocurrency is overbought in comparison to Bitcoin and is headed for a correction. A significant negative divergence, on the other hand, may indicate that the cryptocurrency has been oversold and is cheap in comparison to Bitcoin.
Tracking how an altcoin's price deviates from its average relative to Bitcoin can provide insights about the market's opinion towards that altcoin. Persistent positive divergence may suggest high market confidence, whilst constant negative divergence may imply a lack of interest or eroding fundamentals.
Use divergence data to better time your trades, either by entering when a cryptocurrency is discounted in comparison to its average (negative divergence) or departing when it is overpriced (positive divergence). This allows you to capture value as the price returns to its mean.
Ideal For:
Cryptocurrency Traders who want to understand how altcoins are performing relative to Bitcoin rather than just against fiat currencies.
Long-term Investors looking to ensure their altcoin investments are maintaining or growing their value relative to Bitcoin.
Market Analysts interested in identifying potential reversals or continuations in altcoin prices based on divergence from their average value relative to Bitcoin.
Fear/Greed Zone Reversals [UAlgo]The "Fear/Greed Zone Reversals " indicator is a custom technical analysis tool designed for TradingView, aimed at identifying potential reversal points in the market based on sentiment zones characterized by fear and greed. This indicator utilizes a combination of moving averages, standard deviations, and price action to detect when the market transitions from extreme fear to greed or vice versa. By identifying these critical turning points, traders can gain insights into potential buy or sell opportunities.
🔶 Key Features
Customizable Moving Averages: The indicator allows users to select from various types of moving averages (SMA, EMA, WMA, VWMA, HMA) for both fear and greed zone calculations, enabling flexible adaptation to different trading strategies.
Fear Zone Settings:
Fear Source: Select the price data point (e.g., close, high, low) used for Fear Zone calculations.
Fear Period: This defines the lookback window for calculating the Fear Zone deviation.
Fear Stdev Period: This sets the period used to calculate the standard deviation of the Fear Zone deviation.
Greed Zone Settings:
Greed Source: Select the price data point (e.g., close, high, low) used for Greed Zone calculations.
Greed Period: This defines the lookback window for calculating the Greed Zone deviation.
Greed Stdev Period: This sets the period used to calculate the standard deviation of the Greed Zone deviation.
Alert Conditions: Integrated alert conditions notify traders in real-time when a reversal in the fear or greed zone is detected, allowing for timely decision-making.
🔶 Interpreting Indicator
Greed Zone: A Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity.
Fear Zone Reversal: A Fear Zone is highlighted when the price deviates significantly below the chosen moving average of the selected price source. This suggests market sentiment might be leaning towards fear, potentially indicating a buying opportunity. When the indicator identifies a reversal from a fear zone, it suggests that the market is transitioning from a period of intense selling pressure to a more neutral or potentially bullish state. This is typically indicated by an upward arrow (▲) on the chart, signaling a potential buy opportunity. The fear zone is characterized by high price volatility and overselling, making it a crucial point for traders to consider entering the market.
Greed Zone Reversal: Conversely, a Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity. When the indicator detects a reversal from a greed zone, it indicates that the market may be moving from an overbought condition back to a more neutral or bearish state. This is marked by a downward arrow (▼) on the chart, suggesting a potential sell opportunity. The greed zone is often associated with overconfidence and high buying activity, which can precede a market correction.
🔶 Why offer multiple moving average types?
By providing various moving average types (SMA, EMA, WMA, VWMA, HMA) , the indicator offers greater flexibility for traders to tailor the indicator to their specific trading strategies and market preferences. Different moving averages react differently to price data and can produce varying signals.
SMA (Simple Moving Average): Provides an equal weighting to all data points within the specified period.
EMA (Exponential Moving Average): Gives more weight to recent data points, making it more responsive to price changes.
WMA (Weighted Moving Average): Allows for custom weighting of data points, providing more flexibility in the calculation.
VWMA (Volume Weighted Moving Average): Considers both price and volume data, giving more weight to periods with higher trading volume.
HMA (Hull Moving Average): A combination of weighted moving averages designed to reduce lag and provide a smoother curve.
Offering multiple options allows traders to:
Experiment: Traders can try different moving averages to see which one produces the most accurate signals for their specific market.
Adapt to different market conditions: Different market conditions may require different moving average types. For example, a fast-moving market might benefit from a faster moving average like an EMA, while a slower-moving market might be better suited to a slower moving average like an SMA.
Personalize: Traders can choose the moving average that best aligns with their personal trading style and risk tolerance.
In essence, providing a variety of moving average types empowers traders to create a more personalized and effective trading experience.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
[TR] Engulf Patterns by SM
Engulf Pattern by SM
Overview:
The " Engulf Pattern by SM" script is designed to identify bullish and bearish engulfing candlestick patterns on TradingView charts. Engulfing patterns are significant in technical analysis as they often indicate potential reversals in market trends.
Features:
- Bullish Engulfing Pattern Detection: The script identifies bullish engulfing patterns, which occur when a larger bullish candle completely engulfs the body of the previous smaller bearish candle.
- Bearish Engulfing Pattern Detection: Similarly, it detects bearish engulfing patterns, where a larger bearish candle engulfs the body of the preceding smaller bullish candle.
- Body Size Filtering: The script includes a feature to filter patterns based on the size of the candle bodies, allowing for more precise marking of significant patterns.
- Visual Markers: The script plots visual markers on the chart to highlight the detected engulfing patterns, making it easy for traders to spot them.
How It Works:
1. Bullish Engulfing Pattern:
- The script checks for a smaller bearish candle followed by a larger bullish candle.
- The body of the bullish candle must completely cover the body of the bearish candle.
- The size of the bullish candle's body must meet a specified threshold to be considered significant.
2. Bearish Engulfing Pattern:
- The script looks for a smaller bullish candle followed by a larger bearish candle.
- The body of the bearish candle must completely engulf the body of the bullish candle.
- The size of the bearish candle's body must meet a specified threshold to be considered significant.
Usage:
- Add the Script: Apply the " Engulf Pattern by SM" script to your TradingView chart.
- Configure Settings: Customize the script settings to suit your trading strategy, including visual marker styles and body size thresholds.
- Monitor Visual Markers: Keep an eye on the visual markers to identify potential trading opportunities based on engulfing patterns.
Disclaimer:
This script is not intended to be used as a direct entry signal. It should be used as a confluence in your overall trading plan. Always conduct your own analysis and consider multiple factors before making any trading decisions.
Feel free to customize this writeup further to match your specific needs! If you have any other requests or need additional details, just let me know.
MACD with 1D Stochastic Confirmation Reversal StrategyOverview
The MACD with 1D Stochastic Confirmation Reversal Strategy utilizes MACD indicator in conjunction with 1 day timeframe Stochastic indicators to obtain the high probability short-term trend reversal signals. The main idea is to wait until MACD line crosses up it’s signal line, at the same time Stochastic indicator on 1D time frame shall show the uptrend (will be discussed in methodology) and not to be in the oversold territory. Strategy works on time frames from 30 min to 4 hours and 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.
Higher time frame confirmation: Strategy utilizes 1D Stochastic to establish the major trend and confirm the local reversals with the higher probability.
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:
MACD line of MACD indicator shall cross over the signal line of MACD indicator.
1D time frame Stochastic’s K line shall be above the D line.
1D time frame Stochastic’s K line value shall be below 80 (not overbought)
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 = 3.25, value multiplied by ATR to be subtracted from position entry price to setup stop loss)
ATR Trailing Profit Activation Level (by default = 4.25, value multiplied by ATR to be added to position entry price to setup trailing profit activation level)
Trailing EMA Length (by default = 20, period for EMA, when price reached trailing profit activation level EMA will stop out of position if price closes below it)
User can choose the optimal parameters during backtesting on certain price chart, in our example we use default settings.
Justification of Methodology
This strategy leverages 2 time frames analysis to have the high probability reversal setups on lower time frame in the direction of the 1D time frame trend. That’s why it’s recommended to use this strategy on 30 min – 4 hours time frames.
To have an approximation of 1D time frame trend strategy utilizes classical Stochastic indicator. The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
Strategy logic assumes that on 1D time frame it’s uptrend in %K line is above the %D line. Moreover, we can consider long trade only in %K line is below 80. It means that in overbought state the long trade will not be opened due to higher probability of pullback or even major trend reversal. If these conditions are met we are going to our working (lower) time frame.
On the chosen time frame, we remind you that for correct work of this strategy you shall use 30min – 4h time frames, MACD line shall cross over it’s signal line. The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line=12-period EMA−26-period
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
In our script we are interested in only MACD and signal lines. When MACD line crosses signal line there is a high chance that short-term trend reversed to the upside. We use this strategy on 45 min time frame.
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.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 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: 30%
Maximum Single Position Loss: -4.79%
Maximum Single Profit: +20.14%
Net Profit: +2361.33 USDT (+44.72%)
Total Trades: 123 (44.72% win rate)
Profit Factor: 1.623
Maximum Accumulated Loss: 695.80 USDT (-5.48%)
Average Profit per Trade: 19.20 USDT (+0.59%)
Average Trade Duration: 30 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 between 30 min and 4 hours and chart (optimal performance observed on 45 min 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
MACD Divergence StrategyStrategy Description: MACD Divergence with SMA Crossover Strategy
Overview:
The MACD Divergence with SMA Crossover Strategy is designed to identify high-probability trading opportunities based on the interaction of the MACD (Moving Average Convergence Divergence) indicator and key moving averages. This strategy focuses on detecting divergences between the MACD line and the signal line, combined with specific conditions related to the 50-period and 800-period SMAs. It ensures that the MACD and signal lines do not cross the zero line between the current and previous divergence points, thereby filtering out weaker signals and enhancing the accuracy of trade entries.
Key Components:
Simple Moving Averages (SMAs):
50-period SMA: A short-term trend indicator that helps identify the prevailing market direction.
800-period SMA: A long-term trend indicator used to gauge the overall market trend.
MACD Indicator:
MACD Line: Represents the difference between the 12-period EMA and the 26-period EMA.
Signal Line: A 9-period EMA of the MACD line.
Histogram: The difference between the MACD line and the signal line, used to visualize the strength of the signal.
Trade Conditions:
Long Position (Buy):
The 50 SMA is above the 800 SMA, indicating a bullish market trend.
The MACD line and signal line are both below zero, signifying a potential bullish reversal.
A bullish divergence is detected when the MACD line crosses above the signal line below zero, without either line crossing the zero level between the current and previous cross.
Short Position (Sell):
The 50 SMA is below the 800 SMA, indicating a bearish market trend.
The MACD line and signal line are both above zero, signaling a potential bearish reversal.
A bearish divergence is detected when the MACD line crosses below the signal line above zero, without either line crossing the zero level between the current and previous cross.
Signal Plotting:
Long Signals: Displayed when the conditions for a bullish divergence and SMA alignment are met, marked with a green upward arrow on the chart.
Short Signals: Displayed when the conditions for a bearish divergence and SMA alignment are met, marked with a red downward arrow on the chart.
SUPER EMA SMA 16x [GUSLM]█ Author's Note:
After extensively reviewing the EMA and SMA consolidation tools in the TradingView library, I found that none fully met my expectations or those of friends and colleagues. Some tools were too specific or not configurable enough, with varying sensitivities. Others lacked options or produced many invalid and incorrect ranges when viewed across different timeframes. Some were fixed in their options, others did not allow visualization on different timeframes or lacked crossover signals and customization options for turning each option on or off. Additionally, there was no custom function to view one or more configurable moving averages from different timeframes in the current view, serving as a time-saving shortcut to avoid switching between timeframes to record values. Consequently, I decided to develop my own tool. I hope that you, fellow traders, find it valuable and enjoy using it.
█ Description:
The GUSLM SUPER EMA SMA 16x allows traders to configure and visualize multiple labeled trendlines for various periods on a single chart, all at once. highlighting how prices move over time. It enables simultaneous display of trendlines for different timeframes, with customizable colors and thicknesses. Designed for traders who use moving averages in their strategies, it simplifies the analysis of key moving averages like the 200-period, 100 50 12 26 and 20-period etc, offering a clear, configurable tool to try to identify reactions, trends, supports, and resistances.. This indicator employs algorithms to detect and show signals where price movements are confined, all that can be usefull for helping traders spot potential breakout zones and make informed trading decisions.
█ Key Features:
► Customizable Timeframes: Display in one, multiple moving averages and exponential moving averages across various timeframes (weekly, daily, hourly, and 4-hour) to tailor analysis to your trading strategy.
► Adjustable Display Settings: Choose which moving averages to display and customize their visual characteristics, including color and line width, to match your chart preferences.
► Dynamic Alerts: Activate signals for different timeframes with customizable visual cues, including background color changes and shape indicators to highlight key trading signals.
► Clear Visual Indicators: Enhance chart readability with distinct colors and shapes for different types of moving averages and also crossover events, providing immediate visual feedback for trading decisions.
█ User-Defined Inputs:
► Moving Averages Display Options:
Weekly: MA 200, EMA 200, EMA 100, EMA 50, EMA 20, EMA 12, EMA 26
Daily: MA 200, EMA 200, EMA 100, EMA 50, EMA 20, EMA 12, EMA 26
Hourly: MA 200, EMA 200, EMA 100, EMA 50, EMA 20, EMA 12, EMA 26
4-Hour: MA 200, EMA 200, EMA 100, EMA 50, EMA 20, EMA 12, EMA 26
► Line Width Adjustments:
Hourly, Daily, Weekly, 4-Hour
► Color Options for each range and or individually
► Options for type and Signal; Weekly: On/Off Daily: On/Off Hourly: On/Off 4-Hour: On/Off
► Background color change and arrow shapes for crossover and crossunder signals
█ How It Works:
► Range Detection: The indicator scans the charts in different timeframes of the same asset, based on options, and plot them on the actual view, even if they are from another timeframe. And label it based on configuration, telling wich one is from where as H 4h W etc, and its lenght and range. also for collors widths etc. It calculates the average or exponential average price from other timeframes, and plot it in the current view.
► Visualization: Validated ranges and lines are highlighted on the chart with colored optimized lines, providing a clear visual cue of potential zones.
█ Usage Examples:
► Example 1:
You can configure the ranges you want and timeframes you want and see how it interact with the prices. and can expect eventual future reactions.
█ Practical Applications:
► Identify and Confirm Breakout Zones: Use the lines to identify potential breakout zones and limits, Ex: if is there a key level above your breakout, you may expect a reaction, maybe changing your plan to make an entrance above the initial resistance, you can see eventual resistance and support zones. helping to anticipate significant price movements.
► Identify Key Price Levels: The tool helps in pointing key price levels where there is a high probability of significant price reactions, providing crucial insights for trading strategies.
► Enhance Technical Analysis: Integrate the SUPER EMA SMA 16x into your existing technical analysis toolkits to improve the accuracy of your trading decisions.
█ Conclusion:
The SUPER EMA SMA 16x is a powerful tool, for traders looking to identify periods of price consolidation, support and resistance levels and potential confirmation for breakout zones. Serving as a time-saving shortcut with its customizable settings and algorithms, it provides a reliable and visual method to enhance your trading strategy. Whether you're a beginner or an experienced trader, this indicator can add significant value to your technical analysis.
█ Cautionary Note:
While the SUPER EMA SMA 16x is a powerful tool to see many relevant SMAS and EMAS and signals, it's important to combine it with other indicators and analysis methods for comprehensive trading decisions. Always consider market context and external factors when interpreting detected consolidation ranges.
SDMA (Slope Degree Moving Average)This Pine Script indicator is designed to provide traders with a comprehensive view of market conditions by combining moving averages, VWAP (Volume Weighted Average Price), and custom distance signals. It offers a clean and professional table interface to monitor trend strength, distance from moving averages, and potential trade signals.
Key Features
Moving Averages and VWAP:
The indicator calculates five moving averages (MAs) of user-defined lengths, providing a multi-faceted view of market trends.
VWAP is included to help identify overall market sentiment. VWAP is commonly used by institutional traders to measure the average price at which a security has traded throughout the day, taking into account both price and volume.
Slope Degree Calculation:
The indicator calculates the slope degree of each moving average. The slope is a measure of the moving average's angle, indicating the strength and direction of the trend.
Steeper slopes (positive or negative) indicate stronger trends, while flatter slopes suggest weaker or consolidating trends.
Trend Strength Analysis:
For each moving average, the indicator provides a trend strength rating based on the calculated slope. It categorizes trends as "Strong Bullish," "Moderate Bullish," "Flat," "Moderate Bearish," or "Strong Bearish."
The VWAP trend strength is shown as "Bullish" if the current price is above the VWAP and "Bearish" if below.
Distance Signal (DS):
The indicator includes a user-defined threshold for distance signals. This threshold determines whether the price is "Near" the moving average or significantly above/below it, indicated by "DS" (Distance Signal).
Traders can adjust the threshold to suit their trading strategy. For instance, a higher threshold might be used in volatile markets to identify meaningful deviations from the moving averages.
Table Display:
The indicator displays all relevant data in a clean, minimalistic table format, showing the moving average lengths, slope degrees, trend strengths, minutes since the last reversal, distance from the moving average, and distance signals.
The table also includes a row for VWAP, making it easy to compare the current price with this key level.
Trade Signal:
At the bottom of the table, a summary "Trade Signal" is displayed, showing either "Bullish Signal" or "Bearish Signal" based on the overall trend indications from the moving averages.
How to Use This Indicator
Identifying Trends: Use the slope degree and trend strength indicators to determine the direction and strength of the trend. Steeper slopes and stronger trend ratings suggest stronger trends, ideal for trend-following strategies.
VWAP Analysis: The VWAP row helps to identify whether the market is generally bullish or bearish. A price above VWAP typically suggests buying interest, while a price below suggests selling pressure.
Distance Signals: The DS column alerts traders when the price is significantly away from a moving average, which could signal potential overbought or oversold conditions, useful for mean reversion strategies.
Trade Signal: The final "Trade Signal" offers a quick summary of the overall market condition, combining the insights from all moving averages.
Customization
Moving Averages: Adjust the lengths of the five moving averages to match your trading strategy or the specific asset you're analyzing.
Distance Threshold: Set the distance threshold to control the sensitivity of the DS signals. A lower threshold will generate more signals, while a higher threshold will highlight only significant deviations.
This indicator is a versatile tool that can be used in various trading strategies, whether you're a trend follower, mean reversion trader, or someone looking to identify key levels like VWAP. Its clear, table-based interface ensures that all the critical data is available at a glance, allowing for quick decision-making in fast-moving markets.
MACD Trail | Flux Charts💎 GENERAL OVERVIEW
Introducing our new MACD Trail indicator! Moving average convergence/divergence (MACD) is a well-known indicator among traders. It's a trend-following indicator that uses the relationship between two exponential moving averages (EMAs). This indicator aims to use MACD to generate a trail that follows the current price of the ticker, which can act as a support / resistance zone. More info about the process in the "How Does It Work" section.
Features of the new MACD Trail Indicator :
A Trail Generated Using MACD Calculation
Customizable Algorithm
Customizable Styling
📌 HOW DOES IT WORK ?
First of all, this indicator calculates the current MACD of the ticker using the user's input as settings. Let X = MACD Length setting ;
MACD ~= X Period EMA - (X * 2) Period EMA
Then, two MACD Trails are generated, one being bullish and other being bearish. Let ATR = 30 period ATR (Average True Range)
Bullish MACD Trail = Current Price + MACD - (ATR * 1.75)
Bearish MACD Trail = Current Price + MACD + (ATR * 1.75)
The indicator starts by rendering only the Bullish MACD Trail. Then if it's invalidated (candlestick closes below the trail) it switches to Bearish MACD Trail. The MACD trail switches between bullish & bearish as they get invalidated.
The trail type may give a hint about the current trend of the price action. The trail itself also can act as a support / resistance zone, here is an example :
🚩 UNIQUENESS
While MACD is one of the most used indicators among traders, this indicator aims to add another functionality to it by rendering a trail based on it. This trail may act as a support / resistance zone as described above, and gives a glimpse about the current trend. The indicator also has custom MACD Length and smoothing options, as well as various style options.
⚙️ SETTINGS
1. General Configuration
MACD Length -> This setting adjusts the EMA periods used in MACD calculation. Increasing this setting will make MACD more responseive to longer trends, while decreasing it may help with detection of shorter trends.
Smoothing -> The smoothing of the MACD Trail. Increasing this setting will help smoothen out the MACD Trail line, but it can also make it less responsive to the latest changes.
Dual Chain StrategyDual Chain Strategy - Technical Overview
How It Works:
The Dual Chain Strategy is a unique approach to trading that utilizes Exponential Moving Averages (EMAs) across different timeframes, creating two distinct "chains" of trading signals. These chains can work independently or together, capturing both long-term trends and short-term price movements.
Chain 1 (Longer-Term Focus):
Entry Signal: The entry signal for Chain 1 is generated when the closing price crosses above the EMA calculated on a weekly timeframe. This suggests the start of a bullish trend and prompts a long position.
bullishChain1 = enableChain1 and ta.crossover(src1, entryEMA1)
Exit Signal: The exit signal is triggered when the closing price crosses below the EMA on a daily timeframe, indicating a potential bearish reversal.
exitLongChain1 = enableChain1 and ta.crossunder(src1, exitEMA1)
Parameters: Chain 1's EMA length is set to 10 periods by default, with the flexibility for user adjustment to match various trading scenarios.
Chain 2 (Shorter-Term Focus):
Entry Signal: Chain 2 generates an entry signal when the closing price crosses above the EMA on a 12-hour timeframe. This setup is designed to capture quicker, shorter-term movements.
bullishChain2 = enableChain2 and ta.crossover(src2, entryEMA2)
Exit Signal: The exit signal occurs when the closing price falls below the EMA on a 9-hour timeframe, indicating the end of the shorter-term trend.
exitLongChain2 = enableChain2 and ta.crossunder(src2, exitEMA2)
Parameters: Chain 2's EMA length is set to 9 periods by default, and can be customized to better align with specific market conditions or trading strategies.
Key Features:
Dual EMA Chains: The strategy's originality shines through its dual-chain configuration, allowing traders to monitor and react to both long-term and short-term market trends. This approach is particularly powerful as it combines the strengths of trend-following with the agility of momentum trading.
Timeframe Flexibility: Users can modify the timeframes for both chains, ensuring the strategy can be tailored to different market conditions and individual trading styles. This flexibility makes it versatile for various assets and trading environments.
Independent Trade Logic: Each chain operates independently, with its own set of entry and exit rules. This allows for simultaneous or separate execution of trades based on the signals from either or both chains, providing a robust trading system that can handle different market phases.
Backtesting Period: The strategy includes a configurable backtesting period, enabling thorough performance assessment over a historical range. This feature is crucial for understanding how the strategy would have performed under different market conditions.
time_cond = time >= startDate and time <= finishDate
What It Does:
The Dual Chain Strategy offers traders a distinctive trading tool that merges two separate EMA-based systems into one cohesive framework. By integrating both long-term and short-term perspectives, the strategy enhances the ability to adapt to changing market conditions. The originality of this script lies in its innovative dual-chain design, providing traders with a unique edge by allowing them to capitalize on both significant trends and smaller, faster price movements.
Whether you aim to capture extended market trends or take advantage of more immediate price action, the Dual Chain Strategy provides a comprehensive solution with a high degree of customization and strategic depth. Its flexibility and originality make it a valuable tool for traders seeking to refine their approach to market analysis and execution.
How to Use the Dual Chain Strategy
Step 1: Access the Strategy
Add the Script: Start by adding the Dual Chain Strategy to your TradingView chart. You can do this by searching for the script by name or using the link provided.
Select the Asset: Apply the strategy to your preferred trading pair or asset, such as #BTCUSD, to see how it performs.
Step 2: Configure the Settings
Enable/Disable Chains:
The strategy is designed with two independent chains. You can choose to enable or disable each chain depending on your trading style and the market conditions.
enableChain1 = input.bool(true, title='Enable Chain 1')
enableChain2 = input.bool(true, title='Enable Chain 2')
By default, both chains are enabled. If you prefer to focus only on longer-term trends, you might disable Chain 2, or vice versa if you prefer shorter-term trades.
Set EMA Lengths:
Adjust the EMA lengths for each chain to match your trading preferences.
Chain 1: The default EMA length is 10 periods. This chain uses a weekly timeframe for entry signals and a daily timeframe for exits.
len1 = input.int(10, minval=1, title='Length Chain 1 EMA', group="Chain 1")
Chain 2: The default EMA length is 9 periods. This chain uses a 12-hour timeframe for entries and a 9-hour timeframe for exits.
len2 = input.int(9, minval=1, title='Length Chain 2 EMA', group="Chain 2")
Customize Timeframes:
You can customize the timeframes used for entry and exit signals for both chains.
Chain 1:
Entry Timeframe: Weekly
Exit Timeframe: Daily
tf1_entry = input.timeframe("W", title='Chain 1 Entry Timeframe', group="Chain 1")
tf1_exit = input.timeframe("D", title='Chain 1 Exit Timeframe', group="Chain 1")
Chain 2:
Entry Timeframe: 12 Hours
Exit Timeframe: 9 Hours
tf2_entry = input.timeframe("720", title='Chain 2 Entry Timeframe (12H)', group="Chain 2")
tf2_exit = input.timeframe("540", title='Chain 2 Exit Timeframe (9H)', group="Chain 2")
Set the Backtesting Period:
Define the period over which you want to backtest the strategy. This allows you to see how the strategy would have performed historically.
startDate = input.time(timestamp('2015-07-27'), title="StartDate")
finishDate = input.time(timestamp('2026-01-01'), title="FinishDate")
Step 3: Analyze the Signals
Understand the Entry and Exit Signals:
Buy Signals: When the price crosses above the entry EMA, the strategy generates a buy signal.
bullishChain1 = enableChain1 and ta.crossover(src1, entryEMA1)
Sell Signals: When the price crosses below the exit EMA, the strategy generates a sell signal.
bearishChain2 = enableChain2 and ta.crossunder(src2, entryEMA2)
Review the Visual Indicators:
The strategy plots buy and sell signals on the chart with labels for easy identification:
BUY C1/C2 for buy signals from Chain 1 and Chain 2.
SELL C1/C2 for sell signals from Chain 1 and Chain 2.
This visual aid helps you quickly understand when and why trades are being executed.
Step 4: Optimize the Strategy
Backtest Results:
Review the strategy’s performance over the backtesting period. Look at key metrics like net profit, drawdown, and trade statistics to evaluate its effectiveness.
Adjust the EMA lengths, timeframes, and other settings to see how changes affect the strategy’s performance.
Customize for Live Trading:
Once satisfied with the backtest results, you can apply the strategy settings to live trading. Remember to continuously monitor and adjust as needed based on market conditions.
Step 5: Implement Risk Management
Use Realistic Position Sizing:
Keep your risk exposure per trade within a comfortable range, typically between 1-2% of your trading capital.
Set Alerts:
Set up alerts for buy and sell signals, so you don’t miss trading opportunities.
Paper Trade First:
Consider running the strategy in a paper trading account to understand its behavior in real market conditions before committing real capital.
This dual-layered approach offers a distinct advantage: it enables the strategy to adapt to varying market conditions by capturing both broad trends and immediate price action without one chain's activity impacting the other's decision-making process. The independence of these chains in executing transactions adds a level of sophistication and flexibility that is rarely seen in more conventional trading systems, making the Dual Chain Strategy not just unique, but a powerful tool for traders seeking to navigate complex market environments.
Quatro SMA Strategy [4h]Hello, I would like to present to you The "Quatro SMA" strategy
Strategy is based on four simple moving averages of different lengths and monitoring trading volume. The key idea is to identify strong market trends by comparing short-term moving averages with the long-term SMA. The strategy generates buy signals when all short-term SMAs are above the SMA(200) and the volume confirms the strength of the move. Similarly, sell signals are generated when all short-term SMAs are below the SMA(200), and the volume is sufficiently high.
The strategy manages risk by applying a stop loss and three different Take Profit levels (TP1, TP2, TP3), with varying percentages of the position closed at each level.
Each Take Profit level is triggered at a specific percentage gain, with the position being closed gradually depending on the achieved targets. The percentage of the position closed at each TP level is also defined by the user.
Indicators and Parameters:
Simple Moving Averages (SMA):
The script utilizes four simple moving averages with different lengths (4, 16, 32, 200). The first three SMAs (SMA1, SMA2, SMA3) are used to determine the trend direction, while the fourth SMA (with a length of 200) serves as a support/resistance line.
Volume:
The script monitors trading volume and checks if the current volume exceeds 2.5 times the average volume of the last 40 candles. High volume is considered as confirmation of trend strength.
Entry Conditions:
- Long Position: Triggered when SMA1 > SMA2 > SMA3, the closing price is above SMA(200), and the volume condition is met.
- Short Position: Triggered when SMA1 < SMA2 < SMA3, the closing price is below SMA(200), and the volume condition is met.
Exit Conditions:
- Long Position: Closed when SMA1 < SMA2 < SMA3 and the closing price is above SMA(200).
- Short Position: Closed when SMA1 > SMA2 > SMA3 and the closing price is below SMA(200).
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
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
Three Anchored Moving Averages (VWAP / SMA / EMA)
This indicator allows users to anchor three types of moving averages (Simple Moving Average (SMA), Exponential Moving Average (EMA), and Volume Weighted Average Price (VWAP)) to specific points in time (anchor points)
Key Features:
Select from three Moving Average Types:
Simple Moving Average (SMA): Averages the closing prices over a specified period.
Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to new information.
Volume Weighted Average Price (VWAP): Averages the price weighted by volume, useful for understanding the average price at which the asset has traded over a period.
Up to Three Anchor Points:
Users can set up to three different anchor points to calculate the moving averages from specific dates and times. This allows for analysis of price action starting from significant points or specific events. For example, you can anchor to the low and high of a move to identify key levels or to points where the price takes off from a previous anchored MA.
Customisable Sentiment Options:
Each anchor point can be associated with a sentiment input (Auto, Bull, Bear, None), which influences if the MAs are displayed as lines or zones/bands:
Auto: Automatically determines the sentiment based on whether anchor points are on pivot highs and lows. If anchored to a pivot high, the system will assume a bearish sentiment and display a red band or zone between the MA OHLC4 and High. Anchoring to a pivot low will display a green band (OHLC4 - Low).
Bull: Forces a bullish sentiment (Green Band - OHLC4 to Low)
Bear: Forces a bearish sentiment (Red Band - OHLC4 to High)
None: Ignores sentiment and displays a single line (OHLC4)
Chart Matching:
The indicator includes an option to display the moving averages only if the chart symbol matches a specified ticker. This feature ensures that the indicator is relevant to the specific asset being analysed.
How to Use the Indicator:
1. Set Anchor Points: When added to your chart, select three anchor points by point and click. If you only wish to anchor to a single point, click on that point three times and disable the other two in settings once the indicator is applied.
2. Select Moving Average Type: Choose between SMA, EMA, or VWAP using the dropdown menu. EMAs are the most responsive.
3. Enable/Disable Anchor Points: Use the checkboxes to enable or disable each anchor point.
4. Select Sentiment Type: Choose between Auto, Bull, Bear, or None.
5. Chart Matching: Optionally, specify a chart symbol to restrict the indicator's display to that particular asset.
6. Interpret the Plots: The indicator plots the high, mid, and low values of the selected moving average type from each anchor point. The fills between these plots help identify potential support and resistance zones. These should be used as points of interest for pullback reversals or potential continuation if the price breaks through.
Practical Applications:
Trend Analysis: Identify the overall trend direction from specific historical points.
Support and Resistance: Determine key dynamic support and resistance levels based on anchored moving averages.
Event-Based Analysis: Anchor the moving averages to significant events (e.g., earnings releases, economic data) to study their impact on price trends.
Multi Timeframe Analysis: Higher Timeframe Anchors can be used to identify longer term trend analysis. Switching to a lower timeframe for execution triggers at these points wont distort the MA levels as they are anchored to a specific point in time
Intraday or Swing Trading: trend analysis using anchor points can be used for any style of trading (Intraday / Swing / Invest). Use anchored levels as points of interest and wait for hints in price action to try and catch the next move.
Market Breadth - AsymmetrikMarket Breadth - Asymmetrik User Manual
Overview
The Market Breadth - Asymmetrik is a script designed to provide insights into the overall market condition by plotting three key indicators based on stocks within the S&P 500 index. It helps traders assess market momentum and strength through visual cues and is especially useful for understanding the proportion of stocks trading above their respective moving averages.
Features
1. Market Breadth Indicators:
- Breadth 20D (green line): Represents the percentage of stocks in the S&P 500 that are above their 20-day moving average.
- Breadth 50D (yellow line): Represents the percentage of stocks in the S&P 500 that are above their 50-day moving average.
- Breadth 100D (red line): Represents the percentage of stocks in the S&P 500 that are above their 100-day moving average.
2. Horizontal Lines for Context:
- Green line at 10%
- Lighter green line at 20%
- Grey line at 50%
- Light red line at 80%
- Dark red line at 90%
3. Background Color Alerts:
- Green background when all three indicators are under 20%, indicating a potential oversold market condition.
- Red background when all three indicators are over 80%, indicating a potential overbought market condition.
Interpreting the Indicator
- Market Breadth Lines: Observe the plotted lines to assess the percentage of stocks above their moving averages.
- Horizontal Lines: Use the horizontal lines to quickly identify important threshold levels.
- Background Colors: Pay attention to background colors for quick insights:
- Green: All indicators suggest a potentially oversold market condition (below 20).
- Red: All indicators suggest a potentially overbought market condition (above 80).
Troubleshooting
- If the indicator does not appear as expected, please contact me.
- This indicator works only on daily and weekly timeframes.
Conclusion
This Market Breadth Indicator offers a visual representation of market momentum and strength through three key indicators, helping you identify potential buying and selling zones.
Trend Strength | Flux Charts💎 GENERAL OVERVIEW
Introducing the new Trend Strength indicator! Latest trends and their strengths play an important role for traders. This indicator aims to make trend and strength detection much easier by coloring candlesticks based on the current strength of trend. More info about the process in the "How Does It Work" section.
Features of the new Trend Strength Indicator :
3 Trend Detection Algorithms Combined (RSI, Supertrend & EMA Cross)
Fully Customizable Algorithm
Strength Labels
Customizable Colors For Bullish, Neutral & Bearish Trends
📌 HOW DOES IT WORK ?
This indicator uses three different methods of trend detection and combines them all into one value. First, the RSI is calculated. The RSI outputs a value between 0 & 100, which this indicator maps into -100 <-> 100. Let this value be named RSI. Then, the Supertrend is calculated. Let SPR be -1 if the calculated Supertrend is bearish, and 1 if it's bullish. After that, latest EMA Cross is calculated. This is done by checking the distance between the two EMA's adjusted by the user. Let EMADiff = EMA1 - EMA2. Then EMADiff is mapped from -ATR * 2 <-> ATR * 2 to -100 <-> 100.
Then a Total Strength (TS) is calculated by given formula : RSI * 0.5 + SPR * 0.2 + EMADiff * 0.3
The TS value is between -100 <-> 100, -100 being fully bearish, 0 being true neutral and 100 being fully bullish.
Then the Total Strength is converted into a color adjusted by the user. The candlesticks in the chart will be presented with the calculated color.
If the Labels setting is enabled, each time the trend changes direction a label will appear indicating the new direction. The latest candlestick will always show the current trend with a label.
EMA = Exponential Moving Average
RSI = Relative Strength Index
ATR = Average True Range
🚩 UNIQUENESS
The main point that differentiates this indicator from others is it's simplicity and customization options. The indicator interprets trend and strength detection in it's own way, combining 3 different well-known trend detection methods: RSI, Supertrend & EMA Cross into one simple method. The algorithm is fully customizable and all styling options are adjustable for the user's liking.
⚙️ SETTINGS
1. General Configuration
Detection Length -> This setting determines the amount of candlesticks the indicator will look for trend detection. Higher settings may help the indicator find longer trends, while lower settings will help with finding smaller trends.
Smoothing -> Higher settings will result in longer periods of time required for trend to change direction from bullish to bearish and vice versa.
EMA Lengths -> You can enter two EMA Lengths here, the second one must be longer than the first one. When the shorter one crosses under the longer one, this will be a bearish sign, and if it crosses above it will be a bullish sign for the indicator.
Labels -> Enables / Disables trend strength labels.
LOWESS (Locally Weighted Scatterplot Smoothing) [ChartPrime]LOWESS (Locally Weighted Scatterplot Smoothing)
⯁ OVERVIEW
The LOWESS (Locally Weighted Scatterplot Smoothing) [ ChartPrime ] indicator is an advanced technical analysis tool that combines LOWESS smoothing with a Modified Adaptive Gaussian Moving Average. This indicator provides traders with a sophisticated method for trend analysis, pivot point identification, and breakout detection.
◆ KEY FEATURES
LOWESS Smoothing: Implements Locally Weighted Scatterplot Smoothing for trend analysis.
Modified Adaptive Gaussian Moving Average: Incorporates a volatility-adapted Gaussian MA for enhanced trend detection.
Pivot Point Identification: Detects and visualizes significant pivot highs and lows.
Breakout Detection: Tracks and optionally displays the count of consecutive breakouts.
Gaussian Scatterplot: Offers a unique visualization of price movements using randomly colored points.
Customizable Parameters: Allows users to adjust calculation length, pivot detection, and visualization options.
◆ FUNCTIONALITY DETAILS
⬥ LOWESS Calculation:
Utilizes a weighted local regression to smooth price data.
Adapts to local trends, reducing noise while preserving important price movements.
⬥ Modified Adaptive Gaussian Moving Average:
Combines Gaussian weighting with volatility adaptation using ATR and standard deviation.
Smooths the Gaussian MA using LOWESS for enhanced trend visualization.
⬥ Pivot Point Detection and Visualization:
Identifies pivot highs and lows using customizable left and right bar counts.
Draws lines and labels to mark broke pivot points on the chart.
⬥ Breakout Tracking:
Monitors price crossovers of pivot lines to detect breakouts.
Optionally displays and updates the count of consecutive breakouts.
◆ USAGE
Trend Analysis: Use the color and direction of the smoothed Gaussian MA line to identify overall trend direction.
Breakout Trading: Monitor breakouts from pivot levels and their persistence using the breakout count feature.
Volatility Assessment: The spread of the Gaussian scatterplot can provide insights into market volatility.
⯁ USER INPUTS
Length: Sets the lookback period for LOWESS and Gaussian MA calculations (default: 30).
Pivot Length: Determines the number of bars to the left for pivot calculation (default: 5).
Count Breaks: Toggle to show the count of consecutive breakouts (default: false).
Gaussian Scatterplot: Toggle to display the Gaussian MA as a scatterplot (default: true).
⯁ TECHNICAL NOTES
Implements a custom LOWESS function for efficient local regression smoothing.
Uses a modified Gaussian MA calculation that adapts to market volatility.
Employs Pine Script's line and label drawing capabilities for clear pivot point visualization.
Utilizes random color generation for the Gaussian scatterplot to enhance visual distinction between different time periods.
The LOWESS (Locally Weighted Scatterplot Smoothing) indicator offers traders a sophisticated tool for trend analysis and breakout detection. By combining advanced smoothing techniques with pivot point analysis, it provides a comprehensive view of market dynamics. The indicator's adaptability to different market conditions and its customizable nature make it suitable for various trading styles and timeframes.
Brooks Always In [KintsugiTrading]Brooks Always In
Overview:
The "Brooks Always In Indicator" by KintsugiTrading is a tool designed for traders who follow price action methodologies inspired by Al Brooks. This indicator identifies key bar patterns and breakouts, plots an Exponential Moving Average (EMA), and highlights consecutive bullish and bearish bars. It is intended to assist traders in making informed decisions based on price action dynamics.
Features:
Consecutive Bar Patterns:
Identifies and highlights consecutive bullish and bearish bars.
Differentiates between bars that are above/below the EMA and those that are not.
Customizable EMA:
Option to display an Exponential Moving Average (EMA) with user-defined length and offset.
The EMA can be smoothed using various methods such as SMA, EMA, SMMA (RMA), WMA, and VWMA.
Breakout Patterns:
Recognizes bullish and bearish breakout bars and outside bars.
Tracks inside bars and prior bar conditions to better understand the market context.
Customizable Display:
Users can display or hide the EMA, consecutive bar patterns, and consecutive bars relative to the moving average.
How to Use:
Customize Settings:
First, I like to navigate to the top right corner of the chart (bolt icon), and change both the bull and bear body color to match the background (white/black) - this helps the user visualize the indicator far better.
Next, Toggle to display EMA, consecutive bar patterns, and consecutive bars relative to the moving average using the provided input options.
Adjust the EMA length, source, and offset as per your trading strategy.
Select the smoothing method and length for the EMA if desired.
Analyze Key Patterns:
Observe the highlighted bars on the chart to identify consecutive bullish and bearish patterns.
Use the plotted EMA to gauge the general trend and analyze the relationship between price bars and the moving average.
Informed Decision Making:
Utilize the identified bar patterns and breakouts to make informed trading decisions, such as identifying potential entry and exit points based on price action dynamics.
Good luck with your trading!
Carlos IndexOverview:
The "Carlos Index" is designed to help traders identify potential buy and sell opportunities by combining an Exponential Moving Average (EMA) with recent high and low levels of price action. This indicator is particularly useful for those looking to spot trend reversals and potential support/resistance zones.
How It Works:
EMA Calculation: The indicator uses a customizable EMA to smooth price data, making it easier to identify the underlying trend. The default length of the EMA is set to 20 periods, but this can be adjusted to suit different trading styles or timeframes.
High and Low Levels: The script plots the highest and lowest prices over the last 8 periods, providing a visual representation of recent market extremes. These levels can act as potential support and resistance areas.
Buy and Sell Signals: The indicator generates buy and sell signals based on the crossover and crossunder of the price and the EMA. A "Buy" signal is generated when the price crosses above the EMA and was higher than the previous period, indicating a potential bullish reversal. Conversely, a "Sell" signal appears when the price crosses below the EMA and was lower than the previous period, suggesting a bearish reversal.
Customization:
Length: The period length for the EMA can be adjusted to better fit the user's trading strategy.
Source: Users can select the price source for the EMA calculation, such as close, open, high, or low prices.
Originality and Usefulness:
The "Carlos Index" combines traditional technical analysis tools in a unique way to enhance traders' decision-making processes. While moving averages and price extremes are commonly used in market analysis, this indicator integrates them to provide a more holistic view of market conditions. The combination of EMA crossovers with recent high and low levels helps identify potential trend reversals and market sentiment changes more effectively.
What sets the "Carlos Index" apart is its dual approach to signal generation: it not only uses EMA crossovers but also considers the immediate price movement relative to the previous period, adding a layer of confirmation to buy and sell signals. This feature aims to reduce false signals and improve the accuracy of market entry and exit points.
Additionally, the customizable settings allow traders to tailor the indicator to their specific trading strategies, making it adaptable across different market environments and timeframes. The clear visual cues provided by the plotted EMA and price levels, along with the buy/sell labels, offer an intuitive understanding of market dynamics, even for those new to technical analysis.
Chart Usage:
This indicator should be used on a clean chart for best visibility.
The plotted lines (EMA, highs, and lows) and signals (Buy/Sell labels) provide a straightforward visual guide for traders.
By using the Carlos Index, traders can gain a clearer understanding of market dynamics and make more informed trading decisions. This script combines both trend-following and mean-reversion elements, making it versatile across various market conditions.
WODIsMA Strategy 3 MA Crossover & Bull-Bear Trend ConfirmationWODIsMA Strategy is a versatile trading strategy designed to leverage the strength of moving averages and volatility indicators to provide clear trading signals for both long and short positions. This strategy is suitable for traders looking for a systematic approach to trading with adjustable parameters to fit various market conditions and personal trading styles.
Key Features
Customizable Moving Averages:
The strategy allows users to select different types of moving averages (SMA, EMA, SMMA, WMA, VWMA) for short-term, mid-term, long-term, and bull-bear trend identification.
Each moving average can be customized with different lengths, sources (e.g., close, high, low), timeframes, and colors.
Position Management:
Users can specify the percentage of capital to use per trade and the percentage to close per partial exit.
The strategy supports both long and short positions with the ability to enable or disable each direction.
Volatility Filter:
Incorporates a volatility filter to ensure trades are only taken when market volatility is above a user-defined threshold, enhancing the strategy's effectiveness in dynamic market conditions.
Bull-Bear Trend Line:
Option to enable a bull-bear trend line that helps identify the overall market trend. Trades are taken based on the relationship between the long-term moving average and the bull-bear trend line.
Partial Exits and Full Close Logic:
The strategy includes logic for partial exits based on the crossing of mid-term and long-term moving averages.
Ensures that positions are fully closed when adverse conditions are detected, such as the price crossing below the bull-bear trend line.
Stop Loss Management:
Implements user-defined stop loss levels to manage risk effectively. The stop loss is dynamically adjusted based on the entry price and user input.
Detailed Description
Moving Average Calculation: The strategy calculates up to six different moving averages, each with customizable parameters. These moving averages help identify the short-term, mid-term, long-term trends, and overall market direction.
Trading Signals:
Long Signal: A long position is opened when the short-term moving average is above the long-term moving average, and the mid-term moving average crosses above the long-term moving average.
Short Signal: A short position is opened when the short-term moving average is below the long-term moving average, and the mid-term moving average crosses below the long-term moving average.
Volatility Condition: The strategy includes a volatility filter that activates trades only when volatility exceeds a specified threshold, ensuring trades are made in favorable market conditions.
Bull-Bear Trend Confirmation: When enabled, trades are filtered based on the relationship between the long-term moving average and the bull-bear trend line, adding another layer of confirmation.
Stop Loss and Exits:
The strategy manages risk by placing stop loss orders based on user-defined percentages.
Positions are partially or fully closed based on the crossing of moving averages and the relationship with the bull-bear trend line.
Originality and Usefulness
This strategy is original as it combines multiple moving averages and volatility indicators in a structured manner to provide reliable trading signals. Its versatility allows traders to adjust the parameters to match their trading preferences and market conditions. The inclusion of a volatility filter and bull-bear trend line adds significant value by reducing false signals and ensuring trades are taken in the direction of the overall market trend. The detailed descriptions and customizable settings make this strategy accessible and understandable for traders, even those unfamiliar with the underlying Pine Script code.
By providing clear entry, exit, and risk management rules, the WODIsMA Strategy enhances the trader's ability to navigate different market environments, making it a valuable addition to the TradingView community scripts.
Multi Deviation Scaled Moving Average [ChartPrime]Multi Deviation Scaled Moving Average ChartPrime
⯁ OVERVIEW
The Multi Deviation Scaled Moving Average is an analysis tool that combines multiple Deviation Scaled Moving Averages (DSMAs) to provide a comprehensive view of market trends. The DSMA, originally created by John Ehlers, is a sophisticated moving average that adapts to market volatility. This indicator offers a unique approach to trend analysis by utilizing a series of DSMAs with different periods and presenting the results through a color-coded line and a visual histogram.
◆ KEY FEATURES
Multiple DSMA Calculation: Computes eight DSMAs with incrementally increasing periods for multi-faceted trend analysis.
Trend Strength Visualization: Provides a color-coded moving average line indicating trend strength and direction.
Trend Percentage Histogram: Displays a visual representation of bullish vs bearish trend percentages.
Signal Generation: Identifies potential entry and exit points based on trend strength crossovers.
Customizable Parameters: Allows users to adjust the base period and sensitivity of the indicator.
◆ USAGE
Trend Direction and Strength: The color and intensity of the main indicator line provide quick insights into the current trend.
Trend Percentage Histogram: The histogram value can give you an idea of the market trend ahead
Entry and Exit Signals: Diamond-shaped markers indicate potential trade entry and exit points based on trend strength shifts.
Trend Bias Assessment: The trend percentage histogram offers a visual representation of the overall market bias.
Multi-Timeframe Analysis: By applying the indicator to different timeframes, traders can gain insights into trends across various time horizons.
⯁ USER INPUTS
Period: Sets the initial calculation period for the DSMAs (default: 30).
Sensitivity: Adjusts the step size between DSMA periods. Lower values increase sensitivity (default: 60, range: 0-100).
Source: Uses HLC3 (High, Low, Close average) as the default price source.
The Multi Deviation Scaled Moving Average indicator offers traders a sophisticated tool for trend analysis and signal generation. By combining multiple DSMAs and providing clear visual cues, it enables traders to make more informed decisions about market direction and potential entry or exit points. The indicator's customizable parameters allow for fine-tuning to suit various trading styles and market conditions.
Multi Timeframe Bull Market Support BandsMulti Timeframe Bull Market Support Bands (BMSB) Indicator
Concept and Functionality:
The Multi Timeframe Bull Market Support Bands (BMSB) indicator is a powerful tool designed to identify and visualize support levels across multiple timeframes simultaneously. The primary concept behind BMSB is to plot dynamic support bands derived from moving averages (MAs) that adapt to the prevailing bullish conditions across different timeframes. These bands act as support and resistance (S/R) levels, providing traders with critical insights into potential price bounce areas and market direction.
Key Features:
Multi Timeframe Analysis:
- The indicator plots bull market support bands for the following timeframes concurrently: Chart (with price prediction), 5 minutes (5m), 15 minutes (15m), 1 hour (1h or 60), 4 hours (4h or 240), Daily (D), 3 Days (3D), and Weekly (W).
- These bands allow traders to see how the price interacts with different support levels, potentially bouncing between them as it moves across timeframes.
Dynamic Band Visibility:
- Bands from shorter timeframes are only displayed in relevant higher timeframes:
- 5m is shown only in timeframes ≤ 15m.
- 15m is shown only in timeframes ≤ 1h.
- 1h is shown only in timeframes ≤ 4h.
- 4h is shown only in timeframes ≤ D.
- D and 3D are shown only in timeframes ≤ W.
- W is always shown.
Customizable Moving Averages:
- The period of the moving averages used to calculate the support bands can be adjusted. Any changes made will be applied across all bands to maintain consistency.
Future Band Prediction:
- If the current timeframe lacks sufficient bars to calculate a moving average, the indicator shows a blue line on the bar where the band will appear. When a new band appears on the current bar, it is highlighted in purple, allowing traders to notice the first value of the new band.
- These new bands can act as magnets, attracting price action. Knowing when a new band will appear helps traders anticipate whether the price will be drawn to the upcoming band or potentially break through it.
Benefits:
- Enhanced Market Insight: By layering support bands from multiple timeframes, traders gain a comprehensive view of market dynamics and potential bounce areas.
- Improved Decision-Making: The ability to see upcoming support bands and how the price interacts with them aids in making more informed trading decisions.
- Customization and Flexibility: Adjustable moving average periods ensure that the indicator can be tailored to fit various trading strategies and market conditions.
The Multi Timeframe Bull Market Support Bands indicator is a versatile and insightful tool for traders aiming to leverage multi-timeframe analysis to enhance their trading strategies and better understand market behavior.
Project Monday Strategy [AlgoAI System]Overview
Project Monday is a sophisticated trading strategy designed for active market participants. This strategy can be used alongside other forms of technical analysis, providing traders with additional tools to enhance their market insights. While it offers a flexible approach for identifying and exploiting market inefficiencies, Project Monday does not fit every market condition and requires adjustments. Its core principles include technical analysis and risk management, all aimed at making informed trading decisions and managing risk effectively.
Features
Project Monday Strategy works in any market and includes many features:
Efficient Trading Presets: Offers ready-to-use presets that allow traders to start efficient trading with one click.
Confirmation Signals: Provides signals to help traders validate trends, emphasizing informed decision-making (not to be followed blindly).
Reversal Signals: Identifies signals to alert traders to potential reversals, encouraging careful analysis (not to be followed blindly).
Adaptability: Can be adjusted to fit different market conditions, ensuring ongoing effectiveness.
Multi-Market Application: Suitable for use across various asset classes including stocks, forex, commodities, and cryptocurrencies.
Integration: Can be used alongside other technical analysis tools for enhanced decision-making.
Position Sizing: Allows traders to determine optimal trade size using backtesting and trading performance dashboard.
Backtesting: Supports historical testing to refine and validate the strategy.
Continuous Monitoring: Includes features for ongoing performance evaluation and strategy adjustments.
Unique Project Monday Strategy Features on TradingView:
Adaptive Position Sizing: Dynamically adjusts the size of each position based on market conditions and predefined risk management criteria, ensuring optimal trade sizing and risk exposure.
Preliminary Position Opening: Allows traders to enter a position in anticipation of a signal confirmation, enabling them to capture early market movements and improve entry points.
Preliminary Position Closing: Enables traders to exit a position before a signal reversal, helping to lock in profits and minimize potential losses during volatile market conditions.
Adjusting Strategy Parameters:
Price Band Inputs:
Project Monday Strategy uses a set of configurable inputs to tailor its behavior according to the trader's preferences. The following are the key inputs for the price band calculations. Signals are not generated when the price remains within these bands.
“Length of Calculation” determines how many historical data points are used in the trend calculation. A shorter “Length of Calculation” will make the Price Band more responsive to recent price changes but may also increase the noise and the likelihood of false signals. A longer “Length of Calculation” will make the Price Band smoother, with less noise, but may cause more lag in reacting to price changes.
“Offset” determines the position of the Gaussian filter, which is used to weight the data points in the trend calculation. The offset is expressed as a fraction of the “Length of Calculation”, with a value between 0 and 1. A higher “Offset” will shift the Gaussian filter closer to the more recent data points, making the Price Band more responsive to recent price changes but potentially increasing noise. A lower “Offset” will shift the Gaussian filter closer to the centre of the window, resulting in a smoother Price Band but potentially introducing more lag.
“Sigma” refers to the standard deviation used in the Gaussian distribution function. This parameter determines the smoothness of the curve and the degree to which data points close to the centre of the “Length of Calculation” are weighted more heavily than those further away. A smaller “Sigma” will result in a narrower Gaussian filter, leading to a more responsive Price Band but with a higher chance of noise and false signals. A larger “Sigma” will result in a wider Gaussian filter, creating a smoother Price Band but with more lag.
Adjust the “Source” inputs to specify which type of price data should be used for strategy calculations and signal generation.
“Width of Band” input determines the multiplier for the band width. A higher value of “Width of Band” makes the price band wider, which generates fewer signals due to the lower probability of the price moving outside the band. Conversely, a lower multiplier makes the band narrower, generating more signals but also increasing the likelihood of false signals.
Direction input:
The Project Monday strategy includes an input to specify the direction of trades, allowing traders to control whether the strategy should consider long positions, short positions, or both. The following input parameter is used for this purpose:
This input parameter allows traders to define the type of positions the strategy will take. It has three options:
Only Long: The strategy will generate signals exclusively for buying or closing short positions, focusing on potential uptrends.
Only Short: The strategy will generate signals exclusively for selling or closing long positions, focusing on potential downtrends.
Both: The strategy will generate signals for both buying (long positions) and selling (short positions), allowing for a more comprehensive trading approach that captures opportunities in both rising and falling markets.
Signals Filter:
The Project Monday strategy includes inputs to filter signals based on higher timeframes and the length of the data used for filtering. These inputs help traders refine the strategy's performance by considering broader market trends and smoothing out short-term fluctuations.
Filter Timeframe input specifies the timeframe used for filtering signals. By choosing a higher timeframe, traders can filter out noise from shorter timeframes and focus on more significant trends. The options range from intraday minutes (e.g., 1, 5, 15 minutes) to daily (1D, 2D, etc.), weekly (1W, 2W, etc.), and monthly (1M) timeframes. This allows traders to align their strategy with their preferred trading horizon and market perspective.
Filter Length input defines the number of data points used for filtering signals on the selected timeframe. A longer filter length will smooth out the data more, helping to identify sustained trends and reduce the impact of short-term fluctuations. Conversely, a shorter filter length will make the filter more responsive to recent price changes, potentially generating more signals but also increasing sensitivity to market noise.
Adaptive Position Size:
The Project Monday strategy incorporates inputs for unique feature Adaptive Position Sizing (APS), which dynamically adjusts the size of trades based on market conditions and specified parameters. This feature helps optimize risk management and trading performance.
Enable Adaptive Position Size: Users can check or uncheck this box to enable or disable the Adaptive Position Size feature. When checked, the strategy dynamically adjusts position sizes based on the defined parameters. This allows traders to scale their positions according to market volatility and other factors, enhancing risk management and potentially improving returns. When unchecked, the strategy will not adjust position sizes adaptively, and positions will remain fixed as per other settings.
“Timeframe for Adaptive Position Size “input specifies the timeframe used for calculating the position size. Options range from intraday minutes (e.g., 30, 60 minutes) to daily (1D, 3D), weekly (1W), and monthly (1M) timeframes. Selecting an appropriate timeframe helps align position sizing calculations with the trader’s overall strategy and market perspective, ensuring that position sizes are adjusted based on relevant market data.
“APS Length” input defines the number of data points used to calculate the adaptive position size. A longer APS length will result in higher position sizes. Conversely, a shorter APS length will result in smaller position sizes.
Anticipatory Trading:
Project Monday Strategy includes inputs for unique feature Anticipatory Trading, allowing traders to open and close positions preliminarily based on certain conditions. This feature aims to provide an edge by taking action before traditional signals confirm.
Enable Preliminary Position Opening: Users can check or uncheck this box to enable or disable Preliminary Position Opening. When enabled, the strategy will open positions based on preliminary conditions before the standard signals are confirmed. This can help traders capitalize on early trend movements and potentially gain a better entry point.
Enable Preliminary Position Closing: Users can check or uncheck this box to enable or disable Preliminary Position Closing. When enabled, the strategy will close positions based on preliminary conditions before the standard exit signals are confirmed. This can help traders lock in profits or limit losses by exiting positions at the early signs of trend reversals.
“Position Size in %” input specifies the position size as a percentage of the trading capital. By setting this value, traders can control the amount of capital allocated to each trade. For example, a risk value of 40% means that 40% of the available trading capital will be used for each anticipatory trade. This helps in managing risk and ensuring that the position size aligns with the trader's risk tolerance and overall strategy.
Usage:
Signal Generation
Long signal indicates a potential uptrend, suggesting either buying or closing a short position. Short signal indicates a potential downtrend, suggesting either selling or closing a long position. Signals are generated on your chart when the price moves beyond a calculated price band based on the current trend.
Signal Filtering
The strategy includes a filtering mechanism based on the current or another timeframe. Filtering works best with higher timeframes. This component calculates the trend on a higher timeframe and predicts the trend, ensuring trades on the current timeframe are only opened if they align with the higher timeframe trend. Setting the right filter timeframe is crucial for obtaining the best signals.
Position Direction
Users can choose the direction of positions to open via the settings box. Options include only long positions, only short positions, or both.
Adaptive Position Size (APS)
Users can enable the Adaptive Position Size feature to adjust position sizes based on trend strength. The strategy evaluates the strength of the current trend based on a higher timeframe. The stronger the trend, the larger the position size for opening a position.
Anticipatory Trading
Users can activate this unique feature to enhance trading decisions. The strategy assesses the likelihood of receiving a main signal. If the opportunity appears strong, it opens a partial position, as specified in the settings box. As the probability of the signal strengthens, the strategy gradually increases the position size.
Exit Strategy
The strategy exits positions based on receiving a reverse signal. Positions opened through “Anticipatory trading” are exited incrementally as each preliminary signal reverses.
By following these steps, traders can implement the strategy to navigate various market scenarios, manage risk, and adjust trading performance over time. Adjusting parameters and monitoring signals diligently are key to adapting the strategy to individual trading styles and market conditions.
You will get
By purchasing the Project Monday strategy, you not only gain access to a cutting-edge system but also receive ready-to-use presets designed to help you start trading immediately and achieve optimal results. Additionally, you benefit from comprehensive support and the option to request custom presets for your desired financial instruments through our dedicated support team, ensuring you have the tools and assistance needed for successful trading.
Risk Disclaimer
This information is not a personalized investment recommendation, and the financial instruments or transactions mentioned in it may not be appropriate for your financial situation, investment objective(s), risk tolerance, and/or expected return. AlgoAI shall not be liable for any losses incurred in the event of transactions or investments in financial instruments mentioned in this information.
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