MacroTrend VisionThe "MacroTrend Vision" indicator is crafted with a singular goal – to provide traders with a quick and insightful snapshot of a country's global index. Seamlessly combining macroeconomic and technical perspectives, this tool is designed for those seeking a straightforward yet comprehensive overview. Let's explore the key features that make the "MacroTrend Vision" a valuable asset for traders looking to grasp both the big-picture economic context and technical nuances.
1. Long-Term Vision with Weekly Periods:
Gain a genuine long-term perspective with the ability to process 2500 weekly periods. This feature ensures a holistic understanding of global indices from both macroeconomic and technical viewpoints.
2. Composite Leading Indicator (CLI) Conditions:
Integrate both macroeconomic trends and technical signals through Composite Leading Indicator (CLI) conditions derived from the Relative Strength Index (RSI), offering a comprehensive outlook for informed decision-making.
3. Deviation Bands for Volatility Analysis:
Refine market analysis with strategically integrated deviation bands (0.2 and 0.4) based on smoothed linear regression. Anticipate volatility and potential trend shifts, aligning macro and technical insights.
4. Logarithmic Scale Transformation:
Enhance precision in understanding price movements with a logarithmic scale transformation, especially beneficial for assets with exponential growth patterns.
5. Separated Window for Easy Navigation:
Streamline your analysis with a user-friendly design – a separated window allowing easy navigation through different symbols without altering indicator settings.
6. Alert System for CLI Conditions:
Stay informed about critical shifts with an alert system for both long and close conditions based on the RSI of the CLI. Even during periods of limited chart monitoring, this feature keeps you connected to macroeconomic and technical changes.
In essence, the "MacroTrend Vision" is your go-to tool for a balanced view, simplifying the complexities of global indices with a blend of macroeconomic insights and technical clarity.
在腳本中搜尋"Relative Strength Index (RSI)"
Based RSI (BullDozz)Installation: To use this script, open TradingView and create a new Pine Script strategy. You can paste the code provided into the Pine Script editor.
Customizable Inputs: The script includes various input parameters that you can customize to fit your trading preferences. These parameters are defined using the input function and include values like length, TPPercent, and others. You can adjust these values based on your trading strategy.
Strategy Signals: The script generates buy and sell signals based on the conditions specified in the buySignal and sellSignal variables. These signals are derived from the analysis of the oscillator (osc) and the Relative Strength Index (rsi). When a buy signal occurs, the script enters a long position, and when a sell signal occurs, it enters a short position.
Take Profit: The script includes a take profit feature (useTP) that allows you to enable or disable take profit orders. When enabled, it calculates take profit levels based on the specified percent (TPPercent) and attaches them to the open positions.
Plotting: The script also visualizes the oscillator (osc) and a midline (0) on the chart using histogram-style bars. The colors of these bars change based on the oscillator's direction.
ALMA Smoothed Gaussian Moving AverageThis indicator is an altered version of the Gaussian Moving Average (GMA) (Credit to author: © LeafAlgo ). The GMA applies weights to the prices, giving more importance to the values closer to the current period and gradually diminishing the significance of older prices. The ALMA Smoothed Gaussian Moving Average (ASGMA) applies an ALMA smoothing to its price data to minimize lag and provide a more accurate representation of the underlying trend by dynamically adapting to changing market conditions. The Arnaud Legoux Moving Average (ALMA) is a specialized smoothing technique that adjusts the weights of the moving average based on market volatility. Its calculation uses Wavelet Transform techniques which enables this type of smoothing to capture both high-frequency and low-frequency components of a signal or data. The rationale for this mashup between ALMA and Gaussian filtering is to smooth the moving average line over the smoothed price data and produce stronger trend signals.
ASGMA serves as a trend-following indicator, identifying both bullish and bearish trends. It provides buy and sell signals indicated by "B" and "S" labels plotted alongside the price data. Additionally, the ASGMA's Exponential Moving Average (EMA) line alternates between green and red, indicating bullish and bearish momentum, respectively.
The ASGMA also incorporates two popular momentum indicators, the Relative Strength Index (RSI) and the Chande Momentum Oscillator (CMO). The inclusion of these indicators aims to enhance trend identification and reversal signals. For a strong buy signal, all three indicators (RSI, CMO, and ASGMA) must indicate bullish conditions, resulting in a vertical green line. Conversely, a vertical red line is plotted when all indicators indicate bearish conditions, representing a strong sell signal.
The ASGMA, with its unique combination of smoothing techniques and indicator amalgamation, provides traders and investors with powerful analytical tools. It can be applied in trend-following strategies using the regular buy and sell signals generated by labels and the EMA line. Alternatively, the vertical lines offer stronger buy and sell signals. These features aid in identifying potential entry and exit points, thereby enhancing trading decisions and market analysis. However, it is important to remember that the future performance of any trading strategy is fundamentally unknowable, and past results do not guarantee future performance.
Boxes_PlotIn the world of data visualization, heatmaps are an invaluable tool for understanding complex datasets. They use color gradients to represent the values of individual data points, allowing users to quickly identify patterns, trends, and outliers in their data. In this post, we will delve into the history of heatmaps, and then discuss how its implemented.
The "Boxes_Plot" library is a powerful and versatile tool for visualizing multiple indicators on a trading chart using colored boxes, commonly known as heatmaps. These heatmaps provide a user-friendly and efficient method for analyzing the performance and trends of various indicators simultaneously. The library can be customized to display multiple charts, adjust the number of rows, and set the appropriate offset for proper spacing. This allows traders to gain insights into the market and make informed decisions.
Heatmaps with cells are interesting and useful for several reasons. Firstly, they allow for the visualization of large datasets in a compact and organized manner. This is especially beneficial when working with multiple indicators, as it enables traders to easily compare and contrast their performance. Secondly, heatmaps provide a clear and intuitive representation of the data, making it easier for traders to identify trends and patterns. Finally, heatmaps offer a visually appealing way to present complex information, which can help to engage and maintain the interest of traders.
History of Heatmaps
The concept of heatmaps can be traced back to the 19th century when French cartographer and sociologist Charles Joseph Minard used color gradients to visualize statistical data. He is well-known for his 1869 map, which depicted Napoleon's disastrous Russian campaign of 1812 using a color gradient to represent the dwindling size of Napoleon's army.
In the 20th century, heatmaps gained popularity in the fields of biology and genetics, where they were used to visualize gene expression data. In the early 2000s, heatmaps found their way into the world of finance, where they are now used to display stock market data, such as price, volume, and performance.
The boxes_plot function in the library expects a normalized value from 0 to 100 as input. Normalizing the data ensures that all values are on a consistent scale, making it easier to compare different indicators. The function also allows for easy customization, enabling users to adjust the number of rows displayed, the size of the boxes, and the offset for proper spacing.
One of the key features of the library is its ability to automatically scale the chart to the screen. This ensures that the heatmap remains clear and visible, regardless of the size or resolution of the user's monitor. This functionality is essential for traders who may be using various devices and screen sizes, as it enables them to easily access and interpret the heatmap without needing to make manual adjustments.
In order to create a heatmap using the boxes_plot function, users need to supply several parameters:
1. Source: An array of floating-point values representing the indicator values to display.
2. Name: An array of strings representing the names of the indicators.
3. Boxes_per_row: The number of boxes to display per row.
4. Offset (optional): An integer to offset the boxes horizontally (default: 0).
5. Scale (optional): A floating-point value to scale the size of the boxes (default: 1).
The library also includes a gradient function (grad) that is used to generate the colors for the heatmap. This function is responsible for determining the appropriate color based on the value of the indicator, with higher values typically represented by warmer colors such as red and lower values by cooler colors such as blue.
Implementing Heatmaps as a Pine Script Library
In this section, we'll explore how to create a Pine Script library that can be used to generate heatmaps for various indicators on the TradingView platform. The library utilizes colored boxes to represent the values of multiple indicators, making it simple to visualize complex data.
We'll now go over the key components of the code:
grad(src) function: This function takes an integer input 'src' and returns a color based on a predefined color gradient. The gradient ranges from dark blue (#1500FF) for low values to dark red (#FF0000) for high values.
boxes_plot() function: This is the main function of the library, and it takes the following parameters:
source: an array of floating-point values representing the indicator values to display
name: an array of strings representing the names of the indicators
boxes_per_row: the number of boxes to display per row
offset (optional): an integer to offset the boxes horizontally (default: 0)
scale (optional): a floating-point value to scale the size of the boxes (default: 1)
The function first calculates the screen size and unit size based on the visible chart area. Then, it creates an array of box objects representing each data point. Each box is assigned a color based on the value of the data point using the grad() function. The boxes are then plotted on the chart using the box.new() function.
Example Usage:
In the example provided in the source code, we use the Relative Strength Index (RSI) and the Stochastic Oscillator as the input data for the heatmap. We create two arrays, 'data_1' containing the RSI and Stochastic Oscillator values, and 'data_names_1' containing the names of the indicators. We then call the 'boxes_plot()' function with these arrays, specifying the desired number of boxes per row, offset, and scale.
Conclusion
Heatmaps are a versatile and powerful data visualization tool with a rich history, spanning multiple fields of study. By implementing a heatmap library in Pine Script, we can enhance the capabilities of the TradingView platform, making it easier for users to visualize and understand complex financial data. The provided library can be easily customized and extended to suit various use cases and can be a valuable addition to any trader's toolbox.
Library "Boxes_Plot"
boxes_plot(source, name, boxes_per_row, offset, scale)
Parameters:
source (float ) : - an array of floating-point values representing the indicator values to display
name (string ) : - an array of strings representing the names of the indicators
boxes_per_row (int) : - the number of boxes to display per row
offset (int) : - an optional integer to offset the boxes horizontally (default: 0)
scale (float) : - an optional floating-point value to scale the size of the boxes (default: 1)
Weighted Moving Average Indicator (WMAI) 50/100/200 SMA + 21 EMAThe Weighted Moving Average Indicator (WMAI) is a custom technical analysis tool that combines the information from three Simple Moving Averages (SMA) and one Exponential Moving Average (EMA) to create a single line on the chart. This line can be used to identify trends, potential entry and exit points, and overall market direction. Here's how to use this indicator:
Identifying trends: When the WMAI line is moving upwards, it signals a bullish trend, meaning that the asset's price is generally increasing. Conversely, when the WMAI line is moving downwards, it signals a bearish trend, indicating that the asset's price is generally decreasing. A flat WMAI line suggests a sideways or consolidating market.
Potential entry and exit points: You can use the WMAI line in combination with the asset's price or other technical indicators to identify potential entry and exit points for trades. For example, when the price crosses above the WMAI line, it might be considered a buy signal, as it suggests a potential upward trend. Conversely, when the price crosses below the WMAI line, it might be considered a sell signal, indicating a potential downward trend. Keep in mind that, like any other indicator, WMAI is not foolproof and should be used in conjunction with other technical analysis tools and techniques to increase the chances of successful trades.
Support and resistance levels: The WMAI line can act as a dynamic support and resistance level. When the price is above the WMAI line, the line can act as a support level, making it less likely for the price to drop below the line. Conversely, when the price is below the WMAI line, it can act as a resistance level, making it harder for the price to rise above the line.
Confirming signals from other indicators: You can use the WMAI line to confirm signals from other technical analysis tools. For instance, if you use a momentum oscillator like the Relative Strength Index (RSI) to identify overbought or oversold conditions, you can look for confluence with the WMAI line. If the WMAI line is also pointing in the same direction as the RSI signal, it can add confidence to the trade.
RSI Divergence Method█ OVERVIEW
This is a divergence indicator based on Relative Strength Index (RSI).
My attempt to make this indicator updated based on latest pine script features such as type, object and method.
█ FEATURES
1. Color of plot and label is based on contrast color of chart background. Able to customize color from style menu.
2. Big divergence (Regular Divergence) is based on lime / red color.
3. Small divergence (Hidden Divergence) is based on contrast color of chart background.
█ EXAMPLES / USAGES
QQE of Parabolic-Weighted Velocity [Loxx]QQE of Parabolic-Weighted Velocity is a QQE indicator that takes as its input parabolic-weighted velocity calculation. This version can help in determining trend. Adjust the calculating period to your trading style: longer - to trend traders, shorter - for scalping.
What is Qualitative Quantitative Estimation (QQE)?
The Qualitative Quantitative Estimation (QQE) indicator works like a smoother version of the popular Relative Strength Index ( RSI ) indicator. QQE expands on RSI by adding two volatility based trailing stop lines. These trailing stop lines are composed of a fast and a slow moving Average True Range (ATR).
There are many indicators for many purposes. Some of them are complex and some are comparatively easy to handle. The QQE indicator is a really useful analytical tool and one of the most accurate indicators. It offers numerous strategies for using the buy and sell signals. Essentially, it can help detect trend reversal and enter the trade at the most optimal positions.
Included:
Loxx's Expanded Source Types
Alerts
Signals
Bar coloring
Double-Smoothed Stochastic QQE [Loxx]Double-Smoothed Stochastic QQE is a QQE indicator that uses a double-smoothed stochastic calculation for it's source input instead of traditional RSI.
What is the double-smoothed stochastic?
The Double Smoothed Stochastic indicator was created by William Blau. It applies Exponential Moving Averages (EMAs) of two different periods to a standard Stochastic %K. The components that construct the Stochastic Oscillator are first smoothed with the two EMAs. Then, the smoothed components are plugged into the standard Stochastic formula to calculate the indicator.'
What is Qualitative Quantitative Estimation (QQE)?
The Qualitative Quantitative Estimation (QQE) indicator works like a smoother version of the popular Relative Strength Index ( RSI ) indicator. QQE expands on RSI by adding two volatility based trailing stop lines. These trailing stop lines are composed of a fast and a slow moving Average True Range (ATR).
There are many indicators for many purposes. Some of them are complex and some are comparatively easy to handle. The QQE indicator is a really useful analytical tool and one of the most accurate indicators. It offers numerous strategies for using the buy and sell signals. Essentially, it can help detect trend reversal and enter the trade at the most optimal positions.
Included:
Loxx's Expanded Source Types
Alerts
Signals
Bar coloring
RSI MTF Ob+OsHello Traders,
This indicator use the same concept as my previous indicator "CCI MTF Ob+Os".
It is a simple "Relative Strength Index" ( RSI ) indicator with multi-timeframe (MTF) overbought and oversold level.
It can detect overbought and oversold level up to 5 timeframes, which help traders spot potential reversal point more easily.
There are options to select 1-5 timeframes to detect overbought and oversold.
Aqua Background is "Oversold" , looking for "Long".
Orange Background is "Overbought" , looking for "Short".
Have fun :)
Multi Time Frame (MTF) RSIThis script can display Multi time frame (MTF) Relative Strength Index (RSI) values. It works on any chart and appears at the top left of the screen.
1. It can plot values from 4 different time frames which can be customized.
2. Higher time frame indicates the main trend
3. Overbought and oversold levels are highlighted with different colours.
unRekt - KISS StochieStochie is the StochRSI indicator and is part of the ''keeping it simple' series that have a similar color scheme. The Stochastic RSI technical indicator applies the Stochastic Oscillator to values of the Relative Strength Index (RSI). The indicator thus produces two main plots FullK and FullD oscillating between oversold and overbought levels. The StochRSI can also be used to detect divergence and trend.
Failure Swing IndicatorIdentify Failure Swing nice and easy
J. Welles Wilder Jr. describes Failure Swings as specific chart patterns used in conjunction with the Relative Strength Index (RSI) to identify potential reversals in price trends.
These patterns signal weakening momentum and can indicate a shift in market direction
Wilder emphasized that these patterns are more reliable when confirmed by price action or other technical indicators.
BTCUSDT Premium Prices and EMA360The Exponential Moving Average (EMA) is a widely used technical indicator in trading that helps analysts and traders identify price trends over a specified period. Unlike the Simple Moving Average (SMA), which treats all data points equally, the EMA gives more weight to recent prices, making it more sensitive to recent price movements. This characteristic allows the EMA to react quickly to changes in market conditions, providing timely insights into potential trends.
## **Key Features of EMA**
- **Weighting Mechanism**: The EMA uses a smoothing factor that emphasizes recent price data while still considering older observations. This leads to a more dynamic representation of price trends compared to the SMA .
- **Trend Identification**: The EMA is particularly effective for identifying the direction of a stock's price movement. A rising EMA indicates an uptrend, while a declining EMA suggests a downtrend. Traders often use multiple EMAs with different periods to spot crossovers, which can signal potential buy or sell opportunities .
- **Calculation**: To calculate the EMA, one typically starts with an initial Simple Moving Average (SMA) for the first period, then applies the following formula for subsequent periods:
$$
\text{EMA}_{\text{today}} = \left(\text{Price}_{\text{today}} \times \left(\frac{2}{N + 1}\right)\right) + \left(\text{EMA}_{\text{yesterday}} \times \left(1 - \frac{2}{N + 1}\right)\right)
$$
Where $$N$$ is the number of periods .
## **Applications in Trading**
Traders utilize the EMA in various strategies, including:
- **Crossover Strategies**: By monitoring two EMAs of different lengths (e.g., 50-day and 200-day), traders can identify bullish or bearish signals when one crosses above or below the other .
- **Combining Indicators**: The EMA can be combined with other indicators like the Relative Strength Index (RSI) or Moving Average Convergence Divergence (MACD) for enhanced decision-making .
In summary, the Exponential Moving Average is a crucial tool for traders seeking to navigate market trends effectively. Its ability to prioritize recent data makes it an essential component of many trading strategies, providing insights that can lead to informed investment decisions.
Swing & Day Trading Strategy dddddThis TradingView Pine Script is designed for swing and day trading, incorporating multiple technical indicators and tools to enhance decision-making. It calculates and plots exponential moving averages (EMAs) for 5, 9, 21, 50, and 200 periods to identify trends and crossovers. The Relative Strength Index (RSI) and Moving Average Convergence Divergence (MACD) provide momentum and overbought/oversold signals. The script dynamically identifies and marks support and resistance levels based on recent highs and lows, while also detecting and labeling key candlestick patterns such as bullish and bearish engulfing, doji, and hammer candles. Bullish and bearish signals are highlighted on the chart with green and red backgrounds, respectively, and alerts are generated to notify traders of these conditions. All visualizations, including EMAs, support/resistance lines, and candlestick labels, are overlaid directly on the stock chart for easy interpretation. This comprehensive approach assists traders in spotting potential trading opportunities effectively.
Pivot PointsPivot Points Indicator
The Pivot Points indicator highlights areas on the chart where candles close in opposite colors. These points occur when the price shifts from bullish to bearish, or vice versa, indicating potential reversals or continuation patterns. These points are more easily seen on a line chart and represent areas where the price changes direction to create peak formations.
Foundational Concepts
Before diving into the indicator, it’s important to understand a few key concepts:
When price is trending upward, it creates higher highs and higher lows. Each high or low acts as a pivot point. In an uptrend, the price is more likely to break the previous high (pivot point) and continue higher. You can enter a buy trade when the price breaks the previous high, anticipating the continuation of the trend.
When price is trending downward, it creates lower lows and lower highs. Each high or low is also a pivot point. In a downtrend, the price is more likely to break the previous low (pivot point) and continue lower. You can enter a sell trade when the price breaks the previous low, anticipating the continuation of the trend.
For reversal trades, it’s helpful to be familiar with chart patterns like double tops, double bottoms, and head and shoulders. The Pivot Points indicator can assist in identifying these patterns, helping you determine entry points, as well as where to place your stop loss.
Recommended Setup
It’s recommended to have two charts open side by side: one displaying a line chart and the other showing a candlestick chart, with the Pivot Points indicator applied to both. This setup allows you to easily identify the market structure and price action as it approaches these levels. You can also add a 20-period Simple Moving Average (SMA) to both charts to help identify the overall trend. Additionally, consider adding the Relative Strength Index (RSI) to the line chart to confirm overbought or oversold conditions.
This approach can be used on any timeframe.
Contributing
If you have suggestions, improvements, or bug fixes, I encourage you to submit pull requests. Collaboration helps make the indicator more versatile and useful for everyone.
Disclaimer
Any trading decisions you make are entirely your responsibility.
The MetaTrader 5 version of this indicator is available on my GitHub repository: roshaneforde/pivot-points-indicator
The Most Powerful TQQQ EMA Crossover Trend Trading StrategyTQQQ EMA Crossover Strategy Indicator
Meta Title: TQQQ EMA Crossover Strategy - Enhance Your Trading with Effective Signals
Meta Description: Discover the TQQQ EMA Crossover Strategy, designed to optimize trading decisions with fast and slow EMA crossovers. Learn how to effectively use this powerful indicator for better trading results.
Key Features
The TQQQ EMA Crossover Strategy is a powerful trading tool that utilizes Exponential Moving Averages (EMAs) to identify potential entry and exit points in the market. Key features of this indicator include:
**Fast and Slow EMAs:** The strategy incorporates two EMAs, allowing traders to capture short-term trends while filtering out market noise.
**Entry and Exit Signals:** Automated signals for entering and exiting trades based on EMA crossovers, enhancing decision-making efficiency.
**Customizable Parameters:** Users can adjust the lengths of the EMAs, as well as take profit and stop loss multipliers, tailoring the strategy to their trading style.
**Visual Indicators:** Clear visual plots of the EMAs and exit points on the chart for easy interpretation.
How It Works
The TQQQ EMA Crossover Strategy operates by calculating two EMAs: a fast EMA (default length of 20) and a slow EMA (default length of 50). The core concept is based on the crossover of these two moving averages:
- When the fast EMA crosses above the slow EMA, it generates a *buy signal*, indicating a potential upward trend.
- Conversely, when the fast EMA crosses below the slow EMA, it produces a *sell signal*, suggesting a potential downward trend.
This method allows traders to capitalize on momentum shifts in the market, providing timely signals for trade execution.
Trading Ideas and Insights
Traders can leverage the TQQQ EMA Crossover Strategy in various market conditions. Here are some insights:
**Scalping Opportunities:** The strategy is particularly effective for scalping in volatile markets, allowing traders to make quick profits on small price movements.
**Swing Trading:** Longer-term traders can use this strategy to identify significant trend reversals and capitalize on larger price swings.
**Risk Management:** By incorporating customizable stop loss and take profit levels, traders can manage their risk effectively while maximizing potential returns.
How Multiple Indicators Work Together
While this strategy primarily relies on EMAs, it can be enhanced by integrating additional indicators such as:
- **Relative Strength Index (RSI):** To confirm overbought or oversold conditions before entering trades.
- **Volume Indicators:** To validate breakout signals, ensuring that price movements are supported by sufficient trading volume.
Combining these indicators provides a more comprehensive view of market dynamics, increasing the reliability of trade signals generated by the EMA crossover.
Unique Aspects
What sets this indicator apart is its simplicity combined with effectiveness. The reliance on EMAs allows for smoother signals compared to traditional moving averages, reducing false signals often associated with choppy price action. Additionally, the ability to customize parameters ensures that traders can adapt the strategy to fit their unique trading styles and risk tolerance.
How to Use
To effectively utilize the TQQQ EMA Crossover Strategy:
1. **Add the Indicator:** Load the script onto your TradingView chart.
2. **Set Parameters:** Adjust the fast and slow EMA lengths according to your trading preferences.
3. **Monitor Signals:** Watch for crossover points; enter trades based on buy/sell signals generated by the indicator.
4. **Implement Risk Management:** Set your stop loss and take profit levels using the provided multipliers.
Regularly review your trading performance and adjust parameters as necessary to optimize results.
Customization
The TQQQ EMA Crossover Strategy allows for extensive customization:
- **EMA Lengths:** Change the default lengths of both fast and slow EMAs to suit different time frames or market conditions.
- **Take Profit/Stop Loss Multipliers:** Adjust these values to align with your risk management strategy. For instance, increasing the take profit multiplier may yield larger gains but could also increase exposure to market fluctuations.
This flexibility makes it suitable for various trading styles, from aggressive scalpers to conservative swing traders.
Conclusion
The TQQQ EMA Crossover Strategy is an effective tool for traders seeking an edge in their trading endeavors. By utilizing fast and slow EMAs, this indicator provides clear entry and exit signals while allowing for customization to fit individual trading strategies. Whether you are a scalper looking for quick profits or a swing trader aiming for larger moves, this indicator offers valuable insights into market trends.
Incorporate it into your TradingView toolkit today and elevate your trading performance!
Strong Support and Resistance with EMAs @viniciushadek
### Strategy for Using Continuity Points with 20 and 9 Period Exponential Moving Averages, and Support and Resistance
This strategy involves using two exponential moving averages (EMA) - one with a 20-period and another with a 9-period - along with identifying support and resistance levels on the chart. Combining these tools can help determine trend continuation points and potential entry and exit points in market operations.
### 1. Setting Up the Exponential Moving Averages
- **20-Period EMA**: This moving average provides a medium-term trend view. It helps smooth out price fluctuations and identify the overall market direction.
- **9-Period EMA**: This moving average is more sensitive and reacts more quickly to price changes, providing short-term signals.
### 2. Identifying Support and Resistance
- **Support**: Price levels where demand is strong enough to prevent the price from falling further. These levels are identified based on previous lows.
- **Resistance**: Price levels where supply is strong enough to prevent the price from rising further. These levels are identified based on previous highs.
### 3. Continuity Points
The strategy focuses on identifying trend continuation points using the interaction between the EMAs and the support and resistance levels.
### 4. Buy Signals
- When the 9-period EMA crosses above the 20-period EMA.
- Confirm the entry if the price is near a support level or breaking through a resistance level.
### 5. Sell Signals
- When the 9-period EMA crosses below the 20-period EMA.
- Confirm the exit if the price is near a resistance level or breaking through a support level.
### 6. Risk Management
- Use appropriate stops below identified supports for buy operations.
- Use appropriate stops above identified resistances for sell operations.
### 7. Validating the Trend
- Check if the trend is validated by other technical indicators, such as the Relative Strength Index (RSI) or Volume.
### Conclusion
This strategy uses the combination of exponential moving averages and support and resistance levels to identify continuity points in the market trend. It is crucial to confirm the signals with other technical analysis tools and maintain proper risk management to maximize results and minimize losses.
Implementing this approach can provide a clearer view of market movements and help make more informed trading decisions.
Linear Regression InterceptLinear Regression Intercept (LRI) is a statistical method used to forecast future values based on past data. Financial markets frequently employ it to identify the underlying trend and determine when prices are overextended. Linear regression utilizes the least squares method to create a trendline by minimizing the distance between observed price data and the line. The LRI indicator calculates the intercept of this trendline for each data point, providing insights into price trends and potential trading opportunities.
Calculation and Interpretation of the LRI
The linear regression intercept is calculated using the following formula:
LRI = Y - (b * X)
Where Y represents the dependent variable (price), b is the slope of the regression line, and X is the independent variable (time). To determine the slope b, you can use the formula:
b = Σ / Σ(X - X_mean)^2
Once you have computed the LRI, it can be interpreted as the point at which the regression line intersects the Y-axis (price) when the independent variable (time) is zero. A positive LRI value indicates an upward trend, while a negative value suggests a downward trend. Traders can adjust the parameters of the LRI by modifying the period over which the linear regression is computed, which can impact the indicator’s sensitivity to recent price changes.
How to Use the LRI in Trading
To effectively use the LRI in trading, traders should consider the following:
Understanding the signals generated by the technical indicator: A rising LRI suggests an upward trend, whereas a falling LRI indicates a downward trend. Traders may use this information to help determine the market’s direction and identify reversals.
Combining the technical indicator with other indicators: The LRI can be used in conjunction with other technical indicators, such as moving averages, the Relative Strength Index (RSI), or traditional linear regression lines, to obtain a more comprehensive view of the market. In the case of traditional linear regression lines, the LRI helps traders identify the starting point of the trend, providing additional context to the overall trend direction.
Using the technical indicator for entry and exit signals: When the LRI crosses above or below a specific threshold, traders may consider it a potential entry or exit point. For example, if the LRI crosses above zero, it might signal a possible buying opportunity.
MTF HalfTrendIntroduction
A half-trend indicator is a technical analysis tool that uses moving averages and price data to find potential trend reversal and entry points in the form of graphical arrows showing market turning points.
The salient features of this indicator are:
- It uses the phenomenon of moving averages.
- It is a momentum indicator.
- It can indicate a trend change.
- It is capable of detecting a bullish or bearish trend reversal.
- It can signal to sell/buy.
- It is a real-time indicator.
Multi-Timeframe Application
A standout feature is its flexibility across timeframes. Traders have the liberty to choose any timeframe on the chart, enhancing the tool's versatility and making it suitable for both short-term and long-term analyses.
Principle of the Half Trend indicator
This indicator is based on the moving averages. The moving average is the average of the fluctuation or change in the price of an asset. These averages are taken for a time interval.
So, a half-trend indicator takes the moving averages phenomenon as its principle for working. The most commonly used moving averages in a half trend indicator are:
- Relative strength index (RSI)
- EMA (estimated moving average)
Components of a Half Trend indicator
There are two main components of a half trend indicator:
- Half trend line
- Arrows
- ATR lines
Half trend line
Half trend line represents this indicator on a candlestick chart. This line shows the trend of a chart in real-time. A half-trend line is based on the moving averages.
There are two further components of a half-trend line:
- Redline
- Blue line
A red line represents a bearish trend. When the half-trend line turns red, a trend is facing a dip. It is time for the bears to take control of the market. A bearish control of the market represents the domination of sellers in the market.
On the other hand, the blue line represents the bullish nature of the market. It tells a trader that the bullish sentiment of the market is prevailing. A bullish market means the number of buyers is significantly greater than the number of sellers.
Moreover, a trader can change these colors to his choice by customization.
Arrows
There are two types of arrows in this indicator which help a trader with the entry and exit points. These arrows are,
- Blue arrow
- Red arrow
A blue arrow signals a buying trade; on the other hand, a red arrow tells a trader about the selling of the assets. These arrows work with the moving average line to formulate a trading strategy.
The color of these arrows is changed if a trader desires so.
ATR lines
The ATR blue and red lines represent the Average True Range of the Half trend line. They may be used as stop loss or take profit levels.
Pros and Cons
Pros
- It is a very easy to eyes indicator.
- This is a very useful friendly indicator.
- It provides sufficient information to beginner traders.
- It provides sufficient information for entry points in a trade.
- A half-trend indicator provides a good exit strategy for a trader.
- It provides information about market reversals.
- It helps a trader to find a bullish and bearish sentiment in the market.
Cons
- It is a real-time indicator. So, it can lag.
- The lagging of this indicator can lead to miss opportunities.
- The most advanced and professional traders may not rely on this indicator for crucial trading decisions.
- The lagging of this indicator can predict false reversals of the market.
- It can create false signals.
- It requires the confluence of the other technical tools for a better success ratio.
Settings for Half Trend indicator
The default settings for half trend indicator are:
Amplitude = 2
Channel deviation = 2
Different markets or financial instruments may require different settings for optimal execution.
Amplitude: The degree that the Half trend line takes the internal variables into consideration. The higher the number, the fewer trades. The default value is 2.
Channel deviation: The ATR value calculation from the Half trend line. The default value is 2.
Trading strategy
It is an effective indicator in terms of strategy formation for a trading setup. The new and beginner trades can take benefit from this indicator for the formulation of a good trading setup. This indicator also helps seasoned and professional traders formulate a good trading setup with other technical tools.
The trading strategy involving a half-trend indicator is divided into three parts:
- Entry and exit
- Risk management
- Take profit
Entry and exit
It is an effective indicator that provides sufficient information about the entry and exit points in a trading setup. The profit of a trader is directly proportional to the appropriate entry and exit points. So, it is a crucial step in any trading setup.
The blue and red arrows provide information about the entry and exit points in a trading setup. Furthermore, the entry and exit for the bullish and bearish setups are as follows.
Entry and exit for a bullish setup
If a blue arrow appears under the half-trend line, it means the bullish sentiment of the market is getting stronger in the future. So, it is a signal for entry in a bullish setup.
As the red arrow appears on the chart, it is a signal to exit your trade. The red arrow represents a reversal in the market, so it is a good opportunity to close your trade in a bullish setup.
Entry and exit for a bearish setup
Suppose a red arrow appears above the red moving average line. It is a good opportunity to enter a trade in a bearish setup. The red line represents that sooner the sellers are going to take control and the value of the asset is about to face a dip. So it is the best time to make your move.
As the opposite arrow appears in the chart, it is time to exit from a bearish trade setup.
Re-entering a position
Bullish setup
- The half-trend line is blue.
- At least one candle closes below the blue half-trend line.
- Enter on the candle that closes above the blue half-trend line.
Bearish setup
- The half-trend line is red.
- At least one candle closes above the red half-trend line.
- Enter on the candle that closes below the red half-trend line.
Risk management
Risk management is an integral part of a trading setup. It is an important step to protect your potential profits and losses.
When trading in a bullish market, place the stop loss at the prior swing low. It will help you to cut your losses in case the prices move to the lower end.
In the case of a bearish market, place your stop loss above the prior swing high.
A trader may trail the stop loss using the ATR lines.
The new trader often makes mistakes in the placement of the stop loss. If you don’t place the stop loss at an appropriate point. It can drain your bank account and ruin your trading experience. Is is recommended not to risk more than 2% of your trading account, per trade.
Take profit
The blue ATR line may be used as one take profit level on a bullish setup followed by the previous swing high. The signal reversal would indicate the final take profit and closing of any position.
The red ATR line may be used as one take profit level on a bearish setup followed by the previous swing low. The signal reversal would indicate the final take profit and closing of any position.
Conclusion
A half trend indicator is a decent indicator that can transform your trading experience. It is a dual indicator that is based on the moving averages as well as helps you to form a trading strategy. If you are a new trader, this indicator can help you to learn and flourish in the trading universe. If you are a seasoned trader, I recommend you use this indicator with other technical analysis tools to enhance your success ratio.
All credits go to:
- @everget the original creator of this indicator (I just added the MTF capability).
- Ali Muhammad original author of much of the description used.
Up Down Volume Ratio by 3iauThis script considers the total volume within a user specified time frame, and whether price closed higher or lower at the end of each period within that time frame.
EXAMPLE:
* If the time period of interest is 50-periods, the script considers the volume within each of those 50 periods beginning with the most recent closed period.
* SumUpVol = the sum of all volume occurring within only those periods where price closed higher than that of the previous period.
* SumDnVol = the sum of all volume occurring within only those periods where price closed lower than that of the previous period.
* Difference = the difference between SumUpVol and SumDnVol = SumUpVol - SumDnVol
* Total = the sum of SumUpVol and SumDnVol = SumUpVol + SumDnVol
* The plot will present the change in Difference divided by Total = Difference/Total = (SumUpVol - SumDnVol)/(SumUpVol + SumDnVol) occurring within those 50 periods. What will be plotted is the moving average of this value. The user can specify the moving average type and the number of period for which the average is calculated.
* The plot needs to be fitted into a range, for example, +/- 50 (default) or +/-100, by multiplying the result of Difference/Total by a user specified constant. The constant will contain the majority (not all) of the values within +/- the specified value.
* Range = the user specified constant. If Range = 50, the majority of values plotted will be fall within the range +/- 50.
* Therefore, what is plotted is the moving average of Range * Difference / Total.
* When the value = 0, accumulation = distribution over the user specified 50-periods time frame.
* When the value is positive, accumulation > distribution over the user specified 50-periods time frame.
* When the value is negative, distribution > accumulation over the user specified 50-periods time frame.
This plot allows one to see possible accumulation and distribution occurring within a particular stock. The slope of this plot must be considered, and not any single value. The selected constant (“Range” in the example above) does not have an effect on the slope of the plot.
Three values may be plotted at once, for comparison of accumulation or distribution occurring over different time frames. For example, compare Difference / Total calculated over a 50-periods timeframe with 10-periods timeframe, both time frames beginning with the most recent closed period.
In addition to the above, J. Welles Wilder’s Relative Strength Index (RSI) can be plotted over the Difference / Total.
NOTE: this script is not the same as the more commonly used Up/Down Volume Ratio defined as SumUpVol / SumDnVol over a 50-periods time frame, where SumUpVol = the sum of all volume occurring within only those periods where price closed higher than that of the previous period, and SumDnVol = the sum of all volume occurring within only those periods where price closed lower than that of the previous period.
Compare...
Up Down Volume Ratio = SumUpVol / SumDnVol
Up Down Volume Ratio by 3iau = the moving average of Range * (SumUpVol - SumDnVol) / (SumUpVol + SumDnVol)
Dynamic Trend Fusion (DTF)The "Dynamic Trend Fusion" (DTF) indicator is a powerful technical analysis tool for traders. It stands out from other indicators due to its adaptability and ability to provide insights into different trading styles. Users can choose from various trading options such as "Short-term Trading," "Long-term Trading," "Aggressive Short-term," "Conservative Long-term," "Balanced Approach," "High Sensitivity," "Low Sensitivity," "Day Trading," and "Swing Trading." These options allow traders to customize the indicator to suit their specific trading strategies.
DTF combines the Moving Average Convergence Divergence (MACD) and Relative Strength Index (RSI) indicators, normalizing them to a similar scale for a comprehensive view of market conditions. It then calculates a combined value and smoothes it using a moving average.
One of its standout features is the ability to identify bullish and bearish states, which is represented visually on the chart. When the indicator detects a transition from a bullish to a bearish state or vice versa, the color of the line changes.
Additionally, DTF offers alert conditions, notifying users when the market shifts into a bullish or bearish state, allowing for timely decision-making.
In summary, the DTF indicator sets itself apart by providing traders with a versatile tool that can be tailored to various trading styles and offers clear visual signals for trend changes, enhancing trading precision and efficiency.
Supply and DemandThis is a "Supply and Demand" script designed to help traders spot potential levels of supply (resistance) and demand (support) in the market by identifying pivot points from past price action.
Differences from Other Scripts:
Unlike many pivot point scripts, this one offers a greater degree of customization and flexibility, allowing users to determine how many ranges of pivot points they wish to plot (up to 10), as well as the number of the most recent ranges to display.
Furthermore, it allows users to restrict the plotting of pivot points to specific timeframes (15 minutes, 30 minutes, 1 hour, 4 hours, and daily) using a toggle input. This is useful for traders who wish to focus on these popular trading timeframes.
This script also uses the color.new function for a more transparent plotting, which is not commonly used in many scripts.
How to Use:
The script provides two user inputs:
"Number of Ranges to Plot (1-10)": This determines how many 10-bar ranges of pivot points the script will calculate and potentially plot.
"Number of Last Ranges to Show (1-?)": This determines how many of the most recent ranges will be displayed on the chart.
"Limit to specific timeframes?": This is a toggle switch. When turned on, the script only plots pivot points if the current timeframe is one of the following: 15 minutes, 30 minutes, 1 hour, 4 hours, or daily.
The pivot points are plotted as circles on the chart, with pivot highs in red and pivot lows in green. The transparency level of these plots can be adjusted in the script.
Market and Conditions:
This script is versatile and can be used in any market, including Forex, commodities, indices, or cryptocurrencies. It's best used in trending markets where supply and demand levels are more likely to be respected. However, like all technical analysis tools, it's not foolproof and should be used in conjunction with other indicators and analysis techniques to confirm signals and manage risk.
A technical analyst, or technician, uses chart patterns and indicators to predict future price movements. The "Supply and Demand" script in question can be an invaluable tool for a technical analyst for the following reasons:
Identifying Support and Resistance Levels : The pivot points plotted by this script can act as potential levels of support and resistance. When the price of an asset approaches these pivot points, it might bounce back (in case of support) or retreat (in case of resistance). These levels can be used to set stop-loss and take-profit points.
Timeframe Analysis : The ability to limit the plotting of pivot points to specific timeframes is useful for multiple timeframe analysis. For instance, a trader might use a longer timeframe to determine the overall trend and a shorter one to decide the optimal entry and exit points.
Customization : The user inputs provided by the script allow a technician to customize the ranges of pivot points according to their unique trading strategy. They can choose the number of ranges to plot and the number of the most recent ranges to display on the chart.
Confirmation of Other Indicators : If a pivot point coincides with a signal from another indicator (for instance, a moving average crossover or a relative strength index (RSI) divergence), it could provide further confirmation of that signal, increasing the chances of a successful trade.
Transparency in Plots : The use of the color.new function allows for more transparent plotting. This feature can prevent the chart from becoming too cluttered when multiple ranges of pivot points are plotted, making it easier for the analyst to interpret the data.
In summary, this script can be used by a technical analyst to pinpoint potential trading opportunities, validate signals from other indicators, and customize the display of pivot points to suit their individual trading style and strategy. Always remember, however, that no single indicator should be used in isolation, and effective risk management strategies should always be employed.
Paranoia IndicatorThe Paranoia Indicator is a technical analysis tool that combines three popular indicators: Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), and Stochastic. The Paranoia Indicator formula is calculated by taking a weighted average of the three indicators, with the weights being 23.6%, 61.8%, and 14.6%, respectively.
The Paranoia Indicator is used to identify potential trend reversals and overbought/oversold conditions in the market. When the indicator is above zero, it is considered bullish, and when it is below zero, it is considered bearish. The Paranoia Indicator also has extreme bands that help to identify when the market is overbought or oversold.
Traders can use the Paranoia Indicator in conjunction with other technical analysis tools to confirm trading signals and make more informed trading decisions. The Paranoia Indicator is suitable for all types of markets, including stocks, forex, and commodities, and can be applied to any time frame.
Overall, the Paranoia Indicator is a useful tool for traders looking to identify potential trend reversals and overbought/oversold conditions in the market.
