GDP Recession Indicator by USCG_Vet🌟 GDP Recession Indicator by USCG_Vet 🌟
📈 Overview
The GDP Recession Indicator is a comprehensive economic tool designed to help traders and investors anticipate potential recessions by analyzing key U.S. economic metrics. By consolidating multiple normalized economic indicators into a single, actionable signal, this indicator provides a clear and intuitive way to assess the health of the U.S. economy on a monthly basis.
🔑 Key Features
🔴 Red Line (GDP Discrepancy):
Represents the normalized value of GDP - (PCE + GCE + GPDI), capturing the core GDP components.
⚪ White Line (Signal Line):
A simple moving average of the consolidated indicator, serving as a dynamic threshold for recession signals.
🔵 Consolidated Indicator (Blue Line):
An optional line that aggregates multiple economic indicators for a holistic view.
✨ Customizable Visibility:
By default, only the Red and White lines are displayed, ensuring a clean and focused chart. Additional indicators can be enabled as needed.
🔍 How It Works
📊 Data Normalization:
Processes key economic metrics:
GDP
Personal Consumption Expenditures (PCE)
Government Consumption Expenditures (GCE)
Gross Private Domestic Investment (GPDI)
US Private Debt Growth (USPDG)
US Government Debt Growth (USGDG)
US Balance of Trade (USBOT)
Personal Savings Rate (BEA)
Each metric is normalized using a z-score over a configurable period (default is 6 months), ensuring comparability and mitigating the impact of differing scales.
🔗 Consolidation:
Selected indicators are averaged to form a consolidated economic signal, providing a comprehensive view of economic trends.
📉 Signal Generation:
Recession Signal:
When the Red Line (GDP Discrepancy) crosses below the White Line (Signal Line), it indicates a potential downturn in the economy.
🛠️ How to Use the GDP Recession Indicator
➕ Adding the Indicator:
🔴 Red Line: Displays the normalized GDP Discrepancy (GDP - (PCE + GCE + GPDI)).
⚪ White Line: Shows the signal line derived from the consolidated indicator.
🔵 Blue Line and Other Indicators: Hidden by default for clarity. Enable them in the indicator settings if a more detailed analysis is desired.
🔍 Interpreting the Signals:
Recession Signal:
🔴 Red Line crosses below ⚪ White Line: Signals that the economy may be heading into a recession. Indicates that the GDP Discrepancy is declining relative to the broader economic signals captured by the indicator.
📑 Confirmation:
Look for confirmation from other technical indicators or economic data to validate the recession signal.
⚙️ Customization:
🕒 Normalization Period: Adjust the normalization period to suit different timeframes or sensitivity levels.
🔄 Indicator Visibility: Toggle the visibility of additional economic metrics (e.g., US Private Debt Growth, US Government Debt Growth) to tailor the indicator to your analytical needs.
🔵 Consolidated Indicator: Enable the blue line if you wish to view the aggregated economic signal alongside the primary signals.
🎯 Benefits
⏰ Early Warning System:
Provides timely signals that can help anticipate economic downturns, allowing for proactive portfolio adjustments.
🏁 Conclusion
The GDP Recession Indicator is a powerful tool for anyone looking to navigate the complexities of the economic landscape. By providing clear signals based on robust economic data, it empowers traders and investors to make informed decisions and better manage risk in anticipation of potential recessions.
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Relative Rating Index (RRI)The technical rating is one of the most perfect indicators. The reason is that this indicator is based on a majority vote of multiple indicators. It is logical that the judgment based on a majority vote of multiple indicators would not be inferior to the judgment made using only a single indicator. However, just as any indicator has its shortcomings, the technical rating also has weaknesses. The most significant issue is that it primarily provides only a momentary evaluation of the current situation.
Let's consider this in more detail. In the technical rating, an evaluation of 1.0 by the majority vote of indicators is considered a strong buy. However, in the market, there are naturally varying levels of strength. For example, would a market that only once reached an evaluation of 1.0 within a given period be considered the same as a market that consistently maintains an evaluation of 1.0? The latter clearly shows a stronger trend, but the technical rating does not provide an objective criterion for such differentiation. While it is possible to check the histogram to see how long the buy or sell rating has continued, there is no objective standard for judgment.
The indicator I have created this time compensates for this weakness by using the concept of RSI. As is well known, RSI is an indicator that shows the momentum of the market. RSI typically calculates the strength of the price increase during a 14-period by dividing the total upward movement by the total movement range. Similarly, I thought that if we divide the positive evaluations of the technical rating during a given period by the total evaluations, we could calculate the "momentum of the technical rating," which shows how often positive ratings have appeared during that period.
Below is the calculation formula.
1. Setting the Evaluation Period
Decide the period to calculate (e.g., 14 periods). This is denoted as `n`.
2. Total Positive Ratings of the Technical Rating
Calculate the total number of times the technical rating is evaluated as "strong buy" or "buy" during each period. This is called `positive_sum`.
3. Total Ratings
Count the total number of ratings (including buy, sell, and neutral) during the period. This is called `total_sum`.
4. Calculating the Upward Strength
Divide `positive_sum` by `total_sum` to calculate the ratio of positive ratings in the technical rating. This is called the "ratio of positive ratings."
The ratio of positive ratings, denoted as `P`, is calculated as follows:
P = positive_sum / total_sum
5. Calculating RRI
Following the calculation method of RSI, RRI is calculated by the following formula:
RRI = 100 - (100 / (1 + (P / (1 - P))))
As you can see, the calculation method is similar to that of RSI. Therefore, initially, I intended to name this indicator the Technical Rating RSI. However, RSI calculates based on the difference between the previous bar's price and the current bar's price, whereas this indicator calculates by summing the values of the technical ratings themselves. In the case of prices, if the difference between bars is zero, it indicates a flat market, but in the case of technical rating values, if 1.0 continues for two consecutive periods, it signifies an extremely strong buy rather than a flat market. For this reason, I decided that the calculation method could no longer be considered the same as the traditional RSI, and to avoid confusion, I chose to give this new indicator the name "Relative Rating Index" (RRI), as it provides a new type of numerical evaluation.
The information provided by this indicator is simple. When RRI exceeds 50, it means that more than 50% of the technical rating evaluations during the set period (I recommend 50 periods, but please determine the optimal value based on your timeframe) are buy evaluations. However, since there may be many false signals around exactly 50, I define it as buy-dominant when the value exceeds 60 and sell-dominant when it falls below 40. Additionally, if the graph itself is rising, it indicates that the buying momentum is strengthening, and if it is falling, it indicates that the selling momentum is increasing.
Furthermore, there are lines drawn at 90 and 10, but please note that unlike RSI, these do not indicate overbought or oversold conditions. When RRI exceeds 90, it means that over 90% of the technical rating evaluations during the specified period are buy evaluations, indicating an ongoing extremely strong buy trend. Until the RRI graph turns downward and falls below 90, it should rather be considered a buying opportunity.
With this new indicator, the technical rating becomes an indicator with depth, providing evaluations not only for the moment but over a specified period. I hope you find it helpful in your market analysis.
Tare's Multi-Timeframe Market Heatmap
Tare's Multi-Timeframe Market Heatmap is a powerful tool designed to help traders quickly gauge market sentiment across multiple timeframes using a combination of RSI (Relative Strength Index) and MACD (Moving Average Convergence Divergence) indicators. This indicator analyzes four customizable timeframes to determine whether the market is bullish or bearish, providing a visual heatmap to indicate the overall market direction and strength.
Key Features:
Multi-Timeframe Analysis: The indicator allows you to select up to four different timeframes (e.g., 5 minutes, 15 minutes, 30 minutes, 1 hour) to analyze the market's behavior comprehensively.
RSI and MACD Integration: By combining RSI and MACD indicators, the heatmap provides a more robust analysis, taking into account both momentum (RSI) and trend (MACD) indicators. This dual approach helps in identifying stronger and more reliable signals.
Visual Heatmap: The indicator plots a histogram that changes color and intensity based on the combined bullish or bearish strength across the selected timeframes:
Green: Indicates bullish strength, with a darker shade representing stronger bullish signals across multiple timeframes.
Red: Indicates bearish strength, with a darker shade representing stronger bearish signals across multiple timeframes.
Customizable Settings: You can customize the length settings for RSI and MACD, including the RSI period, MACD fast and slow lengths, and signal length, allowing for tailored analysis based on your trading strategy.
Signal Exposure for Other Strategies: The indicator exposes both bullish and bearish signals, which can be used as inputs for other custom strategies within TradingView. This feature allows seamless integration and enhances the versatility of your trading approach.
How to Use:
Adjust the timeframes and indicator settings in the indicator's input menu to match your trading style.
Observe the color and intensity of the histogram to understand the current market sentiment across the selected timeframes.
Utilize the exposed signals (bullish and bearish) in conjunction with other strategies or indicators for a more comprehensive trading system.
Tare's Multi-Timeframe Market Heatmap provides traders with a clear, concise, and customizable overview of market conditions, making it an essential tool for multi-timeframe analysis and decision-making.
Uptrick: Trend SMA Oscillator### In-Depth Analysis of the "Uptrick: Trend SMA Oscillator" Indicator
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#### Introduction to the Indicator
The "Uptrick: Trend SMA Oscillator" is an advanced yet user-friendly technical analysis tool designed to help traders across all levels of experience identify and follow market trends with precision. This indicator builds upon the fundamental principles of the Simple Moving Average (SMA), a cornerstone of technical analysis, to deliver a clear, visually intuitive overlay on the price chart. Through its strategic use of color-coding and customizable parameters, the Uptrick: Trend SMA Oscillator provides traders with actionable insights into market dynamics, enhancing their ability to make informed trading decisions.
#### Core Concepts and Methodology
1. **Foundational Principle – Simple Moving Average (SMA):**
- The Simple Moving Average (SMA) is the heart of the Uptrick: Trend SMA Oscillator. The SMA is a widely-used technical indicator that calculates the average price of an asset over a specified number of periods. By smoothing out price data, the SMA helps to reduce the noise from short-term fluctuations, providing a clearer picture of the overall trend.
- In the Uptrick: Trend SMA Oscillator, two SMAs are employed:
- **Primary SMA (oscValue):** This is applied to the closing price of the asset over a user-defined period (default is 14 periods). This SMA tracks the price closely and is sensitive to changes in market direction.
- **Smoothing SMA (oscV):** This second SMA is applied to the primary SMA, further smoothing the data and helping to filter out minor price movements that might otherwise be mistaken for trend reversals. The default period for this smoothing is 50, but it can be adjusted to suit the trader's preference.
2. **Color-Coding for Trend Visualization:**
- One of the most distinctive features of this indicator is its use of color to represent market trends. The indicator’s line changes color based on the relationship between the primary SMA and the smoothing SMA:
- **Bullish (Green):** The line turns green when the primary SMA is equal to or greater than the smoothing SMA, indicating that the market is in an upward trend.
- **Bearish (Red):** Conversely, the line turns red when the primary SMA falls below the smoothing SMA, signaling a downward trend.
- This color-coded system provides traders with an immediate, easy-to-interpret visual cue about the market’s direction, allowing for quick decision-making.
#### Detailed Explanation of Inputs
1. **Bullish Color (Default: Green #00ff00):**
- This input allows traders to customize the color that represents bullish trends on the chart. The default setting is green, a color commonly associated with upward market movement. However, traders can adjust this to any color that suits their visual preferences or matches their overall chart theme.
2. **Bearish Color (Default: Red RGB: 245, 0, 0):**
- The bearish color input determines the color of the line when the market is trending downwards. The default setting is a vivid red, signaling caution or selling opportunities. Like the bullish color, this can be customized to fit the trader’s needs.
3. **Line Thickness (Default: 5):**
- This setting controls the thickness of the line plotted by the indicator. The default thickness of 5 makes the line prominent on the chart, ensuring that the trend is easily visible even in complex or crowded chart setups. Traders can adjust the thickness to make the line thinner or thicker, depending on their visual preferences.
4. **Primary SMA Period (Value 1 - Default: 14):**
- The primary SMA period defines how many periods (e.g., days, hours) are used to calculate the moving average based on the asset’s closing prices. The default period of 14 is a balanced setting that offers a good mix of responsiveness and stability, but traders can adjust this depending on their trading style:
- **Shorter Periods (e.g., 5-10):** These make the indicator more sensitive, capturing trends more quickly but also increasing the likelihood of reacting to short-term price fluctuations or "noise."
- **Longer Periods (e.g., 20-50):** These smooth the data more, providing a more stable trend line that is less prone to whipsaws but may be slower to respond to trend changes.
5. **Smoothing SMA Period (Value 2 - Default: 50):**
- The smoothing SMA period determines how much the primary SMA is smoothed. A longer smoothing period results in a more gradual, stable line that focuses on the broader trend. The default of 50 is designed to smooth out most of the short-term fluctuations while still being responsive enough to detect significant trend shifts.
- **Customization:**
- **Shorter Smoothing Periods (e.g., 20-30):** Make the indicator more responsive, better for fast-moving markets or for traders who want to capture quick trends.
- **Longer Smoothing Periods (e.g., 70-100):** Enhance stability, ideal for long-term traders looking to avoid reacting to minor price movements.
#### Unique Characteristics and Advantages
1. **Simplicity and Clarity:**
- The Uptrick: Trend SMA Oscillator’s design prioritizes simplicity without sacrificing effectiveness. By relying on the widely understood SMA, it avoids the complexity of more esoteric indicators while still providing reliable trend signals. This simplicity makes it accessible to traders of all levels, from novices who are just learning about technical analysis to experienced traders looking for a straightforward, dependable tool.
2. **Visual Feedback Mechanism:**
- The indicator’s use of color to signify market trends is a particularly powerful feature. This visual feedback mechanism allows traders to assess market conditions at a glance. The clarity of the green and red color scheme reduces the mental effort required to interpret the indicator, freeing the trader to focus on strategy execution.
3. **Adaptability Across Markets and Timeframes:**
- One of the strengths of the Uptrick: Trend SMA Oscillator is its versatility. The basic principles of moving averages apply equally well across different asset classes and timeframes. Whether trading stocks, forex, commodities, or cryptocurrencies, traders can use this indicator to gain insights into market trends.
- **Intraday Trading:** For day traders who operate on short timeframes (e.g., 1-minute, 5-minute charts), the oscillator can be adjusted to be more responsive, capturing quick shifts in momentum.
- **Swing Trading:** Swing traders, who typically hold positions for several days to weeks, will find the default settings or slightly adjusted periods ideal for identifying and riding medium-term trends.
- **Long-Term Trading:** Position traders and investors can adjust the indicator to focus on long-term trends by increasing the periods for both the primary and smoothing SMAs, filtering out minor fluctuations and highlighting sustained market movements.
4. **Minimal Lag:**
- One of the challenges with moving averages is lag—the delay between when the price changes and when the indicator reflects this change. The Uptrick: Trend SMA Oscillator addresses this by allowing traders to adjust the periods to find a balance between responsiveness and stability. While all SMAs inherently have some lag, the customizable nature of this indicator helps traders mitigate this effect to align with their specific trading goals.
5. **Customizable and Intuitive:**
- While many technical indicators come with a fixed set of parameters, the Uptrick: Trend SMA Oscillator is fully customizable, allowing traders to tailor it to their trading style, market conditions, and personal preferences. This makes it a highly flexible tool that can be adjusted as markets evolve or as a trader’s strategy changes over time.
#### Practical Applications for Different Trader Profiles
1. **Day Traders:**
- **Use Case:** Day traders can customize the SMA periods to create a faster, more responsive indicator. This allows them to capture short-term trends and make quick decisions. For example, reducing the primary SMA to 5 and the smoothing SMA to 20 can help day traders react promptly to intraday price movements.
- **Strategy Integration:** Day traders might use the Uptrick: Trend SMA Oscillator in conjunction with volume-based indicators to confirm the strength of a trend before entering or exiting trades.
2. **Swing Traders:**
- **Use Case:** Swing traders can use the default settings or slightly adjust them to smooth out minor price fluctuations while still capturing medium-term trends. This approach helps in identifying the optimal points to enter or exit trades based on the broader market direction.
- **Strategy Integration:** Swing traders can combine this indicator with oscillators like the Relative Strength Index (RSI) to confirm overbought or oversold conditions, thereby refining their entry and exit strategies.
3. **Position Traders:**
- **Use Case:** Position traders, who hold trades for extended periods, can extend the SMA periods to focus on long-term trends. By doing so, they minimize the impact of short-term market noise and focus on the underlying trend.
- **Strategy Integration:** Position traders might use the Uptrick: Trend SMA Oscillator in combination with fundamental analysis. The indicator can help confirm the timing of entries and exits based on broader economic or corporate developments.
4. **Algorithmic and Quantitative Traders:**
- **Use Case:** The simplicity and clear logic of the Uptrick: Trend SMA Oscillator make it an excellent candidate for algorithmic trading strategies. Its binary output—bullish or bearish—can be easily coded into automated trading systems.
- **Strategy Integration:** Quant traders might use the indicator as part of a larger trading system that incorporates multiple indicators and rules, optimizing the SMA periods based on historical backtesting to achieve the best results.
5. **Novice Traders:**
- **Use Case:** Beginners can use the Uptrick: Trend SMA Oscillator to learn the basics of trend-following strategies.
The visual simplicity of the color-coded line helps novice traders quickly understand market direction without the need to interpret complex data.
- **Educational Value:** The indicator serves as an excellent starting point for those new to technical analysis, providing a practical example of how moving averages work in a real-world trading environment.
#### Combining the Indicator with Other Tools
1. **Relative Strength Index (RSI):**
- The RSI is a momentum oscillator that measures the speed and change of price movements. When combined with the Uptrick: Trend SMA Oscillator, traders can look for instances where the RSI shows divergence from the price while the oscillator confirms the trend. This can be a powerful signal of an impending reversal or continuation.
2. **Moving Average Convergence Divergence (MACD):**
- The MACD is another popular trend-following momentum indicator. By using it alongside the Uptrick: Trend SMA Oscillator, traders can confirm the strength of a trend and identify potential entry and exit points with greater confidence. For example, a bullish crossover on the MACD that coincides with the Uptrick: Trend SMA Oscillator turning green can be a strong buy signal.
3. **Volume Indicators:**
- Volume is often considered the fuel behind price movements. Using volume indicators like the On-Balance Volume (OBV) or Volume Weighted Average Price (VWAP) in conjunction with the Uptrick: Trend SMA Oscillator can help traders confirm the validity of a trend. A trend identified by the oscillator that is supported by increasing volume is typically more reliable.
4. **Fibonacci Retracement:**
- Fibonacci retracement levels are used to identify potential reversal levels in a trending market. When the Uptrick: Trend SMA Oscillator indicates a trend, traders can use Fibonacci retracement levels to find potential entry points that align with the broader trend direction.
#### Implementation in Different Market Conditions
1. **Trending Markets:**
- The Uptrick: Trend SMA Oscillator excels in trending markets, where it provides clear signals on the direction of the trend. In a strong uptrend, the line will remain green, helping traders stay in the trade for longer periods. In a downtrend, the red line will signal the continuation of bearish conditions, prompting traders to stay short or avoid long positions.
2. **Sideways or Range-Bound Markets:**
- In range-bound markets, where price oscillates within a confined range without a clear trend, the Uptrick: Trend SMA Oscillator may produce more frequent changes in color. While this could indicate potential reversals at the range boundaries, traders should be cautious of false signals. It may be beneficial to pair the oscillator with a volatility indicator to better navigate such conditions.
3. **Volatile Markets:**
- In highly volatile markets, where prices can swing rapidly, the sensitivity of the Uptrick: Trend SMA Oscillator can be adjusted by modifying the SMA periods. A shorter SMA period might capture quick trends, but traders should be aware of the increased risk of whipsaws. Combining the oscillator with a volatility filter or using it in a higher time frame might help mitigate some of this risk.
#### Final Thoughts
The "Uptrick: Trend SMA Oscillator" is a versatile, easy-to-use indicator that stands out for its simplicity, visual clarity, and adaptability. It provides traders with a straightforward method to identify and follow market trends, using the well-established concept of moving averages. The indicator’s customizable nature makes it suitable for a wide range of trading styles, from day trading to long-term investing, and across various asset classes.
By offering immediate visual feedback through color-coded signals, the Uptrick: Trend SMA Oscillator simplifies the decision-making process, allowing traders to focus on execution rather than interpretation. Whether used on its own or as part of a broader technical analysis toolkit, this indicator has the potential to enhance trading strategies and improve overall performance.
Its accessibility and ease of use make it particularly appealing to novice traders, while its adaptability and reliability ensure that it remains a valuable tool for more experienced market participants. As markets continue to evolve, the Uptrick: Trend SMA Oscillator remains a timeless tool, rooted in the fundamental principles of technical analysis, yet flexible enough to meet the demands of modern trading.
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.
Uptrick: Bullish/Bearish Signal DetectorDetailed Explanation of the "Uptrick: Bullish/Bearish Signal Detector" Script
The "Uptrick: Bullish/Bearish Signal Detector" script is a sophisticated tool designed for the TradingView platform, leveraging Pine Script version 5. This script is crafted to enhance traders' ability to identify bullish (buy) and bearish (sell) signals directly on their trading charts. By combining the power of the MACD (Moving Average Convergence Divergence) and RSI (Relative Strength Index) indicators, this script provides a unique and efficient method for detecting potential trading opportunities. Below is an in-depth exploration of its purpose, features, and functionality.
Purpose
The primary purpose of this script is to assist traders in identifying potential entry and exit points in the market by signaling bullish and bearish conditions. This automated detection helps traders make more informed decisions without the need to manually analyze complex indicators. By overlaying signals directly on the price chart, the script allows for quick visual identification of market trends and reversals.
Uniqueness
What sets this script apart is its dual use of MACD and RSI indicators. While many trading strategies might rely on a single indicator, combining MACD and RSI enhances the reliability of the signals by filtering out false positives. The script not only identifies trends but also adds a layer of confirmation through the RSI, which measures the speed and change of price movements.
Inputs and Features
Customizable Label Appearance:
The script allows users to customize the appearance of the labels that indicate bullish and bearish signals. Users can set their preferred colors for the labels and the text, ensuring that the signals are easily distinguishable and aesthetically pleasing on their charts.
MACD Calculation:
The script calculates the MACD line and signal line using user-defined input values for the fast length, slow length, and signal length. The MACD histogram, which is the difference between the MACD line and the signal line, is used to determine the momentum of the market.
RSI Calculation:
The RSI is calculated using a user-defined input length. The RSI helps in identifying overbought or oversold conditions, which are crucial for confirming the strength of the trend detected by the MACD.
Bullish and Bearish Conditions:
The script defines bullish conditions as those where the MACD histogram is positive and the RSI is above 50. Bearish conditions are defined where the MACD histogram is negative and the RSI is below 50. This combination of conditions ensures that signals are generated based on both momentum and relative strength, reducing the likelihood of false signals.
Label Plotting:
The script plots labels on the chart to indicate bullish and bearish signals. When a bullish condition is met, and the previous signal was not bullish, a "LONG" label is plotted. Similarly, when a bearish condition is met, and the previous signal was not bearish, a "SHORT" label is plotted. This feature helps in clearly marking the points of interest for traders, making it easier to spot potential trades.
Tracking Previous Signals:
To avoid repetitive signals, the script keeps track of the last signal. If the last signal was bullish, it avoids plotting another bullish signal immediately. The same logic applies to bearish signals. This tracking ensures that signals are spaced out and only significant changes in market conditions are highlighted.
How It Works
The script operates in a loop, processing each bar (or candlestick) on the chart as new data comes in. It calculates the MACD and RSI values for each bar and checks if the current conditions meet the criteria for a bullish or bearish signal. If a signal is detected and it is different from the last signal, a label is plotted on the chart at the current bar's price level. This real-time processing allows traders to see the signals as they form, providing timely insights into market movements.
Practical Application
For practical use, a trader would add this script to their TradingView chart. They can customize the input parameters for the MACD and RSI calculations to fit their trading strategy or preferred settings. Once added, the script will automatically analyze the price data and start plotting "LONG" and "SHORT" labels based on the detected signals. Traders can then use these labels to make decisions on entering or exiting trades, adjusting their strategy as necessary based on the signals provided.
Conclusion
The "Uptrick: Bullish/Bearish Signal Detector" script is a powerful tool for any trader looking to leverage technical indicators for better trading decisions. By combining MACD and RSI, it offers a robust method for detecting market trends and potential reversals. The customizable features and real-time signal plotting make it a versatile and user-friendly addition to any trading toolkit. This script not only simplifies the process of technical analysis but also enhances the accuracy of trading signals, thereby potentially increasing the trader's success rate in the market.
Coins Trend Tracker HTThe Coins Trend Tracker HT script provides a powerful tool for monitoring and comparing the trend signals of multiple cryptocurrencies based on their Exponential Moving Averages (EMAs). This script is particularly useful for traders who want to keep track of multiple coins across different timeframes and identify potential trading opportunities based on EMA crossovers.
Features:
Customizable Coin Selection: Users can select up to four different cryptocurrencies to monitor.
Flexible Timeframes: Users can choose two different timeframes for EMA calculations to suit their trading strategies.
Visual Trend Indicators: The script displays trend indicators (🚀 for bullish and 💀 for bearish) based on the EMA crossover status for each coin and timeframe.
Conditional Cell Coloring: Table cells are color-coded based on the EMA crossover conditions, helping users quickly identify bullish or bearish trends.
Opacity Control: Users can adjust the opacity of the table cell colors for better visualization on the chart.
How It Works:
Coin Selection: Users can select up to four different cryptocurrencies to monitor by entering their ticker symbols.
Timeframe Selection: Users can select two different timeframes for the EMA calculations. The script calculates the 5-period and 20-period EMAs for each coin and timeframe.
EMA Crossovers: The script checks for EMA crossovers (EMA 5 crossing above or below EMA 20) and updates the trend indicators and cell colors accordingly.
Table Display: The script displays a table with the selected coins, their current prices, and trend indicators for the chosen timeframes. The background color of the table cells changes based on the EMA crossover status.
Script Logic:
The get_price function retrieves the latest price of the selected coin for the specified timeframe.
The get_ema_cross function calculates the 5-period and 20-period EMAs and checks for crossover conditions.
The fill_row function populates the table with the coin data, trend indicators, and conditionally colored cells.
The table header and data rows are updated based on the user-selected coins, timeframes, and EMA crossover conditions.
Usage:
Add the script to your TradingView chart.
Customize the coin selection, timeframes, text color, default cell color, bullish and bearish cross colors, and cell opacity through the input settings.
The script will display a table with the selected coins, their current prices, and trend indicators based on the EMA crossovers for the chosen timeframes.
Market Cipher B by WeloTradesMarket Cipher B by WeloTrades: Detailed Script Description
//Overview//
"Market Cipher B by WeloTrades" is an advanced trading tool that combines multiple technical indicators to provide a comprehensive market analysis framework. By integrating WaveTrend, RSI, and MoneyFlow indicators, this script helps traders to better identify market trends, potential reversals, and trading opportunities. The script is designed to offer a holistic view of the market by combining the strengths of these individual indicators.
//Key Features and Originality//
WaveTrend Analysis:
WaveTrend Channel (WT1 and WT2): The core of this script is the WaveTrend indicator, which uses the smoothed average of typical price to identify overbought and oversold conditions. WT1 and WT2 are calculated to track market momentum and cyclical price movements.
Major Divergences (🐮/🐻): The script detects and highlights major bullish and bearish divergences automatically, providing traders with visual cues for potential reversals. This helps in making informed decisions based on divergence patterns.
Relative Strength Index (RSI):
RSI Levels: RSI is used to measure the speed and change of price movements, with specific levels indicating overbought and oversold conditions.
Customizable Levels: Users can configure the overbought and oversold thresholds, allowing for a tailored analysis based on individual trading strategies.
MoneyFlow Indicator:
Fast and Slow MoneyFlow: This indicator tracks the flow of capital into and out of the market, offering insights into the underlying market strength. It includes configurable periods and multipliers for both fast and slow MoneyFlow.
Vertical Positioning: The script allows users to adjust the vertical position of MoneyFlow plots to maintain a clear and uncluttered chart.
Stochastic RSI:
Stochastic RSI Levels: This combines the RSI and Stochastic indicators to provide a momentum oscillator that is sensitive to price changes. It is used to identify overbought and oversold conditions within a specified period.
Customizable Levels: Traders can set specific levels for more precise analysis.
//How It Works//
The script integrates these indicators through advanced algorithms, creating a synergistic effect that enhances market analysis. Here’s a detailed explanation of the underlying concepts and calculations:
WaveTrend Indicator:
Calculation: WaveTrend is based on the typical price (average of high, low, and close) smoothed over a specified channel length. WT1 and WT2 are derived from this typical price and further smoothed using the Average Channel Length. The difference between WT1 and WT2 indicates momentum, helping to identify cyclical market trends.
RSI (Relative Strength Index):
Calculation: RSI calculates the average gains and losses over a specified period to measure the speed and change of price movements. It oscillates between 0 and 100, with levels set to identify overbought (>70) and oversold (<30) conditions.
MoneyFlow Indicator:
Calculation: MoneyFlow is derived by multiplying price changes by volume and smoothing the results over specified periods. Fast MoneyFlow reacts quickly to price changes, while Slow MoneyFlow offers a broader view of capital movement trends.
Stochastic RSI:
Calculation: Stochastic RSI is computed by applying the Stochastic formula to RSI values, which highlights the RSI’s relative position within its range over a given period. This helps in identifying momentum shifts more precisely.
//How to Use the Script//
Display Settings:
Users can enable or disable various components like WaveTrend OB & OS levels, MoneyFlow plots, and divergence alerts through checkboxes.
Example: Turn on "Show Major Divergence" to see major bullish and bearish divergence signals directly on the chart.
Adjust Channel Settings:
Customize the data source, channel length, and smoothing periods in the "WaveTrend Channel SETTINGS" group.
Example: Set the "Channel Length" to 10 for a more responsive WaveTrend line or adjust the "Average Channel Length" to 21 for smoother trends.
Set Overbought & Oversold Levels:
Configure levels for WaveTrend, RSI, and Stochastic RSI in their respective settings groups.
Example: Set the WaveTrend Overbought Level to 60 and Oversold Level to -60 to define critical thresholds.
Money Flow Settings:
Adjust the periods and multipliers for Fast and Slow MoneyFlow indicators, and set their vertical positions for better visualization.
Example: Set the Fast Money Flow Period to 9 and Slow Money Flow Period to 12 to capture both short-term and long-term capital movements.
//Justification for Combining Indicators//
Enhanced Market Analysis:
Combining WaveTrend, RSI, and MoneyFlow provides a more comprehensive view of market conditions. Each indicator brings a unique perspective, making the analysis more robust.
WaveTrend identifies cyclical trends, RSI measures momentum, and MoneyFlow tracks capital movement. Together, they provide a multi-dimensional analysis of the market.
Improved Decision-Making:
By integrating these indicators, the script helps traders make more informed decisions. For example, a bullish divergence detected by WaveTrend might be validated by an RSI moving out of oversold territory and supported by increasing MoneyFlow.
Customization and Flexibility:
The script offers extensive customization options, allowing traders to tailor it to their specific needs and strategies. This flexibility makes it suitable for different trading styles and timeframes.
//Conclusion//
The indicator stands out due to its innovative combination of WaveTrend, RSI, and MoneyFlow indicators, offering a well-rounded tool for market analysis. By understanding how each component works and how they complement each other, traders can leverage this script to enhance their market analysis and trading strategies, making more informed and confident decisions.
Remember to always backtest the indicator first before implying it to your strategy.
Kalman Filtered RSI Oscillator [BackQuant]Kalman Filtered RSI Oscillator
The Kalman Filtered RSI Oscillator is BackQuants new free indicator designed for traders seeking an advanced, empirical approach to trend detection and momentum analysis. By integrating the robustness of a Kalman filter with the adaptability of the Relative Strength Index (RSI), this tool offers a sophisticated method to capture market dynamics. This indicator is crafted to provide a clearer, more responsive insight into price trends and momentum shifts, enabling traders to make informed decisions in fast-moving markets.
Core Principles
Kalman Filter Dynamics:
At its core, the Kalman Filtered RSI Oscillator leverages the Kalman filter, renowned for its efficiency in predicting the state of linear dynamic systems amidst uncertainties. By applying it to the RSI calculation, the tool adeptly filters out market noise, offering a smoothed price source that forms the basis for more accurate momentum analysis. The inclusion of customizable parameters like process noise, measurement noise, and filter order allows traders to fine-tune the filter’s sensitivity to market changes, making it a versatile tool for various trading environments.
RSI Adaptation:
The RSI is a widely used momentum oscillator that measures the speed and change of price movements. By integrating the RSI with the Kalman filter, the oscillator not only identifies the prevailing trend but also provides a smoothed representation of momentum. This synergy enhances the indicator's ability to signal potential reversals and trend continuations with a higher degree of reliability.
Advanced Smoothing Techniques:
The indicator further offers an optional smoothing feature for the RSI, employing a selection of moving averages (HMA, THMA, EHMA, SMA, EMA, WMA, TEMA, VWMA) for traders seeking to reduce volatility and refine signal clarity. This advanced smoothing mechanism is pivotal for traders looking to mitigate the effects of short-term price fluctuations on the RSI's accuracy.
Empirical Significance:
Empirically, the Kalman Filtered RSI Oscillator stands out for its dynamic adjustment to market conditions. Unlike static indicators, the Kalman filter continuously updates its estimates based on incoming price data, making it inherently more responsive to new market information. This dynamic adaptation, combined with the RSI's momentum analysis, offers a powerful approach to understanding market trends and momentum with a depth not available in traditional indicators.
Trend Identification and Momentum Analysis:
Traders can use the Kalman Filtered RSI Oscillator to identify strong trends and momentum shifts. The color-coded RSI columns provide immediate visual cues on the market's direction and strength, aiding in quick decision-making.
Optimal for Various Market Conditions:
The flexibility in tuning the Kalman filter parameters makes this indicator suitable for a wide range of assets and market conditions, from volatile to stable markets. Traders can adjust the settings based on empirical testing to find the optimal configuration for their trading strategy.
Complementary to Other Analytical Tools:
While powerful on its own, the Kalman Filtered RSI Oscillator is best used in conjunction with other analytical tools and indicators. Combining it with volume analysis, price action patterns, or other trend-following indicators can provide a comprehensive view of the market, allowing for more nuanced and informed trading decisions.
The Kalman Filtered RSI Oscillator is a groundbreaking tool that marries empirical precision with advanced trend analysis techniques. Its innovative use of the Kalman filter to enhance the RSI's performance offers traders an unparalleled ability to navigate the complexities of modern financial markets. Whether you're a novice looking to refine your trading approach or a seasoned professional seeking advanced analytical tools, the Kalman Filtered RSI Oscillator represents a significant step forward in technical analysis capabilities.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Machine Learning: Multiple Logistic Regression
Multiple Logistic Regression Indicator
The Logistic Regression Indicator for TradingView is a versatile tool that employs multiple logistic regression based on various technical indicators to generate potential buy and sell signals. By utilizing key indicators such as RSI, CCI, DMI, Aroon, EMA, and SuperTrend, the indicator aims to provide a systematic approach to decision-making in financial markets.
How It Works:
Technical Indicators:
The script uses multiple technical indicators such as RSI, CCI, DMI, Aroon, EMA, and SuperTrend as input variables for the logistic regression model.
These indicators are normalized to create categorical variables, providing a consistent scale for the model.
Logistic Regression:
The logistic regression function is applied to the normalized input variables (x1 to x6) with user-defined coefficients (b0 to b6).
The logistic regression model predicts the probability of a binary outcome, with values closer to 1 indicating a bullish signal and values closer to 0 indicating a bearish signal.
Loss Function (Cross-Entropy Loss):
The cross-entropy loss function is calculated to quantify the difference between the predicted probability and the actual outcome.
The goal is to minimize this loss, which essentially measures the model's accuracy.
// Error Function (cross-entropy loss)
loss(y, p) =>
-y * math.log(p) - (1 - y) * math.log(1 - p)
// y - depended variable
// p - multiple logistic regression
Gradient Descent:
Gradient descent is an optimization algorithm used to minimize the loss function by adjusting the weights of the logistic regression model.
The script iteratively updates the weights (b1 to b6) based on the negative gradient of the loss function with respect to each weight.
// Adjusting model weights using gradient descent
b1 -= lr * (p + loss) * x1
b2 -= lr * (p + loss) * x2
b3 -= lr * (p + loss) * x3
b4 -= lr * (p + loss) * x4
b5 -= lr * (p + loss) * x5
b6 -= lr * (p + loss) * x6
// lr - learning rate or step of learning
// p - multiple logistic regression
// x_n - variables
Learning Rate:
The learning rate (lr) determines the step size in the weight adjustment process. It prevents the algorithm from overshooting the minimum of the loss function.
Users can set the learning rate to control the speed and stability of the optimization process.
Visualization:
The script visualizes the output of the logistic regression model by coloring the SMA.
Arrows are plotted at crossover and crossunder points, indicating potential buy and sell signals.
Lables are showing logistic regression values from 1 to 0 above and below bars
Table Display:
A table is displayed on the chart, providing real-time information about the input variables, their values, and the learned coefficients.
This allows traders to monitor the model's interpretation of the technical indicators and observe how the coefficients change over time.
How to Use:
Parameter Adjustment:
Users can adjust the length of technical indicators (rsi_length, cci_length, etc.) and the Z score length based on their preference and market characteristics.
Set the initial values for the regression coefficients (b0 to b6) and the learning rate (lr) according to your trading strategy.
Signal Interpretation:
Buy signals are indicated by an upward arrow (▲), and sell signals are indicated by a downward arrow (▼).
The color-coded SMA provides a visual representation of the logistic regression output by color.
Table Information:
Monitor the table for real-time information on the input variables, their values, and the learned coefficients.
Keep an eye on the learning rate to ensure a balance between model adjustment speed and stability.
Backtesting and Validation:
Before using the script in live trading, conduct thorough backtesting to evaluate its performance under different market conditions.
Validate the model against historical data to ensure its reliability.
Aroon and ASH strategy - ETHERIUM [IkkeOmar]Intro:
This post introduces a Pine Script strategy, as an example if anyone needs a push to get started. This example is a strategy on ETH, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay. This strategy combines two technical indicators: Aroon and Absolute Strength Histogram (ASH).
Overview:
The strategy employs the Aroon indicator alongside the Absolute Strength Histogram (ASH) to determine market trends and potential trade setups. Aroon helps identify the strength and direction of a trend, while ASH provides insights into the strength of momentum. By combining these indicators, the strategy aims to capture profitable trading opportunities in Ethereum markets. Normally when developing strats using indicators, you want to find some good indicators, but you NEED to understand their strengths and weaknesses, other indicators can be incorporated to minimize the downs of another indicator. Try to look for synergy in your indicators!
Indicator settings:
Aroon Indicator:
- Two sets of parameters are used for the Aroon indicator:
- For Long Positions: Aroon periods are set to 56 (upper) and 20 (lower).
- For Short Positions: Aroon periods are set to 17 (upper) and 55 (lower).
Absolute Strength Histogram (ASH):
ASH is calculated with a length of 9 bars using the closing price as the data source.
Trading Conditions:
The strategy incorporates specific conditions to initiate and exit trades:
Start Date:
Traders can specify the start date for backtesting purposes.
Trade Direction:
Traders can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
1. Long Position Entry: A long position is initiated when the Aroon indicator crosses over (crossover) the lower Aroon threshold, indicating a potential uptrend.
2. Long Position Exit: A long position is closed when the Aroon indicator crosses under (crossunder) the lower Aroon threshold.
3. Short Position Entry: A short position is initiated when the Aroon indicator crosses under (crossunder) the upper Aroon threshold, signaling a potential downtrend.
4. Short Position Exit: A short position is closed when the Aroon indicator crosses over (crossover) the upper Aroon threshold.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Optimal Length BackTester [YinYangAlgorithms]This Indicator allows for a ‘Optimal Length’ to be inputted within the Settings as a Source. Unlike most Indicators and/or Strategies that rely on either Static Lengths or Internal calculations for the length, this Indicator relies on the Length being derived from an external Indicator in the form of a Source Input.
This may not sound like much, but this application may allows limitless implementations of such an idea. By allowing the input of a Length within a Source Setting you may have an ‘Optimal Length’ that adjusts automatically without the need for manual intervention. This may allow for Traditional and Non-Traditional Indicators and/or Strategies to allow modifications within their settings as well to accommodate the idea of this ‘Optimal Length’ model to create an Indicator and/or Strategy that adjusts its length based on the top performing Length within the current Market Conditions.
This specific Indicator aims to allow backtesting with an ‘Optimal Length’ inputted as a ‘Source’ within the Settings.
This ‘Optimal Length’ may be used to display and potentially optimize multiple different Traditional Indicators within this BackTester. The following Traditional Indicators are included and available to be backtested with an ‘Optimal Length’ inputted as a Source in the Settings:
Moving Average; expressed as either a: Simple Moving Average, Exponential Moving Average or Volume Weighted Moving Average
Bollinger Bands; expressed based on the Moving Average Type
Donchian Channels; expressed based on the Moving Average Type
Envelopes; expressed based on the Moving Average Type
Envelopes Adjusted; expressed based on the Moving Average Type
All of these Traditional Indicators likewise may be displayed with multiple ‘Optimal Lengths’. They have the ability for multiple different ‘Optimal Lengths’ to be inputted and displayed, such as:
Fast Optimal Length
Slow Optimal Length
Neutral Optimal Length
By allowing for the input of multiple different ‘Optimal Lengths’ we may express the ‘Optimal Movement’ of such an expressed Indicator based on different Time Frames and potentially also movement based on Fast, Slow and Neutral (Inclusive) Lengths.
This in general is a simple Indicator that simply allows for the input of multiple different varieties of ‘Optimal Lengths’ to be displayed in different ways using Tradition Indicators. However, the idea and model of accepting a Length as a Source is unique and may be adopted in many different forms and endless ideas.
Tutorial:
You may add an ‘Optimal Length’ within the Settings as a ‘Source’ as followed in the example above. This Indicator allows for the input of a:
Neutral ‘Optimal Length’
Fast ‘Optimal Length’
Slow ‘Optimal Length’
It is important to account for all three as they generally encompass different min/max length values and therefore result in varying ‘Optimal Length’s’.
For instance, say you’re calculating the ‘Optimal Length’ and you use:
Min: 1
Max: 400
This would therefore be scanning for 400 (inclusive) lengths.
As a general way of calculating you may assume the following for which lengths are being used within an ‘Optimal Length’ calculation:
Fast: 1 - 199
Slow: 200 - 400
Neutral: 1 - 400
This allows for the calculation of a Fast and Slow length within the predetermined lengths allotted. However, it likewise allows for a Neutral length which is inclusive to all lengths alloted and may be deemed the ‘Most Accurate’ for these reasons. However, just because the Neutral is inclusive to all lengths, doesn’t mean the Fast and Slow lengths are irrelevant. The Fast and Slow length inputs may be useful for seeing how specifically zoned lengths may fair, and likewise when they cross over and/or under the Neutral ‘Optimal Length’.
This Indicator features the ability to display multiple different types of Traditional Indicators within the ‘Display Type’.
We will go over all of the different ‘Display Types’ with examples on how using a Fast, Slow and Neutral length would impact it:
Simple Moving Average:
In this example above have the Fast, Slow and Neutral Optimal Length formatted as a Slow Moving Average. The first example is on the 15 minute Time Frame and the second is on the 1 Day Time Frame, demonstrating how the length changes based on the Time Frame and the effects it may have.
Here we can see that by inputting ‘Optimal Lengths’ as a Simple Moving Average we may see moving averages that change over time with their ‘Optimal Lengths’. These lengths may help identify Support and/or Resistance locations. By using an 'Optimal Length' rather than a static length, we may create a Moving Average which may be more accurate as it attempts to be adaptive to current Market Conditions.
Bollinger Bands:
Bollinger Bands are a way to see a Simple Moving Average (SMA) that then uses Standard Deviation to identify how much deviation has occurred. This Deviation is then Added and Subtracted from the SMA to create the Bollinger Bands which help Identify possible movement zones that are ‘within range’. This may mean that the price may face Support / Resistance when it reaches the Outer / Inner bounds of the Bollinger Bands. Likewise, it may mean the Price is ‘Overbought’ when outside and above or ‘Underbought’ when outside and below the Bollinger Bands.
By applying All 3 different types of Optimal Lengths towards a Traditional Bollinger Band calculation we may hope to see different ranges of Bollinger Bands and how different lookback lengths may imply possible movement ranges on both a Short Term, Long Term and Neutral perspective. By seeing these possible ranges you may have the ability to identify more levels of Support and Resistance over different lengths and Trading Styles.
Donchian Channels:
Above you’ll see two examples of Machine Learning: Optimal Length applied to Donchian Channels. These are displayed with both the 15 Minute Time Frame and the 1 Day Time Frame.
Donchian Channels are a way of seeing potential Support and Resistance within a given lookback length. They are a way of withholding the High’s and Low’s of a specific lookback length and looking for deviation within this length. By applying a Fast, Slow and Neutral Machine Learning: Optimal Length to these Donchian Channels way may hope to achieve a viable range of High’s and Low’s that one may use to Identify Support and Resistance locations for different ranges of Optimal Lengths and likewise potentially different Trading Strategies.
Envelopes / Envelopes Adjusted:
Envelopes are an interesting one in the sense that they both may be perceived as useful; however we deem that with the use of an ‘Optimal Length’ that the ‘Envelopes Adjusted’ may work best. We will start with examples of the Traditional Envelope then showcase the Adjusted version.
Envelopes:
As you may see, a Traditional form of Envelopes even produced with a Machine Learning: Optimal Length may not produce optimal results. Unfortunately this may occur with some Traditional Indicators and they may need some adjustments as you’ll notice with the ‘Envelopes Adjusted’ version. However, even without the adjustments, these Envelopes may be useful for seeing ‘Overbought’ and ‘Oversold’ locations within a Machine Learning: Optimal Length standpoint.
Envelopes Adjusted:
By adding an adjustment to these Envelopes, we may hope to better reflect our Optimal Length within it. This is caused by adding a ratio reflection towards the current length of the Optimal Length and the max Length used. This allows for the Fast and Neutral (and potentially Slow if Neutral is greater) to achieve a potentially more accurate result.
Envelopes, much like Bollinger Bands are a way of seeing potential movement zones along with potential Support and Resistance. However, unlike Bollinger Bands which are based on Standard Deviation, Envelopes are based on percentages +/- from the Simple Moving Average.
We will conclude our Tutorial here. Hopefully this has given you some insight into how useful adding a ‘Optimal Length’ within an external (secondary) Indicator as a Source within the Settings may be. Likewise, how useful it may be for automation sake in the sense that when the ‘Optimal Length’ changes, it doesn’t rely on an alert where you need to manually update it yourself; instead it will update Automatically and you may reap the benefits of such with little manual input needed (aside from the initial setup).
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Alxuse Supertrend 4EMA Buy and Sell for tutorialAll abilities of Supertrend, moreover :
Drawing 4 EMA band & the ability to change values, change colors, turn on/off show.
Sends Signal Sell and Buy in multi timeframe.
The ability used in the alert section and create customized alerts.
To receive valid alerts the replay section , the timeframe of the chart must be the same as the timeframe of the indicator.
Supertrend with a simple EMA Filter can improve the performance of the signals during a strong trend.
For detecting the continuation of the downward and upward trend we can use 4 EMA colors.
In the upward trend , the EMA lines are in order of green, blue, red, yellow from bottom to top.
In the downward trend, the EMA lines are in order of yellow, red, blue, green from bottom to top.
How it works:
x1 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA3, MA4)
x2 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA2, MA3)
x3 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA1, MA2)
y1 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA3, MA4)
y2 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA2, MA3)
y3 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA1, MA2)
Red triangle = x1 or x2 or x3
Green triangle = y1 or y2 or y3
Long = BUY signal and followed by a Green triangle
Exit Long = SELL signal
Short = SELL signal and followed by a Red triangle
Exit Short = BUY signal
It is also possible to get help from the Stochastic RSI and MACD indicators for confirmation.
For receiving a signal with these two conditions or more conditions, i am making a video tutorial that I will release soon.
Supertrend
Definition
Supertrend is a trend-following indicator based on Average True Range (ATR). The calculation of its single line combines trend detection and volatility. It can be used to detect changes in trend direction and to position stops.
The basics
The Supertrend is a trend-following indicator. It is overlaid on the main chart and their plots indicate the current trend. A Supertrend can be used with varying periods (daily, weekly, intraday etc.) and on varying instruments.
The Supertrend has several inputs that you can adjust to match your trading strategy. Adjusting these settings allows you to make the indicator more or less sensitive to price changes.
For the Supertrend inputs, you can adjust atrLength and multiplier:
the atrLength setting is the lookback length for the ATR calculation;
multiplier is what the ATR is multiplied by to offset the bands from price.
When the price falls below the indicator curve, it turns red and indicates a downtrend. Conversely, when the price rises above the curve, the indicator turns green and indicates an uptrend. After each close above or below Supertrend, a new trend appears.
Summary
The Supertrend helps you make the right trading decisions. However, there are times when it generates false signals. Therefore, it is best to use the right combination of several indicators. Like any other indicator, Supertrend works best when used with other indicators such as MACD, Parabolic SAR, or RSI.
Exponential Moving Average
Definition
The Exponential Moving Average (EMA) is a specific type of moving average that points towards the importance of the most recent data and information from the market. The Exponential Moving Average is just like it’s name says - it’s exponential, weighting the most recent prices more than the less recent prices. The EMA can be compared and contrasted with the simple moving average.
Similar to other moving averages, the EMA is a technical indicator that produces buy and sell signals based on data that shows evidence of divergence and crossovers from general and historical averages. Additionally, the EMA tries to amplify the importance that the most recent data points play in a calculation.
It is common to use more than one EMA length at once, to provide more in-depth and focused data. For example, by choosing 10-day and 200-day moving averages, a trader is able to determine more from the results in a long-term trade, than a trader who is only analyzing one EMA length.
It’s best to use the EMA when for trending markets, as it shows uptrends and downtrends when a market is strong and weak, respectively. An experienced trader will know to look both at the line the EMA projects, as well as the rate of change that comes from each bar as it moves to the next data point. Analyzing these points and data streams correctly will help the trader determine when they should buy, sell, or switch investments from bearish to bullish or vice versa.
Short-term averages, on the other hand, is a different story when analyzing Exponential Moving Average data. It is most common for traders to quote and utilize 12- and 26-day EMAs in the short-term. This is because they are used to create specific indicators. Look into Moving Average Convergence Divergence (MACD) for more information. Similarly, the 50- and 200-day moving averages are most common for analyzing long-term trends.
Moving averages can be very useful for traders using technical analysis for profit. It is important to identify and realize, however, their shortcomings, as all moving averages tend to suffer from recurring lag. It is difficult to modify the moving average to work in your favor at times, often having the preferred time to enter or exit the market pass before the moving average even shows changes in the trend or price movement for that matter.
All of this is true, however, the EMA strives to make this easier for traders. The EMA is unique because it places more emphasis on the most recent data. Therefore, price movement and trend reversals or changes are closely monitored, allowing for the EMA to react quicker than other moving averages.
Limitations
Although using the Exponential Moving Average has a lot of advantages when analyzing market trends, it is also uncertain whether or not the use of most recent data points truly affects technical and market analysis. In addition, the EMA relies on historical data as its basis for operating and because news, events, and other information can change rapidly the indicator can misinterpret this information by weighting the current prices higher than when the event actually occurred.
Summary
The Exponential Moving Average (EMA) is a moving average and technical indicator that reflects and projects the most recent data and information from the market to a trader and relies on a base of historical data. It is one of many different types of moving averages and has an easily calculable formula.
The added features to the indicator are made for training, it is advisable to use it with caution in tradings.
[blackcat] L1 Dynamic Volatility IndicatorThe volatility indicator (Volatility) is used to measure the magnitude and instability of price changes in financial markets or a specific asset. This thing is usually used to assess how risky the market is. The higher the volatility, the greater the fluctuation in asset prices, but brother, the risk is also relatively high! Here are some related terms and explanations:
- Historical Volatility: The actual volatility of asset prices over a certain period of time in the past. This thing is measured by calculating historical data.
- Implied Volatility: The volatility inferred from option market prices, used to measure market expectations for future price fluctuations.
- VIX Index (Volatility Index): Often referred to as the "fear index," it predicts the volatility of the US stock market within 30 days in advance. This is one of the most famous volatility indicators in global financial markets.
Volatility indicators are very important for investors and traders because they can help them understand how unstable and risky the market is, thereby making wiser investment decisions.
Today I want to introduce a volatility indicator that I have privately held for many years. It can use colors to judge sharp rises and falls! Of course, if you are smart enough, you can also predict some potential sharp rises and falls by looking at the trend!
In the financial field, volatility indicators measure the magnitude and instability of price changes in different assets. They are usually used to assess the level of market risk. The higher the volatility, the greater the fluctuation in asset prices and therefore higher risk. Historical Volatility refers to the actual volatility of asset prices over a certain period of time in the past, which can be measured by calculating historical data; while Implied Volatility is derived from option market prices and used to measure market expectations for future price fluctuations. In addition, VIX Index is commonly known as "fear index" and is used to predict volatility in the US stock market within 30 days. It is one of the most famous volatility indicators in global financial markets.
Volatility indicators are very important for investors and traders because they help them understand market uncertainty and risk, enabling them to make wiser investment decisions. The L1 Dynamic Volatility Indicator that I am introducing today is an indicator that measures volatility and can also judge sharp rises and falls through colors!
This indicator combines two technical indicators: Dynamic Volatility (DV) and ATR (Average True Range), displaying warnings about sharp rises or falls through color coding. DV has a slow but relatively smooth response, while ATR has a fast but more oscillating response. By utilizing their complementary characteristics, it is possible to construct a structure similar to MACD's fast-slow line structure. Of course, in order to achieve fast-slow lines for DV and ATR, first we need to unify their coordinate axes by normalizing them. Then whenever ATR's yellow line exceeds DV's purple line with both curves rapidly breaking through the threshold of 0.2, sharp rises or falls are imminent.
However, it is important to note that relying solely on the height and direction of these two lines is not enough to determine the direction of sharp rises or falls! Because they only judge the trend of volatility and cannot determine bull or bear markets! But it's okay, I have already considered this issue early on and added a magical gradient color band. When the color band gradually turns warm, it indicates a sharp rise; conversely, when the color band tends towards cool colors, it indicates a sharp fall! Of course, you won't see the color band in sideways consolidation areas, which avoids your involvement in unnecessary trades that would only waste your funds! This indicator is really practical and with it you can better assess market risks and opportunities!
User Defined Momentum Change with Swing VisualsThis script is a groundbreaking, math-centric technical analysis tool that blends two well-established indicators, the Stochastic Oscillator and the Exponential Moving Average (EMA), to deliver a unique and visually engaging way of identifying momentum swings and stochastic indicators. Unlike mashups, this script is tailored to accommodate a wide range of trading strategies, providing traders with a distinctive perspective on market trends.
The innovation in this script lies in its mathematically-driven ability to effectively combine the Stochastic Oscillator and EMA, setting it apart from other available tools that simply offer a rehash of old ideas or slight modifications to popular indicators. The EMA is employed instead of a Simple Moving Average (SMA), enhancing the uniqueness of the calculations. This novel approach creates a new dimension for traders to evaluate potential momentum swings and visualize them on the chart, proving it to be more than just a mere mashup of existing indicators.
Central to the script's utility is its extensive customization options, which allow traders to adjust various inputs to suit their preferences and trading strategies. Users can modify the EMA length, swing range signal offsets, and smoothing factors for both the fast and slow components of the Stochastic Oscillator. Additionally, the script offers the ability to personalize the color thresholds, transparency, and line properties for the Stochastic Oscillator and swing range signal.
This script's visually dynamic representation of momentum swings empowers traders to make more informed trading decisions, particularly on the 6-hour timeframe. The swing range signal, represented by vertical lines on the chart, acts as a valuable visual aid for identifying potential entry or exit points. Furthermore, the Stochastic Oscillator provides insights into the strength and direction of momentum, which is beneficial for confirming potential trade signals.
To conclude, this script is not just another combination of MAs or a slightly modified version of a popular indicator. Instead, it offers traders a comprehensive, visually appealing, and customizable tool for technical analysis, which is both original and useful. By uniquely combining the EMA and the Stochastic Oscillator with a strong mathematical foundation, and allowing traders to adjust a variety of settings, this script adds value to the TradingView community and enhances the body of knowledge available for traders. It is designed to support traders in tailoring their analysis based on their own strategies and preferences, enabling them to make well-informed decisions in the financial markets.
JS-TechTrading: VWAP Momentum_Pullback StrategyGeneral Description and Unique Features of this Script
Introducing the VWAP Momentum-Pullback Strategy (long-only) that offers several unique features:
1. Our script/strategy utilizes Mark Minervini's Trend-Template as a qualifier for identifying stocks and other financial securities in confirmed uptrends.
NOTE: In this basic version of the script, the Trend-Template has to be used as a separate indicator on TradingView (Public Trend-Template indicators are available on TradingView – community scripts). It is recommended to only execute buy signals in case the stock or financial security is in a stage 2 uptrend, which means that the criteria of the trend-template are fulfilled.
2. Our strategy is based on the supply/demand balance in the market, making it timeless and effective across all timeframes. Whether you are day trading using 1- or 5-min charts or swing-trading using daily charts, this strategy can be applied and works very well.
3. We have also integrated technical indicators such as the RSI and the MA / VWAP crossover into this strategy to identify low-risk pullback entries in the context of confirmed uptrends. By doing so, the risk profile of this strategy and drawdowns are being reduced to an absolute minimum.
Minervini’s Trend-Template and the ‘Stage-Analysis’ of the Markets
This strategy is a so-called 'long-only' strategy. This means that we only take long positions, short positions are not considered.
The best market environment for such strategies are periods of stable upward trends in the so-called stage 2 - uptrend.
In stable upward trends, we increase our market exposure and risk.
In sideways markets and downward trends or bear markets, we reduce our exposure very quickly or go 100% to cash and wait for the markets to recover and improve. This allows us to avoid major losses and drawdowns.
This simple rule gives us a significant advantage over most undisciplined traders and amateurs!
'The Trend is your Friend'. This is a very old but true quote.
What's behind it???
• 98% of stocks made their biggest gains in a Phase 2 upward trend.
• If a stock is in a stable uptrend, this is evidence that larger institutions are buying the stock sustainably.
• By focusing on stocks that are in a stable uptrend, the chances of profit are significantly increased.
• In a stable uptrend, investors know exactly what to expect from further price developments. This makes it possible to locate low-risk entry points.
The goal is not to buy at the lowest price – the goal is to buy at the right price!
Each stock goes through the same maturity cycle – it starts at stage 1 and ends at stage 4
Stage 1 – Neglect Phase – Consolidation
Stage 2 – Progressive Phase – Accumulation
Stage 3 – Topping Phase – Distribution
Stage 4 – Downtrend – Capitulation
This strategy focuses on identifying stocks in confirmed stage 2 uptrends. This in itself gives us an advantage over long-term investors and less professional traders.
By focusing on stocks in a stage 2 uptrend, we avoid losses in downtrends (stage 4) or less profitable consolidation phases (stages 1 and 3). We are fully invested and put our money to work for us, and we are fully invested when stocks are in their stage 2 uptrends.
But how can we use technical chart analysis to find stocks that are in a stable stage 2 uptrend?
Mark Minervini has developed the so-called 'trend template' for this purpose. This is an essential part of our JS-TechTrading pullback strategy. For our watchlists, only those individual values that meet the tough requirements of Minervini's trend template are eligible.
The Trend Template
• 200d MA increasing over a period of at least 1 month, better 4-5 months or longer
• 150d MA above 200d MA
• 50d MA above 150d MA and 200d MA
• Course above 50d MA, 150d MA and 200d MA
• Ideally, the 50d MA is increasing over at least 1 month
• Price at least 25% above the 52w low
• Price within 25% of 52w high
• High relative strength according to IBD.
NOTE: In this basic version of the script, the Trend-Template has to be used as a separate indicator on TradingView (Public Trend-Template indicators are available in TradingView – community scripts). It is recommended to only execute buy signals in case the stock or financial security is in a stage 2 uptrend, which means that the criteria of the trend-template are fulfilled.
This strategy can be applied to all timeframes from 5 min to daily.
The VWAP Momentum-Pullback Strateg y
For the JS-TechTrading VWAP Momentum-Pullback Strategy, only stocks and other financial instruments that meet the selected criteria of Mark Minervini's trend template are recommended for algorithmic trading with this startegy.
A further prerequisite for generating a buy signals is that the individual value is in a short-term oversold state (RSI).
When the selling pressure is over and the continuation of the uptrend can be confirmed by the MA / VWAP crossover after reaching a price low, a buy signal is issued by this strategy.
Stop-loss limits and profit targets can be set variably.
Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a technical indicator developed by Welles Wilder in 1978. The RSI is used to perform a market value analysis and identify the strength of a trend as well as overbought and oversold conditions. The indicator is calculated on a scale from 0 to 100 and shows how much an asset has risen or fallen relative to its own price in recent periods.
The RSI is calculated as the ratio of average profits to average losses over a certain period of time. A high value of the RSI indicates an overbought situation, while a low value indicates an oversold situation. Typically, a value > 70 is considered an overbought threshold and a value < 30 is considered an oversold threshold. A value above 70 signals that a single value may be overvalued and a decrease in price is likely , while a value below 30 signals that a single value may be undervalued and an increase in price is likely.
For example, let's say you're watching a stock XYZ. After a prolonged falling movement, the RSI value of this stock has fallen to 26. This means that the stock is oversold and that it is time for a potential recovery. Therefore, a trader might decide to buy this stock in the hope that it will rise again soon.
The MA / VWAP Crossover Trading Strategy
This strategy combines two popular technical indicators: the Moving Average (MA) and the Volume Weighted Average Price (VWAP). The MA VWAP crossover strategy is used to identify potential trend reversals and entry/exit points in the market.
The VWAP is calculated by taking the average price of an asset for a given period, weighted by the volume traded at each price level. The MA, on the other hand, is calculated by taking the average price of an asset over a specified number of periods. When the MA crosses above the VWAP, it suggests that buying pressure is increasing, and it may be a good time to enter a long position. When the MA crosses below the VWAP, it suggests that selling pressure is increasing, and it may be a good time to exit a long position or enter a short position.
Traders typically use the MA VWAP crossover strategy in conjunction with other technical indicators and fundamental analysis to make more informed trading decisions. As with any trading strategy, it is important to carefully consider the risks and potential rewards before making any trades.
This strategy is applicable to all timeframes and the relevant parameters for the underlying indicators (RSI and MA/VWAP) can be adjusted and optimized as needed.
Backtesting
Backtesting gives outstanding results on all timeframes and drawdowns can be reduced to a minimum level. In this example, the hourly chart for MCFT has been used.
Settings for backtesting are:
- Period from April 2020 until April 2021 (1 yr)
- Starting capital 100k USD
- Position size = 25% of equity
- 0.01% commission = USD 2.50.- per Trade
- Slippage = 2 ticks
Other comments
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The RSI qualifier is highly selective and filters out the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• As a result, traders need to apply this strategy for a full watchlist rather than just one financial security.
Divergence Strength OscillatorDetects divergence before it has formed a valid divergent pivot, across multiple indicators. After publishing my Strength of Divergence Across Multiple Indicators script, it seemed there were a lot of people who wanted to see the divergence signals before the divergent pivots were actually confirmed. Everyone complains about indicators repainting, yet in the next breath they complain about not wanting to wait for a signal to be confirmed before it appears on their chart! No matter how many times you ask, you can't have your cake and eat it too.
While this isn't exactly cake, it's as close as you're gonna get. This oscillator will calculate the strength of divergence as it forms on any bar that could potentially be a pivot point (e.g. for a pivot low, the preceding bars must be higher than it) and track the net (bullish - bearish) value.
For example:
PLEASE NOTE that this is not intended to be a "Buy" or "Sell" signal, and it would be foolish to use it as such. The purpose of this script is to show you potential divergences as early as possible, so that you have more time to plan and evaluate confluent signals, etc.
The Divergence Strength Calculation:
The total divergence strength value is the sum of the divergence strengths of all indicators for which divergence was detected at a given bar. Each indicator's individual divergence strength is comprised of two basic components: (1) |ΔPrice| - the magnitude of the change in price over the divergence period (pivot-to-pivot), and (2) |ΔIndicator| - the magnitude of the change in indicator value over the divergence period.
Because different indicators' scales and volatility can vary greatly, the Δ values are expressed in terms of standard deviation to ensure that the values are meaningful and equitable across all indicators and assets/instruments/currency pairs, etc:
|ΔIndicator| = |indicator_value_1 - indicator_value_2| / 2 * StDev(indicator_series,100)
Based on work for my Strength of Divergence Across Multiple Indicators script:
Coral Trend Pullback Strategy (TradeIQ)Description:
Strategy is taken from the TradeIQ YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto".
Check out the full video for further details/clarification on strategy entry/exit conditions.
The default settings are exactly as TradeIQ described in his video.
However I found some better results by some tweaking settings, increasing R:R ratio and by turning off confirmation indicators.
This would suggest that perhaps the current confirmation indicators are not the best options. I'm happy to try add some other optional confirmation indicators if they look to be more effective.
Recommended timeframe: 1H
Strategy incorporates the following features:
Risk management:
Configurable X% loss per stop loss
Configurable R:R ratio
Trade entry:
Based on strategy conditions below
Trade exit:
Based on strategy conditions below
Backtesting:
Configurable backtesting range by date
Trade drawings:
Each entry condition indicator can be turned on and off
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Alerting:
Alerts on LONG and SHORT trade entries
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: Coral Trend is bullish
C2: At least 1 candle where low is above Coral Trend since last cross above Coral Trend
C3: Pullback happens and price closes below Coral Trend
C4: Coral Trend colour remains bullish for duration of pullback
C5: After valid pullback, price then closes above Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Green line is above red line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is blue
C6.2.2: HawkEye Volume Indicator colour is green
SHORT
C1: Coral Trend is bearish
C2: At least 1 candle where high is below Coral Trend since last cross below Coral Trend
C3: Pullback happens and price closes above Coral Trend
C4: Coral Trend colour remains bearish for duration of pullback
C5: After valid pullback, price then closes below Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Red line is above green line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is red
C6.2.2: HawkEye Volume Indicator colour is red
NOTE: All the optional confirmation indicators cannot be overlayed with Coral Trend so feel free to add each separately to the chart for visual purposes
Trade exit:
Stop Loss: Calculated by recent swing low over previous X candles (configurable with "Local High/Low Lookback")
Take Profit: Calculated from R:R multiplier * Stop Loss size
Credits
Strategy origin: TradeIQ's YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto"
It combines the following indicators for trade entry conditions:
Coral Trend Indicator by @LazyBear (Main indicator)
Absolute Strength Histogram | jh by @jiehonglim (Optional confirmation indicator)
Indicator: HawkEye Volume Indicator by @LazyBear (Optional confirmation indicator)
ADX and DI by @BeikabuOyaji (Optional confirmation indicator)
HeikinAshi_Point (HA-P)Hello?
Traders, welcome.
If you "follow", you can always get new information quickly.
Please also click "Like".
Have a good day.
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Following the previously published MACD-Total indicator, we are releasing the second indicator.
- index -
1. HA-P Indicator Description
2. Chart interpretation using HA-P indicators
3. More important than indicators is creating a trading strategy
(1. HA-P Indicator Description)
The Heikin Ashi candle chart is a very good way to see trends.
However, it is a pity that the actual price is not known on the chart made of Heikin Ashi candles.
To compensate for this, the body candle part (Open~Close) of the Heikin Ashi candle was filled with the background of the normal candle.
If you see more candles below the bottom of the body candle, you know the strength of the downtrend is high.
Conversely, if more candles are displayed above their body candles equivalent, you can tell that the bullish strength is high.
It can be seen that when the body candle color is displayed in blue, it is more likely to decline, and when it is in yellow, it is more likely to rise.
The Heikin Ashi candle is a trending candle.
Therefore, Heikin Ashi candles cannot be traded on their own.
To complement this, HA-Low and HA-High indicators were created.
The point where the HA-Low and HA-High indicators are leveled serves as support and resistance.
So, the longer the horizontal line, the stronger the support and resistance role.
A typical RSI is usually expressed as Close.
Since the Close of the Heikin Ashi candle is different from the normal Close, we made it to display when the RSI is oversold and overbought as the background of the price chart.
You cannot trade with the RSI indicator and the Heikin Ashi candle.
However, it can be used to detect a change in trend.
This gives you time to react to trend changes.
In order to trade, it is possible to find support and resistance at the HA-Low and HA-High indicators.
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(2. Chart interpretation using HA-P indicator)
Let's interpret the BTCUSDT 1D chart using the HA-P indicator.
Primary resistance: around 21478.98
Secondary resistance: around 29380.57
It moved higher on the 4th of July, breaking out of the RSI oversold zone.
If it rises above the 19946.21 point and finds support, it is expected to lead to further upside.
However, it needs to rise above 21478.98 for support to lead to further upside.
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(3. More important than indicators is creating a trading strategy)
In order to trade using these indicators, you need to invest a lot of time and observe.
Whether you use an indicator or not, the most important thing in trading is whether you have many trading strategies.
No matter how good indicators and signals are, if you do not have a trading strategy, you will not be able to properly trade due to psychological pressure.
Therefore, it is most important to plan a trading strategy in advance before proceeding with a trade.
- How much money to invest
- How to set up a rough plan for buying in installments and selling in installments
- How to set the Stop Loss point
- How long will the investment be (short-term, medium-term, long-term, etc.)
Basically, the above thoughts must be concretely thought out before proceeding with the investment.
Otherwise, if you buy blindly when the price rises, there is a high possibility that you will end up incurring a loss due to psychological anxiety due to the volatility of the price.
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Money Flow LineWhat is this? The Money Flow Line (MFL) indicator is at its core a more even-tempered version of the Price-Volume-Trend (PVT). The primary difference is the usage of `hlc3` ((high + low + close) / 3) rather than `close` to use the "typical price" that it critical to the calculation of the Money Flow Index (MFI). Other similar indicators include the Accumulation Distribution Line (ADL) and the On Balance Volume (OBV) indicators. The purpose of all of these indicators is to attempt to measure the strength of the money flow by combining price and volume into a rolling measurement that can be compared over time to look for confirmations and divergences.
The indicator also includes an optional averaging (smoothing) line that can be enabled in the display settings. Enabling this smoothing line with a desired period allows for simpler trend comparisons and also allows the user to view how far the line has diverged from the mean. This creates an indicator very similar to Elder's Force Index (EFI), which is also a `close * volume` style indicator.
Why is this important? After an extreme movement or volume spike the MFI will "snap back" sharply as that bar eventually exits the set period. This produces a result that is meaningless and skews the indicator away from the market structure. Because of this behavior, range clamping, and the loss of comparative history I prefer to shy away from oscillator style indicators. The Money Flow Line instead gives you all of the history so you may compare and see the broader trend without sharp snaps in history based on an arbitrary period setting.
Why is this better? This produces a no-lag indicator that isn't subject to the harsh skewing produced by they Money Flow Index's period calculation. It doesn't lose history like MFI or EFI, is clear about the trend direction, and prefers a "typical price" (averaging the entire range of each bar) rather than whatever happens to be the closing price for a given bar.
How can I use it? The indicator is attempting to measure supply and demand in the markets. No indicator is perfect, but we can use all of the information we have available to make our best predictions. There are only 3 pieces of data the market gives us:
1. Price (action)
2. Volume
3. Time
The Money Flow Line combines all of these data points into a readable rolling data set that attempts to show subtle balance of power shifts based on changes in volume and "smart money" (or "big money") stepping in and out of the picture. Much like PVT, we look for the same things:
- Trend Identification: an up or down trend appears in the MFL
- Confirmations: the MFL agrees with price action in direction and magnitude
- Divergence: the MFL disagrees with price action, indicating a reversal may be coming soon
When applying the smoothing line we can also look for similar things we would with EFI. The primary case would be to look for the MFL to jump very far away from the mean (a high magnitude movement) which indicates that price may be reverting towards the mean soon (a "mean reversion"). On the other hand, it may indicate strength in the current price direction. All of these predictions depend heavily on price action and market structure. Good luck!
Adaptive Jurik Filter MACD [Loxx]Adaptive Jurik Filter MACD uses Jurik Volty and Adaptive Double Jurik Filter Moving Average (AJFMA) to derive Jurik Filter smoothed volatility.
What is MACD?
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence (MACD) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
What is Jurik Volty?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- Change colors of oscillators and bars
Adaptive Jurik Filter Volatility Oscillator [Loxx]Adaptive Jurik Filter Volatility Oscillator uses Jurik Volty and Adaptive Double Jurik Filter Moving Average (AJFMA) to derive Jurik Filter smoothed volatility.
What is Jurik Volty?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- UI options to color bars
Adaptive Jurik Filter Volatility Bands [Loxx]Adaptive Jurik Filter Volatility Bands uses Jurik Volty and Adaptive, Double Jurik Filter Moving Average (AJFMA) to derive Jurik Filter smoothed volatility channels around an Adaptive Jurik Filter Moving Average. Bands are placed at 1, 2, and 3 deviations from the core basline.
What is Jurik Volty?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- UI options to shut off colors and bands
