New Tradability by hajiIntroduction:
The New Tradability Indicator is a state-of-the-art, meticulously coded tool designed for traders on TradingView. Crafted with precision and an in-depth understanding of market dynamics, this indicator offers a comprehensive insight into market tradability across various time frames. By leveraging the core metrics of Trend Area and Quality, it aims to empower traders with the right information to make informed decisions, mitigate FOMO, and maximize profitability.
Core Features:
Three-tiered Time Frame Analysis:
Macro Time Frame: This captures the overarching market movement by analyzing long-term trends. It gives a bird's-eye view of the market's direction and momentum, ideal for position and swing traders.
Normal Time Frame: This is aligned with the current chart time frame. It offers real-time insights for those who trade more frequently, such as day traders or those who base their decisions on hourly or daily charts.
Micro Time Frame: Tailored for scalpers and short-term traders, this captures the minutiae of market fluctuations by focusing on smaller time frames.
Dual-metric Analysis:
Trend Area: This metric delves deep into the market's current trend strength. Whether bullish or bearish, it provides a quantified representation of the trend's vigor and possible continuation. A higher percentage indicates a more pronounced trend, offering traders clarity on potential breakout or reversal scenarios.
Quality: Designed to combat one of the trader's arch-nemeses, FOMO (Fear of Missing Out), this metric evaluates the aptness of entering a trade. A high-quality score signifies a ripe opportunity, suggesting that it's an optimal time to enter the market. Conversely, a low-quality score can act as a warning sign, indicating that the prime entry point might have passed, thus cautioning traders against making hasty decisions.
Tradability Bar: The culmination of the indicator's insights is reflected in the Tradability Bar. This holistic bar synthesizes data from all metrics and time frames to present traders with a singular, easy-to-read percentage. The higher the percentage, the more favorable the market conditions are deemed for trading.
Usage Guidelines:
For optimal results, traders are advised to:
Use the Tradability Bar as an initial reference point. A high percentage suggests promising trading conditions.
Dive deeper by analyzing individual metrics (Trend Area & Quality) and respective time frames to validate or refine their trading strategies.
Always consider external market news, events, and other technical analysis tools in conjunction with this indicator for a more rounded decision-making process.
Conclusion:
The New Tradability Indicator for TradingView stands as a beacon for traders navigating the tumultuous seas of the financial markets. By distilling complex market dynamics into actionable insights, it seeks to be an indispensable ally in a trader's journey towards consistent profitability. Whether you're a seasoned trader or just starting out, this tool is tailored to provide clarity, confidence, and a competitive edge in the trading arena. Welcome to the future of informed trading.
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Yearly and 12-Week Percentage Difference with EMAThe indicator "Yearly and 12-Week Percentage Difference with EMA" is designed to display the annual and 12-week difference in the percentage variability of asset prices, as well as their exponential moving averages (EMA) on the TradingView chart.
EMA Period (EMA Period): This is a configurable parameter that allows you to select a period for calculating the EMA.
Yearly % Difference (Annual percentage difference): This indicator shows the percentage difference between the current price and the asset price a year ago on weekly bars. The graph is displayed in blue.
12-Week % Difference (12 weeks difference as a percentage): This indicator shows the percentage difference between the current price and the asset price 12 weeks ago on weekly bars. The graph is displayed in green.
Zero Line (Zero Line): This black line on the chart shows the zero level.
EMA of Yearly % Difference (EMA of annual percentage difference): This line represents the exponential moving average (EMA) of the annual percentage difference. The graph is displayed in red.
EMA of 12-Week % Difference (EMA of the difference over 12 weeks as a percentage): This line represents the exponential moving average (EMA) of the difference over 12 weeks as a percentage. The graph is displayed in orange.
Use this indicator to analyze the percentage variability of asset prices on an annual and 12-week basis, as well as to track their EMA, which can help in making trading decisions.
Русская версия \\\\\
Индикатор "Разница в процентах за год и за 12 недель с EMA" предназначен для отображения цены от год к году, и за 12 недель процентной изменчивости цен актива, а также их экспоненциальных скользящих средних (EMA) на графике TradingView.
- EMA Period (Период EMA): Это настраиваемый параметр, который позволяет выбрать период для расчета EMA.
- Yearly % Difference (Годовая разница в процентах): Этот индикатор показывает процентную разницу между текущей ценой и ценой актива год назад на недельных барах. График отображается синим цветом.
- 12-Week % Difference (Разница за 12 недель в процентах): Этот индикатор показывает процентную разницу между текущей ценой и ценой актива 12 недель назад на недельных барах. График отображается зеленым цветом.
- Zero Line (Линия нуля): Эта черная линия на графике показывает нулевой уровень.
- EMA of Yearly % Difference (EMA годовой разницы в процентах): Эта линия представляет собой экспоненциальное скользящее среднее (EMA) годовой разницы в процентах. График отображается красным цветом.
- EMA of 12-Week % Difference (EMA разницы за 12 недель в процентах): Эта линия представляет собой экспоненциальное скользящее среднее (EMA) разницы за 12 недель в процентах. График отображается оранжевым цветом.
Используйте этот индикатор для анализа процентной изменчивости цен актива на годовой и 12-недельной основе, а также для отслеживания их EMA, что может помочь в принятии торговых решений.
Daily TrendDescription:
The "Daily Trend" script is a powerful technical analysis tool designed for TradingView. This indicator helps traders identify key support and resistance levels based on daily price data. It offers a visual representation of these levels, along with other technical indicators like Exponential Moving Averages (EMA), Supertrend, and Parabolic SAR.
Features:
Past Candle Price Levels: This script calculates and displays past daily candle price levels, including R1, R2, R3, R4, S1, S2, S3, and S4. These levels are vital for identifying potential reversals and breakout points.
Exponential Moving Average (EMA): The script includes an EMA indicator with a customizable period to help traders spot the trend direction and potential crossovers.
Supertrend Indicator: The Supertrend indicator is used to identify trend changes. It plots the Supertrend line and highlights the trend direction with color-coded regions.
Parabolic SAR: The Parabolic SAR indicator is integrated into the script to assist traders in identifying potential entry and exit points in the market.
Customizable Alerts: Traders can customize the indicator by choosing which past candle price levels and other features to display on the chart.
How to Use:
Apply the "Daily Trend" script to your TradingView chart.
Customize the indicator by enabling or disabling specific features, such as past candle price levels and EMA.
Pay attention to the color-coded regions for Supertrend and Parabolic SAR to determine the current trend direction.
Look for potential reversal or bounce signals based on the indicator's signals and the price action.
Consider using this script in conjunction with your trading strategy for enhanced technical analysis.
Risk Warning: Trading involves significant risk, and past performance is not indicative of future results. Always practice proper risk management and consider the broader context of the market before making trading decisions.
TASC 2023.10 COT Commercials Indicator█ OVERVIEW
This script implements the COT Commercials Indicator introduced by Alfred François Tagher in an article featured in TASC's October 2023 edition of Traders' Tips . The indicator is designed for use in futures markets and represents a fast stochastic (%K) calculated based on the commercial open interest values of an asset derived from the weekly Commitments Of Traders (COT) report .
█ CONCEPTS
The COT report, issued by the Commodity Futures Trading Commission (CFTC) , presents a breakdown of reportable open interest positions held by various trader groups—commercial, noncommercial, and nonreportable (small traders). Open interest reflects the total number of derivative contracts entered by market participants but not yet settled. Consequently, it can serve as a measure of market activity and liquidity.
The indicator showcased here aims to analyze changes in the reported net values of open interest for commercial traders/hedgers (often referred to as 'smart money', as they deal directly in underlying commodities). The net values are positive when the commercial traders have more long positions than short ones and negative when they hold more short positions than long ones. Positive net values indicate that commercial traders hold more long positions than short ones, while negative values indicate the opposite. Thus, overbought and oversold conditions of the COT Commercials Indicator potentially suggest collective bullish and bearish sentiments, respectively.
█ CALCULATIONS
The calculations involve these steps:
1. Net open interest values are extracted from COT data using the LibraryCOT library provided by TradingView.
2. A fast stochastic indicator (%K) is then applied to normalize these net values.
The script also provides an option of calculating and plotting the indicator curve for noncommercial (speculators) open interest.
find bulish patternsIn this script:
We continue to calculate the bullish engulfing condition for monthly candlesticks (engulfingConditionM) as before.
We then create two variables (engulfingConditionY and lastYear) to calculate the yearly engulfing condition.
We use an if statement to check if the year has changed compared to the previous bar. If it has, we update the engulfingConditionY variable; otherwise, we keep the previous year's value.
Finally, we plot the monthly and yearly signals on the chart.
This code allows you to work with monthly data and calculate yearly signals based on the monthly data available in TradingView. Please note that this is an approximation and not true yearly resolution data, but it's a common workaround used in TradingView Pine Script.
[blackcat] L1 Magic Moving AverageThis is a code snippet written in the Pine programming language for TradingView platform. It is an implementation of a custom technical indicator called "L1 Magic Moving Average".
Moving averages are widely used in technical analysis to identify trends and reversals in the price of an asset. The idea behind moving averages is to smooth out the price data by calculating the average price over a certain period of time. This helps to filter out the noise in the price data and provides a clearer picture of the underlying trend.
The Magic Moving Average (MMA) is a custom moving average that is calculated using a combination of three different types of moving averages: simple moving average (SMA), exponential moving average (EMA), and weighted moving average (WMA). The MMA is designed to be more responsive to changes in the price of an asset compared to traditional moving averages.
The code starts by defining the input parameters for the indicator. The length parameter determines the number of periods used for calculating the moving averages. The source parameter specifies the price data used to calculate the moving averages. Finally, the smoothness parameter adjusts the weighting of the WMA component of the MMA.
Once the input parameters are defined, the code calculates the MMA by adding the SMA, EMA, and WMA components. The SMA and EMA components are calculated using the standard functions provided by TradingView. The WMA component is calculated using a custom function that takes into account the smoothness parameter.
After the MMA is calculated, the code plots it on the chart as two lines, one for the current value and one for the previous value. The two lines are then filled with colors depending on the position of the current MMA relative to its previous value. If the current value is higher than the previous value, the plot is filled with yellow color, otherwise, it is filled with fuchsia color.
In addition to the plot, the code also includes logic for generating buy and sell signals based on the crossover of the MMA and its previous value. If the MMA crosses above its previous value, a buy signal is generated. Conversely, if the MMA crosses below its previous value, a sell signal is generated. When a signal is generated, an alert is triggered to notify the user.
Finally, the code also includes labels for the generated signals. When a buy signal is generated, a green "B" label is placed at the bottom of the candle. Similarly, when a sell signal is generated, a red "S" label is placed at the top of the candle. These labels help the user to quickly identify the signals on the chart.
Overall, this code provides a simple yet effective way of generating trading signals based on the Magic Moving Average. By using a combination of different types of moving averages, the indicator is able to capture different aspects of the price movement and generate signals that are more reliable. The flexibility of the input parameters also allows the user to adjust the indicator to their specific trading needs.
buyer_seller_scalping_indicatorThis code is a custom script designed for analyzing trading volume within a specific time window on the TradingView platform. It offers a comprehensive analysis of buying and selling activity during a defined period and provides visual aids and data summaries for traders to make informed decisions. Here's a detailed breakdown of its functionality and how to use it:
1. Custom Time Period: The script starts by allowing you to specify a custom time period for analysis. In this example, it's set from 04:00 to 09:29. You can modify these time values to suit your specific trading needs.
2. Volume Calculation: The script calculates buying and selling volume based on price levels. It takes into account the open, high, low, and close prices to determine whether buying or selling pressure is dominant during the specified time frame.
3. Total Volume Calculation: It calculates the total volume within the custom time period. This can help you gauge the overall activity and liquidity during the chosen time window.
4. Visualizations: The script then plots visual elements on the chart:
- A volume histogram, which provides a graphical representation of the total volume during the time period.
- Buying and selling volume indicators, which are shown as circles on the chart, highlighting the relative strength of buyers and sellers.
- An average volume line, represented in gray, which helps you identify the average trading volume over a 50-period moving average.
5. Volume Type Determination: The script determines whether buyers or sellers dominate the market during the specified time period. It labels this as "Buyers Volume > Sellers Volume," "Sellers Volume > Buyers Volume," or "Buyers Volume = Sellers Volume." This information can be crucial for assessing market sentiment.
6. Percentage Breakdown: The script calculates the percentage of buying and selling volume in relation to the total volume, helping you understand the distribution of market participants. These percentages are displayed in a table.
7. Table Display: Finally, the script creates a table that displays the following information:
- The current volume type (buyers, sellers, or balanced), with corresponding text colors.
- The percentage of buyers and sellers in the market.
How to Use:
1. Copy the script and add it as a custom script on TradingView.
2. Apply the script to your desired financial chart.
3. Adjust the custom time period if needed.
4. Interpret the visual elements and table to gain insights into market sentiment and volume distribution during the specified time frame.
5. Use this information to inform your trading decisions and strategies, especially when trading within the chosen time window.
This script is a valuable tool for traders seeking to understand market dynamics and volume behavior during specific trading hours, ultimately aiding in more informed trading decisions.
Disclaimer:
The indicator provided herein is experimental and has not undergone comprehensive testing. Its usage is solely at your own risk.
The publisher assumes no responsibility for any trading decisions made based on the utilization of this indicator.
[TTI] MarketSmith & IBD Style Model Stock Quarters 📜 ––––HISTORY & CREDITS––––
The MarketSmith & IBD Style Model Stock Quarters another Utility indicator is an original creation by TintinTrading inspired by Investor's Business Daily and William O'Neil style of presenting information. While going through the Model Stocks that IBD has been publishing, I realized that I wanted to see the exam same Quarterly presentation on the time axis in order to compare William O'Neil notes better with my own notes from Tradingview. The script is simple and could help you if you study the CANSLIM methodology.
🦄 –––UNIQUENESS–––
The distinctiveness of this indicator lies in its ability to visually delineate stock quarters directly on the price chart. It serves as a handy tool for traders who adopt a quarterly review of stock performance, in line with MarketSmith and IBD's analysis frameworks.
🛠️ ––––WHAT IT DOES––––
Quarter Marking : Draws a black line at the beginning of each financial quarter (January, April, July, and October).
Quarter Labeling : Places a label at the close of the last month in a quarter, indicating the upcoming quarter with its abbreviation and the last two digits of the year.
💡 ––––HOW TO USE IT––––
👉Installation: Add the indicator to your TradingView chart by searching for " MarketSmith & IBD Style Model Stock Quarters" in the indicator library.
👉Add to New Pane and squash the Pane Length: I add the indicator to a new pane under the price and volume charts and squash the height of the pane so that it looks exactly like the MarketSmith visuals.
👉Visual Cues:
Look for the black lines marking the start of a new quarter.
Observe the labels indicating the upcoming quarter and year, positioned at the close of the last month in a quarter.
👉Interpretation: Use these quarterly markers to align your trading strategies with quarterly performance metrics or to conduct seasonal analysis.
👉Settings: The indicator does not require any user-defined settings, making it straightforward to use.
Linear On MACDUnlocking the Magic of Linear Regression in TradingView
In the ever-evolving world of financial markets, traders and investors seek effective tools to gauge price movements, make informed decisions, and achieve their financial goals. One such tool that has proven its worth over time is linear regression, a mathematical concept that has found its way into technical analysis and trading strategies. In this blog post, we will explore the magic behind linear regression, delve into its history, and understand how it's widely used as a technical indicator.
The Birth of Linear Regression: From Mathematics to Trading
Linear regression is a statistical method that aims to model the relationship between two variables by fitting a linear equation to observed data. The formula for a linear regression line is typically expressed as y = a + bx, where y is the dependent variable, x is the independent variable, a is the intercept, and b is the slope.
While the roots of linear regression trace back to the field of statistics, it didn't take long for traders and investors to recognize its potential in the financial world. By applying linear regression to historical price data, traders can identify trends, assess the relationship between variables, and even predict potential future price levels.
The Linear On MACD Strategy
Let's take a closer look at a powerful example of how linear regression is employed in a trading strategy right within TradingView. The "Linear On MACD" strategy harnesses the potential of linear regression in conjunction with the Moving Average Convergence Divergence (MACD) indicator. The goal of this strategy is to generate buy and sell signals based on the interactions between the predicted stock price and the MACD indicator.
Here's a breakdown of the strategy's components:
Calculation of Linear Regression: The strategy begins by calculating linear regression coefficients for the historical stock price based on volume. This helps predict potential future price levels.
Predicted Stock Price: The linear regression results are then used to plot the predicted stock price on the chart. This provides a visual representation of where the price could trend based on historical data.
Buy and Sell Signals: The strategy generates buy signals when certain conditions are met. These conditions include the predicted stock price being between the open and close prices, a rising MACD, and other factors that suggest a potential bullish trend. On the other hand, sell signals are generated based on MACD trends and predicted price levels.
Risk Management: The strategy also incorporates risk tolerance levels to determine entry and exit points. This ensures that traders take into account their risk appetite when making trading decisions.
Embracing the Magic of Linear Regression
As we explore the "Linear On MACD" strategy, we uncover the power of linear regression in aiding traders and investors. Linear regression, a mathematical marvel, seamlessly merges with technical analysis to provide insights into potential price movements. Its historical significance in statistics blends perfectly with the demands of modern financial markets.
Whether you're a seasoned trader or a curious investor, the Linear On MACD strategy exemplifies how a robust mathematical concept can be harnessed to make informed trading decisions. By embracing the magic of linear regression, you're tapping into a tool that continues to evolve alongside the financial world it empowers.
Disclaimer: The information provided in this blog post is for educational purposes only and does not constitute financial advice. Trading and investing carry risks, and it's important to conduct thorough research and consider seeking professional advice before making any trading decisions.
Previous Day High Low Strategy only for LongWelcome to the "Previous Day High Low Strategy only for Long"!.
This strategy aims to identify potential long trading opportunities based on the previous day's high and low prices, along with certain market strength conditions.
Key Features:
Entry Conditions: The strategy triggers a long position when the current day's closing price crosses above the previous day's high or low.
Market Strength Filter: The strategy incorporates a market strength filter using the Average Directional Index (ADX). It only takes long positions when the ADX value is above a specific threshold and when there is a predominance of upward movement.
Trade Timing: The strategy operates within a specified trade window, starting at 09:30 and ending at 15:10. Positions are closed at 15:15 if still active.
Risk Management: The strategy employs dynamic stop-loss and profit-taking levels based on a user-defined Max Profit value. It has three profit targets (T1, T2, T3) and a stop-loss level to manage risk effectively.
Rules:
Ensure that the strategy idea is clearly understandable. Provide an easy-to-read title and a thoughtful description explaining the reasoning behind the strategy.
All content should be ad-free. Avoid any form of promotion, advertising, or solicitation.
No fundraising requests or money solicitation is allowed on TradingView.
Publish in the same language as the TradingView subdomain you're on, except for script titles, which must be in English.
Don't plagiarize. Create and share only unique content, and always give credit when using someone else's work.
Be respectful, kind, and constructive when engaging with others.
Zero tolerance for contentious political discourse, defamatory, threatening, or discriminatory remarks.
Avoid sharing harmful, misleading, or inappropriate content.
Respect the moderators' work and address complaints privately.
Use only your original account and avoid creating duplicate or fake accounts.
Do not attempt to manipulate the reputation system or engage in like-for-like schemes.
Explanation of how the strategy works
1. Previous Day's High and Low (HH, LL):
In this strategy, we start by obtaining the high and low prices of the previous day (not the current day) using the request.security function. This function allows us to access historical data for a specific time frame. The high and low prices are stored in the variables HH and LL, respectively.
2. Entry Conditions:
The strategy uses two conditions to trigger a long position:
Condition 1 (Long Condition 1): If the closing price of the current day crosses above the previous day's high (HH), it generates a long signal. This is achieved using the ta.crossover function, which detects when a crossover occurs.
Condition 2 (Long Condition 2): Similarly, if the closing price of the current day crosses above the previous day's low (LL), it also generates a long signal.
Combined Condition: To take long positions, the strategy combines both long conditions using the logical OR operator (or). This means that if either of the two conditions is met, a long position will be initiated.
3. Market Strength Filter:
The strategy also includes a filter based on the Average Directional Index (ADX) to gauge the market's strength before taking long positions. The ADX measures the strength of a trend in the market. The higher the ADX value, the stronger the trend.
Calculation of ADX: The ADX is calculated using the adx function, which takes two parameters: LWdilength (DMI Length) and LWadxlength (ADX period).
Strength Condition (strength_up): The strategy requires that the ADX value should be above a threshold (11 in this case) and that there is a predominance of upward movement (up > down) before initiating a long position. The LWADX value is multiplied by 2.5 and compared to the highest value of LWADX from the last 4 periods using ta.highest(LWADX , 4). If these conditions are met, the variable strength_up is set to true.
Combined Condition: The strength_up condition is then combined with the long conditions using the logical AND operator (and). This means that the strategy will only take a long position if both the long conditions and the market strength condition are met.
4. Trade Timing:
The strategy sets a specific trade window between 09:30 and 15:10. It will only execute trades within this time frame (TradeTime).
5. Risk Management:
The strategy implements dynamic stop-loss (SL) and profit-taking levels (T1, T2, T3) based on a user-defined Max Profit value. The stop-loss is set as a percentage of the Max Profit value. As the position moves in favor of the trader, the profit targets are adjusted accordingly.
6. Position Management:
The strategy uses the strategy.entry function to enter long positions based on the combined entry conditions. Once a position is open, the script uses strategy.exit to define the exit condition when either the profit target or stop-loss level is hit. The strategy.close function is used to close any open position at the end of the trade window (15:15).
7. Plotting:
The strategy uses the plot function to visualize the previous day's high and low prices, as well as the stop-loss (SL) and profit-taking (T1, T2, T3) levels on the chart.
Overall, the "Previous Day High Low Strategy only for Long" aims to identify potential long trading opportunities based on the previous day's price action and market strength conditions. However, as with any trading strategy, it's essential to thoroughly test it and consider risk management before applying it to real-world trading scenarios.
Disclaimer:
The information presented by this strategy is for educational purposes only and should not be considered as investment advice. The strategy is not designed for qualified investors. Always conduct your own research and consult with a financial advisor before making any trading decisions.
Remember, the success of any trading strategy depends on various factors, including market conditions, risk management, and individual trading skills. Past performance is not indicative of future results.
Multiple Exponential Moving AveragesThe "Multiple Exponential Moving Averages" indicator is a custom technical analysis tool created for TradingView. It combines five different Exponential Moving Averages (EMAs) into a single indicator. Each EMA has a user-defined length, and they are plotted on the chart with different colors to differentiate them.
Exponential Moving Averages are commonly used in technical analysis to smooth out price data and identify trends. They give more weight to recent price data, making them more responsive to recent price changes than Simple Moving Averages (SMAs). By combining multiple EMAs with different lengths, TradingView users will no longer have to worry that they will run out of slots when wanting to add new indicators to their chart.
Highest High and lowest low - Sachin Wakpaijan
The "Highest High and Lowest Low" indicator, created by Sachin Wakpaijan, is a powerful tool designed to identify the highest high and lowest low in a trading instrument's price history. This indicator can be used on TradingView to gain insights into significant price levels and potential trend reversals.
Inputs:
Display Emoji: This input parameter enables or disables the display of emoji symbols on the chart.
Functionality:
The indicator calculates the highest high and lowest low based on the price history. It performs the following steps:
Highest High Calculation: The indicator calculates the highest high by comparing the current high with the previously recorded highest high. If a new high is found, the highest high is updated. The lowest low is set to the highest high.
Lowest Low Calculation: The indicator calculates the lowest low based on the current low. If a new low is found, the lowest low is updated, and the highest after the low is set to the lowest low.
Checking for Highest After Low: If the current high exceeds the highest after the low, the highest after the low is updated.
Plotting: The indicator plots the highest high, highest after low, and lowest high on the chart. Additionally, it displays emoji symbols on the chart based on specific conditions, such as the highest high and the relationship between the high and the open/close prices.
Usage:
The "Highest High and Lowest Low" indicator can be applied to any trading instrument and time frame. It helps traders identify significant price levels, potential trend reversal points, and gauge the strength of price movements. The indicator's customizable input parameter allows users to adjust the visual appearance according to their preferences.
Note:
This indicator is provided for informational purposes only and should not be considered as financial advice. Traders should conduct thorough analysis and use additional indicators or techniques to validate their trading decisions.
Author:
This indicator was created by Sachin Wakpaijan. You can find more of their work on TradingView.
Disclaimer:
Trading involves risks, and it is essential to understand and acknowledge the risks associated with trading before making any investment decisions. The author do not assume any responsibility for any trading losses incurred as a result of using this indicator.
Currency Conversion ChartReleasing this utility indicator I made for myself and thought others may find it helpful.
It is a simple currency conversion indicator. I personally trade both the TSX and the NYSE and hold both CAD and USD. As such, when I take positions in either or, I like to track how the currency I hold is affecting my position.
What the indicator does:
So, as indicated above, it converts a ticker's candlestick chart into the designated currency. You can either manually set the currency exchange rate, or search the currency exchange chart on Tradingview and it will auto-convert:
Purple arrow: The purple arrow points to the auto-input. You can search the currency you want to convert and it will automatically apply the conversion. It defaults to USD to CAD, but you can do USD to JPY, AUD to CAD, whatever currency you want provided it is available on tradingview. Alternatively, you can select manual conversion and input the manual conversion rate to apply.
Green Arrow: The green arrow refers to the conversion type. The indicator will default to static auto. This will pull the previous daily close. As currency trades at all hours, real-time is not advisable because the currency is in constant flux. Static will provide more stable results. However, you can toggle between the two. You can also just toggle Manual conversion.
Yellow arrow and red arrow: These pertain to position management. The indicator will display the change in the currency price over the designated amount of days. If you want to know how much the currency has changed in price over the last 7 or 20 days, simply put that value in the change input.
When you click manage position, you can fill out the position size variable and put the number of days you have had the position in the change parameter. This is the cost of your position. It can be options or shares. It will then adjust your position cost for the current change in the currency based on the number of days you have held it.
The indicator can be viewed on any timeframe and you can see how the conversion price compares to the listed price.
And that's basically the indicator! Its a simple utility indicator and hopefully some people will find use from it like I do!
Safe trades everyone, take care.
Composite MomentumComposite Momentum Indicator - Enhancing Trading Insights with RSI & Williams %R
The Composite Momentum Indicator is a powerful technical tool that combines the Relative Strength Index (RSI) and Williams %R indicators from TradingView. This unique composite indicator offers enhanced insights into market momentum and provides traders with a comprehensive perspective on price movements. By leveraging the strengths of both RSI and Williams %R, the Composite Momentum Indicator offers distinct advantages over a simple RSI calculation.
1. Comprehensive Momentum Analysis:
The Composite Momentum Indicator integrates the RSI and Williams %R indicators to provide a comprehensive analysis of market momentum. It takes into account both the strength of recent price gains and losses (RSI) and the relationship between the current closing price and the highest-high and lowest-low price range (Williams %R). By combining these two momentum indicators, traders gain a more holistic view of market conditions.
2. Increased Accuracy:
While the RSI is widely used for measuring overbought and oversold conditions, it can sometimes generate false signals in certain market environments. The Composite Momentum Indicator addresses this limitation by incorporating the Williams %R, which focuses on the price range and can offer more accurate signals in volatile market conditions. This combination enhances the accuracy of momentum analysis, allowing traders to make more informed trading decisions.
3. Improved Timing of Reversals:
One of the key advantages of the Composite Momentum Indicator is its ability to provide improved timing for trend reversals. By incorporating both RSI and Williams %R, traders can identify potential turning points more effectively. The Composite Momentum Indicator offers an early warning system for identifying overbought and oversold conditions and potential trend shifts, helping traders seize opportunities with better timing.
4. Enhanced Divergence Analysis:
Divergence analysis is a popular technique among traders, and the Composite Momentum Indicator strengthens this analysis further. By comparing the RSI and Williams %R within the composite calculation, traders can identify divergences between the two indicators more easily. Divergence between the RSI and Williams %R can signal potential trend reversals or the weakening of an existing trend, providing valuable insights for traders.
5. Customizable Moving Average:
The Composite Momentum Indicator also features a customizable moving average (MA), allowing traders to further fine-tune their analysis. By incorporating the MA, traders can smooth out the composite momentum line and identify longer-term trends. This additional layer of customization enhances the versatility of the indicator, catering to various trading styles and timeframes.
The Composite Momentum Indicator, developed using the popular TradingView indicators RSI and Williams %R, offers a powerful tool for comprehensive momentum analysis. By combining the strengths of both indicators, traders can gain deeper insights into market conditions, improve accuracy, enhance timing for reversals, and leverage divergence analysis. With the added customization of the moving average, the Composite Momentum Indicator provides traders with a versatile and effective tool to make more informed trading decisions.
FibonRSI / ErkOziHello,
This software is a technical analysis script written in the TradingView Pine language. The script creates a trading indicator based on Fibonacci retracement levels and the RSI indicator, providing information about price movements and asset volatility by using Bollinger Bands.
There are many different scripts in the market that draw RSI and Fibonacci retracement levels. However, this script was originally designed by me and shared publicly on TradingView.
***The indicator uses RSI (Relative Strength Index) and Bollinger Bands (BB) as the basis for the FibonRSI strategy. RSI measures the strength of a price movement, and BB measures the volatility of an asset. The FibonRSI strategy is based on the idea that the Fibonacci ratios and RSI can be used to predict a asset's price retracement levels.
***The script allows for various parameters to be adjusted. Users can specify the price source type and adjust the periods for RSI and Bollinger Bands. The standard deviation number for Bollinger Bands can also be customized.
***The script calculates the current RSI indicator position and the basic, upper, and lower levels of Bollinger Bands. It then calculates and draws the Fibonacci retracement levels. The color of the RSI line is determined by the upper and lower distribution levels of Bollinger Bands. Additionally, the color of the Fibonacci retracement levels can also be customized by the user.
***This script can be used to determine potential buy and sell signals using Fibonacci retracement levels and RSI. For example, when the RSI is oversold and the price is close to a Fibonacci retracement level, it can be interpreted as a buying opportunity. Similarly, when the RSI is overbought and the price is close to a Fibonacci retracement level, it can be interpreted as a selling opportunity.
***The script takes input parameters such as the price source used for calculation, the period for the RSI indicator, the period for the Moving Average in Bollinger Bands, and the number of standard deviations used in Bollinger Bands.
***The script's conditions include elements such as calculating the current position of the RSI indicator, calculating the upper and lower Bollinger Bands, calculating the dispersion factor, and calculating Fibonacci levels.
***The parameters in the code can be adjusted for calculation, including the price type used, the RSI period, the Moving Average period for BB, and the standard deviation count for BB. After this, the current position of the RSI, Moving Average, and standard deviation for BB are calculated. After calculating the upper and lower BB, the levels above and below the average are calculated using a specific dispersion constant.
CONDITIONS FOR THE SCRIPT
current_rsi = ta.rsi(src, for_rsi) // Current position of the RSI indicator
basis = ta.ema(current_rsi, for_ma)
dev = for_mult * ta.stdev(current_rsi, for_ma)
upper = basis + dev
lower = basis - dev
dispersion = 1
disp_up = basis + (upper - lower) * dispersion
disp_down = basis - (upper - lower) * dispersion
// Fibonacci Levels
f100 = basis + (upper - lower) * 1.0
f78 = basis + (upper - lower) * 0.78
f65 = basis + (upper - lower) * 0.65
f50 = basis
f35 = basis - (upper - lower) * 0.65
f23 = basis - (upper - lower) * 0.78
f0 = basis - (upper - lower) * 1.0
***When calculating Fibonacci levels, the distance between the average of BB and the upper and lower BB is used. These levels are 0%, 23.6%, 35%, 50%, 65%, 78.6%, and 100%. Finally, the RSI line that changes color according to a specific RSI position, Fibonacci levels, and BB are visualized. Additionally, the levels of 70, 30, and 50 are also shown.
The script then sets the color of the RSI position according to the EMA and draws Bollinger Bands, RSI, Fibonacci levels, and the 70, 30, and 50 levels.
In conclusion, this script enables traders to analyze market trends and make informed decisions. It can also be customized to suit individual trading strategies.
This script analyzes the RSI indicator using Bollinger Bands and Fibonacci levels. The default settings are 14 periods for RSI, 233 periods and 2 standard deviations for BB. The MA period inside BB is selected as the BB period and is used when calculating Fibonacci levels.
***The reason for selecting these settings is to provide enough time for BB period to confirm a possible trend. Additionally, the MA period inside BB is matched with the BB period and used when calculating Fibonacci levels.
***Fibonacci levels are calculated from the distance between the upper and lower bands of BB and show how RSI movement is related to these levels. Better results can be achieved when RSI periods are set to Fibonacci numbers such as 21, 55, and 89. Therefore, the use of Fibonacci numbers is recommended when adjusting RSI periods. Fibonacci numbers are among the technical analysis tools that can capture the reflection of naturally occurring movements in the market. Therefore, the use of Fibonacci numbers often helps to better track fluctuations in the market.
Finally, the indicator also displays the 70 and 30 levels and the middle level (50) with Fibonacci levels drawn in circles. Changing these settings can help optimize the Fibonacci levels and further improve the indicator.
Thank you in advance for your suggestions and opinions......
4 Pole ButterworthTitle: 4 Pole Butterworth Filter: A Smooth Filtering Technique for Technical Analysis
Introduction:
In technical analysis, filtering techniques are employed to remove noise from time-series data, helping traders to identify trends and make better-informed decisions. One such filtering technique is the 4 Pole Butterworth Filter. In this post, we will delve into the 4 Pole Butterworth Filter, explore its properties, and discuss its implementation in Pine Script for TradingView.
4 Pole Butterworth Filter:
The Butterworth filter is a type of infinite impulse response (IIR) filter that is widely used in signal processing applications. Named after the British engineer Stephen Butterworth, this filter is designed to have a maximally flat frequency response in the passband, meaning it does not introduce any distortions or ripples in the filtered signal.
The 4 Pole Butterworth Filter is a specific type of Butterworth filter that utilizes four poles in its transfer function. This design provides a steeper roll-off between the passband and the stopband, allowing for better noise reduction without significantly affecting the underlying data.
Why Choose the 4 Pole Butterworth Filter for Smoothing?
The 4 Pole Butterworth Filter is an excellent choice for smoothing in technical analysis due to its maximally flat frequency response in the passband. This property ensures that the filtered signal remains as close as possible to the original data, without introducing any distortions or ripples. Additionally, the 4 Pole Butterworth Filter provides a steeper roll-off between the passband and the stopband, enabling better noise reduction while preserving the essential features of the data.
Implementing the 4 Pole Butterworth Filter:
In Pine Script, we can implement the 4 Pole Butterworth Filter using a custom function called `fourpolebutter`. The function takes two input parameters: the source data (src) and the filter length (len). The filter length determines the cutoff frequency of the filter, which in turn affects the amount of smoothing applied to the data.
Within the `fourpolebutter` function, we first calculate the filter coefficients based on the filter length. These coefficients are essential for calculating the output of the filter at each data point. Next, we compute the filtered output using a recursive formula that involves the current and previous data points as well as the filter coefficients.
Finally, we create a script that takes user inputs for the source data and filter length and plots the 4 Pole Butterworth Filter on a TradingView chart.
By adjusting the input parameters, users can configure the 4 Pole Butterworth Filter to suit their specific requirements and improve the readability of their charts.
Conclusion:
The 4 Pole Butterworth Filter is a powerful smoothing technique that can be used in technical analysis to effectively reduce noise in time-series data. Its maximally flat frequency response in the passband ensures that the filtered signal remains as close as possible to the original data, while its steeper roll-off between the passband and the stopband provides better noise reduction. By implementing this filter in Pine Script, traders can easily integrate it into their trading strategies and enhance the clarity of their charts.
Average Cost (Costo Promedio)ENGLISH
This 'Average Cost' script allows the user to input and visualize profit or loss for different stocks (up to 50) with average cost and quantity data on a single chart. This is useful for tracking the profit or loss of each stock in real-time.
To use this script, the user should follow these steps:
1. Add the 'Average Cost' script to your TradingView chart.
2. In the script's configuration window, input the tickers, average costs, and quantity of shares for each ticker you want to monitor.
3. Click 'Accept' to apply the changes.
This script is primarily designed for stock markets, but can also be useful in other financial markets where the user is interested in tracking the performance of multiple assets.
ESPAÑOL
Este script de "Costo Promedio" permite al usuario ingresar y visualizar si hay ganancia o perdida para diferentes acciones (hasta 50) con los datos de costos promedio y cantidad de acciones en un solo gráfico. Esto es útil para realizar un seguimiento de la ganancia o pérdida de cada acción en tiempo real.
Para utilizar este script, el usuario debe seguir estos pasos:
1. Agregue el script "Costo Promedio" a su gráfico en TradingView.
2. En la ventana de configuración del script, ingrese los tickers, costos promedio y cantidad de acciones para cada ticker que desee monitorear.
3. Haga clic en "Aceptar" para aplicar los cambios.
Este script está diseñado principalmente para los mercados de acciones, pero también puede ser útil en otros mercados financieros donde el usuario esté interesado en rastrear el rendimiento de múltiples activos.
Number Formatting Indian/USAThis is a Pine script that helps traders format numbers in different ways to make it easier to read and display big numbers on TradingView.
this script is specifically to help other fellow pinecoder. Its not a indicator.
The above code is an example of how to format numbers in TradingView using two different formats: Indian and USA. The code defines a function called `formatNumber()` which takes two arguments: num (the number to format) and format (the format to use - either "Indian" or "USA").
If the "Indian" format is selected, the function rounds the number to the nearest crore, lakh or thousand and adds the appropriate suffix (i.e. "Cr", "Lac" or "K"). If the "USA" format is selected, the function rounds the number to the nearest billion, million or thousand and adds the appropriate suffix (i.e. "B", "M" or "K").
In both cases, the function then adds commas to the formatted number. The example usage shows how to call the `formatNumber()` function with a given number and format, and then plot the formatted number as a label on the chart.
Dark Energy Divergence OscillatorThe Dark Energy Divergence Oscillator (DEDO)
What makes The Universe grow at an accelerating pace?
Dark Energy.
What makes The Economy grow at an accelerating pace?
Debt.
Debt is the Dark Energy of The Economy.
I pronounce DEDO "Deed-oh", but variations are fine with me.
Note: The Pine Script version of DEDO is improved from the original formula, which used a constant all-time high calculation in the normalization factor. This was technically not as accurate for calculating liquidity pressure in historical data because it meant that historical prices were being tested against future liquidity factors. Now using Pine, the functions can be normalized for the bar at the time of calculation, so the liquidity factors are normalized per candle, not across the entire series, which feels like an improvement to me.
Thought Process:
It's all about the liquidity. What I started with is a correlation between major stock indices such as SPX and WRESBAL , a balance sheet metric on FRED
After September 2008, when QE was initiated, many asset valuations started to follow more closely with liquidity factors. This led me to create a function that could combine asset prices and liquidity in WRESBAL , in order to calculate their divergence and chart the signal in TradingView.
The original formula:
First, we don't want "non-QE" data. we only want data for the market affected by QE .
So, find SPX on the day of pre-QE: 1255.08 and subtract that from the 2022 top 4818.62 = 3563.54
With this post-QE SPX range, now you can normalize the price level simply by dividing by the range = ( SPX -1255.08)/3563.54)
Normalization produces values from 0 to 1 so that they can be compared with other normalized figures.
In order to test the 0 to 1 normalized SPX range measure against the liquidity number, WRESBAL , it's the same idea: normalize it using the max as the denominator and you get a 0 to 1 liquidity index:
( WRESBAL /4276000000000)
Subtract one from the other to get the divergence:
(( WRESBAL /4276000000000)-(( SPX -1255.08)/3563.54))*10
x10 to reduce decimal places, but this option is configurable in DEDO's input settings tab.
Positive values indicate there's ample liquidity to hold up price or even create bullish momentum in some cases. Negative values mean price levels are potentially extended beyond what liquidity levels can support.
Note: many viewers of the charts on social media wanted the values to go down in alignment with price moving down, so inverting the chart is what I do with Option + I. I like the fact that negative values represent a deficit in liquidity to hold up price but that's just me.
Now with Pine Script and some help from other liquidity focused accounts on TradingView , I was able to derive a script that includes central bank liquidity and Reverse Repo liquidity drain, all in one algorithm, with adjustable settings.
Central bank assets included in this version:
-JPY (Japan)
-CNY (China)
-UK (British Pound)
-SNB (Swiss National Bank)
-ECB (European Central Bank )
Central Bank assets can be adjusted to an allocation % so that the formula is adjusted for the market cap of the asset.
A handy table in the lower right corner displays useful information about the asset market cap, and percentage it represents in the liquidity pool.
Reverse repo soak is also an optional addition in the Input settings using the RRPONTSYD value from FRED. This value is subtracted from global liquidity used to determine divergence since it is swept away from markets when residing in the Fed's reverse repo facility.
There is an option to draw a line at the Zero bound. This provides a convenience so that the line doesn't keep having to be redrawn on every chart. The normalized equation produces a value that should oscillate around zero, as price/valuation grows past liquidity support, falls under it, and repeats in cycles.
TOMMAR#TOMMAR #MultiMovingAverages #MMAR
Dear fellow traders, this is Tommy, and today I'd like to introduce you to the Multi-Moving Averages Ribbon (MMAR) indicator, which I believe to be one of the best MMAR indicators available on TradingView. Moving Averages is a popular technical analysis tool used to smooth out price data by creating an average of past price data points over a specified time period. They can be used to identify trends and provide a clearer view of price action, as well as generate buy and sell signals by observing crossovers between different moving average lines.
In the MMAR indicator, we have incorporated 12 different types of Moving Averages, including Simple Moving Averages (SMA), Exponential Moving Averages (EMA), Weighted Moving Averages (WMA), Hull Moving Averages (HMA), and Smoothed Moving Averages (SMMA), among others. This allows traders to choose the optimal type for their preferred trading commodities.
One common technique in technical analysis is using multiple Moving Averages with varying lengths, which provides a more comprehensive view of price action. By analyzing multiple Moving Averages with different timeframes, traders can better understand both short- and long-term trends and make more informed trading decisions. Some of the well-known combinations of multiple moving averages used by traders are (5, 9, 14, 21, 45), (6, 11, 16, 22, 51), [8, 13, 21, 55), (50, 100, 200), and (60, 120, 240).
Another way to gauge the strength of the market trend is to look for the arrangement of the Moving Averages. If they are in a sequential order, with the shortest on top and the longest on the bottom, it is most likely a bullish trend. On the other hand, if they are arranged in reverse order, with the shortest on the bottom and the longest on top, it is most likely a bearish trend. The 'Trend Light' in the indicator settings will automatically signal when the Moving Averages are in either an orderly or reverse arrangement.
Lastly, I have added a useful feature to the indicator: the 'MA Projection'. This feature projects and forecasts the Moving Averages in the future, allowing traders to easily identify confluence zones in future candlesticks. Please note that the projection levels may change in the case of extreme price action that significantly affects the Moving Averages.
This is free so any Tradingview users can use this indicator. Just search TOMMAR in the indicator section located on top of the chart.
#TOMMAR #MultiMovingAverages #MMAR
안녕하세요 트레이더 여러분, 토미입니다. 오늘 여러분들에게 소개드릴 지표는 다양한 길이의 이동평균선 조합을 사용할 수 있는 MMAR (Multiple Moving Averages Ribbon)입니다. 아마 제가 만든 MMAR 지표가 트레이딩뷰에서 가장 쓸만할 겁니다. 이동평균선, 줄여서 이평선은 말 그대로 특정 기간 범위 내의 주가들을 평균한 값들로 이루어진 선입니다. 제가 이평선 관련된 강의 자료는 예전에 올려드린 바 있으니 더 자세한 내용이 궁금하신 분들은 아래 링크/이미지 클릭하시길 바랍니다.
본 지표는 Simple Moving Averages (SMA), Exponential Moving Averages (EMA), Weighted Moving Averages (WMA), Hull Moving Averages (HMA), 그리고 Smoothed Moving Averages (SMMA) 등을 포함해 총 12개 종류의 이평선 지표를 사용할 수 있습니다. 또한 각 이평선의 길이들도 하나하나 일일이 설정하실 수 있습니다. 예를 들어 요즘에 자주 보이는 이평선들의 조합이 , , , , 그리고 등등이 존재하는데 여러분의 취향에 맞게 설정하여 사용하시면 됩니다.
몇 가지 주요 기능에 대해서 설명 드리겠습니다. 설정에서 ‘Trend Light’를 키면 이평선들의 정배열 혹은 역배열 여부를 쉽게 볼 수 있습니다. 이평선이 정배열일때는 맨 아래의 이평선에 초록불이, 역배열일때는 맨 위의 이평선에 빨간불이 켜지며 둘 다 아닐 땐 아무 불도 켜지지 않습니다. 또한 ‘MA Projection’을 키면 이평선들의 미래 예측 값들을 확장해줍니다. 당연히 가격 변동이 갑자기 크게 나오면 이평선 예측 확장 레벨들이 확 바뀌겠죠.
지표창에 TOMMAR 검색하시거나 아래 즐겨찾기 인디케이터에 넣기 클릭하시면 누구나 사용하실 수 있습니다~ 여러분의 구독, 좋아요, 댓글은 저에게 큰 힘이 됩니다.
RSI Multi Alerts MTFThis indicator won't plot anything to the chart.
Please follow steps below to set your alarms based on RSI oversold and overbought levels:
1) Add indicator to the chart
2) Go to settings
3) Choose up to 8 different symbols to get alert notification
4) Choose up to 4 different timeframes
5) Set overbought and oversold levels
6) Once all is set go back to the chart and click on 3 dots to set alert in this indicator, rename your alert and confirm
7) You can remove indicator after alert is set and it'll keep working as expected
What is does:
This indicator will generate alerts based on symbols, timeframes and RSI levels settings.
It will consider overbought and oversold levels to alert in each symbol and each timeframe selected. Once these levels are achieved it will send an alert with the following information:
- Symbol name (BTC, ETH, LTC)
- Specific RSI level achieved (e.g: RSI 30, RSI 70 or any custom level)
- Timeframe (e.g: 5m, 1h, 1D)
- Current symbol price
This script will request RSI OB/OS information through request.security() function from all different symbols and timeframes settings. It also requests symbols' price (close).
Due to Tradingview limitation (40 requests calls) it can only request information for 8 symbols for this script (8 symbols X 4 timeframes = 32 + 8 symbols' price (close) = 40)
Standard symbols are Binance USDT-M Futures but you can choose any symbol from Tradingview.
Standard timeframes are 5m|15m|1h|4h but you can choose from a list.
Standard overbought and oversold levels are 70 and 30 but you can change it to other integer values.
Feel free to give feedbacks on comments section below.
Enjoy!
DonchianFib[Akcay]How does it work?
- The indicator detects the highest and lowest price level in the last x periods every time prices advance by x periods.
- From these values, retracement (0.618, 0.786) and expansion levels (1.272, 1.618, 2, 2.618, 3.14, 3.618, 4.236) are obtained.
- Since the symmetrical counterpart of the retracement levels is used, there are two of each of the 0.618 and 0.786 lines, for a total of four.
How can it be used?
- It can be used for step buying.
- It can be used for step selling.
- Can be used to set a profit target.
- Can be used to set a stop target.
- This indicator can be used in the same way as Pivot levels can be used. You can think of this indicator like the Pivot Points Standard indicator, where you set the period more flexibly.
Which indicators can it be combined with?
- I don't think there are any limitations, but I think it is compatible with trend detection indicators, trend detection with DonchianFib, and stepped buy/sell with limit orders.
- If you want to enter a position with mismatch signals, you can wait for the DonchianFib levels to break.
- Its use is limited by your imagination :)
Where does the name come from?
- As the name suggests, Donchian Channels. I was inspired by Donchian Channels when developing the indicator. Donchian channels show the highs and lows of prices over the last x number of periods. DonchianFib does this once for every x periods and uses the fibonacci levels to create upper and intermediate levels.
Note : I don't know if such an indicator has been done before or not. If it has been done, I haven't seen it in tradingview.
Çalışma mantığı nedir ?
- Gösterge, fiyatlar her x periyot kadar ilerlediğinde son x periyot içerisindeki en yüksek ve en düşük fiyat seviyesini tespit eder.
- Bu değerler üzerinden geri çekilme (0.618, 0.786) ve genişleme seviyeleri (1.272, 1.618, 2, 2.618, 3.14, 3.618, 4.236) elde edilir.
- Geri çekilme seviyelerinin simetrik karşılığı kullanıldığından 0.618 ve 0.786 çizgilerinden her birinden iki adet olmak üzere toplamda dört adet bulunur.
Nasıl kullanılabilir ?
- Kademeli alım yapmak için kullanılabilir.
- Kademeli satım yapmak için kullanılabilir.
- Kâr hedefi belirlemek için kullanılabilir.
- Stop hedefi belirlemek için kullanılabilir.
- Pivot seviyelerinden nasıl faydalanılıyorsa bu göstergeden de aynı şekilde faydalanılabilir. Bu göstergeyi, periyodunu kendinizin daha esnek bir şekilde belirlediğiniz Pivot Noktalar Standartı göstergesi gibi düşünebilirsiniz.
Hangi göstergelerle kombine edilebilir ?
- Bunun için herhangi sınırlama yapmak doğru değil ancak trend tespit etmeye çalışan göstergelerle uyumlu olduğunu düşünüyorum. Bu göstergeler ile trend tespiti yapıp DonchianFib ile alım/satım yerleri belirlenebilir ve limit emirleri ile kademeli alım/satım yapılabilir.
- Uyuşmazlık sinyalleri ile pozisyona girilmek isteniliyorsa DonchianFib seviyelerinin kırılması beklenebilir.
- Kullanımı sizin hayal gücünüz ile sınırlıdır :)
Adı nereden geliyor ?
- Adından da anlaşılacağı üzere Donchian Kanallarından. Göstergeyi geliştirirken Donchian Kanallarından ilham aldım. Donchian kanalları fiyatların son x periyot içerisindeki en yüksek ve en düşük seviyelerini grafikte gösteriyor. DonchianFib ise bunu her x periyot için bir defa yapıp, fibonacci seviyelerini de kullanarak üst ve ara seviyeler oluşturuyor.
Not : Daha önce böyle bir göstergenin yapılıp yapılmadığını bilmiyorum. Yapıldı ise ben tradingview'da görmedim.
WaveTrend 3D█ OVERVIEW
WaveTrend 3D (WT3D) is a novel implementation of the famous WaveTrend (WT) indicator and has been completely redesigned from the ground up to address some of the inherent shortcomings associated with the traditional WT algorithm.
█ BACKGROUND
The WaveTrend (WT) indicator has become a widely popular tool for traders in recent years. WT was first ported to PineScript in 2014 by the user @LazyBear, and since then, it has ascended to become one of the Top 5 most popular scripts on TradingView.
The WT algorithm appears to have origins in a lesser-known proprietary algorithm called Trading Channel Index (TCI), created by AIQ Systems in 1986 as an integral part of their commercial software suite, TradingExpert Pro. The software’s reference manual states that “TCI identifies changes in price direction” and is “an adaptation of Donald R. Lambert’s Commodity Channel Index (CCI)”, which was introduced to the world six years earlier in 1980. Interestingly, a vestige of this early beginning can still be seen in the source code of LazyBear’s script, where the final EMA calculation is stored in an intermediate variable called “tci” in the code.
█ IMPLEMENTATION DETAILS
WaveTrend 3D is an alternative implementation of WaveTrend that directly addresses some of the known shortcomings of the indicator, including its unbounded extremes, susceptibility to whipsaw, and lack of insight into other timeframes.
In the canonical WT approach, an exponential moving average (EMA) for a given lookback window is used to assess the variability between price and two other EMAs relative to a second lookback window. Since the difference between the average price and its associated EMA is essentially unbounded, an arbitrary scaling factor of 0.015 is typically applied as a crude form of rescaling but still fails to capture 20-30% of values between the range of -100 to 100. Additionally, the trigger signal for the final EMA (i.e., TCI) crossover-based oscillator is a four-bar simple moving average (SMA), which further contributes to the net lag accumulated by the consecutive EMA calculations in the previous steps.
The core idea behind WT3D is to replace the EMA-based crossover system with modern Digital Signal Processing techniques. By assuming that price action adheres approximately to a Gaussian distribution, it is possible to sidestep the scaling nightmare associated with unbounded price differentials of the original WaveTrend method by focusing instead on the alteration of the underlying Probability Distribution Function (PDF) of the input series. Furthermore, using a signal processing filter such as a Butterworth Filter, we can eliminate the need for consecutive exponential moving averages along with the associated lag they bring.
Ideally, it is convenient to have the resulting probability distribution oscillate between the values of -1 and 1, with the zero line serving as a median. With this objective in mind, it is possible to borrow a common technique from the field of Machine Learning that uses a sigmoid-like activation function to transform our data set of interest. One such function is the hyperbolic tangent function (tanh), which is often used as an activation function in the hidden layers of neural networks due to its unique property of ensuring the values stay between -1 and 1. By taking the first-order derivative of our input series and normalizing it using the quadratic mean, the tanh function performs a high-quality redistribution of the input signal into the desired range of -1 to 1. Finally, using a dual-pole filter such as the Butterworth Filter popularized by John Ehlers, excessive market noise can be filtered out, leaving behind a crisp moving average with minimal lag.
Furthermore, WT3D expands upon the original functionality of WT by providing:
First-class support for multi-timeframe (MTF) analysis
Kernel-based regression for trend reversal confirmation
Various options for signal smoothing and transformation
A unique mode for visualizing an input series as a symmetrical, three-dimensional waveform useful for pattern identification and cycle-related analysis
█ SETTINGS
This is a summary of the settings used in the script listed in roughly the order in which they appear. By default, all default colors are from Google's TensorFlow framework and are considered to be colorblind safe.
Source: The input series. Usually, it is the close or average price, but it can be any series.
Use Mirror: Whether to display a mirror image of the source series; for visualizing the series as a 3D waveform similar to a soundwave.
Use EMA: Whether to use an exponential moving average of the input series.
EMA Length: The length of the exponential moving average.
Use COG: Whether to use the center of gravity of the input series.
COG Length: The length of the center of gravity.
Speed to Emphasize: The target speed to emphasize.
Width: The width of the emphasized line.
Display Kernel Moving Average: Whether to display the kernel moving average of the signal. Like PCA, an unsupervised Machine Learning technique whereby neighboring vectors are projected onto the Principal Component.
Display Kernel Signal: Whether to display the kernel estimator for the emphasized line. Like the Kernel MA, it can show underlying shifts in bias within a more significant trend by the colors reflected on the ribbon itself.
Show Oscillator Lines: Whether to show the oscillator lines.
Offset: The offset of the emphasized oscillator plots.
Fast Length: The length scale factor for the fast oscillator.
Fast Smoothing: The smoothing scale factor for the fast oscillator.
Normal Length: The length scale factor for the normal oscillator.
Normal Smoothing: The smoothing scale factor for the normal frequency.
Slow Length: The length scale factor for the slow oscillator.
Slow Smoothing: The smoothing scale factor for the slow frequency.
Divergence Threshold: The number of bars for the divergence to be considered significant.
Trigger Wave Percent Size: How big the current wave should be relative to the previous wave.
Background Area Transparency Factor: Transparency factor for the background area.
Foreground Area Transparency Factor: Transparency factor for the foreground area.
Background Line Transparency Factor: Transparency factor for the background line.
Foreground Line Transparency Factor: Transparency factor for the foreground line.
Custom Transparency: Transparency of the custom colors.
Total Gradient Steps: The maximum amount of steps supported for a gradient calculation is 256.
Fast Bullish Color: The color of the fast bullish line.
Normal Bullish Color: The color of the normal bullish line.
Slow Bullish Color: The color of the slow bullish line.
Fast Bearish Color: The color of the fast bearish line.
Normal Bearish Color: The color of the normal bearish line.
Slow Bearish Color: The color of the slow bearish line.
Bullish Divergence Signals: The color of the bullish divergence signals.
Bearish Divergence Signals: The color of the bearish divergence signals.
█ ACKNOWLEDGEMENTS
@LazyBear - For authoring the original WaveTrend port on TradingView
@PineCoders - For the beautiful color gradient framework used in this indicator
@veryfid - For the inspiration of using mirrored signals for cycle analysis and using multiple lookback windows as proxies for other timeframes
