Simple Grid Lines VisualizerAbout Grid Bots
A grid bot is a type of trading bot or algorithm that is designed to automatically execute trades within a predefined price range or grid. It is commonly used in markets that exhibit ranging or sideways movement, where prices tend to fluctuate within a specific range without a clear trend.
The grid bot strategy involves placing a series of buy and sell orders at regular intervals within the predefined price range or grid. The bot essentially creates a grid of orders, hence the name. When the price reaches one of these levels, the bot will execute the corresponding trade. For example, if the price reaches a predefined lower level, the bot will buy, and if it reaches a predefined upper level, it will sell.
The purpose of the grid bot strategy is to take advantage of the price oscillations within the range. As the price moves up and down, the bot aims to generate profits by buying at the lower end of the range and selling at the higher end. By repeatedly buying and selling at these predetermined levels, the bot attempts to capture gains from the price fluctuations.
About this Script
Simple Grid Lines Visualizer is designed to assist traders in visualizing and implementing automated price grids on their charts. With just a few inputs, this script generates gridlines based on your specified top price, bottom price, and the number of grids or profit per grid.
How it Works:
Specify Top and Bottom Prices: Start by setting the top and bottom prices that define the range within which the gridlines will be generated. These prices can be based on support and resistance levels, historical data, or any other factors you consider relevant to your analysis.
Determine Grid Parameters: Choose either the number of grids or profit per grid, depending on your preference and trading strategy. If you select the number of grids, the script will evenly distribute the gridlines within the specified price range. Alternatively, if you opt for profit per grid, the script will calculate the price increment required to achieve your desired profit level per grid.
Note that when choosing Profit per Grid , an approximation usually is performed, as all grid lines must be evenly distributed. To achieve that, the script computes the grid distance using the mean price between top and bottom, then computes how many of those complete distances may enter the entire range, and lastly, creates a grid with evenly distributed distances as close as possible to the previously computed.
Customize Styling and Display: Adjust the line color, line style, transparency, and other visual aspects to ensure clear visibility on your charts.
Analyze and Trade: Once the gridlines are plotted on your chart, carefully observe how the market interacts with them. The gridlines can act as reference points for potential support and resistance levels, as well as simple buy/sell orders for a trading bot.
Try to find gridlines that intersect prices as frequently as possible from one to another.
A grid with too many lines will make lots of potential trades, but the amount traded will be minimal (as the total amount invested is divided over the number of grids).
A grid with too few lines will make lots of profits with each trade, but the trades will be less likely to occur (depending on the top/bottom distance).
This tool aims to help visually which grid parameters seem to optimize this problem.
Future versions may include automatic profit computation.
Полосы и каналы
Dynamic Trend RipperThe "Dynamic Trend Ripper" indicator is designed to identify dynamic support and resistance levels based on exponential moving averages (EMA) and the average true range (ATR). It aims to assist traders in identifying potential trading opportunities by visualizing dynamic support and resistance areas on the price chart. Think of it as more of overbought or oversold areas then true support and resistance,
The indicator calculates two sets of EMAs: two for the top cloud and two for the bottom cloud. The lengths of these EMAs are determined by user-defined input parameters. Additionally, the indicator uses the ATR to adjust the EMAs, enhancing their effectiveness as dynamic support and resistance levels.
The top cloud is formed by adding the ATR to the top fast EMA and subtracting the ATR from the top slow EMA. The bottom cloud is formed by subtracting the ATR from the bottom fast EMA and adding the ATR to the bottom slow EMA.
The indicator plots the dynamic OB (Overbought) level, which is the top fast EMA plus the ATR multiplied by the OBOS multiplier. It also plots the dynamic OS (Oversold) level, which is the top slow EMA minus the ATR multiplied by the OBOS multiplier. These levels are visualized using colored lines on the chart.
The top fast EMA, top slow EMA, bottom fast EMA, and bottom slow EMA are also plotted on the chart. The area between the top slow EMA and top fast EMA is filled with a color, forming the top cloud. The area between the bottom fast EMA and bottom slow EMA is filled with another color, forming the bottom cloud. The color of the clouds changes based on the relationship between the top fast EMA and top slow EMA. If the Regular Fast EMA is greater than the Regular slow EMA, indicating a bullish trend, the clouds are displayed in green. Otherwise, if the top fast EMA is less than the top slow EMA, indicating a bearish trend, the clouds are displayed in red.
The indicator can be used to identify potential support and resistance zones where the price may encounter obstacles or reverse its direction. Traders can look for price interactions with the dynamic support and resistance levels, as well as the OB and OS levels, to make trading decisions. For example, a trader might consider entering a short trade when the price approaches the top cloud, or a long trade when the price bounces off the bottom cloud.
By incorporating the ATR, which measures volatility, the indicator adjusts the EMAs to adapt to changing market conditions. Traders can watch for price reactions or reversals near these levels to gauge potential overextension or exhaustion in the price movement. I'm not going to claim this as my own idea, but I will say that I came up with this version myself. I haven't seen anyone else take this approach which is why I think it can be revolutionary to trading.
EXTREME OVERBOUGHT/SOLD BANDS
ATR-ADJUSTED EMA'S
Powertrend - Volume Range Filter Strategy [wbburgin]The Powertrend is a range filter that is based off of volume, instead of price. This helps the range filter capture trends more accurately than a price-based range filter, because the range filter will update itself from changes in volume instead of changes in price. In certain scenarios this means that the Powertrend will be more profitable than a normal range filter.
Essentials of the Strategy
This is a breakout strategy which works best on trending assets with high volume and liquidity. It should be used on middle to higher timeframes and can be used on all assets that have volume provided by the data source (stocks, crypto, forex). It is long-only as of now. It can work on lower timeframes if you optimize the strategy filters to make less trades or if your exchange/broker is low/no fees, provided that your exchange/broker has high liquidity and volume.
The strategy enters a long position if the range filter is trending upwards and the price crosses over the upper range band, which signifies a price-volume breakout. The strategy closes the long position if the range filter is trending downwards and the price crosses under the lower range band, which signifies a breakdown. Both these conditions can be altered by the three filter options in the settings. The default trend filter is not alterable because it helps prevent false entries and exits that are against the trend.
Settings
The Length setting is the lookback period for the range smoothing.
The ADX Filter setting enables you to turn on an ADX filter, which will halt entries and exits unless the ADX of your customizable length is above a ADX VWMA of that length.
The Range Supertrend setting creates a supertrend from the top and bottom ranges, which can be used to filter entries and exits. The length is customizable. The filter can show you whether the range is making higher highs and lower lows. Below is an example of the Range Supertrend being used as a filter and plotted on-chart:
The VWMA setting halts entries if they are below a customizable length VWMA.
Both the Range Supertrend and the VWMA can also be plotted separately without actually filtering the strategy, so that you can use them independently if you wish. You can turn off the bar color, the highlighting, and the labels if you wish in the settings. A note about the bar color: if the color changes but the strategy does not signal an exit or entry this means that the crossover was against the trend. In these circumstances it may be indicative of a pullback to enter or exit or to add onto your position.
About the Strategy Results Below
A range filter is normally composed of two components - the range filter itself and a smoothing function. In the development of this script I tested both normal and volume-based varieties of the range filter and the smoothing function:
Tests Performed
Volume-based Range x VWMA smoothing
Price-based Range x VWMA smoothing
Price-based Range x EMA smoothing
Volume-based Range x EMA smoothing (final result)
The highest-performing was a volume-based range filter and a normal EMA-based smoothing function, but that does not mean that this strategy will be profitable - exits are based off of signal reversion so I strongly encourage you to develop your own take profits/stop losses for the strategy if you think it may be a good fit for you. The results below are with a commission value of 0.05% (because I built the strategy first for equities), slippage of 3, so if your exchange/broker has a higher fee schedule, I recommend adding filters and/or moving to higher timeframes for the strategy. Additionally, I used 10% of equity in each trade, while using the Range Supertrend filter (the previous upload was unrealistic because it used 100% of equity - missed a 0, apologies, and added in slippage).
Fibonacci Trend Zone The "Fibonacci Trend Zone" indicator is a supplementary tool that helps identify the current trend based on Fibonacci zones. It utilizes Fibonacci levels (0.62, 0.705, and 0.79) to define long-term trend zones. The green zone indicates potential long trades, while the red zone suggests potential short trades. The indicator also includes the Triple Exponential Moving Average (TEMA), which helps confirm trend reversals. When the TEMA crosses the Fibonacci level of 0.5, it may signal a possible trend reversal. Use this indicator in conjunction with your primary trading strategy to make more informed trading decisions. Additionally, the indicator provides flexibility in customizing the styles, allowing you to change the color scheme or disable the display of certain elements to suit your preferences and requirements.
Индикатор "Fibonacci Trend Zone" является вспомогательным инструментом, который помогает определить текущий тренд на основе зон фибоначчи. Он использует уровни фибоначчи (0,62, 0,705 и 0,79) для определения зон долгосрочного тренда. Зеленая зона указывает на возможность лонг-сделок, а красная зона - на возможность шорт-сделок. Индикатор также включает Triple Exponential Moving Average (TEMA), который помогает подтвердить смену тренда. Когда TEMA пересекает уровень фибоначчи 0,5, это может сигнализировать о возможной смене тренда. Используйте данный индикатор в сочетании с вашей основной торговой стратегией для принятия более информированных решений. Индикатор также предоставляет гибкость в настройке стилей, позволяя вам изменить цветовую схему или отключить отображение некоторых элементов, чтобы соответствовать вашим предпочтениям и требованиям.
Anchored VWAP (Auto High & Low)OVERVIEW
This script plots, and auto-updates, 3 separate VWAPs: a traditional VWAP, a VWAP anchored to a trends high, and another anchored to a trends low.
VWAP and Anchored VWAPs are commonly used by institutions responsible for the majority of market volume on a given day. Citadel Trading, for example, accounts for approximately 35% of all U.S. listed retail volume , largely executed through program trades over the course of a day, week, or month.
Because VWAP is a prominent market maker tool for executing large trades, day traders can use it to better anticipate trends, mean reversion, and breakouts.
This is most useful on charts with intraday time frames (1 minute, 5 minute etc.) commonly used for day trading. This is not ideal for larger time frames (1 hour or greater) commonly used for swing trading or identifying larger trends.
INPUTS
You can configure:
The size, color, and visibility of 6 different plots (VWAP, High Anchor, Low Anchor, Average of Anchors, Quarter Values, Interim Bands)
How smooth the average displays
INSPIRATION
1. "How To Measure Anything" by Douglas W. Hubbard
2. "Maximum Trading Gains With Anchored VWAP" by Brian Shannon
Better understanding probability and how to analyze risk (first book), as well as the tools market makers use (second book), has completely reframed how I approach day trading.
Trend Channels With Liquidity Breaks [ChartPrime]Trend Channels
This simple trading indicator is designed to quickly identify and visualize support and resistance channels in any market. The primary purpose of the Trend Channels with Liquidity Breaks indicator is to recognize and visualize the dominant trend in a more intuitive and user-friendly manner.
Main Features
Automatically identifies and plots channels based on pivot highs and lows
Option to extend the channel lines
Display breaks of the channels where liquidity is deemed high
Inclusion of volume data within the channel bands (optional)
Market-friendly and customizable colors and settings for easy visual identification
Settings
Length: Adjust the length and lookback of the channels
Show Last Channel: Only shows the last channel
Volume BG: Shade the zones according to the volume detected
How to Interpret
Trend Channels with Liquidity Breaks indicator uses a combination of pivot highs and pivot lows to create support and resistance zones, helping traders to identify potential breakouts, reversals or continuations of a trend.
These support and resistance zones are visualized as upper and lower channel lines, with a dashed center line representing the midpoint of the channel. The indicator also allows you to see the volume data within the channel bands if you choose to enable this functionality. High volume zones can potentially signal strong buying or selling pressure, which may lead to potential breakouts or trend confirmations.
To make the channels more market-friendly and visually appealing, Trend Channels indicator also offers customizable colors for upper and lower lines, as well as the possibility to extend the line lengths for further analysis.
The indicator displays breaks of key levels in the market with higher volume.
Smart Trend EnvelopeThe "Smart Trend Envelope" indicator is a powerful tool that combines the "Nadaraya-Watson Envelope " indicator by LuxAlgo and the "Strongest Trendline" indicator by Julien_Eche.
This indicator provides valuable insights into price trends and projection confidence levels in financial markets. However, it's important to note that the indicator may repaint, meaning that the displayed results can change after the fact.
The "Strongest Trendline" indicator by Julien_Eche focuses on identifying the strongest trendlines using logarithmic transformations of price data. It calculates the slope, average, and intercept of each trendline over user-defined lengths. The indicator also provides standard deviation, Pearson's R correlation coefficient, and upper/lower deviation values to assess the strength and reliability of the trendlines.
In addition, the "Nadaraya-Watson Envelope " indicator developed by LuxAlgo utilizes the Nadaraya-Watson kernel regression technique. It applies a kernel function to smooth the price data and estimate future price movements. The indicator allows adjustment of the bandwidth parameter and multiplier to control the width of the envelope lines around the smoothed line.
Combining these two indicators, the "Smart Trend Envelope" indicator offers traders and investors a comprehensive analysis of price trends and projection confidence levels. It automatically selects the strongest trendline length based on the highest Pearson's R correlation coefficient. Traders can observe the trendlines on the price chart, along with upper and lower envelope lines generated by the Nadaraya-Watson smoothing technique.
The "Smart Trend Envelope" indicator has several qualities that make it a valuable tool for technical analysis:
1. Automatic Length Selection: The indicator dynamically selects the optimal trendline length based on the highest Pearson's R correlation coefficient, ensuring accurate trend analysis.
2. Projection Confidence Level: The indicator provides a projection confidence level ranging from "Ultra Weak" to "Ultra Strong." This allows traders to assess the reliability of the projected trend and make informed trading decisions.
3. Color-Coded Visualization: The indicator uses color schemes, such as teal and red, to highlight the direction of the trend and the corresponding envelope lines. This visual representation makes it easier to interpret the market trends at a glance.
4. Customizable Settings: Traders can adjust parameters such as bandwidth, multiplier, line color, and line width to tailor the indicator to their specific trading strategies and preferences.
The "Smart Trend Envelope" indicator has been specifically designed and coded to be used in logarithmic scale. It takes advantage of the logarithmic scale's ability to represent exponential price movements accurately. Therefore, it is highly recommended to use this indicator with the chart set to logarithmic scale for optimal performance and reliable trend analysis, especially on higher timeframes.
It's important to remember that the "Smart Trend Envelope" indicator may repaint, meaning that the displayed results can change after the fact. Traders should use this indicator as a tool for generating trade ideas and confirmation, rather than relying solely on its historical values. Combining the indicator with other technical analysis tools and considering fundamental factors can lead to more robust trading strategies.
EFFR Range VisualizerThis script takes the upper and lower target Effective Fed Funds Rate subtracted from 100 to allow the user to quickly visualize how these relate to STIR and Treasury markets.
QuantumBands - Tutor Metatrader🚀 QuantumBands - Tutor Metatrader 🚀
📖 Description:
QuantumBands is a powerful technical indicator designed to enhance your trading analysis. It combines the popular Bollinger Bands with a unique twist, providing you with valuable insights into market dynamics. This indicator is presented by the Tutor Metatrader channel, offering expert guidance and education on using the indicator effectively.
🔍 How it Works:
QuantumBands calculates the Bollinger Bands based on a defined period and multiplier. The indicator plots the middle band (basis), the upper band, and the lower band on your chart, visualizing potential price volatility and areas of support and resistance. Additionally, it generates buy and sell signals when the price crosses the bands, helping you identify potential entry and exit points in your trading strategy.
🎯 Key Features:
- Customizable period and multiplier for the Bollinger Bands.
- Clear visual representation of the bands for easy analysis.
- Buy and sell signals for potential trading opportunities.
- Backed by the expertise of Tutor Metatrader channel.
📚 How to Use:
1. Set the desired period and multiplier for the Bollinger Bands.
2. Look for price action near the bands and monitor for potential reversals or breakouts.
3. Pay attention to buy and sell signals generated when the price crosses the bands.
4. Consider additional factors and perform proper risk management before executing trades.
⚠️ Disclaimer: Trading involves risk, and this indicator should be used as a tool to support your analysis. Always perform your due diligence and combine the indicator with other technical and fundamental analysis methods.
🌟 Enjoy using QuantumBands for your trading analysis, and remember to check out the Tutor Metatrader channel for expert guidance and educational content!
💡 Share your feedback and trading experiences with QuantumBands - Tutor Metatrader in the comments below. Happy trading!
VOLD Ratio (Volume Difference Ratio) by TenozenAnother helpful indicator is here! VOLD Ratio is calculated by the net volume of a buying candle, divided by the net volume of a sell candle.
Formula:
buying net volume/selling net volume
It's a simple indicator, but don't underestimate this simplicity. It's a powerful indicator that would help you to decide whether the volume is getting interested in the direction that the market would take. So assume when the market is above the Bollinger Bands, it means that the volume is at a buying extreme, by that, we could expect the market to get back towards the mean, as there is a lot of buying demand that entered the market. How about below the Bollinger Bands? it means that the volume is at a selling extreme, we could expect that there is a lot of volume getting in toward the sellers, so we could take advantage of the opportunity to go for a long. Lastly, the Bollinger Bands would help you guys to determine the liquidity of the market, if the Bollinger Bands get smaller over time, it means there is no interest for the market to enter yet, and if the Bollinger Bands get bigger over time, it means there is interest for the market to enter in the session.
Tips & Reminder:
- We shouldn't use this indicator by itself, make sure to use an Indicator that would help you guys to determine the momentum and the liquidity of the market.
- The higher the timeframe, the slower this indicator would signal an entry, by that use a smaller timeframe... I suggest using a 15M chart for the execution.
- Always trade in the medium-longterm direction if you want to have a high probability trade.
- Be patient in your execution, it's more likely the market would go higher or lower after going in the extreme of the Bollinger Bands.
Well, that's it! Hope you guys enjoy using this indicator, let me know if there is any question or suggestion. Ciao...
Smoother Momentum Stops [Loxx]Smoother Momentum Stops (SMS) is a dynamic tool that combines the logic of momentum and moving averages to create an overlay of the market price and generate potential trade signals. The original idea for this indicator comes from the beloved and esteemed trading indicator guru Mladen Rakic.
Understanding the Framework
The SMS incorporates various aspects of technical analysis, including momentum calculation, several types of moving averages, and an intelligent stop-and-reverse system that determines when to enter and exit trades.
The indicator initiates by defining the color scheme for visualization, specifically green for bullish trends and red for bearish trends. It further utilizes the 'smmom' and 'fema' functions to calculate smoothed momentum and fast exponential moving averages, respectively. The values computed by these functions are central to the signal generation process.
Momentum Calculation
The 'smmom' function serves to calculate a smoother momentum by taking a source (such as the closing price) and a period as inputs. This function employs a complex algorithm involving exponential moving averages (EMA), wherein two EMAs are calculated with different smoothing factors, and the difference between the two results is returned as the output. This smooth momentum calculation assists in eliminating unnecessary noise from the market and delivers more reliable momentum readings.
Moving Averages Computation
One key feature of the SMS is the ability to select from five different moving average types: Exponential Moving Average (EMA), Fast Exponential Moving Average (FEMA), Linear Weighted Moving Average (LWMA), Simple Moving Average (SMA), and Smoothed Moving Average (SMMA). The 'variant' function assigns the chosen method to the '_avg' variable, which is then used in the trade signal logic.
Trade Signal Generation
SMS employs a complex yet robust mechanism for generating trade signals. A stop-and-reverse system is established, which works on the principle of momentum. If the smoothed momentum is positive, an upper stop is determined and if the momentum is negative, a lower stop is defined.
The process continues by defining long and short entry conditions. The indicator goes long when an upper stop exists, and the previous bar had a lower stop, signifying a shift in momentum. The short entry condition is the opposite: the indicator goes short when a lower stop exists, and the previous bar had an upper stop. Alerts are generated for each of these conditions, helping traders to take timely action.
Visual Representation and UI Options
In terms of visual representation, the indicator plots upper and lower stops, employing green color for upper and red for lower stops. If the option to color bars is chosen, the entire bar is colored green or red, based on whether an upper or lower stop exists. This feature allows traders to visually comprehend market conditions better. Support and reisstance levels are also provided for visual context.
Conclusion
The Smoother Momentum Stops indicator is a potent tool for traders seeking to optimize their trading strategies. It blends the fundamentals of momentum and moving averages, resulting in a robust system that provides clear, reliable, and timely trading signals. By adjusting the smoothing type and period parameters, traders can customize the indicator to fit various market conditions and asset types, thereby adding a layer of flexibility to their trading strategies.
The use of a stop-and-reverse system adds a layer of risk management by offering precise entry and exit points based on momentum shifts. These stops are not just mere levels of entries or exits, but they reflect the undercurrent of the market's momentum, thus providing a dynamic framework to make informed trading decisions.
Additionally, the SMS indicator offers visual simplicity. The color-coded bars and distinct symbols for long and short positions make it easier for traders to interpret the signals and market direction quickly. Combined with the alert system, it ensures that traders never miss an important trading opportunity.
Finally, the power of the SMS indicator lies in its adaptability and comprehensive approach. By providing a selection of moving averages and an intelligent momentum-based system, it encapsulates various aspects of market behavior. As such, it is a useful tool not just for momentum traders, but for any trader who understands the significance of moving averages and momentum in predicting market movements.
In conclusion, the Smoother Momentum Stops indicator stands as an innovative, adaptable, and powerful tool for the modern trader. Its blend of flexibility, dynamic risk management, and straightforward visualization offer a comprehensive solution for traders looking to navigate the complex world of financial markets. With a detailed understanding of its workings as presented in this essay, traders can harness its full potential to optimize their strategies, manage risk, and achieve their trading objectives.
Nexus Blast Trading Strategy [Kaspricci]Nexus Blast Trading Strategy - Kaspricci
This indicator shows the different sessions during the day (London session, New York AM session, New York PM session and Asian session) by adding vertical lines and draws horizontal lines for the high and low during each session. Furthermore those lines turn red once the price has taken this high or low. Blue lines indicate liquidity not yet taken.
On top the indicator draws boxes of different color to indicate bullish and bearish Fair Value Gaps (FVG).
Happy to receive your feedback. Please leave a comment for bugs as well as ideas for improvement.
General Settings
Time Zone - used for marking sessions and end of day.
Sessions
Sessions - start and end time for each session based on set time zone
Number of Days back - for how many days in the past the startegy will draw strategy highs and lows. Theres is a maximum of 50 days defined.
FVG Settings
Threshold in Ticks - you can hide very small FVGs by increasing this threshold
FVG Colors - colors used for the bearish and bullish FVG box
This script is for educational purposes only! It is not meant to be a financial advice.
PS: The former strategy script was removed by TV, as it would violate several rules according to them.
Machine Learning : Torben's Moving Median KNN BandsWhat is Median Filtering ?
Median filtering is a non-linear digital filtering technique, often used to remove noise from an image or signal. Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image). Median filtering is very widely used in digital image processing because, under certain conditions, it preserves edges while removing noise (but see the discussion below), also having applications in signal processing.
The main idea of the median filter is to run through the signal entry by entry, replacing each entry with the median of neighboring entries. The pattern of neighbors is called the "window", which slides, entry by entry, over the entire signal. For one-dimensional signals, the most obvious window is just the first few preceding and following entries, whereas for two-dimensional (or higher-dimensional) data the window must include all entries within a given radius or ellipsoidal region (i.e. the median filter is not a separable filter).
The median filter works by taking the median of all the pixels in a neighborhood around the current pixel. The median is the middle value in a sorted list of numbers. This means that the median filter is not sensitive to the order of the pixels in the neighborhood, and it is not affected by outliers (very high or very low values).
The median filter is a very effective way to remove noise from images. It can remove both salt and pepper noise (random white and black pixels) and Gaussian noise (randomly distributed pixels with a Gaussian distribution). The median filter is also very good at preserving edges, which is why it is often used as a pre-processing step for edge detection.
However, the median filter can also blur images. This is because the median filter replaces each pixel with the value of the median of its neighbors. This can cause the edges of objects in the image to be smoothed out. The amount of blurring depends on the size of the window used by the median filter. A larger window will blur more than a smaller window.
The median filter is a very versatile tool that can be used for a variety of tasks in image processing. It is a good choice for removing noise and preserving edges, but it can also blur images. The best way to use the median filter is to experiment with different window sizes to find the setting that produces the desired results.
What is this Indicator ?
K-nearest neighbors (KNN) is a simple, non-parametric machine learning algorithm that can be used for both classification and regression tasks. The basic idea behind KNN is to find the K most similar data points to a new data point and then use the labels of those K data points to predict the label of the new data point.
Torben's moving median is a variation of the median filter that is used to remove noise from images. The median filter works by replacing each pixel in an image with the median of its neighbors. Torben's moving median works in a similar way, but it also averages the values of the neighbors. This helps to reduce the amount of blurring that can occur with the median filter.
KNN over Torben's moving median is a hybrid algorithm that combines the strengths of both KNN and Torben's moving median. KNN is able to learn the underlying distribution of the data, while Torben's moving median is able to remove noise from the data. This combination can lead to better performance than either algorithm on its own.
To implement KNN over Torben's moving median, we first need to choose a value for K. The value of K controls how many neighbors are used to predict the label of a new data point. A larger value of K will make the algorithm more robust to noise, but it will also make the algorithm less sensitive to local variations in the data.
Once we have chosen a value for K, we need to train the algorithm on a dataset of labeled data points. The training dataset will be used to learn the underlying distribution of the data.
Once the algorithm is trained, we can use it to predict the labels of new data points. To do this, we first need to find the K most similar data points to the new data point. We can then use the labels of those K data points to predict the label of the new data point.
KNN over Torben's moving median is a simple, yet powerful algorithm that can be used for a variety of tasks. It is particularly well-suited for tasks where the data is noisy or where the underlying distribution of the data is unknown.
Here are some of the advantages of using KNN over Torben's moving median:
KNN is able to learn the underlying distribution of the data.
KNN is robust to noise.
KNN is not sensitive to local variations in the data.
Here are some of the disadvantages of using KNN over Torben's moving median:
KNN can be computationally expensive for large datasets.
KNN can be sensitive to the choice of K.
KNN can be slow to train.
Session Tick-BoxThe "Session Tick-Box" is designed to display session-related information on the chart (HIGH/LOW box). Here's a breakdown of its features and functionalities:
Session Settings:
You can specify different sessions such as the Cash Session, Asian Session, European Session, and Offset Session using the input.session() function.
The sat.session_tick() function is used to calculate the low, high, fill color, open bar status, and session open status for each session.
Display Settings:
You have the option to show a new daily session using the separateDays input. The background color for the new session can be customized using the Day_Bg input.
The colorDays input allows you to enable or disable coloring the background based on different days of the week.
You can customize the colors for the Cash, Asian, European, and Offset sessions using the respective color inputs.
Other Features:
The indicator calculates the percentage change between the low and high of each session using the sat.AbsPercentChange() function.
Labels are added to mark the high and low points of the sessions.
A vertical line is drawn between the low and high points of each session using the line.new() function.
The fill() function is used to create a shaded area between the low and high lines of each session.
Overall, the "Session Tick-Box" indicator provides visual representation and analysis of different sessions on the chart, including their respective ranges and percentage changes.
Bollinger Bands Lab - by InFinitoVariation of the Moving Average Lab that includes Bollinger Bands functionality for any manually created Moving Average. It includes:
- Standard Deviations for any MA
- Fixed Symmetrical Deviations for any MA that remain at a constant % away from the MA
- The same Moving Average creation settings from the Moving Average Lab
"The Moving Average Lab allows to create any possible combination of up to 3 given MAs. It is meant to help you find the perfect MA that fits your style, strategy and market type.
This script allows to average, weight, double and triple multiple types and lengths of Moving Averages
Currently supported MA types are:
SMA
EMA
VWMA
WMA
SMMA (RMA)
HMA
LSMA
DEMA
TEMA
Features:
- Double or Triple any type of Moving Average using the same logic used for calculating DEMAs and TEMAs
- Average 2 or 3 different types and lengths of Moving Average
- Weight each MA manually
- Average up to 3 personalized MAs
- Average different Moving Averages with different length each "
The preview screenshot shows:
- The combination of:
- 200 LSMA - Weight: 1
- 200 HMA - Weight: 2
- 200 VWMA - Weight: 1 - Double
- The regular Bollinger Band setting, 2 standard deviations
- Two fixed symmetrical deviations at 15% and 20% away from the XMA
actic-fibbA fibbonacci based bollinger band. Up and down trading arrows are generated based on crossover and crossunder of 200 day vma
Bollinger Bands and SMA Channel Buy and Sell
This Indicator is a combination of a standard BB indicator incorporated with a SSL Channel by ErwinBeckers which is Simple Moving average with a length of set at 10 (Default) and calculates the high and low set for the default 10 to form a Channel.
The Settings for the Bollinger Band is the standard settings on a normal Bollinger Band - Length 20, source close and Standard dev 2
The setting for the SMA is length 10 and the high and low calculated or that length to form a channel.
The SMA Channel gives a green line for the Up channel and the Red line for the down Channel.
The basis of the indicator is that the Candle close above the Basis line of the BB and the SMA green line will give a buy indicator
and the same for Sell indicator the candle close below the basis BB and the SMA line Red will give a Sell indicator.
Please note that this indicator is a mix of 2 basic indicators found in Trading view, giving Buy and Sell indicators to make things easier to not look for this visually.
This code will be open source for anyone to use or back test or use it for whatever they want.
This code is for my own personal trading and cannot be relied upon. This indicator cannot be used and cannot guarantee anything, and caution should always be taken when trading. Use this with other indicators to give certanty.
Again use this for Paper Trading only.
I want to thank TradingView for its platform that facilitates development and learning.
Visible Range Linear Regression Channel [vnhilton](OVERVIEW)
This indicator calculates the linear regression channel for the visible bars shown on the chart instead of the traditional fixed length linear regression channel TradingView provides (and is more accurate I believe). Inspired by TradingView's Linear Regression Channel and Visible Average Price indicator, and the DAS Trader linear regression indicator.
(FEATURES)
- Ability to extend lines to the right
- Show/hide individual lines
- Adjust standard deviation of bands
- Adjust line style and width of basis and band lines
- Change individual line colours and plot fills between the lines
(DIFFERENCES)
If you compare this indicator to TradingView's Linear Regression Channel, you will notice some differences (as of 11th June, 2023). Differences and reasons are:
1) The intercept is wrong. The formula TradingView uses to calculate the intercept includes the addition of the gradient, which I believe is incorrect. Difference #2 is also why the intercept is wrong. This indicator omits that addition. This was verified by comparing the gradient calculated in this indicator with the gradient determined by Excel with the same data.
2) The gradient is "wrong". In quotations as essentially TradingView's code attempts to find the line of best fit, with the y-axis on the most recent bar instead of the oldest bar. This leads to the gradient being the opposite to the gradient found in this indicator, which isn't wrong, but the later formula used to calculate the intercept doesn't take this into account, resulting in an incorrect intercept value. The gradient and intercept values in this indicator matches those found in Excel.
3) Standard deviation bands of both indicators. I believe the code TradingView uses to calculate standard deviation is incorrect (basing this just through visuals). This indicator uses the array.stdev function to find the correct value (verified with Excel numbers).
Stochastic Momentum Channel with Volume Filter [IkkeOmar]A stochastic version of my momentum channel volume filter
The "Stochastic Momentum" indicator combines the concepts of Stochastic and Bollinger Bands to provide insights into price momentum and potential trend reversals. It can be used to identify overbought and oversold conditions, as well as potential bullish and bearish signals.
The indicator calculates a Stochastic RSI using the RSI (Relative Strength Index) of a given price source. It applies smoothing to the Stochastic RSI values using moving averages to generate two lines: the %K line and the %D line. The %K line represents the current momentum, while the %D line represents a filtered version of the momentum.
Additionally, the indicator plots Bollinger Bands around the moving average of the Stochastic RSI. The upper and lower bands represent levels where the price is considered relatively high or low compared to its recent volatility. The distance between the bands reflects the current market volatility.
Here's how the indicator can be interpreted:
Stochastic Momentum (%K and %D lines):
When the %K line crosses above the %D line, it suggests a potential upward move or bullish momentum.
When the %K line crosses below the %D line, it indicates a potential downward move or bearish momentum.
The color of the plot changes based on the relationship between the %K and %D lines. Green indicates %K > %D, while red indicates %K < %D.
Bollinger Bands (Upper and Lower Bands):
When the price crosses above the upper band, it suggests an overbought condition, indicating a potential reversal or pullback.
When the price crosses below the lower band, it suggests an oversold condition, indicating a potential reversal or bounce.
To identify potential upward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses above the lower band, it may signal a potential upward move or bounce.
If the %K line crosses above the %D line while the %K line is below the upper band, it may indicate a potential upward move.
To identify potential downward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses below the upper band, it may signal a potential downward move or pullback.
If the %K line crosses below the %D line while the %K line is above the lower band, it may indicate a potential downward move.
Code explanation
Input Variables:
The input function is used to create customizable input variables that can be adjusted by the user.
smoothK and smoothD are inputs for the smoothing periods of the %K and %D lines, respectively.
lengthRSI represents the length of the RSI calculation.
lengthStoch is the length parameter for the stochastic calculation.
volumeFilterLength determines the length of the volume filter used to filter the RSI.
Source Definition:
The src variable is an input that defines the price source used for the calculations.
By default, the close price is used, but the user can choose a different price source.
RSI Calculation:
The rsi1 variable calculates the RSI using the ta.rsi function.
The RSI is a popular oscillator that measures the strength and speed of price movements.
It is calculated based on the average gain and average loss over a specified period.
In this case, the RSI is calculated using the src price source and the lengthRSI parameter.
Volume Filter:
The code calculates a volume filter to filter the RSI values based on the average volume.
The volumeAvg variable calculates the simple moving average of the volume over a specified period (volumeFilterLength).
The filteredRsi variable stores the RSI values that meet the condition of having a volume greater than or equal to the average volume (volume >= volumeAvg).
Stochastic Calculation:
The k variable calculates the %K line of the Stochastic RSI using the ta.stoch function.
The ta.stoch function takes the filtered RSI values (filteredRsi) as inputs and calculates the %K line based on the length parameter (lengthStoch).
The smoothK parameter is used to smooth the %K line by applying a moving average.
The d variable represents the %D line, which is a smoothed version of the %K line obtained by applying another moving average with a period defined by smoothD.
Momentum Calculation:
The kd variable calculates the average of the %K and %D lines, representing the momentum of the Stochastic RSI.
Bollinger Bands Calculation:
The ma variable calculates the moving average of the momentum values (kd) using the ta.sma function with a period defined by bandLength.
The offs variable calculates the offset by multiplying the standard deviation of the momentum values with a factor of 1.6185.
The up and dn variables represent the upper and lower bands, respectively, by adding and subtracting the offset from the moving average.
The Bollinger Bands provide a measure of volatility and can indicate potential overbought and oversold conditions.
Color Assignments:
The colors for the plot and Bollinger Bands are assigned based on certain conditions.
If the %K line is greater than the %D line, the plotCol variable is set to green. Otherwise, it is set to red.
The upCol and dnCol variables are set to different colors based on whether the fast moving average (fastMA) is above or below the upper and lower bands, respectively.
Plotting:
The Stochastic Momentum (%K) is plotted using the plot function with the assigned color (plotCol).
The upper and lower Bollinger Bands are plotted using the plot function with the respective colors (upCol and dnCol).
The fast moving average (fastMA) is plotted in black color to distinguish it from the bands.
The hline function is used to plot horizontal lines representing the upper and lower bands of the Stochastic Momentum.
The code combines the Stochastic RSI, Bollinger Bands, and color logic to provide visual representations of momentum and potential trend reversals. It allows traders to observe the interaction between the Stochastic Momentum lines, the Bollinger Bands, and price movements, enabling them to make informed trading decisions.
Scalp Tool
This script is primarily intended as a scalping tool.
The theory of the tool is based on the fact that the price always returns to its mean.
Elements used:
1. VWMA as a moving average. VWMA is calculated once based on source close and once based on source open.
2. the bands are not calculated like the Bollinger Band, but only a settlement is calculated for the lower bands based on the Lows and for the upper bands based on the Highs. Thus the bands do not become thicker or thinner, but remain in the same measure to the mean value above or below the price.
3. a volume filter on simple calculation of a MA with deviation. Therefore, it can be identified if a volume breakout has occurred.
4. support and resistance zones which are calculated based on the highs and lows over a certain length.
5. RSI to determine oversold and overbought zones. It also tries to capture the momentum by using a moving average (variable selectable) to filter the signals. The theory is that in an uptrend the RSI does not go below 50 and in a downtrend it does not go above 50.
However, this can be very different depending on the financial instrument.
Explanation of the signals:
The main signal in this indicator Serves for pure short-term trading and is generated purely on the basis of the bands and the RSI.
Only the first bands are taken into account.
Buy signal is generated when the price opens below the lower band 1 and closes above the lower band 1 or the RSI crosses a value of 25 from bottom to top.
Sell signal is generated when the price opens above the Upper Band 1 and closes below the Upper Band 1 or the RSI crosses a value of 75 from top to bottom.
The position should be closed when the price hits the opposite band. Alternatively, it can also be closed at the mean.
Other side signals:
1. breakouts:
The indicator includes 2 support and resistance zones, which differ only in length. For the breakout signals, the short version of the R/S is used. A signal is generated when the price breaks through the zones with increased volume. It is then assumed that the price will continue to follow the breakout.
The values of the S/R are adjustable and marked with "BK".
The value under Threshold 2 defines the volume breakout. 4 is considered as the highest value. The smaller the value, the smaller the volume must be during a breakout.
2. bounce
If the price hits a S/R (here the long variant is used with the designation "Support" or "Resistance") and makes a wick with small volume, the script assumes a bounce and generates a Sell or Buy signal accordingly.
The volume can be defined under "Threshold".
The S/R according to the designation as well.
Combined signals:
If the value of the S/R BK and the S/R is the same and the bounce logic of the S/R BK applies and an RSI signal is also generated, a signal is also plotted.
Here the idea was to get very strong signals for possible swing entries.
4. RSI Signals
The script contains two RSI.
RSI 1:
Bullish signal is generated when the set value is crossed from the bottom to the top.
Bearish signal is generated when the set value is crossed from the top to the bottom.
RSI 2:
Bullish signal is generated when the set value is crossed from the top to the bottom.
Bearish signal is generated when the set value is crossed from bottom to top.
For RSI 2 the theory is taken into account according to the description under Used elements point 5
Optical trend filter:
Also an optical trend filter was generated which fills the bands accordingly.
For this the VWMA is used and the two average values of the band.
Color definition:
Gray = Neutral
Red = Bearish
Green = Bullish
If the mean value is above the VWMA and the mean value based on the closing price is above the mean value based on the open price, the band is colored green. It is a bullish trend
If the mean value is below the VWMA and the mean value based on the closing price is below the mean value based on the open price, the band is colored red.
The band is colored gray if the mean value is correspondingly opposite. A sideways phase is assumed.
The script was developed on the basis of the pair BTCUSD in the 15 minute chart and the settings were defined accordingly on it. The display of S/R for forex pairs does not work correctly and should be hidden. The logic works anyway.
When using the script, all options should first be set accordingly to the asset and tested before trading afterwards. It applies of course also here that there is no 100% guarantee.
Also, a strong breakout leads to false signals and overheating of the indicator.
Multi Bollinger Bands with Over ZoneThis indicator is called "Multi Bollinger Bands with Over Zone". The indicator uses linear regression to calculate the regression line and standard deviation to calculate the upper and lower deviation lines. It also plots filled areas between the deviation lines to highlight overbought and oversold zones.
The indicator has several customizable inputs, including the length of the regression period, depth, and deviations used to calculate the deviation lines.
The regression line is plotted in green color with circle markers. The upper and lower deviation lines are plotted in blue and red colors, respectively. The area between the deviation lines is filled with light blue color for the overbought zone and light pink color for the oversold zone.
This indicator helps traders in identifying trends and potential price reversals. When the price is above the upper deviation line, it indicates a potential overbought zone, while when the price is below the lower deviation line, it indicates a potential oversold zone.
Please note that this indicator is only a tool for analysis and does not provide direct trading signals. It is important to combine this indicator with additional analysis and appropriate trading strategies.
FalconRed VIXThe FalconRed Vix indicator is a trading tool designed to provide insights into the potential price range of the Nifty 50 index in India. It utilizes the IndiaVix value, which represents the annual percentage change of the Nifty 50 price. By analyzing the IndiaVix, the FalconRed Vix indicator helps traders determine the upper and lower price thresholds within which the Nifty 50 could potentially trend over the course of a year.
For example, if the Nifty 50 is currently at 18,500 and the IndiaVix is 10, it suggests that, at the given level of volatility, the Nifty 50 may experience price fluctuations of up to 10% in either direction over the course of a year. Consequently, the price range projected by the FalconRed Vix indicator would be between 16,650 and 20,350.
The indicator further extends its analysis to shorter time frames, including monthly, weekly, daily, hourly, 6-hour, 15-minute, 5-minute, and 1-minute intervals. By considering the Vix level, the FalconRed Vix indicator calculates the respective price ranges for these time frames.
When viewing the indicator on a chart, traders can observe a range band surrounding the current Nifty 50 price. The top line represents the upper threshold of the Nifty 50 price, while the bottom line represents the lower threshold, both based on the Vix level. This range band assists in determining potential selling points for out-of-the-money (OTM) options and aids in identifying entry or exit points for options and futures trading.
Traders can analyze the upper and lower threshold lines by drawing horizontal or trend lines, which can help identify potential breakouts or breakdowns. Furthermore, this analysis can assist in setting target prices and stop losses based on trend analysis.
It is important to note that the FalconRed Vix indicator is not a technical indicator used for determining stock buy or sell signals. Rather, it focuses on defining the potential price range based on the Vix level, which in turn aids in planning trading strategies such as short strangles, iron condors, and others.
Donchian Volatility Indicator - Adaptive Channel WidthThis indicator is designed to help traders assess and analyze market volatility. By calculating the width of the Donchian channels, it provides valuable insights into the range of price movements over a specified period. This indicator helps traders identify periods of high and low volatility, enabling them to make more informed trading decisions.
The indicator is based on the concept of Donchian channels, which consist of the highest high and lowest low over a specified lookback period. The channel width is calculated as the difference between the upper and lower channels. A wider channel indicates higher volatility, suggesting potentially larger price movements and increased trading opportunities. On the other hand, a narrower channel suggests lower volatility, indicating a relatively calmer market environment with potentially fewer trading opportunities.
The adaptive aspect of the indicator refers to its ability to adjust the width of the channels dynamically based on market conditions. The indicator calculates the width of the channels using the Average True Range (ATR) indicator, which measures the average range of price movements over a specified period. By multiplying the ATR value with the user-defined ATR multiplier, the indicator adapts the width of the channels to reflect the current level of volatility. During periods of higher volatility, the channels expand to accommodate larger price movements, providing a broader range for assessing volatility. Conversely, during periods of lower volatility, the channels contract, reflecting the narrower price ranges and signaling a decrease in volatility. This adaptive nature allows traders to have a flexible and responsive measure of volatility, ensuring that the indicator reflects the current market conditions accurately.
To provide further insights, the indicator includes a signal line. The signal line is derived from the channel width and is calculated as a simple moving average over a specified signal period. This signal line acts as a reference level, allowing traders to compare the current channel width with the average width over a given time frame. By assessing whether the current channel width is above or below the signal line, traders can gain additional context on the volatility level in the market.
The colors used in the Donchian Volatility Indicator - Adaptive Channel Width play a vital role in visualizing the volatility levels:
-- Lime Color : When the channel width is above the signal line, it is colored lime. This color signifies that volatility has entered the market, indicating potentially higher price movements and increased trading opportunities. Traders can pay closer attention to the lime-colored channel width as it may suggest favorable conditions for trend-following or breakout trading strategies.
-- Fuchsia Color : When the channel width is below the signal line, it is colored fuchsia. This color represents relatively low volatility, suggesting a calmer market environment with potentially fewer trading opportunities. Traders may consider adjusting their strategies during periods of low volatility, such as employing range-bound or mean-reversion strategies.
-- Aqua Color : The signal line is represented by the aqua color. This color allows traders to easily identify the signal line amidst the channel width. The aqua color provides a visual reference for the average channel width and helps traders assess whether the current width is above or below this average.
The Donchian Volatility Indicator - Adaptive Channel Width has several practical applications for traders:
-- Volatility Assessment : Traders can use this indicator to assess the level of volatility in the market. By observing the width of the Donchian channels and comparing it to the signal line, they can determine whether the current volatility is relatively high or low. This information helps traders set appropriate expectations and adjust their trading strategies accordingly.
-- Breakout Trading : Wide channel widths may indicate an increased likelihood of price breakouts. Traders can use the Donchian Volatility Indicator - Adaptive Channel Width to identify potential breakout opportunities. When the channel width exceeds the signal line, it suggests a higher probability of significant price movements, potentially signaling a breakout. Traders may consider entering trades in the direction of the breakout.
-- Risk Management : The indicator can assist in setting appropriate stop-loss levels based on the current volatility. During periods of high volatility (lime-colored channel width), wider stop-loss orders may be warranted to account for larger price swings. Conversely, during periods of low volatility (fuchsia-colored channel width), narrower stop-loss orders may be appropriate to limit risk in a more range-bound market.
While the Donchian Volatility Indicator - Adaptive Channel Width is a valuable tool, it is important to consider its limitations:
-- Lagging Indicator : The indicator relies on historical price data, making it a lagging indicator. It provides insights based on past price movements and may not capture sudden changes or shifts in volatility. Traders should be aware that the indicator may not generate real-time signals and should be used in conjunction with other indicators and analysis tools.
-- False Signals : Like any technical indicator, the Donchian Volatility Indicator - Adaptive Channel Width is not immune to generating false signals. Traders should exercise caution and use additional analysis to confirm the signals generated by the indicator. Considering the broader market context and employing risk management techniques can help mitigate the impact of false signals.
-- Market Conditions : Market conditions can vary, and volatility levels can differ across different assets and timeframes. Traders should adapt their strategies and consider other market factors when interpreting the signals provided by the indicator. It is crucial to avoid relying solely on the indicator and to incorporate a comprehensive analysis of the market environment.
In conclusion, this indicator is a powerful tool for assessing market volatility. By examining the width of the Donchian channels and comparing it to the signal line, traders can gain insights into the level of volatility and adjust their trading strategies accordingly. The color-coded representation of the channel width and signal line allows for easy visualization and interpretation of the volatility dynamics. Traders should utilize this indicator as part of a broader trading approach, incorporating other technical analysis tools and considering market conditions for a comprehensive assessment of market volatility.
