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!
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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.
Trend hunter strategy - buy & sellThe indicator combines multiple technical indicators and conditions to generate buy and sell signals.
Here's how the indicator works and how to use it:
Strategy Selection:
The indicator provides a dropdown menu to choose the type of strategy. The available options are "Pullback" and "Simple."
Supertrend Settings:
The Supertrend indicator is used to identify the trend direction.
The indicator takes two input parameters:
ATR Length: Specifies the length of the Average True Range (ATR) used in the Supertrend calculation. The default value is 10.
Factor: Specifies the factor used in the Supertrend calculation. The default value is 3.0.
EMA Settings:
The indicator also includes an Exponential Moving Average (EMA) condition.
You can enable or disable the EMA condition using the "Ema Condition On/Off" checkbox.
If enabled, the indicator calculates an EMA based on the close price.
You can specify the length of the EMA using the "Ema Length" input parameter. The default value is 200.
RSI Settings:
The Relative Strength Index (RSI) indicator is used to generate additional conditions.
You can enable or disable the RSI condition using the "Rsi Condition On/Off" checkbox.
If enabled, the indicator calculates the RSI based on the close price.
You can specify the length of the RSI using the "Rsi Length" input parameter. The default value is 14.
Additionally, you can set the overbought and oversold levels for the RSI using the "RSI BUY Level" and "RSI SELL Level" input parameters, respectively. The default value for both is 50.
Final Conditions:
The indicator combines the Supertrend, EMA, and RSI conditions to generate buy and sell signals.
The specific conditions depend on the chosen strategy:
For the "Simple" strategy, the buy condition is when the Supertrend is in an up trend, not in a previous long position, the RSI is above the overbought level, and the close price is above the EMA.
For the "Pullback" strategy, the buy condition is when there is a cross under of the previous low with the Supertrend, the Supertrend is in an up trend, the RSI is above the overbought level, and the close price is above the EMA.
The sell conditions are the opposite of the respective buy conditions.
Backtest Period:
You can specify the start and end dates for the backtesting using the "Start calculations from" and "End calculations" inputs, respectively. The default start date is "2005-01-01" and the default end date is "2045-03-01." (this is work in progress) Still working on the table part, it is a bit tricky.
Trade Direction:
You can choose the trade direction using the "Trade Direction" input parameter. The available options are "Long," "Short," and "Both."
Depending on the selected trade direction, the indicator will generate signals accordingly.
Visual Display:
The indicator plots the Supertrend line on the price chart.
Buy signals are shown as green labels below the price bars.
Sell signals are shown as red labels above the price bars.
Adjust the input parameters according to your preferences, and then apply the indicator to a chart to see the generated signals. Please note that this indicator should be used for educational purposes only and should be thoroughly tested before using it for real trading.
Volatility-Based Mean Reversion BandsThe Volatility-Based Mean Reversion Bands indicator is a powerful tool designed to identify potential mean reversion trading opportunities based on market volatility. The indicator consists of three lines: the mean line, upper band, and lower band. These bands dynamically adjust based on the average true range (ATR) and act as reference levels for identifying overbought and oversold conditions.
The calculation of the indicator involves several steps. The average true range (ATR) is calculated using a specified lookback period. The ATR measures the market's volatility by considering the range between high and low prices over a given period. The mean line is calculated as a simple moving average (SMA) of the closing prices over the same lookback period. The upper band is derived by adding the product of the ATR and a multiplier to the mean line, while the lower band is derived by subtracting the product of the ATR and the same multiplier from the mean line.
Interpreting the indicator is relatively straightforward. When the price approaches or exceeds the upper band, it suggests that the market is overbought and may be due for a potential reversal to the downside. On the other hand, when the price approaches or falls below the lower band, it indicates that the market is oversold and may be poised for a potential reversal to the upside. Traders can look for opportunities to enter short positions near the upper band and long positions near the lower band, anticipating the price to revert back towards the mean line.
The bar color and background color play a crucial role in visualizing the indicator's signals and market conditions. Lime-colored bars are used when the price is above the upper band, indicating a potential bearish mean reversion signal. Conversely, fuchsia-colored bars are employed when the price is below the lower band, suggesting a potential bullish mean reversion signal. This color scheme helps traders quickly identify the prevailing market condition and potential reversal zones. The background color complements the bar color by providing further context. Lime-colored background indicates a potential bearish condition, while fuchsia-colored background suggests a potential bullish condition. The transparency level of the background color is set to 80% to avoid obscuring the price chart while still providing a visual reference.
To provide additional confirmation for mean reversion setups, the indicator incorporates the option to use the Relative Strength Index (RSI) as a confluence factor. The RSI is a popular momentum oscillator that measures the speed and change of price movements. When enabled, the indicator checks if the RSI is in overbought territory (above 70) or oversold territory (below 30), providing additional confirmation for potential mean reversion setups.
In addition to visual signals, the indicator includes entry arrows above or below the bars to highlight the occurrence of short or long entries. When the price is above the upper band and the confluence condition is met, a fuchsia-colored triangle-up arrow is displayed above the bar, indicating a potential short entry signal. Similarly, when the price is below the lower band and the confluence condition is met, a lime-colored triangle-down arrow is displayed below the bar, indicating a potential long entry signal.
Traders can customize the indicator's parameters according to their trading preferences. The "Lookback Period" determines the number of periods used in calculating the mean line and the average true range (ATR). Adjusting this parameter can affect the sensitivity and responsiveness of the indicator. Smaller values make the indicator more reactive to short-term price movements, while larger values smooth out the indicator and make it less responsive to short-term fluctuations. The "Multiplier" parameter determines the distance between the mean line and the upper/lower bands. Increasing the multiplier widens the bands, indicating a broader range for potential mean reversion opportunities, while decreasing the multiplier narrows the bands, indicating a tighter range for potential mean reversion opportunities.
It's important to note that the Volatility-Based Mean Reversion Bands indicator is not a standalone trading strategy but rather a tool to assist traders in identifying potential mean reversion setups. Traders should consider using additional analysis techniques and risk management strategies to make informed trading decisions. Additionally, the indicator's performance may vary across different market conditions and instruments, so it's advisable to conduct thorough testing and analysis before integrating it into a trading strategy.
3 Fib EMAs To Scalp Them AllThe "3 Fib EMAs To Scalp Them All" was made in order to clear up when we should look for shorts, longs, or walk away. Also it can alert you when a trend starts, or when there is a possible reversal. I use it for scalping/day trading in 5m-1h timeframes.
1. EMAs: By default, the indicator uses Fibonacci numbers (21, 55, 233), but you can change them.
2. Color Changes: The color of the Micro EMA line changes depending on its relation to the Mid and Macro EMAs.
When Micro EMA < Mid < Macro EMA, it turns red, indicating a potential bearish trend - that's when you should look for shorts
When Micro EMA > Mid > Macro EMA, it turns green, indicating a potential bullish trend - that's when you should look for longs
A white Micro EMA is when you need to take some rest, enjoy your coffee, and avoid overtrading.
3. Signals: The indicator provides visual signals in the form of diamonds and crosses and corresponding alert signals.
A red diamond above the bar signals a potential beginning of a downtrend
A red cross above the bar signals the end of the downtrend and can be used as a signal for a possible reversal up/breakout.
A green diamond below the bar signals a potential beginning of a downtrend,
A green cross below the bar signals the end of the uptrend and can be used as a signal for a possible reversal down/breakout.
4. Alerts: For algo traders and people who prefer to stay away from the monitor... there are alerts for every signal.
Friendly note: Don't blindly follow the signals for your long and short entries. The signals only pop up when the EMA cross value gets a confirmation. A smart move would be to wait for a retracement to the EMA line and use momentum indicators like market cipher B to pinpoint those ideal entry points.
tlc with False BreakoutThe strategy aims to identify a trend line channel with the potential for a false breakout. Here's an explanation of the strategy:
The script starts by defining the input parameters. The lookback parameter determines the number of previous bars to consider for detecting the trend lines, and the threshold parameter controls the sensitivity of the trend line detection.
The script then initializes variables to store the trend lines, tap count, and the false breakout signal.
Inside the loop, the script iterates over the specified number of bars (lookback) to identify the trend lines. It checks if the current high is greater than the previous and next highs to identify an upper trend line and sets it using the line.new function. Similarly, it checks if the current low is smaller than the previous and next lows to identify a lower trend line and sets it.
The script also keeps track of the price levels of the upper and lower trend lines using the variables upperTrendLinePrice and lowerTrendLinePrice. These price levels are obtained using the line.get_y1 function.
After the fourth tap (when tapCount is equal to 4), the script checks if the current close price is above the upper trend line or below the lower trend line. If this condition is met, it sets the falseBreakout variable to true, indicating a potential false breakout.
Finally, the script plots a shape marker (plotshape) when a false breakout occurs. This is represented by an orange label displayed below the bar.
At the end of the script, the line.delete function is used to remove the old trend lines when the script reaches the last bar (barstate.islast).
By using this strategy, you can visually identify trend line channels where the upper and lower lines touch higher highs or lower highs and higher lows or lower lows. Additionally, it provides a false breakout signal when the price breaks above the upper trend line or below the lower trend line on the fifth tap.
Super Secret 200 EMAThe indicator is called "Super Secret 200 EMA." It combines two technical indicators, the Supertrend and the 200 Exponential Moving Average (EMA), to generate buy and sell opportunities in a trading chart.
Here's how the indicator works and how you can use it:
Supertrend Calculation:
The Supertrend indicator helps identify the current trend in the market. It uses two parameters: Length and Multiplier.
Length: This parameter determines the number of periods used for the calculation.
Multiplier: It controls the width of the Supertrend line, indicating the level of volatility considered in the calculation.
The Supertrend is calculated by looping through the historical data from length to 1.
For each period, it checks whether the closing price has increased or decreased compared to the previous period.
If the closing price has increased, it updates the highestHigh value with the maximum of the current highest high and the high of the current period.
If the closing price has decreased, it updates the lowestLow value with the minimum of the current lowest low and the low of the current period.
Finally, it calculates the Supertrend value using the following formula:
If the change in the closing price is positive: Supertrend = lowestLow + (multiplier * Average True Range (ATR))
If the change in the closing price is negative: Supertrend = highestHigh - (multiplier * ATR)
The Supertrend line will be green if it is above the 200 EMA line and red if it is below.
200 EMA Calculation:
The 200 EMA is a widely used moving average indicator that gives more weight to recent prices.
The EMA period is set to 200 in this case.
The 200 EMA is calculated using the EMA formula, taking into account the closing prices over the specified period.
Plotting:
The Supertrend and 200 EMA lines are plotted on the chart using the plot function.
The Supertrend line is colored green if it is above the 200 EMA line and red if it is below.
The 200 EMA line is colored green if the closing price is above it and red if it is below.
Buy and Sell Conditions:
The indicator determines the buy and sell conditions based on the crossover and crossunder of the closing price with the 200 EMA line and the Supertrend line.
Buy Condition: A buy signal is generated when the closing price crosses above the 200 EMA line and is also above the Supertrend line.
Sell Condition: A sell signal is generated when the closing price crosses below the 200 EMA line and is also below the Supertrend line.
Plotting Buy and Sell Signals:
You can use this indicator to identify potential buy and sell opportunities in your trading strategy. However, please note that this is a simplified explanation, and it's essential to thoroughly understand the indicator's principles and backtest it with historical data before relying on it for actual trading decisions.
Use this with other confluences for best results and never rely on a single indicator
Liquidity Channel with B/SIndicator - Liquidity Level
Which calculates the liquidity levels based on the highest high and lowest low of the specified period. It determines the middle line, upper line, and lower line of the liquidity channel. The liquidity level is the average of the upper and lower lines, and the liquidity level distance is half of the difference between the upper and lower lines.
Here, the code determines if the conditions for overbought and oversold signals are met. It compares the current closing price with the previous opening price to determine the color of the bar (red or green). If the conditions are met and the bar color matches the expected direction (red for overbought and green for oversold), the respective signals are triggered.
The code plots buy and sell signals on the chart using shape labels. It displays "Buy" labels below the bars for buy signals and "Sell" labels above the bars for sell signals. Additionally, it colors the bars in gray. The code also sets up alert conditions to send notifications when buy or sell signals occur.
*************** Please note that this is a high-level overview of the code's functionality. The specific details and calculations may vary based on the parameters and settings provided in the code.
*************** Remember, trading involves risks, and it's important to thoroughly test any strategy and consider risk management principles before using it in live trading. It's recommended to consult with a knowledgeable financial advisor or professional trader for guidance and assistance in developing and implementing trading strategies.
***************Happy trading..
I will try to share my most commonly used strategies with you as much as possible. For this, you can follow me as a source of motivation, and if you like the indicators, you can give me a rocket to make me happy, my friends! :))
BB and KC StrategyThis script is designed as a TradingView strategy that uses Bollinger Bands (BB) and Keltner Channels (KC) as the primary indicators for generating trade signals. It aims to catch potential market trends by comparing the movements of these two popular volatility measures.
Key aspects of this strategy:
1. **Bollinger Bands and Keltner Channels:** Both are volatility-based indicators. The Bollinger Bands consist of a middle band (simple moving average) and two outer bands calculated based on standard deviation, which adjusts itself to market conditions. Keltner Channels are a set of bands placed above and below an exponential moving average of the price. The distance between the bands is calculated based on the Average True Range (ATR), a measure of price volatility.
2. **Entry Signals:** The strategy enters a long position when the upper KC line crosses above the upper BB line and the volume is above its moving average. Conversely, it enters a short position when the lower KC line crosses below the lower BB line and the volume is above its moving average.
3. **Exit Signals:** The strategy exits a position under two conditions. First, if the trade has been open for a certain number of bars defined by the user (default 20 bars). Second, a stop loss and trailing stop are in place to limit potential losses and lock in profits as the price moves favorably. The stop loss is set at a percentage of the entry price (default 1.5% for long and -1.5% for short), and the trailing stop is also a percentage of the entry price (default 2%).
4. **Trade Quantity:** The script allows specifying the investment amount for each trade, set to a default of 1000 currency units.
Remember, this is a strategy script, which means it is used for backtesting and not for real-time signals or live trading. It is also recommended that it is used as a tool to aid your trading, not as a standalone system. As with any strategy, it should be tested over different market conditions and used in conjunction with other aspects of technical and fundamental analysis to ensure robustness and effectiveness.
AggBands (v1) [qrsq]The "AggBands" indicator is a custom trading indicator designed to provide a consolidated view of the price action across multiple assets or trading pairs. It combines the price data from multiple tickers and calculates an aggregated price using user-defined weights for each ticker.
The indicator starts by defining the tickers to be included in the aggregation. You can choose from predefined configurations such as "BTC PAIRS," "CRYPTO TOTAL MARKET CAP," "TOP 5 PAIRS," "TOP 5 MEMECOINS," "SPX," "DXY," or "FANG." Each configuration includes specific tickers or indices relevant to the chosen category.
The indicator then fetches the closing, high, and low prices for each ticker and applies the user-defined weights to calculate the aggregated prices. The aggregated prices are normalized within a specified length to provide a consistent scale across different assets or pairs.
Next, the indicator calculates the midpoint, which is the average of the highest high and lowest low of the aggregated prices over a specified aggregation period.
To assess the volatility, the indicator calculates the price range and applies the Average True Range (ATR) indicator to determine the volatility value. The standard deviation is then computed using the price range and aggregation period, with an additional scaling factor applied to the volatility value.
Based on the standard deviation, the indicator generates multiple bands above and below the midpoint. By default, three standard deviation bands are calculated, but the user can choose between one and five bands. The upper and lower bands are smoothed using various moving average (MA) types, such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA/RMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Volume Weighted Average Price (VWAP), or Arnaud Legoux Moving Average (ALMA). The user can also adjust the length, offset, and sigma parameters for the moving averages.
The indicator can optionally smooth the midpoint, upper bands, and lower bands using a separate set of moving average parameters.
The indicator can be useful for traders and analysts who want to gain a consolidated view of price movements across multiple assets or trading pairs. It helps identify trends, volatility, and potential support and resistance levels based on the aggregated price and standard deviation bands. Traders can use this information to make informed decisions about trading strategies, risk management, and market analysis.
