Machine Learning: Support and Resistance [YinYangAlgorithms]Overview:
Support and Resistance is normally based upon Pivot Points and Highest Highs and Lowest Lows. Many times coders even incorporate Volume, RSI and other factors into the equation. However there may be a downside to doing a pure technical approach based on historical levels. We live in a time where Machine Learning is becoming more and more used; thus we have decided to create a Machine Learning Support and Resistance Projection based Indicator. Rather than using traditional Support and Resistance calculations using historical data, we have taken a rather different approach. This Indicator instead attempts to Predict and Project where Support and Resistance locations will be based on a Machine Learning Model using a form of KNN (k-Nearest Neighbors).
Since this indicator creates a Projection of where it deems Support and Resistance will be, it has the ability to move its Support and Resistance before the price even gets to it if it believes it will surpass its projections. This may create a more accurate placement of Support and Resistance as they’re not based on historical levels.
This Indicator does not Repaint.
How it works:
This Indicator makes its projections based on the source you provide (by default close) of the previous bar and submits the source, RSI and EMA to our Projection Function to get its projection of the current bar.
The Projection function essentially calculates potential movement after finding the differences between the source the MA from the current bar, previous bar and average over the span of Machine Learning Length.
Potential movement is defined as:
Average Difference + Average(Machine Learning Average, Average Last Distance)
Average Difference: (Absolute value of Current Source - Current MA) - (Absolute value of Machine Learning Average - Machine Learning MA)
Average Last Distance: Average(Current Source - Current MA, Previous Source - Previous MA)
It then predicts the next bars directional movement (bullish or bearish bar) using several factors:
Previous Source > Previous MA
Current Source - Current MA > Average Source - Average MA
Current RSI > Previous RSI
Current RSI > 30 and Previous RSI <= 30
Current RSI < 70 and Previous RSI >= 70
This helps us to predict the direction the next bar may move.
We then calculate a multiplier that we apply to our Potential Movement value to get our final result which is our Current Bars Close Projection.
Our multiplier is calculated using:
(Current RSI > 30 and Previous RSI <= 30) OR (Current RSI < 70 and Previous RSI >= 70)
Current Source - Current MA > Previous Source - Previous MA
We then create an array and fill it with the previous X projections (Machine Learning Length) and send it to another function. This function, if told to, will sort the data accordingly and then output the KNN average of the length given.
We calculate and plot various KNN lengths to create different Zones:
Strong Support: Length of 2 but sort the data Ascending (low to high)
Strong Resistance: Length of 2 but sort the data Descending (high to low)
Support: Length of Machine Length Length / 10 or Min of 2 sorted by Ascending
Resistance: Length of Machine Length Length / 10 or Min of 2 sorted by Descending
There are also 4 other plots you may be wondering what they are, there is your AVG, VWMA, Long Term Memory and Current Projection.
By default your Current Projection is disabled in settings but you can enable it if you are curious to see how the projections for each close are calculated. It is, however, not a crucial point of interest (white line).
The average is simply the average value of the Machine Learning Data (purple line).
The VWMA is a VWMA calculation applied to our Data over a length specified in settings (by default 1)(blue line). The VWMA is crucial when combined with the Avg as they can cross over and under each other. These crosses represent potential Bullish and Bearish zones.
Lastly, but certainly not least, we have the Long Term Memory (maroon line). The Long Term Memory can be displayed either as an ‘Average’, ‘Hard Line’ or ‘None’. The Long Term Average is only updated every Machine Learning Length Bar Index’s and is populated with the average of the Machine Learning Data. For Instance, if Machine Learning Length is set to 100, the Long Term Memory is only updated every 100 bars, and since its length is the same as the Machine Learning Length, that means its data is composed of 10,000 bars worth of data. The Long Term Memory may be very beneficial for determining where Support and Resistance lie over the Long Term within a Machine Learning Algorithm. When set to ‘Average’ it plots the connection lines diagonally, and although they may be more visually appealing, they’re less useful when it comes to actually seeing support and resistance as generally speaking, support and resistance lie on the horizontal. When set to ‘Hard Line’ the Long Term Memory is connected with hard lines and holds the price value until the next time it is updated. This makes it much more useful for potentially identifying Support and Resistance.
Tutorial:
Here is an overview of what the Indicator looks like, now let's start to dissect it.
In the example above we can see how all of the lines between the Major Support and Resistance zones may act as BOTH Support and Resistance depending on which side the price is currently on. In the circle on the left, we can see how it can fluctuate between the two. If you look at the circle on the right, we can see how the Average line acts as a strong support before it fails to maintain it. Generally speaking, most Support and Resistance locations may potentially fail to hold after 3 tests, as the Average did in this example.
As you can see, the Support and Resistance doesn’t wait to be tested before adjusting, which is why there are 2 lines which create their zones. The inner line is the Support/Resistance and the outer line is the Strong Support/Resistance. The Yellow Circle shows the inner line was able to calculate the moving resistance correctly and then adjusted accordingly as it was projecting the price to keep increasing. However, if you look at the White Circle, you can see that since there was first a crash, and then parabolic movement, that the inner zone could not move and predict the resistance as well as the outer zone could.
We consider the price to be ‘Overvalued’ when it is above the VWMA (blue line) and ‘Undervalued’ when it is below the VWMA. It is considered ‘fair’ price when it is within the VWMA to Average zone (between the blue and purple lines). If you look at the example above, you’ll notice where the two yellow circles are, it is not only considered ‘Overvalued’, but it then proceeds to ride the inner resistance line upwards. This is common when the market is overly bullish and vice versa when it is bearish. Please keep in mind, although it is common, it doesn’t mean a correction can’t happen.
In this example above we look at the last bull run that may have started due to the halving. This bull run was very bullish as you can see in the example above. The price was constantly sitting within the Resistance Zone and the VWMA that was very close to it was constantly acting as a Support. Naturally, due to the Algorithm used in this Indicator, as the momentum starts to slow down, the VWMA (blue line) will start to space out more and more from the Resistance Zone. This doesn’t mean the momentum is gone, it just means it may be slowing down.
Unfortunately we have to study the Bear Market with a different perspective than the Bull Market. However, there are still some similarities within the two. If you refer to the example above and the previous example, you can clearly see that the Bull Market loves to stay with the Resistance Zone and use the VWMA as a Support. However, the Bear Market does not. This is a normal occurrence, however we can see from the example above you may see a correction / horizontal movement when the Outer Support Line is touched. If you look at all 3 yellow circles, the Outer Support Line was touched, then either a small correction or horizontal consolidation occurred.
We will conclude our Tutorial here, hopefully you’ll be able to benefit from a moving Support and Resistance calculated with Machine Learning that projects its locations, rather than using traditional calculations.
Settings:
Source: This source is the base for all our calculations
Machine Learning Length: How much projection data are we storing and using to make calculations.
Smoothing Length: We need to smooth calculations such as RSI, EMA and VWMA. What length are we smoothing it with?
VWMA ML Projection Length: How far into our Machine Learning data should we average for our VWMA. Please note the 'Smoothing Length' is still applied here after getting the Projection Average.
Long Term Memory: Long term memory has the same storage length but is only updated once per Machine Learning Length. For instance, if Machine Learning Length is 100, it will save the Average of our data once every 100 bars. This means its memory is an average of 10,000 bars of Machine Learning. 'Average' connects its values diagonally whereas 'Hard Line' holds its value until it changes.
Use Average Last Distance In Potential Movement: This can help accuracy but generally also displaces the Support and Resistance by projecting it further.
Show Current Projection: Projections occur for each bar, and our Machine Learning utilizes these projections by storing and evaluating them. This toggle will display the Current Projection Line which is used to create all our Projections.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Forecasting
ZWAP (ZigZag Anchored VWAP) [Kioseff Trading]Hello!
Quick script showcasing the new polyline function for Pine Script!
Features
Up to 100 high/low pivot points auto anchored VWAP
Visible range auto anchored VWAP
Curved ZigZag (Adjustable!)
With the new polyline function, auto-anchored VWAP at specific price points is more viable.
When using line.new() only 500 lines can exist on the chart concurrently and, since VWAP is calculated on every update, a "proper" VWAP drawn using line.new() can extend 500 bars at most, to which no additional VWAP lines can be drawn after.
Of course, when using the plot() function a VWAP line will draw on every bar; however, this method isn't highly compatible with auto-anchoring VWAP lines.
However!
A polyline, from beginning to end irrespective of the number of coordinates used, constitutes 1 polyline; 100 can exist simultaneously with 10,000 xy coordinates per line.
The image above shows an attempt to draw the same auto-anchored VWAP lines using the line.new() function. Not an ideal outcome!
The image above shows the same attempt using the polyline.new() function!
Very nice (:
The image above shows the indicator auto anchoring to zig zag turning points.
Subsequent to a new anchoring, VWAP is calculated for the following bars - up to the current bar.
Thank you for checking this out; if you have any ideas to spice it up feel free to comment!
IU Probability CalculatorHow This Script Works:
1. This script calculate the probability of price reaching a user-defined price level within one candle with the help Normal Distribution Probability Table.
2. Normal Distribution Probability Table is use for calculating probability of events, it's very powerful for calculation of probability and this script is fully based on that table.
3. It takes the Average True Range value or Standard Deviation value of past user-defined length bar.
4. After that it take this formula z = ( price_level - close ) / (ATR or Standard Deviation) and return the value for z, for the bearish side it take z = (close - price level) / (ATR or Standard Deviation ) formula.
5. Once we have the z it look into Normal Distribution Probability Table and match the value.
6. Now the value of z is multiple buy 100 in order to make it look in percentage term.
7. After that this script subtract the final value with 100 because probability always comes under 100%
8. finally we plot the probability at the bottom of the chart the red line indicates "The probability of price not reaching that price level", While the green line indicates "Probability of price Reaching that level " .
9. This script will work fine for both of the directions
How This Is Useful For The User:
1. With this script user can know the probability of price reaching the certain level within one candle for both Directions .
2. This is useful while creating options hedging strategies
3. This can be helpful for deciding stop loss level.
4. It's useful for scalpers for managing their traders and it can be use by binary option traders.
Quadratic & Linear Time Series Regression [SS]Hey everyone,
Releasing the Quadratic/Linear Time Series regression indicator.
About the indicator:
Most of you will be familiar with the conventional linear regression trend boxes (see below):
This is an awesome feature in Tradingview and there are quite a few indicators that follow this same principle.
However, because of the exponential and cyclical nature of stocks, linear regression tends to not be the best fit for stock time series data. From my experience, stocks tend to fit better with quadratic (or curvlinear) regression, which there really isn't a lot of resources for.
To put it into perspective, let's take SPX on the 1 month timeframe and plot a linear regression trend from 1930 till now:
You can see that its not really a great fit because of the exponential growth that SPX has endured since the 1930s. However, if we take a quadratic approach to the time series data, this is what we get:
This is a quadratic time series version, extended by up to 3 standard deviations. You can see that it is a bit more fitting.
Quadratic regression can also be helpful for looking at cycle patterns. For example, if we wanted to plot out how the S&P has performed from its COVID crash till now, this is how it would look using a linear regression approach:
But this is how it would look using the quadratic approach:
So which is better?
Both linear regression and quadratic regression are pivotal and important tools for traders. Sometimes, linear regression is more appropriate and others quadratic regression is more appropriate.
In general, if you are long dating your analysis and you want to see the trajectory of a ticker further back (over the course of say, 10 or 15 years), quadratic regression is likely going to be better for most stocks.
If you are looking for short term trades and short term trend assessments, linear regression is going to be the most appropriate.
The indicator will do both and it will fit the linear regression model to the data, which is different from other linreg indicators. Most will only find the start of the strongest trend and draw from there, this will fit the model to whatever period of time you wish, it just may not be that significant.
But, to keep it easy, the indicator will actually tell you which model will work better for the data you are selecting. You can see it in the example in the main chart, and here:
Here we see that the indicator indicates a better fit on the quadratic model.
And SPY during its recent uptrend:
For that, let's take a look at the Quadratic Vs the Linear, to see how they compare:
Quadratic:
Linear:
Functions:
You will see that you have 2 optional tables. The statistics table which shows you:
The R Squared to assess for Variance.
The Correlation to assess for the strength of the trend.
The Confidence interval which is set at a default of 1.96 but can be toggled to adjust for the confidence reading in the settings menu. (The confidence interval gives us a range of values that is likely to contain the true value of the coefficient with a certain level of confidence).
The strongest relationship (quadratic or linear).
Then there is the range table, which shows you the anticipated price ranges based on the distance in standard deviations from the mean.
The range table will also display to you how often a ticker has spent in each corresponding range, whether that be within the anticipated range, within 1 SD, 2 SD or 3 SD.
You can select up to 3 additional standard deviations to plot on the chart and you can manually select the 3 standard deviations you want to plot. Whether that be 1, 2, 3, or 1.5, 2.5 or 3.5, or any combination, you just enter the standard deviations in the settings menu and the indicator will adjust the price targets and plotted bands according to your preferences. It will also count the amount of time the ticker spent in that range based on your own selected standard deviation inputs.
Tips on Use:
This works best on the larger timeframes (1 hour and up), with RTH enabled.
The max lookback is 5,000 candles.
If you want to ascertain a longer term trend (over years to months), its best to adjust your chart timeframe to the weekly and/or monthly perspective.
And that's the indicator! Hopefully you all find it helpful.
Let me know your questions and suggestions below!
Safe trades to all!
ATR Multiples PlottedInspired by @jeffsuntrading and @Fred6724 's ATR% multiple from 50-MA .
There are no catch-all values, however a high of 6 and a low of -4 generally has been valuable to me. I tend to look at the historical highs and lows of the indicator, and adjust the Value High and Value Low accordingly to get an idea when profit-taking may be sensible.
The essence is the difference between price and the selected moving average, measured in ATRs.
50 Point Stop & Take Profit**50 Point Stop & Take Profit**
This custom TradingView indicator is designed for instruments like US30 or any asset following a point system. It assists traders in setting precise stop-loss and take-profit levels based on different risk-reward ratios. It calculates and plots horizontal lines at various price levels above and below your specified entry price, with a 50-point difference between each ratio.
**How It Benefits Your Strategy:**
- Each risk-reward ratio, whether it's 1:1, 2:1, 3:1, and so on, is separated by precisely 50 points. This deliberate spacing is tailored to provide you with clear and consistent reference points for managing trades in instruments using a point-based system.
- The 50-point increments make it easy to adjust your positions, ensuring that your risk and reward levels align with your trading strategy and objectives.
**Usage:**
1. Set your desired entry price using the "Entry Price" input.
2. The indicator is ideally suited for instruments like US30, where each point represents a distinct price movement. It will automatically calculate and plot multiple lines at the following levels, both for Long (L) and Short (S) positions:
- 1:1 Risk-Reward Ratio (±50 points)
- 2:1 Risk-Reward Ratio (±100 points)
- 3:1 Risk-Reward Ratio (±150 points)
- 4:1 Risk-Reward Ratio (±200 points)
- 5:1 Risk-Reward Ratio (±250 points)
- 6:1 Risk-Reward Ratio (±300 points)
- 7:1 Risk-Reward Ratio (±350 points)
- 8:1 Risk-Reward Ratio (±400 points)
- 9:1 Risk-Reward Ratio (±450 points)
- 10:1 Risk-Reward Ratio (±500 points)
**Customization Options:**
- **Alerts:** You can set alerts for each level to receive notifications when the price reaches a specific risk-reward ratio.
- **Color Customization:** Customize the colors of the plotted lines to suit your chart preferences.
- **Toggle Ratios:** Easily toggle on/off different risk-reward ratios to focus on specific levels that align with your trading strategy.
**How to Use:**
- Use the plotted lines as reference points for setting stop-loss and take-profit orders at your preferred risk-reward ratios.
- The blue horizontal line represents your specified entry price.
This indicator simplifies your trading strategy by providing clear visual cues for managing risk and reward levels, with each level thoughtfully spaced 50 points apart to cater to your strategy's precision.
*Note: Always use risk management and proper trade sizing in your trading strategy.*
**Version:** Pine Script version 5
AI Momentum [YinYang]Overview:
AI Momentum is a kernel function based momentum Indicator. It uses Rational Quadratics to help smooth out the Moving Averages, this may give them a more accurate result. This Indicator has 2 main uses, first it displays ‘Zones’ that help you visualize the potential movement areas and when the price is out of bounds (Overvalued or Undervalued). Secondly it creates signals that display the momentum of the current trend.
The Zones are composed of the Highest Highs and Lowest lows turned into a Rational Quadratic over varying lengths. These create our Rational High and Low zones. There is however a second zone. The second zone is composed of the avg of the Inner High and Inner Low zones (yellow line) and the Rational Quadratic of the current Close. This helps to create a second zone that is within the High and Low bounds that may represent momentum changes within these zones. When the Rationalized Close crosses above the High and Low Zone Average it may signify a bullish momentum change and vice versa when it crosses below.
There are 3 different signals created to display momentum:
Bullish and Bearish Momentum. These signals display when there is current bullish or bearish momentum happening within the trend. When the momentum changes there will likely be a lull where there are neither Bullish or Bearish momentum signals. These signals may be useful to help visualize when the momentum has started and stopped for both the bulls and the bears. Bullish Momentum is calculated by checking if the Rational Quadratic Close > Rational Quadratic of the Highest OHLC4 smoothed over a VWMA. The Bearish Momentum is calculated by checking the opposite.
Overly Bullish and Bearish Momentum. These signals occur when the bar has Bullish or Bearish Momentum and also has an Rationalized RSI greater or less than a certain level. Bullish is >= 57 and Bearish is <= 43. There is also the option to ‘Factor Volume’ into these signals. This means, the Overly Bullish and Bearish Signals will only occur when the Rationalized Volume > VWMA Rationalized Volume as well as the previously mentioned factors above. This can be useful for removing ‘clutter’ as volume may dictate when these momentum changes will occur, but it can also remove some of the useful signals and you may miss the swing too if the volume just was low. Overly Bullish and Bearish Momentum may dictate when a momentum change will occur. Remember, they are OVERLY Bullish and Bearish, meaning there is a chance a correction may occur around these signals.
Bull and Bear Crosses. These signals occur when the Rationalized Close crosses the Gaussian Close that is 2 bars back. These signals may show when there is a strong change in momentum, but be careful as more often than not they’re predicting that the momentum may change in the opposite direction.
Tutorial:
As we can see in the example above, generally what happens is we get the regular Bullish or Bearish momentum, followed by the Rationalized Close crossing the Zone average and finally the Overly Bullish or Bearish signals. This is normally the order of operations but isn’t always how it happens as sometimes momentum changes don’t make it that far; also the Rationalized Close and Zone Average don’t follow any of the same math as the Signals which can result in differing appearances. The Bull and Bear Crosses are also quite sporadic in appearance and don’t generally follow any sort of order of operations. However, they may occur as a Predictor between Bullish and Bearish momentum, signifying the beginning of the momentum change.
The Bull and Bear crosses may be a Predictor of momentum change. They generally happen when there is no Bullish or Bearish momentum happening; and this helps to add strength to their prediction. When they occur during momentum (orange circle) there is a less likely chance that it will happen, and may instead signify the exact opposite; it may help predict a large spike in momentum in the direction of the Bullish or Bearish momentum. In the case of the orange circle, there is currently Bearish Momentum and therefore the Bull Cross may help predict a large momentum movement is about to occur in favor of the Bears.
We have disabled signals here to properly display and talk about the zones. As you can see, Rationalizing the Highest Highs and Lowest Lows over 2 different lengths creates inner and outer bounds that help to predict where parabolic movement and momentum may move to. Our Inner and Outer zones are great for seeing potential Support and Resistance locations.
The secondary zone, which can cross over and change from Green to Red is also a very important zone. Let's zoom in and talk about it specifically.
The Middle Zone Crosses may help deduce where parabolic movement and strong momentum changes may occur. Generally what may happen is when the cross occurs, you will see parabolic movement to the High / Low zones. This may be the Inner zone but can sometimes be the outer zone too. The hard part is sometimes it can be a Fakeout, like displayed with the Blue Circle. The Cross doesn’t mean it may move to the opposing side, sometimes it may just be predicting Parabolic movement in a general sense.
When we turn the Momentum Signals back on, we can see where the Fakeout occurred that it not only almost hit the Inner Low Zone but it also exhibited 2 Overly Bearish Signals. Remember, Overly bearish signals mean a momentum change in favor of the Bulls may occur soon and overly Bullish signals mean a momentum change in favor of the Bears may occur soon.
You may be wondering, well what does “may occur soon” mean and how do we tell?
The purpose of the momentum signals is not only to let you know when Momentum has occurred and when it is still prevalent. It also matters A LOT when it has STOPPED!
In this example above, we look at when the Overly Bullish and Bearish Momentum has STOPPED. As you can see, when the Overly Bullish or Bearish Momentum stopped may be a strong predictor of potential momentum change in the opposing direction.
We will conclude our Tutorial here, hopefully this Indicator has been helpful for showing you where momentum is occurring and help predict how far it may move. We have been dabbling with and are planning on releasing a Strategy based on this Indicator shortly.
Settings:
1. Momentum:
Show Signals: Sometimes it can be difficult to visualize the zones with signals enabled.
Factor Volume: Factor Volume only applies to Overly Bullish and Bearish Signals. It's when the Volume is > VWMA Volume over the Smoothing Length.
Zone Inside Length: The Zone Inside is the Inner zone of the High and Low. This is the length used to create it.
Zone Outside Length: The Zone Outside is the Outer zone of the High and Low. This is the length used to create it.
Smoothing length: Smoothing length is the length used to smooth out our Bullish and Bearish signals, along with our Overly Bullish and Overly Bearish Signals.
2. Kernel Settings:
Lookback Window: The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars. Recommended range: 3-50.
Relative Weighting: Relative weighting of time frames. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel. Recommended range: 0.25-25.
Start Regression at Bar: Bar index on which to start regression. The first bars of a chart are often highly volatile, and omission of these initial bars often leads to a better overall fit. Recommended range: 5-25.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Gann's square of 9 overextended indicatorThis indicator is inspired by the book “The Definitive Guide to Forecasting Using W.D. Gann’s Square of Nine”. It’s designed to identify overextended price levels in the market.
The indicator uses the concept of Gann’s Square of 9, which is a method for forecasting price movements by observing geometric relationships between price and time. It calculates the square root of the price, then subtracts the square root of a simple moving average of the price. The difference is then converted to degrees to create the indicator values.
The indicator plots four horizontal lines, representing two upper and two lower thresholds. When the indicator crosses these lines, it suggests that the price may be overextended and a reversal could be imminent.
Please note that the Price Multiplier parameter needs to be adjusted for each timeframe and security to ensure accurate results. This is because different securities and timeframes can have different price scales, and the multiplier helps to normalize the price data for the calculation.
The indicator also includes a Moving Average Size parameter, which determines the length of the simple moving average used in the calculation.
This indicator can be a useful tool for traders looking to identify potential reversal points in the market. However, like all indicators, it should be used in conjunction with other forms of analysis and it’s not recommended to rely solely on this indicator for trading decisions.
Auto Fibo on IndicatorsThis drawing tool aims to draw auto Fibonacci Retracement Levels on desired indicators.
Users can define the target indicator to draw Auto Fibo Lines, from the "settings tab":
There are six commonly used indicators below the charts that can be selected to draw Fibonacci Retracement lines on:
RSI : Relative Strength Index
CCI : Commodity Channel Index
MFI : Money Flow Index
STOCHASTIC : Stochastic Oscillator
CMF : Chaikin Money Flow
CMO : Chande Momentum Oscillator
Fibonacci Retracement Levels will appear automatically after applying the indicator.
The "Auto Fibo on Indicators" tool looks back. It checks the indicator levels for a desired number of bars and then draws the Fibonacci Levels automatically in the right way, considering the final movements of the indicator.
There are five commonly used Fibonacci Levels added between the Highest and Lowest values such as:
%23.6
%38.2
%50 (Not precisely a Fibonacci Level, indeed)
%61.8 (Golden Ratio)
%78.6
Four extra levels can be added from the settings tab by checking their boxes:
%127.2 (adjustable level)
%161.8
%261.8
%361.8
Default lookback bars of Auto Fibo Levels: 144 (which is also a Fibonacci number)
Default Indicator: RSI
Default Indicator length: 14
Default data source: CLOSE
Users can also define and show overbought and oversold levels by unchecking the "Do not Show Indicator Overbought / Oversold Levels?" button from the settings menu.
In technical analysis, Fibonacci Levels on price can guide valuable trading signals for investors.
Levels can be significant support and resistance levels for breakouts and turning points.
This drawing tool aims to follow those necessary levels on indicators to observe critical levels and breakouts.
Monte Carlo Simulation - Your Strategy [Kioseff Trading]Hello!
This script “Monte Carlo Simulation - Your Strategy” uses Monte Carlo simulations for your inputted strategy returns or the asset on your chart!
Features
Monte Carlo Simulation: Performs Monte Carlo simulation to generate multiple future paths.
Asset Price or Strategy: Can simulate either future asset prices based on historical log returns or a specific trading strategy's future performance.
User-Defined Input: Allows you to input your own historical returns for simulation.
Statistical Methods: Offers two simulation methods—Gaussian (Normal) distribution and Bootstrapping.
Graphical Display: Provides options for graphical representation, including line plots and histograms.
Cumulative Probability Target: Enables setting a user-defined cumulative probability target to quantify simulation results.
Adjustable Parameters: Offers numerous user-adjustable settings like number of simulations, forecast length, and more.
Historical Data Points: Option to specify the amount of historical data to be used in the simulation (price).
Custom Binning: Allows you to select the binning method for histograms, with options like Sturges, Rice, and Square Root.
Best/Worst Case: Allows you to show only the best case / worst case outcome (range) for all simulations!
Scatterplot: allows you to show up to 1000 potential outcomes for a specified trade number (or bars forward price endpoint) using a scatter plot.
The image above shows the primary components of the indicator!
The image above shows the best/worst case outcome feature in action!
The image above shows a "fun feature" where 1000 simulated end points for a 15-bar price trajectory are shown as a scatter plot!
How To Perform a Monte Carlo Simulation On Your Strategy
Really, you can input any data into the indicator it will perform a Monte Carlo Simulation on it :D
The following instructions show how to export your strategy results from TradingView to an Excel File, copy the data, and input it into the indicator.
However , you are not limited to following this method!
Wherever your strategy results are stored, simply copy and paste them into the indicator text area in the settings and simulations will begin.
Returns Should Follow This Format
1
3
-3
2
-5
The numbers are presented as a single column. No commas or separators used.
The numbers above are in sequential order. A return of "1" for the first trade and a return of "-5" for the last trade. Your strategy returns will likely be in sequential order already so don't worry too much about this (:
How To Perform a Monte Carlo Simulation On Your TradingView Strategy With Excel Data
Export your strategy returns to an excel file using TradingView
Navigate to your downloads folder to column G "Profit"
Click the column and press CTRL + SPACE to highlight the entire column
Press CTRL + C to copy the entire column
Open this indicator's settings and paste the returns into the text area
The image above illustrates the process!
Notes on Inputting Returns
*Must input your returns without a separate as a vertical list
*The initial text area can only hold so many return values. If your list of trades is large you can input additional returns into two additional text areas at the bottom of the indicator settings.
That should be it; thank you for checking this out!
Weighted Momentum Forecast
The Weighted Momentum Forecast (EWMF) is a predictive indicator designed to forecast the potential direction and magnitude of the next candle's close. It combines the principles of momentum, trend confirmation, and volatility adjustment to make its predictions.
**Components:**
1. **Rate of Change (ROC)**: Measures the momentum of the market.
2. **Average True Range (ATR)**: Represents the market's recent volatility.
3. **Moving Average Convergence Divergence (MACD)**: Used to confirm the momentum's direction.
4. **Trend Moving Average**: A longer-term moving average to confirm the general trend.
5. **Bollinger Bands**: Adjusts the forecast to account for extreme predictions.
**Logic:**
1. **Momentum Bias**: The crossover and crossunder of the MACD line and its signal line are used to determine the momentum's bias. A crossover indicates a bullish bias, while a crossunder indicates a bearish bias.
2. **Trend Confirmation**: If the current close is above the trend moving average, the indicator has a bullish bias, and vice versa.
3. **Forecast Calculation**: The forecast for the next candle's close is calculated based on the current close, the rate of change, the momentum's bias, and the trend's bias. This value is then adjusted for volatility using the ATR.
4. **Volatility Adjustment**: If the forecasted value is beyond the Bollinger Bands, it's adjusted to be within the bands to account for extreme predictions.
**Usage:**
The EWMF plots a purple line representing the forecasted value of the next candle's close. This forecasted value provides traders with a visual representation of where the price might head in the next period, based on recent momentum, trend, and volatility.
**Note**: This is a heuristic approach and is not guaranteed to be accurate. It's essential to use this indicator in conjunction with other tools, backtest on historical data, and use proper risk management techniques. Always be aware of the inherent risks involved in trading and never risk more than you're willing to lose.
Kaschko's Seasonal TrendThis script calculates the average price moves (using each bar's close minus the previous bar's close) for the trading days, weeks or months (depending on the timeframe it is applied to) of a number of past calendar years (up to 30) to construct a seasonal trend which is then drawn as a seasonal chart (overlay) onto the price chart. Supported are the 1D,1W,1M timeframes.
The seasonal chart is adjusted to the price chart (so that both occupy the same height on the overall chart) and it is also de-trended, which means that the seasonal chart's starting value is the same in each year and the progression during the year is adjusted so that no abrupt gap occurs between years and the highs and lows of consecutive years of the seasonal chart (if projected over more than one year) are also at the same level. Of course, this also means that the absolute value of the seasonal chart has no meaning at all.
You can configure the number of bars the seasonal chart is drawn into the future. This projection shows how price could move in the future if the market shows the same seasonal tendencies like in the past. On the daily chart, the trading week of year (TWOY), trading day of month (TDOM) and trading day of year (TDOY) are shown in the status line.
Caution is advised as seasonality is based on the past. It is not a reliable prediction of the future. But it can still be used as an additional confirmation or contradiction of an otherwise recognized possible impending trend.
I have used a virtually identical indicator for a long time in a commercial software package popular among futures traders, but have not found anything comparable here. Therefore I implemented it myself. I hope you find it useful.
Abz US Real ratesThis indicator shows Fed Funds Rate vs US inflation. It also shows the US 10 year bond yield and provides a color indication that aims to indicate if this is a period where owning TLT is a good idea or not. It is not investment advice and it is only aiming to indicate whether the trend is supportive or not for long dated US bonds in comparison with short dated treasury bills and versus inflation.
Recessions: Recessions are indicated by a grey background.
Yield inversion: Periods where the Fed Funds Rate is above the US 10 year bond yield are shown as a maroon background and frequently are macro indicators of an upcoming recession. Like other macro signals, this can't be relied upon as a timing tool.
This is intended to be used as an indictor on a long term chart. Minimum would be weekly but could be even more valid to focus on a chart with monthly candles.
K's Reversal Indicator IIIK's Reversal Indicator III is based on the concept of autocorrelation of returns. The main theory is that extreme autocorrelation (trending) that coincide with a technical signals such as one from the RSI, may result in a powerful short-term signal that can be exploited.
The indicator is calculated as follows:
1. Calculate the price differential (returns) as the current price minus the previous price.
2. the correlation between the current return and the return from 14 periods ago using a lookback of 14 periods.
3. Calculate a 14-period RSI on the close prices.
To generate the signals, use the following rules:
* A bullish signal is generated whenever the correlation is above 0.60 while the RSI is below 40.
* A bearish signal is generated whenever the correlation is above 0.60 while the RSI is above 60.
YinYang Bar ForecastOverview:
YinYang Bar Forecast is a prediction indicator. It predicts the movement for High, Low, Open and Close for up to 13 bars into the future. We created this Indicator as we felt the TradingView community could benefit from a bar forecast as there wasn’t any currently available.
Our YinYang Bar Forecast is something we plan on continuously working on to better improve it, but at its current state it is still very useful and decently accurate. It features many calculations to derive what it thinks the future bars will hold. Let’s discuss some of the logic behind it:
Each bar has its High, Low, Open and Close calculated individually for highest accuracy. Within these calculations we first check which bar it is we are calculating and base our span back length that we are getting our data from based on the bar index we are generating. This helps us get a Moving Average for this bar index.
We take this MA and we apply our Custom Volume Filter calculation on it, which is essentially us dividing the current bars volume over the average volume in the last ‘Filtered Length’ (Setting) length. We take this decimal and multiply it on our MA and smooth it out with a VWMA.
We take the new Volume Filtered MA and apply a RSI Filter calculation on it. RSI Filter is where we take the difference between the high and low of this bar and we multiply it with an RSI calculation using our Volume Filtered MA. We take the result of that multiplication and either add or subtract it from the Volume Filtered MA based on if close > open. This makes our RSI Filtered MA.
Next, we do an EMA Strength Calculation which is where we check if close > ema(close, ‘EMA Averaged Length’) (Setting). Based on this condition we assign a multiplier that is applied to our RSI Filtered MA. We divide by how many bars we are predicting and add a bit to each predictive bar so that the further we go into the future the stronger the strength is.
Next we check RSI and RSI MA levels and apply multiplications based on its RSI levels and if it is greater than or less than the MA. Also it is affected by if the RSI is <= 30 and >= 70.
Finally we check the MFI and MFI MA levels and like RSI we apply multiplications based on its MFI levels and if it is greater than or less than the MA. It is also affected by if the MFI is <= 30 and >= 70.
Please note the way we calculate this may change in the future, this is just currently what we deemed works best for forecasting the future bars. Also note this script uses MA calculations out of scope for efficiency but there is potential for inconsistencies.
Innately it’s main use is the projection it provides. It only draws the bars for realtime bars and not historical ones, so the best way to backtest it is with TradingView’s Replay Tool.
Well, enough of the logic behind it, let's get to understanding how to use it:
Tutorial:
So unfortunately we aren’t able to plot legit bars/candles into the future so we’ve had to do a bit of a work around using lines and fills. As you can see here we have 4 Lines and 3 Zones:
Lines:
Green: Represents the High
Orange: Represents the Open
Teal: Represents the Close
Red: Represents the Low
Zones:
High Zone: This zone is from either Open or Close to the High and is ALWAYS filled with Green.
Open/Close Zone: This zone is from the Open to the Close and is filled with either Green or Red based on if it's greater than the previous bar (real or forecasted).
Low Zone: This zone is from either Open or Close to the Low and is ALWAYS filled with Red.
As you can see generally the Forecasted bars are generally within strong pivot locations and are a good estimation of what will likely go on. Please note, the WHOLE structure of the prediction can change based on the current bars movements and the way it affects the calculations.
Let's look 1 bar back from the current bar just so we can see what it used to Forecast:
As you can see it has changed quite a bit from the previous bar, but if you look close, we drew horizontal lines around where its projecting the next bar to be (our current realtime bar), if we go back to the live chart:
Its projections were pretty close for the high and low. Generally, right now at least, it does a much better job at predicting the high and low than it does the open and close, however we will do our best to fine tune that in future updates.
Remember, this indicator is not meant to base your trades on, but rather give you a Forecast towards the general direction of the next few bars. Somewhat like weather, the farther the bar (or day for weather), the harder it is to predict. For this reason we recommend you focusing on the first few bars as they are more accurate, but review the further ones as they may help show the trend and the way that pair will move.
We will conclude this tutorial here, hopefully this Predictive Indicator can be of some help and use to you. If you have any questions, comments, ideas or concerns please let us know.
Settings:
Forecast Length: How many bars should we predict into the Future? Max 13
Each Bar Length Multiplier: For each new Forecast bar, how many more bars are averaged? Min 2
VWMA Averaged Length: All Forecast bars are put into a VWMA, what length should we use?
EMA Averaged Length: All Forecast bars are put into a EMA, what length should we use?
Filtered Length: What length should we use for Filtered Volume and RSI?
EMA Strength Length: What length should we use for the EMA Strength
HAPPY TRADING!
AI SuperTrend - Strategy [presentTrading]
█ Introduction and How it is Different
The AI Supertrend Strategy is a unique hybrid approach that employs both traditional technical indicators and machine learning techniques. Unlike standard strategies that rely solely on traditional indicators or mathematical models, this strategy integrates the power of k-Nearest Neighbors (KNN), a machine learning algorithm, with the tried-and-true SuperTrend indicator. This blend aims to provide traders with more accurate, responsive, and context-aware trading signals.
*The KNN part is mainly referred from @Zeiierman.
BTCUSD 8hr performance
ETHUSD 8hr performance
█ Strategy, How it Works: Detailed Explanation
SuperTrend Calculation
Volume-Weighted Moving Average (VWMA): A VWMA of the close price is calculated based on the user-defined length (len). This serves as the central line around which the upper and lower bands are calculated.
Average True Range (ATR): ATR is calculated over a period defined by len. It measures the market's volatility.
Upper and Lower Bands: The upper band is calculated as VWMA + (factor * ATR) and the lower band as VWMA - (factor * ATR). The factor is a user-defined multiplier that decides how wide the bands should be.
KNN Algorithm
Data Collection: An array (data) is populated with recent n SuperTrend values. Corresponding labels (labels) are determined by whether the weighted moving average price (price) is greater than the weighted moving average of the SuperTrend (sT).
Distance Calculation: The absolute distance between each data point and the current SuperTrend value is calculated.
Sorting & Weighting: The distances are sorted in ascending order, and the closest k points are selected. Each point is weighted by the inverse of its distance to the current point.
Classification: A weighted sum of the labels of the k closest points is calculated. If the sum is closer to 1, the trend is predicted as bullish; if closer to 0, bearish.
Signal Generation
Start of Trend: A new bullish trend (Start_TrendUp) is considered to have started if the current trend color is bullish and the previous was not bullish. Similarly for bearish trends (Start_TrendDn).
Trend Continuation: A bullish trend (TrendUp) is considered to be continuing if the direction is negative and the KNN prediction is 1. Similarly for bearish trends (TrendDn).
Trading Logic
Long Condition: If Start_TrendUp or TrendUp is true, a long position is entered.
Short Condition: If Start_TrendDn or TrendDn is true, a short position is entered.
Exit Condition: Dynamic trailing stops are used for exits. If the trend does not continue as indicated by the KNN prediction and SuperTrend direction, an exit signal is generated.
The synergy between SuperTrend and KNN aims to filter out noise and produce more reliable trading signals. While SuperTrend provides a broad sense of the market direction, KNN refines this by predicting short-term price movements, leading to a more nuanced trading strategy.
Local picture
█ Trade Direction
The strategy allows traders to choose between taking only long positions, only short positions, or both. This is particularly useful for adapting to different market conditions.
█ Usage
ToolTips: Explains what each parameter does and how to adjust them.
Inputs: Customize values like the number of neighbors in KNN, ATR multiplier, and moving average type.
Plotting: Visual cues on the chart to indicate bullish or bearish trends.
Order Execution: Based on the generated signals, the strategy will execute buy/sell orders.
█ Default Settings
The default settings are selected to provide a balanced approach, but they can be modified for different trading styles and asset classes.
Initial Capital: $10,000
Default Quantity Type: 10% of equity
Commission: 0.1%
Slippage: 1
Currency: USD
By combining both machine learning and traditional technical analysis, this strategy offers a sophisticated and adaptive trading solution.
Buy/Sell BoxThis indicator tries to identify the points where the price exceeds or falls below a rectangle based on the opening and closing prices of the previous period, the creation of the boxes occurs when a doji is detected therefore it will calculate the coordinates of the rectangle that will be drawn around it, therefore the indicator offers buy or sell signals based on this logic. Specifically, the buy signal is generated if the closing price is above the top of the rectangle and satisfies some previous price conditions while the sell signal is generated if the closing price is below the bottom of the rectangle and satisfies some conditions of previous prices within a further threshold based on the Ema 150.
Lines are then drawn on the graph to visually display the extreme price levels, which can be useful for any confirmation of buy and sell signals, Stop Loss and Take Profit, Trend Filter (to visually understand if the trend is bullish or bearish)
A potentially effective trading strategy could involve identifying buy and sell signals near the extreme price level lines drawn by the indicator. This approach can be used to try to improve the accuracy of your trading signals and make more informed decisions. For example:
When you receive a buy or sell signal based on the dojis and rectangles generated by the indicator, check whether the price is also near one of the extreme price level lines. If you are receiving a buy signal and notice that the current price is near a low of the lower level line, this may further confirm the buying opportunity, as the price is near a significant resistance level. On the contrary, if the sell signal was close to a maximum price level it could confirm an excellent short entry.
It is also possible to use the boxes as reference points to set the stop loss and take profit levels. If you are entering a buy position, you might consider setting your stop loss just below an upper line of the last box. Additionally, you may want to set your take profit near a higher price level if you are looking to maximize profits. This will help manage risks and protect your capital.
Ruth Buy/Sell Signal for Day Trade and Swing TradeRuth is based on the most known technical indicators and designed for intraday traders. Ruth's aim is to find the best Buy/Sell points and decide to stop loss point with minimum Loss also Ruth tries to find multiple Profit points as TP1/TP2/TP3/TP4/TP5. Ruth was designed based on the heat map colors to be user-friendly and easy to read. While cold color preferred for Short positions, warm colors preferred for Long positions. The most important feature of Ruth is that after the signal is generated, the candles in which the profitable levels are painted one by one with their own special color codes, so that even the most inexperienced users can understand where they should close their positions.
There are two types of signal Ruth can produce for fast trade.
Short Signal: These signals means market tends to be move to down.
Short Stop Loss Point: This is the maximum risk for the position. Shown with single red line inside of the signal.
Short Entry Point: This is the best entry price for short side position. Shown with single baby blue line inside of the signal.
Short Take Profit (TP1): This level represents the profit level the signal is most likely to reach. Shown with single blue line inside of the signal.
Short Take Profit (TP2): This level represents the profit level with a high probability of the signal occurring. Shown with single light purple line inside of the signal.
Short Take Profit (TP3): This level represents the profit level with an intermediate probability of the signal occurring. Shown with single dark purple line inside of the signal.
Short Take Profit (TP4): This level represents the profit level with a low probability of the signal occurring. Shown with single light lilac line inside of the signal.
Short Take Profit (TP5): This level represents the profit level with a tight probability of the signal occurring. Shown with single dark lilac line inside of the signal.
Long Signal: These signals means market tends to be move to up.
Long Stop Loss Point: This is the maximum risk for the position. Shown with single red line inside of the signal.
Long Entry Point: This is the best entry price for short side position. Shown with single baby blue line inside of the signal.
Long Take Profit (TP1): This level represents the profit level the signal is most likely to reach. Shown with single greenish yellow line inside of the signal.
Long Take Profit (TP2): This level represents the profit level with a high probability of the signal occurring. Shown with yellow purple line inside of the signal.
Long Take Profit (TP3): This level represents the profit level with an intermediate probability of the signal occurring. Shown with single dark yellow line inside of the signal.
Long Take Profit (TP4): This level represents the profit level with a low probability of the signal occurring. Shown with single orange line inside of the signal.
Long Take Profit (TP5): This level represents the profit level with a tight probability of the signal occurring. Shown with single dark orange line inside of the signal.
Timeframe: In general best and fastest results occurred in shorter timeframes like 1 min / 5 mins / 15 mins but feel free to try higher timeframes.
Tips & Tricks:
1) Gray line drawn ot the graph represents Dema, we suggests you to go on Short Singals under gray line and go on Long Signals upper gray line.
2) Mostly, Signals easily reach their TP2 / TP3 levels and then generally there is reaction or take profit desire so commodity price turns the opposite direction. If in short time price won't turn to Signal direction close position.
3) Don't forget, every positions has own risks and profits but trade in main trend is crucial.
Hoffman Heiken BiasThis indicator uses a couple of different things including the Hoffman moving averages applied with heiken ashi bar data and some volatility to help determine when the bias of the market has shifted for the timeframe you are looking at.
GP - Long Short ScannerThis script is made to predict the point at which price-time charts will rise or fall. The script was inspired by the RSI and TSI formulas. The formula is simply; Calculates the RSI and TSI values of open, high, low and close. Calculated values are converted to an array. The maximum and minimum values in the array are taken for the candles included in the calculation. These values calculate the time when the "Long" label will be seen on the chart of the candle that will increase the price. At the same time, it calculates the time when the "Short" label will appear on the chart of the candle that will decrease the price. Although these calculations are not precise; Seeing the “Long” label means that the price will rise at that candle, and seeing the “Short” label means that the price will decrease at that candle. The “Long”, “Short” tags from this script alone should not be used to determine the direction of the price. It can be used on all price-time charts.
Bursa Malaysia Index SeriesBursa Malaysia Index Series. The index computation is as follows:-
Current aggregate Market Capitalisation/Base Aggregate Market Capitalisation x 100.
The Bursa Malaysia Index Series is calculated and disseminated on a real-time basis at 60-second intervals during Bursa’s trading hours.
Buy/Sell EMA CrossoverThe indicator identifies potential trading opportunities within the market. It is entirely based on the combination of exponential moving averages by drawing triangles on the chart that identify buy or sell signals combined with vertical bars that create areas of interest.
Specifically, when a buy signal occurs, the indicator draws a vertical bar with an azure background, indicating a possible buy area. Similarly, a sell signal is represented by a vertical bar with a fuchsia background, indicating a possible sell area.
These areas represent the main point of the indicator which uses exponential moving averages which, based on the direction of prices, identify the trend and color the background of the graph in order to visually highlight the predominant trend.
The green triangles above the bars of the chart suggest possible upside opportunities (good bullish entry points) when the 21 ema crosses the 200 ema.
While on the contrary the red triangles, 21 ema lower than the 200 ema, can indicate possible bearish trends (good bearish entry points).
While the white and purple triangles reveal moments of potential indecision or market change.
We can think of them as situations of uncertain trend in which it is possible to place a long or short order near some conditions that we are going to see.
The white triangles below, which are created when the 13 ema is higher than the 21 ema, indicate a possible bullish zone while the purple triangles above (13 ema lower than the 21) could suggest a bearish reflex
Colored lines represent moving averages blue = 200, 21= fuchsia and 13 = white. If the price is above the 200 period line then it could be a bullish opportunity, otherwise it could be a bearish one.
An interesting strategy to adopt is to evaluate, for example, the inputs near the vertical bars (azure - long) (fuchsia - short) when a white or purple triangle appears.
The more prominent green triangle indicates that the trend is going in a long direction.
On the contrary, the red (short) triangles are the opposite of the green ones and have the same importance as input logic.
The white triangle instead present more often inside the indicator identifies interesting buying areas of short duration, it is important to consider that the closer the triangles are to the vertical blue bars the stronger the entry signal.
Finally, the purple triangles are the short-term bearish trends whose entry near the fuchsia vertical bars defines a short.
HL 930 by JPThe "High and Low of 9:30 Candle" strategy is a simple trading strategy commonly used in the stock market and other financial markets. It involves using the price range (high and low) of the first candlestick that forms at the opening of a trading session, typically at 9:30 AM, as a basis for making trading decisions. Here's a description of this strategy:
1. Timeframe: This strategy is often applied to intraday trading, where traders focus on short-term price movements within a single trading day.
2. 9:30 AM Candle: The strategy begins by observing the first candlestick that forms at 9:30 AM, which is the opening time for many stock markets, including the New York Stock Exchange (NYSE). This candle represents the price action during the first few minutes of trading.
3. High and Low: Identify the highest price (the candle's high) and the lowest price (the candle's low) during the 9:30 AM candle's time period. These price levels are critical for the strategy.
4. Trading Decisions:
Long (Buy) Signal: If the current market price breaks above the high of the 9:30 AM candle, it may trigger a bullish signal. Traders may consider entering a long (buy) position, anticipating further upward momentum.
Short (Sell) Signal: Conversely, if the market price breaks below the low of the 9:30 AM candle, it may trigger a bearish signal. Traders may consider entering a short (sell) position, anticipating further downward movement.
5. Stop-Loss and Take-Profit: To manage risk, traders often set stop-loss orders just below the low (for long positions) or just above the high (for short positions) of the 9:30 AM candle. They may also establish take-profit levels based on their risk-reward preferences.
6. Time Frame: This strategy is typically used for short-term trading and may be effective in capturing quick price movements that often occur at the market open. Traders often close their positions before the end of the trading day.
7. Caution: While the "High and Low of 9:30 Candle" strategy can be straightforward, it should not be used in isolation. Traders should consider other technical and fundamental factors, such as volume, market sentiment, news events, and overall market trends, when making trading decisions.
Remember that trading strategies always carry risks, and it's essential to have a well-thought-out risk management plan in place. Additionally, backtesting and practice are crucial before implementing any trading strategy in a live market to evaluate its historical performance and suitability for your trading style.
