Time Matrix [Pro+] (DRxICT)Description:
The Time Matrix Pro is an automated Time-based trading tool adaptable to futures, forex, and bond markets. This indicator is inspired by concepts taught by the Inner Circle Trader (ICT) and ICT_Concepts.
ICT’s repertoire encompasses the concepts of liquidity and couples them with Time. The Time Matrix helps the analyst to locate key Time-based price levels to determine bias and recurring price patterns within the market. Analysts can use levels like Previous Day’s Highs and Lows, Weekly Highs and Lows, Session Openings, and Macros to base and qualify Premium and Discount arrays in intraday analysis.
Session Boxes are Time opportunities of the day that identify the market mechanics of consolidation, expansion, retracement, and reversals.
ICT_Concepts's Session Boxes are described as the Premarket, AM Session, PM session:
Premarket is defined as 9:30pm to 1:30am
AM session is defined as 4:00am to 11:00am
PM Session is defined as 11:30am to 2:15pm
Understanding how Time is crucial for identifying intraday profiling, the analyst is able to toggle price levels in conjunction with Time-based macros. These help analyze key market turning points that can correspond to unique market mechanics.
Beyond the Time-based liquidity levels, and the Time macros, there are also predefined Time clusters.
These clusters highlight a significant lower Timeframe candle which was found to hold significant value by ICT_Concepts. Very much alike Time-based liquidity levels, analysts will notice how price reacts to support or negate existing orderflow, trend and direction.
Key Features:
Customizable Extension: the analyst is given the choice to toggle the ending Time Offset to either Noon NY Time or at the end of the trading day.
Time-Based Toggles: choose individual Time-based prices to highlight on your chart.
Time Table: depending on the Timeframe, the Time Table will display the number of bars and the Time elapsed since the Time-based liquidity levels were established.
Other Features
Customize Session Boxes Color
Customize Time-Based Liquidity Line Style
Customize Time-Based Liquidity Level Color
Customize Time-Based Liquidity Line Width
Customize Table Size and Location
Usage Guidance:
Add Time Matrix to your Tradingview chart.
Customize your desired settings of Time-Based Liquidity Levels to align with your personal preference.
Observe where the Time-Based Liquidity Levels as well as Previous Day, Week, and Macros play a role in intraday narrative.
Analysts can choose to utilize Time-Based Liquidity Levels as automated framework to organize models and layouts.
These tools are available ONLY on the TradingView platform.
Terms and Conditions
Our charting tools are products provided for informational and educational purposes only and do not constitute financial, investment, or trading advice. Our charting tools are not designed to predict market movements or provide specific recommendations. Users should be aware that past performance is not indicative of future results and should not be relied upon for making financial decisions. By using our charting tools, the purchaser agrees that the seller and the creator are not responsible for any decisions made based on the information provided by these charting tools. The purchaser assumes full responsibility and liability for any actions taken and the consequences thereof, including any loss of money or investments that may occur as a result of using these products. Hence, by purchasing these charting tools, the customer accepts and acknowledges that the seller and the creator are not liable nor responsible for any unwanted outcome that arises from the development, the sale, or the use of these products.
Finally, the purchaser indemnifies the seller from any and all liability. If the purchaser was invited through the Friends and Family Program, they acknowledge that the provided discount code only applies to the first initial purchase of the Toodegrees Premium Suite subscription. The purchaser is therefore responsible for cancelling – or requesting to cancel – their subscription in the event that they do not wish to continue using the product at full retail price. If the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable. We hold no reimbursement, refund, or chargeback policy. Once these Terms and Conditions are accepted by the Customer, before purchase, no reimbursements, refunds or chargebacks will be provided under any circumstances.
By continuing to use these charting tools, the user acknowledges and agrees to the Terms and Conditions outlined in this legal disclaimer.
Forecasting
Expected Move by Option's Implied Volatility Symbols: EAT - GBDC
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of EAT-GDBC in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Expected Move by Option's Implied Volatility Symbols: CLFD-EARN This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of CLFD - EARN in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Expected Move by Option's Implied Volatility Symbols: B - CLF
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of B - CLF in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Cycle OscillatorThe Cycle Oscillator is a tool developed to help traders analyze market cycles thanks to a simplified version of the Hurst theory and the easy visualization provided by the detrended cycle.
This indicator has two functions:
- The first one is the plotting of a line that oscillates above and below the zero line, which can be used to find the cycle direction and momentum
- The second feature is the next-cycle bottom forecaster, useful for estimating the timing of the future pivot low based on the pivot low of the oscillator.
This last feature shows graphically the period in which the next low will probably happen, using as a calculation method the timing of the previous indicator's lows.
Additionally, the user can choose to modify the cycle length to analyze bigger or smaller price movements.
This indicator can be greatly used in combination with other Cycle Indicators to gain more confluence in the plotted time areas.
Cycle IndicatorThe Cycle Indicator is a tool developed to help traders analyze market cycles thanks to a simplified version of the Hurst theory.
This indicator has two functions:
- The first one is the plotting of a line that can be used to find the cycle direction and momentum
- The second feature is the next-cycle bottom forecaster, useful for estimating the timing of the future pivot low.
This last feature shows graphically the period in which the next low will probably happen, using as a calculation method the timing of the previous lows.
Additionally, the user can choose to extend this time zone or to limit them to the range between the last pivot high and low.
Expected Move by Option's Implied Volatility Symbols: A - AZZ
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of A - AZZ in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Machine Learning: VWAP [YinYangAlgorithms]Machine Learning: VWAP aims to use Machine Learning to Identify the best location to Anchor the VWAP at. Rather than using a traditional fixed length or simply adjusting based on a Date / Time; by applying Machine Learning we may hope to identify crucial areas which make sense to reset the VWAP and start anew. VWAP’s may act similar to a Bollinger Band in the sense that they help to identify both Overbought and Oversold Price locations based on previous movements and help to identify how far the price may move within the current Trend. However, unlike Bollinger Bands, VWAPs have the ability to parabolically get quite spaced out and also reset. For this reason, the price may never actually go from the Lower to the Upper and vice versa (when very spaced out; when the Upper and Lower zones are narrow, it may bounce between the two). The reason for this is due to how the anchor location is calculated and in this specific Indicator, how it changes anchors based on price movement calculated within Machine Learning.
This Indicator changes the anchor if the Low < Lowest Low of a length of X and likewise if the High > Highest High of a length of X. This logic is applied within a Machine Learning standpoint that likewise amplifies this Lookback Length by adding a Machine Learning Length to it and increasing the lookback length even further.
Due to how the anchor for this VWAP changes, you may notice that the Basis Line (Orange) may act as a Trend Identifier. When the Price is above the basis line, it may represent a bullish trend; and likewise it may represent a bearish trend when below it. You may also notice what may happen is when the trend occurs, it may push all the way to the Upper or Lower levels of this VWAP. It may then proceed to move horizontally until the VWAP expands more and it may gain more movement; or it may correct back to the Basis Line. If it corrects back to the basis line, what may happen is it either uses the Basis Line as a Support and continues in its current direction, or it will change the VWAP anchor and start anew.
Tutorial:
If we zoom in on the most recent VWAP we can see how it expands. Expansion may be caused by time but generally it may be caused by price movement and volume. Exponential Price movement causes the VWAP to expand, even if there are corrections to it. However, please note Volume adds a large weighted factor to the calculation; hence Volume Weighted Average Price (VWAP).
If you refer to the white circle in the example above; you’ll be able to see that the VWAP expanded even while the price was correcting to the Basis line. This happens due to exponential movement which holds high volume. If you look at the volume below the white circle, you’ll notice it was very large; however even though there was exponential price movement after the white circle, since the volume was low, the VWAP didn’t expand much more than it already had.
There may be times where both Volume and Price movement isn’t significant enough to cause much of an expansion. During this time it may be considered to be in a state of consolidation. While looking at this example, you may also notice the color switch from red to green to red. The color of the VWAP is related to the movement of the Basis line (Orange middle line). When the current basis is > the basis of the previous bar the color of the VWAP is green, and when the current basis is < the basis of the previous bar, the color of the VWAP is red. The color may help you gauge the current directional movement the price is facing within the VWAP.
You may have noticed there are signals within this Indicator. These signals are composed of Green and Red Triangles which represent potential Bullish and Bearish momentum changes. The Momentum changes happen when the Signal Type:
The High/Low or Close (You pick in settings)
Crosses one of the locations within the VWAP.
Bullish Momentum change signals occur when :
Signal Type crosses OVER the Basis
Signal Type crosses OVER the lower level
Bearish Momentum change signals occur when:
Signal Type crosses UNDER the Basis
Signal Type Crosses UNDER the upper level
These signals may represent locations where momentum may occur in the direction of these signals. For these reasons there are also alerts available to be set up for them.
If you refer to the two circles within the example above, you may see that when the close goes above the basis line, how it mat represents bullish momentum. Likewise if it corrects back to the basis and the basis acts as a support, it may continue its bullish momentum back to the upper levels again. However, if you refer to the red circle, you’ll see if the basis fails to act as a support, it may then start to correct all the way to the lower levels, or depending on how expanded the VWAP is, it may just reset its anchor due to such drastic movement.
You also have the ability to disable Machine Learning by setting ‘Machine Learning Type’ to ‘None’. If this is done, it will go off whether you have it set to:
Bullish
Bearish
Neutral
For the type of VWAP you want to see. In this example above we have it set to ‘Bullish’. Non Machine Learning VWAP are still calculated using the same logic of if low < lowest low over length of X and if high > highest high over length of X.
Non Machine Learning VWAP’s change much quicker but may also allow the price to correct from one side to the other without changing VWAP Anchor. They may be useful for breaking up a trend into smaller pieces after momentum may have changed.
Above is an example of how the Non Machine Learning VWAP looks like when in Bearish. As you can see based on if it is Bullish or Bearish is how it favors the trend to be and may likewise dictate when it changes the Anchor.
When set to neutral however, the Anchor may change quite quickly. This results in a still useful VWAP to help dictate possible zones that the price may move within, but they’re also much tighter zones that may not expand the same way.
We will conclude this Tutorial here, hopefully this gives you some insight as to why and how Machine Learning VWAPs may be useful; as well as how to use them.
Settings:
VWAP:
VWAP Type: Type of VWAP. You can favor specific direction changes or let it be Neutral where there is even weight to both. Please note, these do not apply to the Machine Learning VWAP.
Source: VWAP Source. By default VWAP usually uses HLC3; however OHLC4 may help by providing more data.
Lookback Length: The Length of this VWAP when it comes to seeing if the current High > Highest of this length; or if the current Low is < Lowest of this length.
Standard VWAP Multiplier: This multiplier is applied only to the Standard VWMA. This is when 'Machine Learning Type' is set to 'None'.
Machine Learning:
Use Rational Quadratics: Rationalizing our source may be beneficial for usage within ML calculations.
Signal Type: Bullish and Bearish Signals are when the price crosses over/under the basis, as well as the Upper and Lower levels. These may act as indicators to where price movement may occur.
Machine Learning Type: Are we using a Simple ML Average, KNN Mean Average, KNN Exponential Average or None?
KNN Distance Type: We need to check if distance is within the KNN Min/Max distance, which distance checks are we using.
Machine Learning Length: How far back is our Machine Learning going to keep data for.
k-Nearest Neighbour (KNN) Length: How many k-Nearest Neighbours will we account for?
Fast ML Data Length: What is our Fast ML Length? This is used with our Slow Length to create our KNN Distance.
Slow ML Data Length: What is our Slow ML Length? This is used with our Fast Length to create our KNN Distance.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Lite Trading Diary : equity curveDynamic trading journal with equity curve display. Detailed results with prop firm objectives, editable, $/month estimation, possibility to compare two strategies.
one line in parameter = one trade.
For each trade, specify : RR (Win, or "-1" for a stoploss), type of trade, and a comment.
The bottom left table summarizes the overall performance with some key information. RA return => Risk adjusted performance.
there is the possibility to define a "Type" : type 1, 2 or 3. It allows to split the equity curve. You can thus distinguish the different sub-strategies of your strategy, visually see their effectiveness, and be able to adjust your risk exposure accordingly.
Learn from your backtests. Identify your strengths, your weaknesses, and improve!
All the conditions to succeed in the challenge are adjustable in the parameters. Please note : drawdown on the equity curve is max drawdown. On the table => static drawdown.
Use "A random day trading" indicator to spice up your training.
I hope this will be useful for you to track your performance !
Choose Symbol, candle and Trend modeThis Pine Script code is designed for technical analysis and visualization of price movements on the TradingView platform. It serves as a tool for traders and investors to:
Price Chart Analysis: The code plots the price chart of a selected symbol and utilizes Heikin-Ashi candlesticks to visualize price movements. This aids in better understanding price trends, support and resistance levels, retracements, and other price actions.
Trend Identification: The code also employs the Exponential Moving Average (EMA) to identify the price trend. EMA is commonly used to determine the strength and direction of a trend. Traders and investors can use this information to track trends and develop trading strategies.
Buy and Sell Signals: The code generates buy and sell signals based on EMA. These signals provide information on when to consider buying or selling a specific symbol. This is particularly useful for traders when making trading decisions.
Timeframe Customization: Users can adapt the code to different timeframes. This flexibility is valuable for those looking to develop strategies for both short-term and long-term trading.
Customization: The code allows users to customize various parameters, including the symbol, timeframe, Heikin-Ashi mode, and others. This enables it to be tailored to different assets and trading styles.
Please note that this code is provided for educational and informational purposes only. It does not constitute financial advice or recommendations for specific trading actions. Any trading decisions made using this code should be based on individual research, analysis, and a clear understanding of the associated risks.
AR Forecast Scatterplot [SS]This is a showcase indicator of my recently released SPTS library (the partner of the SPTS indicator).
This is just to show some of the practical applications of the boring statistical functions contained within the library/SPTS indicator :-).
This is an autoregressive (AR), scatter plot forecaster. What this means is it tags a lag of 1, performs an autoregressive assessment over the desired training time, then uses what it learns over that training time to forecast the likely outcome.
Its not a machine learning (I am in the process of creating one like this, but it is taking quite some time to complete), but the model needs to learn to plan the statistical coefficients that will best mimic the current trend.
As of its current state, this actually surpassed my own expectations. I can show you some QQQ examples:
Example #1:
Prediction:
Actual:
Example #2:
Prediction:
Actual:
Pretty nuts, eh?
Statistics, I'm telling you, its the answer haha.
So how do we determine the train time?
Because this is not using machine learning to control for over/under representation of datasize (again, I am making a version that does this, but its a slow process), some quick tips at determine appropriate train time is to use the Tradingview Regression tool:
When you set the parameters to align with the current, strongest trend, it is more reliable.
You will see, that it acutally is forecasting a move back to the exact top of this trend, that is because it is using the same processes as the linear regression trend on Tradingview.
You can use a bar counter indicator ( such as mine available here ) to calculate the number or bars back for your model training.
You can verify that these parameters are appropriate by looking at the Model Data table (which can be toggled on and off). You want to see both a high correlation and a high R2 value.
Quick note on colour:
Green = represents the upper confidence predictions (best case scenario)
Blue = represents the most likely result
red = represents that lower confidence (not as best case scenario)
Hope you enjoy!
Safe trades everyone!
WU Sahm Recession Indicator The Sahm Recession Indicator devised by Economist Claudia Sahm is a rather insightful tool that captures the onset of recessions by utilizing unemployment data, which can provide more real-time insights compared to quarterly GDP reports. If the three-month simple moving average (SMA) of the unemployment rate exceeds the minimum unemployment rate of the previous 12 months by 0.5 percentage points, it indicates a high likelihood of a recession.
This script allows you to visualize this indicator and set up alerts for when this criterion indicates that a recession could be coming.
Leading Economic Indicator (LEI)The Leading Economic Indicator (LEI) is a groundbreaking technical indicator designed to serve as a comprehensive measure of the prevailing direction of economic trends in the United States. This unique index combines two key economic indicators: the Composite Leading Indicator (CLI) from the Organization for Economic Co-operation and Development (OECD) and the Purchasing Managers' Index (PMI) from the Institute for Supply Management (ISM).
The OECD Composite Leading Indicator (CLI) is a globally recognized indicator that assesses the future direction of economic trends by analyzing various leading economic factors. The ISM PMI, on the other hand, provides insights into the business activities of both the manufacturing and services sectors. LEI merges these critical indicators into a single, holistic indicator that empowers traders and investors to grasp the broader economic outlook and the performance of essential economic sectors simultaneously.
By taking into account the CLI and PMI, LEI offers a distinctive perspective, enabling a more accurate assessment of the potential direction of US financial markets.
Usage:
To utilize LEI effectively, it is recommended to apply it on a monthly timeframe (TF Monthly). This extended timeframe is particularly beneficial for investors with a medium to long-term horizon. By focusing on longer-term trends and market stability, LEI becomes an invaluable tool in your investment strategy.
One of the primary applications of LEI is to gauge the risk of market corrections in US financial markets, including the S&P 500, Nasdaq, and Dow Jones indices. Analysts often observe the crossing of the 5-period Simple Moving Average (SMA) with the 10-period SMA. When the 5-period SMA falls below the 10-period SMA, it serves as a potential warning signal for an impending market correction. This feature provides traders with an opportunity to exercise caution and make well-informed investment decisions.
LEI, with its unique blend of the OECD CLI and ISM PMI, provides a reliable tool for assessing the US economic climate, identifying trends, and making informed decisions in the financial markets. It stands as a reference indicator, capturing the essence of economic trends and providing valuable insights to traders and investors.
Sources:
- OECD Composite Leading Indicator (CLI): www.data.oecd.org
- Purchasing Managers' Index: ISM Report on Business (PMI) www.ismworld.org
Linear Regression Forecast Tool [Daveatt]Hello traders,
Navigating through the financial markets requires a blend of analysis, insight, and a touch of foresight.
My Linear Regression Forecast Tool is here to add that touch of foresight to your analysis toolkit on TradingView!
Linear Regression is the heart of this tool, a statistical method that explores the relationship between a dependent variable and one (or more) independent variable(s).
In simpler terms, it finds a straight line that best fits a set of data points.
This "line of best fit" then becomes a visual representation of the relationship in the data, providing a basis for making predictions.
Here's what the Linear Regression Forecast Tool brings to your trading table:
Multiple Indicator Choices: Select from various market indicators like Simple Moving Averages, Bollinger Bands, or the Volume Weighted Average Price as the basis for your linear regression analysis.
Customizable Forecast Periods: Define how many periods ahead you want to forecast, adjusting to your analysis needs, whether that's looking 5, 7, or 10 periods into the future.
On-Chart Forecast Points: The tool plots the forecasted points on your chart, providing a straightforward visual representation of potential future values based on past data.
In this script:
1. We first calculate the indicator using the specified period.
2. We then use the ta.linreg function to calculate a linear regression curve fitted to the indicator over the last Period bars.
3. We calculate the slope of the linear regression curve using the last two points on the curve.
We use this slope to extrapolate the linear regression curve to forecast the next X points of the indicator.
4/ Finally, we use the plot function to plot the original indicator and the forecasted points on the chart, using the offset parameter to shift the forecasted points to the right (into the future).
This method assumes that the trend represented by the linear regression curve will continue, which may not always be the case, especially in volatile or changing market conditions.
Examples:
Works with a moving average
Works with a Bollinger band
The code can be adapted to work with any other indicator (imagine RSI, MACD, other Moving Average Type, PSAR, Supertrend, etc...)
Conclusion
The Linear Regression Forecast Tool doesn't promise to tell the future but provides a structured way to visualize possible future price trends based on historical data. I
Remember, no tool can predict market conditions with certainty.
It's always advisable to corroborate findings with other analysis methods and stay updated with market news and events.
Happy trading!
Machine Learning: Optimal RSI [YinYangAlgorithms]This Indicator, will rate multiple different lengths of RSIs to determine which RSI to RSI MA cross produced the highest profit within the lookback span. This ‘Optimal RSI’ is then passed back, and if toggled will then be thrown into a Machine Learning calculation. You have the option to Filter RSI and RSI MA’s within the Machine Learning calculation. What this does is, only other Optimal RSI’s which are in the same bullish or bearish direction (is the RSI above or below the RSI MA) will be added to the calculation.
You can either (by default) use a Simple Average; which is essentially just a Mean of all the Optimal RSI’s with a length of Machine Learning. Or, you can opt to use a k-Nearest Neighbour (KNN) calculation which takes a Fast and Slow Speed. We essentially turn the Optimal RSI into a MA with different lengths and then compare the distance between the two within our KNN Function.
RSI may very well be one of the most used Indicators for identifying crucial Overbought and Oversold locations. Not only that but when it crosses its Moving Average (MA) line it may also indicate good locations to Buy and Sell. Many traders simply use the RSI with the standard length (14), however, does that mean this is the best length?
By using the length of the top performing RSI and then applying some Machine Learning logic to it, we hope to create what may be a more accurate, smooth, optimal, RSI.
Tutorial:
This is a pretty zoomed out Perspective of what the Indicator looks like with its default settings (except with Bollinger Bands and Signals disabled). If you look at the Tables above, you’ll notice, currently the Top Performing RSI Length is 13 with an Optimal Profit % of: 1.00054973. On its default settings, what it does is Scan X amount of RSI Lengths and checks for when the RSI and RSI MA cross each other. It then records the profitability of each cross to identify which length produced the overall highest crossing profitability. Whichever length produces the highest profit is then the RSI length that is used in the plots, until another length takes its place. This may result in what we deem to be the ‘Optimal RSI’ as it is an adaptive RSI which changes based on performance.
In our next example, we changed the ‘Optimal RSI Type’ from ‘All Crossings’ to ‘Extremity Crossings’. If you compare the last two examples to each other, you’ll notice some similarities, but overall they’re quite different. The reason why is, the Optimal RSI is calculated differently. When using ‘All Crossings’ everytime the RSI and RSI MA cross, we evaluate it for profit (short and long). However, with ‘Extremity Crossings’, we only evaluate it when the RSI crosses over the RSI MA and RSI <= 40 or RSI crosses under the RSI MA and RSI >= 60. We conclude the crossing when it crosses back on its opposite of the extremity, and that is how it finds its Optimal RSI.
The way we determine the Optimal RSI is crucial to calculating which length is currently optimal.
In this next example we have zoomed in a bit, and have the full default settings on. Now we have signals (which you can set alerts for), for when the RSI and RSI MA cross (green is bullish and red is bearish). We also have our Optimal RSI Bollinger Bands enabled here too. These bands allow you to see where there may be Support and Resistance within the RSI at levels that aren’t static; such as 30 and 70. The length the RSI Bollinger Bands use is the Optimal RSI Length, allowing it to likewise change in correlation to the Optimal RSI.
In the example above, we’ve zoomed out as far as the Optimal RSI Bollinger Bands go. You’ll notice, the Bollinger Bands may act as Support and Resistance locations within and outside of the RSI Mid zone (30-70). In the next example we will highlight these areas so they may be easier to see.
Circled above, you may see how many times the Optimal RSI faced Support and Resistance locations on the Bollinger Bands. These Bollinger Bands may give a second location for Support and Resistance. The key Support and Resistance may still be the 30/50/70, however the Bollinger Bands allows us to have a more adaptive, moving form of Support and Resistance. This helps to show where it may ‘bounce’ if it surpasses any of the static levels (30/50/70).
Due to the fact that this Indicator may take a long time to execute and it can throw errors for such, we have added a Setting called: Adjust Optimal RSI Lookback and RSI Count. This settings will automatically modify the Optimal RSI Lookback Length and the RSI Count based on the Time Frame you are on and the Bar Indexes that are within. For instance, if we switch to the 1 Hour Time Frame, it will adjust the length from 200->90 and RSI Count from 30->20. If this wasn’t adjusted, the Indicator would Timeout.
You may however, change the Setting ‘Adjust Optimal RSI Lookback and RSI Count’ to ‘Manual’ from ‘Auto’. This will give you control over the ‘Optimal RSI Lookback Length’ and ‘RSI Count’ within the Settings. Please note, it will likely take some “fine tuning” to find working settings without the Indicator timing out, but there are definitely times you can find better settings than our ‘Auto’ will create; especially on higher Time Frames. The Minimum our ‘Auto’ will create is:
Optimal RSI Lookback Length: 90
RSI Count: 20
The Maximum it will create is:
Optimal RSI Lookback Length: 200
RSI Count: 30
If there isn’t much bar index history, for instance, if you’re on the 1 Day and the pair is BTC/USDT you’ll get < 4000 Bar Indexes worth of data. For this reason it is possible to manually increase the settings to say:
Optimal RSI Lookback Length: 500
RSI Count: 50
But, please note, if you make it too high, it may also lead to inaccuracies.
We will conclude our Tutorial here, hopefully this has given you some insight as to how calculating our Optimal RSI and then using it within Machine Learning may create a more adaptive RSI.
Settings:
Optimal RSI:
Show Crossing Signals: Display signals where the RSI and RSI Cross.
Show Tables: Display Information Tables to show information like, Optimal RSI Length, Best Profit, New Optimal RSI Lookback Length and New RSI Count.
Show Bollinger Bands: Show RSI Bollinger Bands. These bands work like the TDI Indicator, except its length changes as it uses the current RSI Optimal Length.
Optimal RSI Type: This is how we calculate our Optimal RSI. Do we use all RSI and RSI MA Crossings or just when it crosses within the Extremities.
Adjust Optimal RSI Lookback and RSI Count: Auto means the script will automatically adjust the Optimal RSI Lookback Length and RSI Count based on the current Time Frame and Bar Index's on chart. This will attempt to stop the script from 'Taking too long to Execute'. Manual means you have full control of the Optimal RSI Lookback Length and RSI Count.
Optimal RSI Lookback Length: How far back are we looking to see which RSI length is optimal? Please note the more bars the lower this needs to be. For instance with BTC/USDT you can use 500 here on 1D but only 200 for 15 Minutes; otherwise it will timeout.
RSI Count: How many lengths are we checking? For instance, if our 'RSI Minimum Length' is 4 and this is 30, the valid RSI lengths we check is 4-34.
RSI Minimum Length: What is the RSI length we start our scans at? We are capped with RSI Count otherwise it will cause the Indicator to timeout, so we don't want to waste any processing power on irrelevant lengths.
RSI MA Length: What length are we using to calculate the optimal RSI cross' and likewise plot our RSI MA with?
Extremity Crossings RSI Backup Length: When there is no Optimal RSI (if using Extremity Crossings), which RSI should we use instead?
Machine Learning:
Use Rational Quadratics: Rationalizing our Close may be beneficial for usage within ML calculations.
Filter RSI and RSI MA: Should we filter the RSI's before usage in ML calculations? Essentially should we only use RSI data that are of the same type as our Optimal RSI? For instance if our Optimal RSI is Bullish (RSI > RSI MA), should we only use ML RSI's that are likewise bullish?
Machine Learning Type: Are we using a Simple ML Average, KNN Mean Average, KNN Exponential Average or None?
KNN Distance Type: We need to check if distance is within the KNN Min/Max distance, which distance checks are we using.
Machine Learning Length: How far back is our Machine Learning going to keep data for.
k-Nearest Neighbour (KNN) Length: How many k-Nearest Neighbours will we account for?
Fast ML Data Length: What is our Fast ML Length? This is used with our Slow Length to create our KNN Distance.
Slow ML Data Length: What is our Slow ML Length? This is used with our Fast Length to create our KNN Distance.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Purchasing Managers Index (PMI)The Purchasing Managers Index (PMI) is a widely recognized economic indicator that provides crucial insights into the health and performance of an economy's manufacturing and services sectors. This index is a vital tool for anticipating economic developments and trends, offering an early warning system for changes in these sectors.
The PMI is calculated based on surveys conducted among purchasing managers in various businesses and organizations. These managers are asked about their perceptions of current business conditions and their expectations for future economic activity within their sectors. The responses are then compiled and used to calculate the PMI value.
A PMI value above 50 typically indicates that the manufacturing or services sector is expanding, suggesting a positive economic outlook. Conversely, a PMI value below 50 suggests contraction, which may be an early indication of economic challenges or a potential recession.
In summary, the Purchasing Managers Index (PMI) is an essential economic indicator that assesses the health of manufacturing and services sectors by surveying purchasing managers' opinions. It serves as an early warning system for changes in economic activity and is a valuable tool for forecasting economic trends and potential crises.
This code combines the Purchasing Managers Index (PMI) data with two Simple Moving Averages (SMA) and some visual elements.
Let's break down how this indicator works:
1. Loading PMI Data:
The indicator loads data for the "USBCOI" symbol, which represents the PMI data. It fetches the monthly closing prices of this symbol.
2. Calculating Moving Averages:
Two Simple Moving Averages (SMAs) are calculated based on the PMI data. The first SMA, sma_usbcoi, has a length defined by the input parameter (default: 2). The second SMA, sma2_usbcoi, has a different length defined by the second input parameter (default: 14).
3. Color Coding and Thresholds:
The line color of the PMI plot is determined based on the value of the PMI. If the PMI is above 52, the color is teal; if it's below 48, the color is red; otherwise, it's gray. These threshold values are often used to identify specific conditions in the PMI data.
4. Crossing Indicator:
A key feature of this indicator is to determine if the PMI crosses the first SMA (sma_usbcoi) from top to bottom while also being above the value of 52. This is indicated by the crossedUp variable. This condition suggests a specific situation where the PMI crosses a short-term moving average while indicating strength (above 52).
5. Visual Elements:
A "💀" skull emoji is defined as skullEmoji.
The PMI is plotted on the chart with color coding based on its value, as described earlier.
The two SMAs are also plotted on the chart.
When the crossedUp condition is met (PMI crosses the first SMA from top to bottom while above 52), a skull emoji (indicating potential danger) is plotted at the top of the indicator window.
US Composite Leading Indicator (CLI)The US Composite Leading Indicator (CLI), normalized for the United States, closely mirrors the Conference Board "Leading Economic Index" (LEI). It offers unique insights into economic and financial dynamics.
The Composite Leading Indicator (CLI) is an economic tool designed to anticipate economic developments. It is created by aggregating and normalizing a wide range of economic and financial data from various sources.
The normalized data is then aggregated, and a composite indicator is calculated by taking a weighted average of individual indicators.
The CLI is used to provide early insights into the state of the economy and to anticipate future economic trends. It is particularly valuable for predicting economic downturns, including recessions.
The CLI is an essential tool for economists, governments, businesses, and investors seeking to understand economic trends and make informed decisions.
Key Features:
1. Early Warning: Just like its counterpart, the CLI indicator excels at offering early warnings about significant economic events, particularly economic crises. This makes it an indispensable asset for analysts and investors.
2. Recession Indicators: The moving average serves as an early warning system for potential economic recessions. When it crosses the indicator line from the bottom to the top while surpassing a predefined threshold (e.g., 101), it signals a potential crisis.
3. Market Impact: The CLI indicator provides valuable insights into the performance of financial markets, offering cues about indices such as the S&P 500, Nasdaq, Dow Jones, and more.
Why It Matters:
Understanding the US Composite Leading Indicator (CLI) indicator, normalized for the United States, is crucial for anticipating economic shifts and preparing for changes in financial markets. By analyzing a diverse array of economic factors, it provides a holistic view of economic well-being. Whether you're an investor or economist, this indicator can be an invaluable resource for staying informed about market trends and major economic developments.
Source:
www.data.oecd.org
Supertrend Multiasset Correlation - vanAmsen Hello traders!
I am elated to introduce the "Supertrend Multiasset Correlation" , a groundbreaking fusion of the trusted Supertrend with multi-asset correlation insights. This approach offers traders a nuanced, multi-layered perspective of the market.
The Underlying Concept:
Ever pondered over the term Multiasset Correlation?
In the intricate tapestry of financial markets, assets do not operate in silos. Their movements are frequently intertwined, sometimes palpably so, and at other times more covertly. Understanding these correlations can unlock deeper insights into overarching market narratives and directional trends.
By melding the Supertrend with multi-asset correlations, we craft a holistic narrative. This allows traders to fathom not merely the trend of a lone asset but to appreciate its dynamics within a broader market tableau.
Strategy Insights:
At the core of this indicator is its strategic approach. For every asset, a signal is generated based on the Supertrend parameters you've configured. Subsequently, the correlation of daily price changes is assessed. The ultimate signal on the selected asset emerges from the average of the squared correlations, factoring in their direction. This indicator not only accounts for the asset under scrutiny (hence a correlation of 1) but also integrates 12 additional assets. By default, these span U.S. growth ETFs, value ETFs, sector ETFs, bonds, and gold.
Indicator Highlights:
The "Supertrend Multiasset Correlation" isn't your run-of-the-mill Supertrend adaptation. It's a bespoke concoction, tailored to arm traders with an all-encompassing view of market intricacies, fortified with robust correlation metrics.
Key Features:
- Supertrend Line : A crystal-clear visual depiction of the prevailing market trajectory.
- Multiasset Correlation : Delve into the intricate interplay of various assets and their correlation with your primary instrument.
- Interactive Correlation Table : Nestled at the top right, this table offers a succinct overview of correlation metrics.
- Predictive Insights : Leveraging correlations to proffer predictive pointers, adding another layer of conviction to your trades.
Usage Nuances:
- The bullish Supertrend line radiates in a rejuvenating green hue, indicative of potential upward swings.
- On the flip side, the bearish trajectory stands out in a striking red, signaling possible downtrends.
- A rich suite of customization tools ensures that the chart resonates with your trading ethos.
Parting Words:
While the "Supertrend Multiasset Correlation" bestows traders with a rejuvenated perspective, it's paramount to embed it within a comprehensive trading blueprint. This would include blending it with other technical tools and adhering to stringent risk management practices. And remember, before plunging into live trades, always backtest to fine-tune your strategies.
Supertrend Forecast - vanAmsenHello everyone!
I am thrilled to present the "vanAmsen - Supertrend Forecast", an advanced tool that marries the simplicity of the Supertrend with comprehensive statistical insights.
Before we dive into the functionalities of this indicator, it's essential to understand its foundation and theory.
The Theory:
What exactly is the Supertrend?
The Supertrend, at its core, is a momentum oscillator. It's a tool that provides buy and sell signals based on the prevailing market trend. The underlying principle is straightforward: by analyzing average price data and volatility over a period, the Supertrend gives us a line that represents the trend direction.
However, trading isn't just about identifying trends; it's about understanding their strength, potential profitability, and historical accuracy. This is where statistics come into play. By incorporating statistical analysis into the Supertrend, we can gain deeper insights into the market's behavior.
Description:
The "vanAmsen - Supertrend Forecast" isn't just another Supertrend indicator. It's a comprehensive tool designed to offer traders a holistic view of market trends, backed by robust statistical analysis.
Key Features:
- Supertrend Line: A visual representation of the current market direction.
- Win Rate & Expected Return: Delve into the historical accuracy and profitability of the prevailing trend.
- Average Percentage Change: Understand the average price fluctuation for both winning and losing trends.
- Forecast Lines: Project future price movements based on historical data, providing a roadmap for potential scenarios.
- Interactive Table: A concise table in the top right, offering a snapshot of all vital metrics at a glance.
Usage:
- The bullish Supertrend line adopts an Aqua hue, indicating potential upward momentum.
- In contrast, the bearish line is painted in Orange, suggesting potential downtrends.
- Customize your chart by toggling labels, tables, and lines according to preference.
Recommendation:
The "vanAmsen - Supertrend Forecast" is undoubtedly a powerful tool in a trader's arsenal. However, it's imperative to combine it with other technical analysis tools and sound risk management practices. It's always prudent to backtest strategies with historical data before embarking on live trading.
Strong Pullback Indicator [Rami_LB]Strong Pullback Indicator
Description:
The Strong Pullback Indicator is designed to identify potential pullbacks or even trend reversals by utilizing a specific candlestick pattern in conjunction with the Relative Strength Index (RSI). It is advised to employ this indicator in chart intervals of 15 minutes or higher, as intervals below 15 minutes may generate excessive false signals.
Working Mechanism:
Upon detecting the designated candlestick pattern, the indicator examines whether any of the last five candles exhibit RSI values below 30 or above 70 across at least four distinct time intervals, depending on whether the pattern is bullish or bearish. The RSI calculations incorporate eight different intervals: 1 minute (1m), 5 minutes (5m), 15 minutes (15m), 30 minutes (30m), 1 hour (1h), 2 hours (2h), 4 hours (4h), and 1 day (1d). An arrow is rendered above or below the current candle only when these conditions are met.
Users have the option to adjust the number of overbought or oversold intervals, as well as the general settings for the RSI.
SL/TP Lines:
The indicator can also serve as a trade signal to initiate trades in the opposite direction. To evaluate the potential success of a trade in a backtesting scenario, SL (Stop Loss) and TP (Take Profit) lines can be displayed on the chart. The SL is calculated by taking the distance from the close of the current candle to the high/low of the previous candle and multiplying it by 2.
In the settings, you can alter the Risk Reward Ratio (RRR) of the trade. Given the pullback nature of this indicator, a RRR of 1:1 is deemed logical, thus set as the default value.
Bullish vs. Bearish Candle Counter:
An additional feature of this indicator is its ability to analyze the last 100 candles to ascertain the ratio of bullish to bearish candles. When a 60% threshold is reached, the chart background color alters accordingly. This feature was conceived after a thorough analysis of over 50,000 candles of a currency pair revealed nearly identical counts of bullish and bearish candles, suggesting a market tendency to maintain this balance.
Within the settings, you have the flexibility to modify the number of candles to be analyzed and the percentage threshold for each candle type.
Should you have any ideas on how to enhance the accuracy of this indicator, or suggestions for other indicators that could improve the signals, feel free to leave a comment.
Forex Market Fundamental indicatorsThese explanations are provided in both English and Persian languages.
You can read the description in Persian below.
این توضیحات به دو زبان انگلیسی و فارسی ارائه شده است.
در زیر می توانید توضیحات را به زبان فارسی بخوانید.
If you are looking for a fundamental indicator, We suggest you use this indicator.
It provides an advanced and leading model for fundamental market analysis.
The indexes which are used in the “Indicator” include: unemployment rates, GDP, inflation, and M1 money supply.
For the indices of this indicator, a safe range is defined by the central bank of each country.
For example, the inflation target for countries in different periods has specific limits:
United States: 2%
United Kingdom: 2%
Canada: 2%
Australia: 2%
New Zealand: 1 to 3%
Japan: 0 to 2%
Switzerland: 0 to 2%
European Union: 2%
Considering the past events of each country and the goals of each country and the long-term average of the indicators as well as what the economic officials announce, it can be recognized that there is a red line for each country. Therefore, if the value of the index reaches those red lines, it will definitely affect the monetary and financial policies of those countries.
For example, we estimate that if the monthly inflation rate in Japan, Switzerland, the United Kingdom, and the European Union is more than 0.33, the monetary policies of those countries will try to reduce the inflation. They will try to control inflation by using tools such as increasing interest rates, and from our point of view, this is a positive point in the direction of increasing the value of that country's currency.
Likewise, if the monthly inflation rate in the United States, Canada, Australia or New Zealand is below -0.1, our view is that: these countries will try to stimulate the market with policies such as interest rate cuts or liquidity increases. And these economic policies lead to a decrease in the value of the currency of these countries. As a result, we give a negative score to that country's currency.
To be more precise, the view that we have implemented in this indicator is as follows:
Let's say your symbol chart is on the USDJPY pair.
By default, the possibility of growth in the value of each of the currencies relative to each other is 50 to 50.
But suppose the monthly inflation rate in the United States is -0.15.
Our analysis is that the United States will probably try to reduce the value of its currency to control it (due to the adoption of expansionary policies).
As a result, we reduce the probability of growth in the value of the US dollar relative to the Japanese yen by 5% to 45%, and we also increase the probability of growth in the value of the yen to the dollar to 55%.
Now suppose the monthly inflation rate in Japan is 0.4. Then our analysis is: Japan will try to increase the value of its national currency to control the inflation rate (using contractionary policies).
As a result, we reduce the probability that the US dollar will appreciate against the Japanese yen to 40%. Also, we increase the probability of yen to dollar growth by 60%.
Using this indicator and according to the same symbol, based on each of the five economic indicators, we examine both currencies of the symbol. And finally, based on the surveys, we get the probability of price growth between 0 and 100 percent. And we also determine the possibility of price reduction. However, the probability of zero or one hundred is almost impossible.
If you have any questions about our view in relation to other indicators, you can comment and ask.
We will answer you.
These questions and answers will help and evolute both of us. We are trying to keep this Indicator up to date and improve it with the most logical arguments.
The important point is that this indicator never claims to always be correct. The forecast of this Indicator may not be realized or may be realized in different and longer time periods.
As a fact for any financial expert, we should know that there are many parameters that affect the price, and this Indicator cannot analyze all of them. Therefore, look at this Indicator as an auxiliary tool and do not expect miracles from it.
Head of programmers:
Mr. Mojtaba askari - Mr. Mohammad sanaei
Developers:
Mrs. Hamideh Azari
Mr. Peyman Mahdavi
Mr. Mohsen shabani
Mr. Moslem Balasi
Mr. Shahrokh Nakhaei
اگر به دنبال یک اندیکاتور بر پایه تحلیل بنیادی هستید، پیشنهاد می کنیم از این اندیکاتور استفاده کنید.
این یک مدل پیشرفته و پیشرو برای تحلیل بنیادی بازار ارائه می دهد.
شاخص هایی که در این «اندیکاتور» بررسی شده، عبارتند از: نرخ بیکاری، تولید ناخالص داخلی، تورم، نرخ بهره و حجم نقدینگی M1.
برای شاخص های این اندیکاتور، یک محدوده امن توسط بانک مرکزی هر کشور تعریف شده است.
به عنوان مثال، هر کشور، در دوره های مختلف، هدف تورمی خاصی تعیین میکند:
ایالات متحده: 2%
بریتانیا: 2%
کانادا: 2%
استرالیا: 2%
نیوزلند: 1 تا 3 درصد
ژاپن: 0 تا 2 درصد
سوئیس: 0 تا 2 درصد
اتحادیه اروپا: 2%
با توجه به اتفاقات گذشته هر کشور و اهداف هر کشور و میانگین بلندمدت شاخصها و همچنین آنچه مسئولان اقتصادی اعلام میکنند، میتوان تشخیص داد که برای هر کشور یک خط قرمز وجود دارد. بنابراین اگر مقدار شاخص به آن خطوط قرمز برسد، قطعا بر سیاست های پولی و مالی آن کشورها تأثیر خواهد گذاشت.
به عنوان مثال، ما تخمین می زنیم که اگر نرخ تورم ماهانه در ژاپن، سوئیس، انگلستان و اتحادیه اروپا بیش از 0.33 باشد، سیاست های پولی آن کشورها سعی در کاهش تورم خواهد داشت. آنها سعی خواهند کرد با استفاده از ابزارهایی مانند افزایش نرخ بهره، تورم را کنترل کنند و از نظر ما این نکته مثبتی در جهت افزایش ارزش پول آن کشور است.
به همین ترتیب، اگر نرخ تورم ماهانه در ایالات متحده، کانادا، استرالیا یا نیوزلند زیر 0.1- باشد، نظر ما این است که: این کشورها با سیاست هایی مانند کاهش نرخ بهره یا افزایش نقدینگی سعی در تحریک بازار خواهند داشت. و این سیاست های اقتصادی منجر به کاهش ارزش پول این کشورها می شود. در نتیجه به واحد پول آن کشور نمره منفی می دهیم.
به بیان دقیق تر، دیدگاهی که در این اندیکاتور پیاده سازی کرده ایم به شرح زیر است:
فرض کنید نماد نمودار شما روی جفت ارز "USDJPY" است.
به طور پیش فرض امکان رشد ارزش هر یک از ارزها نسبت به یکدیگر 50 تا 50 در نظر گرفته شده.
اما فرض کنید نرخ تورم ماهانه در ایالات متحده 0.15- باشد.
تحلیل ما این است که احتمالا ایالات متحده برای کنترل آن (با استفاده از سیاست های انبساطی) سعی در کاهش ارزش پول خود خواهد داشت.
در نتیجه احتمال رشد ارزش دلار آمریکا نسبت به ین ژاپن را با 5 درصد کاهش به 45 درصد و همچنین احتمال رشد ارزش ین به دلار را به 55 درصد افزایش می دهیم.
حال فرض کنید نرخ تورم ماهانه در ژاپن 0.4 باشد. سپس تحلیل ما این است: ژاپن سعی خواهد کرد ارزش پول ملی خود را افزایش دهد تا نرخ تورم را کنترل کند (با استفاده از سیاست های انقباضی).
در نتیجه، احتمال افزایش ارزش دلار آمریکا در برابر ین ژاپن را به 40 درصد کاهش می دهیم. همچنین، احتمال رشد ین ژاپن به دلار آمریکا را به 60 درصد افزایش می دهیم.
با استفاده از این شاخص و با توجه به همین نماد، بر اساس هر یک از پنج شاخص اقتصادی، هر دو ارز نماد را بررسی می کنیم. و در نهایت بر اساس بررسی های انجام شده احتمال رشد قیمت بین 0 تا 100 درصد را به دست می آوریم و امکان کاهش قیمت را نیز تعیین می کنیم. با این حال، احتمال صفر یا صد تقریبا غیرممکن است.
اگر در مورد دیدگاه ما در ارتباط با سایر شاخص ها سوالی دارید می توانید در قسمت کامنت ها از ما بپرسید.
ما به شما پاسخ خواهیم داد.
این پرسش ها و پاسخ ها به هر دوی ما کمک می کند و باعث رشد و تکامل همه ما می شود. ما سعی میکنیم این اندیکاتور را به روز نگه داریم و با منطقی ترین استدلال ها آن را بهبود ببخشیم.
نکته مهم این است که این اندیکاتور هرگز ادعا نمیکند همیشه درست است. پیش بینی این شاخص ممکن است محقق نشود یا در دوره های زمانی مختلف و طولانی تر محقق شود.
به عنوان یک واقعیت ، هر کارشناس و فعال حوزه مالی میداند که پارامترهای زیادی وجود دارد که بر قیمت تاثیر میگذارد و این اندیکاتور نمیتواند همه آنها را تحلیل کند. بنابراین به این اندیکاتور به عنوان یک ابزار کمکی نگاه کنید و از آن انتظار معجزه نداشته باشید.
سرپرست برنامه نویسان:
آقای محمد ثنائی - آقای مجتبی عسکری
توسعه دهندگان:
خانم حمیده آذری
آقای پیمان مهدوی
آقای محسن شعبانی
آقای مسلم بلاسی
آقای شاهرخ نخعی
Open, Open +/- EMA ATR Lines with LabelsThis indicator provides traders with a clear visualization of the opening price and its potential movement range for a specific timeframe, based on the Exponential Moving Average (EMA) of the Average True Range (ATR).
Features:
Opening Price Line: A green line representing the opening price for the chosen timeframe.
EMA ATR Lines:
An upper blue line, calculated as the opening price plus the EMA of the ATR.
A lower blue line, calculated as the opening price minus the EMA of the ATR.
Labels: Each line comes with a label on its right side, displaying the price level and, for the EMA ATR lines, the distance in pips from the opening price.
Custom Timeframes: Users can select their desired timeframe for calculations, making this tool versatile for different trading strategies.
Usage:
The EMA-smoothed ATR provides a measure of volatility. By plotting this value above and below the opening price, traders get a sense of potential price movement for the selected timeframe. This can be particularly useful for setting stop losses, take profit levels, or identifying breakout points.
For instance, if the price breaks above the upper EMA ATR line, it might indicate a potential upward move, especially if other market conditions align.
Customization:
Timeframe: Choose from various timeframes like 1-minute, 5-minutes, daily, weekly, and more.
ATR Length: Adjust the length of the ATR for more or less sensitivity.
This indicator is designed to offer traders a quick way to gauge potential price movement for their chosen timeframe. By combining the principles of the opening price and volatility measured by the EMA-smoothed ATR, it provides a straightforward yet powerful tool for various trading scenarios.
Liquidity Depth [Pro+]Description:
Liquidity Depth Pro+ is a trading tool with a remarkable adaptability and perfectly aligned with the intricate demands of the futures, forex, and bond markets. This indicator is based on a concept taught by the Inner Circle Trader (ICT), who explains that institutions tend to dig deeper into Liquidity Pools above highs and below lows. Specifically, ICT mentions how in Forex these Liquidity Depths are classically manifested as 10-20-30 pips respectively.
This tool allows the Analyst to adapt this concept based on their understanding of price. It delves into the essence of institutional trading, exposing deeper liquidity depth pursued by institutional giants and astute bank traders that lay further than the mere extremities of price.
CME_MINI:NQ1! Example (Tuesday):
Price raids Monday's low
Price raids Friday's low
Price digs deeper into one of Friday's Deep Liquidity Pools
Low of the Day Reversal
Note: the Depths used in this example are 30-60-90 points.
Key Features:
Versatility Across Assets: Liquidity Depth Pro+ is finely tailored for futures, forex, and bond markets, making it an all-encompassing solution suitable for a broad range of financial instruments.
Timeframe Customization: Liquidity Depth Pro+ allows users to decide Timeframe Liquidity empowering the analyst with flexibility.
Historical Pools: Choose up to the last 20 highs and lows to mark liquidity pools from the User Selected Timeframe.
Universal Trading Style: Regardless of your trading approach, be it trend-following or reversal models, this indicator embraces all styles. It offers a holistic perspective to navigating liquidity zones above highs and below lows of the chosen Timeframe.
Visual Precision: This indicator visualizes the liquidity depth with a customizable style, allowing the analyst to frame the position of deeper liquidity pools above highs and below lows.
Liquidity Table: Keep track of liquidity levels and unlock faster decision making by taking advantage of the visual Liquidity Table cues.
Adaptive Table Colors: When price is above your desired liquidity pool high, the table will match the liquidity high color to indicate a current liquidity raid or deeper pool being attacked. Vice versa, when price is below your desired liquidity pool low, the table will match the liquidity low color.
Real-Time Alerts: Save Time with live alerts that provide valuable insights into potential opportunities and liquidity purges at your desired liquidity levels.
Other Features:
Choose the Depth Type ("Auto", "Value", "Ticks", "Pips"). The “Auto” feature will select the best unit of measurement for the depths based on the current market on chart.
Choose to show up to Three Liquidity Depths.
Customize the Liquidity Line Style.
Customize the Liquidity Line Color.
Customize the Liquidity Line Width.
Customize Table Size and Location
Usage Guidance:
Add Liquidity Depth to your Tradingview chart.
Customize your desired Timeframe and Liquidity Depths to align with your personal preference.
Observe where the Liquidity Lines manifest above and below your chosen Timeframe’s highs and lows respectively, once they are raided.
Leverage this invaluable information to frame the narrative, whether you opt to pursue liquidity or capitalize on post-purge reversals.
These tools are available ONLY on the TradingView platform.
Terms and Conditions
Our charting tools are products provided for informational and educational purposes only and do not constitute financial, investment, or trading advice. Our charting tools are not designed to predict market movements or provide specific recommendations. Users should be aware that past performance is not indicative of future results and should not be relied upon for making financial decisions. By using our charting tools, the purchaser agrees that the seller and the creator are not responsible for any decisions made based on the information provided by these charting tools. The purchaser assumes full responsibility and liability for any actions taken and the consequences thereof, including any loss of money or investments that may occur as a result of using these products. Hence, by purchasing these charting tools, the customer accepts and acknowledges that the seller and the creator are not liable nor responsible for any unwanted outcome that arises from the development, the sale, or the use of these products.
Finally, the purchaser indemnifies the seller from any and all liability. If the purchaser was invited through the Friends and Family Program, they acknowledge that the provided discount code only applies to the first initial purchase of the Toodegrees Premium Suite subscription. The purchaser is therefore responsible for cancelling – or requesting to cancel – their subscription in the event that they do not wish to continue using the product at full retail price. If the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable. We hold no reimbursement, refund, or chargeback policy. Once these Terms and Conditions are accepted by the Customer, before purchase, no reimbursements, refunds or chargebacks will be provided under any circumstances.
By continuing to use these charting tools, the user acknowledges and agrees to the Terms and Conditions outlined in this legal disclaimer.
