Indicator Installation
Interface
Indicator Usage
Machine Learning Settings
Interface Settings
Additional Settings
INDICATOR INSTALLATION
After payment, we will connect indicators to your TradingView account within 24 hours (usually 1-2 hours).
If you don't have a TradingView account yet, register one on the website or mobile app.
Installation on PC
1. Press the button “Indicators” to open the menu “Indicators, Metrics & Strategies”.
2. Go to the section “Invite-only scripts”. If you haven't used invite-only scripts before, sometimes you need to reload TradingView site for this section to appear.
3. Select indicator TradeINEX: AI Forecast.
Installation on a mobile device
1. Press the button “+” to open the menu “Add”.
2. Press the button “Indicators” to open the menu “Indicators, Metrics & Strategies”.
3. Go to the section “Invite-only scripts”. If you haven't used invite-only scripts before, sometimes you need to reload the TradingView app for this section to appear.
4. Select indicator TradeINEX: AI Forecast.
USER INTERFACE
Elements of the indicator interface on the chart:
1. Price Forecast - trajectory of the estimated price movement, based on reference points, in the time space of a given forecast horizon.
2. Price Channel - consists of two lines: the upper and lower boundaries of the probable price fluctuations within the channel.
3. Alternative Variants - alternative variants of the estimated price movement, based on reference points, in the time space of a given forecast horizon.
4. Linear Regression - shows the general direction of the predicted price movement and its fluctuations within the channel by Fibonacci levels.
5. Volatility Channel - shows average market volatility based on historical data.
6. Pivot Points - points on the price chart where local trends change. Pivot points are useful for identifying significant support and resistance levels and for identifying bearish or bullish market sentiment.
7. Fixed Range - shows the upper and lower limits within the monthly price fluctuation range.
8. Market Structure - visualization of the calculation of the price movement structure based on historical data.
9. Statistics - artificial intelligence statistics table.
The indicator interface is fully customizable. You can change the visibility, size, color or style of any element. The indicator works with both light and dark themes of the TradingView platform and on any device.
Visualization of the price movement forecast is presented in 4 options:
Forecast Channel - displays the main line of the price movement forecast, as well as the upper and lower limits of the probable price fluctuations within the channel.
Volatility Range - displays the forecast of volatility of the predicted price movement, and also colors downward and upward local trends in red and green, respectively.
Alternative Scenarios - displays a blue line of the most reliable price movement forecast, as well as two more alternative scenarios in the form of a red and green lines.
Average Forecast - displays a channel of the average value between three scenarios of forecast price movement.
HOW TO USE THE INDICATOR
The TradeINEX: AI Forecast indicator is designed to predict scenarios future price movements using machine learning and predictive modeling methods within a given forecast horizon. And also for modeling market time cycles and seasonal fluctuations.
The indicator's artificial intelligence analyzes a huge stream of chart data, various indicators and on-chain metrics to build a market structure model and predict its behavior in the future.
As new market data is released, the forecast will be automatically updated in real time.
The forecast may differ in time intervals, the price movement may occur with a slight delay or advance relative to the forecast.
GENERAL RECOMMENDATIONS
IMPORTANT: Price forecasts are not guidelines for buying or selling any assets or trading recommendations! Forecasts are informative only and their fulfillment is not guaranteed.
- Machine learning requires a sufficient amount of historical data on the chart: a minimum of 1000 bars.
- Recommended timeframes: from 1H to 1W.
In automatic mode, the length of the forecast horizon can affect the accuracy of the forecast:
The longer the forecast horizon, the greater the deviation could be at the end of the forecast.
The shorter the forecast horizon, the more often the forecast can be adjusted as new data becomes available.
Always consider risk management in your trading strategy and don’t forget to set stop losses!
FORECAST PROBABILITY
Forecasting the further price movement is working with the probabilities of working out a particular scenario. Therefore, when making your trading decisions, it is necessary to take into account additional factors and other indicators of our trading and analytical complex.
How to increase the probability of a forecast?
- In the visualization mode of several price movement scenarios at once (Variance), the probability of a forecast increases if the trajectories of these scenarios match.
- If forecasts on different timeframes match, this also increases the likelihood of their fulfillment.
- If the trajectories of forecasts from different data channels match, the likelihood of their fulfillment increases significantly.
I. AUTOMATIC MODE
In this mode, the artificial intelligence of the indicator will work on the principle of self-learning, analyzing various market data and automatically making forecasts for further price movements in a given time range. If new market data appears, the forecast will be automatically adjusted in real time.
Learning Mode - in AUTO mode AI automatically analyzes and predicts future price movements.
Forecast Horizon - set the forecast horizon. If the value is too high, the forecast accuracy may decrease.
Historical Buffer - the depth of machine learning on historical data. Increasing this parameter, in some cases, can improve the accuracy of the forecast, but at the same time, it can lead to taking into account data that is less relevant at the moment.
Data Cluster Analysis - select the type of market data for cluster analysis. When set to CUMULATIVE, all data clusters will be used simultaneously. In the Data Clusters Weight section, you can configure the degree of importance of each of the data clusters in this mode.
Data Optimization - by increasing this parameter, optimize the data flow to improve indicator performance at high values of the Historical Buffer and Forecast Horizon parameters. Decreasing this parameter can improve forecast accuracy.
II. MARKET CYCLE FORECASTING MODE
In this mode, the artificial intelligence will help simulate the next market cycle of rise and fall, for assets that are characterized by market cycles or seasonal fluctuations.
To simulate and forecast market cycles with a period of several years (for example Bitcoin), it is recommended to use a 1W time frame
To simulate and forecast the next Bitcoin cycle, it is recommended to use a chart with the ticker BTCUSD - BITCOIN ALL TIME HISTORY INDEX, as it has the greatest depth of historical data.
INDICATOR SETTINGS
MACHINE LEARNING
AUTO - in this mode, the artificial intelligence works on the principle of self-learning, collecting and analyzing various market data. Based on them, it will simulate the current market structure and automatically make forecasts for further price movements in a given range. If new market data appears, the forecast will be automatically adjusted in real time.
CYCLE - In this mode, the artificial intelligence of the indicator can simulate multi-year market cycles or seasonal price fluctuations.
Forecast Visualisation - visualization of the price movement forecast is presented in 4 options:
Forecast Channel - displays the main line of the price movement forecast, as well as the upper and lower limits of the probable price fluctuations within the channel.
Volatility Range - displays the forecast of volatility of the predicted price movement, and also colors downward and upward local trends in red and green, respectively.
Alternative Scenarios - displays a blue line of the most reliable price movement forecast, as well as two more alternative scenarios in the form of a red and green lines.
Average Forecast - displays a channel of the average value between three scenarios of forecast price movement.
Historical Buffer - the depth of machine learning on historical data. Increasing this parameter, in some cases, can improve the accuracy of the forecast, but at the same time, it can lead to taking into account data that is less relevant at the moment.
DATA CLUSTER ANALYSIS
Options for selecting data clusters for market analysis:
CUMULATIVE - all data clusters will be used simultaneously. In the Data Clusters Weight section, you can configure the degree of importance of each of the data clusters in this mode.
Raw Data - analysis of raw chart data to identify the structure of time series.
Patterns Analysis - analysis of graphic patterns to identify regularities.
Volumetric Analysis - volumetric data analysis to simulate market structure.
Oscillators Data - analysis of the type of data that is periodically repeated over time.
Trend Analysis - data of trend market analysis to search for reversal formations.
Onchain Metrics - analysis of blockchain data to predict the behavior of market makers.
PREDICTIVE MODELING
This option specifies a predictive modeling method:
Adaptive - adaptive method, for AI AUTO mode or modeling seasonal fluctuations with approximately the same amplitude.
Progressive - a progressive method for modeling multi-year market cycles with varying amplitude of fluctuations.
Data Optimization - by increasing this parameter, optimize the data flow to improve indicator performance at high values of the Historical Buffer and Forecast Horizon parameters. Decreasing this parameter can improve forecast accuracy.
Output Sampling - optimization of the graphical display of the forecast by reducing the detail of the price movement trajectory lines. This setting is required because the TradingView platform has a limit on the total number of graphical elements on a single chart.
DATA CLUSTERS SETTINGS
This section of the menu contains a list of data clusters that are used in the combined mode - CUMULATIVE: Raw Data, Patterns, Volumetric, Oscillators, Trend Analysis and Onchain Metrics, the meanings of which are described above.
You can adjust the influence of each of these data clusters by changing the parameter from 0 to 1.0, or by unchecking/checking the box next to it.
TIME SETTINGS
The following parameters set the start date for forecasting. This is necessary to predict market cycles and seasonal fluctuations.
Starting Time - sets the start time of forecasting in bars, when the ‘Is Now’ checkbox is checked.
Start Date - sets the calendar date for the start of forecasting, with the ‘Is Now’ checkbox unchecked.
INTERFACE SETTINGS
Show Forecast - display a forecast of further price movement on the chart.
Show Volatility - display historical market volatility channel on the chart.
Show Regression - display linear regression channel with Fibonacci levels on the chart.
Show Pivot Points - display turning points of local trends on the chart.
Show Market Structure - display visualization of market structure on the chart.
Show Range Levels - display levels of a fixed range of price movement.
Forecast Style - style of displaying the trajectory of the predicted price movement: solid line, dotted line, dotted line. You can also select the thickness of the lines.
Forecast Colors - colors of display of forecast lines, main and alternative scenarios.
Statistics Table - in the first column there are options for placing the statistics table on the screen. In the second column is the size of the text.
Statistics Text Color - statistics table text color.
Statistics Border Color - color of the statistics table borders.
Statistics Background Color - statistics table background color.
ADDITIONAL SETTINGS
Smoothing - smoothing of small fluctuations in the price chart.
Approximation - choosing an approximation method to optimize the data flow.
Volatility Calculation - choosing a method for calculating market volatility: initial volatility or average volatility.