Data from data
The "Data from Data" indicator, developed by OmegaTools, is a sophisticated and versatile tool designed to offer a nuanced analysis of various market dynamics, catering to traders and investors seeking a comprehensive understanding of price movements considering a large amount of data and variables.
The uses of this indicator are nonconventional. You can use the indicator as a stand-alone tool on the chart, hiding the current symbol price data, to be able to analyze the price action with the Semaphore visualization method, you can also hide the indicator and choose from your favorite indicators and oscillator one of the data output as a source to have additional insight on the asset.
The last use of this indicator, which depends on the X Value that you set in the settings, is to have a possible scenario for the future outcomes of the markets. Remember that there is no tool that can really predict what the market will do in the future, this tool applies a large amount of formulas to use past prices as an indication that aims to be as close as possible to the future prices. The X Value not only changes the lookback of the formulas but also changes the number of future scenarios that the indicator will plot on the chart.
Key Features:
1. Rate of Change Analysis:
The indicator evaluates the rate of change variations in closing prices, providing insights into the current rate of change and expected rate of change variation.
2. Momentum Analysis:
Momentum is analyzed through calculations involving simple moving averages, offering expected values derived from momentum and momentum variation.
3. High/Low Variation:
The expected market behavior is assessed based on the average variation between high and low prices, contributing to a more holistic analysis.
4. Liquidity Targets:
Liquidity targets can be found by analyzing the highs and lows in the direction of the current fair price.
5. Regression Sequence:
Linear regression analysis is applied to closing prices, assessing momentum and providing expected values based on regression sequences.
6. Volume Presence:
The indicator evaluates the Rate of Change (ROC) by volume presence, offering insights into price movements influenced by trading volume.
7. Liquidity Grabs:
Expected market behavior is determined based on liquidity grabs, considering both current and historical price levels.
8. Fair Value Analysis:
Expected values are derived from fair value closes and fair value highs and lows, contributing to a more nuanced analysis of market conditions.
9. STT (Sequential Trend Test):
The Sequential Trend Test is employed to analyze market trends, providing expected values for a more informed decision-making process.
Visualization:
The indicator shows a "Semaphore" on the chart, visually representing all of the data extrapolated from the script. The visualization can be more minimalistic or more complex, to let the user decide that, in the settings, it's possible to decide if to show all of the data or only the average.
Additionally, the user can choose to display bars on the chart, that visualize the standard high and low of the price data, with the difference between the expected forecasted value and the actual closing price.
My suggestion is to try to change the colors of the data to fit best your eye and the data that you find more useful, and also to try to change some parameters from circle to line as a visualization method to catch with more ease some price patterns.
Error Analysis:
The indicator provides a detailed error analysis, including historical error, average error, and present error. This information is presented in a user-friendly table for quick reference. This table can be used to analyze the margin of error of the expected future price.
The uses of this indicator are nonconventional. You can use the indicator as a stand-alone tool on the chart, hiding the current symbol price data, to be able to analyze the price action with the Semaphore visualization method, you can also hide the indicator and choose from your favorite indicators and oscillator one of the data output as a source to have additional insight on the asset.
The last use of this indicator, which depends on the X Value that you set in the settings, is to have a possible scenario for the future outcomes of the markets. Remember that there is no tool that can really predict what the market will do in the future, this tool applies a large amount of formulas to use past prices as an indication that aims to be as close as possible to the future prices. The X Value not only changes the lookback of the formulas but also changes the number of future scenarios that the indicator will plot on the chart.
Key Features:
1. Rate of Change Analysis:
The indicator evaluates the rate of change variations in closing prices, providing insights into the current rate of change and expected rate of change variation.
2. Momentum Analysis:
Momentum is analyzed through calculations involving simple moving averages, offering expected values derived from momentum and momentum variation.
3. High/Low Variation:
The expected market behavior is assessed based on the average variation between high and low prices, contributing to a more holistic analysis.
4. Liquidity Targets:
Liquidity targets can be found by analyzing the highs and lows in the direction of the current fair price.
5. Regression Sequence:
Linear regression analysis is applied to closing prices, assessing momentum and providing expected values based on regression sequences.
6. Volume Presence:
The indicator evaluates the Rate of Change (ROC) by volume presence, offering insights into price movements influenced by trading volume.
7. Liquidity Grabs:
Expected market behavior is determined based on liquidity grabs, considering both current and historical price levels.
8. Fair Value Analysis:
Expected values are derived from fair value closes and fair value highs and lows, contributing to a more nuanced analysis of market conditions.
9. STT (Sequential Trend Test):
The Sequential Trend Test is employed to analyze market trends, providing expected values for a more informed decision-making process.
Visualization:
The indicator shows a "Semaphore" on the chart, visually representing all of the data extrapolated from the script. The visualization can be more minimalistic or more complex, to let the user decide that, in the settings, it's possible to decide if to show all of the data or only the average.
Additionally, the user can choose to display bars on the chart, that visualize the standard high and low of the price data, with the difference between the expected forecasted value and the actual closing price.
My suggestion is to try to change the colors of the data to fit best your eye and the data that you find more useful, and also to try to change some parameters from circle to line as a visualization method to catch with more ease some price patterns.
Error Analysis:
The indicator provides a detailed error analysis, including historical error, average error, and present error. This information is presented in a user-friendly table for quick reference. This table can be used to analyze the margin of error of the expected future price.
릴리즈 노트:
Table Update: Introducing the Average Error/Range Ratio, a new metric that signifies the proportion of the average error in relation to the average range. Expressed as a percentage, this ratio provides valuable insights into the magnitude of the average error relative to the overall price range.
릴리즈 노트:
Table Update: Introducing the "Right Expected Direction," a novel parameter revealing the frequency with which the indicator's expected value accurately predicted the direction of the corresponding period. This insightful metric provides valuable information on the indicator's historical directional accuracy.