Detailed Guide to Analyzing Limits and Deviations with MetricAlgo’s Multi-Matrix

Welcome to MetricAlgo’s exclusive tutorial on our Multi-Metric Matrix, a true revolution in financial market analysis. This sophisticated tool is designed to provide users with a deep and detailed understanding of historical probabilities and distributions of deviations from minimum, maximum, and closing limits. Every calculated data is meticulously organized, following specific metrics, with a particular focus on volatility, to accurately reflect the candle count in the filtered series.

Breakdown of Matrix Elements

The beating heart of this feature is a combination of interactive and intuitive components:

1. Metric Selector: This tool lets you choose and correlate different metrics, enabling customized and targeted analysis.
2. Dropdown Menu: This menu offers flexibility to select the type of calculation, such as probability, frequencies, or historical case distribution. It allows you to adapt the analysis to your specific needs.
3. Personalization Buttons: Adjust the size and colors of the matrix for a customized and optimal viewing experience. This feature makes it easy to adapt your analysis to your preferred methods.
4. Results Table: Displays the results of your selections in a clear and concise way, highlighting the key data.

Table Navigation

Let’s analyze the table structure:

• The Y-axis shows the percentage deviation from the opening, with the current value corresponding to each deviation. This implies that each row of the matrix represents information related to a specific range of deviation.
• The rows represent cumulative ranges of values, starting at 0% and increasing in progressive percentages up to 5%. The intervals can be adjusted to be incremental, depending on the data being analyzed, providing a diversified perspective.
  

Volatility on the X-Axis and Other Metrics

Volatility is the main feature on the X-axis, represented as a percentage, with columns that divide volatility into ranges from 0-10%, 10-20%, and so on. We are already working to integrate other clustering metrics, increasing the versatility of the matrix. Imagine the same matrix showing probabilities, frequencies, and distributions organized by opening gap ranges or other relevant metrics.

Column Title Length

Each column title provides a detailed count and percentage of historical cases where volatility, at the opening of the candle, was within a specific range. The sum of these values represents the total number of candles analyzed in the filtered series.

The Six Dynamic Visualizations of the Matrix

The Multi-Metric Matrix offers six distinct visualization modes, each providing a unique perspective on market dynamics:

• The probability that a deviation will not be reached.
• The probability that a deviation will be reached
• Probability distribution
• The number of historical cases where the deviation was not reached
• The number of historical cases where a deviation was reached
• Limits distribution

  

Data Visualization Exploration

Each visualization provides a clear and accurate picture of probabilities and historical cases, helping you to better understand market movements. For example, the visualization of the probabilities that a limit will not be reached provides incremental percentages based on the total number of cases for each column. This helps you to quickly evaluate the probability of a particular deviation from occurring or not.

Matrix Interaction and Colors

Hovering over each cell reveals frequency or probability values, providing additional depth of analysis. Colors, which you can customize, play a crucial role in representing the progression of data, with options to invert the color scale or add an exotic touch.

Conclusion

This tutorial is designed to walk you through every aspect of MetricAlgo’s Multi-Metric Matrix, highlighting its unique features and the value it can bring to your market analysis. We hope that this guide helps you to make the most of this advanced tool and contributes to enhancing your trading strategy.