{"id":3011,"date":"2023-09-22T14:59:44","date_gmt":"2023-09-22T14:59:44","guid":{"rendered":"https:\/\/metricalgo.com\/funzionalita\/limits-analysis-grouped-by-metric\/"},"modified":"2024-01-09T17:10:04","modified_gmt":"2024-01-09T16:10:04","slug":"limits-analysis-grouped-by-metric","status":"publish","type":"funzionalita","link":"https:\/\/metricalgo.com\/en\/feature\/limits-analysis-grouped-by-metric\/","title":{"rendered":"Grouped limits analysis by metric"},"content":{"rendered":"

Our “Grouped Analysis” feature allows you to look at market data from different perspectives.
\nNo matter if you want to see how volatility affects your trades or how results vary across different months of the year, we have the tools you need.<\/p>\n

The feature offers two types of charts: the radar chart<\/strong> for a circular view and the combined histogram chart.<\/strong><\/p>\n

These graphic indicators display the average of the minimum and maximum deviations (limits) and of the positive and negative closures, grouped by a specific metric such as volatility, month, opening gap, etc.
\nThe “combined histogram” chart adds the frequency line and indicates in which metric groups the most numerous events occur and vice versa. The closing line shows us the deviation between positive and negative closings, indicating the respective trend.<\/p>\n

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This graphical representation is particularly useful because it allows for a concise determination of whether price movements are aligned with typical market behaviors or if we are facing an atypical day.<\/p>\n

In practice, it’s like having a radar and a magnifying glass all in one, making your trading decisions more informed than ever.<\/p>\n

Here are some examples of why grouped visualization is useful for refining the main filter.
\n<\/strong><\/h4>\n

Example 1:<\/strong> Groupings by volatility.<\/span> Consider the analysis of a security and decide to filter the entire series to observe the grouped charts, in order to obtain a comprehensive overview. Examining the chart grouped by volatility, one can notice a significant reduction in occurrences (represented by the purple line) starting from a volatility of 70%.<\/p>\n

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If the intent is to develop an effective strategy during periods of ‘normal’ volatility, that is, when volatility is not excessive, we might consider the idea of refiltering the series, excluding periods with volatility above 52%. This filter will significantly affect the calculations of the limits, as we would be excluding a substantial part of the data.<\/p>\n

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However, the new graph shows that, after applying the filter, the most significant movement is around 2%, whereas previously there were cases exceeding 4%.<\/p>\n

As demonstrated in this example, charts grouped by volatility are extremely useful for understanding, in general terms, the type of data we are filtering. Depending on our strategy, we can choose whether to analyze the entire series, only periods with lower volatility, or exclusively those with high volatility.<\/p>\n

Example 2:<\/strong> Groupings by day of the week<\/strong> Imagine, for example, filtering a series to see how security historically behaves when the market opens positively in a particular month of the year. Once you filter the data set, this indicator shows you an interesting statistic in the grouping by day of the week.<\/p>\n

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Specifically, it shows you that on Thursdays the volatility is always higher and that the related limits are more affected than on other days. This type of analysis could lead you to further filter the series by eliminating Thursdays and then compare the results to make your decisions in a more informed and conscious manner.<\/p>\n

Example 3: Groupings by months<\/strong> Let’s consider the SPX on a monthly timeframe and filter a period of 15 years.<\/p>\n

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The image highlights that there are distinct months, such as March and October, in which the volatility is significantly higher compared to other periods of the year. This information provides us with a solid basis on which to decide which months to include or exclude for a more targeted analysis.<\/p>\n

Suppose we consider opening a position in the month of October and notice that in this month the volatility is high compared to others. We might then choose to exclude months with lower volatility, such as February, April, June, and August, focusing exclusively on the months that exhibit behavior more similar to the period we are analyzing.<\/p>\n

In addition, we can leverage the information provided by the graphical indicators to determine whether the market behavior on a specific day, week, or month aligns with usual standards. For example, if we are operating in November and observe that the volatility fluctuations are much higher than the historical highs\/lows, we might deduce that this month deviates from the standard trends. This gives us an overview that can be further analyzed with additional filters to confirm or refute our initial observations.<\/p>\n

This methodical and data-driven approach allows us to make more informed and strategic decisions based on the volatility and historical movements of the market.<\/p>\n","protected":false},"featured_media":0,"template":"","stato-elemento":[44],"class_list":["post-3011","funzionalita","type-funzionalita","status-publish","hentry","stato-elemento-released"],"acf":[],"_links":{"self":[{"href":"https:\/\/metricalgo.com\/en\/wp-json\/wp\/v2\/funzionalita\/3011","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/metricalgo.com\/en\/wp-json\/wp\/v2\/funzionalita"}],"about":[{"href":"https:\/\/metricalgo.com\/en\/wp-json\/wp\/v2\/types\/funzionalita"}],"wp:attachment":[{"href":"https:\/\/metricalgo.com\/en\/wp-json\/wp\/v2\/media?parent=3011"}],"wp:term":[{"taxonomy":"stato-elemento","embeddable":true,"href":"https:\/\/metricalgo.com\/en\/wp-json\/wp\/v2\/stato-elemento?post=3011"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}