{"id":45,"date":"2022-04-03T22:34:12","date_gmt":"2022-04-03T22:34:12","guid":{"rendered":"https:\/\/pfr.com\/WP1\/?page_id=45"},"modified":"2022-11-08T21:06:06","modified_gmt":"2022-11-08T21:06:06","slug":"scale-invariance","status":"publish","type":"page","link":"https:\/\/pfr.com\/WP1\/our-technology\/scale-invariance\/","title":{"rendered":"Scale Invariance &#038; Chaos Theory"},"content":{"rendered":"\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:60%\">\n<p>R.N. Elliott observed that financial series appear to have the same \u201clook\u201d on many different time scales. Elliott published what he called the <strong>\u201cWave Principle\u201d<\/strong> in 1938. His modeled financial series is comprised of zigzags that are nested within each other at smaller and smaller scales. Market technicians still make wide use of his work.<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:40%\">\n<figure class=\"wp-block-image size-large\"><img data-recalc-dims=\"1\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/pfr.com\/images\/elliott.png?w=900&#038;ssl=1\" alt=\"\"\/><\/figure>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:60%\">\n<p>Scientists now understand this phenomenon as <strong>scale invariance<\/strong>. Scale invariance (also known as self-similarity) is defined as a feature of objects or laws that do not change if length scales are multiplied by a common factor. Benoit Mandelbrot called these objects <strong><a rel=\"noreferrer noopener\" href=\"https:\/\/en.wikipedia.org\/wiki\/Fractal\" target=\"_blank\">fractals<\/a> <\/strong>because they are partially characterized by a real-numbered (decimal number) fractional dimension. The presence of scale invariance means that the object has been produced by feedback process and is governed by the science of feedback systems known as <strong>Chaos theory<\/strong> (which in turn is a subset of Complexity theory).  <\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:40%\">\n<figure class=\"wp-block-image size-large\"><img data-recalc-dims=\"1\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/pfr.com\/images\/H_fractal3.gif?w=900&#038;ssl=1\" alt=\"\"\/><\/figure>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p>We now know that markets are not these perfect real-numbered fractals of Mandelbrot or Elliott. Financial price series often appear to have different degrees of smoothness, or fractal dimension, on different scales at the same time. This inconsistency led to a startling discovery. Our research, as well as that of fellow geophysicist Didier Sornette, confirms that financial series are complex-numbered fractals, that by definition exhibit <strong>discrete scale-invariance<\/strong> and converging <strong>log-periodic cycles<\/strong> on approach to critical trend-change points.<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/pfr.com\/images\/fbmh.bmp\" alt=\"\" width=\"290\" height=\"240\"\/><\/figure>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:60%\">\n<p>Our research has also shown that markets repeatedly self-organize to these critical points. By detecting log-periodic cycling at extreme high or low <a rel=\"noreferrer noopener\" href=\"https:\/\/en.wikipedia.org\/wiki\/Hurst_exponent\" target=\"_blank\">Hursts<\/a> on multiple scales, these predictive points can be found with a high degree of accuracy. This result has the side benefit of explaining the somewhat mysterious use of Fibonacci (1, 1, 2, 3, 5, 8, 13, 21, \u2026) and Gann (1, 2, 4, 8, 16, 32, \u2026) number sequences by market technicians. These number series are both log periodic.<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:40%\">\n<figure class=\"wp-block-image size-full\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" width=\"772\" height=\"499\" src=\"https:\/\/i0.wp.com\/pfr.com\/WP1\/wp-content\/uploads\/2022\/10\/lp.jpg?resize=772%2C499&#038;ssl=1\" alt=\"\" class=\"wp-image-411\" srcset=\"https:\/\/i0.wp.com\/pfr.com\/WP1\/wp-content\/uploads\/2022\/10\/lp.jpg?w=772&amp;ssl=1 772w, https:\/\/i0.wp.com\/pfr.com\/WP1\/wp-content\/uploads\/2022\/10\/lp.jpg?resize=300%2C194&amp;ssl=1 300w, https:\/\/i0.wp.com\/pfr.com\/WP1\/wp-content\/uploads\/2022\/10\/lp.jpg?resize=768%2C496&amp;ssl=1 768w\" sizes=\"auto, (max-width: 772px) 100vw, 772px\" \/><\/figure>\n<\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Log Periodicity in Action<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/i0.wp.com\/pfr.com\/WP1\/wp-content\/uploads\/2022\/10\/image70.gif\" alt=\"\"\/><figcaption class=\"wp-element-caption\">The Effect of Cycle Magnitude on the Critical Point Model<\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/i0.wp.com\/pfr.com\/WP1\/wp-content\/uploads\/2022\/10\/image71.gif\" alt=\"\"\/><figcaption class=\"wp-element-caption\">The Effect of Phase on the Critical Point Model<\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/i0.wp.com\/pfr.com\/WP1\/wp-content\/uploads\/2022\/10\/image72.gif\" alt=\"\"\/><figcaption class=\"wp-element-caption\">The Effect of Wavelength on the Critical Point Model<\/figcaption><\/figure>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-large\"><img decoding=\"async\" src=\"https:\/\/i0.wp.com\/pfr.com\/WP1\/wp-content\/uploads\/2022\/10\/image73.gif\" alt=\"\"\/><figcaption class=\"wp-element-caption\">The Effect of the Post-Critical Power-Law Exponent on the Critical Point Model<\/figcaption><\/figure>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>R.N. Elliott observed that financial series appear to have the same \u201clook\u201d on many different time scales. Elliott published what he called the \u201cWave Principle\u201d in 1938. His modeled financial [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":41,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-45","page","type-page","status-publish","hentry"],"jetpack-related-posts":[],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/pfr.com\/WP1\/wp-json\/wp\/v2\/pages\/45","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pfr.com\/WP1\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/pfr.com\/WP1\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/pfr.com\/WP1\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/pfr.com\/WP1\/wp-json\/wp\/v2\/comments?post=45"}],"version-history":[{"count":29,"href":"https:\/\/pfr.com\/WP1\/wp-json\/wp\/v2\/pages\/45\/revisions"}],"predecessor-version":[{"id":612,"href":"https:\/\/pfr.com\/WP1\/wp-json\/wp\/v2\/pages\/45\/revisions\/612"}],"up":[{"embeddable":true,"href":"https:\/\/pfr.com\/WP1\/wp-json\/wp\/v2\/pages\/41"}],"wp:attachment":[{"href":"https:\/\/pfr.com\/WP1\/wp-json\/wp\/v2\/media?parent=45"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}