{"id":8501,"date":"2022-09-16T12:01:20","date_gmt":"2022-09-16T12:01:20","guid":{"rendered":"https:\/\/www.cuistar.com\/?p=8501"},"modified":"2023-05-10T20:08:56","modified_gmt":"2023-05-10T20:08:56","slug":"statistically-sound-machine-learning-for","status":"publish","type":"post","link":"https:\/\/www.cuistar.com\/my\/statistically-sound-machine-learning-for\/","title":{"rendered":"Statistically Sound Machine Learning For Algorithmic Trading Of Financial Instruments Developing Predictive Model Based Trading Systems Using Tssb Pdf"},"content":{"rendered":"<div id=\"toc\" style=\"background: #f9f9f9;border: 1px solid #aaa;display: table;margin-bottom: 1em;padding: 1em;width: 350px;\">\n<p class=\"toctitle\" style=\"font-weight: 700;text-align: center;\">Contents:<\/p>\n<ul class=\"toc_list\">\n<li><a href=\"#toc-0\">Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments<\/a><\/li>\n<li><a href=\"#toc-1\">Developing Predictive-Model-Based Trading Systems Using TSSB<\/a><\/li>\n<li><a href=\"#toc-2\">Share this document<\/a><\/li>\n<li><a href=\"#toc-3\">Book Details<\/a><\/li>\n<\/ul>\n<\/div>\n<p><img decoding=\"async\" loading=\"lazy\" class='wp-post-image' style='display: block;margin-left:auto;margin-right:auto;' src=\"https:\/\/forexarena.net\/wp-content\/uploads\/2020\/07\/BlackBull-Markets-Review-1280x720-1-275x145.jpg\" width=\"303px\" alt=\"statistically sound machine learning for algorithmic trading of financial instruments\"\/><br \/>\n<img decoding=\"async\" loading=\"lazy\" class='wp-post-image' style='display: block;margin-left:auto;margin-right:auto;' src=\"https:\/\/forexarena.net\/wp-content\/uploads\/2021\/04\/search.svg\" width=\"308px\" alt=\"statistically sound machine learning for algorithmic trading of financial instruments\"\/><\/p>\n<p>The process may takea few minutes but once  it finishes a file will be downloadable from your browser. You may continue to  browse the DL while <a href=\"https:\/\/forexarena.net\/\">https:\/\/forexarena.net\/<\/a> the export process is in progress. Please download or close your previous search result export first before starting a new bulk export.<\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src=\"data:image\/jpeg;base64,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\" width=\"309px\" alt=\"statistically sound machine learning for algorithmic trading of financial instruments\"\/><\/p>\n<p>David Aronson is a pioneer in machine learning and nonlinear trading system development and signal boosting\/filtering. He has worked in this field since 1979 and has been a Chartered Market Technician certified by The Market Technicians Association since 1992. He was an adjunct professor of finance, and regularly taught to MBA and financial engineering students a graduate-level course in technical analysis, data mining and predictive analytics.<\/p>\n<h2 id=\"toc-0\">Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments<\/h2>\n<p>His ground-breaking book &#8220;Evidence-Based Technical Analysis&#8221; was published by John Wiley &#038; Sons 2006. Second, this book shows how the free program TSSB (Trading System Synthesis &#038; Boosting) can be used to develop and test trading systems. The machine learning and statistical algorithms available in TSSB go far beyond those available in other off-the-shelf development software. First, it teaches the importance of using sophisticated yet accessible statistical methods to evaluate a trading system before it is put to real-world use. In order to accommodate readers having limited mathematical background, these techniques are illustrated with step-by-step examples using actual market data, and all examples are explained in plain language. \u2b50 Better System Trader EP028 &#8211; David Aronson shares research into indicators that identify Bull and Bear markets.<\/p>\n<ul>\n<li>Second, this book shows how the free program TSSB (Trading System Synthesis &#038; Boosting) can be used to develop and test trading systems.<\/li>\n<li>&#8220;About this title&#8221; may belong to another edition of this title.<\/li>\n<li>There was a problem preparing your codespace, please try again.<\/li>\n<li>\u2b50 Better System Trader EP028 &#8211; David Aronson shares research into indicators that identify Bull and Bear markets.<\/li>\n<li>Please download or close your previous search result export first before starting a new bulk export.<\/li>\n<\/ul>\n<p>&#8220;About this title&#8221; may belong to another edition of this title. Quant\/Algorithm trading resources with an emphasis on Machine Learning. There was a problem preparing your codespace, please try again. This commit does not belong to any branch <a href=\"https:\/\/forexarena.net\/statistically-sound-machine-learning-for-algorithmic-trading-of-financial-instruments\/\">statistically sound machine learning for algorithmic trading of financial instruments<\/a> on this repository, and may belong to a fork outside of the repository. When you buy books using these links the Internet Archive may earn a small commission. By clicking download,a status dialog will open to start the export process.<\/p>","protected":false},"excerpt":{"rendered":"<p>Contents: Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments Developing Predictive-Model-Based Trading Systems Using TSSB Share this document Book Details The process may takea few minutes but once it finishes a file will be downloadable from your browser. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","footnotes":""},"categories":[68],"tags":[],"class_list":["post-8501","post","type-post","status-publish","format-standard","hentry","category-forex-trading"],"_links":{"self":[{"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/posts\/8501","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/comments?post=8501"}],"version-history":[{"count":1,"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/posts\/8501\/revisions"}],"predecessor-version":[{"id":8502,"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/posts\/8501\/revisions\/8502"}],"wp:attachment":[{"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/media?parent=8501"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/categories?post=8501"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cuistar.com\/my\/wp-json\/wp\/v2\/tags?post=8501"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}