Financial Machine Learning ought to be named its own discipline because of stark contrasts to traditional applications by MeThe most exhilarating and exciting application of machine learning (ML) is in finance. It is easy to value a production model (you see your model\u2019s performance the moment you execute a strategy). It is also the most challenging application of ML I know of.The large majority of popular ML articles, blogs, YouTube videos, or white-papers are focused on, what I call, traditional applications. In this article, I bucket traditional ML applications into a camp when researchers assume normality, where observations are independent, and when the target does not structurally change over time.The purpose of calling out a subsection of ML is to magnify and focus the attention of researchers and practitioners \u2014 for testing, documentation, and to solidify best practices.For your interest, I am not the first practitioner of Financial ML to propose a demarcation from traditional applications: see Marcos Lopez de Prado\u2019s recent book, here.Understanding traditional MLThe most crucial distinction between traditional ML and financial ML is the classical statistical IID assumption. This assumption was etched into my brain during my first statistics course. Although important in traditional applications, it is an unrealistic assumption to uphold in finance.When this assumption is taken, data are assumed to be distributed in a Gaussian-like manner. Observations or participants are assumed to be independent of one another. Both cannot be assumed in finance because observations (e.g., days in a series) are not independent (i.e., today\u2019s level is dependent on yesterday\u2019s level) and, due to trend and regime shifts, data are not normally distributed.Structural breaks are abnormal, and sometimes random, shifts or changes in a time series structure.Imagine that your machine learning target shifts in behavior, jumps to never before seen levels, or changes dramatically because\u2026<\/p>","protected":false},"excerpt":{"rendered":"
Financial Machine Learning ought to be named its own discipline because of stark contrasts to traditional applications by MeThe most exhilarating and exciting application of machine [\u2026]<\/span><\/p>","protected":false},"author":0,"featured_media":2414,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[35],"tags":[],"_links":{"self":[{"href":"https:\/\/afluxcoin.com\/zh\/wp-json\/wp\/v2\/posts\/2413"}],"collection":[{"href":"https:\/\/afluxcoin.com\/zh\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/afluxcoin.com\/zh\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/afluxcoin.com\/zh\/wp-json\/wp\/v2\/comments?post=2413"}],"version-history":[{"count":0,"href":"https:\/\/afluxcoin.com\/zh\/wp-json\/wp\/v2\/posts\/2413\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/afluxcoin.com\/zh\/wp-json\/wp\/v2\/media\/2414"}],"wp:attachment":[{"href":"https:\/\/afluxcoin.com\/zh\/wp-json\/wp\/v2\/media?parent=2413"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/afluxcoin.com\/zh\/wp-json\/wp\/v2\/categories?post=2413"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/afluxcoin.com\/zh\/wp-json\/wp\/v2\/tags?post=2413"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}