With hedge funds failing for years in their struggle to generate alpha in a time when legal insider trading in the form of "expert networks" has long been eliminated following the infamous SAC crackdown, and a 3% drop in the market is enough to cause a shockwave ripple around the globe as central bankers have been tasked with avoiding any declines in capital markets - thus eliminating the need to "hedge" - one increasingly popular approach to trading that has captivated asset managers has become machine learning, or the ability to tap huge data sets, such as social media postings in ways that no mere human could.
Yet, despite the enormous potential, its record remains mixed. According to Bloomberg, the Eurekahedge AI Hedge Fund Index, which tracks the returns of 13 hedge funds that use machine learning, has gained only 7% a year for the past five years, while the S&P 500 returned 13% annually. After peaking in January, in 2018 the Eurekahedge benchmark dropped 5% through September.
What is the reason behind this disappointing performance for a strategy for which so many hedge funds had such great expectations? Simple: machines programmed to find a pattern within the noise of the market will always do so... even when there is no actual pattern at all.
OH THOSE MACHINES LOL,,,,,,,,,
http://www.zerohedge.com/news/2018-10-13/perils-machine-learning-algos-one-pin-drop-can-make-you-lose-20-years-returns?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+zerohedge%2Ffeed+%28zero+hedge+-+on+a+long+enough+timeline%2C+the+survival+rate+for+everyone+drops+to+zero%29
Realist - Everybody in America is soft, and hates conflict. The cure for this, both in politics and social life, is the same -- hardihood. Give them raw truth.
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