The Great Melt-Up Melt Down

By David Haggith – Re-Blogged From Silver Phoenix

That didn’t take long. Just a month ago, I wrote, “Stock Market More Overpriced And Perilous Than Anytime In History  ,” stating that the market was poised for a big fall because “some of the market’s most fundamental valuation metrics are now printing at levels never seen before…. This market is tripping on some pricy hallucinogens.”

.And here we are! A single black swan has knocked the legs out from under the bull. It’s not a full-blown correction yet (requiring indices fall by, at least, 10%) or a crash (20% or more), though it looks like it could hit that mark by the end of today. That would be a full correction in just four days.

The market has fallen off such a steep cliff to where MarketWatch reported that Monday and Tuesday teamed up to be the largest two-day point drop in Dow history! (Some other sites have said it is the largest since the big drop I predicted for the start of 2018 when the market experienced its largest one-day point drop in history.)

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U.S. Health Officials Urge Americans to Prepare for Spread of Coronavirus

The U.S. Centers for Disease Control and Prevention (CDC) on Tuesday alerted Americans to begin preparing for the spread of coronavirus in the United States after infections surfaced in several more countries.

The announcement signaled a change in tone for the Atlanta-based U.S. health agency, which had largely been focused on efforts to stop the virus from entering the country and quarantining individuals traveling from China.

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Wuhan Coronavirus

By Rud Istvan – Re4-Blogged From WUWT

Introduction

The Wuhan coronavirus potential pandemic has been much in the news recently. ctm discussed my doing an update to a rather long comment a few weeks ago. I first agreed but then demurred until now.

The reasons for agreeing were the numerous analogies (below) to climate change ‘science’ and ‘prognostications’—albeit on usefully shortened testable time frames like this year, not 2100. Examples below include assuming we know what we actually don’t based on models, and reporting worst case but unlikely scenarios as ‘likely” because ‘if it bleeds, it leads’.

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