Platform Immunity and “Platform Blocking and Screening of Offensive Material”

In an earlier post, I talked about the big picture of 47 U.S.C. § 230, the federal statute that broadly protects social media platforms (and other online speakers) from lawsuits for the defamatory, privacy-violating, or otherwise tortious speech of their users. Let’s turn now to some specific details of how § 230 is written, and in particular its key operative provision:

(c) Protection for “Good Samaritan” blocking and screening of offensive material

(1) Treatment of publisher or speaker

No provider or user of an interactive computer service shall be treated as the publisher or speaker of any information provided by another information content provider.

(2) Civil liability

No provider or user of an interactive computer service shall be held liable on account of—

(A) any action voluntarily taken in good faith to restrict access to or availability of material that the provider or user considers to be obscene, lewd, lascivious, filthy, excessively violent, harassing, or otherwise objectionable, whether or not such material is constitutionally protected; or

(B) any action taken to enable or make available to information content providers or others the technical means to restrict access to material described in paragraph (1). [Codifier’s note: So in original [as enacted by Congress]. Probably should be “subparagraph (A).”]

Now recall the backdrop in 1996, when the statute was enacted. Congress wanted both to promote the development of the Internet, and to protect users from offensive material. Indeed, § 230 was part of a law named “the Communications Decency Act,” which also tried to ban various kinds of online porn; but such a ban was clearly constitutionally suspect, and indeed in 1997 the Court struck down that part of the law.

One possible alternative to a ban was encouraging service providers to block or delete various materials themselves. But a then-recent court decision, Stratton Oakmont v. Prodigy, held that service providers that engage in such content removal become “publishers” who are more liable for tortious speech (such as libel) that they don’t remove. Stratton Oakmont thus created a disincentive for service provider content control, including content control of the sort that Congress liked.

What did Congress do?

[1.] It sought to protect “blocking and screening of offensive material.”

[2.] It did this primarily by protecting “interactive computer service[s]”—basically anyone who runs a web site or other Internet platform—from being held liable for defamation, invasion of privacy, and the like in user-generated content whether or not those services also blocked and screened offensive material. That’s why Twitter doesn’t need to fear losing lawsuits to people defamed by Twitter users, and I don’t need to fear losing lawsuits to people defamed by my commenters.

[3.] It barred such liability for defamation, invasion of privacy, and the like without regard to the nature of the blocking and screening of offensive material (if any). Note that there is no “good faith” requirement in subsection (1).

So far we’ve been talking about liability when a service doesn’t block and screen material. (If the service had blocked an allegedly defamatory post, then there wouldn’t be a defamation claim against it in the first place.) But what if the service does block and screen material, and then the user whose material was blocked sues?

Recall that in such cases, even without § 230, the user would have had very few bases for suing. You generally don’t have a legal right to post things on someone else’s property; unlike with libel or invasion of privacy claims over what is posted, you usually can’t sue over what’s not posted. (You might have breach of contract claims, if the service provider contractually promised to keep your material up, but service providers generally didn’t do that; more on that, and on whether § 230 preempts such claims, in a later post.) Statutes banning discrimination in public accommodations, for instance, generally don’t apply to service providers, and in any case don’t generally ban discrimination based on the content of speech.

Still, subsection (2) did provide protection for service providers even against these few bases (and any future bases that might be developed)—unsurprising, given that Congress wanted to promote “blocking and screening”:

[4.] A platform operator was free to restrict material that it “considers to be obscene, lewd, lascivious, filthy, excessively violent, harassing, or otherwise objectionable, whether or not such material is constitutionally protected.”

  1. The material doesn’t have to be objectionable in some objective sense—it’s enough that the operator “consider[ it] to be” objectionable.
  2. The material isn’t limited to particular speech (such as sexually themed speech): It’s enough that the operator “consider[ it] to be” sexually themed or excessively violent or harassing or otherwise objectionable. If the categories were all of one sort (e.g., sexual), then “otherwise objectionable” might be read, under the legal principle of ejusdem generis, as limited to things of that sort: “when a generic term follows specific terms, the generic term should be construed to reference subjects akin to those with the specific enumeration.” But, as the Ninth Circuit recently noted,
  3. [T]he specific categories listed in § 230(c)(2) vary greatly: Material that is lewd or lascivious is not necessarily similar to material that is violent, or material that is harassing. If the enumerated categories are not similar, they provide little or no assistance in interpreting the more general category…. “Where the list of objects that precedes the ‘or other’ phrase is dissimilar, ejusdem generis does not apply[.]” …
  4. What’s more, “excessively violent,” “harassing,” and “otherwise objectionable” weren’t defined in the definitions section of the statute, and (unlike terms such as “lewd”) lacked well-established legal definitions. That supports the view that Congress didn’t expect courts to have to decide what’s excessively violent, harassing, or otherwise objectionable, because the decision was left for the platform operator.

[5.] Now this immunity from liability for blocking and screening was limited to actions “taken in good faith.” “Good faith” is a famously vague term.

But it’s hard to see how this would forbid blocking material that the provider views as false and dangerous, or politically offensive. Just as providers can in “good faith” view material that’s sexually themed, too violent, or harassing as objectionable, so I expect that many can and do “in good faith” find to be “otherwise objectionable” material that they see as a dangerous hoax, or “fake news” more broadly, or racist, or pro-terrorist. One way of thinking about is to ask yourself: Consider material that you find to be especially immoral or false and dangerous; all of us can imagine some. Would you “in good faith” view it as “objectionable”? I would think you would.

What wouldn’t be actions “taken in good faith”? The chief example is likely actions that are aimed at “offensive material” but rather that are motivated by a desire to block material from competitors. Thus, in Enigma Software Group USA v. Malwarebytes, Inc., the Ninth Circuit reasoned:

Enigma alleges that Malwarebytes blocked Enigma’s programs for anticompetitive reasons, not because the programs’ content was objectionable within the meaning of § 230, and that § 230 does not provide immunity for anticompetitive conduct. Malwarebytes’s position is that, given the catchall, Malwarebytes has immunity regardless of any anticompetitive motives.

We cannot accept Malwarebytes’s position, as it appears contrary to CDA’s history and purpose. Congress expressly provided that the CDA aims “to preserve the vibrant and competitive free market that presently exists for the Internet and other interactive computer services” and to “remove disincentives for the development and utilization of blocking and filtering technologies.” Congress said it gave providers discretion to identify objectionable content in large part to protect competition, not suppress it. In other words, Congress wanted to encourage the development of filtration technologies, not to enable software developers to drive each other out of business.

The court didn’t talk about “good faith” as such, but its reasoning would apply here: Blocking material ostensibly because it’s offensive but really because it’s from your business rival might well be seen as being not in good faith. But blocking material that you really do think is offensive to many of your users (much like sexually themed or excessively violent or harassing material is offensive to many of your users) seems to be quite consistent with good faith.

I’m thus skeptical of the argument in President Trump’s “Preventing Online Censorship” draft Executive Order that,

Subsection 230 (c) (1) broadly states that no provider of an interactive computer service shall be treated as a publisher or speaker of content provided by another person. But  subsection 230(c) (2) qualifies that principle when the provider edits the content provided by others. Subparagraph (c)(2) specifically addresses protections from “civil liability” and clarifies that  a provider is protected from liability when it acts in “good faith” to restrict access to content that it considers to be “obscene, lewd, lascivious, filthy, excessively violent, harassing or otherwise objectionable.” The provision does not extend to deceptive or pretextual actions restricting online content or actions inconsistent with an online platform’s terms of service. When an interactive computer service provider removes or restricts access to content and its actions do not meet the criteria of subparagraph (c)(2)(A), it is engaged in editorial conduct. By making itself an editor of content outside the protections of subparagraph (c)(2)(A), such a provider forfeits any protection from being deemed a “publisher or speaker” under subsection 230(c)(1), which properly applies only to a provider that merely provides a platform for content supplied by others.

As I argued above, § 230(c)(2) doesn’t qualify the § 230(c)(1) grant of immunity from defamation liability (and similar claims)—subsection (2) deals with the separate question of immunity from liability for wrongful blocking or deletion, not with liability for material that remains unblocked and undeleted.

In particular, the “good faith” and “otherwise objectionable” language doesn’t apply to § 230(c)(1), which categorically provides that, “No provider or user of an interactive computer service shall be treated as the publisher or speaker of any information provided by another information content provider,” period. (Literally, period.)

Removing or restricting access to content thus does not make a service provider a “publisher or speaker”; the whole point of § 230 was to allow service providers to retain immunity from claims that they are publishers or speakers, regardless of whether and why they “block[] and screen[] offensive material.”

Now this does leave the possibility of direct liability for “bad-faith” removal of material. A plaintiff would have to find an affirmative legal foundation for complaining that a private-company defendant has refused to let the plaintiff use the defendant’s facilities—perhaps as Enigma did with regard to false advertising law, or as someone might do with regard to some antitrust statute. The plaintiff would then have to show that the defendant’s action was not “taken in good faith to restrict access to or availability of material that the provider … considers to be … objectionable, whether or not such material is constitutionally protected.”

My sense is that it wouldn’t be enough to show that the defendant wasn’t entirely candid in explaining its reasoning. If I remove your post because I consider it lewd, but I lie to you and say that it’s because I thought it infringed someone’s copyright (maybe I don’t want to be seen as a prude), I’m still taking action in good faith to restrict access to material that I consider lewd; likewise as to, say, pro-terrorist material that I find “otherwise objectionable.” To find bad faith, there would have to be some reason why the provider wasn’t in good faith acting based on its considering material to be objectionable—perhaps, as Enigma suggests, evidence that the defendant was just trying to block a competitor. (I do think that a finding that the defendant breached a binding contract should be sufficient to avoid (c)(2), simply because § 230 immunity can be waived by contract the way other rights can be.)

But in any event, the enforcement mechanism for such alleged misconduct by service providers would have to be a lawsuit for wrongful blocking or removal of posts, based on the limited legal theories that prohibit such blocking or removal. It would not be a surrender of the service provider’s legal immunity for defamation, invasion of privacy, and the like based on posts that it didn’t remove.

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China Proposes A Law Allowing Citizens To Sue US For Starting Coronavirus Pandemic

China Proposes A Law Allowing Citizens To Sue US For Starting Coronavirus Pandemic

Tyler Durden

Thu, 05/28/2020 – 16:24

One month ago, the state of Missouri became the first in the nation to file a lawsuit against China over their role in the coronavirus pandemic. Also named in the suit were the Communist Party of China, the government of Wuhan City, and the Wuhan Institute of Virology, along with the Chinese Academy of Sciences. Filed in late April in the Eastern District of Missouri, Missouri Attorney General Eric Schmitt accused China of knowing that “COVID-19 was dangerous and capable of causing a pandemic, yet slowly acted, proverbially put their head in the sand, and/or covered it up in their own economic self-interest.”

Yet in a world where China has likewise accused the US of creating the coronavirus, why where there no lawsuits seeking similar damages from the US? Well, it now has: according to the Post, China’s legislature has proposed drafting a sovereign immunity law that would allow Chinese citizens to pursue legal actions against the United States over the coronavirus pandemic.

Citing China’s state-run media, the report said the Communist Party is seeking to amend an existing law that would allow legal action against “other countries.”

The Chinese lawmaker leading the efforts, Ma Yide, told the Global Times that the law would “ensure Chinese citizens’ and companies’ rights to sue the Us over its blame game and cover-up of information during the pandemic.” Ma said one of the things Chinese citizens should be able to sue over is the claim from the Chinese Foreign Ministry that the US military brought the coronavirus to China.

“Many believe that U.S. soldiers brought the epidemic to Wuhan. Others believe that the U.S. has hidden key information, which led to the global health crisis. Why can’t Chinese citizens and companies sue the U.S. government?” Ma told Chinese media.

If the proposal should pass, Chinese residents could move ahead with lawsuits that are beginning to surface.

Liang Xuguang, a lawyer from Wuhan where the first cases were reported in late December, has sued the US government, accusing it of spreading misinformation, the report said.

Liang wants the US to come clean on the number of “influenza deaths” caused by the coronavirus.

The proposal set forth in China’s National People’s Congress which concluded today, would naturally be in retaliation for lawsuits brought against China and the ruling Communist Party by several US states and a number of countries around the world.

The suits, one of which was noted above, accuse China of silencing doctors who were raising alarms that the coronavirus was a contagious respiratory disease in the early days of the outbreak and of pressuring foreign countries not to impose travel restrictions on Chinese nationals. They also claim China used its influence with the World Health Organization to downplay the severity of the outbreak.

In addition to Missouri, Mississippi has also sued the Chinese Communist Party, while Texas, New York and Florida have taken legal action against China.

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Dollar Slumps, Small Caps Dump, Oil Pumped

Dollar Slumps, Small Caps Dump, Oil Pumped

Tyler Durden

Thu, 05/28/2020 – 16:02

Today’s stock action was dominated by a dramatic shift in Small Caps vs mega-cap tech as the US Cash open sparked a puke in the former and a panic-bid in the latter…but that all snapped when President Trump confirmed a China news conference tomorrow and commented in more detail on his intent to crack down on social media giants…

A serious shift in the recent regime…

Source: Bloomberg

Sell Small Caps Mortimer, Sell!…

On the week, Trannies are still best and Nasdaq the laggard…

 

Internet stocks v-shaped-recovered from yesterday’s opening drop…

 

FANG Stocks surged…

Source: Bloomberg

TWTR took a beating in the pre-open but was panic-bid as cash markets roused…

Treasury yields were mixed once again in a narrow range relative to stocks’ chaos (30Y +3bps, 2Y -1bps)

Source: Bloomberg

Steepening the yield curve back near the highest since Oct 2017…

Source: Bloomberg

The Dollar continued its recent demise to two-month lows…

Source: Bloomberg

…tumbling back below a key technical level (100DMA)…

Source: Bloomberg

Which helped lift oil prices (despite a huge crude build)

But the dollar doldrums didn’t help gold…

And silver outperformed again, pushing its ratio to gold lower still…

Source: Bloomberg

Bitcoin rallied further (chatter of Hong Kong capital flight)…

Source: Bloomberg

Hong Kong Dollar forwards are pricing in a serious devaluation in the currency (capital flight)…

Source: Bloomberg

Finally, we note that the chaos under the surface continues in quant-factor-land, with momentum underperforming value by the most since September…

Source: Bloomberg

As the recent surge in momo relative to value catches down to bond market reality…

Source: Bloomberg

Turn The Machines back on!!

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DraftKings Shares Soared 300% As COVID Killed Sporting Events

DraftKings Shares Soared 300% As COVID Killed Sporting Events

Tyler Durden

Thu, 05/28/2020 – 15:50

There are no baseball, basketball, golf, equestrian, lacrosse, auto racing, and or other sporting events at the moment. Major League Baseball could restart in July, but there is still too much uncertainty. Football, if the season starts on time, won’t be seen until late August, and the 145th Preakness Stakes won’t be seen until October. 

But DraftKings, an American daily fantasy sports betting website, which recently went public, has seen its stock soar 273% since lockdowns began and all sporting events canceled. 

Howard Lindzon, the co-founder of StockTwits, tweeted: “The chart of the day is Draft Kings, which has quadrupled to $12 billion now since it reverses merged into a shell and then changed ticker to $DKNG…unbelievable outcome considering the long regulated road and the fact that NO SPORTS !? Face with tears of joy.”

The sports betting site has a market cap ($12 billion) larger than Wynn Resorts and American Airlines.

DraftKings CEO Jason Robins recently told CNN Business: “We have a good story that resonates with investors for the long-term.”

Robins admitted that users placing bets on sporting events are down this year due to virus-related lockdowns and social distancing — but he said players have been betting on other types of events, such as Russian table tennis and esports. 

Which explains why the stock has risen 273% as all major sporting events across the world have been canceled? 

JPMorgan CEO Jamie Dimon beautifully summed up the latest V-shaped recovery in markets on Wednesday, indicating that, “Fed liquidity is propping up stocks, all asset classes.” 

And with the Fed blasting a monetary cannon at the stock market, there’s also Robinhood day traders buying every dip possible of the crappiest stocks.   

None of this seems sustainable… 

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Trump Versus Biden: Who Will Win?

Trump Versus Biden: Who Will Win?

Tyler Durden

Thu, 05/28/2020 – 15:38

Authored by James Rickards via The Daily Reckoning,

The novel coronavirus has dominated the headlines for the past two months, as it should. There’s no bigger story in the world. And besides its human toll, I believe we’ll be dealing with its economic fallout for years.

But let’s not forget, this is an election year. Today I want to tie together the pandemic, the economy and the election.

What we are witnessing is a cascade of complex systems.

A pandemic is one complex dynamic system. The economy is another. A political season is still another.

Each complex system is highly unpredictable and capable of throwing out shocks (called “emergent properties” by physicists).

These three dynamic systems could exist on their own without affecting each other. But that’s not the case today.

A contagious virus, an unstable economy and a highly contested election are crashing into each other. Any one of these systems is difficult to model and predict. Collectively, it’s almost impossible.

All three systems go around in a circle affecting each other and being affected by each other. The pandemic has crashed the economy, and the economic collapse will affect the election. They all interact.

There’s no early end to this complex dynamic in sight.

There’s much that we don’t know about the pandemic and the political outcome. We know more about the economy because the specter of mass layoffs and business failure is already plain to see.

Even at that, we don’t know how long the economic distress will last and how long a recovery will take.

At this point, it’s fairly clear that the presidential election will feature Donald Trump versus Joe Biden.

There is some chance that Biden will stumble because of his cognitive disabilities, but it’s more likely the media will cover for him and he’ll be on the ballot on Election Day.

The principal factor in my election model this year was the probability of a recession before Election Day. No president seeking reelection to a second term has lost in the 20th or 21st centuries unless a recession occurred late in his first term.

Jimmy Carter and George H.W. Bush both lost their reelection bids, and both suffered recessions shortly before the election. Absent a recession late in a first term, the incumbent wins.

Until March, the odds of a recession before Election Day were less than 30% (many analysts set those odds even lower). This meant that Trump’s odds of winning were the reciprocal of 30%, which put the odds of winning at 70% (or higher).

And Trump’s odds would have likely improved by 2% per month. This means that if nothing changed, Trump would be an 86% favorite to win on Election Day.

Yet things did change.

Because of coronavirus, the odds of a recession switched to 100%. In theory, that would put the odds of Trump’s reelection at 0%. But Trump certainly has a better chance of reelection than zero. Basically, you have to set aside the rule book in this case.

This isn’t just a garden variety recession. It was deliberately imposed and accepted as a legitimate trade-off to prevent a massive public health crisis that could have overwhelmed the health care system.

I’m not going to get into a debate about whether it was necessary or not, but the point is it was a choice. It wasn’t because the economy suddenly collapsed on its own (although the economy was weaker than most people think it was).

So past comparisons don’t really hold up. This is a completely unprecedented situation.

But if you’re trying to forecast the election, how do you do it?

The best place to start the modeling process is to make the odds 50/50 (which really is just an educated starting place in the absence of better information).

That means Biden’s odds of winning are also 50% (for now).

In other words, the election has gone from being close to a sure thing for Trump to a coin toss.

Stock markets certainly have not had time seriously to contemplate President Biden and his pledges of higher taxes, open borders, the Green New Deal, late-term abortions and gun confiscations.

But that’s coming soon and is another huge headwind for markets.

So you can see how coronavirus, the economy and the election are all densely connected. Few would have imagined seven months ago where we’d be today. But here we are.

We still have nearly six months until the election. The best approach is to reserve judgment on what will happen six months from now.

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As Lockdowns Are Lifted, Is the COVID-19 Reproductive Number Rising or Falling?

If you are a critic of COVID-19 lockdowns, here are some numbers you will like. I also have some numbers you will not like as much, which I will get to in a minute.

According to a model by researchers at the University of Utah, the “real-time reproductive number” for the COVID-19 virus—the number of people infected by the average carrier—has fallen in Florida since the state began loosening its restrictions on businesses and individuals, from 0.98 on April 30 to 0.5 on May 26.

When the reproductive number falls below one, that indicates an epidemic is waning. The daily number of new cases can be expected to decline, and eventually so will the total number of active cases as previously infected people recover.

In Texas and Georgia, two other states with big populations that lifted their lockdowns on April 30, the pattern in the University of Utah model is initially similar but less encouraging in the last few days. In Texas, the model shows the real-time reproductive number falling from 1.13 on April 30 to 0.79 on May 22 and 23 before climbing to 1.32 on May 26. In Georgia, the number drops from 0.96 on April 30 to 0.78 on May 24, then rises to 1.01 as of May 26.

If you are a lockdown supporter, here are some numbers you will like better. According to a different model, this one produced by the independent data scientist Youyang Gu, the reproductive number in Florida rose from 0.96 on April 30 to 1.07 on May 26. Gu’s model also shows the number rising in Texas (from 1.01 to 1.07) and Georgia (from 1.03 to 1.07) during that period.

Feel free to pick the numbers that reinforce your preexisting beliefs. If you want to support the view that lockdowns are overrated as a way to reduce transmission of the COVID-19 virus, the University of Utah model is for you. If you want to support the view that lifting lockdowns is reckless, Gu is your man.

Who is right? I don’t know, but so far the Gu model has been remarkably accurate in predicting COVID-19 deaths, and the reproductive number figures into those projections.

The University of Utah model uses “a collated time series of daily state-wise positive
case counts from the COVID Tracking Project.” The researchers calculate the reproductive number “using two complementary methods”: the Wallinga and Teunis method, “which is forward-looking,” and the Cori method, “which is backward-looking.” The Gu model “builds machine learning techniques on top of a classic infectious disease model” known as SEIR, which starts by dividing the population into four groups: susceptible, exposed, infectious, and recovered.

As my colleague Ron Bailey has noted, the Gu model’s projections “are considerably less optimistic” than the projections from other widely cited models. Historically, Gu notes, his model’s COVID-19 death projections have matched the actual fatalities counted by the Johns Hopkins Coronavirus Resource Center much better than the model used by the University of Washington’s Institute for Health Metrics and Evaluation (IHME). On May 2, for instance, the Gu model predicted 101,950 deaths in the United States by today, compared to the IHME projection (since revised) of 71,918. The current Johns Hopkins tally is 100,415.

The Gu model predicted that the death toll would reach 100,000 by May 25, and that happened just a couple of days later. It is now projecting more than 200,000 deaths by August 28. A projection by the U.S. Centers for Disease Control and Prevention, leaked to the press early this month, predicted that mark would be reached by June 1, which thankfully has proven to be excessively pessimistic. But if history is any guide, the IHME projections err in the opposite direction. They currently go only as far as August 4, when the predicted death toll is about 132,000, compared to more than 173,000 in the Gu model.

Since the Gu model’s death projections incorporate its estimate of the reproductive number, it seems to have a pretty good handle on the latter, which suggests it is closer to the mark than the University of Utah model. Nationally, the Gu model shows the reproductive number falling from 2.26 on February 5 to a low of 0.91 on April 11, then beginning to rise on April 28 and reaching 1.02 today. The University of Utah model puts the national average at 2.66 on March 20, falling more or less steadily to 0.8 on May 24 and 25 before rising slightly to 0.85 as of May 26.

While I would prefer to believe the more optimistic scenario, the Gu model’s historical performance makes a compelling case for (relative) pessimism. Furthermore, it is plausible that lockdowns had some impact on virus transmission and that lifting them would boost the reproductive number. Whether that means they were worth their enormous economic cost is another question, especially since many of the COVID-19 deaths they ostensibly prevented may simply have been delayed.

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As Lockdowns Are Lifted, Is the COVID-19 Reproductive Number Rising or Falling?

If you are a critic of COVID-19 lockdowns, here are some numbers you will like. I also have some numbers you will not like as much, which I will get to in a minute.

According to a model by researchers at the University of Utah, the “real-time reproductive number” for the COVID-19 virus—the number of people infected by the average carrier—has fallen in Florida since the state began loosening its restrictions on businesses and individuals, from 0.98 on April 30 to 0.5 on May 26.

When the reproductive number falls below one, that indicates an epidemic is waning. The daily number of new cases can be expected to decline, and eventually so will the total number of active cases as previously infected people recover.

In Texas and Georgia, two other states with big populations that lifted their lockdowns on April 30, the pattern in the University of Utah model is initially similar but less encouraging in the last few days. In Texas, the model shows the real-time reproductive number falling from 1.13 on April 30 to 0.79 on May 22 and 23 before climbing to 1.32 on May 26. In Georgia, the number drops from 0.96 on April 30 to 0.78 on May 24, then rises to 1.01 as of May 26.

If you are a lockdown supporter, here are some numbers you will like better. According to a different model, this one produced by the independent data scientist Youyang Gu, the reproductive number in Florida rose from 0.96 on April 30 to 1.07 on May 26. Gu’s model also shows the number rising in Texas (from 1.01 to 1.07) and Georgia (from 1.03 to 1.07) during that period.

Feel free to pick the numbers that reinforce your preexisting beliefs. If you want to support the view that lockdowns are overrated as a way to reduce transmission of the COVID-19 virus, the University of Utah model is for you. If you want to support the view that lifting lockdowns is reckless, Gu is your man.

Who is right? I don’t know, but so far the Gu model has been remarkably accurate in predicting COVID-19 deaths, and the reproductive number figures into those projections.

The University of Utah model uses “a collated time series of daily state-wise positive
case counts from the COVID Tracking Project.” The researchers calculate the reproductive number “using two complementary methods”: the Wallinga and Teunis method, “which is forward-looking,” and the Cori method, “which is backward-looking.” The Gu model “builds machine learning techniques on top of a classic infectious disease model” known as SEIR, which starts by dividing the population into four groups: susceptible, exposed, infectious, and recovered.

As my colleague Ron Bailey has noted, the Gu model’s projections “are considerably less optimistic” than the projections from other widely cited models. Historically, Gu notes, his model’s COVID-19 death projections have matched the actual fatalities counted by the Johns Hopkins Coronavirus Resource Center much better than the model used by the University of Washington’s Institute for Health Metrics and Evaluation (IHME). On May 2, for instance, the Gu model predicted 101,950 deaths in the United States by today, compared to the IHME projection (since revised) of 71,918. The current Johns Hopkins tally is 100,415.

The Gu model predicted that the death toll would reach 100,000 by May 25, and that happened just a couple of days later. It is now projecting more than 200,000 deaths by August 28. A projection by the U.S. Centers for Disease Control and Prevention, leaked to the press early this month, predicted that mark would be reached by June 1, which thankfully has proven to be excessively pessimistic. But if history is any guide, the IHME projections err in the opposite direction. They currently go only as far as August 4, when the predicted death toll is about 132,000, compared to more than 173,000 in the Gu model.

Since the Gu model’s death projections incorporate its estimate of the reproductive number, it seems to have a pretty good handle on the latter, which suggests it is closer to the mark than the University of Utah model. Nationally, the Gu model shows the reproductive number falling from 2.26 on February 5 to a low of 0.91 on April 11, then beginning to rise on April 28 and reaching 1.02 today. The University of Utah model puts the national average at 2.66 on March 20, falling more or less steadily to 0.8 on May 24 and 25 before rising slightly to 0.85 as of May 26.

While I would prefer to believe the more optimistic scenario, the Gu model’s historical performance makes a compelling case for (relative) pessimism. Furthermore, it is plausible that lockdowns had some impact on virus transmission and that lifting them would boost the reproductive number. Whether that means they were worth their enormous economic cost is another question, especially since many of the COVID-19 deaths they ostensibly prevented may simply have been delayed.

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The Last Time Albert Edwards Saw “Nonsense” Like This Was 2008: This Is How It Ended

The Last Time Albert Edwards Saw “Nonsense” Like This Was 2008: This Is How It Ended

Tyler Durden

Thu, 05/28/2020 – 15:24

Albert Edwards admits he is “perplexed.”

Writing in his latest Global Strategy report, the SocGen strategist admits that “until recently (ie the last few days), I had thought that the 35%+ rally in the S&P from its 23 March 2190 low would stall at around 2980 – the 62% Fibonacci Retracement level, as occurred in the previous two (2001 and 2008) bear markets. Hence, I was genuinely surprised to see the S&P climb above the technically important 2980 level, and yesterday power above its 200-day moving average.”

Instead, the S&P is now less than 10% from February’s all-time high, and with the US unemployment rate heading towards 20%, Edwards asks rhetorically: “At what point does the stark disconnect between Wall Street and Main Street become a political embarrassment for the Fed? Maybe never.”

Maybe never, but most likely soon: as Bank of America’s Michael Hartnett wrote last Friday, the absolute limit of bear market rallies in 1929, 1938, 1974 was a 61% rebound from lows (after an avg 49% drop), which would take the S&P500 to 3180 this rally, so another 120 points.

Edwards does not look that far back, however, and instead he reminds is that the rally from the March lows is similar to last year’s rally, which similarly was narrowly concentrated on the large cap ‘growth’ stocks aka the FAANGs (Facebook, Apple,  Amazon, Netflix and the stocks formerly known as Google, but now called Alphabet).

And while the bearish strategist offers a mea culpa, saying “I have been very wrong as I had expected to see a collapse in the FAANG stocks and ‘tech’ generally, as the recession exposed large parts of the tech universe as cyclical stocks masquerading as ‘growth’ stocks, … but how wrong I was, as the stay-at-home nature of this coronavirus-induced recession has instead given the FAANG and tech stocks a whole new impetus”, he advises his clients that he, too, has been here before, in the first half of 2008 to be specific.

Cast your minds back. The S&P had topped out in October 2007 – the bear market had begun and the US economy had slipped into recession. Do you remember the mantra that emerging markets had de-coupled from the global downturn and commodities would remain resilient as a result? Do you remember the touting of ‘BRIC’ EM investing? So, for most of H1 2008, commodity prices soared.

At the time Albert said this talk of de-coupling was nonsense, and is “what behaviourists call a bubble of belief as Fed liquidity had funnelled into this asset class as a last refuge from the cyclical meltdown.”

Fast forward to today when Edwards saying the current decoupling of tech/growth/momentum, or generally – the FAANG rally – too “will end in collapse in the same way EM and oil did in H2 2008. Indeed, the title and first paragraph above are taken  directly from my weekly of 5 March 2008 with FAANG replacing commodities and EM.” And just to make his point, we notes that his lead in sentence was taken directly from his weekly of 5 March 2008 with FAANG replacing commodities and EM. 

I have a high conviction that before the end of this year the EMs FAANGs will be unravelling, as the structural arguments supporting these bubbles turn to cyclical sand.

For those who prefer visual reminders, this is what the S&P did for the 6 months after the recession of 2007 had started:

Shifting to the here and now, Edwards then writes that in the run-up to the current recession, “US tech price outperformance far outstripped relative EPS performance.” As the SocGen strategist elaborates, “I felt this was yet another Fed inspired, liquidity driven bubble that would burst in the coming recession – like the late 1990s Nasdaq bubble.” It’s not just him though: even Goldman recently warned that the FAAMGs have gone far too far, and a moment of reckoing is coming as a result of the record concentration in just a handful of stocks as market breadth has plunged to near all time lows.

However, what both Goldman’s David Kostin and Albert Edwards missed, is that the unusual stay-at-home nature of this coronavirus-driven recession has boosted IT and media related expenditures generally in a way that could not have been anticipated. Interestingly, US tech sector profits have only really outperformed decisively in the past few months (see chart
below), but rather than profits merely catching up with previous heady price outperformance, IT stocks have continued to surge higher relative to the market, especially in the rally since March.

This is not the first time we have seen this pattern: in the late 1990s, Edwards writes, tech stocks also enjoyed a period of massive outperformance that had hugely outstripped what was also a moderate outperformance of their EPS relative to the market (see chart below), “and just like recent times, what propelled US tech valuations to stratospherically high valuations back then was ample Fed liquidity and a bubble of belief.”

Then the 2001 recession hit, and many tech stocks suffered a “totally unexpected” fall in profits. These were not growth stocks at all and shouldn’t have been on 40x+ PEs. “These were in reality cyclical stocks trading on peak multiples on peak cyclical earnings when they should have been trading on top of the cycle, single-digit PEs” Edwards booms, but of course it is easier to make such observations in retrospect when the frenzy is long gone. Of course, when the market “discovered” these stocks were on the wrong PE ratings based on the wrong forward earnings, the Nasdaq bubble collapsed. And even the true growth tech stocks collapsed in price as all around them earnings bombs were exploding. At that point, “investors rushed for the hills throwing their true growth tech babies out with the bathwater”, gloomy Albert concludes.

Yet it may (not) come as a surprise that Edwards is even gloomier now, even though as he admits, “his expectation of a similar fate for tech in this recession has been proved wholly wrong. To be honest, I have been left scratching my head. I feel I am suffering from that awful psychological affliction virtually unknown on the sell-side – namely self-doubt!”

For if the large-cap US indices are increasingly dominated by growth sectors such as IT, or specifically the FAANGs (see left-hand chart below), that typically benefit when bond yields fall (and I expect the US 10Y bond yield to fall to -1%), why can’’t the S&P carry on rising in line with falling bond yield? Maybe ever higher PEs are consistent with low bond yields after all if the market is stuffed full of growth sector bond proxies?

This, of course, is taking the Fed model to its ludicrous extreme, one where negative rates would in theory at least, presuppose infinite stock prices. After all if discounting future cash flows using negative discount rates, prices rapidly approach +∞.

Edwards had considered this possibility last year in the run-up to this recession, and while he thought quality stocks (with sound balance sheets) and defensive sectors would continue to re-rate higher with falling bond yields, the IT collapse would surely help lay the overall market low – this is a rehash of Goldman’s bearish April thesis. For even with soaring stay-at-home expenditures on IT, profits for the tech sector have actually fallen. But something was different: unlike 2001, the decline is at a much slower rate than the overall market (see righthand chart below).

Putting it together, Edwards says that we have now reached a permanent market and profit divergence, where the FAANGs specifically, and IT and growth stocks generally, have continued to outperform the market, taking PE valuations to extremes not seen for many a year; which makes sense: after all it is the small, soon to be insolvent “value” companies that trade at a depressed multiples, and as they fail and are removed from the S&P, multiples will only rise. But here a thought: keep in mind that the FAAMGs are for the most part ad-revenue driven. In a world where just the 5 tech megacaps survive (enabling market multiples to approach 30x) and where most small and medium business have collapsed, who will need, or pay for advertising? What will be the FAAMGs business model after the coming tsunami of defaults has wiped out trillions in ad spending? Just a thought to keep in mind as everyone rushes into tech names.

And while everything contemplates this dilemma, Edwards takes us back to a topic familiar to most, namely the massive outperformance of just a handful of stocks vs everyone else, something we discussed most recently in “The FAAMGs Are Up 10% In 2020; The Remaining 495 S&P Stocks Are Down 13%.”

Edwards here reminds us that earlier this year, just before the market peaked in February, SocGen’s quant Andrew Lapthorne, published the charts below showing how the largest cap stocks in the US had outperformed the overall market so comprehensively over the last three years – only.

The word only is a very important caveat and emphasises just how unusual this period of market domination by a small number of stocks really is (the top 5 being the FAANGs). We have been here before with investment fashions like the BRICs, the nifty-50 or indeed the famous five (maybe they weren’’t an investment theme after all, but why let the facts spoil a good acronym!).

Alas, for every such period of massive outperformance by a handful of stocks, the detox is especially painful, and Lapthorne notes that “history shows that periods of extreme outperformance by the 5 or 10 largest cap stocks are eventually counterbalanced by periods of huge underperformance when bear markets occur” (right-hand chart above). In fact, over the long term Andrew noted that the ten biggest stocks have lagged the market by 150bp per annum on average since 1990, while the top five stocks lost 100bp per annum vs the benchmark  link.

Albert concludes by expanding on this topic of super concentration, and using a concept spawned by Gerard Minack, author of the Downunder Daily, namely adding Microsoft to the FAANGs (calling Google by its correct name Alphabet) to form the
FAAANMs (Facebook, Apple, Alphabet, Amazon, Netflix & Microsoft), Gerard and Edwards highlight that the massive outperformance of the S&P versus the MSCI rest of the world (RoW) is almost entirely attributable to the FAAANM, top 6 stocks. The S&P494 ex FAAANM, is almost as dull as the RoW. “This is significant as it is shocking” in the words of everyone’s favorite permabear.

Extending this analysis to fundamentals reveals the same pattern: as Edwards puts it, “the pedestrian price performance of the S&P 494 (ie S&P 500 removing the FAAANM stocks) in line with the RoW stock markets is entirely in line with both their sales and profits performance. Remove the FAAANM stocks and profits are back to 2015 levels.

Echoing Goldman’s April note, Albert exclaims that “it is shocking quite how reliant the US equity market has become on just six mega-cap stocks because it emphasizes the risks if, for any reason the bubble in the FAAANM stocks burst as I believe it surely will. Indeed, as Andrew showed earlier, history supports that view.”

So how do these massive divergences resolve themselves? One, arguably the simplest way, would be for bond yields to keep rising, value stocks to surge, and growth names to plunge. But Edwards expect bond yields to first fall further (before exploding higher).

Instead the SocGen strategist believes that what is really going on, is that profits in the FAAANM stocks are falling (above right chart) in line with the chart shown earlier of forward EPS in IT falling (intuitively this makes sense because as the economic recession gets worse once stimulus payments fade, ad spending will plunge, as will ad revenues for the FAAMGs.

Edwards concludes by repeating what he said two months ago, namely that “this recession will ultimately expose these and the tech sector to be far more cyclical than appreciated. And it will be difficult in that environment to maintain their 32x forward PE (see chart below).”

Furthermore, echoing Minack, the SocGen analyst writes that “it is curious why the S&P494 enjoys a superior rating compared to the RoW when its sales and profits are no better than the RoW. History suggests there is no justification for this and it is part of the bubble of belief driven by Fed liquidity. “

In conclusion, and going back to the “tsunami of liquidity” theme that made this all possible, Edwards ends where he started with a quote from his Global Strategy Weekly from 2008 when the market thought EM and commodities had decoupled from the RoW. This is what he said on 5 June 2008,

Too often at the height of a bubble, liquidity is used as an explanation. This is voodoo strategy. Much of the ‘liquidity’ that supports markets at the height of a bubble is merely investors leveraging up on the back of long-established price momentum trades (often in cyclical risk assets). And even as the fundamentals deteriorate, investors keep borrowing and investing. But like Wile E. Coyote in the Road Runner cartoons, reality eventually catches up and the ocean of liquidity evaporates overnight until the next cycle. Poof!”

via ZeroHedge News https://ift.tt/2AjsPmK Tyler Durden

Stocks Slammed After Trump Confirms China News Conference

Stocks Slammed After Trump Confirms China News Conference

Tyler Durden

Thu, 05/28/2020 – 15:23

US equity markets legged lower after President Trump confirmed that he will hold a news conference tomorrow on China.

No details were revealed but it’s pretty clear he’s not going to walk back any of the recent rhetoric over the “China virus”, the human rights abuses of Uighurs, or the implicit political invasion of Hong Kong…

 

via ZeroHedge News https://ift.tt/2zuhvEB Tyler Durden

Dining In The Financial District Will Never Be The Same 

Dining In The Financial District Will Never Be The Same 

Tyler Durden

Thu, 05/28/2020 – 15:05

New York City has been the epicenter of the COVID-19 pandemic, and now Mayor Bill de Blasio has made remarks considering a phased reopening of the city by the first half of June. When New Yorkers emerge from their homes, they will see an entirely different world, one where social distancing will reshape the landscape of many public areas and commercial spaces. 

Though the Big Apple is a ways off from opening its bars and restaurants. One eatery in the Financial District has offered a view into what the post-corona world of the restaurant industry is going to look like. 

 

FOX 5 New York reports the Brooklyn Chop House has redesigned its dining hall with social distancing in mind. 

Owner Stratis Morfogen said customers can expect to wear a facemask, eat between dividers, and be screened at the door, all moves that will hopefully limit virus transmission risk. 

Morfogen said before the patron steps onto the dining floor, they will be screened by an ultraviolet thermal body scanner. 

“The ultraviolet kills anything that’s on your clothing,” he said. 

He said the scanner will take the guest’s temperature and if someone registers over 99.7 Fahrenheit, staff would immediately deny them access. 

Morfogen also said he’s building a second restaurant that will be “contact-free with the staff.” Customers at the Brooklyn Dumpling Shop will soon have the ability to order via app or phone and pick up through food lockers. He assured this way there will be “zero human interaction.” 

In the last several months, we have allowed readers to peer inside what a post-corona world could look like and how public spaces are rapidly changing with social distancing in mind:

Social distancing will completely reshape how consumers and businesses interact in the economy. Welcome to the post-corona world… 

via ZeroHedge News https://ift.tt/3gwObxW Tyler Durden