Uh, oh….a Crash

Last week, the S&P500 suffered the inevitable downturn.  While it fell 6.4% for the week, it fell about 9% for a few moments during one trading day–May 6.  Volume shot up, confirming the price drop.  And the VIX (or fear) index exploded up 86%.  The world rushed to get out of risk assets, and the selling may not be over.

The macro data were mixed, as usual.  While personal spending rose more than experts had estimated, personal income rose by less than they had forecast.  Average earnings were flat for the month of April; they were expected to rise.  It’s becoming clear than consumer spending over the last few months rose because people reduced saving rates and spent government refunds and unemployment checks.  Clearly this is not sustainable.  ISM Manufacturing was weaker than expected.  Factory orders were stronger.  ISM Services was weaker than the consensus forecast.  Initial claims remain in the mid-400,000 range.  Non-farm payrolls rose 290,000, BUT what the mainstream media will not tell you is that 188,000 of these jobs were assumed into existence via the BLS birth/death model and that 66,000 of these jobs came from census hires which will soon disappear.  The headline unemployment rate rose to 9.9%.  The broader U-6 unemployment rate rose to 17.1%.  And the number of people unemployed over 27 weeks rose to another post-WWII record high.

So what caused the stock market to crash on May 6?

No, it wasn’t a fat finger–a trading error where someone mistakenly sold a billion shares of something rather than a million shares.

And it wasn’t computerized high frequency trading in the way that everyone believes:  prices were OK, until some rogue programs went nuts and caused selling to explode and shove prices downward.

Instead, the WAY in which computerized trading caused the crash has to do with their forcing prices UP over the last 12 months (and before that, from 2005 to 2007) to unrealistic levels.

How did they do this?

Let’s use an analogy.  Imagine a housing market comprised of 100 identical homes in a small self-contained community.  Let’s assume that there are virtually no commissions or other costs that make the buying and selling of homes more costly.

Let’s assume that most owners in this community aren’t selling their homes; they’re owners who want to hold on to them.  So the price of all of these homes gets set on the margin; one very recent sale, sets the price for all the other, 99, homes.  And the last selling price (the comp) was $100,000.

One day, a computerized buyer (Machine A) enters the market by acquiring one home for $100,000.  If the next week, another computer, Machine B, bids $110,000 for this same house, Machine A sells and books a profit of $10,000 (or 10%).  In the following week, Machine A returns to bid on the SAME house for $120,000.  Machine B sells; now it books a $10,000 profit.

This back-and-forth continues until the last sale price hits $200,000.  And voila, it looks like ALL the houses in this community are now worth DOUBLE the original $100,000.  In fact, the non-participating neighbors are ecstatic; at the very least, they have no reason to complain.

Then one day, a new prospective owner decides to move into the neighborhood.  And this owner buys the SAME house from the last machine for $200,000.  After all, the market is “hot” and that’s what homes are going for.  And there are plenty of comparable sales to “prove” it. 

The machines have left–each having booked profits of $50,000.  But the new owner is left holding the bag.


Because some day–and nobody can predict exactly when–one or more of the other 99 owners in the community will also try to sell.  And believing that the prices of their homes have now doubled, they will “ask” at least $200,000. 

But there will be no machines anymore to artificially prop up the price.  Some owners may actually sell for $200,000.  But other homes will sit on the market unsold, as outside buyers worry that homes are being offered at prices above their intrinsic value. 

Sale volumes will fall.  Other owners, worrying that the new high prices may not last, will rush to place their homes on the market, until finally a desperate seller capitulates and accepts “only” $180,000. 

Then all hell will break loose.  Sellers will feel the pressure to lower their asking prices to say, $180,000.  Buyers, smelling blood, will bid even less than $180,000, until eventually the prices return to $100,000, or even LESS because prices tend to over-correct.

Who wins?  The machines. 

Who loses?  All of the owners who bought at prices above $100,000.  Arguably, the owners who did nothing through the run up and the crash also lose, because their “market” will be perceived as unstable, rigged and unfair.  So future buyers will tend to stay away for many years after the crash.

Welcome to the current American stock market.  And brace yourselves for more “Uh, Oh” moments.  Make no mistake, they will happen again.

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