07 April 2014

About Your Mule...

There's that old, and continuing, adage: "you can't beat Mr. Market". Well, baloney. You sure can beat Mr. Market like a rented mule. For some definition of 'you', of course.

If you've billions in moolah, it does get a little harder, from one point of view; yet even easier from another. Warren Buffett is a case in point. The piece exposes him as merely mortal the last few years. May be. Then again, may be not.

Mr. Market is kind of, sort of, Dr. Jekyll and Mr. Hyde. If you've got $100,000 in moolah, then turning it into $1,000,000 is certainly feasible. If you've got billions, turning that into tens of billions, not so easy. Or may be it is.

There are only two factors which cause capital gains in stocks: real events, and real events. (If that sounds familiar, recall this old canard: "there's the three killer apps of the PC; word processing, spreadsheets, and word processing". Still true today, which is why phones and tablets have inhaled the consumer space.) So, Mr. Market is either equities (narrowing focus a bit) across the board, or a particular corporation. For equities, Ukraine is the current event driving his angst. Earlier, it was the tsunami of moolah from The East (more on this later). For the ABC Corporation, it's... who knows?
Mr. Buffett's talents are widely known. But despite his celebrated past performance, his returns since the beginning of 2009 have been disappointing.

He's too big to hit a grand slam.

What's happened since 2009? A so-so stimulus, followed by a number of QEs. And, let's not forget, The Giant Pool of Money still looking for 10%, risk-free returns (the expanding Chinese housing bubble is a chicken come home to roost). In all, Mr. Market, in the large (Mr. Hyde) is floating on helium. In such a situation, Mr. Buffett can't do well, since productive value becomes unstuck from fiduciary value.

Could it be that the Fed's pushing a string? The idea with the QE exercises was to make physical investment desirable, by lowering the cost of money to do so. More investment in physical production, yields more employment, which yields more income, which yields more demand, and around we go. If only we give the carousel enough oomph to turn on its own. Hasn't worked out that way.

On the other hand, the others with moolah piles of Mr. Buffett's sort, can do quite well. Here's where quants can earn their keep (if you assert that money manipulation is 'work') since the tactic is to track gross money flows and move ahead of the lemmings. Since Mr. Buffett chooses to make long-term bets on, often, whole companies, moving in and out of positions is difficult, if he attempted that. Paulson, with a little help from being inside, did just that. So did Jamie Dimon.

What quants aren't very good at, since it's outside their purview, is understanding catalyzing events of individual companies, the Dr. Jekylls of this tale. This is where the lonely $100,000 has the advantage. Did deep into ABC Corporation, tech or biotech these days, and you'll find some type of "innovation" about to be birthed in the next X months or Y years. Buy up a bunch of ABC, and wait for the catalyst. It helps a whole lot to understand the venue in which ABC operates, of course. Buffett's billions are too big to get away with that; the ABC's of the world tend to be, at most, small-cap outfits. The Baker Bros. funds have managed to pull it off with some consistency in bio.

The string pushing hasn't worked out as planned.
According to a report by Moody's Investors Service, American companies outside the financial industry were sitting on a combined $1.64 trillion of cash by the end of 2013. And tech giants like Apple, Google and Microsoft had the most.

That's a really big number. And doesn't include the Too Big to Fail cabal. Is it any wonder that the QEs have had little effect? Other than the ABC Corporations converting old high cost debt into new lower cost debt.

Speaking of Big Numbers, Krugman shares the page with a piece taking the Big Data meme to task. Two doses of reinforcement.

Krugman:
Many people understand that a falling price level is a bad thing; nobody wants to turn into Japan, which has struggled with deflation since the 1990s. What's less understood is that there isn't a red line at zero: an economy with 0.5 percent inflation is going to have many of the same problems as an economy with 0.5 percent deflation. That's why the I.M.F. warned that "lowflation" is putting Europe at risk of Japanese-style stagnation, even though literal deflation hasn't happened (yet).

Here, I still find he's too Pollyanna about the whole thing; there are folks who'd love a Japan. The cash hoarding by the .1% is clearly a move to get deflation up and running; they've run out of ways to productively convert fiduciary capital to real capital, and having no income generating skills, "[We] have always depended on the kindness of strangers." Deflation, while it might not get them 10%/annum, is totally risk free returns. Who can turn that down? "Turning Japanese I think [we're] turning Japanese I really think so" (The Vapors, 1980)

In my dead trees version, more than half the page (less Krugman's full length column) is devoted to a take down of Big Data. Again, comforting to know that some who can finagle a piece on the NYT have figured it out.
The first thing to note is that although big data is very good at detecting correlations, especially subtle correlations that an analysis of smaller data sets might miss, it never tells us which correlations are meaningful. A big data analysis might reveal, for instance, that from 2006 to 2011 the United States murder rate was well correlated with the market share of Internet Explorer: Both went down sharply.

Makes sense to me!

But how to explain this non-sequitor?
FINALLY, big data is at its best when analyzing things that are extremely common, but often falls short when analyzing things that are less common.

Fact is, it's the outliers that Big Data allows us to find, as the murders and IE example (OK, it's not likely causative), or that Target customer that found out his daughter was preggers. Now, their examples are a bit off target, so far as I'm concerned. The issue with Big Data has always been a cost/benefit one: collecting enough of the right data to find black swans early enough to profit is difficult to calculate, especially if you don't know which particular, very valuable, swan you're expecting. That's part of what makes them black. The Great Recession was a black swan to many, simply because they'd ignored the data which really mattered. As lemmings, they all ran over the cliff. Not so black for a few who paid attention. Big Data didn't help them, rather Econ 101.
About a year after Pole created his pregnancy-prediction model, a man walked into a Target outside Minneapolis and demanded to see the manager. He was clutching coupons that had been sent to his daughter, and he was angry, according to an employee who participated in the conversation.

"My daughter got this in the mail!" he said. "She's still in high school, and you're sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?"

Dancing belly to belly.

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