Odograph.com

Is this thing really worth $60,000? I doubt it, but that’s what an on-line pricing tool says.

$60,000 seems crazy, but I suppose the blog has been running for a long time now, and back when I was serious I picked up a few links. Hey, there was the day the Wall Street Journal linked to me! (I can’t find the link now, but I remember that I corrected some math in their energy blog and they kindly linked back.)

Anyway, I’m much less serious about “odograph” now, as you can probably see.

If you want to buy it, email “o d o g r a p h o n e @ g m a i l . c o m” (spaces removed) and tell me what you think is fair.

I like Barry Ritholtz’ The Big Picture, but today he makes an odd claim:

That is a new slant on timing; we’ve evolved from “You cannot time the market” to “most find managers cannot time the market” — a subtle but important distinction.

New? Wasn’t it Charles Dow who dealt out playing cards with stock names on them, and matched the performance of investment advisors, back in the 1920’s? Apparently playing cards predate the dart-board metaphor, but under either name it’s ancient knowledge.

This “new” (irony quotes) fight between buy-and-holders and traders makes me step back, and to think about what we can know about our performance past, present and future. I generally hang with buy-and-holders, and index investors, but I’ve noticed a tension even within that group. Generally back-testing, the testing of a portfolio against decades of market history, is considered good. At the same time, data mining, the process of drilling down in recent market history to find optimum investments and strategies is considered bad. There is some merit in the distinction. At some point mining can become over-mining. I think everyone would agree with that. We can trust history too much, and trap ourselves into thinking that a relationship that was true in the past is likely to be true in the future.

We back-test (or use more arcane technical analysis) even as we say “past performance does not guarantee future results.”

This tension between looking at history and not trusting history is the key to understanding not just the tension between buy-and-holders and traders, but the uncertainty within each group as well.

I think everything is data mining, and that everyone should be using the past as their model with great reluctance.

If you think otherwise … you might become at the minimum a slice-and-dice buy-and-holder, or at the maximum, a trader.

UPDATE: One thing you can say about back-testing is that it lets you say a strategy “at least” works in the past. It may not work in the future, but it probably is safer than a strategy that “did not even” work in the past.

Abnormal Returns thinks so. I’m not so sure.

I track net-worth as my how-mi-doing. I feel that’s the most important step, both to beat the mental accounting impulse, and the last-trade bias. I’m not sure that strategies can be “testable” beyond that though. We pass through history once in our lives. The good or bad strategy I had in the 90’s may or may not be appropriate for the 10’s.

This is an older article (published April 15, 2007) but one that weighs on my thinking about markets and trends:

There’s nothing wrong with these tendencies. Ultimately, we’re all social beings, and without one another to rely on, life would be not only intolerable but meaningless. Yet our mutual dependence has unexpected consequences, one of which is that if people do not make decisions independently — if even in part they like things because other people like them — then predicting hits is not only difficult but actually impossible, no matter how much you know about individual tastes.

The reason is that when people tend to like what other people like, differences in popularity are subject to what is called “cumulative advantage,” or the “rich get richer” effect. This means that if one object happens to be slightly more popular than another at just the right point, it will tend to become more popular still. As a result, even tiny, random fluctuations can blow up, generating potentially enormous long-run differences among even indistinguishable competitors — a phenomenon that is similar in some ways to the famous “butterfly effect” from chaos theory. Thus, if history were to be somehow rerun many times, seemingly identical universes with the same set of competitors and the same overall market tastes would quickly generate different winners: Madonna would have been popular in this world, but in some other version of history, she would be a nobody, and someone we have never heard of would be in her place.

more here.

This is the article I meant to cite earlier:

There is now no question that the sole, undisputed factor driving credit and equity markets is the dollar destructive collusion between the Fed and the major global central banks. As long as the Fed is dead set on inflation, and is willing to throw trillions of free liquidity at any problematic flare up, and is happy to keep interest rates at 0%, liquidity-addicted equities will likely push higher until such time that the incremental hopium “hit” does nothing, and markets overdose, ending up not just in the critical condition reminiscent of fall 2008, but outright death. Until then, expect to see your daily dose of market buoyancy from whatever algo is currently the dominant momentum platform gunning the market ever higher, even past all disconnect with traditional correlations such as FX, credit and commodities. If the Fed wills it, so it shall be. Alas, while the Bank of England was apparently an easy target, when it comes to massive financial fraud and malfeasance, the Fed is untouchable.

more here.

This article at The Confluence starts with a quote about Wal-Mart:

“There are families not eating at the end of the month,” said Stephen Quinn, executive vice president and chief marketing officer at Wal-Mart Stores, and “literally lining up at midnight” at Wal-Mart stores waiting to buy food when paychecks or government checks land in their accounts.

Among the steps Wal-Mart is taking to address the changes in shopping habits, Mr. Quinn listed an overhaul of the retailer’s private-label brand, Great Value, which is promoted in commercials describing how families can fix dinners with Great Value products “for less than $2 a serving.”

and progresses to the GDP story mentioned here a few days ago:

The fundamental shortcoming is in the way imports are accounted for. A carburetor bought for $50 in China as a component of an American-made car, for example, more often than not shows up in the statistics as if it were the American-made version valued at, say, $100. The failure to distinguish adequately between what is made in America and what is made abroad falsely inflates the gross domestic product, which sums up all value added within the country.

American workers lose their jobs when carburetors they once made are imported instead. The federal data notices the decline in employment but fails to revalue the carburetors or even pinpoint that they are foreign-made. Because it seems as if $100 carburetors are being produced but fewer workers are needed to do so, productivity falsely rises — in the national statistics.

It is interesting, and sad, to tie the stories together like this. If GDP has been inflated that would go a long way to explain why we don’t seem to be as rich as we think we are.

As the last of his severance pay dwindled away in March, Brad Cleghorn of northwest suburban Marengo cashed out his 401(k) plan in order to pay his mortgage and feed his family.

Cleghorn is not alone. A Hewitt Associates study shows that 46 percent of workers with 401(k) plans who lost or switched jobs cashed the plans in, a trend that could lead to serious problems when younger generations of people working today reach retirement.

more here.

Computer scientists have spent decades developing techniques for answering a single question: How long does a given calculation take to perform? Constantinos Daskalakis, an assistant professor in MIT’s Computer Science and Artificial Intelligence Laboratory, has exported those techniques to game theory, a branch of mathematics with applications in economics, traffic management — on both the Internet and the interstate — and biology, among other things. By showing that some common game-theoretical problems are so hard that they’d take the lifetime of the universe to solve, Daskalakis is suggesting that they can’t accurately represent what happens in the real world.

more here.

When demand slopes upwards, by Felix Salmon

I’d like to see some empirical data here, but intuitively it’s at least possible that raising a wine from $3 to $6 per bottle might increase rather than decrease sales. That seems to be changing, as Mike Veseth explains in the rest of the article. But let’s say it holds true here, or once did. This isn’t a case of Veblen goods: drinking a $6 bottle of wine hardly counts as conspicuous consumption. Is there a name for this phenomenon? And is it found elsewhere?

“Fred Engels“, in the comments, suggests “the stock market.”

At the NY Times:

A widening gap between data and reality is distorting the government’s picture of the country’s economic health, overstating growth and productivity in ways that could affect the political debate on issues like trade, wages and job creation.

The shortcomings of the data-gathering system came through loud and clear here Friday and Saturday at a first-of-its-kind gathering of economists from academia and government determined to come up with a more accurate statistical picture.

The fundamental shortcoming is in the way imports are accounted for. A carburetor bought for $50 in China as a component of an American-made car, for example, more often than not shows up in the statistics as if it were the American-made version valued at, say, $100. The failure to distinguish adequately between what is made in America and what is made abroad falsely inflates the gross domestic product, which sums up all value added within the country.

It’s too early to say if this is a story which will stick, but it’s worth noting.