Forex Fun Da Mentals

Ever wonder why financial forecasts by economists seem about as reliable as weather forecasts by meteorologists?  The simple answer:  Predicting economic and weather systems ain't easy.  British economist John Kay  offers a more extensive answer in yesterday's Financial Times.  Here's an abbreviated version of the article : 

[E]conomic prediction is hard. National economies, financial markets and businesses are complex, dynamic, non-linear systems. Your economy contains many people and many agents, and there are many interactions between them.

Many of [the successes of the natural sciences] have been achieved because the problems of physics often involve objects large enough to be studied individually - the motion of the earth, for example. Or components small enough to be subject to statistical regularities - we can never predict the behaviour of an individual molecule or electron, but there are so many molecules and electrons that for most purposes it does not matter. Many of the phenomena we deal with in economics and business fall in between - the units of analysis are individualistic but also too numerous for their idiosyncrasies to be individually understood.

Economic systems are also dynamic. Dynamic in the sense that they evolve - which makes the mathematics harder. But also dynamic in the sense that the structural relationships constantly change.

[T]he killer is that dynamic complexity interacts with non-linearity...small differences in initial conditions can have dramatic differences in ultimate outcomes. The problem is often expressed through the metaphor of the butterfly which, by flapping its wings on one side of the world, sets in train a chain of consequences that results in a tornado many thousands of miles away.

The nature of such complex, dynamic, non-linear systems is that we may be able to say a lot about their general properties, while being unable to make specific predictions. You will recognise this characteristic in the work of your Meteorological Office, which can tell you fairly reliably when spring will follow summer, or how much cooler or warmer it will be when you visit far-flung outposts, but which can never predict what the weather will be more than a few days ahead, or even with certainty what it will be like tomorrow.

The market for clairvoyance has existed through history and is satisfied by messages based on hope and ambiguity. The market for economic prediction is similar. Successful proponents are distinguished by their television manner rather than the accuracy of their forecasts.

Shakespeare, traducing Richard III with the connivance of the first Queen Elizabeth, understood better than anyone that a good story is more compelling than the search for truth. The American political scientist, Philip Tetlock, has studied the prognostications of pundits over several decades. He finds that the better known the forecaster, the less accurate the forecast. Business people, politicians and journalists value clarity and certainty of view more highly than acknowledgement of the uncertainty of a complex world. But it is mostly people who appreciate that complexity who have worthwhile things to say about the future.

"Fools ignore complexity.  Pragmatists suffer it.  Some can avoid it.  Geniuses remove it."

Barry Ritholtz points us to this video by MSN Money Senior Markets Editor Jim Jubak.

I was telling Bootcampers last Monday about the recent surge in the euro's trade weighted index.  This past Friday, the Financial Times published an interactive graphic showing the journey this index has taken since the introduction of the single currency 10 years ago next week.  (The image below does not offer all of the multimedia functionality of the original graphic; you'll have to go here for that.)

Barry Ritholtz nails it  :

I wake up every day, and instead of saying, g'morning sweetheart, I say:
     What the f&%$ is going to happen TODAY!
Then I jump out of bed, cause I simply cannot wait to see.
I consider myself fortunate to live in such interesting times...

One tell for U.S. consumer spending is the number of miles they drive.  By that measure, Americans are...um...just read the latest post by Real Time Economics:

The number of miles driven by Americans in October fell by 8.9 billion, or 3.5%, compared with the year-earlier month, the sharpest decline for that month since 1971, the U.S. Department of Transportation reported Friday. The drop came despite gasoline prices that have rapidly fallen from a peak of over $4 this summer to their current national average of about $1.70.

One big question on policymakers’ minds over the past year has been whether Americans would return to previous driving levels once gasoline prices dropped. The data so far suggest the answer is no.

“The fact that the trend persists even as gas prices are dropping confirms that America’s travel habits are fundamentally changing,” Transportation Secretary Mary E. Peters said in a statement.

The new government figures also show that the 12-month period ended Oct. 31 saw the steepest decline in miles driven by Americans of any such period since the government began keeping statistics in 1942. Americans drove 100 billion fewer miles in the year ended Oct. 31, a 3.3% drop from the previous 12-month period. It’s the first time driving has declined for 12 consecutive months.

The Transportation Department tracks miles driven using a system of more than 4,000 data sensors in roadways across the country.

I've been saying for months that there's plenty of blame to go around for the current financial crisis.  Here's a storyline that's chock full of culprits.

Several years ago, the big five investment banks -- Morgan Stanley, Goldman Sachs, Merrill Lynch, Lehman Brothers, and Bear Stearns -- wanted the SEC to reform its net capital rule.   Representatives from these banks met with the SEC on April 28, 2004.  The New York Times described the scene:

On that bright spring afternoon, the five members of the Securities and Exchange Commission met in a basement hearing room to consider an urgent plea by the big investment banks.  They wanted an exemption for their brokerage units from an old regulation that limited the amount of debt they could take on. The exemption would unshackle billions of dollars held in reserve as a cushion against losses on their investments. Those funds could then flow up to the parent company, enabling it to invest in the fast-growing but opaque world of mortgage-backed securities; credit derivatives, a form of insurance for bond holders; and other exotic instruments.

In loosening the capital rules, which are supposed to provide a buffer in turbulent times, the agency also decided to rely on the firms’ own computer models for determining the riskiness of investments, essentially outsourcing the job of monitoring risk to the banks themselves.
Over the following months and years, each of the firms would take advantage of the looser rules. At Bear Stearns, the leverage ratio — a measurement of how much the firm was borrowing compared to its total assets — rose sharply, to 33 to 1. In other words, for every dollar in equity, it had $33 of debt. The ratios at the other firms also rose significantly.

The heady environment permitted traders to enter overoptimistic assumptions and faulty data into their models, jiggering the software to avoid setting off alarm bells.

The software models in question estimate the level of financial risk of a portfolio for a set period at a certain confidence level. As Benoit Mandelbrot, the fractal pioneer who is a longtime critic of mainstream financial theory, wrote in Scientific American in 1999, established modeling techniques presume falsely that radically large market shifts are unlikely and that all price changes are statistically independent; today’s fluctuations have nothing to do with tomorrow’s—and one bank’s portfolio is unrelated to the next’s. Here is where reality and rocket science diverge.

The causes of this fiasco are multifold—the Federal Reserve’s easy-money policy played a big role—but the rocket scientists and geeks also bear their share of the blame. After the crash, the quants and traders they serve need to accept the necessity for a total makeover.

For its part, the quant community needs to undertake a search for better models—perhaps seeking help from behavioral economics, which studies irrationality of investors’ decision making, and from virtual market tools that use “intelligent agents” to mimic more faithfully the ups and downs of the activities of buyers and sellers. These number wizards and their superiors need to study lessons that were never learned during previous market smashups involving intricate financial engineering: risk management models should serve only as aids not substitutes for the critical human factor.

A lone dissenter — a software consultant and expert on risk management — weighed in from Indiana with a two-page letter to warn the commission that the move was a grave mistake.
[Leonard D. Bole] said the computer models run by the firms — which the regulators would be relying on — could not anticipate moments of severe market turbulence.
[He] wrote to the commission on Jan. 22, 2004. “Has the trading environment changed sufficiently since 1997, when the current requirements were enacted, that the commission is confident that current requirements in examples such as these can be disregarded?”

From this weekend's Financial Times (bold text is mine):

With virtually every hedge fund imposing some restrictions on the ability of investors to get their money out, an artificial stability is being forcibly imposed both on the industry and on the markets.  While it is almost impossible to calculate just how much money is being locked up against investors' will, estimates run as high as $400bn.

Hedge fund redemptions had become such a big factor in the markets that, starting about two months ago, JPMorgan Chase started covering them in the markets section of its flagship weekly publication Global Data Watch. Redemption requests often force hedge funds to sell some of their best assets, just to raise cash to meet redemption demands.  Now, by freezing redemptions, natural selling pressure is temporarily in abeyance and market prices for a variety of securities are being supported in a way that is artificial.

But "by suspending redemptions, you delay the inevitable", says Loren Kasowitz, the founder of Guggenheim Partners, which also invests in hedge funds on behalf of a variety of clients.

Hedge fund managers cite a variety of reasons for the decision to hang on to their investors' money against their wishes.  First, they say if they let investors withdraw their money, they themselves may not have the money to repay lenders.  [Some funds] have cited the need to maintain minimum asset values to preserve their financing lines.  More importantly, managers claim that it is virtually impossible to sell many assets that don't trade on any exchange. They say their only exit is when these securities mature - they are essentially illiquid. But to many analysts, that kind of argument rings at least partly hollow. "There is always the possibility to sell - they just don't like the price," adds Mr Kasowitz.

[H]opeful thinking - that current market values cannot possibly reflect true economic value - is likely to prove illusionary. Today it is becoming clearer that it is the high returns of last year and the year before, when money was easy to borrow and interest rates were low, that were the aberration.  Because hedge fund managers promised investors high returns to justify their own generous fees, they had to use massive amounts of borrowed money to amplify their bets and generate returns.  That was possible precisely because interest rates were so low and it was easy to borrow. It was such leverage that made everything trade at levels that were in retrospect artificially high. Investment experts such as Mr Kasowitz believe that values are unlikely to return to those levels.  "If they allow redemptions, hedge fund managers know they will sell at a level that is nowhere near where they were marked and then they will have to mark everything down," he adds.

Slate has created a cool tree-ring-ish interactive graphic which shows the relative magnitude of this year's U.S. financial rescue efforts.  The images below, while interesting, lack the functionality of Slate's own cheat sheet.

Committed funds:

Leverage.  If there were one word that best sums up a significant contribution to the current financial system mess, and the primary driver behind recent market volatility, that is it. 

The latest in Marketplace's Whiteboard series of videos features an explanation of the role of deleveraging in today's markets.
Leveraging and deleveraging from Marketplace on Vimeo.