More.

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“A financial adviser or stock broker should be licensed to provide any consultation on investment in securities.”

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I side with Joe Terranova contra Dennis Gartman and Tim Seymour for the next $50 in gold (12:20), but it’s not like I’m net short across all personal accounts or anything.

[Download this post to watch the embedded video, if your feed reader does not show it to you.]

Editor’s Addendum: A related video….

But in shorter time-frames gold critics do have half a point. Since 2003, on a daily basis, gold returns have only been 12.5% correlated to changes in the inflation rate implied by 10-year TIPs. On a monthly basis, gold returns are 9% correlated to those of the TIPs spread.

We can look back further if we examine the the monthly performance of gold versus year-over-year changes in the CPI index. The CPI index for a given month is released in the subsequent month, so CPI monthly values are shifted forward in this study to correspond to the month of their release. The YoY change in CPI is further assumed to be the market’s expectation of future inflation. All gold prices here are daily averages based on the London PM fix through December 1974, and Comex/CME spot thereafter.

Ignoring the fact that gold generally rose in this period, it doesn’t do particularly well when inflation is elevated by this definition. A cut-off of 4% was used because it was the round number that most nearly bisected the 501 months in question, but the pattern holds-up when this parameter and other assumptions are varied:

So what does gold hedge against? Gold does well when real returns are low. You can’t consider inflation without looking at prevailing rates and growth. The rates used below are the average of daily 10yr constant maturity rates (GS10) within a given month. As Larry David would say, “pretty … pretty good”:

3% was used because it is again the round number that most nearly bisects the observations, but it can be varied without changing the essential result. There are also simple ways to define low real returns without a fixed parameter that show similar performance breakdowns with very different distributions of months. Now, these are retrospective studies, not trading systems, but obviously there is little chance that those returns were drawn from populations with the same mean.

It’s surprising that thoughtful types like Nouriel Roubini and Martin Feldstein have questioned gold’s inflation hedging, but didn’t mention this point — it seems glaring: people hold the relatively useless metal when real rates and opportunity cost are low. This simple point somehow never comes through in the noise surrounding gold: the glib Spam-sagacity vs. the Fall of The Republic, all the go-to arguments.

Clearly there are other factors that may throw the model off for long stretches of time. These may be false positives (e.g. non-dollar weakness) or false negatives (e.g. if gold is monetized to the point that it rises in deflation).

Putting aside the current weakness related to the Euro and elevating risk aversion, since I’m expecting real rates to be on the low end compared to the late 20th century, my bias is still long gold. If yields should rise, especially if they are driven by vigilance, gold might make less sense.

[Cross-posted with minor changes from Seeking Alpha]

[...] If I interpret correctly what you suggest, this will be equivalent to a “prediction market on a prediction market”, aka “options on markets”: Guess where the price of a long term market will be at set points in the future, before the expiration of the long-term market. InTrade experimented with such contracts last Fall (the X contracts). I was initially fascinated. However, we soon realized that such markets do not offer much additional information: Current price of the long-term contract and time to expiration are enough to determine the optimal price of the “X” contract.

The solution: Bite the bullet and have a long-term contract, based on a verifiable outcome. If you are interested in having checkpoints along the way, use conditional prediction markets (e.g., see the tax features, conditional of the result of the presidential election). Or think harder of what you are trying to measure and build a contract that has a verifiable outcome early on.

Previously: Wiser Than The Stock Market — NOT

UPDATE: Andrew Page + Henry Blodget

SELL SELL SELL

REALITY CHECK:

The stock market is up about 12% since Ben Shannon’s “sell sell sell” call on July 10th.

Spot the 10th on the chart… Ben Shannon sold the exact bottom immediately before the rally.

Thanks to Deep Throat for the tip.

UPDATE: Ben Shannon on his “SELL” market call

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I like the way they color this electoral college map —with 5 colors only (simplicity is good). It is very clear and usable, I believe. You can see 6 states in gray (“too close to call”). I am heavily betting on Barack Obama for Florida and North Carolina. There will be a good payoff, next Tuesday —maybe.

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Who will win Florida in the 2008 Presidential Election?

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Who will win North Carolina in the 2008 Presidential Election?

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Explainer On Prediction Markets

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A prediction market is a market for a contract that yields payments based on the outcome of a partially uncertain future event, such as an election. A contract pays $100 only if candidate X wins the election, and $0 otherwise. When the market price of an X contract is $60, the prediction market believes that candidate X has a 60% chance of winning the election. The price of this event derivative can be interpreted as the objective probability of the future outcome (i.e., its most statistically accurate forecast). A 60% probability means that, in a series of events each with a 60% probability, then 60 times out of 100, the favored outcome will occur; and 40 times out of 100, the unfavored outcome will occur.

Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism —with or without an automated market maker.

Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that the traders bring when they agree on prices. These event derivative traders feed on the primary indicators (i.e., the primary sources of information), like the polls, for instance. (Garbage in, garbage out… Intelligence in, intelligence out…) Armed with these bits of information, the speculators then trade based on their anticipations, which will be either confirmed or infirmed. Hence, the prediction markets (which are more than just an information aggregation mechanism) are a meta forecasting tool.

The value of a set of prediction markets consists in the added accuracy that these prediction markets provide relative to the other forecasting mechanisms, times the value of accuracy in improved decisions, minus the cost of maintaining these prediction markets, relative to the cost of the other forecasting mechanisms. According to Robin Hanson, a highly accurate prediction market has little value if some other forecasting mechanism(s) can provide similar accuracy at a lower cost, or if very few substantial decisions are influenced by accurate forecasts on its topic.

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More Info:

- The Best Resources On Prediction Markets = The Best External Web Links + The Best Midas Oracle Posts

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More Charts Of Prediction Markets

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As of this morning, the Dow Jones is barely above the 8,000 level (8,175.77), and the futures say that the stock market will rebound, at least in the first hours. However, I am bearish. I would bet that the Dow Jones will stay around the current level (or lower) until Election Day. In other words, I am betting on the red, on the chart below.

At what level will the Dow Jones Industrial Average close on Election Day?

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[*] And if Emile (whom we highly respect, overall) is pissed off by that statement, then, great, that’s a cool unintended collateral consequence.

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