That’s different than the number of contracts created isn’t it? If I were a speculator, I might buy and sell N contracts repeatedly over any given period just as equity and bond traders give and take positions. On the other hand, consumers don’t repurchase the same physical metal repeatedly. So the quantity comparisons in that paragraph are misleading, over-emphasizing speculative demand.

I don’t think it is misleading about the speculative demand because regardless of how many times the contracts are traded they are being traded speculatively.

Also, there is an inconsistency in two charts I can’t figure out. In one you compare China imports to LME stockpiles. There we see in 2010 LME stockpiles have significantly declined to the lowest point. In the second to the last chart labeled “Copper WCI Plot” you imply prices have risen way above where they should be given the size of stockpiles. But with stockpiles at the “lowest ever” it makes perfect sense for prices to be high. Notice “lowest ever” infers a time span. The time spans on those charts are not the same. The latter begins at the worst part of recent global economic activity when everyone is expecting a global depression. Naturally prices would be below “normal”.

The stockpile scale is inverted, so that the lowest point you are looking at is actually the highest point.

Also, LME isn’t the only stockpile. There are stockpiles in many places of the supply chain, and one can infer that mining production plans represent a form of stockpile – announced production cut backs would produce a similar price affect as declining physical stockpiles.

correct, but the International Copper Studies Group gives estimates of these total stocks. Notwithstanding some variation they tend to track LME stocks.

Thirdly, the supply demand curve has two inferred forces that aren’t obvious by your charts (and are in fact very difficult to measure even if you want to). The supply of financial resources available to trade for something of greater value, and the emotional demand of having something before another gets it. How does your data incorporate all of those stockpiles, production plans, and human factors?

The way look at it is that there is physical supply and demand for the metal and speculative supply and demand for the contracts (i.e. the paper, without the intention to take delivery). Pump money into circulation and it should boost speculative demand. Impossible to measure the human aspects.

http://library.wolfram.com/infocenter/MathSource/7590/

But, just a question, how do you schedule a task in Mathematica ???

thanks

You pointed out “In 2009 24.9 million contracts were traded on the LME”.

That’s different than the number of contracts created isn’t it? If I were a speculator, I might buy and sell N contracts repeatedly over any given period just as equity and bond traders give and take positions. On the other hand, consumers don’t repurchase the same physical metal repeatedly. So the quantity comparisons in that paragraph are misleading, over-emphasizing speculative demand.

Also, there is an inconsistency in two charts I can’t figure out. In one you compare China imports to LME stockpiles. There we see in 2010 LME stockpiles have significantly declined to the lowest point. In the second to the last chart labeled “Copper WCI Plot” you imply prices have risen way above where they should be given the size of stockpiles. But with stockpiles at the “lowest ever” it makes perfect sense for prices to be high. Notice “lowest ever” infers a time span. The time spans on those charts are not the same. The latter begins at the worst part of recent global economic activity when everyone is expecting a global depression. Naturally prices would be below “normal”. Also, LME isn’t the only stockpile. There are stockpiles in many places of the supply chain, and one can infer that mining production plans represent a form of stockpile – announced production cut backs would produce a similar price affect as declining physical stockpiles. Thirdly, the supply demand curve has two inferred forces that aren’t obvious by your charts (and are in fact very difficult to measure even if you want to). The supply of financial resources available to trade for something of greater value, and the emotional demand of having something before another gets it. How does your data incorporate all of those stockpiles, production plans, and human factors?