A nice decline in Sterling is just what we need :)Balance of payments issues, short-term growth prospects, uncertainty over Brexit, decoupling from the US cycle, caught in the Eurodebacle.I think a soft £ is overdue, and helps us in the currency wars to boot!
Can a net importer have a 'petro-currency'? I've long held the view that listing foreign assets on the LSE / AIM (and selling £50m flats in London) means we get away with our trade deficit more than we might.On that basis I'd expect that a big sell-off in these sterling denominated raw materials would cause fall in the pound.
Can a net importer have a 'petro-currency'?in financial risk-management terms, if A is 99% correlated with B, it is (essentially) the same exposure, +/- basis-riskof course, 3 months of high correlation doesn't prove a damn' thing (though if you look at the 12-month charts they are quite closely correlated too, which starts to be a bit more interesting)
Or the fall in the price of Brent may be strongly linked to the fall in crime in the UK too. Or any other falling index you care to mentionhttp://www.ons.gov.uk/ons/resources/figure1_tcm77-318626.png
There is a whole website devoted to spurious correlations.http://www.tylervigen.com/spurious-correlationsBut the world of currency speculation is closed to me, ditto oil, so I have no theory.
So:a) Can you quantify the basis risk?b) Is there actually any point?
b) all insights on serious topics can be useful![didactic mode]E.g. for policy-making. Or for aggregating / netting your exposures appropriately, so you don't unwittingly double-up, or waste money hedging when you might already have a natural offsetAlso, you may be able to hedge exposure A more easily using an instrument from market B, where there may be better liquidity, or access for you, or lower dealing costs, or more precise instruments, or natural offsets for you, etc etc(some US oil companies used to hedge their Brent exposures using the WTI market, with which they were ultra familiar. That was fine in the '90s when the correlation was 99%; OK, though not so justifiable in the more volatile '00s; but absolutely sucked when it cratered in 2011)a) = a purely statistical exercise once you've (i) *identified* there's an appropriate causal relationship (which might be: A causes B; or B causes A; or both A & B have the same root cause) (ii) decided the interval over which to make the calculationFor good order you should then check the entire data-set for paradigm-shifts within the interval, using several statistical tests, then revisit your assumptionshere endeth the lesson [/didactic mode]
Apparently, paying by card (vs cash) is correlated with being fat.
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