among nine big economies, stock market correlations have averaged around 0.5 since the 1960s. in other words, for every 1 percent rise (fall) in, say, american prices, share prices in the other markets typically rise (fall) by 0.5 percent.

the economist 11.8.1997

a correlation of 0.5 does not indicate that a return from stockmarket a will be 50% of stockmarket b's return, or vice-versa..a correlation of 0.5 shows that 50% of the time the return of stockmarket a will be positively correlated with the return of stockmarket b, and 50% of the time it will not.

letter to the economist 11.22.1997

i believe both these assertions are false but can't counterexample
first, correlation measure is not unique
even assuming both are referring
to sample-based, pearson's product moment
socrates, definitions...
"typically"? 50% of "the time"?
but worse, for the application at hand
the q is moot:

as if from a broken record
you can again hear the same warning
this time amplified. if
i want to assign meaningful probabilities
to very rare events
i cannot escape the link between the frequency
of data collection
the relevance of the data and the rarity of the event
in question
and if the event depends on the codependence
among
very many variables, the complexity
of the problem
literally explodes
very rare
events are not just
bigger cousins of normal
occurrences. they belong to a different species
riccardo rebonato / global director market risk + quant r&a: royal bank of scotland
plight of the fortune tellers, 2007