8

Example from recent memory. Right before New York open, Bloomberg posts an article saying country R's local news reported that R's government auditor said that country V has defaulted to R's loans to V. Alsmost everyone goes, oops, we expected V to default only later, not now! And they try to sell V's hards-currrency bonds, finding very few bids. Very few ...


4

They would place an order in the direction they anticipate their information will eventually move the market, and hopefully get filled before anyone notices.


3

Notice that linear correlation is just a standartized measure of variability for two variables around their mean values, loosely speaking. In your concrete case of a linear correlation between stock returns, it won`t say anything about magnitude because the mean of each return series go into the computation. You can only say those stock returns have a strong ...


2

In (value at) risk calculations, we are commonly interested in the risk of changes of the value of our portfolio that are induced by external factors, i.e. thru changes in market prices. To that end, we usually fix the invested asset universe and the market environment (e.g. rates / prices / vols) at the onset of our risk calculation and compute a base ...


1

Should have been a comment as there are already brilliant answers, but posting as an answer only because it is a bit lengthy! Ignoring the sample/population nuances, here is a simple illustration that correlation is an indicator of the strength (and direction) of the linear relationship but not the 'magnitude' : $\text{Correl}(Y,X)= \frac{\text{Cov}(X,Y)}{\...


1

The sad fact here is that "earnings" on the numerator can be measured in a multitude of ways. The "per share" should be consistent (although these can differ a little, depending on whether one uses the year-end vs the year-average share count). More normal is the variation across different "E" figures. First of all, you need to ...


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