the risk. Then, use R for the coefficient of correlation. Note that the use of ‘spread’ facilitates translation from learned journals to popular audiences that are less familiar with ‘standard deviation’. Authors that use the word ‘spread’ for the difference between a futures and a spot price, should relabel to ‘time premium’.
[112] In a personal discussion, Richard Gill (University Utrecht, KNAW) had doubts about my shorthand notation, and preferred E[x * Ix<0[x] where IA[x] is the indicator function with value 1 if x
A and 0 else. Gill’s notation no doubt increases definitory clarity, but the shorthand is not bad and has the advantage of being short.
[113] Alternatively, relative risk can be seen as proportional to another level. What is important in the present discussion is the distinction with conditional risk.
[114] For (relative) risk we don’t want to use the conditional distributions. For example, if there would be a small loss with a small probability p, the conditional might turn this in a large ‘risk’, since 1/p is would be a large number. So for risk we have a proper measure in the ‘probable value’ (loss * probability).
Risk is concerned with one’s worry that bad information might arrive while it may not arrive. The conditional applies only if indeed new information arrives that the returns will remain below that target level. (Though the conditional might remain hypothetical.)
[115] If people would work on welfare, we would speak about workfare. Workfare generally is more efficient, since people on benefit will not have the utility of idleness.
[116] In a purely mathematical tract, the Lemma would be the theorem, and the Theorem would be a corrollary.
[117] This is a strong claim of course. Policy makers are overloaded with data, and they have a hard time turning this into information. But this is often used as a cheap excuse too. They say ‘I didn’t know’ while they should have said ‘I hired an assistant who knew that he had to keep sensitive information from me so that I could later say ‘I didn’t know’.’ The crux of the argument is that policy makers are responsible, by definition, for structuring the information process such that they know the relevant facts. It is up to the jury whether they can be excused for real human mistakes and external errors.