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We start with a statement and proof for Gaussian processes. Theorem 3.2 (Gaussian Rice Formula). Let X = {X(t) : t I } , I an interval on the real line, be a Gaussian process having C 1 -paths. Let k be a positive integer. We assume that for every k pairwise distinct points t1 , . . . , tk in I , the joint distribution of X(t1 ), . . . , X(tk ) does not degenerate. Then

Fat Tony would have taken a look at those low numbers being reported before the credit crisis and would have understood that such placidity was entirely based on historical data that included negligible activity in the very (high-risk) areas where banks had been aggressively diving into for the past few years He would have understood that the numbers were meaningless (don t get him started on Normality!) and that they were encouraging dealers to accumulate funky exposures in a highly leveraged way Consequently, he may have shorted banks stock Dr John, on the other hand, would have seen only prudently scienti cally managed portfolios that didn t seem to forebode malcontent, instantly contacting his broker and buying some Bear Stearns, Merrill Lynch, and Lehman Brothers shares The nancial world was once entirely dominated by Fat Tonys It still, to a large degree, largely is.

y 3/2 4(n 2)! y 3/2 n 2 4(n 2)!

There are tons of important areas that have not succumbed to quanti cation But when it comes to undeniably in uential roles such as risk management and (some) trading, Dr John types and Dr John ideology have taken over The conventionalism that market activities require rocket science has, after three decades of hammering down the message, become stringently unassailable in plenty of quarters We need a new approach The adoration of unworldly theories and their implementation have caused too much mayhem We need to stop treating quantitative constructs as reliable doctrine, and start to reconsider the competitive advantage of experience-honed human common sense.

where lmin is the minimum eigenvalue of A. If A is highly ill-conditioned, the condition number of A equal to lmax =lmin is large, and convergence may be very slow. If ak is optimized at each iteration, the method is called the method of steepest descent. The optimal value of ak is given by ak gtk gk gtk Agk 14:17-6

First, the test is vulnerable to false-positive errors, that is, the false accusation of innocent suspects Introducing CQT verdicts in criminal courts could thus result in a substantial number of innocent suspects being falsely convicted Second, the CQT has a weak theoretical foundation CQT proponents seem to acknowledge the theoretical problems with their test, but believe that it is acceptable to use a test without having a complete understanding of the underlying theory (Raskin & Honts, 2002) I think this point of view is problematic The bene t of a sound theory is that someone can predict when a test does and does not work Take for example the X-ray equipment used in airport security screening Since there is full understanding about how materials are represented in X-ray images, one can accurately predict how different types of material show up on the X-ray screens.

Without a theory, no predictions can be made Perhaps certain people are at high risk of failing the CQT, thereby increasing the likelihood that they will be falsely accused, and perhaps others are at low risk of failing the CQT, thereby increasing the likelihood that they will be undetected Also, perhaps the CQT is more suitable to use for some types of crime than for other types of crime Without a theory we do not know Apart from not having met the Daubert criteria, the second reason why CQT outcomes should not be admissible in criminal courts is that it is not standardised (Ben-Shakhar, 2002; Ben-Shakhar, Bar-Hillel, & Lieblich, 1986) The CQT is not an objective test, and, for example, CQT outcomes can be in uenced by the beliefs examiners have about the guilt of examinees prior to the test.

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