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Figure 7.32 Recollected events.
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kay, let s clarify. After decisively contributing to the worst crash in the history of the equity markets, Black-Scholes was, in fact, not rescued by amicable smile-con guring traders, but rather it was left to die. Black Monday so outrageously exposed the shortcomings of the model s dynamic hedging spirit that there was little option but to do away with it. BSM was indeed con ned to the dustbin of history. The previously model-compliant at volatility smile abruptly became a glowing grin, as traders said enough is enough and sent the miserably failing construct packing. From that point on, they may still use the machine formerly known as Black-Scholes, but they would manipulate the volatility parameter in such a way that the nal output would be something far different from Black-Scholes. As indicated in the prior section, another entirely possible possibility is that traders decided not just to manipulate the model into oblivion, but to actually stop using it (or to continue not using it, if that was the case before the crash) and to revert entirely to their animal spirits when pricing contracts. Learning from the mayhem, they would have pushed up the demand for extreme protection, making out-of-the-money puts costlier, which would
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Size = 392 Av. = 23.45
Option-adjusted spread analysis of more than one security at a time is an extremely powerful tool. It allows for security selection that can take advantage of the natural hedging relationships among securities and for the evaluation of the portfolio as an entity. For example, the portfolio manager might reject a given IO and a given PO as individual securities, because of high prepayment exposure or other risks. OAS analysis may show that the two securities in combination are very suitable candidates. Or it might reveal that the two securities do not complement each other over all possible interest rate paths. Such relationships are dif cult to determine without OAS analysis. For example, investors are at an extreme disadvantage buying IOs or POs based upon simple, static yield tables, which typically do not account for any shifts in prepayment rates or changes in forward rates.
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examinations do increase in accuracy in correlation with the number of questions that are asked. The laboratory and eld studies both show that the GKT is vulnerable to false-negative errors, which is the tendency to classify guilty examinees as innocent. Although such errors are far from desirable, they are in criminal investigations generally perceived as less serious than false-positive errors ( 11), which is the tendency to classify innocent examinees as guilty. It is not surprising that the GKT is vulnerable to false-negative errors. These occur when the suspect has forgotten or never knew the details about which the examiner asks. By the same token it is unsurprising that eld studies are more vulnerable to false-negative errors than laboratory studies. In laboratory settings researchers can increase the likelihood that guilty examinees remember the critical details, for example by carrying out the test directly after the guilty examinee has been given the critical information. In real life it may be considerably more dif cult to select items that culprits are likely to remember. In that respect, laboratory research masks this problem associated with the GKT.
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