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In making his misunderstood attering, the quant-academic was assuming all along that BSM is used in the markets. The sophisticatedly vulgar tool was indisputably thought of as being widely popular among traders, an indelible inhabitant of trading oors and exchange pits around the globe. Scholes should have instantly gotten off his chair and run to the podium to hug the quant-academic for sending such life jacket his way. For you see, it is not entirely clear that (as we had come to religiously believe for more than three decades) BSM is in fact employed by pros. Since the appearance a couple of years ago of earth-shaking research by two former senior traders with quantitative knowledge, we can no longer safely assume that the sophisticated vulgarity should be deemed BSM or, even more Bastille-stormingly, that the sophisticated vulgarity is used at all. Perhaps option traders do not use mathematical devices as often as conventionally enshrined. It could all be the result of plain, staid, untheoretical supply and demand. In other words, the whole thing would be one big vulgarity, with absolutely no role for sophistication. This would obviously be a much bigger indictment of BSM and nancial economics than the mild effrontery of harmless name-calling. By taking for granted that BSM is used in real life, the quant-academic was throwing an olive branch, not a gauntlet, to the best-known exemplar of theoretical nance. Given the unprecedentedly powerful latter-day existence-denying criticisms of the model, theoreticians would be well advised to show gratitude, not derision, towards those still in the habit of toeing the traditionalist line and portraying BSM as an employed success.



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// Call Publishing API method delete_business DispositionReport objDispositionReport = objUDDIApiPublishing.delete_business (objDeleteBusiness); // Discard the Authentication token now objUDDIApiPublishing.discard_authToken (new DiscardAuthToken(objAuthToken.getAuthInfo())); // Check to see if the delete operation was // successful if (objDispositionReport == null) { System.err.println( Unsuccessful in deleting the business information from the registry. ); } else { if (objDispositionReport. resultIs(UDDIErrorCodes.E_SUCCESS)) { System.out.println( \nSuccessful in deleting the business information from the registry. ); } else { System.out.println( \nUnsuccessful in deleting the business information due to following reason(s): ); System.out.println(

Column D contains all the present values calculated, and the sum of that column is the sum of the present values. By definition, the sum of the present values (cell D16) should equal the NPV.

565 567 570 571 571 572 574

338 339 339





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When Excel evaluates the formula, it first evaluates the expression in the argument and then computes the square root of the result.

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Equation (9.5) is the formula for standard deviation, where RPi is the individual portfolio return observations, RP is the arithmetic mean return, and N is the count of returns. Note that because we are squaring the deviations, the standard deviation is affected more by outliers than the mean absolute deviation. Exhibit 9.6 illustrates the calculation of standard deviation for our fund, equal to 4.13%. The standard deviation for the benchmark is lower, 3.65%. Standard deviation is the primary statistic used to describe the variability in a pattern of returns. Because this variability is a proxy for risk, standard deviation of the periodic returns is the chief proxy for risk used in the management and analysis of investments. A higher standard deviation indicates a wider dispersion of returns around the mean return. A portfolio that has twice the standard deviation of another fund has twice the volatility as that fund. There are a few considerations we should keep in mind when using the standard deviation and related measures of risk. These include the number of observations used to form the statistic and the underlying periodicity of the data used.

Figure 3.2 Number-average molecular weight vs. extent of reaction for a simple step polymerization reaction.

In Step 3, you build the profile of your mail item. This includes the To recipients, the CC recipients, the BCC recipients, the Subject, the Body, and the Attachments. Note that the recipients are entered in quotes, and you separate recipients by a semicolon. The standard syntax for an attachment is as follows: .Attachments.Add File Path In this code, you specify the current workbook s file path with the syntax: ActiveWorkbook.Fullname. This sets the current workbook as the attachment for the e-mail. When the message has been built, you use the Send method to send the e-mail.

There are 23 commodity prices in the CRB Spot Index, while the CRB Futures Index has 21. Prices included in the CRB Spot Index that are not in the CRB Futures Index are burlap, butter, hides, lard, lead, print cloth, rosin, rubber, steel scrap, tallow, tin, wool tops, and zinc. One other significant difference is in the industrial weighting. Of the 23 spot prices included in the CRB Spot Index, 13 are industrial prices for a weighting of 56 percent. This contrasts with a 38 percent industrial weighting in the CRB Futures Index. It is this difference in the industrial weightings that accounts for the occasional divergences that exist between the Spot and Futures Indexes. To see why the heavier industrial weighting of the CRB Spot Index can make a major difference in its performance, divide the Spot Index into its two sub-indexes The Spot Raw Industrials and the Spot Foodstuffs.

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