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February 26, 1975 was a business-as-usual day at New York Telephone s lower Manhattan switching center. Located at 2nd Avenue and 13th Street, the massive 11-story building was the telephony nerve center for 12 Manhattan exchanges that provided service to 300 New York City blocks, including 104,000 subscribers and 170,000 telephones. Within the service area were six hospitals, 11 firehouses, three post offices, one police station, nine schools, and three universities. The building was massive, but like most central offices was completely invisible to the public. It was just a big, windowless structure that belonged to the telephone company. No one really knew what went on in there; nobody cared. When night fell, most of the building s employees went home, leaving a small crew to handle maintenance tasks and minor service problems. The night was quiet; work in the building was carried out routinely. It was going to be a boring evening. At 12:30, just after midnight, a relatively inconsequential piece of power equipment in the building s subbasement cable vault shorted and spit a few errant sparks into the air around it. It caused no alarms



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Although the t-test was, in this example, calculated for a sample of trade profit/loss figures, it could just as easily have been computed for a sample of daily returns. Daily returns were employed in this way to calculate the probabilities referred to in discussions of the substantitive tests that appear in later chapters. In fact, the annualized risk-to-reward ratio (ARRR) that appears in many of the tables and discussions is nothing more than a resealed t-statistic based on daily returns. Finally, a con$dence interval on the probability of winning is estimated. In the example, there were 16 wins in a sample of 47 trades, which yielded a percentage of wins equal to 0.3404. Using a particular inverse of the cumulative binomial distribution, upper 99% and lower 99% boundaries are calculated. There is a 99% probability that the percentage of wins in the population as a whole is between 0.1702 and 0.5319. In Excel, the CRITBINOM function may be used in the calculation of confidence intervals on percentages. The various statistics and probabilities computed above should provide the system developer with important information regarding the behavior of the trading model-that is, if the assumptions of normality and independence are met and





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Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website.

if the sample is representative Most likely, however, the assumptions underlying the t-tests and other statistics are violated; market data deviates seriously from the normal distribution, and trades are usually not independent In addition, the sample might not be representative Does this mean that the statistical evaluation just discussed is worthless Let s consider the cases What if the Distribution Is Not Normal An assumption in the t-test is that the underlying distribution of the data is normal However, the distribution of profit/loss figures of a trading system is anything but normal, especially if there are stops and profit targets, as can be seen in Figure 4- 1, which shows the distribution of profits and losses for trades taken by the lunar system Think of it for a moment Rarely will a profit greater than the profit target occur.

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because it didn t actually fail. One of the sparks, however, fell on a piece of insulation and began to smolder. The insulation melted and began to burn, changing from a smoldering spot on the surface of a cable to a fullblown fire. Soon the entire cable vault was aflame. Cables in a central office leave the cable vault on their way to upper floor switching equipment through 6-inch diameter holes cored in the concrete floors of the office. The fire burned its way up the cables, exited the cored holes, and spread from floor to floor. Soon all of the lower floors of the building were engulfed, and New York Telephone was on its way to hosting the single worst disaster that any American telephone company has ever experienced. Emergency service vehicles converged on the building. They evacuated everyone inside and began flooding the lower floors with hundreds of thousands of gallons of water. Smoke and steam billowed up and out of the structure (see Figure 3-1), severely damaging equipment on the upper floors that had not, as yet, been affected by the fire.

Figure 15-2. Setting a Silverlight 4 application to run with elevated trust (as a trusted application) in outof-browser mode When you install the Silverlight out-of-browser application with elevated trust, a security-warning window (instead the regular out-of-browser application installation window) will be displayed, warning that the installed application publisher is not verified and potentially can access the local computer data and resources. If you choose to install the application, the Silverlight application will be installed to the computer and you can run the application in the out-of-browser mode with elevated trust. Figure 15-3 shows the standard out-of-browser application installation window, when the elevated trust is not enabled. Figure 15-4 shows the out-of-browser application installation window with a security warning, when the elevated trust option is enabled and the application is not signed.

Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website.

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