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After all, if an algorithm is exponential, why not wait it out until Moore s law makes it feasible But in reality the exact opposite happens: Moore s law is a huge incentive for developing ef cient algorithms, because such algorithms are needed in order to take advantage of the exponential increase in computer speed Here is why If, for example, an O(2n ) algorithm for Boolean satis ability (SAT) were given an hour to run, it would have solved instances with 25 variables back in 1975, 31 variables on the faster computers available in 1985, 38 variables in 1995, and about 45 variables with today s machines Quite a bit of progress except that each extra variable requires a year and a half s wait, while the appetite of applications (many of which are, ironically, related to computer design) grows much faster.



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An example of the double diagonal is in the S&P example selling the May 855 call option for 3510 and buying the June 865 call option for 4570 while selling the May 825 put for 3650 and buying the June 815 put for 5150 Assuming that the market stayed within the range of the trade, you would capture 7160 against the purchase of 9720 on the deferred options The double diagonal is an excellent method of building premium against the long spread when the market stays within the range of the short options The ideal scenario is this: once the time value has reduced or been exhausted from the short options, you would roll the short strangle forward to the next contract month to create the iron condor with some extra cash already built into the spread.





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MEADOWS JC: Disturbed perception of colors associated with localized cerebral lesions Brain 97:615, 1974 MERZENICH MM, BRUGGE JF: Representation of the cochlear partition on the superior temporal plane of the macaque monkey Brain Res 50:275, 1973 MESULAM M-M (ed): Principles of Behavioral and Cognitive Neurology Oxford, Oxford University Press, 2000 MESULAM M-M: From sensation to cognition Brain 121:1013, 1998 MICHEL D, LAURENT B, CONVERS P, et al: Douleurs corticales: Etude clinique, electrophysiologique, et topographique de 12 cas Rev Neurol 146:405, 1990 MILLER NR: Walsh and Hoyt s Clinical Neuro-ophthalmology, 4th ed Vol 1 Baltimore, Williams & Wilkins, 1982, pp 83 103 MILNER B: Psychological defects produced by temporal lobe excision Res Publ Assoc Res Nerv Ment Dis 36:244, 1956 MILNER B: Interhemispheric differences in the localization of psychological processes in man Br Med Bull 27:272, 1971.

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In contrast, the size of the instances solved by an O(n) or O(n log n) algorithm would be multiplied by a factor of about 100 each decade In the case of an O(n2 ) algorithm, the instance size solvable in a xed time would be multiplied by about 10 each decade Even an O(n 6 ) algorithm, polynomial yet unappetizing, would more than double the size of the instances solved each decade When it comes to the growth of the size of problems we can attack with an algorithm, we have a reversal: exponential algorithms make polynomially slow progress, while polynomial algorithms advance exponentially fast! For Moore s law to be re ected in the world we need ef cient algorithms As Sissa and Malthus knew very well, exponential expansion cannot be sustained inde nitely in our nite world Bacterial colonies run out of food; chips hit the atomic scale.

This is an excellent method for increasing premium returns using the same cover trade positions one or more times In the example we would need to capture only about 2600 additional points between the two new June short options to create the iron condor for a credit This also gives the exibility of having a reduced cost long strangle if the market is not in a position to short additional premium on the June For risk control on the double diagonal, typically you have to have the same risk control setup as for the iron butter y or iron condor For the double diagonal, however, it is not uncommon for traders to allow the near-term spread to be exercised and create a synthetic option with the deferred option position.

Moore s law will stop doubling the speed of our computers within a decade or two And then progress will depend on algorithmic ingenuity or otherwise perhaps on novel ideas such as quantum computation, explored in 10..

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