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market value depend purely on the levels of the index In other words, the VIX is one of those things where misinterpretation and confusion can have critical real-life consequences And yet the inescapable fact is that the VIX has been consistently misunderstood, misrepresented, and misspoken about Conventional wisdom has it that the VIX stands for expected future stock market volatility, purportedly estimated from the market prices of liquid equity options That is why it tends to be described as investors fear gauge A high VIX is consensually characterized as corresponding to enhanced worries on the part of option players The conventional wisdom (espoused by the world s leading nancial media outlets) is that the VIX equates expected movement in the S&P 500 index over the next month.

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Levy: But the same bene t can be achieved by adding to a long-only portfolio a less than perfectly correlated asset with similar risk and return. The unique advantages of market neutral long-short portfolios come only from an integrated optimization.

This discrepancy goes to the heart of what quants.

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Tutorial in using the Barcode Fonts in Microsoft Excel 2007 , 2010, 2013 or 2016. All the functions available in the Encoder like generating a check digit, ...

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For example, a VIX of 30 would typically be seen as irrefutable evidence that the options market expects the S&P 500 to move up or down by 30 12 = 866% (VIX is quoted on an annualized basis) during the following 30 days There are several reasons why all this is not exactly right To illustrate, let s brie y revisit the VIX s lifeline In 1993 the CBOE introduced the VIX, with the noble idea of making it the overall accepted benchmark for market volatility In order to perform such function, the original VIX was made to re ect the levels of implied volatility for one-month S&P 100 at-the-money options, assuming that traders are using the Black-Scholes model when pricing those options That is, for every quoted market option price, a corresponding implied volatility level could be obtained by reverse-engineering the Black-Scholes formula (ie.

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There are three primary methods for calculating impurity: misclassi cation, Gini, and entropy. In the following examples the entropy calculation will be used; however, the other methods give similar results. To illustrate the use of the entropy calculation, a set of ten observations with two possible response values (hot and cold) are used (Table 6.18). All possible scenarios for splitting this set of ten observations are shown: Scenario 1 through 11. In scenario 1, all ten observations have value cold whereas in scenario 2, one observation has value hot and nine observations have value cold. For each scenario, an entropy score is calculated. Cleaner splits result in lower scores. In scenario 1 and scenario 11, the split cleanly breaks the set into observations with only one value. The score for these scenarios is 0. In scenario 6, the observations are split evenly across the two values and this is re ected in a score of 1. In other cases, the score re ects how well the two values are split. The formula for entropy is:

Felber et al present three different approaches for introducing object groups in CORBA, dependent on the position of the group communication module relative to the ORB [6] These are the interception approach, the integration approach, and the service approach The work covers the third alternative The object group service (OGS) uses different CORBA objects to implement fault tolerance related services Narasimhan et al developed and implemented the idea of operating system level interceptors to provide fault tolerance to CORBA [15] The result of research efforts in this direction is the Eternal System With this approach, an ORB s functionality can be enhanced for fault tolerance without changes in the ORB, or in the application DOORS is a fault-tolerant infrastructure built using the service approach [3, 16] Application objects register to DOORS in order to be made fault-tolerant Fault tolerance services are realized with two components: ReplicaManager and WatchDog.

, the number that traders are assumed to be inputting under the formula s volatility gure) This original approach presents two big problems First, implied volatility is not the same as expected future real volatility Many people seem to continue to believe so, essentially assuming that the number traders consensually input under the volatility parameter is their consensual expectation of future turbulence However, this is not exactly accurate Implied volatility would rather be simply a conduit used by traders to arrive at the desired price of an option, a catch-all that would include all aspects deemed relevant by traders, and which are not fully captured by the (famously imperfect and unrealistic) Black-Scholes model It is.

where t0 is the total thickness of the lens. This expression is simpli ed by using paraxial approximation stated by s x2 y2 x2 y2 1 1 Ri 2R2 i 9:2-5

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Solution: Just note that you need to add the * (asterisk) to the front and tail of your data. You can catch up here.

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