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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 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 As with the iron condor, you want to avoid too many rolls to x the spread delta because you will accept the loss and costs of the roll and may not recover the premium The double diagonal is a high-volatility friendly spread, but if implied volatility collapses during the trade, the short near-term.

This shows that when the common satellite is changed from m to p, as long pm as the integer Nro is known, then the double-di erence integer relative to ip the new common satellite Nro can be easily computed from the doubleim di erence integers for the old common satellite Nro

This section considers the integer ambiguity resolution problem The problem has the general format described as follows Two sets of vector measurements are available with the form = = + + + N (8149) (8150)

Identify the sources for the data loads and destination systems for the extracts and their connection methods into the database, whether through SQL*Net, JDBC, or ODBC Identify any replication tools used either to feed into the source system or to replicate changes from the source to external systems Investigate the current replication tool s support for Oracle Databases

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where N is known to be an integer vector, the wavelength is accurately known, and and are mutually uncorrelated measurement noise processes with 100 The question to be resolved is how to determine N so that ( N) can be used as an unbiased measurement of instead of Throughout the discussion, we will only consider di erential GPS data, with the assumption that common-mode errors are small Failure to satisfy this assumption will a ect performance In the case of single di erences, 2 2 the covariance matrix for denoted as = I is diagonal, = I 100 , and m satellites will yield a set of m measurements The majority of the discussion will focus on double-di erenced measurements so that the

receiver and satellite biases are eliminated and the equations simplify to = R+ = R + + N (8151) (8152)

Capture the source code metrics for the custom scripts used for loads and extracts Document the tools or scripts used to perform the loads and extracts and whether they are proprietary to the third-party source technology Capture the ETL tools used for loads, extracts, or ongoing ETL; their complexity; connectivity and driver requirements; source databasespecific features used in ETL; and the tool support for Oracle databases

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