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Let s look at an example of purchasing at-the-money puts on an individual stock Figure 412 illustrates an option chain on Microsoft with July and October expirations showing In the gure let s look at the 1800 put options in October We can calculate the breakeven and pro t-and-loss scenario of buying ve of these October 1800 puts at $275 We know that our out-ofpocket cost will be $1,390 including a $1500 commission ($275 500 shares $1500) which will also be our maximum risk on the position In Figure 412 you can see that the underlying MSFT stock is trading $1833 and that this is an $1800 put so it would be considered at the money The breakeven can be quickly calculated for put options at expiration: Strike price premium (costs of trading/number of contracts or shares) breakeven $1800 $275 ($1500/500) $1495 breakeven When we place this position on a model, we can see how the option behaves with changes in the underlying asset (See Figure 413) You can see from the gure that as the price of Microsoft stock declines, the pro tability of the put options increases The solid line represents the options pro t and loss at expiration, while the dashed line is about halfway to expiration, and the dotted line represents the day of the transaction The maximum risk on the position occurs at an underlying price of $1800 and above at expiration This option has a delta of 420, so it will gain $042 for each $1 the underlying stock price declines Calculations for time value decay, volatility changes, and changes in the delta of the option are done in the same fashion as for call options If the ve purchased $1800 puts experience 100 days of time value decay, then we

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A three term (fourth order) expansion of the cosine has been used The condition |x| 157 indicates the time t is in the night 10 If needed, calculate the L2 ionospheric correction: t2ion = 772 t1ion 602 (C17)

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One of the engines Oracle offers is Essbase, a MOLAP database engine that is external to the Oracle relational database (and therefore is deployed outside of the Oracle Exadata Database Machine) Essbase is especially useful where business analysts want to extract data from Oracle and other data sources for custom analyses of their own design But in some situations, data volumes can be so large that moving data out of an Oracle database across a network link and into Essbase is not desirable In these scenarios, deploying in-database OLAP can make sense as an alternative approach Oracle provides in-database OLAP via the Oracle OLAP Option OLAP cubes are stored as embedded objects called analytic workspaces within the relational structure of the Oracle database The cubes are created by defining dimensions, levels, and hierarchies within dimensions, attributes, and mappings from relational source schema to the OLAP cube dimensions Cubes and other dimensional objects appear in the Oracle database data dictionary Oracle s Analytic Workspace Manager (AWM) is commonly used as the tool for creating and managing this process as an alternative to using SQL commands AWM can also be used to set up and populate allocations of data down a hierarchy Access to the OLAP Option analytic workspace data structures is most commonly via SQL, though a Java OLAP application programming interface (API) is also supported for applications development A variety of functions are available within the OLAP Option, including analytic functions, arithmetic functions, aggregations, statistical time-series, and allocations Forecasts can be generated for short periods using a timeseries approach and for longer periods by doing causal analysis using statistical regression As of Oracle Database 11g, cube-based materialized views provide views over the cubes that have already been created, populated, and aggregated As a result, SQL queries to an Oracle relational database will be transparently redirected to the proper level in the OLAP Option cube to answer a query, much the same as would occur where any materialized view is present Cube-based materialized views also enable OLAP Option cube data refreshes to be handled like those of any materialized views The OLAP Option can provide a highly desirable and simpler alternative database structure in comparison to maintaining large quantities of materialized views across many dimensions in an Oracle relational database.

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