Analytic Space

Typically, pricing models and market data are viewed as two separate processes with no inherent dependency between them. This often gives rise to model uncertainty. Model uncertainty poses a number of challenges to an organization.

• Model uncertainty is tpically not quantified and monitored on a daily basis
• Dependence on underlying market data is often misunderstood
• No easy processes to quantify model uncertainty vs. risk allocation vs. regulatory cost of capital
• Often there is a lack of transparency with respect to closing prices and price uncertainty

Analytic Space is a robust, flexible and easily customizable portfolio pricing and risk analysis framework that provides a transparent pricing approach for the valuation and price analysis for exchange traded and OTC cash and derivatives instruments. Analytic Space amalgamates market data, pricing models and risk analysis into a centralized service thus providing front, middle office and valuation teams with readily sharable, consistent sets of market data, pricing analytics and valuation tools needed for a comprehensive understanding of the relationship between pricing models and market data.

Analytic Space provides a customizable portfolio pricing and risk analysis framework and robust set of algorithms for the construction and effective use of yield curves, volatility surfaces and other market data. Yield curves may be constructed for any trading currency around the globe. Yield curves can easily be shared by end users and the curves can be archived along with the raw market data used in curve construction. In addition, end users may import externally generated yield curves for use within Analytic Space.

Analytic Space helps address model uncertainty by providing the ability to create and save advanced sets of market objects and analytics in a centralized framework whose benefits include:

• Transparent pricing
• Ability to save yield curves and surfaces for historical analysis
• Better understanding of the factors driving model parameters
• Model portability for effective team collaboration
• Ability to utilize multiple analytic models
• Market shift scenarios are inherently built into the models
• Evidence based model validation
• Using different versions of the same model for auditing and backwards compatibility purposes