Patent №
US 7,698,202
Granted
2010-04-13
Filed 2007
Owner
AXIOMA, INC.
Lab
—
AI components
3
ml · planning · evo
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
11668294
Techniques for more accurately estimating the risk, or active risk, of an investment portfolio when using factor risk models are disclosed. This improved accuracy is achieved by identifying and compensating for the inherent “modeling error” present when risk is represented using a factor risk model. The approach adds one or more factors that depend on the investment portfolio and that explicitly compensate for factors that are unspecified or unattributed in the original factor risk model. These unspecified factors of the original factor risk model lead to modeling error in the original factor risk model. The approach can be used with a variety of different factor risk models, such as, fundamental, statistical and macro risk models, for example, and for a variety of securities, such as equities, international equities, composites, exchange traded funds (ETFs), or the like, currencies, and fixed-income, for example. The risk associated with modeling error in a factor risk model relative to a particular portfolio is identified and quantified. Knowledge of this risk associated with modeling error can be utilized when estimating risk, or active risk, using factor risk models or when constructing optimal portfolios by mean-variance optimization or other portfolio construction strategies and procedures that make use of factor risk models.
AI classification
Ownership
AXIOMA, INC.
assignment · 188190120
Assignors
STUBBS, ROBERT A., SCHMIETA, STEFAN H.
On an employer assignment, the assignors are typically the inventors.