For more information on our financial services offerings, contact us at:
Analytic Focus LLC
1116 20th Street South #406
Birmingham, AL 35205
Phone: (205) 672-9253
Fax: (205) 672-9255
E-mail: info@analyticfocus.com

Analytic Focus LLC
5218 Sagail Place
San Antonio, TX 78249
Phone: (210) 465-7838
E-mail: info@analyticfocus.com
Analytic Focus LLC
121 N Washington Street
Suite 300B
Alexandria, VA 22314
Phone: (703) 549-2682
Fax: (703) 483-3977
E-mail: info@analyticfocus.com

Portfolio Optimization

As operations in a financial institution become more complicated, there is a need to consider a variety of tradeoffs in terms of returns on investments. The interaction of accounts, the variety of outcomes to consider, and factors that are outside of the control of the institution make operations more difficult as the variety of choices of investment of limited resources expands.

Analytic Focus helps by considering rates of risk and rates of return for each type of investment, conditioning these on expected market conditions, and developing a strategy for portfolio optimization that considers all tradeoffs. Our models offer alternative strategies, finding where returns are similar under different strategies and impervious to external change.

Case Examples:

For the Office of Finance, Federal Home Loan Banks, we were responsible for project management and oversight of contracted research projects related to bond and swap valuations and GSE markets. Our responsibilities included research design, econometric modeling, and technical documentation based on the priorities established by the Director of Planning and Research in looking at the value of different portfolios of holdings.

For the FDIC, evaluated techniques to distribute returns on portfolio sales back to individual assets in the portfolio. This analysis was important to the responsibilities of the FDIC as receiver for failed banks to correctly allocate returns on sales back to the receiverships affected. This analysis also allowed the FDIC to ascertain rates of return on different types of assets, even though they were pooled together and sold with a common price.

For a large bank in the Northwest, we developed models to estimate likelihood of default and prepay in residential portfolios and credit card portfolios, and fit hazard models on the competing risks of default and prepay in its portfolio of loans. This information, combined with cost models, allowed the institution to do a better job of pricing loans and reserving against loss. AF developed a portfolio optimization solution that considered default and prepay rates, default correlation, and autocorrelation in loans it had originated. By examining timing and evaluating true recovery rates for collateral, we also developed a flagging system for loans to ensure loans at risk were tracked and handled on an efficient schedule. The client developed a longer term horizon for dealing with loans rather than the 12 month horizon that had become part of the corporate culture. The longer horizon allowed the client to become more efficient at predicting when loan review should become more frequent for a subset of loans and when to intervene to maximize the return on the loan when it became risky.