Valuation prediction models in situations with missing inputs

Details Valuation prediction models in situations with missing inputs Valuation prediction models in situations with missing inputs

2007-01-16

2007-01-16

Millin, Vincent (Department: 3624)

Data processing: financial, business practice, management, or co

Automated electrical financial or business practice or...

Finance

C705S035000, C705S037000

Reexamination Certificate

active

09745821

ABSTRACT:
A method of valuation of large groups of assets by partial full underwriting, partial sample underwriting and inferred values of the remainder using an iterative and adaptive supervised and unsupervised statistical evaluation of all assets and statistical inferences drawn from the evaluation and applied to generate the inferred values. Individual asset values are developed and listed in tables so that individual asset values can be rapidly taken from the tables and quickly grouped in any desired or prescribed manner for bidding purposes. The assets are collected into a database, divided into categories by credit variable, subdivided by ratings as to those variables and then rated individually. The assets are then regrouped according to a bidding grouping and a collective valuations established by cumulating the individual valuations.

REFERENCES:
patent: 6035287 (2000-03-01), Stallaert et al.
patent: 2001/0037278 (2001-11-01), Messmer et al.
Gath, I. and Geva, A.B., “Unsupervised Optimal Fuzzy Clustering, ” IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-11, No. 7, pp. 773-781, Jul. 1989.
Bezdek, James C.; Hathaway, Richard J.; Sabin, Michael J.; and Tucker, William T., “Convergence Theory For Fuzzy c-Means: Counterexamples and Repairs,” IEEE Trans. Syst., Man, Cybern., vol. SMC-17, No. 5, pp. 873-877, Sep./Oct. 1987.
Dunn, J.C., “A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters,”J. Cybernetics, vol. 3, No. 3, pp. 32-57, 1973.
L. Breiman, J.H. Friedman, R.A. Olshen and C.J. Stone (1984),Classification and Regression Trees, Chapters 1, 2, 3, 8 and 11, Wadsworth, Belmont, CA.
Brealey, Richard A. and Myers, Stewart, C.,Principles Of Corporate Finance.
Efron, Bradley and Tibshirani, Robert J., “An Introduction to the Bootstrap,” Chapman & Hall publishers.

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