By Maurizio d'Amato, Tom Kauko
This ebook addresses numerous difficulties relating to automatic valuation methodologies (AVM). Following the non-agency loan obstacle, it deals quite a few techniques to enhance the potency and caliber of an automatic valuation technique (AVM) facing rising difficulties and diverse contexts. Spatial factor, evolution of AVM criteria, multilevel types, fuzzy and tough set functions and quantitative ways to outline comparables are only the various themes discussed.
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Extra info for Advances in Automated Valuation Modeling: AVM After the Non-Agency Mortgage Crisis
Table 7 Multilevel analysis: ﬁxed part . . . . . . . . . . . Table 8 Residuals of the second level . . . . . . . . . . . Table 9 Residuals of the second level . . . . . . . . . . . Table 10 Residuals of the third level: district . . . . . . . . . Table 11 Position ratio of commercial area per district. . . . . . Table 12 Results of the ratio study per district . . . . . . . . . 231 .. .. 232 233 233 .. 242 . . . . . . . 244 246 246 247 248 249 255 .
Sales summary grid of short table sales comparison approach . . . . . . . . . . . . . . . . . Marginal price of internal area . . . . . . . . . . Marginal price of internal area . . . . . . . . . . Determination of marginal prices for comparable A . . . Determination of marginal prices for comparable B . . . Determination of marginal prices for comparable C . . . Determination of marginal prices for comparable D . . . Determination of valuation function .
Neural networks (Borst 1992; McCluskey et al. 1997; Nguyen et al. 2001) is one of them. The application of these methods raised several criticisms 10 M. d’Amato (Worzala et al. 1995) observing how outcomes vary with different architectures of neural network-based models. A further application is the self-organizing map (Kauko 2002; Kaklauskas et al. 2012). Another contribution to AVM comes from the application of fuzzy theory. Gonzales et al. (2002) have built a mass appraisal model, where fuzzy rules are extracted from the ANN.