Mile High Trout
Elite Member
- Joined
- Feb 13, 2008
- Professional Status
- Certified Residential Appraiser
- State
- Colorado
Totally true there Highlight 17.
That's why I research by neighborhood names not proximity. If I'm pulling examples from the same market area, the a-typical nature of comparisons that may require weighting is nullified more so than cross neighborhood comparisons and the likes.
Especially in mismatching and rural type markets, or even high end, total variance grows and grows as the variance in owner value in use is more pronounced. The market is what it is, and by identifying the total variance in high/low for applicable example sets, static distributed allotted grid adjustments accommodate and substitute for any weighting needs. Sometimes a simple ranch or two story or size or similar filter can bring about that narrow market picture so you can draw up a distributed total adjustment amount. Usually I can just eyeball that from unfiltered data sets and filtered overview data set pages. I'd say that if you had only 1 comp that matches, that's your benchmark, and other comp examples would all have across the board and increased net/gross adjustments. To indicate the rest of the comps as not being over net/gross and opinioning by weighting instead just seems like another way of working towards illusionary valuation. I simply don't agree with weighting unless it's a very extreme scenario of comparison. And even if you get steep gross adjustments, as long as your net is reasonable, you've applied those adjusts correctly and picked acceptable comps. It's when your net is too excessive that you rethink your comps selection, while if it's only gross, you've merely found an example that needed some applied balance to become a decent match. I more often see a gross crawl over the % cap, than the net does. That's the benefit of distributed allotted adjustment method.
That's why I research by neighborhood names not proximity. If I'm pulling examples from the same market area, the a-typical nature of comparisons that may require weighting is nullified more so than cross neighborhood comparisons and the likes.
Especially in mismatching and rural type markets, or even high end, total variance grows and grows as the variance in owner value in use is more pronounced. The market is what it is, and by identifying the total variance in high/low for applicable example sets, static distributed allotted grid adjustments accommodate and substitute for any weighting needs. Sometimes a simple ranch or two story or size or similar filter can bring about that narrow market picture so you can draw up a distributed total adjustment amount. Usually I can just eyeball that from unfiltered data sets and filtered overview data set pages. I'd say that if you had only 1 comp that matches, that's your benchmark, and other comp examples would all have across the board and increased net/gross adjustments. To indicate the rest of the comps as not being over net/gross and opinioning by weighting instead just seems like another way of working towards illusionary valuation. I simply don't agree with weighting unless it's a very extreme scenario of comparison. And even if you get steep gross adjustments, as long as your net is reasonable, you've applied those adjusts correctly and picked acceptable comps. It's when your net is too excessive that you rethink your comps selection, while if it's only gross, you've merely found an example that needed some applied balance to become a decent match. I more often see a gross crawl over the % cap, than the net does. That's the benefit of distributed allotted adjustment method.
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