Which is better for market conditon adjustments, data master or spark?

[ZZGAMAZZ]

Why do they draw the line from 10-12 months to 0-3 months?

Do you consider at all that the properties in the 0-3 month period may be inferior to the properties in the 4-6 month period?

It's crazy to me that anybody is basing adjustments on that.

The baseline Spark 3-chart addendum page for Competing properties that corresponds with the 1004mc includes 12 month absolute values, relative values [$/sf], and DOM, possibly with polynomial rather than the linear trenddline available...though I personally wish for an addendum exactly identical to thev1004mc, which could be used to report other than competing sales [though this thread is a bit too highbrow for me--dont take much to overwhelmed my lowbrow perspective!!!

 

[Tom D]

Why do you base it on avg price per SF rather than median price per SF or median sale price or average sale price? How much thought is put into what the different stats are saying?

So you act like that 1 chart is all of my support, and insult me. Pretty simple minded thing to do. You do simple reviews.

Did i say that chart was the only basis of my adjustment. That chart is actually a micro chart of the sales i considered in my search. I look at 4 time areas, county, zip code, neighborhood and sales in my choosen list. I just showed 1 chart, showing how difficult it can be to determine what may be happening.

And in my simple urban row home areas most of the comps look pretty much the same. So show me how you complicate finding a time adjustment, oh wait i didn't see any method on you post.

And maybe you can tell me why there is a price per sq foot line on the market grid. How much thought as to why it's there.

 

[Terrel L. Shields]

For my market, rural property, I would have to use something else as a proxy for the dissimilar comps I am dealing with.

The best method I know to have a reasonable time adjustment is to look as a semi-large (say 80 or so) home subdivision built by one builder - Then lay out the sales by time, and size. Ideal is a subdivision that is built out entirely within 2 years. The last homes sold are normally the highest priced. So, if the first houses sold for $189/SF and the last 24 months later sold for $219/SF, then you have something you can calculate. You can pretty much bet the quality of new houses by the same builder are pretty similar. OTOH, it is possible that a builder discounts the last one or two houses, just to close out the subdivision. Not sure I've ever seen that but it could happen.

 

[J Grant]

Thanks to all who replied

I applied myself to my MLS (flex MLS), and it makes charts and graphs, and I have complete control over the data input, plus I won't have to pay more to subscribe to Spark or Data Master.
I suppose if one is using them anyway to auto-populate, it is worth using their other tools as well. I am so happy to be able to use my own MLS for the price trend market conditions exhibits

 

[weird_limbs]

Thanks to all who replied

I applied myself to my MLS (flex MLS), and it makes charts and graphs, and I have complete control over the data input, plus I won't have to pay more to subscribe to Spark or Data Master.
I suppose if one is using them anyway to auto-populate, it is worth using their other tools as well. I am so happy to be able to use my own MLS for the price trend market conditions exhibits

Glad you found something that works for you. But just fyi, if you are looking for a free tool the Valuation Labs might be a good option ( https://valuation-labs.com/ ).

 

[The Bob]

In my experience another factor to consider is what part of the real estate cycle are we in. In the past, as we came out of a slower/weaker market, you started to see more fix and flips, more investor activity, more sales of custom or higher end. This can distort the median sales prices if you just apply that market wide and don't factor the effect of the sales, that until recently weren't that common. I always tried to drill down to the trends that the like/kind of what I was appraising were doing.

 

[J Grant]

Glad you found something that works for you. But just fyi, if you are looking for a free tool the Valuation Labs might be a good option ( https://valuation-labs.com/ ).

I already pay for MLS and it seems the simplest since it does not have to exported etc but thanks for the info.

 

[Terrel L. Shields]

It strikes me that short of investigating every single sale, we have to make some assumption about whether all these sales are arm's length or not, if they are short sales or not, if they are otherwise, unique or impacted by external or functional issues or not. I mean any of the above can distort the data base. While a single such sale would not negate the statistics of a 100 sale sample, as @The Bob noted above, there are times where market conditions are distorted. I recall what happened to Bartlesville, OK when Phillips 66 sold out to Conoco and was moved to Houston. A one-horse town collapsed. Suddenly housing, relatively cheap in the first place, was unsalable at any price and most of the non-top dogs were without a job or any prospect of one short commuting to Tulsa. That collapse was as close to overnight as such a collapse can be. It hurt a lot of people, many with flawless credit histories.

To me, anything short of 90 days it a hairshirt job trying to estimate whether a market is moving up or down. Market activity could be a hint, but in a slow market like today, we risk basing a price change upon insufficient data.

As an aside - Bartlesville was hurt by one Boots Adams - who was prez after the Phillips family passed the torch. Bartlesville also had the Cities Service (Citgo) company, but Boots was determined to force total loyalty upon the Phillips employees. If an employee had relatives who worked for Cities, they were fired. If they were caught buying gasoline from any other dealer than a Phillips station, they were fired, on and on. Boots was a tyrant, and Cities finally packed it in and moved to Tulsa. The town thus became vulnerable to a catastrophe due to the loss of the dominant industry and the subsequent satellite businesses who depended upon Phillips 66.