Tag: statistic

Posted on

Updated San Francisco Market Charts

Sales Price to List Price Percentage & Days on Market

In November, the vast majority of San Francisco homes that sold, sold very quickly without any price reduction, at an average sales price 4% above the list price: That is a strong, hot market. Properties that had to go through price reductions took over 2 months longer to accept offers and sold at a significant discount to original list price. And even in a hot market, there are listings that do not sell at all, but expire or are withdrawn from the market: Many of these will ultimately be relisted at lower prices and eventually sold.

Average Sales Price

The average price is simply the total dollar volume of sales divided by the number of sales. Like median price, it is a general statistic affected by a variety of factors and often fluctuates without great significance on a monthly basis. Among other factors, a decline in distressed home sales and/or an increase in high-end home sales, both of which are occurring now in SF, can have an outsized effect on average sales price. October saw a big jump in average sales price, and then it went up again in November. If the market acts in its typical manner, it will now fall in December and January, since the more affluent home market tends to withdraw for the holidays. (We limit this analysis to sales of up to $3m because the 5% of home sales above that – going up to $12m – $20m – severely distort the overall average by hundreds of thousands of dollars.)

Median Sales Price

The median home sales price is that price at which half the sales occurred for more and half for less. It is a very general statistic and what’s important is the trend over the longer term — monthly fluctuations are normal. Still, October-November saw a large increase over the relatively static median prices seen in the previous 6 months, which followed the big jump in early 2012. Usually, median prices will fall in December and January as the higher end market checks out for the holidays. Remember that sales prices reflect accepted offer activity in the 4 to 10 weeks prior. (The small decline from October to November is probably not statistically significant – unless substantiated as a longer term trend.)

Months Supply of Inventory: Very Low

MSI is a measure of how long it would take to sell the current supply of listings at the existing rate of sales. In October and November, it was about as low as it has ever been. This would typically be interpreted as a strong “seller’s market.”

New Listings & the Inventory of Listings for Sale

After the inventory spike in September from the large influx of new listings, in October and November the number of new listings (the first chart below) and the total number of homes for sale (second chart below) are markedly declining and will almost certainly continue to do so until early 2013.

Percentage of Listings Accepting Offers (Buyer Demand)

The statistic used on this chart boils down the supply and demand dynamics into a single statistic. The percentage of listings accepting offers in October and November was probably about as high as it has ever been, far above the level of previous years. The decline seen in September was the result of a large influx of new listings hitting the market in mid-month – these were snapped up at the same fast rate, but many didn’t accept offers until October, after a reasonable marketing and showing period.

Posted on

What Costs How Much Where in San Francisco

San Francisco Home Values
By Neighborhood, Property Type & Bedroom Count

MLS Sales February 1, 2012 – mid-August 2012

The charts below apply to non-distressed home sales with at least 1 car parking. Distressed home sales — bank-owned property and short sales — typically sell at a discount, but as the market recovers the number of such listings is rapidly declining.

If a price is followed by a “k” it references thousands of dollars; if followed by an “m”, it signifies millions; “N/A” means that there was not enough data to generate a reliable statistic. Where abnormal “outlier” sales were identified that significantly distorted the statistics, these were deleted from the calculations. Within each chart, the neighborhoods are sorted by median sales price, highest to lowest.

Very generally speaking and varying widely by city neighborhood, thus far in 2012, San Francisco home prices have increased by 5% to 15% over 2011 values.

Trends in Dollar per Square Foot Values for Non-Distressed Houses
in Selected San Francisco Neighborhoods

2012 Numbers reflect 2nd Quarter Sales Only


Trends in Median Sales Prices for Non-Distressed 2-Bedroom Condos
in Selected SF Neighborhoods

2012 Numbers reflect 2nd Quarter Sales Only

The MEDIAN SALES PRICE is that price at which half the properties sold for more and half for less. If there were 3 sales, at $1, $2 and $10, the median price would be $2. If there were 4 sales at $2, $2, $5 and $10, the median would be $3.50. Median sales price may be affected by seasonal trends, and by changes in inventory or buying trends, as well as by changes in value.

AVERAGE DOLLAR PER SQUARE FOOT is based upon the home’s interior living space and does not include garages, storage, unfinished attics and basements; rooms and apartments built without permit; decks, patios or yards. These figures are typically derived from appraisals or tax records, but can be unreliable, measured in different ways, or unreported altogether: thus consider square footage and $/sq.ft. figures to be very general approximations. Generally speaking, about 60-80% of listings report square footage, and dollar per square foot statistics are based solely on those listings. All things being equal, a house will have a higher dollar per square foot than a condo (because of land value), a condo will have a higher $/sq.ft. than a TIC (quality of title), and a TIC’s will be higher than a multi-unit building’s (quality of use). All things being equal, a smaller home will have a higher $/sq.ft. than a larger one. The highest dollar per square foot values in San Francisco are typically found in upper floor condos in prestige buildings with utterly spectacular views.

The AVERAGE SIZE of homes of the same bedroom count may vary widely by neighborhood: for example, the average size of a 4-bedroom house in Pacific Heights is much larger than one in Noe Valley; and the average of a Marina 2-bedroom condo is larger than one in South Beach. Besides the affluence factor, the era and style of construction often play large roles in these disparities.

Some neighborhoods are well known for having additional ROOMS BUILT WITHOUT PERMIT, such as the classic 1940′s Sunset house with “bedrooms” and baths built out behind the garage. These additions often add value, but being unpermitted are not reflected in $/sq.ft. figures.

Many aspects of value cannot be adequately reflected in general statistics: curb appeal, age, condition, views, amenities, outdoor space, “bonus” rooms, parking, quality of location within the neighborhood, and so forth. Thus, how these statistics apply to any particular home is unknown.

Posted on

January Data Sings the Blues

Here’s the latest sales data broken down by MLS District.  Full reports are available here under the Market Trends Tab and are well worth a look.

picture-2

Median and Average prices are down substantially year over year for single family homes in all districts except District 7 (“North”, which includes top-shelf enclaves like Pacific Heights and the Marina), but with only 2 sales for the month in that area, it’s not a meaningful statistic.  Indeed, as I’ve pointed out in previous blogs, sales drop off so dramatically every year during December/January that I’d be cautious reading too much into the  statistics for those particular months.

However, the three month moving average  for SF as a whole, which smooths out the seasonal fluctation, has clearly been heading south since last summer, as these two charts show (also available, much more prettily, under that Market Trends Tab):

sfhomesales0109

sfcondosales0109

Details on individual MLS districts to follow in another post.