Santa Clara County (SCC): Reading the Graphs
We get asked occasionally, o.k., maybe a little more than that, about how to read the graphs.
Graphs are a way to provide a visual interpretation of mass quantities of data.
A well-crafted graph will condense large amounts of statistical data into an easy to understand visual. Or at least that’s the theory.
Let’s take the graph below, our Absorption Rate & Median Price graph. This graph was designed to show what direction the local market is trending: does it favor buyers or sellers.
Looking at the graph, it has two main axes: the X axis, which shows the time frame we are considering, in this case from January 2001 to April 2016. The second is the Y axis, of which we have two. These are the axes we use to graph the statistics.
The graph tracks two statistics: the absorption rate, which shows how long it would take to sell all homes for sale at the current rate of sales. You could view the absorption rate by days, weeks, or months. If you use one month, then simply find the number of homes available vs the number of homes sold in the last 30 days. If the available inventory is 90, and 60 homes sell, the 90 divided by 60 is 1.5 – so one and a half months of inventory.
We used a three-month moving average to smooth out month-to-month fluctuations in the data, yet still retain seasonal fluctuations. You can see this in the data where prices rise in the spring and peak in the summer before falling to their low point of the year in January. Absorption rate is charted on the Y1 axis. That is the left hand side axis and the absorption rate is colored in light blue.
The smaller the absorption rate number, the more of a sellers’ market it is. A balanced market, according to the National Association of Realtors, is about 6 months of inventory. In Silicon Valley, though, normal is more like 3-4 months of inventory.
The second statistic is median price, which is tracked by the Y2 axis, the axis on the right and the median price data is graphed in black.
The higher the median price number, the more of a sellers’ market it is.
As you can see, the Santa Clara County real estate market is firmly in a sellers’ market. Some pockets are hotter or cooler, but the county as a whole remains a strong seller’s market.
We will explain the remaining graphs next month.
April Statistics – Home Prices Reach New Highs(SCC)
Single-Family Homes
Year-Over-Year
- Median home prices increased by 12.3% year-over-year to $1,080,000 from $961,353.
- The average home sales price rose by 6.0% year-over-year to $1,342,830 from $1,267,230.
- Home sales fell by 13.8% year-over-year to 936 from 1,086.
- Total inventory* fell 5.7% year-over-year to 2,163 from 2,293. Active listings up third month in a row: +14.1%.
- Sales price vs. list price ratio fell by 2.7% year-over-year to 104.8% from 107.7%.
Month-Over-Month
- Median home prices improved by 2.9% to $1,080,000 from $1,050,000.
- The average home sales price rose by 1.1% to $1,342,830 from $1,328,750.
- Home sales up by 32.8% to 936 from 705.
- Total inventory* increased 15.3% to 2,163 from 1,876.
- Sales price vs. list price ratio dropped by 0.5% to 104.8% from 105.3%.
Condominiums
Year-Over-Year
- Median home prices increased by 17.3% year-over-year to $662,500 from $565,000.
- The average home sales price rose by 16.0% year-over-year to $740,476 from $638,314.
- Home sales rose by 9.1% year-over-year to 420 from 385.
- Total inventory* rose 0.9% year-over-year to 691 from 685. Active listings up fifth month in a row: +32.7%.
- Sales price vs. list price ratio fell by 2% year-over-year to 105.6% from 107.7%.
Month-Over-Month
- Median home prices slipped by 2.1% to $662,500 from $677,000.
- The average home sales price rose by 1.6% to $740,476 from $728,524.
- Home sales up by 21.0% to 420 from 347.
- Total inventory* increased 6.1% to 691 from 651.
- Sales price vs. list price ratio increased by 0.1% to 105.6% from 105.5%.
Call or email me if you have any questions.
For further details and a city-by-city breakdown statistics, go to http://avi.rereport.com/market_reports.
Real estate related Articles
| SFGATE By Anna Marie Erwert November 2, 2015 | New study shows profound impact of tech industry on Bay Area real estate |
| San Jose Mercury By Bruce Newman September 10th | 5 tips for preparing for a wet winter |
| San Jose Mercury By Bruce Newman September 10th | Weather threatening to turn California’s drought into drenching winter, worries mount |
| July 7th Avi Urban | How to reduce your home loan interest payments. Read more |
The Silicon Valley 150 Index Corner
The Silicon Valley’s Real estate market is a derivative of the local economy, it prospers and withers depending on how well the local knowledge-based sector performs. The San Jose Mercury News tracks the largest 150 publicly traded companies headquartered in Silicon Valley via an index called the SV150, which you can lookup at www.mercurynews.com. Stocks are valued based on many criteria, but the most important criterion is a company’s future earnings. Therefore, I view the SV150 as a leading indicator for the Silicon Valley’s real estate market. This month’s annual index chart can be viewed below:
Investors Corner
Home Prices Increases Slow Down in February
According to the S&P/Case-Shiller Home Price Indices
New York, April 26, 2016 – S&P Dow Jones Indices today released the latest results for the S&P/Case-Shiller Home Price Indices, the leading measure of U.S. home prices. Data released today for February 2016 shows that home prices continued their rise across the country over the last 12 months. More than 27 years of history for these data series is available, and can be accessed in full by going to https://goo.gl/XEw55K
Is it time to seriously consider investing in real estate?
Signup for my Real Estate Investment Alerts and you’ll receive my real estate investment opportunities.
San Mateo County (SMC): Reading the Graphs
We get asked occasionally, o.k., maybe a little more than that, about how to read the graphs.
Graphs are a way to provide a visual interpretation of mass quantities of data.
A well-crafted graph will condense large amounts of statistical data into an easy to understand visual. Or at least that’s the theory.
Let’s take the graph below, our Absorption Rate & Median Price graph. This graph was designed to show what direction the local market is trending: does it favor buyers or sellers.
Looking at the graph, it has two main axes: the X axis, which shows the time frame we are considering, in this case from January 2001 to April 2016. The second is the Y axis, of which we have two. These are the axes we use to graph the statistics.
The graph tracks two statistics: the absorption rate, which shows how long it would take to sell all homes for sale at the current rate of sales. You could view the absorption rate by days, weeks, or months. If you use one month, then simply find the number of homes available vs the number of homes sold in the last 30 days. If the available inventory is 90, and 60 homes sell, the 90 divided by 60 is 1.5 – so one and a half months of inventory.
We used a three-month moving average to smooth out month-to-month fluctuations in the data, yet still retain seasonal fluctuations. You can see this in the data where prices rise in the spring and peak in the summer before falling to their low point of the year in January. Absorption rate is charted on the Y1 axis. That is the left hand side axis and the absorption rate is colored in light blue.
The smaller the absorption rate number, the more of a sellers’ market it is. A balanced market, according to the National Association of Realtors, is about six months of inventory. In Silicon Valley, though, normal is more like 3-4 months of inventory.
The second statistic is median price, which is tracked by the Y2 axis, the axis on the right and the median price data is graphed in black.
The higher the median price number, the more of a sellers’ market it is.
As you can see, the San Mateo County real estate market is firmly in a sellers’ market. Some pockets are hotter or cooler, but the county as a whole remains a strong seller’s market.
We will explain the remaining graphs next month.
April Sales Statistics – Home Prices Reach New Highs, Again (SMC)
Single-Family Homes
Year-Over-Year
- Median home prices increased by 12.3% year-over-year to $1,080,000 from $961,353.
- The average home sales price rose by 6.0% year-over-year to $1,342,830 from $1,267,230.
- Home sales fell by 13.8% year-over-year to 936 from 1,086.
- Total inventory* fell 5.7% year-over-year to 2,163 from 2,293. Active listings up third month in a row: +14.1%.
- Sales price vs. list price ratio fell by 2.7% year-over-year to 104.8% from 107.7%.
Compared To Last Month
- Median home prices improved by 2.9% to $1,080,000 from $1,050,000.
- The average home sales price rose by 1.1% to $1,342,830 from $1,328,750.
- Home sales up by 32.8% to 936 from 705.
- Total inventory* increased 15.3% to 2,163 from 1,876.
- Sales price vs. list price ratio dropped by 0.5% to 104.8% from 105.3%.
Condominiums
Year-Over-Year
- Median home prices increased by 17.3% year-over-year to $662,500 from $565,000.
- The average home sales price rose by 16.0% year-over-year to $740,476 from $638,314.
- Home sales rose by 9.1% year-over-year to 420 from 385.
- Total inventory* rose 0.9% year-over-year to 691 from 685. Active listings up fifth month in a row: +32.7%.
- Sales price vs. list price ratio fell by 2% year-over-year to 105.6% from 107.7%.
Month-Over-Month
- Median home prices slipped by 2.1% to $662,500 from $677,000.
- The average home sales price rose by 1.6% to $740,476 from $728,524.
- Home sales up by 21.0% to 420 from 347.
- Total inventory* increased 6.1% to 691 from 651.
- Sales price vs. list price ratio increased by 0.1% to 105.6% from 105.5%.
* Total inventory is active listings plus contingent or pending listings. Active listings do not include contingent listings.
Call or email me if you have any questions.
For further details and a city-by-city breakdown statistics, go to http://avi.rereport.com/market_reports.
