The Realty Exchange offers a unique service in that you can quickly assess the trends in your community as well as the relative performance compared to nearby communities. Our proprietary market trend charts cover over 50 communities in North L.A. County and Conejo Valley. Charts are updated approximately every two weeks and are available for the three main types of residential property:
You can also track the relative performance of these communities through our proprietary
Relative Ranking tables. These tables are also updated on a bi-weekly basis for the three main property types:
While comparable sale information ("comps") are important in finding out what your property may be worth, we believe it is also important to know:
If you are a buyer, choice of neighborhood should always take priority over how a specific property meets your needs. This is where our proprietary charts and statistical data can help you make the best decision - whether you are a home owner, future home owner or investor. For example, communities that have over-performed in what has been a very strong market over the past several years may begin to under perform as the pace of sales and price appreciation slows. This is something that will be most easily recognized be tracking bi-weekly changes in our ranking charts.
If you are a seller, our data analysis can help you determine your listing price as well as estimating how much time will likely be needed to complete the sale. If your home is in a community that is performing well (relative to neighboring communities), you can afford to be more firm in your pricing. If your home is in an area where the average days to sell is 60 days and you need to sell your property in less than 30 days, you will want to consider ways to ensure you can list and sell your property in your required time frame.
For more tips and suggestions on buying or selling residential real estate, simply send us your request.
Our charts and statistical tables are not generated "on the fly" from a live database. For security reasons, our charts and tables are created off-line and then transferred to our web server.
Therefore, the time you will need to wait downloading our charts to your web browser will be longer than the wait time if the charts were generated from a live database. The download time depends primarily on the bandwidth of your internet connection. Our city, zone and specialty charts pages display a set of three or more charts with a typical file size for each chart of 35k to 50k. Therefore, you will be downloading, on average, 150k - 200k data.
In computer software programmer's jargon, "painting" an image refers to the process of displaying a page to the screen. If your internet connection is a dial-up telephone line, loading our chart pages may feel like you're watching paint dry! If this is the case, please accept our apologies. If your connection is DSL or faster, the download time should be typically no more than a few seconds.
Charts and Tables - Our Philosophy Statistical property valuation models should never be used as a substitute for an appraisal by a certified property appraiser. All properties are unique and only an experienced professional can assess the relative "weight" of variances between the subject property and those included in the appraisal. One challenge with all valuation models - no matter how sophisticated they may be - is a tendency for the valuations to "skew" away from the true value as price ranges rise. For example, a property in the $300,000 range may generate an estimated valuation within a few thousand dollars of the listing price. However, properties listed at prices over $1,000,000 may have a variance of as much as 20% away from the listing, or recently sold, price.
With this in mind, we make every effort to present as clear a picture as possible of the fundamental trends in real estate prices. We screen out properties that fall outside of the range of traditional characteristics (by our standards, which may be different from others standards) or for which the raw data appears to be in error. In addition, the following issues affect how our final chart/tables are generated:
1. Our main data source is the Southland Regional Association of REALTORSŪ CRIS-NetŪ MLS. Secondary sources may include data on properties marketed and/or sold privately and not published through any MLS.
2. Data is calculated on a split-month basis and plotted as a rolling four-period moving average. 'Split-month' means the month is divided into two halves - 1st - 15th; 16th - month end. Due to the fact that the month end may be any where from the 28th of the month to the 31st of the month, the data for the second half of each month will be based on anywhere from 13 days to 16 days data. The reason for splitting the month in this way is to make our charts more easily readable.
3. Not all property data in a particular community may be included in the MLS data from which we generate our charts and tables. For example, the charts for Palmdale and Lancaster (the Antelope Valley) are based on MLS data from the Southland Regional Association of REALTORSŪ CRIS-NetŪ MLS. Our charts and tables do not include MLS data from the Greater Antelope Valley association of REALTORSŪ
4. Charts and statistical tables including calculations of property in a 'sold' status may change as time passes. This is due to the fact that properties originally categorized as having been sold (being in a "Pending Sold" status prior to the close of escrow) may fall out of escrow and be either put back on the market or cancelled as an MLS listing. As a result, listings that are cancelled or taken off market will be removed from our sold-properties groupings and therefore impact all sold-properties mathematical calculations. As well, the final selling price is not known until escrow is reported to have been closed. If the final selling price is different from the listing price, our mathematical calculations will be affected accordingly.
5. Properties with a relatively small structure compared to the lot size are not included in our city and zone data calculations, charts and statistical tables. The relative numbers vary depending on the community.
6. In some cases, there may be no property sales or listings within a given two-week period. In this case, we "carry forward" the most recent prior period data values into the current period.
7. The average per square foot listing price has an upward bias partly due to the inclusion of properties listed at prices well above market. Keeping a neutral mathematical model, all listings - under-priced and over-priced - are included in our calculations. Even though property listings at prices well above market have a higher probability of either expiring unsold or eventually being subject to cancellation, the listing prices must still be factored into any per square foot calculations. In market conditions where fewer properties are selling and selling prices are declining, "over market" listings that are later cancelled will place an upward bias in charts of listing price averages.
8. While condominium and townhome charts are not available for some cities (mainly due to lack of sufficient data for the creation of meaningful charts), the raw data from those communities may be included in their respective Zone/Region calculations.
9. Proprietary statistical analysis techniques are used in processing the raw data in generating relative community price performance screens and property specific relative value screens. For example, City Rankings tables reflects each city's percentage change in the 6 month moving average of selling prices. Using a different smoothing factor may produce different relative performance results. We believe the use of shorter averages (e.g. one to three months) in the calculation of Year/Year rates of change generates statistical results too erratic to be interpreted in a meaningful way.
For more information our charting and stats methodology, please see our Frequently Asked Questions.
