Home Owner's Report

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Introduction

Thank you for your interest in our products. Here's some background information about how our valuations are derived, and some guidelines to get the most out of the reports.

HVC Valuations are computer-calculated estimates of the value of residential properties at a point in time, which rely on very large amounts of sales and property data. The underlying database is constantly updated with current information, and the valuations change constantly to reflect the most recent information.

These systems are called AVM's, (Automated Valuation Models), and they have been in use for many years in the financial services marketplace, where they have proven to be very useful in all aspects of residential lending. HVC reports have been specially adapted for the homeowner (or potential owner) to be general-purpose guides for a variety of purposes, by presenting this information in a format intended to help you better understand recent factors affecting your property's value.

First, though, we'd like you to know about a couple of key concepts, which will help you with the reports. The first is what we mean by the cluster, and how that helps to identify market trends.

Each individual property is one of a group of similar nearby properties, which we call the cluster. The number of homes and their proximity to each other within each cluster, and the geographic area which each cluster covers, will vary quite a bit. The clusters have been put together specifically for these valuations. Across Canada, over 15,000 separate clusters have been identified.

Within each cluster, all of the historical sales for all of the individual properties are collected, going back several years. The current valuation of each individual property can be calculated using special techniques (called an algorithm ^*), using the historical sales for that property and the others in the cluster. This unique collection of sales also makes it possible to identify market trends for that cluster, based on the actual sales transactions of the properties in that cluster. Specifically, we're looking to identify overall price trends up or down, and relative market activity for each group.

Each cluster tends to be quite small (most are less than 1000 properties). So, even though the underlying database is vast, with literally millions of sales records going back many years, the current valuations and trends for any single property are local, precise and specific.

A valuation of any property at a point in time is influenced by many factors, and the science of using a computer model to derive this value cannot be exact. Some of these factors have to do with the specific property, some have to do with the cluster that it's in, and some have to do with more general market and economic conditions. If, for example, a specific cluster is made up of highly desirable properties, the market may be very active (hot), and all the property values will rise, regardless of the specifics of any individual property.

Because these reports are used for many different purposes, we've tried to include information about not only the target property, but also the cluster in which it is located, and the associated market trends.

Now that you know more about what is being described in the reports, we can focus on the specific items in the report. This information, taken with any local information you may have about the property and the area, is intended to help guide final conclusions.

Property Valuation

Since predicting a value for any target property is not an exact science, each valuation is shown as a range, as three separate numbers: the High, the Core and the Low.

The Core value can be thought of as a best overall valuation - it is most likely that the property will be worth close to this figure. At each end of the range, it is less likely (based on the history of sales in the cluster) that the property is worth more than the high value, or less than the low value.

The property valuation is displayed on the report as both a value graph and a descriptive summary. The value graph plots two valuations for the target property, one for the date of the report and one for one year earlier. The written summary restates the current valuation in descriptive text.

If you need to determine a specific single value (perhaps you are looking to buy or sell), your local knowledge of the property and area can now guide you to a more precise valuation. Note that these reports cannot account for some factors which can be very relevant, such as the current condition of the property, recent improvements, or proximity to other landmarks (such as schools or parks).

Confidence

The Automated Valuation Model (AVM) measures how well the actual sales data "fits" the expected valuations that the model produces. The better the fit, the more accurate we expect the valuations to be. Some cluster data is very consistent, others are not.

The confidence is an indication of the expected accuracy of the valuation. There are four levels of accuracy reported here: best, good, acceptable and unacceptable.

Best	A "best" confidence will indicate that the value produced for the target property was derived from a cluster with many consistent recent sales with the values of each behaving in a well defined predictable manner. Estimated values from these reports are expected to be: within 5% of the actual value 61% of the time. within 10% of the actual value 90% of the time. within 15% of the actual value 99% of the time.
Good	A "good" confidence is typically a down graded best confidence due to one of more of the following factors: inconsistency in sale prices, smaller cluster or few recent sales. Estimated values from these reports are expected to be: within 5% of the actual value 42% of the time. within 10% of the actual value 68% of the time. within 15% of the actual value 86% of the time. within 20% of the actual value 94% of the time.
Acceptable	Due to the high value of these properties their confidence has been automatically lowered. Every percent variation in estimated price on these properties constitutes a potentially large dollar figure. Estimated values from these reports are expected to be: within 5% of the actual value 59% of the time. within 10% of the actual value 81% of the time. within 15% of the actual value 92% of the time. within 20% of the actual value 96% of the time.
Unacceptable	An "unacceptable" confidence results from clusters where there are far too few comparable property types and/or sales, or where the measured "fit" is so low as to be unusable. This can be a result of extreme variations in sales prices or relatively few recent sales. HVC will not report a value for these properties.

As further clarification to the confidence rating the average percent difference between the HVC valuations for the last 5 sales in the cluster vs. the actual sale price is provided.

Market Trends

This is an analysis of the market trends identified in the historical sales on file. We report on the percentage change in overall property values, and in the relative activity of this market as compared to all others.

First the change in estimated property values over the last year is characterised as rising, stable or falling. A stable market will describe a cluster where the average property value has not changed by more than 3% up or down. An increase of more than 3% will be called a rising market and a decrease of more than 3% a falling market.

Note that this percentage change in price reflects the change in the average price of all properties in the cluster.

Second the long term vs. short term turnover rate is expressed as active, normal and slow. HVC calculates a turnover rate score which considers time, sales and the number of properties in the cluster. This is compared to the average scores of other clusters, and reported as it compares to these others.

Comparative Sales

The property valuation has been derived from many sales throughout the cluster of the target property. Of the sales on file, some will be more relevant to the target property valuation than others, based on sale price, time and proximity. The three sales shown are the most relevant of the available sales on file at this time.

Note that the computer must work with the actual sales which have taken place. It does the best it can with the history on file; but sometimes there just aren't good comparatives. If you have local knowledge of the area, consider how valid you feel these comparatives are to the target market; and base your final conclusions accordingly.

Sales History

The sales history will show all transactions on file for the target property. Sale prices may reflect full or partial property sale values depending on the type of transaction (i.e. ½ sale may occur when one of two owners sells their half to the other). Sales of $1 or $2 indicate that the owner name on file was changed.

Certainly, relatively recent sales history of the target property tends to make the current valuations better. The last sale on record will definitely be factored into the current valuation. If there was a recent sale, consider whether it was a fair price at the time.

Cluster Details

The cluster is the group of similar nearby properties on which the historical sales are based. The cluster information presented is intended to give you an indication of the size of the local marketplace.

We include the following details of the cluster from which this report was produced:

• number of properties of similar type to target
• number of historical sales on record
• number of sales in the last six months leading up to the valuation value (i.e. if the value is for Jan 2006 then recent sales will include August 2005 through January 2006)
• the historical high and low sale price of like properties (derived from entire historical sales set)

This should give you an indication of how the subject property compares within comparative properties nearby. In particular, it may be relevant to you if this property is at the low end, or the high end, of the other properties in the cluster.