The AVC Backtest: Helping You to Establish Data Validity
The Asset Valuation Curves (AVC) provides clients with the information needed to make informed decisions and manage risk in used equipment assets. The AVC Backtest functions as an addendum to the primary AVC releases and aims to ascertain the validity and soundness of the underlying data that makes up the AVC.
Our Backtests use a mix of data points in order to perform this validation check. These points stem from mainly two sources: the underlying AVC data and sales data from associated brands under the RB Global umbrella. We chiefly import data from Ritchie Bros. Auctioneers and Mascus, which helps us to cover both auction and online listings data, respectively.
Both sources of data points undergo an extensive cleaning process before being utilized in the backtest. However, it is not only the quality of the data that undergoes heavy scrutiny. The methodology itself has also been subjected to heavy scrutiny in order for it to align to the European Central Bank’s Capital Adequacy Directive, Basel III.
The Basis of a Backtest
What we offer is an in-depth report that details everything involving a backtest, which can be divided into two key aspects: the methodology of the backtesting process as well as the results of the performed backtest.
In short, the methodology section takes a closer look at how relevant data is collected, altered, and utilized throughout the backtest. It also discusses the reasons behind the choice of presenting the data in the form of charts and curves. Each chart covers one of the product groups that has been requested and, similarly to the AVC releases, displays how the prices of objects within the said product groups depreciate over time.
However, the charts of the backtest also include other price aspects derived from the imported sales data. This allows for direct comparisons to take place between the values of the AVC and real-life sales data, thus showing how well the AVC performs in real-life scenarios. This is the second key aspect of the report, namely presenting the results of the backtesting process.
A third, shorter section covering regional market trends is also included in the report. This allows us to better contextualize the findings of the backtest and put the results into a more regional perspective. All in all, these steps combined help to show how the underlying AVC data remains valid and sound over a multitude of different product groups.
The Building Blocks of a Backtest Chart
Each chart in the results section of the backtest covers how the prices of equipment depreciate over a ten-year span. The example chart to the right shows how we have chosen to present our findings in the backtest report. Five curves in total are utilized in conjunction with the chart, each of which covers distinct pricing aspects. Including all five of these pricing aspects in the chart results in a more nuanced view of how the prices depreciate over time.
The cornerstone of each chart is undoubtedly the curve representing the AVC Index values. This curve presents the underlying data behind the AVC expressed as a percentage of the initial equipment value. The remaining four curves are all based on statistical measures derived from our imported sales data and are thus meant to be directly compared to the AVC Index curve and its values. The Average Price curve represents, just as the name implies, the average price of sold objects present within the chosen product group. Meanwhile, the P25, P50, and P75 curves all represent specific price percentiles of sold objects. Each curve covers the 25th, 50th, and 75th pricing percentiles, respectively, and are included in the chart to better show the price range between expensive and inexpensive objects.