Data quality
Duration of proceedings at district courts
The data basis of the empirical analysis is the complete recording of all foreclosure appoitnments in Germany based on the Argetra database. The duration of the proceedings is determined in each case for one reference year. The reference year is always in the past, as the period up to a first date is often 1-2 years. The analysis considers all foreclosures procedures with an appointment in the reference year. The procedure duration 2018 will be calculated on the basis of the reference year 2016. The details of the duration until the first date are calculated as the duration between the foreclosure-note (in the alternative the valuation date) and the first foreclosure-date. The information provides information about the time between application for the foreclosure and the first foreclosure appointment. The details of the duration until the follow-up date are calculated as the duration between the occurred foreclosure appointments. The information provides information about the expected time span until the next foreclousre appointment. The details of follow-up, first-term and duration of the procedure are given in days as minimum, maximum and average values.
Recovery rates
The data basis of the forecast is current research by Argetra on the exploitation proceeds / surcharge rates for foreclosures. This comprehensive dataset was developed for the years 2014-2016 and was the basis for the results of that time. Now, current data for the years 2016-2018 has been evaluated, which reliably reflect the changed market conditions. The estimate was made in accordance with current methodological standards in real estate market research on the basis of a so-called generalized additive regression model, which, in contrast to the classical linear regression method, provides for regularized consideration of nonlinear relationships and therefore enables particularly efficient analyzes and estimation models. For the individual object types, besides the market value, the object type, the large-scale location and the city type, the type of district court districts and the duration of the procedures / the number of appointments are central determinants. The use of the time-consistent F + B market rating as a predictor allows a risk-specific revenue ratio forecast down to the postal code level. Model quality: The models were optimized on the basis of their forecasting quality. The magnitude of the explained variance is more than 60% in most models, which is a good value for modeling such a heterogeneous size as the revenue rate
Real estate data
All properties are geocoded and provided with community code. In addition, appraisals include information on property interest rates, land values and the assessed land value. Are you interested in historical data or are you interested in evaluations of the foreclosure market?