Starting with the 2016 annual accounts, all housing associations are obliged to value their real estate according to the market value in rented condition as described in the 'Manual model-based valuations market value'. Although this manual stipulates a large number of input parameters of the market value, housing corporations are allowed to manage the level of the market value of a building complex using the so-called 'degrees of freedom'. Ortec Finance Automated Valuation Model (AVM) supports determination of the degrees of freedom 'empty value’ and ‘market rent'.
Insight into market rents and empty values
Ortec Finance AVM is an online application that allows you to efficiently and accurately determine the market-oriented empty values and market rents of your real estate. AVM offers the possibility to determine this for both a single property and a complete portfolio. In addition, it is possible to query empty values and market rents from the past. You can query an unlimited amount of data. It is therefore no longer necessary to use a valuer for every valuation. In addition to determining the empty values and market rents, AVM provides insight into the quality of your property values and the risks of overvaluation or undervaluation. This allows you to make better decisions to mitigate those risks. In addition, you can use AVM to understand different housing trends.
Statistically and scientifically speaking, Ortec Finance AVM is the most reliable valuation model in the Netherlands. It is therefore recognized by regulators, mortgage lenders, the valuation industry and accountants.
Daily appraisal of commercial real estate a new mixed frequency approach
We present a mixed frequency repeat sales model for commercial real estate, taking into account changes in net operating income between the date of buying and selling the property. Moreover, we relate monthly private market index asset returns to lags, up to 1 year, of daily (REIT) index returns.
A Machine Learning Approach to Price Indices: Applications in Commercial Real Estate
This article presents a model agnostic methodology for producing property price indices. The motivation to develop this methodology is to include non-linear and non-parametric models, such as Machine Learning (ML), in the pool of algorithms to produce price indices.
Ortec Finance 2021 Customer Satisfaction Survey shows very high scores
At Ortec Finance, as part of the processes that we have in place to better understand what our clients think of us, our products, and our services, we conduct an annual customer satisfaction survey in the months of October and November. We are proud to announce that the survey shows very high scores for the fourth year in a row!
Forecasting US Commercial Property Price Indexes Using Dynamic Factor Models
The general purpose of a dynamic factor model (DFM) is to summarize a large number of time series into a few common factors. In this paper Alex van de Minne, Marc Francke and David Geltner explore several DFMs on 80 granular, non-overlapping commercial property price indexes in the US, quarterly from 2001Q1 to 2017Q2.
Commonalities in Private Commercial Real Estate Market Liquidity and Price Index Returns
In this paper Dorinth van Dijk and Marc Francke examine co-movements in private commercial real estate index returns and market liquidity in the US (apartment, office, retail) and for eighteen global cities, using data from Real Capital Analytics over the period 2005–2018.