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Cambridge Endowment for Research in Finance (CERF)


Thies Lindenthal

Towards a Realistic Return Estimate for Real Estate

The research is ongoing and has resulted in two working paper being submitted for review since the last report.


Coming to terms with unquantifiable asset dimensions: Quality, beauty, uniqueness and liquidity risk

Transaction costs in real estate easily reach magnitudes of 3-8%, reduce investment returns, depress trading volumes, increase holding periods and leave markets less efficient, overall. One major contributor to transaction costs are search cost or, more general, market liquidity. The ease at which buildings can be bought or sold depend not only on market conditions but also on their location and quality attributes, which differ wildly across individual assets. Advances in machine learning methods make it possible to utilise unstructured data such as images, to better capture asset characteristics and to model asset liquidity at the asset level.

Project Update - August 2021

The Total Return and Risk to Residential Real Estate

This paper estimates the total rate of return to residential real estate investments based on 120,658 hand-collected archival observations of prices, rents, taxes and costs for individual houses in Paris (1809–1942) and Amsterdam (1900–1979).  
The annualized real total return, net of costs and taxes, is 4.2% for Paris and 5.0% for Amsterdam, and entirely comes from rental yields. At the property-level, the yield at purchase is an important determinant of the total holding period return, even for longer holding periods. In the short-term, idiosyncratic risk is the dominant component of total risk, but its importance reduces over time.

Project Update - April 2020


Title of research: Unique Assets, Quality Uncertainty and Noisy Prices

This projects estimates real estate asset uniqueness along previously not quantifiable dimensions, including shape, size, architecture, perceived beauty, maintenance or shape similarity. This richer picture of individual buildings and their comparability to other properties will improve any estimates of fundamental value. More interestingly, though, it will reveal distributions of transaction values in relation to fundamental value. Since uniqueness of the assets co-determines the availability of information from comparable sales, I hypothesise that uniqueness is also linked to the absolute deviations of sales prices from fundamental values: If little is know about fundamental value, then sales prices will contain more noise.

Project Update - August 2020

Project Update - April 2019