Abstract
This research starts from the observation that common desmoothing models are likely to generate some extreme returns that will distort risk measurement and hence can lead to investment decisions that are suboptimal relative to those that would be made if a transaction-based index were available. Thus, we propose to improve the desmoothing models by incorporating a robust filter into the procedure. We report that in addition to properly treating for smoothing, the method prevents the occurrence of extreme values. As shown with U.S. data, our method leads to desmoothed series whose characteristics are akin to those of transaction-based indices.
| Original language | English |
|---|---|
| Pages (from-to) | 75-105 |
| Number of pages | 31 |
| Journal | Real Estate Economics |
| Volume | 49 |
| Issue number | 1 |
| Early online date | 25 May 2020 |
| DOIs | |
| Publication status | Published - 19 Feb 2021 |
Bibliographical note
ACKNOWLEDGMENTSWe thank Shaun Bond, Marc Francke, David Geltner, and Jeffrey Fisher for inspiring thoughts and insights. We also extend our gratitude to Itzhak Ben-David, our discussant at the 2018 Real Estate Finance and Investment Symposium in Gainesville, Florida, and participants at this event for their useful comments.
Keywords
- Desmoothing models
- robust filter
- appraisal-based index
- private real estate
- unlevered REITs
- desmoothing models
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Martin Hoesli
- Business School, Accountancy & Finance, Accountancy - Chair in Accountancy
- Business School, Centre for Real Estate Research (CRER)
Person: Academic