Backcasting, Nowcasting, and Forecasting Residential Repeat-Sales Returns: Big Data meets Mixed Frequency
SSRN, ISSN: 1556-5068
2021
- 1Citations
- 2,091Usage
- 4Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
The Case-Shiller is the reference repeat-sales index for the U.S. residential real estate market, yet it is released with a two-month delay. We find that incorporating recent information from 71 financial and macro predictors improves backcasts, now-casts, and short-term forecasts of the index returns. Combining individual forecasts with recently-proposed weighting schemes delivers large improvements in forecast accuracy at all horizons. Additional gains obtain with mixed-data sampling methods that exploit the daily frequency of financial variables, reducing the mean square forecast error by as much as 13% compared to a simple autoregressive benchmark. The forecast improvements are largest during economic turmoils, throughout the 2020 COVID-19 pandemic period, and in more populous metropolitan areas.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85110993964&origin=inward; http://dx.doi.org/10.2139/ssrn.3798356; https://www.ssrn.com/abstract=3798356; https://dx.doi.org/10.2139/ssrn.3798356; https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3798356; https://ssrn.com/abstract=3798356
Elsevier BV
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