References
- Anundsen, A. K., & Jansen, E. S. (2013). Self-reinforcing effects between housing prices and credit. Journal of Housing Economics, 22, 192–212. https://doi.org/10.1016/j.jhe.2013.07.001
- Barberis, N., Greenwood, R., Jin, L., & Shleifer, A. (2018). Extrapolation and bubbles. Journal of Financial Economics, 129, 203–227. https://doi.org/10.1016/j.jfineco.2018.04.007
- Bartholdy, J., & Peare, P. (2005). Estimation of expected return: CAPM vs. Fama and French. International Review of Financial Analysis, 14, 407–427. https://doi.org/10.1016/j.irfa.2004.10.009
- Bracke, P. (2015). House prices and rents: Microevidence from a matched data set in central London. Real Estate Economics, 43, 403–431. https://doi.org/10.1111/1540-6229.12062
- Bracke, P., Pinchbeck, E. W., & Wyatt, J. (2018). The time value of housing: Historical evidence on discount rates. Economic Journal (London), 128, 1820–1843. https://doi.org/10.1111/ecoj.12501
- Bücker, M., Szepannek, G., Gosiewska, A., & Biecek, P. (2021). Transparency, auditability, and explainability of machine learning models in credit scoring. Journal of the Operational Research Society, 73(1), 70–90. https://doi.org/10.1080/01605682.2021.1922098
- Cabrol, A., Drobetz, W., Otto, T., & Puhan, T. (2024). Predicting corporate bond illiquidity via machine learning. Financial Analysts Journal, 80, 1–25. https://doi.org/10.1080/0015198X.2024.2350952
- Cabrol, A., Drobetz, W., Otto, T., & Puhan, T. (2024). Predicting corporate bond illiquidity via machine learning. Financial Analysts Journal, 80(3), 103–127. https://doi.org/10.1080/0015198X.2024.2350952
- Campbell, J. Y., & Shiller, R. J. (1988). The dividend-price ratio and expectations of future dividends and discount factors. Review of Financial Studies, 1, 195–228. https://doi.org/10.1093/rfs/1.3.195
- Campbell, S. D., Davis, M. A., Gallin, J., & Martin, R. F. (2009). What moves housing markets: A variance decomposition of the rent-price ratio. Journal of Urban Economics, 66, 90–102. https://doi.org/10.1016/j.jue.2009.06.002
- Caruana, R., & Niculescu-Mizil, A. 2006. An empirical comparison of supervised learning algorithms, in: Proceedings of the 23rd International Conference on Machine Learning, ICML ’06. Association for Computing Machinery, New York, NY, USA, pp. 161–168. https://doi.org/10.1145/1143844.1143865
- Chambers, D., Spaenjers, C., & Steiner, E. (2021). The rate of return on real estate: Long-run micro-level evidence. Review of Financial Studies, 34, 3572–3607. https://doi.org/10.1093/rfs/hhab028
- Chen, J., Chen, Y., Hill, R. J., & Hu, P. (2022). The user cost of housing and the price-rent ratio in Shanghai. Regional Science and Urban Economics, 92, 103738. https://doi.org/10.1016/j.regsciurbeco.2021.103738
- Clark, S., & Lomax, N. (2020). Rent/price ratio for English housing sub-markets using matched sales and rental data. Area, 52, 136–147. https://doi.org/10.1111/area.12555
- D’Lima, W., & Schultz, P. (2022). Buy-to-rent investors and the market for single family homes. The Journal of Real Estate Finance and Economics, 64, 116–152. https://doi.org/10.1007/s11146-020-09790-5
- Demers, A., & Eisfeldt, A. L. (2022). Total returns to single-family rentals. Real Estate Economics, 50, 7–32. https://doi.org/10.1111/1540-6229.12353
- Friedman, J. H. (2000). Greedy function approximation: A gradient boosting machine. Annals of Statistics, 29, 1189–1232.
- Gu, S., Kelly, B., Xiu, D. (2020). Why do tree-based models still outperform deep learning on tabular data? Empirical Asset Pricing via Machine Learning. Review of Financial Studies, 33, 2223–2273. https://doi.org/10.1093/rfs/hhaa009
- Halket, J., Nesheim, L., & Oswald, F. (2020). The housing stock, housing prices, and user costs: The roles of location, structure, and unobserved quality. International Economic Review, 61, 1777–1814. https://doi.org/10.1111/iere.12475
- Hill, R. J., & Syed, I. A. (2016). Hedonic price–rent ratios, user cost, and departures from equilibrium in the housing market. Regional Science and Urban Economics, 56, 60–72. https://doi.org/10.1016/j.regsciurbeco.2015.11.001
- Huh, S., & Kim, I. (2021). The housing risk premium in a production economy. Applied Economics Letters, 28, 213–219. https://doi.org/10.1080/13504851.2020.1740158
- Jordà, Ò., Knoll, K., Kuvshinov, D., Schularick, M., & Taylor, A. M. (2019). The rate of return on everything, 1870–2015*. The Quarterly Journal of Economics, 134, 1225–1298. https://doi.org/10.1093/qje/qjz012
- Kaufmann, H., Messow, P., & Vogt, J. (2021). Boosting the equity momentum factor in credit. Financial Analysts Journal, 77, 83–103. https://doi.org/10.1080/0015198X.2021.1954377
- Kim, J., & Lim, G. (2014). Understanding the Irish price–rent ratio: An unobserved component approach. Applied Economics Letters, 21, 836–841. https://doi.org/10.1080/13504851.2014.892191
- Kishor, N. K., & Morley, J. (2015). What factors drive the price–rent ratio for the housing market? A modified present-value analysis. Journal of Economic Dynamics & Control, 58, 235–249. https://doi.org/10.1016/j.jedc.2015.06.006
- Lo, D., McCord, M., Davis, P. T., McCord, J., & Haran, M. E. (2023). Causal relationships between the price-to-rent ratio and macroeconomic factors: A UK perspective. Journal of Property Investment & Finance, 41, 11–34. https://doi.org/10.1108/JPIF-08-2021-0068
- Lo, D., McCord, M.J., McCord, J., Davis, P.T. & Haran, M. (2021). Rent or buy, what are the odds? Analysing the price-to-rent ratio for housing types within the Northern Ireland housing market. International Journal of Housing Markets and Analysis, 14(5), 1062-1091. https://doi.org/10.1108/IJHMA-08-2020-0103
- Lo, D., Yau, Y., McCord, M., & Haran, M. (2022). Lead-lag relationship between the price-to-rent ratio and the macroeconomy: An empirical study of the residential market of Hong Kong. Buildings, 12, 1345. https://doi.org/10.3390/buildings12091345
- Mork, K. A., & Trønnes, H. A. (2023). Expected long-term rates of return when short-term returns are serially correlated. International Review of Financial Analysis, 88, 102696. https://doi.org/10.1016/j.irfa.2023.102696
- Okunev, J., Wilson, P., & Zurbruegg, R. (2000). The causal relationship between real estate and stock markets. The Journal of Real Estate Finance and Economics, 21, 251–261. https://doi.org/10.1023/A:1012051719424
- Piazzesi, M., Schneider, M., & Tuzel, S. (2007). Housing, consumption and asset pricing. Journal of Financial Economics, 83, 531–569. https://doi.org/10.1016/j.jfineco.2006.01.006
- Plogmann, J., Mußhoff, O., Odening, M., & Ritter, M. (2020). What Moves the German Land Market? A Decomposition of the Land Rent-Price Ratio. Ger. J. Agric. Econ., 69. Advance online publication. https://doi.org/10.30430/69.2020.1.1-18
- Rossi, A. G., & Utkus, S. (2024). The diversification and welfare effects of robo-advising. Journal of Financial Economics, 157, 103869. https://doi.org/10.1016/j.jfineco.2024.103869
- Rozemberczki, B., Watson, L., Bayer, P., Yang, H.-T., Kiss, O., Nilsson, S., Sarkar, R. (2022). The shapley value in machine learning. https://doi.org/10.24963/ijcai.2022/778
- Tsai, I.-C. (2015). Dynamic information transfer in the United States housing and stock markets. The North American Journal of Economics and Finance, 34, 215–230. https://doi.org/10.1016/j.najef.2015.09.012