
TL;DR
This paper demonstrates that alternative data variables can effectively forecast Japanese real estate performance, enabling better investment decisions with measurable returns and risk predictions using advanced modeling techniques.
Contribution
It introduces a comprehensive approach combining alternative data and transformer models to predict Japanese real estate prices and investment returns.
Findings
Alternative data variables can forecast real estate performance effectively.
Investment signals based on these variables yield notable returns with low volatility.
Transformer models can predict risk-adjusted returns 4 years in advance with an R-squared of 0.28.
Abstract
The Japanese real estate market, valued over 35 trillion USD, offers significant investment opportunities. Accurate rent and price forecasting could provide a substantial competitive edge. This paper explores using alternative data variables to predict real estate performance in 1100 Japanese municipalities. A comprehensive house price index was created, covering all municipalities from 2005 to the present, using a dataset of over 5 million transactions. This core dataset was enriched with economic factors spanning decades, allowing for price trajectory predictions. The findings show that alternative data variables can indeed forecast real estate performance effectively. Investment signals based on these variables yielded notable returns with low volatility. For example, the net migration ratio delivered an annualized return of 4.6% with a Sharpe ratio of 1.5. Taxable income growth…
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Taxonomy
TopicsHousing Market and Economics · Housing, Finance, and Neoliberalism · Insurance and Financial Risk Management
