This paper studies the pricing of the risk associated with the location of the assets. The local real estate market risk is measured by ‘local beta’, which combines the systematic risk of local property markets and the property allocation strategy of real estate firms. The empirical results...

In some applications of supervised machine learning, it is desirable to trade model complexity with greater interpretability for some covariates while letting other covariates remain a "black box". An important example is hedonic property valuation modeling, where machine learning techniques...

In the aftermath of the COVID-19 pandemic, non-core investments are gaining traction amongst institutional investors due to the shifting preference towards investment vehicles that position higher on the risk-return curve. Non-listed value-add real estate funds in Japan are one such vehicle....

This paper contributes to the literature by identifying the response patterns of direct and indirect real estate returns to shocks in the market fundamentals. The response speeds are estimated with vector autoregressive models using TBI and NAREIT returns for the period 1994-2009 in the United...

The measurement of house price movements is a vital topic from both academic and practical perspectives and hence has been the focus of much research. There is almost unanimous consensus in the literature that house price indexes should control for the quality of properties; the most widely used...

This paper examines the inflation-hedging capability of listed real estate (LRE) companies in the US from 1975 to 2023, and in three other economies—the UK, Japan, and Australia—from 1990 to 2023. By using a Markov switching vector error correction model (MS-VECM), we identify that the...

This paper examines the inflation-hedging capability of listed real estate (LRE) companies in the US from 1975 to 2023, and in three other economies–the UK, Japan, and Australia–from 1990 to 2023. By using a Markov switching vector error correction model (MS-VECM), we identify that the...