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Findings from a Cross-Sectional Housing Risk-Factor Model

机译:跨部门住房风险因素模型的发现

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Housing data from the last 25 years show that returns to residential real estate in the U.S. can be volatile and vary significantly among locations. The variations in returns are driven by economically as well as geographically and psychologically motivated factors, but so far, no asset pricing model that adequately explains systematic risks in cross-sectional housing returns is widely accepted. This paper proposes an asset pricing model for housing returns that includes a market-wide return factor, an economically motivated factor derived from income growth, a geographically based factor derived from land supply elasticity and a momentum factor, which is psychological in nature. The model explains well the systematic risks in housing returns and is robust to different portfolio segmentations. Moreover, the model illustrates that local risk factors indirectly capture the risk previously attributed to market-wide price changes. While housing is not actively traded when compared to other financial assets, understanding the risk-factors that explain housing return in cross-section provides important insight for real estate investors, builders, real estate future traders, homeowners, banks and other mortgage lenders.
机译:最近25年的住房数据显示,美国住宅房地产的回报可能会波动,并且各地间差异很大。收益的变化受经济,地理和心理动机因素的驱动,但是到目前为止,还没有一种资产定价模型能够充分说明横切住房收益中的系统性风险。本文提出了一种用于住房收益的资产定价模型,该模型包括一个市场范围的收益因子,一个由收入增长产生的经济动机因子,一个由土地供应弹性产生的基于地理因素以及动量因子,它本质上是心理的。该模型很好地说明了住房收益的系统性风险,并且对不同的投资组合细分具有鲁棒性。此外,该模型说明,本地风险因素间接捕获了先前归因于整个市场价格变化的风险。与其他金融资产相比,虽然房屋交易不活跃,但了解横截面解释房屋收益的风险因素,可为房地产投资者,建筑商,房地产期货交易员,房主,银行和其他抵押贷款人提供重要的见识。

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