I provide a novel framework for machine learning models to ingest quantified soft information during the life of a loan, using cutting-edge natural language processing techniques on salient unstructured text. This soft information, from servicer call transcripts, is not restricted to mere...

Während direkte Immobilieninvestments lang Zeit als renditeträchtig bei gleichzeitig begrenztem Risiko galten, führte den Anlegern insbesondere die gegenwärtige Finanzmarktkrise vor Augen, dass auch Immobilienanlagen insbesondere in den USamerikanischen Häusermarkt mit hohen Risiken...

Using data for six metropolitan housing markets in three countries, this paper provides a comparison of methods used to measure house price bubbles. We use an asset pricing approach to identify bubble periods retrospectively and then compare those results with results produced by six other...

Exploiting the unique institutional setting of Hong Kong's real estate market, we uncover a curious ripple effect of haunted houses on the prices of nearby houses. Prices drop on average 19% for units that become haunted, 9% for units on the same floor, 6% for units in the same block, and 1% for...

This study proposes the housing "beta" and tests whether the housing "beta" is a significant determinant for stock returns in a multifactor framework. We hypothesize that the housing market is a systematic risk factor given the impact of the housing market on the overall economy and economics...

By using a nonlinear VAR model, we investigate whether the response of the US stock and housing markets to uncertainty shocks depends on financial conditions. Our model allows us to change the response of the US financial markets to volatility shocks in periods of normal and financial distress....

We estimate the transmission of the pandemic shock in 2020 to prices in the residential and commercial real estate market by causal machine learning, using new granular data at the municipal level for Germany. We exploit differences in the incidence of Covid infections or short-time work at the...

We estimate the transmission of the pandemic shock in 2020 to prices in the residential and commercial real estate market by causal machine learning, using new granular data at the municipal level for Germany. We exploit differences in the incidence of Covid infections or short-time work at the...

We estimate the transmission of the pandemic shock in 2020 to prices in the residential and commercial real estate market by causal machine learning, using new granular data at the municipal level for Germany. We exploit differences in the incidence of Covid infections or short-time work at the...

We estimate the transmission of the pandemic shock in 2020 to prices in the residential and commercial real estate market by causal machine learning, using new granular data at the municipal level for Germany. We exploit differences in the incidence of Covid infections or short-time work at the...