We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and non-visual object characteristics. We find that higher automated valuations relative to auction house pre-sale estimates are associated with substantially higher...

We model mortgage refinancing as a bargaining game involving the borrowing household, the incumbent lender, and an outside bank. In equilibrium, the borrower's ability to refinance depends both on the competitiveness of the local banking market and on the cost of switching banks. We find...

This paper investigates the impact of equity markets and top incomes on art prices. Using a long-term art market index that incorporates information on repeated sales since the eighteenth century, we demonstrate that both same-year and lagged equity market returns have a significant impact on...

We dissect the performance of private equity (PE) investors in commercial real estate. We observe acquisitions, dispositions, and granular performance data for several thousand U.S. hotels. Investments by PEs specializing in the hospitality industry lead to more substantial operating efficiency...

Real and private-value assets—defined here as the sum of real estate, infrastructure, collectibles, and noncorporate business equity—compose an investment class worth an estimated $84 trillion in the U.S. alone. Furthermore, private values can affect pricing in many other financial markets,...

Real estate—housing in particular—is a less profitable investment in the long run than previously thought. We hand-collect property-level financial data for the institutional real estate portfolios of four large Oxbridge colleges over the period 1901–1983. Gross income yields initially...

Previous research has shown that non-local household investors make sub-optimal asset selection and market timing decisions. However, in real estate markets, heterogeneity in returns can exist even with identical ex ante investment (timing) choices, given that transaction prices are the outcome...

We study the accuracy and usefulness of automated (i.e., machine-generated) valuations for illiquid and heterogeneous real assets. We assemble a database of 1.1 million paintings auctioned between 2008 and 2015. We use a popular machine-learning technique - neural networks - to develop a pricing...

We hypothesize the existence of a slow-moving fad component in art prices. Using unique panel survey data on art market participants' confidence levels in the outlook for a set of artists, we find that sentiment indeed predicts short-term returns

Real and private-value assets--defined here as the sum of real estate, infrastructure, collectibles, and non-corporate business equity--is an investment class worth an estimated $85 trillion in the U.S. alone. Furthermore, private values can affect pricing in many other financial markets, such...