The paper explores how the standard consumption-CAPM fares in pricing housing returns and regional rental income streams in a cross-section of regions. In particular, we estimate the Euler equations associated with the gross housing returns inclusive of price appreciations and rents jointly for several metropolitan areas of the US. The representative agent has a Constant Relative Risk Aversion (CRRA) utility. The rent growth is allowed to depend on the business cycle. When biannual data from 1978 to 2007 is used, the parameter estimates are reasonable, and the model is not rejected. Large standard errors indicate uninformative estimates. The implied price rent ratio time series averages are similar to the data; however the model misses the boom-bust pattern in the prices. The model significantly understates the average and the variance of the price appreciations. Results are robust to allowing housing consumption directly in the utility function or using the Epstein–Zin–Weil utility.

This paper establishes baseline valuations for housing assets using rent cash flows in 22 regions of the U.S. in a Lucas (1978) framework. The model matches the unconditional averages of the price–rent ratios from 1978 to 2012 quite well; however, the model valuations after 2002 are well below the market price–rent ratios. We explore three mechanisms to understand these housing overvaluations in the post-2002 period relative to the consumption-based model: (1) using cross-sectional subprime consumer and commercial lending characteristics; (2) transaction costs; and (3) turning off the pro-cyclicality of the rent growth in the data. We find that all three factors explain some fraction of the bubble in valuations, but none alone is enough to understand the full extent of post-2002 valuations.

Using intraday trades and quotes data, we study the stock options market before, during, and after the market events of May 6, 2010. Focusing on the S&P 500 and S&P 100 stock options, we explore if the options market provided any discernible signals that forewarned the extreme volatility on that day and whether the recovery was fast and without a permanent impact. We find that the options market reacted to the volatility- rather than predicting it, and almost all of the variables are indistinguishable from their previous levels in the next few trading days. Intraday empirical analysis suggests that most of the impact was over within a few hours from the peak of market volatility.

This paper numerically solves the decision problem of a multiperiod constant relative risk aversion individual who faces transaction costs and has access to two risky assets, both with predictable returns. With proportional transaction costs and independent and identically distributed returns, we numerically find the rebalancing rule to be a no-trade region for the portfolio weights with rebalancing to the boundary. The shape of the no-trade region depends on the correlation between the two risky assets. With predictable returns, there is instead a no-trade region for each state. We also examine several important economic questions, including the utility cost of not being able to buy on margin or short stock.

Young agents with low wealth-income ratios counter factually hold more stock than young, rich agents and old agents using the standard portfolio choice model with i.i.d. stock returns and labor income. This paper matches the countercyclical volatility and procyclical mean of U.S. labor income and finds that, consistent with U.S. data, young, poor agents now hold less stock than both young, rich agents and old agents, and no stock a large fraction of the time. Our results suggest that the predictability of labor income growth at a business-cycle frequency, particularly the countercyclical variation in volatility, plays an important role in a young agent's decision making about her portfolio's stock holding.

Constantinides (1986) documents how the impact of transaction costs on per‐annum liquidity premia in the standard dynamic allocation problem with i.i.d. returns is an order of magnitude smaller than the cost rate itself. Recent papers form portfolios sorted on liquidity measures and find spreads in expected per‐annum return that are the same order of magnitude as the transaction cost spread. When we allow returns to be predictable and introduce wealth shocks calibrated to labor income, transaction costs are able to produce per‐annum liquidity premia that are the same order of magnitude as the transaction cost spread.