Risk–return spectrum

Abstract: This paper uses an equilibrium multifactor model to interpret the cross-sectional pattern of postwar U.S. stock and bond returns. Priced factors include the return on a stock index, revisions in forecasts of future stock returns (to capture intertemporal hedging effects), and revisions in forecasts of future labor income growth (proxies for the return on human capital). Aggregate stock market risk is the main factor determining excess returns; but in the presence of human capital or stock market mean reversion, the coefficient of relative risk aversion is much higher than the price of stock market risk.

Abstract: This paper takes a new look at the predictability of stock market returns with risk measures. We ¢nd a signi¢cant positive relation between average stock variance (largely idiosyncratic) and the return on the market. In contrast, the variance of the market has no forecasting power for the market return. These relations persist after we control for macroeconomic variables known to forecast the stock market. The evidence is consistent with models of timevarying risk premia based on background risk and investor heterogeneity. Alternatively, our ¢ndings can be justi¢ed by the option value of equity in the capital structure of the ¢rms. MOSTASSET PRICING MODELS, starting with Merton’s (1973) ICAPM, suggest a positive relation between risk and return for the aggregate stock market. There is a long empirical literature that has tried to establish the existence of such a tradeoi between risk and return for stock market indices. 1 Unfortunately, the results have been inconclusive. Often the relation between risk and return has been found insigni¢cant, and sometimes even negative. The innovation in this paper is to look at average stock risk in addition to market risk.We measure average stock risk in each month similarly to Campbell et al. (2001; hereafter CLMX), as the cross-sectional average of the variances of all the stocks traded in that month.We then run predictive regressions of market returns on this variance measure as well as the variance of the market. Consistent with some previous studies, we ¢nd that market variance has no forecasting power for the market return. However, we do ¢nd a signi¢cant positive relation between average stock variance and the return on the market.

Abstract: For most homeowners, the house is the single most important consumption good appearing as an argument of the utility function, and, at the same time, the dominant asset in the portfolio. This paper uses a mean-variance efficiency framework to examine the household’s optimal portfolio problem when owner-occupied housing is included in the list of available assets. Housing differs from stocks and bonds in a crucial way: since the household’s ownership of residential real estate determines the level of its consumption of housing services, the household’s demand for real estate is “overdetermined” in the sense that the level of real estate ownership which is optimal from the point of view of the consumption of housing services may differ from the optimal level of housing assets from a portfolio point of view. With rental markets for housing, a household can, in principle, divorce the size of its holdings of real estate assets from the level of housing services it consumes. However, rental housing is by no means a perfect substitute for owner-occupied housing. We assume, instead, that the preferential tax treatment of owner-occupied housing and the transactions costs and agency costs involved in the rental market for housing create frictions large enough to effectively constrain the household to include in its asset portfolio the level of housing consistent with its consumption of housing services. The paper focuses on the impact of the portfolio constraint imposed by the consumption demand for housing on the household’s optimal holdings of financial assets. Section II of the paper is similar in spirit to a recent paper by Jan K. Brueckner (1997), which analyzes the interaction between the consumption demand and the investment demand for housing in a mean-variance portfolio model. Brueckner considers a general covariance matrix and mean vector of returns and a general utility function, and derives analytical results. In contrast, our implementation of the meanvariance framework is quantitative. That is, we estimate the covariance matrix and vector of expected returns for housing and financial assets and solve for the efficient frontiers and optimal portfolios numerically. The risk characteristics of housing are estimated using two distinct sources: data from the Panel Study of Income Dynamics (PSID) and data from Karl E. Case and Robert J. Shiller (1989) based on repeat sales transactions prices for four U.S. cities. Both data sources indicate that housing prices have a large idiosyncratic component; the standard deviation of the return to housing, at the level of the individual house, is about 0.14. In addition to housing, the portfolio can include nonnegative amounts of Treasury bills, Treasury bonds, and stocks. The household can borrow only in the form of a mortgage, which is limited to 100 percent of the value of the house. Using the estimated vector of expected returns and covariance matrix of asset returns, we plot the constrained meanvariance efficient frontiers for various values of the household’s ratio of house value to wealth, h (the “housing constraint”). The housing constraint has an enormous effect on the risk and return trade-off available to the household. Young households, which typically have large holdings of real estate relative to their net worth, are highly leveraged and therefore forced into a situation of high risk (and return). As a result, these young households have a strong incentive to reduce the risk of their portfolio by using their net worth to either pay down their * Flavin: Department of Economics, University of California, San Diego, CA 92093, and National Bureau of Economic Research (e-mail: mflavin@ucsd.edu); Yamashita: Department of Economics, University of Nevada, Las Vegas, NV 89154 (e-mail: tyamashi@ccmail.nevada.edu). We thank Elena Bisagni, Jan Brueckner, Wouter den Haan, James Hamilton, Bruce Lehmann, Greg Mankiw, and the referees for comments, and Robert Shiller for providing the house price transactions data. 1 The implications of the dual role of housing (as both a consumption good and an investment good) for tenure decisions of households were first analyzed by J. Vernon Henderson and Yannis M. Ioannides (1983).

Abstract: This paper examines the implications of bank activity and short-term funding strategies for bank risk and return using an international sample of 1334 banks in 101 countries leading up to the 2007 financial crisis. Expansion into non-interest income generating activities such as trading increases the rate of return on assets, and it may offer some risk diversification benefits at very low levels. Non-deposit, wholesale funding in contrast lowers the rate of return on assets, while it can offer some risk reduction at commonly observed low levels of non-deposit funding. A sizeable proportion of banks, however, attract most of their short-term funding in the form of non-deposits at a cost of enhanced bank fragility. Overall, banking strategies that rely prominently on generating non-interest income or attracting non-deposit funding are very risky, consistent with the demise of the U.S. investment banking sector.