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This article carries out an asset-pricing analysis of the U.S. metropolitan housing market. We use ZIP code-level housing data to study the cross-sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk-return analysis is cross-sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset-pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. Our results on the return-volatility-price relation are robust to (i) metropolitan statistical area clustering effects and (ii) differences in socioeconomic characteristics among submarkets related to income, employment rate, managerial employment, owner-occupied housing, gross rent and population density.It is well known that investment assets trading in financial markets typically exhibit a positive relation between risk and return. For example, as an asset class, the more volatile small-cap stocks exhibit higher returns over the long run than large-cap stocks. Does such a relation also exist in the U.S. housing market where housing has the dual role of consumption and investment and where transaction costs and liquidity risk are high? In other words, do riskier, more volatile housing markets also provide higher returns? Furthermore, what is the impact of the house-price level on this risk-return relation and how does exposure to the stock market affect housing returns?

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This paper studies how CEO pay and its composition is shaped by strategic factors related to the firm's capacity to generate rents and value, the uncertainty of its resource advantage, and the competitive interaction between firm stakeholders and top management. This is done using an analytical framework in which the CEO and other firm stakeholders interact over the firm's resource surplus as utility-maximizing claimants based on their relative bargaining power while providing shareholders their market-based required return. Results from the model yield a number of cogent strategic insights and predictions on the causal interplay between CEO pay, firm growth and risk characteristics, stakeholder management, corporate strategy (e.g., offshoring production), and behavioral biases such as CEO optimism and overconfidence.