Excess Returns of Industrial Stocks and the Real Estate Factor

Abstract

1. Introduction For more than three decades, numerous studies have been devoted to capital asset pricing issues. Identifying key factors influencing returns on capital assets remains the major focus of the studies. According to the first important asset pricing theory, the capital asset pricing model (CAPM) of Sharpe (1964) and Lintner (1965), there is a positive linear relationship between expected stock returns and market betas. This single-factor model is theoretically challenged by the arbitrage pricing theory (APT) developed by Ross (1976). The APT provides a theoretical framework to identify more macro factors that have significant explanatory power for stock returns (Roll and Ross 1980; Chen 1983; Bower, Bower, and Logue 1984; and Chen, Roll, and Ross 1986). In order to be included in a multifactor model, a factor must represent a source of nondiversifiable or systematic risk. In addition to theoretical challenges, the evidence of many empirical studies casts doubts on the adequacy of the long-existing CAPM. For example, the findings of Fama and French (1996) suggest that Ps alone cannot explain expected returns on common stocks. Meantime, other macro factors related to the bond market, such as unanticipated changes in the term structure (Chen, Roll, and Ross 1986), are used to explain stock returns. In recent years, more risk factors have been suggested in the literature. For example, in their time-series study about common risk factors in the returns on common stocks, Fama and French (1993) argue that there are three stock market factors, an overall market factor, a size factor (stock price times number of shares), and a book-to-market equity factor, that have a significant impact on stock returns. In addition, two bond market factors, the term structure and risk factors, can capture common variation in stock and bond returns (Fama and French 1993). Similar to Fama and French's (1993) multifactor models, the present study uses all three stock market factors (an overall stock market factor, a size factor, and a book-to-market equity factor), two bond market factors related to maturity and default risks, and a real estate market factor. The reason for introducing a new risk factor, real estate market factor, although not so obvious, is engendered by the theoretical spirit of the APT Real estate is a major asset class, and as almost all firms have operating expenses under this category, it does not matter if the properties are acquired or rented. According to Zeckhauser and Silverman (1983), a significant portion of corporate assets, on average as high as 25%, is real estate related. Changes in real estate market value, therefore, potentially have a direct impact on the value of corporate assets and operating expenditures. If this impact is significant, as are other systematic risk factors, the real estate market factor must play an important role in stock pricing. In addition, the real estate market risk is a macro factor. Therefore, results about this factor do not have any interpretation problems that are associated with firm-specific variables. In order to identify significant factors in explaining returns for industrial stocks, this study estimates various models based on the following six risk factors: an overall stock market factor, a size factor, a book-to-market equity factor, a term structure factor, a default risk factor, and an unsecuritized real estate market factor. Results of this study provide some empirical evidence about the significance of the six risk factors on excess returns for industrial stocks. In addition, this study also investigates how the inclusion of additional risk factors, for example, the inclusion of the bond market factors or the real estate market factor in the single market-factor model, increases the explanatory power of the model. The remainder of this study is organized as follows. Section 2 describes the data and methodology; section 3 presents the empirical results; and section 4 contains the conclusions. …