A variety of financial models are cast as nonlinear parameter restrictions on multivariate regression models, and the framework seems well suited for empirical purposes. Aside from eliminating the errors-in-the-variables problem which has plagued a number of past studies, the suggested methodology increases the precision of estimated risk premiums by as much as 76%. In addition, the approach leads naturally to a likelihood ratio test of the parameter restrictions as a test for a financial model. This testing framework has considerable power over past test statistics. With no additional variable beyond β, the substantive content of the CAPM is rejected for the period 1926–1975 with a significance level less than 0.001.

The title of this paper is somewhat inappropriate, for it may suggest that finance is a study separate from economics. In fact, most researchers in finance refer to themselves as financial economists, and many have done their graduate work in departments of economics. A more appropriate (but longer) title would refer to the interrelations of financial economics and other fields in economics. Given finance is a field within economics, it is not surprising that finance has borrowed heavily from other disciplines within economics and that the reverse has occurred as well-although the latter is a newer phenomenon than the former. Financial economics has a long tradition of empirical work which will be the focus of this paper. I categorize the cross fertilization between finance and economics in the next four sections. The first section discusses the sharing of econometric methods. Section II focuses on situations where other fields in economics also attempt to explain prices of financial securities. Because of the quality and quantity of financial data, finance has served as an empirical laboratory for other fields in economics; this is discussed in the third section. Finally, since security prices are governed in part by expectations about future economic variables, there have been attempts to extract these expectations (as well as other unobservables) from the observed prices of financial assets. Section IV notes some examples of where unobservables have been extracted from prices of securities. Using financial data to measure the economic impact of certain events or to extract unobservables presumes that the participants in the financial market are rational. To the extent that this rationality assumption is violated calls into question the usefulness of financial data. Section V discusses some of the recent empirical anomalies in financial economics as well as their ramifications for employing financial data. This paper is not an exhaustive survey of all the interrelations between finance and economics. Instead the paper only attempts to illustrate some of the interrelations by relying on a few examples.

Michael R. Gibbons, Empirical Research on Bond Pricing: Discussion, The Journal of Finance, Vol. 38, No. 2, Papers and Proceedings Forty-First Annual Meeting American Finance Association New York, N.Y. December 28-30, 1982 (May, 1983), pp. 648-650

[We test the theory of the term structure of indexed-bond prices due to Cox, Ingersoll, and Ross (CIR). The econometric method uses Hansen's generalized method of moments and exploits the probability distribution of the single-state variable in CIR's model, thus avoiding the use of aggregate consumption data. It enables us to estimate a continuous-time model based on discretely sampled data. The tests indicate that CIR's model for index bonds performs reasonably well when confronted with short-term Treasury-bill returns. The estimates indicate that term premiums are positive and that yield curves can take several shapes. However, the fitted model does poorly in explaining the serial correlation in real Treasury-bill returns.]

When testing portfolio efficiency, empiricists usually perform tests using subperiods and aggregate the results in some manner. Although the power of individual subperiod tests has been studied previously, little is known about the power of the aggregate test. Power is evaluated here through simulations using two different aggregation techniques. Aggregate power is substantially higher than that for a single subperiod. For example, in one scenario the aggregate power is 0.77 over a sixty-year period, but only 0.17 for each five-year subperiod. In addition, the level of power depends on the method of aggregation.

When the assumption of constant risk premiums is relaxed, financial valuation models may be tested, and risk measures estimated without specifying a market index or state variables. This is accomplished by examining the behavior of conditional expected returns. The approach is developed using a single risk premium asset pricing model as an example and then extended to models with multiple risk premiums. The methodology is illustrated using daily return data on the common stocks of the Dow Jones 30. The tests indicate that these returns are consistent with a single, time-varying risk premium.

We test the theory of the term structure of indexed-bond prices due to Cox, Ingersoll, and Ross (CIR). The econometric method uses Hansen’s generalized method of moments and exploits the probability distribution of the single-state variable in CIR’s model, thus avoiding the use of aggregate consumption data. It enables us to estimate a continuous-time model based on discretely sampled data. The tests indicate that CIR’s model for index bonds performs reasonably well when confronted with short-term Treasury-bill returns. The estimates indicate that term premiums are positive and that yield curves can take several shapes. However, the fitted model does poorly in explaining the serial correlation in real Treasury-bill returns.

ABSTRACT The empirical implications of the consumption‐oriented capital asset pricing model (CCAPM) are examined, and its performance is compared with a model based on the market portfolio. The CCAPM is estimated after adjusting for measurement problems associated with reported consumption data. The CCAPM is tested using betas based on both consumption and the portfolio having the maximum correlation with consumption. As predicted by the CCAPM, the market price of risk is significantly positive, and the estimate of the real interest rate is close to zero. The performances of the traditional CAPM and the CCAPM are about the same.