This paper investigates optimal consumption and portfolio mixture for a new discrete-time, discrete-state preference model. In this model, the investor's preferences for future consumption depend on current wealth and on past consumption experience through a summary descriptor of past consumption. Relations between the optimal consumption/investment decisions and the wealth and summary descriptor states are found.

One of the virtues of parameter preference models (presented in general form in Rubinstein [23]) is their empirical content. Applied models of financial theory rely heavily on the mean variance (MV) version of parameter preference. As spelled out in Samuelson [25], MV models are adequate with compact distributions of returns and when portfolio decisions are made frequently so that the risk parameter becomes sufficiently small.

In their article, “Beta as a Random Coefficient,” Fabozzi and Francis [1] present evidence which suggests that beta is a random coefficient for a “significant minority” of NYSE stocks. They obtained their evidence first, by characterizing the market model as a random coefficient model of the type described by Theil and Mennes [7], and second, by estimating its parameters for a sample of NYSE stocks over the period December 1965 through December 1971. This paper describes weaknesses in Fabozzi and Francis' implementation of the estimation procedures of Theil and Mennes [7] and Hildreth and Houck [3]. Improvements are suggested and utilized in an analysis of the returns of 683 NYSE stocks over the period January I960 through December 1971. The results of the analysis indicate that Fabozzi and Francis have overstated the case for beta being a random coefficient of the form described by Theil and Mennes.

Forecasts of financial prices, calculated from the present and past values, are never substantially more accurate than the prediction that future prices will equal the most recently observed price. This conclusion has been summarized by two hypotheses. First, the random walk hypothesis, states that daily returns are uncorrelated. Few people believe that this is exactly correct; indeed, the hypothesis has been refuted both for small stock markets [13] and for American commodity futures markets [3]. Second, the weak-form efficient market hypothesis, as defined by Jensen [15], states that investors cannot make profits from any correlation between returns, after deducting all the costs of trading and adjusting for risk. Strict efficiency, is a special case that occurs when prices fully reflect all information available in the past prices [7], [8].

In a paper published in 1978, Levy [5] proposed a general capital asset pricing model (GCAPM), which he obtained by maximizing investors' utility when the number of securities held in each investor's portfolio is constrained. Although Levy's resultant asset pricing model is somewhat different in appearance than the asset pricing model proposed by Mao [8] in 1971, it can be shown that both models are not only quite comparable in content but that both result in some very promising theoretical and empirical implications. Thus, the purpose of this paper is twofold. First, these two important contributions to the literature on asset pricing in imperfect markets will be compared and contrasted. Second, it will be shown that both models can yield a “clinical” form of the traditional CAPM, which appears to be more desirable for empirical testing purposes.

Recent developments in the finance literature dealing with the valuation of contingent claims have been triggered by Black and Scholes [2] with their valuation of European options on corporate stocks. The type of valuation model derived by Black and Scholes is attractive because it is independent of preferences. This independence is possible due to the fact that the contingent claims are usually assumed to be contingent on traded assets or traded state variables. For example, a European call option is a claim contingent on the value of the corresponding stock. To maintain the independence of the claim from preferences, however, some variables have to be discarded and considered as constants. For example, the rate of interest, which is not a traded state variable, is considered a constant in most of the literature (see Black and Scholes [2], Merton [11], and Ingersoll [9]). Though this approximation might not cause important discrepancies in the case of corporate liabilities and options on corporate liabilities, the effect of such an approximation on the value of default-free bonds and options on default-free bonds is more important since these liabilities depend only on the rate of interest.

The concept of immunization is currently one of the most widely discussed innovations in bond portfolio management. The interest in immunization, which allows one to nearly guarantee a minimum return performance over a specified investment horizon, is due in large measure to the desire on the part of bond managers to reduce the risk which has accompanied the recent swings in interest rates.

While the literature in finance is replete with studies on stock betas, bond betas have, to this day, not attracted much attention. This is quite understandable because much of the finance literature addresses stock betas in the context of the single period Capital Asset Pricing Model (CAPM). In the single period model, the risk-free rate (if it exists) is assumed to be constant over the period in question. Since the interest rate is fixed and investors are required to hold these default-free bonds over the entire period, interest rate risk, and, consequently, systematic risk for bonds do not exist. However, if the constant risk-free rate assumption is relaxedand investors are allowed to trade “intra period,” (say continuously), Merton [4] has argued that an Intertemporal Capital Asset Pricing Model can be derived. Using Merton's framework, Jarrow [3] has recently derived a systematic risk measure for bonds. The primary intent of this paper is to investigate the effect of yield changes on the systematic risk of bonds. As we will demonstrate, the impact of yield changes on bond betas depends on several (sometimes complex) relationships between yields, duration, and bond prices. We derive conditions under which bond betas increase/decrease and show that the elasticity of duration with respect to yields and the sign of the initial beta of a bond will determine the manner in which yield changes affect bond betas.

Much of the empirical research on mutual funds has rather significant implications for mutual fund investors. Unfortunately, many mutual fund investors have probably never heard about these research results or their implications. They probably, however, have heard some rules-of-thumb or guidelines from their brokers or peers about how to select a particular fund. The purpose of this note is to identify the selection criteria investors seem to use in their buying and selling of mutual fund shares once they have selected an investment objective. That is, do investors select mutual funds based on what I will call “efficient market” criteria (whether or not they are familiar with this literature), or do they use other factors? The criterion I use to measure selection by mutual fund investors is the annual net sales ratio, which is gross sales less redemptions divided by total assets at the start of the year.