To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
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.
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.
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.
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.