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UBC Theses and Dissertations

A statistical investigation of the returns on closed-end investment companies Ellis, Denise Taylor


The common shares of closed-end funds, unlike mutual funds, trade on the stock exchanges. A market determined value of the assets of closed-end funds (net asset value) is published weekly for those funds listed on the New York Stock Exchange. A discrepancy exists between the market price of the common share of the closed-end fund and the net asset value per common share of the fund. The size of these discrepancies, premiums and discounts, has never been adequately explained within the context of financial theory. Furthermore, estimates of risk coefficients (betas) are such that the common equity appears les risky than the closed-end fund itself. An investigation was undertaken of the statistical properties associated with both weekly and monthly market value and net asset value return series for twelve closed-end funds listed on the New York Stock Exchange from 1965 to the end of 1972. These twelve funds account for approx imately fifty percent of all funds by asset size listed during that period. Non-parametric tests demonstrated a lack of independence in contiguous observations and some additional support was given by a measure of serial correlation. Goodness-of-fit tests were performed for the normal distribution and it was rejected as representative of the data. The distribution of the return series, as verified by the sample moments, is leptokurtic and shows properties consistent with a stable distribution. The lack of independence and normality in the data causes serious violations of the assumptions necessary to fit the market model in order to estimate the betas of the closed-end funds. The violations are such that the market return betas are likely to be seriously underestimated and therefore cause the common equity of closed-end funds to appear less risky than the funds themselves. Some support for theory which indicates that the common equity should be riskier is given by the results of the lagged market model.

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