Identifier	Thesis 2723
Author	Wiseman, Amy P., 1955-
Title	Closed-end funds : Factors predicting premium-discount
Publisher	Central Connecticut State University
Date of Publication	2018
Resource Type	Master's Thesis
Abstract	Closed-end funds (CEF) are a unique family of mutual funds because they trade at a price that is different than the value of the assets in their portfolios. The deviation of the price of a CEF from the value of its underlying assets is seen as a discount when the price is less than the value and a premium when it is greater. The discrepancy between price and underlying value is perplexing. Why would a seller of fund shares accept less than the value of the assets? Why would a buyer pay more for a share than its assets are worth? These questions are known as the CEF puzzle. This study built multiple regression models using publicly available measures of CEF characteristics to predict premium/discount (PD). Further, these models were used to uncover fund-level factors driving levels of PD. A multiple regression model using 34 measures was generated that predicted a full 87% of the variance PD. Because of the high collinearity and even overlap of the measures used in this model, no statement could be made about the nature of predictors influencing PD. A model using 9 principal components extracted from continuous measures and 4 categorical measures predicted 59% of the variance in PD and yielded a view of factors driving PD. Using PCA components, it was found that whether a fund was sponsored by Pacific Investment Management Company, LLC (PIMCO) was the dominant factor in the level of PD as almost all PIMCO CEFs trade at a premium. Controlling for PIMCO, annualized rate of return followed by distribution rate, past performance measures, prevailed. PD was found to be very strongly determined by past performance.
Notes	"Submitted in Partial Fulfillment of the Requirements for the degree of Master of Science in Data Mining."; Thesis advisor: Daniel Larose.; M.S.,Central Connecticut State University,,2018.; Includes bibliographical references (leaves 83-85).
Subject	Closed-end funds.
Department	Department of Mathematics
Advisor	Larose, Daniel.
Type	Text
Software	System requirements: PC and World Wide Web browser.
Language	eng
OCLC number	1082364035
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Closed-end funds : Factors predicting premium-discount

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