EXPLOITING CLOSED‐END FUND DISCOUNTS: A SYSTEMATIC EXAMINATION OF ALPHAS
系统研究了封闭式基金溢价历史中包含的信息价值，通过参数化估计预期收益并构建多空组合，发现利用历史溢价信息可获得年化18.2%的收益，表明以往仅关注当前溢价的研究低估了信息价值。
Abstract We systematically study the value of the information contained in closed‐end fund (CEF) premiums. We parametrically estimate CEF expected returns as a function of the history of CEF premiums, in addition to the current premium, and buy the quintile of funds with the highest expected returns and sell the quintile of funds with the lowest expected returns. The return on this portfolio suggests that previous studies, which examine the information in current premiums only, have understated the value of the information in premiums. Our strategy values the information in the history of CEF premiums at an annualized return of 18.2%.