2009
DOI: 10.1093/rfs/hhp022
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Assessing the Costs and Benefits of Brokers in the Mutual Fund Industry

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Cited by 458 publications
(99 citation statements)
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“…We reach similar conclusions when we use fund marketing fees (MKTING) in models (xvii)-(xx). The negative relationship between non-advisory fees (either 12B-1 or MKTING) and gross performance is also consistent with Bergstresser, Chalmers, and Tufano (2009). They show that broker-sold mutual funds perform worse and charge significantly higher marketing fees than direct-sold mutual funds.…”
Section: G the Relationship Between Fees And Before-fee Performancesupporting
confidence: 72%
“…We reach similar conclusions when we use fund marketing fees (MKTING) in models (xvii)-(xx). The negative relationship between non-advisory fees (either 12B-1 or MKTING) and gross performance is also consistent with Bergstresser, Chalmers, and Tufano (2009). They show that broker-sold mutual funds perform worse and charge significantly higher marketing fees than direct-sold mutual funds.…”
Section: G the Relationship Between Fees And Before-fee Performancesupporting
confidence: 72%
“…by shifting a portion of the sales loads to annual kick back payments. Some researchers have started to assess the value added by brokers in the mutual fund industry (see Bergstresser et al (2006)), but further clarification is needed.…”
Section: Financial Literacy Bta and The Decision To Select An Activementioning
confidence: 99%
“…This may for instance re ‡ect her concerns about reputational losses following unsuitable sales. 7 In Section 7.1 we show more carefully how these externalities might result from the advisor's sales commissions, and her reputational and career concerns. Of course, when = 0, the advisor's utility is separable across clients, and there is no di¤erence between exclusive and non-exclusive …nancial advice.…”
Section: The Baseline Modelmentioning
confidence: 99%
“…6 An analogous approach is followed in Stocken (2003). 7 Gennaioli et al (2013), for instance, argue that money mangers are particularly sensitive to their reputation. In our model we are implicitly assuming that reputation may be crucially a¤ected by the size of an advisor's clientele via network e¤ects that may arise from (un-modeled) information spillovers between clients.…”
Section: The Baseline Modelmentioning
confidence: 99%