Sánchez González develops an innovative model that considers different management stages of mutual fund companies, overcoming the traditional dispute between the different approaches used in banking and insurance research.

Why are there so many mutual funds around? What leads the industry to segment itself into an ever-increasing number of categories? What can be said about such a market configuration in terms of welfare? To address these questions we model the process that endogenously leads to market segmentation and to fund proliferation in the mutual fund industry.We argue that these phenomena can be seen as marketing strategies used by the managing companies to exploit investors' heterogeneity. We explain category and fund proliferation providing an industry-specific micro foundation on the basis of basis of the quot;spilloverquot; that the perfomance of a fund provides to all the other funds belonging to the same family.We argue that market forces may induce a sub-optimal number of mutual funds and categories and identify the factors that determine such inefficiency.Mutual fund performance is endogenously derived as a function of investors' and managing companies' tastes and technology. This lets us shed new light on the determinants of mutual fund performance and reconsider the traditional methods of testing fund efficiency.

This authoritative book enables readers to evaluate the variousperformance and risk attributes of mutual funds, while also servingas a comprehensive resource for students, academics, and generalinvestors alike. Avoiding the less useful descriptive approach tofund selection, this book employs a balanced approach includingboth technique and application. The chapters combine clearsummaries of existing research with practical guidelines for mutualfund analysis. Enables readers to analyze mutual funds by evaluating a fund'svarious performance and risk attributes. Includes templates, which provide an efficient, sound approachto fund analysis, interpretation of results, buy/sell decisions,and the timing of decisions. Combines clear summaries of existing research with practicalguidelines for mutual fund analysis.

This study examines how the efficiency of trading desks operated by mutual fund families affects the performance and trading of affiliated funds. We estimate the trading efficiency of a fund family's trading desk as the difference between the gross return of the family's index fund, which incorporates trading costs, and the return of the underlying index, which does not incorporate trading costs, around index adjustment dates. By operating more efficient trading desks that help reduce trading costs, fund families improve the performance of their funds significantly and also enable their funds to trade more and hold less liquid portfolios.

The importance of mutual funds for individual investors has increased in recent decades. This becomes apparent when looking at the increased share of households owning mutual funds. These mutual fund investors usually want to receive a return which is above or at least close to the mutual fund’s benchmark. Consequently, investors want to invest in those funds which will show these patterns in the future. Some of these mutual funds receive much attention, since they generate extraordinary high performance. But the question that remains is whether it is possible to predict such performance before funds exhibit such outstanding performance. In the past, mutual fund investors focused extensively on performance or performance linked patterns, like the Morningstar star rating, and thus chased past performance. This seems surprising since performance persists only over a short time and is more persistent to weak mutual funds (1 and 2 star rated) than well performing mutual funds. Thus, chasing past performances seems to be a rather inferior strategy. Therefore, investors should try to identify alternative tools showing a high correlation to future mutual fund performance. In this book, mutual funds are analysed, especially open-end mutual funds and actively managed mutual funds. The main focus is on what purpose and usefulness active investments have and whether performance is persistent and what the determinants of mutual fund flows are. Moreover, some alternative measures will be introduced by explaining which attributes or methods should be used and avoided when selecting mutual funds.

We examine whether accounting for mutual fund families can help explain the performance of their mutual funds, and if so, how they succeed to affect the performance of the funds they manage. We hypothesize that larger families not only have the incentive to selectively push some of their funds, but also the means to do so. When restricting our sample to funds that belong to larger families, a portfolio of funds that longs the portfolio of the previous year's best performing funds and shorts the previous year's worst performing funds has a positive monthly alpha of 58 basis points. We also show that there exists persistence of performance of these funds inside their respective families. This persistence is directly related to the number of funds in the family which we interpret as a measure of the latitude the family has in allocating resources unevenly between its funds. Lastly, we show that indeed the better performing funds in a family have a higher probability of getting more managers, which are one of the main resources available. This seems to imply that families do not always allocate resources proportionally according to the funds' needs but in a way that allows the family to promote certain funds.

We examine whether the previously documented positive association between fund family size and fund performance is affected by significant regulatory changes (i.e., Regulation FD, the Global Settlement (GS), and increased scrutiny as a result of trading scandals) that have occurred in the last decade. Using Regulation Fair Disclosure (Reg FD) as a beginning point for these structural changes, we find that while fund family size was positively associated with fund performance in the period prior to the regulatory changes, this advantage is significantly weaker in the period subsequent to the regulatory changes. Consistent with the weakened advantage of fund family size in fund performance, we find that the greater stock picking skill of larger fund families, measured using the earnings announcement returns of the stocks they trade, also weakened subsequent to the regulatory changes. Using narrower event windows around the regulatory changes, we find that the previously documented superior return of large fund families was partly attributable to selective disclosure. We also find that fund families implicated in the trading scandals experienced a decline in their performance during the scandal period. Finally, we examine the role of large investment banks in providing an advantage to large fund families. Family size was positively associated with the extent to which funds traded in the same direction as forecast revisions by analysts from large investment banks in the period prior to Reg FD and the GS and this association declined significantly after the two regulatory events.