wouldn’t buy a new home just because it looked good from the
outside. We would do a thorough walk-through first. We’d examine the fur-
nace, check for a leaky roof, and look for cracks in the foundation.
Mutual fund investing requires the same careful investigation. You need
to give a fund more than a surface-level once-over before investing in it.
Knowing that the fund has been a good performer in the past isn’t enough
to warrant risking your money. You need to understand what’s inside its
portfolio—or how it invests.
This chapter describe basic features and operating characteristics of a mutual funds and exchange traded funds; differentiate between open- and closed-end mutual funds as well as exchange traded funds, and discuss the various types of fund loads and charges; discuss types of funds available to investors and the different kinds of investors services offered by mutual funds and exchange traded funds;...
Chapter 4 "Mutual funds and other investment companies" presents the following content: services of investment companies, net asset value, types of investment organizations, investment policies, costs of investing in mutual funds, exchange traded funds, a first look at fund performance,...
Many of the same organizations who provided me with data for the first edition of Stocks for the Long Run willingly updated their data for this second edition. I include Lipper Analytical Services and the Vanguard Group for their mutual funds data, Morgan Stanley for their Capital Market indexes,
Smithers & Co. for their market value data and Bloomberg Financial for their graphic representations.
very month, it seems, Wall Street comes up with some newfangled
investment idea. The array of financial products (replete with 164-page
prospectuses) is now so dizzying that the old lumpy mattress is starting to
look like a more comfortable place to stash the cash. But there is one relatively
new product out there definitely worth looking at. It’s something of a
cross between an index mutual fund and a stock, and it’s called an exchangetraded
fund, or ETF.
However, there are a number
of advantages to examining the smart money effect in fund management using
our U.K.mutual fund data. First, ourmoney f low data aremonthly rather than
quarterly. Second, we observe exact f lows rather than approximations based on
fund values and fund returns. Third, we can distinguish between institutional
and individualmoney f lows. Fourth, we can distinguish between purchases and
A further advantage is that we are able to examine mutual fund investor
behavior in a different institutional setting from that of the United States.
Mutual funds charge two kinds of fees: expenses and loads. Expenses comprise the management
fee (typically a fixed percentage of assets under management) and other recurring operating
costs—such as custodian, administration, accounting, registration, and transfer agent fees.
Rather than charging explicit fees for these expenses, funds deduct them on a daily basis from
the fund's net assets. Expenses are expressed as a percentage of assets under management (the
expense ratio). Loads are one-time fees used to compensate distributors.
A board’s role is to provide oversight, not to manage risks. Just as a board does not
manage a fund’s investments or its business operations, it also does not manage the
risks associated with those activities. Board oversight includes understanding the risk
management processes employed by the adviser, asking questions where appropriate,
and obtaining appropriate assurances that the processes are reasonably designed to
manage and control the fund’s material risks.
The second aim of this thesis is to investigate whether Thai mutual fund performance
can be explained by any of its characteristics. The study examines statistic and economic
importance of fund characteristics to its performance. In the literature, evidence is sparse and
mixed on developed markets, let alone that on emerging markets. Rather than focusing on
one particular characteristic, this study draws on the evidence from five important
characteristics in the literature, which offer theoretical and empirical support.
study also offers an auxiliary performance measure to capture this effect and assesses how
important it is to mutual fund performance in Thailand.
The fourth aim of this thesis is to investigate and discuss policy implications in
Thailand which adopt tax-advantaged types of mutual fund in order to encourage retirement
and long-term savings. In this thesis, the performance and characteristics of these tax-
advantaged funds are also investigated in a separate group and compared to those of general
mutual funds. ...
In addition to testing for the presence of smart money, the disaggregated na-
ture of our fund f low data allows us to examine two key hypotheses with respect
to mutual fund investor behavior. Specifically, we are in a position to compare
the quality of fund selection decisions made by individual and institutional
investors, and likewise to compare fund buying and selling decisions.
The Investment Company Products/Variable Contracts Products Limited Representative Qualification Examination
(Test Series 6) is a 100-question multiple-choice examination. A maximum of 135 minutes testing
time is allowed for candidates to complete the examination. The passing grade is equal to 70% of the total
number of questions on the examination. Candidates will be required to correctly answer 70 of the 100 questions
on the examination to receive a passing grade.
With respect to equity mutual funds, the study further notes that funds are experiencing
diseconomies of scale in their expense ratios when their size exceeds $600 million to
Interestingly, the foregoing study does not even address the problem of "market impact costs"
which are clearly an even greater expense to mutual funds than are the more visible costs used in
the calculation of their...
To quantify the impact of luck on mutual fund performance, we use the False Discovery
Rate (F DR) introduced by Benjamini and Hochberg (1995) in the statistical
literature. The F DR measures the proportion of lucky funds among the funds with significant
estimated alphas. We extend this methodology by developing a new approach
which allows us to separately compute the F DR among funds with significant positive
estimated alphas (called hereafter the best funds) and funds with significant negative
estimated alphas (called hereafter the worst funds)....
As I noted, the ﬁnancial crisis has created an increasingly
global outlook among policymakers. More and more, national
regulators are inﬂuenced by policies fashioned abroad, and
international bodies are stepping up policy coordination.
At the same time, the extraordinary worldwide rise of as-
set managers as ﬁnancial intermediaries has created new
opportunities for funds. Responding to these and other
trends, the Institute readied a new initiative —ICI Global—
launched early in ﬁscal year 2012.
Our study has signicant real-world economic implications. European funds grew from a little
over $3 trillion during 2000 to nearly $9 trillion during 2007; by the end of 2007, the European
industry amounted to nearly three-quarters of the size of the U.S. mutual fund industry, which, over
the same period, grew from $7 trillion to $12 trillion. Further, there were over 35,000 European-
domiciled mutual funds by the end of 2010 (Investment Company Institute, 2011), almost ve
times the number of U.S.-domiciled funds, indicating that the European market is highly frag-
We focus on the dynamics of active management skills, and how an investor might optimally
choose active funds during varying business conditions. Building on studies such as Avramov and
Wermers (2006) and Moskowitz (2000), we allow for the possibility of time-varying mutual fund
alphas and betas among active managers in Europe. Following Christopherson, et al. (1998)
and Ferson and Schadt (1996), we model such time-variation using a publicly available set of
conditioning state variables.
More importantly, while most of the theoretical models which we use to evaluate
mutual fund performance are based on the assumption of efficient markets, emerging markets
fail to meet these assumptions. Returns in emerging markets suffer from several chronic
conditions such as high volatility, high trading cost, non-normality, and infrequent trading
(Bekaert and Harvey, 2002). Furthermore, there is still some doubt whether the factors
documented in developed markets can also explain stock returns in emerging markets (for
example, Claessens et al.