provides insight on the average performance of actively managed mutual funds from ~5 years ago:     Growth fund managers fared even worse, with just 6% of growth funds beating their benchmark -- the worst such result since at least 1991. The average margin of underperformance reached a whopping 3.5 percentage points.   If it becomes harder and harder to beat the large indexes, why would one still go with actively managed mutual funds? My understanding is that they are also more pricey, expense ratio-wise, and come with more tax hurdles. Furthermore, I'd assume that modern technology like robo-advisors is going places.
The general consensus is that the single best indicator of a fund's future performance is the its expense ratio . If you look for more than 5 minutes online you discover the  approach to investing; the , etc. It looks like the less you pay for a fund (and therefore the less it's managed), the better it does in the long run.  So why is it that in peoples' 401(k)s there are so many high-cost actively managed funds? Furthermore, why are there so many high-cost actively managed funds in the first place? Shouldn't the market reflect the fact that actively-managed funds typically don't beat the index they benchmark to and and react by purging itself of these crappy funds?
I have a set of surround speakers, connected to my iMac through the headphone jack. I use a switch to control what goes to the speaker set (iMac, iPod, or MacBook/aux). So that I don't have to be constantly unplugging and replugging, I leave the audio cable in the iMac's audio port. This means that when I'm listening to something from another source, I can't hear anything from the iMac unless I unplug the cable.  Is there a way to force sound to come out of the internal speakers, even if there's something in the audio out port? What is the metal sheath surrounding a USB connector, and is it commonly connected? I need to find the closure of these sets on the ordered square: $$A = \{(1/n)\times 0 | n\in \mathbb{Z}_+\}$$ $$B = \{(1-1/n)\times \frac{1}{2}| n\in \mathbb{Z}_+\}$$ $$C = \{x\times 0 | 0&lt;x&lt;1\}$$ $$D = \{x\times \frac{1}{2}| 0&lt;x&lt;1\}$$ $$E = \{\frac{1}{2}\times y | 0&lt;y&lt;1\}$$ I know that the closure is just the set itself united with its limit points. For $A$, the set of limit points, I imagine, are $\{&lt;1,0&gt;\}$, that is, the $x$ coordinate is $1$ and the $y$ is $0$. But  is says the reverse. What am I getting wrong? Following the same reasoning, $B' = \{&lt;1,\frac{1}{2}&gt;\}$ $C' = \{&lt;0,0&gt;,&lt;0,1&gt;\}$ What am I doing wrong? Possible Duplicate:          Is there some rule governing the following, or similar, subject-auxiliary inversions (*"Rarely they do see the light of day", *"Never I have been so insulted")?     In fancy sit-down restaurants, you can order a large meal and halfway through the main course, take a little dead cockroach or a piece of glass out of your pocket and place it deftly on the plate. Jump up astonished and summon the headwaiter. "Never have I been so insulted. I could have been poisoned" you scream slapping down the napkin. You can refuse to pay and leave, or let the waiter talk you into having a brand new meal on the house for this terrible inconvenience. 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Am I missing something on how supporting multi-resolution works or do I indeed do need to do much more work using cocos2d-x? What is the icon next to Spotlight in menu bar, and how to remove it? What is this icon   in OS X menu bar and how do you remove it? What are independent parameters in Hellmann–Feynman theorem? A typical example in textbooks about the application of Hellmann–Feynman theorem is calculating $\left\langle\frac{1}{r^2}\right\rangle$ in hydrogen-like atoms.  has a nice demonstration of this. At some point in the Wikipedia derivation is used that $$\frac{\partial n}{\partial \ell}~=~1. \tag{1}$$   But why is eq. (1) true? I know that  $$n=n_r+\ell+1,$$   but $n_r$ is just another variable with different physical meaning, so why is $n_r$ independent from $\ell$, whereas $n$ is not? The Wikipedia proof for Hellmann–Feynman theorem does not address the problem of independence of different parameters. What variables are kept fixed during the differentiation $(1)$ and why?  The Wikipedia page seems to have only a vague notion of $\frac{\partial\hat{H}}{\partial\lambda}$ and $\frac{\partial E}{\partial\lambda}$, unlike in, e.g., thermodynamics, where all partial derivatives are typically written like  $$\left( \frac{\partial U}{\partial V} \right)_S \qquad ,\qquad  \left( \frac{\partial U}{\partial V} \right)_p \qquad ,\qquad  \ldots $$ so that it is clear which variables are kept fixed during the differentiations. Does one work in or on an aeroplane? In an exam paper, there was a picture of an air stewardess in the aeroplane serving passengers. One of my pupils wrote the following:      The air stewardess works on an aeroplane.    Shouldn't it be the air stewardess works in an aeroplane? I came across the :    Which states:     $\pi$ Pi      Pi is an infinite, nonrepeating $($sic$)$ decimal - meaning that   every possible number combination exists somewhere in pi.  Converted   into ASCII text, somewhere in that infinite string of digits is the   name of every person you will ever love, the date, time and manner    of your death, and the answers to all the great questions of    the universe.   Is this true? Does it make any sense ? What are good basic statistics to use for ordinal data? Photoshop "Export > Export As" or "Export > Save For Web" in size 600px + auto suffix in filename How do I connect to a MSSQL database using Perl's DBI module in Windows? How do I connect to a MSSQL database using Perl's DBI module in Windows? How do you concatenate matrices? And how do you make block matrices? How can I restrict various roles with limit in creating nodes of a particular content type How can I restrict various roles with limit in creating nodes of a particular content type? python get only class attribute no superclasses Which predictions of The Last Jedi: Darths & Droids Bingo were correct?