87% of all funds return less than S&P??????

I read this article in WSJ sometime ago and since I trust their information, I am schocked.

How can this be true? Are all these people unaware of the S&P index fund or any other index funds for that matter?

Forget the return, investors to these funds, why are they paying all those expense ratios and front load charges and back end charges? Just to receive returns less than S&P??? I can understand some funds returning less than the index but 87% of all funds???

C'ommmon what am I missing here?

 

Most people outside of the industry have no idea what an index fund is. Unfortunately, even the ones who do know are locked into company 401k plans that have specific mutual fund choices to pick from (no index funds).

It's all a big scam by the Wall St. titans to keep milking free money from the American sheeple.

 

ZERO SUM GAME.

 

There are many good articles or papers that talk about the challenges of active vs. passive investing but it should be noted that not all funds are attempting to beat the S&P, many are targeting specific sector exposure, others are going for growth or value or capital gains vs. dividend income, lower drawdown, volatility, etc, etc. Those usually get grouped into that 75-80% of funds don't beat the S&P figure that everyone throws around.

Having said that, I don't think you are missing much. Its fairly common knowledge with most investors these days that passive strategies and benchmarking do outpeform many managers.........hence the explosion of money into etf's and the vanguards of this world.

Money flows, where money grows, as they say.

 

The answer is quite simple. Most people are stupid.

 

Hi, kapama

> 87% of all funds return less than S&P??????

I read something similar more than 10 years ago.

Maybe we do not have to pay any penny to professional active managers. But when the market is plunging, they can outperform the index due to their cash positions.

 

Since more and more money is going into "managed" products, the underperformance will continue because people want somebody else to make the buy/sell decisions.

 

It’s normal. For example a significant contribution to the index return can come from a small number of stocks. If a large number of funds don’t have them in their portfolio they will underperform. Put in the equation the expenses etc… To illustrate the point I did a (not so realistic) quick monte carlo experiment with 100 funds each investing in 20 of 100 available uncorrelated stocks. With 2% commissions-expenses more than 60% of the funds underperformed the balanced 100 stocks index.

Code:

' Dimensioning
Randomize
Dim i As Integer
Dim j As Integer
Dim k As Integer
Dim a(1 To 100,1 To 100) As Double ' the allocation table of 100 funds in 100 stocks
Dim s(1 To 100) As Double ' random stock prices
Dim iportf As Double ' index portfolio value
Dim fportf As Double ' fund portfolio value
Dim nportf As Double ' nbr of funds that are bellow index portfolio value
Dim averagen As Double ' average nbr of funds that are bellow index portfolio value after 1000 sims
Dim coms As Double ' commisions 
' Functions
'************************************************************
' random numbers following gauss distribution               *
'************************************************************
Function gaussMT() As Double
Dim fac As Double, r As Double, v1 As Double, v2 As Double
    g_10:
    v1 = 2 * Rnd() - 1
    v2 = 2 * Rnd() - 1
    r = v1 ^ 2 + v2 ^ 2
    If (r >= 1) Then GoTo g_10
    fac = Sqr(-2 * Log(r) / r)
    gaussMT = v2 * fac
End Function
'************************************************************
' next closing price given
'************************************************************
Function F_NextPrice(byval Prev As Double, byval mean As Double, byval vol As Double, byval tm As Double) As Double
    F_NextPrice = Prev * Exp((mean - vol ^ 2 / 2) * tm + vol * gaussMT() * Sqr(tm))
End Function
' populate the allocation matrix
For i = 1 To 100
	For j = 1 To 20
		k = Int(100*Rnd())+1
		a(i,k) = a(i,k) + 5
	Next j	
Next i
' print percentage of allocations that are bellow a ballanced index portfolio (use 10000 simulations)
coms = 2
For k = 1 To 10000
	' genarate 100 uncorrelated stock prices for the 100 stocks
	For i = 1 To 100
		s(i) = F_NextPrice(1, 0.04, 0.3, 1)	
	Next i
	iportf = 0
	For i = 1 To 100
		iportf = iportf + s(i)	
	Next i
	'Print "index: ";iportf
	nportf = 0
	For i = 1 To 100
		fportf = 0
		For j = 1 To 100
			fportf = fportf + a(i,j) * s (j)
		Next j
		'Print "fund ";i; ": ";fportf
		If fportf < iportf + coms Then nportf = nportf + 1
	Next i
	'Print "nbr of funds below index: ";nportf
	averagen = averagen + nportf
Next k
averagen = averagen/10000
Print "average nbr of funds below index: ";averagen
Sleep

 

From what I know most mutual funds do not benchmark against the SP500. Why would a corporate bond fund, japan small cap equity or alternative energy fund be compared to the SP500?

 

From :

Mutual Fund Performance:
An Empirical Decomposition into
Stock-Picking Talent, Style,
Transactions Costs, and Expenses

THE JOURNAL OF FINANCE • VOL. LV, NO. 4 • AUGUST 2000

RUSS WERMERS*


F. Do Funds that Trade More Frequently Generate Better Performance?


A concept that is central to the idea of actively managed funds outperforming
index funds is that higher levels of trading activity are associated
with better stock-picking abilities. Do higher levels of mutual fund trading
result in higher levels of performance? Our next tests address this issue by
examining the performance of high- versus low-turnover funds. If more frequent
trading is associated with managers having better stock-picking talents,
then we should observe a corresponding increase in performance, at least before trading costs and expenses are factored in. If, instead, managers
trade more frequently in an attempt to convince investors that they can
successfully pick stocks, we should see no increase in performance before
costs and expenses. In this case, we should actually see lower performance,
after costs and expenses are deducted, for frequent traders. Carhart ~1997!
finds evidence that supports this view, although his data set does not allow
an examination of performance at the stock holdings level.
We proceed as follows. At the end of each year, beginning on December 31,
1975, and ending December 31, 1993, we rank all mutual funds ~with at
least a one-year history! on their turnover level of the prior year ~the “ranking
year”!. Fractile portfolios are formed based on this ranking, and TNAaverage
fund returns and characteristics are computed over the following
year ~the “test year”!. In computing the test year average returns or performance
measures, we first compute TNA-average measures for each quarter
of the test year, across all funds that existed during that quarter ~whether or
not they survived past the end of the quarter! to minimize survival bias.
Then, these quarterly TNA-weighted buy-and-hold returns are compounded
into a quarterly rebalanced test-year return.

http://www.rhsmith.umd.edu/faculty/rwermers/mutuals.pdf