Monday 30 September 2013

Mutual Fund Sales Charges and Your Fund Performance

Its no secret that many mutual funds are a bit of a ripoff.  There's so many fees hidden and buried in many of the less reputable ones (thankfully that's starting to change) that are completely unjustifiable.

One such fee in my opinion is sales charges.  There's several ways they can work but the most common are front end sales charges and are usually in the 5-6% range.  What happens is that when you invest in that fund, your contribution (lets say $100) will have the sales charge be deducted (lets say 5.5%) so you'll end up investing only $94.5 instead.  That's a horrendous drop in return to begin with.

Other variations of sales charges are back end, deferred, etc etc.  But with so many sales charge free (or no load) funds nowadays, why bother?  Some justification is that sales charges can help pay for better managers which allow the funds to outperform.  Does it?

In my MarketWatch article being published soon, I did a study on large actively managed value funds and took a quick look at this exact question.  What did I find?

Looking at only the 10 largest value funds by asset, I plotted their 10 year return vs total fees.  The funds with sales charges do actually have a slightly better return than the no sales charge ones so there may be something to it.






However!  If you do the return after accounting for the loss from the sales charge, you'll find the performance benefit virtually disappears and you end up at basically the same performance as the non-sales charge.  So yes, some funds with sales charges do outperform but very few do and even the ones that do end up being useless for the investor because the extra return is lost anyway.


Moral of the story?  Don't bother with sales charge funds to begin with.



Sunday 29 September 2013

Gini Coefficient & Singapore

Did some reading the other today about income inequality and its general propensity as an indicator of social unrest.  I found a neat table from CIA World Factbook listing where countries rank.

Very interesting to note that the top developed countries (is South Africa considered developed? Iffy in my opinion) on the list would be:

1 - Hong Kong (53.7)
2 - Singapore (47.8)
3 - USA (45.0)
4 - South Korea (41.9)
5 - UK (40.0)

Its a bit sad that these countries (esp #1 & 2) are on the same level as places like Guatemala, Zimbabwe, Madagascar, and China.  I'm not exactly a socialist or communist but large distributions of wealth and poverty is never a good thing.  Having traveled to many of the countries here, its really appalling to leave the nice snazzy hotel and see tarps/tents on the road median just in front with families huddled together beneath it.

For Hong Kong & Singapore, I suspect the inequality may be worse than listed because the coefficient doesn't take into account several factors like housing costs (its insane to buy a decent home in Singapore & HK without being rich).  For the USA, I'm surprised its so high considering there is still a decently sized middle class there (though shrinking every year).  Below, I also show historical Gini coefficient, notice how many countries are increasing in income inequality over time.


RANK
COUNTRYDISTRIBUTION OF FAMILY INCOME - GINI INDEXDATE OF INFORMATION
1Lesotho
63.2
1995
2South Africa
63.1
2005
3Botswana
63.0
1993
4Sierra Leone
62.9
1989
5Central African Republic
61.3
1993
6Namibia
59.7
2010
7Haiti
59.2
2001
8Colombia
58.5
2011
9Honduras
57.7
2007
10Guatemala
55.1
2007
11Hong Kong
53.7
2011
12Thailand
53.6
2009
13Paraguay
53.2
2009
14Bolivia
53.0
2010
15Chile
52.1
2009
16Panama
51.9
2010 est.
17Brazil
51.9
2012
18Papua New Guinea
50.9
1996
19Zambia
50.8
2004
20Swaziland
50.4
2001
21Costa Rica
50.3
2009
22Gambia, The
50.2
1998
23Zimbabwe
50.1
2006
24Sri Lanka
49.0
2010
25Mexico
48.3
2008
26Singapore
47.8
2012
27Ecuador
47.7
December 2012
28Madagascar
47.5
2001
29China
47.4
2012
30Dominican Republic
47.2
2010 est.
31El Salvador
46.9
2007
32Rwanda
46.8
2000
33Malaysia
46.2
2009
34Peru
46.0
2010
35Georgia
46.0
2011
36Argentina
45.8
2009
37Mozambique
45.6
2008
38Jamaica
45.5
2004
39Bulgaria
45.3
2007
40Uruguay
45.3
2010
41United States
45.0
2007
42Philippines
44.8
2009
43Cameroon
44.6
2001
44Guyana
44.6
2007
45Iran
44.5
2006
46Uganda
44.3
2009
47Nigeria
43.7
2003
48Macedonia
43.2
2009
49Kenya
42.5
2008 est.
50Burundi
42.4
1998


The change in Gini indices has differed across countries. Some countries have change little over time, such as Belgium, Canada, Germany, Japan, and Sweden. Brazil has oscillated around a steady value. France, Italy, Mexico, and Norway have shown marked declines. China and the US have increased steadily. Australia grew to moderate levels before dropping. India sank before rising again. The UK and Poland stayed at very low levels before rising. Bulgaria had an increase of fits-and-starts. .svg alt text

Tuesday 24 September 2013

Easy come, easy go!

The Fed taper surprise last week really caught the markets off guard and led to a big rally.  Oh how short lived that rally was!

Just 4 short days later, we're now below where the S&P 500 was when the taper delay rally started.  A bit surprising.  Did the market already priced in a delay (I don't think so), did the market realize that the delay doesn't mean that much (likely, taper will happen in Dec or so likely now).

Much ado about nothing after all?


Friday 6 September 2013

Why the Declining Unemployment Rate is Deceptive


Guest Post - Today I'll like to introduce a guest post from Daniel Noon, a Ph.D. student at UCLA, courtesy of Otavio Dalarossa, an Los Angeles investor.  He digs a bit into the true meaning of the job situation.

Reading between the lines and spotting uneasy trends


Is the job situation really recovering? The unemployment rate seems to indicate that it is, having declined from 10% to 7.6% since October of 2009. While most economists take this statistic to be a credible measure of broad economic conditions, an alternate unemployment measure shows a starkly different picture.

The employment-to-population ratio measures the number of people who have jobs relative to the number of people of eligible working age as its base. This metric, as well as the unemployment rate, are both maintained by the Bureau of Labor Statistics. The key difference between the two is that the unemployment rate uses the much more restrictive labor forceas its base. The labor force excludes those who have given up looking for employment, yet who say they "want a job now"- this results in a rosier unemployment rate figure. (Source: http://www.bls.gov/cps/cpsaat35.htm).

The chart below compares the unemployment rate to unemployment measured by the employment-to-population ratio with data from 1948. Both unemployment metrics appear to generally move in tandem together during each job boom and bust cycle. The two metrics have been undeniably consistent with each other with respect to their movements over much of US history.


However, this does not hold true for the most recent timeframe. After the 2008 crash, the unemployment rate rose, peaked out on October of 2009 and has been on a steady decline ever since. Unemployment measured by the employment-to-population ratio similarly rose with the unemployment rate after the crash, but has remained flat during the supposed recovery instead of declining (see plot below).

Why is this happening? This can be explained by a stagnant or contracting labor force relative to the country's growing working population. The labor force, central to the unemployment rate's definition, excludes individuals who have essentially given up looking for work. In 2007, the BLS reported that 4.7 million working eligible individuals were "not in the labor force but wanted a job now." This figure has risen each year since 2007 and hit 6.6 million in 2012, a trend that contrasts a job recovery notion. These figures help explain some of the recent discrepancy between the two employment metrics. 

Those who are considered unemployed by the alternate metric are effectively categorized by BLS as "not in labor force, do not want job now." When this category was adjusted for population growth, it experienced an unprecedented surge concomitant with the onset and aftermath of the Great Recession: a rate of increase about substantially worse compared to the early 2000s when the dot-com bubble burst and 9-11 occurred (see table below).



Timeframe
Average Annual Growth Rate in “not in labor force, do not want job now” normalized to 1994 population of working-age individuals
1994-2008
 0.4%
2000-2003
  0.8%
2008-2012
  1.3%
While it is difficult to figure out exactly why this has happened, it’s easy to be skeptical and wonder how many do want a job and are unwilling to admit to it, or are subject to flawed survey procedures. In fact, BLS adds a footnote to some of its “not in the labor force” tabulations admitting that some individuals are not even asked if they want a job (see below). 


With the labor force as a persistent point of debate between supporters and opponents of the unemployment rate, these charts suggest that the employment-to-population ratio could function as a more honest measure of jobs in the economy. For investors seeking to look into real job figures for additional data on the economic picture, this metric may prove to be very useful.