# [R-SIG-Finance] making sense of 100's of funds

paul sorenson sf at metrak.com
Sat Aug 18 13:30:14 CEST 2007

```Tobias,

Thanks for the answer and no problems about the delay (its nothing
compared with trying to move your "hard earned" from one fund manager to
another).

I am really just working my way through this stuff and not much is
"obvious to me".  I will have to go back and check how significant the
alphas are.

At the moment I am just plotting stuff, printing out tables and doing
lots of reading.  I am on a fairly steep learning curve with R, LaTeX,
Sweave as well the core subject matter.  At the end of the day, I want
to be able to select a portfolio of super funds based on some objective
measures.

cheers

Tobias Muhlhofer wrote:
> Paul,
>
> Sorry for the delay in my reply.
>
> Yes you are looking for funds that produce intercepts that are as
> strongly positive as possible when their fund returns are regressed on
> the returns to the benchmark. Remember to consider standard errors!
> Since we are looking at a risk-adjusted return measure, only a fund
> which has a *statistically significantly* positive intercept has a
> positive intercept. Sorry if this is obvious to you, but many people
> miss it.
>
> For choice of benchmark, the ASX SP200 strikes me as a very good
> starting point.
>
> In terms of calculating returns, CalculateReturns (which I have never
> used, but just looked at the manual) does not seem to take into account
> distributions, which is imprecise. The total one-period return at time t is:
>
> r_t = [Price_(t) + Dividends_(t) + CapGainsDist_(t) - Price_(t-1)] /
> Price_(t-1)
>
> Here Price_(t) is the price at time t, Dividends_(t) and
> CapGainsDist_(t) are respectively the dividends and capital gains
> distributions made by the fund between t-1 and t. The distributions may
> be substantial, so they will make a difference. If you use "adjusted
> closing" prices from Yahoo Finance, you are OK, as these are adjusted
> for exactly that (and splits).
>
> Toby
>
>
> paul sorenson wrote:
>> Toby,
>>
>> Thanks for the tips.  I am somewhat of a cynic also. When it is my own
>> retirement fund, academic meets real-life in a fairly personal way!  I
>> have heard figures that something like 98% (from memory) of Australian's
>> "don't understand superannuation".
>>
>> I am trying to get myself well into the 2%.  Writing R code leveraging
>> some of the great packages out there is just a method of learning which
>> I find works for me.  It can be slow going at times though.
>>
>> I have picked out 8 funds to crunch through and using the ASX SP200 as
>> the benchmark for exercising my code.  My "practice" data set is at
>> http://www.metrak.com/tmp/exitprices.csv and I retrieved the SP200 using
>> get.hist.quote("^AXJO", start="2002-01-01", quote="Close", retclass="zoo").
>>
>> I have used CalculateReturns from PerformanceAnalytics to create returns
>> as zoo objects so hopefully I will be able to calculate the alphas.  If
>> I understand your comment below, I am looking for a more positive
>> intercept on my choice of fund compared with the benchmark?
>>
>> cheers
>>
>> Tobias Muhlhofer wrote:
>>> Paul,
>>>
>>> Unless you are looking at index funds, you need to see whether your
>>> funds produce alpha. To do this, pick a set of benchmarks according to
>>> your fund's style and investment strategy, like Morningstar category
>>> index or something like that (or perhaps just the general stock market
>>> plus the two Fama-French factors), regress the fund's returns on the
>>> benchmark returns, and see whether you have a significantly positive
>>> intercept after fees. This is the best way of measuring systematic-risk
>>>
>>> Being a finance academic (and therefore a cynic), and judging from my
>>> own research, if benchmarked correctly, very few fund managers generate
>>> positively significant alphas, and so I personally buy index funds for
>>> whatever style I want to invest in, and there I choose the one with the
>>> lowest expense ratio.
>>>
>>> Best,
>>>     Toby
>>>
>>> _______________________________________________
>>> R-SIG-Finance at stat.math.ethz.ch mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-finance
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>>
>>

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