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the net asset value of a fund and one or more benchmark
indexes as a framework for analysis of an actively managed
fund’s performance.
Net Tracking Error As A Framework
For Fund Performance Evaluation
This section illustrates one way to organize your examination
and evaluation of transaction costs and a number of
other major cost and value-added elements that determine
fund performance. The example is an actively managed
mutual fund (to illustrate the breadth of the analytical possibilities),
but most of the hidden cost and value-added
elements apply to index and actively managed ETFs just as
well. After all, even if an index fund is passively managed,
“passive” should not mean “mindless.” Transaction costs
offset at least some of any value added by both active and
passive investment processes. Transaction costs associated
with index composition changes are a dead-weight drag on
the performance of any portfolio that replicates an index. In
most cases, the composition-change transaction costs are
embedded in the performance of the index, but that does not
mean we can’t estimate them.
In my youth, I was a great fan of the late Don Herbert’s
“Mr. Wizard” science TV show. While childhood memories
are sometimes inaccurate, I recall having heard from time
to time, as Mr. Wizard and his youthful apprentices donned
safety glasses, an admonition something like, “Don’t try
this at home.” While that may not have been the precise
warning Mr. Wizard used, it is probably an appropriate
warning for anyone who might try to assemble the data
described in this section from the fund databases available
today. While most of the information described here can be
developed from SEC filings, the data assembly and calculations
are beyond what most advisers, let alone individual
investors, have the resources to undertake. The purpose of
this discussion is to illustrate what should soon be possible
and to offer a preview of how better data on mutual funds
and ETFs that should become available over the next few
years can raise the level of analytical discourse and improve
the fund selection process. Improvements in data availability
should make this kind of fund analysis almost routine
within a few years.
As indicated at the beginning of the first article in this
series, most fund rating systems explicitly recognize the
limitations of past performance as a predictor of future
investment results—and then proceed to focus on just such
performance comparisons. The overwhelming focus of fund
service ratings is on comparisons of a fund’s historic performance
to peer group performance. One problem with past
performance is that it is a “noisy” measure, at best, of the
value added or subtracted by a fund’s investment process.
Effective fund evaluation will attempt to break down the
components of performance to separate the wheat (valueadded
elements and costs) from the chaff (noise).
I propose to use the net tracking error difference calculation
as an organizing framework to incorporate all the favorable
and unfavorable elements affecting fund performance.
The fund manager’s objective should be to achieve the best
possible performance for investors, not the smallest possible
tracking error relative to a flawed benchmark—or relative to
any benchmark, for that matter. The objective of the manager
of any fund—indexed or active—should be to maximize
positive tracking error relative to an appropriate benchmark,
subject to risk constraints that are appropriate for the fund. 3
Calculating tracking error relative to several benchmarks lets
us use the multiple comparisons to increase our understanding
of why a fund’s performance has been good or poor. A
large positive tracking error in fund performance is almost
certainly more desirable than a negative tracking error (or
than no tracking error at all), but any useful analysis is much
more complex than that statement suggests. 4
To make it most useful, net tracking error should be
viewed as a summary measure of the positive and negative
causal elements of value added—or of poor performance.
Calculating the individual elements of cost and performance
and displaying them as offsetting components of a net
tracking error calculation can provide useful insight into the
interaction of the determinants of performance. Some of
these calculations require methodology that goes far beyond
what fund services can offer today, but this kind of analysis
can enlighten investors in ways that make development and
application of this methodology inevitable as the available
data improves. Of course, there will always be random elements
that limit the value of even the best analysis. Noise
that is not subject to an unequivocal explanation can be a
sizable component of any fund evaluation. While noise limits
the usefulness of the tracking error framework, we are looking
for the causes of performance and are asking appropriate
questions. That is a substantial improvement over what is
being done by most fund evaluators today.
There is no reason to calculate tracking error only relative
to the template index of an index fund or only to a benchmark
for a market segment similar to the fund’s portfolio. Tracking
error for both indexed and actively managed funds measured
relative to several indexes can highlight important index and
fund characteristics. It can reveal elements of index transparency
costs, the quality of the selections in a fund based on
a quantitative security selection process or the astuteness
of the stock picks of a traditional active manager. Multiple
tracking error calculations can reveal that a poorly performing
benchmark is being used as an index fund template. Tracking
error measured relative to competitive funds, particularly
with the comparative or comprehensive tracking error divided
into operating costs, trading costs and other elements, can
highlight features that a skilled fund analyst or a determined
do-it-yourself investor can use to improve fund selection.
When the net tracking error is broken down into security
selection value added, operating costs, transaction costs and
other measures that incorporate and highlight cost elements
and the effect of any risks accepted and management decisions
made, the result is a rich tapestry that reveals important
characteristics of the fund and its investment process that an
adviser will want to understand. Harking back to my earlier
warning, this analysis is not something for the average do-ityourself
investor or even an adviser to undertake at the present
time. However, advisers need to prepare their thinking
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January/February 2010