Here’s Another $72 Billion of Investors' Money that Doesn’t Beat the Benchmark

14th Century Philosophy Helps Understand Why.

I Have A Question For You

Imagine you have to make a car journey in the shortest possible time.   There are two routes you can take, and they are almost identical in every way – distance, quality of road, volume of traffic, etc.  The *only* difference between them is that one route has two junctions with traffic lights, and the other has five junctions with traffic lights.  Which route do you choose?

If you selected the route with only two sets of traffic lights, you are instinctively familiar with the reason why active funds don’t reliably beat their benchmark in the long run.

This is really good stuff.  Read on.  Don’t skip this one!

Valentines Day, 2024

Today, I did something I haven’t done for about 30 years.  I had lunch in the ‘Black Swan’.  If you’re in the financial industry, you’ll probably agree this is a pretty cool name for a pub.  Although, it was named long before Taleb coined the phrase.

When I was a young engineer, we occasionally took a long lunch break, and headed to the ‘Mucky Duck’ as it was fondly known then.  But the pub name is not the pertinent item today.  The location is; Ockham.  

Many years ago I memorised Occam’s Razor (a.k.a. Ockham’s Razor) as “Entities shall not be needlessly multiplied.”  Just six words is a highly efficient way to recall a key philosophy if you are an engineer (or, it turns out, in finance). 

Occam’s Razor was named after William of Ockham, a Franciscan Monk and one of the most important English philosophers and theologians of the Middle Ages.  He was born in Ockham in 1285 and spent his early life there.

Occam’s Razor is phrased in many different forms, here’s how Wikipedia states it:

When presented with competing hypotheses about the same prediction, and both theories have equal explanatory power, one should prefer the hypothesis that requires the fewest assumptions.

The Razor’s wisdom can also quoted as a friendly, “Other things being equal, simpler explanations are generally better than more complex ones.

Here’s a couple of engineering examples:

  • If I can design a circuit board in two different ways to achieve the same functionality, in general I should prefer the one with less components.  
  • If I’m constructing a mechanical widget and there are two different designs to achieve the same result, in general I should prefer the design with less moving parts.

The answer to “Why?” is instinctive to us.  The more moving parts, the more components, (or the more traffic light junctions,) the higher the probability that something will go wrong, or that functionality will be impaired.  

My brass Helson Sharkdiver automatic watch may be a particularly robust and beautiful timekeeping instrument.  But it has many moving parts, and will ultimately break and need fixing.  Whereas, a sundial from William of Ockham’s day would still be operational today.  Only one moving part – the sun.

If I have a functional item with moving parts or components, it’s only a matter of time before something breaks.

Simple versus Complex in Forecasting

In a fascinating 2015 paper, Kesten C. Green, and J. Scott Armstrong looked at simple versus complex methods in forecasting.  They reviewed studies in 32 papers containing 97 comparisons.

Their findings are thus:

  • None of the papers provide a balance of evidence that complexity improves forecast accuracy.
  • Complexity increases forecast error by 27 percent on average in the 25 papers with quantitative comparisons.
  • The finding is consistent with prior research to identify valid forecasting methods: all 22 previously identified evidence-based forecasting procedures are simple.

Green and Armstrong say, “Nevertheless, complexity remains popular among researchers, forecasters, and clients. Some evidence suggests that the popularity of complexity may be due to incentives

(1) researchers are rewarded for publishing in highly ranked journals, which favor complexity; 

(2) forecasters can use complex methods to provide forecasts that support decision-makers’ plans; and 

(3) forecasters’ clients may be reassured by incomprehensibility (Such a fantastic phrase! RW.)"

They state plainly: 

Clients who prefer accuracy should accept forecasts only from simple evidence-based procedures.

This is *highly relevant* to the financial industry, because an investment portfolio is the practical implementation of a set of forecasts.

Using Occam's Razor to Understand the Active vs Passive Problem

Let’s use Ockham’s Razor to examine the philosophical difference between active and passive investment management.  

In shorthand I’ll define active management as “human managers making decisions about asset selection and timing of buy or sell transactions, based on forecasts, assumptions and opinions.”  

I’ll define passive management as “algorithmic ‘managers’ automatically implementing asset selection and timing of buy or sell transactions, based on a predetermined and immutable set of rules.”  (i.e. rules-based).  

Active management requires the investment team to make forecasts and predictions about multiple economic and other factors.  Basic probability theory says that the more forecasts and assumptions a portfolio strategy requires, the more chance there is of errors being introduced.   Statisticians might consider forecasts, assumptions and opinions as ‘degrees of freedom’.  

Because the future is unknowable (with apologies to the time machine of HG Wells, who lived only a short way from Ockham, in Woking), if a complex investment strategy relies on forecasts and assumptions, it’s only a matter of time before something breaks.  All those unknowable variables are the ‘moving parts’ of the portfolio ‘widget’.

This explains why fewer and fewer actively managed funds outperform their benchmark, as we extend the time period of observation.

Passively Managed Funds Have No Moving Parts To Go Wrong

In contrast, how many moving parts does passive management require?  In the purest definition of passive management – none.  No assumptions need be assumed.  No forecasts need be forecast.  There are zero degrees of freedom.  No moving parts.

Therefore, Occam’s Razor tells us that in general we should prefer passive over active management.

For a passively managed portfolio to succeed, to be relatively ‘good’, all that must be done is to find a good index to track (since index-tracking is the usual way that a set of rules is converted to investment implementation).

The great thing about index tracking is that even if an investible passive fund may be relatively new, the index being tracked might have decades of performance data.  Empirical data.  Evidence.

So Why Do People Still Use Active Funds Then?

Let’s rephrase the question asked by Green and Armstrong: given the huge body of evidence on the efficacy of passive investing, why are complex actively managed portfolios still so popular?  (See SPIVA.)

(1) active managers are well rewarded, so continue to offer investment products to the market;  
(2) active managers may seek to offer complex portfolio strategies to match investors’ own ideas or opinions (i.e. the latest fad); and
(3) investors may be reassured by incomprehensibility.

But I'd also propose an additional:

(4) investors, being consumers, are targeted by clever marketing, and are drawn to ‘brand’ as a substitute for qualitative analysis and comparison.

As an advisor, I see first-hand evidence of the above.  And to be honest, you can’t blame inexperienced investors from naturally gravitating towards big brand-name fund houses, discretionary fund managers or private banks (or at least, names they may have heard of before).

Moreover, financial advisors may find that the easiest path is to ‘play along’ with client assumptions and perceptions, instead of educating and guiding clients towards better investment outcomes.  This isn’t always the advisor’s fault.  Sometimes it’s near impossible to overcome a lifetime of indoctrination.

By the way, my guess is that the ‘best’ active funds are quasi-passive.  The management team has a clearly defined set of rules and criteria for asset selection, buys and sells.  Adherence to fixed rules reduces the number of moving parts.  Almost as though the fund manager is passively following a private in-house index.

How Well Do ‘Brand-Name’ Multi-Asset Portfolio Managers Perform?

Passive Index Portfolios (PIPS) are an easy two-dimensional approach to comparing multi-asset funds and other portfolios.  By plotting funds on a risk-return chart, and drawing the PIPS line (the locus of a portfolio of one equity index and one bond index), we can at-a-glance assess the relative performance of multi-asset funds, on a risk-adjusted basis (meaning, when we account for equivalence of volatility).

Here's a quick diagrammatic explanation of how a PIPS Benchmark works.  For more information read this.

I looked at a range of multi-asset funds from some of the most well-known and respected asset managers: 

Manager – Fund – ISIN – Size (US$ Million)

Allianz - Income and Growth  (LU1255915586) - $45,853m

BlackRock - Global Allocation   (LU0072462426) - $14,721m

Fidelity - Global Multi Asset Dynamic   (LU0261961675) - $148m

HSBC - Portfolios World Selection 5   (LU0931137300) - $347m

Janus Henderson – Balanced   (IE0004445015) - $7,365m

JP Morgan - Private Bank I Access Balanced   (LU0540042818) - $1,744m

Ninety One - Global Multi-Asset Sustainable Growth   (LU0947747993) - $1,705m

Schroder - ISF Multi Asset Growth and Income   (LU1195516338) - $355m

Templeton - Global Balance   (LU0052756011) - $490m

Total assets managed in these nine funds: USD $72.7 billion.

Here’s the risk-return chart of those funds plotted against a PIPS tracker (an investible portfolio of two index-tracking funds), over a ten-year period.  (Click to enlarge.)

Across these 9 funds, more than USD $72 billion of investors’ money performs no better than an investible index portfolio of E% x (iShares Core MSCI World) plus (1-E%) x (Vanguard Global Bond Index H-USD).

As an example of how to read the above chart, ‘PIPS-USD-Tracker-70E’ (a simple investible portfolio of 70% equity tracker and 30% bond tracker), has performed slightly better (higher returns for equivalent or lower volatility) than the famous Allianz Income and Growth Fund (USD $46 billion in size) over a ten-year period.

Here’s the historical performance charts of the two portfolios:

The performance and volatility of these two portfolios are near identical.  However, the annual fees of the Allianz fund are between 0.95% and 1.20% depending on share class.   Investors in this fund likely pay about $460 million in fees and charges collectively, every year (excluding any entry charges that are applied).

In contrast, you can invest in the 70% equity PIPS tracker for just 0.19% per annum.  And you don’t need to pay the salaries of a global marketing team and a huge staff of PhDs.

Occam’s Razor wins.  In the long run, most actively managed portfolios cannot be relied on to outperform a rules-based portfolio with zero degrees of freedom (zero moving parts).

I’ll finish with another way of phrasing Occam’s Razor:

"It’s vain to do with many what can be done with fewer."

Charts from FE Analytics, with thanks.  

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