The Great Debate: Active Fund Managers vs. Passive Fund Managers

We like to think that issues are so easily solved with simplistic, watered down answers. To use an old cliché, the truth of an argument usually lies somewhere in the middle. For instance, when I see my fellow advisors arguing for or against active and passive fund managers, their biases come out instead of rational debate on the topic. Their supporting arguments always miss a couple of key points that could potentially alter the results and therefore the conclusions drawn from them. Let’s take a look at some of the flaws in conventional wisdom centered around desired characteristics when selecting fund managers.

Old Isn’t Better

Although many might believe otherwise, as age and size increases in a fund and fund family, the level of risk can actually increase rather than decrease. Why’s that, you ask? Before I tell you, you need to understand that the risk I’m talking about is the perceived risk of not achieving investment goals or the risk of destroying capital.

Alright, now that you’ve got that, know that strength in numbers only works if we’re talking about the reduction of costs through gained efficiency. However, after a certain point (let’s call it the optimal asset level), the bloated asset levels from all that baggage that potentially outweighs the benefits from scale.

People tend to cling to familiarity and old, well-established mutual fund companies are the natural choice for this majority. Unfortunately, familiarity doesn’t help much with your chances of outperforming a benchmark. As a perfect reinforcement to my point, a 2002 study by Otten and Bams found that younger funds performed better than older funds and fund age was negatively related to fund performance.

eVestment Alliance performed a study using investment data obtained between 2003 and 2014. The study grouped funds into age groups consisting of young (less than 2 years), mid-age (between 2 to 5 years), and tenured (greater than 5 years) as well as by assets under management (AUM) consisting of small (less than $250 million), medium (between $250 million and $999 million), and large (greater than $1 billion). Let’s take a look at their results.

Performance of Young, Mid-Age, and Tenured Funds

Source: eVestment Alliance, LLC

 

 

 

 

 

 

 

 

 

 

 

 

 

Performance of Small, Medium, and Large Funds

 

 

 

 

 

 

 

 

 

 

 

 

Source: eVestment Alliance, LLC

 

Among the portfolios of funds grouped by age, the youngest funds had the highest cumulative return from January 2003 to December 2014, at 250.25%. The mid-age index came in second at 144.04%, followed by the tenured index at 137.24%. Among the indices organized by size, the small index had the highest cumulative return from January 2003 to December 2014, at 139.86%. The medium index came in second at 106.49% and the large index third at 96.30%. Of course, past performance is not indicative of future results.

What could potentially be driving this irrational behavior despite evidence to the contrary? In behavioral finance, there is a negative effect known as the familiarity bias and it acts as a subconscious gravitational pull towards familiar or well-known investments. If I may be so bold, I believe this phenomenon is the predominant acting force behind this counterproductive investor behavior. There’s other behavioral forces at force here, such as herding (aka comfort in crowds), but the most pronounced in my experience has been the familiarity bias.

A New Risk

Okay, so we’ve established that many people have a natural bias that pushes them to older funds. However, no one is talking about the significant new risks that arise from this strategy. One such risk is auto-flow and I, like many of you in this industry, have witnessed it firsthand.

For those that don’t know what it is, here’s a definition:

Auto-flow is when the quality of the money into an investment product declines while its volume increases. Depending on the asset class that needs to be invested, these funds are considered an auto include. If there’s ever a hiccup in the auto-flow, there’s bound to be cascading outflows. Quality of the fund could be decreasing due to one of two reasons:

  • Client servicing becomes more difficult with a rapid increase in volume or fund capacity becomes an issue.
  • There’s a disconnect between the reality and investor expectations.

The aforementioned volume increases can be attributed to, as you might expect, increased popularity and/or great performance in the last few years. Check out the charts below from Propinquity to see a visual representation of auto-flow in the wild.

 

Charts courtesy of Propinquity

Marketing is (Sometimes) Everything

A second type of risk is marketing. I won’t name names here, but a fund company’s marketing can be very convincing especially around hot strategies that have just recently blown up in size. Once this cycle begins, people throw money into the strategies without even really understanding what they are investing in, let alone the underlying drivers of performance and whether they are sustainable sources of alpha going forward. With expectations at a peak, one stumble by the fund causes an “awakening” amongst these uninformed late stage investors and they then begin to learn about the strategy.

Something as small as one quarter of underperformance can cause investors with flawless expectations to flee. At this point, panic takes hold and they frantically flip through a prospectus and find something they should have known all along and immediately redeem their investments. At that point, it’s a fully-formed feedback loop that is vicious, if not impossible, to halt.

Propinequity also provides a nice illustration of two real life examples, with the fund names removed for anonymity (shouldn’t be too hard to find with a little research):

 

Running Down a Profit

It’s common for managers to lag their peers in the first half the year, only to chase extra risk toward the end of the year to make up for their losses. This brings us to our third type of risk.

In a study by Kempf and Ruenzi in 2008, they disputed this strategy by examining the role of tournaments within mutual fund families and how that can drive increased levels of risk taking during the second half of the year. First of all, let’s be honest with ourselves; all funds and fund managers are not considered equal within their fund families so there may be rivalry within firms, which leads to tournament-like behavior. Again, this may be mitigated by going with a lesser known fund company but, you know, that line of thinking may be a little too rational for some individuals in this industry.

Herding Investors

We mentioned herding earlier, but let me elaborate a bit on this mentality and why it’s included as a risk factor. Most people find comfort in numbers, but from a risk standpoint I don’t see how. Not only does herding have the potential to ruin things for market participants, but they may also mess everything up for investors as well, which might detrimentally effect the management of a fund.

A study by Bär, Kempf, and Ruenzi in 2011 found that decisions made by a team rather than by an individual has a dampening effect on returns. They concluded that teams have a moderating influence on each other and consequently have less extreme investment styles, less concentrated portfolios, and therefore have less extreme performance outcomes. Although you could argue that you avoid extremes to the downside, I’d counter with this: why not just invest in an index fund?

In another study along the same lines, it was discovered that investors experience a deterioration in performance when switching from a single manager to a team approach, while finding an improvement in performance when switching from a team to a single manager. Older funds run by long-serving managers were also shown to underperform their counterparts.

The top decile portfolio of funds with the highest herding tendency underperformed the bottom decile portfolio of anti-herding funds by about 2.28% on an annualized basis, both before and after expenses. They also obtain similar results when we adjust the fund returns to account for their risk exposures: the underperformance of herding funds is 1.92% based on Carhart (1997) four-factor alphas. Their regression results show that the predictive ability of fund herding is distinct from the effect of past performance and other fund characteristics such as size, age, turnover, expense ratio, and net flows.

In Solomon, Soltes, and Sosyura (2014), they found that not only are investors selecting managers by chasing performance, but they are only doing so when it is trendy and fun to talk about:

Investors reward funds that hold stocks with high past returns, but only if these stocks recently received media coverage. We argue that media coverage of firms increases the salience of their stock returns and attracts investor attention. When faced with a long list of fund holdings, investors appear to respond only to those companies that were recently featured in the news. As a result, funds holding high- visibility winners attract greater capital flows than their counterparts holding less visible winners. Conversely, funds holding high-visibility losers experience a greater attrition of flows than their counterparts holding losers with similarly poor performance but no media coverage. In absolute terms, the effect on fund flows is larger for media-covered winners than for media-covered losers.

At least they are being picky with their performance chasing!

The Bigger Idea

This article isn’t meant to be an exhaustive list, but I think you get the point. Let’s recap.

  • Passive Investing Vehicles – When my objective is to be at or around the index or I want exposure to an entire basket of securities for beta.
  • Active Investing Vehicles – When I want to attempt to add value in the form of alpha.

In my research, I have found and partially demonstrated (via all that writing above) that you can at least tilt the odds of selecting a value-adding manager in your favor when you limit the scope of your analysis to a subset of the population and a specific set of criteria.

There are several ways to explain the outperformance achieved by funds that are newer and smaller. To survive, new asset managers must outperform their peer group to attract assets and build their businesses; thus, they work harder and take more significant positions in their high conviction ideas. Additionally, newer asset managers tend to be nimbler, making investment decisions faster by avoiding the more complicated and bureaucratic approval procedures inherent in many large competitor firms.

An Example

Let me illustrate this with a hypothetical, real-life example of events. Imagine you are a star manager for a fund that is two times the size of your closest competitor. Frequently, you try to differentiate and add value to your fund to justify your fees by employing unique investment opportunities. When you go to implement the idea, you discover that your fund would have to purchase the entire market’s supply of that security to gain a measly one percent.

You really wanted to add value to your fund, but you simply cannot due to capacity constraints. Over the course of a few years, you find dozens of no-brainer investment opportunities, but are met with the same capacity issues. You finally get fed up with these constraints and decide to start fresh with a new fund at a new firm (or by starting your own). That wish list of investment opportunities you were too big to take a piece of are now within reach and represent low hanging fruit you can invest in right out of the gate. Do you think you will outperform your old, gargantuan predecessor fund during the first couple of years?

This phenomenon is also evident in mutual funds. An analysis by Vantage Consulting Group on mutual fund data shows that small funds take roughly one percent more active risk.

Last Thoughts

The bottom line is, just as startups and venture capital can offer above market returns, the same can be extracted from investing in managers by simply reframing the way we evaluate them. New asset management firms, much like any other new business, are generally able to start off with the latest technology and best practices and are unburdened by legacy operational inefficiencies. Smaller and newer asset management firms can enjoy many of the same benefits that startups enjoy in other industries. By learning from past mistakes, managers can use their industry knowledge along with research and innovation to establish a firm using best practices.

If the goal is to outperform a benchmark, you must take career risk and no one likes being the unpopular person. If not, just consider buying low-cost index funds.

It’s often very easy to recommend an investment based on popularity, but if most investors could see the possible negative effects that these short-term decisions have on their long-term wealth, they might be less inclined to make a snap decision. Just as a credit card can be used now for a potential loss down the line, clients need to understand that this short-term happiness could negatively affect their portfolios for years to come. Most portfolio optimizers don’t account for regret minimization and a quality of life reduction later in life.

Do your clients make knee jerk investment decisions? Have you ever turned down a client’s request to shift focus to a less-than-exemplary fund? Email me at [email protected] with your thoughts.

Disclosures

Investing in mutual funds involves risk, including possible loss of principal. The opinions voiced in this material are for general information only and are not intended to provide specific advice or recommendations for any individual. All performance referenced is historical and is no guarantee of future results. Alpha is a measure of a fund’s performance compared to a benchmark. Beta is a measure of a fund’s volatility compared to the market as a whole.

 

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