Active management under the microscope (MUTF:AIVSX)



How actively managed is your mutual fund? And, more importantly, what is the real reward for all this activity?

These long-standing questions have taken center stage with the recent publication of research on the so-called “active share” metric. Simply put, active share is the percentage of a portfolio that deviates from a fund’s benchmark. It is obtained by comparing the weightings of the fund’s securities to those of a benchmark index. Prior to the mathematical quantification of active share, the extent and cost of active management had to be inferred from a fund’s performance.

Equity funds can be thought of as two portfolios in one package. The first, a “passive” component which holds the benchmark securities, much like an index fund, and the second, the “active” part which is made up of securities held in different weightings than those of the benchmark index, even outside of it. The passive segment provides beta, or market exposure, while the active element is the alpha driver that aims for outperformance.

Active share is presented as an indicator of the suitability or “compatibility” of various benchmark indices as well as a measure of the consistency of a fund’s investment strategy. Early studies seemed to indicate that funds with high active stock values ​​outperformed portfolios with low values, although later research cast doubt on this notion.

There are inherent problems in building the active part. First, you need to monitor the fund and benchmark portfolio in real time to assess consistency, a feat not easily accomplished by retail investors or their brokers. Additionally, a stock-by-stock analysis is required, a laborious procedure when the benchmark contains hundreds or thousands of issues.

Active stock readings can also unduly flag a fund. High active share readings can occur when funds use representative sampling rather than full replication to gain beta exposure. This is especially true for funds with risk control mandates.

Perhaps more importantly, most fund sponsors do not publish active stock readings. No matter how useful this information is, it is difficult to access.

On the other hand, the level and expenses of active management can be determined transparently through performance. Using nothing more than an r-squared (r2) correlation (the measure of how well the movement of a portfolio can be explained by the movement of a benchmark), the active bet size of a fund and its cost can easily be quantified.

Whether or not you prefer a portfolio- or performance-based measure of active management really depends on your willingness to include a “duck test” in your analysis. The premise of the test is simple: if a fund acts as if it is actively managed to some degree, it probably is. The active part is based on a strict anatomy; performance-based measures focus on the behavior of the fund.

Investors and their advisers must take into account the quality of the information conveyed by these measures. Does any of them sufficiently explain a portfolio manager’s results to facilitate asset allocation? And are these metrics somehow predictive of future outcomes?

A study published this year by Fidelity (“Active Share: A Misunderstood Measure in Manager Selection”) showed that excess returns seem to increase with high active share, but so does downside risk. In other words, divergence from a benchmark does not necessarily mean outperformance. Fidelity, too, claims that active share does not predict excess returns.

Fidelity research supports Vanguard’s 2012 findings (“The Search for Outperformance: Evaluating ‘Active Share'”). Vanguard found that funds with the highest active share levels tend to be more concentrated in mid- and small-cap stocks and, unsurprisingly, this higher active share correlates with higher fund costs.

Last year, a cover story by Barron (“Is Your Fund Manager Active Enough?”) assessed the active share of 25 major national mutual funds and found that the major funds are not very adventurous . Megafunds – the five largest portfolios – averaged an average active share of 60% (at first, the researchers proposed a breakpoint of 60% to distinguish portfolios with high active share from less active funds).

While active share can give us insight into how active a fund manager is and whether that activity is worth it, we can look at funds within a broader universe of active management and risk metrics to see if we can shed even more light. on the effects and implications of their investment strategies.

First, an introduction to the available metrics:

R-squared (r2): between 0 and 100, the r-squared coefficient represents the percentage of a fund’s movements “explained” by the movements of its benchmark index. More actively managed funds tend to have lower r-squared values. Higher values, say between 85 and 100, indicate performance models that are more in line with the benchmark.

Tracking Error: Tracking error measures, in the form of standard deviation, the difference between the performance of a fund and that of its benchmark index. The higher the tracking error, the greater the deviation from the index.

Sharpe Ratio: An overall measure of a portfolio’s risk-adjusted returns, the Sharpe Ratio indicates the return on investment earned for a fund’s volatility. A “good” reading is 1, which means return on investment: one unit of return earned for every unit of total risk. A ratio of 2 is considered “very good” and a value of 3 or more is “excellent”.

Information ratio: The information ratio measures the number of units of return earned for each unit of tracking error. The higher the ratio, the higher the return obtained through active management. Typically, a ratio of 0.5 is “good”, 0.75 is “very good” and 1 or better is “excellent”.

Active Weighting: The part of a fund’s portfolio, implied by its r-squared coefficient, that deviates from the benchmark. Developed by Ross Miller (“Measuring the True Cost of Active Management by Mutual Funds”), the

The measurement relies on performance rather than portfolio construction to determine the level of active management.

Alpha: Alpha measures the return on investment realized relative to the expected return of a fund. A negative alpha indicates that the fund earned too little for the risk taken, while a positive value indicates a fund that outperformed the reward for the risk taken.

Active Alpha: Using Miller’s methodology, alpha can be deconstructed to find how much, if any, has been earned from the active portion of the portfolio. Active alpha more directly reflects the manager’s skill at stock picking.

Active Expense: The “true cost” of active management determined by allocating the fund’s expenses between the active and passive components. Cost is implied through a fund’s published expense ratio, its r-squared, and the expense ratio for a competitive index fund.

If we were considering funds in this space to fill a large-cap allocation without a value or growth tilt, we would have to choose between AIVSX and ANCFX. Here, the active part does not help us at all. The two funds have the same 60% value, despite radically different r-squared coefficients and active weightings. ANCFX may have performed slightly better over three years, but the portfolio’s other characteristics tell us that the smaller fund could be a worse bet going forward. Although neither fund produced positive active alpha, the value of AIVSX is the least harmful. This, together with a lower active spend, makes AIVSX more attractive. AIVSX managers appear to be making larger active bets and closer to their profitability than ANCFX portfolio managers.

Obviously, there is a lot more granularity achieved by using a suite of portfolio metrics. Active share can indicate some degree of active management in a portfolio, but other metrics give better and more transparent detail.

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