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Actively Changing Landscape

Ben Lavine

BofA Merrill Lynch and S&P (SPIVA) have each recently reported the outperformance of active management versus market-cap-weighted indices so far this year. With record-low volatility and low stock correlations, some are proclaiming the return to favor of active management after years of suffering outflows to passively run index funds.

Our own analysis of the active mutual fund universe shows more of a mixed story. By focusing on the oldest share classes and screening out sector funds and volatility/beta-themed funds, we find the S&P 500 outperformed 68% of the 321 active large core funds with a YTD return of 14.32% through 9/30/2017 (Figure 1).

 

Figure 1: Distribution of YTD Returns (through 9/30/2017) for Active Large Core Funds

 

However, active large-cap growth and value funds have fared better this year against their style benchmarks. The S&P 500 Growth Index has only outperformed 41% of the 365 active large growth funds (Figure 2) while the S&P 500 Value Index has only outperformed 32% of the 301 active large value funds (Figure 3). This shift in fortunes has not gone unnoticed, as actively managed funds saw $2 billion in inflows during the week ending 10/11, the first inflows in 11 weeks.

 

Figure 2: Distribution of YTD Returns (Through 9/30/2017) for Active Large Growth Funds

 

Figure 3: Distribution of YTD Returns (through 9/30/2017) for Active Large Value Funds

 

 

Traditional active managers may be outperforming their cap-weighted indices this year (although arguably it’s been largely driven by a crowded bet on technology, especially in large value; see Figure 4), but the investment landscape for active management has been fundamentally transformed with the advent of smart-beta ETFs as well as new, competitive entrants from alternative asset managers hoping to expand their retail presence.

As a result, investors are closely scrutinizing the sources of relative performance of the active managers and better determining whether value is being delivered beyond what can be explained by common risk factors.

 

Figure 4: % Overweight in Technology Sector One Determinant of Active Fund Outperformance

 

Low Vol Not Always Conducive With Active

Last January, we published an ETF.com piece titled, “Deconstructing Active Management,” where we profiled the active risk, or tracking error, of several U.S.-focused multifactor ETFs. We posited at the time that multifactor ETFs capture much of the active risk found in traditional active management programs that are balanced between value and growth.

In the article, we published a table displaying the active risk, or tracking error, of the multifactor ETFs as of 12/31/2016, which we redisplay here (Figure 5).

 

Figure 5: Active Risk Profiles of U.S.-Focused Multifactor ETFs (as of 12/31/2016)

MultiFactor ETF Ticker Inception Date Net Assets Annual Report Net Expense Ratio (%)
Deutsche X-trackers Russell 1000 CmpsFtr DEUS 24/11/2015 32,634,091 0.25
FlexShares Mstar US Mkt Factors Tilt ETF TILT 16/09/2011 956,756,117 0.27
Global X Scientific Beta US ETF SCIU 12/05/2015 73,008,088 0.20
Goldman Sachs ActiveBeta US LgCp Eq ETF GSLC 17/09/2015 1,432,247,454 0.09
Hartford Multifactor US Equity ETF ROUS 25/02/2015 27,237,185 0.29
iShares Edge MSCI Multifactor USA LRGF 28/04/2015 314,709,474 0.20
JHancock Multifactor Large Cap ETF JHML 29/09/2015 298,575,634 0.35
JPMorgan Diversified Return US Eq ETF JPUS 29/09/2015 173,332,625 0.29
SPDR MSCI USA StrategicFactors ETF QUS 15/04/2015 13,083,167 0.15
    Total 3,321,583,835  

Source: Bloomberg PORT. All risk characteristics shown against the iShares Russell 1000 ETF (IWB) as a proxy for the Russell 1000 Index. Factors displayed in blue represent exposures that exceed that of the "Size" coefficient.

 

 

On Dec. 31, 2016, implied volatility priced into S&P options, or the VIX, was above 14%. As of Sept. 30, 2017, the VIX has dropped to a near record low of 9.5%.

Active managers may love the new low-risk environment with its low stock-level correlations, which may be conducive to stock picking; however, it also means that to achieve 2-3% active risk in this environment, one needs to take on more aggressive active positioning versus what was necessary to achieve similar levels of active risk at the beginning of the year.

In other words, active managers stick their neck out to outperform the benchmark, but today’s low-volatility environment means active managers must stick out their necks even further to achieve similar levels of outperformance.

The low-risk environment has spilled over into risk modeling forecasts. Risk model forecasting is primarily influenced by the risk environment of the last six to 12 months. Over the long run, risk tends to be easier to forecast than returns due to the persistency in risk trends.

However, risk-model forecasts miss the market during inflection points—they can understate risk during a period of rising risk, and vice versa, until the models have had enough time to recalibrate to the new risk regime.

Figure 6 displays the same U.S.-focused multifactor ETFs profiled in the January ETF.com article but with active risk forecasts as of Sept. 30, 2017.

 

Figure 6: Active Risk Profiles of U.S.-Focused Multifactor ETFs (as of 9/30/2017)

 

 

Understated Risk

Now readers will note the magnitude of the drop in active risk forecasts from beginning-of-year forecasts (some as much as half of the beginning of year forecast).

Admittedly, this should be a nervous time for quantitative-based approaches based on these lower risk estimates. We intuitively know that the risk model is likely understating active risk, particularly if we see a pickup in volatility.

Yet if the low risk environment persists (which it has for the better part of the year), then multifactor ETFs should be positioned to deliver two-thirds to one-half the excess return than what was forecasted at the beginning of the year. Presumably, the underlying expense ratios wouldn’t drop to reflect the lower levels of active risk.

The alternative is to crank the portfolio optimizer to ‘11,’ but this would entail taking on greater factor risk to achieve higher forecasted tracking error, which could end up burning investors should the risk regime materially spike to higher levels of volatility. It’s a conundrum, but a more prudent approach would be to just stay the course rather than cranking up factor risk to achieve higher levels of tracking error.

 

Competitive Threats Emerging For Active Mandates

Traditional active management for retail investing is also seeing a new competitive threat. It’s not coming from rules-driven exchange-traded funds (ETFs) but from the opposite side; namely, private equity managers.

Private equity managers such as Blackstone aim to increase their management fee income by going down-market to the $1-5 million household level, down from the $5-25 million-level alternative asset managers typically market to.

Whether these interval funds prove to be successful, particularly when they’re being launched at what is arguably the peak of the business and credit cycles, the willingness for private equity firms to enter the retail marketplace is yet another indication that the value proposition of traditional active managers will come under further scrutiny.

In many ways, private equity represents the pinnacle of conviction-driven, fundamental investing, where the “investors” presumably know so much about the companies they’re investing in they can effectively operate them as well as current company management.

Hedge funds are also having a better year, although the “quant” category is stumbling due to bond market and currency volatility. After having failed to meet expectations for the last several years, hedge fund investing may start to see a comeback alongside traditional active management.

Alternative Framework For Evaluation

In constructing an asset allocation, the investor can decide whether to invest in pure passive strategies that select and weight securities based on the market’s assignment of “value” (market capitalization for equities, debt issuance for fixed income) or whether to deviate from the market consensus and opt for alternative weighting schemes.

The latter can be implemented using rules-based smart-beta (factor) indices through ETFs or through the judgments of a professionally managed portfolio as embodied by traditional active management.

With the advent of ETFs, smart-beta factor investing has brought more transparency to investment programs that deviate from traditional market-cap-weighted indices, such as decomposing sources of active returns (is it factor-driven or skill-driven?) and costs (what are the incremental costs between a smart-beta portfolio versus a traditionally managed portfolio?). Investors can better determine where the value is being delivered and at what cost.

Having access to tools to better evaluate sources of value-add and the associated investment costs calls for an alternative framework when judging performance of the overall investment program.

Whether investing in traditional actively managed strategies or smart-beta indices, investors need to own more of the resulting asset allocation, primarily the residual performance stemming from the choice to invest away from market capitalization-weighted indices (e.g., the S&P 500 Index and the Bloomberg/Barclays Aggregate Bond Index).

 

Suggested Solutions

What we are proposing is, in effect, a new social contract between investors and professional fund managers. Rather than assigning credit or blame based on relative performance versus the S&P 500, investors should “own” that part of the relative performance that can be sourced to asset allocation decisions, or the initial decisions to deviate away from cap-weighted indices.

Why compensate or terminate managers based on the systematic aspects of the relative performance that lie outside managers’ control (e.g., small-caps systematically underperforming large-caps, value underperforming growth and vice versa)?

In addition, professional fund managers should be assessed against smart-beta counterparts on a fee-adjusted basis and over longer periods of time beyond the typical three-year time horizon.

Three years is not enough to judge the success or failure of active management since: 1) three years does not cover a full market cycle; 2) portfolio decisions can take longer time to bear fruit; and 3) short-term performance evaluation invariably leads to a short-term mindset on the part of the manager (e.g., the temptation to “trade” one’s way out of a period of underperformance).

And what would investors get in return for shouldering part of the residual return due to asset allocation and a willingness to extend the time horizon for evaluating active management? Lower fees.

Pricing on smart-beta indices will drive fee compression; however, active management can instill investor loyalty by incorporating time horizon of investments held in the fund as part of the fee equation. The longer the investment held, the lower the fee. Perhaps introduce a lower-fee share class based on meeting a minimum threshold of investments held in the strategy.

Patience is what is required for successful implementation of active management, but patience is in short supply in our industry. The transparency and cost-effective delivery of smart-beta ETFs can enable better benchmarking of active management as well as the appropriate assignment of relative performance rewards/shortfalls between the asset allocator and the active manager.

Active management can thrive if its business of professionally managing portfolios is more properly aligned with the investment needs of the firm’s clients, where both parties can enjoy longer time horizons to judge whether or not the relationship is working out.

Benjamin Lavine, CFA, CAIA, is chief investment officer of 3D Asset Management. At the time of this writing, 3D Asset Management did not hold any of the ETFs listed in the article. The above is the opinion of the author and should not be relied upon as investment advice or a forecast of the future. The projections or other information regarding the likelihood of various investment outcomes are hypothetical in nature, do not reflect actual investment results and are not guarantees of future results. It is not a recommendation, offer or solicitation to buy or sell any securities or implement any investment strategy. It is for informational purposes only. The above statistics, data, anecdotes and opinions of others are assumed to be true and accurate; however, 3D Asset Management does not warrant the accuracy of any of these. There is also no assurance that any of the above is all inclusive or complete. Past performance is no guarantee of future results. None of the services offered by 3D Asset Management are insured by the FDIC, and the reader is reminded that all investments contain risk. The opinions offered above are as of October 18, 2017, and are subject to change as influencing factors change. More detail regarding 3D Asset Management, its products, services, personnel, fees and investment methodologies are available in the firm’s Form ADV Part 2, which is available upon request by calling (860) 291-1998, option 2, or emailing sales@3dadvisor.com or visiting 3D’s website at www.3dadvisor.com.

 

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