Active extension strategies are a natural next step for institutional investors seeking a risk-efficient method of capturing alpha while maintaining beta exposure.
As institutional investors seek new ways to capture excess returns, they are increasingly considering active extension strategies for their portfolios. These strategies, based on decades-old short-investing techniques, offer the potential for improving the magnitude and efficiency of the alpha that’s being generated.
What exactly is “active extension”? In brief, it’s a relative return strategy that combines a traditional long-only active portfolio with the ability to short selected stocks within an established structure. Proceeds from the short are reinvested into long positions within the portfolio.
“By adding opportunities to invest on the short side, you not only allocate more risk, but better risk.”
— Peter Stournaras
Senior Researcher and Portfolio Manager, Northern Trust Global Quantitative Management Group
The most common variations of these approaches are called 120/20 or 130/30 strategies. In the case of 130/30, an investor would hold up to $130 worth of long stocks while short-selling up to $30 worth of stocks.
This technique leaves the investor fully “equitized,” while introducing the opportunity to generate additional alpha through short positions. Every dollar invested short is matched with an additional amount invested long to remain fully invested. “The investor’s exposure to the equity market is constant,” says Peter Stournaras, senior researcher and portfolio manager for Northern Trust’s global quantitative management group. “By focusing on certain higher conviction long and short positions, the manager is seeking to amplify the portfolio’s alpha. A positive alpha would allow for improving active returns without added concentration risk. This neither adds to nor diminishes your market risk.”
How does this injection of additional short- and long-stock selection increase alpha? Within a long-only scenario, any negative views would only be acted upon to the extent of not owning a given stock. The most extreme position would be a zero weighting in a stock. If that stock were one of the largest in a capitalization-weighted index such as the S&P 500, then it would be possible for an underweighted position to have a meaningful impact on the portfolio’s returns.
For example, General Electric has a 3.0% weighting within the S&P 500 Index. An investor that held no shares in G.E. stock would underweight it by its full value. Almost 70% of the names in the S&P 500, however, have a weight of 0.15% or less. With these smaller stocks, it is simply not possible to materially affect the portfolio’s returns by underweighting those positions. But what if an investor were able to take a short position in one of the many smaller index names? Perhaps the quality of negative information available on this one stock — or the investor’s conviction about it — is on a par with the information that led to the investor’s best or most successful long position.
“In the quantitative investment process, the manager has information on all 500 stocks in the S&P 500,” Stournaras says. “In a long-only strategy, you might only be able to exploit information in the top 100 ranked stocks.”
He continues, “By adding opportunities to invest on the short side, you not only allocate more risk, but better risk. You are acting on the sweet spot, where there is the best potential for additional return.” According to Stournaras, the short candidates are names in which an investment manager would have the most conviction based on its models.
“The tails of quantitative processes — the highest and lowest rated stocks — are where models often prove most effective,” Stournaras says. “By going only fractionally short, a manager bets against otherwise underexploited worst-rated stocks but constrains the risks and costs inherent in shorting.” He explains, “The key to successfully implementing these strategies is to understand what the research is telling you and to ensure that your exposures are commensurate with this information. Take calculated risk where you have information, and neutralize it where you do not.”
From the perspective of risk budgeting, active extension can be highly efficient. As the “Modeling the Impact of Relaxing Long-only Constraints” chart (below) shows, with a skilled investment approach, an institutional investor can extract more excess returns for a modest amount of incremental risk. Executed properly, active extension strategies can produce a higher information ratio (defined as excess return generated against risk relative to a benchmark) for the overall portfolio. “This is a very attractive concept in a market in which returns are expected to be quite moderate and where investors are increasingly risk budget-conscious,” says Jeremy Baskin, who is head of Northern Trust’s active global quantitative management group.
“This is a very attractive concept in a market in which returns are expected to be quite moderate and where investors are increasingly risk budget-conscious.”
— Jeremy Baskin
Head, Northern Trust Global Quantitative Management Group
Another way to view the benefit of this risk efficiency is that an investor doesn’t have to sacrifice diversification in the quest for higher returns. “Without the ability to go short, an investor would normally have to pursue higher returns by increasing concentration in the portfolio or by taking active positions on industries or sectors,” Baskin adds.
“Instead, the active extension strategy remains broadly diversified and leverages only the investor’s alpha, not the beta,” Baskin says. “Utilizing this type of strategy allows an investment manager to play to its investment strengths without significantly adding risk.”
In long investing, there is unlimited potential for gain. In short investing, there is unlimited potential for loss. Success depends upon how one addresses these risks.
“It’s important to be careful and thorough in performing all your due diligence. Quantitative managers take a large number of relatively small bets, which limits risks associated with individual securities,” Stournaras explains. “For many years, quantitative managers operating within long-only constraints have studied their research and were frustrated at not being able to exploit negative forecasts more directly.
“With greater acceptance of active extension strategies, now they can,” he continues. “But it needs to be done in a risk-efficient manner with consideration to the impact of short investing. We’ve found that the quantitative approach, which is systematic, fact-based and unemotional, tends to fit well with shorting strategies institutional investors are considering.”
No investment technique is risk-free. It’s important to note a few particular risks and challenges in this area. First, there is an issue related to potential tax liability from shorting. Certain approaches to creating the short and additional long exposure can have tax implications, even for tax-exempt institutions.
Modeling exercises show that as the long-only constraint is relaxed, excess returns increase. In this simulation, for a portfolio benchmarked to the Russell 1000 Index, predicted tracking error has been held constant at 3% with an information correlation of 0.08 and cross-sectional volatility of 30%.
Shorting can involve additional costs, risks and liquidity issues that can grow in significance as smaller capitalization stocks are shorted. The borrowing costs of the short names would rise, while liquidity could diminish. The attribution of returns also becomes more complex when combining negative and positive positions, making it potentially more challenging to fully understand sources of risk and return.
Not all investing processes are conducive to a short strategy, even a limited one. However, for a quantitative manager, active extension strategies provide for a natural progression of its investment process, simply expanding the range of investable securities. The area of active extension equity strategies has gained significantly in popularity within the past few years. It clearly holds promise for institutional investors, particularly for those who are ready to accept incrementally higher risk in the expectation of achieving higher investment returns within a risk-efficient framework.
“Capture your area of strength while limiting risks that wouldnâ€™t be appropriately rewarded.”
— Lingjie Man
Ph.D., senior researcher and portfolio manager, Northern Trust Global Quantitative Management Group
His paper, “Quantile Regression Methods for Recursive Structural Equation Models,” was published in the Journal of Econometrics, October 2006.
Exploiting depth in negative and positive security selection
For institutional investors ready to explore the opportunities associated with active extension strategies, the key question is: “How far should one extend the process into shorting stocks?”
Take three theoretical strategies — a 110/10, a 130/30 and a 150/50 active extension. “For an investment manager who has decent skill at picking only the most extreme losing and winning stocks, but not much depth beyond that, the ideal leverage ratio might be 110/10,” says Lingjie Ma, senior researcher and portfolio manager for Northern Trust’s global quantitative management group. “That way, you should capture your area of strength while limiting risks that wouldn’t be appropriately rewarded.”
However, what if a manager consistently demonstrates great depth in both negative — and positive — security selection? The further it could be exploited, the better. Of these three options, that manager would profit the most from the 150/50 extension. The 130/30 extension would cover a middle ground between the two extremes. Other factors to consider? Higher borrowing costs might lead an investor to select a lower leverage ratio because the costs present a hurdle to attaining desired net returns. The concentration of the chosen benchmark also is a factor. A more highly concentrated index, such as the S&P 500, could present more opportunities to add value through shorting than an equally weighted benchmark.