Richard Yasenchak, a senior vice president and client portfolio manager for INTECH, says his firm has long worked to provide smarter portfolios to a variety of institutional client types, including both defined contribution (DC) retirement plans and traditional defined benefit (DB) pensions. He explains that INTECH utilizes computer algorithms throughout the portfolio-building and maintenance effort to ensure decisions are made in a “scientific and disciplined way.”
The point of the approach is to optimize the processes that may seem less important than choosing a manager or setting the asset allocation—things like, exactly how often should one trade back to the target weight? And how does one watch for rising correlations in the portfolio when rebalancing?
The firm has been particularly interested in developing “smart beta” portfolios, Yasenchak says, which are indexed portfolios that take an alternative weighting approach designed to bring better returns than the market capitalization-weighted index. For example, a smart beta portfolio may be designed to track the Russell 1000 index, but could set underlying equity allocations by factors such as revenue and earnings, among other rules. Other popular smart beta strategies today include equal weighting, fundamental weighting and minimum variance, according to INTECH.
Put simply, smart beta assumes that portfolios built with better diversification and rebalancing rules can generate returns that exceed the capitalization-weighted index without expanded risk or excessive oversight, Yasenchak explains. It may be an often-used and imprecise label, he admits, but the principles underlying “smart beta” are important for investors to grapple with.
“When I talk about rebalancing and why it is so important to smart beta, remember that to really stay true to the risk and return exposure you’re seeking through smart beta, you have to regularly rebalance,” Yasenchak says. “What we’re arguing for at INTECH is that the rebalancing mechanism itself can be a big driver of portfolio returns. That’s what lies at the heart of our process.”
Yasenchak says the rebalancing programs implemented by INTECH seek to take advantage of the market’s cross-sectional volatility—or the largely random dispersion of individual stock prices and movements that exist within the market over a given short time period.
“Consider that over short periods of time—daily, weekly or even quarterly—stocks at the aggregate level are basically moving randomly,” Yasenchak says. “It seems like a strange concept, but what makes one stock go up after a positive earnings report, yet another one go down after similar positive readings? It’s random to a large extent, at least over the short time frame we’re talking about.”
Yasenchak likens this short-term randomness to market “vibrations.” Because these vibrations are constant, he says it makes sense to build a portfolio that tries to account for the vibrations in deciding when to execute a rebalance.
“In essence we are trying to buy low and sell high as we pursue our target weights over time, and we’re doing our best to capture as much of the random upside as possible,” he says. “The other important piece is to ensure you have effective risk controls on this portfolio, that will attempt to ramp down on volatility in the case of exogenous events in which the market itself gets severely punished.”
Yasenchak says there is an ongoing focus in INTECH client meetings on how to manage overall risk. Clients for the most part are not totally adverse to risk, he explains. Instead, their focus is on reducing excess risk—they want to better match their portfolio exposures to their unique growth needs, and many are willing to accept lesser total returns for a greater likelihood of meeting specific targets.
This is another sense in which tracking cross-sectional volatility is a compelling opportunity in portfolio management, Yasenchak says, because it offers a way to track the amount of volatility and vibration in the markets. As cross-section volatility increases over time, the portfolio can incrementally adjust to the increasing risk in the market—and as volatility is dampened, the portfolio can get more aggressive. The important aspect of using cross-sectional volatility to guide risk exposure is that it does not depend on earnings forecasts or attempts to time the market with a fully risk on/risk off approach.
“It makes sense that when you see elements like cross-sectional volatility, and a few others, increasing across the entire marketplace, you want to adjust the portfolio to look more risk averse—and this can happen incrementally,” Yasenchak explains. “And importantly it’s not based on return forecasts—it’s purely based on risk levels in the marketplace, which we believe are easier to track and estimate.”
He hopes this approach to tracking and managing volatility will take a greater hold in the defined contribution plan world, perhaps as a part of target-date funds or within managed accounts.
“As the investors are nearing retirement, the worst thing that can happen to this group is to take a withdrawal of money after the markets get hammered on the downside,” Yasenchak says. “For years in individuals’ equity portfolios we’ve only been looking at equity classes—whether it’s U.S. stocks or international or emerging markets. Within those asset classes there has not been as much of a focus on the granular level of managing the overall risk. We believe the overall experience of the investor is going to be better when more of an effort is made to manage overall portfolio volatility.”