So-called smart beta investment factors and styles are still a proven engine of outperformance, but investors might want to look before they leap.

That was the assertion of smart beta guru Rob Arnott, CEO of Newport Beach, Calif. investment strategist Research Affiliates, in a Thursday morning web conference.

Arnott, one of the founders of smart beta investing, made headlines in recent weeks after publishing a whitepaper predicting a possible "smart beta crash," but on Thursday he said his words were misconstrued and that he meant was that not all methods of constructing smart beta products were created equal.

“Smart beta originally meant strategies that were testable, transparent, low-fee and low turnover that also severed the link between price and weight in a portfolio,” Arnott said. “Today the label has become attached to just about anything, and if the label means anything it means nothing.”

Many of new smart beta strategies look attractive when back-tested, argued Arnott, but it isn’t because the strategy enhances portfolio performance. Instead, asset managers are conflating rising valuations with performance. “When investors see strategies with wonderful three, five or 10-year performance, they should ask the question if this is now more expensive today than historic norms,” Arnott said.

Arnott also criticized widespread performance chasing on the part of academia, practitioners and asset owners.

“Performance chasing is the single biggest source of investor pain and losses in our industry,” Arnott said. “It’s become rampant with the rise in portfolio turnover in the past century.”

Arnott said that academic research into outperformance-generating factors has created a jumbled landscape of smart beta strategies, citing estimates that there are now more than 450 identified factors -- attributes like size, momentum, profitability, volatility and value -- that are being used to construct portfolios.

“Asset owners and managers are looking for investments with the best performance, but past is not prologue,” Arnott said. “If the factor has had a tailwind from rising valuation multiples, that tail wind can be mistaken for persistent alpha.”

Arnott said that academia and practitioners should divide alpha into two different varieties: situational alpha, which can be attributed to rising valuations, and structural alpha, the valuation-adjusted excess returns.

Looking at U.S. equities’ dramatic rise in the latter half of the 20th century, which generated an 8 percent average annualized return, Arnott said that half of the increase could be attributed to the relative rise of valuation levels, thus the real return on stocks was 4 percent, not eight.

Using the same method to compare various smart beta factors, Arnott found that two factors, momentum and illiquidity, produce significant long-term alpha; two more, value and size, produce moderate long-term returns; while low beta and quality factors produce insignificant results.

The smart beta crash, then, is a behavioral one, says Arnott: Investors are buying smart beta products expecting outperformance, when they could see underperformance in the future as valuations revert to the mean.

“If you buy a strategy expecting a 4 percent alpha is likely to be achieved in the future and you end up with negative 4 percent, that’s smart beta gone horribly wrong,” Arnott said. “If enough people pile into these strategies, that’s a smart beta crash.”

Investors should also compare strategies, said Arnott. When comparing equal weighting, fundamental indexing, risk-efficient strategies, low volatility, maximum diversification and quality strategies, Research Affliates found that all six are capable of producing alpha, but in five cases their relative valuations are expensive compared to history.

“Value and value-related smart beta are cheap right now compared to history,” Arnott said. “What a great time to consider committing some assets to value-related smart beta or deep value strategies.”