This article was written by Bloomberg Market Specialist Sean Markowicz for Markets Magazine. It appeared first on the Bloomberg Terminal.

“It seems that now everyone wants to time factors,” Cliff Asness, founder of AQR Capital Markets, wrote on his website in April.

Factors are common characteristics that can explain risk and return in assets. Stocks in the same industry, for example, tend to move together.

Likewise, stocks of companies that pay a high dividend usually rise and fall as a group. Hence, dividend yield—like momentum and value—is considered a style factor.

Strategies that aim to buy factor exposure low and sell high likely owe their popularity to several developments. Smart-beta exchange-traded funds and other funds have made it easy to bet on a specific factor, such as low volatility or momentum. In addition, certain factors clearly outperform in given periods. The $1.3 billion iShares Edge MSCI USA Momentum Index Fund—an ETF that tracks stocks whose prices have been rising—returned 9 percent last year. By comparison, the S&P 500 gained only 1.4 percent. In other words, momentum beat the U.S. market by almost 8 percentage points in 2015.

Certain factors have patterns that reflect risk preferences during different stages of a business cycle. When the economy turns down, quality and low volatility are usually the best-performing style factors. When growth picks up, momentum and value strategies typically perform well. You can potentially tap such patterns to tilt your portfolio toward the factors that you expect will perform best.

To dig into the factor exposures of your holdings, you can use the factor models in the Bloomberg Portfolio & Risk Analytics system. The PORT optimizer then lets you analyze potential trades that you could make to adjust your exposures.

Let’s walk through an example using an ETF that tracks the MSCI World Index as a sample portfolio. (A bit of evidence of smart beta’s popularity: The global market fund, with $276 million in assets, is about one-fifth the size of its sister ETF that tracks momentum.)

In the PORT function, the table at the bottom of the screen lets you see the six factors that contribute the most to the performance of your portfolio. In the case of the MSCI World ETF, the biggest contributor was its U.S. market exposure in late May.

You can also view cumulative factor returns for a period you choose.

The returns of factors in the Bloomberg model track theoretical long-short market-neutral portfolios with unit exposure to a given factor and zero to all others. Through late May, momentum was the worst performer of the 10 style factors in Bloomberg’s global risk model this year, with a return of -2.2 percent. The best performer was dividend yield, which gained 1.6 percent.

PORT provides details about which industries are most exposed to various style factors. In the case of the ETF, the industry with highest profitability factor weighting as of the end of last year was information technology.

Let’s say you want to make a bet on profitability.

First, create a portfolio with $10 million in cash and then select the iShares MSCI World ETF.

The trade simulation featurefirst lets you set goals for your optimization.

Suppose you expect profitable stocks to outperform and momentum names to continue to underperform. Your optimization goals then would be to maximize exposure to the first factor and minimize exposure to the second. You’d set the first goal to maximize GL Profit—the global profit factor. The second you’d set to minimize GL Momentum.

Once you set the constituent stocks of the ETF benchmark as your universe you can specify constraints for your optimization. Finally you can set conditions such as a maximum weight for any given stock.

In a backtest run in May, the optimized portfolio would have generated a year-to-date return of 3.08 percent, vs. -0.07 percent for the benchmark. That equates to an outperformance of 3.14 percent when global markets were volatile. Most important, we can see that exposure to all style factors contributed 2.61 percent to that active return. Specifically, the profit factor weighting contributed 2.17 percent, while underweighting momentum generated 1.08 percent.

This backtest highlights the value that multifactor investing can add to a portfolio’s return. Factor strategies can improve traditional active portfolio management by helping you to isolate themes that persist across various market environments. Just as investors make tactical decisions to invest in certain countries or sectors, factor strategies can be used to express a market view. Such strategies can also offer a way to improve the consistency of returns, lower risk, and increase diversification.

The challenge, of course, is to correctly predict which factors will perform well.

Markowicz is a PORT advanced specialist in the analytics department at Bloomberg in London.

Bloomberg Terminal subscribers can learn more about how to usePORT <GO> by accessing the PORT HELP page which includes useful whitepapers.

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