Factor investing strategies for fast-moving markets

Our dynamic factor timing strategy starts by assessing the current economic regime to identify which factors are likely to have a long-term tailwind or a headwind based on the macroeconomic and market backdrop. Our model then examines the valuation and sentiment of all factors, which influence short-term price behavior, along with factor-specific indicators to create a comprehensive forward-looking outlook for each factor.

This outlook is translated into a portfolio of U.S. stocks, overweighting stocks which have higher exposure to factors which are in favor. The resulting portfolio adapts to changing market conditions and aims to outperform the market cap-weighed benchmark across a variety of market environments.

The iShares U.S. Equity Factor Rotation Active ETF (DYNF), for example, is an actively managed stock selection strategy that seeks to outperform the broad U.S. market by tactically allocating to six well-known factors:

• Value strategies target securities that are inexpensive relative to fundamentals.
• Momentum strategies invest in securities with improving prices or market sentiment.
• Quality strategies favor securities with stable and high-quality earnings.
• Minimum volatility strategies target securities with lower volatility.
• Size strategies favor smaller, more nimble companies over larger ones.
• Growth strategies target companies with future earnings growth potential.

DYNF dynamically selects stocks based on their exposure to characteristics — such as value or low volatility — that the model identifies as well-positioned to outperform in the near term. The current outlook has tilted the portfolio toward defensive value and low volatility exposures, while reducing allocations to growth and momentum.

DYNF will take negative views on factors when needed

While past performance is no indicator of future returns, the dynamic factor timing strategy has been able to deliver significant alpha¹ during volatile periods by adeptly navigating changing market conditions:

• 2021
  Robust economic growth driven by vaccination rollouts, easing of COVID-19 restrictions, and improved consumer spending and business activity. Continued fiscal stimulus and loose monetary policy from the Federal Reserve supported market growth. The strategy pivoted from an underweight to value during the pandemic to an overweight during the recovery.
• 2022
  Persistent inflation, driven by supply chain issues, energy prices, and labor shortages, hurt consumer spending and corporate margins. DYNF shifted to a more defensive posture, favoring low volatility and quality stocks. Central banks raised rates in response to inflationary pressures, increasing market volatility and putting pressure on stock prices.
• 2023
  The U.S. Federal Reserve moderated its rate hikes as inflation showed signs of cooling, stabilizing market sentiment and encouraging some risk-on behavior. The strategy was positioned long in mega caps — overweighting growth and quality — thus, benefiting from a narrow market rally led by the “magnificent seven”.
• 2024
  AI optimism fueled a market rally, extending the technology sector’s leadership. The strategy’s continued bullish outlook on growth, quality and mega caps boosted outperformance.

Where does DYNF fit into a broader equity allocation?

DYNF can serve as a core or complementary exposure within the portfolio, sitting alongside other actively managed strategies or other broad equity market ETFs. Many investors utilize DYNF as a diversifying source of alpha within their active equity manager allocation. While equity portfolio managers often have style tilts or biases (e.g., value or growth investors), they typically do not change their investment style depending on the prevailing macroeconomic conditions. As a result, the alpha stream produced by DYNF, which dynamically allocates to U.S. stocks based on their exposure to historically rewarded factors and our forward-looking outlook for those factors, is differentiated from other high performing managers.

On the other end of the spectrum, some investors use DYNF as a cost and capital efficient way to introduce active returns into a predominantly passively managed portfolio. While the strategy is actively managed by BlackRock Systematic, creating the potential for generating alpha, it is systematic, transparent, and risk controlled. The higher transparency associated with factor-based strategies and with ETFs may appeal to investors who are most familiar with passive strategies.

With equity markets facing potentially slowing economic growth and rising policy uncertainty, we believe a dynamic approach to investing has become increasingly important. In an environment where returns are highly concentrated and static exposures often lag during regime shifts, DYNF delivers a differentiated offering.

Powered by a model-driven, tactical framework, DYNF adapts in real time — positioning the fund to capture alpha as market conditions change. As economic dynamics continue to shift, an actively managed strategy like DYNF introduces valuable flexibility into portfolios. DYNF’s data-driven, risk-controlled process makes it a potentially compelling core holding for investors seeking to remain adaptive, diversified, and aligned with near-term performance drivers.