Strategic Tilts: Managing Factor Exposure In Real-Time
In the last month, multiple articles have come out indicating that the use of factor models is on the rise. Financial Times, for instance, recently forecast that so-called smart, or strategic beta investments – otherwise known as factor investment strategies – are set to grow to USD1 trillion in assets. In the institutional space, Sweden’s USD38.5 billion AP-1 fund is expanding its use of factor exposure as a way to create more diversified and balanced portfolios.
Institutional and retail investors alike are recognizing the benefit of using factors to hedge and diversify market risk. At the same time, some are sounding warnings that factor-based index trading, such as through ETFs, should be approached with caution to prevent concentration of risk and overexposure. While many of these factors might have outperformed the overall market historically, they are still subject to negative returns and relative underperformance as well. One way to do this is to ensure that you’re managing your factor exposure in a hands-on, systematic fashion, adjusting to market conditions in real time.
But we’ll get to that. First, let’s look at what factors are, and what has made them a popular tool in portfolio management, and then we’ll get to how to make the best of what factor models have to offer.
What are factors?
Factors are market phenomena that have driven significant risk or return in a marker over a long period of time. They help explain how the returns of securities in a portfolio are related. MSCI, for instance, has identified volatility, yield, quality, momentum, value, size, growth and liquidity as some of the key factors driving return. Depending on the manager’s style, exposure to these factors will shift, as will the risk premia associated with the securities in the portfolio.
What’s behind the rise of factor investing today?
No longer solely in the realm of quant managers, factor models have been embraced by fundamental managers. Moreover, some managers are even switching their use of factors from a risk management strategy to a portfolio construction strategy. From quantitatively defining what’s moving the market, factor models have produced tools that can help investors and managers understand market sensitivity and better control the source of returns. They are then able to incorporate this knowledge into the investment process leading to the active management of portfolio factor exposure and even deeper granularity in the stock selection and allocation process.
You can argue one reason for this change can be attributed to the broader adoption of factor investing itself. In recent years, smart-beta funds have boomed as investors have looked to reduce costs associated with gaining tilts to market factors by shifting into more passive strategies. The attraction for portfolio managers and allocators, beyond cost, have been the more precise models and tools optimizing the trading ability around factors. The ability to adjust or target portfolio exposure to factors has become more accessible. For instance, MSCI has observed more managers using factors to gain an edge for their international portfolios, and has used its Barra models to pinpoint the precise difference between factor impacts in global, international and U.S.-only portfolios.
To be sure, construction of a factor index investment can be very complex. Eliminating co-linearity is key, with the proposed model needing to be able to withstand significant exposure to the target factor and minimizing tilts to others, all the while remaining robust, pervasive, intuitive and investable. The offering also needs to be liquid and tradable, putting further limits on the construction. These investable indices are thus typically unable to completely eliminate exposure to unintended factors. They are different than pure models which, while not investable, provide only exposure to the target factor and eliminate exposure to the others.
Despite these technical limitations, these factor vehicles are still very viable investments, as their growth has shown, and have put more pressure on active strategies to differentiate. With this, understanding the source of active returns is no longer a “nice to have” but has really become a necessity for today’s managers. And that leads us to using factors strategically.
Real-Time Exposure Measurement
Some portfolio managers may find exploring factor exposure an interesting academic exercise, but may be at a loss about how to make use of the data to really impact their day-to-day tasks. We believe there’s real potential to use factor indexes in real-time market analysis to help manage risk, provided that this is backed by real-time access to solid data.
This is why we recently partnered with MSCI—a leader in factor investing with more than 40 years of data to back up its models—to provide on a real-time basis exposure to MSCI’s factor coefficients of the Barra Global Total Market Equity Model for Long-Term Investors and the Barra US Total Market Equity Model for Medium-Term Investors through Eze OMS. This means users can analyze their portfolio factor exposures pre-trade, diversify to prevent investments from crossing undesirable exposure thresholds, and adjust their exposures as they trade throughout the day.
Access to this information means managers can run what-if scenarios on the impact of a given trade on portfolio factor exposure; be alerted when factor exposure breaches tolerance levels in pre-trade compliance checks; and to target a specific factor exposure level in a single security.
As the world of factor models and investing continues to expand, taking action on the information these models provide ensure managers can move beyond analysis to hands-on management of their portfolios using precise, time-tested factor techniques. We’re looking forward to being part of that revolution.
Curious to learn more? Click here for more information on Eze/MSCI Factor Analytics.
Rob McAllister is Associate Director in the Sales Engineering department. He covers the East Coast, supporting the sales process by designing workflow solutions and delivering proof-of-concept demonstrations to prospects and clients. During his tenure at Eze, he also worked in Client Service, managing implementations and support of several enterprise clients.