Over the last ten months, equity volatility has flared up several times, suggesting greater opportunities for active management.
Volatility often sets the stage for stock picking and sector rotation as prices disconnect from fundamentals and market leadership changes. Yet many managers have struggled in this more unpredictable environment, especially during the tumultuous first quarter of this year. While the success of active management should be assessed over the longer term, it’s worth exploring what the events of this period can teach us about the challenges of twenty-first century equity investing, and how different styles of active management can meet them.
In order to navigate this environment, we believe that active managers need to utilise both new analytical tools and
time-tested research methods.
Most notable among the new tools are those based on data science and risk analysis. Used in support of quantitative strategies, tools such as machine reading and natural language processing can help fund managers analyse previously unimaginable quantities of information that may help shed light on short- and medium-term market movements and the transient factors that drive them.
For example, in the first quarter of the year, Italian equities meaningfully underperformed many of their European counterparts. While Italy certainly faces some real structural challenges, including sub-par growth, a high debt-to-GDP ratio, and an ailing banking sector, we also see reasons for some cautious optimism. Our algorithms for machine-reading conference calls have seen rising sentiment from CEOs and CFOs regarding Italy, and our analysis of Internet search data reveals that Italian consumers are increasingly searching for big-ticket items. See the charts below. Taken together, these two analyses lead us to believe that, despite Italy’s problems, the market may be overstating the bear case.
CEO sentiment, Internet search activity and market performance in Italy
Sources: BlackRock, Bloomberg, Google. May 2016.
The use of new tools and new forms of analysis is not limited to quantitative managers. On the fundamental side, more robust risk models can help managers to reduce volatility in the short term, while staying focused on the long-term drivers of return. In both cases, they are a means of amplifying human intelligence, not replacing it.
As markets continue to adjust to an environment in which macroeconomic policy no longer lifts all boats, investors may have a difficult time generating the type of equity returns they need from beta exposures. With the return outlook for fixed income looking even more challenging than the outlook for equities, it will be increasingly critical for investors to maximise returns in the equity portion of their portfolios. We think that one of the ways to accomplish this is to take an active approach that is underpinned by innovative research.
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