As global macro investors look for opportunity, it’s tempting to seek active return by making big calls on major market inflection points. In the current climate, there seems no shortage of such opportunities, including interest rates, oil prices, trade tensions, and Italian politics. The concept is seductively simple– do in-depth research on the next important market driver, express your view through a big position in your instrument of choice, and collect a substantial return.
If concentrated macro investing were so easy, though, then hedge fund databases would be littered with managers who have displayed a consistent ability to win the “big trade.” The reality is much more complex – and risky. When concentrated bets go wrong, losses may be quite steep, perhaps fatal.
To many investors, the appeal of “the big trade” is that it reflects high conviction. But in concentrated macro investing, consistent profitability (or anything close) is very difficult to achieve. It’s exceedingly challenging to be on the right side of a series of major wagers that involve enormously complex macro circumstances – not only does your view have to be correct but also your timing and your method of implementation. As a painful reminder, consider the subsequent track records of traders who were once lionized for their foresight regarding the mortgage crisis.
We believe that there is a more prudent approach to macro investing. Rather than concentrating risk in a few large bets, we think it makes much more sense to simultaneously express views on many aspects of the macro environment. Creating a diverse portfolio of long/short positions implemented across a wide array of asset classes and markets expands the opportunity set, avoids unnecessary risk, and better reflects the messy reality that no “big trade” plays out in a vacuum. Quantitative methods make a broad macro investing approach possible, allowing the transmission of diverse information through a deliberately constructed multi-asset portfolio.
Quantitative multi-asset investing is high conviction, although some investors might not immediately recognize it as such. We believe that certain factors, including asset fundamentals and price behavior as well as macroeconomic indicators, predict future returns. High conviction calls for designing portfolios that transmit the strongest combination of these predictive signals while reducing uncompensated risks and transaction costs. In “Big Trade Hunting,” the narrow focus on one aspect of the investing climate or lumpy positioning may derive from a limited investment process or a myopic outlook rather than conviction.
To be clear, systematic multi-asset investing approaches can (and should) reflect views on rates, oil prices, trade, and geopolitics. They’ll be transmitted through the predictive factors in the underlying model. Their influence will be diversified with other positions, so that no particular “bet” dominates the portfolio’s risk budget – crucial in a long/short context.
We believe benefits of a quantitative macro investing approach extend beyond the ability to assess diverse predictive information and simultaneously evaluate potential risk and reward. Decades of behavioral research have shown that behavioral vulnerabilities infect our judgment in ways that are particularly relevant to macro investing. Examples would include confirmation bias, recency bias, and emotional factors (e.g., the affect heuristic). A dispassionate systematic process seeks to take advantage of the behavioral errors made by other investors, errors that are likely to be magnified when engaging in large and risky macro calls.
From our perspective, “big trade hunting” resembles high-stakes gambling – taking big risks in the hope of big payoffs, but unlikely to succeed over time. A less glamorous but more sustainable approach is to methodically and repeatedly seek to take advantage of other investors’ mistakes. In other words, we would rather be the house!
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This document has not been updated since it was published and may not reflect the current views of the author(s) or recent market activity. Historical economic and performance information is not indicative of future results.
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