Relative value (RV) investing has grown and evolved greatly over the past 20 years to become an extremely competitive endeavor. Yet, by pursuing a less common approach, we think it remains a compelling source of alpha.
In the mid-1990s, Long-Term Capital Management (LTCM) famously recruited Ph.D.s to create quantitative models that could exploit price inefficiencies in global fixed income markets (and produced some eye-popping returns until its demise via the Russian financial crisis). However, the subsequent flood of academics into Wall Street, hired by banks and hedge funds to mimic the LTCM model, quickly reduced the edge, or alpha, once available in relative value trades; technology, the proliferation of statisticians in high finance and automated trading have all served to further compress alpha. In short, there is not much low-hanging fruit today.
The most common approach to RV trading relies on the expectation that assets trading at levels dislocated from their historical relationship will mean-revert quickly – inefficiencies that are observable through robust time-series analyses and often captured by “big data.” However, we focus on a second approach: taking advantage of structural dislocations that are likely to persist and not converge to historical means. Rather, the edge is captured in terminal payout space and realized over time as the trades expire.
Identifying relative value opportunities
If two assets exhibit the same profile across all payout spaces, they should trade at roughly the same level. In other words, there should never be a significant valuation discrepancy between an asset and its replicating portfolio. We aim to find assets that contradict this thesis – we look for inefficiencies generated by buyers or sellers who act rationally but with an objective other than maximizing expected value. Often these participants are motivated by regulation or by limited access to the full scope of financial products. We like ideas that are not well hidden or feel like a secret: We are seldom as clever as we think we are, and if we did uncover value that the market overlooked, it would not stay so for long. We are much more assured in taking positions in well-known market imbalances and being thoughtful in implementation and position management.
In rare cases, we are able to find mispriced instruments that allow us to capture near-arbitrage opportunities by buying or selling the assets and hedging with a fairly valued near-replicating portfolio. More often, we are not presented with such closed-form RV opportunities. However, we take the same approach and look for structural forces that push asset prices out of fair value, and we try to harvest that deviation by pairing opportunities within or across asset classes with highly correlated terminal payouts.
One example that can illustrate our approach is the persistent risk premium of long-dated equity index options compared to long-dated interest rate options. Long-dated options on the S&P 500 typically trade at a considerable premium both to short-dated options and to fair value based on long-term realized volatility. This is because market participants with beta exposure to risk assets buy long-dated equity options for portfolio hedging and are often insensitive to the valuation. For example, implied volatility of three-year options has averaged 15% above realized volatili