*Step 5: Simulation*

In general, our simulation for the CS Equity Dynamic Tail Hedge Index embodied the two traits we felt were desirable in a tail-hedging algo, delivering outsized returns during periods of market crisis, and efficiently reducing the effect of negative carry over stable market periods via the dynamic signals (Figure 6).

An important consideration is that tail-risk strategies that incorporate some element of market timing, regardless of whether it is actively determined by a PM or signal-based, face the very real risk that a hedge may not be in place when it is needed. One must therefore evaluate the benefit of reducing carry costs in times of stable markets versus the risk of potentially missing the event because the signals have been “switched off.”

The final step to the process of algo construction is therefore to conduct an additional test of efficacy above and beyond the basic simulation in order to determine 1) whether the inclusion of the proposed signals provide adequate cost reduction to compensate for the risk of the hedge being “deactivated” during the days leading up to a tail event; and 2) how the chosen algo stacks up against the nondynamic version.

*Step 6: Additional Tests of Efficacy *

The primary criteria we use to evaluate the efficacy of tail-risk algos is to compare the tail-to-carry ratio of each strategy with one another. The tail-to-carry ratio is computed by dividing the average performance during tail events by the negative annualized carry. The metric essentially conveys how many years of negative carry can be paid for by one single tail event. The higher the ratio, the more efficient the hedge.

In our first example, we test the efficacy of our signal overlay, by comparing our signal-based Dynamic Tail S&P Strategy index (DTSP) to its unconstrained parent strategy, the Tail Hedge S&P Index (TLSP), which is 100 percent invested at all times.

Figure 7 compares the performance of DTSP versus TLSP from 2008 to 2014. At first glance, one might conclude the unconstrained “always on” strategy is superior given that DTSP provided comparable returns to TLSP during the Lehman collapse and the emergence of the Greek sovereign crisis in 2008 and 2010, but as shown in Figure 8, because the CDS signal activated late into the tail strategy in summer 2011, DTSP underperformed. Note, however, that during periods of market stability, DTSP reduced the cost of carry on average by a factor of 4.5, producing a higher and therefore efficient tail-to-carry ratio.