There is growing talk that volatility targeting and risk parity are the dangerous new “portfolio insurance” strategy of the decade. The view in the post-’87 crash period was that portfolio insurance sowed the seeds of market destruction by creating a market decline feedback loop. Portfolio insurance, as an option replication strategy, automatically increased risk exposure in up markets and cut exposure in down markets in order to form an option-like pay-off of returns. The feedback loop meant that a market sell-off would be exacerbated as equity prices declined. Selling would only lead to more selling as the insurance adjust kicked-in. This came to a head in the ’87 crash as portfolio insurance strategies generated wave upon wave of selling in a down market. Given the systematic behavior in an illiquid market, portfolio insurance sellers became a bigger portion of futures index trading. Whether cause or contributor, portfolio insurance was never the same after October 1987 and there is now a fear of other strategies or algorithms that may have feedback loops to further a market decline.
Risk parity and volatilities strategies have feedback loops that may exacerbate a market sell-off tied to changes in volatility. The idea is simple, albeit different from portfolio insurance. If there is an increase in volatility for strategies that have a volatility target, there will have to be a cut in positions. Similarly, if there is risk parity across a set of assets, an increase in equity volatility will lead to a selling of equity exposure relative to other markets. Hence, volatility increases will lead to a market sell-off that could further lead to volatility increases that will then contribute to further selling.
This is a good story that should be a concern, but it is still just a story. It is true but it is a matter of significance. It needs to be translated into numbers and market impact. The impact or feedback associated with the story is related to the size of selling relative to the size of the market. We can form a measure of size through a simple model.
Let’s assume that an investor wants to target a 60/40 stock/bond blend at 8% using mini-SPY contracts and Treasury (TY) note contracts. The current combination will generate volatility of 5.98% using volatility for 9% for equities and 5.25% for bonds and a correlation of .1. The portfolio volatility would be lower if the stock/bond correlation is negative.
We can calculate the number of futures necessary to replicate this 60/40 mix per $100 mm. The portfolio will have to levered by 164 equity and 147 bonds contracts per $100 mm to go from a 5.98% vol to an 8% vol target. If the volatility for stocks and bonds both increase by 1% point and correlation stays the same, there will have to be a selling of 72 equity and 64 bond contracts per $100 mm. Therefore, for this simple volatility targeting program, we can determine that there will be a change of 720 equity mini-contracts per billion dollars to hit the portfolio target. This would be .17% of daily volume given about 414,000 equity index contracts per day. You would need about $6 billion of equity exposure or about $10 billion in 60/40 volatility target programs to represent about 1% of daily volume. This tells us the sensitivity in contracts and dollars of exposure to a change in volatility. If volatility increases significantly, the selling pressure would be even greater.
So how much is in volatility targeted programs?
That is the critical question. If the answer is $100 billion, then an adjustment of 1% higher equity volatility will be 10% of daily volume if the adjustments are all made at the same time. Of course, this is from a very simple stylized example.
Is this volume from volatility adjustment strategies enough to create a feedback loop? I don’t know. But, it gives us a better idea of what can be be expected if we know the extent of trading. We do know that some hedge funds may have tens of billions tied to volatility adjustments.
Of course, we know that market liquidity is elusive. It will not be present when we need it. We can count on the discipline of models. We cannot count on volume on the other side of these trades.