Part VII: Non-Correlated Hedged Convexity Capture Bulldozes Through Market Chop

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Hedged Convexity Capture continues to plow through market turbulence.

Investors must embrace data and systematic quant techniques.

Traditional stock-picking cannot effectively compete with advanced quant approaches.

Most investors and traders resist change until they are sick and tired of being sick and tired.

Unfortunately, emotional rock-bottom usually correlates with financial rock-bottom.

In this series, we have examined Hedged Convexity Captures, a strategy my firm invented which seeks to capture the negative convexity associated with leveraged ETPs. The idea behind Hedged Convexity Capture, as I outline in my book, is to capture the potential returns from shorting leveraged inverse equity ETPs with lower drawdowns and far higher Sharpe ratios than by just shorting them outright. The strategy seeks to accomplish this by shorting leveraged inverse equity ETPs like SPXU (NYSEARCA:SPXU), and pairing that short with a short position in TMV (NYSEARCA:TMV), an inverse-leveraged long bond ETP.

Not only does shorting TMV often provide a hedge for the equity portion of the strategy, but TMV itself suffers from negative convexity, further increasing the effectiveness of the long bond hedge.

Hedged Convexity Capture is a perfect example of an actuarial approach to trading. We are making the same shrewd bet on convexity again and again, by focusing on a repeatable phenomenon (remember that concept from science?) called negative convexity. We are not making helter-skelter individual predictions every day like most investors or traders. And when the phenomenon observed is especially strong, the results of that phenomenon become proportionally more predictable. And the negative convexity associated with leveraged inverse ETPs is an especially strong phenomenon.

While would-be hedgers are attempting to lay off market risk by buying inverse leveraged ETPs, they are actually taking on negative convexity risk. And that decision is grossly inefficient, because the negative convexity risk turns out to be, on average (remember, on average!), a far larger risk than the market risk they were seeking to avoid. Therefore, we would be shrewd to take the other side of these trades by using Hedged Convexity Capture.

As before, we will use some simple rules, but this time, will focus on Non-Correlated Hedged Convexity Capture. We shall efficiently capture this negative convexity in a hedged manner with the following rules:

I. Short SPXU with 40% of the dollar value of the portfolio.

II. Short TMV with 60% of the dollar value of the portfolio.

III. Rebalance weekly to maintain the 40%/60% dollar value weighting between the two instruments.

Here is a graph of the YTD results, which have achieved a new high even in the face of a choppy broader market:


I could not be more pleased. A 19.9% YTD return for the strategy vs. a 0.2% YTD return for the SPY (NYSEARCA:SPY) ETF, a Sharpe of 4.28, and a Max Drawdown of 3.64%. And the MAR is off-the-charts excellent. The results are so good that one would almost think they suffered from hindsight bias, but we are seven articles into the series (you're welcome planet earth)!

However, even though the strategy tests well, I never rely on theory alone. The advanced non-public refinement of this strategy does not use shorting. I believe the public strategy's major risk, since it uses shorting, is a discontinuous drop in markets, which causes the SPXU leg of the trade to skyrocket far more than the TMV could drop.

As I often say, no strategy is even close to perfect. There are only strategies which are preferable to all other possible alternatives. We have created an advanced non-public version of the strategy for clients, which does not use shorting. I think the public version presented here has the ability to stimulate thinking on the part of investors by clearly illustrating that even seemingly simple strategies using powerful mathematical principles can dramatically outperform strategies presented in popular bestsellers, while using fewer instruments with less hassle to implement.

Investors are constantly bombarded with intuitive strategies. And intuitive strategies may be excellent marketing vehicles, but they are often far worse performers than non-intuitive strategies. Strategies which rely upon an understanding of pure mathematics have a higher probability of sustained outperformance, because most people are not wired to feel emotionally comfortable with mathematical strategies.

It is this emotional discomfort which not only hinders the popular adoptions of such strategies, but also creates the potential for sustained outperformance for those unique investors who do appreciate their logic.

Investors need to make a total change in their approach to markets which embraces data and systematic quantitative techniques. But most investors and traders resist change until they are sick and tired of being sick and tired. Unfortunately, such emotional rock-bottom usually correlates with financial rock-bottom. But as Benjamin Franklin reminds us, only a fool needs to learn from experience.

Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.