Hedging The Most Actively-Traded ETFs
Fellow Slopers,
In this post we’ll look at the costs of hedging the most actively-traded ETFs, but first, a quick update on an old post. A couple of years ago on Slope (“A Nano Cap Bargain“), I mentioned I had purchased a few shares of nano cap mobile phone accessory maker, Wireless Xccessories Group (WIRX). Shares of WIRX were up significantly this week, after the company announced sizeable revenue gains. As I noted in my post a couple of years ago, it’s a thinly-traded OTC stock, with all the risks that implies, so caution is warranted. Now onto the most actively-traded ETFs.
Continuing Signs Of Market Complacency
In indications of continuing market complacency, four of the five most actively traded ETFs on Friday were quite inexpensive to hedge against significant declines over the next several months. The one exception was the iPath S&P 500 VIX Short Term Futures ETF (VXX), but given its historical performance (down 98.85% over the last five years, as of Friday’s close), that shouldn’t come as any surprise. In order of their trading volumes on Friday, these were the most active ETFs:
- SPDR S&P 500 (SPY)
- iShares MSCI Emerging Index Fund (EEM)
- iPath S&P 500 VIX Short Term Fund (VXX)
- iShares Russell 2000 Index Fund (IWM)
- iShares MSCI Japan Index Fund (EWJ)
Below, we’ll look at two ways to hedge the last of those ETFs, EWJ, and then we’ll look at the costs of hedging the other ETFs in a similar way.
Two Ways Of Hedging EWJ
Below are two ways for an EWJ long to hedge 1000 shares against a greater-than-20% drop between now and late September.
1) The first way uses optimal puts*; this way allows uncapped upside, but is more expensive. These were the optimal puts, as of Friday’s close, for an investor looking to hedge 1000 shares of EWJ against a greater-than-20% drop between now and September 20th:
As you can see at the bottom of the screen capture above, the cost of this protection, as a percentage of position value, was 1.04%.
2) An EWJ investor interested in hedging against the same, greater-than-20% decline between now and mid late September, but also willing to cap his potential upside at 20% over that time frame, could have used the optimal collar** below to hedge instead.
As you can see at the bottom of the screen capture above, the net cost of this collar, as a percentage of position value, 0.69%.
Note that, to be conservative, the cost of both hedges was calculated using the ask price for the optimal puts and the put leg of the optimal collar, and the bid price of the call leg of the optimal collar. In practice, an investor can often buy puts for some price less than the ask price (i.e., some price between the bid and ask) and sell calls for some price higher than the bid price (i.e., some price between the bid and the ask).
Hedging Costs For All Of the ETFs Mentioned Above
The table below shows the costs, as of Friday’s close, of hedging the ETFs mentioned above in a similar manner as EWJ above: first, with optimal puts against a >20% drop over the next several months; then (where possible), with optimal collars against the same percentage drop over the same time frame, while capping the potential upside at 20%. There were no optimal collars available for the first two ETFs as of Friday’s close, given these parameters.
| Name | Symbol | Optimal Put Hedging Cost | Optimal Collar Hedging Cost |
| SPDR S&P 500 | SPY | 0.44% | NA |
| iShares MSCI Emerging Market | EEM | 0.92% | NA |
| iPath S&P 500 VIX | VXX | 18.5% | 5.93% |
| iShares Russel 2000 | IWM | 1.39% | 1.26% |
| iShares MSCI Japan | EWJ | 1.04% | 0.69% |
*Optimal puts are the ones that will give you the level of protection you want at the lowest possible cost. Portfolio Armor uses an algorithm developed by a finance Ph.D to sort through and analyze all of the available puts for your stocks and ETFs, scanning for the optimal ones.
**Optimal collars are the ones that will give you the level of protection you want at the lowest net cost, while not limiting your potential upside by more than you specify. The algorithm to scan for optimal collars was developed in conjunction with a post-doctoral fellow in the financial engineering department at Princeton University. The screen captures above come from the Portfolio Armor iOS app.
