In a recent StockTwits post, New York City-based trader Alex Tarhini shared the graphic below, which suggests that the iShares Silver Trust ETF (SLV) is seasonally strong in February.
Last Two Years Suggests Caution Is Warranted
Time will tell whether this February ends up being another strong one for SLV, but investors in the ETF have had to weather 3 drops of approximately 30% within just the last two years:
For SLV investors holding the ETF and hoping for further upside this month, but also looking for some downside protection, in this post, we'll look at two ways to hedge it.
Two Ways To Hedge SLV
The first way uses optimal puts*; this way has a cost, but allows uncapped upside. These are the optimal puts, as of Friday's close, for an investor looking to hedge 1000 shares of SLV against a greater-than-20% drop between now and July 19th:
As you can see in the screen capture above, the cost of those optimal puts, as a percentage of position, is 1.18%. Note that, to be conservative, cost here was calculated using the ask price of the optimal puts; in practice an investor can often buy puts for a lower price (i.e., some price between the bid and the ask). By way of comparison, the current cost of hedging the SPDR Gold Shares ETF (GLD) against the same decline, over a somewhat longer time frame (until September 20th), is 0.35% of position value.
An SLV investor interested in hedging against the same, greater-than-20% decline between now and July 19th, but also willing to cap his potential upside at 20% over that time frame, could use the optimal collar** below to hedge instead.
As you can see at the bottom of the screen capture above, the net cost of this optimal collar is zero.
*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 latest build of the soon-to-come 2.0 version of the Portfolio Armor iOS app. Optimal collar capability will be available as an in-app subscription in the 2.0 version of the app.