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Protecting Against The Bursting Of A Bond Bubble
1/29/2013 1:43:00 PM
On Bloomberg Television Monday, GAMCO Investors portfolio manager Larry Haverty offered a stark warning for bond investors:
Haverty didn't predict precisely when this bubble would burst, but fortunately for ETF investors, it is possible to hedge some bond ETFs. In this post, we'll focus on the most heavily-traded bond exchange traded fund, the iShares Barclays 20 year+ Treasury Bond ETF ( TLT ). Note that, although this ETF invests in bonds backed by the full faith and credit of the United States government, those bonds are not without risk. One of the risks associated with Treasury Bonds is interest rate risk. As iShares explains :
Downside Protection For TLT Investors
For TLT investors considering adding downside protection, here are two ways to hedge this ETF against greater-than-15% drops from its current price over the next several months.
The first way uses optimal puts*; this way has a small cost, but allows uncapped upside potential. These were the optimal puts, as of Monday's close, for an investor looking to hedge 1,000 shares of TLT against a greater-than-15% drop between now and June 21:
As you can see in the screen capture above, the cost of those optimal puts, as a percentage of position, is quite low, 0.40%.
A TLT investor interested in hedging against the same, greater-than-15% decline over the same time frame, but also willing to cap his potential upside at 10% between now and June 21, could use the optimal collar below to hedge.
As you can see at the bottom of the screen capture above, the net cost of this optimal collar is negative - that means that the TLT investor would be getting paid to hedge in this case.
*Optimal puts are the ones that will give you the level of
protection you want at the lowest possible cost.
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.