**How Two Microsoft Hedges Reacted To Friday’s Drop**

Last month, when Microsoft hit a new high, I posted two ways for longs to hedge against greater-than-19% drops over the next several months (“Two Ways Of Locking In Microsoft Gains”). This was the first hedge, the optimal puts* to protect against a greater-than-19% drop in MSFT by January 17th:

As you can see at the bottom of the screen capture above, the cost of this protection, as a percentage of position value, was 2.26%.

Here is how that hedge reacted to MSFT’s drop on Friday:

**How That Hedge Cushioned MSFT’s Drop**

MSFT closed at $35.47 on June 10th. An investor who owned 1000 shares and opened the optimal put hedge above to hedge it against a >19% drop that day had $35,470 in MSFT and a net cost of $800 on the hedge (assuming, conservatively, that he bought the puts at the ask). $35,470 + $800 = $36,250.

MSFT closed at $31.40 on Friday, and those puts closed at $1.50. As of Friday’s close, the investor’s MSFT shares were worth $31,400 and his put options were worth $1,500. So: $31,400 + 1,500 = $32,900. $32,900 represents a 9.2% drop from $36,250.

So, although MSFT dropped about 11.5% from June 10th’s close to Friday’s close (July 19th), an investor who opened that optimal put hedge on June 10th was only down about 9.2% on his combined hedge + underlying stock position over the same time frame.

**More Protection Than Promised**

Recall that the optimal put hedge was designed to protect against a greater-than-19% decline. In this case, it limited the investor’s downside to only 9.2%.

**How Microsoft Longs Could Have Gotten Paid To Hedge**

This was the second hedge I posted on June 10th, the optimal collar** to protect 1000 shares of MSFT against a greater-than-19% drop between then and January 19th, while capping potential upside at 12% over the same time frame (a cap that MSFT shares didn’t hit).

As you can see at the bottom of the screen capture above, the net cost of this optimal collar negative, meaning you would have gotten paid ($230, or 0.06% of position value) to hedge in this case.

**How That Optimal Collar Reacted To MSFT’s Drop**

The screen capture below shows how the put leg of that collar reacted to MSFT’s drop as of Friday’s close.

And here is how the call leg of that collar reacted:

**How That Hedge Cushioned MSFT’s Drop**

MSFT closed at $35.47 on June 10th. An investor who owned 1000 shares and opened the optimal collar above to hedge it against a >19% drop that day had $35,470 in MSFT and a net income of $20 on the collar (assuming, conservatively, that he bought the puts at the ask and sold the calls at the bid). $35,470 - $20 = $35,450.

MSFT closed at $31.40 on Friday, the puts in that optimal collar closed at $1.13, and the calls on that optimal collar closed at $0.10. As of Friday’s close, the investor’s MSFT shares were worth $31,400 and his put options were worth $1,130, and if he wanted to close out the short call leg of his collar, it would cost him $10. So: ($31,400 + $1,130) - $20 = $33,520. $32,520 represents a 8.3% drop from $35,450.

So, although MSFT dropped about 11.5% from June 10th’s close to Friday’s close (July 19th), an investor who opened that collar on June 10th was only down about 8.3% on his combined hedge + underlying stock position over the same time frame.

**More Protection Than Promised**

Recall that the optimal collar hedge was designed to protect against a greater-than-19% decline. In this case, it limited the investor’s downside to only 8.3%.

**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 PhD 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**.*