One big trader has come up with an interesting way of playing Facebook in the run up to the social network’s earnings announcement.
The trader has sold 17,000 Facebook 100-strike puts expiring on April 29 for $1 each, to use round numbers. The move was one of the biggest options transactions on Monday, writes Alex Rosenberg for CNBC.
Strategy could lead to major profits
There are a few positive outcomes here. The trader took in $1.7 million for selling the puts, so if shares in the social network close above $100 at the end of the month the seller will keep that full amount. That would represent a share price 9% below the closing price on Monday.
If shares in Facebook close below $100 at the end of the month, the trader will have to buy the stock at that price even if it is trading far below that price. At $99 the trade will result in a loss.
However this is leads to another potential positive outcome. Should Facebook fall sharply after the earnings report on April 27 and then rebounds, the trader will essentially have one negative event placed in between two positive events. After being forced to buy the stock at a premium, the trader will receive a premium for selling the put and then ride the stock above the $100 level.
Facebook trade strategy is “shrewd”
As a result selling puts is sometimes known as being “paid to wait.” In other words if the trader knows that they will want to pay $100 per share for Facebook at the end of April, they can sell that put and monetize that willingness.
“It’s a very shrewd trade,” commented Dennis Davitt, an options strategist at Harvest Volatility Management, in a Monday “Trading Nation” segment. Davitt says that the options price implies volatility that is three times higher than the volatility displayed by the stock of late. This could mean that the option is overvalued and a good bet to be sold.
The other possible outcome is that Facebook falls sharply following the earnings report, leaving the trader seriously out of pocket. For each dollar that the share price drops below $99, the trader will effectively lose $1.7 million.
