Selling Premiums On Stocks
- Thread starter tyrant
- Start date
Interesting discussion. I predict this going for a few more pages.
Data mining can be very tricky when it comes to selling naked premium. If i studied 10 thousand tickers out there i am sure i could find 10 that never experienced a fat tail during a market(index) fat tail event. Then i can go ahead and call these "my market" and think i am better off selling juice in my market vs the indices. Flip that and reverse for selling index premium. The mere fact that one market("my market" or the index market) saw no fat tail or the tail wasnt as fat in the past doesnt mean it will be so in the future. False sense of security? Anyone? I suppose i am in the minority yet again.
Data mining can be very tricky when it comes to selling naked premium. If i studied 10 thousand tickers out there i am sure i could find 10 that never experienced a fat tail during a market(index) fat tail event. Then i can go ahead and call these "my market" and think i am better off selling juice in my market vs the indices. Flip that and reverse for selling index premium. The mere fact that one market("my market" or the index market) saw no fat tail or the tail wasnt as fat in the past doesnt mean it will be so in the future. False sense of security? Anyone? I suppose i am in the minority yet again.
It doesn't matter what the actual volatility figure is in determining over or under value. 100% vol could be considered cheap if the realized volatility is 150%.
With indexes, implied volatilities are consistently higher than realized volatilities, therefore overvalued.
All the while IVs have been 10%, the realized vols have been 6 or 7%.
The rub in this circumstance comes if selling at 10% and then getting a realized volatility spike.
Quote from rallymode:
The mere fact that one market("my market" or the index market) saw no fat tail or the tail wasnt as fat in the past doesnt mean it will be so in the future. False sense of security? Anyone? I suppose i am in the minority yet again.
Agree,
A good case for limited risk strategies... flies, condors etc.
I know the number sound strange but it is correct. If the data set contains some extreme events, then kurtosis is very high.
Taking sub periods for exampleâ¦.
During the 1990s , kurtosis only 4.34 (relatively quite period)
During the 1980s , kurtosis skyrocketing to 100 (the crash data contribute a lot to it)
etc.
Two reasons. First, currency risk. Second, Iâm doing quite well trading the UK markets, so have no reason to look elsewhere. If it ainât broke Iâm not one to fix it.
Almost exclusively selling naked premium. I know the risks involved, but do believe that if you limit exposure such that a fairly hard hit can be taken, youâll make a good return.
Iâve never had an option exercised against me. I won't deny an element of luck there, but I wonât be short an American option with a delta more than 0.80, neither will I be short Calls over ex-div day.
Makes perfect sense to me.
That Kurtosis value is more like it - slightly fatter tails than a perfectly normal distribution. I wouldnât mind betting that if you looked at each component stock, the weighted average would be less than 3.31.
I agree entirely. But, if you are going to trade options you have to make some assumptions based on (amongst other things) historic data. Refusing to trade in case you get hit by a 6-sigma is rather like refusing to go into your house in case it gets hit by a thunderbolt, no ?
That sounds about right. Iâm just wondering how far back in time is relevant ? 10 years ? 20 years ? Subjective !
GBOS
Thanks for that data. Any chance you could post it up in Excel format ?
Thanks for that data. Any chance you could post it up in Excel format ?