Hello,
I have a very big question mark about "selling bull credit spread" in option trading.
As my statistics shows, it seems to be a "breakeven game" or worse as in my simulation.
Notice: I am not 100% sure that I calculate everything correct?
I will show my exact simulation I did on the most 179 liquid stocks on Nasdaq and Nyse for the year 2015.
Let us assume weekly options with a lifespan of 6 trading days
This is now RAW statistics to get a mathematical model of probability!
1. I let the simulation buy if close > 0 which means anytime and then always exit the trade 6 trading days later.
2. Let us assume a strike price for the put option we SELL for credit 5% below the entry price.
STATISTICS:
Total: 3513 signals
3187 of those signals or 91% of the signals CLOSED ABOVE the strike price for the PUT we sell, - which means that we KEEP the premium. Our goal is to keep the premium as I understand.
Now let us take a trading example from this where the stock is trading at $100 and we sell and buy 1 contract in each leg:
95 strike for $0.23 (sell at bid)
94 strike for $0.18 (buy at ask)
$23 sell - $18 buy = credit 5$ (Max profit)
(95 - 94) * 100 = $100
$100 - $23(premium) = $77 (Max loss)
So if we now win 9 times out of 10 times(91% of the time), it should look like this:
Profits: 5$ + 5$ + 5$ + 5$ + 5$ + 5$ + 5$ + 5$ + 5$ = 45$
Loss: 77$
SUM: 45$ - 77$ = -32$
So my question is. We actually have a good winning rate here. As much as 91% but still we end up with -32$.
Now I wonder if I have calculated everything correct and if I have done that, I wonder how it even is possible to make a credit spread strategy that generates positive results. If that is possible, what is missing to improve the results etc?
Thank you!
I have a very big question mark about "selling bull credit spread" in option trading.
As my statistics shows, it seems to be a "breakeven game" or worse as in my simulation.
Notice: I am not 100% sure that I calculate everything correct?
I will show my exact simulation I did on the most 179 liquid stocks on Nasdaq and Nyse for the year 2015.
Let us assume weekly options with a lifespan of 6 trading days
This is now RAW statistics to get a mathematical model of probability!
1. I let the simulation buy if close > 0 which means anytime and then always exit the trade 6 trading days later.
2. Let us assume a strike price for the put option we SELL for credit 5% below the entry price.
STATISTICS:
Total: 3513 signals
3187 of those signals or 91% of the signals CLOSED ABOVE the strike price for the PUT we sell, - which means that we KEEP the premium. Our goal is to keep the premium as I understand.
Now let us take a trading example from this where the stock is trading at $100 and we sell and buy 1 contract in each leg:
95 strike for $0.23 (sell at bid)
94 strike for $0.18 (buy at ask)
$23 sell - $18 buy = credit 5$ (Max profit)
(95 - 94) * 100 = $100
$100 - $23(premium) = $77 (Max loss)
So if we now win 9 times out of 10 times(91% of the time), it should look like this:
Profits: 5$ + 5$ + 5$ + 5$ + 5$ + 5$ + 5$ + 5$ + 5$ = 45$
Loss: 77$
SUM: 45$ - 77$ = -32$
So my question is. We actually have a good winning rate here. As much as 91% but still we end up with -32$.
Now I wonder if I have calculated everything correct and if I have done that, I wonder how it even is possible to make a credit spread strategy that generates positive results. If that is possible, what is missing to improve the results etc?
Thank you!
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