Delta is an estimate of the amount of gain or loss with a 1-point change in underlying price. Standard deviation works into this mathematically as a normal distribution. A delta of 16 correlates to 1 standard deviation away, a delta of 32 correlates to 2 standard deviations away, and etc.
The best way to look at the risk of your portfolio is to analyze the SPY Beta Weighted Deltas. This summarizes the movement of a portfolio considering a $1 move in the overall market.
So for example, if we had a portfolio beta of -90, the means for every up-movement in the SPY, we would see a loss of $90 in our portfolio.
It’s best to have a balanced portfolio, and make sure that your beta isn’t ridiculously high or low. I like to keep my portfolio beta in the negatives, since I am bearish on the market. (Contrarian forever)
However, in the current atmosphere, it seems as though it would be beneficial to have a positive beta. That way you could benefit from these crazy upmoves and perhaps take your profits and run before the market completely collapses.
Now let’s take a look at theta.
Theta tells us how much of a daily decay we can see in an option. If a portfolio is short premium, then there should be positive theta. We should collect theta decay each day in this situation.
If we had a theta value of -0.05, that means the long option position can be expected to lose $5 per day in time value. Short theta has positive theta, so we would gain $5 per day in value.
We can see the overall portfolio theta just like we could see the overall beta portfolio. If we had an overall theta of 3, then the portfolio would collect $3 in time value.
The Greek metrics of Delta and Theta give us an idea of how price and time affect our portfolios. They are great tools to use to learn how make some $$$!
Disclaimer: These views are not investment advice, and should not be interpreted as such. These views are my own, and do not represent my employer. Trading has risk. Big risk. Make sure that you can balance your risk/reward, and trade small, and trade often.
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