Edit: I guess the better question than the below might be, what is the equation for quantifying the 3 factors of Return, Risk, and Time?


So, when looking at options for the same underlying in different experations, I'm looking for a way to compare the ROI to the days to expiration.

For example how does a 20% ROI with 25 DTE compare to a 25% ROI with 30 DTE, as far as risk to reward?

Would comparing the daily ROI accrual for each option in question be a good way to quantify it?

For example 15% total ROI over 25 days is superior to 20% over 40 days, due to the higher daily accrual.

Assuming other factors such as probability ect... are the same in said situation.




Is there a better way to go about it, or is it just a non factor that I am overthinking?


Thanks,

Return on investment is an important point. But it is only one point in a very complex system.

Higher ROI for a trade often means a higher probability to be stopped out with a loss. And selling options it can take several successful trades to earn back the money you lost in one trade (depending on your stop loss).

Thus, you have to consider ROI per day, probability to be stopped out, your stop loss. Further more, you can include your expectation of the price of the underlying for the time until expiration of your option. There might be support in the chart, and you want to chose your options in way that you are not stopped out above this support.

You can backtest your options. @ron99 has developped an excellent system to do so. I do not think that there is a simple equation for the relation between return, risk, and time.

In some commodity markets I include the fundamentals to chose the options. Example: In the cattle market there was a Cattle on Feed report short time ago. Since then we know the number of cattle that will be avalable for marketing in June. Thus, I chose the June options instead of the August options, as risk for unexpected development of the underlying is smaller.

I am not sure if this directly answers your question. But it should give you my view how to tackle the problem.

Best regards, Myrrdin

Thank you for your reply. Yes, the more I thought about it, the more factors have to be considered.

However, I came up with the following in Excel. With Delta being used as an indicator of percentage success rate, then IV and DTE should already be baked into that figure... I think?

It seems, with all other things being equal, the Long Term Return rate, factoring in the % of expected losses is the difference between ROI and Delta. Which with both being equal, the Long Term Return would equal zero.

The shorter the Daily Acrued Return, both positive and negative, the quicker the average will normalize to the Long Term Return figure, but eventually assuming no adjustments such as taking profits early ect... the long term figure is where the actual ROI will statistically end up being.

In the following example of current SPY options, the ROI is higher than the Delta. I would assume this is due to the way TOS prices expected credits from the Mid Point between Bid and Ask. Either that, or there is some other information baked in somewhere. Otherwise gaining an ROI in excess of your percentage of expected loses, would be arbitrage, which I'm fairly certain is not the case here.

I included the equation I'm using to calculate the Long Term Return.
Simply subtracting the (loss amount * % of loss occurances) from (profit amount * % of profit occurrences)




Any feedback is appreciated, as to if parts of the above reasoning are correct or flawed...


Thanks,



Edit: Doesn't matter, but noticed that DTE for Apr16 is 42 days not 50.