Using Gradient Decent to derive Stock Predictions from Option Prices [Possible Insider Trading Exposed?]
THESE PREDICTIONS ARE ONLY AS ACCURATE AS THE OPTIONS THAT EXIST
Lines go [95%, 65%, Average, 65%, 95%] in terms of confidence intervals. I.E. the stock has a 65% chance of remaining within two dark lines, and a 95% chance of remaining within the grey two lines.
I can not show you the code or the programs used to generate this data, I can only describe what was done to find this data. Using the option prices I was able to extract what the market believes the possible future prices of different stocks are.
TLDR; I have access (as a developer of the software) of an algorithm that tells you what options are prices based off of, and theres something you should take a look at.
Look at these graphs and tell me if you notice something odd...
The predictions for the google stock seem to take this large jump on `2024-06-21`. I have no idea what this is, perhaps some google exec thought they were slick by buying a bunch of options for after some product announcement. Anyways.
Based on this info, I'd be going in on some `2024-07-19` calls. You could go for some `2024-06-21` calls but the option prices seem to be weird for that date.
Anyways, hope you find this stuff interesting. Ask me to run this on another stock and I'll do it.
Look at the large volume of google calls:
