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I use a hybrid complex event processing system that is mostly custom built, as well as a large scale data ingestion framework that takes in around 2-3GB of price data and other relevant information every day. It took a really long time to get this part of my setup working because without a decent way to kick off a process that subscribes to this data easily, everything else is going to be a huge pain in the ass. I put on trades on a 2week-1 month time frame, and aggressively sell winners and use stop losses to get rid of shitty positions. I use GARCH, ARIMA models, and have recently been playing around with some more exotic ML techniques, but I've found that momentum trades work the most reliably. I'm working on a SaaS API to try and make some money off of my data collection systems, but that's still in the works. EDIT: I try to identify interesting individual options that are, according to my model "mispriced" given a few signals. I seek out multibagger options. Most recently, I purchased the $PLTR 11/27 $22 strike calls two days ago, and made a killing (was around a 6x gain). If you are methodical in your data collection processing, there's a lot of valuable information that can be obtained. It just requires lots of data munging (which, honestly, is so painful all things considered). But turning 1k into 10k is a wonderful experience, especially if you can reproduce it. I have taken the well known 30-40 advanced options strategies and created a dynamic programming algo to basically run through every single listed security and every reasonable combination of options that would yield these strategies, with some filtering to make it computationally tractable, and then computed what the collateral costs would be (for spread trades, for ex.). That creates a reasonable doable list, and then I run a straightforward backtest. From here, I either pursue a trade or not. I like the idea of fully automating this stuff but its just not there yet. In any case, systematizing a lot of the boring crap is a great way to more deeply understand the landscape. You're never going to compete with execution-based firms but you can definitely take a view based on underlying fundamentals/macro landscape and then tune a slightly longer based system appropriately. |
I've been hesitant to pull the trigger on any of the "professional quality" feeds given that I've been treating this sort of thing largely as a hobby, but the less pricy options seem highly variable in data quality, granularity and availability. I guess if you're trading on week/month timescale this may not be necessary, thus my musing.
Thanks for sharing, sorry if this is probing more deeply than you'd be willing to broach.