In a nutshell, I am working on handling risk of derivatives such as Options, Futures, FOP’s, etc with deep learning. Some risk model exists, pricing model exists, but the complexity of these models is mindblowing and I am wondering whether AI can do a similar job with less modeling complexity.
As for the article, when I started rebuilding the dataset today, I noticed that the 2265 days in the dataset imply an very ugly bias widely spread in financial modeling: Excluding the last financial crisis. Just including the 10 years bull market that started in 2010 really raises concerns of overly optimistic assumptions that may lead to poor performance during the next market downturn. Usually, I try to get at least 20 years of data (~5k days), depending on the IPO date of the included companies.
However, the remaining feature engineering is absolutely spot on b/c asset correlation is omnipresent, option/equity interrelation is very real, and reverse correlation to Bonds is as real as it gets. Technical/Fundamental analysis is bread and butter, and so is ARIMA.
However, my current thinking gravitates about applying transfer learning. The idea goes back to Jeremy’s idea to use transfer learning in NLP and that turned out to be a hit, just as it was it for CNN/images.
The core idea is to use the above feature engineering on the S&P index because that gives about 50 years* of reliable data to learn various patterns and while also having plenty of data for testing and validation. Once the model is good enough, just export, and apply it to a set of given stocks fit as to see how that goes. I guess the main idea is the same in the sense of putting the majority of engineering work in the master model to make life easier.
That said, for modeling derivates risk, predicting equity prices is about a quarter of the equation with the rest being linked to other factors such as volatility. Thus simplifying equity price prediction is on the very top of my list.
I post an update once I know how that works out.
M
[*] Most electronic stock data records begin with Jan/1970, although the S&P started back in 1957 and the Dow Jones in 1896.