My Learning Process of Coding to Outperform the Stock Market

    If you have been following along with my progress, first off let me say: I am very grateful that you are interested in my learning process involved with trying to build this trading algorithm over this summer. By all means, this isn't the final progress report/blog post and there will be more to come. The reason I am saying this is that my progress will be significantly slowed due to me going back to college. My main focus will be shifted back to school work and pursuing a Bachelor's of Science degree in Economics and (hopefully...) an Undergraduate degree in Finance.     This doesn't mean that I am done or finished with this little project of mine. I will  make small progress on the algorithm whenever I have some downtime in my college life. But it won't be anything near the progress that I have made during the last 2 months. I will  shift focus to this project during school breaks (Spring break, Winter break, etc.) if those situations allow me. B...

    Interesting progress was made this week. I fixed my coding problem with the interactions between all the algorithm models that I discussed in the last update which allowed me to see the results of importing my strategy I created in TradingView's PineScript way back in Progress Update 3 . I read a lot more of my book, Conquering The Seven Faces of Risk  by Scott Juds  learning about strategies like differential signal processing between multiple assets to pick the "fastest horse".     Starting with what I did in QuantConnect this week. I fixed my code to make my algorithm execute versus running into Python runtime errors where I couldn't even see if my trading strategy was working or not. Despite talking about my usage of several models in my previous blog update, I decided to eliminate the complicated multi-model setup to just do everything in one model mostly inside the OnData() method. I did this because I was taking way too long trying to figure out ...

    I just got back from a weekend getaway yesterday so now I am back to work. During this getaway, I brought my laptop and book Conquering The Seven Faces of Risk  by Scott Juds  to get some work done while away from my desk. I did more reading than coding this weekend so I learned a lot more from reading this book than I did making progress on coding on QuantConnect. So let me share a few things.     To start off of what progress I made in my coding, I started to make less progress today as I run into some compatibility issues. These issues are mainly coding issues with me trying to figure out how all of my Python classes will communicate with each other. Let me explain.     According to QuantConnect, a good trading algorithm consists of 5 models (Python classes) which all handle different parts of the algorithm. The diagram below from QuantConnect shows how these 5 parts interact with each other to create a trading algorithm.    ...

    This week I got a lot done towards my ultimate goal of creating my SPY trading algorithm. Last week I just started using QuantConnect and made myself try and complete their "Boot Camp" that they had which is used to showcase what Python functions and development tools they offer. Yesterday I completed QuantConnect's Boot Camp which went over a variety of different strategies. Today I started to build the framework of my algorithm in QuantConnect's IDE (Integrated Development Environment) and continued reading Conquering The Seven Faces of Risk  by Scott M. Juds  which I started reading this week as well.     Now I'll be real, I most likely won't use most of the strategies that the Boot Camp taught me because they still stem from the "diversify & rebalance" views of Modern Portfolio Theory (MPT) which I basically discussed the flaws of it in the last blog update. Instead, I mainly saw the Boot Camp as a way to familiarize myself with QuantConn...