Is this block for you?
Well, that’s a good question. FinBlobs will focus on two main topics. The first will be systematic trading, with a focus on algorithmic equity strategies. I plan to write about everything connected to it, such as position sizing, risk management, various strategy types, combining strategies, backtesting, and book reviews. I also plan to analyze market data from the last 25 years to inspire new insights and ideas. My goal is to share what I have learned, further digest it, get feedback, and hopefully add value for my readers.
Who am I?
Hey there, I’m Adrian, living in southern Germany, close to France. I wear a few different hats as a freelance data scientist, data engineer, and algorithmic trader, trying to learn something new every day. My journey started with a fascination for good decision-making, considering constraints and scarcity and applying operations research techniques. I soon realized that the real world is full of uncertainty, which has to be properly considered to make good decisions. I therefore started to get familiar with machine learning and was blown away by its possibilities and also its (Python) community.
I eventually landed my first job in the industry and discovered a dark side to the glamour that I had never considered before – data engineering. Poor data quality, massive amounts of unaligned data stored in data swamps, scalability problems, and many other challenges that data engineers must overcome. This is where I am currently stuck, but enough whining – overall, I enjoy it.
All in all, I’m just a regular guy trying to make my way in the world of data, one algorithm at a time.
How did I get into systematic trading?
The finance courses I took in university never really appealed to me because they were too academic and disconnected from the real world, at least for my taste. Later on, I got hooked on passive index investing and the ideas of the FIRE (Financial Independence, Retire Early) movement. I also became more and more interested in algorithmic trading and loosely teamed up with two friends of mine, meeting once a week to discuss which data sources to use, potential strategies to investigate, self-implemented indicators, and how a potent architecture for live trading could look like.
At first, still blown away by machine learning and its seemingly endless possibilities, I tried to predict equity market prices, which didn’t work as well as I had hoped. I soon shifted my focus to systematic equity strategies, especially trend-following and momentum strategies. I read, watched, and listened to everything related to trend-following strategies from people like Andreas Clenow, Alan Clement, or Nick Radge, to name a few. Especially the book “Stocks on the Move” by Andreas Clenow motivated me. I implemented my own backtesting engine and tested the strategy. This was the breakthrough for me. I began to develop my own trend-following strategy that focused on US-listed equities, but it took quite a while before I was fully convinced and finally started trading systematically.
Why the name FinBlobs?
I had to name the blog somehow, so I came up with FinBlobs. “fin” should indicate the financial focus of the blog, and “blobs” should refer to data science and technology. The term “blob” is commonly used to refer to binary large object files, which are used to store large amounts of unstructured data. I know this connection is not really straightforward, but I still like it. It also reminds me of a blob of ink, which relates to a blog, I guess. So here we go, FinBlobs.
What are the next steps?
I am currently collecting topics and prioritizing them. My plan is to write a new blog post every two weeks, but I will start by writing more frequently to be able to offer at least a handful of posts at the beginning. This will give me a good starting point to establish a regular posting schedule. I am also open to feedback and suggestions from my readers, as I want to provide content that is useful and relevant to the data science and finance communities.