A Software Engineer Plays Quant: Building a Market-Data Research Stack in Python
For most of my career I built the plumbing of finance from the engineering side — feed handlers, order books, low-latency messaging, the systems that carry trading decisions without ever making them. I knew the microstructure cold and the strategy not at all. That division of labour is normal and mostly correct: the quant researches the signal, the engineer builds the system that executes it at scale. I’m starting a series of side projects that deliberately cross that line. Not to become a quant — I have no illusions about competing with people who do this full-time with better data and better maths. The goal is narrower and more interesting to me: what does market-data analysis look like when a software engineer does it? What does the engineering discipline I’ve spent fourteen years accumulating buy you when you point it at financial time series in Python? This first post is about the part nobody writes about because it isn’t exciting: the research foundation. Get this wrong and everything built on top is sand. ...