A weekly Python tutorial for beginners in algorithmic trading, market data analysis and quant finance, with each issue building a small practical tool such as a Dash analytics app, a capture-ratio performance check or a straddle profit-and-loss chart. Readers get step-by-step code with explanations of why each measure matters.

A quant researcher's newsletter covering high-frequency trading engineering, cloud latency, and quant development, alongside announcements for paid lectures and the quantpylib library. Recent issues mix short announcements with a technical guide on clock synchronization for microbenchmarking.