About
The Stochastic Ledger is a quantitative research and trading blog. The purpose of this blog is academic - that is to say, unlike many blogs and media on trading, the aim is not to sell a trading strategy or enter the space of the YouTube guru. The main focus is on studying markets and associated statistical phenomena. I am a theoretical physicist by training, but I also day trade. I am fascinated in a first-principle, logical approach to understanding market behaviour (with as minimal assumptions as possible). The Stochastic Ledger is a field journal to document such interests, and to also share my own journey in the world of day trading.
Although the content is quant-heavy, my goal is to describe my understanding with clarity and accessibility for the average retail trader. You’ll find logically driven research notes spanning microstructure, price action, and statistically grounded technical analysis.
The content on this blog is for informational and educational purposes only. It does not constitute investment advice, stock recommendations, or a solicitation to buy or sell any securities. Trading stocks, options, and futures involves high risk, and you may lose your entire investment. The author is not a registered financial advisor. Always consult with a professional before making financial decisions.
About me
I am a theoretical physicist by training. And, yes, I remain active in scientific research. I am also interested in studying and modelling financial markets, and I am an active day trader (it is inside knowledge that many physicist's also participate in the markets in one way or another).
The purpose of this blog is, firstly, to serve as a document of my journey in day trading (think of it as retail trading from a physicist's perspective). Secondly, my goal is to describe my understanding of the microstructure theory of markets and, what I would describe as, a first-principle quantitative approach to trading. As an academic and scientist, emphasis is placed mainly on a research and scientific orientated approach to studying market behaviour. A key theme that will run throughout this blog (as I foresee it) is inference: extracting signal from noisy data with as minimal assumptions as possible, and with clearly testable hypotheses.