Like most aspiring quants, I was also a victim of poorly curated information out there. I wish I can get back the time I spent studying cointegration, hurst exponent, regressing prices etc. This blog is my *small* attempt to improve the signal-to-noise ratio of content out there.
Trading stuff that amateurs traders seem to care about a lot, and which are mostly ignored or seen as trivial by practitioners -
— cephalopod (@macrocephalopod) May 26, 2022
1. Stationarity / unit root tests for time series
2. Cointegration
3. Volatility forecasting
4. Exit signals
5. Stop losses
...has all the qualities to potentially be a good trader. if only he reads some news about the Fed instead of just reading some fake maths.
...very pleasant as a lunch buddy. can perform some card magic tricks as well surprisingly.
...love him a lot but he should get a real job with real skills.
Little project: In the next few days, I'd like to link to/comment on a few posts (long-form, on the web) by @KrisAbdelmessih, @quantymacro and @markku_kurtti, and @0xfdf. For the simple reason that they are good, I am (re-)reading them and they should not be forgotten. I was…
— Giuseppe Paleologo (aka gappy) (@__paleologo) July 29, 2024
I read this, it's good, I guess my only comment would be that I would be careful about taking my opinions as facts because I know many successful PMs who do things completely differently to me and it clearly works for them 😅
— cephalopod (@macrocephalopod) March 14, 2024
i really liked your ridge regression thing you sent today 🙏
— Robot James 🤖🏖 (@therobotjames) April 4, 2024
This blog is not focused on backtesting random entry/exit rules, or Python snippets on how to fit complex ML models on price data. The blog focuses heavily on understanding the inner workings of quantitative methods, as well as some pitfalls that the author has fallen into. Yes, sometimes this does mean that we will go back to the basics (you probably need it). My biggest nightmare is going into a quant interview with ML in my CV and bomb a linear regression question.
I'm hiring a junior quant and out of 30 applicants only 4 have passed my first round interview. Despite having tier 1 math/stats degrees and prior roles, most are weeded out if you simply ask them basic questions about regression. I'm talking chapter 1 linear model stuff here. https://t.co/6yhAlbyAe6
— fdf (@0xfdf) May 7, 2024
the growing popularity of machine learning had a large negative impact on the average quality of applied finance projects in the MFE program I taught in -- we would warn teams extensively of the pitfalls but still 30% of them turned into exactly this https://t.co/r8CYH4yckv
— Benn Eifert 🥷🏴☠️ (@bennpeifert) March 30, 2022
It’s a strong opinion of mine that really intuitively understanding the properties of time series filters and really understanding the properties of univariate and multivariate OLS will pay off many times over.
— cephalopod (@macrocephalopod) December 5, 2023
