Hi there 👋 , I am Weijie Chen.
I am a macroeconomic analyst/trader seeking for trading opportunities based on global macro framework, my favorite markets are currency and commodity.
I am also a fervent quantitative researcher, exploring in Bayesian time series and machine learning framework for short turn profit gain.
The training materials in my Github pages are completely written by myself, used to be new-hire training materials in my previous institute (I was both a macro analyst and quantitative instructor in a boutique hedge fund). We used to organize internal training sessions for interns and new-hires to ensure they are on the same page with us, usually these trainings are intensive (commonly held from 7pm-11pm in our conference room). Though never intended as a substitution of formal education from universities, some of my academic friends are using my training material in their university's lectures too.
Please note that all institutional proprietary information and data has been cleared from training materials. So please do not ask me my institute's proprietary models or data, which unfortunately cannot be disclosed due to Non-Disclosure Agreement I signed.
| Course | Description |
|---|---|
| Linear Algebra with Python | This series of trainings will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician, econometrician, quantitative analysts, data scientists and etc. to quickly refresh linear algebra with the assistance of Python computation and visualization. |
| Basic Statistics with Python | These notes aim to refresh the essential concepts of frequentist statistics, such as descriptive statistics, parameter estimations, hypothesis testing, ANOVA and etc. All codes are straightforward to understand. We were spending roughly three hours in total to cover all sections. |
| Econometrics with Python | This is a crash course for reviewing the most important concepts and techniques of econometrics. The theories are presented lightly without hustles of mathematical derivation and Python codes are mostly procedural and straightforward. |
| Time Series Analysis with Python | This is a compound training sessions of time series analysis, it covers basic concepts such as ARIMA, GARCH ans (S)VAR, also cover more advanced theory such as State Space Model. The training will also show the practicalities, e.g. algorithmic trading. The training will try to explain the mathematical/statistical mechanism behind each theory, rather than forcing you to memorize a bunch of black box operations. |
| Bayesian Statistics with Python | Bayesian statistics and econometrics are the last pillar of quantitative analysis, also the most complicated subject. The course will explore the algorithms of Markov chain Monte Carlo (MCMC), we will build up our own toy model from crude Python functions. In the meanwhile, we will cover the PyMC3, which is a library for probabilistic programming specializing in Bayesian statistics. |