Jeonghoe Lee

Several financial concepts including BASEL and some common technical indicators.

Lots of proofs and, by virtue of doing so many proofs, some proof techniques. Ordinary least squares regression, generalized least squares, weighted least squares, logistic, penalized. Diagnostic testing, back testing.

theorical knowledge and implemented codes about finance and machine learning

Linear Regression models (OLS, WLS, GLS, penalized regressions), diagnostic statistics, applications and limitations of linear regression models. Python and R coding to implement the regression models and do data visualization.

Penalized regressions, proofs for linear regressions, and presentation skills.

This course will cover concepts about several machine learning models (traditional learning and deep learning), some time-series and stochastic models(kind of superficial level), stock market, and credibility related fields.

I learned fundamentals of linear regressions and coding methods.

Topics Included Statistics Basics Machine Learning Deep Learning Technical and Fundamental Indicators Other Topics in Finance

If you haven't taken econometrics then you learn a lot

I learned about making models, choosing independent variables and all of the different diagnostic testing