Scientific seminar on financial economics (Spring 2012 – Spring 2015, Financial University and MGIMO)

Course description: the course is intended to prepare 2nd-year master students for writing their master theses. It briefly overviews some of the most influential and/or controversial papers in financial economics, econometrics and macroeconomy. Papers are replicated in R using original datasets. During class students are obliged to take 2 individual projects, make 4 peer-reviews and one literature survey. All homeworks, R models and codes, datasets, reports, peer-reviews, and discussions are stored in internal knowledge base. 

Prerequisites: course is taught to master students of the final year, final semester.  It is assumed that student had successfully completed classes on financial markets, corporate governance, statistics, econometrics, financial mathematics, portfolio theory. Knowledge of R language is preferable, but not necessary. 

Continue reading


Algotrading in Bloomberg, R, and beyond (Financial University, Spring-Fall 2014). 

Class description: introductory course on developing trading algorithms and algotrading industry as a whole. Class is held in financial lab with 9 Bloomberg terminals; students are learning to fast-prototype algorithms using R language and real data from markets. Focus is on practice, but good understanding of underlying theory is a must. Knowledge of Bloomberg platform and R language is an advantage.

Prerequisites: basics of financial markets, technical and fundamental analysis, financial mathematics, modern portfolio theory, statistics and probability theory.

Continue reading