Enrolment options

The evolution from analogue to digital technologies continues to dominate the attention of decision makers today. Many tools in industrial production processes have been automated or replaced by highly complex mechanisms with pre-programmed decision-making. The change to digital modes of operations increasingly determines the lives of individuals and does so in increasingly unexpected ways.

The students get insight into the area of modern internet based Computational Statistics Methods and Time Series Analysis in Python. Practically relevant knowledge on methods, data forms and Gestalt will be trained. The use of GITHUB and network techniques will be taught and transferred into www.quantlet.de and www.quantinar.com. Direct computer oriented knowledge and possibilities of empirical research will be shown. key = DedaSS2023

Literature 

Franke J, Härdle WK, Hafner C (2019) Statistics of Financial Markets: An Introduction. 5th Ed., Springer Verlag, Heidelberg. ebook ISBN: 978‑3‑030‑13751‑9 (print), ISBN 978‑3‑030‑13750‑2 (softcover) 

Härdle WK, Simar L (2019) Applied Multivariate Statistical Analysis. 5th ed., Springer Verlag, Heidelberg. ISBN 978‑3‑030‑26006‑ 4 (print) 

Chen C YH, Härdle WK, Overbeck L (2017) Applied Quantitative Finance. 3rd extended ed., Springer Verlag, Heidelberg. 

Härdle WK, Okhrin O, Okhrin Y (2017) Basics of Computational Statistics, Springer Verlag, Heidelberg.


Semester: SuTerm 2023
Self enrolment (Participant)
Self enrolment (Participant)