智慧數據分析方法I

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 Smart Data Analytics (SDA) course presents tools and concepts for unstructured data with a strong focus on applications and implementations. It presents decision analytics in a way that is understandable for non-mathematicians and practitioners who are confronted with day to day number crunching statistical data analysis. All practical examples may be recalculated and modified: software and Quantlets are in www.quantlet.de. The SDA course endows the practitioner with ready to use practical tools for smart data analytics. The students get insight into the area of modern internet based Computational Statistics Methods. Practically relevant knowledge on methods, data forms and Gestalt will be trained. The use of GITHUB and network techniques will be taught. Direct computer oriented knowledge and possibilities of empirical research will be shown. We present hands on practical examples from finance, Crypto currencies and network analysis.

Good knowledge in programming on laptop and presentation skills in keynote or PPTX. Basic knowledge of Applied Multivariate Statistical Analysis, like the following reference: Härdle WK, Simar L (2019) Applied Multivariate Statistical Analysis, 5th ed., Springer Verlag, Heidelberg. (https://www.springer.com/gp/book/9783030260057#otherversion=9783030260064)

http://misg.stat.nctu.edu.tw/hslu/course/SmartDataAnalyticsI.htm

• Homework: 70% • Term Project: 30%

Franke J, Härdle WK, Hafner C (2019) Statistics of Financial Markets: An Introduction. 5th Ed. Springer Verlag, Heidelberg. (https://www.springer.com/gp/book/9783030137502) Härdle WK, Simar L (2019) Applied Multivariate Statistical Analysis, 5th ed., Springer Verlag, Heidelberg. (https://www.springer.com/gp/book/9783030260057#otherversion=9783030260064) Chen C YH, Härdle WK, Overbeck L (2017) Applied Quantitative Finance. 3rd extended ed., Springer Verlag, Heidelberg. (https://www.springer.com/gp/book/9783662544853) Härdle WK, Okhrin O, Okhrin Y (2017) Basics of Computational Statistics, Springer Verlag, Heidelberg. (https://link.springer.com/book/10.1007/978-3-319-55336-8) Hardle WK, Lu HHS, Shen X. (2018) (eds) Handbook of Big Data Analytics, Springer Verlag, Heidelberg. (https://www.springer.com/gp/book/9783319182834) All examples are presented in R or Python. The Quantlets are available here: www.quantlet.de The CRIX is here: thecrix.de The FRM links: https://firamis.de/frm/ hu.berlin/FRM

地點

A418.

時間

By appointment.

聯絡方式

By email.