Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/176471 
Autor:innen: 
Erscheinungsjahr: 
2017
Quellenangabe: 
[Journal:] Financial Innovation [ISSN:] 2199-4730 [Volume:] 3 [Issue:] 32 [Publisher:] Springer [Place:] Heidelberg [Year:] 2017 [Pages:] 1-14
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
A motivated finance-major student should master at least one programming language. This is especially true for students from quantitative finance, business analytics, those attending a Master of Science in Finance or other financial engineering programs. Among the preferred languages, R holds one of the first places. This paper explains seven critical factors for designing and teaching a programming course: strong motivation, a good textbook, hands-on learning environment, being data intensive, a challenging term project, multiple supporting R datasets, and an easy way to upload such R datasets.
Schlagwörter: 
Programming skills
Quantitative-finance
Financial engineering
R
Open-source finance
Data analytics
JEL: 
A2
I22
G00
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