Why Use Python?
Dany Cajas
Additional contact information
Dany Cajas: Orenji EIRL
Chapter Chapter 2 in Advanced Portfolio Optimization, 2025, pp 9-12 from Springer
Abstract:
Abstract The Python programming language has gained a lot of popularity in recent years, mainly in applications of data analysis, machine learning, deep learning, and quantitative finance. In finance industry, most banks, hedge funds, pension funds, insurance companies, fintechs, among others use Python to perform several tasks like data cleaning, feature engineering, derivative valuation, algorithmic trading, credit scoring, econometrics, and portfolio optimization. These companies noted the advantages of Python over proprietary software based on graphical interfaces or proprietary programming languages, which limit the ability of quantitative analysts to analyze large volumes of information and make it difficult to design customized models for real-world applications.
Date: 2025
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-84304-4_2
Ordering information: This item can be ordered from
http://www.springer.com/9783031843044
DOI: 10.1007/978-3-031-84304-4_2
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().