@article{1452157,
      recid = {1452157},
      author = {Lee, John C., and Lee, Cheng F.,},
      title = {Essentials of Excel VBA, Python, and R., Volume I,:  Financial statistics and portfolio analysis /},
      pages = {1 online resource (xvi, 696 pages) :},
      abstract = {This advanced textbook for business statistics teaches  statistical analyses and research methods utilizing  business case studies and financial data, with the  applications of Excel VBA, Python and R. Each chapter  engages the reader with sample data drawn from individual  stocks, stock indices, options, and futures. Now in its  second edition, it has been expanded into two volumes, each  of which is devoted to specific parts of the business  analytics curriculum. To reflect the current age of data  science and machine learning, the used applications have  been updated from Minitab and SAS to Python and R, so that  readers will be better prepared for the current industry.  This first volume is designed for advanced courses in  financial statistics, investment analysis and portfolio  management. It is also a comprehensive reference for active  statistical finance scholars and business analysts who are  looking to upgrade their toolkits. Readers can look to the  second volume for dedicated content on financial  derivatives, risk management, and machine learning.},
      url = {http://library.usi.edu/record/1452157},
      doi = {https://doi.org/10.1007/978-3-031-14236-9},
}