000			01747nam a22002297a 4500
005			20241123174516.0
008			241123b |||||||| |||| 00| 0 eng d
020			_a9781032389349
082			_a332.6 _bSCH
100			_aScheuch, Christoph _918870
245			_aTidy finance With R
260			_bCRC Press _aBoca Raton _c2023
300			_axvii, 249 p.
365			_aGBP _b61.99
490			_aThe R Series
520			_aThis textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with R, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using the tidyverse family of R packages. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques. (https://www.routledge.com/Tidy-Finance-with-R/Scheuch-Voigt-Weiss/p/book/9781032389349?srsltid=AfmBOoroSNESA3pTcTkQmopX2BFJkmbSwPOmhY6fk3hW64HPaxhNf3C4)
650			_aFinance with R _918871
650			_aR (Programming language)--Finance _918872
700			_aVoigt, Stefan _96857
700			_aWeiss, Patrick _918873
942			_cBK _2ddc
999			_c7630 _d7630