LEADER 04795nam 2200673 450 001 996508570103316 005 20240223124013.0 010 $a3-031-14236-5 024 7 $a10.1007/978-3-031-14236-9 035 $a(CKB)5580000000496330 035 $a(DE-He213)978-3-031-14236-9 035 $a(MiAaPQ)EBC30766856 035 $a(Au-PeEL)EBL30766856 035 $a(PPN)267811209 035 $a(EXLCZ)995580000000496330 100 $a20231020d2022 uy 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEssentials of Excel VBA, Python, and R$hVolume I$iFinancial Statistics and Portfolio Analysis /$fJohn Lee and Cheng-Few Lee 205 $aSecond edition. 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$d©2022 215 $a1 online resource (XVI, 696 p. 1113 illus., 1005 illus. in color.) 311 $a3-031-14235-7 320 $aIncludes bibliographical references. 327 $aChapter 1. Introduction -- Chapter 2. Data Collection, Presentation, and Yahoo Finance -- Chapter 3. Histograms and the Rate of Returns of JPM and JNJ -- Chapter 4. Numerical Summary Measures on Stock Rates of Return and Market Rates of Return -- Chapter 5. Probability Concepts and their Analysis -- Chapter 6. Discrete Random Variables and Probability Distributions -- Chapter 7. The Normal and Lognormal Distributions -- Chapter 8. Sampling Distributions and Central Limit Theorem -- Chapter 9. Other Continuous Distributions -- Chapter 10. Estimation -- Chapter 11. Hypothesis Testing -- Chapter 12. Analysis of Variance and Chi-Square Tests -- Chapter 13. Simple Linear Regression and the Correlation Coefficient -- Chapter 14. Simple Linear Regression and Correlation: Analyses and Applications -- Chapter 15. Multiple Linear Regression -- Chapter 16. Residual and Regression Assumption Analysis -- Chapter 17. Nonparametric Statistics -- Chapter 18. Time Series: Analysis, Model, and Forecasting -- Chapter 19. Index Numbers and Stock Market Indexes -- Chapter 20. Sampling Surveys: Methods and Applications -- Chapter 21. Statistical Decision Theory -- Chapter 22. Sources of Risks and their Determination -- Chapter 23. Risk-Aversion, Capital Asset Allocation, and Markowitz Portfolio Selection Model -- Chapter 24. Capital Asset Pricing Model and Beta Forecasting -- Chapter 25. Single-Index Models for Portfolio Selection -- Chapter 26. Sharpe Performance Measure and Treynor Performance Measure Approach to Portfolio Analysis. 330 $aThis 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. 606 $aElectronic spreadsheets$xComputer programs 606 $aFinance$xData processing 606 $aFinance$xStatistical methods 606 $aPython (Computer program language) 606 $aFinances$2thub 606 $aEstadística matemàtica$2thub 606 $aProcessament de dades$2thub 606 $aPython (Llenguatge de programació)$2thub 606 $aR (Llenguatge de programació)$2thub 608 $aLlibres electrònics$2thub 615 0$aElectronic spreadsheets$xComputer programs. 615 0$aFinance$xData processing. 615 0$aFinance$xStatistical methods. 615 0$aPython (Computer program language) 615 7$aFinances 615 7$aEstadística matemàtica 615 7$aProcessament de dades 615 7$aPython (Llenguatge de programació) 615 7$aR (Llenguatge de programació) 676 $a005.54 700 $aLee$b John$0364392 702 $aLee$b Cheng F. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996508570103316 996 $aEssentials of Excel VBA, Python, and R$93091295 997 $aUNISA