語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
到查詢結果
[ subject:"R (Computer program language)- Statistical methods." ]
切換:
標籤
|
MARC模式
|
ISBD
Essentials of Excel VBA, Python, and...
~
Lee, John C.
FindBook
Google Book
Amazon
博客來
Essentials of Excel VBA, Python, and R.. Volume I, . Financial statistics and portfolio analysis
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Essentials of Excel VBA, Python, and R./ by John Lee, Cheng-Few Lee.
其他題名:
Financial statistics and portfolio analysis
作者:
Lee, John C.
其他作者:
Lee, Cheng F.
出版者:
Cham :Springer International Publishing : : 2022.,
面頁冊數:
xvi, 696 p. :ill. (chiefly color), digital ;24 cm.
內容註:
Chapter 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.
Contained By:
Springer Nature eBook
標題:
Finance - Data processing. -
電子資源:
https://doi.org/10.1007/978-3-031-14236-9
ISBN:
9783031142369
Essentials of Excel VBA, Python, and R.. Volume I, . Financial statistics and portfolio analysis
Lee, John C.
Essentials of Excel VBA, Python, and R.
Volume I, Financial statistics and portfolio analysis[electronic resource] /Financial statistics and portfolio analysisby John Lee, Cheng-Few Lee. - Second edition. - Cham :Springer International Publishing :2022. - xvi, 696 p. :ill. (chiefly color), digital ;24 cm.
Chapter 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.
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.
ISBN: 9783031142369
Standard No.: 10.1007/978-3-031-14236-9doiSubjects--Uniform Titles:
Microsoft Excel (Computer file)
Subjects--Topical Terms:
657417
Finance
--Data processing.
LC Class. No.: HG173
Dewey Class. No.: 332.0285
Essentials of Excel VBA, Python, and R.. Volume I, . Financial statistics and portfolio analysis
LDR
:03777nmm a2200373 a 4500
001
2307021
003
DE-He213
005
20230102180738.0
006
m d
007
cr nn 008maaau
008
230421s2022 sz s 0 eng d
020
$a
9783031142369
$q
(electronic bk.)
020
$a
9783031142352
$q
(paper)
024
7
$a
10.1007/978-3-031-14236-9
$2
doi
035
$a
978-3-031-14236-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
HG173
072
7
$a
PBT
$2
bicssc
072
7
$a
K
$2
bicssc
072
7
$a
BUS061000
$2
bisacsh
072
7
$a
PBT
$2
thema
072
7
$a
K
$2
thema
082
0 4
$a
332.0285
$2
23
090
$a
HG173
$b
.L478 2022
100
1
$a
Lee, John C.
$3
874416
245
1 0
$a
Essentials of Excel VBA, Python, and R.
$n
Volume I,
$p
Financial statistics and portfolio analysis
$h
[electronic resource] /
$c
by John Lee, Cheng-Few Lee.
246
3 0
$a
Financial statistics and portfolio analysis
250
$a
Second edition.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2022.
300
$a
xvi, 696 p. :
$b
ill. (chiefly color), digital ;
$c
24 cm.
505
0
$a
Chapter 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.
520
$a
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.
630
0 0
$a
Microsoft Excel (Computer file)
$3
543656
$3
543656
650
0
$a
Finance
$x
Data processing.
$3
657417
650
0
$a
Finance
$x
Statistical methods.
$3
578739
650
0
$a
Electronic spreadsheets
$x
Computer programs.
$3
678510
650
0
$a
Python (Computer program language)
$3
729789
650
0
$a
R (Computer program language)
$x
Statistical methods.
$3
2169042
700
1
$a
Lee, Cheng F.
$3
667184
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
856
4 0
$u
https://doi.org/10.1007/978-3-031-14236-9
950
$a
Mathematics and Statistics (SpringerNature-11649)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9447981
電子資源
11.線上閱覽_V
電子書
EB HG173
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入