國立高雄大學圖資館 |

登入

回首頁

Essentials of Excel VBA, Python, and R.Volume II,Financial derivatives, risk management and machine learning

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 ... [et al.].
其他題名:	Financial derivatives, risk management and machine learning
其他作者:	Lee, John.
出版者:	Cham :Springer International Publishing :2023.
面頁冊數:	xv, 523 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	FinanceData processing.
電子資源:	https://doi.org/10.1007/978-3-031-14283-3
ISBN:	9783031142833$q(electronic bk.)

Essentials of Excel VBA, Python, and R.Volume II,Financial derivatives, risk management and machine learning
Essentials of Excel VBA, Python, and R.Volume II,Financial derivatives, risk management and machine learning[electronic resource] /Financial derivatives, risk management and machine learningby John Lee ... [et al.]. - Second edition. - Cham :Springer International Publishing :2023. - xv, 523 p. :ill. (chiefly col.), digital ;24 cm.

Chapter 1. Introduction -- Chapter 2. Introduction to Excel Programming -- Chapter 3. Introduction to VBA Programming -- Chapter 4. Professional Techniques Used in Excel and Excel VBA Techniques -- Chapter 5. Decision Tree Approach for Binomial Option Pricing Model -- Chapter 6. Microsoft Excel Approach to Estimating Alternative Option Pricing Models -- Chapter 7. Alternative Methods to Estimate Implied Variances -- Chapter 8. Greek Letters and Portfolio Insurance -- Chapter 9. Portfolio Analysis and Option Strategies -- Chapter 10. Alternative Simulation Methods and Their Applications -- Chapter 11. Linear Models for Regression -- Chapter 12. Kernel Linear Model -- Chapter 13. Neural Networks and Deep Learning -- Chapter 14. Applications of Alternative Machine Learning Methods for Credit Card Default Forecasting -- Chapter 15. An Application of Deep Neural Networks for Predicting Credit Card Delinquencies -- Chapter 16. Binomial/Trinomial Tree Option Pricing Using Python -- Chapter 17. Financial Ratios and its Applications -- Chapter 18. Time Value Money Analysis -- Chapter 19. Capital Budgeting under Certainty and Uncertainty -- Chapter 20. Financial Planning and Forecasting -- Chapter 21. Hedge Ratios: Theory and Applications -- Chapter 22. Application of simultaneous equation in finance research: Methods and empirical results -- Chapter 23. Using R Program to Estimate Binomial Option Pricing Model and Black & Scholes Option Pricing Model.

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 second volume is designed for advanced courses in financial derivatives, risk management, and machine learning and financial management. In this volume we extensively use Excel, Python, and R to analyze the above-mentioned topics. 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 first volume for dedicated content on financial statistics, and portfolio analysis.

ISBN: 9783031142833$q(electronic bk.)

Standard No.: 10.1007/978-3-031-14283-3doiSubjects--Uniform Titles:

Microsoft Excel (Computer file)
Subjects--Topical Terms:

200666
Finance
--Data processing.

LC Class. No.: HF1017

Dewey Class. No.: 330.015195

Essentials of Excel VBA, Python, and R.Volume II,Financial derivatives, risk management and machine learning
LDR:03832nmm a2200373 a 4500 001 643336
003 DE-He213
005 20230323212158.0
006 m d
007 cr nn 008maaau
008 231123s2023 sz s 0 eng d
020 $a 9783031142833$q(electronic bk.)
020 $a 9783031142826$q(paper)
024 7 $a 10.1007/978-3-031-14283-3 $2 doi
035 $a 978-3-031-14283-3
040 $a GP $c GP
041 0 $a eng
050 4 $a HF1017
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 330.015195 $2 23
090 $a HF1017 $b .E78 2023
245 0 0 $a Essentials of Excel VBA, Python, and R. $n Volume II, $p Financial derivatives, risk management and machine learning $h [electronic resource] / $c by John Lee ... [et al.].
246 3 0 $a Financial derivatives, risk management and machine learning
250 $a Second edition.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a xv, 523 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
505 0 $a Chapter 1. Introduction -- Chapter 2. Introduction to Excel Programming -- Chapter 3. Introduction to VBA Programming -- Chapter 4. Professional Techniques Used in Excel and Excel VBA Techniques -- Chapter 5. Decision Tree Approach for Binomial Option Pricing Model -- Chapter 6. Microsoft Excel Approach to Estimating Alternative Option Pricing Models -- Chapter 7. Alternative Methods to Estimate Implied Variances -- Chapter 8. Greek Letters and Portfolio Insurance -- Chapter 9. Portfolio Analysis and Option Strategies -- Chapter 10. Alternative Simulation Methods and Their Applications -- Chapter 11. Linear Models for Regression -- Chapter 12. Kernel Linear Model -- Chapter 13. Neural Networks and Deep Learning -- Chapter 14. Applications of Alternative Machine Learning Methods for Credit Card Default Forecasting -- Chapter 15. An Application of Deep Neural Networks for Predicting Credit Card Delinquencies -- Chapter 16. Binomial/Trinomial Tree Option Pricing Using Python -- Chapter 17. Financial Ratios and its Applications -- Chapter 18. Time Value Money Analysis -- Chapter 19. Capital Budgeting under Certainty and Uncertainty -- Chapter 20. Financial Planning and Forecasting -- Chapter 21. Hedge Ratios: Theory and Applications -- Chapter 22. Application of simultaneous equation in finance research: Methods and empirical results -- Chapter 23. Using R Program to Estimate Binomial Option Pricing Model and Black & Scholes Option Pricing Model.
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 second volume is designed for advanced courses in financial derivatives, risk management, and machine learning and financial management. In this volume we extensively use Excel, Python, and R to analyze the above-mentioned topics. 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 first volume for dedicated content on financial statistics, and portfolio analysis.
630 0 0 $a Microsoft Excel (Computer file) $3 190780
650 0 $a Finance $x Data processing. $3 200666
650 0 $a Finance $x Statistical methods. $3 240075
650 0 $a Python (Computer program language) $3 215247
650 0 $a R (Computer program language) $3 210846
650 0 $a Electronic spreadsheets $x Computer programs. $3 220170
650 0 $a Derivative securities $x Data processing. $3 233797
650 0 $a Risk management. $3 174339
650 0 $a Machine learning. $3 188639
650 1 4 $a Statistics in Business, Management, Economics, Finance, Insurance. $3 913173
650 2 4 $a Statistics and Computing. $3 922173
650 2 4 $a Programming Language. $3 913494
650 2 4 $a Business Mathematics. $3 696407
650 2 4 $a Data Analysis and Big Data. $3 913147
700 1 $a Lee, John. $3 470243
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-14283-3
950 $a Mathematics and Statistics (SpringerNature-11649)