Tidy Finance with Python
portes grátis
Tidy Finance with Python
Frey, Christoph; Scheuch, Christoph; Weiss, Patrick; Voigt, Stefan
Taylor & Francis Ltd
07/2024
246
Mole
9781032676418
15 a 20 dias
Descrição não disponível.
Preface
Author Biographies
Part 1: Getting Started
1. Setting Up Your Environment
2. Introduction to Tidy Finance
Part 2: Financial Data
3. Accessing and Managing Financial Data
4. WRDS, CRSP, and Compustat
5. TRACE and FISD
6. Other Data Providers
Part 3: Asset Pricing
7. Beta Estimation
8. Univariate Portfolio Sorts
9. Size Sorts and p-Hacking
10. Value and Bivariate Sorts
11. Replicating Fama and French Factors
12. Fama-MacBeth Regressions
Part 4: Modeling and Machine Learning
13. Fixed Effects and Clustered Standard Errors
14. Difference in Differences
15. Factor Selection via Machine Learning
16. Option Pricing via Machine Learning
Part 5: Portfolio Optimization
17. Parametric Portfolio Policies
18. Constrained Optimization and Backtesting
Appendices
A. Colophon
B. Proofs
C. WRDS Dummy Data
D. Clean Enhanced TRACE with Python
E. Cover Image
Bibliography
Index
Author Biographies
Part 1: Getting Started
1. Setting Up Your Environment
2. Introduction to Tidy Finance
Part 2: Financial Data
3. Accessing and Managing Financial Data
4. WRDS, CRSP, and Compustat
5. TRACE and FISD
6. Other Data Providers
Part 3: Asset Pricing
7. Beta Estimation
8. Univariate Portfolio Sorts
9. Size Sorts and p-Hacking
10. Value and Bivariate Sorts
11. Replicating Fama and French Factors
12. Fama-MacBeth Regressions
Part 4: Modeling and Machine Learning
13. Fixed Effects and Clustered Standard Errors
14. Difference in Differences
15. Factor Selection via Machine Learning
16. Option Pricing via Machine Learning
Part 5: Portfolio Optimization
17. Parametric Portfolio Policies
18. Constrained Optimization and Backtesting
Appendices
A. Colophon
B. Proofs
C. WRDS Dummy Data
D. Clean Enhanced TRACE with Python
E. Cover Image
Bibliography
Index
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
tidyverse, portfolio, machine learning, option pricing
Preface
Author Biographies
Part 1: Getting Started
1. Setting Up Your Environment
2. Introduction to Tidy Finance
Part 2: Financial Data
3. Accessing and Managing Financial Data
4. WRDS, CRSP, and Compustat
5. TRACE and FISD
6. Other Data Providers
Part 3: Asset Pricing
7. Beta Estimation
8. Univariate Portfolio Sorts
9. Size Sorts and p-Hacking
10. Value and Bivariate Sorts
11. Replicating Fama and French Factors
12. Fama-MacBeth Regressions
Part 4: Modeling and Machine Learning
13. Fixed Effects and Clustered Standard Errors
14. Difference in Differences
15. Factor Selection via Machine Learning
16. Option Pricing via Machine Learning
Part 5: Portfolio Optimization
17. Parametric Portfolio Policies
18. Constrained Optimization and Backtesting
Appendices
A. Colophon
B. Proofs
C. WRDS Dummy Data
D. Clean Enhanced TRACE with Python
E. Cover Image
Bibliography
Index
Author Biographies
Part 1: Getting Started
1. Setting Up Your Environment
2. Introduction to Tidy Finance
Part 2: Financial Data
3. Accessing and Managing Financial Data
4. WRDS, CRSP, and Compustat
5. TRACE and FISD
6. Other Data Providers
Part 3: Asset Pricing
7. Beta Estimation
8. Univariate Portfolio Sorts
9. Size Sorts and p-Hacking
10. Value and Bivariate Sorts
11. Replicating Fama and French Factors
12. Fama-MacBeth Regressions
Part 4: Modeling and Machine Learning
13. Fixed Effects and Clustered Standard Errors
14. Difference in Differences
15. Factor Selection via Machine Learning
16. Option Pricing via Machine Learning
Part 5: Portfolio Optimization
17. Parametric Portfolio Policies
18. Constrained Optimization and Backtesting
Appendices
A. Colophon
B. Proofs
C. WRDS Dummy Data
D. Clean Enhanced TRACE with Python
E. Cover Image
Bibliography
Index
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.