Python for Finance : Data analysis, financial modeling, and portfolio management
Description: Python's intuitive syntax and beginner-friendly nature makes it an ideal programming language for financial professionals. It acts as a bridge between the world of finance and data analysis.This book will introduce essential concepts in financial analysis methods and models, coveri...
Enregistré dans:
| Auteur principal: | |
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| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
New Delhi :
BPB Publications
2024.
Paris : Cyberlibris |
| Accès en ligne: | Accès Université d'Orléans et IFPM |
| Note: |
Couverture. https://static2.cyberlibris.com/books_upload/136pix/9789355516893.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Python for Finance, Data analysis, financial modeling, and portfolio management, Dmytro Zherlitsyn, New Delhi, BPB Publications, 2024, 1 vol. (488 p.), 978-93-5551-689-3 |
| Résumé: | Description: Python's intuitive syntax and beginner-friendly nature makes it an ideal programming language for financial professionals. It acts as a bridge between the world of finance and data analysis.This book will introduce essential concepts in financial analysis methods and models, covering time-series analysis, graphical analysis, technical and fundamental analysis, asset pricing and portfolio theory, investment and trade strategies, risk assessment and prediction, and financial ML practices. The Python programming language and its ecosystem libraries, such as Pandas, NumPy, SciPy, Statsmodels, Matplotlib, Seaborn, Scikit-learn, Prophet, and other data science tools will demonstrate these rooted financial concepts in practice examples.This book will help you understand the concepts of financial market dynamics, estimate the metrics of financial asset profitability, predict trends, evaluate strategies, optimize portfolios, and manage financial risks. You will also learn data analysis techniques using Python programming language to understand the basics of data preparation, visualization, and manipulation in the world of financial data. Key Features: Comprehensive guide to Python for financial data analysis and modeling. Practical examples and real-world applications for immediate implementation. Covers advanced topics like regression, Machine Learning and time series forecasting. What you will learn: Learn financial data analysis using Python data science libraries and techniques. Learn Python visualization tools to justify investment and trading strategies. Learn asset pricing and portfolio management methods with Python. Learn advanced regression and time series models for financial forecasting. Learn risk assessment and volatility modeling methods with Python. Who this book is for: This book is designed for financial analysts and other professionals interested in the financial industry with a basic understanding of Python programming and statistical analysis. It is also suitable for students in finance and data science who wish to apply Python tools to financial data analysis and decision-making |
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| Description: | Couverture. https://static2.cyberlibris.com/books_upload/136pix/9789355516893.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Accès: | L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris |