Financial Data Analysis Using Python

Author:   Dmytro Zherlitsyn
Publisher:   De Gruyter
ISBN:  

9781501523861


Pages:   505
Publication Date:   01 January 2025
Format:   Paperback
Availability:   Available To Order   Availability explained
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Financial Data Analysis Using Python


Overview

This book will introduce essential concepts in financial analysis methods & 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 also 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 the Python programming language to understand the basics of data preparation, visualization, and manipulation in the world of financial data. FEATURES • Illustrates financial data analysis using Python data science libraries & techniques • Uses Python visualization tools to justify investment and trading strategies • Covers asset pricing & portfolio management methods with Python

Full Product Details

Author:   Dmytro Zherlitsyn
Publisher:   De Gruyter
Imprint:   De Gruyter
Weight:   0.700kg
ISBN:  

9781501523861


ISBN 10:   1501523864
Pages:   505
Publication Date:   01 January 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Author Information

Dmytro Zherlitsyn, PhD, has dedicated over 20 years to university teaching, business training, financial consulting, scientific research & data analysis. He has authored over 250 academic publications (e-learning courses, textbooks, scientific papers & monographs) in Economics, Finance, Data Science, System Analysis & Software Engineering. His work encompasses the development of predictive models for business & market analysis, including advanced regression, simulation & machine learning methods for financial sectors & the cryptocurrency market.

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