December 2022
Beginner to intermediate
740 pages
18h 11m
English
Overview
Explore effective techniques for financial data analysis using Python with the 'Python for Finance Cookbook - Second Edition.' This book provides over 80 recipes that guide you through essential financial modeling, data preprocessing, and visualization techniques, bolstered by modern machine learning and deep learning approaches.
What this Book will help me do
- Gain proficiency in preprocessing, analyzing, and visualizing financial data using Python.
- Learn time series forecasting using models like ARIMA and Prophet for financial applications.
- Understand volatility modeling with GARCH models and its role in financial analysis.
- Master Monte Carlo simulations for risk assessment and derivative valuation.
- Develop and backtest trading strategies using technical analysis indicators.
Author(s)
Eryk Lewinson, the author of this cookbook, is a seasoned expert in financial data analysis and Python programming. With extensive knowledge of quantitative finance and experience in applying modern techniques to practical problems, Eryk brings a wealth of expertise to this work. His background in both theory and application seamlessly combines classical methods and cutting-edge machine learning algorithms for financial modeling.
Who is it for?
This book is ideal for financial and data analysts, Python developers interested in finance, and professionals aiming to enhance their data analytics skills. It is particularly suitable for those familiar with Python libraries such as NumPy and pandas. If you're eager to learn advanced techniques in financial data analysis and avoid common pitfalls, this book is the perfect resource for you.
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