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Key benefits

Explore unique recipes for financial data processing and analysis with Python

Apply classical and machine learning approaches to financial time series analysis

Calculate various technical analysis indicators and backtest trading strategies

Description

Python is one of the most popular programming languages in the financial industry, with a huge collection of accompanying libraries. In this new edition of the Python for Finance Cookbook, you will explore classical quantitative finance approaches to data modeling, such as GARCH, CAPM, factor models, as well as modern machine learning and deep learning solutions. You will use popular Python libraries that, in a few lines of code, provide the means to quickly process, analyze, and draw conclusions from financial data. In this new edition, more emphasis was put on exploratory data analysis to help you visualize and better understand financial data. While doing so, you will also learn how to use Streamlit to create elegant, interactive web applications to present the results of technical analyses. Using the recipes in this book, you will become proficient in financial data analysis, be it for personal or professional projects. You will also understand which potential issues to expect with such analyses and, more importantly, how to overcome them.

Who is this book for?

This book is intended for financial analysts, data analysts and scientists, and Python developers with a familiarity with financial concepts. You’ll learn how to correctly use advanced approaches for analysis, avoid potential pitfalls and common mistakes, and reach correct conclusions for a broad range of finance problems. Working knowledge of the Python programming language (particularly libraries such as pandas and NumPy) is necessary.

What you will learn

Preprocess, analyze, and visualize financial data

Explore time series modeling with statistical (exponential smoothing, ARIMA) and machine learning models

Uncover advanced time series forecasting algorithms such as Meta's Prophet

Use Monte Carlo simulations for derivatives valuation and risk assessment

Explore volatility modeling using univariate and multivariate GARCH models

Investigate various approaches to asset allocation

Learn how to approach ML-projects using an example of default prediction

Explore modern deep learning models such as Google's TabNet, Amazon's DeepAR and NeuralProphet

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Modern Time Series Forecasting with Python

€39.99

Python for Finance Cookbook – Second Edition

€37.99

Machine Learning for Algorithmic Trading

€43.99

Total € 121.97

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bin Sep 11, 2023

This book is very comprehensive, with useful knowledge points. It is really a highly recommended book!

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Rubens C. Machado Jun 07, 2024

Feefo Verified review

David Zhang May 01, 2023

Die 2. Version ist nochmal viel kompakter als die erste von vor 3 Jahren. Grundlegende als auch tiefgreifende Prozesse der Statistik und Programmierung werden gut erklärt dargestellt. Die fast 800 Seiten des Buches decken theoretisch mehr als nur einen ganzen Semester ab.

Amazon Verified review

Ram Seshadri Feb 08, 2023

I was recently given the Python for Finance cookbook to review by Packt based on my experience with Finance and ML. I have to say that this is one hell of a book!! It is one of the most comprehensive and sweeping write-ups of Python in Finance I have read. Just for starters: it’s 720 pages long.Second, it has over 15 chapters covering everything from downloading and processing Time series data to EDA to modeling and finally explaining and evaluating results.The book provides over 80 recipes for everything from ARIMA to Garch to ML to Monte Carlo. The subjects range from derivatives evaluation to asset management and Bitcoin forecasting.The book has tons and tons of code. Every page is filled with step by step instructions with code and charts and graphs. I can go and on. If there is only one book that you plan to buy for learning to apply Python to financial problems, this is probably the book to buy. Highly recommended!

Asha Jan 19, 2023

Having just started as a Junior Data Scientist this book was really helpful for time series analysis and forecasting. It's not for beginners you need to have some basic understanding of Python and data analysis to get the most out of this book. I don't work in the Finance industry but it was nice to learn more about financial data.

Python for Finance Cookbook – Second Edition: Over 80 powerful recipes for effective financial data analysis , Second Edition

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