--- product_id: 502495752 title: "Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition" price: "€ 93.50" currency: EUR in_stock: true reviews_count: 12 url: https://www.desertcart.be/products/502495752-python-for-finance-cookbook-over-80-powerful-recipes-for-effective store_origin: BE region: Belgium --- # Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition **Price:** € 93.50 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition - **How much does it cost?** € 93.50 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.be](https://www.desertcart.be/products/502495752-python-for-finance-cookbook-over-80-powerful-recipes-for-effective) ## Best For - Customers looking for quality international products ## Why This Product - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Description Use modern Python libraries such as pandas, NumPy, and scikit-learn and popular machine learning and deep learning methods to solve financial modeling problems Purchase of the print or Kindle book includes a free eBook in the PDF format Key Features 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 Book 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. 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, desertcart's DeepAR and NeuralProphet Who this book is 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. Table of Contents Acquiring Financial Data Data Preprocessing Visualizing Financial Time Series Exploring Financial Time Series Data Technical Analysis and Building Interactive Dashboards Time Series Analysis and Forecasting Machine Learning-Based Approaches to Time Series Forecasting Multi-Factor Models Modelling Volatility with GARCH Class Models Monte Carlo Simulations in Finance Asset Allocation Backtesting Trading Strategies Applied Machine Learning: Identifying Credit Default Advanced Concepts for Machine Learning Projects Deep Learning in Finance Review: Excellent - Really well structured, well written, and the code is thoughtfully put together. This is a complex topic and the direct writing style and real world insights make this a book well worth the asking price. Solid. Review: Good Financial Analysis with Python - Review: Python for Finance Cookbook – Second Edition This book offers a solid blend of financial concepts and Python programming, making it a valuable resource for anyone looking to apply coding skills to real-world finance problems. The financial objectives are well-chosen, and the Python examples are clear, practical, and well-explained. The only downside is that some of the data sources referenced have changed or become outdated. However, with minor adjustments or alternative APIs, the code can still be adapted effectively. Overall, it remains an excellent learning tool for finance-focused Python developers. ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | 312,737 in Books ( See Top 100 in Books ) 317 in Computing & Internet Databases 478 in E-Business 1,614 in Computing & Internet Programming | | Customer Reviews | 4.4 out of 5 stars 60 Reviews | ## Images ![Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition - Image 1](https://m.media-amazon.com/images/I/81LSZf+TpqL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ Excellent *by A***K on 9 February 2023* Really well structured, well written, and the code is thoughtfully put together. This is a complex topic and the direct writing style and real world insights make this a book well worth the asking price. Solid. ### ⭐⭐⭐⭐ Good Financial Analysis with Python *by R***H on 6 May 2025* Review: Python for Finance Cookbook – Second Edition This book offers a solid blend of financial concepts and Python programming, making it a valuable resource for anyone looking to apply coding skills to real-world finance problems. The financial objectives are well-chosen, and the Python examples are clear, practical, and well-explained. The only downside is that some of the data sources referenced have changed or become outdated. However, with minor adjustments or alternative APIs, the code can still be adapted effectively. Overall, it remains an excellent learning tool for finance-focused Python developers. ### ⭐⭐⭐⭐⭐ Essential reference for financial data analyst *by I***A on 21 September 2023* Very good reference book. it covers a lot of essential materials for analysing financial data. --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.be/products/502495752-python-for-finance-cookbook-over-80-powerful-recipes-for-effective](https://www.desertcart.be/products/502495752-python-for-finance-cookbook-over-80-powerful-recipes-for-effective) --- *Product available on Desertcart Belgium* *Store origin: BE* *Last updated: 2026-06-21*