Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition

Excellent book. Good discussion on each topic, self-contained code examples and they work! I hope author will come up with an updated version covering newer techniques in detail e.g., using pytorch !! Must have as a reference

Good; I think the one for Machine Learning for Algorithmic training is a little better

amazing

Really great book with super detailed explanations. I was honestly amazed at how clearly and systematically everything was explained — it made it so much easier to follow and stay interested.

Love this book since it is really useful for my study and work!

Time series section gave me info and idea to find out a sharpe ratio 0.8 strategies (2020-). But i rate this book as 4 stars as the model factor section makes no sense to me. I am expecting the author shows me cookbook to use stock leading factor (as mentioned in the opening of the section in the book) to put in the model and how to use this model on algo strategy. But it turns out the code example is nothing related to it.

As the title states is a Cookbook. It introduces many python libraries to analyzed and apply Machine Learning (ML) applications to financial time series data. Does a great job on how to download financial data. All the code in the book is available from the URLs provided in the book. I found the book very useful and recommend the book, for those getting started in analyzing and forecasting financial time series data in python.

For a cookbook it's great. It teaches the user how to apply Quantitative techniques using python. The only issue i have with it is Dependancy updates have changed, some platforms are depreciated entirely, the explanations can be rather unclear at times and short winded (each me how to cook, dont just show me the food). This makes it difficult to follow along and forced me to put down the book for some other analog to time series analysis.

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.

Guter Einstieg in Python, Pandas, Numpy und grundlegende Vorgehensweise in Quant programming mit Python. Es macht Spaß es durchzuarbeiten und ist pragmatisch aufgebaut. Der Autor kommt auch gleich auf den Punkt... so mag ich das. Heutzutage leider keine Selbstverständlichkeit mehr - diese Fachbuch hat gut lesbaren Schriftsatz.

Read all the chapters, simple and easy to understand. Recommended revision with AI recipe. Thick and heavy, split for reading during commute.

Low level printing quality disaster copy from Poland but book is GOOD

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.