Book

Python for Finance Cookbook

Explore recipes for both classical quantitative finance approaches to modeling financial data, as well as modern machine learning and deep learning solutions

Offered byPackt Logo

Difficulty Level

Intermediate

Completion Time

24h40m

Language

English

About Book

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.

Book content

chapters 24h40m total length

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

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