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 by
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.
Python for Finance Cookbook
- About Book
- Who Is This Book For?
- Book Content
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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