Key Features
Book Description
What you will learn
- Modeling and manipulating financial data using the pandas DataFrame
- Indexing, grouping, and calculating statistical results on financial information
- Timeseries modeling, frequency conversion, and deriving results on fixed and moving windows
- Calculating cumulative returns and performing correlations with index and social data
- Algorithmic trading and backtesting using momentum and mean reversion strategies
- Option pricing and calculation of Value at Risk
- Modeling and optimization of financial portfolios
Who this book is for
If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.
Table of Contents
- Getting Started with Pandas
- Using DataFrame and Indexes
- Deriving results from manipulated data
- Financial Time Series Data
- Crunching Historical Stock Quotes
- Analyzing Google Trends with Pandas
- Algorithmic Trading Strategies
- Option Pricing and Value At Risk
- More Example Applications
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