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.