Mastering pandas for Finance > PACKT 원서리스트

1: Getting Started with pandas Using Wakari.io
What is Wakari?
Creating a Wakari cloud account
Installing the samples in Wakari
Summary

2: Introducing the Series and DataFrame
Notebook setup
The main pandas data structures – Series and DataFrame
The basics of the Series and DataFrame objects
Reindexing the Series and DataFrame objects
Summary

3: Reshaping, Reorganizing, and Aggregating
Notebook setup
Loading historical stock data
Reorganizing and reshaping data
Grouping and aggregating
Summary

4: Time-series
Notebook setup
Time-series data and the DatetimeIndex
Creating time-series with specific frequencies
Representing intervals of time using periods
Shifting and lagging time-series data
Frequency conversion of time-series data
Resampling of time-series
Summary

5: Time-series Stock Data
Notebook setup
Obtaining historical stock and index data
Visualizing financial time-series data
Fundamental financial calculations
Moving windows
Volatility calculation
Comparing stocks to the S&P 500
Summary

6: Trading Using Google Trends
Notebook setup
A brief on Quantifying Trading Behavior in Financial Markets Using Google Trends
Data collection
Generating order signals
Computing returns
Cumulative returns and the result of the strategy
Summary

7: Algorithmic Trading
Notebook setup
The process of algorithmic trading
Moving averages
Technical analysis techniques
Algo trading with Zipline
Summary

8: Working with Options
Introducing options
Notebook setup
Calculating payoff on options
Profit and loss calculation
The pricing of options
Summary

9: Portfolios and Risk
Notebook setup
An overview of modern portfolio theory
Modeling a portfolio with pandas
Constructing an efficient portfolio
Constructing an optimal portfolio
Visualizing the efficient frontier
Value at Risk
Summary

backindex: Appendix A: Index