Requirements

Data

You have to add Histrical Data such as GOOG.csv to /data directry. For example, YAHOO! FINANCE helps you.

1. Access to the summary page of symbol (ex. google（GOOG.csv）).
2. Click the Histrical Data at top of the page.
3. Make sure Time Period: is the period you want, and Frequency: is Daily. Then click Download Data.
4. Rename the file if necessary (ex: table.csv to `GOOG.c

python

• pandas and NumPy : For manipulating data. I used pandas 0.18.0 and NumPy 1.10.4
• matplotlib : For making animation. I used matplotlib 0.18.0.

Udacity

The codes depend on functions defined in Machine learning for trading at Udacity. Refer to the class (and take it!). You have to add udacity.py which defines get_data(), fill_missing_values(), and compute_daily_returns() to the current directry.

Model

Hereinafter, we assume SPY as the benchmark. The figure shows daily-returns of SPY and GOOG from Dec. 1, 2006 to Dec. 1, 2016. The regression line can be defined as y = beta x + alpha.

• alpha: Intercept of the line. It can be considered as the return over the benchmark.
• beta: Slope of the line. It can be considered as the relative volatility.

How to use

import animab as ab

ab.animate_a_b()

Variables

• symbols: List of symbols to animate
• start_date and end_date: Defines the animation period. Strings with yyyy-mm-dd format.
• period: Calculation period of alpha and beta.

License

MIT