Gaining perspective on stock prices

Investors who have purchased long stock positions would obviously like to sell stocks at or near their all-time highs. This, of course, is very difficult to do in practice, especially if a stock price has only spent a small portion of its history above a certain threshold. We can use boolean indexing to find all points in time that a stock has spent above or below a certain value. This exercise may help us gain perspective as to what a common range for some stock to be trading within.

Getting ready

In this recipe, we examine Schlumberger stock from the start of 2010 until mid-2017. We use boolean indexing to extract a Series of the lowest and highest ten percent of closing prices during this time period. We then plot all points and highlight those that are in the upper and lower ten percent.

How to do it...

1. Read in the Schlumberger stock data, put the Date column into the index, and convert it to a DatetimeIndex:

>>> slb = pd.read_csv('data/slb_stock...