Python for Finance - Second Edition by Yuxing Yan

Author:Yuxing Yan [Yan, Yuxing]
Language: eng
Format: azw3, pdf
Publisher: Packt Publishing
Published: 2017-06-30T04:00:00+00:00

In the preceding example, we didn't process or clean the data. Usually, we have to process data by adding various filters, such as delete quotes with negative spread, bidsiz is zero, or ofrsiz is zero, before we estimate spread and do other estimates.

Introduction to CRSP

For this book, our focus is free public data. Thus, we only discuss a few financial databases since some readers might from schools with valid subscription. CRSP is the one. In this chapter, we mention just three Python datasets.

Center for Research in Security Prices (CRSP). It contains all trading data, such as closing price, trading volume, and shares outstanding for all listed stocks in the US from 1926 onward. Because of its quality and long history, it has been used intensively by academic researchers and practitioners. The first dataset is called crspInfo.pkl, see the following code:

import pandas as pd x=pd.read_pickle("c:/temp/crspInfo.pkl") print(x.head(3)) print(x.tail(2))

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