Python for high-frequency data
High-frequency data is referred to as second-by-second or millisecond-by-millisecond transaction and quotation data. The New York Stock Exchange's Trade and Quotation (TAQ) database is a typical example (http://www.nyxdata.com/data-products/daily-taq). The following program can be used to retrieve high-frequency data from Google Finance:
import tempfile import re, string import pandas as pd ticker='AAPL' # input a ticker f1="c:/temp/ttt.txt" # ttt will be replace with above sticker f2=f1.replace("ttt",ticker) outfile=open(f2,"w") #path="http://www.google.com/finance/getprices?q=ttt&i=300&p=10d&f=d,o, h,l,c,v" path="https://www.google.com/finance/getprices?q=ttt&i=300&p=10d&f=d,o,%20h,l,c,v" path2=path.replace("ttt",ticker) ...Get Python for Finance - Second Edition now with the O’Reilly learning platform.
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