High-frequency data is referred to second-by-second or millisecond-by-millisecond transaction and quotation data. The New York Stock Exchange's TAQ (Trade and Quotation) 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 re, string >>>import pandas as pd >>>ticker='AAPL' # input a ticker >>>f1="c:/temp/ttt.txt" # ttt will be replace with aboove 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" >>>path2=path.replace("ttt",ticker) >>>df=pd.read_csv(path2,skiprows=8,header=None) >>>df.to_csv(outfile,header=False,index=False) >>>outfile.close()
In the preceding program, we have two input variables: ticker and path. After we choose...